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computer Model for Analysis of the Process of Image Construction in Optical-Electronic Visualization Systems 1st

Computer Model for Analysis of the Process of Image Construc...

引用

1st international Scientific conference on Telecommunications, Computing and Control, TELECCON 2019

作者： Gritskevich, Evgenij Egorenko, Marina Makarova, Diana Novikov, Sergei Polikanin, Alexey Shaburova, Aelita Siberian State University of Geosystems and Technologies Novosibirsk Russia

ISBN: (纸本)9789813366312

A simulation computer model of an image visualization system is considered. The model allows to analyze the effectiveness of the use of such systems together with the observer’s eye according to the probability criterion for solving the observational problem using Johnson’s equivalent bar. This method of formalizing input actions provides the possibility of their analytical presentation in the form of a set of harmonic signals, which greatly simplifies the modeling task while maintaining the adequacy of the model. The proposed simulation model is intended for computer analysis of any visualization systems that include links of various physical nature. In this case, each link is displayed by its own model, taking into account the features of the link, but the composition of the information signal parameters at the input and output of each link does not change, which allows a uniform methodological approach to the development of software modules that implement link models. At the model output, the probability of solving the observational problem by the observer’s visual apparatus on the device’s screen is calculated at the required degree of decryption of the object. This allows for a given probability to determine the range of the device, and for a given range and probability—to carry out optimal coordination of link parameters. In addition, the model provides the calculation of the most important characteristics of visualization systems, for example, the modulation transfer function, which, combined with the calculation of the effective values of the noise fluctuations of the output image, makes it possible to generate these images for typical objects of observation on the screen of a computer monitor, as when operating a real visualization system. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Probability

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A simplified approach to include confinement induced band structure changes into the NsFET compact model

A simplified approach to include confinement induced band st...

引用

international conference on Emerging Electronics (ICEE)

作者： Aishwarya Singh Mohit D. Ganeriwala Ramandeep Kaur Nihar R. Mohapatra Electrical Engineering IIT Gandhinagar Gandhinagar India Electronics and Computer Technology Universidad de Granada Granada Spain

This work presents a simplified mathematical method to capture the k.p-based band structure modifications with confinement and device substrate/transport orientation in the compact model of quantum confined Nanosheet FETs. The change in effective mass with confinement is captured in terms of non-parabolic sub-bands. The estimated sub-bands are used to compute inversion charge density and gate capacitance using a bottom-up scalable compact model for different device dimensions and substrate/channel orientations. The accuracy of the proposed method is confirmed using k.p simulation in Global TCAD Solutions (GTS).

关键词： Band structures Quantum computing Computational modeling Logic gates Data models Nanoscale devices Mathematical models

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CLASSIFICATION OF VARIOUS STAGES OF HERNIATED CERVICAL SPINE IMAGES USING EDGE DETECTION OPERATORS

CLASSIFICATION OF VARIOUS STAGES OF HERNIATED CERVICAL SPINE...

引用

Computational Modelling, simulation and Optimization (ICCMSO), international conference on

作者： C. Malarvizhi P. Balamurugan Department of Computer Technology Dr. N.G.P Arts and Science College Coimbatore India Department of Computer Science Government Arts College Coimbatore India

A herniated disc is a state that can happen anywhere along the spine, but utmost in the lower back and neck. Cervical discs are the cushionsthat can link the vertebrae in the upper back and neck. When the gelatinous inner disc material, the nucleus pulposus ruptures or herniates through the outer cervical disc wall it can lead to herniation. Some herniated disc causes no symptoms but other disc related problems can irritate nearby nerves and result in pain, numbness or weakness in an arm or leg. In this work, cervical spine abnormal (herniated) Magnetic Resonance Images (MRI) are taken for classification. Generally, there are four stages of herniation in cervicalspine named as disc degeneration, disc prolapse, disc extrusion and disc sequestration. These herniated cervical spine images are transformed into herniated canny images, because canny edge detection algorithm is better to provide high image quality and allows removing of any noise in an image. Artificial Neural Network classifier is used for classifying the different stages of images. It follows the supervised learning method, and is the process of learning to separate samples into different classes by finding common features between samples of known classes. In this paper, various stages of herniated canny images are processed with different level of combinations of texture features are analyzed. Classification is done on different stages of herniated cervical spine images. This classification is used in different variants and utilizes it with suitable algorithm to improve its performance.

关键词： Pain Image edge detection Computational modeling Magnetic resonance imaging Supervised learning Magnetic resonance Back

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Improved One-Stage Algorithm with Attention Fusion for Human Sperm Detection Based on Deep Learning 7th

Improved One-Stage Algorithm with Attention Fusion for Human...

