A Usability Evaluation Framework for

Currently, more than two billions people access the Web for various purposes. The majority are people without programming or modelling background. Part of these people (called end-users) also likes to create their own Web applications to meet their daily needs. Mashup Makers are tools to create such end-user’s Web applications. As such, Mashup Makers could become the dominant environment for end-user development of Web applications. Existing Mashup Makers promise that creating a Web Mashup is very easy and just a matter of a few mouse clicks. However, there is no evidence that this is indeed the case. On the contrary, research has already revealed usability problems with Mashup Makers. Therefore, this thesis concentrates on the usability of Mashup Makers as development environments for Web applications for end-users. Usability is a key issue for the success of software artifacts, and especially if the artifacts are intended for non-technical users. Therefore, we target the achievement of a consolidated approach, model, and framework for the evaluation of the usability of Mashup Makers for end-users. Such a framework will not only allow evaluating the usability of existing Mashup Makers, but it will also provide key issues concerning usability (ie usability impact factors) that developers of Mashup Makers and of other future end-user development tools can take into consideration when developing new tools

Applying Agile Software Engineering On Medical Ubiquitous Computing (MUC)

Nowadays, people are involved in using computation capabilities to meet their daily life needs although most of the time they may be unaware as to how this actually happens. Ubiquities Computing is considered the future trend for providing unlimited computing capabilities that handle every service in human life. One of the most crucial implementation of Ubiquities Computing is in Medical and Hospital Service. This is due to their great importance in saving people's lives. The huge amount of data and information delivered by MUC systems draw the attention to the necessity of having a new and modern software engineering methodology; Agile Software engineering methodology is highly considered in the matter. In this paper, we present an implementation of applying agile SWE methodology on MUC System, research related issues are also discussed

A Case Study on Academic Services Application Using Agile Methodology for Mobile Cloud Computing

Recently, Mobile Cloud Computing reveals many modern development areas in the Information Technology industry. Several software engineering frameworks and methodologies have been developed to provide solutions for deploying cloud computing resources on mobile application development. Agile methodology is one of the most commonly used methodologies in the field. This paper presents the MCCAS a Web and Mobile application that provide feature for the Palestinian higher education/academic institutions. An Agile methodology was used in the development of the MCCAS but in parallel with emphasis on Cloud computing resources deployment. Also many related issues is discussed such as how software engineering modern methodologies (advances) influenced the development process

Toward usability evaluation criteria for web mashup makers for end-users

Currently, more than two billions people access the web for various purposes. The majority are people without programming or modeling backgrounds. Part of these people also likes to create their own Web applications to meet their daily needs. Mashup Makers are tools to create such enduser’s Web applications. As such, Mashup Makers could become the dominant environment for end-user development of Web applications. Several Mashup creation tools, socalled Mashup makers, exist and many of them are advertised as easy to use tools for end-users. These tools target Web users without programming background and promise that creating a Web Mashup is just a matter of a few mouse clicks. However, no profound usability evaluations have been performed to justify those claims. In this paper, we report on an initial usability study on Web Mashup makers for end-users. For this study, we have selected a representative set of Web Mashup makers for end-users, and defined a number of evaluation criteria based on the cognitive dimensions of notations framework. The results of this study are presented in this paper. We also reflect on the methodology used

Towards Rules Induction Optimization for Cerebral Palsy Diagnosis: An Empirical Study

According to the World Health Organization, there are about 15% of universe population have some forms of disability. One of these disabilities is Cerebral Palsy CP which is a permanent motor disorder that appears in early age causing mental and physical disabilities. Based on WHO, between 1.5 to 2.8 cases per 1000 birth have CP Disability in the world. In Gaza Strip, 2.6% of population has some forms of disability. The children under 18 years with CP disability represent 3.1% of disability population in Gaza Strip. Based on domain experts' opinion, there are very little studies that target disability in Gaza Strip especially Cerebral Palsy. In this paper we propose a new approach for rules induction and optimization for Cerebral Palsy diagnosis based on symptoms that appear on the children aged from 1 day to 3 years. We used knowledge-based survey technique to extract tacit knowledge related to disability

Improving Premium Domain Names Registration for .PS Domain Cctld Basing on Knowledge Discovery and Data Mining Techniques

Country code top-level domain represents the identity of its own country. About ten million Palestinians spread in the world belong or affiliate to the domain name (.PS), for which it represents their identity although they do not have their own state. In addition, the (.PS) represents Palestinians history, culture, and lifestyle as well as to the Palestine homeland issue on the cyber and internet space. Domain names are valuable in today's e-commerce and are considered one of the potential intellectual capital assets worldwide. However, Premium Domain Names (PDN) is generic single keywords that are high value, memorable and easily marketable; its cost can be significantly more than a typical domain purchase due to its perceived higher value. In this paper, the research is based on Knowledge Discovery and Data Mining Techniques to discover the most attention regions in the world that register .PS domains in order to manage acquisition knowledge, which will benefit in providing marketing plans, identify stakeholders and target customers. Two phases were performed to achieve the required work plan: Data Mining (the knowledge discovery) phase and Knowledge Management (sharing and planning). The techniques in both phases were chosen to give the best accuracy and particularity of the involved target audience in the study. The results show that what we suggested could be efficiently used to recognize patterns in such data set behavior to generate new marketing strategies and plans

