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3rd International Conference on Education and Information Systems: Technologies and Applications, EISTA 2005

作者： Pruengkarn, Ratchakoon Praneetpolgrang, Prasong Srivihok, Anongnart Department of Computer Science Kasetsart University Bangkok Thailand Master of Science Program in Information Technology Sripatum University Bangkok Thailand

ISBN: (纸本)9806560345

The objective of this research is to evaluate the total quality of e-Leaming websites for university in Thailand by using quality criteria which based on IEEE 1061 and ISO/IEC 9126. In this research, we determine 6 quality aspects (include 2 new aspects) such as functionality, reliability, usability, efficiency, maintainability and portability. In the research process, we categorize subjects into 5 groups. The result has found that the average of quality on e-Leaning websites in Thailand is 50.34% and this can be exploited as beneficial information for e-Leaming webmaster to motivate and improve the quality of e-Leaming website according to the proposed quality model for optimizing the effective e-Learning.

关键词： Websites

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A Reduced Features of Public Health Development Index by Using Clustering Methods 4

A Reduced Features of Public Health Development Index by Usi...

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4th International Conference on Informatics and Computing, ICIC 2019

作者： Adi Darmawan, Muhammad Prihandoko Gunadarma University Technology and Engineering Program Depok Indonesia Gunadarma University Department of Computer Science and Information Technology Depok Indonesia

ISBN: (纸本)9781728122076

Public Health Development Index (PHDI) is an index that released by Ministry of Health of The Republic of Indonesia which is used to measure the health of Indonesian people. The PHDI is divided into seven categories and measured by using 30 features. There are 497 cities that contributed to PHDI 2013. The problem emerged is that not all the cities have those 30 features required by PHDI. The objective of this paper is to reduce PHDI features with various Feature Selection For Clustering (FSFC) method. The subset of features resulted from FSFC method is then used to generate two types of clusters, i.e. k-means and DBSCAN clustering. The clusters generated from k-means and DBSCAN techniques will be evaluated by using internal and external validation method. The subset of features is then compared with the original ranking of PHDI. Experimental results show that the results of each FSFC method producing a different rank compared to the original rank of PHDI. This result concludes that all the features that are used to measure PHDI are important to be included in the process of calculation. © 2019 IEEE.

关键词： Feature Selection

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Image Size, Color Depth, Age variant on Convolution Neural Network 1

Image Size, Color Depth, Age variant on Convolution Neural N...

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1st Indonesian Association for Pattern Recognition International Conference, INAPR 2018

作者： Pranoto, Hady Budiharto, Widodo Hendric Spits Warnars, Harco Leslie Matsuo, Tokuro Heryadi, Yaya Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Graduate School of Industrial Technology Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9781538694220

Facial recognition as of biometric authentication used in the field of security, military, finance and daily use is become a trend or famous, because of its natural and not intrusive nature. Many methods for face recognition such as holistic learning, the use of local features, shallow learning and deep learning, some methods are susceptible to variations in pose change, illumination, expression and age variation. State of the art of face recognition today is a deep learning technique that delivers high accuracy. In this paper author replicate an face recognition using deep learning architecture called OpenFace Convolutional Neural Network. In this research author make variation on the size of image, color dept and age, and see how that factor impact on accuracy of face recognition in that architecture. As the result from the research, the accuracy of a model depends on the image size, color depth, and age variation, but in OpenFace CNN that recognition still provides fairly good accuracy when reducing the size of image and color depth, as long as the image can still be detected on the landmark facial, so the alignment process can be done on the face image. © 2018 IEEE.

关键词： Face recognition

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The Deep Learning Approach For American Sign Language Detection

The Deep Learning Approach For American Sign Language Detect...

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2022 IEEE Creative Communication and Innovative technology, ICCIT 2022

作者： Pangestu, Gusti Heryadi, Yaya Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University School of Computer Science Computer Science Department Binus Graduate Program Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara 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)9781665468763

Sign language has importance rule to deal with communication process especially with impairments hearing people. Sign language detection also attract lot of researchers to join the challenge of research to detect and recognize the sign language in the field of computer science. Hence, there is still no any standard approach and method to recognize the meaning in every pose of sign language. This research proposed a mechanism to detect Alphabet American Sign Language by utilizing Convolutional Neural Network (CNN) process. The CNN approach was chosen based on the ability and capability to recognize image. In this research, MNIST dataset is used for traning and testing process. The proposed CNN architecture produced 97% of accuracy that outperform the previous research using the same dataset which made this architecture promising. © 2022 IEEE.

