International Journal of Information Management Data Insights
Recently, the population density in cities has increased at a higher pace. According to the Unite... more Recently, the population density in cities has increased at a higher pace. According to the United Nations Population Fund, cities accommodated 3.3 billion people (54%) of the global population in 2014. By 2050, around 5 billion people (68%) will be residing in cities. In order to make lifestyles in cities more comfortable and cost-effective, the city must be smart and intelligent. It is mainly accomplished through an intelligent decision-making process using computational intelligence-based technologies. This paper explored how artificial intelligence (AI) is being used in the smart city concept. From 2014 to 2021, we examined 133 articles (97% of Scopus and 73% of WoS) in healthcare, education, environment and waste management, agriculture, mobility and smart transportation, risk management, and security. Moreover, we observed that the healthcare (23% impact), mobility (19% impact), privacy and security (11% impact), and energy sectors (10% impact) have a more significant influence on AI adoption in smart cities. Since the epidemic hit cities in 2019, the healthcare industry has intensified its AI-based advances by 60%. According to the analysis, AI algorithms such as ANN, RNN/LSTM, CNN/R-CNN, DNN, and SVM/LS-SVM have a higher impact on the various smart city domains.
Abstract Today wearable devices can be used to monitor the health of patients, among other uses. ... more Abstract Today wearable devices can be used to monitor the health of patients, among other uses. This chapter proposes an intelligent wearable device (IWD) with a pedometer algorithm that detects and records physical movement such as walking. This device uses a smart algorithm for IWDs for step detection that analyzes the instantaneous acceleration versus time waveform and can detect the specific movements involved in stepping. The results of the algorithm are discussed with different cases and threshold values considered. This algorithm uses a mobile app using the Internet of Things to keep track of steps, and the Gaussian noise is removed from the accelerometer data. This power-efficient pedometer algorithm can be used for IWDs.
Lecture Notes on Data Engineering and Communications Technologies, 2021
Background: Despite extensive research on employee turnover intention in the existing literature.... more Background: Despite extensive research on employee turnover intention in the existing literature. Previous studies have paid rare attention to the role of workload (WL), nepotism (N), job satisfaction (JS), and organization politics (OP) on turnover intention, especially, mediating the effect of harassment between WL, N, JS and OP on turnover intention in the Pakistani context. This study is using Hobfoll's conservation of resources (COR) theory. Methods: Data were collected from 189 female employees (doctors and nurses) working in public and private hospitals in the province of Sindh, Pakistan, by adopting a purposive sampling technique. SmartPLS and SPPS were used to analyze the data. Results: The results demonstrated that workload and job satisfaction are positively related to harassment. At the same time, harassment has a direct effect on turnover intention. More importantly, harassment partially mediated the effect between workload and job satisfaction on turnover intention. In contrast, nepotism and organizational politics did not observe any significant relationship with harassment. However, it also did not have any mediating impact of harassment between nepotism and organizational politics on turnover intention. Conclusion: There is a lack of research on the antecedents of turnover intention in the existing literature especially in the developing country context (Pakistan). Furthermore, this study examined the mediation mechanism of harassment on turnover intention. In this way, this is an original contribution to the body of knowledge. Finally, COR theory has been utilized to explain how antecedents of turnover intention play their role along with harassment at the workplace. This study also advances the existing literature on human resource management. The current study provides insightful guidelines to policymakers, managers, and HRM practitioners for devising employee-friendly policies at the workplace.
The enthusiasm for blockchain innovation has been expanding since the thought was authored in 200... more The enthusiasm for blockchain innovation has been expanding since the thought was authored in 2008. Blockchain refers to the system where records of transactions made in cryptocurrency are maintained. The reason behind the eagerness for blockchain is its key credits that give safety, ambiguity, and information uprightness with no third-party organization in charge of the exchanges, and thus it makes bewitching exploration zones, especially from the view point of exclusive difficulties and limitations. In this chapter, we have led a conscious planning concentrate with the sole purpose of collecting all the important developments on blockchain innovation. The primary goal of this chapter is to comprehend the momentum research points, identifying difficulties in the existing system and future headings with respect to innovations in blockchain from the specialized viewpoint. Results indicate that 80% of the papers focus on the framework and 20% focus on the applications which include ag...
