Special Issue on Recent Advances in Engineering Systems 2018-19

In this research human gait database is collected using different possible methods such as Wearable sensors, Smartphone and Cameras. For a gait recognition accelerometer data from wearable shimmer modules and smartphone are used. Data from different sensors location is compared to know which sensor location have better recognition rate. Different walking scenarios like slow, normal and fast walk were investigated. Wearable sensors and smartphone data are compared to know whether mobile phones can be used for gait recognition or not. Also effects of age, height, weight on gait recognition are also studied. The obtained results of gait biometric matrices like Genuine Recognition Rate (GRR), Total Recognition Rate (TRR) and Equal Error Rate (EER) showed better results. EER in different walking scenarios ranged from 0.17% to 2.27% for the five wearable sensors at different locations, whereas EER results of smartphone data ranged from 1.23% to 4.07%. For sensors located at leg, pocket and hand the average GRR value falls with increase in age group, while for sensors located at upper pocket and bag, the GRR value doesn’t follow any trend. Moreover GRR results on all sensors show no significance regarding height or weight variations.

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Screening the abnormal development of the zebrafish embryos before and after being hatched for a large number of samples is always carried out manually. The manual process is presented as a tedious work and low-throughput. The single female fish produce hundreds of eggs in every single mating process, the samples of the zebrafish embryos should be studied and analyzed within a short time according to the fast response of their bodies and the ethical regulations. The limited number of the automatic screening systems for aquaculture experiments encourage researchers to find out a high-throughput screening systems with a fast prediction results according to the large number of experimental samples. This work aims to design an automatic segmentation, classification system for zebrafish eggs using two ways for feature extraction and also a classifier. Using the whole image generally with several feature vectors useful for detection process, this way does not depend on the type of the image. The second way focus on specific characteristics of the image which are the colour and the texture features relating to the system purposes. Two different ways for feature extraction integrated by the Classification And Regression Tree (CART) classifier are proposed, analysed, and qualified by comparing the two methods performance and accuracies. The experimental results for zebrafish eggs classification into three distinct classes: live egg, live embryo, dead egg show higher accuracy using the texture and colour feature extraction with an accuracy 97% without any manual intervention. The proposed system results very promising for another type of classification such as the zebrafish larva deformations.

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Animal movement is inherent in the marketing between the rural productive units, establishing space-time connections between them. The relational nature of such information is kept in the Animal Transit Guides (GTA), a mandatory issuance in Brazil. When evaluating such set of information, this work aimed at characterizing the bovine movement network in the state of Pará through the application of concepts from Social Network and Network Theory analysis. Where the nodes and edges that structure the network are respectively the rural properties and the number of cattle moved between them. The results obtained characterize the bovine movement in the state, which show distinct patterns such as the movement of a great number of animals rambling and a clear seasonality due to commercialization purposes. The evaluation of the network components’ modularity also shows the subdivision of the state in four commercial clusters, where the central measures of its components define municipalities of economic and epidemiological interest. The results described herein help in the support of health surveillance and control measures, as well as the adoption of economic strategies and policies.

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This survey paper deals with the structural health monitoring systems on the basis of methodologies involving intelligent techniques. The intelligent techniques are the most popular tools for damage identification in terms of high accuracy, reliable nature and the involvement of low cost. In this critical survey, a thorough analysis of various intelligent techniques is carried out considering the cases involved in civil structures. The importance and utilization of various intelligent tools to be mention as the concept of fuzzy logic, the technique of genetic algorithm, the methodology of neural network techniques, as well as the approaches of hybrid methods for the monitoring of the structural health of civil structures are illustrated in a sequential manner.

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This paper is the extension of the work originally presented in 2nd International Conference on Man and Machine Interfacing (MAMI 2017) and the paper of Yue et al. The present study aims at observing the effect of various parameters on temperature distribution profiles at various environmental temperature, tissue thermal conductivities, metabolic rates, blood perfusion rates, and heat transfer coefficients. The analytic solution of Pennes’ bioheat equation in the steady-state case is obtained by using the Modified Bessel’s equation incorporating the effect of sweating and non-sweating state of the body. From the study, it was observed that the variation of atmospheric temperature and heat transfer coefficients have a significant effect for the temperature distribution in the body towards the skin surface.

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Mental health disorder is becoming a social problem, and there is a need for technology that can easily check for states of stress and depression as a countermeasure. Conventional methods of diagnostic support and screening include self-administered psychological tests and use of biomarkers. However, there are problems such as burden on subjects, examination costs, dedicated reagents and equipment required for examinations, and reporting bias. On the other hand, voice-based evaluations are advantageous in terms of providing diagnostic support for physicians. They are non-invasive, do not require special and exclusive equipment, and can therefore be easily conducted remotely. We are pursuing the research and development of the Mind Monitoring System (MIMOSYS), which estimates the state of mental health from voice. Recorded audio is often compressed for efficient storage and transmission. However, there are concerns regarding the effects of deterioration of sound quality on analysis by MIMOSYS. Therefore, this study aims to verify the influence of the deterioration of voice quality due to coding on MIMOSYS analysis. As a verification experiment, coding was applied on the recording of 704 subjects reading 17 fixed phrases, assuming compression for transmission and storage. Then, the results of MIMOSYS analysis before and after encoding were compared. A strong correlation was observed before and after encoding, suggesting that MIMOSYS analysis is also valid for voice to which coding was applied.

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The idea of monitoring several types of parameters in various environments has been motivating significant research works in Internet of Things (IoT). This paper presents the design and construction of iSensA, a system for integrating and collecting information from sensors. The solution implements a multi-sensor monitoring system and then expands the monitoring concept to an IoT solution, by employing multi-network access, Web services, database and web and mobile applications for user interaction. iSensA system is highly configurable, enabling several monitoring solutions with different types of sensors. Experiments have been performed on real application scenarios to validate and evaluate our proposition.

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In densely located loosely coupled wireless charger environments, cross-connection errors can occur when wireless chargers operate at the same time within the same wireless communication range. In this work, an effective algorithm is proposed to prevent cross-connection error. The algorithm based on the cross-connection abatement technique with the received signal strength indicator of out-band BLE communication has improved using an in-band magnetic field signal controlled by a pulse-width-modulation-like waveform. The experimental results obtained from a proper test set in a RF shield room verify that the wireless charging system using the proposed algorithm provides wireless charging services without cross-connection errors.

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Due to their efficient flight control systems and their camera of high quality modern drones can fly precisely and take aerial photos of high resolution. Although these multi-rotor devices are not able to fly long distances yet, they are very efficient instruments for taking aerial photographs of their proximate environment. As they are able to float and rotate along their vertical axis to a discretionary direction, they can be used for monitoring and taking pictures of a building from several directions. If pictures are taken of a building from all directions with significant overlap (of at least 50%) the 3D reconstruction of the building in a photogrammetric way becomes possible. The reconstructed models do not only contain the spatial forms but also the visualinformation based on the snapshots. As a result of the entire reconstruction a virtual object is gained in the virtual space that can freely be accessed and visible from all directions by enlarging or reducing the size. A virtual collection can be established for monuments, historical buildings or other spectacular objects worth recording. The objects of the collection (buildings) are lifelike and can be perceived and studied by anyone. The 3D models, of course, cannot substitute the photographs of high resolution but they can complement them in the collection.

