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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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Braess paradox in dynamic routing for the cohen-kelly network

Braess paradox in dynamic routing for the cohen-kelly networ...

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Fourth IASTED International Conference on Communications, Internet, and Information Technology, CIIT 2005

作者： Inoie, Atsushi Kameda, Hisao Touati, Corinne E. Doctoral Program in Computer Science University of Tsukuba Tsukuba Sci. City Ibaraki305-8573 Japan Department of Computer Science University of Tsukuba Tsukuba Sci. City lbaraki305-8573 Japan

ISBN: (纸本)0889865159

A paradox of dynamic routing in the Cohen-Kelly network is studied. Intuitively, we expect that adding capacity to a network improves the performance of the users. Braess showed an example wherein the opposite occurs. We refer to such a situation as a paradox. In this paper, we deal with a class of queueing networks in which Cohen and Kelly discovered a paradox in static routing. We consider the dynamic routing problems in the above mentioned class of networks, and show the existence of a paradox in dynamic routing of the above mentioned class of networks through simulation experiments analogous to what Cohen and Kelly showed.

关键词： Routers

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Analysis of Application of the SAW, WP and TOPSIS Methods in Decision Support System Determining Scholarship Recipients at University 3

Analysis of Application of the SAW, WP and TOPSIS Methods in...

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3rd International Conference on Computational science and Information Management, ICoCSIM 2019

作者： Marbun, Murni Zarlis, Muhammad Nasution, Zulkifli Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Teknik Informatika STMIK Pelita Nusantara Medan Indonesia

This research is an analysis of the application of the SAW, WP and TOPSIS methods to the support system for decision making at university. The types of scholarships provided are PPA education scholarships given by the Kementerian Riset, Teknologi dan Pendidikan Tinggi. The research variables are the attributes or criteria specified by the Directorate General of Learning and Student Affairs as contained in the 2018 Academic Achievement Improvement (PPA) guidebook. Decision Support Systems apply the classic FMADM method SAW, WP and TOPSIS. The results of this study are the application of the both methods of SAW and WP produce the same ranking and TOPSIS giving different rankings. © Published under licence by IOP Publishing Ltd.

关键词： Decision support systems

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Analysis of Feature Selection Methods On Clove Quality Classification

Analysis of Feature Selection Methods On Clove Quality Class...

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International Conference on Information Technology (INCIT)

作者： Firman Tempola Aina Musdholifah Retantyo Wardoyo Doctoral Program Department of Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia Department of Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9798350366303

ISBN: (纸本)9798350366310

Proper feature selection is becoming increasingly important in the context of clove quality classification in Indonesia; effective feature selection can identify the most relevant attributes of clove quality. This study investigates 3 famous feature selection methods, namely mutual information, recursive feature selection, and lasso regression, for classifying clove quality using various models, i.e. Naïve Bayes, K-NN, and Decision Tree. The study results showed that the mutual information feature selection method impacted the K-NN method by 1.05%; for naïve Bayes and decision trees, the accuracy did not increase. For the recursive feature elimination (RFE) feature selection method, the accuracy of K-NN increased by 2.16%, the decision tree by 0.37%, and naïve Bayes accuracy did not increase. In addition, using Lasso Regression feature selection, the accuracy of naïve Bayes increased by 2.97%, K-NN by 2.28%, and decision tree accuracy decreased.

关键词： Analytical models Accuracy Lighting Machine learning Nearest neighbor methods Feature extraction Bayes methods Information technology Mutual information Regression tree analysis

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Enhancing safety with an AI-empowered assessment and monitoring system for BSL-3 facilities

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Heliyon 2025年第1期11卷 e40855页

作者： Fan, Yi-Ling Hsu, Ching-Han Wu, Ju-Yu Tsai, Ying-Ying Chen, Wei J. Lee, Min-Shi Hsu, Fang-Rong Liao, Lun-De Institute of Biomedical Engineering and Nanomedicine National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan Department of Biomedical Engineering & Environmental Sciences National Tsing-Hua University Hsinchu Taiwan Doctoral Program in Tissue Engineering and Regenerative Medicine National Chung Hsing University Taichung Taiwan Center for Neuropsychiatric Research National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan National Institute of Infectious Diseases and Vaccinology National Health Research Institutes 35 Keyan Road Miaoli County Zhunan Town 350 Taiwan Department of Information Engineering and Computer Science Feng Chia University Taichung 407 Taiwan

