Volume 3, Issue 6

Metaheuristic hybridization has recently been widely studied and discussed in many research works as it allows benefiting from the strengths of metaheuristics by combining adequately the dierent algorithms. MMACS is a new hybrid ant colony optimization algorithm based on the foraging behavior of ants. This algorithm presents two hybridization levels. The first hybridization consists in integrating the Ant Colony System selection rule in MAX-MIN Ant System. The second level of hybridization is to combine the hybridized ACO and an algorithm based on a local search heuristic, then both algorithms are operating sequentially. The optimal performance of MMACS algorithm depends mainly on the identification of suitable values for the parameters. Therefore, a comparative study of the solution quality and the execution time for MMACS algorithm is presented. The aim of this study is to provide insights towards a better understanding of the behavior of the MMACS algorithm with various parameter settings and to develop parametric guidelines for the application of MMACS to the Strongly Correlated Knapsack Problems. Results are compared with well-known Ant Colony Algorithms and recent methods in the literature.

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Advances in technology have enabled the installation of an increasing number of sensors in various mechanical systems allowing for more detailed equipment health monitoring capabilities. It is hoped the sensor data will enable development of predictive tools to prevent system failures. This work describes continued analysis of sensor data surrounding a seizure of a turbocharger within a propulsion system. The objective of the analysis was to characterize and distinguish healthy and failed states of the turbocharger. The analysis approach included mapping of multi-dimensional sensor data to a low-dimensional space using various linear and nonlinear techniques in order to highlight and visualize the underlying structure of the information. To provide some physical insight into the structure of the low-dimensional representation, the transformation plots were analyzed from the perspective of several engine signals. By overlaying operating ranges of individual sensor signals, certain regions of the mappings could be associated with distinct operational states of the engine, and several anomalies could be related to various points in the turbocharger seizure. Although the failed points did not map to an obvious outlier location in the transformations, incorporating expert domain knowledge with the data mining tools significantly enhanced the insight derived from the sensor data.

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Our research deals with the single-vehicle routing problem (VRP) with multi-shift and fuzzy uncertainty. In such a problem, a company constantly uses one vehicle to serve demand over a scheduling period of different work shifts. Our issue relies on a routing problem in maintenance jobs, where a crew executes jobs in different sites. The crew runs during several work shifts but repeatedly returns to the depot before the shift ends. The goal is executing all the activities minimizing the makespan. We examine the impact of uncertainty in driving and maintenance processing time on system performance. We realize an Artificial Immune Heuristic to find optimal solutions considering both makespan and overtime avoidance. First, we introduce a framework to assess the uncertainty impact. Then, we produce a numerical company case study to examine the problem. Outcomes present significant improvements are obtained with the proposed approach.

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This article discusses IoT security in situations whereby devices do not share the same security domains, which raises security, privacy and safety concerns. It then presents an Access Control and Privacy infrastructure for addressing these concerns in the context of distributed environments. IoT deployments allow billions of connected physical devices to collect, process and share data; collaborate and cooperate in automating tasks in an unrivaled fashion. However, security and safety are still top major fears that demand holistic approach, particularly when devices do not share the same digital trust. This is not a surprise, as a revolutionary system, IoT comes with inherent vulnerabilities, threats and risks like most other computing and data processing systems. Conversely, when security breaches or compromises occur, it is most likely to have a far-reaching and upsetting consequences that extends traditional concerns. The fact that IoT can be deployed in plethora of application scenarios; means that end-to-end security should be treated contextually and in a dynamic manner. Consequently, these concerns; trust, confidentiality, and privacy at the IoT application stack need to be addressed robustly. Thus, in this article, a novel distributed access control infrastructure based on configurable policy constructs is presented. The infrastructure provides a mechanism for gradual negotiated release of provable attributes to dynamically build trust before protected resources are made available. In this configuration, IoT transaction parties can express their Capabilities (competences, features, etc.) and Requirements (rules and provable attributes required to access the capabilities) as the basis for sharing data or collaboration in solving business problems.

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Acute Myocardial Infarction (Heart Attack), a Coronary Heart Disease (CHD) is one of the major killers worldwide. Around one thousand data has been collected from AMI patients, people are at risk of maybe a heart attack and individuals with the significant features closely related to heart attack. The sophistication in mobile technology, health care applications offers remarkable opportunities to improve our health, safety and in some sense preparedness to common illnesses. The excess delay time between the onset of a heart attack and seeking treatment is a major issue which may lead to permanent blockage or even die often. So, a proficient mobile application approach is projected in this paper that may predict the possibilities of a attack once an individual is bearing the noticeable symptoms of chest pain. Random forest predicts the result of the user input features and the automated result is shown on the smartphone application. The application categorizes the prediction of the user’s input as a heart attack, maybe heart attack and no heart attack. The experimental results showed that the accuracy of the proposed technique is 92%, whereas the precision is 95%, 92%, 87% respectively for heart attack, maybe heart attack and no heart attack prediction. Our research target is to raise heart attack awareness on time in an innovative way through available and accessible medium to mass people.

