This paper describes the implementation of an Information Systems （IS） capstone project management course that is a requirement for graduating seniors in an undergraduate Computer Information Systems （CIS） program...This paper describes the implementation of an Information Systems （IS） capstone project management course that is a requirement for graduating seniors in an undergraduate Computer Information Systems （CIS） program at a regional university. The description provides a model which includes the culmination of students＇ academic training in an IS curriculum which is part of a Bachelor of Business Administration （BBA） program in an accredited college of business. The course requires an application of technical and business skills, as well as systems development and project management skills--while students are working on an actual IS project for an external sponsoring organization. Rationale for implementing this type of course includes the benefits it provides to the students, the project sponsors, and the IS department providing the course. Feedback from the course is used as integral part of the C1S curriculum assessment process used for accreditation purposes.展开更多
The complexity of computer architectures, software, web applications, and its large spread worldwide using the internet and the rapid increase in the number of users in companion with the increase of maintenance cost ...The complexity of computer architectures, software, web applications, and its large spread worldwide using the internet and the rapid increase in the number of users in companion with the increase of maintenance cost are all factors guided many researchers to develop software, web applications and systems that have the ability of self-healing. The aim of the self healing software feature is to fast recover the application and keep it running and available for 24/7 as optimal as possible. This survey provides an overview of self-healing software and system that is especially useful in all of those situations in which the involvement of humans is costly and hard to recover and needs to be automated with self healing. There are different aspects which will make us understand the different benefits of these self-healing systems. Finally, the approaches, techniques, mechanisms and individual characteristics of self healing are classified in different tables and then summarized.展开更多
This paper aims to design and implement an automatic heart disease diagnosis system using?MATLAB. The Cleveland data set for heart diseases was used as the main database for training and testing the developed system. ...This paper aims to design and implement an automatic heart disease diagnosis system using?MATLAB. The Cleveland data set for heart diseases was used as the main database for training and testing the developed system. In order to train and test the Cleveland data set, two systems were developed. The first system is based on the Multilayer Perceptron (MLP) structure on the Artificial Neural Network (ANN), whereas the second system is based on the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach. Each system has two main modules, namely, training and testing,?where 80% and 20% of the Cleveland data set were randomly selected for training and testing?purposes respectively. Each system also has an additional module known as case-based module,?where the user has to input values for 13 required attributes as specified by the Cleveland data set,?in order to test the status of the patient whether heart disease is present or absent from that particular patient. In addition, the effects of different values for important parameters were investigated in the ANN-based and Neuro-Fuzzy-based systems in order to select the best parameters that obtain the highest performance. Based on the experimental work, it is clear that the Neuro-Fuzzy system outperforms the ANN system using the training data set, where the accuracy for each system was 100% and 90.74%, respectively. However, using the testing data set, it is clear that the ANN system outperforms the Neuro-Fuzzy system, where the best accuracy for each system was 87.04% and 75.93%, respectively.展开更多
This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends t...This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].展开更多
Aims: This study aims at designing and implementing syllabus-oriented question-bank system that is capable of producing paper-based exams with multiple forms along with answer keys. The developed software tool is nam...Aims: This study aims at designing and implementing syllabus-oriented question-bank system that is capable of producing paper-based exams with multiple forms along with answer keys. The developed software tool is named Χ(Chi)-Pro Milestone and supports four types of questions, namely: Multiple-choice, True/False, Short-Answer and Free-Response Essay questions. The study is motivated by the fact that student number in schools and universities is continuously growing at high, non-linear, and uncontrolled rates. This growth, however, is not accompanied by an equivalent growth of educational resources (mainly: instructors, classrooms, and labs). A direct result of this situation is having relatively large number of students in each classroom. It is observed that providing and using online-examining systems could be intractable and expensive. As an alternative, paper-based exams can be used. One main issue is that manually produced paper-based exams are of low