Optimization is the process of finding parameters that return the maximum or minimum value of a f... more Optimization is the process of finding parameters that return the maximum or minimum value of a function, where the function symbolizes the effort needed or the desired benefit. First-order stochastic gradient (SG) methods are often used to solve deep learning models that involve a hard non-convex optimization problem. Although second-order methods can ensure faster convergence, they have been less explored because processing time and costs are high. Optimizing deep learning models is a challenging problem; many deep learning companies spend a lot of their resources on training deep models. This paper proposes an implementation and evaluation of Newton's second-order optimization method, Hessian Free Optimization (HFO), on fully connected feed-forward networks, and enhances the method by the integration with some acceleration techniques such as Momentum and Root Mean Square Propagation (RMSProp). The paper also proposed a hybrid algorithm capable of combining two-degree orders, first-order, and second-order optimization methods. The hybrid algorithm can achieve better convergence (5% better in testing loss) compared to first-order methods with approximately the same time consumption.
Spatial self-organizations appear in many natural and artificial systems. Spatial systems creatio... more Spatial self-organizations appear in many natural and artificial systems. Spatial systems creation and development, called morphogenesis, is the subject of many research studies since many years (1). Fractal computation approach is, for exemple, one of the methods
Recently, deep learning has gained significant attention as a noteworthy division of artificial i... more Recently, deep learning has gained significant attention as a noteworthy division of artificial intelligence (AI) due to its high accuracy and versatile applications. However, one of the major challenges of AI is the need for more interpretability, commonly referred to as the black-box problem. In this study, we introduce an explainable AI model for medical image classification to enhance the interpretability of the decision-making process. Our approach is based on segmenting the images to provide a better understanding of how the AI model arrives at its results. We evaluated our model on five datasets, including the COVID-19 and Pneumonia Chest X-ray dataset, Chest X-ray (COVID-19 and Pneumonia), COVID-19 Image Dataset (COVID-19, Viral Pneumonia, Normal), and COVID-19 Radiography Database. We achieved testing and validation accuracy of 90.6% on a relatively small dataset of 6432 images. Our proposed model improved accuracy and reduced time complexity, making it more practical for m...
Convolutional Neural Networks (CNNs) have exhibited remarkable potential in effectively tackling ... more Convolutional Neural Networks (CNNs) have exhibited remarkable potential in effectively tackling the intricate task of classifying MRI images, specifically in Alzheimer’s disease detection and brain tumor identification. While CNNs optimize their parameters automatically through training processes, finding the optimal values for these parameters can still be a challenging task due to the complexity of the search space and the potential for suboptimal results. Consequently, researchers often encounter difficulties determining the ideal parameter settings for CNNs. This challenge necessitates using trial-and-error methods or expert judgment, as the search for the best combination of parameters involves exploring a vast space of possibilities. Despite the automatic optimization during training, the process does not guarantee finding the globally-optimal parameter values. Hence, researchers often rely on iterative experimentation and expert knowledge to fine-tune these parameters and ma...
International Journal of Emerging Technologies in Learning (iJET)
The field of Artificial Intelligence in Education (AIED) will change the shape of education in th... more The field of Artificial Intelligence in Education (AIED) will change the shape of education in the future completely, current classroom environment management, collaboration with teachers, and development of AI-based technology platforms. The intelligent adaptive transformation of learning and teaching in higher education required the emergence of all educational process structures. This paper presents a revolutionary educational process called AI-based learning, Which involves technologies within universities, cultures, practices, goals, and communities. This transformation reduces the gap between higher education’s outcome and industry’s needs, by producing lifelong learners. The proposed framework illustrates the full structure, the development steps, and the implementation benefits. The proposed framework also provides connections of scattered scientific research work in different related domains. Using AI competency-based learning will let students achieve the course outcomes ...
Optimization is the process of finding parameters that return the maximum or minimum value of a f... more Optimization is the process of finding parameters that return the maximum or minimum value of a function, where the function symbolizes the effort needed or the desired benefit. First-order stochastic gradient (SG) methods are often used to solve deep learning models that involve a hard non-convex optimization problem. Although second-order methods can ensure faster convergence, they have been less explored because processing time and costs are high. Optimizing deep learning models is a challenging problem; many deep learning companies spend a lot of their resources on training deep models. This paper proposes an implementation and evaluation of Newton's second-order optimization method, Hessian Free Optimization (HFO), on fully connected feed-forward networks, and enhances the method by the integration with some acceleration techniques such as Momentum and Root Mean Square Propagation (RMSProp). The paper also proposed a hybrid algorithm capable of combining two-degree orders, ...