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There are high expectations for commercial cloud services as an economical computation resource when executing scientific computing workflows, for which the computation is increasing on a daily basis. However, no method has been developed for determining whether a scientific computing workflow can be executed at a low usage cost, and thus scientists have difficulty in selecting from the diverse range of computational resources. The aim of this study is to provide clear criteria for selecting a computational resource while executing a scientific computing workflow. This study focuses on the performance of application execution for one such commercial cloud service, Amazon EC2, and proposes a method for selecting the optimal resource showing high similarity to a target application in execution time and usage cost. The novelty of this study is its approach of employing application similarity in resource selection, which enables us to apply our method to unknown applications. The contributions of this work include (1) formularizing performance values of computational resources, as well as similarity values of applications, and (2) demonstrating the effectiveness of using these values for resource selection.

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This study presented a prototype augmented reality (AR) application that helps visualize the affordances of everyday objects for infants in their home environments to prevent accidents and promote development. To detect and visualize affordances, we observed 16 infants regarding how they perceive and handle common objects from 4 to 12 months of age in their homes in Tokyo, Japan and in Lisbon, Portugal. Based on the longitudinal observation data, we developed an AR application for handheld devices (iPhone and iPad) and tested two types of vision-based markers. Ten types of basic objects were selected from the results of the observation and embedded into the AR markers. AR contents illustrated infants’ actions toward objects based on actual video data recorded for security purposes. To confirm the prototype’s advantages and improvements, informal user interviews and user tests were conducted. The results demonstrated that the prototype reveals the relationship between infants and their home environments, what kinds of objects they have, how they perceive objects, and how they interact with these objects. Our study demonstrates the potential of this application’s AR contents to enable adults to better understand infants’ behavior towards objects by considering the affordances of everyday objects. Specifically, our app assists in improving the perspective of adults who live with infants and promotes the creation of more flexible and safer environments.

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Climate change, increasing fuel oil prices and new international regulation on ship emissions lead to more focus on shipping fuel consumption and energy efficiency. There are various solutions for improving the ship energy efficiency. In this manuscript, we aim to present a real case of energy saving by adopting the central cooling system with box cooler on the ship instead of conventional system. The electric energy power necessary for operating the machinery cooling system of the ship is calculated for conventional cooling system and compared to the cooling system using box coolers in term of fuel oil consumption and CO2 emissions. This study quantified the fuel saving potential that could be achieved with use of keel coolers. Adopting central cooling with box coolers may contribute in reduction of fuel oil consumption and improving the ship energy efficiency. systems. should not contain citations.

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Climate change, increasing fuel oil prices and new international regulation on ship emissions lead to more focus on shipping fuel consumption and energy efficiency. There are various solutions for improving the ship energy efficiency. In this manuscript, we aim to present a real case of energy saving by adopting the central cooling system with box cooler on the ship instead of conventional system. The electric energy power necessary for operating the machinery cooling system of the ship is calculated for conventional cooling system and compared to the cooling system using box coolers in term of fuel oil consumption and CO2 emissions. This study quantified the fuel saving potential that could be achieved with use of keel coolers. Adopting central cooling with box coolers may contribute in reduction of fuel oil consumption and improving the ship energy efficiency. systems. should not contain citations.

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Exploring the ocean underneath has always been an area of great scientific and environmental concern. However, the study of underwater environment was very difficult due to the extreme conditions. Undersea descriptions undergo severe distortion attributed to absorptive as well as scattering properties. Absorption substantially removes illumination, whereas a ray of light redirected in several path when it interacts by substance. Because of these, undersea descriptions encompass blur as well as color loss. In this paper we suggested an effective technique namely, a turbidity removal method for deblurring the image. If the deblurred image has a lighting problem, we make use of a color-correction method to find the clear image. Our substantial qualitative and quantitative assessment expose that the proposed algorithm progress the excellence as well as lessen color distortion loyally, also improves the state-of-the-art undersea technique.

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In the world today, the rapid development of the Internet of Things (IoT) and the application of the Connected Vehicle Cloud (CVC) as the Internet of Things in the intelligent transportation are becoming widespread. They can improve people’s safety, vehicle security as well as reduce the cost of ownership of an automobile. At the same time the security of the Internet is a non-negligible factor in the development of the Internet of Vehicles. Therefore, the security of vehicle networking is of great concern. This article starts with the network architecture of vehicle networking and combines the examples of vehicle networking security issues, which analyzes and researches the security problems of vehicle networking, and proposes solutions to the security problems faced.

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This is a study on non-bearing masonry walls, in a high, reinforced concrete walls building. It will be built in Bucharest, Romania. This is a high seismic area. The building will be used as a dwelling. The structure is composed of a ground floor and 10 stories above. It is interesting to see the interaction between the structure and the partitioning masonry walls. The paper presents the non-bearing walls design, the structure’s behavior in the elastic and plastic stage, in particular the failing mechanism and the non-bearing walls stresses development. The paper will also compare the non-bearing walls seismic force from the design code and from the model. It will show the non-bearing walls important effect on the structure’s behavior in the elastic and plastic stage.