Introduction: The COVID-19 pandemic has created an urgent demand for research, which has spurred the development of enhanced biosafety protocols in biosafety level (BSL)-3 laboratories to safeguard against the risks associated with handling highly contagious pathogens. Laboratory management failures can pose significant hazards. Methods: An external system captured images of personnel entering a laboratory, which were then analyzed by an AI-based system to verify their compliance with personal protective equipment (PPE) regulations, thereby introducing an additional layer of protection. A deep learning model was trained to detect the presence of essential PPE items, such as clothing, masks, hoods, double-layer gloves, shoe covers, and respirators, ensuring adherence to World Health Organization (WHO) standards. The internal laboratory management system used a deep learning model to delineate alert zones and monitor compliance with the imposed safety protocols. Results: The external detection system was trained on a dataset consisting of 4112 images divided into 15 PPE compliance classes. The model achieved an accuracy of 97.52 % and a recall of 97.03 %. The identification results were presented in real time via a visual interface and simultaneously stored on the administrator's dashboard for future reference. We trained the internal management system on 3347 images, achieving 90 % accuracy and 85 % recall. The results were transmitted in JSON format to the internal monitoring system, which triggered alerts in response to violations of safe practices or alert zones. Real-time notifications were sent to the administrators when the safety thresholds were met. Conclusion: The BSL-3 laboratory monitoring system significantly reduces the risk of exposure to pathogens for personnel during laboratory operations. By ensuring the correct use of PPE and enhancing adherence to the imposed safety protocols, this system contributes to maintaining the integrity of BSL-3 facilities

关键词： Bioengineering Biomedical instrumentation Biomedical laboratory safety Biosafety level-3 laboratory

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Optimal grid quantization

Optimal grid quantization

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16th International Conference on Pattern Recognition, ICPR 2002

作者： Song, Mingzhou Haralick, Robert M. Department of Computer Science Queens College of CUNY FlushingNY11367 United States Computer Science Doctoral Program Graduate Center of CUNY New YorkNY10016 United States

ISBN: (纸本)0769516963

Optimal quantization, a non-parametric technique for pattern recognition, determines a compact and efficient density representation of data by optimizing a global quantizer performance measure, which is a weighted combination of average log likelihood, entropy and correct classification probability. In multi-dimensions, we obtain the quantization grid using genetic algorithms. Smoothing is an important aspect as it affects the generalization ability of the quantizer. We propose a fast k neighborhood smoothing algorithm. Optimal quantization is much more efficient than other non-parametric methods. For not very welt separated Gaussian mixture models, it produces much better results than the EM algorithm, which fails to converge to the true parameters of the underlying density. © 2002 IEEE.

关键词： Pattern recognition

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Advancing Total Communication in SIBI: A Proposed Conceptual Framework for Sign Language Translation

Advancing Total Communication in SIBI: A Proposed Conceptual...

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2023 International Conference on Smart-Green Technology in Electrical and Information Systems, ICSGTEIS 2023

作者： Darmawan, I Dewa M. Bayu A. Linawati, Linawati Sukadarmika, Gede Wirastuti, Ni M. Ary Esta Dewi Pulungan, Reza Mulyanto Hariyanti, Ni Kadek Dessy Udayana University Doctoral Engineering Department Denpasar Indonesia Udayana University Electrical Engineering Department Jimbaran Indonesia Universitas Gadjah Mada Computer Science and Electronics Department Yogyakarta Indonesia National Taiwan University of Science and Technology Doctoral Engineering of Electronic and Computer Engineering Department Taipei Taiwan Politeknik Negeri Bali Business Administration Department Badung Indonesia

ISBN: (纸本)9798350382822

Total communication in sign language involves hand gestures as manual signs and facial expressions as non-manual signs. Both types of signs have an important role in communication. Research related to sign language translators focuses more on manual signs. Ignoring the non-manual components causes the translation of spoken language to be less precise because of the loss of information from the signer's facial emotions. Indonesian Sign Language (SIBI) is different from other sign languages. SIBI follows the rules of the Indonesian language, which consist of structure and syntax. This paper proposes a framework for sign language translation composed of manual and non-manual components. Two propositions will be tested and contribute to this research. The first proposition is related to the use of sign gesture detection and segmentation methods using optical flow-based methods, and the second proposition is associated with the use of STMC, Facial Expression Recognition, and Transformer methods at the stage of recognition and translation of sign language. The proposed work arrangement is expected to improve performance measured by WER, BLEU, and METEOR and reduce computational load as measured by processing time. © 2023 IEEE.