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In recent years, research on game AI has expanded, and now it has become possible to construct even AI of complex games. In accordance with this trend, we constructed the AI of the Hanafuda with a certain degree of complexity. Because of applying the method used in other games to the ball game, we could create a computer player with a certain strength. However, some players feel that strong players are not fun. Therefore, we tried to build a computer player that feels interesting. In the previous experiments, the evaluation for the constructed player was not good. In this research, we conducted a questionnaire survey on players of Hanafuda to raise the evaluation of computer players. The result proved that there are some elements of fun in common among the players.

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Domain specific modeling (DSM) has become popular in the software development field during these last years. It allows to design an application using a domain specific modeling language (DSML) and to generate an end-solution software product directly from models. However providing a new DSML is a complex and costly job. This can be reduced by the reuse of existing DSMLs to compose new ones trough a metamodel composition approach. This paper provides a composition rules based code generator facility for extending DSMLs. In doing so, it proposes three rules to compose DSMLs by composing there metamodels: reference rule, specialization rule and fusion rule. The results of an exploratory case study on using these rules are depicted. In addition a proof of concept of the code generator facility which generates the necessary infrastructure to quickly build new DSMLs is implemented and applied to the case study. The benefits of our approach are measured relying on three indicators: the reduced development time, the reused software components and the gain on learnability.

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Many existing system modeling techniques based on statistical modeling, data mining and machine learning have a shortcoming of building variable relations for the full ranges of variable values using one model, although certain variable relations may hold for only some but not all variable values. This shortcoming is overcome by the Partial-Value Association Discovery (PVAD) algorithm that is a new multivariate analysis algorithm to learn both full-value and partial-value relations of system variables from system data. Our research used the PVAD algorithm to model variable relations of energy consumption from data by learning full-and partial-value variable relations of energy consumption. The PVAD algorithm was applied to data of energy consumption obtained from a building at Arizona State University (ASU). Full- and partial-value variable associations of building energy consumption from the PVAD algorithm are compared with variable relations from a decision tree algorithm applied to the same data to show advantages of the PVAD algorithm in modeling the energy consumption system.

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This paper deals with the control problem for nonholonomic wheeled mobile robots moving on the plane, and in particular, the use of a Fuzzy controller technique for achieving a given motion task which consists of following a rectilinear trajectory until an obstacle occurs on the path. After a background part, in which the fundamental knowledge of Fuzzy control is considered, the problem of the avoidance of an obstacle is taken into consideration. When an obstacle occurs on the path, the drive assistant provides for its avoidance calculating the minimal distance from which the avoidance maneuver starts. Conditions on the parameters of a PD controller are calculated using a Fuzzy based approach. An observer is designed to obtain unmeasurable states to be used in the control loop. In the Appendix of this paper a formal demonstration of a Proposition is proven in which the convergence of the system state estimation of the observer is shown. Simulations considering a real transporter vehicle for a storage service are shown.

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Considering link vibrations, the main limitation affecting flexible manipulators, this article seeks to make a contribution by presenting an enhanced two degree of freedom vibration controller. This controller uses a filtered right inverse controller in the feedforward and strain feedback controller in the feedback path. The Filtered inverse controller damps transient vibrations while preserving joint trajectories. On the other hand, strain feedback controller ensures a rapid decay of residue vibrations. Modeling of the manipulator was carried out in Maplesim, linearized and inverted in Matlab. Experiments were conducted in the SPACE environment. Both the simulations and the experimental results showed that the two-degree-of-freedom controller yielded a superior performance over the two controllers individually.

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Service providers are transferring their static optical transport networks from semi-permanent connections to agile automatic switched optical networks (ASON) with dynamic optical connection provisioning and restoration. To achieve this goal, service providers are looking for flexible optical network ROADMs with CDC capabilities. Although many contention scenarios during network connection provisioning and restoration have been illustrated, surprisingly academic simulations have showed that the blocking probability improvement of CDC ROADM comparing with CD ROADM is not significant. This is good news for service providers since most deployed optical networks are only CD ROADM capable, instead of CDC ROADM capable. How to make use of existing CD ROADMs to achieve network automation becomes an urgent challenge. In this paper, we present two research results to attack this challenge: (1) first, we built an analytical mode to estimate the CD ROADM contention blocking probability and show that when a CD ROADM add/drop local direction capacity occupation ratio is low or moderate, the contention blocking probability is not significant. From this model, we estimate that one can use a CD add/drop local direction capacity occupation ratio up to 75% before installing another CD ROADM add/drop local direction or installing a CDC add/drop local direction when available. Simulation results on real network topologies and traffic matrices verified our recommendation; (2) second, we observed that most deployed optical networks are usually providing 100G or 200G per wavelength while majority applications are still requesting much smaller bandwidths and service providers often provide OTN (Optical Transport Network) over ROADM architecture for transport services. Since OTN provides electronic switching capability, in this paper, we present a new algorithm and methodology to make use of both OTN switch and CD ROADM to avoid service contention without using CDC ROADM.

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Distraction, drowsiness, and fatigue are the main factors of car accidents recently. To solve such problems, an Eye-tracking system based on camera is proposed in this paper. The system detects the driver’s Distraction or sleepiness and gives an alert to the driver as an assistance system. The camera best position is chosen to be on the dashboard without distracting the driver. The system will detect the driver’s face and eyes by using Viola-Jones Algorithm that includes Haar Classifiers that showed significant advantages regarding processing time and correct detection algorithms. A prepared scenario is tested in a designed simulator that is used to simulate real driving conditions in an indoor environment. The system is added in real-vehicle and tested in an outdoor environment. Whenever the system detects the distraction or sleepiness of the driver, the driver will be alerted through a displayed message on a screen and an audible sound for more attention. The results show the accuracy of the system with a correct detection rate of 82% for indoor tests and 72.8 % for the outdoor environment.

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The application of protective coatings is the primary method of protecting marine and offshore structures from corrosion. Coating breakdown and corrosion (CBC) assessment is a major aspect of coating failure management. Evaluation methods can result in unnecessary maintenance costs and a higher risk of failure. To achieve a comprehensive collection of data for CBC assessment, an unmanned arial system (UAS), assisted by the latest technological innovations, will be used to facilitate data collection in inaccessible locations. A convolutional neural network (CNN)-based CBC assessment system is developed to provide objective assessment of the severity of coating failure. This method is more suitable for inspecting large areas by capturing and analyzing pictures/videos of the target area than the surveyor’s existing manual inspection solution. In this paper, deep learning-based object detection in the CBC assessment system has been developed to provide an effective CBC assessment for the marine and offshore industries. By using active thermal imaging, it can identify corrosion behind the coating. This will greatly improve the efficiency and reliability of coating inspection.

