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2013 IEEE International Conference on Multimedia and Expo, ICME 2013

作者： Hsu, Chao-Yung Kang, Li-Wei Mark Liao, Hong-Yuan Institute of Information Science Academia Sinica Taipei Taiwan Graduate School of Engineering Science and Technology-Doctoral Program Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781479900152

The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications. © 2013 IEEE.

关键词： Tracking (position)

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Student engagement through mathematical applications in electrical power systems

Student engagement through mathematical applications in elec...

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113th Annual ASEE Conference and Exposition, 2006

作者： Osorno, Bruno California State University Northridge United States Department of Electrical and Computer Engineering California State University Northridge United States Electric Power Systems Graduate and Undergraduate Program

Historically, electrical engineering students have been very proficient in the application of mathematics. At California State University we have experienced, recently, a negative shift of mathematical interest and therefore a lack of progress in the understanding of basic concepts that require a strong mathematical background. This problem stems from the lack of mathematical skills and studying habits. One way to solve this problem is to engage our students into the application of mathematics with simple, yet, powerful problems. An assessment of such engagement occurs every week with a quiz that spans the material covered during the previous week and tests some of the mathematical and engineering skills. This paper attempts to show the results of such assessment and the outcome of a class in which such approach was tasted. During this semester we are testing this technique again in a different course. © American Society for engineering Education, 2006.

关键词： Students

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High Resolution of City-Level Climate Simulation by GPU with Multi-physical Phenomena 18th

High Resolution of City-Level Climate Simulation by GPU with...

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18th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2021

作者： Watanabe, Koei Kikuchi, Kohei Boku, Taisuke Sato, Takuto Kusaka, Hiroyuki Master’s Program in Computer Science Graduate School of Systems and Information Engineering University of Tsukuba Tsukubashi Japan Center for Computational Sciences University of Tsukuba Tsukubashi Tennodi Japan

ISBN: (纸本)9783030935702

In this paper, we describe the Graphics Processing Unit (GPU) implementation of our City-LES code on detailed large eddy simulations, including the multi-physical phenomena on fluid dynamics, heat absorption and reflection by surface and building materials, cloud effects, and even sunlight effect. Because a detailed simulation involving these phenomena is required for analyses at the street level and several meters of resolution, the computation amount is enormous, and ordinary CPU computation cannot provide sufficient performance. Therefore, we implemented the entire code on GPU clusters with large-scale computing. We applied OpenACC coding to incrementally implement relatively easy programming and eliminate data transfers between the CPU and GPU memories. Based on this research, we determined that the elimination of data transfers is effective, even in the case where a part of the code execution on the GPU is slower than the CPU, owing to the absence of spatial parallelism. The objective of this study is to perform a complete climate simulation on a few square-kilometers field around the Tokyo Station, considering the finest resolution of the original highlighted area of the Marathon race in the Olympic Games Tokyo 2020. We successfully transferred the entire code to the GPU to provide approximately eight times the performance of CPU-only computation on multi-GPU per node with a large scale cluster. © 2022, IFIP International Federation for Information Processing.

关键词： Graphics processing unit

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Unraveling the genetic mechanisms of UV radiation resistance in Bacillus through biofilm formation, sporulation, and carotenoid production

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Genomics 2025年

作者： Prasansah Shrestha Byeollee Kim So-Ra Han Hyun Lee Tae-Jin Oh Department of Life Science and Biochemical Engineering Graduate School SunMoon University Asan 31460 Republic of Korea Bio Big Data-based Chungnam Smart Clean Research Leader Training Program SunMoon University Asan 31460 Republic of Korea Genome-based BioIT Convergence Institute Asan 31460 Republic of Korea Division of Computer Science and Engineering SunMoon University Asan 31460 Republic of Korea Department of Pharmaceutical Engineering and Biotechnology SunMoon University Asan 31460 Republic of Korea

Bacillus species are Gram-positive bacteria that are rod-shaped, endospore-forming, and aerobic or facultatively anaerobic. With over 300 recognized species, Bacillus subtilis stands out as a well-studied model organism. The genus's various species exhibit a wide range of physiological capabilities, allowing them to thrive in diverse environmental conditions. Each cell produces a single endospore, which is highly resistant to heat, cold, radiation, desiccation, and disinfectants. Among Bacillus strains, those capable of producing spores, biofilms, and carotenoids demonstrate significant resilience to UV light. This review examines the genes involved in spore formation, biofilm development, and carotenoid synthesis, emphasizing their roles in UV radiation survival. We explore the interconnections between these processes and their combined contribution to UV resistance, focusing on the underlying genetic mechanisms. These insights will benefit researchers studying the genetic basis of UV radiation resistance in Bacillus species. Importance Bacteria employ adaptive strategies in extreme environments through rapid changes in gene expression, altering their phenotype for survival. Bacillus species, for example, defend against UV radiation by making spores, creating biofilms, and producing pigments . During sporulation, sigma factors (σ F , σ E , σ G , and σ K ) regulate gene expression to adapt to environmental shifts. It has been found that the spores of some species may contain pigments that strongly absorb UV radiation, playing a crucial role in spore UV resistance. UV light penetrates biofilm matrices minimally, mainly affecting surface cells, which produce compounds like mycosporine-like amino acids and carotenoids to shield against UV damage.

