Metaheuristic approaches in cloud computing have shown significant results due to theirmulti-objective *** approaches are now considering hybridmetaheuristics combining the relative optimized benefits of two or more a...
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Metaheuristic approaches in cloud computing have shown significant results due to theirmulti-objective *** approaches are now considering hybridmetaheuristics combining the relative optimized benefits of two or more algorithms resulting in the least tradeoffs among several *** critical factors such as execution time,throughput time,response time,energy consumption,SLA violations,communication overhead,makespan,and migration time need careful attention while designing such dynamic *** improve such factors,an optimizedmulti-objective hybrid algorithm is being proposed that combines the relative advantages of Cat Swarm Optimization(CSO)with machine learning classifiers such as Support Vector Machine(SVM).The adopted approach is based on SVMone to many classification models of machine learning that performs the classifications of various data format types in the cloud with best *** CSO,grouping phase is used to divide the data files as audio,video,image,and text which is further extended by polynomial Kernel function based on various input features and used for optimized load ***,proposed approach works well and achieved performance efficiency in evaluated QoS metrics such as average energy consumption by 12%,migration time by 9%,and optimization time by 10%,in the presence of competitor baselines.
Biometric verification has become essential to authenticate the individuals in public and private *** several biometrics,iris has peculiar features and its working mechanism is complex in *** recent developments in Ma...
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Biometric verification has become essential to authenticate the individuals in public and private *** several biometrics,iris has peculiar features and its working mechanism is complex in *** recent developments in Machine Learning and Deep Learning approaches enable the development of effective iris recognition *** this motivation,the current study introduces a novel Chaotic Krill Herd with Deep Transfer Learning Based Biometric Iris Recognition System(CKHDTL-BIRS).The presented CKHDTL-BIRS model intends to recognize and classify iris images as a part of biometric *** achieve this,CKHDTL-BIRS model initially performs Median Filtering(MF)-based preprocessing and segmentation for iris *** addition,MobileNetmodel is also utilized to generate a set of useful feature ***,Stacked Sparse Autoencoder(SSAE)approach is applied for *** last,CKH algorithm is exploited for optimization of the parameters involved in SSAE *** proposed CKHDTL-BIRS model was experimentally validated using benchmark dataset and the outcomes were examined under several *** comparison study results established the enhanced performance of CKHDTL-BIRS technique over recent approaches.
University timetabling problems are a yearly challenging task and are faced repeatedly each *** problems are considered nonpolynomial time(NP)and combinatorial optimization problems(COP),which means that they can be s...
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University timetabling problems are a yearly challenging task and are faced repeatedly each *** problems are considered nonpolynomial time(NP)and combinatorial optimization problems(COP),which means that they can be solved through optimization algorithms to produce the aspired optimal *** techniques have been used to solve university timetabling problems,and most of them use optimization *** paper provides a comprehensive review of the most recent studies dealing with concepts,methodologies,optimization,benchmarks,and open issues of university timetabling *** comprehensive review starts by presenting the essence of university timetabling as NP-COP,defining and clarifying the two formed classes of university timetabling:University Course Timetabling and University Examination Timetabling,illustrating the adopted algorithms for solving such a problem,elaborating the university timetabling constraints to be considered achieving the optimal timetable,and explaining how to analyze and measure the performance of the optimization algorithms by demonstrating the commonly used benchmark datasets for the *** is noted that meta-heuristic methodologies are widely used in the ***,recently,multi-objective optimization has been increasingly used in solving such a problem that can identify robust university timetabling ***,trends and future directions in university timetabling problems are *** paper provides good information for students,researchers,and specialists interested in this area of *** challenges and possibilities for future research prospects are also explored.
In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause *** technique rising on daily basis for detecting illness in mag...
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In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause *** technique rising on daily basis for detecting illness in magnetic resonance through pictures is the inspection of ***(computerized)illness detection in medical imaging has found you the emergent region in several medical diagnostic *** diseases that cause death need to be identified through such techniques and technologies to overcome the mortality *** brain tumor is one of the most common causes of *** have already proposed various models for the classification and detection of tumors,each with its strengths and weaknesses,but there is still a need to improve the classification process with improved effi***,in this study,we give an in-depth analysis of six distinct machine learning(ML)algorithms,including Random Forest(RF),Naïve Bayes(NB),Neural Networks(NN),CN2 Rule Induction(CN2),Support Vector Machine(SVM),and Decision Tree(Tree),to address this gap in improving *** the Kaggle dataset,these strategies are tested using classification accuracy,the area under the Receiver Operating Characteristic(ROC)curve,precision,recall,and F1 Score(F1).The training and testing process is strengthened by using a 10-fold cross-validation *** results show that SVM outperforms other algorithms,with 95.3%accuracy.
About 17.5% of adults worldwide are infertile, which emphasizes the urgent need for cutting-edge reproductive healthcare solutions. Based on statistics from June 2023. According to the World Health Organization (WHO),...
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The conception of e-learning is major class and broad area. E-learning measures to the utilization of measured programs and learning. It is embodied internet based learning, computer based learning, virtual rooms and ...
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The massive growth of internet enabled devices increases the users every day active in social media networks. People on social groups getting instant alerts on news, entertainment, education, business and many more. T...
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Number recognition can be an important and necessary challenge because handwritten numbers are not similar in size, thickness, position and direction;this method should consider different difficulties to deal with the...
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作者：
Sii, Jia WeiChan, Chee SengCISiP
Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur Malaysia
We introduce Gorgeous, a diffusion-based generative method that redefines digital makeup application by enabling the generation of creative makeup designs through image prompts. Unlike conventional makeup transfer tec...
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