Engineering, Technology & Applied Science Research最新文献_第6页

Improved Whale Optimization Algorithm with Deep Learning-Driven Retinal Fundus Image Grading and Retrieval 基于深度学习的改进鲸鱼优化算法视网膜眼底图像分级与检索

Engineering, Technology & Applied Science Research Pub Date : 2023-10-13 DOI: 10.48084/etasr.6111

Syed Ibrahim Syed Mahamood Shazuli, Arunachalam Saravanan

{"title":"Improved Whale Optimization Algorithm with Deep Learning-Driven Retinal Fundus Image Grading and Retrieval","authors":"Syed Ibrahim Syed Mahamood Shazuli, Arunachalam Saravanan","doi":"10.48084/etasr.6111","DOIUrl":"https://doi.org/10.48084/etasr.6111","url":null,"abstract":"Several Deep Learning (DL) and medical image Machine Learning (ML) methods have been investigated for efficient data representations of medical images, such as image classification, Content-Based Image Retrieval (CBIR), and image segmentation. CBIR helps medical professionals make decisions by retrieving similar cases and images from electronic medical image databases. CBIR needs expressive data representations for similar image identification and knowledge discovery in massive medical image databases explored by distinct algorithmic methods. In this study, an Improved Whale Optimization Algorithm with Deep Learning-Driven Retinal Fundus Image Grading and Retrieval (IWOADL-RFIGR) approach was developed. The presented IWOADL-RFIGR method mainly focused on retrieving and classifying retinal fundus images. The proposed IWOADL-RFIGR method used the Bilateral Filtering (BF) method to preprocess the retinal images, a lightweight Convolutional Neural Network (CNN) based on scratch learning with Euclidean distance-based similarity measurement for image retrieval, and the Least Square Support Vector Machine (LS-SVM) model for image classification. Finally, the IWOA was used as a hyperparameter optimization technique to improve overall performance. The experimental validation of the IWOADL-RFIGR model on a benchmark dataset exhibited better performance than other models.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918457","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

A Novel Framework to Strengthen Early Warning Systems 加强预警系统的新框架

Engineering, Technology & Applied Science Research Pub Date : 2023-10-13 DOI: 10.48084/etasr.6289

Harita Ahuja, Sunita Narang, Rakhi Saxena

引用次数: 0

The Impact of Web Analytics Tools on the Performance of Small and Medium Enterprises 网络分析工具对中小企业绩效的影响

Engineering, Technology & Applied Science Research Pub Date : 2023-10-13 DOI: 10.48084/etasr.6261

Abrar M. Almatrafi, Zahyah H. Alharbi

{"title":"The Impact of Web Analytics Tools on the Performance of Small and Medium Enterprises","authors":"Abrar M. Almatrafi, Zahyah H. Alharbi","doi":"10.48084/etasr.6261","DOIUrl":"https://doi.org/10.48084/etasr.6261","url":null,"abstract":"In the era of data analytics, the use of web analytics tools is widely spread among Small and Medium Enterprises (SMEs), especially in the e-commerce sector, to analyze web usage data and measure website performance due to the several features it provides. Most web analytics studies were conducted based on marketing rather than a managerial point of view. Therefore, there is a necessity to study the impact from a managerial perspective by exploring the impact on financial and non-financial performance and the decision-making process. This study assessed the impact of web analytics tools on the overall performance of SMEs, targeting Saudi SMEs and considering the lack of web analytics studies in this sector in Saudi Arabia. The sample involved eight Saudi SMEs who participated by answering interview questions, which were analyzed using thematic analysis. The findings demonstrated four main themes: the current web analytics tools used by Saudi SMEs, the motivations behind their use, and their impact on SMEs' performance and decision-making. The results showed that these tools positively affect the overall performance of SMEs. Google Analytics (GA) was the tool most used by the sample. Seven motives were discovered that encourage SMEs to use web analytics tools. This study also addressed the common Key Performance Indicators (KPIs) used by the participants. Concerning decision-making, it was found that web analytics tools affected and supported SMEs' decisions. Furthermore, this study evaluated the role of Zid, the Saudi e-commerce platform for data analytics and performance measurement.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135917997","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: 1

