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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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Cost optimization in CNN for big data of share price

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AIP Conference Proceedings 2023年第1期2587卷

作者： R. Saravanakumar Gokul Talele Ali Hazim Alyamoor Kaushal Kishor Bhatt Prashant Vats Malik Bader Alazzam Dept. of Computer Science and Engineering Dayananda Sagar Academy of Technology and Management Bangalore India Dept. of Data Science IIIT Banglore India Dept. of Accounting Economic and Administration College University of Mosul Ninawa Iraq Dept. of Computer Science and Engineering Birla Institute of Applied Science Bhimtal Nainital Uttarakhand India Dept. of Computer Science and Engineering Dr. Akhilesh Das Gupta Institute of Technology and Management New Delhi India Faculty of Computer Science and Informatics Amman Arab University Mubis-Amman Jordan

Optimization of share price in order to evaluate whether to invest in specific share or not is subject of study paper. Optimized value has been utilized to enhance the performance and accuracy when dataset is trained using CNN. Review has been given on big cap, mid cap & small cap fund which are accessible in large, medium and small amount for the purpose of investing. It has been found that share in big cap are more dependable but offers limited return. However share in case of mid cap are considered comparatively more hazardous than big cap yet return may be substantial. The suggested study has given mechanism that will make use of optimization mechanism to filter the data set considering PSO and MVO mechanism. The suggested CNN based training model is claimed high performance system with improved accuracy.

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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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Integration Design and Process of 3-D Heterogeneous 6T SRAM with Double Layer Transferred Ge/2Si CFET and IGZO Pass Gates for 42% Reduced Cell Size

Integration Design and Process of 3-D Heterogeneous 6T SRAM ...

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International Electron Devices Meeting (IEDM)

作者： X.-R. Yu M.-H. Chuang S.-W. Chang W.-H. Chang T.-C. Hong C.-H. Chiang W.-H. Lu C.-Y. Yang W.-J. Chen J.-H. Lin P.-H. Wu T.-C. Sun S. Kola Y.-S. Yang Yun Da P.-J. Sung C.-T. Wu T.-C. Cho G.-L. Luo K.-H. Kao M.-H. Chiang W. C.-Y. Ma C.-J. Su T.-S. Chao T. Maeda S. Samukawa Y. Li Y.-J. Lee W.-F. Wu J.-H. Tarng Y.-H. Wang Dept. of Electrical Engineering National Cheng Kung University Tainan Taiwan College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Taiwan Semiconductor Research Institute (TSRI) Hsinchu Taiwan National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Japan Dept. of Electrophysics National Yang Ming Chiao Tung University Hsinchu Taiwan Dept. of Electrical Engineering Natl. Sun Yat-Sen University Kaohsiung Taiwan Inst. of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung University Hsinchu Taiwan Dept. of Electrical Engineering National University of Kaohsiung Kaohsiung

ISBN: (纸本)9781665489607

In this work, we propose an advanced 3-D heterogeneous 6T SRAM with a newly designed hetero-integration method. CFET inverters and IGZO pass gates are vertically stacked within a 2T footprint area. The Low-Temperature Hetero-Layers Bonding Technique (LT-HBT) process is utilized successfully to fabricate single crystalline heterogeneous Double Layer Transferred (DLT) Ge/2Si CFET-OI on an 8-inch full wafer. Furthermore, an IGZO nFET is deposited and treated as a pass gate (PG) to realize a 6T SRAM operation. The hetero-integration of IGZO PG and self-align DLT Ge/2Si CFET inverters showed improved Read Static Noise Margin (RSNM) and stand-by leakage power. The state-of-the-art 3-D heterogeneous 6T SRAM leads to 42% area reduction.