quality because of some human factors such as instability and relatively narrow range of topics [1]. Further, it is observed that instructors usually need to spend a lot of time and energy in composing paper-based exams with multiple forms. Therefore, the use of computers for automatic production of paper-based exams from question banks is becoming more and more important. Methodology: The design and evaluation of X-Pro Milestone are done by considering a basic set of design principles that are based on a list of identified Functional and Non-Functional Requirements. Deriving those requirements is made possible by developing X-Pro Milestone using the Iterative and Incremental model from software engineering domain. Results: We demonstrate that X-Pro Milestone has a number of excellent characteristics compared to the exam-preparation and question banks tools available in market. Some of these characteristics are: ease of use and operation, user-friendly interface and good usability, high security and protection of the question bank-items, high stability, and reliability. Further, X-Pro Milestone makes initiating, maintaining and archiving Question-Banks and produced exams possible. Putting X-Pro Milestone into real use has showed that X-Pro Milestone is easy to be learned and effectively used. We demonstrate that X-Pro Milestone is a cost-effective alternative to online examining systems with more and richer features and with low infrastructure requirements.展开更多
This article explores the evolution of cloud computing, its advantages over traditional on-premises infrastructure, and its impact on information security. The study presents a comprehensive literature review covering...This article explores the evolution of cloud computing, its advantages over traditional on-premises infrastructure, and its impact on information security. The study presents a comprehensive literature review covering various cloud infrastructure offerings and security models. Additionally, it deeply analyzes real-life case studies illustrating successful cloud migrations and highlights common information security threats in current cloud computing. The article concludes by offering recommendations to businesses to protect themselves from cloud data breaches and providing insights into selecting a suitable cloud services provider from an information security perspective.展开更多
This research paper analyzes data breaches in the human service sector. The hypothesis for the solution to this problem is that there will be a significant reduction in data breaches in the human service sector due to...This research paper analyzes data breaches in the human service sector. The hypothesis for the solution to this problem is that there will be a significant reduction in data breaches in the human service sector due to an increase in information assurance. The hypothesis is tested using data from the United States Department of Health and Human Services data breach notification repository during January 2018-December 2020. Our result shows that without the increased mitigation of information assurance, data breaches in the human service sector will continue to increase.展开更多
The rapid development of information communication technology blazed a trail in our learning, work, and lives. This study was conducted to ascertain the computer and internet literacy level of medical faculties’ stud...The rapid development of information communication technology blazed a trail in our learning, work, and lives. This study was conducted to ascertain the computer and internet literacy level of medical faculties’ students. 171 first-year medical students from 4 different medical colleges of the University of Jordan participated in the study. A semi-structured questionnaire was used to collect the data and the data analysis was done by using SPSS, Version 17. The results indicated that most medical students have average 5 or advance knowledge on the basic use of computer and internet. Google was found to be the most commonly used search engine. Also the study found that ICT (Information and Communication Technology) can be a useful tool in medical education but the lack of time, internet connectivity and resources is still a serious constraint.展开更多
Cloud computing is a set of Information Technology services offered to users over the web on a rented base. Such services enable the organizations to scale-up or scale-down their in-house foundations. Generally, cloud...Cloud computing is a set of Information Technology services offered to users over the web on a rented base. Such services enable the organizations to scale-up or scale-down their in-house foundations. Generally, cloud services are provided by a third-party supplier who possesses the arrangement. Cloud computing has many advantages such as flexibility, efficiency, scalability, integration, and capital reduction. Moreover, it provides an advanced virtual space for organizations to deploy their applications or run their operations. With disregard to the possible benefits of cloud computing services, the organizations are reluctant to invest in cloud computing mainly due to security concerns. Security is one of the main challenges that hinder the growth of cloud computing. At the same time, service providers strive to reduce the risks over the clouds and increase their reliability in order to build mutual trust between them and the cloud customers. Various security issues and challenges are discussed in this research, and possible opportunities are stated.展开更多
