2020 International Conference on Computational Intelligence (ICCI)最新文献_第2页

Cybersecurity Impact over Bigdata and IoT Growth 网络安全对大数据和物联网增长的影响

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247722

Dhuha Khalid Alferidah, Noor Zaman Jhanjhi

{"title":"Cybersecurity Impact over Bigdata and IoT Growth","authors":"Dhuha Khalid Alferidah, Noor Zaman Jhanjhi","doi":"10.1109/ICCI51257.2020.9247722","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247722","url":null,"abstract":"Big Data and IoT based applications are promising and being necessary for almost all the fields. IoT applications provide us with beneficial services, and also they gather and transmit data to Big Data databases where data can be stored and analyzed. Big Data and IoT started to be involved in smart homes, smart healthcare, education, shopping and even in agriculture field. These Big Data and IoT based applications are growing rapidly. The more these technologies are giving us great applications and making our life better; the more cybersecurity attacks start against them. These applications are the target for attackers due to the useful and massive amount of data they have. Cybersecurity is a significant issue for these technologies. Cybersecurity threats and attacks can stop these technologies from growing, which is considered to be a negative point for us and these promising technologies. Cybersecurity threats weaken these technologies to gain full access over the user’s data. Understanding the possible applications and benefits that we could learn from these technologies is important Also, understanding and being aware of the possible threats that could threaten the various Big Data and IoT based applications is more critical Understanding the possible cybersecurity attacks and threats can help us to know about how to protect these technologies and applications from cybersecurity attacks. This research presents critical cybersecurity impacts in the form of security threats, and attacks that could be initiated against Big Data and IoT based applications and affect their growth. These impacts are elaborated using a case study of a healthcare system with its possible cybersecurity attacks, which shows the relation between cybersecurity attacks and the growth of Big Data and IoT technologies.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128721848","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: 12

Interactive Tool Using Augmented Reality (AR) for Learning Knee and Foot Anatomy Based on CT Images 3D Reconstruction 基于CT图像三维重建的增强现实(AR)学习膝关节和足部解剖的交互式工具

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247820

Liew Set Lee, S. Aluwee, Goh Chuan Meng, P. Palanisamy, Ramani Subramaniam

{"title":"Interactive Tool Using Augmented Reality (AR) for Learning Knee and Foot Anatomy Based on CT Images 3D Reconstruction","authors":"Liew Set Lee, S. Aluwee, Goh Chuan Meng, P. Palanisamy, Ramani Subramaniam","doi":"10.1109/ICCI51257.2020.9247820","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247820","url":null,"abstract":"Anatomy is the branch of biological science in medical education that focuses on structured parts of living things, especially the human body. Traditional teaching methods and learning materials of human body anatomy are usually available in the form of textbooks with pictures and images or artificial anatomy mannequins. There are still not enough to help the students in understanding it with actual and accurate knowledge about our human body anatomy. It is because students are challenging in learning the human anatomy body part by through imagining it’s real and lack of interaction and hard to understand with those 2D images model on the textbooks. Although there are artificial anatomy mannequins available for learning, it is limited in number and access. Technological developments, especially applications based on 3D, are expected to help the learning process of this science subject. In this study, we proposed to develop an augmented reality (AR) mobile application for learning human anatomy knee and foot through medical 3-dimensional (3D) reconstruction based on medical images. By using this application, students expected can easily understand human anatomy using 3D image visualisation on the mobile computing platform.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127512405","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

