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Identification and Classification of Crowd Activities

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computers, Materials & Continua 2022年第7期72卷 815-832页

作者： Manar Elshahawy Ahmed O.Aseeri Shaker El-Sappagh Hassan Soliman Mohammed Elmogy Mervat Abu-Elkheir department of information Technology Faculty of Computers and InformationMansoura UniversityEgypt department of computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia department of information Systems Faculty of Computers and Artificial IntelligenceBenha UniversityEgypt faculty of computer Science and Engineering Galala University435611SuezEgypt department of computer Science Faculty of Media Engineering and TechnologyGerman UniversityEgypt

The identification and classification of collective people’s activities are gaining momentum as significant themes in machine learning,with many potential applications *** need for representation of collective human behavior is especially crucial in applications such as assessing security conditions and preventing crowd *** paper investigates the capability of deep neural network(DNN)algorithms to achieve our carefully engineered pipeline for crowd *** includes three principal stages that cover crowd analysis ***,individual’s detection is represented using the You Only Look Once(YOLO)model for human detection and Kalman filter for multiple human tracking;Second,the density map and crowd counting of a certain location are generated using bounding boxes from a human detector;and Finally,in order to classify normal or abnormal crowds,individual activities are identified with pose *** proposed system successfully achieves designing an effective collective representation of the crowd given the individuals in addition to introducing a significant change of crowd in terms of activities *** results onMOT20 and SDHA datasets demonstrate that the proposed system is robust and *** framework achieves an improved performance of recognition and detection peoplewith a mean average precision of 99.0%,a real-time speed of 0.6ms non-maximumsuppression(NMS)per image for the SDHAdataset,and 95.3%mean average precision for MOT20 with 1.5ms NMS per image.

关键词： Crowd analysis individual detection You Only Look Once(YOLO) multiple object tracking kalman filter pose estimation

Suggestion Mining from Opinionated Text of Big Social media Data

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computers, Materials & Continua 2021年第9期68卷 3323-3338页

作者： Youseef Alotaibi Muhammad Noman Malik Huma Hayat Khan Anab Batool Saif ul Islam Abdulmajeed Alsufyani Saleh Alghamdi department of computer Science College of Computer and Information SystemsUmm Al-Qura UniversitySaudi Arabia department of computer Science Faculty of Engineering and Computer SciencesNational University of Modern LanguagesIslamabadPakistan department of Software Engineering Faculty of Engineering and Computer SciencesNational University of Modern LanguagesIslamabadPakistan department of computer sciences Institute of Space TechnologyIslamabadPakistan department of computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia department of information Technology College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia

:Social media data are rapidly increasing and constitute a source of user opinions and tips on a wide range of products and *** increasing availability of such big data on biased reviews and blogs creates challenges for customers and businesses in reviewing all content in their decision-making *** overcome this challenge,extracting suggestions from opinionated text is a possible *** this study,the characteristics of suggestions are analyzed and a suggestion mining extraction process is presented for classifying suggestive sentences from online customers’reviews.A classification using a word-embedding approach is used via the XGBoost *** two datasets used in this experiment relate to online hotel reviews and Microsoft Windows App Studio discussion reviews.F1,precision,recall,and accuracy scores are *** results demonstrated that the XGBoost classifier outperforms—with an accuracy of more than 80%.Moreover,the results revealed that suggestion keywords and phrases are the predominant features for suggestion ***,this study contributes to knowledge and practice by comparing feature extraction classifiers and identifying XGBoost as a better suggestion mining process for identifying online reviews.

