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Advanced engineering and Technologies (ICONNIC), International Conference on

作者： Bonifacius Vicky Indriyono Natalinda Pamungkas Fatima Hashim Abbas Ery Mintorini Mohammed Almohamadi Sarmad Nozad Mahmood Sameer Alani Ahmed H. Alkhayyat Eko Hari Rachmawanto Information System University of Dian Nuswantoro Kediri Indonesia Medical Laboratories Techniques Department Al-Mustaqbal University College Hillah Babil Iraq Visual Communication Design University of Dian Nuswantoro Kediri Indonesia College of Information Technology Imam Ja'afar Al-Sadiq University Al-Muthanna Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq Medical Laboratories Techniques University of Mashreq Research center Baghdad Iraq College of technical engineering University of Mashreq The Islamic University Najaf Iraq Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia

Mobile Adhoc Networks (MANETs) is an emerging technology in both the industrial and academic research. The major drawback in MANETs is improving the battery capacity. MANETs are dynamic in nature therefore during communication it consumes more energy that reduces the overall energy efficiency of the network. Many past and present researches are concern about this problem. In this paper, Energy Preservation in MANETs using Self-Adaptive Cluster Head Selection with Advanced Genetic Algorithm (EPMSA-CHAG) approach is proposed where the CH selection is performed using two segments; they are initial parameter based on CH selection and Advanced Genetic Algorithm (AGA) based CH selection. At the initial stage the parameters which are considered for the CH selection are node degree, node stability, distance, residual energy, and speed and delivery rate. Using these parameters are the best fit for CH selection is chosen then in order to find the optimal best fit from the best fit calculation, Advanced Genetic Algorithm (AGA). The proposed EPMSA-CHAG approach is simulated using NS2 and the parameters which are considered for the performance analysis are packet delivery rate, energy efficiency, end to end delay, routing overhead and throughput. The methods that are taken for the comparative analysis are HLSPM-CHSR and HAMBO-CHLD. From the results calculated it is proven that the proposed EPMSA-CHAG approach achieved high packet delivery rate, energy efficiency and throughput as well as lower end to end delay and routing overhead when compared with the earlier methods HLSPM-CHSR and HAMBO-CHLD.

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A DISEASE-SPECIFIC FOUNDATION MODEL USING OVER 100K FUNDUS IMAGES: RELEASE AND VALIDATION FOR ABNORMALITY AND MULTI-DISEASE CLASSIFICATION ON DOWNSTREAM TASKS

arXiv

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arXiv 2024年

作者： Jang, Boa Ahn, Youngbin Choe, Eun Kyung Yoon, Chang Ki Choi, Hyuk Jin Kim, Young-Gon Interdisciplinary Program in Bioengineering College of Engineering Seoul National University Korea Republic of Department of Transdisciplinary Medicine Seoul National University Hospital Korea Republic of Interdisciplinary Program of Medical Informatics Seoul National University College of Medicine Korea Republic of Department of Surgery Seoul National University Hospital Healthcare System Gangnam Center Korea Republic of Department of Ophthalmology Seoul National University College of Medicine Korea Republic of Department of Ophthalmology Seoul National University Hospital Healthcare System Gangnam Center Korea Republic of Department of Medicine Seoul National University College of Medicine Korea Republic of

Artificial intelligence applied to retinal images offers significant potential for recognizing signs and symptoms of retinal conditions and expediting the diagnosis of eye diseases and systemic disorders. However, developing generalized artificial intelligence models for medical data often requires a large number of labeled images representing various disease signs, and most models are typically task-specific, focusing on major retinal diseases. In this study, we developed a Fundus-Specific Pretrained Model (Image+Fundus), a supervised artificial intelligence model trained to detect abnormalities in fundus images. A total of 57,803 images were used to develop this pretrained model, which achieved superior performance across various downstream tasks, indicating that our proposed model outperforms other general methods. Our Image+Fundus model offers a generalized approach to improve model performance while reducing the number of labeled datasets required. Additionally, it provides more disease-specific insights into fundus images, with visualizations generated by our model. These disease-specific foundation models are invaluable in enhancing the performance and efficiency of deep learning models in the field of fundus imaging. Copyright © 2024, The Authors. All rights reserved.