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This is a study on a confined masonry slender walls building in a high seismic area. The structure also contains frames, but the walls bear most of the gravity and seismic loads. The building will be used as a school. It will be built in Bucharest, Romania. It contains a ground floor and 2 stories above it. Story height is 4m. The structure is interesting as it is not common practice to use slender masonry walls for buildings with large bays. Such a structure is allowed by the design codes in force but this solution is not often used. The building will be studied in the elastic state, as the structure bears important gravity and seismic loads, then in the plastic state to establish the walls stresses development and the failure mechanism. It is interesting to see how the walls behave in the nonlinear stage, as they are slender, but masonry is a stiff material.

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This was a study on the behavior of a confined masonry bearing wall in a medium height dual building. This wall had to be placed at one corner of the building. It had to be a masonry wall, not to be too stiff and drag the rigidity center too far from the building’s center. The structure’s stiffness was also to be analyzed by using a concrete wall instead of the masonry one, as an alternative solution. This showed the importance of using a masonry wall. The dual structure contained only one other wall, made of reinforced concrete. The 2 bearing walls bore most of the shear force from seismic loads, because they were the stiffest load bearing elements in the structure. It was interesting to see if the masonry wall could bear these loads. The structure was unusual, as it contained frames, a concrete and a masonry wall. These elements behave differently. The structure was analyzed for both the elastic and plastic stage. The loadbearing elements stiffness, the stresses development and structure failure mechanism were studied for both solutions. The results showed it is appropriate to use a masonry wall at the corner. This wall can bear the loads it is subjected to.

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This paper deals about an application of optimal power flows (OPF) constrained with synchronous generator capability curve for power market analysis (SGCC). OPF main features gather in its mathematical formulation non-convexity, non-linearity, and it shows to be a hard to solve optimization problem. In some operational scenarios, SGCC can limit power flows bringing the theoretical OPF situation to not be applied for real context on power plants. Thus, for electric market analysis solutions without those constraints could provide results that are not exact for systems Locational Marginal Prices (LMPs), messing with the power cost estimation .For this work SGCC includes limits of current and power, preserving the generator against overheating and immoderate mechanical stress. Properties of convexification brings to mathematical problems in general a good performance if compared to original problem and a simpler way of its formulation and solution. Thereby, OPF formulation is given as a second order cone programming (SOCP) approach handled by techniques of convex relaxation, with active power generators cost objective function. Numerical results are obtained in MATLAB® environment and applied in IEEE 14-bus test system. OPF results shows the good performance of the proposed methodology, whereas solutions will not violate SGCC limits constraints.

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This paper showed visualization of technics about cardiopulmonary resuscitation contributed to acquiring the skills and understanding them. Especially, this system is focused on the individuality in each object (men, women, and babies) There are problems of a general cardiopulmonary resuscitation (CPR) training because learners are generally taught by instruction based on a subjective judgment. Because of this way, they are difficult to get a knack about the CPR themselves.
Our system solved these problems by using Kinect (Augmented Reality) and Wii Balance Board (Weight Scale) when it calculates pressure and posture. They can understand the CPR training as fixed information. The system also expresses the features of compression as results whether the posture is extension or bending. However, it cannot evaluate a process of the compression. In the inspection, 84 people wrote a questionnaire which focused on impression of before and after. This questionnaire expressed two things. The one is that general public don’t know the presence of CPR for infants. The other is that visualization was effective and enjoyable. As future works, Another function is going to be added to the present system to evaluate CPR in a process.

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The drive for this report is to inaugurate the innumerable techniques espoused by the refactoring tools in coding development. The software product is a very complex and time-consuming process of development. Difficulty understanding and maintaining poorly designed software systems Software maintenance can take up to 50% of total development costs for software production. As a modus operando, the refactoring tools purpose ultimately to amend the basis codes into an easier and more comprehensible way.
Moreover, refactoring succors to check the trifle of the coding procedure. This is apparent through having deliberation on the program catalog, precision and the use of the deconstruct trees. Refactoring tools are convenient for innumerable observes done by the human beings. Software refactoring has a direct impact on reducing the cost of software maintenance by changing the internal structure of the code without changing its external behavior. So the time taken to process as well as doing a critical analysis of complex codes is reduced.
This report proposes to have a precarious scrutiny on the various use including the pluses of using refactoring tools.

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Optical switching provided the means for the development of Data Centers with high throughput interconnection networks. A significant contribution to the advanced optical Data Centers designs is the Nephele architecture that employs optical data planes, optical Points of Delivery (PoD) switches and Top of Rack (ToR) switches equipped with 10 Gbps connections to the PoDs and the servers. Nephele follows the Software Defined Network (SDN) paradigm based on the OpenFlow protocol and it employs an Agent communicating the protocol commands to the data plane. The current paper presents a management tool for the Agent. The Agent’s management tool is utilized to configure the Agent, create commands, perform step operations and monitor the results and the status. Moreover, as a testing and validation tool, it plays a significant role in the improvement of the Agent’s design as well as in the upgrade of the entire data center’s organization and performance.

