There is an emerging interest in using agile methodologies in Global software Development(GSD)to get the mutual benefits of both *** is currently admired by many development teams as an agile most known meth-odology a...
详细信息
There is an emerging interest in using agile methodologies in Global software Development(GSD)to get the mutual benefits of both *** is currently admired by many development teams as an agile most known meth-odology and considered adequate for collocated *** the same time,stake-holders in GSD are dispersed by geographical,temporal,and socio-cultural *** to the controversial nature of Scrum and GSD,many significant challenges arise that might restrict the use of Scrum in *** conducted a Sys-tematic Literature Review(SLR)by following Kitchenham guidelines to identify the challenges that limit the use of Scrum in GSD and to explore the mitigation strategies adopted by practitioners to resolve the *** validate our reviewfindings,we conducted an industrial survey of 305 *** results of our study are consolidated into a research *** framework represents current best practices and recommendations to mitigate the identified distributed scrum challenges and is validated byfive experts of distributed *** of the expert review were found supportive,reflecting that the framework will help the stakeholders deliver sustainable products by effectively mitigating the identified challenges.
Geographic information system (GIS) has become widespread with the management of geographically-based information, constituting a large part of the new data obtained and produced today in electronic platform. Three-di...
详细信息
As a crucial data preprocessing method in data mining,feature selection(FS)can be regarded as a bi-objective optimization problem that aims to maximize classification accuracy and minimize the number of selected *** c...
详细信息
As a crucial data preprocessing method in data mining,feature selection(FS)can be regarded as a bi-objective optimization problem that aims to maximize classification accuracy and minimize the number of selected *** computing(EC)is promising for FS owing to its powerful search ***,in traditional EC-based methods,feature subsets are represented via a length-fixed individual *** is ineffective for high-dimensional data,because it results in a huge search space and prohibitive training *** work proposes a length-adaptive non-dominated sorting genetic algorithm(LA-NSGA)with a length-variable individual encoding and a length-adaptive evolution mechanism for bi-objective highdimensional *** LA-NSGA,an initialization method based on correlation and redundancy is devised to initialize individuals of diverse lengths,and a Pareto dominance-based length change operator is introduced to guide individuals to explore in promising search space ***,a dominance-based local search method is employed for further *** experimental results based on 12 high-dimensional gene datasets show that the Pareto front of feature subsets produced by LA-NSGA is superior to those of existing algorithms.
In recent years,wearable devices-based Human Activity Recognition(HAR)models have received significant *** developed HAR models use hand-crafted features to recognize human activities,leading to the extraction of basi...
详细信息
In recent years,wearable devices-based Human Activity Recognition(HAR)models have received significant *** developed HAR models use hand-crafted features to recognize human activities,leading to the extraction of basic *** images captured by wearable sensors contain advanced features,allowing them to be analyzed by deep learning algorithms to enhance the detection and recognition of human *** lighting and limited sensor capabilities can impact data quality,making the recognition of human actions a challenging *** unimodal-based HAR approaches are not suitable in a real-time ***,an updated HAR model is developed using multiple types of data and an advanced deep-learning ***,the required signals and sensor data are accumulated from the standard *** these signals,the wave features are *** the extracted wave features and sensor data are given as the input to recognize the human *** Adaptive Hybrid Deep Attentive Network(AHDAN)is developed by incorporating a“1D Convolutional Neural Network(1DCNN)”with a“Gated Recurrent Unit(GRU)”for the human activity recognition ***,the Enhanced Archerfish Hunting Optimizer(EAHO)is suggested to fine-tune the network parameters for enhancing the recognition *** experimental evaluation is performed on various deep learning networks and heuristic algorithms to confirm the effectiveness of the proposed HAR *** EAHO-based HAR model outperforms traditional deep learning networks with an accuracy of 95.36,95.25 for recall,95.48 for specificity,and 95.47 for precision,*** result proved that the developed model is effective in recognizing human action by taking less ***,it reduces the computation complexity and overfitting issue through using an optimization approach.
