Pub Date : 2023-06-08DOI: 10.1109/HORA58378.2023.10156679
Mohammed Y. Al-khuzaie, S. Zearah, Noor J. Mohammed
Acute lymphoblastic leukemia (ALL) is a form of blood cancer that affects the lymphoid cells, leading to the excessive proliferation of immature lymphocytes. A pathologist typically examines the bone marrow to recognize the specific type of leukemia cells present. However, This time-honoured approach takes a lot of effort and time and may not always yield accurate results due to variations in specialist expertise. As a result, there is a need for automated methods that can increase efficiency and accuracy in identifying leukemia cells. Deep learning techniques have shown promise in this regard, as they can analyze images of leukemia cells and make predictions about their type. In our study, we utilized the VGG19 convolutional neural network (CNN) model to analyze images from the ALL-IDB-1 dataset of ALL. Our results demonstrate a remarkable accuracy rate of 99.49%, indicating that our proposed model outperformed other tested models in simplicity and performance. These findings suggest that machine learning and deep learning techniques may offer an effective way to streamline the identification of leukemia cells and improve patient outcome.
{"title":"Developing an efficient VGG19-based model and transfer learning for detecting acute lymphoblastic leukemia (ALL)","authors":"Mohammed Y. Al-khuzaie, S. Zearah, Noor J. Mohammed","doi":"10.1109/HORA58378.2023.10156679","DOIUrl":"https://doi.org/10.1109/HORA58378.2023.10156679","url":null,"abstract":"Acute lymphoblastic leukemia (ALL) is a form of blood cancer that affects the lymphoid cells, leading to the excessive proliferation of immature lymphocytes. A pathologist typically examines the bone marrow to recognize the specific type of leukemia cells present. However, This time-honoured approach takes a lot of effort and time and may not always yield accurate results due to variations in specialist expertise. As a result, there is a need for automated methods that can increase efficiency and accuracy in identifying leukemia cells. Deep learning techniques have shown promise in this regard, as they can analyze images of leukemia cells and make predictions about their type. In our study, we utilized the VGG19 convolutional neural network (CNN) model to analyze images from the ALL-IDB-1 dataset of ALL. Our results demonstrate a remarkable accuracy rate of 99.49%, indicating that our proposed model outperformed other tested models in simplicity and performance. These findings suggest that machine learning and deep learning techniques may offer an effective way to streamline the identification of leukemia cells and improve patient outcome.","PeriodicalId":247679,"journal":{"name":"2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122480987","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}
Pub Date : 2023-06-08DOI: 10.1109/HORA58378.2023.10156675
Modher Almufti, R. Sellami, Lamia Hadrich Belguith
E-governments in developing countries should seek to keep pace with the rapid technology development in order to improve their systems and provide better services to citizens through the governments' portals with minimal effort and time. However, many developing countries, particularly most Arabic countries, face many e-government implementation and adoption challenges. The citizen's adoption is still beyond the ambition despite utilizing several models to understand the factors affecting the user's intention to use the e-government services. All the models did not consider the external factors that may hinder the citizen adoption process. This study proposes a new conceptual model based on integrating the unified theory of technology acceptance and use (UTAUT) with the external factors represented by the PEST framework. This model helps to understand the effect of the specific factors related to user's perception in addition to the external factors that may play a significant importance in shaping the intentions and behavior of e-government users.