Summary. In this paper, we deal with some specific domains of applications to game theory. This i... more Summary. In this paper, we deal with some specific domains of applications to game theory. This is one of the major class of models in the new approaches of modelling in the economic domain. For that, we use genetic automata which allow to buid adaptive strategies for the players. We explain how the automata-based formalism proposed- matrix representation of automata with multiplicities- allows to define a semi-distance between the strategy behaviors. With that tools, we are able to generate an automatic processus to compute emergent systems of entities whose behaviors are represented by these genetic automata. Key words: adaptive behavior, game theory, genetic automata, prisoner dilemma, emergent systems computing
generalized derangement, Schelling’s model This paper proposes a definition of Schelling’s model ... more generalized derangement, Schelling’s model This paper proposes a definition of Schelling’s model of segregation using generalized derangements. Many of urban or territorial modellings are based on decentralized approaches where rule-based systems have to be integrated inside a whole interaction system to describe complex phenomena. The goal of these decentralized modellings is to deal with emergent computing able to detect dynamically emergent organizations in an unsupervized way, thanks to complex systems theory. The convergence of these modern computings is generally hard to study because of the use of asynchronised processes dealing with a number of autonomous entities which are acting and interacting, in non linear way, during the whole simulation. Our approach is to define a non sequential-dependant algorithm, thanks to generalized derangements, and so to use this efficient tool to study some properties on the evolutive process.
International Journal of Scientific & Technology Research, 2019
This paper proposes a mobile application that targets the local Arabic speaking audience who use ... more This paper proposes a mobile application that targets the local Arabic speaking audience who use the local pharmacies in Jord an. It is aimed toward providing the ability for this specific audience to acquire the Arabic leaflets of the medication approved by Jordan food and drug administration. The application uses optical character recognition to recognize the enquired medication and provides a u ser-friendly interface to interact with the user and display required information in Arabic. We provide a small-scale experiment over 20 medication boxes. Every step in the process of identifying the medication is tested separately. The experimental results show that the applicat ion was able to identify the majority of medication boxes tested.
International Journal of Recent Technology and Engineering (IJRTE), 2020
Autism Spectrum Disorder (ASD) is a psychiatric disorder that puts constraints on the ability to ... more Autism Spectrum Disorder (ASD) is a psychiatric disorder that puts constraints on the ability to use of cognitive, linguistic, communicative, and social skills. Recently, many data mining techniques employed to serve this domain by determining the main features of the condition and the correlation between them. In this article, we investigate the Association Classification (AC) technique as a data mining technique in predicting whether an individual has autism or not. Accordingly, seven well-known algorithms are selected to conduct analysis and evaluation of the performance of the AC technique in term of identifying correlations between the features to help decide early on whether an individual has autism; this is particularly significant for children. The evaluation for the behavior and the performance in the prediction tasks for the AC algorithms was conducted for the common metrics of including Precision, Accuracy F-Measure as well as Recall. Finally, a comparative performance an...
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2014
Now a day, usage of mobile devices is becoming indispensable. This is evident with current mobile... more Now a day, usage of mobile devices is becoming indispensable. This is evident with current mobile penetration rates reaching 100% and even more in some countries. Customers across the world are enjoying competitive prices due to high competition among telecommunication companies. As a result of this, it is mandatory for mobile companies to provide high quality services to their customers to retain them. One aspect which will maximize customers’ trust and lead to high retention rate is to offer them a suitable plan that matches their usage. Mobile customer usage categorization is therefore an essential task to develop intelligent business plans. Personalized recommendation system is needed to dynamically adapt the different customer behaviours with the most appropriate plan for them. In this paper we propose a new automatic approach for costumers’ categorization. This will be the basis for the recommendation system. The proposed method is built using Fuzzy rule and aims at usag...
