�ݺ�ߣshows by User: sarfraznawaz

�ݺ�ߣshows by User: sarfraznawaz / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: sarfraznawaz / Tue, 07 Aug 2018 10:59:08 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: sarfraznawaz Towards Smart Cities Development: A Study of Public Transport System and Traffic-related Air Pollutants in Malaysia /slideshow/towards-smart-cities-development-a-study-of-public-transport-system-and-trafficrelated-air-pollutants-in-malaysia/108906937 brohi2018iopconf-180807105908
Increasing number of privately owned vehicles are depicting Malaysians preferred mode of mobility and lack of interest in the public transport system. In most developing countries such as Malaysia, motorized vehicles are the major contributors to air pollution in urban zones. Air pollution is a silent killer as it infiltrates the vital organs, leading to serious diseases and death. This research critically analyses the emissions of air pollutants such as CO, NO2, SO2, hydrocarbon, and PM from various sources in Malaysia with emphasis mainly on the emission of pollutants from motor vehicles. This research also discusses the public transport initiatives undertaken by the government of Malaysia such as enhancing the bus and rail system, transforming Malaysia’s taxi system, managing travel demand and enhancing the integration of urban public transport system. Furthermore, considering the smart cities initiatives, this research identified that weather, safety, security and inappropriate infrastructure are major barriers in Malaysia’s move towards the implementation of smart and eco-friendly mobility practices such as cycling, carpooling and car sharing.]]>
Increasing number of privately owned vehicles are depicting Malaysians preferred mode of mobility and lack of interest in the public transport system. In most developing countries such as Malaysia, motorized vehicles are the major contributors to air pollution in urban zones. Air pollution is a silent killer as it infiltrates the vital organs, leading to serious diseases and death. This research critically analyses the emissions of air pollutants such as CO, NO2, SO2, hydrocarbon, and PM from various sources in Malaysia with emphasis mainly on the emission of pollutants from motor vehicles. This research also discusses the public transport initiatives undertaken by the government of Malaysia such as enhancing the bus and rail system, transforming Malaysia’s taxi system, managing travel demand and enhancing the integration of urban public transport system. Furthermore, considering the smart cities initiatives, this research identified that weather, safety, security and inappropriate infrastructure are major barriers in Malaysia’s move towards the implementation of smart and eco-friendly mobility practices such as cycling, carpooling and car sharing.]]> Tue, 07 Aug 2018 10:59:08 GMT /slideshow/towards-smart-cities-development-a-study-of-public-transport-system-and-trafficrelated-air-pollutants-in-malaysia/108906937 sarfraznawaz@slideshare.net(sarfraznawaz) Towards Smart Cities Development: A Study of Public Transport System and Traffic-related Air Pollutants in Malaysia sarfraznawaz Increasing number of privately owned vehicles are depicting Malaysians preferred mode of mobility and lack of interest in the public transport system. In most developing countries such as Malaysia, motorized vehicles are the major contributors to air pollution in urban zones. Air pollution is a silent killer as it infiltrates the vital organs, leading to serious diseases and death. This research critically analyses the emissions of air pollutants such as CO, NO2, SO2, hydrocarbon, and PM from various sources in Malaysia with emphasis mainly on the emission of pollutants from motor vehicles. This research also discusses the public transport initiatives undertaken by the government of Malaysia such as enhancing the bus and rail system, transforming Malaysia’s taxi system, managing travel demand and enhancing the integration of urban public transport system. Furthermore, considering the smart cities initiatives, this research identified that weather, safety, security and inappropriate infrastructure are major barriers in Malaysia’s move towards the implementation of smart and eco-friendly mobility practices such as cycling, carpooling and car sharing. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/brohi2018iopconf-180807105908-thumbnail.jpg?width=120&height=120&fit=bounds" /> Increasing number of privately owned vehicles are depicting Malaysians preferred mode of mobility and lack of interest in the public transport system. In most developing countries such as Malaysia, motorized vehicles are the major contributors to air pollution in urban zones. Air pollution is a silent killer as it infiltrates the vital organs, leading to serious diseases and death. This research critically analyses the emissions of air pollutants such as CO, NO2, SO2, hydrocarbon, and PM from various sources in Malaysia with emphasis mainly on the emission of pollutants from motor vehicles. This research also discusses the public transport initiatives undertaken by the government of Malaysia such as enhancing the bus and rail system, transforming Malaysia’s taxi system, managing travel demand and enhancing the integration of urban public transport system. Furthermore, considering the smart cities initiatives, this research identified that weather, safety, security and inappropriate infrastructure are major barriers in Malaysia’s move towards the implementation of smart and eco-friendly mobility practices such as cycling, carpooling and car sharing.

