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2023 15th International Conference on Developments in eSystems Engineering (DeSE)最新文献

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Architectural Design and Recommendations for a Smart Wearable Device for Women's Safety 一种用于女性安全的智能可穿戴设备的建筑设计与建议
Pub Date : 2023-01-09 DOI: 10.1109/DeSE58274.2023.10099522
Manahil, Raed M. T. Abdulla, Muhammad Ehsan Rana
The Internet of Things (loT) has lately grown across various applications, drawing much attention to its development. This research proposes to use loT to improve women's safety and ensure a much safer environment for their protection. It proposes to use an loT-based safety system designed to help women in danger or stress by alerting authorities and emergency contacts. The final artefact was derived based on experimental calculations. Multiple testing techniques were applied to check the accuracy and effectiveness of the proposed artefact.
近年来,物联网(loT)在各种应用领域的发展引起了人们的广泛关注。本研究建议使用loT来提高女性的安全性,并确保一个更安全的环境来保护她们。它建议使用一个基于lot的安全系统,旨在通过提醒当局和紧急联系人来帮助处于危险或压力中的女性。在实验计算的基础上推导出最终的伪影。应用了多种测试技术来检查所提出的人工制品的准确性和有效性。
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引用次数: 0
The Role and Potential Applications of Cloud Computing in the Banking Industry 云计算在银行业中的作用和潜在应用
Pub Date : 2023-01-09 DOI: 10.1109/DeSE58274.2023.10099662
Muhammad Ehsan Rana, Lai Zhen Ji
The introduction of cloud computing has altered how IT demands are satisfied. Every chief information officer is focused on cloud computing because it has ushered in a new era in IT. Many banks are now utilising cloud technologies to accomplish their ever-demanding goals. Cloud computing offers business models for providing cutting-edge customer experiences, successful teamwork, improved IT efficiency and faster speed to market. Banks can react to changing business requirements rapidly by using cloud computing. The paper offers a valuable perspective on the potential applications of cloud computing in the banking sector and its various business models, cloud service providers, and adoption challenges.
云计算的引入改变了IT需求的满足方式。每个首席信息官都关注云计算,因为它开创了it的新时代。许多银行现在都在利用云技术来实现他们日益苛刻的目标。云计算为提供尖端的客户体验、成功的团队合作、改进的IT效率和更快的上市速度提供了商业模式。通过使用云计算,银行可以快速响应不断变化的业务需求。本文对云计算在银行业及其各种业务模型、云服务提供商和采用挑战中的潜在应用提供了有价值的观点。
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引用次数: 1
Real- Time Healthcare Monitoring and Treatment System Based Microcontroller with IoT 基于物联网微控制器的实时医疗监测和治疗系统
Pub Date : 2023-01-09 DOI: 10.1109/DeSE58274.2023.10099758
Mohammed K. Awsaj, Y. A. Mashhadany, L. Chaari
Health monitoring systems have achieved great popularity and great importance, especially with the presence of pandemics, large numbers of patients, and a lack of health staff. The presence of sensors on the patient's body to measure blood pressure, body temperature, and heart rate, in addition to room temperature and humidity, constantly supports the specialized medical staff in measuring these indicators. The advantage of these devices is that they are with the patient all the time, and a nurse cannot accompany a patient for this period. In this paper, a health care system is designed and implemented to measure vital signs and room environment temperature and humidity. ESP32 receives the vital signs data from the patient and his room. This information has been sent to the Raspberry Pi 4 where the information was compared to the information provided by the doctor to ensure obtaining the alarm when the measure has a large difference. The system obtains two types of alarms; the first is a medical alarm that accrues when vital signs are high or low from the normal measurements. This alarm calls the medical staff, while the second alarm occurs during a hardware malfunction. The second type of alarm call the technical staff. Testing the system shows that the two types of alarm have been recognized on their occurrence. All these measurements and alarms have been stored in the cloud for patient health monitoring.
