A Study to Assess the Employment Ambitions of Graduating Students from College of Applied Medical Sciences, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia

Introduction: Students make plans for their career and are keen in exploring options of employment in those carriers. They make their employment choice based on their desires and preferences. This study aims to identify if students of King Saud Bin Abdulaziz for Health Sciences, College of Applied Medical Sciences after obtaining appropriate education prefer to work as clinicians, university faculty, or full-time researchers. There are limited studies in Saudi Arabia exploring the university student’s employment choices and preferences. This study would help employers to build the required job positions and prevent misleading employers from opening undesired positions in the job market. Methodology: The study included 394 students from third and fourth years both male and female among the eighth programs of college of applied medical sciences, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh campus. A prospective quantitative cross-sectional study was conducted; data were collected by distributing a seven item questionnaire and analyzed using SPSS. Results: Among the participants, 358 (90.9%) of them chose one of the three listed career choices, 263 (66.8%) decided to work as hospital staff after their education, 75 students (19.0%) chose to work as a faculty member in a university after obtaining appropriate degree, 20 students (5.1%) preferred to work as full-time researcher after obtaining appropriate degree, the remaining 36 students (9.1%) had different career goals, such as obtaining a master degree after graduating, to obtain a bachelor of medicine and bachelor in surgery degree, and working in the private sector. The most recurrent reason behind the participants' choice was "career goal", where 276 (70.1%) chose it as a reason. Conclusion: The findings of the study showed that most student’s preferred to work in hospitals as clinicians, followed by choice of working as a faculty in a university, the least choice was to be working as full-time researchers.

Exporting Physiochemical Changes during the Fermentation of Aloe Vera

Aloe Vera is a short-stemmed succulent plant which is commonly used in Myanmar traditional medicine. A. vera gel was also used as food addictive. This study aims to improve the Myanmar folk medicine to a functional beverage. In this research, Aloe vera was fermented with Saccharomyces cerevisiae for 6 months. Three different processes were carried out. Process I contains A. vera 10%, sugar 30%, water 50%, and starter culture 10%, process II contains A. vera 10%, sugar 15%, honey 15%, and water 50%, starter culture 10%; process III contains A. vera 10%, honey 30%, water 50%, starter culture 10%. During wine fermentation, the wine parameters such as alcohol content, total soluble solid (ºBrix), pH, color and cell population were analyzed. After 30 days of fermentation, total cell population remained 2.8x106 in P-I, P-II and 3.2x106 in P-III. Total soluble solid content dropped to 15.8 in P-I, P-II and 15.7 in P-III. After 30 days, clear wine was transferred to other vassals for racking. After 6 months of racking, microbial population reached under detectable level and alcohol content was round about 11% but not significantly different among these processes. P-II was found to have the highest color intensity at 450 nm and it got the most taster satisfaction when sensory evaluation was carried out using five hedonic scales after 6 month of racking.

Fabrication of a High-Performance Polyetherimide Membrane for Helium Separation

Helium market is continuously growing due to its essential uses in the electronic and healthcare sectors. Currently, helium is produced by cryogenic distillation but the process is uneconomical especially for low production volumes. On the other hand, polymeric membranes can provide a cost-effective solution for helium purification due to their low operating energy. However, the preparation of membranes involves the use of very toxic solvents such as chloroform. In this work, polyetherimide membranes were prepared using a less toxic solvent, n-methylpyrrolidone with a polymer-to-solvent ratio of 27 wt%. The developed membrane showed a superior helium permeability of 15.9 Barrer that surpassed the permeability of membranes made by chloroform.

Solvent Extraction and Spectrophotometric Determination of Palladium(II) Using P-Methylphenyl Thiourea as a Complexing Agent

A precise, sensitive, rapid and selective method for the solvent extraction, spectrophotometric determination of palladium(II) using para-methylphenyl thiourea (PMPT) as an extractant is developed. Palladium(II) forms yellow colored complex with PMPT which shows an absorption maximum at 300 nm. The colored complex obeys Beer’s law up to 7.0 µg ml-1 of palladium. The molar absorptivity and Sandell’s sensitivity were found to be 8.486 x 103 l mol-1cm-1 and 0.0125 μg cm-2 respectively. The optimum conditions for the extraction and determination of palladium have been established by monitoring the various experimental parameters. The precision of the method has been evaluated and the relative standard deviation has been found to be less than 0.53%. The proposed method is free from interference from large number of foreign ions. The method has been successfully applied for the determination of palladium from alloy, synthetic mixtures corresponding to alloy samples.

