2023 9th International Conference on Information Technology Trends (ITT)最新文献_第3页

Lightweight Convolutional Network For Automated Photovoltaic Defect Detection 光电缺陷自动检测的轻量级卷积网络

2023 9th International Conference on Information Technology Trends (ITT) Pub Date : 2023-05-24 DOI: 10.1109/ITT59889.2023.10184236

Arsalan Zahid, Muhammad Hussain, Richard Hill, Hussain Al-Aqrabi

引用次数: 1

Smart Irrigation with Recycled Water: A Promising Solution for Sustainable Farming 循环水智能灌溉:可持续农业的一个有希望的解决方案

2023 9th International Conference on Information Technology Trends (ITT) Pub Date : 2023-05-24 DOI: 10.1109/ITT59889.2023.10184258

Ossama H. Embarak, Najmah Aldhanhani, Manal Almansoori, Jawaher Aldarmaki

{"title":"Smart Irrigation with Recycled Water: A Promising Solution for Sustainable Farming","authors":"Ossama H. Embarak, Najmah Aldhanhani, Manal Almansoori, Jawaher Aldarmaki","doi":"10.1109/ITT59889.2023.10184258","DOIUrl":"https://doi.org/10.1109/ITT59889.2023.10184258","url":null,"abstract":"This research aims to investigate the effectiveness of a sensor-based irrigation system in conserving water in agricultural activities. The system uses IoT sensors to detect the humidity, soil moisture, water level, and rain to automate the irrigation process, with a mobile application for remote monitoring and control. Results demonstrated that the sensor-based irrigation system can save up to 60% of water compared to manual irrigation methods, with estimated annual water savings per acre ranging from 1.5 million gallons for surface irrigation to 2.5 million gallons for drip irrigation. The implementation of the system showed a significant reduction in water usage compared to manual irrigation methods, providing an estimated annual water savings of up to 50% per acre. Future work involves integrating machine learning algorithms to optimize irrigation schedules and exploring the use of wireless sensor networks and cloud-based technologies for remote monitoring and control. This research highlights the importance of technology in conserving water resources in agriculture.","PeriodicalId":223578,"journal":{"name":"2023 9th International Conference on Information Technology Trends (ITT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114540705","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

Privacy-Preserving Data Sharing Scheme for E-Health Systems 电子医疗系统中保护隐私的数据共享方案

2023 9th International Conference on Information Technology Trends (ITT) Pub Date : 2023-05-24 DOI: 10.1109/ITT59889.2023.10184235

C. Bourn, Joseph Heirendt, Kamsiyochukwu Ben-Chiobi, Alexander Haastrup, Ahmed B. T. Sherif, M. Elsersy

{"title":"Privacy-Preserving Data Sharing Scheme for E-Health Systems","authors":"C. Bourn, Joseph Heirendt, Kamsiyochukwu Ben-Chiobi, Alexander Haastrup, Ahmed B. T. Sherif, M. Elsersy","doi":"10.1109/ITT59889.2023.10184235","DOIUrl":"https://doi.org/10.1109/ITT59889.2023.10184235","url":null,"abstract":"With the constant threat of cyber attacks and their associated risks, it is more important than ever to have a secure system for uploading, viewing, and sharing patient health data. Hospitals, doctors, nurses, and technicians all have a moral and legal obligation to protect the confidentiality of the patients trusted with their care. For this obligation to be met, there must be a method for both patients and doctors to conduct secure searches over encrypted health records. The scheme proposed in this paper allows doctors and patients to securely search over multiple encrypted files while maintaining the confidentiality and privacy of the patient’s health data. Our proposed scheme utilizes a lightweight modified k-Nearest Neighbor (kNN) algorithm that relies on simple computations rather than complex data transformations, which affords our scheme the functionality of searching over encrypted data while maintaining a low computational overhead. Our performance analysis shows that our scheme is lightweight regarding computation and communication overheads. Additionally, our security and privacy analysis further indicates that our proposed scheme efficiently achieves our security and privacy design goals.","PeriodicalId":223578,"journal":{"name":"2023 9th International Conference on Information Technology Trends (ITT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124446058","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

