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Time Series Mining Approach for Noninvasive Intracranial Pressure Assessment: An Investigation of Different Regularization Techniques

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Time Series Mining Approach for Noninvasive Intracranial Pre...

computer Science and Information engineering, CSIE, WRI World Congress on FLAGGED

作者： Shaozhi Wu Peng Xu Shadnaz Asgari Marvin Bergsneider Xiao Hu Biomedical Engineering Graduate Program Henry Samueli School of Engineering and Applied Science University of California Los Angeles USA Neural Systems and Dynamics Laboratory Department of Neurosurgery the David Geffen School of Medicine University of California Los Angeles USA School of Computer Science and Engineering University of Electronic Science and Technology Chengdu China

A data mining framework has been proposed to estimate intracranial pressure (ICP) non-invasively in our previous work. In the corresponding approach, the feature vector extracted from arterial blood pressure (ABP) and flow velocity (FV) is translated to the estimated errors by the mapping function for each entry in the database. In this paper, three different mapping function solutions, linear least squares (LLS), truncated singular value decomposition (TSVD) and standard Tikhonov regularization (STR) are systemically tested to compare the possible effects of different solutions on the non-invasive ICP estimation. The conducted comparison demonstrated that the selection of mapping function solution actually influences the estimation. Among the tested three solutions for mapping function, TSVD and STR show better ICP estimation performance with smaller ICP errors than LLS.

关键词： Cranial pressure Data mining Biomedical engineering Data engineering Spatial databases computer science Feature extraction Arterial blood pressure Biomedical measurements Laboratories

A genetic algorithm for the optimization of cable routing

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systems and computers in Japan 2006年第7期37卷 61-71页

作者： Ma, Xuan Iida, Kazuhiro Xie, Mengchun Nishino, Junji Odaka, Tomohiro Ogura, Hisakazu Graduate School of Engineering University of Fukui Fukui City 910-8507 Japan Wakayama National College of Technology Gobo City 644-0023 Japan Faculty of Automation and Information Engineering Xi an University of Technology B Techno College Department of Electrical and Computer Engineering Wakayama National College of Technology Information Processing Society of Japan China Mechanical Design Society Department of Systems Engineering University of Electro-Communications Japan Society for Fuzzy Theory and Intelligent Informatics Japanese Academy of Facial Studies Japan Society of Kansei Engineering Graduate Program of Nuclear Power and Energy Safety Engineering Graduate School of Engineering Fukui University IEEE CS ACM IPSJ IEICE JSMBET Department of Human and Artificial Intelligent Systems JSAI Japan SOFT IEEE

In this paper the authors propose a structural method for a genetic algorithm (GA) for the optimization problem of cable routing in which cables have to be laid optimally. When there are no limits on the layout routes, the optimal routes for the individual cables can be found using the Dijkstra method in a finite discrete graph. However, when there are limits on the capacity in the layout routes, optimization cannot be performed using the Dijkstra method. The proposed GA is a two-level hierarchical GA that uses chromosome coding involving two levels. The routes for each cable and the combinations of cable routes are defined respectively, and layout route selection is optimized overall through genetic operations involving these levels. Block crossover and block mutation are used as genetic operations in the first level. In addition, a method to take advantage of lethal genes, which do not satisfy the constraints and are generated in the second level is used. computer simulations confirm that the two-level hierarchical GA with these genetic operations functions effectively for the optimization problem of cable routing. © 2006 Wiley Periodicals, Inc.

关键词： Electric cable laying

Enabling AI-Generated Content (AIGC) Services in Wireless Edge Networks

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arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Shen, Xuemin Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. However, due to the instability of AIGC models, e.g., the stochastic nature of diffusion models, the quality and accuracy of the generated content can vary significantly. In wireless edge networks, the transmission of incorrectly generated content may unnecessarily consume network resources. Thus, a dynamic AIGC service provider (ASP) selection scheme is required to enable users to connect to the most suited ASP, improving the users’ satisfaction and quality of generated content. In this article, we first review the AIGC techniques and their applications in wireless networks. We then present the AIGC-as-a-service (AaaS) concept and discuss the challenges in deploying AaaS at the edge networks. Yet, it is essential to have performance metrics to evaluate the accuracy of AIGC services. Thus, we introduce several image-based perceived quality evaluation metrics. Then, we propose a general and effective model to illustrate the relationship between computational resources and user-perceived quality evaluation metrics. To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for the optimal ASP selection. Simulation results show that the proposed algorithm can provide a higher quality of generated content to users and achieve fewer crashed tasks by comparing with four benchmarks, i.e., overloading-avoidance, random, round-robin policies, and the upper-bound schemes. © 2023, CC BY.