Sedimentological Study of Bivalve Fossils Site Locality in Hong Hoi Formation, Lampang, Thailand

Hong Hoi Formation is a Middle Triassic deep marine succession presented in outcrops throughout the Lampang Basin of northern Thailand. The primary goal of this research is to diagnose the paleoenvironment, petrographic compositions, and sedimentary sources of the Hong Hoi Formation in Ban Huat, Ngao District. The Triassic Hong Hoi Formation is chosen because the outcrops are continuous and fossils are greatly exposed and abundant. Depositional environment is reconstructed through sedimentological studies along with facies analysis. The Hong Hoi Formation is petrographically divided into two major facies, they are: sandstones with mudstone interbeds, and mudstones or shale with sandstone interbeds. Sandstone beds are lithic arenite and lithic greywacke, volcanic lithic fragments are dominated. Sedimentary structures, paleocurrent data and lithofacies arrangement indicate that the formation deposited in a part of deep marine abyssal plain environment. The sedimentological and petrographic features suggest that during the deposition the Hong Hoi Formation received sediment supply from nearby volcanic arc. This suggested that the intensive volcanic activity within the Sukhothai Arc during the Middle Triassic is the main sediment source.

Development of a Real Time Axial Force Measurement System and IoT-Based Monitoring for Smart Bearing

The purpose of this research is to develop a real time axial force measurement system for a smart bearing through the use of strain-gauges, whereby the data acquisition is performed by an Arduino microcontroller due to its easy manipulation and low-cost. The measured signal is acquired and then discretized using a Wheatstone Bridge and an Analog-Digital Converter (ADC) respectively. For bearing monitoring, a real time monitoring system based on Internet of things (IoT) and Bluetooth were developed. Experimental tests were performed on a bearing within a force range up to 600 kN. The experimental results show that there is a proportional linear relationship between the applied force and the output voltage, and the error R squared is within 0.9878 based on the regression analysis.

Development of a Small-Group Teaching Method for Enhancing the Learning of Basic Acupuncture Manipulation Optimized with the Theory of Motor Learning

This study developed a method for teaching acupuncture manipulation in small groups optimized with the theory of motor learning. Sixty acupuncture students and their teacher participated in our research. Motion videos were recorded of their manipulations using the lifting-thrusting method. These videos were analyzed using Simi Motion software to acquire the movement parameters of the thumb tip. The parameter velocity curves along Y axis was used to generate small teaching groups clustered by a self-organized map (SOM) and K-means. Ten groups were generated. All the targeted instruction based on the comparative results groups as well as the videos of teacher and student was provided to the members of each group respectively. According to the theory and research of motor learning, the factors or technologies such as video instruction, observational learning, external focus and summary feedback were integrated into this teaching method. Such efforts were desired to improve and enhance the effectiveness of current acupuncture teaching methods in limited classroom teaching time and extracurricular training.

Effect of Copper Ions Doped-Hydroxyapatite 3D Fiber Scaffold

The mineral in human bone is not pure stoichiometric calcium phosphate (Ca/P) as it is partially substituted by in organic elements. In this study, the copper ions (Cu2+) substituted hydroxyapatite (CuHA) powder has been synthesized by the co-precipitation method. The CuHA powder has been used to fabricate CuHA fiber scaffolds by sol-gel process and the following sinter process. The resulted CuHA fibers have slightly different microstructure (i.e. porosity) compared to HA fiber scaffold, which is denser. The mechanical properties test was used to evaluate CuHA, and the results showed decreases in both compression strength and hardness tests. Moreover, the in vitro used endothelial cells to evaluate the angiogenesis of CuHA. The result illustrated that the viability of endothelial cell on CuHA fiber scaffold surfaces tends to antigenic behavior. The results obtained with CuHA scaffold give this material benefit in biological applications such as antimicrobial, antitumor, antigens, compacts, filling cavities of the tooth and for the deposition of metal implants anti-tumor, anti-cancer, bone filler, and scaffold.