{"title":"Towards A Conceptual Model for Citizen's Adoption of E-Government Services in Developing Countries","authors":"Modher Almufti, R. Sellami, Lamia Hadrich Belguith","doi":"10.1109/HORA58378.2023.10156675","DOIUrl":"https://doi.org/10.1109/HORA58378.2023.10156675","url":null,"abstract":"E-governments in developing countries should seek to keep pace with the rapid technology development in order to improve their systems and provide better services to citizens through the governments' portals with minimal effort and time. However, many developing countries, particularly most Arabic countries, face many e-government implementation and adoption challenges. The citizen's adoption is still beyond the ambition despite utilizing several models to understand the factors affecting the user's intention to use the e-government services. All the models did not consider the external factors that may hinder the citizen adoption process. This study proposes a new conceptual model based on integrating the unified theory of technology acceptance and use (UTAUT) with the external factors represented by the PEST framework. This model helps to understand the effect of the specific factors related to user's perception in addition to the external factors that may play a significant importance in shaping the intentions and behavior of e-government users.","PeriodicalId":247679,"journal":{"name":"2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"267 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123056681","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}
Pub Date : 2023-06-08DOI: 10.1109/HORA58378.2023.10156658
Vassil Milev, Georgi Shipkovenski, D. Valcheva, Teodor Kalushkov, E. Petkov
This paper offers a solution for storing of data models, based on data building blocks. The aim of the developed application is to store conceptual models of data, created from database developers. The stored models of data, described and categorized with data building blocks, can be of substantial help for the developers during creation process of new data models, properly covering the organization's activities. The usage of conceptual models, described with data building blocks can optimize and ease the database design process, as it allows developers to use predefined and optimized building blocks to build their models. This makes the application a helpful tool in creating organizational databases. The results from the work with the application show, that it can be an effective solution for creation and storing various data models.
{"title":"Development and Storage of Data Models Based on Data Building Blocks","authors":"Vassil Milev, Georgi Shipkovenski, D. Valcheva, Teodor Kalushkov, E. Petkov","doi":"10.1109/HORA58378.2023.10156658","DOIUrl":"https://doi.org/10.1109/HORA58378.2023.10156658","url":null,"abstract":"This paper offers a solution for storing of data models, based on data building blocks. The aim of the developed application is to store conceptual models of data, created from database developers. The stored models of data, described and categorized with data building blocks, can be of substantial help for the developers during creation process of new data models, properly covering the organization's activities. The usage of conceptual models, described with data building blocks can optimize and ease the database design process, as it allows developers to use predefined and optimized building blocks to build their models. This makes the application a helpful tool in creating organizational databases. The results from the work with the application show, that it can be an effective solution for creation and storing various data models.","PeriodicalId":247679,"journal":{"name":"2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129684268","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}
Pub Date : 2023-06-08DOI: 10.1109/HORA58378.2023.10156713
A. J. Haleel, L. Dawood
Modern-day maintenance scheduling is a complex optimization problem that combines resource constraints, uncertain environments, and critical times. With more applications and recent advances in artificial intelligence techniques, a review is needed to collate and categorize these advances in the Maintenance domain. The purpose of This study aims to provide an overview of artificial intelligence techniques that have been used to solve maintenance schedule optimization problems. Based on the publications from three databases, IEEE explore, springer link, and science direct for the time frame from 2010-2022 the review process identified 130 publications in maintenance scheduling optimization terms. A total of 37 publications that used AI techniques to optimize maintenance scheduling were selected in this work. The results of this work will enable researchers to gain a good overview of the existing AI tools used in maintenance scheduling optimization problems for the different application domains.