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A mobile retail app is a growing innovation in a retailing setting and there is an argument on the prominent status of a mobile application in contrast with a mobile website and web applications. The study used quantitative data to run multiple regression analysis with keen attention to linear regression assumption and compare four models for mobile retail app use and continuous use based on mobile retail app technology, trust, and gratification. Theoretically, the study integrates the unified theory of acceptance and use of technology (UTAUT), trust and gratification and expand the technology acceptance model with the trust and gratification elements. To have a better understanding of the hypothesized theory and clearer perception of the model that have explanatory power, the study employs SPSS linear regression and general linear regression to look at the relationship of mobile app technology, trust and gratification predictors and the outcome variable. The study emphasized the importance of trust, privacy assurance, learning and relaxation features in a mobile retail app as an antecedent of its use and continuous use. This is a novel contribution to the literature on technology acceptance and retailing. This study also shed more light on the importance of age as a moderator of gender and marital status regarding mobile retail app use and continuous use. Further, it also explicates the managerial implication of mobile app and makes a necessary future recommendation.

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Although there are many research domains with very good software support and workflow automation, there are even more which do not have it: software development is too expensive to create domain specific applications for every research topic. This leaves many domain experts to work for example with general purpose image processing and statistics tools. Many research ideas get even omitted as requiring unfeasible much manual work. This paper presents a multi-disciplinary image processing software framework called cv4s (cv4sensorhub). Its aim is to create an environment where reusable components make development of domain specific image processing software solutions easier, and thus, more feasible. The paper presents the basic architecture of the framework and two example applications: GrainAutLine which is for analysis of microscopy images of marble, sandstone and schist thin sections, and ChemoTracker which is designed for the motion analysis of white blood cells. As many image processing operations are relatively domain independent, the possible application areas are not limited to petrographic and medical images processing.

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This is a comparative study on the behavior of a dual medium height building with different walls solutions, in a high seismic area (Bucharest, Romania). The main feature of those buildings is the placement of load bearing walls on the perimeter of the building. This is done to limit the lateral displacement when the structure is subjected to seismic loading. The walls cannot be placed inside because of architecture demands. The structure has frames on the inside. The walls may be made of confined masonry, as the medium height buildings are allowed to have, but they may also be made of reinforced concrete. The wall area on direction Y is smaller than on X. There may be high efforts on direction Y. This study will show witch walls solution ensures the best behavior for the building. It is also interesting to see the way frames, masonry and concrete walls work together. The study contains both elastic and plastic state analysis results. This study results may be used for any dual medium height building with perimeter walls, and smaller walls area on one direction.

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The paper shows the influence of nonbearing masonry walls for medium rise framed buildings placed at higher stories but not at the ground floor. The building studied here is a hotel that will be built in Bucharest, Romania. This is a high seismic area according to the seismic codes in force. The structure is composed of a basement, a ground floor and 3 stories above it. It is necessary to use a frames structure to have a free partitioning at the ground story. Masonry nonbearing walls placed only at the upper stories may generate a weak story behavior for the structure. This becomes particularly difficult when the building is subjected to seismic loads. The ground floor columns are subjected to high bending moments and shear forces. This study will show the behavior of such buildings in the elastic state, but also the failure mechanism. The influence the nonbearing walls have on the structure’s behavior, their ability to bear the efforts they are subjected to and whether or not this solution is usable are very important aspects to be highlighted in the study. The results may be used for framed buildings with small bays and masonry partitioning walls placed at the higher stories and not at the ground floor.

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In this age of smart devices, many people are carrying a smartphone with them all the time. When they are at home, most of them are connected with the home Wi-Fi network. In this paper, a Wi-Fi network based architecture is proposed to control home appliances using a smartphone and also with a touchscreen-based wall display panel. The proposed system enables the user to control appliances from anywhere in the home without the pain of walking towards the switch panel on the wall. In this project, the mechanical switch based panel on the wall is replaced by the state-of-the-art touch-based liquid crystal display. Along with buttons, the display also shows current weather and time widgets. The smartphone app and a prototype of the display panel using Raspberry Pi with Android Things operating system is developed and tested.

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There is no doubt that the wind was the renewable source of energy that had the most significant growth during the last five years, and more importantly, the wind power source in Brazil has always been the cheapest and most competitive of all the others, so it is worth saying that wind have never been so well used. The wind energy generation in Brazil is hugely getting stronger, mostly in Northeast region where for the first-time energy auctions trough hydroelectric has been surpassed wind ones. Besides, there are still those who want to benefit from this significant advance, making Brazil the first country to collect royalties from the wind. In this paper a reviewed about Brazilian wind energy scenario and prospects will be done, enumerating the main impacts caused by this kind of power injection in a static analysis. In addition, a Quasi-Steady Power Flow (QSPF) will be simulated to show the impacts of loss, and voltage fluctuation created by the intermittence of wind resource. Numerical evaluation was performed in IEEE-30 bus benchmark system. Computer results, demonstrated the needing of control to make electrical variations smoothly on different periods of the day.

