Computer Engineering Commons^™

การแปลงแผนภาพลำดับที่มีตัวยืนยงสถานะเป็นไทม์ออโตมาตา, ศุภพิชญ์ แสงมณี ฐิตารีย์เดชากุล

Chulalongkorn University Theses and Dissertations (Chula ETD)

ในช่วงการออกแบบระบบหลังจากที่ได้รับความต้องการมาแล้ว และได้ผลลัพธ์ออกมาเป็นข้อตกลงตามความต้องการของระบบแล้ว แผนภาพลำดับคือส่วนสำคัญที่อธิบายถึงพฤติกรรมของระบบที่มีปฏิสัมพันธ์กัน เป็นประโยชน์มากเพื่อให้กลุ่มผู้พัฒนาเห็นการทำงานเชิงพฤติกรรมของระบบ และมองพฤติกรรมของระบบไปทิศทางเดียวกันได้ สามารถใช้ในการทวนสอบข้อตกลงของระบบว่าครบถ้วน สมบูรณ์หรือไม่ แต่แผนภาพลำดับมีปัญหาเรื่องไม่สามารถทวนสอบแบบอัตโนมัติได้ ต้องใช้การวิเคราะห์และทวนสอบโดยการตัดสินใจของมนุษย์ และพฤติกรรมในบางระบบมีรูปแบบเชิงไม่กำหนด มีความซับซ้อนและไม่สามารถทวนสอบได้ งานวิจัยนี้เล็งเห็นถึงปัญหาที่เกิดขึ้นจึงคิดวิธีการทวนสอบข้อตกลงตามความต้องการของระบบของแผนภาพลำดับ โดยใช้แบบจำลองเชิงรูปนัยชื่อ ไทม์ออโตมาตาโดยการเปรียบเทียบและวิเคราะห์โครงสร้างแผนภาพลำดับที่มีตัวยืนยงสถานะตามหลักยูเอ็มแอลเวอร์ชัน 2.0, 2.5 และเครื่องมือ UPPAAL นิยามกฎการแปลงและพัฒนาเครื่องมือสำหรับใช้ในการแปลงแผนภาพลำดับที่มีตัวยืนยงสถานะเป็นไทม์ออโตมาตา เริ่มแปลงแผนภาพลำดับที่มีตัวยืนยงสถานะด้วยแฟ้มข้อความเป็นแฟ้มเอกซ์เอ็มแอลของเครื่องมือ UPPAAL จำลองและทวนสอบไทม์ออโตมาตาตามคุณสมบัติที่สนใจที่เขียนด้วยสูตร TCTL โดยในการทดสอบเครื่องมือแปลงแผนภาพลำดับที่มีตัวยืนยงสถานะเป็นไทม์ออโตมาตากับกรณีศึกษาพบว่า สามารถช่วยให้ผู้พัฒนาระบบสามารถเห็นพฤติกรรมเชิงระบบและนำมาสู่การปรับปรุงแผนภาพให้สอดคล้องกับข้อตกลงตามความต้องการของระบบ และทวนสอบระบบได้ผลลัพธ์ออกมาน่าพึงพอใจและเป็นไปตามข้อตกลงตามความต้องการของระบบ

การบูรณาการระบบความมั่นคงสารสนเทศตามมาตรฐานไอเอสโอ/ไออีซี 27001 กับการจัดการโครงการซอฟต์แวร์, วชิรวิทย์ เซียวสกุล

Chulalongkorn University Theses and Dissertations (Chula ETD)