{"title":"Maintenance Scheduling Optimization using Artificial Intelligence Techniques: A Review","authors":"A. J. Haleel, L. Dawood","doi":"10.1109/HORA58378.2023.10156713","DOIUrl":"https://doi.org/10.1109/HORA58378.2023.10156713","url":null,"abstract":"Modern-day maintenance scheduling is a complex optimization problem that combines resource constraints, uncertain environments, and critical times. With more applications and recent advances in artificial intelligence techniques, a review is needed to collate and categorize these advances in the Maintenance domain. The purpose of This study aims to provide an overview of artificial intelligence techniques that have been used to solve maintenance schedule optimization problems. Based on the publications from three databases, IEEE explore, springer link, and science direct for the time frame from 2010-2022 the review process identified 130 publications in maintenance scheduling optimization terms. A total of 37 publications that used AI techniques to optimize maintenance scheduling were selected in this work. The results of this work will enable researchers to gain a good overview of the existing AI tools used in maintenance scheduling optimization problems for the different application domains.","PeriodicalId":247679,"journal":{"name":"2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"349 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131146023","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}
Pub Date : 2023-06-08DOI: 10.1109/HORA58378.2023.10156665
M. Mustafa, A. A. Khalifa, Korhan Cengiz
The body sensor network plays a vital role in the analysis of the gait analysis of human, sensing the various events happening in the human body. The communication that takes place between the sensed device and the processing system is very important in which the nodes worn on the human body communicate with the sink node placed in the center of the human body. A wireless communication mechanism TDMA was used and the results gave around 60 percent reliability among the nodes. The dynamic TDMA gave a reliability of 90 percent and retransmission mechanism of 95 percent. Our research work focused on to improve the reliability between the nodes and to develop an application for the users to retrieve the data from the sink node. A Symmetric TDMA algorithm was used in which the reliability was increased up to 2 percent resulted in 97 percent. Also, a Bayesian model was developed to identify the probability of nodes initiating to transmit at the same time. The model proved that the chances of nodes transmitting at the same time are 8 percent when comparing to all other techniques. The reliability of the network was also increased. Further, the work will be developed to bring the security concepts into the transmission of data packets, so that the loss can be minimized.
{"title":"A Symmetric TDMA Mechanism to Optimize the Performance of the Body Sensor Network for Sports Application","authors":"M. Mustafa, A. A. Khalifa, Korhan Cengiz","doi":"10.1109/HORA58378.2023.10156665","DOIUrl":"https://doi.org/10.1109/HORA58378.2023.10156665","url":null,"abstract":"The body sensor network plays a vital role in the analysis of the gait analysis of human, sensing the various events happening in the human body. The communication that takes place between the sensed device and the processing system is very important in which the nodes worn on the human body communicate with the sink node placed in the center of the human body. A wireless communication mechanism TDMA was used and the results gave around 60 percent reliability among the nodes. The dynamic TDMA gave a reliability of 90 percent and retransmission mechanism of 95 percent. Our research work focused on to improve the reliability between the nodes and to develop an application for the users to retrieve the data from the sink node. A Symmetric TDMA algorithm was used in which the reliability was increased up to 2 percent resulted in 97 percent. Also, a Bayesian model was developed to identify the probability of nodes initiating to transmit at the same time. The model proved that the chances of nodes transmitting at the same time are 8 percent when comparing to all other techniques. The reliability of the network was also increased. Further, the work will be developed to bring the security concepts into the transmission of data packets, so that the loss can be minimized.","PeriodicalId":247679,"journal":{"name":"2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134388317","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}
Pub Date : 2023-06-08DOI: 10.1109/HORA58378.2023.10156706
Ahmet Said Dedeoğlu, Serkan Özbay, Orhan Tunç
An accurate segmentation of the maxillary sinus (MS) is crucial for the preoperative planning of MS-related surgeries and for preventing postoperative complications. Manual segmentation is challenging, time-consuming, and highly dependent on the practitioner's experience. Therefore, it is not applicable for clinical practice, and accurate, efficient automatic segmentation of MS is required. Convolutional neural networks (CNNs) have recently become the most preferred method for automatic medical image segmentation. In this study, an automatic MS segmentation model based on a convolutional neural network model, U-Net, is proposed. Instead of using the original U-Net encoder, the VGG16 network pre-trained with the ImageNet dataset, apart from the fully connected layers, was used as the encoder of the U-Net architecture to improve the segmentation accuracy. Furthermore, during the training period, models were also trained with focal dice loss (FDL), an equally weighted combination of dice loss (DL) and focal loss, to overcome the imbalanced dataset. The segmentation model based on U-Net with a VGG16 encoder trained with FDL obtained the best results with a dice similarity coefficient (DSC) of 0.93253 and an Intersection over Union (IoU) of 0.88775 on the test dataset.