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7th international conference on Life System modeling and simulation, LSMS 2021, and 7th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021

作者： Li, Chuanjiang Han, Haozhi Hu, Ziwei Zhang, Chongming Zhi, Erlei College of Information Mechanical and Electronic Engineering Shanghai Normal University Shanghai201418 China Department of Andrology Center for Men’s Health Department of ART Institute of Urology Urologic Medical Center Shanghai General Hospital Shanghai Key Lab of Reproductive Medicine Shanghai Jiao Tong University Shanghai200080 China

ISBN: (纸本)9789811672064

The popular methods of human sperm detection are mostly based on machine learning. Although most deep learning methods have got state-of-art performance in object detection with the advancement of deep learning, only a few of them were used successfully in human sperm detection. With the deep learning method, the detection task is divided into different scales in feature maps of different level. The sperm target is so small under the phase-contrast microscope that the detection task is hard even with deep learning technology. Feature Pyramid Network (FPN) was designed to mitigate this problem in one-stage detector. In this paper, we proposed a new FPN based method in which the feature map was fused with attention module to get the correlation information of low-level feature maps. Eventually, we got an AP of 83.77 which is higher than YOLO v4 and some other detectors. © 2021, Springer Nature Singapore Pte Ltd.

关键词： computer vision

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computer-Aided modeling of the Hot Forming Staking Process Based on Experimental Data 13th

Computer-Aided Modeling of the Hot Forming Staking Process B...

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13th international conference on the Technology of Plasticity, ICTP 2021

作者： Härtel, Sebastian Brückner, Eric Awiszus, Birgit Gehde, Michael Virtual Production Engineering TU Chemnitz Reichenhainer Str. 70 Chemnitz09126 Germany Professorship of Plastics Engineering Reichenhainer Str. 70 Chemnitz09126 Germany

ISBN: (纸本)9783030753801

As a non-detachable and point-acting joint, thermoplastic staking is primarily used for the production of electronic and sensor elements as well as for the joining of components in the automotive interior and exterior. Commonly, the advantages of staking processes are its cost-efficient and seemingly simple process control. Regarding the industrial application, staking is principally a well-established forming process. However, despite the high number of applications, the joint design and the process settings are mainly based on extensive empirical tests. At present, the FE simulation of these thermoplastic staking processes is not state-of-the-art. Due to these facts, within the frame of the paper, these gaps are to be closed by the computer-aided modeling of the hot forming staking to map the heating and forming behavior of this process close to reality. This procedure demands the associated experimental validation of the simulation. In summary, the numerical model shows high conformity to the experimental data and allows a simulative mapping of the morphological characteristics of the riveted joint as well as indicative statements to the process parameters, which means in particular the minimal heating time for forming and the optimized post-heating time for a morphological homogenization. © 2021, The Minerals, Metals & Materials Society.

关键词： Optimization

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computer simulation in proton therapy 9

Computer simulation in proton therapy

引用

9th international conference on Mathematical modeling in Physical Sciences, IC-MSQUARE 2020

作者： Echkina, E. Guzminova, N. Moscow State University Computational Mathematics and Cybernetics A.I. Yevdokimov Moscow State University of Medicine and Dentistry Russia

The ionising radiation as a method of cancer treatment has a long history. Any types of radiation have been employed to achieve control of tumour viability such as a'low' linear energy transfer (LET) beam of photons, two'high' LET unmodified and spread-out Bragg peak (SOBP) beams of protons. Per the end of 2018, about 190036 patients have been treated with protons [1), 93 facilities in clinical operation worldwide in April 2020 (2). The unattainable goal so far is the creation and implementation of such a treatment plan in which the target volume receives 100 % of the prescribed dose and healthy surrounding tissue 0%. The goal of modern science to find ways to "optimised"treatment plan especially in childhood cancer, where the preservation of healthy tissue surrounding the tumour is especially important. In our work we presented the results of a calculated experiment of the interaction of a laser impulse with various targets and showed the dependence of energy distribution from the target types. © Published under licence by IOP Publishing Ltd.

关键词： Tumors

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Adaptive Conflict Detection Algorithm Based on Rochester Software Transactional Memory 3

Adaptive Conflict Detection Algorithm Based on Rochester Sof...

引用

2020 3rd international conference on modeling, simulation and Optimization Technologies and Applications, MSOTA 2020

作者： Liu, Ying Liu, Junting Gao, Fuxiang College of Computer Science and Engineering Northeastern University Shenyang China

When the transactional memory system detects conflicts, the more read-write addresses are, the higher the false positive rate of this algorithm is. This paper studies the problem and proposes a new signature based optimization algorithm, adaptive increase signature algorithm (AISA). The algorithm can calculate the saturation value of the number of read-write addresses, and dynamically adjust the size of bit string through the calculated saturation value, thus greatly reducing the false positive rate. The experimental results show that AISA can control the false positive rate at a low level on the basis of considering the space cost, and its effect is almost the same as that of 6 times of space, which will improve the performance of transactional memory system greatly. © Published under licence by IOP Publishing Ltd.

