Pub Date : 2018-12-01DOI: 10.1109/ICONIC.2018.8601246
Temitope Oluwafunmilayo Adetunji, T. Zuva, M. Appiah
The global use of the internet has improved the growth of the educational sector over the years, while electronic assessments have turn out to be one of the major tools in the development of both non-academic and academic establishments. The effective assessment of a student is mostly perceived as one of the foremost challenges that is frequently experienced during online examination in that it can be very difficult to provide accurate user authentication. The requirement to secure and authenticate a user during e-assessments owing to the high rate of misconduct has led to the proposal of this research. The purpose is to examine potential threats to student authentication during e-assessments and propose a framework which uses a bi-modal authentication approach to provide successful authentication during e-assessment. In implementing this approach, we propose a framework that provides security to improve e-assessments by introducing authentication classifiers to demonstrate its application in biometrics technologies. The proposed model was evaluated based on set of thresholds using Accuracy, FAR and FRR as performance metrics. the proposed model gave a high accuracy of 94.52%. The single-modal model of keystrokes had percentage accuracy of 92.025% and face had percentage accuracy of 92.58%. This implies that the bimodal model integrating keystrokes and face outperforms the single-modal model of keystrokes and single-modal model of face respectively. The study concludes that the proposed model contributes to existing works on e-assessment systems by integrating keystrokes and face bimodal biometric to optimally minimize fraud and impersonation thereby providing accurate authentication of a user.
{"title":"A Framework of Bimodal Biometrics for E-assessment Authentication Systems","authors":"Temitope Oluwafunmilayo Adetunji, T. Zuva, M. Appiah","doi":"10.1109/ICONIC.2018.8601246","DOIUrl":"https://doi.org/10.1109/ICONIC.2018.8601246","url":null,"abstract":"The global use of the internet has improved the growth of the educational sector over the years, while electronic assessments have turn out to be one of the major tools in the development of both non-academic and academic establishments. The effective assessment of a student is mostly perceived as one of the foremost challenges that is frequently experienced during online examination in that it can be very difficult to provide accurate user authentication. The requirement to secure and authenticate a user during e-assessments owing to the high rate of misconduct has led to the proposal of this research. The purpose is to examine potential threats to student authentication during e-assessments and propose a framework which uses a bi-modal authentication approach to provide successful authentication during e-assessment. In implementing this approach, we propose a framework that provides security to improve e-assessments by introducing authentication classifiers to demonstrate its application in biometrics technologies. The proposed model was evaluated based on set of thresholds using Accuracy, FAR and FRR as performance metrics. the proposed model gave a high accuracy of 94.52%. The single-modal model of keystrokes had percentage accuracy of 92.025% and face had percentage accuracy of 92.58%. This implies that the bimodal model integrating keystrokes and face outperforms the single-modal model of keystrokes and single-modal model of face respectively. The study concludes that the proposed model contributes to existing works on e-assessment systems by integrating keystrokes and face bimodal biometric to optimally minimize fraud and impersonation thereby providing accurate authentication of a user.","PeriodicalId":277315,"journal":{"name":"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128917789","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}
Pub Date : 2018-12-01DOI: 10.1109/ICONIC.2018.8601202
R. Moloo, Kavi Kumar Khedo, T. Prabhakar
This work is a continuation of a larger research work which advocates that Distance Education (DE) through audio-only learning mode can be developed into a full fledge audio-MOOC. Audio MOOC framework is an innovative framework which enables learning through mere phone calls. It has been conceived to digitally include low literate population in the education process by opening up access to learning materials to the unreached and the have-nots usually hindered by barriers such as language, literacy, culture, connectivity and distance which existing MOOCs have failed to address. This work demonstrates how our proposed framework is used to connect to a remote island lost in the middle of the Indian Ocean with limited maritime and air access but which since some few years back can be connected via basic phones through voice calls. Agalega is an ideal test case scenario for our research since it characterizes remoteness, limited connectivity, semi-literate population with limited access to education which our research aims at addressing. A group of 50 Fishermen was identified from both the Agalega islands. The course was of 9 days duration from 15 to 23 September 2017. The system was conducted live over the telephony network making use of our GSM gateway. The specificity of the system was that our GSM gateway resided in Mauritius connected to a cloud server, while the course was delivered to people of Agalega 1100 Km far from Mauritius over the sea. Nevertheless, our system performed as expected and proved to be a success.