Towards Smart Cities Development: A Study of Public Transport System and Traffic-related Air Pollutants in Malaysia from sarfraznawaz

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0 BIG DATA IN SMART CITIES: A SYSTEMATIC MAPPING REVIEW /slideshow/big-data-in-smart-cities-a-systematic-mapping-review-108906831/108906831 13725-180807105701
Big data is an emerging area of research and its prospective applications in smart cities are extensively recognized. In this study, we provide a breadth-first review of the domain “Big Data in Smart Cities” by applying the formal research method of systematic mapping. We investigated the primary sources of publication, research growth, maturity level of the research area, prominent research themes, type of analytics applied, and the areas of smart cities where big data research is produced. Consequently, we identified that empirical research in the domain has been progressing since 2013. The IEEE Access journal and IEEE Smart Cities Conference are the leading sources of literature containing 10.34% and 13.88% of the publications, respectively. The current state of the research is semi-matured where research type of 46.15% of the publications is solution and experience, and contribution type of 60% of the publications is architecture, platform, and framework. Prescriptive is least whereas predictive is the most applied type of analytics in smart cities as it has been stated in 43.08% of the publications. Overall, 33.85%, 21.54%, 13.85%, 12.31%, 7.69%, 6.15%, and 4.61% of the research produced in the domain focused on smart transportation, smart environment, smart governance, smart healthcare, smart energy, smart education, and smart safety, respectively. Besides the requirement for producing validation and evaluation research in the areas of smart transportation and smart environment, there is a need for more research efforts in the areas of smart healthcare, smart governance, smart safety, smart education, and smart energy. Furthermore, the potential of prescriptive analytics in smart cities is also an area of research that needs to be explored.]]>
Big data is an emerging area of research and its prospective applications in smart cities are extensively recognized. In this study, we provide a breadth-first review of the domain “Big Data in Smart Cities” by applying the formal research method of systematic mapping. We investigated the primary sources of publication, research growth, maturity level of the research area, prominent research themes, type of analytics applied, and the areas of smart cities where big data research is produced. Consequently, we identified that empirical research in the domain has been progressing since 2013. The IEEE Access journal and IEEE Smart Cities Conference are the leading sources of literature containing 10.34% and 13.88% of the publications, respectively. The current state of the research is semi-matured where research type of 46.15% of the publications is solution and experience, and contribution type of 60% of the publications is architecture, platform, and framework. Prescriptive is least whereas predictive is the most applied type of analytics in smart cities as it has been stated in 43.08% of the publications. Overall, 33.85%, 21.54%, 13.85%, 12.31%, 7.69%, 6.15%, and 4.61% of the research produced in the domain focused on smart transportation, smart environment, smart governance, smart healthcare, smart energy, smart education, and smart safety, respectively. Besides the requirement for producing validation and evaluation research in the areas of smart transportation and smart environment, there is a need for more research efforts in the areas of smart healthcare, smart governance, smart safety, smart education, and smart energy. Furthermore, the potential of prescriptive analytics in smart cities is also an area of research that needs to be explored.]]