关键词： Suggestion mining word embedding Naïve Bayes random forest XGBoost dataset

An Ensemble-Based Hotel Reviews System Using Naive Bayes Classifier

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computer Modeling in Engineering & sciences 2023年第10期137卷 131-154页

作者： Joseph Bamidele Awotunde Sanjay Misra Vikash Katta Oluwafemi Charles Adebayo department of computer Science Faculty of Information and Communication SciencesUniversity of IlorinIlorin240003Nigeria department of computer Science and Communication Otfold University CollegeHaldenNorway

The task of classifying opinions conveyed in any form of text online is referred to as sentiment *** emergence of social media usage and its spread has given room for sentiment analysis in our daily *** media applications and websites have become the foremost spring of data recycled for reviews for sentimentality in various *** subject matter can be encountered on social media platforms,such as movie product reviews,consumer opinions,and testimonies,among others,which can be used for sentiment *** rapid uncovering of these web contents contains divergence of many benefits like profit-making,which is one of the most vital of them *** to a recent study,81%of consumers conduct online research prior to making a *** the reviews available online are too huge and numerous for human brains to process and ***,machine learning classifiers are one of the prominent tools used to classify sentiment in order to get valuable information for use in companies like hotels,game companies,and so *** the sentiments of people towards different commodities helps to improve the services for contextual promotions,referral systems,and market ***,this study proposes a sentiment-based framework detection to enable the rapid uncovering of opinionated contents of hotel reviews.A Naive Bayes classifier was used to process and analyze the dataset for the detection of the polarity of the *** dataset from Datafiniti’s Business Database obtained from Kaggle was used for the experiments in this *** performance evaluation of the model shows a test accuracy of 96.08%,an F1-score of 96.00%,a precision of 96.00%,and a recall of 96.00%.The results were compared with state-of-the-art classifiers and showed a promising performance andmuch better in terms of performancemetrics.

关键词： Sentiment analysis hotel reviews Naive Bayes algorithm consumer opinions web 2.0 machine learning

Evolution of AVS video coding standards: twenty years of innovation and development

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Science China(information sciences) 2022年第9期65卷 50-73页

作者： Siwei MA Li ZHANG Shiqi WANG Chuanmin JIA Shanshe WANG Tiejun HUANG Feng WU Wen GAO Institute of digital media School of Computer Science Peking University Bytedance Inc. department of computer Science City University of Hong Kong CAS Key Laboratory of Technology in Geo-Spatial information Processing and Application System University of Science and Technology of China

Ever since the founding of the Audio and Video Coding Standard(AVS) Workgroup of China in 2002, it has been dedicated to advancing and innovating the digital audio-video industry with highly efficient and economical encoding/decoding technologies. Three representative generations of video coding standards have been finalized and published, consistently improving the coding performance in the past two *** series of AVS standards establish solid foundations for ubiquitous video applications in the areas including acquisition, coding, production, delivery, integrated system, public service, general screen content, and mixed reality media. Along with the standardization process, an extensive amount of studies have been carried out on efficiency-aware designation, algorithm optimization, and hardware implementation of these innovative video coding techniques. This paper explains how those developed techniques provide a lasting impact on the video coding community, extensively, technologically, and systematically. In particular, we provide a comprehensive survey of the three generations of the standards, and timely and in-depth summarize the efforts of the AVS video coding standards in the twenty years. The rate-distortion performance comparisons,in particular in terms of the 8K ultra-high-definition(UHD) contents, reflect the elegant design of the state-of-the-art AVS3 standards. We have also elaborated on a variety of well-established and promising applications, including commercial level real-time 8K encoder, high-frame-rate decoder chip for cell phone,and live streaming solution for sports. In addition, the China Central Television(CCTV) of China media Group(CMG), the state television of China, has officially launched the first 8K broadcasting channel(CCTV-8K) since 2021 using AVS3. Given the significant success realized by the AVS standards, it is envisioned that a new era of 8K UHD video is arriving.

