TOWARDS CLOUD COMPUTING: A SWOT ANALYSIS ON ITS ADOPTION IN SMES
Authors : Mohammad Hijjawi, Omar Fuad Alsheiksalem, Hazem Qattous
Abstract : "Over the past few years, emergence of Cloud Computing has notably made an evolution in the IT industry by putting forward an ‘everything as a service’ idea .Cloud Computing is of growing interest to companies throughout the world, but there are many barriers associated with its adoption which should be eliminated. This paper aims to investigate Cloud Computing and discusses the drivers and inhibitors of its adoption. Moreover, an attempt has been made to identify the key stakeholders of Cloud Computing and outline the current security challenges. A SWOT analysis which consists of strengths, weaknesses, opportunities and threats has also carried out in which Cloud Computing adoption for SMEs (Small and Medium-sized Enterprises) is evaluated. Finally, the paper concludes with some further research areas in the field of Cloud Computing. "
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performance Analysis of Supervised Classifying Algorithms to Predict Diabetes
Authors : Mohammad Hijjawi, Ahmed Mousa Altamimi
Abstract : Improving the precision of diabetes in children detection has been extensively considered in the literature. The healthcare expenditures and erroneous diagnosis have motivated this concern. If it is not well-controlled over a prolonged period of time, diabetes complications can include Heart disease, Nerve damage, and Kidney damage, which eventually be life-threatening for children. Various methodologies and methods have been proposed to analyze the disease factors aiming to decrease the physicians' practice variation and reduce medical costs. Data mining techniques, for example, have been commonly used for a variety of domains for predicting or diagnosing diseases with reasonable accuracy. In this regard, expert systems (that use Data mining techniques) are used to emulate the decision-making ability of a human expert for reducing medical errors and improve diagnose results. In this work, a performance analysis of supervised classifying algorithms to predict diabetes in children is carried out. Four supervised data mining classifying algorithms, Naïve Bayes, Decision Tree, Random Forest, and Support Vector Machine, with large datasets, are utilized to assess and analyze the risk factors statistically related to diabetes. As proof of concept, the selected classifiers are implemented using the MATLAB tool to validate our conceptual idea. Results show that Support Vector Machine (SVM) accuracy outperformed other classification algorithms with 76.4%, while the Decision Tree in the lowest with 72.1%. We belive that this research forms a basis for further studies that develops systems for accuretly predicting diabetes in children
Keywords : diabetes, diagnosis, Data mining, classification, supervised algorithms
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APPLYING AN ARABIC CONVERSATIONAL AGENT IN THE JORDANIAN EGovernment
Authors : Mohammad Hijjawi, Hesham Abusaimeh
Abstract : This paper discusses a prototype idea of applyinga Conversational Agent (CA) to be embedded into the Jordanian E-government websites. The Conversational Agent is a smart system used to handle natural conversations between user and machine. A Jordanian citizen facing struggles when he/she want to apply for a service through the E-government portal. In addition the Jordanians struggling when searched for a piece of information (for example the needed documents for a specific service) inside the E-government websites. This struggling comes from number of reasons such as the needed knowledge that the user could have to deal with such services and the big number of links that the user must رابط البحثto achieve his/her target. In addition, the Jordanian E-Government websites does not meet the users’ requirements in their design. Instead, this paper proposes the idea of applying a prototype called CA into those websites as a general helpdesk automated service to save the Jordanians time and effort. Simply, the user will chat with the proposed CA with what he/she coming to do through the targeted website using a text based Arabic conversations. The CA’s responses might be the exact needed link or the targeted information. Such a proposed service will strength the Jordanian E-government platform especially for accessibility and usability factors and as to best of our knowledge, no country has been applied it before.
Keywords : Electronic government, Jordan, usability, accessibility and Conversational Agent.
