Big Data (BD) is the massive amount of data that has been collected as a result of recent develop... more Big Data (BD) is the massive amount of data that has been collected as a result of recent developments in sensor networks and IoT technology. More effective techniques with high analytical accuracy are required for the investigation of such vast amounts of data. The ability to analyze large amounts of data in real time is severely limited by the standard neural network and artificial intelligence algorithms. In the past several years, DL has started to take center stage in BD's analytics solutions. When it comes to BD analytics, DL can produce results that are more accurate, quicker, and scalable. In domains including natural language processing, speech recognition, and computer vision, it has achieved before unseen success. DL is an interesting and useful technique for BD analytics because of its capacity to extract high-level complicated representations as well as data scenarios, particularly unsupervised data from big volume data. To the best of our knowledge, no comprehensive survey covering all DL approaches for BD analytics exists, despite this interest. The current survey's goal is to examine the BD analytics research that has been done with DL methods. Several studies that offer very accurate analytical findings explore the potential use of DL with BD analytics.
Modeling Deep Neural Networks for Breast Cancer Thermography Classification, 2021
Building up a breast cancer screening platform is vital to encourage early "Breast cancer" detect... more Building up a breast cancer screening platform is vital to encourage early "Breast cancer" detection and treatment. Proposing a screening system utilizing clinical imaging methodology that doesn't cause body tissue harm (non-obtrusive) and doesn't include actual touch is a major challenge. Thermography, a "non-intrusive" and "non-contact" malignancy screening strategy, can recognize tumors at the beginning phase significantly under determined conditions by noticing temperature circulation in the two bosoms. The thermograms can be deciphered utilizing Deep learning models, for example, "convolutional neural networks (CNN)". CNNs can naturally group bosom thermograms into classifications, for example, ordinary and up-normal. In this work, we intend to cover the most significant studies identified with the usage of deep neural networks for bosom thermogram classification. As we accept that, an overview of breast thermogram possibilities shows that the early manifestations of bosom malignant can be seen by recognizing the asymmetrical warm dispersions between the bosoms. The asymmetrical warm appropriation on bosom thermograms can be assessed utilizing a computeraided platform that depended on deep learning models.
Applications of IoT in Smart Grids Using Demand Respond for Minimizing On-peak Load, 2021
Increased on-peak loads requests have gotten quite possibly the most difficult issues addressed b... more Increased on-peak loads requests have gotten quite possibly the most difficult issues addressed by numerous electric utilities and governments. Electricity power outages in developing nations are an everyday reality because of expanded economic activities. Consequently, traditional electric grids are being changed into smart grids (SGs) to address such issue of on-peak loads events. SGs enable "bi-directional" electricity and data flow between electric utilities and end-uses, and utilize different gadgets deployed at power plants, distribution centers and in customers' buildings for checking and control the grid functions. Consequently, a SG requires automation, tracking and connectivity of such gadgets. This is accomplished via the applications of Internet of Things (IoT). IoT supports different functions of SG frameworks through the generation, transmission and utilization of energy by deploying IoT gadgets (like sensors), just as by giving the
The Principle Internet of Things (IoT) Security Techniques Framework Based on Seven Levels IoT’s Reference Model, 2021
Basically, by increasing Internet of Things (IoT) paradigm involvement in our lives, a lot of thr... more Basically, by increasing Internet of Things (IoT) paradigm involvement in our lives, a lot of threats and attacks regarding IoT security and privacy are realized and raised. If they are left without taking extensive considerations, such security and privacy issues and challenges can certainly threaten the IoT existence. Such security and privacy issues are derived from many reasons. One of these reasons is the unavailability of universal accepted appropriate IoT security techniques, methods, and guidelines. These methods and techniques will greatly guide IoT developers and engineering, draw the success road for developing, and implementing secure IoT systems. So, our contribution focusses on such objective in which, we propose a comprehensive IoT security and privacy framework based on the seven levels of IoT reference architecture introduced by Cisco, in which a set of proper security techniques and guidelines is specified for each level. Additionally, we identify several critical techniques which can be accomplished for blocking many possible attacks against the IoT seven levels.