关键词： video coding AVS standards video applications intelligent coding

Analyzing Customer Reviews on Social media via Applying Association Rule

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computers, Materials & Continua 2021年第8期68卷 1519-1530页

作者： Nancy Awadallah Awad Amena Mahmoud department of computer and information Systems Sadat Academy for Management SciencesCairo11742Egypt faculty of computers and information Department of Computer ScienceKafr el Sheikh UniversityKafr El Sheikh33511Egypt

The rapid growth of the use of social media opens up new challenges and opportunities to analyze various aspects and patterns in ***-text mining,several techniques are available such as information clustering,extraction,summarization,*** this study,a text mining framework was presented which consists of 4 phases retrieving,processing,indexing,and mine association rule *** is applied by using the association rule mining technique to check the associated term with the Huawei P30 Pro *** reviews are extracted from many websites and Facebook groups,such as ***,*** and *** technology,where customers from all over the world placed their notes on cell *** this analysis,a total of 192 reviews of Huawei P30 Pro were collected to evaluate them by text mining *** findings demonstrate that Huawei P30 Pro,has strong points such as the best safety,high-quality camera,battery that lasts more than 24 hours,and the processor is very *** paper aims to prove that text mining decreases human efforts by recognizing significant *** will lead to improving the awareness of customers to choose their products and at the same time sales managers also get to know what their products were accepted by customers suspended.

关键词： Machine learning text mining social media big data association rule document clustering

Intelligent Optimization-Based Clustering with Encryption Technique for Internet of Drones Environment

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computers, Materials & Continua 2022年第12期73卷 6617-6634页

作者： Dalia H.Elkamchouchi Jaber S.Alzahrani Hany Mahgoub Amal S.Mehanna Anwer Mustafa Hilal Abdelwahed Motwakel Abu Sarwar Zamani Ishfaq Yaseen department of information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia department of computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia faculty of computers and information Computer Science DepartmentMenoufia UniversityEgypt department of digital media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo 11845Egypt department of computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The recent technological developments have revolutionized the functioning of Wireless Sensor Network(WSN)-based industries with the development of Internet of Things(IoT).Internet of Drones(IoD)is a division under IoT and is utilized for communication amongst *** drones are naturally mobile,it undergoes frequent topological *** alterations in the topology cause route election,stability,and scalability problems in *** is considered as an effective method to transmit the images in IoD *** current study introduces an Atom Search Optimization basedClusteringwith Encryption Technique for Secure Internet of Drones(ASOCE-SIoD)*** key objective of the presented ASOCE-SIoD technique is to group the drones into clusters and encrypt the images captured by *** presented ASOCE-SIoD technique follows ASO-based Cluster Head(CH)and cluster construction *** addition,signcryption technique is also applied to effectually encrypt the images captured by drones in IoD *** process enables the secure transmission of images to the ground *** order to validate the efficiency of the proposed ASOCE-SIoD technique,several experimental analyses were conducted and the outcomes were inspected under different *** comprehensive comparative analysis results established the superiority of the proposed ASOCE-SIoD model over recent approaches.

关键词： Internet of drones atom search algorithm clustering encryption signcryption

Optimal Bottleneck-Driven Deep Belief Network Enabled Malware Classification on IoT-Cloud Environment

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computers, Materials & Continua 2023年第2期74卷 3101-3115页

作者： Mohammed Maray Hamed Alqahtani Saud S.Alotaibi Fatma S.Alrayes Nuha Alshuqayran Mrim M.Alnfiai Amal S.Mehanna Mesfer Al Duhayyim department of information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia department of information Systems College of Computer ScienceCenter of Artificial IntelligenceUnit of CybersecurityKing Khalid UniversityAbhaSaudi Arabia department of information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia department of information systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of information Systems College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic UniversitySaudi Arabia department of information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia department of digital media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt department of computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia