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In this paper an omnidirectional dual band monopole antenna at 28 GHz and 60 GHz which is fit for indoor and outdoor wireless applications is developed. The proposed antenna consists of two rectangular patches with a T folded patch. The design, analysis, and optimization processes through this article are executed by the numerical method, Finite Element Method (FEM) and verified with another numerical method, Finite integration Technique (FIT). Good agreement between the results by these two simulators is obtained. The proposed antenna has achieved dual bands with omnidirectional patterns. The first band at 28 GHz is extended from 27.5 GHz to 28.958 GHz with 5.1 % bandwidth and total efficiency of more than 93% along the entire band which serves the LMDS band. The second band at 60 GHz is extended from 45.2 GHz to 84.4 GHz which serves the WiGig band with bandwidth of 60.6% and total efficiency of 85.5% along the entire band. The proposed antenna performance makes it a good candidate for the fifth generation (5G) applications.

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In today’s technology, 3D presentation is vital in conveying a realist and comprehensive understanding of a specific notion or demonstrating certain functionality for a specific device or tool, especially on the World Wide Web. Therefore, the importance of this field and how its continuous enhancement has become one of the dominant topics in web development research. Virtual Reality (VR) combined with the use of a 3D scene and 3D content is one of the best delivering mechanisms of this realist ambience to users. AquaFlux and Epsilon are clinical instruments that were built, designed, and developed at London South Bank University as research projects for medical and cosmetic purposes. Currently, They have been marketed and used in almost 200 institutions internationally. Nevertheless, considering the type of these tools, they often involve on-site thorough training, which is costly and time-consuming. There is a real necessity for a system or an application where the features and functionalities of these two instruments can be illustrated and comprehensively explained to clients or users. Virtual User Manual (VUM) environment would serve this purpose efficiently, especially if it is introduced in 3D content. The newly created system consists of a detailed virtual guide that will assist users and direct them on how to use these two devices step-by-step. Presenting this work in a VR immersed environment will benefit clients, user and trainees to fully understand all the features and characteristics of AquaFlux and Epsilon and to master all their functionalities.

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This article examines the use of non-ideal current and voltage sensors for sensorless speed control for a fixed field DC motor. A PID type speed controller with KF estimator was applied to control the DC motor and IAE, settling time, and peak overshoot were taken as performance indices. However, KF facilitated the noise reduction. After tuning controller gains through MATLAB yielded high peak overshoot as well as IAE with an extended settling time. When we applied, a PID-Type FLC tuned by means of GA (genetic algorithms) caused a 75.98%, 97.89% and 56.2% cut in settling time, maximum overshoot and IAE correspondingly. The FLC-PID fundamentally enhanced sudden load changes disturbance rejection and the reference command speed tracking for the dc motor design in comparison to the conventional PID with no KF. This study was also able to replace the designed FLC-PID with linear lookup-table while achieving the same performance improvements.

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Large power transformers generally include a customer request for a technically appropriate regulation unit. The selection process of the regulation unit consists of defining the required input data, performing mathematical calculations necessary to find the technical limit values that the regulation unit has to satisfy, and finally optimizing and selecting the appropriate regulation unit. The number of possible permutations consists of thousands of different combinations, depending on the type of regulation and other technical limitations. The automation system presented in this paper significantly reduces the time required to obtain the optimal regulation unit solution in both offer and order stages of the project, providing significant overall productivity increase. This paper presents an example of managing a part of a complex system such as power transformer design using a software solution. The process of finding the optimal regulation unit „manually” can take up to several hours. Implementing the developed algorithm and introducing Tap Changer Selection application, the required time is reduced to several minutes. This represents significant time savings and reduced possibility of errors, thus improving the power transformer design process.

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As the technology grows scientists and engineers are trying to combine their work to compensate some body parts that is lost. Prosthetic devices grabbed the attention of most of the doctors and engineers working on solution for lost body parts. Generally prosthetic devices are either external wearable devices or internal ones. Such devices may depend on a built on microcontroller or the brain signals from the patient himself. Although it is used for lost body parts it can also be used for rehabilitation, power assistance, diagnostics, monitoring, ergonomics, etc. The currently used devices usually have the disadvantages of big size and high cost. The suggested device in this paper is targeting the design of portable rehabilitation device with light weight and low cost for paralyzed hand people. The suggested device allows the user to train the patient’s hand or perform some needed exercises for his impaired hand. This helps the user to restore the normal hand movement and functionality. The device includes two modes of operation to be chosen by the user through the platform built on a microprocessor which can help controlling the exoskeleton to perform the needed exercises or tasks. Collaboration with several healthcare organizations will be considered to verify or test the effectiveness of this exoskeleton.

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We present a privacy-preserving approach for discovering nearby places of interest to Alice. In this approach, the proposed protocol allows Alice to learn whether there is any place that she is looking for near her. However, the location-based service (LBS) that tries to help Alice to find nearby places does not learn Alice’s location. Alice can send a request to the LBS database to retrieve nearby places of interest (POIs) without the database becoming aware of what Alice fetched by using private information retrieval (PIR). The common criticism of previous PIR approaches is that they are not practical for smartphones with limited processing power, memory, and wireless bandwidth due to the computational overhead. Therefore, the main focus of this work is to propose a scheme to reduce the computation cost on the client-side to make PIR appropriate and practical for the smartphone environments, and then apply the proposed PIR to LBS applications. We have implemented our protocol in Percy++ to evaluate its performance over a commercial-grade database of POIs. Our implementation results demonstrate that our approach has faster decode and retrieve time for the nearby POIs on smartphones compared with current similar work.

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Big data can be considered to be at the forefront of the present and future research activities. The volume of data needing to be processed is growing dramatically in both velocity and variety. In response, many big data technologies have emerged to tackle the challenges of collecting, processing and storing such large-scale datasets. High-performance computing (HPC) is a technology that is used to perform computations as fast as possible. This is achieved by integrating heterogeneous hardware and crafting software and algorithms to exploit the parallelism provided by HPC. The performance capabilities afforded by HPC have made it an attractive environment for supporting scientific workflows and big data computing. This has led to a convergence of the HPC and big data fields.
However, big data applications usually do not fully exploit the performance available in HPC clusters. This is so due to such applications being written in high-level programming languages and does not provide support for exploiting parallelism as do other parallel programming models.
The objective of this research paper is to enhance the performance of big data applications on HPC clusters without sacrificing the power consumption of HPC. This can be achieved by building a parallel HPC-based Resource Management System to exploit the capabilities of HPC resources efficiently.

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Metal (silver)-Assisted Chemical Etching (MACE) method is used to fabricate silicon nanostructures like silicon nanowires (SiNWs) and silicon nanocones (SiNCs). The morphological characterization of fabricated SiNWs has shown that 5 minutes is the optimal time of silver deposition on silicon substrate. Silicon nanocones (SiNCs) were also fabricated by etching vertical SiNWs with a AgNO3=HF=H2O2 solution. The optical and electrical properties of SiNWs and SiNCs are analyzed and compared with those of the bulk silicon. The fabricated SiNWs (SiNCs) reduce the surface reflectance and the sheet resistance down to 6% (3%) and 9.143 /sq (6.997 /sq) respectively.

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This paper deals with the theoretical aspect of bat echolocation and bionics, and image processing-based target recognition and identification methods. The state estimation methods utilizing the linear rustic filters such as fixed gain and Kalman filters are studied and implemented for echolocation bionics for estimating the LOS distance. A complete mathematical modeling and simulation of bat dynamics and its prey are presented upon which the relative LOS distance is reconstructed with state estimators and less RMS errors. Also, target recognition and identification using Optical, IR Digital Night Vision and Thermal camera is studied and implemented at different environmental conditions to demonstrate the superiority of thermal camera.

