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丛书名： Lecture Notes in computer Science

1000年

作者： Xiaodong Li Michael Kirley Mengjie Zhang David Green Vic Ciesielski Hussein Abbass Zbigniew Michalewicz Tim Hendtlass Kalyanmoy Deb Kay Chen Tan Jürgen Branke Yuhui Shi

ISBN: (数字)9783540896944

ISBN: (纸本)9783540896937

This LNCS volume contains the papers presented at SEAL 2008, the 7th Int- nationalConference on Simulated Evolutionand Learning,held December 7–10, 2008, in Melbourne, Australia. SEAL is a prestigious international conference series in evolutionary computation and learning. This biennial event was ?rst held in Seoul, Korea, in 1996, and then in Canberra, Australia (1998), Nagoya, Japan (2000), Singapore (2002), Busan, Korea (2004), and Hefei, China (2006). SEAL 2008 received 140 paper submissions from more than 30 countries. After a rigorous peer-review process involving at least 3 reviews for each paper (i.e., over 420 reviews in total), the best 65 papers were selected to be presented at the conference and included in this volume, resulting in an acceptance rate of about 46%. The papers included in this volume cover a wide range of topics in simulated evolution and learning: from evolutionarylearning to evolutionary optimization, from hybrid systems to adaptive systems, from theoretical issues to real-world applications. They represent some of the latest and best research in simulated evolution and learning in the world.

关键词： Programming Techniques Computation by Abstract Devices Artificial Intelligence Simulation and Modeling User Interfaces and Human computer Interaction Discrete Mathematics in computer Science

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A Study of Cantilever Beam Vibration Wireless Transmission System

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Procedia engineering 2011年 14卷 1300-1306页

作者： Guangxiang Yang WenHui Duan Hua Liang School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing China Faculty of Mechanical Engineering Monash University Australia

ZigBee is a wireless communication technology which based on IEEE 802.15.4 protocol, communicating within short distance and with low power. ZigBee is applied in cantilever beam vibration measurement system in this paper, and the old wired transmission system are substituted by IEEE 802.15.4, software and sensor circuit are designed, reliable data transmission method and half byte compression algorithm are analyzed, and also provide basis and data analyzing solution for dynamics model of cantilever beam which using piezoelectric transducer. Experimental results show that with wireless ZigBee transmission solution and compression algorithm, the acquisition data of 150 bytes per second can be achieved, which will improve the quality of vibration analysis.

关键词： ZigBee Piezoelectric Transducer Compression Algorithm Cantilever Beam

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Determination of Compression Response for Various Dried Vegetables 1

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International Conference of Experimental and Numerical Investigations and New Technologies, CNNTech 2023

作者： Milošević, Miloš Jevtić, Ivana Trajković, Isaak Zlatanović, Ivan Mladenović, Goran Korolija, Nenad Innovation Centre of the Faculty of Mechanical Engineering Kraljice Marije 16 Street Belgrade11120 Serbia Faculty of Mechanical Engineering University of Belgrade Kraljice Marije 16 Street Belgrade11120 Serbia School of Electrical Engineering The Department of Computer Science and Information Technology University of Belgrade Belgrade11000 Serbia

ISBN: (数字)9783031464324

ISBN: (纸本)9783031464317

The texture of food plays a vital role in its overall quality, affecting both sensory experience and functional aspects, such as processing and preservation. To study texture in the field of food science and technology, various analytical methods are used to measure mechanical properties such as hardness, cohesiveness, and viscosity. One widely utilized technique for evaluating the texture of solid foods, particularly those with high firmness or brittleness such as dried vegetables, is compression testing. Here, a force is applied to a food sample until it deforms or fractures. In this particular study, dried onions, carrots, and peppers were chosen as test samples to investigate their texture and compression properties. To perform the tests, the researchers employed a Shimadzu AGS-X universal testing machine equipped with a 1 kN load cell capacity. This machine allowed them to compress the samples and measure the force required to achieve a specific deformation. The obtained results revealed that the texture and compression properties of the dried vegetables were significantly influenced by the specific part of the vegetable being tested. For instance, when examining the dried onions, a notable disparity was observed between the inner and outer parts. The basal plate of the onion, in particular, exhibited much greater hardness compared to the middle portion of the dried onion. Consequently, breaking the sample required a higher compression force. This discovery implies that the texture and compression properties of dried vegetables are closely tied to their inherent characteristics, internal structure, and composition. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Compression testing

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An Intelligent Prediction Model for Target Protein Identification in Hepatic Carcinoma Using Novel Graph Theory and ANN Model

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computer Modeling in engineering & Sciences 2022年第10期133卷 31-46页

作者： G.Naveen Sundar Stalin Selvaraj D.Narmadha K.Martin Sagayam A.Amir Anton Jone Ayman A.Aly Dac-Nhuong Le Computer Science and Engineering Karunya Institute of Technology and SciencesCoimbatore641114India Centre for Nanotechnology&Advanced Biomaterials(CeNTAB) School of Chemical&BiotechnologySASTRA Deemed to be UniversityThanjavur613401India Department of ECE Karunya Institute of Technology and SciencesCoimbatore641114India Department of Mechanical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia Institute of Research and Development Duy Tan UniversityDanang550000Vietnam Faculty of Information Technology Duy Tan UniversityDanang550000Vietnam

