2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC)最新文献_第2页

Applying Design Science Research Methodology for Development of a Mobile-Based Digital Quail Farming Guide 应用设计科学研究方法开发基于移动的数字鹌鹑养殖指南

2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC) Pub Date : 2022-10-27 DOI: 10.1109/MAJICC56935.2022.9994157

A. S. Shminan, Siti Nor Ain Romly, Merikan Aren, Lee Jun Choi, Wan Norizan Wan Hashim

{"title":"Applying Design Science Research Methodology for Development of a Mobile-Based Digital Quail Farming Guide","authors":"A. S. Shminan, Siti Nor Ain Romly, Merikan Aren, Lee Jun Choi, Wan Norizan Wan Hashim","doi":"10.1109/MAJICC56935.2022.9994157","DOIUrl":"https://doi.org/10.1109/MAJICC56935.2022.9994157","url":null,"abstract":"This study aimed to design and develop a mobile-based digital quail farming guide for the B40 elderly group. This mobile application, known as Quaillogy, provides learning materials for basic quail farming and different topics in entrepreneurship and marketing. The underlying motivator is to provide a tool for the B40 household income elderly to learn independently at their own pace about quail farming through mobile devices. The recently increased request for quail production will benefit the target users in becoming beginner breeders and entrepreneurs. Design Science Research Methodology (DSRM) was selected as the methodology that fit the requirement of developing the mobile application. It consisted of six stages: problem identification, definition objective, design and development, demonstration, evaluation, and communication. The evaluations from experts and users' views were conducted to examine the content and user interface design. In sum, this research achieved the objectives as the evaluations showed positive feedback. Quaillogy does contribute to the elderly by offering knowledge about basic quail farming and exposing them to basic digital marketing strategy knowledge. It indirectly benefits the elderly to initiate quail farming and eventually generate side income to support the upsurge in living expenses. The findings were aligned with several Sustainable Development Goals (SDGs) of “Quality Education”, “No Poverty”, and “Decent Work and Economic Growth”. Knowledge transmission using mobile technology can provide an inclusive and equitable quality of education. At the same time, reducing income inequality and enriching economic growth can eradicate poverty. Future research may also be able to take more advantage of Quaillogy.","PeriodicalId":205027,"journal":{"name":"2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124453390","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 Novel Deep Learning-based Approach to encounter cyber threats in IIoT 一种新的基于深度学习的方法来应对工业物联网中的网络威胁

2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC) Pub Date : 2022-10-27 DOI: 10.1109/MAJICC56935.2022.9994173

Syed Nawaz Ali Shah, Ghufran Ahmed, Adnan Akhunzada, Engr. Shahbaz Siddiqui

{"title":"A Novel Deep Learning-based Approach to encounter cyber threats in IIoT","authors":"Syed Nawaz Ali Shah, Ghufran Ahmed, Adnan Akhunzada, Engr. Shahbaz Siddiqui","doi":"10.1109/MAJICC56935.2022.9994173","DOIUrl":"https://doi.org/10.1109/MAJICC56935.2022.9994173","url":null,"abstract":"Internet of Things (IoT) is a growing field and it has reached the multi-million dollar market. The research in the field of IoT, networks and AI is in initial stages due to the growing nature of IoT market. The IoT devices are used in many different applications to automate processes. In Industrial Internet of Things (IIoT), millions of such tiny devices are used to automate the quality assurance, safety protocols and other industrial processes. Due to resource constraint nature of such tiny devices, security is a big challenge for researchers to detect the security-based threats in IoT. Hence, intrusion detection is a big problem in IoT. In this paper, a novel approach to detect intrusions and cyber threats is proposed. In the proposed approach, the out class deep learning based algorithms are used to detect cyber threats in IoT. For this purpose, a latest data set named as Kitsune is used. This data set is already pre-processed and contains rich feature sets. Moreover, it has latest data of 9 types of attacks. In the proposed strategy, work has been done on a single type of attack namely Mirai Botnet and four different algorithms LSTM, GRU, DNN, RNN with the combinations of CNN1d, CNN2d and CNN3d are used. The simulation results show that the proposed approach with an accuracy of 99.73 outperforms traditional approaches.","PeriodicalId":205027,"journal":{"name":"2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134601938","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 Systematic Literature Review on Smart Waste Management Using Machine Learning 利用机器学习进行智能废物管理的系统文献综述