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Cervical cancer is the 4th most common cancer in women in low to middle income group countries (LMIC). Various methods for screening cervical cancer are practiced, such as the Conventional Pap Smear (CPS), Liquid Based Cytology with its ancillary techniques like Cell Block with immunocytochemistry. VIA is another method which is being advocated as a primary screening tool. Molecular diagnostics such as use of HPV DNA testing has been at the forefront of the screening programs. In the present study, we have utilized all the above methods by using cost effective in-house procedures to explore their possible utility in the clinical settings. We found them useful with need for more work and training of personnel for better diagnosis of cervical cancer.

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Proportional navigation (PN) is a widely-used guidance law for missiletarget engagement. The goal of the missile intercept problem is to reduce the closest distance between the missile and target by diminishing the line-of-sight rate (LOS rate). In general, PN guidance law necessitates information of the LOS rate and missile velocity. The closing velocity (relative approaching speed to the target) instead of the missile velocity is an additional option for effective guidance. However, there are cases where a sensing device for measuring target motions that can be mounted on a missile is limited. In this paper, we propose a novel guidance law on the basis of proportional navigation (PN) using only line-of-sight (LOS) rate information. In this paper, an uncertainty and disturbance estimator (UDE) is applied to estimate such target motions including velocity change or unpredictable movement etc. The UDE works also for compensating uncertain modeled dynamics such as a missile’s bearing uncertainty and velocity changes. The proposed guidance law is referred to as uncertainty and disturbance-compensated intercept guidance. Numerical simulations with some engagement scenarios are presented taking account of the velocity changes of the missile to demonstrate the potential of the proposed guidance law.

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To gather information rapidly in disaster sites, a lot of search/rescue robots have been developed. It is difficult to correspond to the complicated environment composed of fields requiring various locomotion strategies, because most of these robots have only one type of locomotion device. To increase the available search routes under such conditions with the aim of gathering information more efficiently, we have previously proposed a legged aerial vehicle. The vehicle has tandem rotors to fly in the air and four legs to walk on the ground. The particular feature of this robot is that it has fewer actuators than the sum of those required for controlling a quadrupedal robot and a tandem-rotor helicopter individually. This paper presents modeling of the robot and development of an attitude control system that uses the leg motions. The behavior of the vehicle with the proposed attitude control is simulated using Multibody Dynamics (MBD) simulation software.

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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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With the introduction of new services and new more sophisticated mobile devices the radio network operators are faced with new challanges to increase the system performance. The most recent standards introduced by 3GPP for the new architectures of the Long Term Evolution network address these issues and outline possibilities for optimizing network performance and user QoS. A major instrument in that respect is the resource scheduling and allocation procedure. So far many different algorithms have ben proposed. Uplink resource allocation however is less covered, beacsue it poses additional constraints which make it difficult to balance the optimization between channel state information, system throughput and user perceived throughput. In this paper we propose a novel algorithm for resource allocation which balances the advantages of two previously suggested ones, specifically Round Robin and Best-CQI. We also define a new parameter, the user ratio, which allows us to explicitly quantify the trade-off between fairness, system throughput and user throughput for different channel conditions.

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Almost every cells in human’s body contain the same number of genes so what makes them different is which genes are expressed at any time. Measuring gene expression can be done by measuring the amount of mRNA molecules. However, it is a very expensive and time consuming task. Using computational methods can help biologists to perform gene expression measurements more efficiently by providing prediction techniques based on partial measurements. In this paper we describe how we can recover a gene expression dataset by employing Euclidean distance, Pearson correlation coefficient, Cosine similarity and Robust PCA. To do this, we can assume that the gene expression data is a matrix that has missing values. In that case the rows of the matrix are different genes and columns are different subjects. In order to find missing values, we assume that the data matrix is low rank. We then used different correlation metrics to find similar genes. In another approach, we employed RPCA method to differentiate the underlying low rank matrix from the sparse noise. We used existing implementations of state-of-the-art algorithms to compare their accuracy. We describe that RPCA approach outperforms the other approaches with reaching improvement factors beyond 4.8 in mean squared error.

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This article presents the design and realization of decoder mobile for distress beacon 406 MHz. The use of the sparse Fourier transforms in the processing of distress beacon signals. The characteristics of these decoders are mobility, able to decode all the frequencies of the beacons. It locates with great precision the location of the emitting emergency beacon, which is equipped with GPS, indicates the actual distance from which the alerts emanate. This compressed detection can give us a more detailed form of signals, so new results are given in the detection, the performance of the results is presented through experience.

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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 this research work, we are implementing a student performance evaluation model using Mamdani Fuzzy Inference System (FIS) and Neuro Fuzzy system and comparing the results with classical averaging method for Network Analysis (NA) course studied by third semester Electronics and Communication Engineering students. This work explains the designing of scoring rubrics using Bloom’s levels as the criteria of assessment for NA course. Also at initial stages of learning how students’ strengths and weaknesses can be identified using rubrics and develop critical thinking skills. The five inputs identify, understand, apply, analyze and design/create are five levels of learning as per Bloom’s Taxonomy. Fuzzy rules are applied and the evaluated results are expressed in both crisp and linguistic variables and compared with classical aggregate scores.

