Journal of Materials Engineering and Performance, 2011
Your article is protected by copyright and all rights are held exclusively by ASM International. ... more Your article is protected by copyright and all rights are held exclusively by ASM International. This e-offprint is for personal use only and shall not be self-archived in electronic repositories. If you wish to selfarchive your work, please use the accepted author's version for posting to your own website or your institution's repository. You may further deposit the accepted author's version on a funder's repository at a funder's request, provided it is not made publicly available until 12 months after publication.
Andalusite, as a refractory material, transforms to mullite and a silica rich liquid phase at 110... more Andalusite, as a refractory material, transforms to mullite and a silica rich liquid phase at 1100-1600uC. The glassy phase constitutes about 20 wt-% of the reaction products, which is undesirable in refractories. In this research, alumina and zirconia were added to andalusite in order to reduce the amount of the glassy phase. Alumina was introduced by dry and solution mixing, while zirconia was added only by dry mixing method. The effects of MgO on andalusitemullite and andalusite-zirconia mixes were also studied. MgO was introduced by solution (precipitation) method on andalusite surface. The samples were fired at 1400, 1500 and 1600uC. X-ray diffraction and SEM results showed that alumina reduces the liquid phase at all of the temperatures, but zirconia was effective only at 1400 and 1500uC. MgO seemed to be capable of reducing in andalusite transformation by 100uC and had positive effect on reaction between alumina and liquid phase; it was not effective on reaction between zirconia and liquid phase.
2020 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)
Increasing importance of energy, equipment, and consumables is the main motivation for many resea... more Increasing importance of energy, equipment, and consumables is the main motivation for many researches. One of the most efficient and, of course, very old equipment is the reluctance synchronous motor, which has not received much attention until now due to the problems of analog controllers. However, in the years to come, thanks to the remarkable development of control equipment and digital equipment, these motors can be controlled with great flexibility and stability. Therefore, in this research, we have tried to design an optimum drive for these motors, while controlling these motors with the least dependence on different operating conditions and load changes with minimum losses and, of course, unwanted harmonics. They are also a good alternative to induction motors with about 60% less loss and, of course, for permanent magnet synchronous motors because of the lower construction cost and no dependency on the permanent magnet. And, of course, due to the smooth operation and the lack of a ripple in torque, they can replace with switch reluctance motors.
The Journal of Qazvin University of Medical Sciences, 2017
Background: Children, due to their insufficient risk detection, are more vulnerable to accidents ... more Background: Children, due to their insufficient risk detection, are more vulnerable to accidents than adults. Objective: The present study has been done to explore the prevalence of accidents and related factors among children under five years old from 2006 to 2016 in Qazvin. Methods: This descriptive-analytic study concluded all 18184 children who had exposure to accidents during study time section from 2006 to 2016. All recorded data in Health Information System (HIS) of Qazvin Health Management Office were probed to explore the target figures, and then were entered in a qualified checklist. All data were analyzed by descriptive statistical methods and Multinomial Logistic Regression. Findings: The prevalence rate of accidents in the target children was eight percent, which more than half (62.9 %) were taken place in boys. Accidents in children before one year old (31.4 %), and home accidents (46.5%) were the most prevalent one. In addition to these, the rates of Trauma, Fallings,...