关键词： Wafer bonding Surface cleaning Three-dimensional displays Microprocessors Stacking Random access memory computer architecture

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Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms

arXiv

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arXiv 2021年

作者： Suman, Sudhir Singh, Gagandeep Sakla, Nicole Gattu, Rishabh Green, Jeremy Phatak, Tej Samaras, Dimitris Prasanna, Prateek Dept. of Electrical Engineering Indian Institute of Technology Bombay India Dept. of Radiology Newark Beth Israel Medical Center NJ United States Dept. of Computer Science Stony Brook University NY United States Dept. of Biomedical Informatics Stony Brook University NY United States

With more than 60,000 deaths annually in the United States, Pulmonary Embolism (PE) is among the most fatal cardiovascular diseases. It is caused by an artery blockage in the lung;confirming its presence is time-consuming and is prone to over-diagnosis. The utilization of automated PE detection systems is critical for diagnostic accuracy and efficiency. In this study we propose a two-stage attention-based CNN-LSTM network for predicting PE, its associated type (chronic, acute) and corresponding location (leftsided, rightsided or central) on computed tomography (CT) examinations. We trained our model on the largest available public Computed Tomography Pulmonary Angiogram PE dataset (RSNA-STR Pulmonary Embolism CT (RSPECT) Dataset, N=7279 CT studies) and tested it on an in-house curated dataset of N=106 studies. Our framework mirrors the radiologic diagnostic process via a multi-slice approach so that the accuracy and pathologic sequela of true pulmonary emboli may be meticulously assessed, enabling physicians to better appraise the morbidity of a PE when present. Our proposed method outperformed a baseline CNN classifier and a single-stage CNN-LSTM network, achieving an AUC of 0.95 on the test set for detecting the presence of PE in the study. Copyright © 2021, The Authors. All rights reserved.

关键词： computerized tomography

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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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Pigmented skin lesions classification using convolutional neural networks

Pigmented skin lesions classification using convolutional ne...

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2019 International Conference on Biomedical Innovations and Applications, BIA 2019

作者： Naronglerdrit, Prasitthichai Mporas, Iosif Perikos, Isidoros Paraskevas, Michael Kasetsart University Sriracha Campus Dept. of Computer Engineering Chonburi Thailand University of Hertfordshire Dept. of Engineering Hatfield United Kingdom University of Patras Computer Engineering and Informatics Dept. Patras Greece Computer Technology Institute and Press 'Diophantus Patras Greece University of Peloponnesse Dept. of Electrical and Computer Engineering Patras Greece

ISBN: (纸本)9781728147543

In this paper we present an architecture for classification of pigmented skin lesions from dermatoscopic images. The architecture is using image pre-processing for natural hair removal and image segmentation for extraction of the skin lesion area. The segmented images were processed by a convolutional neural network classifier. The training process was done by using the Keras and TensorFlow python packets with CUDA supported. The best performance was achieved by a convolutional neural network architecture with three convolution layers and the classification accuracy was equal to 76.83%. © 2019 IEEE.

关键词： Image classification

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Security enhancement of big data in cloud application using block-chain

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AIP Conference Proceedings 2023年第1期2587卷

作者： Avein Jabar Al-Asadi J. V. S. Arundathi Omdev Dahiya Abdul Wahab Hashmi Ankur Gupta Malik Bader Alazzam Dept. of Information Technology Technical College of Informatics TCI Sulaimani Polytechnic University Sulaymaniyah Iraq Dept. of Computer Science SR & BGNR Government Arts and Science Degree & PG College (Autonomous) Khammam Telangana India School of Computer Science and Engineering Lovely Professional University Phagwara Punjab India Advanced Manufacturing and Mechatronics Lab Mechanical Engineering Department Malaviya National Institute of Technology Jaipur India Dept. of Computer Science and Engineering Vaish College of Engineering Rohtak Haryana India Faculty of Computer Science and Informatics Amman Arab University Amman Jordan