关键词： Signal detection

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Continuous Human Learning Optimization with Enhanced Exploitation 7th

Continuous Human Learning Optimization with Enhanced Exploit...

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7th international conference on Life System modeling and simulation, LSMS 2021, and the 7th international conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021

作者： Wang, Ling Huang, Bowen Wu, Xian Yang, Ruixin Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronics Engineering and Automation Shanghai University Shanghai200444 China Department of Computer Science North Carolina State University RaleighNC United States

ISBN: (纸本)9789811672125

Human Learning Optimization (HLO) is an emerging meta-heuristic with promising potential. Although HLO can be directly applied to real-coded problems as a binary algorithm, the search efficiency may be significantly spoiled due to "the curse of dimensionality". To extend HLO, Continuous HLO (CHLO) is developed to solve real-values problems. However, the research on CHLO is still in its initial stages, and further efforts are needed to exploit the effectiveness of the CHLO. Therefore, this paper proposes a novel continuous human learning optimization with enhanced exploitation (CHLOEE), in which the social learning operator is redesigned to perform global search more efficiently so that the individual learning operator is relieved to focus on performing local search for enhancing the exploitation ability. Finally, the CHLOEE is evaluated on the benchmark problem and compared with CHLO as well as recent state-of-the-art meta-heuristics. The experimental results show that the proposed CHLOEE has better optimization performance. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Optimization

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Application of Virtual Reality Technology in the Maintenance of Steam Turbine

Application of Virtual Reality Technology in the Maintenance...

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2021 international conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2021

作者： Pan, Zijie Sun, Hairong Li, Li School of Control and Computer Engineering North China Electric Power University Baoding071000 China Hebei Engineering Research Center of Simulation Optimized Control for Power Generation North China Electric Power University Baoding071003 China

Traditional steam turbine maintenance work has many shortcomings, such as poor effectiveness, high cost, and long cycle. In order to solve this problem and improve the professional skills and maintenance efficiency of steam turbine maintenance personnel, we first collect steam turbine equipment drawings and 3D dimension data of parts, and use 3D modeling software to establish augmented reality scene model. Then combined with the virtual reality technology and image fusion technology to realize the maintenance procedure training and maintenance auxiliary guidance of the steam turbine unit. The practical application results show that this technology can realize the virtual and real operation of the model by users in augmented reality scenes, bring interactive and immersive experience to operators, and improve the work efficiency of maintenance personnel. © Published under licence by IOP Publishing Ltd.

关键词： Maintenance

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Intelligent Resource Scheduling for Edge-Integrated IoT Using Deep Learning

Intelligent Resource Scheduling for Edge-Integrated IoT Usin...

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international conference on ICT in Business Industry & Government (ICTBIG)

作者： M. Vigenesh Ashu Katyal Hemalatha S Gunveen Ahluwalia Mansi Kukreja Piyush Mathurkar Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of EEE Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Mangement-PG Management JAIN (Deemed to be University) Bangalore Karnataka E&TC Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

With the proliferation of connected devices brought about by the IoT, new obstacles have developed in the way of effective management of resources and processing of data. Autonomous cars, smart cities, healthcare, and industrial automation all rely on real-time processing and minimal latency responses. Some of the disadvantages of the conventional architecture in cloud computing are issues with the network congestion, latency, and scalability. But it is quite possible in edge computing that utilizes network bandwidth efficiently, has less latency, and includes computation in data origination. Rendering resource management at the edge challenging is due to constantly evolving IoT environments and the variability of workload and applications/devices’ demands. Drawing from deep learning approaches, this paper proposes an intelligent resource scheduling framework for IoT systems with edge integration. Thereby acting in real-time based on the existing condition of the network and the availability and needs of the connected devices, the framework adjusts the offloading and allocation of tasks. This means that when future workloads are predicted and resources properly assigned, the deep learning model adjusts task schedules. In conditions of scarce resources and a high rate of change in the environment, this method ensures the rational distribution of resources, reduces the load on the network, and significantly reduces the time required to complete work. Substantial experimental and simulation data show that the projected framework is better than the existing scheduling algorithms in terms of system outcome, power consumption, and time to task execution.

关键词： Deep learning Job shop scheduling Computational modeling Real-time systems Internet of Things Time factors Resource management Particle swarm optimization Edge computing Genetic algorithms

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