Pervasive schemes are the significant techniques that allow intelligent communication among the devices without any human intervention.Recently Internet of Vehicles(IoVs)has been introduced as one of the applications ...Pervasive schemes are the significant techniques that allow intelligent communication among the devices without any human intervention.Recently Internet of Vehicles(IoVs)has been introduced as one of the applications of pervasive computing that addresses the road safety challenges.Vehicles participating within the IoV are embedded with a wide range of sensors which operate in a real time environment to improve the road safety issues.Various mechanisms have been proposed which allow automatic actions based on uncertainty of sensory and managed data.Due to the lack of existing transportation integration schemes,IoV has not been completely explored by business organizations.In order to tackle this problem,we have proposed a novel trusted mechanism in IoV during communication,sensing,and record storing.Our proposed method uses trust based analysis and subjective logic functions with the aim of creating a trust environment for vehicles to communicate.In addition,the subjective logic function is integrated with multi-attribute SAW scheme to improve the decision metrics of authenticating nodes.The trust analysis depends on a variety of metrics to ensure an accurate identification of legitimate vehicles embedded with IoT devices ecosystem.The proposed scheme is determined and verified rigorously through various IoT devices and decision making metrics against a baseline solution.The simulation results show that the proposed scheme leads to 88%improvement in terms of better identification of legitimate nodes,road accidents and message alteration records during data transmission among vehicles as compared to the baseline approach.展开更多
The proposed study focuses on the critical issue of corrosion,which leads to significant economic losses and safety risks worldwide.A key area of emphasis is the accuracy of corrosion detection methods.While recent st...The proposed study focuses on the critical issue of corrosion,which leads to significant economic losses and safety risks worldwide.A key area of emphasis is the accuracy of corrosion detection methods.While recent studies have made progress,a common challenge is the low accuracy of existing detection models.These models often struggle to reliably identify corrosion tendencies,which are crucial for minimizing industrial risks and optimizing resource use.The proposed study introduces an innovative approach that significantly improves the accuracy of corrosion detection using a convolutional neural network(CNN),as well as two pretrained models,namely YOLOv8 and EfficientNetB0.By leveraging advanced technologies and methodologies,we have achieved high accuracies in identifying and managing the hazards associated with corrosion across various industrial settings.This advancement not only supports the overarching goals of enhancing safety and efficiency,but also sets a new benchmark for future research in the field.The results demonstrate a significant improvement in the ability to detect and mitigate corrosion-related concerns,providing a more accurate and comprehensive solution for industries facing these challenges.Both CNN and EfficientNetB0 exhibited 100%accuracy,precision,recall,and F1-score,followed by YOLOv8 with respective metrics of 95%,100%,90%,and 94.74%.Our approach outperformed state-of-the-art with similar datasets and methodologies.展开更多
Digital watermarking is one of the most powerful tools used in ownership and copyrights protection in digital media. This paper presents a blind digital video watermarking technique based on a combination scheme betwe...Digital watermarking is one of the most powerful tools used in ownership and copyrights protection in digital media. This paper presents a blind digital video watermarking technique based on a combination scheme between the Discrete Wavelet transform in (DWT) and the real Schur Decomposition. The scheme starts with applying twolevel DWT to the video scene followed by Schur decomposition in which the binary watermark bits are embedded in the resultant block upper triangular matrix. The proposed technique shows high efficiency due to the use of Schur decomposition which requires fewer computations compared to other transforms. The imperceptibility of the scheme is also very high due to the use of DWT transform;therefore, no visual distortion is noticed in the watermarked video after embedding. Furthermore, the technique proves to be robust against set of standard attacks like: Gaussian, salt and pepper and rotation and some video attacks such as: frame dropping, cropping and averaging. Both capacity and blindness features are also considered and achieved in this technique.展开更多