Hepatocellular carcinoma(HCC)is one major cause of cancer-related mortality around the ***,at advanced stages of HCC,systematic treatment options are currently *** a result,new pharmacological targetsmust be discovered regularly,and then tailored medicines against HCC must be *** this research,we used biomarkers of HCC to collect the protein interaction network related to ***,DC(Degree Centrality)was employed to assess the importance of each *** an improved Graph Coloring algorithm was used to rank the target proteins according to the interaction with the primary target protein after assessing the top ranked proteins related to ***,physio-chemical proteins are used to evaluate the outcome of the top ranked *** proposed graph theory and machine learning techniques have been compared with six existing *** the proposed approach,16 proteins have been identified as potential therapeutic drug targets for Hepatic *** is observable that the proposed method gives remarkable performance than the existing centrality measures in terms of Accuracy,Precision,Recall,Sensitivity,Specificity and F-measure.

关键词： Drug target detection hepatic carcinoma degree centrality graph coloring artificial neural network model

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Stakeholder Identification Overview and Challenges in Requirements engineering Prospective 2

Stakeholder Identification Overview and Challenges in Requir...

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2nd International Conference on Computing and information technology, ICCIT 2022

作者： Elneel, Duha Awad Fakharudin, Abdul Sahli Ahmed, Elsadig Musa Kahtan, Hasan Abdullateef, Mansoor Universiti Malaysia Pahang Faculty of Computing Kuantan26300 Malaysia Multimedia University Faculty of Business Melaka Malaysia Universiti Malaya Faculty of Computer Science and Information Technology Department of Software Engineering Kuala Lumpur50603 Malaysia Knowbis Solutions Consultancy Selangor Malaysia

ISBN: (纸本)9781665436052

Stakeholder identification (SI) illustrates a critical part of the requirements elicitation activity. It helps software analysts gather accurate system requirements to ensure high quality and avoid system failure. Stakeholder identification considered one of the earliest stages of project development. The main problem related to project success and failure is identifying the real stakeholders and selecting the right one. The lack of stakeholder identification methodologies and the shortage of previous research in identifying the stakeholders for different systems, encourage the research to propose a guideline framework, assist analysts in building the convenient methodology for identifying real stakeholders. Stakeholders are defined based on different projects and the various services they provide. This difference leads to the fact that a particular and systematic technique must be used to identify stakeholders based on the project's types. The exploration of stakeholder identification matters and the guideline framework is a baseline for future research in requirements engineering. © 2022 IEEE.

关键词： Requirements engineering

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A Novel Deep Learning Based Healthcare Model for COVID-19 Pandemic Stress Analysis

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computers, Materials & Continua 2022年第9期72卷 6029-6044页

作者： Ankur Dumka Parag Verma Rajesh Singh Anil Kumar Bisht Divya Anand Hani Moaiteq Aljahdali Irene Delgado Noya Silvia Aparicio Obregon Computer Science and Engineering Women Institute of TechnologyUttarakhand-248007India Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia Research and Innovation Uttranchal UniversityDehradunUttrakhand248007India Department of Computer Science&IT MJP Rohilkhand UniversityBareilly236006UPIndia Computer Science and Engineering Lovely Professional UniversityPunjab144411India Higher Polytechnic School Universidad Europea del Atlántico39011SantanderSpain Faculty of Computing and Information Technology King Abdulaziz University37848JeddahSaudi Arabia Universidad Internacional Iberoamericana CampecheMexico Universidade Internacional do Cuanza Bairro Kaluanda EN 250CuitoBié.Angola

Coronavirus(COVID-19)has impacted nearly every person across the globe either in terms of losses of life or as of *** current coronavirus(COVID-19)pandemic is a rare/special situation where people can express their feelings on Internet-based social *** media is emerging as the biggest platform in recent years where people spend most of their time expressing themselves and their *** research is based on gathering data from Twitter and analyzing the behavior of the people during the COVID-19 *** research is based on the logic expressed by people in this perspective and emotions for the suffering of COVID-19 and *** this research,we have used a Long Short-Term Memory(LSTM)network model with Convolutional Neural Network using Keras python deep-learning library to determine whether social media platform users are depressed in terms of positive,negative,or neutral emotional out bust based on their Twitter *** results showed that the model has 88.14%accuracy(representation of the correct prediction over the test dataset)after 10 epochs which most tweets showed had neutral *** evaluation shows interesting results in positive(1),negative(–1),and neutral(0)emotions through different visualization.

关键词： COVID-19 lockdown stress analysis depression analysis sentiment analysis social media COVID-19 twitter dataset coronavirus

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N-Gram-Based Machine Learning Approach for Bot or Human Detection from Text Messages 22

N-Gram-Based Machine Learning Approach for Bot or Human Dete...

