2022 International Conference on Frontiers of Information Technology (FIT)最新文献_第2页

Verification and Validation of a VANET-based Formal Model for Online Taxi Service using VDM-SL Toolbox 利用VDM-SL工具箱验证基于vanet的在线出租车服务形式化模型

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00037

Sidra Iqbal, Tariq Ali, N. Zafar, Tahira Batool

{"title":"Verification and Validation of a VANET-based Formal Model for Online Taxi Service using VDM-SL Toolbox","authors":"Sidra Iqbal, Tariq Ali, N. Zafar, Tahira Batool","doi":"10.1109/FIT57066.2022.00037","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00037","url":null,"abstract":"Vehicular Ad hoc Networks (VANETs) have garnered a lot of interest due to their distinctive qualities, such as dynamic topology and predictable mobility. The development of VANETs in road transportation systems is receiving significant funding from both the academic community and the automobile industry. Taxi service has currently faced various issues such as security, privacy, efficiency, payment, and robbery in the transportation system which needs state-of-the-art technologies for its modeling and verification. Further, basic security requirements, driver’s authentication, and passenger’s on-journey protection and privacy are addressed by using this model. Passenger registration, taxi reservation, cancellation, payment, refund payment as well as taxi monitoring are considered in the model. Roadside units have been utilized to sense environmental data as well as by using non-deterministic finite automata (NFA) in terms of states and transitions, we put forth a model for an automatic system. Vienna development method-specification language (VDM-SL), has been utilized for formal specification, formal analysis, and formal model verification and validation via the VDM-SL toolbox.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133508473","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

Sequence-driven Neural Network models for NER Tagging in Roman Urdu 罗马乌尔都语NER标注的序列驱动神经网络模型

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00040

Maaz Ali Nadeem, Khadija Irfan, Khaula Atiq, M. O. Beg, Muhammad Umair Arshad

引用次数: 0

Experimental Study and Results on Real-Time Communication via Gigabit Ethernet in Underwater Sensor Array Systems 水下传感器阵列系统中千兆以太网实时通信的实验研究与结果

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00017

K. Waqas, U. Hamid, Shahid Ali

{"title":"Experimental Study and Results on Real-Time Communication via Gigabit Ethernet in Underwater Sensor Array Systems","authors":"K. Waqas, U. Hamid, Shahid Ali","doi":"10.1109/FIT57066.2022.00017","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00017","url":null,"abstract":"The paper focuses on Ethernet based data transfers in real-time processing systems. These systems require fast and reliable data transfers among all the involved resources. In underwater acoustic processing systems, large amount of data is digitized, processed and displayed in real-time. These systems involve hundreds of acoustic sensors producing analog signals that are digitized and generate a large set of data points to be transferred to other processing units in a real-time. This time constraint is important in underwater applications as the processed data displayed to the system operator is critical for undersea operations. Data losses are not acceptable because it may result in incorrect information for the system operator thereby producing a wrong interpretation of the incoming information. Hence an efficient and reliable data transfer mechanism to meet real-time constraint becomes imperative. In this paper we have proposed a Gigabit Ethernet based data transfer methodology using TCP/IP for data transfers among different processing units of an underwater acoustic processing system. Here we have attempted to address some important challenges such as large amount of data to be transferred efficiently in a computer network and the ability to meet processing time (on average) required for successful completion of Gigabit Ethernet based data transfers.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121909622","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

Multi-Encoder Convolution Block Attention Model for Binary Segmentation 二值分割的多编码器卷积块注意模型

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00042

Keita Mamadou, M. Ullah, Ø. Nordbø, F. A. Cheikh

{"title":"Multi-Encoder Convolution Block Attention Model for Binary Segmentation","authors":"Keita Mamadou, M. Ullah, Ø. Nordbø, F. A. Cheikh","doi":"10.1109/FIT57066.2022.00042","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00042","url":null,"abstract":"Behavioural research in animals can be assisted significantly with an automatic identification system. Such systems can evaluate animals’ behaviour non-intrusively, hence preserving their typical habitat. Recently, methods based on deep learning have shown promising results in this domain. In particular, object and key-point detectors have been used to detect individual animals. Although good results are obtained, bounding boxes and dispersed key points do not follow the animal’s contour, resulting in a large amount of information loss. This work proposed a binary segmentation model that precisely segments individual animal pixels in an indoor setting. In a nutshell, we proposed a new model with multiple encoders and a single decoder incorporating the attention mechanism. The method is tested on a specially created dataset with 1280 hand-labelled images and achieves detection rates of about 91% (dice coefficient) despite perturbations such as occlusions and illumination variations. The results are compared with state-or-the-art segmentation models, and a substantial boost in performance is achieved.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129933998","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

An Improved Deep Learning Approach for Heart Attack Detection from Digital Images 基于数字图像的心脏病发作检测的改进深度学习方法