2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC) Pub Date : 2022-10-27 DOI: 10.1109/MAJICC56935.2022.9994104

Hamid Umer, Awais Ahmed, Farman Ali, Syed Sarmad Ali, Munim Ali Khan

引用次数: 1

Mask R-CNN Based Real Time near Drowning Person Detection System in Swimming Pools 基于掩模R-CNN的泳池溺水者实时检测系统

2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC) Pub Date : 2022-10-27 DOI: 10.1109/MAJICC56935.2022.9994135

Muhammad Aftab Hayat, Goutian Yang, Atif Iqbal

引用次数: 0

Towards Human Cognition Level-based Experiment Design for Counterfactual Explanations 基于人类认知层次的反事实解释实验设计

2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC) Pub Date : 2022-10-27 DOI: 10.1109/MAJICC56935.2022.9994203

M. Nizami, Muhammad Yaseen Khan, A. Bogliolo

{"title":"Towards Human Cognition Level-based Experiment Design for Counterfactual Explanations","authors":"M. Nizami, Muhammad Yaseen Khan, A. Bogliolo","doi":"10.1109/MAJICC56935.2022.9994203","DOIUrl":"https://doi.org/10.1109/MAJICC56935.2022.9994203","url":null,"abstract":"Explainable Artificial Intelligence (XAI) has recently gained a swell of interest, as many Artificial Intelligence (AI) practitioners and developers are compelled to rationalize how such AI-based systems work. Decades back, most XAI systems were developed as knowledge-based or expert systems. These systems assumed reasoning for the technical description of an explanation, with little regard for the user's cognitive capabilities. The emphasis of XAI research appears to have turned to a more pragmatic approaches of explanation for a better understanding. An extensive area where cognitive science research may substantially influence XAI advancements is evaluating user knowledge and feedback, which are essential for XAI system evaluation. To this end, we propose a framework to experiment with generating and evaluating the explanations on the grounds of different cognitive levels of understanding. In this regard, we adopt Bloom's taxonomy, a widely accepted model for assessing the users' cognitive capability. We utilize the counterfactual explanations as an explanation-providing medium encompassed with user feedback to validate the levels of understanding about the explanation at each cognitive level and improvise the explanation generation methods accordingly.","PeriodicalId":205027,"journal":{"name":"2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130394683","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

Deep Learning System for Detecting the Diabetic Retinopathy 糖尿病视网膜病变检测的深度学习系统

2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC) Pub Date : 2022-10-27 DOI: 10.1109/MAJICC56935.2022.9994195

Faisal Hayat, Rabbia Mahum

{"title":"Deep Learning System for Detecting the Diabetic Retinopathy","authors":"Faisal Hayat, Rabbia Mahum","doi":"10.1109/MAJICC56935.2022.9994195","DOIUrl":"https://doi.org/10.1109/MAJICC56935.2022.9994195","url":null,"abstract":"Retinal blood veins of an eyes are destructive directly by DR that is Complexity of diabetes. Firstly, it becomes problematic for an eye vision. However, if it develops on serious condition, it can badly affect for both eyes and moreover, it can damage the eyesight partly or completely. Primarily it happens because of the blood having excess sugar level. Thus, the diabetic patient is at high risk to attain such disease who has diabetes sugary constantly. Primary detection of this disease can totally discourage the likelihood of blindness. Therefore, well-organized system for screening is mandatory. This procedure reflects the deep learning practice particularly densely connected conv. network DenseNet-169 that is functional for primarily diagnosis the DR. Pics are ordered on the basis of their harshness level i.e. NDR (Nil Diabetic Retinopathy), MDR (Mild DR), MoDR (MoD. Diabetic Retinopathy), Severe & PDR. Kaggle is the source of data for this process to driveDR detection. The recommended method consists of several stages including Data info/collecting, info/preprocessing, augmentation of data and modelling/demonstrating.","PeriodicalId":205027,"journal":{"name":"2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133519441","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

