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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Jou-Ken Hsiao Li-Wei Kang Ching-Long Chang Chao-Yung Hsu Chia-Yen Chen Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan Graduate School of Engineering Science and Technology-Doctoral Program National Yunlin University of Science and Technology Yunlin Taiwan Institute of Information Science Taipei Taiwan Department of Computer Science and Information Engineering National University of Kaohsiung Taiwan

Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, a novel leaf image recognition technique via sparse representation is proposed for automatic plant identification. In order to model leaf images, we learn an overcomplete dictionary for sparsely representing the training images of each leaf species. Each dictionary is learned using a set of descriptors extracted from the training images in such a way that each descriptor is represented by linear combination of a small number of dictionary atoms. For each test leaf image, we calculate the correlation between the image and each learned dictionary of leaf species to achieve the identification of the leaf image. As a result, efficient leaf recognition can be achieved on public leaf dataset based on the proposed framework leading to a more compact and richer representation of leaf images compared to traditional clustering approaches. Moreover, our method is also adapted to newly added leaf species without retraining classifiers and suitable to be highly parallelized as well as integrated with any leaf image descriptors/features.

关键词： Image recognition Dictionaries Training Feature extraction Shape Educational institutions Computer vision

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Perceptron Partition Model to Minimize Input Matrix

Perceptron Partition Model to Minimize Input Matrix

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International Conference on Science and Innovated Engineering 2018, i-COSINE 2018

作者： Azmi, Zulfian Nasution, Mahyuddin K.M. Zarlis, Muhammad. Mawengkang, Herman Efendi, Syahril Postgraduate Doctoral of Computer Science Universitas Sumatera Utara Padang Bulan USU Medan20155 Indonesia Information Technology Department Universitas Sumatera Utara Padang Bulan USU Medan20155 Indonesia Program Pasca Sarjana Doktoral Ilmu Komputer Universitas Sumatera Utara Indonesia Department of Mathematics Universitas Sumatera Utara Padang BulanUSU Medan20155 Indonesia

Implementation of Neuron Network model using Perceptron has not given optimal result in real time learning. The large number of inputs expressed in matrix form makes the process slower in pattern recognition. So, it takes characteristic to represent all the input matrices by using the partition method. By partitioning each input and with the best weight and using the activation function will produce an output value. And learning is valid in recognizing patterns only 1 iteration only. Further validation is done on the water mill control module with dissolved oxygen input, water pH, salinity and water temperature. With Perceptron Partition learning algorithm more real-time than perceptron model. Testing on the waterwheel input whether rotating or stopping by Matrix Laboratory software simulation. © Published under licence by IOP Publishing Ltd.

关键词： Neural networks

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Understanding Future Trends in Digital Banking Research Through Bibliometric Analysis

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Procedia Computer Science 2024年 234卷 764-771页

作者： Jimmy Carter Sudianjaya Heri Kuswanto Reny Nadlifatin Doctoral Program in Management of Technology School of Interdisciplinary Management and Technology Institut Teknologi Sepuluh Nopember Surabaya 6011 Indonesia Department of Statistics Institut Teknologi Sepuluh Nopember Surabaya 60111 Indonesia Department of Information System Institut Teknologi Sepuluh Nopember Surabaya 60111 Indonesia

To generate a research overview of digital banking, we did a bibliometric analysis. In our bibliometric analysis, we identified 2475 papers about digital banking that were published in the previous 10 years (2013–2023) from 1492 different sources under the direction of 6777 academics. The bibliographic information was gathered using the Scopus database. The dataset was examined using the bibliometric R program Biblioshiny. The number of digital banking research publications published each year, the most relevant author, the most cited articles, thematic maps, and trending topics are all listed. A keyword analysis showed that “blockchain”, “security”, “digital banking”, and “digital storage” appeared most often. The research results will be significant to scholars, researchers, and policymakers in banking, as the study showed the roadmap and pathways to scientifically understanding current and future research trends.

关键词： digital banking bibliometric biblioshiny

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An Analysis Air Traffic Prediction During a Pandemic

An Analysis Air Traffic Prediction During a Pandemic

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Darmeli Nasution Herman Mawengkang Fahmi Muhammad Zarlis Departmen Of Computer Science and Information Technology Doctoral Program Universitas Sumatera Utara Medan Indonesia Departmen Of Math and Science Universitas Sumatera Utara Medan Indonesia Departmen Of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Departmen Of Computer Science and Information Technology Universitas Bina Nusantara Jakarta Indonesia

ISBN: (纸本)9781665453967

Air transportation during the covid-19 pandemic experienced a very drastic decline. The decrease in the number of passengers was caused by national and international restrictions. The troublesome administration makes passengers discouraged from traveling using Air transportation. Based on the National Statistics Agency, air transportation experienced a decline from early 2020 to 2021. This study focuses on air traffic predictions, namely the number of aircraft passengers during the COVID-19 pandemic at Indonesia's main airports, namely Kuala Namu, Sukarno Hatta, and Juanda airports., Ngurah Rai and Hasanuddin. The method used to predict the number of airplane passengers during a pandemic is the backpropagation algorithm using the Fletcher Reeves method.