{"title":"Delivery of an Interactive Audio Course on Fisheries Law via Dumb Phones: Agalega Island as a Case Study for Testing a Novel Distance Education Platform - The Audio MOOC","authors":"R. Moloo, Kavi Kumar Khedo, T. Prabhakar","doi":"10.1109/ICONIC.2018.8601202","DOIUrl":"https://doi.org/10.1109/ICONIC.2018.8601202","url":null,"abstract":"This work is a continuation of a larger research work which advocates that Distance Education (DE) through audio-only learning mode can be developed into a full fledge audio-MOOC. Audio MOOC framework is an innovative framework which enables learning through mere phone calls. It has been conceived to digitally include low literate population in the education process by opening up access to learning materials to the unreached and the have-nots usually hindered by barriers such as language, literacy, culture, connectivity and distance which existing MOOCs have failed to address. This work demonstrates how our proposed framework is used to connect to a remote island lost in the middle of the Indian Ocean with limited maritime and air access but which since some few years back can be connected via basic phones through voice calls. Agalega is an ideal test case scenario for our research since it characterizes remoteness, limited connectivity, semi-literate population with limited access to education which our research aims at addressing. A group of 50 Fishermen was identified from both the Agalega islands. The course was of 9 days duration from 15 to 23 September 2017. The system was conducted live over the telephony network making use of our GSM gateway. The specificity of the system was that our GSM gateway resided in Mauritius connected to a cloud server, while the course was delivered to people of Agalega 1100 Km far from Mauritius over the sea. Nevertheless, our system performed as expected and proved to be a success.","PeriodicalId":277315,"journal":{"name":"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124932461","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}
Pub Date : 2018-12-01DOI: 10.1109/ICONIC.2018.8601096
Fawaz S. Al-Anzi, Dia AbuZeina
The Vector Space Model (VSM) is a common document representation model that is widely used in data mining and information retrieval (IR) systems. However, this technique poses some challenges such as high dimensional space and semantic loss representation. Therefore, the latent semantic indexing (LSI) is proposed to reduce the feature dimensions and to generate semantic rich features that represent conceptual term-document associations. In particular, LSI has been successfully implemented in search engines and text classification tasks. In this paper, we propose a novel approach to enhance the quality of the retrieved documents in search engines for Arabic language. That is, we propose to use a new extension of the LSI technique instead of just using the standard LSI technique. The LSI method proposed is based on employing the word co-occurrences to form a term-by-document matrix. The proposed method is to be based on the documents evaluating cosine similarity measures for term-by-document matrix. We will empirically evaluate the performance using an Arabic data collection that contains no less than 500 documents with no less than 30,000 unique words. A testing set contains keywords from a specific domain will be used to evaluate the quality of the top 20-30 retrieved documents using different singular values (i.e. different number of dimensions). The results will be judged on the performance of the proposed method as it is compared to the standard LSI.