关键词： Bacillus UV-radiation resistance Spore Biofilm Carotenoid

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Model for Estimating the Probability of a Customer to Have a Transaction 7

Model for Estimating the Probability of a Customer to Have a...

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7th International Conference on computer Science and engineering, UBMK 2022

作者： Sayar, Alperen Bozkan, Tunaban Cakar, Tuna Ertugrul, Seyit Mef University Information Technology Graduate Program Istanbul Turkey Mef University Computer Engineering Department Istanbul Turkey Mef University Department of Information Technology Istanbul Turkey

ISBN: (数字)9781665470100

ISBN: (纸本)9781665470100

In this study, it is aimed to estimate the probability of a customer who comes to the institution for the first time to make a transaction in the next 3 months, using data-driven machine learning models, in order to provide financing to the seller company by assigning the receivables arising from the sale of goods and services in a company actively operating in the factoring sector. Accordingly, it was aimed to directly contribute to the transaction volume on a business basis by acting and taking action with more effective, efficient and correct approaches by finding high-potential and low-potential customers. In this context, provided by KKB (Credit Registration Bureau);The data set to he used in machine learning models was created with feature engineering and exploratory data analysis, using the Risk, Mersis, GIB information of the prospective customers and the historical information of the customers, check issuers, customer representatives and branches kept in the database. Since the leads coming to the institution are in two different types of organizations (Individual and Legal), two different forecasting models were applied. Multiple classification models were tried, and the highest F1-Score of 86% for private companies was obtained with the Random Forest model, and the highest F1- Score for commercial companies was obtained with the Random Forest model with 82%. © 2022 IEEE.

关键词： Machine learning

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Exploring Shifted Domain Problem within MNIST Dataset

Exploring Shifted Domain Problem within MNIST Dataset

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2023 International Conference on computer Science, Information Technology and engineering, ICCoSITE 2023

作者： Hidayaturrahman Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Bina Nusatara University BINUS Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350320954

Domain data can be shifted in any direction so it will be shared in different distributions to its original domain. This could be a problem since the model was trained with different distributions. It is found that adversarial domain adaptation using domain adversarial neural networks (DANN) can help to solve this problem on some scale. DANN can minimize the discrepancy between source and target data so the model can work well in both domains. The experiment is done by utilizing MNIST dataset that shifted into some conditions. In a condition when the shifting of distribution is too far, DANN is struggling to maintain the knowledge extracted from source data which leads to underperformance in the source and target domain. In contrast, when the shifting is closer, DANN can easily fit the model so it can perform well in both domains. It proves DANN is one of the good approaches to performing domain adaptation in small discrepancies. © 2023 IEEE.

关键词： Adversarial Domain Adaptation Domain Shifting Problem MNIST Transfer Learning

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Hybrid descriptor definition for content based image classification using fusion of handcrafted features to convolutional neural network features

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International Journal of Information Technology (Singapore) 2021年第4期13卷 1365-1374页

作者： Das, Rik Kumari, Khusbu De, Sourav Manjhi, P.K. Thepade, Sudeep Department of Post Graduate Program in Information Technology Xavier Institute of Social Service Ranchi Jharkhand India Department of Computer Applications Yogoda Satsanga Mahavidyalaya Ranchi Jharkhand India Department of Computer Science & Engineering Cooch Behar Government Engineering College Cooch Behar India Department of Mathematics Vinoba Bhave University Hazaribag Jharkhand India Department of Computer Engineering Pimpri Chinchwad College of Engineering Pune India

The efficacy of content-based image classification is dependent on the richness of the feature vectors extracted from the image data. Traditional feature extraction techniques highlight single low level image characteristics like shape, size, texture, color etc. for feature generation. The process often fails to extract meaningful descriptors since considering a single image characteristic will ignore other rich properties of image contents. Mass adoption of Convolutional Neural Network (CNN) has significantly improved classification performances for content-based image data. Recent literature has documented high level of precision for image classification by carrying out transfer learning with open source pre trained Convolutional Neural Network (CNN). However, the concept of transfer learning experiences major setback in case of limited training data due to overfitting of training instances during finetuning. This work has identified this challenge and has attempted to capture probability distribution of input images to a pre trained Convolution Neural Network by utilizing it as a fixed weight feature extractor. The proposed approach has addressed the overfitting problem by removing the finetuning step involved in transfer learning. Further investigation on robust descriptor definition is carried out by concatenating the pre-trained CNN features to handcrafted features. The hybrid architecture has encouraging outcomes that have outclassed the classification accuracies of state-of-the-art handcrafted techniques. © 2021, Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Augmented feature learning Feature fusion Handcrafted features Image classification Pre trained Convolutional Neural Network (CNN) Representation learning