The Internet of Things (IoT) is a new worldview which syndicates the advances and technologies of... more The Internet of Things (IoT) is a new worldview which syndicates the advances and technologies of different computing domains together such as ubiquitous computing, pervasive computing, communication, and sensing technologies. In recent times, the IoT has emerged significantly as it has many applications in real time such as in smart home, smart city, smart health care, etc. In this chapter, authors have presented an introduction to the energy conservation techniques in IoT ecosystem and pragmatic energy-efficient IoT system architecture in detail. Issues involved in the implementation of the energy conservation in IoT framework as well as energy conservation approaches with its perspective are also discussed in this chapter.
Nowadays, a large amount of valuable uncertain data is easily available in many real-life applica... more Nowadays, a large amount of valuable uncertain data is easily available in many real-life applications. Many industries and government organizations can exploit this data to extract valuable information. This information can help the managers to enhance their strategies and optimize their plans in making decisions. In fact, various private companies and governments have launched programs with investments and funds in order to maximize profits and optimize resources. This vast amount of data is called big data. The analysis of big data is important for future growth. This paper depicts big data analytics through experimental results. In this paper, data for New York stock exchange has been analyzed using two mapper files in Hadoop. For each year, the calculation of maximum and minimum price of every stock exchange and the average stock price is done.
One of the adverse effects of population growth and urbanization in developing countries is air p... more One of the adverse effects of population growth and urbanization in developing countries is air pollution. Due to which more than 4.2 million deaths occur every year. Therefore, prediction of air quality is a subject worth in-depth research and has received substantial interest in the recent years from academic units and the government. Feature selection methods are applied before prediction to identify potentially significant predictors based on exploratory data analysis. In this research work, a feature selection method based on Least Absolute Selection and Shrinkage Operator (LASSO) named Correlation based Adaptive LASSO (CbAL) Regression method has been proposed for predicting the air quality. For the experimental evaluation, cross regional data, including the concentration of pollutants and the meteorological factors of Delhi and its surrounding cities, has been taken from the Central Pollution Control Board (CPCB) Website. Further, to validate this feature selection method, various machine learning techniques have been taken into consideration and some preventive measures have been suggested to enhance the air quality. Feature selection analysis reveals that carbon monoxide, sulphur dioxide, nitrogen dioxide and Ozone are the most important factors for forecasting the air quality and the pollutants found in the cities of Noida and Gurugram have a more substantial impact on the Air Quality Index of Delhi than other surrounding cities. The model evaluation depicts that the feature subset extracted by the proposed method performs better than the complete dataset and the subset extracted by LASSO Regression with an average classification accuracy of 78%. The findings of this study can help to identify important contributors of AQI so that viable measures to improve the air quality of Delhi can be carried out.
The world of Industry 4.0 has been quarantined due to the outbreak of highly contagious coronavir... more The world of Industry 4.0 has been quarantined due to the outbreak of highly contagious coronavirus disease (COVID-19) which has been characterized as a pandemic by World Health Organization. Quarantine, which refers to strict isolation, helps to prevent the spread of the disease. However, the prediction and analysis of the impact of the quarantine in containing the disease still remain a challenge. Such predictions may provide assistance to the governments in preparing effective standard operating procedures which could help in mitigating the effects of the pandemic. For this purpose, the area of machine learning has been explored by the researchers to develop tools and technologies that could help in quantifying the effects of quarantine in several parts of the world. Various techniques such as deep learning algorithms, association rules, decision trees, predictive analytics, reinforcement learning and big data visualization are being used to help address the pandemic issue. This chapter provides insights into various machine learning tools and techniques which have been used to measure the impact of quarantine worldwide.
International Journal for Research in Applied Science and Engineering Technology, 2019
Ebola virus (EBOV) is a zoonotic pathogen that poses a significant threat to public health, causi... more Ebola virus (EBOV) is a zoonotic pathogen that poses a significant threat to public health, causing sporadic yet devastating outbreaks that have the potential to spread worldwide, as demonstrated during the 2013-2016 West African outbreak. Mouse models of infection are important tools for the development of therapeutics and vaccines. Exposure of immunocompetent mice to clinical isolates of EBOV is nonlethal; consequently, EBOV requires prior adaptation in mice to cause lethal disease. Until now, the only immunocompetent EBOV mouse model was based on the Mayinga variant, which was isolated in 1976. Here, we generated a novel mouse-adapted (MA)-EBOV based on the 2014 Makona isolate by inserting EBOV/Mayinga-MA mutations into the EBOV/Makona genome, followed by serial passaging of the rescued virus in suckling mice. The resulting EBOV/Makona-MA causes lethal disease in adult immunocompetent mice within 6 to 9 days and has a lethal dose (LD50) of 0.004 plaque forming units (PFU). Two additional mutations emerged after mouse-adaptation in the viral nucleoprotein (NP) and membrane-associated protein VP24. Using reverse genetics, we found the VP24 mutation to be critical for EBOV/Makona-MA virulence. EBOV/Makona-MA infected mice that presented with viremia, high viral burden in organs, increased release of pro-inflammatory cytokines/chemokines, and lymphopenia. Our mouse model will help advance pre-clinical development of countermeasures against contemporary EBOV variants.