Visual cryptography (VC) is one of the best techniques used to secure information. It uses the human vision to decrypt the encrypted images without any cryptographic computations. The basic concept of visual cryptogra...Visual cryptography (VC) is one of the best techniques used to secure information. It uses the human vision to decrypt the encrypted images without any cryptographic computations. The basic concept of visual cryptography is splitting the secret image into shares such that when the shares are stacked, the secret image is revealed. In this paper we proposed a method that is based on the concept of visual cryptography for color images and without any pixel expansion which requires less space. The proposed method is used to encrypt halftone color images by generating two shares, random and key shares which are the same size as the secret color image. The two shares are generated based on a private key. At the receiving side, the secret color image is revealed by stacking the two shares and exploiting the human vision system. In this paper, we produce an enhanced form of the proposed method by modifying the encryption technique used to generate the random and the key shares. Experimental results have shown that the proposed and the enhanced methods suggest an efficient way to encrypt a secret color image with better level of security, less storage space, less time of computation and with a better value of PSNR.展开更多
The main objective of software testing is to have the highest likelihood of finding the most faults with a minimum amount of time and effort. Genetic Algorithm (GA) has been successfully used by researchers in softwar...The main objective of software testing is to have the highest likelihood of finding the most faults with a minimum amount of time and effort. Genetic Algorithm (GA) has been successfully used by researchers in software testing to automatically generate test data. In this paper, a GA is applied using branch coverage criterion to generate the least possible set of test data to test JSC applications. Results show that applying GA achieves better performance in terms of average number of test data?generations, execution time, and percentage of branch coverage.展开更多
Autonomic software recovery enables software to automatically detect and recover software faults. This feature makes the software to run more efficiently, actively, and reduces the maintenance time and cost. This pape...Autonomic software recovery enables software to automatically detect and recover software faults. This feature makes the software to run more efficiently, actively, and reduces the maintenance time and cost. This paper proposes an automated approach for Software Fault Detection and Recovery (SFDR). The SFDR detects the cases if a fault occurs with software components such as component deletion, replacement or modification, and recovers the component to enable the software to continue its intended operation. The SFDR is analyzed and implemented in parallel as a standalone software at the design phase of the target software. The practical applicability of the proposed approach has been tested by implementing an application demonstrating the performance and effectiveness of the SFDR. The experimental results and the comparisons with other works show the effectiveness of the proposed approach.展开更多
Cloud computing aims to maximize the benefit of distributed resources and aggregate them to achieve higher throughput to solve large scale computation problems. In this technology, the customers rent the resources and...Cloud computing aims to maximize the benefit of distributed resources and aggregate them to achieve higher throughput to solve large scale computation problems. In this technology, the customers rent the resources and only pay per use. Job scheduling is one of the biggest issues in cloud computing. Scheduling of users’ requests means how to allocate resources to these requests to finish the tasks in minimum time. The main task of job scheduling system is to find the best resources for user’s jobs, taking into consideration some statistics and dynamic parameters restrictions of users’ jobs. In this research, we introduce cloud computing, genetic algorithm and artificial neural networks, and then review the literature of cloud job scheduling. Many researchers in the literature tried to solve the cloud job scheduling using different techniques. Most of them use artificial intelligence techniques such as genetic algorithm and ant colony to solve the problem of job scheduling and to find the optimal distribution of resources. Unfortunately, there are still some problems in this research area. Therefore, we propose implementing artificial neural networks to optimize the job scheduling results in cloud as it can find new set of classifications not only search within the available set.展开更多
The development of multimedia and digital imaging has led to high quantity of data required to represent modern imagery. This requires large disk space for storage, and long time for transmission over computer network...The development of multimedia and digital imaging has led to high quantity of data required to represent modern imagery. This requires large disk space for storage, and long time for transmission over computer networks, and these two are relatively expensive. These factors prove the need for images compression. Image compression addresses the problem of reducing the amount of space required to represent a digital image yielding a compact representation of an image, and thereby reducing the image storage/transmission time requirements. The key idea here is to remove redundancy of data presented within an image to reduce its size without affecting the essential information of it. We are concerned with lossless image compression in this paper. Our proposed approach is a mix of a number of already existing techniques. Our approach works as follows: first, we apply the well-known Lempel-Ziv-Welch (LZW) algorithm on the image in hand. What comes out of the first step is forward to the second step where the Bose, Chaudhuri and Hocquenghem (BCH) error correction and detected algorithm is used. To improve the compression ratio, the proposed approach applies the BCH algorithms repeatedly until “inflation” is detected. The experimental results show that the proposed algorithm could achieve an excellent compression ratio without losing data when compared to the standard compression algorithms.展开更多
