Volume 4, Issue 2

High Performance Computing (HPC) systems o?er excellent metrics for speed and e?ciency when using bare metal hardware, a high speed interconnect, and massively parallel applications. However, this leaves out a signi?cant portion of scienti?c computational tasks, namely high throughput computing tasks that can be trivially parallelized and scienti?c work?ows that require their own well de?ned software environments. Cloud computing provides such management and implementation ?exibility at the expense of a tolerable fraction of performance. We show two approaches to make HPC resources available in a dynamically recon?gurable hybrid HPC/Cloud architecture. Both can be achieved with few modi?cations to existing HPC/Cloud environments. The ?rst approach, from the University of Melbourne, generates a consistent compute node operating system image with variation in the virtual hardware speci?cation. The second approach, from the University of Freiburg, deploys a cloud-client on the HPC compute nodes, so the HPC hardware can run Cloud-Workloads using the scheduling and accounting facilities of the HPC system. Extensive use of these production systems provide evidence of the validity of either approach.

Read more…

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.

Read more…

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.

Read more…

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.

Read more…

In this paper, the impact of interconnection among isolated and dispersed electric power systems have been Investigated and analyzed. Therefore, the methodology proposed in this work is implemented in three real electric power systems in the western part of Saudi Arabia (designated as I, II and III). The outcome of this study revealed positive benefits resulting from power systems interconnection for reliability enhancement as well as cost saving.

Read more…

A method for coupling of local and global fields related to currents, voltages and magnetic fields in magnetodynamic problems is developed in the frame of the finite subproblem finite element method. The method allows to correct the errors arising from thin conducting regions, that replace volume thin regions by surfaces but neglect border effects in the vicinity of geometrical discontinuities, edges and corners, increasing with the thickness, which limits their range of validity. This leads to errors when solving the thin shell finite element magnetic models in electrical machines and devices. It also permits to perform a natural coupling between local and global quantities weak formulations. A subproblem finite element method is developed to split a complete problem/model composed of local and global fields (some of these being thin regions) into a series of subproblems with the change of materials. Each subproblem is performed on its own separate domain and mesh.

Read more…

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.

Read more…

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.

Read more…

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.

Read more…

An ultra-wideband (UWB) printed antenna (PMA) powered by a compact coplanar waveguide (CPW) is featured. The propounded antenna is supposed to cover the UWB range from 7 GHz to 10 GHz, with return loss values below ?10 dB in the whole frequency range, for X-band applications, often used for dense satellite communications. The 30 x 35 x 1.6 mm3 antenna is mounted on a dielectric substrate named FR-4 with thickness h=1.6mm, relative permittivity ?r=4.3 and loss tangent of 0.025. All the conception and simulated results are realized using the 3D Electromagnetic Simulator software CST Microwave Studio. The results show wide bandwidth and good omnidirectional radiation patterns in the operating band, with a very reduced size. The global satisfying achievement with a very simple structure and small size makes the propounded antenna attractive for use in ultra-wide band (UWB) systems, especially for X-band applications.

Read more…

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.

Read more…

Cloud computing is an exceptional paradigm, which is facilitating the developments and utilization of resources over the internet. Fog computing operates at the edge of the network saving bandwidth, by not sending all information to the cloud, while edge computing does processing of data at the edge of the cloud. Edge computing reduces the distance data must travel on the network. The unique relationship between cloud, fog and edge computing makes research in these areas mandatory. Deciding on a specific area of research as regards these subjects could be a bulky procedure for a scientist. Therefore, reviews and paper studies for recognizing potential research gaps are required. A systematic mapping study is utilized in giving a summary of the conducted research in a particular study area. The objective of this paper is to conduct systematic mapping studies on cloud, fog, edge/mobile devices management, hierarchy models and business models. The results showed that publications that discussed process in relations to the field of study is 14.04% out of the 114 papers included. Also method contributed 24.56%, model had 42.98% and tool contributed 18.42%. Furthermore, evaluation research in terms of the field of study was 27.5% out of 120 papers included. Also, validation was discussed in 17.5% of the papers, solution was 32.5%, philosophical was 5.83%, experience was 15.83% and opinion was 0.83%. The clearly highlighted gaps ought to inspire more enthusiasm for additional research by both researchers and industry practitioners.

