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2nd International Conference on Mechanical, Electronics, computer, and Industrial technology, MECnIT 2018

作者： Sulindawaty Zarlis, Muhammad Situmorang, Zakarias Sihotang, Hengki Tamando Doctoral Program Faculty of Computer Science and InformationTechnology Universitas Sumatera Utara Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia

The development of technology has been very significant, not only in the fields of information, industry, education, but in agriculture. Therefore technological sophistication is also utilized by corn farmers to obtain information about corn crops. Corn is included in plantation commodities in Indonesia. However, in corn cultivation there are various problems associated with the disease that is likely to attack the plant. Therefore, the authors designed the expert system of corn disease diagnosis using certainty method. This system will analyze based on symptoms - symptoms that are in the input by the user so that in obtaining a result of disease identification on corn in the name of the disease, the cause of the disease, the percentage value and how to handle it. This expert system is developed by using the visual basic application and Microsoft Access database with Certainty Factor method to measure the value of certainty of a hypothesis against a fact. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Expert systems

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STP: single-cell partition for subcellular spatially-resolved transcriptomics

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Nature Communications 2025年第1期16卷 1-10页

作者： Li, Haoyang Hu, Qinan Qiu, Zhaowen Xiong, Hui Hu, Yuhui Gao, Xin Computer Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Center of Excellence for Smart Health (KCSH) King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Center of Excellence on Generative AI King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Department of Pharmacology School of Medicine Southern University of Science and Technology Shenzhen China Joint Laboratory of Guangdong-Hong Kong Universities for Vascular Homeostasis and Diseases School of Medicine Southern University of Science and Technology Shenzhen Guangdong China SUSTech Homeostatic Medicine Institute School of Medicine Southern University of Science and Technology Shenzhen China College of Computer and Control Engineering Northeast Forestry University Harbin China Key Laboratory of Hepatosplenic Surgery Ministry of Education The First Affiliated Hospital of Harbin Medical University Harbin China Heilongjiang Tuomeng Technology Co. Ltd. Harbin China Thrust of Artificial Intelligence The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Department of Computer Science and Engineering The Hong Kong University of Science and Technology SAR Hong Kong Research center for chemical biology and omics analysis Guangming Advanced Research Institute Southern University of Science and Technology Shenzhen China

Spatially-resolved transcriptomics (SRT) technologies now allow exploration of gene expression with spatial context. Recent advances achieving subcellular resolution provide richer data but also introduce challenges, such as aggregating subcellular spots into individual cells, which is a task distinct from traditional deconvolution. Existing methods often grid SRT data into predefined squares, which is unrealistic for accurately capturing cellular boundaries. We propose a method, STP, that integrates subcellular SRT data with nuclei-stained images to partition individual cells. STP first segments nuclei and maps their masks onto the SRT data, then uses a simulated-annealing-inspired approach to expand nuclear boundaries to the full cellular level. Evaluated on subcellular SRT datasets from Drosophila embryos at multiple developmental stages and from mouse embryos with a large field-of-view, STP demonstrated accurate single-cell partitioning, unveiling significant spatial tissue patterns and identifying undetected cell types beyond previous methods. © The Author(s) 2025.

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An IoT Based Smart Garbage Monitoring and Disposal Support System 5

An IoT Based Smart Garbage Monitoring and Disposal Support S...

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5th International Conference on Computing Methodologies and Communication, ICCMC 2021

作者： Vamsi, T.M.N. Kalyan Chakravarthi, G. Lanka, Pratibha Divakar, B. Dept of Computer Science and Engineering Engineering and Technology Program Visakhapatnam AP India Depts of Computer Science Visakhapatnam AP India Department of Computer Applications Visakhapatnam AP India

ISBN: (纸本)9781665403603

Today globally people designed different systems based on Internet of Things (IoT) principles and made human with smart living. In this article, an important application is proposed for our daily usage and is named as Smart Garbage Monitoring and Disposal Support System (SGMDSS). Since the advent of mobile communication and the spread of the Internet anywhere and anytime, there is a lot of scopes to control the devices from remote places. Solid garbage is one of the prior concerns today globally because improper execution of garbage removal from the villages, towns, and cities affects the people living there and it is the ultimate cause for new diseases. So, proper garbage management by using technology is a major concern of the hour. In the traditional existing system, the monitoring and disposal of garbage are done by humans and it is cumbersome, therefore supporting the traditional system with the flavor of IoT, then monitoring of garbage bins will be easy. This helps the people who are involved in the traditional garbage collection system and it will be the best feasible solution. The SGMDSS is a very innovative information management control system that helps the metros, cities, and villages hygiene and clean with a better garbage disposal. This system uses an advanced approach in which waste monitoring and disposal support are automated. SGMDSS monitors the garbage bins located at different locations and notifies about the level of garbage accumulated in the garbage bins through an android mobile application to the cleaning personnel for disposal and provides the shortest path to the garbage bin location that is almost filled. This information is also sent to the webpage and the entire data is stored and accessed through the cloud. Also, an alert message is sent to the worker. © 2021 IEEE.