Proteins Classification Using An Improve Darknet-53 Deep Learning Model 使用改进的Darknet-53深度学习模型的蛋白质分类

2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC) Pub Date : 2022-10-27 DOI: 10.1109/MAJICC56935.2022.9994209

Dur-E-Maknoon Nisar, Rabbia Mahum, Tabinda Azim, Noor-Ul-Huda Shah

引用次数: 0

Cricket Videos Summary generation using a Novel Convolutional Neural Network 基于卷积神经网络的板球视频摘要生成

2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC) Pub Date : 2022-10-27 DOI: 10.1109/MAJICC56935.2022.9994106

Shahbaz Sikandar, Rabbia Mahmum, Nouman Akbar

{"title":"Cricket Videos Summary generation using a Novel Convolutional Neural Network","authors":"Shahbaz Sikandar, Rabbia Mahmum, Nouman Akbar","doi":"10.1109/MAJICC56935.2022.9994106","DOIUrl":"https://doi.org/10.1109/MAJICC56935.2022.9994106","url":null,"abstract":"Video is the combination of frames, many sequences of images known as frames are grouped together to form a video. The exponential growth of video data requires constant exploration from original videos by extracting only informative content present in the video. Traditional video processing applications process frame one by one and consume a lot of time, however, video summarization techniques based on deep learning extract only key-frames in the video based on classification for informative content. Supervised and unsupervised video processing techniques help people to reduce their efforts for video summarization. In this paper, we propose a novel customized convolutional neural network i.e. a supervised model of deep learning for summarization of cricket videos. Our proposed Cricket- Convolutional Neural Network (C-CNN) learns the most informative features from video frames and performs binary classification into positive and negative class. We have performed an extensive experimentation which ensures that our proposed C-CNN network outperforms the existing techniques for cricket video summarization.","PeriodicalId":205027,"journal":{"name":"2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124809291","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

Urdu News Classification: An Empirical Study Using Machine Learning Techniques 乌尔都语新闻分类:使用机器学习技术的实证研究

2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC) Pub Date : 2022-10-27 DOI: 10.1109/MAJICC56935.2022.9994152

Aman Farooq, Zainab Noreen, Safiyah Batool, Fouzia Naz

{"title":"Urdu News Classification: An Empirical Study Using Machine Learning Techniques","authors":"Aman Farooq, Zainab Noreen, Safiyah Batool, Fouzia Naz","doi":"10.1109/MAJICC56935.2022.9994152","DOIUrl":"https://doi.org/10.1109/MAJICC56935.2022.9994152","url":null,"abstract":"Text is a rich source of information and there is unlimited text on the internet. Automatic text classification is a technique to label those text documents with predefined categories. This has various applications including sentiment analysis, spam detection, NLP etc. There is much work done on english text classification but there is a huge gap with Urdu. There isn't any standard algorithm known that outperforms all others. Also it is observed that classifiers usually perform better when the text is preprocessed, but there aren't any standard stemmer, stop word list, tokenizer etc. available for urdu text. Urdu is rich morphologically and it's a challenge to design preprocessing tools for urdu. This research tends to reduce the gap by testing different classification algorithms using different dimensionality reduction combinations on urdu news data set to know which performs better. It also includes designing a stemmer, tokenizer and preparing a stop word list. In this research it was concluded that SVM performed better with the combination of both preprocessing techniques. Fasttext library was also tested for urdu text classification which achieved 95%accuracy and f-score 1 %less than SVM. Another approach used is that topic modeling has been performed using LDA and documents have been weighed as topics. Classification using documents as topics didn't perform well but Random Forest performed better than Naive Bayes and SVM. It's in future work to design a POS tagger that may improve performance of stemmer and to test deep learning methods for urdu text classification.","PeriodicalId":205027,"journal":{"name":"2022 Mohammad Ali Jinnah University International Conference on Computing (MAJICC)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129314313","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