Volume 3, Issue 1

Hereby in this paper, we are going to refer image classification. The main issue in image classification is features extraction and image vector representation. We expose the Bag of Features method used to find image representation. Class prediction accuracy of varying classifiers algorithms is measured on Caltech 101 images. For feature extraction functions we evaluate the use of the classical Speed Up Robust Features technique against global color feature extraction. The purpose of our work is to guess the best machine learning framework techniques to recognize the stop sign images. The trained model will be integrated into a robotic system in a future work.

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In this paper, the performance and reliability of oxide-based Resistive RAM (ReRAM) memory is investigated in a 28nm FDSOI technology versus interconnects resistivity combined with device variability. Indeed, common problems with ReRAM are related to high variability in operating conditions and low yield. At a cell level ReRAMs suffer from variability. At an array level, ReRAMs suffer from different voltage drops seen across the cells due to line resistances. Although research has taken steps to resolve these issues, variability combined with resistive paths remain an important characteristic for ReRAMs. In this context, a deeper understanding of the impact of these characteristics on ReRAM performances is needed to propose variability tolerant designs to ensure the robustness of the technology. The presented study addresses the memory cell, the memory word up to the memory matrix.

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This paper is an extension of work originally presented in WITS-2017 CONF. We extend our previous works by improving the Risk calculation formula, and risk assessment of an alert cluster instead of every single alert. Also, we presented the initial results of the implementation of our model based on risk assessment and alerts prioritization. The idea focuses on a new approach to estimate the risk of each alert and a cluster of alerts. This approach uses indicators such as priority, reliability and asset value as decision factors to calculate alert’s risk. The objective is to determine the impact of alerts generated by Intrusion detection system (IDS) on the security status of an information system, and also improve the detection of intrusions using snort IDS by classifying the most critical alerts by their levels of risk. Thus, only alerts that present a real threat will be displayed to the security administrator. The implementation of this approach will reduce the number of false alerts and improve the performance of the IDS.

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In today’s information based world, it is increasingly important to safeguard the data owned by any organization, be it intellectual property or personal information. With ever increasing sophistication of malware, it is imperative to come up with an automated and advanced methods of attack vector recognition and isolation. Existing methods are not dynamic enough to adapt to the behavioral complexity of new malware. Widely used operating systems, especially Linux, have a popular perception of being more secure than other operating systems (e.g. Windows), but this is not necessarily true. The open source nature of the Linux operating system is a double edge sword; malicious actors having full access to the kernel code does not reassure the IT world of Linux’s vulnerabilities. Recent widely reported hacking attacks on reputable organizations have mostly been on Linux servers. Most new malwares are able to neutralize existing defenses on the Linux operating system. A radical solution for malware detection is needed – one which cannot be detected and damaged by malicious code. In this paper, we propose a novel framework design that uses virtualization to isolate and monitor Linux environments. The framework uses the well-known Xen hypervisor to host server environments and uses a Virtual Memory Introspection framework to capture process behavior. The behavioral data is analyzed using sophisticated machine learning algorithms to flag potential cyber threats. The framework can be enhanced to have self-healing properties: any compromised hosts are immediately replaced by their uncompromised versions, limiting the exposure to the wider enterprise network.

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To advance Java programming educations, we have developed the Java Programming Learning Assistant System (JPLAS) that provides the code writing problem. This problem asks a student to write a source code to satisfy the specification of a given assignment, where the correctness is verified by running test code on JUnit. For a novice student, a code of implementing the standard input/output with the exception handling should be mastered at the early stage as the first step programming for human interfaces. However, for a teacher, it is not easy to write the test code for it. In this paper, we propose a test code generation method to generate the test code using the reference source code for the assignment. In the evaluation of this proposal, all the students completed the codes using the generated test codes for exception handling, although the use of exception handling functions was sometimes insucient or incorrect.

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Ensuring the compliance of developed software with general and application-specific security requirements is a challenging task due to the lack of automatic and formal means to lead this verification. In this paper, we present our approach that aims at integrating the formal specification and verification of security guidelines in early stages of the development lifecycle by combining both the model checking analysis together with information flow analysis. We present our framework that is based on an extension of LTS (labelled transition Systems) by data dependence information to cover the end-to-end specification and verification of security guidelines.

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Quality assurance of modern-day safety-critical systems is continually facing new challenges with the increase in both the level of functionality they provide and their degree of interaction with their environment. We propose a novel selection method for black-box regression testing on the basis of machine learning techniques for increasing testing efficiency. Risk-aware selection decisions are performed on the basis of reliability estimations calculated during an online training session. In this way, significant reductions in testing time can be achieved in industrial projects without uncontrolled reduction in the quality of the regression test for assessing the actual system reliability.

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The uncertain nonlinear systems can be modeled with fuzzy differential equations (FDEs) and the solutions of these equations are applied to analyze many engineering problems. However, it is very difficult to obtain solutions of FDEs.
In this paper, the solutions of FDEs are approximated by utilizing the fuzzy Sumudu transform (FST) method. Here, the uncertainties are in the sense of Z-numbers. Important theorems are laid down to illustrate the properties of FST. The theoretical analysis and simulation results show that this new technique is effective to estimate the solutions of FDEs.

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Microelectromechanical Systems (MEMS) are devices made up of several electrical and mechanical components. They consist of mechanical functions (sensing, thermal, inertial) and electrical functions (switching, decision making) on a single chip made by microfabrication methods. These chips exhibit combined properties of the two functions. The size of system has characteristic dimensions less than 1mm but more than 1?m. The configuration of these components determine the final deliverables of the switch. MEMS can be designed to meet user requirements on any level from microbiological application such as biomedical transducers or tissue engineering, to mechanical systems such as microfluidic diagnoses or chemical fuel cells. The low cost, small mass and minimal power consumption of the MEMS makes it possible to readily integrate to any kind of system in any environment. MEMS are faster, better and cheaper. They offer excellent electrical performances. MEMS working at Radio frequencies are RF MEMS. RF-MEMS switches find huge market in the modern telecommunication networks, biological, automobiles, satellites and defense systems because of their lower power consumptions at relatively higher frequencies and better electrical performances. But the reliability is the major hurdle in the fate of RF MEMS switches. Reliability mainly arises due to the presence of residual stresses, charging current, fatigue and creep and contact degradation. The presence of residual stresses in switches the S-Parameters of the switches are affected badly and the residual stress affects the final planarity of the fabricated structure. Design and simulation of an RF-MEMS switch is proposed considering the residual stresses in both on and off state. The operating frequency band is being optimized and the best possible feasible fabrication technique for the proposed switch design is being analyzed. S-Parameters are calculated and a comparison for the switches with stress and without stress is performed in FEM based HFSS software.