As one chemical composition,nicotine content has an important influence on the quality of tobacco leaves.Rapid and nondestructive quantitative analysis of nicotine is an important task in the tobacco industry.Near-inf...As one chemical composition,nicotine content has an important influence on the quality of tobacco leaves.Rapid and nondestructive quantitative analysis of nicotine is an important task in the tobacco industry.Near-infrared(NIR)spectroscopy as an effective chemical composition analysis technique has been widely used.In this paper,we propose a one-dimensional fully convolutional network(1D-FCN)model to quantitatively analyze the nicotine composition of tobacco leaves using NIR spectroscopy data in a cloud environment.This 1D-FCN model uses one-dimensional convolution layers to directly extract the complex features from sequential spectroscopy data.It consists of five convolutional layers and two full connection layers with the max-pooling layer replaced by a convolutional layer to avoid information loss.Cloud computing techniques are used to solve the increasing requests of large-size data analysis and implement data sharing and accessing.Experimental results show that the proposed 1D-FCN model can effectively extract the complex characteristics inside the spectrum and more accurately predict the nicotine volumes in tobacco leaves than other approaches.This research provides a deep learning foundation for quantitative analysis of NIR spectral data in the tobacco industry.展开更多
文摘This paper describes the implementation of an Information Systems （IS） capstone project management course that is a requirement for graduating seniors in an undergraduate Computer Information Systems （CIS） program at a regional university. The description provides a model which includes the culmination of students＇ academic training in an IS curriculum which is part of a Bachelor of Business Administration （BBA） program in an accredited college of business. The course requires an application of technical and business skills, as well as systems development and project management skills--while students are working on an actual IS project for an external sponsoring organization. Rationale for implementing this type of course includes the benefits it provides to the students, the project sponsors, and the IS department providing the course. Feedback from the course is used as integral part of the C1S curriculum assessment process used for accreditation purposes.
文摘The complexity of computer architectures, software, web applications, and its large spread worldwide using the internet and the rapid increase in the number of users in companion with the increase of maintenance cost are all factors guided many researchers to develop software, web applications and systems that have the ability of self-healing. The aim of the self healing software feature is to fast recover the application and keep it running and available for 24/7 as optimal as possible. This survey provides an overview of self-healing software and system that is especially useful in all of those situations in which the involvement of humans is costly and hard to recover and needs to be automated with self healing. There are different aspects which will make us understand the different benefits of these self-healing systems. Finally, the approaches, techniques, mechanisms and individual characteristics of self healing are classified in different tables and then summarized.
文摘This paper aims to design and implement an automatic heart disease diagnosis system using?MATLAB. The Cleveland data set for heart diseases was used as the main database for training and testing the developed system. In order to train and test the Cleveland data set, two systems were developed. The first system is based on the Multilayer Perceptron (MLP) structure on the Artificial Neural Network (ANN), whereas the second system is based on the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach. Each system has two main modules, namely, training and testing,?where 80% and 20% of the Cleveland data set were randomly selected for training and testing?purposes respectively. Each system also has an additional module known as case-based module,?where the user has to input values for 13 required attributes as specified by the Cleveland data set,?in order to test the status of the patient whether heart disease is present or absent from that particular patient. In addition, the effects of different values for important parameters were investigated in the ANN-based and Neuro-Fuzzy-based systems in order to select the best parameters that obtain the highest performance. Based on the experimental work, it is clear that the Neuro-Fuzzy system outperforms the ANN system using the training data set, where the accuracy for each system was 100% and 90.74%, respectively. However, using the testing data set, it is clear that the ANN system outperforms the Neuro-Fuzzy system, where the best accuracy for each system was 87.04% and 75.93%, respectively.
文摘This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].