Internet of Things (IoT) Technologies for Empowering E-Education in Digital campuses of Smart Cities, 2021
This article centers around the exploration related to the e-learning in the smart cities. The re... more This article centers around the exploration related to the e-learning in the smart cities. The recent innovation, for example, Internet of Things (IoT) is quickly grown in the computerized life. Formation of the intelligent urban communities is developing with the idea of the IoT in the same time. E-residents as the fundamental component play an imperative part in building the keen urban communities. It is undeniable that another type of the resident in the smart cities can assume a fundamental part in case he/she gets satisfactory e-learning. In the computerized life, the IoT grounds in the intelligent urban communities are focused on the enhancement of the e-Leaning part by utilizing advanced communications and methods. Our work here centers around the requirement of embracing IoT techniques in campuses of intelligent cities , as well as supporting the theoretical analysis about the anticipated benefits of the smart learning and its application in the brilliant communities in a definite discussion.
Deep Learning Techniques for Improving Breast Cancer Detection and Diagnosis, 2022
In this paper, we aim to introduce a survey on the applications of deep learning for breast cance... more In this paper, we aim to introduce a survey on the applications of deep learning for breast cancer detection and diagnosis to provide an overview of the progress in this field. In the survey, we firstly provide an overview on deep learning and the popular architectures used for breast cancer detection and diagnosis. Especially we present four popular deep learning architectures, including convolutional neural networks, fully convolutional networks, auto encoders, and deep belief networks in the survey. Secondly, we provide a survey on the studies exploiting deep learning for breast cancer detection and diagnosis.
Business Intelligence (BI) Significant Role in Electronic Health Records - Cancer Surgeries Prediction: Case Study, 2022
Medical datasets reflect a great environment as they integrate analyses of structured and unstruc... more Medical datasets reflect a great environment as they integrate analyses of structured and unstructured data that holds several benefits for medical sector. With a continues demand for implementing Electronic Health Records (EHRs), there is a relative requirement for utilizing data mining (DM) techniques to find out useful data, unknown patterns and inference rules from data stored in EHRs which help in a real-time decisions making process and prove-based practice for medical providers and experts. Business Intelligence (BI) is a technology able to process the huge data inside EHRs repository for enhancing the quality of medical delivery. DM is data processing techniques that considered a critical part of the BI platform. In this paper, we highlight significance of the BI integration with the EHRs to aid medical providers and professionals in real-time detection and prediction for several diseases. For more explanation, we apply BI technology with support of clustering technique as one of DM methods, for cancer surgeries prediction to prove the power of cooperating BI and EHRs in medical area.
Electricity load demand converts from time to time frequently in a day. Encountering time-varying... more Electricity load demand converts from time to time frequently in a day. Encountering time-varying demand particularly in peak times is considered a big challenge that faces electric utilities. Persistent growth in peak load increases the prospect of power failure and increases the electricity equipping marginal cost. Therefore, balancing production and consumption of electricity or addressing peak load has become a key attention of utilities. Most previous works and researches were focused on applying Shave/Shift peak load to solve energy scarcity. In this study, we introduce four significant technologies and techniques for achieving peak load shaving, namely "Internet of Things (IoT) in Energy System", "On-site Generation systems (Renewable Energy Resources)", "Demand Side Management (DSM)" applications of control center and "Energy Storage Systems (ESSs)". The impact of these four major methods for peak load shaving to the grid has been discussed in detail. Finally, we suggest a conceptual framework as guiding tool for illustrating the presented technologies of Shave/Shift peak load in energy systems.
Big Data with Column Oriented NOSQL Database to Overcome the Drawbacks of Relational Databases, 2020
Due to the Era of Big Data with the large amount of distributed databases in the web and the rapi... more Due to the Era of Big Data with the large amount of distributed databases in the web and the rapid growth in the smart systems a rapid growth happening in database models and the relational database fails to dealing with such a big amount of data and have many limitations the need to new technologies comes up, which makes DBMS developers move towards column oriented NOSQL database. The main goal of this paper is to provide a survey on NOSQL Model especiallya column oriented NOSQL database, providing the user with the benefit of using NOSQL database, Instead of using the (row database) relational to overcome the drawbacks of the relational database Model.