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Microelectromechanical Systems (MEMS) are devices made up of several electrical and mechanical components. They consist of mechanical functions (sensing, thermal, inertial) and electrical functions (switching, decision making) on a single chip made by microfabrication methods. These chips exhibit combined properties of the two functions. The size of system has characteristic dimensions less than 1mm but more than 1?m. The configuration of these components determine the final deliverables of the switch. MEMS can be designed to meet user requirements on any level from microbiological application such as biomedical transducers or tissue engineering, to mechanical systems such as microfluidic diagnoses or chemical fuel cells. The low cost, small mass and minimal power consumption of the MEMS makes it possible to readily integrate to any kind of system in any environment. MEMS are faster, better and cheaper. They offer excellent electrical performances. MEMS working at Radio frequencies are RF MEMS. RF-MEMS switches find huge market in the modern telecommunication networks, biological, automobiles, satellites and defense systems because of their lower power consumptions at relatively higher frequencies and better electrical performances. But the reliability is the major hurdle in the fate of RF MEMS switches. Reliability mainly arises due to the presence of residual stresses, charging current, fatigue and creep and contact degradation. The presence of residual stresses in switches the S-Parameters of the switches are affected badly and the residual stress affects the final planarity of the fabricated structure. Design and simulation of an RF-MEMS switch is proposed considering the residual stresses in both on and off state. The operating frequency band is being optimized and the best possible feasible fabrication technique for the proposed switch design is being analyzed. S-Parameters are calculated and a comparison for the switches with stress and without stress is performed in FEM based HFSS software.

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Feature extraction is taking a very vital and essential part of bio-signal processing. We need to choose one of two paths to identify and select features in any system. The most popular track is engineering handcrafted, which mainly depends on the user experience and the field of application. While the other path is feature learning, which depends on training the system on recognising and picking the best features that match the application. The main concept of feature learning is to create a model that is expected to be able to learn the best features without any human intervention instead of recourse the traditional methods for feature extraction or reduction and avoid dealing with feature extraction that depends on researcher experience. In this paper, Auto-Encoder will be utilised as a feature learning algorithm to practice the recommended model to excerpt the useful features from the surface electromyography signal. Deep learning method will be suggested by using Auto-Encoder to learn features. Wavelet Packet, Spectrogram, and Wavelet will be employed to represent the surface electromyography signal in our recommended model. Then, the newly represented bio-signal will be fed to stacked autoencoder (2 stages) to learn features and finally, the behaviour of the proposed algorithm will be estimated by hiring different classifiers such as Extreme Learning Machine, Support Vector Machine, and SoftMax Layer. The Rectified Linear Unit (ReLU) will be created as an activation function for extreme learning machine classifier besides existing functions such as sigmoid and radial basis function. ReLU will show a better classification ability than sigmoid and Radial basis function (RBF) for wavelet, Wavelet scale 5 and wavelet packet signal representations implemented techniques. ReLU will illustrate better classification ability, as an activation function, than sigmoid and poorer than RBF for spectrogram signal representation. Both confidence interval and Analysis of Variance will be estimated for different classifiers. Classifier fusion layer will be implemented to glean the classifier which will progress the best accuracies’ values for both testing and training to develop the results. Classifier fusion layer brought an encouraging value for both accuracies either training or testing ones.

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A new statistical approach to predict the gain bandwidth of Phoenix-cell based reflectarrays is proposed. It combines the effects of both main factors that limit the bandwidth of reflectarrays: spatial phase delays and intrinsic bandwidth of radiating cells. As an illustration, the proposed approach is successfully applied to two reflectarrays based on new Phoenix cells.

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Through-Silicon-Vias (TSVs) are utilized for high density 3D integration, which induce crosstalk problems and impact signal integrity. This paper focuses on TSV crosstalk characterization in 3D integrated circuits, where several TSV physical and environmental configurations are investigated. In particular, this work shows a detailed study on the influence of signal-ground TSV locations, distances and their structural configurations on crosstalk. Embedded 3D testing circuits are also presented to evaluate the coupling effects between adjacent TSVs such as crosstalk induced delay and glitches for different crosstalk modes. Additionally, A 3D parallel Ring Oscillators testing structure is proposed to provide crosstalk strength coupling indicator between adjacent TSVs. Simulation results are conducted using a 3D electromagnetic field solver (HFSS) from Ansoft Corporation and a Spice-like simulator (ADS) from Keysight Technologies Corporation based on MIT 0.15µm 3DFDSOI process technology.

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The United Arab Emirates (UAE) is dedicated to establishing the best teaching and learning environment for students and staff across all higher education institutions. To heed this call, the engineering division adopted the Learning-by-Doing (LBD) pedagogical philosophy for 21st Century education at the heart of its strategic directions. This study intends to explore how LBD is understood and practiced in UAE colleges and how 21st Century skills can be explicitly incorporated into its engineering curriculum by using constructive alignment as a pattern for instructional design. This work intends to investigate the general question: “What constructively aligned Learning-by-Doing pedagogical model, with the incorporation of 21st Century skills, needs to be developed to effectively teach and prepare engineering students at the Higher College of Technology, UAE for successful long-term employment in the global working economy?”. Using mixed method research design and input from its major stakeholders, student survey questionnaires, engineering instructors and dean structured interviews, overt class observation and syllabi examination have all been utilized for data triangulation. In conclusion, the study developed a collaborative LBD model tailor-fitted to the institution’s engineering program and to UAE’s culture.