DNA microarray analysis is the main core in genome mapping. Each microarray image contains millio... more DNA microarray analysis is the main core in genome mapping. Each microarray image contains millions of information about genes. Microarray analysis is considered one of the most recent and important technologies in exploring the genome. One of the key steps in microarray analysis is to extract gene information from the gene spots, these information represent gene expression levels in the microarray. This paper proposes a new methodology to improve microarray spot analysis based on spot extracted segments. It concentrates on each spot segment area independently rather than analyzing all the spots area together of the microarray image. This paper provides a formal model to enhance the intensity values obtained from gene expression levels of the microarray at any intensity expressed level. It also this paper presents the adaptive threshold techniques to be used for microarray segmentation. The experimental results show that the mean of the gene expression intensity value was 87.77.
International Journal of Enterprise Information Systems, 2016
Search engines are crucial for information gathering systems (IGS). New challenges face search en... more Search engines are crucial for information gathering systems (IGS). New challenges face search engines concerning automatic learning from user requests. In this paper, a new hybrid intelligent system is proposed to enhance the search process. Based on a Multilayer Fuzzy Inference System (MFIS), the first step is to implement a scalable system to relay logical rules in order to produce three classifications for search behavior, user profiles, and query characteristics from analysis of navigation log files. These three outputs from the MFIS are used as inputs for the second step, an Adaptive Neuro-Fuzzy Inference System (ANFIS). The training process of the ANFIS replaced the rules by adjusting the weights in order to find the most relevant result for the search query. This proposed system, called MFIS-ANFIS, is implemented as an experimental system. The system performance is evaluated using quantitative and comparative analysis. MFIS-ANFIS aimed to be the core of intelligent and relia...
In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organi... more In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.
International Journal of Interactive Mobile Technologies (iJIM), 2015
Mobile usage is witnessing a booming growth attributed to advances in smartphone technologies, th... more Mobile usage is witnessing a booming growth attributed to advances in smartphone technologies, the extremely high penetration rate and the availability of popular mobile applications. Telecommunication markets have been injecting huge investments to fulfil the sheer demand on wireless network and mobile services as a result. Such potentials highlights the importance of behavioral segmentation of mobile network users to target different sectors of customers with efficient marketing strategies and ensure customer retention in light of the intense competition. A major hurdle in applying this approach is the number of dimensions underlying customer preferences which makes it hard to visualize similarities among customers and formulate behavioral segments correctly and efficiently. In this paper, we use self-organizing maps, to detect different usage patterns of mobile users. The proposed system is tested using a large sample of customers’ data provided by major mobile operator in Jordan...
Self-organization is common in natural systems. This tutorial describes some of these systems, sp... more Self-organization is common in natural systems. This tutorial describes some of these systems, specifically from insect societies like in bees, termites or ant colonies. In a first part, a modeling process is explained. Objects and phenomena targeted by these methods are presented. Natural or social complex systems are the context of these objects and phenomena. Basic algorithms presented for example in [10] are given. These algorithms belongs to the class of swarm intelligence methods describing how a network of interacting entities can lead to emergent properties of the whole system. In a second part, more original applications are presented, based on extensions of these basic algorithms in order to model ecosystems, urban dynamics or to propose a decentralized method to distribute simulations over dynamical communication graphs.
Journal of Software Engineering and Applications, 2014
The concept of Webpage visibility is usually linked to search engine optimization (SEO), and it i... more The concept of Webpage visibility is usually linked to search engine optimization (SEO), and it is based on global in-link metric [1]. SEO is the process of designing Webpages to optimize its potential to rank high on search engines, preferably on the first page of the results page. The purpose of this research study is to analyze the influence of local geographical area, in terms of cultural values, and the effect of local society keywords in increasing Website visibility. Websites were analyzed by accessing the source code of their homepages through Google Chrome browser. Statistical analysis methods were selected to assess and analyze the results of the SEO and search engine visibility (SEV). The results obtained suggest that the development of Web indicators to be included should consider a local idea of visibility, and consider a certain geographical context. The geographical region that the researchers are considering in this research is the Hashemite kingdom of Jordan (HKJ). The results obtained also suggest that the use of social culture keywords leads to increase the Website visibility in search engines as well as localizes the search area such as google.jo, which localizes the search for HKJ.