A Comparative Study of Cardio Respiratory Efficiency between Aquatic and Track and Field Performers

The present study was conducted to explore the basic pulmonary functions which may generally vary according to the bio-physical characteristics including age, height, body weight, and environment etc. of the sports performers. Regular and specific training exercises also change the characteristics of an athlete’s prowess and produce a positive effect on the physiological functioning, mostly upon cardio-pulmonary efficiency and thereby improving the body mechanism. The objective of the present study was to compare the differences in cardio-respiratory functions between aquatics and track and field performers. As cardio-respiratory functions are influenced by pulse rate and blood pressure (systolic and diastolic), so both of the factors were also taken into consideration. The component selected under cardio-respiratory functions for the present study were i) FEVI/FVC ratio (forced expiratory volume divided by forced vital capacity ratio, i.e. the number represents the percentage of lung capacity to exhale in one second) ii) FVC1 (this is the amount of air which can force out of lungs in one second) and iii) FVC (forced vital capacity is the greatest total amount of air forcefully breathe out after breathing in as deeply as possible). All the three selected components of the cardio-respiratory efficiency were measured by spirometry method. Pulse rate was determined manually. The radial artery which is located on the thumb side of our wrist was used to assess the pulse rate. Blood pressure was assessed by sphygmomanometer. All the data were taken in the resting condition. 36subjects were selected for the present study out of which 18were water polo players and rest were sprinters. The age group of the subjects was considered between 18 to 23 years. In this study the obtained data inform of digital score were treated statistically to get result and draw conclusions. The Mean and Standard Deviation (SD) were used as descriptive statistics and the significant difference between the two subject groups was assessed with the help of statistical ‘t’-test. It was found from the study that all the three components i.e. FEVI/FVC ratio (p-value 0.0148 < 0.01), FVC1 (p-value 0.0010 < 0.01) and FVC (p-value 0.0067 < 0.01) differ significantly as water polo players proved to be better in terms of cardio-respiratory functions than sprinters. Thus study clearly suggests that the exercise training as well as the medium of practice arena associated with water polo players has played an important role to determine better cardio respiratory efficiency than track and field athletes. The outcome of the present study revealed that the lung function in land-based activities may not provide much impact than that of in water activities.

Comparative Effect of Self-Myofascial Release as a Warm-Up Exercise on Functional Fitness of Young Adults

Warm-up is an essential component for optimizing performance in various sports before a physical fitness training session. This study investigated the immediate comparative effect of Self-Myofascial Release through vibration rolling (VR), non-vibration rolling (NVR), and static stretching as a part of a warm-up treatment on the functional fitness of young adults. Functional fitness is a classification of training that prepares the body for real-life movements and activities. For the present study 20male physical education students were selected as subjects. The age of the subjects was ranged from 20-25 years. The functional fitness variables undertaken in the present study were flexibility, muscle strength, agility, static and dynamic balance of the lower extremity. Each of the three warm-up protocol was administered on consecutive days, i.e. 24 hr time gap and all tests were administered in the morning. The mean and SD were used as descriptive statistics. The significance of statistical differences among the groups was measured by applying ‘F’-test, and to find out the exact location of difference, Post Hoc Test (Least Significant Difference) was applied. It was found from the study that only flexibility showed significant difference among three types of warm-up exercise. The observed result depicted that VR has more impact on myofascial release in flexibility in comparison with NVR and stretching as a part of warm-up exercise as ‘p’ value was less than 0.05. In the present study, within the three means of warm-up exercises, vibration roller showed better mean difference in terms of NVR, and static stretching exercise on functional fitness of young physical education practitioners, although the results were found insignificant in case of muscle strength, agility, static and dynamic balance of the lower extremity. These findings suggest that sports professionals and coaches may take VR into account for designing more efficient and effective pre-performance routine for long term to improve exercise performances. VR has high potential to interpret into an on-field practical application means.

Numerical Study of Bubbling Fluidized Beds Operating at Sub-atmospheric Conditions

Fluidization at vacuum pressure has been a topic that is of growing research interest. Several industrial applications (such as drying, extractive metallurgy, and chemical vapor deposition (CVD)) can potentially take advantage of vacuum pressure fluidization. Particularly, the fine chemical industry requires processing under safe conditions for thermolabile substances, and reduced pressure fluidized beds offer an alternative. Fluidized beds under vacuum conditions provide optimal conditions for treatment of granular materials where the reduced gas pressure maintains an operational environment outside of flammability conditions. The fluidization at low-pressure is markedly different from the usual gas flow patterns of atmospheric fluidization. The different flow regimes can be characterized by the dimensionless Knudsen number. Nevertheless, hydrodynamics of bubbling vacuum fluidized beds has not been investigated to author’s best knowledge. In this work, the two-fluid numerical method was used to determine the impact of reduced pressure on the fundamental properties of a fluidized bed. The slip flow model implemented by Ansys Fluent User Defined Functions (UDF) was used to determine the interphase momentum exchange coefficient. A wide range of operating pressures was investigated (1.01, 0.5, 0.25, 0.1 and 0.03 Bar). The gas was supplied by a uniform inlet at 1.5Umf and 2Umf. The predicted minimum fluidization velocity (Umf) shows excellent agreement with the experimental data. The results show that the operating pressure has a notable impact on the bed properties and its hydrodynamics. Furthermore, it also shows that the existing Gorosko correlation that predicts bed expansion is not applicable under reduced pressure conditions.