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6th International Conference on Intelligent Systems, Metaheuristics and Swarm Intelligence, ISMSI 2022

作者： Kavadi, Durga Prasad Sanaboina, Chandra Sekhar Patan, Rizwan Gandomi, Amir Department Of Information Technology B V Raju Institute Of Technology Narsapur Telangana India Department Of Computer Science And Engineering University College Of Engineering Kakinada Jawaharlal Nehru Technological University Kakinada India Decentralized Science Lab College Of Computing And Software Engineering Kennesaw State University MariettaGA30060 United States Faculty Of Engineering And Information Systems University Of Technology Sydney UltimoNSW Australia

ISBN: (纸本)9781450396288

Social bots are computer programs created for automating general human activities like the generation of messages. The rise of bots in social network platforms has led to malicious activities such as content pollution like spammers or malware dissemination of misinformation. Most of the researchers focused on detecting bot accounts in social media platforms to avoid the damages done to the opinions of users. In this work, n-gram based approach is proposed for a bot or human detection. The content-based features of character n-grams and word n-grams are used. The character and word n-grams are successfully proved in various authorship analysis tasks to improve accuracy. A huge number of n-grams is identified after applying different pre-processing techniques. The high dimensionality of features is reduced by using a feature selection technique of the Relevant Discrimination Criterion. The text is represented as vectors by using a reduced set of features. Different term weight measures are used in the experiment to compute the weight of n-grams features in the document vector representation. Two classification algorithms, Support Vector Machine, and Random Forest are used to train the model using document vectors. The proposed approach was applied to the dataset provided in PAN 2019 competition bot detection task. The Random Forest classifier obtained the best accuracy of 0.9456 for bot/human detection. © 2022 ACM.

关键词： Feature Selection

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First Order Features Extraction from Thermal Images for Human State Recognition 8

First Order Features Extraction from Thermal Images for Huma...

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8th International Symposium on Electrical and Electronics engineering, ISEEE 2023

作者： Moldovanu, Simona Pavel, Sorin Aiordachioaie, Dorel Dunarea de Jos University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Computer Science and Information Technology Galati Romania Dunarea de Jos University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Electronics and Telecommunications Galati Romania

ISBN: (纸本)9798350301670

Due to the common limitation of the human visual system, internal features of thermal images cannot be fully discovered. To overcome these drawbacks, a lot of studies analyzed the facial expressions corroborating the features extracted from thermal images with machine learning tools. This paper proposed the first-order features extracted from the image histogram and a binary classification performed by the k-nearest neighbor algorithm (K-NN). The proposed method tests separately the performance of different input data, firstly, the features were extracted from raw images and the robustness of the K-NN algorithm led to an accuracy of 92.6%. Secondly, the features were extracted sequentially from corrupted images with noise. The novelty of the proposed method consists of verifying the quality classification when the images have bad quality, in this case, the accuracy decreased to 70.7%, as a result, the classification of facial expressions is sensitive to the quality of images. © 2023 IEEE.

关键词： Emotion Recognition

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Energy-Optimized with Multi-Population Differential Annealed Optimization in Mobile Edge Computing

Energy-Optimized with Multi-Population Differential Annealed...

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

作者： Wu, Ruixuan Shi, Yuliang Yuan, Haitao Bi, Jing Zhang, Jia Beijing University of Technology Faculty of Information Technology Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Lyle School of Engineering Southern Methodist University Dept. of Computer Science DallasTX United States

ISBN: (纸本)9798350337020

Mobile devices (MDs) cannot fully run all computation/delay-sensitive tasks due to their limited computing resources. Mobile edge computing (MEC) meets the demand by providing massive resources for MDs and offloading task partitions to MEC servers. However, task offloading also brings communication delay and energy consumption. Therefore, it is challenging to associate resource-constrained MDs with appropriate MEC servers to minimize power consumption. To address this problem, a constrained mixed integer nonlinear program is formulated to optimize the total energy consumption of the system including MDs and MEC servers. To solve this problem, this work designs an improved meta-heuristic optimization algorithm called Self-adaptive and Multi-population Differential Annealed Optimization (SMDAO). Experimental results demonstrate that compared with its two state-of-the-art peers, the proposed SMDAO yields the best solution with the smallest total energy consumption in the least time. © 2023 IEEE.

关键词： computation offloading energy optimization Mobile edge computing multi-population optimization simulated annealing

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Methodology of Transformation of Fuzzy Queries into Queries in the SQL Standard

Methodology of Transformation of Fuzzy Queries into Queries ...

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IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems

作者： Grzegorz Nowakowski Department of Automatic Control and Information Technology Faculty of Electrical and Computer Engineering Cracow University of Technology

ISBN: (纸本)9781728140704

The article presents two approaches to the method of implementation of transformations of fuzzy queries into queries in the SQL standard. This implementation can be carried out: (1) in a database (in the form of functions, procedures, triggers or other acceptable form), using the existing query processing system in the database, and thus it can expand the functionality of that database;(2) in an application (which communicates with the database), and thus a considerable portion of calculations will be transferred from the database to that application. An analysis of those approaches was conducted and it was demonstrated that the presented methods should enjoy extensive practical application.

关键词： Fuzzy logic Fuzzy queries Conversion Transformation Methodology SQL SQL Database Fuzzy logic methodology

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