关键词： Reinforcement learning

Decanting the contribution of instruction types and loop structures in the reuse of traces

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arXiv 2017年

作者： Coppieters, Andrey M. de Oliveira, Sheila França, Felipe M.G. Pilla, Maurício L. da Costa, Amarildo T. Program of Systems and Computer Engineering Federal University of Rio de Janeiro PO Box 68511 Rio de Janeiro RJ21941-972 Brazil Graduate Program in Computer Sciences Federal University of Pelotas R. Gomes Carneiro 1 PelotasRS/96010-610 Brazil Military Institute of Engineering Praça Gen. Tibúrcio 80 Rio de Janeiro RJ22290-270 Brazil

Reuse has been proposed as a microarchitecture-level mechanism to reduce the amount of executed instructions, collapsing dependencies and freeing resources for other instructions. Previous works have used reuse domains such as memory accesses, integer or not floating point, based on the reusability rate. However, these works have not studied the specific contribution of reusing different subsets of instructions for performance. In this work, we analysed the sensitivity of trace reuse to instruction subsets, comparing their efficiency to their complementary subsets. We also studied the amount of reuse that can be extracted from loops. Our experiments show that disabling trace reuse outside loops does not harm performance but reduces in 12% the number of accesses to the reuse table. Our experiments with reuse subsets show that most of the speedup can be retained even when not reusing all types of instructions previously found in the reuse domain. Copyright © 2017, The Authors. All rights reserved.

关键词： Reusability

Dynamic programming Algorithm using Furniture Industry 0/1 Knapsack Problem

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Dynamic Programming Algorithm using Furniture Industry 0/1 K...

International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Mietha Anditta Natashya Amartya Laurens Spits Warnars Harco Leslie Hendric Spits Warnars Arief Ramadhan Teddy Siswanto Teddy Mantoro Nurulhuda Noordin Computer Science Departement School of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Departement School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Departement BINUS Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia PJJ Informatika Telkom University Bandung Indonesia Information Systems Department Trisakti University Jakarta Indonesia Faculty of Engineering and Technology Sampoerna University Jakarta Indonesia School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Malaysia

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset.

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Web based testing application security system using semantic comparison method 2

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Web based testing application security system using semantic...

2nd Nommensen International Conference on Technology and engineering, NICTE 2018

作者： Iskandar, Akbar Fahlepi Tuasamu, Muhammad Resa Syamsu, Suryadi Mansyur, M. Listyorini, Tri Sallu, Sulfikar Supriyono, S. Saddhono, Kundharu Napitupulu, Darmawan Rahim, Robbi Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Negeri Makassar Makassar Indonesia Informatics Engineering Universitas Maria Kudus Central Java Indonesia Computer Information Systems Universitas Sembilan Belas November Kolaka Indonesia Department of Geography Education Universitas Prof Dr Hazairin SH Bengkulu Indonesia Indonesian Language Education Departement Faculty of Teacher Training and Education Universitas Sebelas Maret Surakarta Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Indonesia Sekolah Tinggi Ilmu Manajemen Sukma Medan Indonesia

computer and web security system is an attempt to avoid attacks from crackers because a form and method of crime on internet network can not be predicted. Therefore, we just keep trying to use various methods in securing the system that is running. It is the same in web testing that can be accessed online by people who are not responsible from along distance to change and remove the test results or even damage the web testing system. So, the purpose of this paper is to design and implement web security testing system by using semantic comparison method to avoid structured query language injection (SQLI) attack and to do security on web testing application using Message Digest 5 encryption (MD5). Research data were obtained by using direct observation and documentation and literature review. After the design and application of the system, it can be obtained that by using semantic comparison method in web testing can prevent the occurrence of SQL injection attacks and can secure account from web testing users by using MD5. © Published under licence by IOP Publishing Ltd.