Recovery and Concurrency Challenging in Big Data and NoSQL Database Systems, 2020
Big data is becoming a very important concept nowadays as it can handle data in different formats... more Big data is becoming a very important concept nowadays as it can handle data in different formats and structures, velocity, and huge volume. NOSQL databases are used for handling the data with these characteristics as traditional database can't be used in managing this type of data. NoSQL database design is based on horizontal scalability with the concept of BASE which supports eventual consistence and data is considered in a soft state and basically available. Although NoSQL has a lot to offer when used in big data it is still not mature enough and faces some challenges including low join performance, concurrency control and recovery. Not only this but also it is very challenging for organizations to know which NoSQL data model to use and how does it fit with its organizational needs. This paper mainly displays the different NOSQL data models and the opportunities and challenges alongside with some techniques for handling these challenges.
Int. J. Advanced Networking and Applications , 2019
Abnormal temperature of human body is a natural extensive indicator of illness. Infrared thermogr... more Abnormal temperature of human body is a natural extensive indicator of illness. Infrared thermography (IRT) is a fast, non-invasive, non-contact and passive substitution to ordinary medical thermometers for monitoring and observation human body temperature. Aside from, IRT is able to chart body surface heat remotely. Last five decades testified a stationary development in thermal imaging cameras utilization to obtain relations between the thermal physiology and surface temperature. IRT has effectively used in diagnosis and detection of breast cancer, diabetes neuropathy and peripheral vascular disorders. It has been employed to detect issues related to gynecology, dermatology, heart, neonatal physiology, and brain imaging. With the advent of modern infrared cameras, data acquisition and processing techniques, it is now possible to have real time high resolution thermographic images, which is likely to surge further research in this field. The emergent technology known as the Internet of Things (IoT) has guided practitioners, physicians and researchers to design innovative solutions in different environments, particularly in medical and healthcare using smart sensors, computer networks and a remote server. This paper aims to propose IoT-enabled medical system enables diagnostics and detection for several medical anomalies remotely; in real-time and simultaneous depend on combination of IoT and Thermal Infrared imaging techniques. It will detect and diagnostics any abnormal and alert the user through IoT remotely and in real-time.
The Success Implementation CRM Model for Examining the Critical Success Factors Using Statistical Data Mining Techniques, 2017
The customer relationship management (CRM) implementation success is not easy and seems to be a c... more The customer relationship management (CRM) implementation success is not easy and seems to be a complex task. Almost about 65% of all CRM implementation projects fail to achieve their expected objectives. Therefore, most researchers and IS developers concentrate on the critical success factors approach which can enhance the success of CRM implementation and turn the failure, and drawbacks faced CRM into successful implementation. This paper aims to propose a successful CRM model based on the critical success factors approach, and test it in an international context. The results significantly supported that the human factors, technology factors, and CRM effectiveness dimensions (relationship quality and transactions quality) have a relatively positive impact on the success of CRM (in financial and marketing results). However, the process factors have not shown a positive influence on the CRM success.
The Future of Internet of Things for Anomalies Detection using Thermography, 2019
Abnormal temperature of human body is a natural extensive indicator of illness. Infrared thermogr... more Abnormal temperature of human body is a natural extensive indicator of illness. Infrared thermography (IRT) is a fast, non-invasive, non-contact and passive substitution to ordinary medical thermometers for monitoring and observation human body temperature. Aside from, IRT is able to chart body surface heat remotely. Last five decades testified a stationary development in thermal imaging cameras utilization to obtain relations between the thermal physiology and surface temperature. IRT has effectively used in diagnosis and detection of breast cancer, diabetes neuropathy and peripheral vascular disorders. It has been employed to detect issues related to gynecology, dermatology, heart, neonatal physiology, and brain imaging. With the advent of modern infrared cameras, data acquisition and processing techniques, it is now possible to have real time high resolution thermographic images, which is likely to surge further research in this field. The emergent technology known as the Internet of Things (IoT) has guided practitioners, physicians and researchers to design innovative solutions in different environments, particularly in medical and healthcare using smart sensors, computer networks and a remote server. This paper aims to propose IoT-enabled medical system enables diagnostics and detection for several medical anomalies remotely; in real-time and simultaneous depend on combination of IoT and Thermal Infrared imaging techniques. It will detect and diagnostics any abnormal and alert the user through IoT remotely and in real-time.