{"title":"Enhanced Search for Arabic Language Using Latent Semantic Indexing (LSI)","authors":"Fawaz S. Al-Anzi, Dia AbuZeina","doi":"10.1109/ICONIC.2018.8601096","DOIUrl":"https://doi.org/10.1109/ICONIC.2018.8601096","url":null,"abstract":"The Vector Space Model (VSM) is a common document representation model that is widely used in data mining and information retrieval (IR) systems. However, this technique poses some challenges such as high dimensional space and semantic loss representation. Therefore, the latent semantic indexing (LSI) is proposed to reduce the feature dimensions and to generate semantic rich features that represent conceptual term-document associations. In particular, LSI has been successfully implemented in search engines and text classification tasks. In this paper, we propose a novel approach to enhance the quality of the retrieved documents in search engines for Arabic language. That is, we propose to use a new extension of the LSI technique instead of just using the standard LSI technique. The LSI method proposed is based on employing the word co-occurrences to form a term-by-document matrix. The proposed method is to be based on the documents evaluating cosine similarity measures for term-by-document matrix. We will empirically evaluate the performance using an Arabic data collection that contains no less than 500 documents with no less than 30,000 unique words. A testing set contains keywords from a specific domain will be used to evaluate the quality of the top 20-30 retrieved documents using different singular values (i.e. different number of dimensions). The results will be judged on the performance of the proposed method as it is compared to the standard LSI.","PeriodicalId":277315,"journal":{"name":"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128063159","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}
Pub Date : 2018-12-01DOI: 10.1109/ICONIC.2018.8601294
Yaseen Khan, S. Thakur
Internet platforms such as Twitter allow cause-related campaigning as well as analysis through the opportunistic classification and aggregation capability provided by the hashtag (#). South African students leveraged Twitter to launch and sustain a campaign now known as the #FeesMustFall campaign. This campaign aimed to lobby government to provide free university education to disadvantaged students. This study examines the #FeesMustFall campaign to determine if automated software robots played a role. The research question was "Did bots and cyborgs play a role in the #FeesMustFall campaign?" 576 823 tweets were harvested, and the data was cleaned by removing duplicate entries. The remaining 490 449 tweets and 90 783 unique users were used to analyze tweet behavior in terms of frequency, volume, content and tweet source. The results show that bots and cyborgs did indeed play a role. This is a significant finding as #FeesMustFall is the first major South African campaign to leverage bots and cyborgs. An important additional finding was the DeBot API revealed 4 bots not found in our harvested tweets while other trait-driven techniques used identified suspicious accounts which revealed two bot or cyborg accounts ranked 1st and 2nd amongst the highest tweeters. This demonstrated a presence of bots during the campaign that assisted in the amplification of the #FeesMustFall hashtag on Twitter.
像Twitter这样的互联网平台允许与事业相关的竞选活动，以及通过标签(#)提供的机会分类和聚合功能进行分析。南非学生利用Twitter发起并维持了一项运动，现在被称为#学费必须下降运动。这项运动旨在游说政府为贫困学生提供免费大学教育。本研究考察了#FeesMustFall运动，以确定自动化软件机器人是否发挥了作用。研究的问题是“机器人和半机器人在#学费必须下降运动中发挥了作用吗?”收集了576 823条tweet，并通过删除重复条目来清理数据。剩余的490449条推文和90783个独立用户从频率、数量、内容和推文来源等方面分析推文行为。结果表明，机器人和半机械人确实发挥了作用。这是一个重要的发现，因为# fee must fall是南非第一个利用机器人和电子人的大型运动。另一个重要的发现是，DeBot API发现了我们收集的推文中没有发现的4个机器人，而使用的其他特征驱动技术发现了可疑账户，其中两个机器人或半机械人账户在推特用户中排名第一和第二。这表明在竞选期间机器人的存在，帮助扩大了推特上的#FeesMustFall标签。
