• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.179-192
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• 2023

The widespread use of Cloud Computing, Internet of Things (IoT), and social media in the Information Communication Technology (ICT) field has resulted in continuous and unavoidable cyber-attacks on users and critical infrastructures worldwide. Traditional security measures such as firewalls and encryption systems are not effective in countering these sophisticated cyber-attacks. Therefore, Intrusion Detection and Prevention Systems (IDPS) are necessary to reduce the risk to an absolute minimum. Although IDPSs can detect various types of cyber-attacks with high accuracy, their performance is limited by a high false alarm rate. This study proposes a new technique called Fuzzy Logic - Objective Risk Analysis (FLORA) that can significantly reduce false positive alarm rates and maintain a high level of security against serious cyber-attacks. The FLORA model has a high fuzzy accuracy rate of 90.11% and can predict vulnerabilities with a high level of certainty. It also has a mechanism for monitoring and recording digital forensic evidence which can be used in legal prosecution proceedings in different jurisdictions.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.11-23
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• 2024

Triage is a practice of accurately prioritizing patients in emergency department (ED) based on their medical condition to provide them with proper treatment service. The variation in triage assessment among medical staff can cause mis-triage which affect the patients negatively. Developing ED triage system based on machine learning (ML) techniques can lead to accurate and efficient triage outcomes. This study aspires to develop a triage system using machine learning techniques to predict ED triage levels using patients' information. We conducted a retrospective study using Security Forces Hospital ED data, from 2021 through 2023 during Hajj period in Saudia Arabi. Using demographics, vital signs, and chief complaints as predictors, two machine learning models were investigated, naming gradient boosted decision tree (XGB) and deep neural network (DNN). The models were trained to predict ED triage levels and their predictive performance was evaluated using area under the receiver operating characteristic curve (AUC) and confusion matrix. A total of 11,584 ED visits were collected and used in this study. XGB and DNN models exhibit high abilities in the predicting performance with AUC-ROC scores 0.85 and 0.82, respectively. Compared to the traditional approach, our proposed system demonstrated better performance and can be implemented in real-world clinical settings. Utilizing ML applications can power the triage decision-making, clinical care, and resource utilization.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3034-3055
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• 2014

Wireless Sensor Networks have extensively been utilized for ambient data collection from simple linear structures to dense tiered deployments. Issues related to optimal resource allocation still persist for simplistic deployments including linear and hierarchical networks. In this work, we investigate the case of dimensioning parameters for linear and tiered wireless sensor network deployments with notion of providing extended lifetime and reliable data delivery over extensive infrastructures. We provide a single consolidated reference for selection of intrinsic sensor network parameters like number of required nodes for deployment over specified area, network operational lifetime, data aggregation requirements, energy dissipation concerns and communication channel related signal reliability. The dimensioning parameters have been analyzed in a pipeline monitoring scenario using ZigBee communication platform and subsequently referred with analytical models to ensure the dimensioning process is reflected in real world deployment with minimum resource consumption and best network connectivity. Concerns over data aggregation and routing delay minimization have been discussed with possible solutions. Finally, we propose a node placement strategy based on a dynamic programming model for achieving reliable received signals and consistent application in structural health monitoring with multi hop and long distance connectivity.

• 한국IT서비스학회:학술대회논문집
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• 2003.11a
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• pp.233-240
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• 2003

To develop high-quality software systems satisfying the customer's needs, user-centered design (UCD) process has been emphasized in the area of human-computer interaction. And component-based development (CBD) has been extensively studied to realize a systematic software reuse, thereby reducing the time-to-market and the development cost. Balanced integration of user-centered design process and CBD process will be a promising way for successful software construction, which effectively achieves three goals: the quality of software, the cost of software development, and the time-to-market. However, traditional CBD methodology seems to lack the concept of user-centered design process and the relevant methods. This paper proposes a way of incorporating user-centered design process into a CBD methodology. Firstly, this paper gives the brief introduction of UCD. Secondly, we explain typical UCD activities and methods along the phase of systems development lifecycle and propose the use of usability maturity model (UMM) for integrating UCD activities and methods with those of CBD methodology. Finally, as a case study, we describe the results of comparing the UCD activities to the activities of MaRMI-III, which has been developed as a CBD methodology at ETRI.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.863-872
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• 2021

The main goal of this research is to understand how small and medium enterprises (SMEs) owners in Oman perceive the factors that drive or impede their growth and sustainability. Based on survey data of 395 SMEs in Oman, factor analysis was conducted to check if all the items load as one factor in each of the constructs. The results show that all the items measuring motivators and barriers loaded significantly for the respective scales, with high reliability (Cronbach alpha for Motivators = 0.991 and Barriers = 0.995). Relationships between the demographic factors of entrepreneurs and firm characteristics were tested and it was found that all the four variables: age of the entrepreneur (p = 0.00), qualification of the entrepreneur (p = 0.00), SME sector (p = 0.00), and age of the firm (p = 0.00) have a significant relationship with both the Motivators and the Barriers. The findings of this study could have significant implications for policymakers in Oman and other Middle Eastern countries. Since SMEs face similar problems and are given priority around the world, the findings could be applicable to other countries, as well. The findings also add important results to the empirical literature on SMEs.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.673-685
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• 2021