A Recommendation Engine Model for Giant Social Media Platforms using a Probabilistic Approach 基于概率方法的大型社交媒体平台推荐引擎模型

Engineering, Technology & Applied Science Research Pub Date : 2023-10-13 DOI: 10.48084/etasr.6325

Aadil Alshammari, Mohammed Alshammari

{"title":"A Recommendation Engine Model for Giant Social Media Platforms using a Probabilistic Approach","authors":"Aadil Alshammari, Mohammed Alshammari","doi":"10.48084/etasr.6325","DOIUrl":"https://doi.org/10.48084/etasr.6325","url":null,"abstract":"Existing recommender system algorithms often find it difficult to interpret and, as a result, to extract meaningful recommendations from social media. Because of this, there is a growing demand for more powerful algorithms that are able to extract information from low-dimensional spaces. One such approach would be the cutting-edge matrix factorization technique. Facebook is one of the most widely used social networking platforms. It has more than one billion monthly active users who engage with each other on the platform by sharing status updates, images, events, and other types of content. Facebook's mission includes fostering stronger connections between individuals, and to that end, the platform employs techniques from recommender systems in an effort to better comprehend the actions and patterns of its users, after which it suggests forming new connections with other users. However, relatively little study has been done in this area to investigate the low-dimensional spaces included within the black box system by employing methods such as matrix factorization. Using a probabilistic matrix factorization approach, the interactions that users have with the posts of other users, such as liking, commenting, and other similar activities, were utilized in an effort to generate a list of potential friends that the user who is the focus of this work may not yet be familiar with. The proposed model performed better in terms of suggestion accuracy in comparison to the original matrix factorization, which resulted in the creation of a recommendation list that contained more correct information.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918772","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

Development of Renewable Energy Sources to Serve Agriculture in Vietnam: A Strategic Assessment using the SWOT Analysis 越南发展可再生能源服务农业:利用SWOT分析的战略评估

Engineering, Technology & Applied Science Research Pub Date : 2023-10-13 DOI: 10.48084/etasr.6211

Dam Xuan Dong, Phap Vu Minh, Nguyen Quang Ninh, Dam Xuan Dinh

{"title":"Development of Renewable Energy Sources to Serve Agriculture in Vietnam: A Strategic Assessment using the SWOT Analysis","authors":"Dam Xuan Dong, Phap Vu Minh, Nguyen Quang Ninh, Dam Xuan Dinh","doi":"10.48084/etasr.6211","DOIUrl":"https://doi.org/10.48084/etasr.6211","url":null,"abstract":"Agriculture plays an important role in the economy of many countries, including Vietnam. Traditional agricultural manufacturing processes are inefficient in energy and material consumption and generate substantial carbon emissions. In recent decades, environmentalists and policymakers have been actively involved in the transition from conventional fossil fuels to renewables. This study investigated the potential Strengths, Weaknesses, Opportunities, and Threats (SWOT) associated with developing Renewable Energy sources to serve agriculture in Vietnam. The results of the analysis revealed that renewable energy sources have numerous strengths, including reducing greenhouse gas (GHG) emissions and the cost of electricity, accessing new technologies, and providing economic benefits to farmers. However, the system also faces several weaknesses and threats, such as policy mechanisms, infrastructure, investment capital, foreign-dependent technologies, and potential environmental impacts. This study provides strategic recommendations to maximize the potential of agrivoltaic systems while mitigating their weaknesses and threats. The findings can help stakeholders make informed decisions and take appropriate actions in the development of renewable energy sources in agriculture.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"288 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135917890","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

Enhanced System Usability Scale using the Software Quality Standard Approach 使用软件质量标准方法的增强系统可用性量表

Engineering, Technology & Applied Science Research Pub Date : 2023-10-13 DOI: 10.48084/etasr.5971