International Journal of Communication Systems, 2021
Over the last decade, the Internet of Things (IoT) had impressive growth and became the new direc... more Over the last decade, the Internet of Things (IoT) had impressive growth and became the new direction of information technology. Also, the energy consumption has reached distressing rates due to the large scale of digital context, a number of subscribers, and the number of smart devices. By capturing and processing sensitive information in human life, the IoT devices and cloud data centers are increasing energy consumption with a high carbon emission phenomenon. In the IoT ecosystem, intelligent applications require to select smart devices with low energy consumption and battery saving because all smart devices have limited battery life and may lead to disconnect data transmission. However, it is challenging to design a fully optimized framework due to the interconnected nature of smart devices with different technologies. On the other hand, green energy-efficient computing has become a potential research focus in the IoT environment. Finally, energy consumption techniques are incoming a more advanced stage in the IoT communications. Also, green energy-efficient techniques can use on-demand protocols, machine learning, deep learning, and artificial intelligence methods to manage cost-effective and power-saving methods on smart devices in IoT communications. To this point, green energy-efficient computing solutions in IoT systems have emerging efforts and high potential to evaluate the critical points and safety conditions. The goal of this special issue is to highlight the latest research focusing on green energy-efficient computing solutions in IoT systems to address the challenges and critical points. We also aim to invite researchers to publish selected original articles presenting intelligent trends to solve new challenges of new problems. We are also interested in review articles as the state-of-the-art of this topic, showing recent major advances and discoveries, significant gaps in the research, and new future issues. This special issue provides a new platform for researchers and scientific experts to share and analyze existing technical case studies to the field of energy-efficient computing solutions in the IoT environments. Our special issue has attracted 35 manuscripts. After a peer review process, 10 papers have been selected for publication in this special issue. Details of these selected papers are presented in the next section.
Today, a growing number of the world population face a rise in the cost of living, especially an ... more Today, a growing number of the world population face a rise in the cost of living, especially an increase in energy costs. That is why Energy-saving has become a vital issue. In this regard, one of the remarkable ways to reduce energy consumption is using cool pigments; therefore, many kinds of research have been done to improve pigments' infrared reflection capability. In this paper, the role of particle morphology was investigated to boost the infrared reflection property of iron-chromium-based pigments. For this purpose, a series of inorganic pigments based on the Fe0.7Cr1.3O3 formula was prepared via a hydrothermal method. The particles' morphology was altered by using surfactants to improve the pigments' reflecting properties. The IR reflectance results proved that the flaky particles exhibit an enhanced IR reflection, which is significantly higher than in the spherical one. Furthermore, the results have revealed that silica coating leads to a meaningful improvement...
Nowadays, one of the new solutions to develop Internet of Things (IoT) applications is cloud manu... more Nowadays, one of the new solutions to develop Internet of Things (IoT) applications is cloud manufacturing. By increasing the number of actuators, industrial devices and sensors in industry 4.0 technology, the IoT is going to improve the intelligence of the enterprise information systems with a fast transition towards flexible, smarter, automated and reactive services. In order to respond the needs more quickly or matching the cloud services with modified requirements, cloud manufacturing service composition is used to take advantage of several services available in the Industrial IoT applications. The cloud-based manufacturing services can be characterized, published, shared, and retrieved over the cloud infrastructure to provide integrated services according to the user QoS requirements in a collaborative environment. In this work, a service composition approach is provided for cloud manufacturing in IoT applications. For evaluating the correctness of the proposed solution, a formal verification method is presented based on Labeled Transition System (LTS). Also, Whale Optimization Algorithm (WOA) is utilized to enhance the Quality of Service (QoS), when the number of cloud services have been increased. Finally, deadlock-free and reachability factors as important logical problems are satisfied in verification of the proposed approach. The verification results obtained under different Linear Temporal Logic (LTL) properties and various number of cloud providers indicate that the proposed approach is a correct and valid solution and it outperforms in terms of the reachability, verification time, deadlock, and memory usage.
In recent years, a massive amount of genomic DNA sequences are being created which leads to the d... more In recent years, a massive amount of genomic DNA sequences are being created which leads to the development of new storing and archiving methods. There is a major challenge to process, store or transmit the huge volume of DNA sequences data. To lessen the number of bits needed to store and transmit data, data compression (DC) techniques are proposed. Recently, DC becomes more popular, and large number of techniques is proposed with applications in several domains. In this paper, a lossless compression technique named Arithmetic coding is employed to compress DNA sequences. In order to validate the performance of the proposed model, the artificial genome dataset is used and the results are investigated interms of different evaluation parameters. Experiments were performed on artificial datasets and the compression performance of Arithmetic coding is compared to Huffman coding, LZW coding, and LZMA techniques. From simulation results, it is clear that the Arithmetic coding achieves si...