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This paper reports the results of an empirical, 3D full wave inversion (FWI) numerical analysis which provides an estimation of the performance of multi-static handheld ground penetrating radar (GPR,) compared to a bi-static system, for landmine detection using FWI imaging. The experiments are based on simulated data and provide a more realistic evaluation of the performance of multi-static handheld GPR for the landmine problem based on FWI, than previous studies based on a 2D analysis.. Furthermore, a novel method of estimating a parameter set that is closer to the global minimum for an iterative FWI optimization is introduced.

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This article describes the modeling procedure of a direct resistive heat model of the molybdenum sheet and its simulation with electrodes made from various materials. The main characteristic of the proposed model is its dynamic behavior, because model considers the movement of the molybdenum sheet. The simulation results are mutually compared and the optimal material parameters are selected. The development of the model, in which the movement of molybdenum sheet is considered is used for determination of optimal movement speed of the molybdenum sheet in order to achieve requested temperature. The presented model can be also used for determination of optimal electrode materials and its geometrical properties/shape.

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This paper critically evaluates the operational perspective of Virtual Power Plants (VPP) in Germany by analyzing key factors to replace conventional power plants in the future power system. Therefore, its necessity for the secure operation as well as the technical and economic benefits for the German power system are pointed out. The single sections describe in detail how the requirements on technical functions and standardized communication can be reconciled with the increasing challenges on volatile generation. Furthermore, different operation concepts (profit maximization, intra-day schedule loyalty and system services maximization) are described with respect to their mathematical algorithms and their practical feasibility under consideration of given circumstances and future developments. The impact on the power system by the different possible VPP-operational concepts are exemplary pointed out in a case study with use of a medium voltage Cigre-Benchmark Network. The results indicate a high impact on hand-over points by VPP operational concepts.

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Reliable operation of a power transformer with a certain load depends on the technical condition of individual construction parts and the ability to prevent defects that can cause a failure. During the lifecycle of a transformer, valuable data is constantly accumulated, which forms the basis for technical or risk assessment of the equipment. Therefore it also serves as a ground for the decisions on further operation, or repairs, or replacement. To achieve this goal, data need to be systematized. Since technical condition indexing allows combining various types of data including results of diagnostic tests is used within the framework of this research.
As part of a larger risk assessment methodology, algorithms for two indicators are proposed in this paper, and they are based on results of electrical measurements and analysis of oil parameters, respectively. The novelty of the algorithms for indicators introduced in this paper is based on analysis of features specific to the power system in Latvia such as large proportion of aged transformers, low loading level, significant variation in oil volumes, and statistics on typical faults. Proposed limits of parameters are verified with data from operation history. Taking into account the differences in the measurement periodicity, the indicator that is based on electrical measurements assesses the individual constructive parts of the transformer (windings and core, bushing and on-load tap changer) separately, whereas the other, indicator combines the results of oil parameters into a single assessment. These indicators were verified by using 30 transformers from the Latvian power system and the obtained results coincide well with the operation history.

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This paper is an extension of work originally presented in EIC-2017. It deals with influence of the supply frequency for dissipation factor measurements, mainly for tests under power frequency and low frequency. After a theoretical reminder, we present some experiments on single coils and stators of high voltage motors. Finally, we discuss the results and the desirability of choosing one or the other of these methods.

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The main target of this article is to perform the multidimensional analysis of multipath propagation in an indoor and outdoor environment at higher frequencies i.e. 15 GHz, 28 GHz and 60 GHz, using “sAGA” a 3D ray tracing tool. A real world outdoor Line of Sight (LOS) microcellular environment from the Yokusuka city of Japan is considered for the analysis. The simulation data acquired from the 3D ray tracing tool includes the received signal strength, power angular spectrum and the power delay profile. The different propagation mechanisms were closely analyzed. The simulation results show the difference of propagation in indoor and outdoor environment at higher frequencies and draw a special attention on the impact of diffuse scattering at 28 GHz and 60 GHz. In a simple outdoor microcellular environment with a valid LOS link between the transmitter and a receiver, the mean received signal at 28 GHz and 60 GHz was found around 5.7 dB and 13 dB inferior in comparison with signal level at 15 GHz. Whereas the difference in received signal levels at higher frequencies were further extended in an indoor environment due to higher building penetration loss. However, the propagation and penetration loss at higher frequency can be compensated by using the antenna with narrow beamwidth and larger gain.

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The article considers linear algebra as an alternative mathematical tool of logic synthesis of digital structures to Boolean algebra and synthesis methods of digital electronic component base (ECB) on its ground. The methods of solving the applied problems of logic synthesis are shown, including the expansion of an arbitrary logic function by means of monotonic functions. The proposed mathematical apparatus actually provides the creation of digital structures on the principles of analog circuitry. It can find application in the design of multivalued digital ECB, specialized system-on-chip and analog-digital sensors with current output. The examples of synthesis of the combinational and sequential two-valued and multivalued digital devices are given. In conclusion, the advantages of linear algebra in comparison with Boolean algebra are formulated.

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The key objective of this study is to analyse the heat transfer processes involved in the evaporation and condensation of water in a water distillation system employing a thermoelectric module. This analysis can help to increase the water production and to enhance the system performance. For the analysis, a water distillation unit prototype integrated with a thermoelectric module was designed and fabricated. A theoretical model is developed to study the effect of the heat added, transferred and removed, in forced convection and laminar flow, during the evaporation and condensation processes. The thermoelectric module is used to convert electricity into heat under Peltier effect and control precisely the absorbed and released heat at the cold and hot sides of the module, respectively. Temperatures of water, vapour, condenser, cold and hot sides of the thermoelectric module and water production have been measured experimentally under steady state operation. The theoretical and experimental water production were found to be in agreement. The amount of heat that needs to be evaporated from water-vapour interface and transferred through the condenser surface to the thermoelectric module is crucial for the design and optimization of distillation systems.