Yarshini Thamilarasan, Raja Rina Raja Ikram, Mashanum Osman, Lizawati Salahuddin, Wan Yaakob Wan Bujeri, Kasturi Kanchymalay

{"title":"Enhanced System Usability Scale using the Software Quality Standard Approach","authors":"Yarshini Thamilarasan, Raja Rina Raja Ikram, Mashanum Osman, Lizawati Salahuddin, Wan Yaakob Wan Bujeri, Kasturi Kanchymalay","doi":"10.48084/etasr.5971","DOIUrl":"https://doi.org/10.48084/etasr.5971","url":null,"abstract":"The objective of this paper is to improve the current System Usability Scale (SUS) and assess its applicability in the context of Learning Management Systems (LMS). The need to evaluate the usability of systems has become increasingly important in today's market, as it can have a significant impact on the user experience. In light of the COVID-19 pandemic, e-learning has become an essential tool for students, making LMS an appropriate research case study. Through a comprehensive literature review, it was discovered that SUS is the most widely used tool for evaluating system usability. However, SUS fails to satisfy some of the usability criteria outlined in ISO 9126 and ISO 9241-11. Therefore, this paper proposes an enhanced SUS model and its conceptual framework to address these limitations. The proposed model was validated using a case study approach, involving subject matter experts and software testing students, who evaluated the reliability of the enhanced SUS. Additionally, the existing and enhanced SUS models were evaluated based on an LMS case study and the results were used to calculate the enhanced SUS's reliability coefficient using Cronbach's alpha. The validation results show that the enhanced SUS has higher reliability with improved quality coverage compared to the original SUS. The proposed model has the potential to enhance the evaluation of system usability and, consequently, improve user experience.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918049","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

Artificial Neural Network Performance Modeling and Evaluation of Additive Manufacturing 3D Printed Parts 增材制造3D打印零件的人工神经网络性能建模与评价

Engineering, Technology & Applied Science Research Pub Date : 2023-10-13 DOI: 10.48084/etasr.6185

Sivarao Subramonian, Kumaran Kadirgama, Abdulkareem Sh. Mahdi Al-Obaidi, Mohd Shukor Mohd Salleh, Umesh Kumar Vatesh, Satish Pujari, Dharsyanth Rao, Devarajan Ramasamy

{"title":"Artificial Neural Network Performance Modeling and Evaluation of Additive Manufacturing 3D Printed Parts","authors":"Sivarao Subramonian, Kumaran Kadirgama, Abdulkareem Sh. Mahdi Al-Obaidi, Mohd Shukor Mohd Salleh, Umesh Kumar Vatesh, Satish Pujari, Dharsyanth Rao, Devarajan Ramasamy","doi":"10.48084/etasr.6185","DOIUrl":"https://doi.org/10.48084/etasr.6185","url":null,"abstract":"This research article presents a comprehensive study on the performance modeling of 3D printed parts using Artificial Neural Networks (ANNs). The aim of this study is to optimize the mechanical properties of 3D printed components through accurate prediction and analysis. The study focuses on the widely employed Fused Deposition Modeling (FDM) technique. The ANN model is trained and validated using experimental data, incorporating input parameters such as temperature, speed, infill direction, and layer thickness to predict mechanical properties including yield stress, Young's modulus, ultimate tensile strength, flexural strength, and elongation at fracture. The results demonstrate the effectiveness of the ANN model with an average error below 10%. The study also reveals the significant impact of process parameters on the mechanical properties of 3D printed parts and highlights the potential for optimizing these parameters to enhance the performance of printed components. The findings of this research contribute to the field of additive manufacturing by providing valuable insights into the optimization of 3D printing processes and facilitating the development of high-performance 3D printed components.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918439","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

Pneumonia Detection in Chest X-Rays using Transfer Learning and TPUs 利用迁移学习和tpu检测胸片中的肺炎

Engineering, Technology & Applied Science Research Pub Date : 2023-10-13 DOI: 10.48084/etasr.6335

