Rise of Augmented Reality: Current and Future Application Areas

The massive technological advancements around the world have created significant challenging competition among companies where each of the companies tries to attract the customers using different techniques. One of the recent tech- niques is Augmented Reality (AR). The AR is a new technology which is capable of presenting possibilities that are difficult for other technologies to offer and meet. Nowadays, numerous augmented reality applications have been used in the industry of different kinds and disseminated all over the world. AR will really alter the way individuals view the world. The AR is yet in its initial phases of research and development at different colleges and high-tech institutes. Throughout the last years, AR apps became transportable and generally available on various devices. Besides, AR be- gins to occupy its place in our audio-visual media and to be used in various fields in our life in tangible and exciting ways such as news, sports and is used in many domains in our life such as electronic commerce, promotion, design, and business. In addition, AR is used to facilitate the learning whereas it enables students to access location-specific infor- mation provided through various sources. Such growth and spread of AR applications pushes organizations to compete one another, every one of them exerts its best to gain the customers. This paper provides a comprehensive study of AR including its history, architecture, applications, current challenges and future trends.

The Internet-EDI Systems Adoption by Enterprises in Jordan: Descriptive analysis of Adoption, Strategies and Benefits

This paper reviewed and explored the current extent of the Internet Electronic Data Interchange systems adoption in Jordan particularly in the SME sector. Also the paper presented the benefits of IEDI adoption and showed the main obstacles facing the SME in Jordan to adopt. This paper used the descriptive and theoretical analysis approaches for collecting and analysis the historical and archived data. The literature showed that Jordan, as a developing country, has achieved forward steps in introducing the Internet to the different sectors of life. The adoption of the electronic tools in business became a governmental target in recent years to make it possible for SMEs to be able to continue to achieve success in their business [1]. Most of Jordanian SMEs have little or no competitive pressure to use I-EDI systems, since most suppliers, customers and other competitors do not seem to promote I-EDI systems. The study concluded that SMEs in Jordan could grow and become larger companies, and supporting national economy. Thus it is very important to develop and grow Jordanian SMEs by doing more research.

Bayesian Classifier Based on Robust Kernel Density Estimation and Harris Hawks Optimisation

In real-world applications, datasets frequently contain outliers, which can hinder the generalization ability of machine learning models. Bayesian classifiers, a popular supervised learning method, rely on accurate probability density estimation for classifying continuous datasets. However, achieving precise density estimation with datasets containing outliers poses a significant challenge. This paper introduces a Bayesian classifier that utilizes optimized robust kernel density estimation to address this issue. Our proposed method enhances the accuracy of probability density distribution estimation by mitigating the impact of outliers on the training sample’s estimated distribution. Unlike the conventional kernel density estimator, our robust estimator can be seen as a weighted kernel mapping summary for each sample. This kernel mapping performs the inner product in the Hilbert space, allowing the kernel density estimation to be considered the average of the samples’ mapping in the Hilbert space using a reproducing kernel. M-estimation techniques are used to obtain accurate mean values and solve the weights. Meanwhile, complete cross-validation is used as the objective function to search for the optimal bandwidth, which impacts the estimator. The Harris Hawks Optimisation optimizes the objective function to improve the estimation accuracy. The experimental results show that it outperforms other optimization algorithms regarding convergence speed and objective function value during the bandwidth search. The optimal robust kernel density estimator achieves better fitness performance than the traditional kernel density estimator when the training data contains outliers. The Naïve Bayesian with optimal robust kernel density estimation improves the generalization in the classification with outliers.

A Study on the Development of Touchless Mouse by Object Tracking through Webcam

In this paper, we study the continuous growth of computer technology and the increasing importance of human-computer interaction. Interactive touch-less is now an undergoing developing technology in real life. Touchless technology introduces a new way of interacting with computers by object tracking method. Nowadays most mobile devices are using touchscreen technology. However, this technology is still not cheap enough to be used in desktop systems. Designing a touchless device such as a mouse or keyboard using a webcam and computer vision techniques can be an alternative way of touch screen technology. Recent trends in technology aim to build highly interactive and easy-to-use applications as a replacement for conventional devices. Such a device is touchless mouse. Its development is completed on the MATLAB platform. The overall objective is to apply image processing techniques from video to track the movement of color which is captured by a webcam and that is converted into mouse movements and operations to control the system. The sub-system which is implemented here would allow a person to control his/her mouse without any input other than the marker movements. We use three fingers (with color) as three color markers (red, green, blue) for completing the activities of a mouse. My first goal was to successfully track the marker color and the second goal was to track the marker position from the acquired image frame for performing the mouse operations. The webcam is used to capture the information on the marker and trigger the associated actions. I use java.awt. Robot file for performing the mouse operations using the acquired data from the image frame.