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Combinatorial optimization problems are often NP-hard and too complex to be solved within a reasonable time frame by exact methods. Heuristic methods which do not offer a convergence guarantee could obtain some satisfactory resolution for combinatorial optimization problems. However, it is not only very time consuming for Central Processing Units (CPU) but also very difficult to obtain an optimized solution when solving large problem instances. So, parallelism can be a good technique for reducing the time complexity, as well as improving the solution quality. Nowadays Graphics Processing Units (GPUs) have evolved supporting general purpose computing. GPUs have become many core processors, multithreaded, highly parallel with high bandwidth memory and tremendous computational power due to the market demand for high definition and real time 3D graphics. Our proposed work aims to design an efficient GPU framework for parallelizing optimization heuristics by focusing on the followings: distribution of data processing efficiently between GPU and CPU, efficient memory management, efficient parallelism control. Our proposed GPU accelerated parallel models can be very efficient to parallelize heuristic methods for solving large scale combinatorial optimization problems. We have made a series of experiments with our proposed GPU framework to parallelize some heuristic methods such as simulated annealing, hill climbing, and genetic algorithm for solving combinatorial optimization problems like Graph Bisection problem, Travelling Salesman Problem (TSP). For performance evaluation, we’ve compared our experiment results with CPU based sequential solutions and all of our experimental evaluations show that parallelizing combinatorial optimization heuristics with our GPU framework provides with higher quality solutions within a reasonable time.

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This article is devoted to the issues of ensuring the security of a group of mobile robots in the implementation of attacks aimed at the property of accessibility of information and the availability of network nodes. The article presents a method for detecting an abnormal behavior of a network node based on the analysis by the group members of the parameters: residual energy and network load. Analysis of the behavior of individual robots relative to general behavior using probabilistic methods avoids the problem of creating a reference distribution for describing the behavior of a node, as well as creating a signature database for detecting anomalies. The developed method demonstrates high detection rate of denial of service attack and distributed denial of service attack with the number of malicious nodes not exceeding or slightly exceeding the number of trusted nodes. It also provides detection of the Sybil attack.

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This paper reports on an empirical study (an extension of a pilot study) that analyses the design of icons in a German 3-D virtual art gallery interface. It evaluates the extent to which a sample of typical computer users from a range of ages, educational attainments and employments can interpret the meaning of icons from the virtual interface taken ‘out of context’ and ‘in context’. The study assessed a sample of 21 icons representing the ‘action’, ‘information’ and ‘navigation’ functions of the virtual interface using a new Icon Recognition Testing method (IRT) developed by the researchers from existing usability test methods. The Icon Recognition Rate (IRR) of the icons was calculated and they were classified as ‘identifiable’, ‘mediocre’ or ‘vague’ in a novel and useful classification system. The IRT results show that the IRR of almost a quarter of the icons was below the ‘identifiable’ standard, which could seriously compromise the usability of a virtual interface. A comparison is made, using textual and thematic analysis, between the participants’ understanding of the icons’ meaning in and out of context and of the effect of positioning icons in relation to their virtual surroundings and of grouping them in tool bars. From the findings of the study, conclusions are drawn, and recommendations are made for economical icon redesign and replacement. It is suggested in the conclusions that further research is needed into how designers’ conceptual models can be better matched to users’ mental models in the design of virtual interfaces by bringing user profiles into the study.

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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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Facility location problem is a problem that many organizations still face today because of its increasing constraints and objectives. Decision makers want this problem solved in order to maximize profit and as such, it became a field of interest to many computer scientists over the years. The solution tool used by these scientists; a function of technological advancement, has evolved from the use of classical mathematical approaches to the use of metaheuristics. Some of the metaheuristics used include particle swarm optimization metaheuristics, genetic algorithm metaheuristics and tabu search. The problem considered in this research evolves the study of waste management in Lagos state. How the location of waste evacuation centers could be allocated in order to minimize resources such as transportation cost, facility cost, distance and the capacity of each centers. A mathematical model was developed that serves as a template for the algorithm used to solve the problem. Then particle swarm optimization metaheuristics was used to find the optimal solution in terms of capacity to the problem. Particle swarm optimization minimizes the use of memory and still gives a satisfactory solution. With the result obtained, respective agencies could make good decision as to the best location to build a new facility.

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The power market in China is faced with problems such as the continuous widening of terminal load peak-valley difference and the imbalance between supply and demand. Under this background, this paper to establish the mathematical model of the contract price of active demand response. The first is to consider the load component of the user’s electricity consumption, whether it can be transferred or can be reduced. Then consider the market incentive conditions and purchase costs, whether the market electricity price difference is enough to attract users to transfer or reduce the load during peak hours. Those can guide users as much as possible Improve the peak consumption pattern, that is, reduce the peak load during peak hours, or use it during off-peak hours.