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Just as electricity has an essential role in our lives, the internet network and especially web services have become of vital importance nowadays. Without security service layers, apparently small things like checking a child’s school schedule on web may turn the daily routine into a nightmare. Web services users are still required to use many combinations of usernames and passwords. Despite technologically advances that bring many benefits to those owning top of range smartphones, complex combinations of identifiers and passwords are still required for basic security. Top tier smart mobile phones also add device-specific vulnerabilities to the risk of misuse or may expose sensitive data like biometrics. To meet users’ expectations, authentication systems must be safe, fast, efficient, intuitive and easy to use, especially on mobile phones. User satisfaction, reduced fraudulent authentication issues, increased security, reduced management costs, regulatory compliance are main goals for the new advanced web technologies systems. This paper presents some real-time multi-factor authentication methods that uses voice calls to communicate random passwords to registered users. The ultimate goal is to relieve web service users from the stress of memorizing complex combinations, or copying text strings for user identifiers and passwords from paper or external memory devices like mobile phones. The new features are presented for a web service after migration from the traditional authentication system to the one with the proposed new method. This work is an extension of the paper entitled “Securing Web Accounts by Graphical Password and Voice Notification” published in 2018 IEEE International Conference on Engineering, Technology and Innovation (ICEITMC).

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This paper investigates the methods of optimal design construction for step-stress accelerated life testing (ALT) when a Cox’s hazards model is adopted with either a linear or a quadratic baseline hazard function. We discuss multiple step-stress plans for time-censored ALT experiments. The maximum likelihood method is utilized for estimating the model parameters. The information matrices have been derived for both models. The optimal stress-changing times and optimal stress levels are determined simultaneously under three different optimality criteria. In order to demonstrate the performance of the resulting designs, a simulation procedure is also provided. The efficiencies of our resulting optimal three-step-stress ALT plans are compared with their competitors using both practical examples and a simulation study. The efficiency comparison results have shown that the three-step-stress designs obtained with two optimal stress changing times and an optimal middle stress level are most efficient, compared to the corresponding optimal two-step-stress designs and to the optimal three-step-stress designs with a conveniently chosen middle stress. Furthermore, the efficient gains are most significant for hazard rate prediction for both cases when either a linear or a quadratic baseline hazard is assumed. Additionally, such efficiency gain is much greater for the case when the baseline function being quadratic than the case when that being simple linear.

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There exists a profound difficulty of communication between the people that works in the EMC area in circuit terms and the people that works in field terms.
In this paper we show that when the matter is predominantly distributed along a certain direction in space, as for transmission lines, the electromagnetic field can be divided in two modes, each of them with two degrees of freedom, that are practically independent: a longitudinal TM (transverse magnetic) mode and a transversal TE (transverse electric) mode. We also show that two degrees of freedom of the longitudinal mode are the ones that are described by circuit’s theory.
This formulation is based on the observation that, when the matter is macroscopically described by constitutive laws, the electromagnetic field within the matter can be fully characterized in terms of the potential fields, in total four degrees of freedom.
Using the above formulation, we put forward a generalized formulation of the coupling of an external electromagnetic field to a transmission line, valid in any time scale.
We apply the above concepts to study, in a common theoretical framework, the iconic case of the conducted and radiated interferences on a transmission line, and we show that:
1-Differently than what is normally assumed in standard transmission-line theory, the normal operation mode and the internally-produced electromagnetic field are predominantly a longitudinal TM mode;
2-The longitudinal mode is affected by both the conducted disturbances and the radiated disturbances; while
3- The transverse mode is affected only by the radiated disturbances.
Then, only for systems where the longitudinal mode is predominant, and, the longitudinal and the transversal modes are practically decoupled, EMI can be simulated using circuit simulation software’s.
Also, to further illustrate the interpretation power of this formulation, we present some other application examples.

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Low contrast images degrade the performance of image processing system. To solve the issue, plenty of image enhancement methods have been proposed. But the methods work properly on the fixed environment or specific images. The methods dependent on fixed image conditions cannot perform image enhancement properly and perspective of smart device users, algorithms including iterative calculations are inconvenient for users. To avoid these issues, we propose a locally adaptive contrast enhancement method using CNN and simple reflection model. The experimental results show that the proposed method reduces over-enhancement, while recovering the details of the low contrast regions.

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Zirconium trisulfide ZrS3 is a representative of transition metal polysulfides containing sulfur as S–1 in polysulfide, usually disulfide S22– groups. Semiconductive zirconium trisulfide which absorbs visible light near UV edge was considered as a possible photocatalyst. We experimentally studied photodecoloration of methyl orange in presence of ZrS3. It was shown for the first time that crystalline ZrS3 strongly deepens photodegradation reaction, and in one case the methylene orange conversion reached almost 100%. The rates of degradation curves were associated with the ZrS3 samples morphology; the best result revealed for microribbons ZrS3 synthesized at 650°C.

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This work extends the development of the nonuniform Parallel Digital Ramp Pulse Position Modulation Analog-to-Digital Converter (PDRADC) architecture. The continuous to discrete transform of the PDRADC is achieved by partitioning the signal amplitude axis into P nonoverlapping partitions that sample the analog input at input signal driven instances. Each partition contains L uniform levels with different quantization step sizes such that the dynamic range of the partitions are related as a geometric series. It is shown that this new architecture satisfies the Nyquist requirement on average (Beutler’s condition) and results in a random additive sampling architecture that is alias free (Shapiro- Silverman condition). Additionally, it is shown that the geometric partitioning causes the signal-to-quantization noise ratio (SQNR) to remain approximately constant. A comprehensive design paradigm is presented, including circuits to affect the desired response, the format of the encoded digital samples and the corresponding transformation to determine the equivalent analog voltage. Lastly, although the thrust of this paper is not reconstruction techniques, reconstruction is, nevertheless, compulsory, and recovery and reconstruction is demonstrated through simulations.

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Chronic diseases such as heart disease, cancer, diabetes, and asthma continue to increase in the general public within the modern era. With careful observation of the symptoms potential diseases may be detected early and managed properly. For that to happen, the awareness of the symptoms and proper knowledge about the diseases may be needed for each patient. To acquire such knowledge, patients may need to gather essential health information from a variety of sources such as the Internet, articles, or some type of e-learning systems. However, the amount of available information, often too much, which discourages patients to continue. In response to such scenarios, we propose an approach that delivers only the relevant information that is specific to each patient’s condition. In our approach, we utilized observed symptoms and vital signs to identify potential diseases of a patient. As they use the system, their profile may be constructed to deliver patient-specific set of learning materials called a study plan. To monitor and promote their study, we developed a mobile application that allows patients to view their study plan(s) and to study the customized learning materials. Such customized learning allows patients to take control of their symptoms and potential diseases, which eventually helps them to improve their outcomes as a result.