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An Empirical Evaluation of Gesture Recognition System for Education Purposes
Authors : Mohammad Hijjawi, Omar Alsheiksalem, Hazem Qattous
Abstract : Most education lectures at universities are presented these days using a presentation tool to help lecturer remember the points that should be presented and the audience, to follow the presentation. The traditional methods of controlling such presentations, mouse and keyboard, restrict the movement of the lecturer, as s/he needs to stay close to the keyboard and mouse to run and control the presentation. However, such traditional techniques lack the naturalness of communication and cumbersomeness. This paper presents a solution for these problems using an intuitive gesture recognition system for education purposes called TeachMe for controlling presentation and mouse pointer movement. The system depends on Microsoft Kinect® device in capturing the gestures. An empirical study was conducted to evaluate the system by comparing between the gesture technique implemented into TeachMe, and traditional technique for controlling MS PowerPoint presentation and mouse pointer movement with respect to flexibility, performance and user satisfaction. Controlling presentation results show that there is a significant difference regarding the flexibility to the favor of gesture technique. However, such difference does not exist in case of performance. Some differences exist in the user satisfaction results. Controlling mouse pointer results show that difference exist in performance and user satisfaction the favor of mouse technique over the gesture one.
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How Artificial Intelligence can fight Coronavirus
Authors : Mohammad Hijjawi
Abstract : "The world started the 2020 year with a big pandemic came from china, which is covid-19. This pandemic caused by the coronavirus that is spreading quickly from china to the whole world. This spreading does not affect only the human health. Rather, it affects all the human life activities from business, education, travelling, jobs and even the social activities. This paper illustrates how Artificial Intelligence can fight this virus and help people to live comfortably and safely. The pandemic is not end and it seems will not end soon as it is might needs years. Therefore, the artificial intelligence with all disciplines should enter this war to reduce the pandemic period. AI can play important roles in all sectors, works remotely, educate remotely, find new jobs, open new markets and socially. Artificial Intelligence contributed significantly in this war (Covid-19 spreading) and this appeared in this paper in a novel illustration and structure. The paper uses the systematic approach to utilize showing the effects of Artificial Intelligence of fighting the Coronavirus."
Keywords : artificial intelligence, coronavirus and covid-19
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Comparison of multiple machine learning algorithms for urban air quality forecasting
Authors : Mohammad Hijjawi, Maryam Aljanabi, Mohammad Shkoukani
Abstract : Environmental air pollution has become one of the major threats to human lives nowadays in developed and developing countries. Due to its importance, there exist various air pollution forecasting models, however, machine learning models proved one of the most efficient methods for prediction. In this paper, we assessed the ability of machine learning techniques to forecast NO2, SO2, and PM10 in Amman, Jordan. We compared multiple machine learning methods like artificial neural networks, support vector regression, decision tree regression, and extreme gradient boosting. We also investigated the effect of the pollution station and the meteorological station distance on the prediction result as well as explored the most relevant seasonal variables and the most important minimal set of features required for prediction to improve the prediction time. The experiments showed promising results for predicting air pollution in Amman with artificial neural network outperforming the other algorithms and scoring RMSE of 0.949 ppb, 0.451 ppb, and 5.570 µg/m3 for NO2, SO2, and PM10 respectively. Our results indicated that when the meteorological variables were obtained from the same pollution station the results were better. We were also able to reduce the time by reducing the set of variables required for prediction from 11 down to 3 and achieved major time improvement by about 80% for NO2, 92% for SO2, and 90% for PM10. The most important variables required for predicting NO2 were the previous day values of NO2, humidity and wind direction. While for SO2 they were the previous day values of SO2, temperature, and wind direction values of …
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Unit Selection Model in Arabic Speech Synthesis
Authors : Mohammad Hijjawi, Nedhal Al-Saiyd
Abstract : In text-to-speech synthesis the speech unit is segmented and extracted from natural speech, coded, classified, labelled and stored in the inventory of units. To generate a smooth synthesized speech the unit selection plays an important and crucial role. A multiple-instances approach of speech unit is suggested. A set of speech units is prepared for each speech unit type, taking into consideration target unit structure, the preceding and the succeeding syllables, and position in the utterance. In this paper, a diacritic Arabic Text-To-Speech system is described. The goal of this paper is to get intelligible, high quality speech synthesis based on unit selection using a syllables model.
Keywords : Arabic Speech, Unit Selection, Segmentation, Syllable, Speech Analysis.
