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Articles 5461 - 5490 of 25622
Full-Text Articles in Computer Engineering
A New Classification Method Using Soft Decision-Making Based On An Aggregation Operator Of Fuzzy Parameterized Fuzzy Soft Matrices, Samet Memi̇ş, Serdar Engi̇noğlu, Uğur Erkan
A New Classification Method Using Soft Decision-Making Based On An Aggregation Operator Of Fuzzy Parameterized Fuzzy Soft Matrices, Samet Memi̇ş, Serdar Engi̇noğlu, Uğur Erkan
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, a precise and stable machine learning algorithm, i.e. eigenvalue classification method (EigenClass), has been developed by using the concept of generalised eigenvalues in contrast to common approaches, such as k-nearest neighbours, support vector machines, and decision trees. In this paper, we offer a new classification algorithm called fuzzy parameterized fuzzy soft aggregation classifier (FPFS-AC) to combine the modelling ability of soft decision-making (SDM) and classification success of generalised eigenvalues. FPFS-AC constructs a decision matrix by employing the similarity measures of fuzzy parameterized fuzzy soft matrices fpfs -matrices) and a generalised eigenvalue-based similarity measure. Then, it applies an SDM method …
Defect Classification Of Railway Fasteners Using Image Preprocessing And Alightweight Convolutional Neural Network, İlhan Aydin, Mehmet Sevi̇, Mehmet Umut Salur, Erhan Akin
Defect Classification Of Railway Fasteners Using Image Preprocessing And Alightweight Convolutional Neural Network, İlhan Aydin, Mehmet Sevi̇, Mehmet Umut Salur, Erhan Akin
Turkish Journal of Electrical Engineering and Computer Sciences
Railway fasteners are used to securely fix rails to sleeper blocks. Partial wear or complete loss of these components can lead to serious accidents and cause train derailments. To ensure the safety of railway transportation, computer vision and pattern recognition-based methods are increasingly used to inspect railway infrastructure. In particular, it has become an important task to detect defects in railway tracks. This is challenging since rail track images are acquired using a measuring train in varying environmental conditions, at different times of day and in poor lighting conditions, and the resulting images often have low contrast. In this study, …
Developing A Fake News Identification Model With Advanced Deep Languagetransformers For Turkish Covid-19 Misinformation Data, Mehmet Bozuyla, Akin Özçi̇ft
Developing A Fake News Identification Model With Advanced Deep Languagetransformers For Turkish Covid-19 Misinformation Data, Mehmet Bozuyla, Akin Özçi̇ft
Turkish Journal of Electrical Engineering and Computer Sciences
The massive use of social media causes rapid information dissemination that amplifies harmful messages such as fake news. Fake-news is misleading information presented as factual news that is generally used to manipulate public opinion. In particular, fake news related to COVID-19 is defined as 'infodemic' by World Health Organization. An infodemic is a misleading information that causes confusion which may harm health. There is a high volume of misinformation about COVID-19 that causes panic and high stress. Therefore, the importance of development of COVID-19 related fake news identification model is clear and it is particularly important for Turkish language from …
Smart Charging Of Electric Vehicles To Minimize The Cost Of Chargingand The Rate Of Transformer Aging In A Residential Distribution Network, Arjun Visakh, M P. Selvan
Smart Charging Of Electric Vehicles To Minimize The Cost Of Chargingand The Rate Of Transformer Aging In A Residential Distribution Network, Arjun Visakh, M P. Selvan
Turkish Journal of Electrical Engineering and Computer Sciences
Electric vehicles (EVs) exhibit several benefits over combustion engine vehicles, making them an attractive mode of mobility for the future. However, supplying the electrical energy required to recharge their batteries could adversely affect the power system infrastructure. The most severe impact of EV integration is expected to be on the distribution transformers, which are among the costliest equipment in the distribution network. Sustained overloads on the transformer could lead to accelerated aging and early retirement. As the rate of EV deployment rises, so does the probability of transformer overloads and the subsequent loss of life. There is a need for …