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The presence of atmospheric hazards in confined space can contribute towards atmospheric hazards accidents that threaten the worker safety and industry progress. To avoid this, the environment needs to be observed. The air sample can be monitored using the integration of electronic nose (e-nose) and mobile robot. Current technology to monitor the atmospheric hazards is applied before entering confined spaces called pre-entry by using a gas detector. This work aims to develop an instrument to assist workers during pre-entry for atmosphere testing. The developed instrument using specific sensor arrays which were identified based on main hazardous gasses effective value. The instrument utilizes multivariate statistical analysis that is Principal Component Analysis (PCA) for discriminate the different concentrations of gases. The Support Vector Machine (SVM) and Artificial Neural Network (ANN) that is Radial Basis Function Neural Network (RBFNN) are used to classify the acquired data from the air sample. This will increase the instrument capability while the portability will minimize the size and operational complexity as well as increase user friendliness. The instrument was successfully developed, tested and calibrated using fixed concentrations of gases samples. The results proved that the developed instrument is able to discriminate an air sample using PCA with total variation for 99.42%, while the classifier success rate for SVM and RBFNN indicates at 99.28% for train performance and 98.33% for test performance. This will contribute significantly to acquiring a new and alternative method of using the instrument for monitoring the atmospheric hazards in confined space.

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For mission-critical and time-sensitive navigation of autonomous vehicles, controller design must exhibit excellent tracking performance with respect to the speed of convergence to reference command and steady-state accuracy. In this article, a novel design integration of the neural network with the traditional control system is proposed to adaptively obtain optimized controller parameters resulting in improved transient and steady-state performance of motion and position control of autonomous vehicles. Application of the proposed intelligent control scheme to mobile robot navigation was presented for an eight-shaped trajectory by optimizing a Lyapunov-based nonlinear controller. Furthermore, a Linear Quadratic Regulator-based controller was optimized based on the proposed strategy to control the pitch and yaw angles of a 2-Degree-of –Freedom helicopter. The simulation results showed that the proposed scheme outperforms the traditional controllers in terms of the speed of convergence to the desired trajectory and overall error minimization.

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An Orthogonal Frequency Division Multiplexing (OFDM) system with Quadrature Phase Shift Keying (QPSK) mapper is considered. A novel low-complexity Tone Reservation (TR) technique is proposed for reduction of Peak-to-Average Power Ratio (PAPR) of the system. The technique is easy-to-implement and minimizes the search space of phases of reserved tones in the system. The ability of PAPR reduction of this proposed TR technique is assessed and compared with conventional TR technique that uses Pseudo Noise (PN) sequences to determine phases of reserved tones. The simulation results illustrate that the proposed TR technique is nearly the same as that of the conventional TR technique in terms of PAPR reduction capability but with reduced complexity. The Bit Error Rate (BER) performance of QPSK-OFDM system with the novel TR scheme over frequency non-selective Rayleigh fading channel is also determined and illustrated.

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Trusted systems are becoming more integrated into everyday life. Security and reliability are at the forefront of trusted system design and are often directed at hardware-only solutions, especially for safety critical systems. This is because hardware has a well-established process for achieving strong, precise, and reliable systems. These attributes have been achieved in the area of safety critical systems through the use of consistent and repeatable development processes, and a standardized metric for measuring reliability. However, due to the increase in complexity of systems and the looming end of Moore’s Law, software is being incorporated more into the design of these trusted systems. Unfortunately, software typically uses agile development in modern design and uses unreliable metrics for illustrating reliability. This does not make it suitable for safety-critical applications or for total system reliability in mixed hardware/software systems. Therefore, a comprehensive process of systems development needs to be utilized to allow for total system specification at the beginning and a comparable reliability metric in the end which covers software and hardware. Henceforth, we discuss an initial solution to these problems, leading to the establishment of a development process that allows for the proven correctness of a system specification via formal methods. This process also establishes a testing and error reporting process to allow software to be represented in a way that allows the application of reliability metrics similar to those used for hardware.

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Robotic catching of thrown objects is one of the common robotic tasks, which is explored in a number of papers. This task includes subtask of tracking and forecasting the trajectory of the thrown object. Here we propose an algorithm for estimating future trajectory based on video signal from two cameras. Most of existing implementations use deterministic trajectory prediction and several are based on machine learning. We propose a combined forecasting algorithm where the deterministic motion model for each trajectory is generated via the genetic programming algorithm. Object trajectory is extracted from video sequence by the image processing algorithm, which include Canny edge detection, Random Sample Consensus circle recognition and stereo triangulation. After that rajectory is forecasted using proposed method. Numerical experiments with real trajectories of the thrown tennis ball show that the algorithm is able to forecast the trajectory accurately.

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In this paper, behavioral approach has been adopted for the calculation of total power losses that has been further used to derive an analytical model for the conduction and switching losses in a boost Power Factor Correction (PFC) stage of an On-board Charger (OBC). Detailed investigation of power losses can help in finding out ways to improve efficiency and for this purpose, commutation-speed based methodology has been used to split total power losses into their root causes. This gives opportunity to find the impact that an individual part creates on total losses which can serve as a starting point for efficiency improvement. For the analysis, two devices (IGBT with Si diode and IGBT with SiC diode) are used in the considered topology of PFC and a reduction of 40% was calculated when SiC diode was used instead of Si with the same IGBT. Hence it was found that the implemented method proves to be significantly useful in the optimization of efficiency.

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The task of optimal path planning for drilling tool with numerical control is considered. Such tools are used in the production of printed circuit boards. The algorithm modification of level-by-level route construction for the approximate solution of the traveling salesman problem is discussed. Bypass objects can be specified either as a table of distances or values represented by a symmetric matrix, or as Cartesian coordinates (in applied cases of using numerically controlled equipment). The algorithm was tested on many different examples. As a result of the calculations performed for examples from the TSPLIB library (defined through a full distance matrix or Cartesian coordinates) with a dimension of up to 100 cities, the ability of the algorithm to construct the optimal route was confirmed. For examples from other sources or for artificially constructed ones (up to 130 objects), in the testing of the algorithm, the declared record values of the route minimum length were also achieved or improved.

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Modern automobiles have been turning more and more into wireless sensor and communication networks. Accordingly, the number of radio systems is steadily increasing. Due to strict safety requirements, these radio systems need to be tested extensively for functionality and reliability, especially under poor radio channel conditions. Beside the large electrical size of cars at frequencies of mobile communication services, access to the antennas imposes challenges for testing, due to an increasingly high integration of the antennas with frontends and digital signal processing. This paper proposes an over-the-air testing procedure for automotive radio systems on the basis of the wireless communication standard Long Term Evolution (LTE). A method to derive the radiation patterns of automotive antennas from reference signals in the LTE downlink scheme without requiring any access to the analogue RF feed point is proposed. A comparison of the LTE approach with the usual antenna measurement techniques shows good agreement. As a logical step from the antenna towards a complete wireless link, a concept of spatially distributed channel emulation on the basis of Software Defined Radio (SDR) modules is proposed, aiming at the emulation of essential multipath features of the wireless channel. RF measurements of the channel transfer function as well as by over-the-air end-to-end tests prove this approach to be a cost-efficient alternative to commercial channel emulators.