การบูรณาการระบบการจัดการความมั่นคงสารสนเทศและการจัดการโครงการซอฟต์แวร์มีความสําคัญอย่างยิ่ง เนื่องจากข้อมูลที่เกิดขึ้นในระบบสารสนเทศน้ันมีความละเอียดอ่อน เช่น ข้อมูลทางการเงิน หรือ ข้อมูลส่วนบุคคล เป็นต้น ซึ่งหากข้อมูลสารสนเทศดังกล่าวถูกเข้าถึงโดยไม่ได้รับอนุญาตจากเจ้าของข้อมูล หรือถูกนําไปใช้ในทางที่ไม่ถูกต้อง จะส่งผลให้เกิดความเสียหายต่อเจ้าของข้อมูล รวมถึงองค์กรที่ให้บริการระบบสารสนเทศดังกล่าว ดังนั้นระบบการจัดการความเสี่ยงด้านความมั่นคงสารสนเทศจึงจําเป็นต้องบูรณาการเข้ากับการจัดการโครงการในทุกขั้นตอนของวัฏจักรการพัฒนาซอฟต์แวร์ ปัจจุบันโครงการพัฒนาซอฟต์แวร์มักจะเกิดในสภาพแวดล้อมที่มีการเปลี่ยนแปลงอย่างรวดเร็ว การประยุกต์ใช้แนวปฏิบัติแบบสกรัมจะช่วยเข้ามาตอบโจทย์ความต้องการในการพัฒนาซอฟต์แวร์ที่มีการเปลี่ยนแปลงอย่างรวดเร็วนี้ นอกจากนี้ยังมีความท้าทายในการบูรณาการระบบการจัดการความมั่นคงสารสนเทศกับการจัดการโครงการซอฟต์แวร์แบบสกรัมเฟรมเวิร์กคือ จากการรักษาความสมดุลระหว่างมาตรการความมั่นคงสารสนเทศที่มีความเข้มงวดกับระเบียบวิธีแบบสกรัมที่เน้นความรวดเร็วและคล่องตัว โครงงานนี้ผู้จัดทําโครงงานได้นําเสนอการบูรณาการระบบการจัดการความมั่นคงสารสนเทศกับการจัดโครงการซอฟต์แวร์แบบสกรัม โดยอ้างอิงจากมาตรฐานสากล ความต้องการของระบบจัดการความมั่นคงสารสนเทศ (ISO/IEC 27001:2022) มาตรการควบคุมความมั่นคงสารสนเทศ (ISO/IEC 27002:2022) และ การจัดการความเสี่ยง (ISO/IEC 31000:2018) นอกจากนี้ผู้จัดทําโครงงานได้อ้างอิงองค์ความรู้ด้านการจัดการโครงการซอฟต์แวร์แบบสกรัม จากการจัดการโครงการของสถาบันการจัดการโครงการ (Project Management Institute) และคู่มือสกรัมจากองค์กรแนวทางปฏิบัติสกรัม (Scrum Guides Organization) โดยกระบวนการที่ผ่านการบูรณาการแบ่งออกเป็น 6 ขั้นตอน ซึ่งได้ออกแบบรายละเอียดกิจกรรมและบทบาทของผู้เกี่ยวข้องที่เกิดขึ้นในแต่ละกิจกรรม เพื่อให้การจัดการโครงการซอฟต์แวร์มีความมั่นคงสารสนเทศอย่างทนทาน พร้อมทั้งพัฒนาเครื่องมือต้นแบบสำหรับการจัดการความมั่นคงสารสนเทศของโครงการซอฟต์แวร์แบบสกรัม ซึ่งช่วยสนับสนุนให้การจัดการโครงการมีประสิทธิภาพมากยิ่งขึ้น

Ssvep-Bci In Augmented Reality In Realistic Environment, Bhuwit Chaiyarit

Chulalongkorn University Theses and Dissertations (Chula ETD)

This study investigates Augmented Reality-based Steady-State Visual Evoked Potentials (AR-SSVEP) in Brain-Computer Interface (BCI) systems, utilizing Extended Filter Bank Canonical Correlation Analysis (Extended-FBCCA) for SSVEP recognition optimization across various frequencies in various scenarios. The 10 Hz stimulus consistently achieves the highest recognition accuracy. Frequency-specific variations at 12 Hz, 13 Hz, and 15 Hz highlight nuanced SSVEP responses. White stimuli yield PC-SSVEP recognition ranging from 68.32% to 81.98%, slightly outperforming AR-SSVEP-Controlled (63.59% to 73.23%). Red stimuli impact AR-SSVEP-Controlled less than PC-SSVEP, with recognition ranges of 68.65% to 76.30% and 67.97% to 76.72%, respectively. Comparisons show a general slight outperformance of PC-SSVEP, …