卫生监测系统已经获得了极大的普及和重要性,特别是在出现流行病、大量患者和缺乏卫生人员的情况下。除了室内温度和湿度外,患者身上还存在测量血压、体温和心率的传感器,不断支持专业医务人员测量这些指标。这些设备的优点是它们一直和病人在一起,而护士不能在这段时间陪伴病人。本文设计并实现了一套测量人体生命体征和室内环境温湿度的卫生保健系统。ESP32接收来自病人及其房间的生命体征数据。该信息被发送到Raspberry Pi 4,并与医生提供的信息进行比较,以确保在测量值差异较大时获得警报。系统获取两种类型的告警;第一种是当生命体征高于或低于正常测量值时产生的医疗警报。此警报呼叫医务人员,而第二个警报在硬件故障期间发生。第二类报警呼叫技术人员。系统测试表明,两种类型的报警在发生时都能被识别出来。所有这些测量和警报都存储在云中,用于患者健康监测。
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引用次数: 0
An Exploratory Study on the Impact of Hosting Blockchain Applications in Cloud Infrastructures 托管区块链应用对云基础设施影响的探索性研究
Pub Date : 2023-01-09 DOI: 10.1109/DeSE58274.2023.10100137
Terence. Chee, Muhammad Ehsan Rana
Blockchain presents many new examples of delivering a robust audit trail using the distributed ledger. However, some potential issues, especially scalability and privacy, are still ongoing in the blockchain. Fortunately, these issues can be settled by using cloud computing. Cloud computing is an on-demand service that enables consumers to purchase and use IT resources. It saves the consumer's cost as consumers don't have to spend extra on building their on-premises server and providing extra security to the application. Enterprises interested in joining the blockchain flow can run their blockchain in the cloud. Cloud Service Providers (CSPs) provide multiple services such as IaaS, PaaS, SaaS and BaaS that can help a business start its blockchain application. But there are still risks that should be carefully noted. Data leaks and breaching are still possible despite the safety and privacy guarantees. The failure to achieve proper security will have to face massive potential fines. In this research, the authors addressed the impact of utilising the cloud in the blockchain and provided an in-depth understanding of the relationship between blockchain technology and cloud computing.
区块链提供了许多使用分布式账本提供可靠审计跟踪的新示例。然而,一些潜在的问题,特别是可扩展性和隐私,仍然存在于区块链中。幸运的是,这些问题可以通过使用云计算来解决。云计算是一种按需服务,它使消费者能够购买和使用IT资源。它节省了用户的成本,因为用户不必在构建本地服务器和为应用程序提供额外的安全性上花费额外的费用。有兴趣加入区块链流程的企业可以在云中运行区块链。云服务提供商(csp)提供多种服务,如IaaS、PaaS、SaaS和BaaS,可以帮助企业启动其区块链应用程序。但仍有一些风险需要谨慎注意。尽管有安全和隐私保障,数据泄露和破坏仍然是可能的。未能实现适当的安全将面临巨额潜在罚款。在这项研究中,作者讨论了在区块链中利用云的影响,并深入了解了区块链技术与云计算之间的关系。
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引用次数: 0
Identify Type of Lung Infection from Lung Patients X-RAY Image LIVERAGING Computer Vision 利用计算机视觉识别肺部感染患者的x线图像
Pub Date : 2023-01-09 DOI: 10.1109/DeSE58274.2023.10099479
M. Mahyoub, Thomas Coombs, M. Jayabalan, J. Mustafina, A. Hussain
This research proposes a computer vision-based solutions to identify whether a patient is covid19/normal/Pneumonia infected with comparable or better state-of-the-art accuracy. Proposed solution is based on deep learning technique CNN (Convolutional Neural networks) with multiple approaches to cover all open issues. First approach is based on CNN models based on pre-trained models; second approach is to create CNN model from scratch. Experimentation and evaluation of multiple approaches helps in covering all open points and gaps left unattended in related work performed to solve this problem. Based on the experimentation results of both the approaches and study of related work done by other researchers, Both the approaches are equally effective can be recommended for multi-class classification of lung disease.
本研究提出了一种基于计算机视觉的解决方案,以相当或更好的精度识别患者是否感染了covid - 19/正常/肺炎。提出的解决方案基于深度学习技术CNN(卷积神经网络),采用多种方法覆盖所有开放问题。第一种方法是基于CNN模型的预训练模型;第二种方法是从头开始创建CNN模型。对多种方法的试验和评估有助于覆盖为解决这一问题而进行的相关工作中所有未注意到的开放点和空白。根据两种方法的实验结果和其他研究者相关工作的研究,两种方法都是同样有效的,可以推荐用于肺部疾病的多类分类。
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引用次数: 0
Technology-Driven Implementation of Smart Entrances in Public Places During the COVID-19 新冠肺炎疫情期间公共场所智能出入口的技术驱动
Pub Date : 2023-01-09 DOI: 10.1109/DeSE58274.2023.10100044
Moo Chi Yuen, Muhammad Ehsan Rana, Kamalanathan Shanmugam, Raed M. T. Abdulla
This research proposes a smart entrance system to cope with the COVID-19 pandemic in public places. The system can help automate standard operating procedures (SOPs) for checking. The paper focuses on exploring the problem context related to the COVID-19 SOPs for public places. The research on technologies involves using thermal cameras, fingerprint recognition, face recognition, iris recognition, object detection and cloud computing. These technologies can be integrated to provide a more versatile and effective solution. The technological solutions proposed by contemporary researchers are also critically analysed by investigating their advantages and disadvantages.
