The unprecedented growth in the amount of online information available in many languages to users and businesses, including news articles and social media, has made it difficult and time consuming for users to identify and consume sought after content. Hence, automatic text summarization for various languages to generate accurate and relevant summaries from the huge amount of information available is essential nowadays. Techniques and methodologies for automatic Arabic text summarization are still immature due to the inherent complexity of the Arabic language in terms of both structure and morphology. This work attempts to improve the performance of Arabic text summarization. We propose a new Arabic text summarization approach based on a new noun extraction method and fuzzy logic. The proposed summarizer is evaluated using EASC corpus and benchmarked against popular state of the art Arabic text summarization systems. The results indicate that our proposed Fuzzy logic approach with noun extraction outperforms existing systems.
The use of Kubernetes containers in cloud computing has been steadily increasing. With the emergence of Kubernetes, the management of applications inside containers (or pods) is simplified. Kubernetes allows automated actions like self-healing, scaling, rolling back and updates for application management. At the same time, security threats have evolved with attacks on pods to perform malicious actions becoming ever more sophisticated. Out of several recent malware types, cryptomining has emerged as one of the most serious threats with its hijacking of server resources cryptocurrency mining. During application deployment and execution in the pod, a cryptomining process, started by a hidden malware executable can also run in the background. A method to detect malicious cryptomining software is thus needed. Most ML-based anomaly detection methods create black-box models and don?t provide sufficient insight into their outputs. In this paper, we describe the design and implementation in a Kubernetes cluster of an MLbased detection system of anomalous pods by monitoring Linux kernel system calls (syscalls). The explainable model generated is intended to provide sufficient information for visualization, explanation, and interpretation. The ML engine uses neural network, decision tree, and ensemble learning models that are compared in terms of their performance metrics.
When programming parallel applications, barriers are one of the most commonly used synchronizations mechanisms. A barrier ensures that all threads in a given set have reached a specific point in the execution of the parallel program, and that those arriving earlier will wait for the remaining ones before all of them continue beyond that point. The availability of fast implementations of this basic mechanism for multicore architectures can greatly improve the performance of a wide range of applications. We evaluate their performance and compare against more complex existing barrier algorithms. In addition, the main contribution of this paper is the introduction of a novel implementation of barriers based on Scalable NonZero Indicators (SNZI), and compare its performance against the existing algorithms. The performance evaluation two applications benchmark; part of the JavaGrande benchmark suite. These benchmarks are executed on Masdar Institute cluster (MI HPC) at Khalifa University. We observe that there is no a single winner for all the scenarios. Nonetheless our proposed SNZI barriers shows that our SNZI barrier outperforms or is competitive in some scenarios.
With the rising number of malwares, incident handlers are having difficulty keeping up with malware analysis. The Cuckoo Sandbox (CSB) tool was utilized to study the behaviors of malware used by NSA malware. This was done using social media web sites such as twitter to monitor the discussions. The process started with tracing a malicious session with a unique URL. It was pretending to be MS Office 365, with the letter ?O? in the word office replaced with a zero digit. It is captured and place in the search engine of Google and later examined by Twitter for traces. It is discovered that a Twitter chat has a malicious file that was communicating with it. The dynamic malware CSB tool was used for further analysis of this file. The CSB is used by online engines to scan and detonate malware. It is found that the malware was communicating through an IP Address. It is then scanned in the CSB. After an in-depth investigation more variant was found that have similar behavior. We then researched more and found it was an NSA malware. Twitter and other tools were used to analyze the program and then was verified to be NSA malware.
There is an increasing awareness that healthcare organizations have been facing challenges on efficiency and quality due to increasing demand and cost. In order to address such challenges, lean has gained growing attention in healthcare to develop efficient and waste-free processes. It involves stakeholders? participation to identify all possible wastes in health systems and implement lean solutions. To guide stakeholders and provide a comprehensive picture of all system-wide wastes, system modelling techniques (SMTs) can be used. In this study, lean applications in healthcare will be reviewed, particularly those associated with using visual process representation. To further investigate the usability and utility of using SMTs in waste identification.