{"title":"The Presence of Twitter Bots and Cyborgs in the #FeesMustFall Campaign","authors":"Yaseen Khan, S. Thakur","doi":"10.1109/ICONIC.2018.8601294","DOIUrl":"https://doi.org/10.1109/ICONIC.2018.8601294","url":null,"abstract":"Internet platforms such as Twitter allow cause-related campaigning as well as analysis through the opportunistic classification and aggregation capability provided by the hashtag (#). South African students leveraged Twitter to launch and sustain a campaign now known as the #FeesMustFall campaign. This campaign aimed to lobby government to provide free university education to disadvantaged students. This study examines the #FeesMustFall campaign to determine if automated software robots played a role. The research question was \"Did bots and cyborgs play a role in the #FeesMustFall campaign?\" 576 823 tweets were harvested, and the data was cleaned by removing duplicate entries. The remaining 490 449 tweets and 90 783 unique users were used to analyze tweet behavior in terms of frequency, volume, content and tweet source. The results show that bots and cyborgs did indeed play a role. This is a significant finding as #FeesMustFall is the first major South African campaign to leverage bots and cyborgs. An important additional finding was the DeBot API revealed 4 bots not found in our harvested tweets while other trait-driven techniques used identified suspicious accounts which revealed two bot or cyborg accounts ranked 1st and 2nd amongst the highest tweeters. This demonstrated a presence of bots during the campaign that assisted in the amplification of the #FeesMustFall hashtag on Twitter.","PeriodicalId":277315,"journal":{"name":"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114297082","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}
Pub Date : 2018-12-01DOI: 10.1109/ICONIC.2018.8601288
I. Zicmane, K. Berzina, T. Lomane, Konstantins Kasperjuks
Creating decentralized energy supply systems, there arises the task of providing consumers with electric energy, the parameters of which satisfy the necessary requirements. This problem is especially acute when developing systems based on non-traditional sources using the mechanical energy of renewable natural resources. Taking into account the probabilistic nature of their changes, as well as the significant interaction with each other, the choice of operating modes, types and parameters of energy storage devices for such systems becomes quite a complex and ambiguous task of innovative technologies. The article is devoted to the solution of the problem of developing technical solutions for conjugation of various renewable energy sources ensuring guaranteed electricity supply to autonomous consumers and increasing the energy efficiency of such a system as a whole.
{"title":"Improving the Energy Efficiency of an Autonomous Power System with Renewable Sources","authors":"I. Zicmane, K. Berzina, T. Lomane, Konstantins Kasperjuks","doi":"10.1109/ICONIC.2018.8601288","DOIUrl":"https://doi.org/10.1109/ICONIC.2018.8601288","url":null,"abstract":"Creating decentralized energy supply systems, there arises the task of providing consumers with electric energy, the parameters of which satisfy the necessary requirements. This problem is especially acute when developing systems based on non-traditional sources using the mechanical energy of renewable natural resources. Taking into account the probabilistic nature of their changes, as well as the significant interaction with each other, the choice of operating modes, types and parameters of energy storage devices for such systems becomes quite a complex and ambiguous task of innovative technologies. The article is devoted to the solution of the problem of developing technical solutions for conjugation of various renewable energy sources ensuring guaranteed electricity supply to autonomous consumers and increasing the energy efficiency of such a system as a whole.","PeriodicalId":277315,"journal":{"name":"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122607355","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}
Pub Date : 2018-12-01DOI: 10.1109/ICONIC.2018.8601243
Mduduzi Manana, Chunling Tu, P. Owolawi
This paper presents a pre-processed faster region convolution neural network (faster RCNN) for the purpose of on-road vehicle detection. The system introduces a preprocessing pipeline on faster RCNN. The preprocessing method is for the improvement on training and detection speed of Faster RCNN. A preprocessing lane detection pipeline based on the Sobel edge operator and Hough Transform is used to detect lanes. A Rectangular region is then extracted from lane coordinates which is a reduced region of interest (ROI). Results show that the proposed method improves the training speed of faster RCNN when compared to faster RCNN without preprocessing.
