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The article describes an innovative methodology for the design and experimental validation of monitoring and anomaly detection algorithms, with a particular focus on the aging phenomenon, linked to the anomalous modification of the Rds(on)$R_{ds_{(on)}}$, in devices switching in power electronic systems integrated into modern high‐performance electrified vehicles. The case study concerns an electric drive for fully electrified vehicles, in which a three‐phase axial flux synchronous motor integrated into a wheel motor (Elaphe) is used and in which a high‐efficiency three‐phase inverter, designed with SiC technology (silicon carbide). The article proposes the design and validation of the innovative aging monitoring and detection system, in four consecutive phases. The first phase involves the creation of a real‐time model of electric drive, validated through experimental data extrapolated directly during a WLTP (Worldwide Harmonized Light Vehicle Test Procedure) test. The second phase consists of the creation of a virtual dataset representative of the aging phenomenon, via an anomaly injection procedure, emulating this phenomenon with a scaling factor (depending on the value of the Rds(on)$R_{ds_{(on)}}$) on the current phase of the motor, relating to the inverter branch whose SiC device is affected. The third phase concerns the design of an estimator of the Rds(on)$R_{ds_{(on)}}$, based on an ANN (Artificial Neural Network) regression model, and involves a data manipulation phase with features extraction and reduction techniques. The fourth and final phase, involves the experimental validation of the method, through PIL (Processor‐In‐the‐Loop) tests, integrating the monitoring algorithm (consisting of a real‐time model and AI‐based regression model) on the NXPs32k144 embedded platform (based on Cortex‐M4), making the algorithm interact with the electric drive model on which anomaly injection is applied. [ABSTRACT FROM AUTHOR]

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The study presents a developed and implemented innovative system for electronic health care and prevention, using a complex assessment of momentary disturbances in the electrocardiographic signals, and through reasonable modeling and quantitative digital analyzes to diagnose people after physical, emotional or rehabilitation stress. The priorities of e-health and its main structures are discussed, as well as an analysis of the systemic characteristics of e-health and services. Adapted methods for the evaluation of electrocardiographic signals are proposed, which are statistically studied and applicable in practice for prevention. The developed innovative system for electronic health care and prevention through the analysis of electrocardiographic signals provides quantitative and qualitative assessments of the current state of the heart system in prevention for the purpose of health safety during exercise and training. The electronic health system has been implemented at the University of Ruse in the training of midwives, nurses and electronics engineers. [ABSTRACT FROM AUTHOR]

Expanding the set of stable, accurate, and scalable methods for simulating molecular quantum dynamics is important for accelerating the computational exploration of molecular processes. In this paper, we adapt the signed particles Monte Carlo algorithm for solving the transient Wigner equation to scenarios of chemical interest. This approach was used in the past to study electronic processes in semi-conductors, but to the best of our knowledge, it had never been applied to molecular modeling. We present the algorithm and demonstrate its excellent performance on harmonic and double well potentials for electronic and nuclear systems. We explore the stability of the algorithm, discuss the choice of hyper-parameters, and cautiously speculate that it may be used in quantum molecular dynamics simulations. [ABSTRACT FROM AUTHOR]

The object of this study is the process of segmentation of images acquired from space optoelectronic surveillance systems. The method to segment images from space optoelectronic surveillance systems based on the Sine-Cosine algorithm involves determining the threshold level; unlike the known ones, the following is carried out in it: – preliminary selection of red-greenblue color space brightness channels in the original image; – calculation of the maximum distance of movement of agents in the image in each brightness channel; – calculation of the values that determine the movement of agents in the image in each brightness channel; – determining the position of agents in the image using trigonometric functions of the sine and cosine in each brightness channel. An experimental study into segmenting images acquired from space optoelectronic surveillance systems based on the Sine-Cosine algorithm was carried out. It was found that the improved method of image segmentation based on the SineCosine algorithm makes it possible to segment the images. In this case, objects of interest, snow-covered objects of interest, background objects, and undefined areas of the image (anomalous areas) are identified. The quality of image segmentation was assessed using the Sine-Cosine algorithm-based method. It was found that the improved segmentation method based on the Sine-Cosine algorithm reduces the segmentation error of the first kind by an average of 21 % and the segmentation error of the first kind by an average of 17 %. Methods of image segmentation can be implemented in software and hardware systems that process images acquired from space optoelectronic surveillance systems. Further studies may involve comparing the quality of segmentation by the method based on the Sine-Cosine algorithm with segmentation methods based on evolutionary algorithms (for example, genetic ones). [ABSTRACT FROM AUTHOR]