关键词： Convolutional neural networks

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An approach for crop recommendation with uncertainty quantification based on machine learning for sustainable agricultural decision-making

Results in Engineering

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Results in Engineering 2025年

作者： Md. Sakib Bin Alam Vatcharaporn Esichaikul Aiman Lameesa Shams Forruque Ahmed Amir H. Gandomi Department of Information Technology University of Information Technology and Sciences (UITS) Dhaka 1212 Bangladesh Computer Science and Information Management Program School of Engineering and Technology Asian Institute of Technology Pathum Thani 12120 Thailand Department of Computer Science American International University-Bangladesh Dhaka 1229 Bangladesh School of Mathematical Sciences Sunway University Bandar Sunway Petaling Jaya 47500 Selangor Darul Ehsan Malaysia Department of Mathematics & Physics North South University Dhaka 1229 Bangladesh Faculty of Engineering and Information Technology University of Technology Sydney Sydney NSW 2007 Australia University Research and Innovation Center (EKIK) Óbuda University 1034 Budapest Hungary Department of Computer Science Khazar University Mahsati 41 Baku Azerbaijan

While machine learning (ML) models for crop recommendation have demonstrated high predictive accuracy, a critical gap persists in their practical reliability: the omission of uncertainty quantification. Existing studies predominantly deliver deterministic recommendations, neglecting inherent uncertainties arising from data noise. This raises concerns about the reliability of the decision support systems for crop recommendation. To address this, we propose an ensemble ML framework incorporating entropy-based uncertainty quantification. Trained on a publicly available Indian agricultural dataset with 2,200 samples across seven agro-climatic features (nitrogen, phosphorus, potassium, temperature, humidity, pH, and rainfall) and 22 crop classes, the model achieves a predictive accuracy of 99.54%. By estimating prediction confidence using entropy, the framework offers probabilistic recommendations that support environmentally informed decision-making under uncertainty. These findings suggest that integrating uncertainty measures into ML-driven crop recommendation systems can enhance reliability and promote sustainable agricultural practices.

关键词： Crop recommendation Machine learning Uncertainty Precision agriculture

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TextAI 3.0 (Multimodal): multimodal sentiment analysis using attention-enabled ensemble-based deep learning in hyperbolic space

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International Journal of Information technology (Singapore) 2025年 1-16页

作者： Singh, Jaskaran Sanga, Prabhav Khanna, Narendra N. Laird, John R. Singh, Inder M. Kalra, Mannudeep K. Mantella, Laura E. Johri, Amer M. Faa, Gavino Tiwari, Ekta Singh, Rajesh Abbas, Mohamed Saba, Luca Suri, Jasjit S. Stroke Monitoring and Diagnostic Division AtheroPoint™ Roseville 95661 CA United States Bharati Vidyapeeth’s College of Engineering New Delhi India Department of Cardiology Indraprastha APOLLO Hospitals New Delhi 110001 India Department of Neurology and Stroke Program University of Maryland School of Medicine Baltimore United States Department of Radiology Harvard Medical School Boston 02115 MA United States Department of Biomedical and Molecular Sciences Queen’s University Kingston ON Canada Division of Cardiology Department of Medicine Queen’s University Kingston ON Canada Department of Pathology University of Cagliari Cagliari Italy Department of Computer Science Visvesvaraya National Institute of Technology (VNIT) Nagpur 440010 India Department of Research and Innovation Uttaranchal Institute of Technology Uttaranchal University Dehradun 248007 India Central Labs King Khalid University P.O. Box 960 AlQura’a Abha Saudi Arabia Electrical Engineering Department College of Engineering King Khalid University Abha 61421 Saudi Arabia Department of Neurology University of Cagliari Cagliari Italy Department of ECE Idaho State University Pocatello 83209 ID United States Department of CE Graphic Era Deemed to Be University Dehradun 248002 India University Center for Research and Development Chandigarh University Mohali India Symbiosis Institute of Technology Symbiosis International (Deemed University) Nagpur Campus Pune India Department of Innovation Global Biomedical Technologies Inc. Roseville 95661 CA United States