关键词： Semantics

Near-Optimal Pilot Assignment in Cell-Free Massive MIMO

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arXiv 2023年

作者： Guedes, Raphael M. de Rezende, José F. Barbosa, Valmir C. Informatics and Computer Science Department State University of Rio de Janeiro RJ Rio de Janeiro20550-900 Brazil Systems Engineering and Computer Science Program Federal University of Rio de Janeiro RJ Rio de Janeiro21941-914 Brazil Graduate Program in Computational Sciences State University of Rio de Janeiro RJ Rio de Janeiro20550-900 Brazil

Cell-free massive MIMO systems are currently being considered as potential enablers of future (6G) technologies for wireless communications. By combining distributed processing and massive MIMO, they are expected to deliver improved user coverage and efficiency. A possible source of performance degradation in such systems is pilot contamination, which contributes to causing interference during uplink training and affects channel estimation negatively. Contamination occurs when the same pilot sequence is assigned to more than one user. This is in general inevitable, as the number of mutually orthogonal pilot sequences corresponds to only a fraction of the coherence interval. We introduce a new algorithm for pilot assignment and analyze its performance both from a theoretical perspective and in computational experiments. We show that it has an approximation ratio close to 1 for a plausibly large number of orthogonal pilot sequences, as well as low computational complexity under massive parallelism. We also show that, on average, it outperforms other methods in terms of per-user SINR and throughput on the uplink. Copyright © 2023, The Authors. All rights reserved.

关键词： Channel estimation

Exploring Collaborative Distributed Diffusion-Based AI-Generated Content (AIGC) in Wireless Networks

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arXiv 2023年

作者： Du, Hongyang Zhang, Ruichen Niyato, Dusit Kang, Jiawen Xiong, Zehui Kim, Dong In Shen, Xuemin Poor, H. Vincent The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Driven by advances in generative artificial intelligence (AI) techniques and algorithms, the widespread adoption of AI-generated content (AIGC) has emerged, allowing for the generation of diverse and high-quality content. Especially, the diffusion model-based AIGC technique has been widely used to generate content in a variety of modalities. However, the real-world implementation of AIGC models, particularly on resource-constrained devices such as mobile phones, introduces significant challenges related to energy consumption and privacy concerns. To further promote the realization of ubiquitous AIGC services, we propose a novel collaborative distributed diffusion-based AIGC framework. By capitalizing on collaboration among devices in wireless networks, the proposed framework facilitates the efficient execution of AIGC tasks, optimizing edge computation resource utilization. Furthermore, we examine the practical implementation of the denoising steps on mobile phones, the impact of the proposed approach on the wireless network-aided AIGC landscape, and the future opportunities associated with its real-world integration. The contributions of this paper not only offer a promising solution to the existing limitations of AIGC services but also pave the way for future research in device collaboration, resource optimization, and the seamless delivery of AIGC services across various devices. Our code is available at https://***/HongyangDu/DistributedDiffusion. © 2023, CC BY.

关键词： Wireless networks

DDG-51 CLASS computer-AIDED-DESIGN

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NAVAL ENGINEERS JOURNAL 1994年第4期106卷 165-173页

作者： OUILLETTE, JJ THE AUTHOR is the DDG-51 class computer-aided design project manager in the Navy's Aegis program office. Ms. Ouillette is 1986 graduate of the University of Maine with a B.S. in mechanical engineering. Prior to her current position Ms. Ouillette was employed by the Supervisor of Shipbuilding Conversion and Repair Bath Me. where she was involved with engineering systems management for the DDG-51 class program.

computer-Aided Design and computer-Aided Manufacturing technology is being implemented in the U.S. Navy's Arleigh Burke (DDG-51) Class Aegis Destroyer program. Under the Navy's direction, the DDG-51 class construction yards are aggressively pursuing the transition to CAD-based design, construction and life cycle support. Through the CAD initiative, acquisition costs can be reduced without reduction of ships' capability. Building a three dimensional (3D) computer generated model of the ship prior to construction will facilitate the identification and resolution of interference and interface problems that would otherwise remain undetected until actual ship construction. The 3D database contains geometry and design data to support system design and concurrent engineering and is exchanged electronically between the construction yards. Detailed design drawings, fabrication sketches, and numerical control (NC) data are extracted directly from the database to support construction. At the completion of ship construction, as-built models will be provided to the planning yard for life cycle support.

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