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00055

Zaheer Ahmed, Aun Irtaza, Awais Mehmood, Muhammad Faheem Saleem

{"title":"An Improved Deep Learning Approach for Heart Attack Detection from Digital Images","authors":"Zaheer Ahmed, Aun Irtaza, Awais Mehmood, Muhammad Faheem Saleem","doi":"10.1109/FIT57066.2022.00055","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00055","url":null,"abstract":"The mortality rate due to different diseases is alarmingly rising day by day across the world. The major reason for this death rate includes heart-related problems occurring due to age factors, blood pressure, and diabetes. Normally, old people like living by on their own which creates problems in cases of an emergency, and it gets hard for the paramedical staff to provide them with prompt help. Several people die just because of not getting emergency medical attention during a heart attack. The patients usually cannot convey a request for help due to severe pain in the chest which stops them to do any activity. Hence, timely identification of a patient with an ongoing heart attack becomes a matter of life and death. In this research, we propose a new methodology for the identification of people with an ongoing heart attack in color images. For this, we implement various pre-trained deep learning Convolutional Neural Networks (CNNs) models including a modified version of ResNet-50 to identify a person with a heart attack by detecting special heart attack-related postures. A special set of images containing the people having a heart attack are input to these models for comprehensive training. As compared to the other implemented pre-trained models, our modified ResNet-50 model achieved an accuracy of 92% during the classification of infarcts.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127101892","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

Defeating Modern Day Anti-Viruses for Defense Evaluation 击败现代反病毒防御评估

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00054

Abdul Basit Ajmal, Shawal Khan, Farhana Jabeen

引用次数: 0

Emotional States Detection Model from Handwriting by using Machine Learning 基于机器学习的手写情绪状态检测模型

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00059

Khadija Nadeem, Mudassar Ahmad, Muhammad Asif Habib

引用次数: 0

Stroke Sequence Identification in Handwritten Urdu Alphabets Using Convolutional Neural Networks 用卷积神经网络识别手写乌尔都语字母笔画序列

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00041

A. Qarni, Muhammad Shoaib, Muhammad Abdullah, Saba Khalid, A. Aslam, Noreen Kausar, Ayesha Khan, M. Tariq, Fizza Jameel, Tayyab Gull Khan

{"title":"Stroke Sequence Identification in Handwritten Urdu Alphabets Using Convolutional Neural Networks","authors":"A. Qarni, Muhammad Shoaib, Muhammad Abdullah, Saba Khalid, A. Aslam, Noreen Kausar, Ayesha Khan, M. Tariq, Fizza Jameel, Tayyab Gull Khan","doi":"10.1109/FIT57066.2022.00041","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00041","url":null,"abstract":"There is a lack of attention to early childhood handwriting in developing countries like Pakistan, where a single teacher teaches 50 to 100 students at a time. Children need a lot of attention from the teacher during their early stages (4-8 years), especially when they start writing the alphabet to assure that they adopted a correct stroke sequence. It is almost impossible for a teacher to pay attention to all his/her students to observe their stroke sequences. Due to a lack of teacher attention, the students may write the alphabet with correct or incorrect stroke sequences. If a student follows an incorrect stroke sequence, it badly affects the writing speed and the beauty of his/her cursive handwriting. As the research on this topic is concerned, so far, it has been conducted mainly in Chinese and Japanese languages to find out the correct stroke sequence. Arabic has received far fewer studies and Urdu is the most neglected till now. In this paper, we have proposed Urdu Handwriting E-Tutor (UHET). UHET is a Computer Vision based method that continuously monitors the handwriting activity of a child and successfully points out whether the stroke sequence (while writing an Urdu alphabet) is correct or not. To conduct this study, we created a new dataset that consists of images and videos of five Urdu alphabets. UHET exploits Convolutional Neural Network to train the model for predicting the alphabet (written by the child) and its stroke sequence. Results show that our UHET performs well achieving 80% accuracy on the average on the given data set.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114082027","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

Cyber Attacks and Vulnerabilities Assessment for Unmanned Aerial Vehicles Communication Systems 无人机通信系统的网络攻击与漏洞评估

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00047

Hassan Jalil Hadi, Yue Cao

{"title":"Cyber Attacks and Vulnerabilities Assessment for Unmanned Aerial Vehicles Communication Systems","authors":"Hassan Jalil Hadi, Yue Cao","doi":"10.1109/FIT57066.2022.00047","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00047","url":null,"abstract":"In the developing world, the trend of using Unmanned Aerial Vehicles (UAVs) is being increased in many fields. These UAVs are now available in many different versions which ranges from children toy to military level combat equipment. Manufacturing companies are mostly mainly paying attention on reducing power consumption, high data transfer rate, less weight and more speed. However, by keeping focus on these features, most of the UAVs manufacturing companies overlook the factor of security and the risk in case of exploitation is ignored. This fact cannot be ignored that an exploited/hacked UAV with malicious intent can cause serious harm to the target in many ways. In the UAVs development, focus on the less computation power, restricted correspondence data transfer capacity, light weight data carrying limit and robustness captivity in UAVs has become a challenge for security practitioners and researchers. UAVs use numerous communication protocols and one among these protocols is Micro Air Vehicle (MAV) link protocol which is reliable as well as efficient. Currently, there are two versions of MAVlink communication protocol called MAVlink1 and MAVlink2. This protocol is used to establish a communication between Ground Control Station and UAV. The second version of this protocol (i.e. MAVlink2) is recent and there is not much data available about the potential exploitable vulnerabilities present in this protocol. This research paper has explored and identified security vulnerabilities in MAVlink2, specifically linked to the communication of UAV and their impact on UAV. The paper has further analyzed MAVlink2 communication protocol in order to exploit the vulnerabilities in the MAVlink2 protocol for hijacking the UAV.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127305864","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

Locomotion Classification of Bipedal Humanoid Robot using Fast Fourier Transform 基于快速傅里叶变换的两足人形机器人运动分类

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00027

Saad Imran, Farrukh Zeeshan Khan, F. Subhan

引用次数: 0