Robustness of the electronic cryptographic devices against fault injection attacks is a great concern to ensure security. Due to significant resource constraints, these devices are limited in their capabilities. The increasing complexity of cryptographic devices necessitates the development of a fast simulation environment capable of performing security tests against fault injection attacks. SystemC is a good choice for Electronic System Level (ESL) modeling since it enables models to run at a faster rate. To enable fault injection and detection inside a SystemC cryptographic model, however, the model’s source code must be updated. Without altering the source code, Aspect-Oriented Programming (AOP) may be used to evaluate the robustness of cryptographic models. This might replace conventional cryptanalysis methods in the real world. At the ESL, we discuss a unique technique for simulating security fault attacks on cryptographic systems. The current study presents a fault injection/detection environment for assessing the KECCAK SystemC model’s resistance against fault injection attacks. The approach of injecting faults into KECCAK SystemC model is accomplished via the use of weaving faults in AspectC++ based on AOP programming language. We confirm our technique by applying it to two scenarios using a SystemC KECCAK hash algorithm case study: The first concerns discuss the effect of the AOP on fault detection capabilities, while the second concerns discuss the effect of the AOP on simulation time and executable file size. The simulation results demonstrate that this technique is fully capable of evaluating the fault injection resistance of a KECCAK design. They demonstrate that AOP has a negligible effect on simulation time and executable file size. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The goal of this research is to enhance the performance and functionality of Artificial Intelligence (AI) and Machine Learning (ML) in electronic devices and systems. Electronic devices and systems have become an integral part of our lives, with an increasing amount of data being generated and processed. The integration of AI and ML technologies in these devices and systems can significantly improve their performance, efficiency, and user experience. The research will focus on developing new algorithms, improving existing ones, or finding new ways to integrate AI and ML into electronic devices and systems. Areas of focus may include image and speech recognition, natural language processing, and decision making. In conclusion, this research aims to improve the performance and functionality of AI and ML in electronic devices and systems by developing new algorithms, improving existing ones, and finding new ways to integrate AI and ML into these devices and systems. The ultimate goal is to make electronic devices and systems more intelligent, efficient, and useful for users. [ABSTRACT FROM AUTHOR]

Due to the technical barriers between radars and jammers and the poor performance of the traditional detection‐jamming shared signal in integrated radar‐electronic warfare systems, a new detection‐jamming shared signal waveform based on the virtual force field algorithm (VFFA) is proposed in this article. First, a multiobjective and multidimensional characteristic parameter optimization model, based on a virtual force field, is established, and then the design principle of the shared signal is presented in detail. The simulation results show that the detection‐jamming shared signal based on the VFFA presents the deceptive jamming of multiple false targets in a noncollaborative target's radar screen. Further, there is better detection performance with the advantages of multiple pulse repetition frequency (PRF) and pulse accumulation numbers, which are highly sensitive to the multijagged PRF signals emitted by the noncollaborative target. According to the VFFA described in this article, the optimum detection‐jamming shared signal waveform can be output in real time for specific free space targets, to improve the efficiency of integrated radar and electronic warfare systems. [ABSTRACT FROM AUTHOR]

Discrete cosine transforms (DCTs) are widely used in intelligent electronic systems for data storage, processing, and transmission. The popularity of using these transformations, on the one hand, is explained by their unique properties and, on the other hand, by the availability of fast algorithms that minimize the computational and hardware complexity of their implementation. The type-I DCT has so far been perhaps the least popular, and there have been practically no publications on fast algorithms for its implementation. However, at present the situation has changed; therefore, the development of effective methods for implementing this type of DCT becomes an urgent task. This article proposes several algorithmic solutions for implementing type-I DCTs. A set of type-I DCT algorithms for small lengths N = 2 , 3 , 4 , 5 , 6 , 7 , 8 is presented. The effectiveness of the proposed solutions is due to the possibility of fortunate factorization of the small-size DCT-I matrices, which reduces the complexity of implementing transformations of this type. [ABSTRACT FROM AUTHOR]

The pitch control of electronic equipment is the overall and key problem of electronic equipment system. The traditional pitch control of electronic equipment mainly depends on the volume control table, but this method depends too much on the hardware design, the corresponding pitch control effect is relatively unstable, and the cost is high. Based on the research of traditional pitch control software, this project improves the collaborative filtering algorithm and reduces the range of nearest neighbour set of pitch samples by introducing clustering algorithm, to further shorten the search time of neighbour set and finally improve the real time and scalability of the system. To adapt to the environment and user preferences, this study proposes to calculate the attributes between different items when improving the collaborative filtering algorithm, so as to further determine the unique attributes between items and determine the similarity between items, so as to introduce the pitch preference correction factor based on user attributes, so as to realize the high precision of electronic equipment based on pitch control software preference recommendation setting. Based on this, this project takes the improved collaborative filtering algorithm as the core algorithm to build a set of digital TV pitch control software system and realizes the verification of the algorithm proposed in this study based on MATLAB simulation software. The experimental results show that the pitch control accuracy of the algorithm is about 10% higher than that of the traditional algorithm. In terms of the intelligence of the corresponding algorithm, the algorithm proposed in this study has obvious advantages compared with the traditional algorithm. At the same time, its intelligent recommendation to users also has high intelligence, and the corresponding intelligent recommendation rate is about 4%–10% higher than that of the traditional algorithm, which proves that the algorithm in this study has obvious advantages. [ABSTRACT FROM AUTHOR]

The complexity of electronic systems for RF and digital applications is ever increasing, and the corresponding compliance analysis for ensuring the required specifications in terms of performances, signal and power integrity is a challenging task often accomplished by relying on commercial circuit simulators. The modeling of multiport devices involves the assembly of electrical networks usually described in terms of S‐parameter. This work proposes a new single‐step algorithm that computes the global S‐parameter matrix for a cascade of multiple networks with multiple ports without the need of any S‐parameter transformation in T‐parameters and their inverse transformation. The proposed method involves the construction of a large matrix filled with all S‐parameters of all networks, and the subsequent evaluation of only one matrix expression. The proposed method is shown to be very efficient and reliable, since it can be easily automated without the need of a manual connections of tens or even hundreds of ports of the multiple blocks, which is an action that needs to be performed within a typical circuit simulator environment. Also, the proposed method overcomes the limitation of the standard method based on S‐to‐T parameter transformation since it is of general applicability to networks with different number of input and output ports. Examples involving the cascade of multiple 2‐ports and multiports networks are considered, and the results are validated and compared with the reference results obtained from a commercial circuit simulator. The proposed method is shown to be effective and fast compared to its counterpart based on the T‐parameters. [ABSTRACT FROM AUTHOR]