关键词： computer vision

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Direct Machine Translation Indonesian-Batak Toba 7

Direct Machine Translation Indonesian-Batak Toba

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7th International Conference on New Media Studies, CONMEDIA 2023

作者： Abidin, Zaenal Junaidi, Akmal Wamiliana Togatorop, Frengky Marulitua Ahmad, Imam Puspaningrum, Ajeng Savitri Universitas Lampung Doctoral Program of Mathematics and Natural Sciences Bandarlampung Indonesia Universitas Lampung Department of Computer Science Bandarlampung Indonesia Universitas Lampung Department of Mathematics Bandarlampung Indonesia Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia

ISBN: (纸本)9798350307504

The translation application was developed using Python and Visual Studio Code as the primary programming environment. Technological progress has led to the younger generation forsaking the Batak language in their daily interactions, perceiving it as inconsequential to their social circle and contributing to the decline of regional languages. There is concern that regional languages, namely the Batak language, may lose significance or face extinction if this trend persists. This translation program is being implemented to aid in preserving regional languages, specifically the Batak language, enabling it to conform to contemporary circumstances. The development of this translation engine utilized the Batak language dictionary. The process of designing, coding, and testing is responsible for creating this direct machine translation. The BLEU score is employed to assess the caliber of machine translation. The study's findings indicate that the % BLEU value for ten sentences was 32.3%. This score falls within the category of sentences whose meaning can be understood, but the sentence structure still needs development. The direct machine translation developed in this Web platform is highly proficient and practical. © 2023 IEEE.

关键词： Python

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Automatic Identification and Reconstruction 3D Image of the Rhinosinusitis Mucus 12

Automatic Identification and Reconstruction 3D Image of the ...

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12th International Conference on Information and Communication Technology, ICoICT 2024

作者： Eka Putra, Ondra Sumijan Tajuddin, Muhammad Universitas Putra Indonesia YPTK Padang Faculty of Computer Science Department of Informatics Technology Padang Indonesia Doctoral Program in Information Technology Universitas Putra Indonesia YPTK Padang Padang Indonesia Bumigora University Department of Computer Science Mataram Indonesia

ISBN: (纸本)9798350363432

Rhinosinusitis Mucus is mucus produced by mucus glands found in the nose in the paranasal sinus area which indicates inflammation. Segmentation of rhinosinusitis mucus is very difficult to do because of the many characteristics of different objects in the image of the paranasal Sinus CT-Scan in separating the mucus object with its background before the extraction process. The purpose of this study was to accurately identify and measure the mucus area of rhinosinusitis from CT-scan images of rhinosinusitis patients. The test data used in this study is secondary data from CT-Scan of paranasal sinus sagittal view in radiology RSUP M. Djamil Padang, Padang City, West Sumatra, Indonesia, using the Philips Ingenuity CT CT-Scan model type MRC880 numbered Tube series 163889. The segmentation process is carried out to obtain the optimal multi threshold value from each slice of the test image using the Improved Adaptive Multi Threshold (IAMT) segmentation method which produces a binary image to separate the mucus object with its background before the extraction process. Furthermore, the results of IAMT are applied to the identification and extraction model automatically to obtain the area of the rhinosinusitis mucus object. The extraction results were used for 2D to 3D image reconstruction in calculating the volume of rhinosinusitis mucus objects. The test results showed that the smallest area of rhinosinusitis mucus was 0.516 cm2 and the largest was 1.807 cm2, and the average volume was 0.95 cm3 with Accuracy is 96,5%. The identified areas and volumes indicate inflammation in the area of the paranasal sinuses and require treatment. Thus, this study can help doctors in making the right decision to take further medical action. © 2024 IEEE.

关键词： computerized tomography

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Privacy Preserving Electronic Health Record with Consortium Blockchain 6

Privacy Preserving Electronic Health Record with Consortium ...

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6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022

作者： Gautama, Adri Rochim, Adian Fatchur Bayuaji, Luhur Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Diponegoro University Department of Computer Engineering Semarang Indonesia Computer Science Budi Luhur University Jakarta Indonesia

ISBN: (纸本)9798350399615

Every patient has health record, it was written as statement of patient's conditions, treatments, and medications, and nowadays it is become digitalized, it can be copied and shared easily, but the nature of EHR is private, not for public, private between patients and healthcare provider. Privacy preserving can be done by implementing Blockchain network for storing EHR, only authorized users or nodes can access and write data to the network. New block in blockchain created as per consensus among nodes, every node can join a blockchain network if it is public, to meet a consensus required resources intensive cryptographic challenge, in private blockchain, only selected can join and involved in the network or specific transaction. In healthcare, data privacy is the main concerned, need a secure, scalable, and efficient blockchain hence implementing consortium blockchain is perfect match for EHR where multiple healthcare provider can operate in a single platform to conduct transaction or sharing EHR among members. This study analyzes 15 articles derived from IEEE Explore, science Direct and Scopus by implementing screening with keyword Consortium Blockchain and EHR and proposing new blockchain model accommodating solution for challenges on access, storage, sharing, privacy, and performance. © 2022 IEEE.

关键词： Consortium Blockchain e-health EHR Privacy

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