Deaf people or people facing hearing issues can communicate using sign language(SL),a visual *** works based on rich source language have been proposed;however,the work using poor resource language is still *** other ...
详细信息
Deaf people or people facing hearing issues can communicate using sign language(SL),a visual *** works based on rich source language have been proposed;however,the work using poor resource language is still *** other SLs,the visuals of the Urdu Language are *** study presents a novel approach to translating Urdu sign language(UrSL)using the UrSL-CNN model,a convolutional neural network(CNN)architecture specifically designed for this *** existingworks that primarily focus on languageswith rich resources,this study addresses the challenge of translating a sign language with limited *** conducted experiments using two datasets containing 1500 and 78,000 images,employing a methodology comprising four modules:data collection,pre-processing,categorization,and *** enhance prediction accuracy,each sign image was transformed into a greyscale image and underwent noise *** analysis with machine learning baseline methods(support vectormachine,GaussianNaive Bayes,randomforest,and k-nearest neighbors’algorithm)on the UrSL alphabets dataset demonstrated the superiority of UrSL-CNN,achieving an accuracy of ***,our model exhibited superior performance in Precision,Recall,and F1-score *** work not only contributes to advancing sign language translation but also holds promise for improving communication accessibility for individuals with hearing impairments.
Specific medical data has limitations in that there are not many numbers and it is not *** solve these limitations,it is necessary to study how to efficiently process these limited amounts of *** this paper,deep learn...
详细信息
Specific medical data has limitations in that there are not many numbers and it is not *** solve these limitations,it is necessary to study how to efficiently process these limited amounts of *** this paper,deep learning methods for automatically determining cardiovascular diseases are described,and an effective preprocessing method for CT images that can be applied to improve the performance of deep learning was *** cardiac CT images include several parts of the body such as the heart,lungs,spine,and *** preprocessing step proposed in this paper divided CT image data into regions of interest and other regions using K-means clustering and the Grabcut *** compared the deep learning performance results of original data,data using only K-means clustering,and data using both K-means clustering and the Grabcut *** data used in this paper were collected at Soonchunhyang University Cheonan Hospital in Korea and the experimental test proceeded with IRB *** training was conducted using Resnet 50,VGG,and Inception resnet V2 models,and Resnet 50 had the best accuracy in validation and *** the preprocessing process proposed in this paper,the accuracy of deep learning models was significantly improved by at least 10%and up to 40%.
In recent times,real time wireless networks have found their applicability in several practical applications such as smart city,healthcare,surveillance,environmental monitoring,*** the same time,proper localization of...
详细信息
In recent times,real time wireless networks have found their applicability in several practical applications such as smart city,healthcare,surveillance,environmental monitoring,*** the same time,proper localization of nodes in real time wireless networks helps to improve the overall functioning of *** study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization(IM-EECNL)approach for real-time wireless *** proposed IM-EECNL technique involves two major processes namely node localization and ***,Chaotic Water Strider Algorithm based Node Localization(CWSANL)technique to determine the unknown position of the ***,an Oppositional Archimedes Optimization Algorithm based Clustering(OAOAC)technique is applied to accomplish energy efficiency in the ***,the OAOAC technique derives afitness function comprising residual energy,distance to cluster heads(CHs),distance to base station(BS),and *** performance validation of the IM-EECNL technique is carried out under several aspects such as localization and energy efficiency.A wide ranging comparative outcomes analysis highlighted the improved performance of the IM-EECNL approach on the recent approaches with the maximum packet delivery ratio(PDR)of 0.985.
Retrieval augmented generation (RAG) models, which integrate large-scale pre-trained generative models with external retrieval mechanisms, have shown significant success in various natural language processing (NLP) ta...
详细信息
This study presents a real-time streetlamp detection system using a Raspberry Pi and dashcam, leveraging YOLOv5 and YOLOv8 models. Tested in various conditions, YOLOv8n outperformed YOLOv5n with a mean Average Precisi...
详细信息
Fasttext is a powerful word representation method that creates word representations based on vectors of character n-grams. In this work, we propose a method that utilizes fasttext features for a novel feature engineer...
详细信息
暂无评论