This study aims to determine theoretically the best workers layoff/training strategy that entrepreneurs should apply to manage the COVID-19 crisis successfully. It also examines the impacts of the Saudi government's emergency measures on firm performance. The paper develops a theoretical framework in which the optimal control technics is applied to model the entrepreneur's hiring, layoff, and training behaviors. The results show that, during the current COVID-19 pandemic, the entrepreneur should first lay off the less productive workers to reduce labor costs. As more and more inefficient workers quit and profit increases, the entrepreneur starts expanding his activity and training workers. In the long run, only the training activity allows the firm efficiency to grow at a constant rate. This finding suggests that the key to long-run economic recovery in Saudi Arabia will rely on training, innovation, and adaptability to the new digital environment. The paper also shows that the Saudi government initiative of covering 60% of salaries for the small- and medium-sized entrepreneurs during the COVID-19 pandemic will enhance training activities in small- and medium-sized enterprises and improve their efficiency in both the short and long run. This policy will also prevent Saudi entrepreneurs from laying off half of their staff.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.373-380
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• 2022

The field of land surveying is changing dramatically due to the way data is processed, analyzed and presented. Also, there is a growing demand for digital spatial information, coming primarily from the GIS (Geographical Information System) user community. Such a demand has created a strong development potential for a new land surveying software. An overview of the development and capabilities of a land surveying software platform based on the Windows system, SurveyingMap, is presented. Among its many features, SurveyingMap provides a lot of adaptability for networks adjustment, geodetic and plane coordinates transformation, contouring, sectioning, DTM (Digital Terrain Model) generation, and large scale mapping applications. The system output is compatible with well known computer aided drafting (CAD) /GIS packages to expand its scope of applications. SurveyingMap is also suitable for non-technical users due to the user-friendly graphic user interface. The system could be used in engineering, architecture, GIS, and academic teaching and research, among other fields. Two applications of SurveyingMap, extension of field control and large scale mapping, for the case study area are established. The results demonstrate that the system is adaptable and reasonably priced for use by college and university students.

• Progress in Medical Physics
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• v.33 no.1
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• pp.1-9
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• 2022

Purpose: To evaluate the effective volume of the Korea Research Institute of Standards and Science free air chamber (KRISS FAC) L1 used for the primary standard device of the low-energy X-ray air kerma. Methods: The mechanical dimensions were measured using a 3-dimensional coordinate measuring machine (3-d CMM, Model UMM 500, Carl Zeiss). The diameter of the diaphragm was measured by a ring gauge calibrator (Model KRISS-DM1, KRISS). The elongation of the collector length due to electric field distortion was determined from the capacitance measurement of the KRISS FAC considering the result of the finite element method (FEM) analysis using the code QuickField v6.4. Results: The measured length of the collector was 15.8003±0.0014 mm with a 68% confidence level (k=1). The aperture diameter of the diaphragm was 10.0021±0.0002 mm (k=1). The mechanical measurement volume of the KRISS FAC L1 was 1.2415±0.0006 cm³ (k=1). The elongated length of the collector due to the electric field distortion was 0.170±0.021 mm. Considering the elongated length, the effective measurement volume of the KRISS FAC L1 was 1.2548±0.0019 cm³(k=1). Conclusions: The effective volume of the KRISS FAC L1 was determined from the mechanically measured value by adding the elongated volume due to the electric field distortion in the FAC. The effective volume will replace the existing mechanically determined volume in establishing and maintaining the primary standard of the low-energy X-ray.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.203-209
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• 2023

The paper brings across data that is utilized in the Bring Your Own Device (BYOD) status collected between February and April of 2021 across Saudi Arabia. The data set was collected using questionnaires established through online mechanisms for the respondents. In the questionnaire, personal details included five questions while seven questions addressed the working model of personal mobile devices. Six questions addressed the awareness of employees bring your own device awareness for employees comprised seven questions and two questions addressed the benefits of business achievements. In the identification of suitable respondents for the research, two approaches were applied. The research demanded that the respondents be Saudi Arabian nationals and have attained 18 years. Snowball and purposive techniques were applied in the collection of information from a wide area of Saudi Arabia while employing social media approaches that include the use of WhatsApp and emails in the collection of data. The approach ensured the collection of data from 857 respondents used in the identification of the status as well as issues across the BYOD environment and accompanying solutions. The data was also used in the provision of awareness in the community through short-term courses, cyber security training and awareness programs. The results of the research are therefore applicable to the context of the Saudi Arabian country that is currently facing issues in dealing with the application of personal devices in the work environment.