Journal of Ambient Intelligence and Humanized Computing, 2020
Advancement of sensor technologies has conducted to the rapid evolution of platforms, tools and a... more Advancement of sensor technologies has conducted to the rapid evolution of platforms, tools and approaches such as Internet of Things (IoT) for developing behavioral and physiological monitoring systems. Nowadays, According to growing number of elderlies living alone without their relatives scattered over the wide geographical areas, it is significantly essential to track their health function status continuously. In this paper, an IoT-based health monitoring system is proposed to check vital signs and detect biological and behavioral changes via smart elderly care technologies. It provides a health monitoring system for the involved medical teams to continuously monitor and assess a disabled or elderly's behavioral activity as well as the biological parameters, applying sensor technology through the IoT devices. In this approach, vital data is collected via IoT monitoring objects and then, data analysis is carried out through different machine learning methods such as Decision Tree (J48), Sequential Minimal Optimization (SMO), Multi-Layer Perceptron (MLP) and Naïve Bayes (NB) classifiers for detecting the level of probable risks of elderly's physiological and behavioral changes. The experimental results confirm that the SMO, MLP and NB classifiers meet approximately close performance considering the accuracy, precision, recall, and f-score factors. However, the J48 method shows the highest performance for health function status predicting in our scenario with 99%, of accuracy and precision, 100% of recall and 97% of f-score. Moreover, the J48 performs with the lowest execution time in comparison to the other applied classifiers.
Children with autism spectrum disorders (ASDs) have some disturbance activities. Usually, they ca... more Children with autism spectrum disorders (ASDs) have some disturbance activities. Usually, they cannot speak fluently. Instead, they use gestures and pointing words to make a relationship. Hence, understanding their needs is one of the most challenging tasks for caregivers, but early diagnosis of the disease can make it much easier. The lack of verbal and nonverbal communications can be eliminated by assistive technologies and the Internet of Things (IoT). The IoT-based systems help to diagnose and improve the patients' lives through applying Deep Learning (DL) and Machine Learning (ML) algorithms. This paper provides a systematic review of the ASD approaches in the context of IoT devices. The main goal of this review is to recognize significant research trends in the field of IoT-based healthcare. Also, a technical taxonomy is presented to classify the existing papers on the ASD methods and algorithms. A statistical and functional analysis of reviewed ASD approaches is provided based on evaluation metrics such as accuracy and sensitivity.
Advancement in sensor technologies has resulted in rapid evolution of Internet of Things (IoT) ap... more Advancement in sensor technologies has resulted in rapid evolution of Internet of Things (IoT) applications for developing behavioral and physiological monitoring systems such as IoT-based student healthcare monitoring system. Nowadays, a growing number of students living alone scattered over wide geographical areas, and tracking their health function status is necessary. In this paper, an IoT-based student healthcare monitoring model is proposed to continuously check student vital signs and detect biological and behavioral changes via smart healthcare technologies. In this model, vital data are collected via IoT devices and data analysis is carried out through the machine learning methods for detecting the probable risks of student's physiological and behavioral changes. The experimental results reveal that the proposed model meets the efficiency and proper accuracy for detecting the students' condition. After evaluating the proposed model, the support vector machine has achieved the highest accuracy of 99.1% which is a promising result for our purpose. The results outperformed decision tree, random forest, and multilayer perceptron neural network algorithms as well.