关键词： Internet of things

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Edit propagation via edge-aware filtering

Edit propagation via edge-aware filtering

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作者： Hu, Wei Dong, Zhao Yuan, Guo-Dong Department of Computer Science and Technology Beijing University of Chemical Technology Beijing 100028 China Program of Computer Graphics Cornell University Ithaca 14853 United States Department of Computer Science and Technology Tsinghua University Beijing 100084 China

This paper presents a novel framework for efficiently propagating the stroke-based user edits to the regions with similar colors and locations in high resolution images and videos. Our framework is based on the key observation that the edit propagation intrinsically can also be achieved by utilizing recently proposed edge-preserving filters. Therefore, instead of adopting the traditional global optimization which may involve a time-consuming solution, our algorithm propagates edits with the aid of the edge-preserve filters. Such a propagation scheme has low computational complexity and supports multiple kinds of strokes for more flexible user interactions. Further, our method can be easily and efficiently implemented in GPU. The experimental results demonstrate the efficiency and user-friendliness of our approach. © 2012 Springer science+Business Media, LLC & science Press. China.

关键词： Global optimization

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Teaching Abstraction to Novices: Pattern-Based and ADT-Based Problem-Solving Processes

Teaching Abstraction to Novices: Pattern-Based and ADT-Based...

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IEEE Frontiers in Education Conference 2008

作者： Haberman, Bruria Muller, Orna Computer Science Department Holon Institute of Technology Israel CS Academia and Industry Program Israel Science Education Department Computer Science Group Tel-Aviv University Israel Software Engineering Department Ort Braude College of Engineering Israel

ISBN: (纸本)9781424419692

is taught to computer-science students as part of a comprehensive curriculum. The students encounter the concept of abstraction in various contexts while learning the different modules, each of which emphasizes some specific aspects of the concept. In this paper we present two instructional approaches, both related to utilizing abstraction in problem-solving processes: (1) pattern-oriented instruction (POI), and (2) abstract data type (ADT)-oriented instruction. We present these methods with respect to their employment in teaching problem solving to novices, and elaborate on abstraction processes.

关键词： Abstraction algorithmic patterns abstract data types problem solving

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Improving university e-Learning with exploratory data analysis and web log mining

Improving university e-Learning with exploratory data analys...

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6th International Conference on computer science and Education, ICCSE 2011

作者： Nukoolkit, Chakarida Chansripiboon, Praewphan Sopitsirikul, Satita Computer Science Program School of Information Technology King Mongkut's University of Technology Thonburi Bangkok 10140 Thailand

ISBN: (纸本)9781424497188

The success of an e-Learning system depends on several factors: a supportive infrastructure, high-quality content, effective format, and high availability to satisfy ongoing user needs. In this paper, we perform exploratory data analysis and data mining on an e-Learning web log, which spans one academic year. The study uncovers the e-Learning users' usage behavior in accessing the content. The study discovers e-Learning media popularity and usage patterns, and helps the institution fine tune future courseware, from strategic changes to the fine-grain of lesson content improvement. © 2011 IEEE.

关键词： Data mining

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Development of a healthcare monitoring diabetes mobile application for community

Development of a healthcare monitoring diabetes mobile appli...

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2022 International Conference on Computational science and Computational Intelligence, CSCI 2022

作者： Bussaban, Kanyarat Waraporn, Phanu Roonrakwit, Pattarapan Sangsuwan, Chanyapat Kularbphettong, Kunyanuth Suan Sunandha Rajabhat University Faculty of Science and Technology Bangkok Thailand Suan Sunandha Rajabhat University Computer Science Program Bangkok Thailand Silpakorn University Faculty of Information and Communication Technology Bangkok Thailand Suan Sunandha Rajabhat University Computer Science Program Faculty of Science and Technology Bangkok Thailand

ISBN: (纸本)9798350320282

The purpose of this project is to develop the mobile application, by applied Machine learning, for analyzing, collecting, monitoring, and retrieving information between patients with diabetes especially diabetes type 2 and village public health volunteers and to study the impact of using mobile application based on self-learning and self-management in diabetes information. This is a research and development mobile application and the sample consisted of 30 diabetes patients and 5 village health volunteers participated in this research. The project has demonstrated the effectiveness of using mobile application to support patients and village health volunteers. The results showed that user satisfaction has a high level. © 2022 IEEE.

