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IEEE Silicon Nanoelectronics Workshop (SNW)

作者： Xin-Ren Yu Wen-Hsiang Lu Shu-Wei Chang Wen-Hsin Chang Darsen D. Lu Yao-Jen Lee Tatsuro Maeda Wen-Fa Wu Yi-Ming Li Yeong-Her Wang Inst. of Microelectronics Natl. Cheng Kung University Tainan Taiwan Dept. of Electrical Engineering Natl. Cheng Kung University Tainan Taiwan National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Japan Inst. of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung University Hsinchu Taiwan Taiwan Semiconductor Research Inst. (TSRI) Hsinchu Taiwan College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

The CFETs can provide high-performance characteristics with significant area reduction for Å technology nodes. However, mobilities between n/p FETs need to be considered for the performance balance of CMOS. This ... 详细信息

ISBN: (数字)9798350391633

ISBN: (纸本)9798350391640

关键词： Wafer bonding Conferences Field effect transistors Silicon Nanoelectronics

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Emotion Detection of Contextual Text using Deep learning 4

Emotion Detection of Contextual Text using Deep learning

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4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020

作者： Rashid, Umar Iqbal, Muhammad Waseem Skiandar, Muhammad Akmal Raiz, Muhammad Qasim Naqvi, Muhammad Raza Shahzad, Syed Khuram COMSATS University Islamabad Vehari Campus Vehari Pakistan The Superior College Dept of Software Engineering Lahore Pakistan The Superior College Dept of Information Technology Lahore Pakistan The Superior College Dept of Computer Sciecne Lahore Pakistan University Of Management Technology Dept of Informatics and Systems Lahore Pakistan

ISBN: (数字)9781728190907

ISBN: (纸本)9781728190907

In recent years, the data in the form of text is created in very huge amount in day to day conversation on social media. We need a naive approach to analyzed and summarized data to extract meaningful information. Textual dialogue is given in contextual emotion detection. We have to recognize user emotions either it is happy, sad, angry or others. This paper describes Aimens system which detect emotions from textual dialogues. This system used the Long short term memory (LSTM) model based on deep learning to detect the emotions like happy, sad and angry in contextual conversation. The main input to the system is a combination of word2vec and doc2vec embeddings. The output results are shown substantial changes in f-scores over the model baseline where Aimens system score is 0.7185. © 2020 IEEE.

关键词： Contextual Conversation Emotion Detection Happy LSTM Machine Learning

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Generative Adversarial Networks Based Cognitive Feedback Analytics System for Integrated Cyber-Physical System and Industrial Iot Networks

Research Square

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Research Square 2021年

作者： Upreti, Kamal Syed, Mohammad Haider Alam, Mohammad Shabbir Alhudhaif, Adi Shuaib, Mohammed Sharma, Arvind K. Department of Information & Technology Inderprastha Engineering College Ghaziabad India College of Computing and Informatics Saudi Electronic University Saudi Arabia Department of Computer Science College of computer science and Information Technology Jazan University Saudi Arabia Department of Computer Science College of Computer Engineering and Sciences in Al-kharj Prince Sattam bin Abdulaziz University P.O. Box 151 al-Kharj11942 Saudi Arabia College of Computer Science & IT Jazan University Saudi Arabia Dept. of CSI University of Kota Rajasthan India

In the modern era of technologies, the internet grows in the advancement of our day-to-day life like automation devices. The devices to set up industries with integrated cyber-physical systems and industrial IoT applications. Generative adversarial networks (GAN) can generate Cognitive feedback analysis with various data for both generator and discriminator in a supervised model. Neural networks are used for artificial intelligence algorithms, but in adversarial networks, feedback analytics is analyzed with the significance of data. The modern age of intelligent manufacturing will indeed be ushered in by Cyber-Physical Production Systems (CPPS). However, because of the connections between the virtual and physical worlds, CPPS would be subject to cross-domain assaults. Against Denial-of-Service (DoS) threats, this paper concentrates on complex performance feedback management of Cyber-Physical Systems (CPS). To begin, a swapping system modelling approach for the complex response feedback CPS is provided by analyzing the distinct effects of DoS assaults on the sensor-controller (SC) and controller-to-actuator (C-A) channels, accordingly. Given the difference in bandwidth between the dual channels and the accused's energy cap, it is reasonable to conclude that an offender can only jam a single communication stream at a point and also that the possible number of successive DoS attacks is limited. Second, using a packet-based transfer scheme, a nested switching paradigm is built on the foundation of the switching mechanism, considering both the spatial heterogeneity and the temporal durability of DoS attacks. The probability of discriminator gets analyzed feedback data to check whether actual data or fake data is sampled, and it is generated. Cognitive feedback supports genetic algorithms to sample the feedback data in a system for advanced technologies. © 2021, CC BY.