Journal of Software Engineering and Applications, 2014
Electronic government (e-Government) in its simplest form can mean using information and communic... more Electronic government (e-Government) in its simplest form can mean using information and communication technology (ICT) tools to provide services to citizens. Still with the huge benefits and synergies that e-Government grants to governments and societies, it faces many obstacles and challenges. Therefore, there are always a number of critical success factors and risks associated with e-Government. This paper highlights some of the key ones; it critically assesses key factors that influence e-Government services adoption and diffusion. Thus, the aim of this study is to examine and identify the factors that influence and affect the utilization of e-Government in the developing countries, specifically in Jordan. Furthermore, this article investigates the challenges and barriers that must be overcome in order to successfully implement e-Government in Jordan. Semistructured interviews were conducted and used in this study to collect the data. The results of this study show that the most significant challenges and factors influencing the implementation of e-Government services in Jordan are related to budgeting and financial costs, human expertise, social influence, technological issues, lack of awareness, resistance of public employees, data privacy and security, the legal framework, the needed technology, administrative obstacles, and trust or believing in e-Government. Conclusions, recommendations and future work are stated at the end of the paper.
In this paper, we deal with some specific domains of applications to game theory. This is one of ... more In this paper, we deal with some specific domains of applications to game theory. This is one of the major class of models in the new approaches of modelling in the economic domain. For that, we use genetic automata which allow to buid adaptive strategies for the players. We explain how the automata-based formalism proposed-matrix representation of automata with multiplicities-allows to define a semi-distance between the strategy behaviors. With that tools, we are able to generate an automatic processus to compute emergent systems of entities whose behaviors are represented by these genetic automata.
The development of distributed computations and complex systems modelling lead to the creation of... more The development of distributed computations and complex systems modelling lead to the creation of innovative algorithms based on interacting virtual entities, specifically for optimisation purpose within complex phenomena. Particule Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) are two of these algorithms. We propose in this paper a method called Community Swarm Optimisation (CSO). This method is based on more sophisticated entities which are defined by behavioral automata. This algorithm leads to the emergence of the solution by the co-evolution of their behavioral and spatial characteristics. This method is suitable for urban management, according to improve the understanding of the individual behaviors over the emergent urban organizations.
Optimization is the process of finding parameters that return the maximum or minimum value of a f... more Optimization is the process of finding parameters that return the maximum or minimum value of a function, where the function symbolizes the effort needed or the desired benefit. First-order stochastic gradient (SG) methods are often used to solve deep learning models that involve a hard non-convex optimization problem. Although second-order methods can ensure faster convergence, they have been less explored because processing time and costs are high. Optimizing deep learning models is a challenging problem; many deep learning companies spend a lot of their resources on training deep models. This paper proposes an implementation and evaluation of Newton's second-order optimization method, Hessian Free Optimization (HFO), on fully connected feed-forward networks, and enhances the method by the integration with some acceleration techniques such as Momentum and Root Mean Square Propagation (RMSProp). The paper also proposed a hybrid algorithm capable of combining two-degree orders, first-order, and second-order optimization methods. The hybrid algorithm can achieve better convergence (5% better in testing loss) compared to first-order methods with approximately the same time consumption.
Spatial self-organizations appear in many natural and artificial systems. Spatial systems creatio... more Spatial self-organizations appear in many natural and artificial systems. Spatial systems creation and development, called morphogenesis, is the subject of many research studies since many years (1). Fractal computation approach is, for exemple, one of the methods
Recently, deep learning has gained significant attention as a noteworthy division of artificial i... more Recently, deep learning has gained significant attention as a noteworthy division of artificial intelligence (AI) due to its high accuracy and versatile applications. However, one of the major challenges of AI is the need for more interpretability, commonly referred to as the black-box problem. In this study, we introduce an explainable AI model for medical image classification to enhance the interpretability of the decision-making process. Our approach is based on segmenting the images to provide a better understanding of how the AI model arrives at its results. We evaluated our model on five datasets, including the COVID-19 and Pneumonia Chest X-ray dataset, Chest X-ray (COVID-19 and Pneumonia), COVID-19 Image Dataset (COVID-19, Viral Pneumonia, Normal), and COVID-19 Radiography Database. We achieved testing and validation accuracy of 90.6% on a relatively small dataset of 6432 images. Our proposed model improved accuracy and reduced time complexity, making it more practical for m...