关键词： Machine learning

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Development of Learning Skills by Using a computer Assisted Instruction on Problem Solving with Equations to Enhance Critical Thinking Skills of the Fifth Grade Students 2

Development of Learning Skills by Using a Computer Assisted ...

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2nd International Annual Meeting on STEM Education, IAMSTEM 2019

作者： Paengtip, Pannee Paengtip, Sittichai Dermrach, Praewsree Computer Education Program Faculty of Science Technology and Agriculture Yala Rajabhat University Yala95000 Thailand English and Educational Technology Program Faculty of Education Yala Rajabhat University Yala95000 Thailand Computer Program Faculty of Science Technology and Agriculture Yala Rajabhat University Yala95000 Thailand

The purpose of this study was to develop a computer assisted instruction about problem solving with equations to enhance critical thinking skills of the fifth grade students. Two phases were undertaken in the study. The first phase aimed to develop and monitor the quality of the CAI in which five experts on design and CAI were the main group to evaluate it. The second was to test and evaluate the CAI in which 30 fifth grade students within Bankotabaru School in Yala province were the main participants. The data collected within the first academic term of 2017 in Thailand were analysed using descriptive statistics, such as percentages, means, standard deviations, and t-test. The results were that the CAI aiming to enhance critical thinking skills of the students were divided into 3 parts;1) an introduction;2) teaching processes;and 3) an evaluation. There was a higher percentage of critical thinking skills of the participants in association with before and after the use of the CAI at 52.18 and 80.41 with the difference value of 28.23 and the statistical significance of 0.05 level. © Published under licence by IOP Publishing Ltd.

关键词： computer aided instruction

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Annotating TSSs in Multiple Cell Types Based on DNA Sequence and RNA-seq Data via DeeReCT-TSS

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Genomics, Proteomics & Bioinformatics 2022年第5期20卷 959-973页

作者： Juexiao Zhou Bin Zhang Haoyang Li Longxi Zhou Zhongxiao Li Yongkang Long Wenkai Han Mengran Wang Huanhuan Cui Jingjing Li Wei Chen Xin Gao Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Computational Bioscience Research Center King Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Department of Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Gene Regulation and Systems Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Academy for Advanced Interdisciplinary Studies Southern University of Science and TechnologyShenzhen 518055China

The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological *** fulfill this,specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner,and various computational tools have also been developed for in silico prediction of TSSs solely based on genomic *** of these computational tools cast the problem as a binary classification task on a balanced dataset,thus resulting in drastic false positive predictions when applied on the genome ***,we present Dee Re CT-TSS,a deep learningbased method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing *** show that by effectively incorporating these two sources of information,Dee Re CT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell ***,we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types,which enables the identification of cell type-specific ***,we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin *** source code for Dee Re CT-TSS is available at https://github.-com/Joshua Chou2018/Dee Re CT-TSS_release and https://***/biocode/tools/BT007316.

关键词： Transcription start site Machine learning Deep learning Meta-learning RNA sequencing

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Optimal Deep Canonically Correlated Autoencoder-Enabled Prediction Model for Customer Churn Prediction

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computers, Materials & Continua 2022年第11期73卷 3757-3769页

作者： Olfat M.Mirza GJose Moses R.Rajender E.Laxmi Lydia Seifedine Kadry Cheadchai Me-Ead Orawit Thinnukool Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science Engineering Malla Reddy Engineering College500100India Department of Computer Science Engineering Lendi Institute of Engineering&TechnologyDenkada535005India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeNorway Program in Statistics and Information Management Faculty of ScienceMaejo UniversityChiang Mai50290Thailand Department of Modern Management and Information Technology College of Arts Media and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Presently,customer retention is essential for reducing customer churn in telecommunication *** churn prediction(CCP)is important to predict the possibility of customer retention in the quality of *** risks of customer churn also get essential,the rise of machine learning(ML)models can be employed to investigate the characteristics of customer ***,deep learning(DL)models help in prediction of the customer behavior based characteristic *** the DL models necessitate hyperparameter modelling and effort,the process is difficult for research communities and business *** this view,this study designs an optimal deep canonically correlated autoencoder based prediction(ODCCAEP)model for competitive customer dependent application *** addition,the O-DCCAEP method purposes for determining the churning nature of the *** O-DCCAEP technique encompasses preprocessing,classification,and hyperparameter ***,the DCCAE model is employed to classify the churners or ***,the hyperparameter optimization of the DCCAE technique occurs utilizing the deer hunting optimization algorithm(DHOA).The experimental evaluation of the O-DCCAEP technique is carried out against an own dataset and the outcomes highlighted the betterment of the presented O-DCCAEP approach on existing approaches.

关键词： Churn prediction customer retention deep learning machine learning archimedes optimization algorithm

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