The rising prevalence of depression presents a significant global health challenge, underscoring the need for effective early detection through sentiment analysis. Traditional multimodal sentiment analysis methods, which rely on Euclidean space for data representation, often fail to capture the complex hierarchical relationships and non-linear structures inherent in multimodal data. To address this limitation, we propose a novel multimodal architecture that operates in hyperbolic space and incorporates attention-based ensemble learning to enhance feature representation and model performance. We developed and evaluated ten AI models—five utilizing Euclidean space and five leveraging hyperbolic space—on the Spoken Language Understanding Evaluation (SLUE) benchmark dataset. The models were assessed using cross-validation techniques to ensure robustness, and statistical analyses were conducted to validate the findings. Our results indicate that hyperbolic-based multimodal models achieve a 2.32% improvement in accuracy compared to their Euclidean counterparts, while the integration of self-attention mechanisms further contributes an average accuracy gain of 0.96%. Additionally, we observed a 3.76% decline in performance when reducing the training-to-test data ratio from 90:10 to 50:50, highlighting the importance of data distribution in model training. These findings confirm that attention-enhanced multimodal models in hyperbolic space offer superior representations for sentiment analysis. © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： Attention-enabled Deep learning Euclidean space Hyperbolic space Multimodal Sentiment analysis

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Mobile game Application for Religion engagement

Mobile game Application for Religion engagement

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2019 International Congress on Applied Information technology, AIT 2019

作者： Kristiadi, Dedy Prasetya Vindy, V. Sambera, Richard Julianto, Andy Warnars, Harco Leslie Hendric Spits Hashimoto, Kiyota STMIK Raharja Computer Systems Department Tangerang15117 Indonesia Game Application Technology Program School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Faculty of Technology and Environment Prince Songkla University Phuket Campus Thailand

ISBN: (纸本)9781728158624

Religion is a part of a fundamental human right to serve and worship their God according to their religion and belief. Mobile game application along with the development of mobile phone technology such as a smartphone, tablet, and laptop, can be used to increase the player or user interest to engage with religion thing. Using the mobile game application in mobile gadgets will expand quickly to install and use for religion engagement. The player can learn religion things with fun and entertain ways, where the player does not realize that they do something serious in an unserious way. This paper will explain the model system design for mobile game application for learning Catholicism in fun and entertaining way and for the first development was limited to only three Catholic catechisms such as bible learning, church lesson, and liturgy celebration. For the early development, three types of games were developed such as True or False game, Scramble words game, and multiple-choice game. The mobile game model was designed with a use case diagram, storyboard, and class diagram, where for the current implementation the mobile game application was implemented using a ten tables database. © 2019 IEEE.

关键词： Serious games

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Thermal energy dependent transient permittivity of epsilon-near-zero material

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science China(Physics,Mechanics & Astronomy) 2022年第8期65卷 96-101页

作者： Heng Wang Lixun Sun Kang Du Wending Zhang SooJin Chua Guixin Li Ting Mei MOE Key Laboratory of Material Physics and Chemistry under Extraordinary Conditions and Shaanxi Key Laboratory of Optical Information TechnologySchool of Physical Science and TechnologyNorthwestern Polytechnical UniversityXi’an710129China Department of Materials Science and Engineering Southern University of Science and TechnologyShenzhen518055China Shenzhen Institute for Quantum Science and Engineering Southern University of Science and TechnologyShenzhen518055China Department of Electrical and Computer Engineering National University of SingaporeSingapore117583Singapore LEES Program Singapore-MIT Alliance for Research&Technology(SMART)Singapore138602Singapore