{"title":"Preprocessed Faster RCNN for Vehicle Detection","authors":"Mduduzi Manana, Chunling Tu, P. Owolawi","doi":"10.1109/ICONIC.2018.8601243","DOIUrl":"https://doi.org/10.1109/ICONIC.2018.8601243","url":null,"abstract":"This paper presents a pre-processed faster region convolution neural network (faster RCNN) for the purpose of on-road vehicle detection. The system introduces a preprocessing pipeline on faster RCNN. The preprocessing method is for the improvement on training and detection speed of Faster RCNN. A preprocessing lane detection pipeline based on the Sobel edge operator and Hough Transform is used to detect lanes. A Rectangular region is then extracted from lane coordinates which is a reduced region of interest (ROI). Results show that the proposed method improves the training speed of faster RCNN when compared to faster RCNN without preprocessing.","PeriodicalId":277315,"journal":{"name":"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126536260","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}
Pub Date : 2018-12-01DOI: 10.1109/ICONIC.2018.8601219
K. Akom, M. Joseph, T. Shongwe
Due to the high cost of fuel and as unfavourable weather conditions which have affected power generation in Ghana, the country has experienced power crises for the past seven years. Renewable Energy Resources (RES) like wind and solar are being considered by many countries as alternatives for the energy requirements of the country. Ghana’s Energy Commission’s (EC) report in October, 2017 indicated that, RE contributes 2MW of power to the country’s energy mix, representing about 1.73% of the total installed capacity. However, the current EC’s energy policy has projected 600MW power through RE in 2030. 340 MW from solar and 260 MW from wind energies. The then Ministry of Energy through the Energy Commission started the rooftop PV programme implementation in early 2016 in some government institutions. The main aim of the rooftop programme was to produce about 200 MW maximum load respite on the national grid as a medium term programme through PV solar technology. However, RE and grid integration has various issues and challenges, large scale RE power generation are mainly connected to the transmission systems and small-scale generation are mostly linked with the distribution system. Direct integration these systems poses a lot of challenges and issues. This paper examines the main issues and proposes some probable solutions for future RE generations and integration.
{"title":"Renewable Energy Sources and Grid Integration in Ghana: Issues, Challenges and Solutions","authors":"K. Akom, M. Joseph, T. Shongwe","doi":"10.1109/ICONIC.2018.8601219","DOIUrl":"https://doi.org/10.1109/ICONIC.2018.8601219","url":null,"abstract":"Due to the high cost of fuel and as unfavourable weather conditions which have affected power generation in Ghana, the country has experienced power crises for the past seven years. Renewable Energy Resources (RES) like wind and solar are being considered by many countries as alternatives for the energy requirements of the country. Ghana’s Energy Commission’s (EC) report in October, 2017 indicated that, RE contributes 2MW of power to the country’s energy mix, representing about 1.73% of the total installed capacity. However, the current EC’s energy policy has projected 600MW power through RE in 2030. 340 MW from solar and 260 MW from wind energies. The then Ministry of Energy through the Energy Commission started the rooftop PV programme implementation in early 2016 in some government institutions. The main aim of the rooftop programme was to produce about 200 MW maximum load respite on the national grid as a medium term programme through PV solar technology. However, RE and grid integration has various issues and challenges, large scale RE power generation are mainly connected to the transmission systems and small-scale generation are mostly linked with the distribution system. Direct integration these systems poses a lot of challenges and issues. This paper examines the main issues and proposes some probable solutions for future RE generations and integration.","PeriodicalId":277315,"journal":{"name":"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126655705","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}
Pub Date : 2018-12-01DOI: 10.1109/ICONIC.2018.8601258
Mariapaola Saponaro, Diane Le Gal, Manjiao Gao, Matthieu Guisiano, I. Manière
This article is depicting the Strengths and weaknesses of Artificial Intelligence related to the improvement of customer online and offline experience, and the possible methods in order to measure them. These methods include both researches non-based and based on interviews. The presence of AI in the retail industry is becoming a key component of the customer experience. Through a deep analysis of existing tools to extract information, we try to explain ways to interpret them, in order for companies to create a real usage out of them, either on online or offline retail experience. Hence, with this research, we also want to provide an insight on how this experience could be improved in the future, and how it will most likely be inherent to our daily customer experience.