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The contemporary electrical power systems (EPS) impose increased requirements for the functionality of the protection systems. The necessity of improved EPS stability is in some extent resulting of the increased integration of renewable sources of electrical energy. The future grid development gives perspective for connection of more converter based generations. The power electronic schemes and associated functional requirements impose necessity of high speed, sensitive, selective and reliable operation of the protection devices. These requirements have always been target of the protection equipment producers and grid operators. The electronic converting schemes specifics impose these requirements for the protection devices in more straightened way, as the converter connected generator may need to trip in shorter time than classical machine generator. In the article is presented a generalized overview of some of the characteristics of the digital “relay” protection devices, and approach for device selection is proposed. Investment planning may utilize such approach in order to have an optimal design from financial point of view.

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This paper is the extended reflection of work originally presented in conference of Electrical, Computer and Communication Engineering (ECCE)-CUET 2017, entitled “Automated Anti Collision System for Automobiles”. Automated collision avoidance system is a trending technology of science in automobile engineering. The aim of this paper is to design a system which will prevent collision from the front as well as the back for automobiles. This paper gives an overview of secure and smooth journey of car (vehicles) as well as the certainty of human life. This system is controlled by microcontroller ATMEGA32. Two Sharp distance sensors are used to detect object within the danger range where one is for front detection and other is for back detection. A crystal oscillator is used to produce the oscillation and generates the clock pulse of the microcontroller. An LCD and a GLCD are used to give information about the safe distance for front and rear respectively, and a buzzer is used as alarm. An actuator is used as automatic brake and inside the actuator there is a motor driver that runs the actuator. For coding “microC PRO for PIC” is used and “Proteus Design Suite Version 8 Software” is used for simulation.

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CdTe-based photovoltaic (PV) cells provide the lowest EBPT (energy payback time) and emit less amount of GHG (green house gases) among different types of PV cells. Thus, it is very essential to enhance the efficiency of CdTe-based solar cells. A high efficiency CdTe/CdS p-i-n heterostructure solar cell is designed and the performance of the cell is investigated. All the simulations have been done using AMPS 1D (Analysis of Microelectronic and Photonic Structures) simulator. The cell consists of a transparent conducting oxide (TCO) layer (ZnO), a window layer (n-type CdS), an intrinsic layer (CdTe), an absorber layer (p-type CdTe) and a highly doped CdTe and Si as back surface field (BSF) layer. After the optimization of layer thicknesses and doping densities of different layers, we obtained a conversion efficiency of 26.01% for a total cell thickness of 1.8 ?m. It is also found that the conversion efficiency can be increased by simply increasing the thickness of intrinsic layer. At 1.5 AM solar irradiance, the proposed cell structure attained a Voc of 1.09 V, a Jsc of 26.78 mA/cm2, and a fill factor of 89%, reaching an overall conversion efficiency of 26.01% with CdTe as BSF layer.

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Sentiment analysis is one of the most popular information extraction tasks both from business and research prospective. From the standpoint of research, sentiment analysis relies on the methods developed for natural language processing and information extraction. One of the key aspects of it is the opinion word lexicon. Product’s feature from online reviews is an important and challenging task in opinion mining. Opinion Mining or Sentiment Analysis is a Natural Language Processing and Information Extraction task that identifies the user’s views or opinions. In this paper, we developed an approach to extract domain independent product features and opinions without using training examples i.e, lexicon-based approach. Noun phrases are extracted using not only dependency rules but also textblob noun phrase extraction tool. Dependency rules are predefined according to dependency patterns of words in the sentences. StandfordCoreNlp Dependency parser is used to identify the relations between words. The orientation of words is classified by using lexicon-based approach. According to the experimental results the system gets good performance in six different domains.

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This paper addresses the motion planning problem of Reeds-Shepp-type car-like mobile robots moving among static and dynamic obstacles. If the positions and the velocity vectors of the obstacles are known or well estimated, the Velocity Obstacles (VO) method and its non-linear version (NLVO) can be used to plan a collision-free trajectory for a robot in the dynamic environment. VO and NLVO algorithms determine a velocity vector for the robot which corresponds not necessarily to the orientation of the robot, hence a nonholonomic car-like mobile robot cannot apply it exactly. Previously, the NLVO method was adopted for Dubins-like mobile robots, which are able to move forward only. In this paper, a method similar to NLVO is presented, but it results motions feasible for Reeds-Shepp-type robots, which are able to drive both forward and backward. Longitudinal velocities and curvatures of turning circles are calculated, which ensure collision-free motion if the arbitrary movement of the obstacles are known for some time-horizon.

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This paper presents various concepts related to the application of a microgrid pilot project in a residential condominium at Fortaleza / CE – Brazil, such as battery energy system, renewable and distributed generation, islanding recloser and all different units using interface based on power electronics. This papers main objective is to create information about microgrid operation and the interaction between its main equipment, such as power converters, utility energy distribution system and control units responsible for algorithms and changes in microgrids operation mode. This information is important for understanding the need for a test setup construction. To perform the test procedures, a temporary setup in a controlled environment within the microgrid is proposed. During the test periods, intentional power outages are required to evaluate the operating mode switching on each unit. The test setup described in this paper aims to mitigate the tests effects on other residential units inside the condominium.

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Log-periodic antennas have high electrical characteristics over a wide frequency range. The large length of the antennas is their significant disadvantage caused by the fact that each active region consisting of several radiators operates in a narrow frequency range. To extend this range, it is proposed to use radiators with concentrated capacitive loads, providing in-phase currents with a linear amplitude distribution law. An approximate calculation of the fields and directional characteristics of a complex multielement radiating structure is performed using a new method of electrostatic analogy based on the assumption that the ratio of emf in the radiator centers is equal to the charge ratio on the conductors of the electrically neutral system. The problem of optimization of considered antennas by methods of mathematical programming is formulated.