TOWARDS CEREBRAL PALSY DIAGNOSIS: AN-ONTOLOGY BASED APPROACH

Cerebral Palsy (CP) is one of the most complicated disabilities which is a permanent motor disorder causing mental and physical disabilities. Different reports published by different health organizations asked for researches on CP disability in order to improve diagnosis. Globally, there are different researches conducted to improve CP diagnosis, but most of those studies do not diagnose CP in children’s early ages, which limit the treatment impact. This paper report on a research conducted to develop an ontology-based approach to diagnose children with CP in early ages. In this paper, Ontology was used to represent CP domain. Then, a set of manually built rules have been optimized through a knowledge-based survey to be used in CP diagnosis. The proposed approach improves CP diagnosis and by consequence positively reflects physical therapy treatment. The proposed approach was evaluated by a real dataset consisted of 70 pre-diagnosed cases, where 84% correctly diagnosed

Web mashup makers for casual users: a user experiment

Web mashups are become increasingly popular. A mashup is a Web application that combines data from more than one source into a single integrated form. Several mashup creation tools, so-called mashup makers, exist and many of them are advertised as easy to use tools for casual users. These tools target Web users without programming background and promise that creating a Web mashup is just a matter of a few mouse clicks. However, no profound usability evaluations have been performed to justify those claims. In this paper, we report on a usability study and user experiment on Web mashup makers for casual users. For this study, we have selected a representative set of mashup makers for casual users, and defined a number of evaluation criteria based on the cognitive dimensions of notations framework and the ISO 9241 part 11 Usability definition. Next, a user experiment was performed. The results of

The impact of factors of success on the in-house software development for preserving tacit knowledge: survey

Factors of success are aimed to provide knowledge-intensive organisations to better manage their knowledge value. There are multiple ways to capture organization‟ s knowledge and make it available to all their members while it is not easy to capture/share the tacit knowledge among the stakeholders. The purpose of this study was to investigate the impact of factors of success on the in-house software development for preserving tacit knowledge. We conducted a survey to study the impact of these five factors on the tacit knowledge sharing between the developers within the in-house software development environment. This paper is firstly exploring the definition of the knowledge and introducing the types of knowledge those are explicit and tacit knowledge. We discuss the in-house software development concept in which the non-IT organizations may need to develop their own software internally with no need to have a third party software development organization. For tacit knowledge sharing, we considered four factors reviewed in other researches and we added to them the pair programming as a practice. Case study is local bank in Palestine. Based on the results we have, it is confirmed the hypothesis of a positive impact of factors of success on the process of knowledge sharing

التنبؤ بسرطان الدم وتشخيصه باستخدام خوارزميات التصنيف

Algorithms used in data mining techniques are of great importance in the field of health care, especially in the case of getting patterns or models that are undiscovered in databases. In the area of health care, leukemia affects the blood status and can be discovered by using the Blood Cell Counter (CBC). This study aims to predict the leukemia existence by determining the relationships of blood properties and leukemia with gender, age, and health status of patients using data mining techniques. More than 4,000 patients were taken from a blood test laboratory from European Gaza Hospital at Gaza Strip. Three classification algorithms are identified for blood Cancer classification; k-nearest neighbor (k-NN), decision tree (DT) and Support Vector Machine (SVM). These three classifiers were implemented and studied thoroughly in terms of classification accuracy and F-Measure. From our experimental results, it was noticed that the decision-tree algorithm had the highest percentage of 77.30% compared with the other two techniques. In addition, the DT classifier obtains properties regarding outer attributes such as city (eastern regions) that are most vulnerable to leukemia.Algorithms used in data mining techniques are of great importance in the field of health care, especially in the case of getting patterns or models that are undiscovered in databases. In the area of health care, leukemia affects the blood status and can be discovered by using the Blood Cell Counter (CBC). This study aims to predict the leukemia existence by determining the relationships of blood properties and leukemia with gender, age, and health status of patients using data mining techniques. More than 4,000 patients were taken from a blood test laboratory from European Gaza Hospital at Gaza Strip. Three classification algorithms are identified for blood Cancer classification; k-nearest neighbor (k-NN), decision tree (DT) and Support Vector Machine (SVM). These three classifiers were implemented and studied thoroughly in terms of classification accuracy and F-Measure. From our experimental results, it was noticed that the decision-tree algorithm had the highest percentage of 77.30% compared with the other two techniques. In addition, the DT classifier obtains properties regarding outer attributes such as city (eastern regions) that are most vulnerable to leukemia