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ArabChat: An Arabic Conversational Agent. in proceeding of the 6th International Conference on Computer Science and Information Technology (CSIT). 2014
Authors : Mohammad Hijjawi, Zuhair Bandar, Keeley Crockett, David Mclean
Abstract : The Enhanced ArabChat is a complement of the previous version of ArabChat. This paper details an enhancements development of a novel and practical Conversational Agent for the Arabic language called the “Enhanced ArabChat”. A conversational Agent is a computer program that attempts to simulate conversations between machine and human. Some of lessons was learned by evaluating the previous work of ArabChat . These lessons revealed that two major issues affected the ArabChat’s performance negatively. Firstly, the need for a technique to distinguish between question and non-question utterances to reply with a more suitable response depending on the utterance’s type (question and non-question based utterances). Secondly, the need for a technique to handle an utterance targeting many topics that require firing many rules at the same time. Therefore, in this paper, the “Enhanced ArabChat” will cover these enhancements to improve the ArabChat’s performance. A real experiment has been done in Applied Science University in Jordan as an information point advisor for their native Arabic students to evaluate the Enhanced ArabChat
Keywords : Artificial Intelligence; Conversational Agents and Arabic
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Mobile Arabchat: An Arabic Mobile-Based Conversational Agent
Authors : Mohammad Hijjawi, Omar Fuad Alsheiksalem, Hazem Qattous
Abstract : The conversation automation/simulation between a user and machine evolved during the last years. A number of research-based systems known as conversational agents has been developed to address this challenge. A conversational Agent is a program that attempts to simulate conversations between the human and machine. Few of these programs targeted the mobilebased users to handle the conversations between them and a mobile device through an embodied spoken character. Wireless communication has been rapidly extended with the expansion of mobile services. Therefore, this paper discusses the proposing and developing a framework of a mobile-based conversational agent called Mobile ArabChat to handle the Arabic conversations between the Arab users and mobile device. To best of our knowledge, there are no such applications that address this challenge for Arab mobile-based users. An Android based application was developed in this paper, and it has been tested and evaluated in a large real environment. Evaluation results show that the Mobile ArabChat works properly, and there is a need for such a system for Arab users.
Keywords : Conversational Agent; Mobile; ArabChat; Chatterbot and Arabic
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Online reputation model using multiple quality factors
Authors : Mohammad Hijjawi, Ahmed Mousa Altamimi, Mohammad Azzeh
Abstract : Users on internet are looking for ways to minimize their experiences on performing online transactions. Reputation systems as a decision support tool are trying to facilitate online transactions. However, many reputation systems use Naïve methods to compute the reputation of an item. These methods are unstable when there is sparsity in the ratings. In addition, they do not have the ability to discover trends emerging from recent ratings. Other methods, which use weighted average or probabilistic model, usually focus on one aspect of the reviewer ratings. Even though models that combine multiple factors often accomplish that through arbitrary set of weights. This research study looks at various aspects of reviewers’ ratings, and proposes a new reputation model that attempts to assess the reviewer reputation by combining four factors through a Fuzzy model. These weights are then involved in computing the item reputation. The proposed reputation model has been validated against state-of-art reputation models, and presented significant accuracy in terms of Mean Absolute Errors (MAE) and Kendall correlation. The proposed reputation model also works well with sparse and dense dataset.
Keywords : Online rating system; reputation model; ratings systems; Fuzzy model; aggregation methods
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A novel hybrid rule mechanism for the Arabic conversational agent ArabChat
Authors : Mohammad Hijjawi, Zuhair Bandar, Keeley Crockett, David Mclean
Abstract : This paper depicts an enhancement work upon a previous research work called ArabChat. The ArabChat is an Arabic rule-based conversational agent used the pattern matching approach to handle conversations between the user and human. After evaluating the previous version of ArabChat, it has been revealed that the user might speak with ArabChat with more than one topic inside the same utterance (sentence or conversation). Therefore, this paper continue the work on ArabChat to handle a conversation contains more than one topic by enhancing the ArabChat scripting engine methodology to issue a new version of it which it discussing in this paper
Keywords : conversational agent, chatterbot, Arabic and hybrid rule.