Refining visibility through haze removal from image becomes an inevitable chore and essential to ... more Refining visibility through haze removal from image becomes an inevitable chore and essential to recognize and track vehicles, traffic signal, and signs clearly under road safety. That can face a recurrent degradation under destitute climatic circumstances for instance fog, rain, cloud, and smog. To diminish this constraint, various methods were designed and implemented, but most were not capable of obtaining the improved quantitative outcomes. Therefore, a new algorithm Fog Elimination using Multiple Thresholds (FEMT) for single image haze eviction that meritoriously obtains the significant results on both gray and colored over real and synthetic images using multiple thresholds is proposed in this paper. The proposed method targets on the light regions by reducing the brightness and increasing the contrast of image at different levels. Finally, by grouping all the obtained resultant images leads to the generation of the resultant defogged image. The qualitative and quantitative analysis is carried out for an assessment of digitalized de-hazed images acquired from the proposed algorithm and compared to the prior techniques. Simulated fallouts entitle high resemblance to the corresponding ground truth, reduction in computation time consumption to 88% and error of 98%. The proposed approach can be applied in the field of robotics, human activity monitoring, smart systems, and digital investigation on the hazy images.
Bioinformatics is everywhere, from disease detection to disease prevention and curation, from the... more Bioinformatics is everywhere, from disease detection to disease prevention and curation, from the study of microorganisms to study of all life on earth and from sequence alignment to gene expression. This book provides in-depth information regarding the explosively growing new discipline i.e. Bioinformatics. It provides coverage of important topics like sequence alignment, phylogenetics, DNA, RNA, and proteins. From basics of central dogma of biology to computational algorithms for RNA secondary structure prediction, this book covers it all. Also, it provides implementation of few important algorithms in Dot Net framework. This book also enlightens the application areas of bioinformatics.
This article is available in open access under Creative Common Attribution-Non-Commercial-No Deri... more This article is available in open access under Creative Common Attribution-Non-Commercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0) license, allowing to download articles and share them with others as long as they credit the authors and the publisher, but without permission to change them in any way or use them commercially.
International journal of imaging and robotics, 2018
This research work proposes the design of a field programmable gate array (FPGA) based efficient ... more This research work proposes the design of a field programmable gate array (FPGA) based efficient surveillance robot. A bifurcated processing approach has been developed with an implementation of a part of video processing algorithms on the ZYNQ XC7Z010-1CLG400C FPGA (on the surveillance robot) and another part of the controller system. Video processing filters on the video signals to be transmitted are mapped onto the peripherals of the surveillance robot whereas detection and tracking algorithms have been applied to Control Unit system. Wi-Fi module on the surveillance robot transmits the Processed signals. The control unit system receives the transmitted video signals via IEEE 802.11 protocol. The control on robot has been achieved by the gaming console at control unit system with the manual feedback provided by a human. Wireless control with the portable controller has also been enabled with the help of an application developed on the Android device. Unlike conventional Surveilla...
2017 International Conference on Infocom Technologies and Unmanned Systems (Trends and Future Directions) (ICTUS), 2017
In the current scenario, the data on the web is growing exponentially. Social media is generating... more In the current scenario, the data on the web is growing exponentially. Social media is generating a large amount of data such as reviews, comments, and customers' opinions on a daily basis. This huge amount of user generated data is worthless unless some mining operations are applied to it. As there are a number of fake reviews so opinion mining technique should incorporate Spam detection to produce a genuine opinion. Nowadays, there are a number of people using social media opinions to create their call on shopping for product or service. Opinion Spam detection is an exhausting and hard problem as there are many faux or fake reviews that have been created by organizations or by the people for various purposes. They write fake reviews to mislead readers or automated detection system by promoting or demoting target products to promote them or to or to degrade their reputations. In this paper, the proposed technique includes ontology, Geo location and IP address tracking, Spam wor...