关键词： COVID-19 Analytical models Airplanes Pandemics Atmospheric modeling Backpropagation algorithms Predictive models

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Convolutional Neural Network (CNN) Algorithm Development for Quality Measurement in Tire Product Classification: A Systematic Literature Review

Convolutional Neural Network (CNN) Algorithm Development for...

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International Conference on Informatics and Computing (ICIC)

作者： Armando Tirta Dwilaga Lintang Yuniar Banowosari Sudaryanto Aini Suri Talita Department of Information Technology Doctoral Program Gunadarma Information Technology University West Java Indonesia Department of Informatics Gunadarma University West Java Indonesia Department of Industrial Engineering and Management Gunadarma University West Java Indonesia Department of Information System Management Gunadarma University West Java Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

Convolutional Neural Networks (CNN) have shown potential in tire defect classification, but challenges like image quality variations and model limitations persist. This Systematic Literature Review (SLR) employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology and a qualitative approach. It uses the Population, Intervention, Comparison, Outcome, and Context (PICOC) framework to analyze 30 articles from Google Scholar, published between 2018 and 2024 in Q1-Q4 journals. The review examines article distribution by publisher, evaluates the impact of key pre-training parameters (such as data split ratio, dropout rate, optimization algorithm, learning rate, and pre-trained models on CNN performance), and identifies challenges in defect classification. MDPI (Multidisciplinary Digital Publishing Institute) is the most frequent publisher, with the highest number of publications occurring in 2021. AlexNet and VGG16 are the most common models, and an 80:20 data split ratio, 0.5 dropout rate, and a 0.001 learning rate are frequently used. The Adam (Adaptive Momentum) optimization algorithm is widely adopted, but challenges remain in detecting small defects. Further improvements in CNN models, lighting techniques, and larger datasets are needed to enhance defect detection. This review highlights current trends and future research opportunities in tire quality measurement.

关键词： Image quality Adaptation models Current measurement Lighting Tires Data models Classification algorithms Convolutional neural networks Optimization Systematic literature review

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Height Estimation via Stereo Vision System for Unmanned Helicopter Autonomous Landing

Height Estimation via Stereo Vision System for Unmanned Heli...

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2010 International Symposium on Computer,Communication, Control and Automation

作者： Kuo-Hsien Hsia Shao-Fan Lien Juhng-Perng Su Department of Management Information System Far East University Graduate School of Engr.Sci.&Tech.(Doctoral Program) National Yunlin University of Science&Technology Department of Electrical Engineering National Yunlin University of Science&Technology Department of Information Technology Overseas Chinese University

ISBN: (纸本)9781424455652;9781424455669

Auto landing is a very important function of control in the development of autonomous unmanned *** this paper,the stereo vision system is proposed to provide the height information on landing control instead of global positioning system(GPS).GPS provided 3-axis information,but the height error of GPS is usually in meters,which is not accurate enough for *** stereo vision system provided a more accurate height information to correct the error of *** this paper,the stereo vision system is composed of two webcams and the variable baseline method is selected to increase the measurement *** results show that variable baseline method did increase the accuracy of the stereo vision system with the webcams,and that not only provided an authentic piece of height information but also provided another option of sensor for autonomous unmanned helicopter's auto landing control.

关键词： stereo vision system height estimation helicopter landing

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The relationship between each length of REM - NREM sleep cycle and sleep stage

The relationship between each length of REM - NREM sleep cyc...