Read more…

The basic processes like addition, subtraction can be done using various types of binary adders with dissimilar addition times (delay), area and power consumption in any digital processing applications. To minimize the Power Delay Product (PDP) of Digital Signal Processing (DSP) processors is necessary for high performance in Very Large Scale Integration (VLSI) applications. In this paper, a 32–bit various Parallel Prefix adders design is proposed and compared the performance results on the aspects of area, delay and power. Implementation (Simulation and Synthesis) results really achieve significant improvement in power and power-delay product when compared with the previous bit adders which is used in processors. To reduce the power, here apply the energy recovery logic like power gating technique for all three adders. All the simulations and synthesis results can be noted using Xilinx ISE 14.2i tool.

Read more…

Face sketch recognition aims at matching face sketch images to face photo images. The main challenge lies in modality discrepancy between face photo and sketch images. In this work, we propose a new facial sketch-to-photo recognition approach by adopting VGG-Face deep learning network, with which face images can be represented by compact and highly discriminative feature vectors. Different from existing VGG-Face based methods which directly match face sketches to photos, we firstly transform the gallery photos to sketches for decreasing the modality difference. Experimental results on multiple face photo-sketch datasets indicate the superiority of our method.

Read more…

This article presents a nonlinear model of the continuous weighing conveyor system as considering the delay time of material transport, and then given a novel two-loop control strategy based on PID combined with fuzzy logic: inner velocity control loop and outer mass flowrate control loop. Then, two designed controllers for the velocity and mass flowrate control loops are simulated and evaluated in MATLAB. After that, experimental setup of real-time weighing conveyor system is built in the UTC’s laboratory. Finally, these controllers are installed into PLC to control the material mass flowrate following on the reference input. The simulation and experimental results show that the proposed fuzzy-PID algorithm is right and able to improve the material mass flowrate control quality in industrial continuous weighing conveyor system using PLC controller.

Read more…

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.

Read more…

Image stitching is a process of creating a panoramic image by combining multiple images that have overlapping regions of the same scene. It is a challenging topic in image processing, multimedia, and medical applications. The proposed system can be applied in medical applications for scoliosis operations and other long limb operations. The problem of the traditional x-ray machine is the narrow view. So, it can’t produce the large view of body x-ray image in a single frame. Therefore, this problem is solved by combining two or more x-ray images into a panorama one. This paper proposes a system which automatically stitches the x-ray images and produced a panorama x-ray image. The proposed stitching method is based on feature based approach, ORB (Oriented FAST and Rotated BRIEF). In feature detection stage, Oriented FAST approach is used. In feature description stage, Rotated BRIEF approach is applied. The two important criterias for determining the stitching performance are stitched image quality and processing time. Therefore, the aim of my proposed system is to produce a panorama x-ray image with high resolution and low processing time based on feature extraction approach. We compared our proposed method with three different features detectors. SIFT, SURF, and Harris corner detectors were tested and measured the rate of correct features detection and computation time. Finally, we measured the quality of result images that produced by stitching system of different feature based methods. According to the experimental results, ORB approach can produce high quality panorama image with least processing time.

Read more…

Mass media plays an important role in leading public opinion, including in the election of regional head candidates. The tendency of mass media coverage can be used as a parameter to measure the strength of each regional head candidate. To analyze the tendency of media opinion, sentiment analysis is needed. In this study, text mining techniques were used to analyze opinion sentiments of a regional head election in East Java from the national media perspective. The researcher used the Support Vector Machine algorithm to build a sentiment analysis model. News documents about candidates for the regional head in East Java 2018 were taken from national mass media samples, namely JPNN, Kompas, Detik and Republika. From the test results, the model built on Khoffifah’s data as a candidate for regional head number one has a value of precision, recall and AUC of 0.927, 0.931 and 0.902, respectively. Furthermore, the model built on Gus Ipul’s data as a candidate for regional head number two has a value of precision, recall, and AUC of 0.940, 0.948 and 0.890 respectively. The models built on both data shows good performance with accurate estimation results. Based on the data obtained, the national media tends to have alignments to the regional head candidate number two namely Gus Ipul.

