2022 International Conference on Frontiers of Information Technology (FIT)最新文献_第5页

Measurement-based analysis of characteristics of fast moving underwater acoustic communication channel 基于测量的快速移动水声通信信道特性分析

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00019

Yang Wang, Honglu Yan, Chenyu Pan, Songzuo Liu

引用次数: 0

Impact of Serious Game Design Factors and Problem based Pedagogy on Learning outcome 严肃游戏设计因素和问题教学法对学习结果的影响

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00064

Fatima Gillani, Irum Inayat, C. V. Carvalho

{"title":"Impact of Serious Game Design Factors and Problem based Pedagogy on Learning outcome","authors":"Fatima Gillani, Irum Inayat, C. V. Carvalho","doi":"10.1109/FIT57066.2022.00064","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00064","url":null,"abstract":"Serious Games encompasses a wide range of goals including social awareness, public health initiatives, marketing, communications, industry, and so on but their primary concern is Education and training. These games intend to teach subject to players more than just emphasizing players' amusement and entertainment. The primary objective is to teach and train players in a playful environment. Games are too often developed in an ad-hoc manner while overlooking the use of pedagogical aspects and active learning principles. In this paper, we aim to address this issue by designing a serious game design model using Problem-based learning pedagogical aspects to assist the serious game designer. For this purpose, we mapped the problem-based learning principles with the game design factors and proposed a game design model based on 13 identified factors that are Goal, Scenario Exposition, autonomous, Control, Immersion, Challenge, Stimulus, Collaboration, Feedback, Authentic Learning, and Assessment. Followed by that, two experimental studies were conducted. First study was conducted to measure the impact of problem-based pedagogical game design factors on the learning outcome using an open source game that was customized based on the proposed model. The second study was conducted to check the impact of Collaboration and feedback on learning outcome. The results of the study reveal (1) problem based pedagogical mapped game design factors have a positive impact on the learning outcome of students and (2) procedural feedback to be the contributing factor in enhancing student performance.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"20 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":"125318465","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

Summarization of Cricket Videos Using Deep Learning Technique 使用深度学习技术的板球视频总结

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00016

Tabinda Nasir, M. Iqbal, Mehmoon Anwar

{"title":"Summarization of Cricket Videos Using Deep Learning Technique","authors":"Tabinda Nasir, M. Iqbal, Mehmoon Anwar","doi":"10.1109/FIT57066.2022.00016","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00016","url":null,"abstract":"Video Summarization plays a ignificant role in many fields of life and it can be employed to avoid wastage of time and effort in watching long and boring different types of sports videos. In literature, several computer vision-based techniques have been proposed for predicting useful classes from different perspectives, which is quite challenging. The prediction accuracy results of previous techniques were not satisfactory due to the complex nature and lot of redundant events in sports videos. This work focuses on the video summarization of cricket videos due to their overwhelming interest. To make predictions accurately and precisely, a well-organized dataset of four main classes of cricket like, catch, lbw, four, and sixer as the viewer is not interested in unnecessary coverage of the crowd and replays that just waste its time and interest. In the experiments, cricket videos were extracted from different sources, especially YouTube. Subsequently, these videos have been processed and the most useful frames were extracted to run several experiments. The Resnet152 V2 transfer learning model was implemented to carry out the classification and video summarization task. The proposed method performs well and produces more accurate results. The approach of making datasets reduces inter-class similarity problems that occurred in previous methods of video summarization. The proposed work will be helpful in saving the time of viewers by viewing and observing summarized videos instead of long content videos.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"20 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":"125666367","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

Modeling and Optimizing the Integrated Energy-Water Nexus for Hydrogen Generation 氢气生成的综合能源-水关系建模与优化

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00020

M. B. Rasheed, M. Rodríguez-Moreno

{"title":"Modeling and Optimizing the Integrated Energy-Water Nexus for Hydrogen Generation","authors":"M. B. Rasheed, M. Rodríguez-Moreno","doi":"10.1109/FIT57066.2022.00020","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00020","url":null,"abstract":"To meet the carbon-free energy and water demand requirements by Europe, this work has proposed an interconnected and integrated-energy-water-hydrogen (IEWH) system. Typically these systems are generally uncoupled, however, they may be interconnected and can be operated to provide green energy and water with reduced carbon footprints. This work has used power, water, and co-generation facilities to generate power, water, and hydrogen through the electrolysis process. Co-generation and power plants meet the water and energy demand for the electrolysis process. We propose an initial formulation of the mathematical models and objective functions of power, water, co-generation, and electrolysis facilities. The final optimization problem subject to generation, transmission, and process constraints is formulated as a nonlinear programming problem, which is solved using the CONOPT solver. Finally, the developed model is tested on a test case comprised of IEEE 30 standard bus and Hanoi water distributions, (UK), to validate the achievements in cost and CO2 reduction. Simulation results show that integration of hydrogen facilities to produce the electricity power significantly reduces the carbon emissions.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"42 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":"131752698","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

Churn Prediction of Customers in a Retail Business using Exploratory Data Analysis 使用探索性数据分析的零售企业客户流失预测