The Analysis And Optimization Of Cnn Hyperparameters With Fuzzy Tree Modelfor Image Classification, Kübra Uyar, Şaki̇r Taşdemi̇r, İlker Ali̇ Özkan
The Analysis And Optimization Of Cnn Hyperparameters With Fuzzy Tree Modelfor Image Classification, Kübra Uyar, Şaki̇r Taşdemi̇r, İlker Ali̇ Özkan
Turkish Journal of Electrical Engineering and Computer Sciences
The meaningful performance of convolutional neural network (CNN) has enabled the solution of various state-of-the-art problems. Although CNNs achieve satisfactory results in computer-vision problems, they still have some difficulties. As the designed CNN models are deepened to achieve much better accuracy, computational cost and complexity increase. It is significant to train CNNs with suitable topology and training hyperparameters that include initial learning rate, minibatch size, epoch number, filter size, number of filters, etc. because the initialization of hyperparameters affects classification results. On the other hand, it is not possible to make a definite inference for the hyperparameter initialization and there …
A Novel Instrumentation Amplifier With High Tunable Gain And Cmrr Forbiomedical Applications, Riyaz Ahmad, Amit Joshi, Dharmendar Boolchandani
A Novel Instrumentation Amplifier With High Tunable Gain And Cmrr Forbiomedical Applications, Riyaz Ahmad, Amit Joshi, Dharmendar Boolchandani
Turkish Journal of Electrical Engineering and Computer Sciences
A new design of current mode instrumentation amplifier (CMIA) with tunable gain and low voltage operation capability is proposed in this paper, which is suitable for biomedical signals processing, especially in electrocardiogram (ECG). It consists of a new design of current differencing transconductance amplifier (CDTA) and dual z copy CDTA (DZC-CDTA). The gain of the proposed CMIA is controlled by a MOS-based tunable resistor. The main advantage of the proposed CMIA is its high gain that can be tuned over a significant range with the help of two resistances. The performance of the proposed instrumentation amplifier is evaluated through simulation …
45-Nm Cds Qds Photoluminescent Filter For Photovoltaic Conversionefficiency Recovery, Victor Juárez-Luna, Daniel Sauceda-Carvajal, Ivett Zavala-Guillen, Enrique Rodarte-Guajardo, Francisco Carranza-Chávez, Carlos Villa Angulo
45-Nm Cds Qds Photoluminescent Filter For Photovoltaic Conversionefficiency Recovery, Victor Juárez-Luna, Daniel Sauceda-Carvajal, Ivett Zavala-Guillen, Enrique Rodarte-Guajardo, Francisco Carranza-Chávez, Carlos Villa Angulo
Turkish Journal of Electrical Engineering and Computer Sciences
Different energy loss mechanisms have restricted the breakthroughs in concentrated photovoltaic/thermal (CPVT) hybrid solar systems that use photoluminescent filters. Re?ected and transmitted light, emission spectrum, nonideal absorption, Stokes shift (proportional to $f_1 f_2$), overlapping absorption, and scattering of light are mechanisms in photoluminescent filters that restrict optical efficiency to below theoretical limits. In addition, increases in temperature by light concentration affect the operation of photovoltaic cells and photoluminescent filters because of an increase in molecular motion and collisions that consequently lead to energy loss. Meanwhile, nanocrystals or quantum dots (QDs) from groups II VI hold electrical, optical, chemical, and physical …
Visual Interpretability Of Capsule Network For Medical Image Analysis, Mighty Abra Ayidzoe, Yu Yongbin, Patrick Kwabena Mensah, Jingye Cai, Faiza Umar Bawah
Visual Interpretability Of Capsule Network For Medical Image Analysis, Mighty Abra Ayidzoe, Yu Yongbin, Patrick Kwabena Mensah, Jingye Cai, Faiza Umar Bawah
Turkish Journal of Electrical Engineering and Computer Sciences
Deep learning (DL) models are currently not widely deployed for critical tasks such as in health. This is attributable to the "black box", making it difficult to gain the trust of practitioners. This paper proposes the use of visualizations to enhance performance verification, improve monitoring, ensure understandability, and improve interpretability needed to gain practitioners' confidence. These are demonstrated through the development of a CapsNet model for the recognition of gastrointestinal tract infection. The gastrointestinal tract comprises several organs joined in a long tube from the mouth to the anus. It is susceptive to diseases that are difficult for medics to …