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IEEE Global Conference on Life Sciences and Technologies (LifeTech)

作者： Hiroko Sawai Maki Matsumoto Emi Koyama Core Technology Division Toyota Central R&D Labs. Inc Aichi Japan Doctoral Program of Engineering Design Kyoto Institute of Technology Kyoto Japan Faculty of Information and Human Science Kyoto Institute of Technology Kyoto Japan

ISBN: (数字)9781665418751

ISBN: (纸本)9781665448086

A series of non rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep (REM-NREM sleep cycle) repeats across night. The length of REM-NREM sleep cycle varies between nights or individuals. However, the cause of the variation, which may represent characteristics of sleep, has not been well understood. To verify the cause of the variation, the relationship between each length of REM-NREM sleep cycle and included sleep stage was analyzed. We used the obtained data which consisted of 143 days with 6 to 7-hour sleep (37 healthy males in their 20s). The variation in each length of REM-NREM sleep cycle (Cycle No.1-4 in order of appearance) were observed. Each length of Cycle No.1-4 had positive correlations with stage 1+2 and stage REM. Therefore, each length of REM-NREM sleep cycle represented characteristics of each phase of sleep and could be useful to evaluate sleep quality.

关键词： Correlation Sleep Conferences Market research Life sciences Biology Rapid eye movement sleep

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Purchasing Intention of Tour Package Brands in Access to Digital technology and User Generated Content on Bali Travel Tour

Purchasing Intention of Tour Package Brands in Access to Dig...

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IEEE International Symposium on Consumer Electronics (ISCE)

作者： Ngr. Putu Raka Novandra Asta Erma Suryani Raden Venantius Hari Ginardi Doctoral Program in Technology Management Interdisciplinary School of Management Technology Institut Teknologi Sepuluh Nopember Surabaya Surabaya Indonesia Politeknik NegeriBali Bali Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Surabaya Indonesia

ISBN: (数字)9798350365191

ISBN: (纸本)9798350365207

Digital technology is currently a vital medium to influence consumers with diverse behaviours and a high level of sensitivity when purchasing goods and services. The purpose of this study is to analyse the impact of exposure to digital technology and user-generated content on the brand purchase intention of travel packages in the Bali tourism sector. As digital technology changes the way we communicate or convey information to attract consumers, one of the methods used to attract consumers is user-generated content (UGC) to create a more intimate engagement between products, services, and consumers. A total of 200 tourists who bought tour packages were used as respondents using accidental sampling. The results of the study explain that digital technology and user integration center have a significant influence on brand purchase intention, and brand exposure and brand familiarity have a considerable positive influence on brand purchase intention. A different influence is found: brand knowledge and attitude have a negative impact on brand purchase intention. The results of this study can enrich knowledge about the currently developing topic of e-marketing aimed at academics. From a practical perspective, this research can provide marketers with insight into the effectiveness of content as an advertising platform in the travel and tourism industry.

关键词： Sensitivity Consumer behavior Brand management User-generated content Tourism industry Companies Media Sustainable development Advertising

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The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Vishakha D Bhandarkar Aruna Sri Rongali Mohamed Dawood Shamout Prof. Sachin Pund Gigih Forda Nama Shrishailappa Patil Applied Mathematics and Humanities Yeshwantrao Chavan College of Engineering India Graduate Doctoral Information Technology/Graduate (Information Technology Emphasis/Information Technology Ph.D.) University of The Cumberlands US Department of Management College of Business Administration University of Sharjah Sharjah United Arab Emirates Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India Department of Informatics Doctoral Program of Environtmental Science University of Lampung Bandar Lampung Computer engineering Vishwakarma Institute of Technology Pune

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way..

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An Improvement Data Hiding Scheme Based on Formula Fully Exploiting Modification Directions and Pixel Value Differencing Method

An Improvement Data Hiding Scheme Based on Formula Fully Exp...

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Asia Joint Conference on information Security (Asia JCIS)

作者： Wen-Chung Kuo Jyun-Jia Li Chun-Cheng Wang Lih-Chyau Wuu Yu-Chih Huang Department of Computer Science and Information Engineering National Yunlin University of Science & Technology Taiwan R.O.C. Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science & Technology Taiwan R.O.C.

ISBN: (纸本)9781509022861

Recently, a modified data hiding scheme based on pixel value differencing and improving exploiting modification directions is proposed by Shen and Huang. There are two major contributions in this scheme. One is to enhance the embedding rate and good embedding capacity and the other is an optimization problem used to solve the overflow/ underflow problem. In fact, they propose the similar brute force method to solve overflow/underflow problem in their proposed scheme. To overcome the overflow/underflow problem exactly, we will propose the close form to solve this problem in this paper. Then, an improvement data hiding scheme based on FFEMD (Formula Fully Exploiting Modification Directions) and pixel value differencing method is proposed. According to our analysis, it is not only to keep the advantages of Shen-Huang scheme but also to use the close form to solve the overflow/ underflow problem.

关键词： Integrated circuits Cryptography Partitioning algorithms Streaming media Electronic mail Distortion

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