A systematic review for the determination and classification of the CRM critical success factors supporting with their metrics, 2018
The successful implementation of customer relationship management (CRM) is not easy and seems to ... more The successful implementation of customer relationship management (CRM) is not easy and seems to be a complex task. Almost about 70% of all CRM implementation projects fail to achieve their expected objectives. Therefore, most researchers and information systems developers concentrate on the critical success factors approach which can enhance the success of CRM implementation and turn the failure and drawbacks faced CRM into successful CRM systems adoption and implementation. In this paper, the number of the previous studies is reviewed to demonstrate the barriers behind this high failure rate. In addition, an extensive review is conducted in order to identify and prioritize the critical success factors (CSFs) that if the organizations are aware of and have knowledge of them properly; they will achieve success and will obtain the expected benefits of their CRM initiative. And then, an extensive CSFs classification is proposed. Finally, the work proposes an extensive list of metrics as the means to help in measuring these critical success factors.
Diabetes Disease Detection through Data Mining Techniques, 2019
Diabetes is a inveterate defect and disturbance resulted from metabolic conk out in carbohydrate ... more Diabetes is a inveterate defect and disturbance resulted from metabolic conk out in carbohydrate metabolism thus it has occupied a globally serious health problem. In general, the detection of diabetes in early stages can greatly has significant impact on the diabetic patients treatment in which lead to drive out its relevant side effects. Machine learning is an emerging technology that providing high importance prognosis and a deeper understanding for different clustering of diseases such as diabetes. And because there is a lack of effective analysis tools to discover hidden relationships and trends in data, so Health information technology has emerged as a new technology in health care sector in a short period by utilizing Business Intelligence 'BI' which is a data-driven Decision Support System. In this study, we proposed a high precision diagnostic analysis by using k-means clustering technique. In the first stage, noisy, uncertain and inconsistent data was detected and removed from data set through the preprocessing to prepare date to implement a clustering model. Then, we apply k-means technique on community health diabetes related indicators data set to cluster diabetic patients from healthy one with high accuracy and reliability results.
Big Data (BD) is the massive amount of data that has been collected as a result of recent develop... more Big Data (BD) is the massive amount of data that has been collected as a result of recent developments in sensor networks and IoT technology. More effective techniques with high analytical accuracy are required for the investigation of such vast amounts of data. The ability to analyze large amounts of data in real time is severely limited by the standard neural network and artificial intelligence algorithms. In the past several years, DL has started to take center stage in BD's analytics solutions. When it comes to BD analytics, DL can produce results that are more accurate, quicker, and scalable. In domains including natural language processing, speech recognition, and computer vision, it has achieved before unseen success. DL is an interesting and useful technique for BD analytics because of its capacity to extract high-level complicated representations as well as data scenarios, particularly unsupervised data from big volume data. To the best of our knowledge, no comprehensive survey covering all DL approaches for BD analytics exists, despite this interest. The current survey's goal is to examine the BD analytics research that has been done with DL methods. Several studies that offer very accurate analytical findings explore the potential use of DL with BD analytics.
Modeling Deep Neural Networks for Breast Cancer Thermography Classification, 2021
Building up a breast cancer screening platform is vital to encourage early "Breast cancer" detect... more Building up a breast cancer screening platform is vital to encourage early "Breast cancer" detection and treatment. Proposing a screening system utilizing clinical imaging methodology that doesn't cause body tissue harm (non-obtrusive) and doesn't include actual touch is a major challenge. Thermography, a "non-intrusive" and "non-contact" malignancy screening strategy, can recognize tumors at the beginning phase significantly under determined conditions by noticing temperature circulation in the two bosoms. The thermograms can be deciphered utilizing Deep learning models, for example, "convolutional neural networks (CNN)". CNNs can naturally group bosom thermograms into classifications, for example, ordinary and up-normal. In this work, we intend to cover the most significant studies identified with the usage of deep neural networks for bosom thermogram classification. As we accept that, an overview of breast thermogram possibilities shows that the early manifestations of bosom malignant can be seen by recognizing the asymmetrical warm dispersions between the bosoms. The asymmetrical warm appropriation on bosom thermograms can be assessed utilizing a computeraided platform that depended on deep learning models.