Cloud Computing(CC)is the most promising and advanced technology to store data and offer online services in an effective *** such fast evolving technologies are used in the protection of computerbased systems from cyberattacks,it brings several advantages compared to conventional data protection *** of the computer-based systems that effectively protect the data include Cyber-Physical Systems(CPS),Internet of Things(IoT),mobile devices,desktop and laptop computer,and critical *** software(malware)is nothing but a type of software that targets the computer-based systems so as to launch cyberattacks and threaten the integrity,secrecy,and accessibility of the *** current study focuses on design of Optimal Bottleneck driven Deep Belief Network-enabled Cybersecurity Malware Classification(OBDDBNCMC)*** presentedOBDDBN-CMCmodel intends to recognize and classify the malware that exists in IoT-based cloud *** attain this,Zscore data normalization is utilized to scale the data into a uniform *** addition,BDDBN model is also exploited for recognition and categorization of *** effectually fine-tune the hyperparameters related to BDDBN model,GrasshopperOptimizationAlgorithm(GOA)is *** scenario enhances the classification results and also shows the novelty of current *** experimental analysis was conducted upon OBDDBN-CMC model for validation and the results confirmed the enhanced performance ofOBDDBNCMC model over recent approaches.

关键词： Malware detection security Internet of Things cloud computing machine learning parameter adjustment

Near real-time characterisation of urban environments: a holistic approach for monitoring dengue fever risk areas

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International Journal of digital Earth 2014年第11期7卷 916-934页

作者： Muhammad Shahzad Sarfraz Nitin Kumar Tripathi Asanobu Kitamoto department of computer Science COMSATS Institute of Information Technology(CIIT)AbbottabadPakistan Remote Sensing and GIS Asian Institute of Technology(AIT)BangkokThailand digital Content and media sciences Research Division National Institute of Informatics(NII)TokyoJapan

Despite frequent use of digital devices in everyday life,cost-effective measurement of public health issues in urban areas is still *** study was,therefore,planned to extract land-use types using object-based and spatial metric approaches to explore the dengue incidence in relation to the surrounding environment in near real-time using Google and Advanced Land Observation Satellite *** characterised image showed useful classification of an urban areawith 77%accuracy and 0.68 *** analysis on public health data indicated that most of the dengue cases were found in densely populated areas surrounded by dense *** living in independent houses having sparsely vegetated surroundings were found to be less *** incidence was more prevalent in people of 5-24 years of age(67%);while in terms of occupation,mostly students,the unemployed,labourers and farmers(88%)were *** general,males were affected slightly more(10%)than *** analyses indicated that most of the dengue cases were around institutions(40%),religious places(18%)and markets(15%).Thus,usage of digital Earth scalable tools for monitoring health issues would open new ways for maintaining a healthy and sustainable society in the years ahead.

关键词： dengue fever land-use land-cover monitoring dengue risk urban environment object-based classification

Metaheuristics Enabled Clustering with Routing Scheme for Wireless Sensor Networks

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computers, Materials & Continua 2022年第12期73卷 5491-5507页

作者： Mashael M.Asiri Saud S.Alotaibi Dalia H.Elkamchouchi Amira Sayed A.Aziz Manar Ahmed Hamza Abdelwahed Motwakel Abu Sarwar Zamani Ishfaq Yaseen department of computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia department of information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia department of information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of digital media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt department of computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Wireless Sensor Network(WSN)is a vital element in Internet of Things(IoT)as the former enables the collection of huge quantities of data in energy-constrained *** offers independent access to the target region and performs data collection in an effective *** energy constraints remain a challenging issue in WSN since it operates on in-built *** studies conducted earlier recommended that the energy spent on communication processmust be considerably reduced to improve the efficiency of *** organization and optimal selection of the routes are considered as NP hard optimization problems which can be resolved with the help of metaheuristic *** and routing are considered as effective approaches in enhancing the energy effectiveness and lifespan of *** this background,the current study develops an Improved Duck and Traveller Optimization(IDTO)-enabled cluster-based Multi-Hop Routing(IDTOMHR)technique for ***,IDTO algorithm is exploited for the selection of Cluster Head(CH)and construction of ***,Artificial Gorilla Troops Optimization(ATGO)technique is also used to derive an optimal set of routes to the *** clustering and routing approaches derive a fitness function with the inclusion of multiple input *** proposed IDTOMHR model was experimentally validated for its performance under different *** extensive experimental results confirmed the better performance of IDTOMHR model over other recent approaches.

关键词： Wireless sensor network clustering routing metaheuristics energy efficiency lifetime