{"title":"Challenges and Opportunities of Artificial Intelligence in the Fashion World","authors":"Mariapaola Saponaro, Diane Le Gal, Manjiao Gao, Matthieu Guisiano, I. Manière","doi":"10.1109/ICONIC.2018.8601258","DOIUrl":"https://doi.org/10.1109/ICONIC.2018.8601258","url":null,"abstract":"This article is depicting the Strengths and weaknesses of Artificial Intelligence related to the improvement of customer online and offline experience, and the possible methods in order to measure them. These methods include both researches non-based and based on interviews. The presence of AI in the retail industry is becoming a key component of the customer experience. Through a deep analysis of existing tools to extract information, we try to explain ways to interpret them, in order for companies to create a real usage out of them, either on online or offline retail experience. Hence, with this research, we also want to provide an insight on how this experience could be improved in the future, and how it will most likely be inherent to our daily customer experience.","PeriodicalId":277315,"journal":{"name":"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130005871","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}
Pub Date : 2018-12-01DOI: 10.1109/ICONIC.2018.8601257
Fhatuwani Vivian Mapande, M. Appiah
E-commerce has many advantages reflected in our life, as it makes the daily life of people convenient. This paper aims to investigate the factors influencing customers to conduct online shopping. The paper used the quantitative approach where questionnaires were used to gather information in the format of a survey. For e-commerce adoption factors, Diffusion of Innovation (DOI) model was used to assess participants’ perspectives when it comes to the adoption of e-commerce. More specifically, the paper proposed the framework for South African customers. The proposed framework was tested on a sample of South African residents. The final sample consisted of 235 respondents. The reliability of the questionnaire was thoroughly examined. Empirical data were analyzed using the linear regression. The results of the research revealed that privacy & security, customer trust, perceived service quality, IT knowledge and Relative advantage are significant factors in influencing customers to adopt e-commerce. On the other hand, privacy was found not to be the statistically significant impact on the adoption of e-commerce.
{"title":"The Factors Influencing Customers to Conduct Online Shopping: South African Perspective","authors":"Fhatuwani Vivian Mapande, M. Appiah","doi":"10.1109/ICONIC.2018.8601257","DOIUrl":"https://doi.org/10.1109/ICONIC.2018.8601257","url":null,"abstract":"E-commerce has many advantages reflected in our life, as it makes the daily life of people convenient. This paper aims to investigate the factors influencing customers to conduct online shopping. The paper used the quantitative approach where questionnaires were used to gather information in the format of a survey. For e-commerce adoption factors, Diffusion of Innovation (DOI) model was used to assess participants’ perspectives when it comes to the adoption of e-commerce. More specifically, the paper proposed the framework for South African customers. The proposed framework was tested on a sample of South African residents. The final sample consisted of 235 respondents. The reliability of the questionnaire was thoroughly examined. Empirical data were analyzed using the linear regression. The results of the research revealed that privacy & security, customer trust, perceived service quality, IT knowledge and Relative advantage are significant factors in influencing customers to adopt e-commerce. On the other hand, privacy was found not to be the statistically significant impact on the adoption of e-commerce.","PeriodicalId":277315,"journal":{"name":"2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126432768","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}
Pub Date : 2018-12-01DOI: 10.1109/ICONIC.2018.8601277
Tsítso Maphatsoe, M. Masinde
The prospects of achieving a trillion connected internet of things (IoT) devices by 2020 has created the urgency for effective intrusion detection systems (IDS) for these devices. Although it has been argued that the most effective technique used in such systems is anomaly detection, there exist no mechanisms to determine their performance in real-life deployment. In this paper, we report the results of applying asymptotic analysis to evaluate the performance of an anomaly detection algorithm which is designed using logic reasoning through fuzzy logic methodologies. In order to achieve this, the IDS was included as part of intrusion detection software for ZigBee Wireless Sensor Networks (WSNs). In particular, the solution is targeted to address the ZigBee protocol’s vulnerability to flood attacks during node discovery and association to the network. The intrusion detection software is hosted external to the WSNs in pursue of a light solution mindful of resource preservation in sensor nodes.
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