Exploiting The Advantages And Overcoming The Challenges Of The Cable In A Tethered Drone System, Rogerio Rodrigues Lima

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation proposes solutions for motion planning, localization, and landing of tethered drones using only tether variables. A tether-based multi-model localization framework for tethered drones is proposed. This framework comprises three independent localization strategies based on a different model. The first strategy uses simple trigonometric relations assuming that the tether is taut; the second method relies on a set of catenary equations for the slack tether case; the third estimator is a neural network-based predictor that can cover different tether shapes. Multi-layer perceptron networks previously trained with a dataset comprised of the tether variables (i.e., length, tether angles on the …

Co-Design Of An Interactive Wellness Park: Exploring Design Requirements For A Multimodal Outdoor Physical Web Installation With Older Adults, Fatima Badmos

Academic Posters Collection

The global demographic landscape is experiencing a notable shift, characterised by a growing proportion of adults over 60. According to projections, the proportion of individuals aged 60 and above is expected to reach one-sixth of the global population by 2030. Furthermore, by 2050, this demographic is projected to exceed a staggering two billion people. Amidst this shift, there is an urgent need to develop interactive and innovative solutions to address older adults' unique challenges, particularly in outdoor physical activity.

A co-design methodology involving older adults’ participation from the idea generation to the application development process will be adopted to address …

An Adaptive Image Restoration Algorithm Based On Hybrid Total Variation Regularization, Cong Thang Pham, Thi Thu Thao Tran, Hung Vi Dang, Hoai Phuong Dang

Turkish Journal of Electrical Engineering and Computer Sciences

In imaging systems, the mixed Poisson-Gaussian noise (MPGN) model can accurately describe the noise present. Total variation (TV) regularization-based methods have been widely utilized for Poisson-Gaussian removal with edge-preserving. However, TV regularization sometimes causes staircase artifacts with piecewise constants. To overcome this issue, we propose a new model in which the regularization term is represented by a combination of total variation and high-order total variation. We study the existence and uniqueness of the minimizer for the considered model. Numerically, the minimization problem can be efficiently solved by the alternating minimization method. Furthermore, we give rigorous convergence analyses of our algorithm. …

Deep Learning-Based Classification Of Chaotic Systems Over Phase Portraits, Sezgi̇n Kaçar, Süleyman Uzun, Burak Aricioğlu

Turkish Journal of Electrical Engineering and Computer Sciences

This study performed a deep learning-based classification of chaotic systems over their phase portraits. To the best of the authors' knowledge, such classification studies over phase portraits have not been conducted in the literature. To that end, a dataset consisting of the phase portraits of the most known two chaotic systems, namely Lorenz and Chen, is generated for different values of the parameters, initial conditions, step size, and time length. Then, a classification with high accuracy is carried out employing transfer learning methods. The transfer learning methods used in the study are SqueezeNet, VGG-19, AlexNet, ResNet50, ResNet101, DenseNet201, ShuffleNet, and …

A Type-2 Fuzzy Rule-Based Model For Diagnosis Of Covid-19, İhsan Şahi̇n, Erhan Akdoğan, Mehmet Emi̇n Aktan

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a type-2 fuzzy logic-based decision support system comprising clinical examination and blood test results that health professionals can use in addition to existing methods in the diagnosis of COVID-19 has been developed. The developed system consists of three fuzzy units. The first fuzzy unit produces COVID-19 positivity as a percentage according to the respiratory rate, loss of smell, and body temperature values, and the second fuzzy unit according to the C-reactive protein, lymphocyte, and D-dimer values obtained as a result of the blood tests. In the third fuzzy unit, the COVID-19 positivity risks according to the clinical …

