2023 International Conference on Smart Applications, Communications and Networking (SmartNets)最新文献_第4页

The Development of Smart E-Portfolio Generator System for University students: An SDLC Approach 基于SDLC的大学生智能电子档案生成系统的开发

2023 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2023-07-25 DOI: 10.1109/SmartNets58706.2023.10216270

Ahmed Shuhaiber, Aysha Alkuwaiti, Mera Alremeithi, Hamda Almenhali

{"title":"The Development of Smart E-Portfolio Generator System for University students: An SDLC Approach","authors":"Ahmed Shuhaiber, Aysha Alkuwaiti, Mera Alremeithi, Hamda Almenhali","doi":"10.1109/SmartNets58706.2023.10216270","DOIUrl":"https://doi.org/10.1109/SmartNets58706.2023.10216270","url":null,"abstract":"E-portfolio is a creative tool for documenting, analysing and monitoring students’ learning achievements and milestones. An e-portfolio is a computerized collection of documents and certifications that reflect a university student, such as demos, resources, and accomplishments. Since earning a university degree is not enough anymore and other soft and technical skills and certification are required, it became hard for students and graduates to collect and display their achievements in one environment, especially ones with imposter syndrome. Therefore, an e-portfolio generator system has been proposed to collect, store and display user’s documents and certifications in a dashboard. The methodology followed to develop this system is System Development Life Cycle (SDLC). The E-portfolio generator system is a user-friendly system. It enables the users to upload user documents, live-chat, dashboard creation and receiving alerts. Furthermore, the system will optimize the process of gathering, displaying, and storing user’s data in one dashboard. The research is concluded with conclusions and suggestions for further improvement.","PeriodicalId":301834,"journal":{"name":"2023 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122199185","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 Transfer Learning Application on the Reliability of Psychological Drugs' Comments 迁移学习在心理药物评价信度中的应用

2023 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2023-07-25 DOI: 10.1109/SmartNets58706.2023.10215681

Tarık Üveys Şen, Gokhan Bakal

{"title":"A Transfer Learning Application on the Reliability of Psychological Drugs' Comments","authors":"Tarık Üveys Şen, Gokhan Bakal","doi":"10.1109/SmartNets58706.2023.10215681","DOIUrl":"https://doi.org/10.1109/SmartNets58706.2023.10215681","url":null,"abstract":"As digitalization and the Internet stay emerging concepts by gaining popularity, the accuracy of personal reviews/opinions will be a critical issue. This circumstance also particularly applies to patients taking psychological drugs, where accurate information is crucial for other patients and medical professionals. In this study, we analyze drug reviews from drugs.com to determine the effectiveness of reviews for psychological drugs. Our dataset includes over 200,000 drug reviews, which we labeled as positive, negative, or neutral according to their rating scores. We apply machine learning (ML) models, including Logistic Regression, Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) algorithms, to predict the sentiment class of each review. Our results demonstrate an F1-Weighted score of 85.3% for the LSTM model. However, by applying the transfer learning technique, we further improved the F1 score (nearly 3% increase) obtained by the LSTM model. Our findings proved that there is no contextual difference between the comments made by the patients suffering from psychological or other diseases.","PeriodicalId":301834,"journal":{"name":"2023 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132323004","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

Identification and Classification of Retinal Diseases by Using Deep Learning Models 基于深度学习模型的视网膜疾病识别与分类

2023 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2023-07-25 DOI: 10.1109/SmartNets58706.2023.10215740

Noor B. Khalaf, Hadeel K. Aljobouri, Mohammed S. Najim

{"title":"Identification and Classification of Retinal Diseases by Using Deep Learning Models","authors":"Noor B. Khalaf, Hadeel K. Aljobouri, Mohammed S. Najim","doi":"10.1109/SmartNets58706.2023.10215740","DOIUrl":"https://doi.org/10.1109/SmartNets58706.2023.10215740","url":null,"abstract":"Vision and eye health are crucial for human life; they must be well-preserved to maintain the life of people. Retinal eye diseases for example Diabetic macular edema (DME), Drusen, and Choroidal neovascularization (CNV) conditions are primarily the result of retinal damage, and since the damage to the retina is identified at a late stage, there is nearly no opportunity to reverse the condition and cure it, meaning the patient would likely lose some or all of their vision. Optical Coherence Tomography (OCT) is a powerful scanning technique that uses optical reflection measurements to provide non-invasive cross-sectional imaging of internal biological tissue structures. This will allow ophthalmologists to get a clear view of the posterior part of the eye and diagnose damage to the retina, macula, and optic nerve at an early stage. The proposed work aims to provide a novel model for classification based on deep learning and a free dataset of retinal images obtained from an OCT device is used to automatically classify the various retinal disorders. We demonstrate the architecture of a deep convolutional neural network (CNN), and visual geometry group 16 (VGG-16) compared the performance of pre-trained models and CNN. We suggested CNN architecture achieved 98.3% accuracy, whereas the VGG-16 model achieved 99.28% accuracy.","PeriodicalId":301834,"journal":{"name":"2023 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121302541","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