上颌窦(MS)的准确分割对于MS相关手术的术前规划和预防术后并发症至关重要。手动分割具有挑战性，耗时，并且高度依赖于从业者的经验。因此并不适用于临床实践，需要对质谱进行准确、高效的自动分割。近年来，卷积神经网络(cnn)已成为医学图像自动分割的首选方法。本文提出了一种基于卷积神经网络模型U-Net的MS自动分割模型。利用ImageNet数据集预训练的VGG16网络作为U-Net架构的编码器，而不是使用原始的U-Net编码器，以提高分割精度。此外，在训练期间，模型还使用focal dice loss (FDL)进行训练，FDL是骰子损失(DL)和焦点损失的等加权组合，以克服数据集的不平衡。使用FDL训练的VGG16编码器的U-Net分割模型在测试数据集上获得了最佳分割效果，其骰子相似系数(DSC)为0.93253，交集/联合(IoU)为0.88775。
{"title":"Automatic Segmentation of Maxillary Sinus with U-Net Model with Pre-trained Encoder","authors":"Ahmet Said Dedeoğlu, Serkan Özbay, Orhan Tunç","doi":"10.1109/HORA58378.2023.10156706","DOIUrl":"https://doi.org/10.1109/HORA58378.2023.10156706","url":null,"abstract":"An accurate segmentation of the maxillary sinus (MS) is crucial for the preoperative planning of MS-related surgeries and for preventing postoperative complications. Manual segmentation is challenging, time-consuming, and highly dependent on the practitioner's experience. Therefore, it is not applicable for clinical practice, and accurate, efficient automatic segmentation of MS is required. Convolutional neural networks (CNNs) have recently become the most preferred method for automatic medical image segmentation. In this study, an automatic MS segmentation model based on a convolutional neural network model, U-Net, is proposed. Instead of using the original U-Net encoder, the VGG16 network pre-trained with the ImageNet dataset, apart from the fully connected layers, was used as the encoder of the U-Net architecture to improve the segmentation accuracy. Furthermore, during the training period, models were also trained with focal dice loss (FDL), an equally weighted combination of dice loss (DL) and focal loss, to overcome the imbalanced dataset. The segmentation model based on U-Net with a VGG16 encoder trained with FDL obtained the best results with a dice similarity coefficient (DSC) of 0.93253 and an Intersection over Union (IoU) of 0.88775 on the test dataset.","PeriodicalId":247679,"journal":{"name":"2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132386510","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}
Pub Date : 2023-06-08DOI: 10.1109/HORA58378.2023.10156684
Poom Separattananan, Jetnipat Thongprasith, Phumrapee Meyer, R. Chancharoen
Robots will become far more integral to human daily life in the future. In particular, the robot is used in various types of tasks in the food industry, for example, the partition of chicken breast. Applying robots is the solution to optimizing the production process because the traditional method, which is operated by human labor, is prone to error. The objective of this paper is to design and develop the robotic application to control the IAI Robot and depth camera for slicing a solid, which represents a chicken breast, into equal-mass slices perpendicular to the x-axis. The robotic application consists of four procedures: the settings of the operating system, the point cloud capture and transformation, the solid slicing algorithm, and the robot operation. Furthermore, we designed an experiment to estimate the error of each slice that is sliced using this developed robotic application. In terms of conclusion, the developed robotic application can be applied according to the objective of this paper, where the average percentage of error of a slice that is sliced from 100 grams of solid into two, three, and four equal-mass slices is approximately 0.77%, 2.64%, and 3.67%, respectively.