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Knowing how and types of talk shows discussed in social media is significant to all stakeholders in a talk show’s program. There are many messages that can be found in social media that need to be noticed so the messages from the user could reach the viewer. Social media provides promising as well as challenging data to business intelligence. By using data warehouse and business intelligence, the data from social media can be proceeded to monitor and understand adoption and sentiment. In this research, data warehouse and business intelligence will be designed and implemented using data from social medias; Facebook, Twitter, Instagram, and Youtube which are expected to be the source to do monitoring to social media contents that are shared by each stakeholder from the talk shows that are going to be analyzed. As for the sentiment analysis, word2vec, Naïve Bayes and Random Forest will be applied for the qualification methods. As a result, this monitoring is used to give understanding of how information spread and the sentiment which underlies the spreading messages could give critical perception to the management on how their product recognized and valued in society.

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The 5G is the fifth generation of mobile broadband, cellular technologies, and networks that promises a major change in mobility by evolving connected business realities. In such an emerging environment, reliable Service Level Agreements (SLA) and anticipation of breaches of Service Level Objectives (SLO) become compulsory. Thus, guaranteeing the required service quality, while also ensuring efficient recourse allocation becomes a challenge. In addition, 5G networks are expected to provide diverse Quality of Service (QoS) guarantees for a wide range of services, applications and users with a variety of requirements. However, there is an increased difficulty in translating user-friendly business terms into resource-specific monitoring attributes that can be used to manage resources in the 5G core network. To address these gaps, an SLA management framework, enabling QoS provisioning is introduced. The aforementioned framework will be supported by an adaptive monitoring algorithm, which removes the static time interval used in the monitoring system, in order to provide highly accurate information in real time, without the produce of unnecessary traffic to the network. The proposed architecture also incorporates a recommendation mechanism to determine the significance of various QoS parameters in order to ensure that relevant QoS metrics are included in the SLAs, using enriched metadata information from a Network Function Virtualization (NFV) Catalogue.

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This paper explores the problem of robust synchronization of complex dynamical network with stochastic coupling and time-varying delays through the application of nonfragile control. A well defined Lyapunov Krasovskii functional is established and by employing the widely acknowledged extended Jensen’s integral inequality and the Bernoulli’s distribution sequences, the stochastic nature of network coupling is modeled which entails the occurrence of randomness in the controller gain uncertainties are presented. Sufficient delay dependent conditions are given for the purposes of synchronization. Additionally, a nonfragile controller is designed based on linear matrix inequalities (LMIs). Two numerical examples are finally given to exhibit the effectiveness and usefulness of the proposed theoretical results.

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A systematic study of wide bandgap (WBG) based light emitting diodes (LEDs) and photodiodes (PDs) were conducted for the assessment of modular integration of optoelectronic devices into power modules. The temperature dependence of the photoluminescence (PL) efficiency of Indium gallium nitride/Gallium nitride (InGaN/GaN) multiple quantum wells (MQWs) material was studied from 10 to 800 K. The photoluminescence efficiency is calculated using the power law relation connecting the integrated photoluminescence signal and the excitation pump power. A peak PL efficiency of 43.97 % was recorded at 800 K. Electroluminescence (EL) study was conducted on Gallium nitride (GaN) based LEDs in the temperature range of 300 – 800 K. An intensity drop of three orders of magnitude is recorded at 800 K as compared to room temperature. The full width half maximum (FWHM) of the spectra was also calculated from the EL measurements. The S-shaped shift of FWHM at high temperature indicates a strong localization effect. High-temperature spectral response analysis of 4H-Silicon carbide (4H-SiC) pn-junction photodiode is performed at zero voltage bias condition. Enhancement of spectral response is observed at higher wavelengths due to increased phonon population at higher temperatures.

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Combining state-of-the-art additive manufacturing technologies with structural optimization has the potential to produce geometrically complex multi-material components with integrated functionalities and desired structural behavior. In this article, the simulation-driven design process of a multi-material light-weight gripper with an integrated pneumatic bellows actuator is described. The design of the bellows structure is based on a previously published contribution to the RoboSoft2018 conference in Livorno, Italy. The conference paper contains the shape optimization and experimental investigations of the structural and fatigue behavior of linear type multi-material PolyJet bellows actuators. In this extended version, the main findings of the conference paper are translated into the design of a rotary type bellows actuator that is finally integrated into a multi-material light-weight gripper. In order to define the lay-out of the gripper’s support structure, a density-based topology optimization is performed and the application on a PolyJet printed light-weight robot is demonstrated. The presented design approach and results are useful for researchers and engineers involved in the development of multi-material additive manufacturing, simulation-driven design and functionally integrated structures for pneumatic robotic systems.

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Food waste disposal and food availability are both problems in the world today. The ability to monitor food waste is currently limited by the use of manual data collection and sparsity of monitoring. Using sensors to automate the process of measuring and collecting data on food waste would allow constant monitoring and provide a better dataset for analysis. This data can also be used to create ambient displays geared educate a target audience and produce behavioral changes. Student cafeterias serve as the focal point for data collection within this study, presenting both an abundance of data and unique challenges. We have created, deployed, and tested an autonomous, real-time system to collect data on food waste which includes an ambient display tailored to effect behavioral change in students.

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Relation Extraction is an important subtask of Information Extraction that involves extracting significant facts from natural language text. Extracting structured information from the plaintext is the ultimate goal of IE systems. The Indian language content on the internet is increasing day to day. Extracting relevant information from this huge unstructured data is a challenging task especially when the business firms are interested in ascertaining public view on their products and processes. The primary objective of relation extraction systems is to find those entities which can be targeted through social networking and digital marketing. Cannibalisation of the product is nowadays done using these Social Networks. Different methods are proposed and experimented for Relation extraction problems. In this paper, we propose a Relation Extraction system using Convolutional Neural Networks. Deep learning based methods have produced state of the art results in many domains. Training and testing are conducted using the shared corpus provided by ’ARNEKT-IECSIL 2018’ competition organisers. The evaluation results show that the proposed system could outperform most of the reported methods in the competition.

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In advanced metering infrastructure (AMI) of smart grid, WiFi is an appropriate choice for its bidirectional communication requirement to transmit data to the billing center. But, WiFi functions in the free spectrum bands and LTE also requires to use the same free bands for its network expansion being licensed spectrum is limited and expansive. LTE and WiFi can operate simultaneously in the 3.5 GHz band (also known as citizen broadband radio service (CBRS)), which has large amount of free and clean spectrum. In this paper, we propose a smart grid metering infrastructure based on fixed duty cycled LTE and WiFi, where smart meters and its’ data collectors (known as Access Point) use WiFi and LTE, respectively, for transferring data. Under a system level simulation environment, we investigated the LTE-WiFi coexistence performance in CBRS band considering a time division duplexing (TDD)-LTE associated with FTP traffic, and IEEE 802.11n (WiFi). The simulation performance demonstrates a good neighborhood coexistence between WiFi and LTE, which makes it a potential communication solution for the AMI.