The Design of a Cough Disease Classification System Using Cube-Transformer 基于立方体变压器的咳嗽病分类系统设计

2023 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2023-07-25 DOI: 10.1109/SmartNets58706.2023.10215518

Y. Chen, Chih-Shun Hsu, Bo-Xuan Yang

{"title":"The Design of a Cough Disease Classification System Using Cube-Transformer","authors":"Y. Chen, Chih-Shun Hsu, Bo-Xuan Yang","doi":"10.1109/SmartNets58706.2023.10215518","DOIUrl":"https://doi.org/10.1109/SmartNets58706.2023.10215518","url":null,"abstract":"Cough is a common symptom of respiratory diseases. Hence, making a correct diagnosis of the respiratory diseases through cough classification is an important issue. The current methods for diagnosing COVID-19 include rapid screening and PCR testing. However, the cost of the above approaches is high and require the contact with patients and there is a risk of infection. Most patients diagnosed with COVID-19 have cough symptoms. Hence, diagnosis based on cough sounds is a cheaper and safer approach. In order to improve the quality of training data, the data conversion method of MFCCs is used in the preprocessing of the data. The target data is extracted from the sound data and then projected into the image data, and the sound is analyzed for the diagnosis of the respiratory diseases. Regarding the AI model for calculating the correlation between different data, the self-attention operation mechanism in Transformer can calculate the degree of the correlation between sequence nodes. Therefore, the Transformer model originally used in the translation field is used as the basis for improvement. Based on the concept of hypercube, a self-attention architecture with hypercube characteristics is proposed, which is named as Cube-Transformer. The Cube-Transformer model is mainly optimized and improved from the self-attention operation mechanism and the Star-Transformer model. The Cube-Transformer model can provide data with different self-attention computation scores on different planes and pay attention to the correlation of different data spaces. The experimental results show that the Cube-Transformer model can learn more feature aspects than the Star-Transformer model does and thus improve the identification accuracy by 1.5%.","PeriodicalId":301834,"journal":{"name":"2023 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"20 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128703564","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

Hardware-Based Error Correction Systems for Hamming Codes: a Review of the Literature 基于硬件的汉明码纠错系统:文献综述

2023 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2023-07-25 DOI: 10.1109/SmartNets58706.2023.10215549

Khawla A. Alnajjar, Abdallah Abushawish, Samreen Ansari

引用次数: 0

Appliances Operation Modes Identification Using States Clustering 使用状态聚类的电器操作模式识别

2023 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2023-07-25 DOI: 10.1109/SmartNets58706.2023.10215762

Abdelkareem Jaradat, Muhamed Alarbi, H. Lutfiyya, Anwar Haque

{"title":"Appliances Operation Modes Identification Using States Clustering","authors":"Abdelkareem Jaradat, Muhamed Alarbi, H. Lutfiyya, Anwar Haque","doi":"10.1109/SmartNets58706.2023.10215762","DOIUrl":"https://doi.org/10.1109/SmartNets58706.2023.10215762","url":null,"abstract":"The increasing cost, energy demand, and environmental issues have led many researchers to find approaches for energy monitoring, and hence energy conservation. The emerging technologies of the Internet of Things (IoT) and Machine Learning (ML) deliver techniques that have the potential to conserve energy and improve the utilization of energy consumption efficiently. Smart Home Energy Management Systems (SHEMSs) have the potential to contribute to energy conservation through the application of Demand Response (DR) in the residential sector. In this paper, the aPpliances opeRation mOdes idenTification using statEs ClusTering (PROTECT) is proposed, a SHEMS analytical component that utilizes the sensed residential disaggregated power consumption in supporting DR by providing consumers with the opportunity to select lighter Appliance Operation Modes (AOMs). The states of an appliance’s Single Usage Profile (SUP) are extracted and reformed into features in terms of clusters of states. These features are then used to identify the AOM used in every occurrence using K-Nearest Neighbors (KNN). AOM identification is considered a basis for many potential smart DR applications within SHEMS, contributing to up to 78% energy reduction for some appliances.","PeriodicalId":301834,"journal":{"name":"2023 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114260254","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

BioEnvsense: A Usable Cybersecurity Framework for Critical Infrastructure BioEnvsense:关键基础设施可用的网络安全框架

2023 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2023-07-25 DOI: 10.1109/SmartNets58706.2023.10215755