An Effective Hilbert-Huang Transform-Based Approach For Dynamic Eccentricity Fault Diagnosis In Double-Rotor Double-Sided Stator Structure Axial Flux Permanent Magnet Generator Under Various Load And Speed Conditions, Makan Torabi, Yousef Alinejad Beromi

Turkish Journal of Electrical Engineering and Computer Sciences

Eccentricity fault in double-sided axial flux permanent magnet generator is very difficult to be detected as the fault generated variations in terminal electrical parameters are very weak and chaotic, especially at the initial stages of the fault occurrence. In addition, one of the most important problems in any fault diagnosis approach is the investigation of load and speed variation on the proposed indices. To overcome the aforementioned difficulty and problems, this paper adopts a novelty detection algorithm based on Hilbert-Huang transform (HHT) which is a time-frequency signal analysis approach based on empirical mode decomposition and the Hilbert transform. It is …

Transmission Network Planning For Realistic Egyptian Systems Via Encircling Prey Based Algorithms, Abdullah M. Shaheen, Ragab Elsehiemy, Mohammed Kharrich, Salah Kamel

Turkish Journal of Electrical Engineering and Computer Sciences

Transmission network planning problem (TNPP) is one of the pertinent issues of the planning activities in power systems. It aims to optimally pick out the routs, types, and number of the new installed lines to confront the expected future loading conditions. In this line, this study proposes a new economic model to the TNPP. The aim of the model is to find the optimal transmission routes at least investment and operating costs. Three recent algorithms called grey wolf optimization algorithm (GWOA), spotted hyena optimization algorithm (SHOA) and whale optimization algorithm (WOA) are developed to solve the TNPP. The concept of …

Early Diagnosis Of Pancreatic Cancer By Machine Learning Methods Using Urine Biomarker Combinations, İrem Acer, Firat Orhan Bulucu, Semra İçer, Fatma Lati̇foğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The most common type of pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC), which accounts for the vast majority of pancreatic cancers. The five-year survival rate for PDAC due to late diagnosis is 9%. Early diagnosed PDAC patients survive longer than patients diagnosed at a more advanced stage. Biomarkers can play an essential role in the early detection of PDAC to assist the health professional. Machine learning and deep learning methods are used with biomarkers obtained in recent studies for diagnostic purposes. In order to increase the survival rates of PDAC patients, early diagnosis of the disease with a noninvasive test …

Binary Text Classification Using Genetic Programming With Crossover-Based Oversampling For Imbalanced Datasets, Mona Aljero, Nazi̇fe Di̇mi̇li̇ler

Turkish Journal of Electrical Engineering and Computer Sciences

It is well known that classifiers trained using imbalanced datasets usually have a bias toward the majority class. In this context, classification models can present a high classification performance overall and for the majority class, even when the performance for the minority class is significantly lower. This paper presents a genetic programming (GP) model with a crossover-based oversampling technique for oversampling the imbalanced dataset for binary text classification. The aim of this study is to apply an oversampling technique to solve the imbalanced issue and improve the performance of the GP model that employed the proposed technique. The proposed technique …

Lvq Treatment For Zero-Shot Learning, Firat İsmai̇loğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In image classification, there are no labeled training instances for some classes, which are therefore called unseen classes or test classes. To classify these classes, zero-shot learning (ZSL) was developed, which typically attempts to learn a mapping from the (visual) feature space to the semantic space in which the classes are represented by a list of semantically meaningful attributes. However, the fact that this mapping is learned without using instances of the test classes affects the performance of ZSL, which is known as the domain shift problem. In this study, we propose to apply the learning vector quantization (LVQ) algorithm …

Hashes Are Not Suitable To Verify Fixity Of The Public Archived Web, Mohamed Aturban, Martin Klein, Herbert Van De Sompel, Sawood Alam, Michael L. Nelson, Michele C. Weigle

