2023 4th International Conference on Advancements in Computational Sciences (ICACS)最新文献

Experimenting Ensemble Machine Learning for DDoS Classification: Timely Detection of DDoS Using Large Scale Dataset 集成机器学习在DDoS分类中的实验:基于大规模数据集的DDoS实时检测

2023 4th International Conference on Advancements in Computational Sciences (ICACS) Pub Date : 2023-02-20 DOI: 10.1109/ICACS55311.2023.10089656

Hafiz Amaad, Hajrah Mughal

引用次数: 0

Natural Language Processing (NLP) based Extraction of Tacit Knowledge from Written Communication during Software Development 基于自然语言处理(NLP)的软件开发过程中书面交流隐性知识的提取

2023 4th International Conference on Advancements in Computational Sciences (ICACS) Pub Date : 2023-02-20 DOI: 10.1109/ICACS55311.2023.10089779

Maham Noor, Z. Rana

{"title":"Natural Language Processing (NLP) based Extraction of Tacit Knowledge from Written Communication during Software Development","authors":"Maham Noor, Z. Rana","doi":"10.1109/ICACS55311.2023.10089779","DOIUrl":"https://doi.org/10.1109/ICACS55311.2023.10089779","url":null,"abstract":"Software engineering, in general, and Global Software Engineering (GSE), in particular, face challenges such as handling communication and collaboration issues and inappropriate knowledge management. It is difficult to ensure availability of right knowledge at the right time to the right person during software engineering activity. The knowledge needs to be shared across the organization but limitations of knowledge sharing tools or dispersed knowledge sharing media and improper handling of tacit knowledge makes it more challenging to share knowledge. Significant amount of communication during software engineering process takes place via emails and discussion forums. Decisions taken during planning activities are also communicated through emails. These emails and the discussions do not necessarily cover the rationale behind a decision or approach adopted. This leaves a substantial portion of shared knowledge as tacit. Mostly, due to undefined tacit knowledge handling procedures, organizations suffer with the loss of critical knowledge and information. One way to handle this loss of knowledge is to store every information in knowledge repository but this can increase the size of the knowledge repository. This paper presents a three step approach to identify tacit knowledge in the written communication such that the organizations can save the tacit knowledge for future use. The presented approach does not only extract up to 57% of tacit knowledge but also indicates that only 20% of the whole communication need to be externalized hence saving 80% capacity of the knowledge repository, if every communication was to be preserved as potential tacit knowledge.","PeriodicalId":357522,"journal":{"name":"2023 4th International Conference on Advancements in Computational Sciences (ICACS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124095222","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

Organizing Committee ICACS 2023 组委会ICACS 2023

2023 4th International Conference on Advancements in Computational Sciences (ICACS) Pub Date : 2023-02-20 DOI: 10.1109/icacs55311.2023.10089640

引用次数: 0

Common Problems in Software Requirement Engineering Process: An Overview of Pakistani Software Industry 软件需求工程过程中的常见问题:巴基斯坦软件业概况

2023 4th International Conference on Advancements in Computational Sciences (ICACS) Pub Date : 2023-02-20 DOI: 10.1109/ICACS55311.2023.10089703

Sadia Khalid, Uzair Rasheed, Mishal Muneer, Wasi Haider Butt, R. Mehmood, Usman Qamar

引用次数: 1

A Novel Framework for Human Action Recognition Based on Features Fusion and Decision Tree 基于特征融合和决策树的人体动作识别新框架

2023 4th International Conference on Advancements in Computational Sciences (ICACS) Pub Date : 2023-02-20 DOI: 10.1109/ICACS55311.2023.10089752

Tanvir Fatima Naik Bukht, Hameedur Rahman, Ahmad Jalal

{"title":"A Novel Framework for Human Action Recognition Based on Features Fusion and Decision Tree","authors":"Tanvir Fatima Naik Bukht, Hameedur Rahman, Ahmad Jalal","doi":"10.1109/ICACS55311.2023.10089752","DOIUrl":"https://doi.org/10.1109/ICACS55311.2023.10089752","url":null,"abstract":"Image-based detection of human actions has recently emerged as a hot research area in the fields of computer vision and pattern recognition. It is concerned with detecting a person's actions or behavior from a static image. In this article, we are using a decision tree to develop an action recognition technique. In order to enhance the clarity of the video frames, the proposed method begins by implementing the HSI color transformation in the initial stage. Subsequently, it utilizes filters to minimize noise. The silhouette is extracted using a statistical method. We use SIFT and ORB for feature extraction. Next, using a parallel process, extract the shape and texture features needed for fusion applying name length control features. Additionally, the best high-dimensional data for classification is explored using vectors and the t-distributed stochastic neighbour embedding (t-SNE).The final step involves the features to be input into a decision tree, where they will be sorted into relevant human actions based on those final characteristics. The recognition rate of the UT interaction data used in the experimental process is 94.6%.","PeriodicalId":357522,"journal":{"name":"2023 4th International Conference on Advancements in Computational Sciences (ICACS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127992208","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: 10