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Voice problems are routinely assessed in hospital voice clinics by speech and language therapists (SLTs) who are highly skilled in making audio-perceptual evaluations of voice quality. The evaluations are often presented numerically in the form of five-dimensional ‘GRBAS’ scores. Computerised voice quality assessment may be carried out using digital signal processing (DSP) techniques which process recorded segments of a patient’s voice to measure certain acoustic features such as periodicity, jitter and shimmer. However, these acoustic features are often not obviously related to GRBAS scores that are widely recognised and understood by clinicians. This paper investigates the use of machine learning (ML) for mapping acoustic feature measurements to more familiar GRBAS scores. The training of the ML algorithms requires accurate and reliable GRBAS assessments of a representative set of voice recordings, together with corresponding acoustic feature measurements. Such ‘reference’ GRBAS assessments were obtained in this work by engaging a number of highly trained SLTs as raters to independently score each voice recording. Clearly, the consistency of the scoring is of interest, and it is possible to measure this consistency and take it into account when computing the reference scores, thus increasing their accuracy and reliability. The properties of well known techniques for the measurement of consistency, such as intra-class correlation (ICC) and the Cohen and Fleiss Kappas, are studied and compared for the purposes of this paper. Two basic ML techniques, i.e. K-nearest neighbour regression and multiple linear regression were evaluated for producing the required GRBAS scores by computer. Both were found to produce reasonable accuracy according to a repeated cross-validation test.

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Brain tumor is the abnormal growth of cancerous cells in Brain. The development of automated methods for segmenting brain tumors remains one of the most difficult tasks in medical data processing. Accurate segmentation can improve diagnosis, such as evaluating tumor volume. However, manual segmentation in magnetic resonance data is a laborious task. The main problem to detect brain tumors is less precise to determine the area of the tumor and determine the segmentation accuracy of the tumor. The system proposed the fusion based results binding for MRI image enhancement and combination of adaptive K-means clustering and morphological operation for tumor segmentation. BRATS multimodal images of brain tumor Segmentation Benchmark dataset was used in experiment testing.

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Rescue operations require technology to assist the rescue process. The robotic technology in these missions is becoming very important. The important aspects investigated in this study are the integration of a mechatronic system that will allow for a robotic platform with a vision system.
The research collaboration between Argentina and South Africa is discussed, with the correlating research areas that each country investigated. The study permitted the development and advancement of a search and rescue system for different robots (wayfarer and drones) with different vision capabilities. A novel and innovative vision approach is presented.

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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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The paper presents design and implementation of a mobile robot, located in an accommodation. As opposed to other known solutions, the presented one is entirely based on standard, cheap and accessible devices and tools. An algorithm for transformation of the 2D coordinates of the robot into 3D coordinates is described. The design and implementation of the system are presented. Finally, experimental results with different devices are shown.

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Production of garri (edible processed and granulated form of cassava) and sustaining the production process has become so laborious, time consuming, and predisposes one to some form of danger, especially as it concerns the hot fire that one is disposed to during the process. In west African tradition, where this garri serves as one of the major staple food in the sense that it can be taken soaked in water, or served with soup in the form of “eba”, is produced mainly by women. They do this by frying it over a wood fire in a shallow-ware cast iron pans (Agbada). For even circulation of heat that comes from that wood fire via the iron pans, they use spatula – like paddles of wood or calabash on the hot surface, where placed the granules for processing, to vigorously turn to avoid caking. This process brings about great discomfort as the processor (the woman) will have to sit sideways, just close to the frying fire from the wood. It is against this backdrop that this work seeks to establish a mechanized method of garri processing which is design innovation and sustainability analysis of garri frying machine. This mechanized method appears in form of machine with stainless steel drum, rotary conveyor and paddles fixed along the conveyor to a slower rotation in the same axis of the drum. This project also presents how important this design innovation is especially in the areas of economic growth, welfare and job creation.

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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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This paper investigates the electronic book production and distribution practices adopted by the Publishers in Southeast Nigeria because of the global growing interest in writing new book titles in digital form as well as converting paper titles to digital content. To investigate this study, the researcher formulated three research questions to guide the study. A number of relevant literatures were reviewed to establish the gap anchored on the Technological Determinism Theory. Descriptive Survey design and In-depth interviews were used to elicit data for the study. Fifteen publishing firms were randomly selected from Enugu (Enugu State) and Onitsha (Anambra States). Data from the survey were analyzed using the Statistical Package for Social Sciences (SPSS). The key findings of the study include that: the rate of adaptation of e-book technology by educational publishers in the southeast Nigeria is relatively low. However, books are now distributed and sold in digital forms as online books and print on demand titles by publishers in southeast Nigeria through the Internet; Lack of adequate regulations for the protection of intellectual resources, high cost of digital equipment, incessant power failure and high cost of using alternative power supply for e-book distribution, are some of the challenges undermining the adaptation of e-book publishing technology in Southeast Nigeria. It was recommended that the government should provide an enabling environment through dependable infrastructure for the promotion, distribution and marketing of e-books in the Southeast Nigeria. The Book Publishers Association of Nigeria should also make commitment to the development of indigenous book market.

