Ammar M Huneiti

University of Jordan | UJ · Department of Computer Information Systems

Convolutional Neural Network is a deep learning method that is used in many image-related applications, such as image recognition and classification, it has achieved great performance in these fields, but it still suffers from some shortcomings. One of these shortcomings is not being able to be invariant to the input data due to some image transfor...

Peer-to-Peer (P2P) energy trading has gained much attention recently due to the advanced development of distributed energy resources. P2P enables prosumers to trade their surplus electricity and allows consumers to purchase affordable and locally produced renewable energy. Therefore, it is significant to develop solutions that are able to forecast...

Twitter is one of the most popular microblogging and social networking platforms where massive instant messages (i.e. tweets) are posted every day. Twitter sentiment analysis tackles the problem of analyzing users’ tweets in terms of thoughts, interests and opinions in a variety of contexts and domains. Such analysis can be valuable for several res...

—Convolutional Neural Networks (CNN) is a powerful deep learning method which is mostly used in image classification and image recognition applications. It has achieved acceptable accuracy in these fields but it still suffers some limitations. One of these limitations of CNN is the lack of ability to be invariant to the input data due to some trans...

The increasing availability of cutting-edge location-acquisition technologies such as GPS devices, has led to the generation of huge datasets of spatial trajectories. These trajectories store important information regarding the movement of people, vehicles, robots, animals, users of social networks, etc. Many research initiatives have applied data...

Aims: This open label prospective Phase I/IIa clinical study used autologous Bone Marrow derived Mesenchymal Stromal Cells (BM-MSCs) followed by Mesenchymal Stromal Cells Conditioned Media (MSC-CM) for the first time to treat MS patients. The primary goal was to assess the safety and feasibility and the secondary was efficacy. The correlation betwe...

The tree-hypercube (TH) interconnection network is relatively a new interconnection network, which is constructed from tree and hypercube topologies. TH is developed to support parallel algorithms for solving computation and communication intensive problems. In this paper, we propose a new parallel multiplication algorithm on TH network to present...

The cheapest form of communication in the world today is email, and its simplicity makes it vulnerable to many threats. One of the most important threats to email is spam, unsolicited email, normally with an advertising content sent out as a mass mailing. Malicious spam is spam with malicious content in forms of harmful attachments or links to phis...

Content-Based Image Retrieval (CBIR) from a large database is becoming a necessity for many applications such as medical imaging, Geographic Information Systems (GIS), space search and many others. However, the process of retrieving relevant images is usually preceded by extracting some discriminating features that can best describe the database im...

The watermarking is a digital process that preserves copyright and ownership of digital media such as audio, video, and images. This process depends on hiding a digital signature in a carrier signal where this signature has to be related to the original signal. In this paper we develop a simple watermarking method operating in the frequency domain...

Abstract – The rapid and huge growth of the web has emphasized the need to monitor the behavior of web users and to identify their interest, knowledge, preferences, goals, etc. This paper introduces a methodology for classifying users and pages of an educational online hypermedia using a hybrid clustering technique based on Self Organizing Map (SOM...

Efficient patient care delivery by physicians and clinicians is a necessity for healthcare organizations. Physicians need timely access to patient data and information stored in the hospital and clinical information systems. The integration of information systems must be seamless to the user. Physicians may need to use multiple systems and workstat...

Data mining deals with clustering and classifying large amounts of data, in order to discover new knowledge from the existent data by identifying correlations and relationships between various data-sets. Cellular automata have been used before for classification purposes. This paper presents a cellular automata enhanced classification algorithm for...

Universities all over the world have many buildings and facilities distributed inside and outside of their campus location, and they are used by students for different reasons such as academic, entertainment, services, etc. These may include faculty buildings, cafés, libraries, restaurants and others. For newly registered students and even current...

The rapid and huge growth of the web has emphasized the need to monitor the behavior of web users and to identify their interest, knowledge, preferences, goals, etc. This paper introduces a methodology for classifying users and pages of an educational online hypermedia using a hybrid clustering technique based on Self Organizing Map (SOM) neural ne...

This paper introduces a set of data models for facilitating the retrieval of task-specific and user-adaptive hypermedia documents concerning product fault diagnosis. These models include an integrated fault data model, a stereotype user model, and a semantic product data model. Moreover, the paper outlines the benefits of employing adaptive hyperme...

One of the most popular clustering techniques is the k-means clustering algorithm.However, the utilization of the k-means is severely limited by its high computational complexity. Inthis study, we propose a new strategy to accelerate the k-means clustering algorithm through the PartialDistance (PD) logic. The proposed strategy avoids many unnecessa...

This paper introduces a strategy, a user model, and a methodology for utilising adaptive hypermedia in performance support domain and specifically for fault diagnosis. This utilisation is implemented by employing task-specific and user-centred hypermedia which allows supporting content to be synchronized with the diagnostic expert system inference...

The problem of partitioning a large number of entities into a fixed number of groups on the basis of a set of attributes associated with each entity has required an intensive research work in the literature. We have investigated a previous research related to this problem and proposed a method that is based on fuzzy clustering techniques. Jordan Un...

Compared to other product lifecycle phases, the development of product documentation and technical manuals in particular, is an area currently undersupported by tools. This is in contrast with the benefits associated with the production of high quality product documentation, and the effort involved to produce it. This paper addresses this problem b...

This paper highlights the need for advanced performance support methods to deal with the increasing complexity of modern products and systems. The paper introduces a conceptual model for advanced PSSs outlining a review of the state of practice in recently developed PSSs. In these systems, Job-related tasks of the abstract type "know-how" are proce...

This paper shows how product lifecycle information can be utilized to assist people engaged in product lifecycle tasks, in particular those concerned with product support. A progression of product data management methods based on knowledge engineering techniques is presented to allow the creation and delivery of effective, personalized performance...

Organisations need a structured approach for managing the design of their electronic product support systems (PSSs) since, although technology can assist users with faster information retrieval, if the information is incorrect, the technology could actually increase the error rate. We present an approach for the semantic design and analysis of PSSs...

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