Design of an Ensemble Learning Behavior Anomaly Detection Framework

Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Development of Requirements Analysis Tool for Medical Autonomy in Long-Duration Space Exploration Missions

Improving resources for medical autonomy of astronauts in prolonged space missions, such as a Mars mission, requires not only technology development, but also decision-making support systems. The Advanced Crew Medical System - Medical Condition Requirements study, funded by the Canadian Space Agency, aimed to create knowledge content and a scenario-based query capability to support medical autonomy of astronauts. The key objective of this study was to create a prototype tool for identifying medical infrastructure requirements in terms of medical knowledge, skills and materials. A multicriteria decision-making method was used to prioritize the highest risk medical events anticipated in a long-term space mission. Starting with those medical conditions, event sequence diagrams (ESDs) were created in the form of decision trees where the entry point is the diagnosis and the end points are the predicted outcomes (full recovery, partial recovery, or death/severe incapacitation). The ESD formalism was adapted to characterize and compare possible outcomes of medical conditions as a function of available medical knowledge, skills, and supplies in a given mission scenario. An extensive literature review was performed and summarized in a medical condition database. A PostgreSQL relational database was created to allow query-based evaluation of health outcome metrics with different medical infrastructure scenarios. Critical decision points, skill and medical supply requirements, and probable health outcomes were compared across chosen scenarios. The three medical conditions with the highest risk rank were acute coronary syndrome, sepsis, and stroke. Our efforts demonstrate the utility of this approach and provide insight into the effort required to develop appropriate content for the range of medical conditions that may arise.

Investigation of Flow Characteristics on Upstream and Downstream of Orifice Using Computational Fluid Dynamics

The main parameter of the orifice hole diameter was designed according to the range of throttle diameter ratio which gave the required discharge coefficient. The discharge coefficient is determined by difference diameter ratios. The value of discharge coefficient is 0.958 occurred at throttle diameter ratio 0.5. The throttle hole diameter is 80 mm. The flow analysis is done numerically using ANSYS 17.0, computational fluid dynamics. The flow velocity was analyzed in the upstream and downstream of the orifice meter. The downstream velocity of non-standard orifice meter is 2.5% greater than that of standard orifice meter. The differential pressure is 515.379 Pa in standard orifice.

A Weighted Group EI Incorporating Role Information for More Representative Group EI Measurement

Emotional intelligence (EI) is a well-established personal characteristic. It has been viewed as a critical factor which can influence an individual's academic achievement, ability to work and potential to succeed. When working in a group, EI is fundamentally connected to the group members' interaction and ability to work as a team. The ability of a group member to intelligently perceive and understand own emotions (Intrapersonal EI), to intelligently perceive and understand other members' emotions (Interpersonal EI), and to intelligently perceive and understand emotions between different groups (Cross-boundary EI) can be considered as Group emotional intelligence (Group EI). In this research, a more representative Group EI measurement approach, which incorporates the information of the composition of a group and an individual’s role in that group, is proposed. To demonstrate the claim of being more representative Group EI measurement approach, this study adopts a multi-method research design, involving a combination of both qualitative and quantitative techniques to establish a metric of Group EI. From the results, it can be concluded that by introducing the weight coefficient of each group member on group work into the measurement of Group EI, Group EI will be more representative and more capable of understanding what happens during teamwork than previous approaches.