International Journal of Information Management Data Insights
Recently, the population density in cities has increased at a higher pace. According to the Unite... more Recently, the population density in cities has increased at a higher pace. According to the United Nations Population Fund, cities accommodated 3.3 billion people (54%) of the global population in 2014. By 2050, around 5 billion people (68%) will be residing in cities. In order to make lifestyles in cities more comfortable and cost-effective, the city must be smart and intelligent. It is mainly accomplished through an intelligent decision-making process using computational intelligence-based technologies. This paper explored how artificial intelligence (AI) is being used in the smart city concept. From 2014 to 2021, we examined 133 articles (97% of Scopus and 73% of WoS) in healthcare, education, environment and waste management, agriculture, mobility and smart transportation, risk management, and security. Moreover, we observed that the healthcare (23% impact), mobility (19% impact), privacy and security (11% impact), and energy sectors (10% impact) have a more significant influence on AI adoption in smart cities. Since the epidemic hit cities in 2019, the healthcare industry has intensified its AI-based advances by 60%. According to the analysis, AI algorithms such as ANN, RNN/LSTM, CNN/R-CNN, DNN, and SVM/LS-SVM have a higher impact on the various smart city domains.
Abstract Today wearable devices can be used to monitor the health of patients, among other uses. ... more Abstract Today wearable devices can be used to monitor the health of patients, among other uses. This chapter proposes an intelligent wearable device (IWD) with a pedometer algorithm that detects and records physical movement such as walking. This device uses a smart algorithm for IWDs for step detection that analyzes the instantaneous acceleration versus time waveform and can detect the specific movements involved in stepping. The results of the algorithm are discussed with different cases and threshold values considered. This algorithm uses a mobile app using the Internet of Things to keep track of steps, and the Gaussian noise is removed from the accelerometer data. This power-efficient pedometer algorithm can be used for IWDs.
Lecture Notes on Data Engineering and Communications Technologies, 2021
Background: Despite extensive research on employee turnover intention in the existing literature.... more Background: Despite extensive research on employee turnover intention in the existing literature. Previous studies have paid rare attention to the role of workload (WL), nepotism (N), job satisfaction (JS), and organization politics (OP) on turnover intention, especially, mediating the effect of harassment between WL, N, JS and OP on turnover intention in the Pakistani context. This study is using Hobfoll's conservation of resources (COR) theory. Methods: Data were collected from 189 female employees (doctors and nurses) working in public and private hospitals in the province of Sindh, Pakistan, by adopting a purposive sampling technique. SmartPLS and SPPS were used to analyze the data. Results: The results demonstrated that workload and job satisfaction are positively related to harassment. At the same time, harassment has a direct effect on turnover intention. More importantly, harassment partially mediated the effect between workload and job satisfaction on turnover intention. In contrast, nepotism and organizational politics did not observe any significant relationship with harassment. However, it also did not have any mediating impact of harassment between nepotism and organizational politics on turnover intention. Conclusion: There is a lack of research on the antecedents of turnover intention in the existing literature especially in the developing country context (Pakistan). Furthermore, this study examined the mediation mechanism of harassment on turnover intention. In this way, this is an original contribution to the body of knowledge. Finally, COR theory has been utilized to explain how antecedents of turnover intention play their role along with harassment at the workplace. This study also advances the existing literature on human resource management. The current study provides insightful guidelines to policymakers, managers, and HRM practitioners for devising employee-friendly policies at the workplace.
The enthusiasm for blockchain innovation has been expanding since the thought was authored in 200... more The enthusiasm for blockchain innovation has been expanding since the thought was authored in 2008. Blockchain refers to the system where records of transactions made in cryptocurrency are maintained. The reason behind the eagerness for blockchain is its key credits that give safety, ambiguity, and information uprightness with no third-party organization in charge of the exchanges, and thus it makes bewitching exploration zones, especially from the view point of exclusive difficulties and limitations. In this chapter, we have led a conscious planning concentrate with the sole purpose of collecting all the important developments on blockchain innovation. The primary goal of this chapter is to comprehend the momentum research points, identifying difficulties in the existing system and future headings with respect to innovations in blockchain from the specialized viewpoint. Results indicate that 80% of the papers focus on the framework and 20% focus on the applications which include ag...