Read more…

The aim of this paper is to develop the educational domain management knowledge content identification and knowledge updating method, based on formal descriptions of enterprise management information interactions. This is very important because the progress of modern science leads to the emergence of new factual or conceptual knowledge. There is a need for proper methods that allow, first, to study and make decisions regarding the relevance of the content, and then take practical steps on the content and possibly of the corresponding structure adaptation. The authors suggest a systematic solution for this problem. The hierarchical Detailed Value Chain Model and Elementary Management Cycle model of educational domain knowledge content identification and updating is formally described, computerized process measures are proposed. The paper provides a method for updating the knowledge of the analyzed domain, referred to as “enterprise domain”, based on enterprise modelling in terms of management information interactions. A method, whose formal DVCM and EMC descriptions are provided in BPMN notation, was designed, allowing to develop a two-level (granular) model for describing knowledge of educational domain management information interactions. In implementing this model and its algorithms in technological terms, a subsystem of enterprise knowledge has been created in a knowledge-based CASE system (computerized knowledge-based IS engineering), performing the function of a domain knowledge database.

Read more…

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.

Read more…

Music genre classification is an important multimedia research domain, including aspects of music piece representation, distances between genres, and categorization of music databases. The objective of this study was to develop a model for automatic classification of musical genres from audio data by using features from low-level time and frequency domains. These features can highlight the differences between different genres. In the model, feature selection is performed using a genetic algorithm (GA), and the resulting dataset is classified using the k-nearest neighbor (KNN), naive Bayes classifier (NBC), and support vector machine (SVM) learning methods. Tenfold cross-validation is used to obtain the optimal f-measure value. In this study, the data were obtained from the GTZAN genre collection datasets. In the performance evaluation, it was found that the GA-based feature selection strategy can improve the F-measure rate from 5% to 20% for the KNN, NBC, and SVM-based algorithms. In addition, the proposed SVM-GA algorithm can exactly better than other comparison algorithms.

Read more…

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.

Read more…

In Opportunistic Mobile social networks (OMSNs), the social characteristics and behavior of humans carrying mobile devices are exploited to improve information provision and data routing in the network. Social-based routing algorithms attempt to exploit users’ social features such as similarity, centrality and betweenness, singularly or combined, to select a suitable relay node among neighbors. However, when combining multiple social metrics to enhance routing performance in opportunistic mobile social networks, most existing algorithms ignore considering the correlation and the mutual impacts among these social metrics. In this paper, we propose a social-based routing approach called Multi Social Metrics (MSM) to enhance data routing in OMSN. In MSM, three social metrics, namely degree centrality, social similarity, and social activeness are exploited, also the mutual impacts among them are considered for performance enhancement. Using real dataset traces, simulation results show the efficiency of MSM by comparing it with other benchmark schemes. Empirical results show that MSM scheme decreases the overhead ratio and the average hop count while achieving competitive delivery ratio and average latency in OMSN.

Read more…

Recently, educational-support robots have been attracting increasing attention as studying-support gadgets. Previous studies used the sympathy expression method in which the robot expressed emotions in sympathy with the learners; however, the robots considered in those studies expressed only facial emotions. Presently, there is no study that uses body movements together with facial expressions in the sympathy expression method. Thus, in this paper, we examine the effects of two types of robots that have different method of expressing emotions on learners in two experiments.

Read more…

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.

Read more…

The approach to the construction of promising cognitive monitoring systems is considered. Based on the analysis of known solutions, the problem of automatic synthesis of computational models of cognitive monitoring is posed. In the synthesis of models, it is proposed to reduce them to relatively finite operational automata. An example of a synthesized model of cognitive monitoring is given.

Read more…

Building massively parallel applications has become increasingly important with coming Exascale related technologies. For building these applications, a combination of programming models is needed to increase the system’s parallelism. One of these combinations is the dual-programming model (MPI+X) which has many structures that increase parallelism in heterogeneous systems that include CPUs and GPUs. MPI + OpenACC programming model has many advantages and features that increase parallelism with respect heterogeneous architecture and support different platform with more performance, productivity, and programmability.
The main problem in building systems with different programming models that it is a hard job for programmers and it is more error-prone, which is not easy to test. Also, testing parallel applications is a difficult task, because of the non-determined behavior of the parallel application. Even after detecting the errors and modifying the source code, it is not easy to determine whether the errors have been corrected or remain hidden. Furthermore, integrating two different programming models inside the same application makes it even more difficult to test. Also, the misusage of OpenACC can lead to several run-time errors that compilers cannot detect, and the programmers will not know about them.
To solve this problem, we proposed a parallel hybrid testing tool for detecting run-time errors for systems implemented in C++ and MPI + OpenACC. The hybrid techniques combine static and dynamic testing techniques for detecting real and potential run-time errors by analyzing the source code and during run time. Using parallel hybrid techniques will enhance the testing time and cover a wide range of errors. Also, we propose a new assertion language for helping in detecting potential run-time errors. Finally, to the best of our knowledge, identifying and classifying OpenACC errors has not been done before, and there is no parallel testing tool designed to test applications programmed by using the dual-programming model MPI + OpenACC or the single-programming models OpenACC.

