Int. J. Sociotechnology Knowl. Dev.最新文献_第10页

Automatic Gun Detection Approach for Video Surveillance 用于视频监控的枪支自动检测方法

Int. J. Sociotechnology Knowl. Dev. Pub Date : 2020-01-01 DOI: 10.4018/ijskd.2020010103

Mai Kamal el den Mohamed, A. Taha, H. Zayed

{"title":"Automatic Gun Detection Approach for Video Surveillance","authors":"Mai Kamal el den Mohamed, A. Taha, H. Zayed","doi":"10.4018/ijskd.2020010103","DOIUrl":"https://doi.org/10.4018/ijskd.2020010103","url":null,"abstract":"The immense crime rates resulting from using pistols have led governments to seek solutions to deal with such terrorist incidents. These incidents have a negative impact on public security and cause panic among citizens. From this point, facing a pandemic of weapon violence has become an important research topic. One way to reduce this kind of violence is to prevent it via remote detection and to give an appropriate response in a short time. Video surveillance is the process of monitoring the behavior of people and objects. Surveillance systems can be employed in security applications as legal evidence. Moreover, it is used widely in suspicious activity detection applications. Intelligent video surveillance systems (IVSSs) are the use of automatic video analytics to enhance the effectiveness of traditional surveillance systems. With the rapid development in Deep Learning (DL), it is now widely used to address the problems existing in traditional detection techniques. In this article, an approach to detect pistols and guns in video surveillance systems is proposed. The presented approach does not need any invasive tools in the weapon detection process. It uses DL in the classification and the detection processes. The proposed approach enhances the obtained results by applying Transfer Learning (TL). It employs two different DL techniques: AlexNet and GoogLeNet. Experimental results verify the adaptability of detecting different types of pistols and guns. The experiments were conducted on a benchmark gun database called Internet Movie Firearms Database (IMFDB). The results obtained suggest that the proposed approach is promising and outperforms its counterparts.","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"5 1","pages":"49-66"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88885250","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: 11

Copy-Move Forgery Detection Based on Automatic Threshold Estimation 基于自动阈值估计的复制移动伪造检测

Int. J. Sociotechnology Knowl. Dev. Pub Date : 2020-01-01 DOI: 10.4018/ijskd.2020010101

A. Hegazi, A. Taha, M. Selim

{"title":"Copy-Move Forgery Detection Based on Automatic Threshold Estimation","authors":"A. Hegazi, A. Taha, M. Selim","doi":"10.4018/ijskd.2020010101","DOIUrl":"https://doi.org/10.4018/ijskd.2020010101","url":null,"abstract":"Recently,usersandnewsfollowersacrosswebsitesfacemanyfabricatedimages.Moreover,itgoes farbeyondthattothepointofdefamingorimprisoningaperson.Hence,imageauthenticationhas becomeasignificantissue.Oneofthemostcommontamperingtechniquesiscopy-move.Keypointbasedmethodsareconsideredasaneffectivemethodfordetectingcopy-moveforgeries. Insuch methods,thefeatureextractionprocessisfollowedbyapplyingaclusteringtechniquetogroupspatially closekeypoints.Mostclusteringtechniqueshighlydependontheexistenceofaspecificthreshold toterminatetheclustering.Determinationofthemostsuitablethresholdrequiresahugeamountof experiments.Inthisarticle,acopy-moveforgerydetectionmethodisproposed.Theproposedmethod isbasedonautomaticestimationoftheclusteringthreshold.Thecutoffthresholdofhierarchical clusteringisestimatedautomaticallybasedonclusteringevaluationmeasures.Experimentalresults testedonvariousdatasetsshowthattheproposedmethodoutperformsotherrelevantstate-of-the-art methods. KEywoRDS Clustering Evaluation Measures, Copy-Move Detection, Image Forensics, Keypoint-Based Methods, MultipleCopied Matching","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"138 1","pages":"1-23"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78516760","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: 6

Organisational Memory and its Impact on Competitive Strategies in IT Companies in Jordan 组织记忆及其对约旦IT公司竞争战略的影响

Int. J. Sociotechnology Knowl. Dev. Pub Date : 2019-10-01 DOI: 10.4018/ijskd.2019100104

Ghassan Issa Al Omari, M. Maraqa, M. Al-Jarrah

引用次数: 3

Using Social Media in Education and Using Social Media Strategies in Education and Corporate Organizations in the U.S. and Belarus: A Practitioner Study 在教育中使用社会媒体以及在美国和白俄罗斯的教育和企业组织中使用社会媒体策略:一项实践者研究

Int. J. Sociotechnology Knowl. Dev. Pub Date : 2019-10-01 DOI: 10.4018/ijskd.2019100102

