Scalable Computing-Practice and Experience最新文献_第4页

General Layout Planning Model of Landscape Ceramic Sculpture Based on NSGA - Ⅱ Algorithm 基于NSGA -Ⅱ算法的景观陶瓷雕塑总体布局规划模型

Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI: 10.12694/scpe.v24i3.2273

Henan Feng, Liqun Zheng, Shuang Qiao

{"title":"General Layout Planning Model of Landscape Ceramic Sculpture Based on NSGA - Ⅱ Algorithm","authors":"Henan Feng, Liqun Zheng, Shuang Qiao","doi":"10.12694/scpe.v24i3.2273","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2273","url":null,"abstract":"The current overall layout planning model matrix of landscape ceramic sculpture is generally unidirectional, and the planning efficiency is low, resulting in a decline in the layout optimization ratio of the model. Therefore, the design and verification analysis of landscape ceramic sculpture’s overall layout planning model based on the Nondominated Sorting Genetic Algorithm (NSGA - II) algorithm is proposed. According to the actual planning needs and standards, first set the basic layout points, establish a cross-planning matrix in a multi-level manner, and improve the efficiency of the overall layout planning of the sculpture. The NSGA - II calculation landscape ceramic sculpture layout planning structure is constructed on this basis, and the model design is realized by level conversion. This novel NSGA-II with level conversion performs better layout planning when compared with other conventional models. The final test results show that through three stages of layout optimization processing, compared with the initial planning layout, the optimal layout optimization ratio for the setting of the plaza sculpture can reach more than 60%, indicating that with the help of this method, the layout planning of sculpture has been further improved, the space has been expanded, and has practical application value.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136071667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Improving Bert Model Accuracy for Uni-modal Aspect-Based Sentiment Analysis Task 提高Bert模型在单模态基于方面的情感分析任务中的准确性

Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI: 10.12694/scpe.v24i3.2444

Amit Chauhan, Rajni Mohana

{"title":"Improving Bert Model Accuracy for Uni-modal Aspect-Based Sentiment Analysis Task","authors":"Amit Chauhan, Rajni Mohana","doi":"10.12694/scpe.v24i3.2444","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2444","url":null,"abstract":"Techniques and methods for examining users’ feelings, emotions, and views in text or other media are known as ”sentiment analysis,” this phrase is used frequently. In many areas, including marketing and online social media, analysis of user and consumer opinions has always been essential to decision-making processes. The development of new methodologies that concentrate on analysing the sentiment associated with specific product characteristics, such as aspect-based sentiment analysis (ABSA), was prompted by the need for a deeper understanding of these opinions. Despite the growing interest in this field, some misunderstanding exists about ABSA’s core ideas. Even though sentiment, affect, emotion, and opinion refer to various ideas, they are frequently used synonymously. This ambiguity commonly causes user opinions to be analysed incorrectly. This work provides an overview of ABSA and the issue of overfitting. Following this analysis, we improved the model by enhancing the accuracy and F1 score of the existing model by fine-tuning the technique. Our model outperformed the others, achieving the best results for the restaurant dataset with an 85.02 accuracy and a 79.19 F1 score, respectively.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136071672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Scalability and Sustainability in the Construction of a Social Sports Management Information Platform based on Web Technology 基于Web技术的社会体育管理信息平台建设的可扩展性与可持续性

Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI: 10.12694/scpe.v24i3.2382

Mengyan Wu, Yuanyuan Hou, Yueqin Tang

引用次数: 0

Deep Learning-Based Education Decision Support System for Student E-learning Performance Prediction 基于深度学习的学生网络学习绩效预测教育决策支持系统

Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI: 10.12694/scpe.v24i3.2188

Sudha Prathyusha Jakkaladiki, Martina Janečková, Jan Krunčík, Filip Malý, Tereza Otčenášková

{"title":"Deep Learning-Based Education Decision Support System for Student E-learning Performance Prediction","authors":"Sudha Prathyusha Jakkaladiki, Martina Janečková, Jan Krunčík, Filip Malý, Tereza Otčenášková","doi":"10.12694/scpe.v24i3.2188","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2188","url":null,"abstract":"Information Technology (IT) and its advancements change the education environment. Conventional classroom education has been transformed into a modernized form. Education field decision-makers are always searching for new technologies that provide fast solutions to support Education Decision Support Systems (EDSS). There is a significant need for an effective decision support system to utilize student data which helps the university in making the right decisions. The Electronic learning system (e-learning) provides a live forum for faculties and students to connect with learning portals and virtually execute educational activities. Even though these modern approaches support the education system, active student participation still needs to be improved. Moreover, accurately measuring student performance using collected attributes remains difficult for parents and teachers. Therefore, this paper seeks to understand and predict student performance using effective data processing and a deep learning-based decision model. The implementation of EDSS starts with data preprocessing, Extraction-Transformation-Load (ETL), a data mart area to store the extracted data with Online Analytical Processing (OLAP) processing, and decision-making using Deep Graph Convolutional Neural Network (DGCNN). The statistical evaluation is based on the student dataset from the Kaggle repository. The analyzed results depict that the proposed EDSS model on an independent data mart with efficient decision support and OLAP provides a better platform to make academic decisions and help educators to make necessary decisions notified to the students.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136071894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis, Prediction and Classification of Skin Cancer using Artificial Intelligence - A Brief Study and Review 基于人工智能的皮肤癌分析、预测与分类研究综述

Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI: 10.12694/scpe.v24i3.2241

Madhavi Latha Pandala, None S. Periyanayagi

{"title":"Analysis, Prediction and Classification of Skin Cancer using Artificial Intelligence - A Brief Study and Review","authors":"Madhavi Latha Pandala, None S. Periyanayagi","doi":"10.12694/scpe.v24i3.2241","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2241","url":null,"abstract":"World Health Organization (WHO) records that skin cancer has vigorously affected people in recent decades. Worldwide, many people are affected by skin cancer, and its affected count will increase yearly. Hence, skin cancer has become a threatening disease. Skin cancer prediction at an earlier time is becoming the higher priority and most challenging task worldwide. A computer-based diagnosis is needed to perform the automatic prognosis of skin cancer. It assists dermatologists in many ways, including the prediction of skin cancer at the earlier stages, easy to diagnose and effective. Nowadays, artificial intelligence based machine learning approaches have been implemented for an early prediction of cancer in the skin through medical images. This paper is focused on a detailed, comprehensive review of skin cancer analysis, forecast, and algorithmic-based procedures for classifying skin diseases. Moreover, this review paper focused on various stages of algorithm approaches for skin tumor detection like pre-processing data, segmenting data, feature selection, and disease classifier. This detailed review of neoplasm diseases like cancer on the skin is done based on machine and deep learning algorithms to help further research.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136072013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of Improving ABC in Cold Chain Low Carbon Logistics Path Planning 改进作业成本法在冷链低碳物流路径规划中的应用

Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI: 10.12694/scpe.v24i3.2357

Xiazu Bai

{"title":"Application of Improving ABC in Cold Chain Low Carbon Logistics Path Planning","authors":"Xiazu Bai","doi":"10.12694/scpe.v24i3.2357","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2357","url":null,"abstract":"The market has set higher efficiency and environmental requirements for cold chain logistics, and path planning plays an important role. This study proposes a low-carbon cold chain logistics path planning model based on an improved artificial bee colony algorithm (this paragraph refers to ”fusion algorithm”). The study first establishes the fusion algorithm. Then, in response to the shortcomings of this algorithm, the artificial fish swarm algorithm and genetic algorithm are used to improve it. The final results express that the shortest distance for solving Eil51 using this algorithm is 421.38, the longest distance is 448.58, and the average distance is 439.34; The shortest distance for solving Ulysses22 is 72.46, the longest distance is 73.63, and the average distance is 72.84. The average convergence times for Eil51 and Ulysses22 are 133.57 and 7.86, and the optimal performance ratios for relative error are 0.0076 and 0.0051. The robust performance ratios are 0.0362 and 0.0117. The optimal total cost solution and the average value for solving the relevant distribution problem are 47,894.6 yuan and 48,562.7 yuan, respectively. In summary, the model proposed in the study has good application effects in cold chain low-carbon logistics path planning, and has a certain promoting effect on the development of cold chain logistics.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136071685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient Net-based Transfer Learning Technique for Facial Autism Detection 基于网络的高效面部自闭症检测迁移学习技术

Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI: 10.12694/scpe.v24i3.2233

Tariq Saeed Mian

{"title":"Efficient Net-based Transfer Learning Technique for Facial Autism Detection","authors":"Tariq Saeed Mian","doi":"10.12694/scpe.v24i3.2233","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2233","url":null,"abstract":"Autism Spectrum Disorder is a neurological disorder in which an individual faces life-long effects in communication and interaction with others. Nowadays, the Autism Spectrum disorder ratio is increasing drastically more than ever before. Autism can be identified at all developmental levels as a ”behavioural condition,” and its symptoms often arise between the ages of two and four. The ASD issue starts during puberty and persists through adolescence and adulthood. Children with ASD use both nonverbal and verbal behaviour to communicate, and they struggle with joint attention and social reciprocity. Children with autism are frequently socially isolated as a result of these problems. Through very expensive and time-consuming screening exams, autism spectrum features can be identified. As one of the possible mirrors of the brain, children’s faces can be utilised as a biomarker and as a quick and convenient technique for the early identification of ASD. An effective, genuine, and automatic method of face-based spectrum disorder identification is required. In this study we compare the transfer learning approach used for autism identification with the convolutional neural network (CNN)-based efficient-net strategy to identify autistic children using facial images. We used an open-source Kaggle dataset and evaluated the model performance in terms of accuracy, confusion matrix, precision, recall, and F1 measure. Efficient shows an accuracy of 97% on the benchmark dataset and beats the baseline technique of transfer learning-based approaches. This study can be used to help medical professionals validate their initial screening procedures for finding youngsters with ASD disease.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136071903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Big Data in Healthcare - A Comprehensive Bibliometric Analysis of Current Research Trends 医疗保健中的大数据——当前研究趋势的综合文献计量学分析

Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI: 10.12694/scpe.v24i3.2155

Aijaz Reshi, Arif Shah, Shabana Shafi, Majid Hussain Qadri

{"title":"Big Data in Healthcare - A Comprehensive Bibliometric Analysis of Current Research Trends","authors":"Aijaz Reshi, Arif Shah, Shabana Shafi, Majid Hussain Qadri","doi":"10.12694/scpe.v24i3.2155","DOIUrl":"https://doi.org/10.12694/scpe.v24i3.2155","url":null,"abstract":"The primary purpose of this study is to perform a comprehensive bibliometric analysis of research landscape of big data in healthcare. Big data as a significant technology used in healthcare during the past decade has led to the exponential growth in scientific literature. This study is focused on analysis of many crucial bibliometric indicators such as, overall research output, author productivity, institutional productivity, country wise productivity, collaboration analysis, research trends along with a thematic focus of research output in big data and healthcare. The analysis has been performed on 2294 research articles published in 1018 publication sources from SCOPUS and Web of Science databases. The initial results of the study performed from year 2012 reveals that in the first year 6 research articles were published in the given domain. Then every year the growth of published articles in the field was exponential, however years 2019 to 2021 were the most productive and incremental in terms of number of publications. The analysis results of the study present the performance analysis of research production in terms of annual scientific production, most globally cited articles, author’s production over the time, most productive countries, and most relevant affiliations. In addition, the science mapping analysis including the indicators such as, keyword Co-occurrence, Thematic Mapping, Most Relevant Authors, annual source distribution, and collaboration Network analysis has been presented. The study delivers expedient contribution to the field of study by noticeably offering comprehensive analysis results regarding research hotspots and trends, thematic emphasis, and future direction of research in the field. These outcomes will aid researchers in big data and healthcare in planning and designing the research and the challenges and opportunities needed to be explored.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136072017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of Association Rule Mining Algorithm based on 5G Technology in Information Management System 基于5G技术的关联规则挖掘算法在信息管理系统中的应用

IF 1.1

Scalable Computing-Practice and Experience Pub Date : 2023-07-30 DOI: 10.12694/scpe.v24i2.2150

Juan Gao, Zidi Chen

{"title":"Application of Association Rule Mining Algorithm based on 5G Technology in Information Management System","authors":"Juan Gao, Zidi Chen","doi":"10.12694/scpe.v24i2.2150","DOIUrl":"https://doi.org/10.12694/scpe.v24i2.2150","url":null,"abstract":"In this paper, an application method of association rule mining algorithm based on 5G technology in information management system is proposed to solve the problems of long running time and low processing efficiency in traditional financial information processing system. The association rule mining algorithm's employment in information management systems is the main topic of this research study, which is based on 5G technology. The efficiency and efficacy of information management systems have a lot of room to grow with the introduction of 5G. Large datasets may be mined for patterns and associations using the potent approach known as association rule mining. We want to improve the performance of information management systems by fusing association rule mining with the capabilities of 5G technology. The experimental findings indicate that in the first group of trials, the traditional system’s time for information mining is identical to that of the developed system, which is around one minute. The typical system's time to mine financial information, however, steadily grows with the amount of experimental data. The difference between the two is most obvious in the sixth experiment. Because the design system can delve deeply into the financial information, the overall information mining time of the financial information management system based on the association rule mining algorithm of the design is shorter. It is confirmed that the system for automatically processing financial information described in this study has a high level of processing accuracy and a positive processing outcome.","PeriodicalId":43791,"journal":{"name":"Scalable Computing-Practice and Experience","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73234313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research Highlight Generation with ELMo Contextual Embeddings 基于ELMo上下文嵌入的亮点生成研究

IF 1.1

Scalable Computing-Practice and Experience Pub Date : 2023-07-30 DOI: 10.12694/scpe.v24i2.2238

Tohida Rehman, Debarshi Kumar Sanyal, S. Chattopadhyay

引用次数: 1