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Simplified BFGS Method Estimate Mechanical Parameters of a Moving-Coil Loudspeaker

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Journal of the Chinese Society of Mechanical Engineers, Transactions of the Chinese Institute of Engineers, Series C/Chung-Kuo Chi Hsueh Kung Ch'eng Hsuebo Pao 2017年第4期38卷 349-358页

作者： Chi-Chang, Wang Chih-Hung, Wang Department of Mechanical and Computer-Aided Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung40724 Taiwan Electro-acoustic Graduate Program Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung40724 Taiwan

This paper develops an inverse electroacoustic theory which can obtain the mechanical domain parameters of moving-coil loudspeaker simultaneously based on variable-metric method. By measuring the information of loudspeaker displacement and current, three hardly measured mechanical domain parameters, including loudspeaker diaphragm mass Mm, nonlinear damping coefficient Rm(x) and diaphragm suspension system stiffness coefficient Km(x), can be calculated inversely through direct solution problem, adjoint equation problem and the new simple step computing procedures. The validation of numerical simulation shows that the inverse electroacoustic theory proposed in this paper is characterized by short computing time, fewer iterations and high accuracy. Based on simple electroacoustic measurement and numerical calculation, even if there is measurement error, the predicted mechanical domain parameter error is very small, meaning the method proposed in this paper can reduce the effect of measurement error on the precision of prediction. © 2017, Chinese Mechanical engineering Society. All right reserved.

关键词： Loudspeakers

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The use of android smart phones as a tool for absences

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Procedia computer Science 2019年 157卷 238-246页

作者： Benfano Soewito Fergyanto E. Gunawan Indra Permana Rusli Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480

One of the issues of current attendance system is not being able to record employees who working outside the office. This work discussed a solution designed to solve common operational project problems, especially in attendance and tasklist management activity in companies who has employee working outside of the office. Considering the number of employees who have to visit various places, conventional attendance system is no longer feasible as be the solution. Similar problem occured in tasklist management, with so many employees to manage in different places will make it difficult for Project Manager to assign task and monitor the progress. Based on the problems, solusion was then designed using SDLC Waterfall using the field research data. This research conclude that by using the proposed application, complexity can be reduced and effectiveness can be improved in performing day-to-day operational task and make sure that they can be monitored. Moreover, the number of employee who responsible to make reports of projects and attendance can be reduced about 50%.

关键词： Attendance system Android Smartphone HTML5 Mobile application

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AxRSU- : Higher-Order m-Bit Approximate Encoders for Radix- Squarer Units

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Circuits, Systems, and Signal Processing 2024年第6期43卷 1-30页

作者： da Rosa, Morgana M. A. Paim, Guilherme da Costa, Eduardo A. C. Soares, Rafael Bampi, Sergio Graduate Program on Computing Federal University of Pelotas (UFPel) Pelotas Brazil Graduate Program in Microelectronics Federal University of RGS Porto Alegre Brazil Graduate Program in Electronics and Computer Engineering Catholic University of Pelotas Pelotas Brazil

Approximate computing has emerged as a design alternative to enhance design efficiency by capitalizing on the inherent error resilience observed in numerous applications. Various error-resilient and compute-intensive applications, such as signal, image and video processing, computer vision, and supervised machine learning, necessitate dedicated hardware accelerators for mean squared error estimation during runtime. In these application domains, using efficient arithmetic operators, particularly a squarer unit, represents one of the most effective strategies for low-power design. This work introduces an approximate Radix- $$2^{m}$$ squarer unit, denoted as AxRSU- $$2^{m}$$ . The proposed squarer unit employs m-bit approximate encoders to execute operations on m-bit data concurrently. The AxRSU- $$2^{m}$$ under consideration explores encoders with m equal to 2 (AxRSU-4), 3 (AxRSU-8), and 4 (AxRSU-16). These approximate encoders exhibit low complexity and diminish the necessary partial products operating on m bits simultaneously, thereby substantially enhancing energy efficiency and reducing circuit area in the AxRSU- $$2^{m}$$ . To illustrate the trade-off between error and quality in the AxRSU- $$2^{m}$$ , we apply it to an SSD (sum squared difference) hardware accelerator designed for video processing, with a square-accumulate serving as a case study. Our findings reveal a novel Pareto front, presenting eight optimal AxRSU- $$2^{m}$$ solutions that achieve accuracy levels ranging from 3.76 to 75.53%. These solutions yield energy savings ranging from 46.20 to 95.57% and circuit area reductions ranging from 37.68 to 66.73%.

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