文摘Aims: This study aims at designing and implementing syllabus-oriented question-bank system that is capable of producing paper-based exams with multiple forms along with answer keys. The developed software tool is named Χ(Chi)-Pro Milestone and supports four types of questions, namely: Multiple-choice, True/False, Short-Answer and Free-Response Essay questions. The study is motivated by the fact that student number in schools and universities is continuously growing at high, non-linear, and uncontrolled rates. This growth, however, is not accompanied by an equivalent growth of educational resources (mainly: instructors, classrooms, and labs). A direct result of this situation is having relatively large number of students in each classroom. It is observed that providing and using online-examining systems could be intractable and expensive. As an alternative, paper-based exams can be used. One main issue is that manually produced paper-based exams are of low quality because of some human factors such as instability and relatively narrow range of topics [1]. Further, it is observed that instructors usually need to spend a lot of time and energy in composing paper-based exams with multiple forms. Therefore, the use of computers for automatic production of paper-based exams from question banks is becoming more and more important. Methodology: The design and evaluation of X-Pro Milestone are done by considering a basic set of design principles that are based on a list of identified Functional and Non-Functional Requirements. Deriving those requirements is made possible by developing X-Pro Milestone using the Iterative and Incremental model from software engineering domain. Results: We demonstrate that X-Pro Milestone has a number of excellent characteristics compared to the exam-preparation and question banks tools available in market. Some of these characteristics are: ease of use and operation, user-friendly interface and good usability, high security and protection of the question bank-items, high stability, and reliability. Further, X-Pro Milestone makes initiating, maintaining and archiving Question-Banks and produced exams possible. Putting X-Pro Milestone into real use has showed that X-Pro Milestone is easy to be learned and effectively used. We demonstrate that X-Pro Milestone is a cost-effective alternative to online examining systems with more and richer features and with low infrastructure requirements.
文摘This article explores the evolution of cloud computing, its advantages over traditional on-premises infrastructure, and its impact on information security. The study presents a comprehensive literature review covering various cloud infrastructure offerings and security models. Additionally, it deeply analyzes real-life case studies illustrating successful cloud migrations and highlights common information security threats in current cloud computing. The article concludes by offering recommendations to businesses to protect themselves from cloud data breaches and providing insights into selecting a suitable cloud services provider from an information security perspective.
文摘This research paper analyzes data breaches in the human service sector. The hypothesis for the solution to this problem is that there will be a significant reduction in data breaches in the human service sector due to an increase in information assurance. The hypothesis is tested using data from the United States Department of Health and Human Services data breach notification repository during January 2018-December 2020. Our result shows that without the increased mitigation of information assurance, data breaches in the human service sector will continue to increase.
文摘The rapid development of information communication technology blazed a trail in our learning, work, and lives. This study was conducted to ascertain the computer and internet literacy level of medical faculties’ students. 171 first-year medical students from 4 different medical colleges of the University of Jordan participated in the study. A semi-structured questionnaire was used to collect the data and the data analysis was done by using SPSS, Version 17. The results indicated that most medical students have average 5 or advance knowledge on the basic use of computer and internet. Google was found to be the most commonly used search engine. Also the study found that ICT (Information and Communication Technology) can be a useful tool in medical education but the lack of time, internet connectivity and resources is still a serious constraint.
文摘Cloud computing is a set of Information Technology services offered to users over the web on a rented base. Such services enable the organizations to scale-up or scale-down their in-house foundations. Generally, cloud services are provided by a third-party supplier who possesses the arrangement. Cloud computing has many advantages such as flexibility, efficiency, scalability, integration, and capital reduction. Moreover, it provides an advanced virtual space for organizations to deploy their applications or run their operations. With disregard to the possible benefits of cloud computing services, the organizations are reluctant to invest in cloud computing mainly due to security concerns. Security is one of the main challenges that hinder the growth of cloud computing. At the same time, service providers strive to reduce the risks over the clouds and increase their reliability in order to build mutual trust between them and the cloud customers. Various security issues and challenges are discussed in this research, and possible opportunities are stated.
基金funded by the Abu Dhabi University,Faculty Research Incentive Grant(19300483–Adel Khelifi),United Arab Emirates.Link to Sponsor website:https://www.adu.ac.ae/research/research-at-adu/overview.