Analyzing Probabilistic Optimal Power Flow Problem By Cubature Rules, Qing Xiao
Analyzing Probabilistic Optimal Power Flow Problem By Cubature Rules, Qing Xiao
Turkish Journal of Electrical Engineering and Computer Sciences
This paper is devoted to revealing some properties of the probabilistic optimal power flow (POPF) problem. In conjunction with Hermite polynomial model, Nataf transformation is introduced to map POPF problem to the independent standard normal space. Firstly, a multivariate polynomial model is employed to represent the function relationship between POPF inputs and outputs. Then, moment matching equations are derived to characterize the uncertainty effects of POPF inputs on outputs; three cubature rules are derived to calculate statistical moments of POPF outputs. Finally, along with Monte Carlo simulation method, the proposed methods are tested on IEEE 57-bus system and IEEE 118-bus …
Tara: Temperature Aware Online Dynamic Resource Allocation Scheme For Energyoptimization In Cloud Data Centres, Narayanamoorthi Thilagavathi, Arockiasamy John Prakash, Sridhar Sridevi, Vaidyanathan Rhymend Uthariaraj
Tara: Temperature Aware Online Dynamic Resource Allocation Scheme For Energyoptimization In Cloud Data Centres, Narayanamoorthi Thilagavathi, Arockiasamy John Prakash, Sridhar Sridevi, Vaidyanathan Rhymend Uthariaraj
Turkish Journal of Electrical Engineering and Computer Sciences
Cloud data centres, which are characteristic of dynamic workloads, if not optimized for energy consumption, may lead to increased heat dissipation and eventually impact the environment adversely. Consequently, optimizing the usage of energy has become a hard requirement in today's cloud data centres wherein the major part of energy consumption is mostly attributed to computing and cooling systems. Motivated by which this paper proposes an online algorithm for dynamic resource allocation, namely, temperature aware online dynamic resource allocation algorithm (TARA). TARA demonstrates a novel algorithm design to adapt dynamic resource allocation based on the temperature of a data centre using …
Event-Related Microblog Retrieval In Turkish, Çağri Toraman
Event-Related Microblog Retrieval In Turkish, Çağri Toraman
Turkish Journal of Electrical Engineering and Computer Sciences
Microblogs, such as tweets, are short messages in which users are able to share any opinion and information. Microblogs are mostly related to real-life events reported in news articles. Finding event-related microblogs is important to analyze online social networks and understand public opinion on events. However, finding such microblogs is a challenging task due to the dynamic nature of microblogs and their limited length. In this study, assuming that news articles are given as queries and microblogs as documents, we find event-related microblogs in Turkish. In order to represent news articles and microblogs, we examine encoding methods, namely traditional bag-of-words …
Biometric Identification Using Panoramic Dental Radiographic Images Withfew-Shot Learning, Musa Ataş, Cüneyt Özdemi̇r, İsa Ataş, Burak Ak, Esma Özeroğlu
Biometric Identification Using Panoramic Dental Radiographic Images Withfew-Shot Learning, Musa Ataş, Cüneyt Özdemi̇r, İsa Ataş, Burak Ak, Esma Özeroğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Determining identity is a crucial task especially in the cases of mass disasters such as tsunamis, earthquakes, fires, epidemics, and in forensics. Although there are various studies in the literature on biometric identification from radiographic dental images, more research is still required. In this study, a panoramic dental radiographic (PDR) imagebased human identification system was developed using a customized deep convolutional neural network model in a few-shot learning scheme. The proposed model (PDR-net) was trained on 600 PDR images obtained from a total of 300 patients. As the PDR images of the patients were very different in terms of pose …