The Internet of Things (IoT) is a new worldview which syndicates the advances and technologies of... more The Internet of Things (IoT) is a new worldview which syndicates the advances and technologies of different computing domains together such as ubiquitous computing, pervasive computing, communication, and sensing technologies. In recent times, the IoT has emerged significantly as it has many applications in real time such as in smart home, smart city, smart health care, etc. In this chapter, authors have presented an introduction to the energy conservation techniques in IoT ecosystem and pragmatic energy-efficient IoT system architecture in detail. Issues involved in the implementation of the energy conservation in IoT framework as well as energy conservation approaches with its perspective are also discussed in this chapter.
Nowadays, a large amount of valuable uncertain data is easily available in many real-life applica... more Nowadays, a large amount of valuable uncertain data is easily available in many real-life applications. Many industries and government organizations can exploit this data to extract valuable information. This information can help the managers to enhance their strategies and optimize their plans in making decisions. In fact, various private companies and governments have launched programs with investments and funds in order to maximize profits and optimize resources. This vast amount of data is called big data. The analysis of big data is important for future growth. This paper depicts big data analytics through experimental results. In this paper, data for New York stock exchange has been analyzed using two mapper files in Hadoop. For each year, the calculation of maximum and minimum price of every stock exchange and the average stock price is done.
One of the adverse effects of population growth and urbanization in developing countries is air p... more One of the adverse effects of population growth and urbanization in developing countries is air pollution. Due to which more than 4.2 million deaths occur every year. Therefore, prediction of air quality is a subject worth in-depth research and has received substantial interest in the recent years from academic units and the government. Feature selection methods are applied before prediction to identify potentially significant predictors based on exploratory data analysis. In this research work, a feature selection method based on Least Absolute Selection and Shrinkage Operator (LASSO) named Correlation based Adaptive LASSO (CbAL) Regression method has been proposed for predicting the air quality. For the experimental evaluation, cross regional data, including the concentration of pollutants and the meteorological factors of Delhi and its surrounding cities, has been taken from the Central Pollution Control Board (CPCB) Website. Further, to validate this feature selection method, various machine learning techniques have been taken into consideration and some preventive measures have been suggested to enhance the air quality. Feature selection analysis reveals that carbon monoxide, sulphur dioxide, nitrogen dioxide and Ozone are the most important factors for forecasting the air quality and the pollutants found in the cities of Noida and Gurugram have a more substantial impact on the Air Quality Index of Delhi than other surrounding cities. The model evaluation depicts that the feature subset extracted by the proposed method performs better than the complete dataset and the subset extracted by LASSO Regression with an average classification accuracy of 78%. The findings of this study can help to identify important contributors of AQI so that viable measures to improve the air quality of Delhi can be carried out.
The world of Industry 4.0 has been quarantined due to the outbreak of highly contagious coronavir... more The world of Industry 4.0 has been quarantined due to the outbreak of highly contagious coronavirus disease (COVID-19) which has been characterized as a pandemic by World Health Organization. Quarantine, which refers to strict isolation, helps to prevent the spread of the disease. However, the prediction and analysis of the impact of the quarantine in containing the disease still remain a challenge. Such predictions may provide assistance to the governments in preparing effective standard operating procedures which could help in mitigating the effects of the pandemic. For this purpose, the area of machine learning has been explored by the researchers to develop tools and technologies that could help in quantifying the effects of quarantine in several parts of the world. Various techniques such as deep learning algorithms, association rules, decision trees, predictive analytics, reinforcement learning and big data visualization are being used to help address the pandemic issue. This chapter provides insights into various machine learning tools and techniques which have been used to measure the impact of quarantine worldwide.
International Journal for Research in Applied Science and Engineering Technology, 2019
Ebola virus (EBOV) is a zoonotic pathogen that poses a significant threat to public health, causi... more Ebola virus (EBOV) is a zoonotic pathogen that poses a significant threat to public health, causing sporadic yet devastating outbreaks that have the potential to spread worldwide, as demonstrated during the 2013-2016 West African outbreak. Mouse models of infection are important tools for the development of therapeutics and vaccines. Exposure of immunocompetent mice to clinical isolates of EBOV is nonlethal; consequently, EBOV requires prior adaptation in mice to cause lethal disease. Until now, the only immunocompetent EBOV mouse model was based on the Mayinga variant, which was isolated in 1976. Here, we generated a novel mouse-adapted (MA)-EBOV based on the 2014 Makona isolate by inserting EBOV/Mayinga-MA mutations into the EBOV/Makona genome, followed by serial passaging of the rescued virus in suckling mice. The resulting EBOV/Makona-MA causes lethal disease in adult immunocompetent mice within 6 to 9 days and has a lethal dose (LD50) of 0.004 plaque forming units (PFU). Two additional mutations emerged after mouse-adaptation in the viral nucleoprotein (NP) and membrane-associated protein VP24. Using reverse genetics, we found the VP24 mutation to be critical for EBOV/Makona-MA virulence. EBOV/Makona-MA infected mice that presented with viremia, high viral burden in organs, increased release of pro-inflammatory cytokines/chemokines, and lymphopenia. Our mouse model will help advance pre-clinical development of countermeasures against contemporary EBOV variants.