> Tue, 07 Aug 2018 10:57:01 GMT /slideshow/big-data-in-smart-cities-a-systematic-mapping-review-108906831/108906831 sarfraznawaz@slideshare.net(sarfraznawaz) BIG DATA IN SMART CITIES: A SYSTEMATIC MAPPING REVIEW sarfraznawaz Big data is an emerging area of research and its prospective applications in smart cities are extensively recognized. In this study, we provide a breadth-first review of the domain “Big Data in Smart Cities” by applying the formal research method of systematic mapping. We investigated the primary sources of publication, research growth, maturity level of the research area, prominent research themes, type of analytics applied, and the areas of smart cities where big data research is produced. Consequently, we identified that empirical research in the domain has been progressing since 2013. The IEEE Access journal and IEEE Smart Cities Conference are the leading sources of literature containing 10.34% and 13.88% of the publications, respectively. The current state of the research is semi-matured where research type of 46.15% of the publications is solution and experience, and contribution type of 60% of the publications is architecture, platform, and framework. Prescriptive is least whereas predictive is the most applied type of analytics in smart cities as it has been stated in 43.08% of the publications. Overall, 33.85%, 21.54%, 13.85%, 12.31%, 7.69%, 6.15%, and 4.61% of the research produced in the domain focused on smart transportation, smart environment, smart governance, smart healthcare, smart energy, smart education, and smart safety, respectively. Besides the requirement for producing validation and evaluation research in the areas of smart transportation and smart environment, there is a need for more research efforts in the areas of smart healthcare, smart governance, smart safety, smart education, and smart energy. Furthermore, the potential of prescriptive analytics in smart cities is also an area of research that needs to be explored. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/13725-180807105701-thumbnail.jpg?width=120&height=120&fit=bounds" /> Big data is an emerging area of research and its prospective applications in smart cities are extensively recognized. In this study, we provide a breadth-first review of the domain “Big Data in Smart Cities” by applying the formal research method of systematic mapping. We investigated the primary sources of publication, research growth, maturity level of the research area, prominent research themes, type of analytics applied, and the areas of smart cities where big data research is produced. Consequently, we identified that empirical research in the domain has been progressing since 2013. The IEEE Access journal and IEEE Smart Cities Conference are the leading sources of literature containing 10.34% and 13.88% of the publications, respectively. The current state of the research is semi-matured where research type of 46.15% of the publications is solution and experience, and contribution type of 60% of the publications is architecture, platform, and framework. Prescriptive is least whereas predictive is the most applied type of analytics in smart cities as it has been stated in 43.08% of the publications. Overall, 33.85%, 21.54%, 13.85%, 12.31%, 7.69%, 6.15%, and 4.61% of the research produced in the domain focused on smart transportation, smart environment, smart governance, smart healthcare, smart energy, smart education, and smart safety, respectively. Besides the requirement for producing validation and evaluation research in the areas of smart transportation and smart environment, there is a need for more research efforts in the areas of smart healthcare, smart governance, smart safety, smart education, and smart energy. Furthermore, the potential of prescriptive analytics in smart cities is also an area of research that needs to be explored.

