Over the past few years,the application and usage of Machine Learning(ML)techniques have increased exponentially due to continuously increasing the size of data and computing *** the popularity of ML techniques,only a...
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Over the past few years,the application and usage of Machine Learning(ML)techniques have increased exponentially due to continuously increasing the size of data and computing *** the popularity of ML techniques,only a few research studies have focused on the application of ML especially supervised learning techniques in Requirement engineering(RE)activities to solve the problems that occur in RE *** authors focus on the systematic mapping of past work to investigate those studies that focused on the application of supervised learning techniques in RE activities between the period of 2002–*** authors aim to investigate the research trends,main RE activities,ML algorithms,and data sources that were studied during this ***-five research studies were selected based on our exclusion and inclusion *** results show that the scientific community used 57 *** those algorithms,researchers mostly used the five following ML algorithms in RE activities:Decision Tree,Support Vector Machine,Naïve Bayes,K-nearest neighbour Classifier,and Random *** results show that researchers used these algorithms in eight major RE *** activities are requirements analysis,failure prediction,effort estimation,quality,traceability,business rules identification,content classification,and detection of problems in requirements written in natural *** selected research studies used 32 private and 41 public data *** most popular data sources that were detected in selected studies are the Metric Data Programme from NASA,Predictor Models in Software engineering,and iTrust Electronic Health Care System.
作者:
Hiasat, Ahmad
School of Engineering Computer Engineering Department Amman Jordan
In this work, a new efficient modular adder that deals with modulus (2n-2k-1) is proposed, where n is a positive integer and k is a positive odd integer within the range 1 ≤ k ≤ n-3. The suggested circuit uses the r...
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Due to recent expansion of wireless communications, it has become impossible to cope with the allotment of the precious spectrum while resources for wireless communication are bounded and finite. Hence, the cognitive ...
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Wireless body area networks(WBANs)guarantee timely data processing and secure information preservation within the range of the wireless access network,which is in urgent need of a new type of security ***,with the spe...
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Wireless body area networks(WBANs)guarantee timely data processing and secure information preservation within the range of the wireless access network,which is in urgent need of a new type of security ***,with the speedy development of hardware,the existing security schemes can no longer meet the new requirements of anonymity and *** solutions that do not require complex calculations,such as certificateless cryptography,attract great attention from *** resolve these difficulties,Wang et *** a new authentication architecture for the WBANs environment,which was claimed to be secure and ***,in this paper,we will show that this scheme is prone to ephemeral key leakage ***,based on this authentication scheme,an anonymous certificateless scheme is proposed for lightweight ***,user anonymity is fully *** proposed scheme is proved to be secure under a specific security *** addition,we assess the security attributes our scheme meets through BAN logic and Scyther *** comparisons of time consumption and communication cost are given at the end of the paper,to demonstrate that our scheme performs prior to several previous schemes.
Convolutional Neural Networks (CNNs) have become instrumental in advancing image classification, particularly in the context of garbage image classification, a critical component for efficient waste management. This p...
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Natural Language Processing (NLP) is increasingly pivotal in the natural sciences, with sentiment analysis emerging as a crucial application in the era of big data. Efficiently and accurately extracting meaningful ins...
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Bagging is an essential skill that humans perform in their daily ***,deformable objects,such as bags,are complex for robots to manipulate.A learning-based framework that enables robots to learn bagging is *** novelty ...
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Bagging is an essential skill that humans perform in their daily ***,deformable objects,such as bags,are complex for robots to manipulate.A learning-based framework that enables robots to learn bagging is *** novelty of this framework is its ability to learn and perform bagging without relying on *** learning process is accomplished through a reinforcement learning(RL)algorithm introduced and designed to find the best grasping points of the bag based on a set of compact state *** framework utilises a set of primitive actions and represents the task in five *** our experiments,the framework reached 60% and 80% success rates after around 3 h of training in the real world when starting the bagging task from folded and unfolded states,***,the authors test the trained RL model with eight more bags of different sizes to evaluate its generalisability.
Group testing is a well-studied approach for identifying defective items among a large amount of items by conducting a relatively small number of tests on pools of items. In this paper, we propose a novel method for g...
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Machine learning has emerged as one transformative tool in predicting student academic performance. This study evaluates machine learning models regression in predicting student academic performance. It can be found o...
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Research on voice recognition for African languages is limited due to the scarcity of digital resources for training and adaptation, despite its broad usefulness. The Hausa language, spoken by almost fifty million inh...
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