Read more…

Software architecture and design is an important component in the software engineering field. This aspect of software engineering covers the functional and non-functional requirements of any system being proposed to be developed, while software architecture deals with non-functional requirements, software design entails the functional requirements.
The objective of this paper is to critically analyze current topics in Software architecture and design. The method of analysis involved the use of inclusion and exclusion criteria of papers published in journals and conferences. These papers were accessed from digital libraries like ScienceDirect, and IEEE explore, with a quantitative approach of analysis been imbibed. From the analysis, the result showed that, of 35 papers used in analysis, 34.3% discussed stakeholders’ involvement and decisions in software design. 17.1% for design quality, 20% examined software reuse while 11.4% discussed software evaluation and 8.6% of papers reviewed discussed software management, evolution and software development life cycle each which should be more focused as it is the fundamentals of software design and architecture. From the analysis derived, stakeholder’s involvement and decision in software design is an integral part in software building for effective use. Thereby making researchers dwell more on the topic. The least discussed topics was due to the expectations of researchers. Expecting readers to have a fore knowledge of the fundamentals of design which includes software management, evolution and software development life cycle.

Read more…

Cloud computing recently emerged as an interesting model that enables computing and other related internet activities to take place anywhere, anytime. Cloud service providers centralize all servers, networks, and applications to allow their users’ access at any time and from any location. Cloud computing uses already existing resources like server, CPU and storage memory but runs on a new technology known as virtualization. The core idea of virtualization is to create several virtual versions of one single computing device or resource. This enables many user operating systems to work on such a single underlying piece of device. Network bandwidth is one of the critical resources in a cloud environment. Bandwidth management involves the use of techniques, technologies, tools, and policies to help avoid network congestion and ensure optimal use of the subscribed bandwidth resources while also being a bedrock of any subscription-based access network. Bandwidth management is being utilized by organizations to allow them to efficiently utilize their subscribed bandwidth resources. Bandwidth management deals with the measurement and control of packets or traffic on a network link in order to refrain from overburdening or overloading the link which can lead to poor performance and network congestion. In this paper, the highest development with respect to virtualization in cloud computing is presented. This study review papers available on cloud computing and relevant published literature in multiple areas like conferences, journals etc. This paper examined present mechanisms that enable cloud service providers to distribute bandwidth more effectively. This paper is therefore a study of virtualization in cloud computing, and the identification of bandwidth management mechanisms in the cloud environment. This will benefit forthcoming cloud providers and even cloud users..

Read more…

Cloud computing is a technical “as-a-service” usage model utilizing virtualization. Virtual machines are the core of cloud computing that runs as independent machine grouped into different networks within the hypervisor. Practically done by deployment of clouds computing hosts enterprise servers in virtual machines on an array of high-end servers. Managing cloud resources has to do with controlling and limiting access to the pool of available resources. This brings about the conception of an agreement between the resource services cloud providers and the customers otherwise known as Service Level Agreement, in other to restrict access to provisioned resources. Resource provisioning is a flexible on-demand pay-as-you-go package that is negotiated; and signed based on SLAs between customers and cloud providers. SLAs enable cloud providers to evade costly SLA consequences payable when there are violations, optimizing the performance of customers’ applications and professionally manage resources to reduce cost. These documents are the agreements called Service Level Agreements (SLAs). SLAs outline the expectations which are: terms, conditions, and services of the clients from their service providers regarding availability, redundancy, uptime, cost, and penalties in cases of violations. These ensure clients’ confidence in the services offered. Managing resource is an on-going major issue in cloud computing. Considering the limitation of resources, it poses a challenge for cloud service providers to make provision for all resources as needed. This paper seeks a solution to problems that relates to the present trends and developments of what cloud Service Level Agreements are and it ensures so by reviewing current literature. Thus, this research is a study of cloud Service Level Agreements, cloud resource management and their challenges. This paper has made provision to act as guidance for future research and it is anticipated to be beneficiary to potential cloud end users and cloud service providers.