Interference detection is an important part of the electronic defense system. It is difficult to detect interference with the traditional method of extracting characteristic parameters for interference generated at the same frequency as the original signal. Aiming at this special time-frequency overlapping interference signal, this paper proposes an interference detection algorithm based on the long short-term memory-support vector machines (LSTM-SVM) model. LSTM is used for the time series prediction of the received signal. The difference between the predicted signal and the received signal is used as the feature sample, and the SVM algorithm is used to classify the feature samples to obtain the recognition rate of whether the sample has interference. The LSTM-SVM model is compared with the gate recurrent unit-support vector machines (GRU-SVM) model, and the comparison results are visualized using a confusion matrix. The simulation results show that this LSTM-SVM model algorithm cannot only detect the existence of the interference signal but also can determine the specific position of the interference signal in the received waveform, and the detection performance is better than the GRU-SVM model. [ABSTRACT FROM AUTHOR]

The precision agriculture and soil tillage are tasks which can be achieved by Automated Tractors (AT) through the integration of several servomechanisms. In order to reach a high autonomy under various work conditions of the AT, control laws' design and tuning are paramount. The aim of this work is to develop an angle position controller for steering systems applied to an AT. We introduce an automatic electronic steering system by using a fuzzy model, obtained through an Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm training. A proportional derivative (PD) controller is also tuned through a Takagi-Sugeno fuzzy model (T-S). Furthermore, several closed-loop stability tests were carried out, in numerical simulation and real-time implementation. The feasibility of our methodology is illustrated through the tracking of several angles' profiles in a real test scenario. For the tracking of a trajectory or several set-points, we have obtained mean errors about 0.6545 and 0.8651 degrees, respectively. Some mechatronic integrations to convert a conventional tractor into a basic Autonomous Agriculture Off-road Tractor (AAOT) are also shown. [ABSTRACT FROM AUTHOR]

In this article, a method for solving cable layout optimization problems in electronic systems based on ensemble learning (EL) and improved differential evolution (DE) algorithm is proposed. Using this method, we produced two cable layout schemes with the considerations of the electromagnetic compatibility performance and the total length of cables. First, several different individual machine learning (ML) models for all output variables were established. On this basis, we established EL models with better performance than previous individual ML models. Then, aiming at the optimization problem presented in this article, an improved DE algorithm was proposed. On this basis, a method for solving cable layout optimization problems in electronic systems based on EL and the improved DE algorithm was proposed. Finally, the effectiveness of the proposed method was verified by two examples of electronic system cable layout optimization with different routing modes. Each example problem was solved using four different methods. The results indicate that the method proposed here outperformed existing methods. [ABSTRACT FROM AUTHOR]

This paper describes the construction of an electronic system that can recognise twelve manual motions made by an interlocutor with one of their hands in a situation with regulated lighting and background in real time. Hand rotations, translations, and scale changes in the camera plane are all supported by the implemented system. The system requires an Analog Devices ADSP BF-533 Ez-Kit Lite evaluation card. As a last stage in the development process, displaying a letter associated with a recognized gesture is advised. However, a visual representation of the suggested algorithm may be found in the visual toolbox of a personal computer. Individuals who are deaf or hard of hearing will communicate with the general population thanks to new technology that connects them to computers. This technology is being used to create new applications. [ABSTRACT FROM AUTHOR]

Digital communication plays a vital role in today's communication system in this electronic world. However, the applications of digital communication are limited due to the requirements of antenna with fully programmable circuits having modulators and de-modulators. It may also end with hardware complexities. In order to overcome such complexities, a universal modulator is designed with an efficient iterative method named as CORDIC algorithm in prior methods. Although, the CORDIC (Coordinate Rotation Digital Computer) algorithm works efficiently, it leads to computational as well as memory complexities. Additionally it creates a need for latency reduction strategy. Therefore, to compete with all these issues faced with the prior method, we proposed an amended CORDIC algorithm in universal modulator working with the principle of the harmonized Stone–Weierstrass theorem. In addition, the Newton–Raphson method and Remz algorithm are introduced here to reduce the memory complexity by doubling the number of iterations and to select the best carrier signal, respectively. Thus, our proposed work effectively unravels all the notorious issues caused with the conventional CORDIC algorithm and the proposed universal modulator is implemented in Xilinx. [ABSTRACT FROM AUTHOR]

This study presents the implementation of a new unsupervised machine learning based system called a buck converter controller using unsupervised machine learning (ABCML) to control the operation of a type of switching voltage regulators, commonly called buck converters. The system uses the voltage and current state variables of buck converters to evaluate four switching-based clustering algorithms, namely a Gaussian mixture model, a self-organising mapping (SOM), a k-means clustering and a hierarchical clustering algorithm. Step response results of the controller implementation with the buck converter show that the SOM controller improves the performance of the voltage regulator system by 99.77% in terms of voltage overshoot and by 63.24% in terms of fall time, whereas the hierarchical clustering algorithm improves the settling time of the output voltage by 3.91%. This finding of optimal machine learning implementation approaches and their comparison could be used to improve the stability and the performance of switching voltage regulation systems which are widely used in electronic systems of today. [ABSTRACT FROM AUTHOR]