Transparent conductive oxides exhibit attractive optical nonlinearity with ultrafast response and giant refractive index change near the epsilon-near-zero(ENZ) wavelength, originating from the intraband dynamics of conduction electrons. The optical nonlinearity of ENZ materials has been explained by using the overall-effective-mass and the overall-scattering-time of electrons in the extended Drude model. However, their response to optical excitation is yet the last building block to complete the theory. In this paper, the concept of thermal energy is theoretically proposed to account for the total energy of conduction electrons exceeding their thermal equilibrium value. The time-varying thermal energy is adopted to describe the transient optical response of indium-tin-oxide(ITO), a typical ENZ material. A spectrally-resolved femtosecond pump-probe experiment was conducted to verify our theory. By correlating the thermal energy with the pumping density, both the giant change and the transient response of the permittivity of ITO can be predicted. The results in this work provide a new methodology to describe the transient permittivities of ENZ materials, which will benefit the design of ENZ-based nonlinear photonic devices.

关键词： epsilon-near-zero optical nonlinearity transient response thermal energy hot electron indium tin oxide

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Case study on installing a porting process for embedded operating system in a small team

Case study on installing a porting process for embedded oper...

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International Conference on Secure Software Integration and Reliability Improvement Companion

作者： Cho, DongSeok Bae, DooHwan Korea Advanced Institute of Science and Technology Software Graduate Program Seoul Korea Republic of Korea Advanced Institute of Science and Technology Division of Computer Science Taejon Korea Republic of

ISBN: (纸本)9780769544540

Recently as the demand of smart devices increases, the porting of embedded operating systems such as Google Android, Microsoft Windows Mobile, and Embedded Linux, becomes more important. Consequently, the importance of efficient, systematic porting is also raised. Generally, developers initiate embedded operating system porting from getting operating system source codes and materials. After they get source codes, they modify the source codes, and then they test them. To identify porting in detail, we investigated a small porting team which has fifteen members. In this team, each developer has done porting depending on his or her knowledge and experience. Therefore, we tried to find studies for efficient, systematic porting, but we couldn't find sufficient study results. This study aims to analyze porting process in a small organization. Also, we'll suggest productive a porting process and evaluate productivity of the new process through a case study. © 2011 IEEE.

关键词： Embedded systems

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Analyzing Human Observer Ability in Morphing Attack Detection - Where Do We Stand?

IEEE Transactions on Technology and Society

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IEEE Transactions on technology and Society 2023年第2期4卷 125-145页

作者： Godage, Sankini Rancha Lovasdal, Froy Venkatesh, Sushma Raja, Kiran Ramachandra, Raghavendra Busch, Christoph Norwegian University of Science and Technology Department of Computer Science Trondheim 22 Gjovik2815 Norway National Police Directorate National Technology Team Euis Program Oslo0369 Norway Norwegian University of Science and Technology Department of Information Security and Communication Technology Trondheim 22 Gjovik2815 Norway

Morphing attacks are based on the technique of digitally fusing two (or more) face images into one, with the final visage resembling the contributing faces. Morphed images not only pose a challenge to Face-Recognition Systems (FRS) but also challenge experienced human observers due to high quality, postprocessing eliminating any visible artifacts, and further the printing and scanning process. Few studies have concentrated on examining how human observers can recognize morphing attacks, even as several publications have examined the susceptibility of automated FRS to morphing attacks and offered morphing attack detection (MAD) approaches. MAD approaches base their decisions either on a single image with no reference to compare against (Single-Image MAD (S-MAD)) or using a reference image (Differential MAD (D-MAD)). One prevalent misconception is that an examiner's or observer's capacity for facial morph detection depends on their subject expertise, experience, and familiarity with the issue. No works have reported the specific results of observers who regularly verify identity (ID) documents for their jobs. As human observers are involved in checking ID documents having facial images, a lapse in their competence can result in significant societal challenges. To assess the observers' proficiency, this research first builds a new benchmark database of realistic morphing attacks from 48 different subjects, resulting in 400 morphed images. Unlike the previous works, we also capture images from Automated Border Control (ABC) gates to mimic realistic border-crossing scenarios in the D-MAD setting with 400 probe images, to study the ability of human observers to detect morphed images. A new dataset of 180 morphing images is also produced to research human capacity in the S-MAD environment. In addition to creating a new evaluation platform to conduct S-MAD and D-MAD analysis, the study employs 469 observers for D-MAD and 410 observers for S-MAD who are primarily governmenta

关键词： Face recognition

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