Applications of IoT in Smart Grids Using Demand Respond for Minimizing On-peak Load, 2021
Increased on-peak loads requests have gotten quite possibly the most difficult issues addressed b... more Increased on-peak loads requests have gotten quite possibly the most difficult issues addressed by numerous electric utilities and governments. Electricity power outages in developing nations are an everyday reality because of expanded economic activities. Consequently, traditional electric grids are being changed into smart grids (SGs) to address such issue of on-peak loads events. SGs enable "bi-directional" electricity and data flow between electric utilities and end-uses, and utilize different gadgets deployed at power plants, distribution centers and in customers' buildings for checking and control the grid functions. Consequently, a SG requires automation, tracking and connectivity of such gadgets. This is accomplished via the applications of Internet of Things (IoT). IoT supports different functions of SG frameworks through the generation, transmission and utilization of energy by deploying IoT gadgets (like sensors), just as by giving the
The Principle Internet of Things (IoT) Security Techniques Framework Based on Seven Levels IoT’s Reference Model, 2021
Basically, by increasing Internet of Things (IoT) paradigm involvement in our lives, a lot of thr... more Basically, by increasing Internet of Things (IoT) paradigm involvement in our lives, a lot of threats and attacks regarding IoT security and privacy are realized and raised. If they are left without taking extensive considerations, such security and privacy issues and challenges can certainly threaten the IoT existence. Such security and privacy issues are derived from many reasons. One of these reasons is the unavailability of universal accepted appropriate IoT security techniques, methods, and guidelines. These methods and techniques will greatly guide IoT developers and engineering, draw the success road for developing, and implementing secure IoT systems. So, our contribution focusses on such objective in which, we propose a comprehensive IoT security and privacy framework based on the seven levels of IoT reference architecture introduced by Cisco, in which a set of proper security techniques and guidelines is specified for each level. Additionally, we identify several critical techniques which can be accomplished for blocking many possible attacks against the IoT seven levels.
Internet of Things (IoT) Technologies for Empowering E-Education in Digital campuses of Smart Cities, 2021
This article centers around the exploration related to the e-learning in the smart cities. The re... more This article centers around the exploration related to the e-learning in the smart cities. The recent innovation, for example, Internet of Things (IoT) is quickly grown in the computerized life. Formation of the intelligent urban communities is developing with the idea of the IoT in the same time. E-residents as the fundamental component play an imperative part in building the keen urban communities. It is undeniable that another type of the resident in the smart cities can assume a fundamental part in case he/she gets satisfactory e-learning. In the computerized life, the IoT grounds in the intelligent urban communities are focused on the enhancement of the e-Leaning part by utilizing advanced communications and methods. Our work here centers around the requirement of embracing IoT techniques in campuses of intelligent cities , as well as supporting the theoretical analysis about the anticipated benefits of the smart learning and its application in the brilliant communities in a definite discussion.
Deep Learning Techniques for Improving Breast Cancer Detection and Diagnosis, 2022
In this paper, we aim to introduce a survey on the applications of deep learning for breast cance... more In this paper, we aim to introduce a survey on the applications of deep learning for breast cancer detection and diagnosis to provide an overview of the progress in this field. In the survey, we firstly provide an overview on deep learning and the popular architectures used for breast cancer detection and diagnosis. Especially we present four popular deep learning architectures, including convolutional neural networks, fully convolutional networks, auto encoders, and deep belief networks in the survey. Secondly, we provide a survey on the studies exploiting deep learning for breast cancer detection and diagnosis.
Business Intelligence (BI) Significant Role in Electronic Health Records - Cancer Surgeries Prediction: Case Study, 2022
Medical datasets reflect a great environment as they integrate analyses of structured and unstruc... more Medical datasets reflect a great environment as they integrate analyses of structured and unstructured data that holds several benefits for medical sector. With a continues demand for implementing Electronic Health Records (EHRs), there is a relative requirement for utilizing data mining (DM) techniques to find out useful data, unknown patterns and inference rules from data stored in EHRs which help in a real-time decisions making process and prove-based practice for medical providers and experts. Business Intelligence (BI) is a technology able to process the huge data inside EHRs repository for enhancing the quality of medical delivery. DM is data processing techniques that considered a critical part of the BI platform. In this paper, we highlight significance of the BI integration with the EHRs to aid medical providers and professionals in real-time detection and prediction for several diseases. For more explanation, we apply BI technology with support of clustering technique as one of DM methods, for cancer surgeries prediction to prove the power of cooperating BI and EHRs in medical area.