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Health services are under increasing pressure to reduce large waiting times for appointments. The delayed diagnosis of a human illnesses could have profound consequences for the patient. The large waiting times may be attributed to lack of data, the accuracy of the data or the timeliness of the availability of the data. In addition to this people often priorities their busy lives over their health. Other factors that affect delayed diagnosis of patients could be attributed to ill-health and the difficulty in the patient visiting the health-care practitioner, this is more evident in elderly patients that may have suffered a deterioration of their health. To overcome these obstacles eHealth systems could be put in place to facilitate the transmission of real-time and accurate data regarding a patient’s health directly to secure database that can be accessed by authorized practitioners. This paper outlines the use of eHealth (electronic health) to improve health care services which makes use of a wearable set of secure sensors and a secure database that is accessible using a web application. The proposed wearable system records and stores encrypted data which is related to the body’s physical parameters. Then, the encrypted data are transmitted using wireless technologies from the wearable device to a secure relational multi-user database using a protected protocol. The data can be accessed by the patient and professionals, such as general practitioners, using a web interface once authentication has taken place. This secure wearable architecture alleviates the problems of the lack of data, the inaccuracy of data and the timeliness of data by recording vital body parameters throughout the day and by sending real-time live data to a system that can be immediately accessed by the practitioner. The system also allows for the automatic analysis of data and presentation of the data using graphs which could aid the practitioner in determining patterns in the patients’ health statistics.

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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 decision support systems regarding the Supply Chains (SCs) management services can be significantly improved if an effective viable method is utilised. This paper presents a robust simulation optimisation approach (SOA) for the design and analysis of a granularity controlled and complex system known as Consumer Supply Network (CSN) incorporating uncertain demand and capacity. Minimising the total cost of running the network, calculating optimum values of orders and optimum capacity of the inventory associated with each product family are the objectives pursued in this study. A mixed integer non-linear programming (MINLP) model was formulated, mathematically described, simulated and optimised using Genetic Algorithms (GA). Also, the influence of the problem’s attributes (e.g. product classes, consumers, various planning horizons), and controllable parameters of the search algorithm (e.g. size of the population, crossover rate, and mutation rate) as well as the mutual interaction of various dependencies on the quality of the solution was scrutinised using Taguchi method along with regression. The robustness of the proposed SOA was demonstrated by a series of representative case studies.

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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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Space debris removal is currently a critical issue for space development. It has been reported that five pieces of debris should be removed each year to avoid further increase in the amount of debris in orbit. One approach for the removal of multiple pieces of debris is to launch multiple satellites that can each remove one target debris from orbit. The benefit of this approach is that the target debris can be removed without orbit transition, and thus, the satellite can be developed considering simple satellite mechanics. However, to realize this concept, multiple satellites need to be launched. Another approach is to use one satellite to remove multiple pieces of space debris. This approach can reduce the launch costs and achieve efficient removal of space debris. However, the satellite must change its orbit after the removal of each debris piece, and a technique for optimizing the orbit transition is required. In this study, the latter strategy and developed a satellite trajectory optimization method for efficient space debris removal were focused on. The similarity between the problem of multiple space debris removal and the travelling serviceman problem (TSP) were considered, and the TSP solution involving an evolutionary algorithm (EA) was applied. To improve the efficiency of multiple debris removal, the total radar cross-section (RCS), which indicates the amount of space debris, and the total thrust of the satellite was minimized. The TSP solution method was extended to multiple objectives by coupling it with a satellite trajectory simulation. To evaluate the developed method, a set of 100 pieces of space debris was selected from a database. The results indicated a trade-off between the total RCS and total thrust.

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Driven by today’s market demand, semiconductor is pushing towards the zero-defect direction. The improvement demanded in semiconductor manufacturing is becoming increasingly challenging. In this paper, common molding defects comprise of voids, incomplete fills, and piping holes are studied systematically, focusing on three key areas: 1) Potential mold flow weakness; 2) Molding temperature stability; as well as 3) Defined pressure effects. The in-depth understanding of mold flow in the LF design is achieved via mold flow numerical tool. The numerical model prediction is verified by short shots and end-of-line auto vision data. Advance Process Control (APC) is adopted to measure the stability of key molding parameters like temperature, transfer profile and pressure. The mechanism of transferring the compound in relation to pressure is also analyzed and its effect to molding quality is also assessed. A methodical approach is utilized to understand the process and equipment built-in capabilities from two different equipment manufacturers. The real time transfer profile monitoring is activated for diagnosis of the system issue which leads to the finding of design error of a critical component. The dual temperature controller on one of the systems is analyzed to stabilize temperature for improved compound flow-viscosity control. The process limitations are assessed and transfer profiles are optimized to modify the melt front. By shifting the molding defects to non-critical location, the formation of void at the 500um diameter bonded wire loop peak will be avoided. The verification of potential negative impacts resulted from changes to improve voids, incomplete fills and piping holes are also included in this study. Up-front analysis by adopting numerical tool as a means of understanding the existing design and identifying improvement approach are proven to be useful.

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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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