Nowadays, detecting anomaly events in communication networks is highly under consideration by man... more Nowadays, detecting anomaly events in communication networks is highly under consideration by many researchers. In a large communication network, traffic is massive, which leads to a larger amount of data travelling and also the growth of noise. Therefore, to extract meaningful data for anomaly detection would be very challenging. Each attack has its own behaviour that determines the type of attack. However, some attacks may have similar behaviours and only differ in some features. Extracting such meaningful features is of special importance. In this study, an association rule mining algorithm, in particular, the Apriori algorithm is employed to extract appropriate features from the raw data including rules and repetitive patterns. The extracted features would be used then for classifying the data and detecting anomalies in communication networks. A hybrid of artificial neural network and AdaBoost classification algorithms are employed for classifying the detected events with normal behaviour and attack events. The proposed method is compared with previous methods reported in this field such as CART, CHAID, multiple linear regression and logistic regression on KDDCUP99 data set. The results showed that the proposed method outperformed other classifiers examined. The strategy of reinforcement learning is used to combine the classifier's results which is based on Max vote strategy.
International Journal of Pervasive Computing and Communications, 2019
PurposeGrid computing is an effective environment for the execution of parallel applications that... more PurposeGrid computing is an effective environment for the execution of parallel applications that requires great computing power. This paper aims to present, based on the hierarchical architecture, an improved weighted resource discovery (WRD) algorithm to manage allocation of resources and minimize cost of communications between grid nodes.Design/methodology/approachA behavioral modeling method is addressed to prove the proposed method correctness. The behavioral model of the proposed algorithm is implemented by StarUML tool with two different model-checking mechanisms. Then, the resource discovery correctness is analyzed in terms of reachability condition, fairness condition and deadlock-free using NuSMV model checker.FindingsThe results show that WRD algorithm has better performance in requiring re-discovery process, the number of examined nodes in each request and discovering the free resources with high-bandwidth links.Originality/valueTo store information of resources, a new d...
SummaryIn recent years, users are becoming increasingly accustomed to using the Internet to gain ... more SummaryIn recent years, users are becoming increasingly accustomed to using the Internet to gain software resources in the form of web services provided by information technology organizations. Cloud computing is a service delivery paradigm that shares services and resources to access the web services to the end users over the Internet. In the cloud environment, based on the user's needs, various types of services with similar functionalities but different quality‐of‐service (QoS) criteria can be delivered, which often must be combined to meet the users' requests. The optimal selection and composition of these services are realized as an interesting issue. In this paper, we propose a moth‐flame optimization (MFO) algorithm, which is a novel nature‐inspired metaheuristic paradigm for the web service composition (WSC) problem called “MFO‐WSC,” to improve the QoS criteria in the distributed cloud environment. Also, formal modeling is presented for the QoS‐aware MFO‐WSC algorith...
Human-centric Computing and Information Sciences, 2019
Model checking is an influential method to verify complex interactions, concurrent and distribute... more Model checking is an influential method to verify complex interactions, concurrent and distributed systems. Model checking constructs a behavioral model of the system using formal concepts such as operations, states, events and actions. The model checkers suffer some weaknesses such as state space explosion problem that has high memory consumption and time complexity. Also, automating temporal logic is the main challenge to define critical specification rules in the model checking. To improve the model checking weaknesses, this paper presents Graphical Symbolic Modeling Toolkit (GSMT) to design and verify the behavioral models of distributed systems. A behavioral modeling framework is presented to design the system behavior in the forms of Kripke structure (KS) and Labeled Transition System (LTS). The behavioral models are created and edited using a graphical user interface platform in four layers that include a design layer, a modeling layer, a logic layer and a symbolic code layer...
Highlight Providing a summary of the current challenges related to the formal verification appr... more Highlight Providing a summary of the current challenges related to the formal verification approaches in the cloud computing. Presenting a Systematic Literature Review (SLR) method for the formal verification approaches in the cloud computing topics and additional significant achievement in this area. Exploring a structure of the important methods that are significant in formal verification approaches. Discussing the important factors of formal verification approaches in the cloud environment to improve their problems in the future.