Refining visibility through haze removal from image becomes an inevitable chore and essential to ... more Refining visibility through haze removal from image becomes an inevitable chore and essential to recognize and track vehicles, traffic signal, and signs clearly under road safety. That can face a recurrent degradation under destitute climatic circumstances for instance fog, rain, cloud, and smog. To diminish this constraint, various methods were designed and implemented, but most were not capable of obtaining the improved quantitative outcomes. Therefore, a new algorithm Fog Elimination using Multiple Thresholds (FEMT) for single image haze eviction that meritoriously obtains the significant results on both gray and colored over real and synthetic images using multiple thresholds is proposed in this paper. The proposed method targets on the light regions by reducing the brightness and increasing the contrast of image at different levels. Finally, by grouping all the obtained resultant images leads to the generation of the resultant defogged image. The qualitative and quantitative analysis is carried out for an assessment of digitalized de-hazed images acquired from the proposed algorithm and compared to the prior techniques. Simulated fallouts entitle high resemblance to the corresponding ground truth, reduction in computation time consumption to 88% and error of 98%. The proposed approach can be applied in the field of robotics, human activity monitoring, smart systems, and digital investigation on the hazy images.
Bioinformatics is everywhere, from disease detection to disease prevention and curation, from the... more Bioinformatics is everywhere, from disease detection to disease prevention and curation, from the study of microorganisms to study of all life on earth and from sequence alignment to gene expression. This book provides in-depth information regarding the explosively growing new discipline i.e. Bioinformatics. It provides coverage of important topics like sequence alignment, phylogenetics, DNA, RNA, and proteins. From basics of central dogma of biology to computational algorithms for RNA secondary structure prediction, this book covers it all. Also, it provides implementation of few important algorithms in Dot Net framework. This book also enlightens the application areas of bioinformatics.
This article is available in open access under Creative Common Attribution-Non-Commercial-No Deri... more This article is available in open access under Creative Common Attribution-Non-Commercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0) license, allowing to download articles and share them with others as long as they credit the authors and the publisher, but without permission to change them in any way or use them commercially.
International journal of imaging and robotics, 2018
This research work proposes the design of a field programmable gate array (FPGA) based efficient ... more This research work proposes the design of a field programmable gate array (FPGA) based efficient surveillance robot. A bifurcated processing approach has been developed with an implementation of a part of video processing algorithms on the ZYNQ XC7Z010-1CLG400C FPGA (on the surveillance robot) and another part of the controller system. Video processing filters on the video signals to be transmitted are mapped onto the peripherals of the surveillance robot whereas detection and tracking algorithms have been applied to Control Unit system. Wi-Fi module on the surveillance robot transmits the Processed signals. The control unit system receives the transmitted video signals via IEEE 802.11 protocol. The control on robot has been achieved by the gaming console at control unit system with the manual feedback provided by a human. Wireless control with the portable controller has also been enabled with the help of an application developed on the Android device. Unlike conventional Surveilla...
2017 International Conference on Infocom Technologies and Unmanned Systems (Trends and Future Directions) (ICTUS), 2017
In the current scenario, the data on the web is growing exponentially. Social media is generating... more In the current scenario, the data on the web is growing exponentially. Social media is generating a large amount of data such as reviews, comments, and customers' opinions on a daily basis. This huge amount of user generated data is worthless unless some mining operations are applied to it. As there are a number of fake reviews so opinion mining technique should incorporate Spam detection to produce a genuine opinion. Nowadays, there are a number of people using social media opinions to create their call on shopping for product or service. Opinion Spam detection is an exhausting and hard problem as there are many faux or fake reviews that have been created by organizations or by the people for various purposes. They write fake reviews to mislead readers or automated detection system by promoting or demoting target products to promote them or to or to degrade their reputations. In this paper, the proposed technique includes ontology, Geo location and IP address tracking, Spam wor...
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