关键词： Cyber Physical System

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A Study of Multilayer Omega Networks Operating with Cut-Through Mechanism under Uniform Traffic

A Study of Multilayer Omega Networks Operating with Cut-Thro...

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South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

作者： Eleftherios Stergiou John Garofalakis Dimitrios Liarokapis Spiridoula V. Margariti Dept. Informatics & Telecommunications University of Ioannina Arta Greece Dept. of Computer Engineering and Informatics University of Patras and Computer Technology Institute and Press—“DIOPHANTUS” (CTI)) Patras Greece

ISBN: (数字)9781728164458

ISBN: (纸本)9781728164465

There is an enduring interest in developing more efficient multistage interconnection networks (MINs), as they are a key aspect of various switching sectors and the demands for higher data transfer rates. Here, semi-layer Omega type networks operating under the cut-through forwarding policy are selected as a test-bed subject for performance evaluation. This special shuffle-exchange network was modelled, analysed, and simulated. Moreover, this type of fabric is compared with corresponding single-layer Omega networks operating via cut-through or a `store and forward' forwarding technique. The results show, in a quantitative manner, how superior is the under study fabric compared to the corresponding single-layer constructions, in terms of network size, showing the advantages that are provided by both usages: fan-out and cut-through mechanisms. Moreover, the roles of the switch element's size and the reliability metric were investigated. The findings that are derived can be valuable assets for MIN designers, in order to achieve more efficient delivering networks with low overall deployment costs.

关键词： Omega network banyan networks performance evaluation cut-through semi-layer multistage interconnection networks uniform traffic multistage interconnection networks cut-through Performance Evaluation Materials

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Machine learning approach to enhance performance of suspicious activity detection system

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AIP Conference Proceedings 2023年第1期2587卷

作者： Shahanawaj Ahamad B. Bhaskara Rao K. Srikanth V. P. Hara Gopal Pritika Mehra Malik Bader Alazzam College of Computer Science and Engineering University of Hail Hail City Saudi Arabia Dept. of Computer Science and Engineering RGM College of Engineering and Technology Nandyal Kurnool Andhra Pradesh India Dept. of Computer Science and Engineering G Pulla Reddy Engineering College Kurnool Andhra Pradesh India Research Scholar Dept. of Computer Science Guru Nanak Dev University Amritsar Punjab India Faculty of Computer Science and Informatics Amman Arab University Amman Jordan

Deep learning algorithms are a subset of the machine learning algorithms, which aim at finding several layers of distributed representations. Recently, many deep learning methods have been suggested to tackle conventional artificial intelligence issues. Machine learning is an important component of artificial intelligence, which is used to build algorithms based on the data trends and historical connections between data. Machine learning is utilized in many areas such as bioinformatics, intrusion detection, Information retrieval, game playing, marketing, virus detection, picture de-convolution and so on. Image processing and deep learning methods are linked to machine learning system to identify the fire, unauthentic vehicle and person in this study. More over gadgets such as AC, LED and other electronic equipment have been controlled in suggested system. The suggested model is offering scalable machine learning based solution to control electrical equipment remotely gives protection against fire and un authentic person. The purpose of deep learning is to build intelligent trained network that should be competent to track fire and unauthentic items in organization. The aim of study is to consider research connected to machine learning, deep learning and image processing and analyzing the limits of earlier works. Proposed work includes linked machine learning model to collect the signal and forecast and detect on the basis of trained neural network. The presentation of prediction on web page linked to web interface has been created. Simulation guarantees the improvement of performance of model using user specified trained neural network and conducts the comparative analysis of performance. Capturing is made frame by frame in form of picture and captured information are preprocessed to minimize size of graphics then the pattern in frame is identified using deep learning method. Here pre-trained set is utilized to track recurrence of specific event. The combination of

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Combining Photometric Features and Relative Position to Detect and Track Target Person 2

Combining Photometric Features and Relative Position to Dete...

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2nd International Conference on computer engineering, Network, and Intelligent Multimedia, CENIM 2019

作者： Dewantara, Bima Sena Bayu Miura, Jun Politeknik Elektronika Negeri Surabaya Dept. of Informatics and Computer Engineering Surabaya Indonesia Toyohashi University of Technology Dept. of Computer Science and Engineering Toyohashi Japan

ISBN: (纸本)9781728129655

Tracking a target person is a vital job in human-robot interaction. The robot must always notice a particular person as the interaction target partner. However, it is sometimes very hard to distinguish the target person because there are many other persons around the target. In this paper, we propose a target person detection and tracking system by combining person's frontal photometric features such as face and clothing color, and coordinate of the person's location in the real world. We apply an illumination invariant face recognition method named OptiFuzz. Hue-Saturation histogram (HS-histogram) is used to obtain the clothing color feature, and a location of the person is acquired from a calibrated single camera view. All these features are then fed into an algorithm of Naive Bayes to discriminate between the target person and others. Our experimental results indicate a successful outcome as it is always possible to detect and track the target person. © 2019 IEEE.