Pathogenic Bacteria Isolated from Diseased Giant Freshwater Prawn in Shrimp Culture Ponds

Pathogenic bacterial flora was isolated from giant freshwater prawns, Macrobrachium rosenbergii. Infected shrimp samples were collected from BuaBan Aquafarm in Kalasin Province, Thailand, between June and September 2018. Bacterial species were isolated by serial dilution and plated on Thiosulfate Citrate Bile Salt Sucrose (TCBS) agar medium. A total 89 colonies were isolated and identified using the API 20E biochemical tests. Results showed the presence of genera Aeromonas, Citrobacter, Chromobacterium, Providencia, Pseudomonas, Stenotrophomonas and Vibrio. Maximum number of species was recorded in Pseudomonas (50.57%) with minimum observed in Chromobacterium and Providencia (1.12%).

Modified Hybrid Genetic Algorithm-Based Artificial Neural Network Application on Wall Shear Stress Prediction

Prediction of wall shear stress in a rectangular channel, with non-homogeneous roughness distribution, was studied. Estimation of shear stress is an important subject in hydraulic engineering, since it affects the flow structure directly. In this study, the Genetic Algorithm Artificial (GAA) neural network is introduced as a hybrid methodology of the Artificial Neural Network (ANN) and modified Genetic Algorithm (GA) combination. This GAA method was employed to predict the wall shear stress. Various input combinations and transfer functions were considered to find the most appropriate GAA model. The results show that the proposed GAA method could predict the wall shear stress of open channels with high accuracy, by Root Mean Square Error (RMSE) of 0.064 in the test dataset. Thus, using GAA provides an accurate and practical simple-to-use equation.

A Recognition Method of Ancient Yi Script Based on Deep Learning

Yi is an ethnic group mainly living in mainland China, with its own spoken and written language systems, after development of thousands of years. Ancient Yi is one of the six ancient languages in the world, which keeps a record of the history of the Yi people and offers documents valuable for research into human civilization. Recognition of the characters in ancient Yi helps to transform the documents into an electronic form, making their storage and spreading convenient. Due to historical and regional limitations, research on recognition of ancient characters is still inadequate. Thus, deep learning technology was applied to the recognition of such characters. Five models were developed on the basis of the four-layer convolutional neural network (CNN). Alpha-Beta divergence was taken as a penalty term to re-encode output neurons of the five models. Two fully connected layers fulfilled the compression of the features. Finally, at the softmax layer, the orthographic features of ancient Yi characters were re-evaluated, their probability distributions were obtained, and characters with features of the highest probability were recognized. Tests conducted show that the method has achieved higher precision compared with the traditional CNN model for handwriting recognition of the ancient Yi.

Segmentation of Arabic Handwritten Numeral Strings Based on Watershed Approach

Arabic offline handwriting recognition systems are considered as one of the most challenging topics. Arabic Handwritten Numeral Strings are used to automate systems that deal with numbers such as postal code, banking account numbers and numbers on car plates. Segmentation of connected numerals is the main bottleneck in the handwritten numeral recognition system.  This is in turn can increase the speed and efficiency of the recognition system. In this paper, we proposed algorithms for automatic segmentation and feature extraction of Arabic handwritten numeral strings based on Watershed approach. The algorithms have been designed and implemented to achieve the main goal of segmenting and extracting the string of numeral digits written by hand especially in a courtesy amount of bank checks. The segmentation algorithm partitions the string into multiple regions that can be associated with the properties of one or more criteria. The numeral extraction algorithm extracts the numeral string digits into separated individual digit. Both algorithms for segmentation and feature extraction have been tested successfully and efficiently for all types of numerals.

Modified Plastic-Damage Model for Fiber Reinforced Polymer-Confined Repaired Concrete Columns

Concrete Damaged Plasticity Model (CDPM) is capable of modeling the stress-strain behavior of confined concrete. Nevertheless, the accuracy of the model largely depends on its parameters. To date, most research works mainly focus on the identification and modification of the parameters for fiber reinforced polymer (FRP) confined concrete prior to damage. And, it has been established that the FRP-strengthened concrete behaves differently to FRP-repaired concrete. This paper presents a modified plastic damage model within the context of the CDPM in ABAQUS for modelling of a uniformly FRP-confined repaired concrete under monotonic loading. The proposed model includes infliction damage, elastic stiffness, yield criterion and strain hardening rule. The distinct feature of damaged concrete is elastic stiffness reduction; this is included in the model. Meanwhile, the test results were obtained from a physical testing of repaired concrete. The dilation model is expressed as a function of the lateral stiffness of the FRP-jacket. The finite element predictions are shown to be in close agreement with the obtained test results of the repaired concrete. It was observed from the study that with necessary modifications, finite element method is capable of modeling FRP-repaired concrete structures.