Multi-Pedestrians Anomaly Detection via Conditional Random Field and Deep Learning 基于条件随机场和深度学习的多行人异常检测

2023 4th International Conference on Advancements in Computational Sciences (ICACS) Pub Date : 2023-02-20 DOI: 10.1109/ICACS55311.2023.10089730

F. Abdullah, Ahmad Jalal

{"title":"Multi-Pedestrians Anomaly Detection via Conditional Random Field and Deep Learning","authors":"F. Abdullah, Ahmad Jalal","doi":"10.1109/ICACS55311.2023.10089730","DOIUrl":"https://doi.org/10.1109/ICACS55311.2023.10089730","url":null,"abstract":"Automated video surveillance frameworks quickly distinguish surprising and basic circumstances in a packed climate that would help to pursue sufficient choices for security and crisis control. Hence, In this paper, an innovative method for automatically detect and localize anomalous objects among multi-pedestrian crowds via conditional random field and deep learning is introduced. Initially, necessary preprocessing is performed on extracted frames and then super-pixels are generated using improved watershed transform, the objects are then segmented using a conditional random field. The region of interests are localized using conditional probability and temporal association is implemented to locate the regions with a group of pedestrians and pedestrians with other objects. A deep learning feature pyramid network is then implemented to detect and categorized the objects in each region and finally, the anomalous objects are identified using Jaccard similarity. The effectiveness of proposed framework is assessed on openly accessible UCSD Ped 1 and Ped 2 datasets and it accomplishes an accuracy rate of 94.2% and 95.4% respectively. Extensive experimental data and comparative analysis show that our model outperformed current state-of-the-art models in terms of accuracy.","PeriodicalId":357522,"journal":{"name":"2023 4th International Conference on Advancements in Computational Sciences (ICACS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122978933","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: 8

Cyber Security Intrusion Detection Using Deep Learning Approaches, Datasets, Bot-IOT Dataset 使用深度学习方法的网络安全入侵检测，数据集，机器人-物联网数据集

2023 4th International Conference on Advancements in Computational Sciences (ICACS) Pub Date : 2023-02-20 DOI: 10.1109/ICACS55311.2023.10089688

Iram Manan, Faisal Rehman, Hana Sharif, C. Ali, Rana Rashid Ali, Amiad Liaqat

{"title":"Cyber Security Intrusion Detection Using Deep Learning Approaches, Datasets, Bot-IOT Dataset","authors":"Iram Manan, Faisal Rehman, Hana Sharif, C. Ali, Rana Rashid Ali, Amiad Liaqat","doi":"10.1109/ICACS55311.2023.10089688","DOIUrl":"https://doi.org/10.1109/ICACS55311.2023.10089688","url":null,"abstract":"Cyber Security is a crucial point of the current world; it is used to analyze, defend, and detect network intrusion systems. An intrusion detection system has been designed using Deep learning techniques, which helps the network user to detect malicious intentions. The dataset plays a crucial part in intrusion detection. As a result, we describe various well-known cyber datasets. Mainly we have analysed the IoT traffic-based dataset with some other datasets. We have also analyzed deep learning DL models, including Feed forward deep neural network (FDNN), deep auto-encoder, De-noising auto-encoder, deep migration, stacked de-noising auto-encoders, Replicator Neural networks, and Self-Taught Learning. We observe the effectiveness of models individually in two different types (multiclass and binary) through real-world traffic datasets, such as Bot-IoT dataset. Moreover, we evaluate the effectiveness of various methods based on the most critical key performance indicators, namely correctness, rate of false alarms and detection rate.","PeriodicalId":357522,"journal":{"name":"2023 4th International Conference on Advancements in Computational Sciences (ICACS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116207264","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

Automated White Matter Segmentation in MR Images Using Residual UNet 残差UNet在MR图像中自动分割白质

2023 4th International Conference on Advancements in Computational Sciences (ICACS) Pub Date : 2023-02-20 DOI: 10.1109/ICACS55311.2023.10089627

Yaqeen Ali, M. A. Iftikhar, Qamar Abbas, Tayyab Wahab

引用次数: 0

Deep Activity Recognition based on Patterns Discovery for Healthcare Monitoring 基于模式发现的医疗监控深度活动识别

2023 4th International Conference on Advancements in Computational Sciences (ICACS) Pub Date : 2023-02-20 DOI: 10.1109/ICACS55311.2023.10089764

M. Javeed, Ahmad Jalal

引用次数: 13

Vehicle Detection and Tracking Using Kalman Filter Over Aerial Images 基于卡尔曼滤波的航拍图像车辆检测与跟踪

2023 4th International Conference on Advancements in Computational Sciences (ICACS) Pub Date : 2023-02-20 DOI: 10.1109/ICACS55311.2023.10089701

Asifa Mehmood Qureshi, A. Jalal

引用次数: 7