Farnaz Farid

{"title":"BioEnvsense: A Usable Cybersecurity Framework for Critical Infrastructure","authors":"Farnaz Farid","doi":"10.1109/SmartNets58706.2023.10215755","DOIUrl":"https://doi.org/10.1109/SmartNets58706.2023.10215755","url":null,"abstract":"Cybersecurity solutions require a multidisciplinary approach, as around 95% of cybersecurity incidents stem from behavioral issues. Insider threats are a significant concern, with 90% of enterprises reporting experiencing such threats. Behavioral-based solutions have been proposed to deal with non-intentional insider threats, which include timely notifications and effective training materials. Biometric-based solutions such as face recognition and fingerprints have also been proposed to minimize such threats. However, there is still a need for new approaches to introduce controls on systems to deal with unpredictable user behavior and states to mitigate such malicious cybersecurity incidents. This work proposes a conceptual framework for determining the emotional states of users using soft biometrics and contextual working conditions using sensors to minimize non-intentional behavioral-based malicious cyber incidents. The framework will measure users' mental and emotional states and environmental conditions and take extra precautions when necessary, such as providing instructions, backups or limiting access. Overall, the proposed framework offers a usable contextual and biometric-based cybersecurity solution that could significantly improve the security of systems and users alike.","PeriodicalId":301834,"journal":{"name":"2023 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125443039","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

Failures to Food, Energy, and Water Systems: Mapping and Simulating Components to Improve Resilience 食物、能源和水系统的故障:映射和模拟组件以提高弹性

2023 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2023-07-25 DOI: 10.1109/SmartNets58706.2023.10215865

Alex Modarresi, J. Symons

引用次数: 1

An empirical study on utilizing online k-means clustering for intrusion detection purposes 基于在线k-均值聚类的入侵检测实证研究

2023 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2023-07-25 DOI: 10.1109/SmartNets58706.2023.10215737

Remah Younisse, Q. A. Al-Haija

{"title":"An empirical study on utilizing online k-means clustering for intrusion detection purposes","authors":"Remah Younisse, Q. A. Al-Haija","doi":"10.1109/SmartNets58706.2023.10215737","DOIUrl":"https://doi.org/10.1109/SmartNets58706.2023.10215737","url":null,"abstract":"K-means clustering is widely used in data mining applications. The k-means algorithm is built to pass over the data to be classified in multiple iterations assuming that the whole data is reachable in every iteration. While the pleasure of having the complete data at a time is not available for online data, the online versions of the k-means clustering have to be used when needed. Online data is a notable pattern extensively used in cybersecurity applications such as intrusion detection systems (IDS). In this work, we develop an unsupervised learning-based IDS using an online k-means clustering algorithm. We also measure the IDS efficiency of clustering highly unbalanced online data generated from an IoT network environment attacked by diverse intrusions and using various cluster centers. Besides, the evaluation process was performed for raw (unnormalized) and normalized data records. The performance of online k-means clustering was compared to offline k-means clustering. The results showed that the online clustering method could operate adequately as the offline k-means clustering, especially when used with normalized data traffic scoring an overall clustering purity of 99% for normal packets and 93% for anomaly packets. Besides, the model peaked at an overall F1 score of 99% for normal packet prediction and 94% for anomaly packet prediction.","PeriodicalId":301834,"journal":{"name":"2023 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124722362","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

Optimal configuration method of edge computing unit considering computing load balancing in fault location of power distribution grid* 考虑配电网故障定位计算负载均衡的边缘计算单元优化配置方法*

2023 International Conference on Smart Applications, Communications and Networking (SmartNets) Pub Date : 2023-07-25 DOI: 10.1109/SmartNets58706.2023.10215962

Peng Wu, Wei Wang, Lanxin Qiu, Yue Yu, Jiming Yao

{"title":"Optimal configuration method of edge computing unit considering computing load balancing in fault location of power distribution grid*","authors":"Peng Wu, Wei Wang, Lanxin Qiu, Yue Yu, Jiming Yao","doi":"10.1109/SmartNets58706.2023.10215962","DOIUrl":"https://doi.org/10.1109/SmartNets58706.2023.10215962","url":null,"abstract":"With the improvement of the automation level of the power distribution grid, millions of power distribution equipment are perceived, and the distribution and usage data is heterogeneous and massive. As a result, real-time fault location is very important to ensure the stable supply of electric energy. In order to improve the emergency repair efficiency of distribution network and comprehensively improve service quality, this paper proposes an optimal configuration method of edge computing unit for fault location in distribution network. First, the optimal number of edges is solved based on the economic and real-time communication indicators. Next, spectral clustering combined with k-means algorithm determines the jurisdiction of each edge. Then, the jurisdiction of the edge is corrected according to the computing load balance of the entire network. Finally, IEEE 33-node and IEEE 69-node systems are used as examples for verification. Simulation results show that compared with the traditional method, the equilibrium of the proposed method is increased by 69. 8%, the total computational load is reduced by 27. 2%, and the rapid location of faults in the distribution network can be better realized, so as to ensure the safe and stable operation of the distribution network.","PeriodicalId":301834,"journal":{"name":"2023 International Conference on Smart Applications, Communications and Networking (SmartNets)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124963423","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