本研究提出了一种应对新冠肺炎疫情的公共场所智能入口系统。该系统可以帮助自动执行检查的标准操作程序(sop)。本文重点探讨新冠肺炎公共场所标准操作规程的相关问题脉络。技术研究涉及热像仪、指纹识别、人脸识别、虹膜识别、目标检测和云计算。这些技术可以集成在一起,以提供更通用、更有效的解决方案。当代研究人员提出的技术解决方案也通过调查其优点和缺点进行批判性分析。
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引用次数: 0
Intelligent Detection System for Multi-Step Cyber-Attack Based on Machine Learning 基于机器学习的多步网络攻击智能检测系统
Pub Date : 2023-01-09 DOI: 10.1109/DeSE58274.2023.10100226
K. Alheeti, Abdulkareem Alzahrani, Omar Hammad Jasim, Duaa Al-Dosary, Hamsa M. Ahmed, M. Al-Ani
Cyber-attacks involve stifling processes and activities, conciliating data, or restricting data access by carefully modifying computer systems and networks with malware. There has been a significant increase in these types of attacks over time. Due to the rise in complexity and structure, advanced defensive methods are needed. In the face of growing security threats, traditional methods of identifying cyber-attacks are ineffective. In this paper, the intelligent of intrusion a detection system is suggested. Moreover, the suggested system attempts to evaluate the capability of the k-nearest neighbour's algorithm (KNN) in terms of distinguishing between authentic and tampered data. A reliable dataset named the Multi-Step Cyber-Attack Dataset (MSCAD) is utilized to determine the behavior Among the new sorts of attacks. Moreover, 60% of the dataset was utilized for training the model, and a remaining 40% was used for testing. Evaluation metrics like accuracy, precision, recall, and F1 score are used. Experiments suggest that the proposed system-based KNN could enhance detection performance. Moreover, the suggested approach increases detection accuracy while minimizing false alarms.
网络攻击包括通过使用恶意软件仔细修改计算机系统和网络来抑制进程和活动、调和数据或限制数据访问。随着时间的推移,这些类型的攻击显著增加。由于复杂性和结构的增加,需要先进的防御方法。面对日益增长的安全威胁,传统的网络攻击识别方法已经失效。本文对入侵检测系统的智能化提出了建议。此外,建议的系统试图评估k近邻算法(KNN)在区分真实数据和篡改数据方面的能力。利用多步网络攻击数据集(Multi-Step Cyber-Attack dataset, MSCAD)来确定新类型攻击的行为。此外,60%的数据集用于训练模型,其余40%用于测试。评估指标,如准确性、精度、召回率和F1分数被使用。实验表明,基于系统的KNN可以提高检测性能。此外,该方法提高了检测精度,同时最大限度地减少了误报。
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引用次数: 0
Design and Implementation of Algorithmic Stock Trading 算法股票交易的设计与实现
Pub Date : 2023-01-09 DOI: 10.1109/DeSE58274.2023.10100293
Piers Blackmun, Sahar Al-Sudani, D. Al-Jumeily
The act of trading in the financial markets from a discretionary standpoint comes with a vast number of pitfalls that lead to participants achieving poor returns on their investments. With trading being a psychologically intense activity, the paper presents development of trading algorithms that will not only eliminate the psychological barriers to trading but do so in a way that ensures that significant returns on investments are made, with these returns being evaluated by testing the strategies on past historical price data of various assets. Findings noted that the algorithms performances varied depending on the market circumstances with certain strategies only being applicable to either strong or weak market conditions. The implication of these findings opens the door to new discussions since the algorithms developed resided outside of the traditional high frequency trading model which are the most prominent trading applications found on the markets. This unconventional algorithmic approach to the markets verifies a way of obtaining significant returns without the requisite of having low latency, thus enabling one to compete with the more sophisticated algorithms developed and used by the major financial institutions without the need for human intervention or any additional resources.