This paper proposed an electronic voting scheme based on one-time ring signature and blockchain to solve the problems of the current e-voting system in terms of anonymity, transparency and open vote-counting. This paper introduced one-time ring signature, blockchain and stealth address technology. The one-time ring signature technology solved the problem of voter anonymity, repeated voting and public verification. The blockchain technology could ensure the openness and transparency of the e-voting system. The one-time ring signature technology could ensure no one or institution could obtain the voting intermediate result before the voting ends. In order to improve the efficiency of vote-counting,it used the method of key sharing to improve the vote-counting algorithm. Through security and performance analysis, the scheme conforms to the basic security standards of an electronic voting system. [ABSTRACT FROM AUTHOR]

The real-time simulation based on the field programmable gate array (FPGA) is receiving more and more attention. However, up to now, the simulation scale for the power electronic system is not so satisfactory due to the real-time requirement and the FPGA resource limitation. This paper proposes a sub-microsecond level real-time simulation method for microgrids. The power converters are modeled with fixed-admittance models and simulated with a compact electromagnetic transients program (EMTP) algorithm. In the meanwhile, the distribution lines/cables are modeled with π-circuit models and simulated with a distributed circuit solution method, called the latency insertion method (LIM). As a result, the distribution generation (DG) systems are decoupled with each other and can be simulated in parallel. The case study shows that the proposed simulation method consumes much fewer FPGA resources compared with the traditional one. Besides, the time step can be much smaller and doesn't need to increase with the simulation scale. With these advantages, the real-time simulation of a microgrid consisting of three three-phase converters, three boost circuits and 21 three-phase lines can be achieved on the Xilinx Kintex-7 410T FPGA with a minmum time-step of 380 ns. [ABSTRACT FROM AUTHOR]

The literature suggests that specific keywords included in summative rotation assessments might be an early indicator of abnormal progress or failure. This study aims to determine the possible relationship between specific keywords on in-training evaluation reports (ITERs) and subsequent abnormal progress or failure. The goal is to create a functional algorithm to identify residents at risk of failure. A database of all ITERs from all residents training in accredited programs at Université Laval between 2001 and 2013 was created. An instructional designer reviewed all ITERs and proposed terms associated with reinforcing and underperformance feedback. An algorithm based on these keywords was constructed by recursive partitioning using classification and regression tree methods. The developed algorithm was tuned to achieve 100% sensitivity while maximizing specificity. There were 41 618 ITERs for 3292 registered residents. Residents with failure to progress were detected for family medicine (6%, 67 of 1129) and 36 other specialties (4%, 78 of 2163), while the positive predictive values were 23.3% and 23.4%, respectively. The low positive predictive value may be a reflection of residents improving their performance after receiving feedback or a reluctance by supervisors to ascribe a "fail" or "in difficulty" score on the ITERs. Classification and regression trees may be helpful to identify pertinent keywords and create an algorithm, which may be implemented in an electronic assessment system to detect future residents at risk of poor performance. [ABSTRACT FROM AUTHOR]

We describe an efficient algorithm to compute forces in quantum Monte Carlo using adjoint algorithmic differentiation. This allows us to apply the space warp coordinate transformation in differential form, and compute all the 3M force components of a system with M atoms with a computational effort comparable with the one to obtain the total energy. Few examples illustrating the method for an electronic system containing several water molecules are presented. With the present technique, the calculation of finite-temperature thermodynamic properties of materials with quantum Monte Carlo will be feasible in the near future. [ABSTRACT FROM AUTHOR]

The key factors that distinguish algorithms for nonadiabatic mixed quantum/classical (MQC) simulations from each other are how they incorporate quantum decoherence—the fact that classical nuclei must eventually cause a quantum superposition state to collapse into a pure state—and how they model the effects of decoherence on the quantum and classical subsystems. Most algorithms use distinct mechanisms for modeling nonadiabatic transitions between pure quantum basis states ("surface hops") and for calculating the loss of quantum-mechanical phase information (e.g., the decay of the off-diagonal elements of the density matrix). In our view, however, both processes should be unified in a single description of decoherence. In this paper, we start from the density matrix of the total system and use the frozen Gaussian approximation for the nuclear wave function to derive a nuclear-induced decoherence rate for the electronic degrees of freedom. We then use this decoherence rate as the basis for a new nonadiabatic MQC molecular-dynamics (MD) algorithm, which we call mean-field dynamics with stochastic decoherence (MF-SD). MF-SD begins by evolving the quantum subsystem according to the time-dependent Schrödinger equation, leading to mean-field dynamics. MF-SD then uses the nuclear-induced decoherence rate to determine stochastically at each time step whether the system remains in a coherent mixed state or decoheres. Once it is determined that the system should decohere, the quantum subsystem undergoes an instantaneous total wave-function collapse onto one of the adiabatic basis states and the classical velocities are adjusted to conserve energy. Thus, MF-SD combines surface hops and decoherence into a single idea: decoherence in MF-SD does not require the artificial introduction of reference states, auxiliary trajectories, or trajectory swarms, which also makes MF-SD much more computationally efficient than other nonadiabatic MQC MD algorithms. The unified definition of decoherence in MF-SD requires only a single ad hoc parameter, which is not adjustable but instead is determined by the spatial extent of the nonadiabatic coupling. We use MF-SD to solve a series of one-dimensional scattering problems and find that MF-SD is as quantitatively accurate as several existing nonadiabatic MQC MD algorithms and significantly more accurate for some problems. [ABSTRACT FROM AUTHOR]