Convolutional Neural Networks (CNNs) have exhibited remarkable potential in effectively tackling ... more Convolutional Neural Networks (CNNs) have exhibited remarkable potential in effectively tackling the intricate task of classifying MRI images, specifically in Alzheimer’s disease detection and brain tumor identification. While CNNs optimize their parameters automatically through training processes, finding the optimal values for these parameters can still be a challenging task due to the complexity of the search space and the potential for suboptimal results. Consequently, researchers often encounter difficulties determining the ideal parameter settings for CNNs. This challenge necessitates using trial-and-error methods or expert judgment, as the search for the best combination of parameters involves exploring a vast space of possibilities. Despite the automatic optimization during training, the process does not guarantee finding the globally-optimal parameter values. Hence, researchers often rely on iterative experimentation and expert knowledge to fine-tune these parameters and ma...
International Journal of Emerging Technologies in Learning (iJET)
The field of Artificial Intelligence in Education (AIED) will change the shape of education in th... more The field of Artificial Intelligence in Education (AIED) will change the shape of education in the future completely, current classroom environment management, collaboration with teachers, and development of AI-based technology platforms. The intelligent adaptive transformation of learning and teaching in higher education required the emergence of all educational process structures. This paper presents a revolutionary educational process called AI-based learning, Which involves technologies within universities, cultures, practices, goals, and communities. This transformation reduces the gap between higher education’s outcome and industry’s needs, by producing lifelong learners. The proposed framework illustrates the full structure, the development steps, and the implementation benefits. The proposed framework also provides connections of scattered scientific research work in different related domains. Using AI competency-based learning will let students achieve the course outcomes ...
Optimization is the process of finding parameters that return the maximum or minimum value of a f... more Optimization is the process of finding parameters that return the maximum or minimum value of a function, where the function symbolizes the effort needed or the desired benefit. First-order stochastic gradient (SG) methods are often used to solve deep learning models that involve a hard non-convex optimization problem. Although second-order methods can ensure faster convergence, they have been less explored because processing time and costs are high. Optimizing deep learning models is a challenging problem; many deep learning companies spend a lot of their resources on training deep models. This paper proposes an implementation and evaluation of Newton's second-order optimization method, Hessian Free Optimization (HFO), on fully connected feed-forward networks, and enhances the method by the integration with some acceleration techniques such as Momentum and Root Mean Square Propagation (RMSProp). The paper also proposed a hybrid algorithm capable of combining two-degree orders, ...
Summary. In this paper, we deal with some specific domains of applications to game theory. This i... more Summary. In this paper, we deal with some specific domains of applications to game theory. This is one of the major class of models in the new approaches of modelling in the economic domain. For that, we use genetic automata which allow to buid adaptive strategies for the players. We explain how the automata-based formalism proposed- matrix representation of automata with multiplicities- allows to define a semi-distance between the strategy behaviors. With that tools, we are able to generate an automatic processus to compute emergent systems of entities whose behaviors are represented by these genetic automata. Key words: adaptive behavior, game theory, genetic automata, prisoner dilemma, emergent systems computing
generalized derangement, Schelling’s model This paper proposes a definition of Schelling’s model ... more generalized derangement, Schelling’s model This paper proposes a definition of Schelling’s model of segregation using generalized derangements. Many of urban or territorial modellings are based on decentralized approaches where rule-based systems have to be integrated inside a whole interaction system to describe complex phenomena. The goal of these decentralized modellings is to deal with emergent computing able to detect dynamically emergent organizations in an unsupervized way, thanks to complex systems theory. The convergence of these modern computings is generally hard to study because of the use of asynchronised processes dealing with a number of autonomous entities which are acting and interacting, in non linear way, during the whole simulation. Our approach is to define a non sequential-dependant algorithm, thanks to generalized derangements, and so to use this efficient tool to study some properties on the evolutive process.
International Journal of Scientific & Technology Research, 2019
This paper proposes a mobile application that targets the local Arabic speaking audience who use ... more This paper proposes a mobile application that targets the local Arabic speaking audience who use the local pharmacies in Jord an. It is aimed toward providing the ability for this specific audience to acquire the Arabic leaflets of the medication approved by Jordan food and drug administration. The application uses optical character recognition to recognize the enquired medication and provides a u ser-friendly interface to interact with the user and display required information in Arabic. We provide a small-scale experiment over 20 medication boxes. Every step in the process of identifying the medication is tested separately. The experimental results show that the applicat ion was able to identify the majority of medication boxes tested.