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00033

W. Abbas, M. Usman, Usman Qamar

{"title":"Churn Prediction of Customers in a Retail Business using Exploratory Data Analysis","authors":"W. Abbas, M. Usman, Usman Qamar","doi":"10.1109/FIT57066.2022.00033","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00033","url":null,"abstract":"These days retail stores and supermarkets are rapidly increasing, and they became very high saturated business. Due to its rapid growth, retail sector is facing very serious problems of customer attrition and churns. So, to overcome this problem, the retail stores and supermarkets need to have an effective churn management strategy. Machine learning, and Data Mining can be used by the management to analyze the churning behavior of customers and help them to retain their customers. To do so, this paper executed explorative data analysis and feature engineering on retail store data set. Five different techniques have been applied namely, Logistic Regression, Random Forest, Decision Tree, K nearest neighbors and XGboost, while Precision, Accuracy, AUC, F1-Score and Recall been used to analyze the performance of classification techniques. This study shows that the proposed model can predict the customer churn with an accuracy of 73% and help management to retain their customers. It is demonstrated in the result that the XGboost is the most efficient classifier for this data set which surpassed all other classifiers in all performance evaluation metrics.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"148 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":"132406909","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

Automatic Detection of Leukemia through Convolutional Neural Network 基于卷积神经网络的白血病自动检测

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00044

R. Arif, Shahzad Akbar, A. Farooq, Syed Ale Hassan, Sahar Gull

{"title":"Automatic Detection of Leukemia through Convolutional Neural Network","authors":"R. Arif, Shahzad Akbar, A. Farooq, Syed Ale Hassan, Sahar Gull","doi":"10.1109/FIT57066.2022.00044","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00044","url":null,"abstract":"Leukemia is a fatal cancer disease that develops in blood-forming tissue by the excessive development of white blood cells (WBCs) in the human body. However, a bone marrow test is recommended by the pathologist to diagnose leukemia and further types of leukemia. Leukemia has two classes i.e., acute and chronic leukemia. Therefore, early leukemias detection enables preventative actions to be taken to avoid any harm to human life. In addition, several manual and automatic methods have been proposed, however, they possess some drawbacks and are inefficient for the precise detection of leukemia. This research proposes a deep learning-based framework for precise and automatic leukemia identification using microscopic images. The proposed framework comprises four stages which are pre-processing, data augmentation, segmentation, and the classification of leukemia. Moreover, pre-processing is utilized to clean the dataset images and eliminate the noise. Following that, data augmentation approaches have been employed to increase the number of images, and remove the class imbalance, and overfitting problems. The modified Convolutional Neural Network (CNN) based model is employed to segment the leukemia images. A well-known pre-trained AlexNet architecture has been used for classification. Besides that, a publicly available dataset Acute Lymphoblastic Leukemia Image DataBase (ALL-IDB) has been utilized to train and test the proposed model. The proposed model yielded 98.05% accuracy, a specificity of 97.59%, 100% of recall, and a 99.06% of F1-score. The experimentation results demonstrate that this model is effective and reliable for leukemia identification using the ALL-IDB dataset and suitable for deployment in clinical applications.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"30 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":"134191908","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: 1

Towards Automatic Retinal Blood Vessels Segmentation in Retinal Images 视网膜图像中血管自动分割的研究

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00021

Noshaba Khurshid, Muhammad Ibrahim Syed, Khurram Khan, Z. Mahmood

引用次数: 0

Inspecting Mega Solar Plants through Computer Vision and Drone Technologies 通过计算机视觉和无人机技术检查大型太阳能发电厂

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00014

Syed Umaid Ahmed, M. Affan, Muhammad Ilyas Raza, Muhammad Harris Hashmi

引用次数: 5

A Lecture Centric Automated Distractor Generation for Post-Graduate Software Engineering Courses 研究生软件工程课程中以讲座为中心的自动干扰物生成

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00028

Rudeema Chughtai, F. Azam, Muhammad Waseem Anwar, Wasi Haider Butt, M. U. Farooq

引用次数: 0

Traffic Classification based on Incremental Learning Algorithms for the Software-Defined Networks 基于增量学习算法的软件定义网络流分类

2022 International Conference on Frontiers of Information Technology (FIT) Pub Date : 2022-12-01 DOI: 10.1109/FIT57066.2022.00068

Arwa Mohamed, Mosab Hamdan, Suleman Khan, Muzaffar Hamzah, M. N. Marsono

{"title":"Traffic Classification based on Incremental Learning Algorithms for the Software-Defined Networks","authors":"Arwa Mohamed, Mosab Hamdan, Suleman Khan, Muzaffar Hamzah, M. N. Marsono","doi":"10.1109/FIT57066.2022.00068","DOIUrl":"https://doi.org/10.1109/FIT57066.2022.00068","url":null,"abstract":"A new era of network administration has been ushered in by recent developments in software-defined networks (SDN) and traffic classification (TC) using machine learning (ML) techniques. All network devices are centrally managed and accessible through the SDN, which can simplify the TC process. The traditional data mining/ML approach that uses TC assumes that all of the task's data is always accessible and can be viewed simultaneously without processing time and memory restrictions. Therefore, these approaches are not effective in the case of stream learning since, in more realistic settings, the data is not available all at once and has a distinct distribution. Consequently, incremental learning algorithms (ILAs) can handle online data mining. This study's primary goal is to contrast various ILA approaches to enhance SDN's TC performance. In this study, we propose four ILAs: the self- adjusting memory coupled with the k Nearest Neighbor (kNN) classifier (SAMKNNC), the very fast decision rules classifier (VFDRC), the extremely fast decision tree classifier (EFDTC), and the streaming random patches ensemble classifier (SRPC). Both real and synthetic datasets are used for validation. Experimental findings reveal that the proposed techniques perform better in SDN traffic classification since they can effectively identify drift and use less memory and time.","PeriodicalId":102958,"journal":{"name":"2022 International Conference on Frontiers of Information Technology (FIT)","volume":"19 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":"122795869","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