Journal of Materials Engineering and Performance, 2011
Your article is protected by copyright and all rights are held exclusively by ASM International. ... more Your article is protected by copyright and all rights are held exclusively by ASM International. This e-offprint is for personal use only and shall not be self-archived in electronic repositories. If you wish to selfarchive your work, please use the accepted author's version for posting to your own website or your institution's repository. You may further deposit the accepted author's version on a funder's repository at a funder's request, provided it is not made publicly available until 12 months after publication.
Andalusite, as a refractory material, transforms to mullite and a silica rich liquid phase at 110... more Andalusite, as a refractory material, transforms to mullite and a silica rich liquid phase at 1100-1600uC. The glassy phase constitutes about 20 wt-% of the reaction products, which is undesirable in refractories. In this research, alumina and zirconia were added to andalusite in order to reduce the amount of the glassy phase. Alumina was introduced by dry and solution mixing, while zirconia was added only by dry mixing method. The effects of MgO on andalusitemullite and andalusite-zirconia mixes were also studied. MgO was introduced by solution (precipitation) method on andalusite surface. The samples were fired at 1400, 1500 and 1600uC. X-ray diffraction and SEM results showed that alumina reduces the liquid phase at all of the temperatures, but zirconia was effective only at 1400 and 1500uC. MgO seemed to be capable of reducing in andalusite transformation by 100uC and had positive effect on reaction between alumina and liquid phase; it was not effective on reaction between zirconia and liquid phase.
2020 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)
Increasing importance of energy, equipment, and consumables is the main motivation for many resea... more Increasing importance of energy, equipment, and consumables is the main motivation for many researches. One of the most efficient and, of course, very old equipment is the reluctance synchronous motor, which has not received much attention until now due to the problems of analog controllers. However, in the years to come, thanks to the remarkable development of control equipment and digital equipment, these motors can be controlled with great flexibility and stability. Therefore, in this research, we have tried to design an optimum drive for these motors, while controlling these motors with the least dependence on different operating conditions and load changes with minimum losses and, of course, unwanted harmonics. They are also a good alternative to induction motors with about 60% less loss and, of course, for permanent magnet synchronous motors because of the lower construction cost and no dependency on the permanent magnet. And, of course, due to the smooth operation and the lack of a ripple in torque, they can replace with switch reluctance motors.
The Journal of Qazvin University of Medical Sciences, 2017
Background: Children, due to their insufficient risk detection, are more vulnerable to accidents ... more Background: Children, due to their insufficient risk detection, are more vulnerable to accidents than adults. Objective: The present study has been done to explore the prevalence of accidents and related factors among children under five years old from 2006 to 2016 in Qazvin. Methods: This descriptive-analytic study concluded all 18184 children who had exposure to accidents during study time section from 2006 to 2016. All recorded data in Health Information System (HIS) of Qazvin Health Management Office were probed to explore the target figures, and then were entered in a qualified checklist. All data were analyzed by descriptive statistical methods and Multinomial Logistic Regression. Findings: The prevalence rate of accidents in the target children was eight percent, which more than half (62.9 %) were taken place in boys. Accidents in children before one year old (31.4 %), and home accidents (46.5%) were the most prevalent one. In addition to these, the rates of Trauma, Fallings,...