Read more…

The point of this study is to explore and elucidating the performance of the four-point Half-Sweep EGSOR (4HSEGSOR) iterative method to solve fractional two-point boundary value problems by using Caputo’s fractional operator and family of finite differences (FD) schemes. To apply the iterative methods, linear system needs to be constructed via the discretization process with fractional order to get the approximation equation of the linear fractional two point boundary value problem by using the Caputo’s derivative operator. Then the generated linear system has been solved using the proposed 4HSEGSOR iterative method. In the addition, the formulation and application of the 4HSEGSOR method to solve the problems are also presented. Three numerical examples and comparison are used to illustrate with tested FSSOR and HSSOR methods. The numerical results reveals the effectiveness of 4HSEGSOR method compared with tested iterative methods.

Read more…

STIE XYZ is one of the universities of economics that has not been optimal in the use of information technology. IT implementation is applied when there are urgent and sudden needs. So it is not planned carefully according to the development needs of this educational institution. Therefore many patchy applications are created. As the consequence, it affects the quality of service for all stake holder include students, lectures and all staffs. This study aims to provide solutions to existing problems by designing an output or blueprint that can be used as a foundation for the development of a better academic system in support of business process STIE XYZ. The blueprint is designed by using framework TOGAF and ADM framework. The solution is built by creating artifacts of each core architecture in TOGAF (business, data, application and technology architecture). This research focuses on new admissions services, study plan cards, lectures, study cards, graduation, and finance. The results show some recommendations to build based on each architecture.

Read more…

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.

Read more…

Convolutional LSTMs are widely used for spatiotemporal prediction. We study the effect of using different activation functions for two types of units within convolutional LSTM modules, namely gate units and non-gate units. The research provides guidance for choosing the best activation function to use in convolutional LSTMs for video prediction. Moreover, this paper studies the behavior of the gate activation and unit activation functions for spatiotemporal training. Our methodology studies the different non-linear activation functions used deep learning APIs (such as Keras and Tensorflow) using the moving MNIST dataset which is a baseline for video prediction problems. Our new results indicate that: 1) the convolutional LSTM gate activations are responsible for learning the movement trajectory within a video frame sequence; and, 2) the non-gate units are responsible for learning the precise shape and characteristics of each object within the video sequence.

Read more…

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.

Read more…

To date, software development is vital since software is a critical element in information technology. Requirements gathering, planning, estimation, estimation, development, collaboration, testing, and deployment. The problem is when it is delivered, so it reduces the risk of the problem which could happen is important. Threat prediction should be made. It will be aimed at both the threat and control of the risks which appear when the software development is performed. Fuzzy logic is one powerful method for solving management risk problems. Since the risk management of software development influence directly to the success of software development, this study proposes that fuzzy logic for risk management problems in software development. The case study of software development projects is divided into the category of medium and small. Based on the research program, the development environment, and the Constraint Program. Each of these indicators has sub-classes and factors that explain the indicators in detail from a technical point of view.

Read more…

There are various software related to the implementation of IT Service Management (ITSM) for a company, including those that are open source and commercial. An input is needed for companies in determining what software to choose from various software, especially for small and medium enterprises (SMEs) that have limited human and financial resources. In this study, we have contributed in evaluating open source ITSM software (including OTRS, ITOP, and SDP) that are suitable for use by small and medium-sized companies. In the evaluation process, we evaluated various appropriate criteria, so that we finally chose the quick-win criteria from ITIL V3 (one of the best practices that are widely used in ITSM). The method used for training is Fuzzy SIR (Superiority and Inferiority Ranking) with assessment criteria for data taken in the form of quantitative data from experts who have used and had certificates in the field of ITSM. The results showed that OTRS was the best software with a value of 0.86, SDP was in second place with a value of 0.77, and ITOP was in the last place with a value of 0.04.

Read more…

A 3D image adds realism in viewing experience and can assist in simplifying the graphical displays. A Third dimension supplement to the input can improve pattern recognition, and can be used for 3D scene reconstruction and robot navigation. Recently popularity of 3D hardware is also increased which makes it a hot topic. The production of content as 3D is not matching with its need so there is scope of improvement of these 3D contents. Monocular cues give profundity data when seeing a scene with one eye. When a spectator moves, the evident relative movement of a few stationary articles against a foundation gives indicates about their relative separation. Depth estimation from monocular cues is a difficult task because single image lacks prior information like depth information, motion information etc. In Depth using scene features depth is estimated by exploring the features like shape, edges, color, texture and as well as an analysis of the environment of the scene that are of interest with respect to the target. Different objects have different hue and value and hence color is useful for depth estimation. Shape and texture provides disparity which is used to estimate depth. The main problem in converting a 2 dimensional to 3 dimensional images using single image is that it lacks information required for reconstruction in 3D data. While doing conversion by taking different cues or combination of multiple cues from scene conversion has been done e.g. structure form shape, motion, defocus etc. But such methods work for restricted scenarios not for global scenes. For instance, outdoor algorithms worked poor for indoor algorithms. Here we have implemented automatic conversion of 2 dimensional to 3 dimensional images using monocular image which can convert global images in visually comfortable 3D image.