Impact Of Teaching Practices And Communication Climates On Participation In Computer Science Education, Jackie Krone
Impact Of Teaching Practices And Communication Climates On Participation In Computer Science Education, Jackie Krone
Master's Theses
One way to understand teaching is to view it as a people process rather than a presentation of knowledge. It follows that the role of an educator often extends beyond the primary subject matter and into the realm of classroom management. With this in mind, our research aimed to capture the various teaching practices, participation patterns, and communication climates that occur in virtual computer science classrooms. We sought to answer the following research questions related to virtual computer science classrooms at our institution: Who participates in virtual computer science classrooms, and is participation proportional to student demographics? Is there any …
High-Resistance Connection Diagnosis In Five-Phase Pmsms Based On The Method Of Magnetic Field Pendulous Oscillation And Symmetrical Components, Hao Chen, Jiangbiao He, Xing Guan, Nabeel Demerdash, Ayman M. El-Refaie, Christopher H.T. Lee
High-Resistance Connection Diagnosis In Five-Phase Pmsms Based On The Method Of Magnetic Field Pendulous Oscillation And Symmetrical Components, Hao Chen, Jiangbiao He, Xing Guan, Nabeel Demerdash, Ayman M. El-Refaie, Christopher H.T. Lee
Electrical and Computer Engineering Faculty Research and Publications
An online approach for diagnosing high-resistance connection (HRC) faults in five-phase permanent magnet synchronous motor drives is presented in this article. The development of this approach is based on a so-called “magnetic field pendulous oscillation (MFPO)” technique and symmetrical components method. Under HRC fault condition, a “swing-like” MFPO phenomenon is observed compared to the healthy condition. Furthermore, with the extracted current features in symmetrical components domain, different HRC fault types are successfully identified and distinguished. These fault types include single-phase faults, e.g., HRC fault in phase-A; two-phase nonadjacent faults, e.g., HRC fault in phase-A&C; and two-phase adjacent faults, e.g., HRC …
Faster Multidimensional Data Queries On Infrastructure Monitoring Systems, Yinghua Qin, Gheorghi Guzun
Faster Multidimensional Data Queries On Infrastructure Monitoring Systems, Yinghua Qin, Gheorghi Guzun
Faculty Research, Scholarly, and Creative Activity
The analytics in online performance monitoring systems have often been limited due to the query performance of large scale multidimensional data. In this paper, we introduce a faster query approach using the bit-sliced index (BSI). Our study covers multidimensional grouping and preference top-k queries with the BSI, algorithms design, time complexity evaluation, and the query time comparison on a real-time production performance monitoring system. Our research work extended the BSI algorithms to cover attributes filtering and multidimensional grouping. We evaluated the query time with the single attribute, multiple attributes, feature filtering, and multidimensional grouping. To compare with the existing prior …
Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D
Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D
Articles
Healthcare systems are under siege globally regarding technology adoption; the recent pandemic has only magnified the issues. Providers and patients alike look to new enabling technologies to establish real-time connectivity and capability for a growing range of remote telehealth solutions. The migration to new technology is not as seamless as clinicians and patients would like since the new workflows pose new responsibilities and barriers to adoption across the telehealth ecosystem. Technology-mediated workflows (integrated software and personal medical devices) are increasingly important in patient-centered healthcare; software-intense systems will become integral in prescribed treatment plans [1]. My research explored the path to …
Designing Respectful Tech: What Is Your Relationship With Technology?, Noreen Y. Whysel
Designing Respectful Tech: What Is Your Relationship With Technology?, Noreen Y. Whysel
Publications and Research