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A Replicated Assessment of the Critical Success Factors for the Adoption of Mobile Government Services: the Case of Jordan
Authors : Mohammad Hijjawi, Yousef Elsheikh
Abstract : Previous research indicates that there is a failure in the adoption of e-government services to citizens as planned in the context of developing countries. Obstacles behind this failure are varied, including sociocultural, economic and technical obstacles. But with recent advances in mobile technologies as well as the pervasive penetration of mobile phones, governments in developing countries including Jordan have been able to overcome most of these obstacles through the so-called mobile government (or m-government). This has provided an alternative channel for governments to improve the interaction with their citizens, as well as the quality of services provided to them. Accordingly, the exploration of the factors that affect the adoption of m-government services would reduce the gap between government strategies and policies relating to the development of m-government services on the one hand, and the perceptions of citizens on the other hand, allowing for a better understanding of citizens' needs and priorities that must be taken into account by the governments in order to ensure the success of such services on a large scale. This research is based on a re-evaluation of the empirical results of a comprehensive study conducted by Susanto and Goodwin (2010), which concludes that there are fifteen factors that are likely to affect citizens in 25 countries around the world to adopt SMS-based e-government services, but in the context of a different country in the Arab world, namely Jordan.
Keywords : Mobile-Government, Electronic-Government, SMS Technology, Developing Countries, Jordan
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An overview of the Internet of things closed source operating systems
Authors : Mohammad Hijjawi, Hossam S. Hassanein, Fadi Almasalha, Mahmoud H. Qutqut, Aya Al-Sakran
Abstract : The Internet of Things (IoT) attract a great deal of research and industry attention recently and are envisaged to support diverse emerging domains including intelligent transportation, smart cities, and health informatics. Operating system support for IoT plays a pivotal role in developing interoperable and scalable applications that are efficient and reliable. IoT is implemented by both high-end and low-end devices that require an operating system to run. Recently, we have witnessed a diversity of OSs emerging into IoT environment to facilitate IoT deployments and developments. In this paper, we present an overview of the common and existing closed source OSs for IoT. This paper is written in a tutorial style where each OS is described in details based on a set of designing and development aspects that we established. These aspects include architecture and kernel, memory management, scheduling, power …
Keywords : Memory management, Protocols, Kernel, Internet of Things, Hardware, Programming, Internet of Things (IoTs), Operating System (OS), closed source, high-end, low-end
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An application of pattern matching stemmer in arabic dialogue system
Authors : Mohammad Hijjawi, Zuhair Bandar, Keeley Crockett, David Mclean
Abstract : This paper proposes the building of a stemmer for the Arabic language. This stemmer is largely based on pattern matching and pattern strength techniques. Stemmers are algorithms to extract root from a word by removing its affixes. Stemming has been applied for large number of applications, such as: indexing, information retrieval systems, and web search engines. This paper will also proposes the application of stemming as a pre-processing stage in a dialogue system (DS). The proposed stemmer was compared with three other well known stemmers and achieved favourable accuracy.
