Pub Date : 2018-03-19DOI: 10.1109/MINTC.2018.8363161
G. Bhatia, Ismail Al Noutaki, Sheikha Al Ruzeiqi, Jawaher Al Maskari
Higher Education Institutions requires ready to access dedicated devices and various operating systems to assist in teaching, learning various courses. Due to the high cost of hardware, providing physical devices in ever changing IT field is neither economical nor feasible. A higher education IT course may demand specific software running on the specific operating system at particular hardware configuration. Different operating systems requirement and their complex installation and maintenance process poses difficulty to manage them. OpenStack can address both issues by providing IaaS for hardware resources and standard mechanism to manage and distribute course specific VMs. This paper provides design of private cloud for higher education and proof-of-concept implementation methodology for OpenStack platform. Furthermore, to facilitate the construction of the private cloud, the resource requirement model is formulated by which the requirement of physical resources can be measured for a specific number of virtual machines.
{"title":"Design and implementation of private cloud for higher education using OpenStack","authors":"G. Bhatia, Ismail Al Noutaki, Sheikha Al Ruzeiqi, Jawaher Al Maskari","doi":"10.1109/MINTC.2018.8363161","DOIUrl":"https://doi.org/10.1109/MINTC.2018.8363161","url":null,"abstract":"Higher Education Institutions requires ready to access dedicated devices and various operating systems to assist in teaching, learning various courses. Due to the high cost of hardware, providing physical devices in ever changing IT field is neither economical nor feasible. A higher education IT course may demand specific software running on the specific operating system at particular hardware configuration. Different operating systems requirement and their complex installation and maintenance process poses difficulty to manage them. OpenStack can address both issues by providing IaaS for hardware resources and standard mechanism to manage and distribute course specific VMs. This paper provides design of private cloud for higher education and proof-of-concept implementation methodology for OpenStack platform. Furthermore, to facilitate the construction of the private cloud, the resource requirement model is formulated by which the requirement of physical resources can be measured for a specific number of virtual machines.","PeriodicalId":250088,"journal":{"name":"2018 Majan International Conference (MIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126817126","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 : 2018-03-19DOI: 10.1109/MINTC.2018.8363162
Alrence S. Halibas, Abubucker Samsudeen Shaffi, Mohamed Mohamed
In the recent years, social networks in business are gaining unprecedented popularity because of their potential for business growth. Companies can know more about consumers' sentiments towards their products and services, and use it to better understand the market and improve their brand. Thus, companies regularly reinvent their marketing strategies and campaigns to fit consumers' preferences. Social analysis harnesses and utilizes the vast volume of data in social networks to mine critical data for strategic decision making. It uses machine learning techniques and tools in determining patterns and trends to gain actionable insights. This paper selected a popular food brand to evaluate a given stream of customer comments on Twitter. Several metrics in classification and clustering of data were used for analysis. A Twitter API is used to collect twitter corpus and feed it to a Binary Tree classifier that will discover the polarity lexicon of English tweets, whether positive or negative. A k-means clustering technique is used to group together similar words in tweets in order to discover certain business value. This paper attempts to discuss the technical and business perspectives of text mining analysis of Twitter data and recommends appropriate future opportunities in developing this emerging field.
{"title":"Application of text classification and clustering of Twitter data for business analytics","authors":"Alrence S. Halibas, Abubucker Samsudeen Shaffi, Mohamed Mohamed","doi":"10.1109/MINTC.2018.8363162","DOIUrl":"https://doi.org/10.1109/MINTC.2018.8363162","url":null,"abstract":"In the recent years, social networks in business are gaining unprecedented popularity because of their potential for business growth. Companies can know more about consumers' sentiments towards their products and services, and use it to better understand the market and improve their brand. Thus, companies regularly reinvent their marketing strategies and campaigns to fit consumers' preferences. Social analysis harnesses and utilizes the vast volume of data in social networks to mine critical data for strategic decision making. It uses machine learning techniques and tools in determining patterns and trends to gain actionable insights. This paper selected a popular food brand to evaluate a given stream of customer comments on Twitter. Several metrics in classification and clustering of data were used for analysis. A Twitter API is used to collect twitter corpus and feed it to a Binary Tree classifier that will discover the polarity lexicon of English tweets, whether positive or negative. A k-means clustering technique is used to group together similar words in tweets in order to discover certain business value. This paper attempts to discuss the technical and business perspectives of text mining analysis of Twitter data and recommends appropriate future opportunities in developing this emerging field.","PeriodicalId":250088,"journal":{"name":"2018 Majan International Conference (MIC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123530006","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 : 2018-03-19DOI: 10.1109/MINTC.2018.8363148
K. Stephen, V. Mathivanan
A Wireless sensor networks (WSN) typically has no infrastructure. It is composed of number of sensor nodes working together to monitor an environment to obtain data about it. Structured and unstructured are the two types of WSNs. An unstructured WSN contains a dense collection of sensor nodes. These sensors are small, computing resources, with limited processing and they are inexpensive. It can sense, measure, and gather information from the environment based on some local decision process; they can transmit the sensed data to the user. Security and lifetime of a sensor node in a network plays an important role. Data Securing is very important as these networks usually are put in dangerous scenarios and the sensor nodes in these networks have very limited battery life. Authorizing a new node involves a major work in the fundamental build for a secure WSN. In this paper, we propose a mobile sinks along with Particle Swarm Optimization for combined WSN. The new algorithm outperforms the normal convergence algorithm both in efficiency and in the quality of solutions.