BIG DATA IN SMART CITIES: A SYSTEMATIC MAPPING REVIEW from sarfraznawaz

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0 Identifying and analyzing the transient and permanent barriers for big data /slideshow/identifying-and-analyzing-the-transient-and-permanent-barriers-for-big-data/69947958 identifyingandanalyzingthetransientandpermanentbarriersforbigdata-161208104914
Auspiciously, big data analytics had made it possible to generate value from immense amounts of raw data. Organizations are able to seek incredible insights which assist them in effective decision making and providing quality of service by establishing innovative strategies to recognize, examine and address the customers’ preferences. However, organizations are reluctant to adopt big data solutions due to several barriers such as data storage and transfer, scalability, data quality, data complexity, timeliness, security, privacy, trust, data ownership, and transparency. Despite the discussion on big data opportunities, in this paper, we present the findings of our in-depth review process that was focused on identifying as well as analyzing the transient and permanent barriers for adopting big data. Although, the transient barriers for big data can be eliminated in the near future with the advent of innovative technical contributions, however, it is challenging to eliminate the permanent barriers enduringly, though their impact could be recurrently reduced with the efficient and effective use of technology, standards, policies, and procedures. ]]>
Auspiciously, big data analytics had made it possible to generate value from immense amounts of raw data. Organizations are able to seek incredible insights which assist them in effective decision making and providing quality of service by establishing innovative strategies to recognize, examine and address the customers’ preferences. However, organizations are reluctant to adopt big data solutions due to several barriers such as data storage and transfer, scalability, data quality, data complexity, timeliness, security, privacy, trust, data ownership, and transparency. Despite the discussion on big data opportunities, in this paper, we present the findings of our in-depth review process that was focused on identifying as well as analyzing the transient and permanent barriers for adopting big data. Although, the transient barriers for big data can be eliminated in the near future with the advent of innovative technical contributions, however, it is challenging to eliminate the permanent barriers enduringly, though their impact could be recurrently reduced with the efficient and effective use of technology, standards, policies, and procedures. ]]> Thu, 08 Dec 2016 10:49:14 GMT /slideshow/identifying-and-analyzing-the-transient-and-permanent-barriers-for-big-data/69947958 sarfraznawaz@slideshare.net(sarfraznawaz) Identifying and analyzing the transient and permanent barriers for big data sarfraznawaz Auspiciously, big data analytics had made it possible to generate value from immense amounts of raw data. Organizations are able to seek incredible insights which assist them in effective decision making and providing quality of service by establishing innovative strategies to recognize, examine and address the customers’ preferences. However, organizations are reluctant to adopt big data solutions due to several barriers such as data storage and transfer, scalability, data quality, data complexity, timeliness, security, privacy, trust, data ownership, and transparency. Despite the discussion on big data opportunities, in this paper, we present the findings of our in-depth review process that was focused on identifying as well as analyzing the transient and permanent barriers for adopting big data. Although, the transient barriers for big data can be eliminated in the near future with the advent of innovative technical contributions, however, it is challenging to eliminate the permanent barriers enduringly, though their impact could be recurrently reduced with the efficient and effective use of technology, standards, policies, and procedures. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/identifyingandanalyzingthetransientandpermanentbarriersforbigdata-161208104914-thumbnail.jpg?width=120&height=120&fit=bounds" /> Auspiciously, big data analytics had made it possible to generate value from immense amounts of raw data. Organizations are able to seek incredible insights which assist them in effective decision making and providing quality of service by establishing innovative strategies to recognize, examine and address the customers’ preferences. However, organizations are reluctant to adopt big data solutions due to several barriers such as data storage and transfer, scalability, data quality, data complexity, timeliness, security, privacy, trust, data ownership, and transparency. Despite the discussion on big data opportunities, in this paper, we present the findings of our in-depth review process that was focused on identifying as well as analyzing the transient and permanent barriers for adopting big data. Although, the transient barriers for big data can be eliminated in the near future with the advent of innovative technical contributions, however, it is challenging to eliminate the permanent barriers enduringly, though their impact could be recurrently reduced with the efficient and effective use of technology, standards, policies, and procedures.

Identifying and analyzing the transient and permanent barriers for big data from sarfraznawaz