Computer Science Faculty Publications

Web archives, such as the Internet Archive, preserve the web and allow access to prior states of web pages. We implicitly trust their versions of archived pages, but as their role moves from preserving curios of the past to facilitating present day adjudication, we are concerned with verifying the fixity of archived web pages, or mementos, to ensure they have always remained unaltered. A widely used technique in digital preservation to verify the fixity of an archived resource is to periodically compute a cryptographic hash value on a resource and then compare it with a previous hash value. If the …

Efficient Gpu Implementation Of Automatic Differentiation For Computational Fluid Dynamics, Mohammad Zubair, Desh Ranjan, Aaron Walden, Gabriel Nastac, Eric Nielsen, Boris Diskin, Marc Paterno, Samuel Jung, Joshua Hoke Davis

Computer Science Faculty Publications

Many scientific and engineering applications require repeated calculations of derivatives of output functions with respect to input parameters. Automatic Differentiation (AD) is a method that automates derivative calculations and can significantly speed up code development. In Computational Fluid Dynamics (CFD), derivatives of flux functions with respect to state variables (Jacobian) are needed for efficient solutions of the nonlinear governing equations. AD of flux functions on graphics processing units (GPUs) is challenging as flux computations involve many intermediate variables that create high register pressure and require significant memory traffic because of the need to store the derivatives. This paper presents a …

A Structure-Aware Generative Adversarial Network For Bilingual Lexicon Induction, Bocheng Han, Qian Tao, Lusi Li, Zhihao Xiong

Computer Science Faculty Publications

Bilingual lexicon induction (BLI) is the task of inducing word translations with a learned mapping function that aligns monolingual word embedding spaces in two different languages. However, most previous methods treat word embeddings as isolated entities and fail to jointly consider both the intra-space and inter-space topological relations between words. This limitation makes it challenging to align words from embedding spaces with distinct topological structures, especially when the assumption of isomorphism may not hold. To this end, we propose a novel approach called the Structure-Aware Generative Adversarial Network (SA-GAN) model to explicitly capture multiple topological structure information to achieve accurate …

Examining Early Elementary Computer Science Identity Repertoires Within A Curriculum: Implications For Epistemologically Pluralistic Identities, Eleanor Richard, Shakhnoza Kayumova

Journal of Computer Science Integration

As computer science (CS) enters an increasing number of elementary classrooms, researchers must investigate the representations of what kinds of people are presented as doing computer science within CS curricula. In this paper, we explore a widely used, freely accessible, web-based, early elementary CS curriculum to examine the kinds of identity repertoires (behaviors, actions, skills, and socioemotional norms) that are promoted as representative of being/becoming a CS person. More specifically, we draw on identity studies and employ critical discourse analysis to examine how the kinds of norms and repertoires of CS practice made available in the curricular materials might construct …

Overview Of Research And Application On Autonomous Vehicle Oriented Perception System Simulation, Ruoxuan Wang, Jianping Wu, Hui Xu

Journal of System Simulation

Abstract: Following the rapid progress of science and technology, vehicles with autonomous driving or auxiliary driving function enter into vehicle market. However, in the past decade, traffic accidents still occurred frequently, and the safety of these functions become the focus. Simulation technology provides a good platform to test the perception system of autonomous vehicle. Focus on the sensor simulation modeling of autonomous vehicle perception system, from the perspective of single sensor simulation, multi-sensor simulation and classic simulation platform including millimeter wave radar, lidar and camera, the existing research are reviewed, and the shortcomings and development trends of simulation modeling of …

Anomaly Detection Method Of Electrical Power Consumption Based On Deep Autoencoder, Ningke Sun, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the nonlinear and non-stationary characteristics of electrical power consumption data, an abnormal electrical power consumption detection model based on deep autoencoder is proposed. Gated recurrent unit (GRU) network of the deep learning is combined with autoencoder structure, and the encoder and decoder parts of traditional autoencoder are realized by gated recurrent unit network, which gives full play to the data feature extraction capability of gated recurrent unit and the data reconstruction function of autoencoder structure. Based on the reconstruction error between original data and reconstructed data, abnormal data points of the electrical power consumption are detected. By …