{"title":"An energy aware secure wireless network using particle swarm optimization","authors":"K. Stephen, V. Mathivanan","doi":"10.1109/MINTC.2018.8363148","DOIUrl":"https://doi.org/10.1109/MINTC.2018.8363148","url":null,"abstract":"A Wireless sensor networks (WSN) typically has no infrastructure. It is composed of number of sensor nodes working together to monitor an environment to obtain data about it. Structured and unstructured are the two types of WSNs. An unstructured WSN contains a dense collection of sensor nodes. These sensors are small, computing resources, with limited processing and they are inexpensive. It can sense, measure, and gather information from the environment based on some local decision process; they can transmit the sensed data to the user. Security and lifetime of a sensor node in a network plays an important role. Data Securing is very important as these networks usually are put in dangerous scenarios and the sensor nodes in these networks have very limited battery life. Authorizing a new node involves a major work in the fundamental build for a secure WSN. In this paper, we propose a mobile sinks along with Particle Swarm Optimization for combined WSN. The new algorithm outperforms the normal convergence algorithm both in efficiency and in the quality of solutions.","PeriodicalId":250088,"journal":{"name":"2018 Majan International Conference (MIC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117035905","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 : 2018-03-19DOI: 10.1109/MINTC.2018.8363157
S. Mary, S. Joe, M. Siddique
The information in the digital form encounters various form of attacks while it is being sent through the communication channel. To withstand the attacks the information has to be secured by any one of the security mechanism. Digital Right Management (DRM) system is one where the right of ownership, authentication and integrity of the information and such other safety protocols are maintained. This paper consists of a working model for DRM system that is a combination of Improved Rational Dither Modulation (IRDM) for watermarking and Enhanced Modified Rivet Cipher 6 (EMRC6) for encryption. Since both the watermarking and encryption schemes are integrated together, this model provides a high level of security thus making the DRM system more robust. The input information can be either text or two dimensional image but this model can be extended to multidimensional information also. IRDM is a frequency domain scheme and is used for improving the robustness of the watermarking system. When compared to its predecessor RDM, IRDM is resistant to all attacks on watermark information and especially to scaling attack. The EMRC6 encryption scheme is a block ciphering method that is faster than the other version of RC6 and it has no attack. Hence it provides a high level of security to the information. The information from the output of this model ensures that the output digital image does not have any visual artifact since the PSNR value is around 41 dB on an average and the correlation coefficient is near to zero. The encryption time is very low and the throughput is high thus concluding that the working model is very fast.