According to research at the Me2B Alliance, people feel they have a relationship with technology. It’s emotional. It’s embodied. And it’s very personal. We are studying digital relationships to answer questions like “Do people have a relationship with technology?” “What does that relationship feel like?” And “Do people understand the commitments that they are making when they explore, enter into and dissolve these relationships?” There are parallels between messy human relationships and the kinds of relationships that people develop with technology. As with human relationships, we move through states of discovery, commitment and breakup with digital applications as well. Technology …
Job Scheduling And Simulation In Cloud Based On Deep Reinforcement Learning, Qirui Li, Xinyi Peng
Job Scheduling And Simulation In Cloud Based On Deep Reinforcement Learning, Qirui Li, Xinyi Peng
Journal of System Simulation
Abstract: To solve the difficulty in job scheduling in the complex and transient multi-user, multi-queue, and multi-data-center cloud computing environment, this paper proposed a job scheduling method based on deep reinforcement learning. A system model of cloud job scheduling and its mathematical model were built, and an optimization goal consisting of transmission time, waiting time, and execution time was obtained. A job scheduling algorithm based on deep reinforcement learning was designed, and its state space, action space, and reward function were given. A simulated cloud job scheduler was designed and developed, and simulated scheduling experiments were conducted on it. The …
Multi-Floor Evacuation Model Based On Wavelet Neural Network, Juan Wei, Lei You, Yangyong Guo, Zhihai Tang
Multi-Floor Evacuation Model Based On Wavelet Neural Network, Juan Wei, Lei You, Yangyong Guo, Zhihai Tang
Journal of System Simulation
Abstract: Crowd evacuation in a multi-floor environment is a popular social concern, while the stagnation phenomenon easily occurs when simulating a multi-floor complex environment with the traditional social force model. Therefore, An improved social force model is proposed by a wavelet neural network, and a new multi-floor evacuation model is built. In the model, a pedestrian's direction of movement is obtained by the field model, which is used as the self-driving direction of the social force model. Meanwhile, the evaluation indexes of the exit congestion degree, path congestion degree, and average velocity in a multi-floor environment are given, and a …
Research On Semantic Segmentation Of Natural Landform Based On Edge Detection Module, Qizong Shen, Chunyan Gao
Research On Semantic Segmentation Of Natural Landform Based On Edge Detection Module, Qizong Shen, Chunyan Gao
Journal of System Simulation
Abstract: To classify pixels of natural landform edges in remote sensing images, this paper proposes a multi-channel fusion model and a decoder-side module model both integrating an edge detection module. The edge detection module takes the Canny operator as the base to perform closed operations and mean filtering, as a result of which accurate image edges can be achieved. Based on DeepLabV3+, the semantic segmentation network is connected with an edge planning module in parallel at encoder and decoder sides respectively. The experimental results show that the two improved networks can achieve a better segmentation effect on a high-resolution natural …
Zoomfft-Based Demodulation Algorithm For Underwater Acoustic Ofdm Signals, Qing Guo, Angdi Li, Jing Wu, Haitao Su
Zoomfft-Based Demodulation Algorithm For Underwater Acoustic Ofdm Signals, Qing Guo, Angdi Li, Jing Wu, Haitao Su
Journal of System Simulation
Abstract: The picket fence effect of fast Fourier transform (FFT) restricts the demodulation performance of the underwater acoustic(UWA) communication systemusing orthogonal frequency division multiplexing (OFDM). To solve this problem, we propose a demodulation algorithm based on ZoomFFT. Specifically, the received signal is processed by frequency shifting and downsampling forarefined spectrum, which improves the spectralresolution and weakens the picketfence effect.Meanwhile, the channel response is refined, and the channel equalization algorithm is constructed on the basis of the minimum mean square error (MMSE) principle to eliminate the channel influence. Simulations show that the performance of underwater acoustic OFDM demodulation algorithm based on …