Abstract Flow thinning (FT) is an active traffic protection mechanism destined for communication networks with variable capacity of links, for example wireless networks. In FT, end-to-end traffic demands are equipped with dedicated logical tunnels (for example MPLS tunnels) whose maximal capacities are subject to thinning in order to follow the fluctuations of the currently available link capacities. It follows that for each demand the instantaneous traffic realized between its end nodes must accommodate to the current total capacity available on its dedicated tunnels. In the paper we develop an optimization model for network dimensioning for an applicative modification of FT, the so called Quadratic Flow Thinning (QFT), and present a solution algorithm based on the path generation method. We derive relevant pricing problems for basic variants of the QFT mechanism (and for its special case Affine Flow Thinning, AFT), and present a numerical study that illustrates efficiency of the optimization algorithm, as well as compares the network cost for different variants of QFT and AFT. [ABSTRACT FROM AUTHOR]

In order to solve the problem of detection efficiency and the detection speed in botnet detection, a novel botnet detection method is proposed based on hill-climbing algorithm and FARIMA. At first, the evaluation indexes are presented in this method, and botnet and infection hosts are quickly searched with hill-climbing algorithm. Then, FARIMA model is introduced to cut down the long-correlation of detection index. Finally, a simulation was conducted to research on the key factors with MATLAB. The result shows that, compared to other algorithms, it has good adaptability, and it could effectively search for infected hosts and botnets. [ABSTRACT FROM AUTHOR]

In recent years, with the development of different types of new energy sources, cross‐area power systems (CAPS), whose purpose is to maintain reasonable distribution and power sharing among different areas, have gained great attention. In this paper, aimed at CAPS with random delay and packet dropouts in the process of data transmission, a novel wide‐area stabiliser on sliding mode control (SMC) is designed. Such stabilisers mainly includes two parts: the design of the wide‐area controller and compensation of the communication constraints. First, a new sliding mode switching function is proposed for designing the wide‐area controller. Then, the networked predictive control (NPC) algorithm based on the designed controller is used to compensate the network‐induced delay and packet dropouts in CAPS. Furthermore, the stability of the close‐loop error system is proved. Finally, one three‐area power system is employed to demonstrate the effectiveness of the proposed methods. The results verify that the stabiliser designed in this paper is reasonable and effective. [ABSTRACT FROM AUTHOR]

A tandem AGV (automated guided vehicle) system is composed of several non-overlapping closed loops. Stations within each loop are served by a single dedicated vehicle. The transit area located between two adjacent loops serves as an interface and allows toads to be transferred from one loop to another. If a load needs to be delivered to a station not located within the same loop, the load needs more than one vehicle to carry it to its destination. We regard this routeing problem as a problem of finding the shortest travel time. After a command to deliver a load is issued, finding a route from the source to the destination as rapidly as possible without disrupting other active travel schedules was the objective of this study. A task-list time-window algorithm to find a shortest travel time based on the current status to route a load from point A to point B is presented. Two idle-vehicle managements are considered: circulating (CIRC) and STAY policies. Experiments showed that the STAY policy is more efficient than the CIRC policy in routeing control. [ABSTRACT FROM AUTHOR]

A common problem of cellular manufacturing systems is the formation of part families and machine cells. The total number of inter- and intracellular movements have to be minimized because both contribute to lower productivity. Nevertheless, we show here that intracellular movements are not so important compared with the intercellular movements. We give an efficient algorithm based on minimizing the total intercellular movements, pointing out the importance of being very careful in the selection of the key workstation of each cell. The algorithm has been tested with problems selected from the literature. The results show that in all cases we get a higher utilization rate and lower central processing unit times that other algorithms published in the past. [ABSTRACT FROM AUTHOR]

Electronics switches commonly used in power electronics circuits are the part of the electronics system depending on energy efficiency, circuit topology, switching matrix design, interaction with filter elements, and many other parameters. For the first new switch design prototype to identify of electrical efficiency of the semiconductor switch working with a system, it is very important that estimation of the variables saves time, labor, and economical resources. In this study, the new algorithm is proposed and applied to circuit estimate efficiency of power electronics switches. The current-voltage-power capacities, switching rate, power losses, physical dimensions, heating levels of power electronics switches used in the circuit are investigated and algorithmically estimated according to the result of experimental performance switches. [ABSTRACT FROM AUTHOR]

The computational complexity of wideband sparse representation (SR) greatly restricts the application of SR-based wideband direction-of-arrival (DOA) estimation in practical system. Here, an efficient method for wideband direction finding based on SR is proposed. This method combines the focusing operation with weighted subspace fitting (WSF) to not only decrease the computational complexity but also improve the performance of DOA estimation. Exploiting the result of the focusing operation, the covariance matrix at the focusing frequency can be obtained and used as the data for sparse recovery to get wideband DOA estimates. The WSF is employed to reduce the sensitivity to the noise and the regularisation parameter is given by the asymptotic distribution of the WSF cost function. Simulations are provided to show the efficiency and performance of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents three procedures for the extraction of parametric Dynamic Compact Thermal Models (DCTMs) with controlled and user-chosen accuracy, namely, (i) a DCTM with dense matrices obtained by a direct conventional method, (ii) a partition-based approach leading to a sparse DCTM suited for heat conduction problems suffering from a massive number of independent heat sources and/or parameters, for which extracting conventional dense DCTMs may be too resource-demanding or even unviable, and (iii) a novel algorithm that quickly translates a sparse DCTM into a dense one, which allows reducing the simulation time. The proposed methodologies are validated through the application to two state-of-the-art electronics systems. [ABSTRACT FROM AUTHOR]