An Overview of Information and Communication Technology (ICT) in Jordan: Review the Literature of Usage, Benefits and Barriers

This paper presented a background of the extent of the ICT, IT, and EC-B2B in Jordan. It was mentioned that the development of the ICT in Jordan brings benefits to the enterprises and their TPs. In this paper the EC-B2B systems’ readiness in Jordan is defined as the degree of preparation of a nation or community to participate in and benefits from ICT development. The government in Jordan has taken forceful measures towards adoption IT and IS applications and Internet awareness. In 2010, it was reported from the DOS in Jordanthat the percentage of individual Internet usage did not exceed 4.7 percent of the population inJordan[1]. This paper highlighted through subsections on the benefits and risks faced EC-B2B system adoption in Jordan. Based on the recent studies and reports in Jordan, the EC-B2B system adoption was mainly adopted by large enterprises in the supply chain rather than by SMEs. The study concluded that the main two barriers of ICT development and adoption inJordanare organizational readiness including lack of new education methods, and lack of information and knowledge.

How Interlinks Influence Federated over SPARQL Endpoints

As the Web of Data grows, the number of available SPARQL endpoints increases. SPARQL endpoints conceptually represent RPC-style, coarse-grained data access mechanisms. Nevertheless, through the potential interlinking of the contained entities, SPARQL endpoints should be able to over distinct advantages over plain Web APIs. To our knowledge, to date, there has been no study conducted that gauges the impact of the link on SPARQL query execution, especially in a federated set-up. In this paper, we investigate how the existence and types of typed links influences the execution characteristics of different SPARQL federation frameworks. In order to measure the query performance, we propose a combined cost model based on a statistic analysis of the query performance metrics that involves parameters such as type of link, the data catalogues and cache, number of links, and number of distinct subjects. As result, we show that number of distinct subject and number of links have significant impact on Federation over SPARQL Endpoints performance whereas type of link does not have significantly influence in federation query performance.

Editorial: When the Cloud Computing Becomes Mobile!

Editorial: When the Cloud Computing Becomes Mobile!

Assessing the Usability of Institutions Web Pages

The usability of the web pages is assessed using some statistical models. Researchers argue that many usability results and recommendations lack empirical and experimental data. Universities web pages are chosen as subjects for this work. Series of experiments have been conducted to investigate into the usability and design of the universities web pages. Prototype web pages have been developed according to the structured methodologies of web pages design and development. Four universities web pages were evaluated together with the prototype web pages using a questionnaire which was designed according to the Human Computer Interactions (HCI) concepts. The data collected was analyzed using correlation and regression models. The correlation analysis showed that there were significant positive and negative correlations between many items. The regression analysis revealed that the most significant factors (items) that contributed to the best model of the universities web pages design and usability were: multimedia in the web pages, the web pages icons (alone) organization and design, and graphics attractiveness. The results showed some of the limitations of some heuristics used in conventional interface system design and proposed some additional heuristics in web pages design and usability.

G-Phenomena as a Base of Scalable Distributed Computing—G-Phenomena in Moore’s Law

Today we witness the exponential growth of scientific research. This fast growth is possible thanks to the rapid development of computing systems since its first days in 1947 and the invention of transistor till the present days with high performance and scalable distributed computing systems. This fast growth of computing systems was first observed by Gordon E. Moore in 1965 and postulated as Moore’s Law. For the development of the scalable distributed computing systems, the year 2000 was a very special year. The first GHz speed processor, GB size memory and GB/s data transmission through network were achieved. Interestingly, in the same year the usable Grid computing systems emerged, which gave a strong impulse to a rapid development of distributed computing systems. This paper recognizes these facts that occurred in the year 2000, as the G-phenomena, a millennium cornerstone for the rapid development of scalable distributed systems evolved around the Grid and Cloud computing paradigms.