International Journal of Communication Systems, 2021
Over the last decade, the Internet of Things (IoT) had impressive growth and became the new direc... more Over the last decade, the Internet of Things (IoT) had impressive growth and became the new direction of information technology. Also, the energy consumption has reached distressing rates due to the large scale of digital context, a number of subscribers, and the number of smart devices. By capturing and processing sensitive information in human life, the IoT devices and cloud data centers are increasing energy consumption with a high carbon emission phenomenon. In the IoT ecosystem, intelligent applications require to select smart devices with low energy consumption and battery saving because all smart devices have limited battery life and may lead to disconnect data transmission. However, it is challenging to design a fully optimized framework due to the interconnected nature of smart devices with different technologies. On the other hand, green energy-efficient computing has become a potential research focus in the IoT environment. Finally, energy consumption techniques are incoming a more advanced stage in the IoT communications. Also, green energy-efficient techniques can use on-demand protocols, machine learning, deep learning, and artificial intelligence methods to manage cost-effective and power-saving methods on smart devices in IoT communications. To this point, green energy-efficient computing solutions in IoT systems have emerging efforts and high potential to evaluate the critical points and safety conditions. The goal of this special issue is to highlight the latest research focusing on green energy-efficient computing solutions in IoT systems to address the challenges and critical points. We also aim to invite researchers to publish selected original articles presenting intelligent trends to solve new challenges of new problems. We are also interested in review articles as the state-of-the-art of this topic, showing recent major advances and discoveries, significant gaps in the research, and new future issues. This special issue provides a new platform for researchers and scientific experts to share and analyze existing technical case studies to the field of energy-efficient computing solutions in the IoT environments. Our special issue has attracted 35 manuscripts. After a peer review process, 10 papers have been selected for publication in this special issue. Details of these selected papers are presented in the next section.
Today, a growing number of the world population face a rise in the cost of living, especially an ... more Today, a growing number of the world population face a rise in the cost of living, especially an increase in energy costs. That is why Energy-saving has become a vital issue. In this regard, one of the remarkable ways to reduce energy consumption is using cool pigments; therefore, many kinds of research have been done to improve pigments' infrared reflection capability. In this paper, the role of particle morphology was investigated to boost the infrared reflection property of iron-chromium-based pigments. For this purpose, a series of inorganic pigments based on the Fe0.7Cr1.3O3 formula was prepared via a hydrothermal method. The particles' morphology was altered by using surfactants to improve the pigments' reflecting properties. The IR reflectance results proved that the flaky particles exhibit an enhanced IR reflection, which is significantly higher than in the spherical one. Furthermore, the results have revealed that silica coating leads to a meaningful improvement...
Nowadays, one of the new solutions to develop Internet of Things (IoT) applications is cloud manu... more Nowadays, one of the new solutions to develop Internet of Things (IoT) applications is cloud manufacturing. By increasing the number of actuators, industrial devices and sensors in industry 4.0 technology, the IoT is going to improve the intelligence of the enterprise information systems with a fast transition towards flexible, smarter, automated and reactive services. In order to respond the needs more quickly or matching the cloud services with modified requirements, cloud manufacturing service composition is used to take advantage of several services available in the Industrial IoT applications. The cloud-based manufacturing services can be characterized, published, shared, and retrieved over the cloud infrastructure to provide integrated services according to the user QoS requirements in a collaborative environment. In this work, a service composition approach is provided for cloud manufacturing in IoT applications. For evaluating the correctness of the proposed solution, a formal verification method is presented based on Labeled Transition System (LTS). Also, Whale Optimization Algorithm (WOA) is utilized to enhance the Quality of Service (QoS), when the number of cloud services have been increased. Finally, deadlock-free and reachability factors as important logical problems are satisfied in verification of the proposed approach. The verification results obtained under different Linear Temporal Logic (LTL) properties and various number of cloud providers indicate that the proposed approach is a correct and valid solution and it outperforms in terms of the reachability, verification time, deadlock, and memory usage.
In recent years, a massive amount of genomic DNA sequences are being created which leads to the d... more In recent years, a massive amount of genomic DNA sequences are being created which leads to the development of new storing and archiving methods. There is a major challenge to process, store or transmit the huge volume of DNA sequences data. To lessen the number of bits needed to store and transmit data, data compression (DC) techniques are proposed. Recently, DC becomes more popular, and large number of techniques is proposed with applications in several domains. In this paper, a lossless compression technique named Arithmetic coding is employed to compress DNA sequences. In order to validate the performance of the proposed model, the artificial genome dataset is used and the results are investigated interms of different evaluation parameters. Experiments were performed on artificial datasets and the compression performance of Arithmetic coding is compared to Huffman coding, LZW coding, and LZMA techniques. From simulation results, it is clear that the Arithmetic coding achieves si...