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Model driven development is an important role in software engineering. It consists of multiple transformation functions. This development is a paradigm for writing and implementing computer program quickly, effectively, at minimum cost and reducing development efforts because it transforms design model to object-oriented code. Our approach is rule-based model driven development in which textual Umple model is used as primary artifact and transformed to mobile applications. In this model driven development, evaluation of quality of transformation is critical. This paper has presented a set of metrics to assess the quality attribute of modifiability and evaluated using these object-oriented metrics. Results represent our approach achieves high efficiency in quality of modifiability.

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Constant Envelope Discrete Cosine Transform based Orthogonal Frequency Division Multiplexing (CE-DCT-OFDM) system with M-ary Pulse Amplitude Modulation (PAM) mapper is considered. In the system phase modulation is used to achieve constant envelope signals that have 0 dB Peak-to-Average-Power Ratio (PAPR). Transmission of such signals permit high power amplifiers in the system to operate with maximum power efficiency. The performance of CE-DCT-OFDM system is examined over Additive White Gaussian Noise (AWGN) and over fading channels. Closed-form expressions for Bit Error Rate (BER) over Ricean and Rayleigh channels are derived. The performances of CE-DCTOFDM and conventional DCT-OFDM systems are compared as a function of Input power Back-Off (IBO) and Signal-to-Noise Ratio (SNR) for the Traveling-Wave Tube Amplifier (TWTA) model. Results show that CE-DCT-OFDM system offers superior BER performance compared to DCT-OFDM system and has other advantages as well.

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Hosen-ciphertext attacks (CCA) are typical threat on public-key encryption schemes. We show direct chosen-ciphertext security modification in the case of attribute-based encryption (ABE), where an ABE scheme secure against chosen-plaintext attacks (CPA) is converted into an ABE scheme secure against CCA by individual techniques. Our modification works in the setting that the Diffie-Hellman tuple to be verified in decryption is in the target group of a bilinear map. The employed techniques result in expansion of the secret-key length and the decryption cost by a factor of four, while the public-key and the ciphertext lengths and the encryption cost remain almost the same.

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Internet of things (IoT) is an innovative technology subject to all kind of imaginary and science fictional solutions. Dreams and speculations are still possible about it. A technology combining real life objects and virtual life (Internet) is indeed a fertile pitch of fantasy and original ideas. However, IoT has in practice to face several challenges to ensure its function and operability in a near future. This paper defines first some technical challenges of IoT today, before focusing on security-related ones via a layered architecture of IoT that we suggest. Finally, a number of actions and required future work is presented to enhance IoT security (Privacy, Lightweight crypto, etc.).

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In this paper, stabilization of uncertain systems was established using zonotopic sets. The obtained state feedback control laws are computed by an off-line approach reducing computational burdens. The resolution of a robust model predictive control (MPC) allows computing a sequence of state feedback control laws corresponding to a sequence of zonotopic invariant sets. The implemented control laws are then calculated by linear interpolation between the state feedback gains corresponding to the nested pre-computed zonotopic sets. The proposed interpolation with the use of zonotopic sets achieves better control performances.

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The world’s pollution rates have been increasing exponentially due to the many reckless lifestyle practices of human beings as well as their choices of contaminating power sources. Eventually, this lead to a worldwide awareness on the risks of those power sources, and in turn, a movement towards the exploration and deployment of several green technologies emerged.
Proton Exchange Membrane Fuel cells (PEMFCs) are one of those green technologies. However, in order to be able to successfully and efficiently deploy PEMFC systems, a solid fault diagnosis scheme is needed. The development of accurate model based fault diagnosis schemes has been imposing a lot of challenge and difficulty on researchers due to the high complexity of the PEMFC system. Furthermore, confidentiality issues with the manufacturer can also impose further constraints on the model development of a commercial PEMFC system. In this work, an approach to develop an accurate PEMFC system model despite the lack of crucial system information is presented through the use of Siemens LMS AMESim software. The developed model is then used to develop a fault diagnosis scheme that is able to detect and isolate five system faults.

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Due to the increasing bandwidth requirement of modern wireless communication systems, developing antenna having wider bandwidth have been receiving significant attention in the recent years. In this paper, a comparative analysis of the contacting feed (micro strip line and coaxial probe) and non-contacting feed mechanism (both Aperture Coupling and Proximity Coupling) in micro strip patch antenna has been done. In case of contacting feed, RF power is fed directly to the radiating patch using a connecting element such as a micro strip line whereas in case of non-contacting feeds, electromagnetic field coupling is done to transfer power between the micro strip line and the radiating patch. As per the latest research, ultra wide band technology is used in the frequency range from 3 GHz to 10 GHz. We have analyzed and compared the return loss and corresponding bandwidth of these four types of antenna at 5.853GHz so that this antenna may be used in medical as well as wireless applications.

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This paper, presents the design of a temperature sensor based on RO (Ring Oscillator) in order to make a thermal study for the detection and localization of thermal peaks in a complex system. In this work, a simulation and FPGA implementation of a fully digital temperature sensor features a number of exact inverters that can be dynamically inserted. Before the transition to the implementation in FPGA board, the use of VHDL code is necessary to describe the exact number of inverters that form a single ring oscillator, in order to verify and validate the results obtained. This paper offers a solution to thermally induced stress and local overheating in complex system design which has been a major concern for the designers during the design of integrated circuit. In this paper a DE1 FPGA board cyclone V family 5CSEMA5F31C6 is used for the implementation.

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This article proposes a new MAC scheme for Vehicle-to-Infrastructure (V2I) communications that dynamically reallocates unused TDMA slots. By maintaining a balanced waiting time, the proposed TDMA based scheduling scheme allocates TDMA slots in a rational way to minimize merging and one-hop neighboring collision. The proposed scheme ensures dynamic reallocation of unused slots by using “time slot reassignment” mechanism. The scheme has been simulated in VEINS framework of OMNET++ network simulator and its performance has been compared with other conventional protocols. Experimental results show that our scheme performs better than existing schemes in terms of successfully transmitted data packets.