Read more…

Noise control is essential when applying speech recognition in noisy environments such as factories. In this study, a signal processing for noise cancellation is proposed by using a noise-insensitive bone-conducted speech signal together with an air-conducted speech signal. The speech signal is generally expressed by a nonlinear model. The extended Kalman filter is very famous as a state estimation method for nonlinear systems. However, this filter needs a linearized approximation model for the nonlinear systems. By using the sample point called Sigma point, the unscented Kalman filter (UKF) can be applied to the nonlinear system model without linear approximation. In this study, new type method is proposed based on the UKF. Although UKF considers Gaussian noise, an extended UKF considering non-Gaussian noise is proposed. A noise cancellation method is derived by use of air- and bone-conducted speech signals. The validity of this method is investigated by using both conducted speech signals measured in a noisy real environment.

Read more…

The purpose of this work is to present new technology in acquiring energy from the compact fluorescent lamp (CFL) and store it in a super-capacitor to operate the emergency exit lights. Many studies show energy-efficient light bulbs may emit harmful radiation. This type of lamp emits high levels of radiation, causing migraine headaches, fatigue, and other health problems. The proposed system is based on the magnetic near-field coupling between the flat wound induction coil and the compact fluorescent lamp. CFL bulbs emit excessive dirty energy, the most of this energy will energize the super-capacitor and then in emergency lighting batteries through DC/DC step-up converter. So the proposed electronic device show a new technology to harvest the radiation generated by the bulb and charging batteries and secondly reduce the electromagnetic radiation inside a home, offices, and protect our children from radiation. The primary objective of the device is to reduce electromagnetic pollution at home and offices and re-generate energy from harmful radiation. The results are satisfactory and advantages of using technology to recycle electromagnet radiation to charge a battery, use at a critical time like an emergency light system. Besides, we can use it for many other applications. This purpose of this working is an extension of work initially presented in 2017 Ninth International Conference on Advanced Computational Intelligence (ICACI).

Read more…

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.

Read more…

STATCOM a shunt connected Flexible Alternative Current Systems (FACTS) device using for fast control of voltage and reactive power control in the power grid. To optimize Nouakchott power system at 2030 year, we anticipate both generation and demand grow. A set of nonlinear equations are solved through Newton Raphson method and programmed in PSS/E and MATLAB. The results will be analyzed for two situations, without STATCOM and with STATCOM connected to the grid. The found results show the degree of performance and capacity of STATCOM to reduce the power mismatches, improve the voltage at buses and reduce the harmonics in Nouakchott power system. The impact of the renewable energies to improve transient stability of system will be considered. In the end, the power system is optimized at 2030 year by integration the STATCOM device. It will be generating or absorb reactive power to stabilize the system voltage at 1 pu. That means enhances transits active power thereby providing additional capacity to consumers.

Read more…

Enhancing underwater visualization using hybrid technique is generally employed into oceanic production. Through growing oceanic learning, undersea processing has drawn extra importance owing towards necessary task of picture towards attaining data. Although, suitable to reality of dust-like constituent and beam reduction, undersea descriptions continually experience small contrast and color alteration. In this paper, we estimate submerged beam transmission progression also intend an effectual means to defeat the backscatter trouble. Our scheme generally includes three steps; first, we reconstruct the picture using adaptive regularization. Second, we separate the reconstructed picture with weighted decomposition; third, we exploit color adjustment along with dehazed process via gradient guided filter towards holding dual mechanisms independently; at last, re-establish fine effect, we use hybrid technique for enhancing the picture. The tentative outcome illustrates that our proposed process extensively get better quality of unclear submerged descriptions. In common, our proposed method verified as well-performed and effectual than existing technique.

Read more…

Read more…

Read more…

Read more…

Read more…

Read more…

Read more…

Read more…

Read more…

Read more…