Journal of Ambient Intelligence and Humanized Computing, 2020
Advancement of sensor technologies has conducted to the rapid evolution of platforms, tools and a... more Advancement of sensor technologies has conducted to the rapid evolution of platforms, tools and approaches such as Internet of Things (IoT) for developing behavioral and physiological monitoring systems. Nowadays, According to growing number of elderlies living alone without their relatives scattered over the wide geographical areas, it is significantly essential to track their health function status continuously. In this paper, an IoT-based health monitoring system is proposed to check vital signs and detect biological and behavioral changes via smart elderly care technologies. It provides a health monitoring system for the involved medical teams to continuously monitor and assess a disabled or elderly's behavioral activity as well as the biological parameters, applying sensor technology through the IoT devices. In this approach, vital data is collected via IoT monitoring objects and then, data analysis is carried out through different machine learning methods such as Decision Tree (J48), Sequential Minimal Optimization (SMO), Multi-Layer Perceptron (MLP) and Naïve Bayes (NB) classifiers for detecting the level of probable risks of elderly's physiological and behavioral changes. The experimental results confirm that the SMO, MLP and NB classifiers meet approximately close performance considering the accuracy, precision, recall, and f-score factors. However, the J48 method shows the highest performance for health function status predicting in our scenario with 99%, of accuracy and precision, 100% of recall and 97% of f-score. Moreover, the J48 performs with the lowest execution time in comparison to the other applied classifiers.
Children with autism spectrum disorders (ASDs) have some disturbance activities. Usually, they ca... more Children with autism spectrum disorders (ASDs) have some disturbance activities. Usually, they cannot speak fluently. Instead, they use gestures and pointing words to make a relationship. Hence, understanding their needs is one of the most challenging tasks for caregivers, but early diagnosis of the disease can make it much easier. The lack of verbal and nonverbal communications can be eliminated by assistive technologies and the Internet of Things (IoT). The IoT-based systems help to diagnose and improve the patients' lives through applying Deep Learning (DL) and Machine Learning (ML) algorithms. This paper provides a systematic review of the ASD approaches in the context of IoT devices. The main goal of this review is to recognize significant research trends in the field of IoT-based healthcare. Also, a technical taxonomy is presented to classify the existing papers on the ASD methods and algorithms. A statistical and functional analysis of reviewed ASD approaches is provided based on evaluation metrics such as accuracy and sensitivity.
Advancement in sensor technologies has resulted in rapid evolution of Internet of Things (IoT) ap... more Advancement in sensor technologies has resulted in rapid evolution of Internet of Things (IoT) applications for developing behavioral and physiological monitoring systems such as IoT-based student healthcare monitoring system. Nowadays, a growing number of students living alone scattered over wide geographical areas, and tracking their health function status is necessary. In this paper, an IoT-based student healthcare monitoring model is proposed to continuously check student vital signs and detect biological and behavioral changes via smart healthcare technologies. In this model, vital data are collected via IoT devices and data analysis is carried out through the machine learning methods for detecting the probable risks of student's physiological and behavioral changes. The experimental results reveal that the proposed model meets the efficiency and proper accuracy for detecting the students' condition. After evaluating the proposed model, the support vector machine has achieved the highest accuracy of 99.1% which is a promising result for our purpose. The results outperformed decision tree, random forest, and multilayer perceptron neural network algorithms as well.