Vaxina: Decentralized Vaccination Tracking System Vaxina:分散疫苗接种跟踪系统

2023 9th International Conference on Information Technology Trends (ITT) Pub Date : 2023-05-24 DOI: 10.1109/ITT59889.2023.10184231

W. Almobaideen, Mohammad Mohammed

{"title":"Vaxina: Decentralized Vaccination Tracking System","authors":"W. Almobaideen, Mohammad Mohammed","doi":"10.1109/ITT59889.2023.10184231","DOIUrl":"https://doi.org/10.1109/ITT59889.2023.10184231","url":null,"abstract":"With the epidemic of Covid-19, a realisation has come into effect that the healthcare industry requires a more efficient method of storing non-tamperable vaccination certificates as well as sharing them with the relevant parties when required. As such, the need for efficient and secure vaccination tracking has led to the development of decentralized solutions. This paper aims to bring forth a Ethereum platform-based vaccination blockchain certificate system which supports authenticated consensual vaccination certificate sharing through the use of solidity smart contracts. We analyse the system architecture, implementation and evaluation, which will support the system's ability to resolve some of the security issues associated with centralised database systems such as low availability, integrity of the vaccination information as well as confidentiality and privacy of patient medical records. Vaxina system is a real-world implementation of a decentralized vaccination tracking system based on the Ethereum platform. It focuses more on the practical implementation and addresses some of the limitations of the previous proposed systems. It has been implemented and tested on the Ethereum blockchain and is available on GitHub for public use. The paper provides valuable insights for future work in the field of decentralized healthcare solutions.","PeriodicalId":223578,"journal":{"name":"2023 9th International Conference on Information Technology Trends (ITT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114891487","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 Proposed AI Method for Tracking College Students’ Academic Progress 一种用于跟踪大学生学业进步的人工智能方法

2023 9th International Conference on Information Technology Trends (ITT) Pub Date : 2023-05-24 DOI: 10.1109/ITT59889.2023.10184256

H. Allam, Z. Khan, Keletso J. Letsholo, Bharti Pandya, Kavita A. Shah, Jinesh Ahamed

{"title":"A Proposed AI Method for Tracking College Students’ Academic Progress","authors":"H. Allam, Z. Khan, Keletso J. Letsholo, Bharti Pandya, Kavita A. Shah, Jinesh Ahamed","doi":"10.1109/ITT59889.2023.10184256","DOIUrl":"https://doi.org/10.1109/ITT59889.2023.10184256","url":null,"abstract":"Educators face significant challenges in monitoring the academic progress of their students in a particular course. Identifying students who are struggling academically can be a daunting task, but teachers can take proactive steps to provide them with additional support once these students come to their attention. Educational institutions today collect vast amounts of data on students from various sources, but they are constantly seeking innovative ways to leverage this information to enhance their reputation and the quality of their instruction. This research delves into the potential of utilizing machine learning algorithms to effectively track students’ academic progress and notify teachers about those who may be at risk of failing a class. The translated prediction model presents an easily accessible visual representation that enables teachers to promptly implement appropriate interventions. Our proposed approach employs various machine learning techniques to create a predictive model that can identify students who may be at risk early on, thus mitigating factors that could hinder their learning. This could serve as a foundation for future predictive models to aid university educators in optimizing the overall learning process.","PeriodicalId":223578,"journal":{"name":"2023 9th International Conference on Information Technology Trends (ITT)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127603302","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 Comparative Evaluation of Airplane Boarding Strategies with a Novel Method for Sustainable Air Travel 基于可持续航空旅行新方法的登机策略比较评价

2023 9th International Conference on Information Technology Trends (ITT) Pub Date : 2023-05-24 DOI: 10.1109/ITT59889.2023.10184234

Thaeer Kobbaey, Ghazala Bilquise, Ahmad Ali Naqi

引用次数: 0

Using Deep Neural Networks to Predict Performance of Software Applications 使用深度神经网络预测软件应用程序的性能

2023 9th International Conference on Information Technology Trends (ITT) Pub Date : 2023-05-24 DOI: 10.1109/ITT59889.2023.10184272