Covid-19 Disease Simulation using GAMA platform 基于GAMA平台的Covid-19疾病模拟

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247632

Tran Quy Ban, Phan Lac Duong, Nguyễn Hoàng Sơn, Tran Van Dinh

{"title":"Covid-19 Disease Simulation using GAMA platform","authors":"Tran Quy Ban, Phan Lac Duong, Nguyễn Hoàng Sơn, Tran Van Dinh","doi":"10.1109/ICCI51257.2020.9247632","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247632","url":null,"abstract":"In less than three months after its emergence in China, the Covid-19 pandemic has spread to at least 180 countries. In the absence of previous experience with this new disease, public health authorities have implemented many experiments in a short period and, in a mostly uninformed way, various combinations of interventions at different scales. These include a ban on large gatherings, closure of borders— individual and collective containment, monitoring of population movements, social tracing, social distancing, etc. However, as the pandemic is progressing, data are collected from various sources. On the one hand, authorities allow to make informed adjustments to the current and planned interventions and reveal them. On the other hand, an urgent need for tools and methodologies that enable fast analysis, understanding, comparison, and forecasting of the effectiveness of the responses against COVID-19 across different communities and contexts. In this perspective, computational modeling appears as invaluable leverage as it allows us to explore in silico a range of intervention strategies before the potential phase of field implementation.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127971992","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: 5

Semantic Segmentation for Visually Adverse Images – A Critical Review 视觉不良图像的语义分割研究综述

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247758

M. Hashmani, M. Memon, Kamran Raza

{"title":"Semantic Segmentation for Visually Adverse Images – A Critical Review","authors":"M. Hashmani, M. Memon, Kamran Raza","doi":"10.1109/ICCI51257.2020.9247758","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247758","url":null,"abstract":"Semantic Segmentation is one of the high-end visual tasks that has remained a topic of interest in various domains. Segmentation of visual scenes was confined to the extraction of object boundaries present in the image data. However, with the progressive developments in technology, machines are expected to produce assistive decisions to aid versatile tasks. Subsequently, these assistive decisions are dependent on efficient results and must project information on a granular level from the visual scenes. The visual scenes are usually of vast variety depending on the scenarios in which the image data is captured. As per recent trends, semantic segmentation is still an open area of research, one of its worth mentioning challenges is to handle the visually adverse images. These visually adverse images are the result of low light/ high light, rain, fog and sometimes in the form of too many objects present in the scene. The study sheds light on the non-trivial problem and diverts attention to the gaps present in literature by providing in-depth critical analysis. This study comprehensively presents unidentified problems prevailing in existing semantic segmentation techniques. A critical literary study is conducted to examine the working mechanics of existing solutions to identify their limitations to produce accurate results for the visually adverse scenarios. The study discusses some of the possible reasons which result in erroneous semantic segmentation results for visually adverse images. Finally, the problems and challenges to be tackled are concluded which highlight the future direction of analysis.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122546665","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

Fine-tuned Surface Object Detection Applying Pre-trained Mask R-CNN Models 应用预训练掩模R-CNN模型的微调表面目标检测

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247666

Haruhiro Fujita, Masatoshi Itagaki, Kenta Ichikawa, Yew Kwang Hooi, Kazuyoshi Kawahara, A. Sarlan

引用次数: 3

Binary Grey Wolf Optimizer with K-Nearest Neighbor classifier for Feature Selection 基于k近邻分类器的特征选择二元灰狼优化器

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247792

Ranya Al-wajih, Said Jadid Abdulakaddir, Norshakirah Aziz, Qasem Al-Tashi

引用次数: 2

A Preliminary Study on the Factors Affecting the Adoption of E-Government Services by Malaysians 马来西亚人采用电子政务服务的影响因素初探

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247752

Joel Lim Yong Jin, Aamir Amin

{"title":"A Preliminary Study on the Factors Affecting the Adoption of E-Government Services by Malaysians","authors":"Joel Lim Yong Jin, Aamir Amin","doi":"10.1109/ICCI51257.2020.9247752","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247752","url":null,"abstract":"E-government is no longer stranger to everyone in this technological era. In Malaysia, e-government was used to enhance governmental processes and services and to shorten the time and increase efficiency. It is also known to enhance communication between government, citizens, businesses, agencies. However, it is reported that the government’s objective is not aligned with citizens’ needs in implementing e-government. After the adoption of e-government services by the Malaysian government, it is crucial to study the adoption of these services by Malaysian citizens and the factors which affect this adoption. Through Technology Acceptance Model, the present study has proposed a theoretical framework for the impact of social influence, awareness, perceived usefulness, perceived ease of use, and behavioral intention on the actual usage of online services by Malaysian citizens. The results show that social influence and awareness of the online services are significant predictors of perceived usefulness as well as perceived ease of use. In the future, the proposed framework will be statistically validated by first collecting the data from Malaysian citizens and then analyzing the data with the use of statistical software tools. This study will provide significant value towards the Knowledge Body which pertains to e-services, especially in Malaysia.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"186 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114091392","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