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Consumers of electrical energy have looked more closely to the energy consumption in last years due to the successive increase of the electricity bill. Nowadays it is possible to notice that many consumers have been looking for ways to reduce their consumption or the value of their electricity bill. Such a cost reduction is obtained mainly by means of own generation, distributed generation, investment in electrical efficiency, migration to the open market, or intelligent demand management. Considering that there are opportunities to reduce the bill at the end of the month for consumers that opt for the Free Market, particularly companies that has the possibility to reduce their energy consumption, is proposed here the development of a system (hardware and software) implemented in LabVIEW and hardware resources of National Instruments company, to make an intelligent demand management system for a free consumer. The program looks optimize the financial results through the demand response concept taking advantage of the price difference in the spot market. A study was done for the Federal University of ABC – UFABC in Santo André Brazilian city looking for check the implemented system. Authors hope that the results obtained with this system can help companies and consulting firms in the decision-making process as some companies can eventually adopt the energy open market. Therefore, this article seeks contribute to the reduction of monthly costs of companies through the developed system. The importance of this system lies in the fact that it is possible to identify loads considered as non-priority and can therefore be temporarily disconnected in order to maintain energy consumption within the limits established in contracts with the energy concessionaire. The results presented here are quite promising taking into account that the intelligent management of demand in the free energy market is still underexplored.

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Consumers of electrical energy have looked more closely to the energy consumption in last years due to the successive increase of the electricity bill. Nowadays it is possible to notice that many consumers have been looking for ways to reduce their consumption or the value of their electricity bill. Such a cost reduction is obtained mainly by means of own generation, distributed generation, investment in electrical efficiency, migration to the open market, or intelligent demand management. Considering that there are opportunities to reduce the bill at the end of the month for consumers that opt for the Free Market, particularly companies that has the possibility to reduce their energy consumption, is proposed here the development of a system (hardware and software) implemented in LabVIEW and hardware resources of National Instruments company, to make an intelligent demand management system for a free consumer. The program looks optimize the financial results through the demand response concept taking advantage of the price difference in the spot market. A study was done for the Federal University of ABC – UFABC in Santo André Brazilian city looking for check the implemented system. Authors hope that the results obtained with this system can help companies and consulting firms in the decision-making process as some companies can eventually adopt the energy open market. Therefore, this article seeks contribute to the reduction of monthly costs of companies through the developed system. The importance of this system lies in the fact that it is possible to identify loads considered as non-priority and can therefore be temporarily disconnected in order to maintain energy consumption within the limits established in contracts with the energy concessionaire. The results presented here are quite promising taking into account that the intelligent management of demand in the free energy market is still underexplored.

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The aim of this article is to analyze and evaluate the performance of Coordinated Multipoint (CoMP) transmission approach at a frequency of 28 GHz using three dimensional ray tracing simulations in an urban macrocellular environment. The new performance metric introduced in this article is the relative power usage. Other performance metrics examined in this article are received power, the Signal to Interference plus Noise Ratio (SINR), user throughput, relative throughput gain, and the percentage of overlapping area with multiple cells. Indoor and outdoor users are separately analyzed for few key performance indicators. Different cases of coordinated multipoint transmission i.e. intra-node and inter-node coordination is analyzed. The post analysis of the acquired simulation data shows that the use of CoMP functionality is more beneficial for the cell edge users compared with the other users in terms of improving the user’s experience. The throughput gain as well as the transmission overhead of the CoMP approach increases with the increase in number CoMP ports. Inter-node CoMP is much more power efficient and beneficial in comparison with the intra-node CoMP case.

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The paper presents a novel concept of design of electric system for Off-shore Wind Power Plant (OWPP) based on frequency. In the literature, a new transmission system i.e. Fractional Frequency Transmission System (FFTS) has been proposed as an economic alternative to High Voltage AC (HVAC) and High Voltage DC (HVDC) for power transmission from Off-shore Wind Farm (OWF) to on-shore grid. In the FFTS power transmission is proposed at 1/3rd of conventional frequency (50Hz). The choice of this frequency (50/3Hz) for FFTS is not based on any mathematical analysis and seems to be a compromise. Since, frequency is one of the prominent parameter that reflects on the project economy, the paper explores on the choice of operational frequency for electric system in view of reduction in the investment cost. The existence of optimum frequency is realized based on the finding that, the costs of power system components are frequency-dependent and they imbibe the trade-off in their costs. The paper presents a comprehensive methodology to compute the most economical operational frequency for electric system by optimization of frequency-based cost model of the system using Genetic Algorithm (GA). The proposed methodology is applied to 160MW OWF (Horns-Rev) as a case study. For off-shore distances of 50km, 100km, 150km and 200km, the optimum operational frequencies are obtained as 52Hz, 32Hz, 22Hz and 16Hz respectively. The proposed methodology for the design of electric system based on frequency results in significant saving in the investment cost for moderate transmission distance. Hence it is concluded that, the work presented in this paper gives a new dimension for planning and cost effective design of electric system for OWPP. Further, it promotes the investor for deployment of OWF which leads to reduction in air pollution and global warming which are major concerns of the world today in the endeavor.

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Nowadays over speeding is one of the most common traffic violations. Generally, over speeding is the result of restless and bad behavior of drivers. As the accident rates are increasing it is important to develop and implement a system which can automatically detect and report over speeding to the traffic control authorities as early as possible. Nearly all the roads are marked with speed limits depending upon the size of moving vehicles and heaviness of traffic, but some drivers habitually ignore this speed limit. The advancement in technology has replaced most of the manual or semi-automatic systems with an automated system. To add on to various systems in place, this research is making the use of Internet of Things to detect and report over speeding of the vehicle on which the device has been preinstalled. IoT is a technique to integrate various devices to exchange data among themselves. This research proposes the design, development and functioning of a smart device that helps in automatically detect and report to competitive authority, when so ever the subject vehicle exceeds the speed limit. The device has been developed based on the Global Positioning System (GPS) Technology using Raspberry Pi hardware and Android OS and has been practically tested on real time basis by installing it in a car.

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In this paper, an analytical modeling is proposed to compute the static and dynamic characteristics of linear variable reluctance motors with taking account of the saturation and the non-linearity of the magnetic circuit. The proposed model is based on the Fourier series expression of the phase flux in which the variation of the linkage flux with phase current is defined by arc tangent function. Then, an analytical expression for the co-energy and electromagnetic forces are derivative. The effectiveness of the proposed method is proved in terms of accuracy by comparing the computed results obtained by the two dimensional finite elements method with analytic model. Subsequently, the proposed modeling approach is simple and provides accurate representation of linear variable reluctance motor, as confirmed by the compared results.

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In the last years, industrial company began to understand the central role that plays sustainable supplier selection (SSS) process for obtaining a sustainable supply chain (SSC). This paper proposes a new multi-criterion decision-making (MCDM) model for managers, which makes it possible to select the best suppliers who respect the sustainable development (SD) concept for a SSC. We start our paper by selecting the most recent economic, environmental and social criterion used in researches. After, we develop a new model mathematic that take into consideration the SD criteria in sustainable supplier rank and selection. Finally, we present a case study for testing our model.