Keywords : Arabic, Stemming, Morphological analyser, Pattern Matching, Dialogue system
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A proposed performance evaluation of NoSQL databases in the field of IoT
Authors : Mohammad Hijjawi, Hazem Qattous, Aya Al-Sakran
Abstract : As one of the largest-technology penetrations, Internet of Things (IoT) has gained a considerable attention across both, research communities and industrial domains. IoT is a network of billions of connected devices that are capable of communicating over the Internet. In IoT, data is generated exponentially by different real-time applications (e.g., social network sites and sensor-based devices). The traditional relational database management technologies are inappropriate to deal with such new generation of data due to its limited processing speed, scalability issues, and limited storage capacity. The advent of Big Data requires new advanced technologies that are capable of handling (storing, retrieving and processing) large amount of unstructured data that IoT applications produce. Not Only SQL (NoSQL) databases emerged as a solution to overcome some limitations of the traditional relational database. Recently …
Keywords : Internet of Things (IoT), NoSQL, MongoDB, Big Data, Chord protocol, RDBMS, BASE
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The Enhanced Arabchat: An Arabic Conversational Agent
Authors : Mohammad Hijjawi, Zuhair Bandar, Keeley Crockett, David Mclean
Abstract : The Enhanced ArabChat is a complement of the previous version of ArabChat. This paper details an enhancements development of a novel and practical Conversational Agent for the Arabic language called the “Enhanced ArabChat”. A conversational Agent is a computer program that attempts to simulate conversations between machine and human. Some of lessons was learned by evaluating the previous work of ArabChat . These lessons revealed that two major issues affected the ArabChat’s performance negatively. Firstly, the need for a technique to distinguish between question and non-question utterances to reply with a more suitable response depending on the utterance’s type (question and non-question based utterances). Secondly, the need for a technique to handle an utterance targeting many topics that require firing many rules at the same time. Therefore, in this paper, the “Enhanced ArabChat” will cover these enhancements to improve the ArabChat’s performance. A real experiment has been done in Applied Science University in Jordan as an information point advisor for their native Arabic students to evaluate the Enhanced ArabChat.
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ArabChat: an Arabic conversational agent
Authors : Hijjawi, Moh'd Hatim Husni
Abstract : This thesis details the development of a novel and practical Conversational Agent for the Arabic language called ArabChat. A conversational Agent is a computer program that attempts to simulate conversations between machine and human. In this thesis, the term 'conversation' or 'utterance' refers to real-time chat exchange between machine and human. The proposed framework for developing the Arabic Conversational Agent (ArabChat) is based on Pattern Matching approach to handle users' conversations. The Pattern Matching approach is based on the matching process between a user's utterance and pre-scripted patterns that represents different topics organised through novel scripting structure. ArabChat classifies users' utterances as either question or nonquestion utterances in order to response to an utterance depending on its type (question or non-question). In addition, ArabChat has the ability to reply to an utterance targets many topics at the same time. Moreover, this thesis proposes to use the stemming technique (a process to return a word to its original root) as a pre-processing stage in ArabChat in order to convert the processed utterance's words to stemmed words and then match them with stemmed pre-scripted patterns. This proposal might decrease the number of needed patterns to script a domain to the minimum as discussed in this thesis. Furthermore, two new Arabic stemmers have been proposed, developed and discussed in this thesis In order to assess ArabChat, different techniques have been developed and used to validate its performance. Three experiments with online users have been carried out. The results have …
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A general evaluation framework for text based conversational agent
Authors : Mohammad Hijjawi, Zuhair Bandar, Keeley Crockett
Abstract : This paper details the development of a new evaluation framework for a text based Conversational Agent (CA). A CA is an intelligent system that handle spoken or/and text based conversations between machine and human. Generally, the lack of evaluation frameworks for CAs effects its development. The idea behind any system’s evaluation is to make sure about the system’s functionalities and to continue development on it. A specific CA has been chosen to test the proposed framework on it; namely ArabChat. The ArabChat is a rule based CA and uses pattern matching technique to handle user’s Arabic text based conversations. The proposed and developed evaluation framework in this paper is natural language independent. The proposed framework is based on the exchange of specific information between ArabChat and user called “Information Requirements”. This information are tagged for each rule in the applied domain and should be exist in a user’s utterance (conversation). A real experiment has been done in Applied Science University in Jordan as an information point advisor for their native Arabic students to evaluate the ArabChat and then evaluating the proposed evaluation framework.
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An Arabic Stemming approach using machine learning with Arabic dialogue system
Authors : Mohammad Hijjawi, Zuhair Bandar, Keeley Crockett, David Mclean
Abstract : Stemming plays a vital role in text-based searching systems in general and particularly in information retrieval systems. The current Arabic stemming approaches especially those which deal with linguistics still face a number of challenges and they have not been highly accurate yet. This is mostly due to rich derivational and inflectional features in the Arabic language. This paper proposes a novel machine learning based methodology in order to overcome the stemming problem in the Arabic language. Results have shown that this novel methodology achieved a very high level of accuracy. Also, such a stemming approach has been proposed in this paper to be usable in Arabic dialogue systems as a preprocessing stage.