关键词： Ophthalmology

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Supply chain information system for product management control using rule based reasoning model

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AIP Conference Proceedings 2023年第1期2665卷

作者： Mufadhol Mufadhol Mustafid Mustafid Suryono Suryono Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Informatics Engineering STEKOM University Semarang Indonesia

Accuracy, fast and efficiency in performing digital transactions are needed especially during the pandemic covid 19, this need to be done for persevering and improving customer confidence. The supply chain is a concept applied by companies to analyze production needs from raw material providers, transportation to be used, production processes and even determine expeditions to send goods to customers according to a predetermined time. This research has never been done by other researchers where the supply chain process is carried out by a company by involving algorithms in computer science in the form of applying rule based reasoning methods to obtain optimal results. The supply chain information system combined with the rule based reasoning method allows companies to control production management that can improve product quality even up to the marketing model that will be used accompanied by consultants who are experts in their fields and can communicate actively to customers so that customers feel satisfied and feel well served. Computational rules will be run through the system developed in the form of rule based reasoning so that the company can obtain fast and precise analysis to take a decision with the purpose of obtaining the maximum benefit from any activities and transactions.

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Contour Detection from Ultrasound Kidney Images with A Coarse-to-Fine Approach

Contour Detection from Ultrasound Kidney Images with A Coars...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Peng, Tao Gu, Yidong Xu, Yanqing Wang, Caishan Zhang, Lei Cai, Jing School of Future Science and Engineering Soochow University Suzhou China UT Southwestern Medical Center Department of Radiation Oncology DallasTX United States The Affiliated Suzhou Hospital of Nanjing Medical University Department of Medical Ultrasound Suzhou Municipal Hospital Jiangsu Suzhou China University of Texas Southwestern Medical Center McDermott Center for Human Growth and Development DallasTX United States The Second Affiliated Hospital of Soochow University Department of Ultrasound Suzhou China Duke Kunshan University Graduate Program of Medical Physics and Data Science Research Center Jiangsu Kunshan China The Hong Kong Polytechnic University Department of Health Technology and Informatics Hong Kong Hong Kong

ISBN: (纸本)9798350337020

Ultrasound kidney image segmentation presents significant challenges due to missing or ambiguous boundaries. In this study, we introduce a coarse-to-refinement approach incorporating four novel aspects. Firstly, we leverage the properties of a principal curve (PC) to automatically fine-tune the curve shape and employ a neural network's learning ability to reduce model error. Secondly, a deep fusion learning network is utilized for the coarse segmentation step, incorporating a parallel architecture to enhance deep-learning performance. Thirdly, addressing the limitation of standard PC-based methods in determining the number of vertices automatically, we propose an automatic searching polygon tracking method using a mean shift clustering-based approach to replace the projection and vertex extension step in standard PC-based methods. Lastly, we develop an explainable mathematical map function for the kidney contour, as denoted by the neural network output (i.e., optimized vertices), which aligns well with the ground truth contour. We conducted various experiments to evaluate our method's performance, demonstrating its effectiveness in ultrasound kidney image segmentation. © 2023 IEEE.

关键词： Artificial intelligence Explainable mathematical model Ultrasound kidney segmentation

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Efficiency analysis of a 150 Wp solar power system as a water pump electric power source

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AIP Conference Proceedings 2023年第1期2746卷

作者： A. N. Woro W. M. W. Muda N. Irwansyah D. A. Erica Electrical Engineering Study Program Faculty of Engineering Pamulang University Tangerang Selatan Banten Indonesia Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu 2103 Kuala Nerus Terengganu Malaysia

The 1970 – 1979 when a world energy crisis occurred and since then new and renewable energy has started to gain attention. Water and electricity are very important sources of life. Solar energy can be used to turn on a water pump through a solar power generation system as a water pump energy source. it is very important to know the level of efficiency of the PV module as a solar energy absorber that will produce current and voltage values. This solar power system will be equipped with 150 Wp PV, SCC, Battery, Inverter and also a 125 watt Pump. To determine the efficiency level of PV as a water pump power system, observations and measurements carried out for data collection for one day. The measurement shows that the highest voltage at 15:00 WIB 20.85 Voc with a temperature of 34.95°C with a current of 4.80 Isc when solar radiation is 560 W/m^2 and produces a power of 100.08 watts with an input power of 563 watts and an efficiency value of 17%. While the lowest voltage at 12:00 WIB 18.60 Voc when the temperature 41.16 °C and the current generated 6.90 Isc with solar radiation of 1013 W/m^2 and the power generated 128.34 watts with an input power of 1019 watts and the resulting efficiency 12%. Temperature is the main factor in the voltage generated, while solar radiation will affect the current output to be generated by PV. Incoming and outgoing power will determine the efficiency of the PV system as a water pump power source.