Organizations are inundated on a daily basis with vast, difficult-to-manage volumes of structured and unstructured data, which is known as “big data.” Analysis of large amounts of data may provide useful information that can be used to improve decision-making and boost employee morale. This kind of data storage makes it almost hard to change, hack, or otherwise deceive. Every computer in a block-chain network has a copy of the block-transaction chain’s log, which is called a “block-chain.” In previous researches it has been observed that security of big data is a major issue. Block chain has been found suitable mechanism to deal with such issues. Block-chain has also been considered a service in the context of cloud computing, termed Block-chain as a Service (BaaS). By using virtual storage nodes, block-chain technology may create whole new cloud storage services that are very resistant to data tampering. The proposed research has focused on the enhancement of security of big data from SQL injection attack that is transferred over cloud application. Research is making use of block chain technology in order to resolve the issue of security. The major objective of research is to propose block chain based security model for big data that should be more secure and efficient in case of SQL injection attack. Research work has proposed modified algorithm enhances the security of big data in cloud application against.SQL injection, cross script.

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Clustering big data for novel health care system

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AIP Conference Proceedings 2023年第1期2587卷

作者： R. Saravanakumar S. P. Maniraj Anindita Das Barshan Santanu Das Hasibul Hasan Malik Bader Alazzam Dept. of Computer Science and Engineering Dayananda Sagar Academy of Technology and Management Bangalore India Dept. of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Campus Tamilnadu Chennai India Dept. of Medicine Dhaka Medical College Hospital Dhaka Bangladesh Dept. of Biotechnology Seshadripuram First Grade College Yelahanka New Town Bangalore India Dept. of Applied Nutrition and Food Technology Islamic University Bangladesh Faculty of Computer Science and Informatics Amman Arab University Jordan

In research, the relevance of data science in health care is being explored. It has been proposed that the health-care sector benefit from a Nutrition Prescription System. In the proposed model, the Map Reduce, Enhanced K-Mean clustering technique was used. Actual datasets are represented by rectangular rectangles, which contain the health care centre dataset and frequency dataset generated by the map reduction method. Operations in original data flow are represented by the elliptical boxes. Patients will be able to use this technique to access specific and specialized health care inst.tution. As a consequence, consumers will get better services that are tailored to their specific requirements. Patients would have secure access to planned system because of backup facilities. Because diagnosis has no side effects, the concept of nutrition prescription system is better than that of medicine prescription system. In suggested dietary prescription system, patient selects symptoms. The patient is provided information on his nutritional deficits, requirements and food supply. In addition, the patient is provided additional nutritional data stored in an unstructured dataset. The outcome was derived from the data set. In milliseconds, the report also shows the time spent on traditional and contemporary duties.

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License plate detection and recognition: A study of review

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AIP Conference Proceedings 2023年第1期2834卷

作者： Naaman Omar Subhi R. M. Zeebaree Mohammed A. M. Sadeeq Rizgar R. Zebari Hanan M. Shukur Ahmed Alkhayyat Lailan M. Haji Shakir Fattah Kak Technical College of Administration Information Technology Management Dept. Duhok Polytechnic University Duhok-Iraq Technical College of Engineering Energy Dept. Duhok Polytechnic University Duhok-Iraq Computer Science Department Nawroz University Duhok –Iraq Computer Engineering Dept. Al-Kitab University Kirkuk-Iraq Technical Engineering Dept. Islamic University Najaf Najaf-Iraq Computer Science Dept. University Of Zakho Duhok-Iraq Technical College of Informatics Information Technology Dept. Duhok Polytechnic University Duhok-Iraq

The detection and recognition of automatic license plates (ALPs) is an important task for traffic surveillance and parking management systems, as well as for sustaining the flow of modern civic life. It’s been suggested that there are a variety of ways to detect and recognize ALPs thus far Image processing and machine learning techniques are typically used in these approaches. For object detection and license plate identification, this article reviews most of the approaches. In order to improve the suitability of the input pictures for subsequent processing, many pre-processing approaches including Gaussian filtering and adaptive image contrast augmentation were examined. Deep semantic segmentation networks and deep learning techniques are also utilized to find the license plate areas in the input picture… For example, deep encoder-decoder network architecture and convolutional neural network (CNN) models used to recognize license plate.

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