An algorithm based on a support vector machine (SVM) is proposed for hydrometeor classification. The training phase is driven by the output of a fuzzy logic hydrometeor classification algorithm, i.e., the most popular approach for hydrometer classification algorithms used for ground-based weather radar. The performance of SVM is evaluated by resorting to a weather scenario, generated by a weather model; the corresponding radar measurements are obtained by simulation and by comparing results of SVM classification with those obtained by a fuzzy logic classifier. Results based on the weather model and simulations show a higher accuracy of the SVM classification. Objective comparison of the two classifiers applied to real radar data shows that SVM classification maps are spatially more homogenous (textural indices, energy, and homogeneity increases by 21% and 12% respectively) and do not present non-classified data. The improvements found by SVM classifier, even though it is applied pixel-by-pixel, can be attributed to its ability to learn from the entire hyperspace of radar measurements and to the accurate training. The reliability of results and higher computing performance make SVM attractive for some challenging tasks such as its implementation in Decision Support Systems for helping pilots to make optimal decisions about changes inthe flight route caused by unexpected adverse weather. [ABSTRACT FROM AUTHOR]

In recent years elastic optical networks have been perceived as a prospective choice for future optical networks due to better adjustment and utilization of optical resources than is the case with traditional wavelength division multiplexing networks. In the paper we investigate the elastic architecture as the communication network for distributed data centers. We address the problems of optimization of routing and spectrum assignment for large-scale computing systems based on an elastic optical architecture; particularly, we concentrate on anycast user to data center traffic optimization. We assume that computational resources of data centers are limited. For this offline problems we formulate the integer linear programming model and propose a few heuristics, including a meta-heuristic algorithm based on a tabu search method. We report computational results, presenting the quality of approximate solutions and efficiency of the proposed heuristics, and we also analyze and compare some data center allocation scenarios. [ABSTRACT FROM AUTHOR]

This paper deals with the development of methodology suited for design of computation algorithm which is able to determine power losses of electronic systems based on measured temperature distribution (thermo-vision measurements). For such purpose deterministic algorithms for power loss identification were developed using two different approaches. Both of them were verified by simulation experiments and relevant simulation models. Applications of proposed methodologies were further used for more complex electronic systems – brick power supply module. First, thermo-vision measurements of selected system's operation were done in order to verify proposed estimation methodologies. The power loss determination estimated from designed methodologies was verified by the comparison of results from the thermo-vision measurements of operation and the experiments of thermal simulation. Finally, the suitability of methodologies was tested in more complex systems such as smartphones. The investigation of accuracy of the designed methodology was performed similarly by the comparison of simulation and measurements. [ABSTRACT FROM AUTHOR]

We propose two novel e-coupon systems that can achieve the following new properties: (1) The coupon issuer (or service provider) can trace the identity of a dishonest user while the identity privacy (or anonymity) of a honest user is still well protected. (2) A honest user's redemption privacy (i.e., the items chosen when redeeming an e-coupon) is well protected from the service provider. (3) If a dishonest user redeems an e-coupon for more than the pre-determined number of times, then the user will lose the redemption privacy (i.e., all the choices the user has made in the previous redemptions can be revealed). We first propose a novel blind signature scheme that we employ together with oblivious transfer to construct our first e-coupon system, which achieves the first two properties without the involvement of any trusted third party. Then we propose a novel oblivious transfer scheme and use it to construct the second e-coupon system that can achieve all the properties given above. We also define the formal security models for these new security requirements, and show that our new e-coupon systems are proven secure in the proposed models. [ABSTRACT FROM AUTHOR]

In order to maximize the utilization of computing resources in Distributed System and resolve multi-tasks collaboration problem, a distributed multi-task collaboration mechanism based on game theory in SoftMan (SM) System is put forward in this paper. Since computing resources and Multi-tasks are the key issues in distributed collaboration mechanism, the relationship between computing resources and Multi-tasks is discussed in detail, and the decomposition method of multitasks is given at first. Then on the basis of the game theory, the auction model, the distributed collaboration mechanism of SoftMan System is established. Finally, under the application of the friction assessment of production equipment in Ansteel, comparative experiments are designed to test the performance of distributed multi-task collaboration mechanisms based on the game theory proposed in this paper. Results show that distributed multi-task collaboration mechanisms based on the game theory have a higher success rate and accuracy with good algorithm stability and reliability. [ABSTRACT FROM AUTHOR]