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Glucose-mediated mitochondrial reprogramming by cholesterol export at TM4SF5-enriched mitochondria-lysosome contact sites

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Cancer Communications 2024年第1期44卷 47-75页

作者： Ji Eon Kim So-Young Park Chulhwan Kwak Yoonji Lee Dae-Geun Song Jae Woo Jung Haesong Lee Eun-Ae Shin Yangie Pinanga Kyung-hee Pyo Eun Hae Lee Wonsik Kim Soyeon Kim Chang-Duck Jun Jeanho Yun Sun Choi Hyun-Woo Rhee Kwang-Hyeon Liu Jung Weon Lee Department of Pharmacy College of PharmacySeoul National UniversitySeoulRepublic of Korea Research Institute of Pharmaceutical Sciences College of PharmacySeoul National UniversitySeoulRepublic of Korea BK21 FOUR Community-Based Intelligent Novel Drug Discovery Education Unit College of Pharmacy and Research Institute of Pharmaceutical SciencesKyungpook National UniversityDaeguRepublic of Korea Department of Chemistry Seoul National UniversitySeoulRepublic of Korea College of Pharmacy Chung-Ang UniversitySeoulRepublic of Korea Natural Product Informatics Research Center Korea Institute of Science and Technology(KIST)Gangneung-siGangwon-doRepublic of Korea School of Life Sciences Gwangju Institute of Science and Technology(GIST)GwangjuRepublic of Korea Department of Biochemistry College of MedicineDong-A UniversityBusanRepublic of Korea Global AI Drug Discovery Center College of Pharmacy and Graduate School of Pharmaceutical SciencesEwha Womans UniversitySeoulRepublic of Korea Interdisciplinary Program in Genetic Engineering Seoul National UniversitySeoulRepublic of Korea

Background:Transmembrane 4 L six family member 5(TM4SF5)translocates subcellularly and functions metabolically,although it is unclear how intracellu-lar TM4SF5 translocation is linked to metabolic *** is thus of interests to understand how the traffic dynamics of TM4SF5 to subcellular endosomal membranes are correlated to regulatory roles of ***:Here,we explored the metabolic significance of TM4SF5 localization at mitochondria-lysosome contact sites(MLCSs),using in vitro cells and in vivo animal systems,via approaches by immunofluorescence,proximity labelling based proteomics analysis,organelle reconstitution ***:Upon extracellular glucose repletion following depletion,TM4SF5 became enriched at MLCSs via an interaction between mitochondrial FK506-binding protein 8(FKBP8)and lysosomal *** labeling showed molecular clustering of phospho-dynamic-related protein I(DRP1)and certain mitophagy receptors at TM4SF5-enriched MLCSs,leading to mitochondrial fis-sion and ***4SF5 bound NPC intracellular cholesterol transporter 1(NPC1)and free cholesterol,and mediated export of lysosomal cholesterol to mitochondria,leading to impaired oxidative phosphorylation but intact tri-carboxylic acid(TCA)cycle andβ-*** mouse models,hepatocyte Tm4sf5 promoted mitophagy and cholesterol transport to mitochondria,both with positive relations to liver ***:Our findings suggested that TM4SF5-enriched MLCSs regu-late glucose catabolism by facilitating cholesterol export for mitochondrial reprogramming,presumably while hepatocellular carcinogenesis,recapitulating aspects for hepatocellular carcinoma metabolism with mitochondrial repro-gramming to support biomolecule synthesis in addition to glycolytic energetics.

关键词： cholesterol fluorescent imaging glucose catabolism hepatocellular carcinogenesis mem-brane contact sites mitochondria function mitophagy oxidative phosphorylation protein-protein interaction tetraspanin

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Crowd and Urban Storytelling: Evaluating a Collective Intelligence Model to Support Discussions about the City

Crowd and Urban Storytelling: Evaluating a Collective Intell...

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International Conference on Computer Supported Cooperative Work in Design

作者： Ramon Chaves Claudia Motta Antó nio Correia Hugo Paredes Bá rbara Caetano Jano Moreira De Souza Daniel Schneider Postgraduate Program in Informatics PPGI/UFRJ Rio de Janeiro Brazil T&#x00E9 rcio Pacitti Institute of Computer Applications and Research (NCE) Federal University of Rio de Janeiro Brazil UTAD INESC TEC and University of Tr&#x00E1 s-os-Montes e Alto Douro Vila Real Portugal Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil

In recent years, digital technologies have been used to support discussions about the city and also to involve citizens in participatory public processes. However, despite the widespread use of social media platforms, old issues related to engagement and participation still persist in digital initiatives. The main goal of this study is to carry out an empirical evaluation of a collective intelligence model that combines crowdsourcing and social storytelling to support discussions about the city from a bottom-up perspective. Within a design science research approach we designed a participatory action study that was carried out through a workshop with students and professionals from different areas, such as architecture, urban design and information technology. As a result, we were able to assess whether the collective intelligence model was acceptable to the participants by investigating whether the behavioral assumptions were valid and thus outlining some contributions to the field of urban informatics.