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0 Design and implementation of a privacy preserved off premises cloud storage /slideshow/design-and-implementation-of-a-privacy-preserved-off-premises-cloud-storage/28551804 designandimplementationofaprivacypreservedoffpremisescloudstorage-131123060137-phpapp01
Despite several cost-effective and flexible characteristics of cloud computing, some clients are reluctant to adopt this paradigm due to emerging security and privacy concerns. Organization such as Healthcare and Payment Card Industry where confidentiality of information is a vital act, are not assertive to trust the security techniques and privacy policies offered by cloud service providers. Malicious attackers have violated the cloud storages to steal, view, manipulate and tamper client's data. Attacks on cloud storages are extremely challenging to detect and mitigate. In order to formulate privacy preserved cloud storage, in this research paper, we propose an improved technique that consists of five contributions such as Resilient role-based access control mechanism, Partial homomorphic cryptography, metadata generation and sound steganography, Efficient third-party auditing service, Data backup and recovery process. We implemented these components using Java Enterprise Edition with Glassfish Server. Finally we evaluated our proposed technique by penetration testing and the results showed that client’s data is intact and protected from malicious attackers. ]]>
Despite several cost-effective and flexible characteristics of cloud computing, some clients are reluctant to adopt this paradigm due to emerging security and privacy concerns. Organization such as Healthcare and Payment Card Industry where confidentiality of information is a vital act, are not assertive to trust the security techniques and privacy policies offered by cloud service providers. Malicious attackers have violated the cloud storages to steal, view, manipulate and tamper client's data. Attacks on cloud storages are extremely challenging to detect and mitigate. In order to formulate privacy preserved cloud storage, in this research paper, we propose an improved technique that consists of five contributions such as Resilient role-based access control mechanism, Partial homomorphic cryptography, metadata generation and sound steganography, Efficient third-party auditing service, Data backup and recovery process. We implemented these components using Java Enterprise Edition with Glassfish Server. Finally we evaluated our proposed technique by penetration testing and the results showed that client’s data is intact and protected from malicious attackers. ]]> Sat, 23 Nov 2013 06:01:37 GMT /slideshow/design-and-implementation-of-a-privacy-preserved-off-premises-cloud-storage/28551804 sarfraznawaz@slideshare.net(sarfraznawaz) Design and implementation of a privacy preserved off premises cloud storage sarfraznawaz Despite several cost-effective and flexible characteristics of cloud computing, some clients are reluctant to adopt this paradigm due to emerging security and privacy concerns. Organization such as Healthcare and Payment Card Industry where confidentiality of information is a vital act, are not assertive to trust the security techniques and privacy policies offered by cloud service providers. Malicious attackers have violated the cloud storages to steal, view, manipulate and tamper client's data. Attacks on cloud storages are extremely challenging to detect and mitigate. In order to formulate privacy preserved cloud storage, in this research paper, we propose an improved technique that consists of five contributions such as Resilient role-based access control mechanism, Partial homomorphic cryptography, metadata generation and sound steganography, Efficient third-party auditing service, Data backup and recovery process. We implemented these components using Java Enterprise Edition with Glassfish Server. Finally we evaluated our proposed technique by penetration testing and the results showed that client’s data is intact and protected from malicious attackers. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/designandimplementationofaprivacypreservedoffpremisescloudstorage-131123060137-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Despite several cost-effective and flexible characteristics of cloud computing, some clients are reluctant to adopt this paradigm due to emerging security and privacy concerns. Organization such as Healthcare and Payment Card Industry where confidentiality of information is a vital act, are not assertive to trust the security techniques and privacy policies offered by cloud service providers. Malicious attackers have violated the cloud storages to steal, view, manipulate and tamper client's data. Attacks on cloud storages are extremely challenging to detect and mitigate. In order to formulate privacy preserved cloud storage, in this research paper, we propose an improved technique that consists of five contributions such as Resilient role-based access control mechanism, Partial homomorphic cryptography, metadata generation and sound steganography, Efficient third-party auditing service, Data backup and recovery process. We implemented these components using Java Enterprise Edition with Glassfish Server. Finally we evaluated our proposed technique by penetration testing and the results showed that client’s data is intact and protected from malicious attackers.

Design and implementation of a privacy preserved off premises cloud storage from sarfraznawaz

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0 Empirical research methods for software engineering /slideshow/empirical-research-methods-for-software-engineering/8068207 empiricalresearchmethodsforsoftwareengineering-110523084737-phpapp01
A guide for research students to perform empirical research in software engineering.]]>
A guide for research students to perform empirical research in software engineering.]]> Mon, 23 May 2011 08:47:35 GMT /slideshow/empirical-research-methods-for-software-engineering/8068207 sarfraznawaz@slideshare.net(sarfraznawaz) Empirical research methods for software engineering sarfraznawaz A guide for research students to perform empirical research in software engineering. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/empiricalresearchmethodsforsoftwareengineering-110523084737-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> A guide for research students to perform empirical research in software engineering.

Empirical research methods for software engineering from sarfraznawaz

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0 https://public.slidesharecdn.com/v2/images/profile-picture.png https://cdn.slidesharecdn.com/ss_thumbnails/brohi2018iopconf-180807105908-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/towards-smart-cities-development-a-study-of-public-transport-system-and-trafficrelated-air-pollutants-in-malaysia/108906937 Towards Smart Cities D... https://cdn.slidesharecdn.com/ss_thumbnails/13725-180807105701-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/big-data-in-smart-cities-a-systematic-mapping-review-108906831/108906831 BIG DATA IN SMART CITI... https://cdn.slidesharecdn.com/ss_thumbnails/identifyingandanalyzingthetransientandpermanentbarriersforbigdata-161208104914-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/identifying-and-analyzing-the-transient-and-permanent-barriers-for-big-data/69947958 Identifying and analyz...