Design Of Fatigue Driving Detection System Based On Cascaded Neural Network, Bangqian Ao, Sha Yang, Jinqing Linghu, Zhenhuan Ye
Design Of Fatigue Driving Detection System Based On Cascaded Neural Network, Bangqian Ao, Sha Yang, Jinqing Linghu, Zhenhuan Ye
Journal of System Simulation
Abstract: An algorithm is proposed to greatly improves the face detection rate and ensures the accuracy by adjusting the size of input images, expanding the minimum face size, and reducing the scaling ratio between layers of the detection window. The detection efficiency of this algorithm is 18 times higher than that of the original MTCNN. By building a new CNN structure model for the detection of eyes and mouths, we can achieve network detection accuracy of 95.6%. The proposed network is cascaded with the original MTCNN to continue classifying and locating the eyes and mouth in the formerly …
Segmentation Line Detection In Dental Model Based On Target Region Constraint, Tian Ma, Yun Li, Jiaojiao Li, Yuancheng Li
Segmentation Line Detection In Dental Model Based On Target Region Constraint, Tian Ma, Yun Li, Jiaojiao Li, Yuancheng Li
Journal of System Simulation
Abstract: It is an important pretreatment of a virtual orthodontic system to accurately segment teeth from a dental model. In the present methods, all patches are computed directly. To solve this problem, this paper proposes a segmentation line detection method based on target region constraint, which narrows down the detection range to the area around the actual segmentation line. In this method, the cutting plane and the cutting line are automatically formed according to the positions of seed points. The detection range is determined by the search for the position with the greatest negative curvature on the cutting line. The …
Modeling & Simulation Based System Of Systems Engineering, Lin Zhang, Kunyu Wang, Yuanjun Laili, Lei Ren
Modeling & Simulation Based System Of Systems Engineering, Lin Zhang, Kunyu Wang, Yuanjun Laili, Lei Ren
Journal of System Simulation
Abstract: To accommodate the dark and unstructured underwater working environment, the near-body pressure distribution characteristics of a bionic robot fish undulating in near wall region is studied. The feasibility of using artificial lateral line(ALL) to estimate the wall effect and flow field parameters is analyzed theoretically. A CFD(computational fluid dynamics) coupled solution model for near-body pressure simulation of a bionic robotic fish swimming near the wall is established and a near-body pressure data extraction and processing method is proposed. The effect of the wall clearance, inlet flow velocity and strouhal number (St) on the fish near-body pressure distribution …
Constructing The Agent Discrete Simulation Based On Devs Atomic Model, Xiaohan Wang, Lin Zhang, Yuanjun Laili, Kunyu Xie, Tingchun Hu
Constructing The Agent Discrete Simulation Based On Devs Atomic Model, Xiaohan Wang, Lin Zhang, Yuanjun Laili, Kunyu Xie, Tingchun Hu
Journal of System Simulation
Abstract: In order to resolve the nonlinear and ill-posed inverse problem of the image reconstruction of electrical capacitance tomography (ECT), an image reconstruction algorithm based on one-dimensional convolutional neural network (1D CNN) is presented. The nonlinear mapping relationship between the independent measurement value of ECT system and the gray value of reconstructed image is established by 1D CNN. Six typical flow regimes with random distribution are obtained by the finite element simulation software and a 1D CNN is successfully trained. Simulation and static experiments are carried out and the reconstructed images using linear back projection, Landweber iterative algorithm and 1D …
Transmission Line Operation And Inspection Training Simulation Based On Multiple Time Scales And Vr, Jiawen Yan, Jijie Huang, Lie Zhou, Changjin Chen, Qiang Wu, Jintao Zhao
Transmission Line Operation And Inspection Training Simulation Based On Multiple Time Scales And Vr, Jiawen Yan, Jijie Huang, Lie Zhou, Changjin Chen, Qiang Wu, Jintao Zhao
Journal of System Simulation