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This paper investigates the efficiency benefits of replacing the Silicon diodes of a commercial IGBT module for the main inverter application of an electric vehicle with Silicon Carbide diodes, leaving the package, operating conditions and the system unchanged. This ensures that the comparison is directly between the chip technologies without any scope for discrepancies arising out of differences in the packaging, gatedriver circuit etc. A behavioral power loss calculation model is used to investigate the performance of the two modules for various drive cycles (Artemis, WLTP, NEDC). The behavioral power loss model is experimentally validated using two independent measurement methods, namely, power analyser based electrical input output method, and a calorimetric method which was developed especially for the low lossy light load condition. Furthermore, it is shown that the electrical method has close to 30% inaccuracy making it unsuitable for the main inverter applications, especially for comparing two different chip technologies, e.g., Silicon versus Silicon Carbide. The developed calorimetric method in contrast offers lower than 3% uncertainty.

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In the current industrial development, an increasing number of sensors is applied for monitoring of any kind of appliances and machines. A predictive mathematical model allows for realistic assessment of the health state of the appliance, indication of service requirements, as well as control of the appliance, serving as so-called digital twin on a control device.
Completely analogous modeling can be used for virtual testing, i.e. a (partial) substitution of physical experiments. The software-in-the-loop model provides realistic feedback to the physical specimen on the test rig and helps to increase the representativeness of the experiment and to reduce costs.
In a joint research project partially sponsored by the German Federal Ministry of Economics and Energy, the authors developed an approach for meta-modeling of dynamic systems. While the modeling process is fed by results from sophisticated simulations, or even test results as input data, the resulting model can be used for fast stochastic analyses as well as software-in-the-loop in dynamic real-time experiments. The approach was verified on tests of an aircraft high lift system.

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This work describes computerized data acquisition system for current-voltage (I-V) characteristics of diodes. The proposed system consist of a personal computer pre-installed with LabVIEW, two units of power supply, an interface board, current and voltage sensors. Two devices under test (DUTs) are selected namely 1N4007 silicon and 1N34 germanium diodes. The current flow through the circuit and voltage across the diode is measured and I-V characteristic is successfully plotted. When data acquisition interrupted by the user, real time I-V curve with least-square fitting is plotted. The LabVIEW was employed primarily to display data from sensors and storing collected data for further post-measurement processing. Estimated forward voltage drop from plotted I-V curve was then compared with the published value from manufacturer’s datasheet. Comparison revealed that developed system has been successfully characterized both DUTs base on the forward voltage drop obtained from the plotted I-V curve. Furthermore, proposed system architecture offers extra flexibility where stored data can be manipulated with minimum programming efforts. The application of the proposed system can also be extended for in-situ device characterization in various circuits.

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In this study, we use a new proposed framework to develop the Hamiltonian circuit learning games for college students. The framework is for enhancing learners’ activities with learning reflexiveness. The design of these games is based on this framework to achieve the targeted learning outcomes. In recent years, the game-based learning is a very popular research topic. The Hamiltonian circuit is an important concepts for learning many computer science and electric engineering topics, such as IC design routing algorithm. The developed games use guiding rules to enable students to learn the Hamiltonian circuit in complicate graph problem. After the game, the learners are given a reviewing test which using the animation film for explaining the knowledge. This design concept is different from the previous studies. Through this new design, the outcome gets the better learning results under the effect of reflection. The students will have a deeper impression on the subject, and through self-learning and active thinking, in the game will have a deeper experience.

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Solving the Unit Commitment problem (UCP) optimizes the combination of production units operations and determines the appropriate operational scheduling of each production units to satisfy the expected consumption which varies from one day to one month. Besides, each production unit is conducted to constraints that render this problem complex, combinatorial and nonlinear. In this paper, we proposed a new strategy based on the combination three optimization methods: Tabu search, Particle swarm optimization and Lagrangian relaxation methods in order to develop a proper unit commitment scheduling of the production units while reducing the production cost during a definite period. The proposed strategy has been implemented on a the IEEE 9 bus test system containing 3 production unit and the results were promising compared to strategies based on meta-heuristic and deterministic methods.

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To avoid biopsies, doctors use non invasive medical techniques such as the computed tomography. Even that, the detection of the liver remains a big challenge because of the gray level and shape variations which depend on patients and acquisition modalites. In this work, we propose to create a 3D liver model in the training phase of 3D active shape model algorithm. This training model will be deformed according to any given 3D data for liver segmentation. The contribution of our work is the use of the Non-rigid registration with a B-spline registration on the training phase. We tested our method on an open access database (”3DIRCADb”) and on our database obtained from the radiology department of the National Oncology Institute of Tunis. Both data-sets showed the reliability of the method with an accuracy equal to 69.98% and 71.18% respectively for our database and ”3D-IRCADb”.

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This paper deals with the design of adaptive observer for a class of nonlinear systems with time delays. Within this work, we develop an adaptive observer for a bilinear time delay system, then we extend those results in the presence of Lipschitz nonlinear functions in the system’s dynamics. In the stability analysis of the estimation errors, we combine a Linear Parameter Varying (LPV) approach in the presence of time delays with a polytopic approach. The obtained stability conditions are given in terms of the solvability of Linear Matrix Inequalities (LMIs) on the vertices of a convex polytope. Numerical examples are finally given to show the effectiveness and feasibility of our results.

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One of the prominent challenges of the automotive-transportation system is represented by the integration of security and safety properties within protocols, applications and connectivity mechanisms. A joint safety/security design can sometimes expose to trade-offs, since their requirements may not match perfectly or even be incompatible. This paper analyses an example of security and safety design, by combining integrity with encryption considering the constraints of a typical CAN protocol and real-time traffic. The analysis is presented modelling differently attackers, packet fragmentation issues and the residual probability of error of the combined scheme.

