Search results for: Fahd M. Aldosari

Authors: M. H. Imam, Imran A. Tasadduq, Abdul-Rahim Ahmad, Fahd M. Aldosari

Abstract:

Learning outcomes of a course (CLOs) and the abilities at the time of graduation referred to as Student Outcomes (SOs) are required to be assessed for ABET accreditation. A question in an assessment must target a CLO as well as an SO and must represent a required level of competence. This paper presents the idea of an Expert System (ES) to select a proper question to satisfy ABET accreditation requirements. For ES implementation, seven attributes of a question are considered including the learning outcomes and Bloom’s Taxonomy level. A database contains all the data about a course including course content topics, course learning outcomes and the CLO-SO relationship matrix. The knowledge base of the presented ES contains a pool of questions each with tags of the specified attributes. Questions and the attributes represent expert opinions. With implicit rule base the inference engine finds the best possible question satisfying the required attributes. It is shown that the novel idea of such an ES can be implemented and applied to a course with success. An application example is presented to demonstrate the working of the proposed ES.

Keywords: Expert system, student outcomes, course learning outcomes, question attributes.

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Authors: Amjad F. Alharbi, Bashayer A. Alotaibi, Fahd S. Alotaibi

Abstract:

The emergence of Internet of Things (IoT) technology provides capabilities for a huge number of smart devices, services and people to be communicate with each other for exchanging data and information over existing network. While as IoT is progressing, it provides many opportunities for new ways of communications as well it introduces many security and privacy threats and challenges which need to be considered for the future of IoT development. In this survey paper, an IoT security issues as threats and current challenges are summarized. The security architecture for IoT are presented from four main layers. Based on these layers, the IoT security requirements are presented to insure security in the whole system. Furthermore, some researches initiatives related to IoT security are discussed as well as the future direction for IoT security are highlighted.

Keywords: Internet of Things, IoT, IoT security challenges, IoT security requirements, IoT security architecture.

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

Abstract:

In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: Data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data.

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Authors: Saad M. Al-Garni, Adel A. Abdennour

Abstract:

Freeways are originally designed to provide high mobility to road users. However, the increase in population and vehicle numbers has led to increasing congestions around the world. Daily recurrent congestion substantially reduces the freeway capacity when it is most needed. Building new highways and expanding the existing ones is an expensive solution and impractical in many situations. Intelligent and vision-based techniques can, however, be efficient tools in monitoring highways and increasing the capacity of the existing infrastructures. The crucial step for highway monitoring is vehicle detection. In this paper, we propose one of such techniques. The approach is based on artificial neural networks (ANN) for vehicles detection and counting. The detection process uses the freeway video images and starts by automatically extracting the image background from the successive video frames. Once the background is identified, subsequent frames are used to detect moving objects through image subtraction. The result is segmented using Sobel operator for edge detection. The ANN is, then, used in the detection and counting phase. Applying this technique to the busiest freeway in Riyadh (King Fahd Road) achieved higher than 98% detection accuracy despite the light intensity changes, the occlusion situations, and shadows.

Keywords: Background Extraction, Neural Networks, VehicleDetection, Freeway Traffic.

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Authors: Ibrahim A. Al-Muhaisen, Mohammad N. Al Ymemeni

Abstract:

Ozone (O3) is considered as one of the most phytotoxic pollutants with deleterious effects on living and non living components of Ecosystems. It reduces growth and yield of many crops as well as alters the physiology and crop quality. The present study described series of experiments to investigate the effects of ambient O3 at different locations with different ambient levels of O3 depending on proximity to pollutant source and ranged between 17 ppb/h in control experiment to 112 ppb/h in industrial area respectively. The ambient levels in other three locations (King Saud University botanical garden, King Fahd Rd, and Almanakh Garden) were 61,61,77 ppb/h respectively. Tow legume crops species (vicia vaba L ; and Pisum sativum) differ in their phenology and sensitivity were used. The results showed a significant negative effect to ozone on morphology, number of injured leaves, growth and productivity with a difference in the degree of response depending on the plant type. Visia Faba showed sensitivity to ozone to number and leaf area and the degree of injury leaves 3, pisum sativum show higher sensitivity for the gas for degree of injury 1,The relative growth rate and seed weight, it turns out there is no significant difference between the two plants in plant height and number of seeds.

Keywords: Ozone, Legume crops, growth and production, Resistance, Riyadh city.

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Authors: Muhammad Farhan, Sayed Faruque, Amr Mohammed, Sami Osman, Omar Al-Jabari, Abdul Almojil

Abstract:

Saudi Arabia in recent years has seen drastic increase in traffic related crashes. With population of over 29 million, Saudi Arabia is considered as a fast growing and emerging economy. The rapid population increase and economic growth has resulted in rapid expansion of transportation infrastructure, which has led to increase in road crashes. Saudi Ministry of Interior reported more than 7,000 people killed and 68,000 injured in 2011 ranking Saudi Arabia to be one of the worst worldwide in traffic safety. The traffic safety issues in the country also result in distress to road users and cause and economic loss exceeding 3.7 billion Euros annually. Keeping this in view, the researchers in Saudi Arabia are investigating ways to improve traffic safety conditions in the country. This paper presents a multilevel approach to collect traffic safety related data required to do traffic safety studies in the region. Two highway corridors including King Fahd Highway 39 kilometre and Gulf Cooperation Council Highway 42 kilometre long connecting the cities of Dammam and Khobar were selected as a study area. Traffic data collected included traffic counts, crash data, travel time data, and speed data. The collected data was analysed using geographic information system to evaluate any correlation. Further research is needed to investigate the effectiveness of traffic safety related data when collected in a concerted effort.

Keywords: Crash Data, Data Collection, Traffic Safety.

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Authors: Kaukab Azeem

Abstract:

Introduction: Obesity is a major health risk issue in the present day of life for one and all globally. Obesity is one of the major concerns for public health according to recent increasing trends in obesity-related diseases such as Type 2 diabetes. ( Kazuya, 1994).and hyperlipidemia, (Sakata,1990) .which are more prevalent in Japanese adults with body mass index (BMI) values Z25 kg/m2.( Japanese Ministry of Health and Welfare,1997). The purpose of the study was to assess the effect of twelve weeks of brisk walking on blood pressure and body mass index, anthropometric measurements of obese males. Method: Thirty obese (BMI= above 30) males, aged 18 to 22 years, were selected from King Fahd University of Petroleum & Minerals, Saudi Arabia. The subject-s height (cm) was measured using a stadiometer and body mass (kg) was measured with a electronic weighing machine. BMI was subsequently calculated (kg/m2). The blood pressure was measured with standardized sphygmomanometer in mm of Hg. All the measurements were taken twice before and twice after the experimental period. The pre and post anthropometric measurements of waist and hip circumference were measured with the steel tape in cm. The subjects underwent walking schedule two times in a week for 12 weeks. The 45 minute sessions of brisk walking were undertaken at an average intensity of 65% to 85% of maximum HR (HRmax; calculated as 220-age). Results & Discussion: Statistical findings revealed significant changes from pre test to post test in case of both systolic blood pressure and diastolic blood pressure in the walking group. Results also showed significant decrease in their body mass index and anthropometric measurements i.e. (waist & hip circumference). Conclusion: It was concluded that twelve weeks brisk walking is beneficial for lowering of blood pressure, body mass index, and anthropometric circumference of obese males.

Keywords: Anthropometric, Blood pressure, Body mass index

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