International Journal of Recent Technology and Engineering (IJRTE), 2020
Autism Spectrum Disorder (ASD) is a psychiatric disorder that puts constraints on the ability to ... more Autism Spectrum Disorder (ASD) is a psychiatric disorder that puts constraints on the ability to use of cognitive, linguistic, communicative, and social skills. Recently, many data mining techniques employed to serve this domain by determining the main features of the condition and the correlation between them. In this article, we investigate the Association Classification (AC) technique as a data mining technique in predicting whether an individual has autism or not. Accordingly, seven well-known algorithms are selected to conduct analysis and evaluation of the performance of the AC technique in term of identifying correlations between the features to help decide early on whether an individual has autism; this is particularly significant for children. The evaluation for the behavior and the performance in the prediction tasks for the AC algorithms was conducted for the common metrics of including Precision, Accuracy F-Measure as well as Recall. Finally, a comparative performance an...
INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2014
Now a day, usage of mobile devices is becoming indispensable. This is evident with current mobile... more Now a day, usage of mobile devices is becoming indispensable. This is evident with current mobile penetration rates reaching 100% and even more in some countries. Customers across the world are enjoying competitive prices due to high competition among telecommunication companies. As a result of this, it is mandatory for mobile companies to provide high quality services to their customers to retain them. One aspect which will maximize customers’ trust and lead to high retention rate is to offer them a suitable plan that matches their usage. Mobile customer usage categorization is therefore an essential task to develop intelligent business plans. Personalized recommendation system is needed to dynamically adapt the different customer behaviours with the most appropriate plan for them. In this paper we propose a new automatic approach for costumers’ categorization. This will be the basis for the recommendation system. The proposed method is built using Fuzzy rule and aims at usag...
DNA microarray analysis is the main core in genome mapping. Each microarray image contains millio... more DNA microarray analysis is the main core in genome mapping. Each microarray image contains millions of information about genes. Microarray analysis is considered one of the most recent and important technologies in exploring the genome. One of the key steps in microarray analysis is to extract gene information from the gene spots, these information represent gene expression levels in the microarray. This paper proposes a new methodology to improve microarray spot analysis based on spot extracted segments. It concentrates on each spot segment area independently rather than analyzing all the spots area together of the microarray image. This paper provides a formal model to enhance the intensity values obtained from gene expression levels of the microarray at any intensity expressed level. It also this paper presents the adaptive threshold techniques to be used for microarray segmentation. The experimental results show that the mean of the gene expression intensity value was 87.77.
International Journal of Enterprise Information Systems, 2016
Search engines are crucial for information gathering systems (IGS). New challenges face search en... more Search engines are crucial for information gathering systems (IGS). New challenges face search engines concerning automatic learning from user requests. In this paper, a new hybrid intelligent system is proposed to enhance the search process. Based on a Multilayer Fuzzy Inference System (MFIS), the first step is to implement a scalable system to relay logical rules in order to produce three classifications for search behavior, user profiles, and query characteristics from analysis of navigation log files. These three outputs from the MFIS are used as inputs for the second step, an Adaptive Neuro-Fuzzy Inference System (ANFIS). The training process of the ANFIS replaced the rules by adjusting the weights in order to find the most relevant result for the search query. This proposed system, called MFIS-ANFIS, is implemented as an experimental system. The system performance is evaluated using quantitative and comparative analysis. MFIS-ANFIS aimed to be the core of intelligent and relia...
In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organi... more In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.
International Journal of Interactive Mobile Technologies (iJIM), 2015
Mobile usage is witnessing a booming growth attributed to advances in smartphone technologies, th... more Mobile usage is witnessing a booming growth attributed to advances in smartphone technologies, the extremely high penetration rate and the availability of popular mobile applications. Telecommunication markets have been injecting huge investments to fulfil the sheer demand on wireless network and mobile services as a result. Such potentials highlights the importance of behavioral segmentation of mobile network users to target different sectors of customers with efficient marketing strategies and ensure customer retention in light of the intense competition. A major hurdle in applying this approach is the number of dimensions underlying customer preferences which makes it hard to visualize similarities among customers and formulate behavioral segments correctly and efficiently. In this paper, we use self-organizing maps, to detect different usage patterns of mobile users. The proposed system is tested using a large sample of customers’ data provided by major mobile operator in Jordan...