Keywords : Arabic, Stemming, Machine Learning, Decision Tree, Pattern Matching, and Dialogue system
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Intelligent automatic cutting-tool selections for turning operations
Authors : Joze Balic, Franc Cus, B Vaupotic, M Hijjawi, Z Bandar, K Crockett, D Mclean
Abstract : This paper introduces an intelligent system for selecting the best set of tools on the basis of a 3D CAD model and other relevant selection factors. An artificial intelligence method (neural networks) has been used for solving this complex classification problem. On the basis of the knowledge acquired during this process of learning, the system responds to new unknown examples in the manner nearest to the experience acquired during learning. This concept was used for the most widespread cutting process ie turning and the results reached are in conformity with expectations. The resulting solutions are comparable with the solutions given by experts. The system can be adapted for demand of practically users.
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Arabic language challenges in text based conversational agents compared to the English language
Authors : Mohammad Hijjawi, Yousef Elsheikh
Abstract : This paper is not to compare between the Arabic language and the English language as natural languages. Instead, it focuses on the comparison among them in terms of their challenges in building text based Conversational Agents (CAs). A CA is an intelligent computer program that used to handle conversations among the user and the machine. Nowadays, CAs can play an important role in many aspects as this work figured. In this paper, different approaches that can be used to build a CA will be differentiated. In each approach, the comparison aspects among the Arabic and English languages will be debated with the respect to the Arabic language.
Keywords : Conversational Agents, Chatterbots, Arabic Language and English Language.
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Ground-level Ozone Prediction Using Machine Learning Techniques: A Case Study in Amman, Jordan
Authors : Mohammad Hijjawi, Maryam Aljanabi, Mohammad Shkoukani
Abstract : Air pollution is one of the most serious hazards to humans' health nowadays, it is an invisible killer that takes many human lives every year. There are many pollutants existing in the atmosphere today, ozone being one of the most threatening pollutants. It can cause serious health damage such as wheezing, asthma, inflammation, and early mortality rates. Although air pollution could be forecasted using chemical and physical models, machine learning techniques showed promising results in this area, especially artificial neural networks. Despite its importance, there has not been any research on predicting ground-level ozone in Jordan. In this paper, we build a model for predicting ozone concentration for the next day in Amman, Jordan using a mixture of meteorological and seasonal variables of the previous day. We compare a multi-layer perceptron neural network (MLP), support vector regression (SVR), decision tree regression (DTR), and extreme gradient boosting (XGBoost) algorithms. We also explore the effect of applying various smoothing filters on the time-series data such as moving average, Holt-Winters smoothing and Savitzky-Golay filters. We find that MLP outperformed the other algorithms and that using Savitzky-Golay improved the results by 50% for coefficient of determination (R2) and 80% for root mean square error (RMSE) and mean absolute error (MAE). Another point we focus on is the variables required to predict ozone concentration. In order to reduce the time required for prediction, we perform feature selection which greatly reduces the time by 91% as well as shrinking the number of features required for prediction to the previous day values of ozone, humidity, and temperature. The final model scored 98.653% for R2, 1.016 ppb for RMSE and 0.800 ppb for MAE
Keywords : Ozone prediction, machine learning, neural networks, supervised learning, regression
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User's utterance classification using machine learning for Arabic Conversational Agents
Authors : Mohammad Hijjawi, Zuhair Bandar, Keeley Crockett
Abstract : This paper presents a novel technique for the classification of Arabic sentences as Dialogue Acts, based on structural information contained in Arabic function words. It focuses on classifying questions and non-questions utterances as they are used in Conversational Agents. The proposed technique extracts function words features by replacing them with numeric tokens and replacing each content word with a standard numeric token. The Decision Tree has been chosen for this work to extract the classification rules. Experiments provide evidence for highly effective classification. The extracted classification rules will be embedded into a Conversational Agent called ArabChat in order to classify Arabic utterances before further processing on these utterances. This paper presents a complement work for the ArabChat to improve its performance by differentiating among question-based and non question-based utterances.