Abstract: Social learning is defined as the process that consumers use online reviews to fetch more precise information about product quality.Consequently, consumers would be more likely to purchase the product if the product quality learned was higher than their expectation, reference point effect named.To understand the impact of this effect in social learning on a firm's product decisions, we built a multi-agent model to solve the problem through simulation. According to the results, the reference point effect has a negative influence on the firm. The firm has to higher the product quality and price and therefore loses some profits. …
Product Decisions In Presence Of Social Learning And Reference Point Effect, Feng Li, Ying Wei
Product Decisions In Presence Of Social Learning And Reference Point Effect, Feng Li, Ying Wei
Journal of System Simulation
Abstract: In order to find out the source of VOCs(volatile organic compounds) emission and diffusion to the target area, and prevent the target area from further pollution, this paper propose an analytical method of VOCs hazard causes in related areas based on object function Petri net. The net structure describes the relationship between the potential pollution sources and the target area, and the operation of the net system reflects the change of VOCs hazard degree in the target area, and the calculation of hazard degree is integrated into the operation of the Petri net system. Through the actual case study, …
Review Of System Of Systems Combat Effectiveness Evaluation And Optimization Methods, Ziwei Zhang, Qisheng Guo, Zhiming Dong, Ang Gao, Yifei Wang
Review Of System Of Systems Combat Effectiveness Evaluation And Optimization Methods, Ziwei Zhang, Qisheng Guo, Zhiming Dong, Ang Gao, Yifei Wang
Journal of System Simulation
Abstract: The characteristics of system-of-systems combat effectiveness evaluation and optimization are analyzed. In light of the "holism", this paper proposes an idea of dividing system of systems combat effectiveness evaluation and optimization into three stages of comprehensive evaluation, analysis, and optimization. As for the practical problems that need to be solved in the three stages, typical methods suitable for each stage are summarized.The advantages and disadvantages of different methods are then compared. In view of the practical difficulties in implementing system of systems combat effectiveness evaluation and optimization guided by the "holism", this paper puts forward the next research directions …
Simulation And Optimization Of A New Multi-Channel Contact Center System, Junxiang Li, Lichao Li, Kun Ma
Simulation And Optimization Of A New Multi-Channel Contact Center System, Junxiang Li, Lichao Li, Kun Ma
Journal of System Simulation
Abstract: In the actual operation of a contact center, it often encounters a large number of calls caused by an emergency. A traditional call center with a simple first-come-first-served queuing rule can hardly handle the rapid increase of calls properly. In this regard, without changing the number of seats, the call-back service channel for evacuating tasks and the special service channel for ensuring the service level are added. Considering customer abandonment, a new multi-channel queuing model for a contact center is built. This model is simulated by FlexSim software, and the results are comparatively analyzed. It is found that …
Modeling And Optimization For Manufacturing Cell Scheduling Based On Improved Wolf Pack Algorithm And Simulation, Zi'an Zhao, Hong Zhou, Yingjian Lei
Modeling And Optimization For Manufacturing Cell Scheduling Based On Improved Wolf Pack Algorithm And Simulation, Zi'an Zhao, Hong Zhou, Yingjian Lei
Journal of System Simulation
Abstract: Aiming at the domestic aircraft stall spin simulation training need, a stall spin simulation training system is developed. The training system consists of the multi-channel dome visual system, the semi-physical simulation cockpit and the maneuvering force control loading system, etc. Distributed simulation technology is used to develop a realistic man-in-the-loop simulation training environment. For the stall spin simulation, the multi-source aerodynamic data is processed comprehensively, and an unsteady aerodynamic model at high angle of attack (AOA) is constructed, and the heavy-load digital electric control loading technology is used to realize the simulation of stall spin alternating force and jitter …