Reliable Content Distribution in P2P Networks Based on Peer Groups

Peer-to-Peer (P2P) networks are highly dynamic systems which are very popular for content distribution in the Internet. A single peer remains in the system for an unpredictable amount of time, and the rate in which peers enter and leave the system, i.e. the churn, is often high. A user that is obtaining content from a selected peer is frequently informed that particular peer is not available anymore, and is asked to select another peer, or will have another peer assigned, often without enough checks to confirm that the content provided by the new peer presents the same quality of the previous peer. In this work we present a strategy based on group communication for transparent and robust content access in P2P networks. Instead of accessing a single peer for obtaining the desired content, a user request is received and processed by a group of peers. This group of peers, called PCG (Peer Content Group) provides reliable content access in sense that even as members of the group crash or leave the system, users continue to receive the content if at least one group member remains fault-free. Each PCG member is capable of independently serving the request. A PCG is transparent to the user, as the group interface is identical to the interface provided by a single peer. A group member is elected to serve each request. A fault monitoring component allows the detection of member crashes. If the peer is serving request crashes, another group member is elected to continue providing the service. The PCG and a P2P file sharing applications were implemented in the JXTA platform. Evaluation results are presented showing the latency of group operations and system components.

Deep Learning-Based Two-Step Approach for Intrusion Detection in Networks

Intrusion Detection Systems (IDS) are essential for computer security, with various techniques developed over time. However, many of these methods suffer from high false positive rates. To address this, we propose an approach utilizing Recurrent Neural Networks (RNN). Our method starts by reducing the dataset’s dimensionality using a Deep Auto-Encoder (DAE), followed by intrusion detection through a Bidirectional Long Short-Term Memory (BiLSTM) network. The proposed DAE-BiLSTM model outperforms Random Forest, AdaBoost, and standard BiLSTM models, achieving an accuracy of 0.97, a recall of 0.95, and an AUC of 0.93. Although BiLSTM is slightly less effective than DAE-BiLSTM, both RNN-based models outperform AdaBoost and Random Forest. ROC curves show that DAE-BiLSTM is the most effective, demonstrating strong detection capabilities with a low false positive rate. While AdaBoost performs well, it is less effective than RNN models but still surpasses Random Forest.

A Network Coding Based Cloud Storage Scheme

With this paper, we propose a network coding based cloud storage scheme. The storage system is in the form of an m * n data array. The n columns stand for n storage nodes, which are comprised of a part of systematic nodes storing source symbols and a part of nonsystematic nodes storing parity symbols. Every row of the data array is a (n, k) systematic Maximum Distance Separable (MDS) code. A source symbol is only involved in the encoding with the unique row;it locates at and is not used by other rows. Such a design significantly decreases the complexity of encoding and decoding. Moreover, in case of single node failures, we use interference alignment to further reduce repair bandwidth. Compared to some existing cloud storage schemes, our scheme significantly reduces resource consumption on storage, update bandwidth and repair bandwidth.

Operational Sustainability and Digital Leadership for Cybercrime Prevention

The digital world of work and social media, despite its challenges, is here to stay as an integrated part of our day-to-day operational norms. Therefore, we must make the best of it on a proactive basis before the private data of our employees and consumers becomes hacked remotely by criminals. Privacy violations and hacking of data cannot be sustained since they can be very costly and may even lead to bankruptcy. As such, today’s leaders, managers, and educators have the responsibility of preparing their future replacements for the modern digital economy, so their organizations’ operational processes can remain competitive, safe, and sustainable. Operational sustainability, in this paper, is proposed as a tripod or “three-legged stool” of environmental, social, and digital responsibility. With more employees and entrepreneurs accessing digital data remotely through vulnerable or unsecure online platforms, the opportunities for cybercrimes rise. Therefore, this article focuses more on the often-neglected digitalization element of operational sustainability. All leaders must be aware of the legal, social, and environmental expectations of a digital society by doing what is good for the world while also being efficient and safe from cybercriminals. The paper proposes that future leaders must be socialized with a sustainability mindset about data privacy and safety measures that are necessary for this fast-changing digital economy where hackers and artificial intelligence (AI) tools can make the process more challenging. With AI being used by some actors to generate false yet realistic content, companies will have to do more to make sure their brands are not defamed or tarnished. As such, this conceptual article discusses a model for operational sustainability, which includes the privacy and safety of data that can be used by managers, educators and other leaders for training and development purposes in today’s digital world of work.

Challenges and Considerations in Developing and Architecting Large-Scale Distributed Systems

This paper investigates large-scale distributed system design. It looks at features, main design considerations and provides the Netflix API, Cassandra and Oracle as examples of such systems. Moreover, the paper investigates the challenges of designing, developing, deploying, and maintaining such systems, in regard to the features presented. Finally, the paper discusses aspects of available solutions and current practices to challenges that large-scale distributed systems face.