Electricity load demand converts from time to time frequently in a day. Encountering time-varying... more Electricity load demand converts from time to time frequently in a day. Encountering time-varying demand particularly in peak times is considered a big challenge that faces electric utilities. Persistent growth in peak load increases the prospect of power failure and increases the electricity equipping marginal cost. Therefore, balancing production and consumption of electricity or addressing peak load has become a key attention of utilities. Most previous works and researches were focused on applying Shave/Shift peak load to solve energy scarcity. In this study, we introduce four significant technologies and techniques for achieving peak load shaving, namely "Internet of Things (IoT) in Energy System", "On-site Generation systems (Renewable Energy Resources)", "Demand Side Management (DSM)" applications of control center and "Energy Storage Systems (ESSs)". The impact of these four major methods for peak load shaving to the grid has been discussed in detail. Finally, we suggest a conceptual framework as guiding tool for illustrating the presented technologies of Shave/Shift peak load in energy systems.
Big Data with Column Oriented NOSQL Database to Overcome the Drawbacks of Relational Databases, 2020
Due to the Era of Big Data with the large amount of distributed databases in the web and the rapi... more Due to the Era of Big Data with the large amount of distributed databases in the web and the rapid growth in the smart systems a rapid growth happening in database models and the relational database fails to dealing with such a big amount of data and have many limitations the need to new technologies comes up, which makes DBMS developers move towards column oriented NOSQL database. The main goal of this paper is to provide a survey on NOSQL Model especiallya column oriented NOSQL database, providing the user with the benefit of using NOSQL database, Instead of using the (row database) relational to overcome the drawbacks of the relational database Model.
Recovery and Concurrency Challenging in Big Data and NoSQL Database Systems, 2020
Big data is becoming a very important concept nowadays as it can handle data in different formats... more Big data is becoming a very important concept nowadays as it can handle data in different formats and structures, velocity, and huge volume. NOSQL databases are used for handling the data with these characteristics as traditional database can't be used in managing this type of data. NoSQL database design is based on horizontal scalability with the concept of BASE which supports eventual consistence and data is considered in a soft state and basically available. Although NoSQL has a lot to offer when used in big data it is still not mature enough and faces some challenges including low join performance, concurrency control and recovery. Not only this but also it is very challenging for organizations to know which NoSQL data model to use and how does it fit with its organizational needs. This paper mainly displays the different NOSQL data models and the opportunities and challenges alongside with some techniques for handling these challenges.
Int. J. Advanced Networking and Applications , 2019
Abnormal temperature of human body is a natural extensive indicator of illness. Infrared thermogr... more Abnormal temperature of human body is a natural extensive indicator of illness. Infrared thermography (IRT) is a fast, non-invasive, non-contact and passive substitution to ordinary medical thermometers for monitoring and observation human body temperature. Aside from, IRT is able to chart body surface heat remotely. Last five decades testified a stationary development in thermal imaging cameras utilization to obtain relations between the thermal physiology and surface temperature. IRT has effectively used in diagnosis and detection of breast cancer, diabetes neuropathy and peripheral vascular disorders. It has been employed to detect issues related to gynecology, dermatology, heart, neonatal physiology, and brain imaging. With the advent of modern infrared cameras, data acquisition and processing techniques, it is now possible to have real time high resolution thermographic images, which is likely to surge further research in this field. The emergent technology known as the Internet of Things (IoT) has guided practitioners, physicians and researchers to design innovative solutions in different environments, particularly in medical and healthcare using smart sensors, computer networks and a remote server. This paper aims to propose IoT-enabled medical system enables diagnostics and detection for several medical anomalies remotely; in real-time and simultaneous depend on combination of IoT and Thermal Infrared imaging techniques. It will detect and diagnostics any abnormal and alert the user through IoT remotely and in real-time.