{"title":"Design of the Robot Application for Slicing Food into Equal-Mass Slices","authors":"Poom Separattananan, Jetnipat Thongprasith, Phumrapee Meyer, R. Chancharoen","doi":"10.1109/HORA58378.2023.10156684","DOIUrl":"https://doi.org/10.1109/HORA58378.2023.10156684","url":null,"abstract":"Robots will become far more integral to human daily life in the future. In particular, the robot is used in various types of tasks in the food industry, for example, the partition of chicken breast. Applying robots is the solution to optimizing the production process because the traditional method, which is operated by human labor, is prone to error. The objective of this paper is to design and develop the robotic application to control the IAI Robot and depth camera for slicing a solid, which represents a chicken breast, into equal-mass slices perpendicular to the x-axis. The robotic application consists of four procedures: the settings of the operating system, the point cloud capture and transformation, the solid slicing algorithm, and the robot operation. Furthermore, we designed an experiment to estimate the error of each slice that is sliced using this developed robotic application. In terms of conclusion, the developed robotic application can be applied according to the objective of this paper, where the average percentage of error of a slice that is sliced from 100 grams of solid into two, three, and four equal-mass slices is approximately 0.77%, 2.64%, and 3.67%, respectively.","PeriodicalId":247679,"journal":{"name":"2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130272635","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}
Pub Date : 2023-06-08DOI: 10.1109/HORA58378.2023.10156791
E. Iseri, K. Uyar, Umit Ilhan
Accessibility is the process of making information and electronic communication environments meaningful and usable for most people including those with disabilities. It is not always an easy task to provide all user communities with different areas of interests and needs with exact styles and contents. It is a good practice to employ responsible designs and a certain degree of interaction that provide equitable conditions to suit the needs of the most user communities. It became evident that in the passed two years the world went thru a terrifying Coronavirus disease which made the accessibility of web sites of retailers even more challenging. Most of the food supplying companies introduced shop-to door deliveries of food products with web based applications. Although, technically speaking, these web sites accomplished the task for most of the people but with some accessibility issues. These issues can be identified and solved by following the international standards to gain world wide acceptance. This study covers the investigation of the accessibility of the Food Retailers' websites in the whole of Cyprus Island. Web Content Accessibility Guidelines 2.1 (WCAG 2.1) published by the World Wide Web Consortium (W3C) is followed in the process. Three testing software are used to determine the degree of compliance of the food retailers with the WCAG 2.1 in Cyprus Island. The aim of this study is to raise awareness about web accessibility among general public. The findings are not so promising and the sites examined are not in compliance with the standard of the guidelines defined in WCAG.
{"title":"Web Accessibility of the Cyprus Island Food Retailers' Websites","authors":"E. Iseri, K. Uyar, Umit Ilhan","doi":"10.1109/HORA58378.2023.10156791","DOIUrl":"https://doi.org/10.1109/HORA58378.2023.10156791","url":null,"abstract":"Accessibility is the process of making information and electronic communication environments meaningful and usable for most people including those with disabilities. It is not always an easy task to provide all user communities with different areas of interests and needs with exact styles and contents. It is a good practice to employ responsible designs and a certain degree of interaction that provide equitable conditions to suit the needs of the most user communities. It became evident that in the passed two years the world went thru a terrifying Coronavirus disease which made the accessibility of web sites of retailers even more challenging. Most of the food supplying companies introduced shop-to door deliveries of food products with web based applications. Although, technically speaking, these web sites accomplished the task for most of the people but with some accessibility issues. These issues can be identified and solved by following the international standards to gain world wide acceptance. This study covers the investigation of the accessibility of the Food Retailers' websites in the whole of Cyprus Island. Web Content Accessibility Guidelines 2.1 (WCAG 2.1) published by the World Wide Web Consortium (W3C) is followed in the process. Three testing software are used to determine the degree of compliance of the food retailers with the WCAG 2.1 in Cyprus Island. The aim of this study is to raise awareness about web accessibility among general public. The findings are not so promising and the sites examined are not in compliance with the standard of the guidelines defined in WCAG.","PeriodicalId":247679,"journal":{"name":"2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132220047","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}
Pub Date : 2023-06-08DOI: 10.1109/HORA58378.2023.10156697
P. Goswami, G. Goswami, Hussain Falih Mahdi, A. Vaish, B. Dewangan, T. Choudhury
Internet of things is the most emergent technology, expanding interconnected device networks day by day to enhance the ease of device control and monitoring. IoTs are not covering the commercial utility but also providing emergency benefits to health care centres too. The extensive number of device connections over a network challenges a huge cost of operation management. The most recent research activity deals with anomaly detection in IoT networks over wide IoT networks. The automatic malfunctioning over the network is the most tedious task for researchers. The real-world IoT system analysis motivates this work to identify the anomalies in wireless networks. The link layer is selected to analyse, identifies and detect the wireless network anomalies. A comprehensive review on the performance threshold of machine learning-based algorithms is presented for automatic detection.