A raindrop size distribution (DSD) retrieval method for a weather radar network consisting of several X-band dual-polarization radars is proposed. An iterative maximum likelihood (ML) estimator for DSD retrieval in a single radar was developed in the authors' previous work, and the proposed algorithm in this paper extends the single-radar retrieval to radar-networked retrieval, where ML solutions in each single-radar node are integrated based on a Bayesian scheme in order to reduce estimation errors and to enhance accuracy. Statistical evaluations of the proposed algorithm were carried out using numerical simulations. The results with eight radar nodes showed that the bias and standard errors are −0.05 and 0.09 in log( N w); and N w (mm−1 m−3) and 0.04 and 0.09 in D0 (mm) in an environment with fluctuations in dual-polarization radar measurements (normal distributions with standard deviations of 0.8 dB Z, 0.2 dB, and 1.5° in ZHm, ZDRm, and ΦDPm, respectively). Further error analyses indicated that the estimation accuracy depended on the number of radar nodes, the ranges of varying μ, the raindrop axis ratio model, and the system bias errors in dual-polarization radar measurements. [ABSTRACT FROM AUTHOR]

Barter is the direct exchange of goods or services without using a medium of exchange, such as money. Barter faced a number of limitations, and according to Smith (1776), these limitations led to the emergence of money. However, trading with money also exposes traders to the problems of monetary economy such as inflation, deflation, currency de-valuation, and currency exchange fluctuation. According to Statista.com (2015), in 2016, global Business to Customer (B2C) e-commerce sales will reach 1.92 trillion US dollars. On the other hand, online barter solutions are rare on the market. The only attempts to tackle online barter are mobile applications, carried out by small businesses. The market gap is caused by the unsolved inefficiencies of barter. The aim of this thesis is to identify the problems of barter, propose an IT solution for the problems of barter, and finally, produce an artefact, which is the realisation of the proposed IT solution by utilising computer systems and computer algorithms. [ABSTRACT FROM AUTHOR]

An implementation of a joint filter (JF) for unmanned aircraft formation missions is proposed. Such a filter utilizes the fact that velocity of formation members is almost the same in its core structure. In that manner, an advantage of a JF is in situations in which one of the targets is not detected, yet its state can still be estimated. [ABSTRACT FROM AUTHOR]

A coordinated jamming and communications technique for degrading enemy user transmission performance in a multicarrier code-division multiple-access system is introduced. A linear minimum mean square error (MMSE) algorithm with jamming matrix estimation in single-tone jamming is presented. Furthermore, a blind linear MMSE multiuser detection algorithm in multitone jamming is investigated. Simulation results show that friendly users are able to achieve reliable communications, while the transmission performance of enemy users is significantly degraded. [ABSTRACT FROM AUTHOR]

The state of many dynamic systems evolves subject to some equality constraints. Most existing work focuses on developing state estimation algorithms for an equality-constrained dynamic system assuming the system is given. How to design and analyze such a system is rarely addressed, even though it is critically important for application and performance evaluation. In this paper, we first analyze the underlying structural information of linear equality-constrained (LEC) dynamic systems through direct elimination. It is found that the process noise of such a system is state dependent in general. This means that existing formulations of such a system are quite limited. Based on the analysis, we then propose a new systematic way to design LEC systems. The key idea is to design only the unconstrained part of the system. Unlike existing system conversion-based design techniques, in our work the desired model class is given and only the distributions of the initial state and process noise need to be determined, which is comparatively easier. To handle state dependency of the process noise, a new constrained state estimation algorithm based on direct elimination is also proposed. Three examples are provided to illustrate the effectiveness of the proposed methods of analysis, design, and estimation, respectively. [ABSTRACT FROM PUBLISHER]

To solve the off grid problem in compressed sensing (CS) based inverse synthetic aperture radar (ISAR) imaging, a fast and accurate algorithm has been proposed in the paper. By jointly estimating the off grid error and the sparse solution, off grid ISAR imaging is transformed into a joint optimization problem. Interestingly, it can be solved efficiently through two least squares problems based on first order Taylor approximation. When applied to complex sinusoids and quasi real ISAR data, the proposed algorithm has got better results than the conventional algorithm. Therefore, it is a promising off grid CS based ISAR imaging algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we deal with a multi-level redundancy allocation problem for a multi-level system and system, modules and component levels in the system are simultaneously considered as candidates for redundancy. System availability and life cycle cost are used as the constraint and objective function, respectively, and are estimated by simulation. The level and degree of redundancy are determined that minimize the life cycle cost and satisfy the target system availability. An estimation of distribution algorithm is used to determine best solutions, and numerical examples are studied in order to compare module redundancy with component redundancy. [ABSTRACT FROM AUTHOR]

In this paper, a novel kriging-based multi-fidelity method is proposed. Firstly, the model uncertainty of low-fidelity and high-fidelity models is quantified. On the other hand, the prediction uncertainty of kriging-based surrogate models(SM) is confirmed by its mean square error. After that, the integral uncertainty is acquired by math modeling. Meanwhile, the SMs are constructed through data from low-fidelity and high-fidelity models. Eventually, the low-fidelity (LF) and high-fidelity (HF) SMs with integral uncertainty are obtained and a proposed fusion algorithm is implemented. The fusion algorithm refers to the Kalman filter's idea of optimal estimation to utilize the independent information from different models synthetically. Through several mathematical examples implemented, the fused SM is certified that its variance is decreased and the fused results tend to the true value. In addition, an engineering example about autonomous underwater vehicles' hull design is provided to prove the feasibility of this proposed multi-fidelity method in practice. In the future, it will be a helpful tool to deal with reliability optimization of black-box problems and potentially applied in multidisciplinary design optimization. [ABSTRACT FROM AUTHOR]