从自由裁量的角度来看,在金融市场进行交易的行为存在大量陷阱,导致参与者的投资回报率很低。由于交易是一种心理紧张的活动,本文介绍了交易算法的发展,该算法不仅可以消除交易的心理障碍,而且可以确保获得可观的投资回报,这些回报是通过测试各种资产的过去历史价格数据来评估的。研究结果指出,算法的表现因市场环境而异,某些策略仅适用于强弱市场条件。这些发现的含义为新的讨论打开了大门,因为开发的算法位于传统高频交易模型之外,而传统高频交易模型是市场上最突出的交易应用。这种非常规的市场算法方法验证了一种在不需要低延迟的情况下获得可观回报的方法,从而使人们能够在不需要人工干预或任何额外资源的情况下与主要金融机构开发和使用的更复杂的算法竞争。
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引用次数: 0
A comparative Time Series analysis of the different categories of items based on holidays and other events 基于假日和其他事件的不同类别项目的比较时间序列分析
Pub Date : 2023-01-09 DOI: 10.1109/DeSE58274.2023.10099814
Shatha Ghareeb, M. Mahyoub, J. Mustafina
Daily retail sales are impacted by a lot of external factors, holidays and special events are one such category. In general, retail sales are largely impacted by fluctuations in demand hence, it is common for a retailer to run out of stock for some items and overstock the other items and this happens due to the lack of understanding of the actual number of items in demand for a particular item at a particular time of the month. This research work examines the impact of holidays or special events on the sales of a wide category of items using predictive analytics. It is done by performing exploratory data analysis and pre-processing methods followed by feature engineering and information extraction to extract the optimal input parameters to be fed into the model. The dataset is time-series data however, advanced machine learning algorithms are also used along with time-series methods to see if time-series data works well with non-time-series algorithms. Different time-series methods along with gradient boosting and the Facebook prophet model are evaluated in this work, achieving 92.83 % forecast accuracy with the Facebook prophet model. The gradient boosting model performs well with a MAPE value of 22.25% and time-series Holt Winters' additive method provides a MAPE value of 12.84 %. Each of the algorithms provides a good score with this time-series data and an appropriate algorithm can be chosen as per the business need.
日常零售额受到许多外部因素的影响,假日和特殊事件就是其中之一。一般来说,零售销售在很大程度上受到需求波动的影响,因此,零售商经常会出现一些商品缺货而另一些商品积压的情况,这是由于缺乏对每月特定时间特定商品的实际需求数量的了解而发生的。这项研究工作考察了假期或特殊事件对使用预测分析的各种物品的销售的影响。它是通过探索性的数据分析和预处理方法,然后进行特征工程和信息提取,以提取最优的输入参数馈送到模型中。数据集是时间序列数据,但是,先进的机器学习算法也与时间序列方法一起使用,以查看时间序列数据是否与非时间序列算法一起工作。本文对不同的时间序列方法以及梯度增强和Facebook先知模型进行了评估,Facebook先知模型的预测准确率达到了92.83%。梯度增强模型的MAPE值为22.25%,时间序列Holt Winters的加性方法的MAPE值为12.84%。每种算法都能很好地处理这些时间序列数据,并且可以根据业务需要选择合适的算法。
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引用次数: 1
Identifying a Student as a Subject of Educational Activity: Methodology and Web-based Application 将学生确定为教育活动的主体:方法和基于网络的应用
Pub Date : 2023-01-09 DOI: 10.1109/DeSE58274.2023.10100140
N. Chernova, R. Akhunzyanova, Abbas Alatrani, J. Mustafina
The purpose of the article is to outline the core concepts of a subject intension, molding and development, being also important to the intensification of AI-enhanced university education. Cognitive development clearly suggests that it is inseparably linked with speech intellectual activity and because of it is reality reflection as if refracted in the light of linguistic meaning. The developed program reflects the logic of the teacher's activities in the formation of a student's personal qualities [participating in subject-subject relations; participating in a joint, discursive practice on the part of all participants, which leads to the active transformation of the students' “Image of the World”; contribution to the development of self-regulation, that is, the capacity for independent problem solving and self-directed activity]. This program is intended by the authors for estimating the accomplished results with the use of any textbook and course in any subject on condition of changing test materials for such a factor attribute as the quality of knowledge in the subject. This teaching methodology is more flexible and means developing a sensitivity to students' current abilities.
本文旨在概述学科内涵、塑造和发展的核心概念,对加强高校人工智能教育具有重要意义。认知发展清楚地表明,它与言语智力活动有着不可分割的联系,因为它是现实的反映,就像在语言意义的光中折射出来的一样。开发的程序反映了教师活动在学生个人素质形成中的逻辑[参与主体-主体关系];所有参与者都参与到共同的话语实践中,从而导致学生“世界形象”的主动转变;促进自我调节的发展,即独立解决问题和自我指导活动的能力]。这个程序的目的是由作者估计完成的结果与使用任何教科书和课程在任何科目的条件下,改变测试材料的因素属性,如知识的质量,在这个主题。这种教学方法更加灵活,意味着培养对学生当前能力的敏感度。
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引用次数: 0
期刊
2023 15th International Conference on Developments in eSystems Engineering (DeSE)
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