文摘Pervasive schemes are the significant techniques that allow intelligent communication among the devices without any human intervention.Recently Internet of Vehicles(IoVs)has been introduced as one of the applications of pervasive computing that addresses the road safety challenges.Vehicles participating within the IoV are embedded with a wide range of sensors which operate in a real time environment to improve the road safety issues.Various mechanisms have been proposed which allow automatic actions based on uncertainty of sensory and managed data.Due to the lack of existing transportation integration schemes,IoV has not been completely explored by business organizations.In order to tackle this problem,we have proposed a novel trusted mechanism in IoV during communication,sensing,and record storing.Our proposed method uses trust based analysis and subjective logic functions with the aim of creating a trust environment for vehicles to communicate.In addition,the subjective logic function is integrated with multi-attribute SAW scheme to improve the decision metrics of authenticating nodes.The trust analysis depends on a variety of metrics to ensure an accurate identification of legitimate vehicles embedded with IoT devices ecosystem.The proposed scheme is determined and verified rigorously through various IoT devices and decision making metrics against a baseline solution.The simulation results show that the proposed scheme leads to 88%improvement in terms of better identification of legitimate nodes,road accidents and message alteration records during data transmission among vehicles as compared to the baseline approach.
文摘The proposed study focuses on the critical issue of corrosion,which leads to significant economic losses and safety risks worldwide.A key area of emphasis is the accuracy of corrosion detection methods.While recent studies have made progress,a common challenge is the low accuracy of existing detection models.These models often struggle to reliably identify corrosion tendencies,which are crucial for minimizing industrial risks and optimizing resource use.The proposed study introduces an innovative approach that significantly improves the accuracy of corrosion detection using a convolutional neural network(CNN),as well as two pretrained models,namely YOLOv8 and EfficientNetB0.By leveraging advanced technologies and methodologies,we have achieved high accuracies in identifying and managing the hazards associated with corrosion across various industrial settings.This advancement not only supports the overarching goals of enhancing safety and efficiency,but also sets a new benchmark for future research in the field.The results demonstrate a significant improvement in the ability to detect and mitigate corrosion-related concerns,providing a more accurate and comprehensive solution for industries facing these challenges.Both CNN and EfficientNetB0 exhibited 100%accuracy,precision,recall,and F1-score,followed by YOLOv8 with respective metrics of 95%,100%,90%,and 94.74%.Our approach outperformed state-of-the-art with similar datasets and methodologies.
文摘Digital watermarking is one of the most powerful tools used in ownership and copyrights protection in digital media. This paper presents a blind digital video watermarking technique based on a combination scheme between the Discrete Wavelet transform in (DWT) and the real Schur Decomposition. The scheme starts with applying twolevel DWT to the video scene followed by Schur decomposition in which the binary watermark bits are embedded in the resultant block upper triangular matrix. The proposed technique shows high efficiency due to the use of Schur decomposition which requires fewer computations compared to other transforms. The imperceptibility of the scheme is also very high due to the use of DWT transform;therefore, no visual distortion is noticed in the watermarked video after embedding. Furthermore, the technique proves to be robust against set of standard attacks like: Gaussian, salt and pepper and rotation and some video attacks such as: frame dropping, cropping and averaging. Both capacity and blindness features are also considered and achieved in this technique.
文摘Visual cryptography (VC) is one of the best techniques used to secure information. It uses the human vision to decrypt the encrypted images without any cryptographic computations. The basic concept of visual cryptography is splitting the secret image into shares such that when the shares are stacked, the secret image is revealed. In this paper we proposed a method that is based on the concept of visual cryptography for color images and without any pixel expansion which requires less space. The proposed method is used to encrypt halftone color images by generating two shares, random and key shares which are the same size as the secret color image. The two shares are generated based on a private key. At the receiving side, the secret color image is revealed by stacking the two shares and exploiting the human vision system. In this paper, we produce an enhanced form of the proposed method by modifying the encryption technique used to generate the random and the key shares. Experimental results have shown that the proposed and the enhanced methods suggest an efficient way to encrypt a secret color image with better level of security, less storage space, less time of computation and with a better value of PSNR.