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ArabChat: An arabic conversational agent
Authors : Mohammad Hijjawi, Zuhair Bandar, Keeley Crockett, David Mclean
Abstract : This paper details the development of a novel and practical Conversational Agent for the Arabic language called ArabChat. A conversational Agent is a computer program that attempts to simulate conversations between machine and human. In this paper, the term `conversation' or `utterance' refers to real-time chat exchange between machine and human. The proposed framework for developing the Arabic Conversational Agent (ArabChat) is based on Pattern Matching approach to handle users' conversations. The Pattern Matching approach is based on the matching process between a user's utterance and pre-scripted patterns that represents different topics organized through novel scripting structure. A real experiment has been done in Applied Science University in Jordan as an information point advisor for their native Arabic students to evaluate the ArabChat.
Keywords : Conversational agent, chatterbot, Arabic and scripting
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Machine learning classification techniques for heart disease prediction: A review
Authors : Mohammad Hijjawi, Maryam Aljanabi, Mahmoud H. Qutqut
Abstract : The most crucial task in the healthcare field is disease diagnosis. If a disease is diagnosed early, many lives can be saved. Machine learning classification techniques can significantly benefit the medical field by providing an accurate and quick diagnosis of diseases. Hence, save time for both doctors and patients. As heart disease is the number one killer in the world today, it becomes one of the most difficult diseases to diagnose. In this paper, we provide a survey of the machine learning classification techniques that have been proposed to help healthcare professionals in diagnosing heart disease. We start by overviewing the machine learning and describing brief definitions of the most commonly used classification techniques to diagnose heart disease. Then, we review representable research works on using machine learning classification techniques in this field. Also, a detailed tabular comparison of the surveyed papers is presented.
Keywords : heart disease; heart disease diagnosis; heart disease prediction; machine learning; machine learning classification techniques
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Mobile Television: Understanding The Technology And Opportunities
Authors : Mohammad Hijjawi, Omar Fuad Alsheiksalem, Hazem Qattous
Abstract : Television have converged the technologies of movies and radio and now being converged with mobile phones. Mobile TV is the result of the convergence between mobile devices and television. Mobile TV is akey device and service that enrich civilization with applications, vast market and great investment. MobileTV is an important subject that has a potential impact on leading edge technologies for promising future. Inthe time being Mobile TV is still in its early stages and has many potential; therefore some applicationssuch as mobile advertising and learning are discussed in this paper. When it comes to advertising, MobileTV presents a new opportunity different from the traditional TV advertisements producing an interactivetype of advertisements, enabling user engagement. While in the case of mobile learning, mobile devicesopen up new chances for absorbing knowledge and most recent information without forgetting the practicalexperience aspect
Keywords : Convergence, Mobile TV, Customization, Interaction, Mobile Content.
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A Replicated Assessment of the Critical Success Factors for the Adoption of Mobile Government Services : The Case of Jordan
Authors : Mohammad Hijjawi, Yousef Elsheikh
Abstract : Previous research indicates that there is a failure in the adoption of e-government services to citizens as planned in the context of developing countries. Obstacles behind this failure are varied, including socio-cultural, economic and technical obstacles. But with recent advances in mobile technologies as well as the pervasive penetration of mobile phones, governments in developing countries including Jordan have been able to overcome most of these obstacles through the so-called mobile government (or m-government). This has provided an alternative channel for governments to improve the interaction with their citizens, as well as the quality of services provided to them. Accordingly, the exploration of the factors that affect the adoption of m-government services would reduce the gap between government strategies and policies relating to the development of m-government services on the one hand, and the perceptions of citizens on the other hand, allowing for a better understanding of citizens' needs and priorities that must be taken into account by the governments in order to ensure the success of such services on a large scale. This research is based on a re-evaluation of the empirical results of a comprehensive study conducted by Susanto and Goodwin (2010), which concludes that there are fifteen factors that are likely to affect citizens in 25 countries around the world to adopt SMS-based e-government services, but in the context of a different country in the Arab world, namely Jordan.
Keywords : Mobile-Government, Electronic-Government, SMS Technology, Developing Countries, Jordan
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