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In this paper, we investigate the decentralized control problem for largescale interconnected systems. The synthesis of the decentralized controller consists in determining gains which ensure the stability of the global system. To calculate these gains, three approaches are presented. Our main contribution is to develop a new decentralized stabilization approach which the decentralized local gains are calculated and formulated via the resolution of linear matrix inequalities (LMIs) problem. A numerical simulation comparison of the three methods is performed on an interconnected double-parallel inverted pendulum.

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The occurrence of many failures in the power system can lead to power instability and affects the system parameters to go beyond its operating limits. It may lead to obstructing the secure operations and reliability of power systems. Ensuring power system security needs proper actions to be taken for the undesirable contingency. Thus, security analysis is important tasks in modern energy management systems. This paper proposes an approach based on the Newton Raphson power flow method for power system security analysis. Firstly, the contingencies will be specified to assess their impact on the transient stability. Secondly, the selected contingencies will be classified in the order of severity. In addition, the integration of the Unified Power Flow Controller (UPFC) to enhance the transient stability of the power system is considered. The proposed method is implemented on the IEEE-14 bus system. We performed this case study using the well-known software EUROSTAG.

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Examples of analytical calculations of the system characteristics of the hardware and time complexity of the correlation system based on a certain number of microphones and the corresponding number of interrelations are presented. The structural solutions of the hardware special processor implementation of such class of multichannel devices for recognition and identification of types and the spatial location of sources of acoustic signals are developed. The structural model of the spatial identification of sources of acoustic signals in Cartesian coordinates of a two-dimensional Hamming space with the priority placement of microphones as receivers of acoustic signals is proposed.

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Engineering schools must adopt or develop their own systems and processes for graduate attribute assessment. In this paper, we take a systems engineering approach to graduate attribute assessment and propose a system architecture and tool-supported continuous improvement process with key algorithms and mathematical analysis to process the data and provide performance management reporting. Over several iterations, we have introduced and evaluated improved systems support in a collection of tools called the Graduate Attribute Information Analysis system (GAIA). GAIA integrates course indicators as well as external indicators from a variety of sources. It provides a tool-supported continuous improvement process with templates and notifications for all deliverables. There are sound algorithms and tool support and built-in mathematical analysis for data collection and reporting that includes quantitative and qualitative data; weighted grading; historic trend analysis; improved visualization of results; and standardized reports at both the course level and the program level that can be used either for accreditation or to inform program improvement.

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Fully Homomorphic Encryption (FHE) is considered as a key cryptographic tool in building a secure cloud computing environment since it allows computing arbitrary functions directly on encrypted data. However, existing FHE implementations remain impractical due to very high time and resource costs. These costs are essentially due to the computationally intensive modular polynomial multiplication. In this paper, we present a software/hardware co-designed modular polynomial multiplier in order to accelerate homomorphic schemes. The hardware part is implemented through a High-Level Synthesis (HLS) flow. Experimental results show competitive latencies when compared with hand-made designs, while maintaining large advantages on resources. Moreover, we show that our high-level description can be easily configured with different parameters and very large sizes in negligible time, generating new designs for numerous applications.

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Drug abuse problem is not a new problem, but it is still serious in Hong Kong. The emergence of hidden drug abuse youth has brought more difficulties to them and their parents. The usual ways of providing anti-drug abuse assistance are not sufficient to these types of young people. Intelligent methods have been developed to assist anti-drug workers. In this paper, we present three mobile applications with a set of intelligent tools for parents and social workers to help our young people. The applications have an alerting tool to detect the possibility of drug abuse of a young student, and to alert corresponding parents and social workers for remedial actions. Another function is the nearby notification tool to help social workers in identifying people who may need assistance. For the alerting function, a number of data mining and text analysis techniques have been adopted for behavior analysis. A supporting instant messaging has been co-developed for communicating alerting messages.

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This paper is an extension of work originally presented in conference name. The goal is to propose new fault detection and fault isolation techniques for a polytypic linear parameter-varying system (LPV). In this work, an adaptive observer design is formulated for a given polyquadratic Lyapunov function. Subsequently, new sufficient conditions are given in terms of Linear Matrix Inequalities (LMIs). To show the effectiveness of the proposed algorithm, an illustrative example is included.

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In recent years, a number of studies have been conducted exploring the potential of digital tour guides, that is, multimedia components (e.g., 2D graphic, 3D models, and sound effects) that can be integrated into digital storytelling with location-based services. This study uses component-based software engineering to develop the content of game-based tourism information services. The results of this study are combined with 3D VR/AR technology to implement the digital 2D/3D interactive tour guide and show all the attractions’ information on a service platform for the gamification of cultural tourism. Nine kinds of game templates have been built in the component module. Five locations have completed indoor or external 3D VR real scenes and provide online visitors with a virtual tour of the indoor or outdoor attractions. The AR interactive work has three logos. The interactive digital guide includes animated tour guides, interactive guided tours, directions and interactive guides. Based on the usage analysis of the component databases built by this study, VR game types are suited to object-oriented game templates, such as the puzzle game template and the treasure hunt game template. Background music is the database component required for each game. The icons and cue tones are the most commonly used components in 2D graphics and sound effects, but the icons are gathered in different directions to approximate the shape of the component to be consistent. This study built a vivid story of a scene tour for online visitors to enhance the interactive digital guide. However, the developer can rapidly build new digital guides by rearranging the components of the modules to shorten the development time by taking advantage of the usage frequency of various databases that have been built by this study to effectively continue to build and expand the database components. Therefore, more game-based digital tour guides can be created to make better defined high-quality heritage attractions understood.

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This paper describes the design and analysis of a regenerative braking system for a permanent magnet synchronous motor (PMSM) drive for electric vehicle (EV) applications. First studied is the principle for electric braking control of a PMSM motor under field-oriented control (FOC). Next, the maximum braking torque in the regeneration mode as well as the braking torque for the maximum regeneration power, respectively, are deduced. Additionally, an optimum switching scheme for the inverter is developed with the objective of maximizing energy recovery during regenerative braking to the DC-bus capacitor. The integration of an ultra-capacitor module with the battery allows for the efficient and high power transfer under regenerative braking. It was important to manage the power flow to the DC-bus as this is a key issue that affects the efficiency of the overall system. Finally, the amounts of braking energy that can be recovered, and the efficiency with which it can be returned to the battery/ultra-capacitor, is analyzed for a PMSM coupled with a DC motor as the load. The results of the analysis are validated through experimentation.