文摘The main objective of software testing is to have the highest likelihood of finding the most faults with a minimum amount of time and effort. Genetic Algorithm (GA) has been successfully used by researchers in software testing to automatically generate test data. In this paper, a GA is applied using branch coverage criterion to generate the least possible set of test data to test JSC applications. Results show that applying GA achieves better performance in terms of average number of test data?generations, execution time, and percentage of branch coverage.
文摘Autonomic software recovery enables software to automatically detect and recover software faults. This feature makes the software to run more efficiently, actively, and reduces the maintenance time and cost. This paper proposes an automated approach for Software Fault Detection and Recovery (SFDR). The SFDR detects the cases if a fault occurs with software components such as component deletion, replacement or modification, and recovers the component to enable the software to continue its intended operation. The SFDR is analyzed and implemented in parallel as a standalone software at the design phase of the target software. The practical applicability of the proposed approach has been tested by implementing an application demonstrating the performance and effectiveness of the SFDR. The experimental results and the comparisons with other works show the effectiveness of the proposed approach.
文摘Cloud computing aims to maximize the benefit of distributed resources and aggregate them to achieve higher throughput to solve large scale computation problems. In this technology, the customers rent the resources and only pay per use. Job scheduling is one of the biggest issues in cloud computing. Scheduling of users’ requests means how to allocate resources to these requests to finish the tasks in minimum time. The main task of job scheduling system is to find the best resources for user’s jobs, taking into consideration some statistics and dynamic parameters restrictions of users’ jobs. In this research, we introduce cloud computing, genetic algorithm and artificial neural networks, and then review the literature of cloud job scheduling. Many researchers in the literature tried to solve the cloud job scheduling using different techniques. Most of them use artificial intelligence techniques such as genetic algorithm and ant colony to solve the problem of job scheduling and to find the optimal distribution of resources. Unfortunately, there are still some problems in this research area. Therefore, we propose implementing artificial neural networks to optimize the job scheduling results in cloud as it can find new set of classifications not only search within the available set.
文摘The development of multimedia and digital imaging has led to high quantity of data required to represent modern imagery. This requires large disk space for storage, and long time for transmission over computer networks, and these two are relatively expensive. These factors prove the need for images compression. Image compression addresses the problem of reducing the amount of space required to represent a digital image yielding a compact representation of an image, and thereby reducing the image storage/transmission time requirements. The key idea here is to remove redundancy of data presented within an image to reduce its size without affecting the essential information of it. We are concerned with lossless image compression in this paper. Our proposed approach is a mix of a number of already existing techniques. Our approach works as follows: first, we apply the well-known Lempel-Ziv-Welch (LZW) algorithm on the image in hand. What comes out of the first step is forward to the second step where the Bose, Chaudhuri and Hocquenghem (BCH) error correction and detected algorithm is used. To improve the compression ratio, the proposed approach applies the BCH algorithms repeatedly until “inflation” is detected. The experimental results show that the proposed algorithm could achieve an excellent compression ratio without losing data when compared to the standard compression algorithms.
文摘As one chemical composition,nicotine content has an important influence on the quality of tobacco leaves.Rapid and nondestructive quantitative analysis of nicotine is an important task in the tobacco industry.Near-infrared(NIR)spectroscopy as an effective chemical composition analysis technique has been widely used.In this paper,we propose a one-dimensional fully convolutional network(1D-FCN)model to quantitatively analyze the nicotine composition of tobacco leaves using NIR spectroscopy data in a cloud environment.This 1D-FCN model uses one-dimensional convolution layers to directly extract the complex features from sequential spectroscopy data.It consists of five convolutional layers and two full connection layers with the max-pooling layer replaced by a convolutional layer to avoid information loss.Cloud computing techniques are used to solve the increasing requests of large-size data analysis and implement data sharing and accessing.Experimental results show that the proposed 1D-FCN model can effectively extract the complex characteristics inside the spectrum and more accurately predict the nicotine volumes in tobacco leaves than other approaches.This research provides a deep learning foundation for quantitative analysis of NIR spectral data in the tobacco industry.