Shadi Ghaith, Azmi Alazzam

{"title":"Using Deep Neural Networks to Predict Performance of Software Applications","authors":"Shadi Ghaith, Azmi Alazzam","doi":"10.1109/ITT59889.2023.10184272","DOIUrl":"https://doi.org/10.1109/ITT59889.2023.10184272","url":null,"abstract":"It is of paramount importance that software applications stay performant as the number of users increases due to certain predictable events such as sales, promotional campaigns and seasons. Modeling, typically using Queuing Networks, is commonly used to predict the application’s performance characteristics to help in finding the extra required computing resources.Building Queueing Network Models to represent the various hardware and software components is a complex and ad-hoc task due to the lack of generalized models. Additionally, obtaining model parameters, known as Service Demands, is a time consuming inaccurate process. Furthermore, solving such complex models requires the use of slow and resource consuming simulation techniques. Simplifying models and solutions to rectify these issues results of inaccurate predictions leading to wasted computing resources.In this work, we propose the use of Deep Neural Networks to build software application models to predict performance characteristics under varying workloads. Unlike Queuing Networks, Deep Neural Networks are built using well-established generalized approaches. Additionally, their input data can be obtained from the applications performance monitoring data or using typical performance measuring techniques. Finally, solving Deep Neural Networks is way more efficient than the simulation techniques of Queuing Networks.","PeriodicalId":223578,"journal":{"name":"2023 9th International Conference on Information Technology Trends (ITT)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130279453","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

High Performance Cervical Cancer Detection Using Gradient Boosting Algorithm and Bayesian Optimization 基于梯度增强算法和贝叶斯优化的高性能宫颈癌检测

2023 9th International Conference on Information Technology Trends (ITT) Pub Date : 2023-05-24 DOI: 10.1109/ITT59889.2023.10184266

M. Sangeetha, V. Sugumaran, T. Karthick, Jagadeesh Puli

{"title":"High Performance Cervical Cancer Detection Using Gradient Boosting Algorithm and Bayesian Optimization","authors":"M. Sangeetha, V. Sugumaran, T. Karthick, Jagadeesh Puli","doi":"10.1109/ITT59889.2023.10184266","DOIUrl":"https://doi.org/10.1109/ITT59889.2023.10184266","url":null,"abstract":"Early treatment, a higher survival rate, fewer fatalities, and a higher standard of living for individuals who have been diagnosed with the disease are all benefits of cervical cancer screening. It is an important field for study and development because precancerous lesion treatment can help stop the progression of the cancer and stop the onset of cervical cancer. Based on the dataset, this paper provides a method for detecting cervical cancer using a gradient boosting technique. Selected characteristics and preprocessed data were used to train the model. Bayesian optimization was used for hyperparameter tuning to determine the ideal hyperparameter values. Using evaluation criteria such as precision, accuracy, F1-score, recall and AUC-ROC the effectiveness of the model was assessed. The findings demonstrate that the suggested method performed well in detecting cervical cancer, with precision, accuracy, F1-score and recall all exceeding 88%. In addition, the area under the ROC curve was 92% (AUC-ROC). The results show that utilizing the gradient boosting algorithm in conjunction with Bayesian optimization for hyperparameter tweaking on the dataset can be a successful method for detecting cervical cancer. fostering community, dialogue, and outcomes in the fields of leadership development, mentoring, entrepreneurship, and social good in order to support the professional achievement of South Asian women.","PeriodicalId":223578,"journal":{"name":"2023 9th International Conference on Information Technology Trends (ITT)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128114798","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

Towards Classifying File Segments in Memory Using Machine-Learning 基于机器学习的内存文件段分类研究

2023 9th International Conference on Information Technology Trends (ITT) Pub Date : 2023-05-24 DOI: 10.1109/ITT59889.2023.10184243

Mohammed I. Al-Saleh, Akram Alkouz, A. Alarabeyyat, Majed Bouchahma

引用次数: 0

Heart Rate Detection and Estimation System Using Webcam 基于网络摄像头的心率检测与估计系统

2023 9th International Conference on Information Technology Trends (ITT) Pub Date : 2023-05-24 DOI: 10.1109/ITT59889.2023.10184261

Sanjukta Sen, Suvradeep Bala, Gouthaman. P

引用次数: 0