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Detect and tracking of moving weak targets is a complicated dynamic state estimation problem whose difficulty is increased in case of high clutter conditions or low signal to noise ratio (SNR). In this case, the track-before-detect filter (TBDF) that uses unthresholded measurements considers as an effective method for detecting and tracking a single target under low SNR conditions. In this paper, a particle filter based track-before-detect (PF-TBD) method is proposed to address the problem of detection and tracking with unthersholded data and a binary variable of the existence of the target for two motion models. Simulation results using image measurements based on TBD scenarios are also presented to demonstrate the capability of the proposed approach.

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In this work, a representative combinational circuit is visualized in various ways. It is abstracted (concretized) from transistor level to gate level and a structure-preserving transition is carried out into a signal flow graph. For creating a signal flow plan it is necessary to swap the nodes and the edges in the signal flow graph. After having executed this action the result is a signal flow plan. A value table exhibits the coding of the whole circuit. Then the so called module view is used to get the familiar compact and directed display and neighborhood relations are repeated once more, the resolution method is used. It is observed that undefined results can occur in digital circuits. But, these must be avoided in safety critical circuits. These events have to be secured in practice by costly and expensive verification and testing. In order to deal with the problem now, the structure-preserving modeling has to be understood, since this is the only way to achieve a onepurpose, qualitative and cost effective search for errors.

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Cloud computing allows users and enterprises to process their data in high performance servers, thus reducing the need for advanced hardware at the client side. Although local processing is viable in many cases, collecting data from multiple clients and processing them in a server gives the best possible performance in terms of processing rate. In this work, the implementation of a high performance cloud computing engine for recognizing handwritten digits is presented. The engine exploits the benefits of cloud and uses a powerful hardware accelerator in order to classify the images received concurrently from multiple clients. The accelerator implements a number of neural networks, operating in parallel, resulting to a processing rate of more than 10 MImages/sec.

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In this modern age, information technology (IT) plays a role in a number of different fields. And therefore, the role of security is very important to control and assist the flow of activities over the network. Intrusion detection (ID) is a kind of security management system for computers and networks. There are many approaches and methods used in ID. Each approach has merits and demerits. Therefore this paper highlights the similar distribution of attacks nature by using K-means and also the effective accuracy of Random Forest algorithm in detecting intrusions. This paper describes full pattern recognition and machine learning algorithm performance for the four attack categories, such as Denial-of-Service (DoS) attacks (deny legitimate request to a system), Probing attacks (information gathering attacks), user-to-root (U2R) attacks (unauthorized access to local super-user), and remote-to-local (R2L) attacks (unauthorized local access from a remote machine) shown in the KDD 99 Cup intrusion detection dataset.

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This paper is devoted to the analysis of aircraft dynamics in the cruise flight phase under windshear conditions. The study is conducted with reference to a point-mass aircraft model restricted to move in a vertical plane. We formulate the problem as a differential game against the wind disturbances: The first player, autopilot, manages, via additional smoothing filters, the aircraft’s angle of attack and power setting. The second player, wind, produces disturbances that are transferred, also via smoothing filters, into most dangerous wind gusts. The state variables of the game are subject to state constraints representing aircraft safety conditions related, for example, to the altitude, path inclination and velocity. Viability theory is used to compute the so-called viability kernels, the maximal subsets of state constraints where an appropriate feedback strategy of the first player can keep aircraft trajectories arbitrary long for all admissible disturbances generated by the second player. A grid method is utilized, and challenging computations in seven dimensions are conducted on a supercomputer system.

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Mobile broadband has gained momentum with the growing demand of user data rates. Long Term Evolution (LTE) technology is the step in mobile communications evolution, developed to satisfy high data rate demand, and meet better spectral efficiency requirements. Effective radio resource management and inter cell interferences are the major challenges. Fractional Frequency Reuse (FFR) is one of the effective interference avoidance mechanisms applied to LTE networks to yield optimal throughput. In this extended paper, we propose a novel performance metric, weighted throughput on user satisfaction, and evaluate an existing adaptation process that dynamically adjusts to optimal network performance determined by FFR mechanism with mobile users. The performance of FFR mechanism with mobility model, adaptation process, and femtocell densification is evaluated and optimized for proposed metric and other metrics. Results optimized by proposed metric show comparatively higher average throughput and lower variance among user throughput.

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Cloud computing has become a compelling paradigm built on compute and storage virtualization technologies. The current virtualization solution in the Cloud widely relies on hypervisor-based technologies. Given the recent booming of the container ecosystem, the container-based virtualization starts receiving more attention for being a promising alternative. Although the container technologies are generally considered to be lightweight, no virtualization solution is ideally resource-free, and the corresponding performance overheads will lead to negative impacts on the quality of Cloud services. To facilitate understanding container technologies from the performance engineering’s perspective, we conducted two-stage performance investigations into Docker containers as a concrete example. At the first stage, we used a physical machine with “just-enough” resource as a baseline to investigate the performance overhead of a standalone Docker container against a standalone virtual machine (VM). With findings contrary to the related work, our evaluation results show that the virtualization’s performance overhead could vary not only on a feature-by-feature basis but also on a job-to-job basis. Moreover, the hypervisor-based technology does not come with higher performance overhead in every case. For example, Docker containers particularly exhibit lower QoS in terms of storage transaction speed. At the ongoing second stage, we employed a physical machine with “fair-enough” resource to implement a container-based MapReduce application and try to optimize its performance. In fact, this machine failed in affording VM-based MapReduce clusters in the same scale. The performance tuning results show that the effects of different optimization strategies could largely be related to the data characteristics. For example, LZO compression can bring the most significant performance improvement when dealing with text data in our case.

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