With the upsurge in technological advancements and the internet having such a great impact on peoples? everyday lives, it has become necessary for businesses to keep up with these changes. The banking industry is one of the growing industries with huge contribution to the economy. The purpose of this research is to identify the factors that play a role in customer?s acceptance of online banking services. A conceptual model based on the Technology Acceptance Model (TAM) by Davis (1989) was developed. The questionnaire results were gathered from 115 respondents from across the UAE and the hypothesis were tested. The results of the correlation test revealed that there was a significant relationship between the following variables: income and the perceived usefulness, banking information and the perceived ease of use, amount of banking information and security and the perceived ease of use and perceived usefulness. So, we accepted all the hypotheses.
Business incubators have shown as an effective approach for enhancing entrepreneurs? success in several countries. In UAE, business incubators have been established to nurture entrepreneurs. However, due to the novelty of incubators in the country, few incubators have sustained their existence. This paper investigates the success factors of incubators and examine their roles in the UAE. Due to the limited number of incubators, this research adopted a multi-method approach combining semi-structured interviews and structured survey. The results showed that incubators are successful when they are able to graduate entrepreneurs, establish, and sustain start-ups in the market, while the success factors of incubators were related to four internal factors (such as commercialization activities) and four external factors (such as government support). In addition, nurturing entrepreneurs, creating jobs, and developing entrepreneurship culture were the main expected roles of incubators in the UAE. The research proposed a conceptual framework of incubations? success, which provide the government with a comprehensive guideline for establishing success model of incubators across the targeted sectors in the country. The study recommends having a conducive bylaw that supports incubators and building a systemized collaboration between the stakeholders of incubators in which it promotes entrepreneurial practices in the UAE.
This study aims to provide theoretical and empirical insights into how a firm can enhance its performance strategically and financially to achieve competitive advantage through integrating R&D activities with the dynamic capabilities approach. In order to achieve this, two business models have been proposed. The first is solely related to the firm?s practice of its own R&D activities and the second is through collaboration in R&D. According to the relevant literature, collaboration and alliance generally constitutes a better business model option for the performance of a firm. The PLS-SEM approach was used, and the statistics support the theoretical assumptions that the strength and significance of R&D relationships with the competitive advantage of the firm are influenced in collaborative R&D environment rather than in R&D alone. It is recommended that more study needs to be conducted to show that companies should foster collaboration in R&D to achieve a competitive advantage for the firm.
This study is to examine innovation readiness in the context of organizational human oriented knowledge management within public services organizations in Sharjah. Three research questions will be explored to meet its aims. Firstly, what is the nature of service innovation readiness and knowledge required by public services organizations in Sharjah to fulfil service delivery mandate? Secondly, what are the mechanisms to enact service innovation readiness and how can it be operationalized? Thirdly, what are the mechanisms to operationalize the interplay between the attributes of service innovation and the organizational factors that encompass knowledge management. The study will be a fine-grained exploratory case study with the Sharjah municipality teams. Data will be obtained from interviews with stakeholders. This study will have major implications for not only service innovation theory and practice, but also for Public Sector theory. It is expected that the findings may suggest the need for managers to simultaneously consider cross-implications of these two concepts. Particularly interesting will be the possible context of the multiplicity of not only stakeholder interest but also customer interest in public service innovation within the Emirate of Sharjah.
This paper aims to study the impact of the use of technology in the Human Resources Management (HRM) applications in higher education institutions in the UAE. It investigates the efficient ways that should be learned and followed in using the technology in the different HRM practices aiming to add value to the overall institutional performance and raise the academic excellence. The study adopted qualitative method where seven UAE universities have been visited to conduct interviews with HR employees and other staff. In addition to that, secondary data has been also used to support our study analysis and findings. The study found that most of the universities in UAE are already using the latest technology methods and applications which are directed to improve their service quality and their outputs from both the faculty and the administrative staff. However, the study provides more recommendations, finding and discussions that aims to strength and improve the process of e-HRM applications.