Nowadays, detecting anomaly events in communication networks is highly under consideration by man... more Nowadays, detecting anomaly events in communication networks is highly under consideration by many researchers. In a large communication network, traffic is massive, which leads to a larger amount of data travelling and also the growth of noise. Therefore, to extract meaningful data for anomaly detection would be very challenging. Each attack has its own behaviour that determines the type of attack. However, some attacks may have similar behaviours and only differ in some features. Extracting such meaningful features is of special importance. In this study, an association rule mining algorithm, in particular, the Apriori algorithm is employed to extract appropriate features from the raw data including rules and repetitive patterns. The extracted features would be used then for classifying the data and detecting anomalies in communication networks. A hybrid of artificial neural network and AdaBoost classification algorithms are employed for classifying the detected events with normal behaviour and attack events. The proposed method is compared with previous methods reported in this field such as CART, CHAID, multiple linear regression and logistic regression on KDDCUP99 data set. The results showed that the proposed method outperformed other classifiers examined. The strategy of reinforcement learning is used to combine the classifier's results which is based on Max vote strategy.
International Journal of Pervasive Computing and Communications, 2019
PurposeGrid computing is an effective environment for the execution of parallel applications that... more PurposeGrid computing is an effective environment for the execution of parallel applications that requires great computing power. This paper aims to present, based on the hierarchical architecture, an improved weighted resource discovery (WRD) algorithm to manage allocation of resources and minimize cost of communications between grid nodes.Design/methodology/approachA behavioral modeling method is addressed to prove the proposed method correctness. The behavioral model of the proposed algorithm is implemented by StarUML tool with two different model-checking mechanisms. Then, the resource discovery correctness is analyzed in terms of reachability condition, fairness condition and deadlock-free using NuSMV model checker.FindingsThe results show that WRD algorithm has better performance in requiring re-discovery process, the number of examined nodes in each request and discovering the free resources with high-bandwidth links.Originality/valueTo store information of resources, a new d...
SummaryIn recent years, users are becoming increasingly accustomed to using the Internet to gain ... more SummaryIn recent years, users are becoming increasingly accustomed to using the Internet to gain software resources in the form of web services provided by information technology organizations. Cloud computing is a service delivery paradigm that shares services and resources to access the web services to the end users over the Internet. In the cloud environment, based on the user's needs, various types of services with similar functionalities but different quality‐of‐service (QoS) criteria can be delivered, which often must be combined to meet the users' requests. The optimal selection and composition of these services are realized as an interesting issue. In this paper, we propose a moth‐flame optimization (MFO) algorithm, which is a novel nature‐inspired metaheuristic paradigm for the web service composition (WSC) problem called “MFO‐WSC,” to improve the QoS criteria in the distributed cloud environment. Also, formal modeling is presented for the QoS‐aware MFO‐WSC algorith...
Human-centric Computing and Information Sciences, 2019
Model checking is an influential method to verify complex interactions, concurrent and distribute... more Model checking is an influential method to verify complex interactions, concurrent and distributed systems. Model checking constructs a behavioral model of the system using formal concepts such as operations, states, events and actions. The model checkers suffer some weaknesses such as state space explosion problem that has high memory consumption and time complexity. Also, automating temporal logic is the main challenge to define critical specification rules in the model checking. To improve the model checking weaknesses, this paper presents Graphical Symbolic Modeling Toolkit (GSMT) to design and verify the behavioral models of distributed systems. A behavioral modeling framework is presented to design the system behavior in the forms of Kripke structure (KS) and Labeled Transition System (LTS). The behavioral models are created and edited using a graphical user interface platform in four layers that include a design layer, a modeling layer, a logic layer and a symbolic code layer...
Highlight Providing a summary of the current challenges related to the formal verification appr... more Highlight Providing a summary of the current challenges related to the formal verification approaches in the cloud computing. Presenting a Systematic Literature Review (SLR) method for the formal verification approaches in the cloud computing topics and additional significant achievement in this area. Exploring a structure of the important methods that are significant in formal verification approaches. Discussing the important factors of formal verification approaches in the cloud environment to improve their problems in the future.
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Papers by Alireza Souri