{"title":"IRDM watermarking with EMRC6 encryption for DRM system","authors":"S. Mary, S. Joe, M. Siddique","doi":"10.1109/MINTC.2018.8363157","DOIUrl":"https://doi.org/10.1109/MINTC.2018.8363157","url":null,"abstract":"The information in the digital form encounters various form of attacks while it is being sent through the communication channel. To withstand the attacks the information has to be secured by any one of the security mechanism. Digital Right Management (DRM) system is one where the right of ownership, authentication and integrity of the information and such other safety protocols are maintained. This paper consists of a working model for DRM system that is a combination of Improved Rational Dither Modulation (IRDM) for watermarking and Enhanced Modified Rivet Cipher 6 (EMRC6) for encryption. Since both the watermarking and encryption schemes are integrated together, this model provides a high level of security thus making the DRM system more robust. The input information can be either text or two dimensional image but this model can be extended to multidimensional information also. IRDM is a frequency domain scheme and is used for improving the robustness of the watermarking system. When compared to its predecessor RDM, IRDM is resistant to all attacks on watermark information and especially to scaling attack. The EMRC6 encryption scheme is a block ciphering method that is faster than the other version of RC6 and it has no attack. Hence it provides a high level of security to the information. The information from the output of this model ensures that the output digital image does not have any visual artifact since the PSNR value is around 41 dB on an average and the correlation coefficient is near to zero. The encryption time is very low and the throughput is high thus concluding that the working model is very fast.","PeriodicalId":250088,"journal":{"name":"2018 Majan International Conference (MIC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116201905","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 : 2018-03-19DOI: 10.1109/MINTC.2018.8363165
Manal N. K. Al-Rawahi, Tripti Sharma, Praba Palanisamy
Nanotechnology is an upfront technology used to develop and design devices in the scale of nanometers. It offers opportunities and effective solutions in the field of medicine, military, agriculture, environment and computing systems. There are a lot of funding, initiatives by different countries around the world such as US, China for the project based on Nanotechnology in different areas. Recently, Oman is also incorporating nanotechnology to be deployed in different fields. Getting different sensors connected and interact intelligently with each other is the main application of IoT. However, replacing sensors with Nano sensors has provided a completely a new aspect to the Internet of Things (IoT) that is IoNT. IoNT is the new evolution that is a blend of IoT and nanotechnology. Because of its promising prospects and applications in the different areas, IoNT can be considered as the next generation of the IoT. Therefore in this paper, we will study and analyze the opportunities and the challenges of IoNT in the applications pertaining to the various domains.
{"title":"Internet of nanothings: Challenges & opportunities","authors":"Manal N. K. Al-Rawahi, Tripti Sharma, Praba Palanisamy","doi":"10.1109/MINTC.2018.8363165","DOIUrl":"https://doi.org/10.1109/MINTC.2018.8363165","url":null,"abstract":"Nanotechnology is an upfront technology used to develop and design devices in the scale of nanometers. It offers opportunities and effective solutions in the field of medicine, military, agriculture, environment and computing systems. There are a lot of funding, initiatives by different countries around the world such as US, China for the project based on Nanotechnology in different areas. Recently, Oman is also incorporating nanotechnology to be deployed in different fields. Getting different sensors connected and interact intelligently with each other is the main application of IoT. However, replacing sensors with Nano sensors has provided a completely a new aspect to the Internet of Things (IoT) that is IoNT. IoNT is the new evolution that is a blend of IoT and nanotechnology. Because of its promising prospects and applications in the different areas, IoNT can be considered as the next generation of the IoT. Therefore in this paper, we will study and analyze the opportunities and the challenges of IoNT in the applications pertaining to the various domains.","PeriodicalId":250088,"journal":{"name":"2018 Majan International Conference (MIC)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127667187","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 : 2018-03-19DOI: 10.1109/MINTC.2018.8363152
M. Shahid, A. Jaekel, C. Ezeife, Qasim Al-Ajmi, Ikjot Saini
Vehicular Ad hoc Networks (VANETs) is a special branch of ad hoc network which consists of cars as network nodes, Road-side units (RSU) and On-Board Unit(OBU). Basic purpose of VANETs is to provide efficient routing and better safety for drivers and passengers. This emerging technology is gaining more and more popularity as car accidents are increasing in the world. In this self-oriented network, security and privacy is so crucial. In this paper, we review the potential threats to Availability, Confidentiality, Authentication and Integrity in VANETs and, we also compare the type of potential attacks and its solutions.