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Hybrid Intelligent-Annotation Organ Segmentation on Medical Datasets

Hybrid Intelligent-Annotation Organ Segmentation on Medical ...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Peng, Tao Zhao, Jing Gu, Yidong Di, Gongye Zhang, Lei Cai, Jing School of Future Science and Engineering Soochow University Suzhou China Ut Southwestern Medical Center Department of Radiation Oncology DallasTX United States Tsinghua University Affiliated Beijing Tsinghua Changgung Hospital Department of Ultrasound Beijing China The Affiliated Suzhou Hospital of Nanjing Medical University Suzhou Municipal Hospital Department of Medical Ultrasound Jiangsu Suzhou China The Affiliated Taizhou People's Hospital of Nanjing Medical University Department of Ultrasonic Taizhou China Duke Kunshan University Graduate Program of Medical Physics Data Science Research Center Jiangsu Kunshan China The Hong Kong Polytechnic University Department of Health Technology and Informatics Hong Kong

ISBN: (纸本)9798350337020

Ultrasound image segmentation is crucial for early disease detection and treatment planning but remains a challenging task due to the low contrast of organ boundaries and varying image quality. Current methods often require manual intervention or have limited accuracy. In this paper, we propose a novel hybrid framework that combines an automatic option polygon segment (AOPS) algorithm and a distributed- and memory-based evolution (DME) algorithm for precise ultrasound organ segmentation. Our pipeline consists of two cascaded stages: (1) a coarse segmentation step using the AOPS algorithm, which determines the number of vertices/clusters without human intervention, and (2) a refinement step using the DME algorithm to hunt for the optimal neural network, which is then used to represent a smooth, explainable mathematical expression of the organ boundary. We employ the fractional backpropagation learning network with L2 regularization (FBLN) for training and use the scaled exponential linear unit (SELU) activation function to address the vanishing gradient problem. This is a new attempt such a hybrid framework is applied to ultrasound organ segmentation tasks, and it demonstrates significant contributions in terms of accuracy, smoothness, and computational efficiency. © 2023 IEEE.

关键词： distributed-evolution learning network Multi-organs segmentation principal curve SEL U-based explainable mathematical model ultrasound

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Comparison heuristics method for solving two echelon vehicle routing problem

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AIP Conference Proceedings 2024年第1期3029卷

作者： Muhammad Khahfi Zuhanda Saib Suwilo Opim Salim Sitompul Mardiningsih Informatics Engineering Study Program Faculty Engineering Universitas Medan Area Medan Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

Today, almost everyone has done online shopping activities. The presence of e-commerce makes it easier for humans to do shopping. E-commerce companies compete to provide the best service to the community. One of them is in the delivery within the city. In terms of city delivery, the 2E-VRP model has been discussed a lot lately in terms of consolidating shipments. This study aims to present the 2E-VRP mathematical model and work in two stages to find a solution. In this article, the author also compares solutions with several heuristic models including 2-opt, repetitive nearest neighbor, nearest neighbor, farthest insertion, cheapest insertion, arbitrary insertion, and nearest insertion. From the results of research conducted by the 2-opt method, farthest insertion, cheapest insertion, and nearest insertion, the total distance is the best, all three get the same distance, then followed by the nearest insertion, arbitrary insertion, and nearest insertion methods.

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Autoencoders as Weight Initialization of Deep Classification Networks for Cancer versus Cancer Studies

arXiv

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arXiv 2020年

作者： Ferreira, Mafalda Falcão Camacho, Rui Teixeira, Luís F. Doctoral Program in Informatics Engineering Faculty of Engineering University of Porto INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Department of Informatics Engineering Faculty of Engineering University of Porto Porto - Portugal

Cancer is still one of the most devastating diseases of our time. One way of automatically classifying tumor samples is by analyzing its derived molecular information (i.e., its genes expression signatures). In this work, we aim to distinguish three different types of cancer: thyroid, skin, and stomach. For that, we compare the performance of a Denoising Autoencoder (DAE) used as weight initialization of a deep neural network. Although we address a different domain problem in this work, we have adopted the same methodology of Ferreira et al.. In our experiments, we assess two different approaches when training the classification model: (a) fixing the weights, after pre-training the DAE, and (b) allowing fine-tuning of the entire classification network. Additionally, we apply two different strategies for embedding the DAE into the classification network: (1) by only importing the encoding layers, and (2) by inserting the complete autoencoder. Our best result was the combination of unsupervised feature learning through a DAE, followed by its full import into the classification network, and subsequent fine-tuning through supervised training, achieving an F1 score of 98.04% ± 1.09 when identifying cancerous thyroid samples. Copyright © 2020, The Authors. All rights reserved.

关键词： Classification (of information)

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