{"title":"ML-based Anomalies Detection in Wireless Network Link Layer of the Internet of Things (IoT)","authors":"P. Goswami, G. Goswami, Hussain Falih Mahdi, A. Vaish, B. Dewangan, T. Choudhury","doi":"10.1109/HORA58378.2023.10156697","DOIUrl":"https://doi.org/10.1109/HORA58378.2023.10156697","url":null,"abstract":"Internet of things is the most emergent technology, expanding interconnected device networks day by day to enhance the ease of device control and monitoring. IoTs are not covering the commercial utility but also providing emergency benefits to health care centres too. The extensive number of device connections over a network challenges a huge cost of operation management. The most recent research activity deals with anomaly detection in IoT networks over wide IoT networks. The automatic malfunctioning over the network is the most tedious task for researchers. The real-world IoT system analysis motivates this work to identify the anomalies in wireless networks. The link layer is selected to analyse, identifies and detect the wireless network anomalies. A comprehensive review on the performance threshold of machine learning-based algorithms is presented for automatic detection.","PeriodicalId":247679,"journal":{"name":"2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133192456","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}
Pub Date : 2023-06-08DOI: 10.1109/HORA58378.2023.10156715
Rahaf Adam Alnuaimi, Ranem Khaled Almasalmeh, Sarah A. Baker, Maryam Nasser Alsaiaari, Moatsum Alawida
In this paper, we aim to solve critical issues organizations face during attendance monitoring. Conventional log-in systems fail to effectively ensure successful attendance monitoring, and challenges such as user manipulation, social distancing making biometric devices obsolete, and other issues arise. To address these challenges, we propose a two-factor authentication system based on distance and face recognition. The system incorporates advanced geo-tracking tools and technologies with web3 features and double-factor authentication using face recognition technologies and accompanying distance monitoring devices and tools. Our system provides secure, adaptive, and advanced log-ins for employees and attendance monitoring for employers. The proposed system is scalable by simply accompanying more distance-tracking devices with no additional support systems required. It is a smart, user-friendly, and effective log-in system designed to optimize resource and time allocation for any organization. Compared to other two-factor authentication systems, our system is faster, more secure, and does not require central devices. It is also more friendly and flexible, offering a viable solution for maintaining a safe environment and easing procedures for employees and managers.
{"title":"Twajood: Two-Factor Authentication Based on Distance and Face Recognition for Secure and Efficient Employee Attendance Monitoring","authors":"Rahaf Adam Alnuaimi, Ranem Khaled Almasalmeh, Sarah A. Baker, Maryam Nasser Alsaiaari, Moatsum Alawida","doi":"10.1109/HORA58378.2023.10156715","DOIUrl":"https://doi.org/10.1109/HORA58378.2023.10156715","url":null,"abstract":"In this paper, we aim to solve critical issues organizations face during attendance monitoring. Conventional log-in systems fail to effectively ensure successful attendance monitoring, and challenges such as user manipulation, social distancing making biometric devices obsolete, and other issues arise. To address these challenges, we propose a two-factor authentication system based on distance and face recognition. The system incorporates advanced geo-tracking tools and technologies with web3 features and double-factor authentication using face recognition technologies and accompanying distance monitoring devices and tools. Our system provides secure, adaptive, and advanced log-ins for employees and attendance monitoring for employers. The proposed system is scalable by simply accompanying more distance-tracking devices with no additional support systems required. It is a smart, user-friendly, and effective log-in system designed to optimize resource and time allocation for any organization. Compared to other two-factor authentication systems, our system is faster, more secure, and does not require central devices. It is also more friendly and flexible, offering a viable solution for maintaining a safe environment and easing procedures for employees and managers.","PeriodicalId":247679,"journal":{"name":"2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130586502","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}
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