{"title":"Review of potential security attacks in VANET","authors":"M. Shahid, A. Jaekel, C. Ezeife, Qasim Al-Ajmi, Ikjot Saini","doi":"10.1109/MINTC.2018.8363152","DOIUrl":"https://doi.org/10.1109/MINTC.2018.8363152","url":null,"abstract":"Vehicular Ad hoc Networks (VANETs) is a special branch of ad hoc network which consists of cars as network nodes, Road-side units (RSU) and On-Board Unit(OBU). Basic purpose of VANETs is to provide efficient routing and better safety for drivers and passengers. This emerging technology is gaining more and more popularity as car accidents are increasing in the world. In this self-oriented network, security and privacy is so crucial. In this paper, we review the potential threats to Availability, Confidentiality, Authentication and Integrity in VANETs and, we also compare the type of potential attacks and its solutions.","PeriodicalId":250088,"journal":{"name":"2018 Majan International Conference (MIC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126311616","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 : 2018-03-19DOI: 10.1109/MINTC.2018.8363163
Wisam Ahmed Al Farsi, Geetha Achuthan
Due to the observed growth in world population and high utilization of basic services, a prerequisite to transform cities into urban ones had emerged in last few years. Oman is now running urbanization process as its cities are improved day by day. With this framework, a vast amount of data is generated and it can be analysed in appropriate manner & utilized in order to make these cities smart and can adopt themselves. Here, the concept of Big Data was born to be the primary factor of rapid urbanization and towards smart city. Thus, this paper aims to study the smart city concept, analyse and provide a clear illustration of the effectiveness of smart city implementation in public transportation in Oman using Big Data and its applications. Data collected from five of the Mwasalat internal bus routes in Muscat are used to predict passengers travel pattern in these routes. The predictions are formed using different forecasting methods namely TBATS and ARIMA. These methods are applied to passengers' dataset and is found that TBATS method is perfectly fitted with the dataset.
{"title":"Analysis of effectiveness of smart city implementation in transportation sector in Oman","authors":"Wisam Ahmed Al Farsi, Geetha Achuthan","doi":"10.1109/MINTC.2018.8363163","DOIUrl":"https://doi.org/10.1109/MINTC.2018.8363163","url":null,"abstract":"Due to the observed growth in world population and high utilization of basic services, a prerequisite to transform cities into urban ones had emerged in last few years. Oman is now running urbanization process as its cities are improved day by day. With this framework, a vast amount of data is generated and it can be analysed in appropriate manner & utilized in order to make these cities smart and can adopt themselves. Here, the concept of Big Data was born to be the primary factor of rapid urbanization and towards smart city. Thus, this paper aims to study the smart city concept, analyse and provide a clear illustration of the effectiveness of smart city implementation in public transportation in Oman using Big Data and its applications. Data collected from five of the Mwasalat internal bus routes in Muscat are used to predict passengers travel pattern in these routes. The predictions are formed using different forecasting methods namely TBATS and ARIMA. These methods are applied to passengers' dataset and is found that TBATS method is perfectly fitted with the dataset.","PeriodicalId":250088,"journal":{"name":"2018 Majan International Conference (MIC)","volume":"08 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127327229","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 : 2018-03-01DOI: 10.1109/MINTC.2018.8363153
V. Anand, S. K. Abdul Rahiman, E. Ben George, A. S. Huda
Automated prediction of students' performance in the earlier stage is a useful prospect in the teaching learning process. If the students who are probably going to fail are identified in the initial stage, a set of corrective measures can be taken to improve their grades. This paper employs the machine learning approach called the Recursive Clustering technique to group the students of the programming course into groups based on their performance in the prerequisite courses, co-requisite, CGPA and current course work result. Students present in the lower groups will be taken into consideration since they are highly prone to fail. Each of these groups will be provided with the set of programs and notes automatically based on their group. After a time period another assessment will be carried out and again the students will be clustered based on their new performance. This process will be repeated for three times so that most of the students from the lower group will move to the higher group. The results are compared to the number of students in each group before applying the recursive clustering technique and after. The results prove that this approach provides an effective way to predict the low performing students from their early in-class assessment, thereby enabling the student to be on track.
{"title":"Recursive clustering technique for students' performance evaluation in programming courses","authors":"V. Anand, S. K. Abdul Rahiman, E. Ben George, A. S. Huda","doi":"10.1109/MINTC.2018.8363153","DOIUrl":"https://doi.org/10.1109/MINTC.2018.8363153","url":null,"abstract":"Automated prediction of students' performance in the earlier stage is a useful prospect in the teaching learning process. If the students who are probably going to fail are identified in the initial stage, a set of corrective measures can be taken to improve their grades. This paper employs the machine learning approach called the Recursive Clustering technique to group the students of the programming course into groups based on their performance in the prerequisite courses, co-requisite, CGPA and current course work result. Students present in the lower groups will be taken into consideration since they are highly prone to fail. Each of these groups will be provided with the set of programs and notes automatically based on their group. After a time period another assessment will be carried out and again the students will be clustered based on their new performance. This process will be repeated for three times so that most of the students from the lower group will move to the higher group. The results are compared to the number of students in each group before applying the recursive clustering technique and after. The results prove that this approach provides an effective way to predict the low performing students from their early in-class assessment, thereby enabling the student to be on track.","PeriodicalId":250088,"journal":{"name":"2018 Majan International Conference (MIC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133214304","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}
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