Short-Term Prediction Method Of Wind Power Based On Blp-Alo-Svm, Yefeng Jiao, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: To effectively predict the short-term wind power and its fluctuation range, a prediction method based on hybrid algorithm-optimized support vector machine is proposed. Exploratory data analysis is used to preprocess the original wind speed data to improve the data quality. Chaotic map, Levy flight strategy and particle swarm optimization are used to improve the ant lion algorithm. The support vector machine model optimized by hybrid algorithm is used to predict the wind power. The experimental results show that, compared with the new wind power prediction model, the prediction error of the output results of the method is lower, and …

Long-Term Resilience Simulation On Low-Carbon Urban Grid Based On Evolutionary Game, Zhengda Cui, Weiqiang Yao, Qin Xu, Chen Fang, Ying Chen

Journal of System Simulation

Abstract: Because of the more frequent extreme disasters, the resilience of urban grid becomes more important. In the background of carbon neutralization policy, the decarbonization transition of urban grid also affects the development of grid resilience. An evolutionary game is used to simulate the resilience evolution of low-carbon urban grid and the evolution model is constructed. The decision to install photovoltaic and energy storage system for residents and to upgrade the grid for resilience is considered in the model and the stability conditions of equilibriums of the evolutionary game are analyzed. The resilience evolution simulation model considering disaster stochasticity is …

Simulation-Driven Based Utility Evaluation And Recommendation Of Expressway Proactive Speed Limit, Geqi Qi, Sijin Liu, Yikang He, Meng Wang, Ailing Huang

Journal of System Simulation

Abstract: Outside the specific punishment area, the traditional roadside passive speed limit mode lacks traffic management, and thus which indirectly leads to the inconsistency or even sudden change of vehicle behaviors in time and space, thereby affects the traffic efficiency and safety. Focusing on the proactive speed limit mode at vehicle side, a utility evaluation and recommendation method is proposed, which carries out the multi-scenario traffic simulation for varied proactive and passive speed limit considering road line types, traffic flow and vehicle type proportion. From the two perspectives of safety and efficiency, the utility evaluation indicators and weights are extracted …

Simulation On Flood Disaster In Urban Building Complex System Based On Lbm, Shen Zhang, Zewang Yang, Yifan Wang, Liang Sun, Ming Cheng, Fankai Meng, Ting Li

Journal of System Simulation

Abstract: Because of the extreme climate change, the potential flood disaster risk in the southeast coastal areas of China can not be ignored. Based on lattice Boltzmann computational fluid dynamics method, a three-dimensional simulation study of waterlogging process in tsunami impact scenario is carried out for a coastal city building complex system, and the reliability and accuracy of the numerical simulation method for the flood impact test of an ideal building complex are verified. The results show that the buildings along rivers and coastlines have obvious cloaking effect, while the buildings inside the city are less affected by floods. The …

Research On Modeling And Simulation Technology Of Microwave Radar High Precision Tracking Loop, Jiaji Lou, Jing Ma, Xiaowei Li, Yue Zhao, Youbin Song

Journal of System Simulation

Abstract: Aiming at the key problem of high-precision tracking loop design of a measurement radar for the weak signal (low carrier to noise ratio signal) in dynamic environment, the design and optimization methods of carrier tracking loop and code tracking loop are focused on. A signal structure with a single carrier as a pilot is proposed, and the loop structure of the frequency-locked loop and the phase-locked loop working together is studied. The modeling and simulation on the two structures show that for the week signal tracking in a dynamic environment, the loop combination structure of the frequency-serial auxiliary …

Research On Parameter Construction Method Of Blue Army Equipment Model Based On A Deep Network, Boyuan Zhang, Guanghong Gong, Ze Wang, Ni Li