IoT based Secure Digital Forensic Process according to Process Management 基于流程管理的物联网安全数字取证流程

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247710

Venkata Venugopal Rao Gudlur Saigopal, Dr. Valliappan Raju

{"title":"IoT based Secure Digital Forensic Process according to Process Management","authors":"Venkata Venugopal Rao Gudlur Saigopal, Dr. Valliappan Raju","doi":"10.1109/ICCI51257.2020.9247710","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247710","url":null,"abstract":"the implementation of Secure FI process by digitally by adapting the IoT based connecting many wireless smart devices may expose security vulnerabilities. The DF related to IoT based can be characterized as a field of study however ought to be utilized in defensive condition which is absence of the present world and the use of innovative and constant techniques for collect, preserve, validate, analyze, interpret and present the evidences extracted using the forensic tools and carefully separated from various sources and presenting official courtroom for justice and fair judicial processor legal cycle. The IoT smart devices will require appropriate procedural and ensured remote condition with safer and secure information reinforcement in place from secure home control to cutting edge city the executives connected networks. The smart gadgets will detect their condition with interconnected one another to shape canny brilliant spaces and any suspected or unapproved occasion will be put away and set off to the requirement office to heighten the issue or Forensic examination [1], [2]. These smart devices all things considered produce and store enormous sum delicate criminological information. The paper clarifies the current Process by zeroing in and improving on pre and post examination measure with more solid and secure cycle with back up Data stockpiling with proof. The information stream from Pre-examination to post examination and capacity or cloud-based focusing on key zones of character on irregular action registering impressions to the worker (pre-examination) when recognized and continue to post examination with assessment and sparing the information in to make sure storage.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115784558","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: 2

An Evolutionary Stream Clustering Technique for Outlier Detection 一种用于离群点检测的进化流聚类技术

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247832

Nadilah Ayu Supardi, S. J. Abdulkadir, Norshakirah Aziz

{"title":"An Evolutionary Stream Clustering Technique for Outlier Detection","authors":"Nadilah Ayu Supardi, S. J. Abdulkadir, Norshakirah Aziz","doi":"10.1109/ICCI51257.2020.9247832","DOIUrl":"https://doi.org/10.1109/ICCI51257.2020.9247832","url":null,"abstract":"Clustering data streams appeared to be the most popular studies among the researchers due to their developing field. Data streams address numerous threats on clustering such as limited time, memory and single scan clustering. Besides, identifying arbitrary shapes clusters approach are very significant in data streams applications. Data streams are an infinite sequence of the element, evolve over time with no knowledge on the number of the clusters. Various factors such as some noise appear occasionally have the potential to negatively impact on data streams environment. The density-based technique is proven to be an astounding method in clustering data streams. It is computationally efficient to yield arbitrary shape clusters and detect noise immediately. Generally, it does not require the number of clusters in advance. Most of the traditional density-based clustering is not applicable in data streams due to its own characteristics. Nearly all traditional density-based clustering algorithms can be extended to the latest ones for data streams study purposes. This concept is mainly focused on the density-based technique in the clustering process to overcome the constraint from data streams nature. This paper proposes a preliminary result on a density-based algorithm (evoStream) for clustering which is to investigate outlier detection on three different real data sets named, KDDCup99, sensor and power supply. Later, this algorithm will be extended to optimize the model in detecting outlier on data streams.","PeriodicalId":194158,"journal":{"name":"2020 International Conference on Computational Intelligence (ICCI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123309863","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: 2

SCADA System Framework for Monitoring, Controlling and Data Logging of Industrial Processing Plants 用于工业加工厂监控和数据记录的SCADA系统框架

2020 International Conference on Computational Intelligence (ICCI) Pub Date : 2020-10-08 DOI: 10.1109/ICCI51257.2020.9247645

S. S. Mohani, Muhammad Khalid, Syed Saiq Hussain, Shahwaiz Ghori, Hamza Akbar

引用次数: 0