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The telecommunications industry continues to move forward with plans for 5G service with rates including 6Gb/s followed by upgrade paths promising 20Gb/s. Despite advances in wireless technology associated with 5G roll-outs, there remains the problem of providing sufficient backhaul throughput and efficient handling of hand-off services within the relatively small projected cell boundaries that can handle the higher frequencies required for these data rates. Dense network discussions include proposals for macrocell centric groupings that directly support multiple micro-cells to create a larger service area. The two-tiered approach presents additional complexities when considering the dynamic nature of mobile wireless networks. The added delays of multi-tier hand-offs compound the already heavily burdened throughput capability of the back-haul service towers. The 5G enabled network should easily allow legacy technology 4G and 3G connectivity without sacrificing usable bandwidth by dedicating limited back-haul ports to legacy technology. The presented methodology is a hybrid distributed optical switch embedded directly within the micro-cell towers that simplify hand-off and allows for dynamic allocation of bandwidth on demand. Simulation results and a test-bed optical network interface suggests that bandwidth on demand topology is possible combined with software-defined dynamic routing in a flat plane topology. The solution uses already available technology found in high-speed Internet backbone distributions.

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The traditional long-term evolved (LTE) network architecture faces major challenges due to the rapid development of mobile intelligent applications. Evolved packet core (EPC) network, as the core network of the LTE system, faces the same problem as well. In this paper, we propose an innovative EPC architecture, i.e., Not only stack (NOS)-EPC, in which we redesign the control paradigm based on the NOS framework. NOSEPC contains the user plane (U-plane), the control plane (C-plane), the management plane (M-plane), and the global network view (GNV). By using NOS framework, distributed control paradigm is turned into a centralized manner which simplifies the signaling flows, reducing the procedure latency and overheads. The operation of NOS-EPC is expounded by four main EMM procedures, including initial attachment, service request, handover, and detachment. Through comparison to LTE/EPC, and software-defined networking(SDN)-EPC, we elaborate the advantages of NOS-EPC on operating expense (OPEX), scalability, flexibility, signaling overheads, and user traffic transmission capability. The simulation results confirm that the proposed NOS-EPC takes advantages on the procedure latency and signalling overheads compared to the other EPC solutions, e.g., LTE/EPC and SDN-EPC.

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We have already succeeded in findings that stereoscopic video clips enhance brain activity. We herein increase the knowledge about the in?uence of 3D and blurred images on the human body, especially on brain activity. From of old, it has been pointed out that the motion sickness is induced by the blurred images. In this study, stabilogram and cerebral blood flow are measured to investigate the process in the brain during the 3D sickness. Activity in the ventral and dorsal streams is enhanced. The most suitable cutoff frequency for viewing the effects of the dorsal stream are estimated between 0.1–0.3 Hz in a Fourier-Shuffle surrogate data analysis of the cerebral blood flow.

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The research programme reported in this paper is set within the framework of our research under the theme of ICT support for Active Healthy Ageing (AHA). This longitudinal empirical research is focused on the study of the impact on the management of cardio-vascular disease if supported by sustained health monitoring using wearable connected devices. One of the key objectives is stress monitoring and its classification during the daily routine of life thus enabling psycho-physiological monitoring to study the correlation between emotional states including variable stress levels and the evolution and prognosis of cardiovascular disease. In this paper, the calibration phase will be studied in order to distinguish between two emotional states: i) meditation and ii) stress condition. For this, the Heart Rate Variability (HRV) features are used as extracted from the RR interval and a support vectors machine (SVM) classifier deployed which resulted in 74% and 87% recognition accuracy based on HRV data for the recognition of the two emotional states, namely meditative, and, stressed, respectively.
The main objective is to prevent Cardio-Vascular Disease (CVD) in healthy people and to treat those who already suffer from it. Creating a reference database was our first step in this research project. The sensor choice was made based on doctors’ recommendations. The work methodology was as follows: first validate the « objective data » issuing from the calibration state. Second, set up the automatic algorithm and detect automatically the patient’s emotional states during the experimentation period (subjective data). Third analyse the physical activities correlated to the blood pressure and emotions. This study has involved the challenge of distinguishing the influence of stress versus relaxation on the Cardio-Vascular function and in particular on the risk of exacerbation of pre-existing Cardio-Vascular Disease.

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In this paper, a novel method is proposed for the dynamic analysis of fractional- order three-dimensional electrically coupled cell network. In general, three- dimensional cell network is constructed by combining three one-dimensional circuit networks. Analysis method is based on the principles of the dynamic analysis with transfer function approximation. Although fractional-order three-dimensional circuit network model contains nonlinear fractal elements such as fractional-order capacitors and inductors, transfer function approximation is employed in dynamic analysis of the network by using the Laplace transform.
First by using nodal analysis method, general expression in matrix forms for the transfer function and typical equivalent impedance of the fractional-order three-dimensional circuit network are derived in fractional domain. Transfer function and Equivalent network impedance of the cell network model are obtained in the form of matrix equation with the implicit analytical expression. Secondly the effects of five network parameters such as inductance L, capacitance C, number of cell unit n and fractional- orders (?, ?) on the impedance and electrical network characteristics such as transfer function and output responses are investigated by means of MATLAB Simulation programs. Finally, the validity of the proposed method is done by using PSPICE simulations which show the experimental performance and PSPICE simulation results is presented.

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Digitization is viewed as the capability to utilize digital technologies for generating processing, sharing and transacting information. Studies show that digitization has now become ubiquitous. In almost all the sectors, we routinely interact with digital technologies. As a result, the impact of digitization is being observed in such sectors. For instance, the positive impact of digitization in education sector includes more efficient administration, reduction in workload, better accessibility to information, better management of school resources and enhanced quality of reports. However, in the context of secondary schools, the literature is conspicuously silent on the formal way of assessing the impact of digitization on both the academic performance and service delivery. As an attempt to address the gap, this paper describes a model that can evaluate the impact of digitization in such schools. Python programming tools were used to demonstrate implementation of the model. The model can help governments to formulate policies related digitization of secondary schools and can also be used by funding organization to demonstrate accountability when making investment decisions.

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Digitization is viewed as the capability to utilize digital technologies for generating processing, sharing and transacting information. Studies show that digitization has now become ubiquitous. In almost all the sectors, we routinely interact with digital technologies. As a result, the impact of digitization is being observed in such sectors. For instance, the positive impact of digitization in education sector includes more efficient administration, reduction in workload, better accessibility to information, better management of school resources and enhanced quality of reports. However, in the context of secondary schools, the literature is conspicuously silent on the formal way of assessing the impact of digitization on both the academic performance and service delivery. As an attempt to address the gap, this paper describes a model that can evaluate the impact of digitization in such schools. Python programming tools were used to demonstrate implementation of the model. The model can help governments to formulate policies related digitization of secondary schools and can also be used by funding organization to demonstrate accountability when making investment decisions.

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In previous study, it is difficult to estimate the biological states such as postural ones and aetas in accordance with the previous analysis of electrogastrograms (EGGs), basically the frequency resolution of healthy individuals. In addition, few studies have compared gastric myoelectrical activity in supine and sitting posture. The aim of this study is to evaluate the severity of 3D sickness in daily life. The authors herein conduct nonlinear analysis of EGGs of the healthy young and give the feasibility to discriminate the postural differences. It is suggested that the EGGs acquired in the seated position have increased wavelength irregularity and attractor complexity than those acquired in the supine position.

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