M. O. Vilceanu, Suzanne Fitzgerald, Jekaterina Yurievna Sadovskaya

{"title":"Using Social Media in Education and Using Social Media Strategies in Education and Corporate Organizations in the U.S. and Belarus: A Practitioner Study","authors":"M. O. Vilceanu, Suzanne Fitzgerald, Jekaterina Yurievna Sadovskaya","doi":"10.4018/ijskd.2019100102","DOIUrl":"https://doi.org/10.4018/ijskd.2019100102","url":null,"abstract":"Rapid growth of new media technologies allows organizations to communicate with consumers in immediate and interactive ways via blogs and social media websites such as Facebook and Twitter. Consumers, companies, and organizations bypass mass media gatekeepers and engage in direct communication exchanges. This study examines social media efficacy from the perspective of corporate and educational organizations in the United States and Belarus. Using the Delphi method, authors administered iterative surveys to a panel of sixteen experts, seeking consensus points. Access to financial, staff, and technical resources allow corporations to make intensive and effective use of social media. Non-profit and education organizations are interested in ability to relate to stakeholders by low-cost technologies, human interest stories, and personal connections. US organizations valued appropriateness for target audience as the most important factor in evaluating the best use of social media. Belorussian organizations valued effectiveness of the channel itself or ease of use.","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"13 1","pages":"20-33"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89487688","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

Weighted Rough Set Theory for Fetal Heart Rate Classification 胎儿心率分类的加权粗糙集理论

Int. J. Sociotechnology Knowl. Dev. Pub Date : 2019-10-01 DOI: 10.4018/ijskd.2019100101

S. U. Kumar, A. Azar, H. Inbarani, O. J. Liyaskar, K. Almustafa

{"title":"Weighted Rough Set Theory for Fetal Heart Rate Classification","authors":"S. U. Kumar, A. Azar, H. Inbarani, O. J. Liyaskar, K. Almustafa","doi":"10.4018/ijskd.2019100101","DOIUrl":"https://doi.org/10.4018/ijskd.2019100101","url":null,"abstract":"A novel weighted rough set-based classification approach is introduced for the evaluation of fetal nature acquired from a CardioTocoGram (CTG) signal. The classification is essential to anticipate newborn's well-being, particularly for the life-threatening cases. CTG monitoring comprises of electronic fetal heart rate (FHR), fetal activities and the uterine contraction (UC) signals. These signals are extensively used as a part of the pregnancy and give extremely significant data on fetal health. The obtained data from these recordings can be utilized to anticipate the condition of the newborn baby, which gives an open door for early medication before perpetual deficiency to the fetus. The dimension of the obtained features from CTG is high and decreases the accuracy of classification algorithms. In this article, supervised particle swarm optimization (PSO) with a rough set-based dimensionality reduction method is used to find a minimal set of significant features from CTG extracted features. The proposed weighted rough set classifier (WRSC) method is utilized for predicting the fetal condition as normal and pathological states. The performance of the proposed WRSC algorithm is compared with various classification algorithms such as bijective soft set neural network classifier (BISONN), rough set-based classifier (RST), multi-layered perceptron (MLP), decision table (DT), Java repeated incremental pruning (JRIP) classifier, J48 and Naïve Bayes (NB) classifiers. The experimental results demonstrated that the proposed algorithm is capable of forecasting the fetal state with 98.5% classification accuracy, and the results show that the proposed classification algorithm performed considerably superior than other classification techniques.","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"235 1","pages":"1-19"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75720699","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: 7

Innovation in a Context of Declining Returns to R&D: A Critical Review of Novel Theoretical Developments 研发收益下降背景下的创新:对新理论发展的批判性回顾

Int. J. Sociotechnology Knowl. Dev. Pub Date : 2019-10-01 DOI: 10.4018/ijskd.2019100103

C. Callaghan

引用次数: 1

Employment and Technology in Manufacturing 制造业中的就业与技术

Int. J. Sociotechnology Knowl. Dev. Pub Date : 2019-07-01 DOI: 10.4018/IJSKD.2019070102

Alister McLeod

引用次数: 3

The Concept of Big Data in Bureaucratic Service Using Sentiment Analysis 基于情感分析的官僚服务大数据概念

Int. J. Sociotechnology Knowl. Dev. Pub Date : 2019-07-01 DOI: 10.4018/IJSKD.2019070101

L. Muliawaty, Kamal Alamsyah, Ummu Salamah, D. Maylawati

引用次数: 9

Modeling the Success of Windows Domain Network (WDN) Using the DeLone and McLean Information System (IS) Success Model: A University Case 用DeLone和McLean信息系统(IS)成功模型建模Windows域网络(WDN)的成功:一个大学案例

Int. J. Sociotechnology Knowl. Dev. Pub Date : 2019-07-01 DOI: 10.4018/IJSKD.2019070103

M. Himang, Eduardo Mendoza, Rebecca Manalastas, L. Ocampo, Celbert M. Himang

引用次数: 12

Leveraging Technology for Talent Management: Foresight for Organizational Performance 利用技术进行人才管理:组织绩效的前瞻

Int. J. Sociotechnology Knowl. Dev. Pub Date : 2019-04-01 DOI: 10.4018/IJSKD.2019040102

Brijesh Sivathanu, Rajasshrie Pillai

引用次数: 13