Niranjan C. Kundur, Bellary Chiterki Anil, Praveen M. Dhulavvagol, Renuka Ganiger, Balakrishnan Ramadoss

{"title":"Pneumonia Detection in Chest X-Rays using Transfer Learning and TPUs","authors":"Niranjan C. Kundur, Bellary Chiterki Anil, Praveen M. Dhulavvagol, Renuka Ganiger, Balakrishnan Ramadoss","doi":"10.48084/etasr.6335","DOIUrl":"https://doi.org/10.48084/etasr.6335","url":null,"abstract":"Pneumonia is a severe respiratory disease with potentially life-threatening consequences if not promptly diagnosed and treated. Chest X-rays are commonly employed for pneumonia detection, but interpreting the images can pose challenges. This study explores the efficacy of four popular transfer learning models, namely VGG16, ResNet, InceptionNet, and DenseNet, alongside a custom CNN model for this task. The model performance is evaluated using Mean Absolute Error (MAE) as the performance metric. The findings reveal that VGG16 outperforms the other transfer learning models, achieving the lowest MAE (66.19). To optimize the model training process, a distributed training strategy utilizing TensorFlow's TPU (Tensor Processing Unit) strategy is implemented. The custom CNN model is parallelized using TPU's multiple instances available over the cloud, enabling efficient computation parallelization and significantly reducing model training times. The experimental results demonstrate a remarkable decrease of 68.36% and 54.74% in model training times for the CNN model when trained using TPU compared to training on a CPU and GPU, respectively.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135918620","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

A Study regarding the Technical-Economical Optimization of Structural Components for enhancing the Buckling Resistance in Stiffened Cylindrical Shells 提高加劲圆柱壳结构构件抗屈曲性能的技术经济优化研究

Engineering, Technology & Applied Science Research Pub Date : 2023-10-13 DOI: 10.48084/etasr.6135

Maria Tanase, Dragos Gabriel Zisopol, Alexandra Ileana Portoaca

引用次数: 0

Mix Design of Fly Ash and GGBS based Geopolymer Concrete activated with Water Glass 水玻璃活化粉煤灰与GGBS基地聚合物混凝土配合比设计

Engineering, Technology & Applied Science Research Pub Date : 2023-10-13 DOI: 10.48084/etasr.6216

Rajashekar Sangi, Bollapragada Shesha Sreenivas, Kandukuri Shanker

{"title":"Mix Design of Fly Ash and GGBS based Geopolymer Concrete activated with Water Glass","authors":"Rajashekar Sangi, Bollapragada Shesha Sreenivas, Kandukuri Shanker","doi":"10.48084/etasr.6216","DOIUrl":"https://doi.org/10.48084/etasr.6216","url":null,"abstract":"Geopolymer Concrete (GPC) has emerged as an alternative to cement concrete due to its reduced carbon footprint and excellent mechanical properties. However, not much emphasis is made on the development of mix designs using industrial waste. The current study focuses on the mix-design considerations for GPC using fly ash and Ground Granulated Blast Furnace Slag (GGBS). The mix design of GPC involves in selecting materials to produce the desired strength. In this investigation, Water Glass (WG) is used as an activator for the activation of the polymerization reaction. The mix design of GPC is the optimization of a group of various parameters, such as the activator to binder ratio, aggregate to binder ratio, coarse aggregate to fine aggregate ratio, activator concentration, and amount of binder content. The activator to binder ratio affects workability and strength, while the activator concentration influences the polymerization reaction and final strength development. The selection of suitable aggregates plays a vital role in achieving a dense and durable GPC matrix. The mix design for GPC requires a holistic approach that considers the selection of appropriate binders, activators, and aggregates. Proper optimization of these factors can result in excellent strength and durability of the GPC and a reduced carbon footprint. Further research is needed to explore alternative binders, evaluate long-term performance, and establish standardized mix design guidelines for the widespread adoption of GPC in construction.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135917855","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