The Success Implementation CRM Model for Examining the Critical Success Factors Using Statistical Data Mining Techniques, 2017
The customer relationship management (CRM) implementation success is not easy and seems to be a c... more The customer relationship management (CRM) implementation success is not easy and seems to be a complex task. Almost about 65% of all CRM implementation projects fail to achieve their expected objectives. Therefore, most researchers and IS developers concentrate on the critical success factors approach which can enhance the success of CRM implementation and turn the failure, and drawbacks faced CRM into successful implementation. This paper aims to propose a successful CRM model based on the critical success factors approach, and test it in an international context. The results significantly supported that the human factors, technology factors, and CRM effectiveness dimensions (relationship quality and transactions quality) have a relatively positive impact on the success of CRM (in financial and marketing results). However, the process factors have not shown a positive influence on the CRM success.
The Future of Internet of Things for Anomalies Detection using Thermography, 2019
Abnormal temperature of human body is a natural extensive indicator of illness. Infrared thermogr... more Abnormal temperature of human body is a natural extensive indicator of illness. Infrared thermography (IRT) is a fast, non-invasive, non-contact and passive substitution to ordinary medical thermometers for monitoring and observation human body temperature. Aside from, IRT is able to chart body surface heat remotely. Last five decades testified a stationary development in thermal imaging cameras utilization to obtain relations between the thermal physiology and surface temperature. IRT has effectively used in diagnosis and detection of breast cancer, diabetes neuropathy and peripheral vascular disorders. It has been employed to detect issues related to gynecology, dermatology, heart, neonatal physiology, and brain imaging. With the advent of modern infrared cameras, data acquisition and processing techniques, it is now possible to have real time high resolution thermographic images, which is likely to surge further research in this field. The emergent technology known as the Internet of Things (IoT) has guided practitioners, physicians and researchers to design innovative solutions in different environments, particularly in medical and healthcare using smart sensors, computer networks and a remote server. This paper aims to propose IoT-enabled medical system enables diagnostics and detection for several medical anomalies remotely; in real-time and simultaneous depend on combination of IoT and Thermal Infrared imaging techniques. It will detect and diagnostics any abnormal and alert the user through IoT remotely and in real-time.
A systematic review for the determination and classification of the CRM critical success factors supporting with their metrics, 2018
The successful implementation of customer relationship management (CRM) is not easy and seems to ... more The successful implementation of customer relationship management (CRM) is not easy and seems to be a complex task. Almost about 70% of all CRM implementation projects fail to achieve their expected objectives. Therefore, most researchers and information systems developers concentrate on the critical success factors approach which can enhance the success of CRM implementation and turn the failure and drawbacks faced CRM into successful CRM systems adoption and implementation. In this paper, the number of the previous studies is reviewed to demonstrate the barriers behind this high failure rate. In addition, an extensive review is conducted in order to identify and prioritize the critical success factors (CSFs) that if the organizations are aware of and have knowledge of them properly; they will achieve success and will obtain the expected benefits of their CRM initiative. And then, an extensive CSFs classification is proposed. Finally, the work proposes an extensive list of metrics as the means to help in measuring these critical success factors.
Diabetes Disease Detection through Data Mining Techniques, 2019
Diabetes is a inveterate defect and disturbance resulted from metabolic conk out in carbohydrate ... more Diabetes is a inveterate defect and disturbance resulted from metabolic conk out in carbohydrate metabolism thus it has occupied a globally serious health problem. In general, the detection of diabetes in early stages can greatly has significant impact on the diabetic patients treatment in which lead to drive out its relevant side effects. Machine learning is an emerging technology that providing high importance prognosis and a deeper understanding for different clustering of diseases such as diabetes. And because there is a lack of effective analysis tools to discover hidden relationships and trends in data, so Health information technology has emerged as a new technology in health care sector in a short period by utilizing Business Intelligence 'BI' which is a data-driven Decision Support System. In this study, we proposed a high precision diagnostic analysis by using k-means clustering technique. In the first stage, noisy, uncertain and inconsistent data was detected and removed from data set through the preprocessing to prepare date to implement a clustering model. Then, we apply k-means technique on community health diabetes related indicators data set to cluster diabetic patients from healthy one with high accuracy and reliability results.
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Papers by Amira H A S S A N Abed