关键词： Human robot interaction

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Topological modes observed in Si photonics SSH integrated circuit

Topological modes observed in Si photonics SSH integrated ci...

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2022 Conference on Lasers and Electro-Optics Pacific Rim, CLEO/PR 2022

作者： Nakamura, R. Nakama, T. Balčytis, A. Ozawa, T. Ota, Y. Iwamoto, S. Ito, H. Baba, T. Dept of Electrical & Computer Eng. Yokohama National Univ. 79-5 Tokiwadai Hodogaya-ku Yokohama240-8501 Japan School of Engineering RMIT University MelbourneVIC3000 Australia Advanced Institute for Materials Research Tohoku Univ. Sendai980-8577 Japan Dept. of Applied Physics and Physico-Informatics Keio Univ. 3-14-1 Hiyoshi Kohoku-ku Yokohama223-8522 Japan Research Center for Advanced Science and Technology The University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo153-8904 Japan

We fabricated a sophisticated Si photonic integrated circuit for investigating topological photonics SSH model. In the selective excitation and observation of SSH coupled microrings, we observed the wavefunctions of e... 详细信息

关键词： Timing circuits

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Quality Grading of Beef using Deep Convolutional Neural Network

Quality Grading of Beef using Deep Convolutional Neural Netw...

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HCT Information technology Trends (ITT)

作者： Aarav Sharma Tanupriya Choudhury Tanmay Sarkar Madhusmita Mohanty Nikunj Bansal Sachi Nandan Mohanty Informatics Cluster School of Computer Science University of Petroleum and Energy Studies (UPES) Dehradun Uttarakhand India CSE Dept. University of Petroleum and Energy Studies (UPES) CSE Dept. Graphic Era Hill University Dehradun Uttarakhand India Department of Food Processing Technology West Bengal State Council of Technical Education Govt. of West Bengal Malda Polytechnic Malda India VIT-AP School of Business (VSB) VIT-AP University Amaravati Andhra Pradesh India School of Computer Science & Engineering VIT-AP University Amaravati Andhra Pradesh India

Beef is one of the most widely consumed meat, being an organic substance it is prone to degradation over time. In our paper we have proposed a Convolutional Neural Network model to grade a given sample of Beef and predict its freshness as good or bad. We have proposed a CNN model architecture along with a data (image) pre-processing pipeline that can be used to classify a given Beef sample. We have done comparative analysis between different pre-processing pipelines as well as other CNN based classification models and after training have achieved 99.63% test accuracy.

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Techno-economic analysis of cognitive radio models in 5G networks

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Procedia computer Science 2020年 175卷 300-307页

作者： Christos Bouras Anastasia Kollia Andreas Papazois Computer Technology Institute & Press ”Diophantus” Patras P.C. 26504 Greece Computer Engineering & Informatics Dept. University of Patras Patras P.C. 26504 Greece

The first commercial products of 5G will be released within 2020 and therefore, it becomes an absolute necessity to research whether the key enabling technologies are advantageous for the operators to invest in. One of the most fundamental technologies Cognitive Radio (CR), since there is not much research in the field. This paper develops a techno-economic framework for the CR technology and is contrasted with an already existing model for Software Defined Networks (SDN). A Sensitivity Analysis (SA) indicates the cost parameters that are the most expensive ones and should be reconsidered for the model’s wide adoption and viability.

关键词： 5G cost models mobile networks SDN cognitive radio

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Topological modes observed in Si photonics SSH integrated circuit

Topological modes observed in Si photonics SSH integrated ci...

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2022 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2022

作者： Nakamura, R. Nakama, T. Balčytis, A. Ozawa, T. Ota, Y. Iwamoto, S. Ito, H. Baba, T. Dept of Electrical &Computer Eng. Yokohama National Univ. 79-5 Tokiwadai Hodogaya-ku Yokohama240-8501 Japan School of Engineering RMIT University MelbourneVIC3000 Australia Advanced Institute for Materials Research Tohoku Univ. Sendai980-8577 Japan Dept. of Applied Physics and Physico-Informatics Keio Univ. 3-14-1 Hiyoshi Kohoku-ku Yokohama223-8522 Japan Research Center for Advanced Science and Technology The University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo153-8904 Japan

ISBN: (纸本)9798350350012

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