Journal of System Simulation

Abstract: The modeling of blue army equipment is an indispensable part of adversarial simulation environment construction. Aiming at the limited available parameters of "information-poor" and "small sample" characteristics to the blue system, a deep network-based method is proposed to generate the parameters of blue army equipment model. By injecting the information into the simulation model of the blue army equipment, the simulation data is generated and trained in the deep neural network. The obtained network has a certain generalization ability to the unknown parameters prediction of the same type of equipment and can be used directly in prediction or be …

Multi-Robot Path Planning Based On Cbs Algorithm, Qiao Qiao, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the long multi-robot planning path and long one-way search running time of conflict-based search(CBS) in the multi-agent path finding(MAPF), an improved CBS algorithm is proposed, which in a two-way A^* focus search is used to optimize the search direction and search method. The suboptimal factorωis introduced into the underlying search function of the CBS algorithm to improve the efficiency of path search. The one-way search in the conflict search algorithm is optimized to a two-way A^* search. The experimental results show that the path cost of the improved CBS algorithm is shortened …

Research On Emotional Contagion And Intervention Strategy Of Indoor Evacuation Based On Risk Perception, Yang Zeng, Jinling Li, Haixiang Guo, Weiming Chen

Journal of System Simulation

Abstract: Aiming at the panic emotion contagion in the indoor emergency evacuation with multi-exit and multi-obstacle, an emotional contagion model is constructed on personality traits, risk perception differences of age and gender, and consciousness regulation. The simulation is carried out by using AnyLogic, which combines individual emotions with evacuation speed to realize the real-time updating of emotional state and speed. That personnel intervention in the process of evacuation can effectively alleviate the spread of panic emotion, is verified and can provide the theoretical basis for panic contagion in the process of emergency evacuation. The results show that the degree of …

Research On Complex Combat Network Dynamic Evolution Based On Information Entropy, Lianyi Zhang, Xisheng Shen, Duzheng Qing, Han Zhang, Min Zhou, Xifu Wang

Journal of System Simulation

Abstract: Network-centric warfare, distributed and decentralized command and control gradually replace separately the traditional platform-centric warfare and centralized command and control, and information has become a combat capability. Based on the new information weapon equipment system operation loop, a complex combat network model based on information entropy is constructed, and the combat capability measurement method is proposed. On the basis of the combat capability upgrade being the network driving force, the dynamic evolution rule of the complex combat network is designed and the preferential evolution and stochastic evolution models are constructed. According to a typical system combat example, the influence …

Low Voltage Ride-Through Modeling For Wind Turbines Based On Neural Odes, Qiping Lai, Tannan Xiao, Dongsheng Li, Chen Shen

Journal of System Simulation

Abstract: Considering the difficulty of equivalent modeling of low voltage ride-through(LVRT) characteristics of a wind farm, a neural ordinary differential equation(ODE)-based wind farm LVRT modeling methodis proposed. The input of the model is the voltage and wind speed of each wind turbine at the grid connection point of wind farm, and the output is the current at the grid connection point. The model can better characterize the strong nonlinear switching process and describe LVRT characteristics of wind farms under different wind speed scenarios. A simulation example of a wind farm including three doubly-fed induction generators(DFIGs) is established on …

Simulation Research On Appearance Detection Of Ampoules Based On Lightweight Network And Model Compression, Zhihao Zhu, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the large scale and redundant parameters of target detection network model, which result in the difficult to deploy the ampoule bottle appearance defect detection model to edge devices, an LC-Faster R-CNN defect detection algorithm based on lightweight network and model compression is proposed. MobileNet-V2 is used as the backbone, and the redundant channels in the convolutional network are trimmed by model pruning strategy. The floating-point parameters are quantized into integers through saturation truncation mapping. Knowledge distillation is used to restore the accuracy of the compressed network. Tested on the self-built ampoule appearance defect dataset, the model volume …