The beamspace unitary ESPRIT (B-UESPRIT) algorithm for estimating the joint direction of arrival (DOA) and the direction of departure (DOD) in bistatic multiple-input multiple-output (MIMO) radar is proposed. The conjugate centrosymmetrized DFT matrix is utilized to retain the rotational invariance structure in the beamspace transformation for both the receiving array and the transmitting array. Then the real-valued unitary ESPRIT algorithm is used to estimate DODs and DOAs which have been paired automatically. The proposed algorithm does not require peak searching, presents low complexity, and provides a significant better performance compared to some existing methods, such as the element-space ESPRIT (E-ESPRIT) algorithm and the beamspace ESPRIT (B-ESPRIT) algorithm for bistatic MIMO radar. Simulation results are conducted to show these conclusions. [ABSTRACT FROM AUTHOR]

Space-time adaptive processing (STAP) is a family of algorithms frequently employed in surface moving target indication radar systems to enable detection of moving objects in the presence of fixed (i.e., nonmoving) clutter. In this paper, two new closed-form expressions that quantify the loss associated with the STAP notch centered on clutter are derived in terms of system parameters of interest. Although there are many excellent reports, books, and papers focused on STAP, a simple yet accurate approximation for the STAP notch has not previously appeared. It is also shown that a new, accurate approximation for the important STAP metric known as minimum detectable velocity may be derived from the STAP notch expression. Furthermore, accurate expressions are derived that predict when ?aperture-limited? STAP performance may be obtained. This work provides the first analytical, unifying connection between these STAP metrics. As they are implemented in compact closed-form expressions, the new results are attractive for system design. The significant computational benefits associated with the new results can be very advantageous in trade studies or large simulations in which STAP performance estimates must be computed thousands of times. It is expected that this work will be of great use to both readers with a background in STAP and readers new to this field. For readers with STAP experience, this work provides a new understanding of the drivers of STAP performance and of the interconnections between STAP performance measures. For readers new to the STAP field, this work removes the mystery associated with STAP by providing intuition into how STAP works. With accurate, analytical expressions, system engineers can now implement accurate predictions of STAP performance without the necessity of constructing patch-based analysis tools that estimate STAP performance by computing the notch associated with hundreds to thousands of clutter patches. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of estimating the instantaneous frequency (IF) of multicomponent radar signals, which are assumed to be frequency-modulated (FM). The difficulties lie in that different FM components which overlap in time-frequency (TF) domain have different time-supports, and their spectral contents may present continuous and stepped IF laws. We propose an IF estimation algorithm by exploiting the combination of TF distributions (TFDs) and image processing techniques. Numerical results are provided to demonstrate desirable capabilities of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Binary sequences with low aperiodic autocorrelation levels, defined in terms of the peak sidelobe level (PSL) and/or merit factor, have many important engineering applications, such as radars, sonars, spread spectrum communications, system identification, and cryptography. Searching for low autocorrelation binary sequences (LABS) is a notorious combinatorial problem, and has been chosen to form a benchmark test for constraint solvers. Due to its prohibitively high complexity, an exhaustive search solution is impractical, except for relatively short lengths. Many suboptimal algorithms have been introduced to extend the LABS search for lengths of up to a few hundred. In this paper, we address the challenge of discovering even longer LABS by proposing an evolutionary algorithm (EA) with a new combination of several features, borrowed from genetic algorithms, evolutionary strategies (ES), and memetic algorithms. The proposed algorithm can efficiently discover long LABS of lengths up to several thousand. Record-breaking minimum peak sidelobe results of many lengths up to 4096 have been tabulated for benchmarking purposes. In addition, our algorithm design can be easily adapted to tackle various extensions of the LABS problem, say, with a generic sidelobe criterion and/or for possibly nonbinary sequences. [ABSTRACT FROM AUTHOR]

The author addresses the problem of subcarrier sharing with discrete rate allocation in the downlink of multicell and multihop orthogonal frequency division multiple access networks. The co-channel interference makes the problem computationally intractable. The author therefore models the problem as a non-cooperative game among the transmitting nodes with smaller scale problems. Each problem is solved using dual decomposition. Moreover, to mitigate the degradation effect of co-channel interference in this game, the author additionally proposes a price-based game. This game charges the nodes for their transmit power on subcarriers. Numerical results demonstrate that price-based game outperforms the noncooperative game as a result of distributed interference avoidance. In addition, both the games with subcarrier sharing achieve higher sum-rate in comparison with resource allocation schemes with no subcarrier sharing. [ABSTRACT FROM AUTHOR]

Relaying is a promising technology in time-division duplexing long-term evolution-advanced networks to improve cell-edge performance. Owing to the great degree of difference between the transmitting power of evolved node B and relay nodes, uplink performance and downlink performance sometimes cannot be optimised simultaneously. As an important aspect of radio resource management, the conventional route-selection strategies optimise either downlink performance only or uplink performance only. However, the users launching different types of services have different requirements in uplink and downlink. By taking service type into consideration, an adaptive bidirectional optimisation (ABO) route-selection strategy is proposed to adaptively and dynamically optimise uplink and downlink performance. The objective of the proposed ABO strategy is to maximise the user bidirectional throughput which is the sum throughput of uplink and downlink. Moreover, load balancing is considered in the formulation of the proposed strategy. Through system-level simulation, it can be seen that the proposed strategy is better than the benchmark strategies in different frame configurations. [ABSTRACT FROM AUTHOR]