Self-organization is common in natural systems. This tutorial describes some of these systems, sp... more Self-organization is common in natural systems. This tutorial describes some of these systems, specifically from insect societies like in bees, termites or ant colonies. In a first part, a modeling process is explained. Objects and phenomena targeted by these methods are presented. Natural or social complex systems are the context of these objects and phenomena. Basic algorithms presented for example in [10] are given. These algorithms belongs to the class of swarm intelligence methods describing how a network of interacting entities can lead to emergent properties of the whole system. In a second part, more original applications are presented, based on extensions of these basic algorithms in order to model ecosystems, urban dynamics or to propose a decentralized method to distribute simulations over dynamical communication graphs.
Journal of Software Engineering and Applications, 2014
The concept of Webpage visibility is usually linked to search engine optimization (SEO), and it i... more The concept of Webpage visibility is usually linked to search engine optimization (SEO), and it is based on global in-link metric [1]. SEO is the process of designing Webpages to optimize its potential to rank high on search engines, preferably on the first page of the results page. The purpose of this research study is to analyze the influence of local geographical area, in terms of cultural values, and the effect of local society keywords in increasing Website visibility. Websites were analyzed by accessing the source code of their homepages through Google Chrome browser. Statistical analysis methods were selected to assess and analyze the results of the SEO and search engine visibility (SEV). The results obtained suggest that the development of Web indicators to be included should consider a local idea of visibility, and consider a certain geographical context. The geographical region that the researchers are considering in this research is the Hashemite kingdom of Jordan (HKJ). The results obtained also suggest that the use of social culture keywords leads to increase the Website visibility in search engines as well as localizes the search area such as google.jo, which localizes the search for HKJ.
Journal of Software Engineering and Applications, 2014
Electronic government (e-Government) in its simplest form can mean using information and communic... more Electronic government (e-Government) in its simplest form can mean using information and communication technology (ICT) tools to provide services to citizens. Still with the huge benefits and synergies that e-Government grants to governments and societies, it faces many obstacles and challenges. Therefore, there are always a number of critical success factors and risks associated with e-Government. This paper highlights some of the key ones; it critically assesses key factors that influence e-Government services adoption and diffusion. Thus, the aim of this study is to examine and identify the factors that influence and affect the utilization of e-Government in the developing countries, specifically in Jordan. Furthermore, this article investigates the challenges and barriers that must be overcome in order to successfully implement e-Government in Jordan. Semistructured interviews were conducted and used in this study to collect the data. The results of this study show that the most significant challenges and factors influencing the implementation of e-Government services in Jordan are related to budgeting and financial costs, human expertise, social influence, technological issues, lack of awareness, resistance of public employees, data privacy and security, the legal framework, the needed technology, administrative obstacles, and trust or believing in e-Government. Conclusions, recommendations and future work are stated at the end of the paper.
In this paper, we deal with some specific domains of applications to game theory. This is one of ... more In this paper, we deal with some specific domains of applications to game theory. This is one of the major class of models in the new approaches of modelling in the economic domain. For that, we use genetic automata which allow to buid adaptive strategies for the players. We explain how the automata-based formalism proposed-matrix representation of automata with multiplicities-allows to define a semi-distance between the strategy behaviors. With that tools, we are able to generate an automatic processus to compute emergent systems of entities whose behaviors are represented by these genetic automata.
The development of distributed computations and complex systems modelling lead to the creation of... more The development of distributed computations and complex systems modelling lead to the creation of innovative algorithms based on interacting virtual entities, specifically for optimisation purpose within complex phenomena. Particule Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) are two of these algorithms. We propose in this paper a method called Community Swarm Optimisation (CSO). This method is based on more sophisticated entities which are defined by behavioral automata. This algorithm leads to the emergence of the solution by the co-evolution of their behavioral and spatial characteristics. This method is suitable for urban management, according to improve the understanding of the individual behaviors over the emergent urban organizations.
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Papers by Rawan Ghnemat