A Comparative Study of Student Motivation for Learning Science and Science Achievement in The English and Thai Programs at Mathayomwatsing School in Bangkok, Thailand

The purpose of this study was to explore the relationship betweenstudent motivation for learning science and science achievement of 55 mathayom 3 students in the English and Thai Programs at Mathayomwatsing School in Bangkok, Thailand. This study employed a quantitative methodology employing both a questionnaire as well as “O” Net scores to address the research objectives. The study had six objectives which were 1) To determine the level of student motivation for learning science in the English Program at Mathayomwatsing school, in Bangkok, Thailand. 2) To determine the level of student motivation for learning science in the Thai Program at Mathayomwatsing school, Bangkok, Thailand. 3) To find the correlation between student motivation for learning science and science achievement in the English Program at Mathayomwatsing school in Bangkok, Thailand. 4) To find the correlation between student motivation for learning science and science achievement in the Thai Program at Mathayomwatsing school in Bangkok, Thailand. 5) To compare student motivation for learning science betweenstudents in the English and Thai programs at Mathayomwatsing school in Bangkok, Thailand. 6) To compare science achievement between students in the English and Thai programs at Mathayomwatsing school in Bangkok, Thailand. The researchfindings were the level of student motivation for learning science in the English and Thai Programs at Mathayomwatsing School in Bangkok, Thailand were “rarely to sometimes” motivated and there was a significant relationship between student motivation for learning and the student science achievement in the English and Thai Programs at Mathayomwatsing School in Bangkok, Thailand. There was no significant difference of student motivation for learning science and science achievement between students in the English and Thai programs at Mathayomwatsing School in Bangkok, Thailand

A GENERIC ARCHITECTURE FOR INSIDER MISUSE MONITORING IN IT SYSTEMS

Intrusion Detection Systems (IDS) have been widely deployed within many organisations' IT nenvorks to delect network penetration attacks by outsiders and privilege escalation attacks by insiders. However, traditional IDS are ineffective for detecting o f abuse o f legitimate privileges by authorised users within the organisation i.e. the detection of misfeasance. In essence insider IT abuse does not violate system level controls, yet violates acceptable usage policy, business controls, or code of conduct defined by the organisation. However, the acceptable usage policy can vary from one organisation to another, and the acceptability o f user activities can also change depending upon the user(s), application, machine, data, and other contextual conditions associated with the entities involved. The fact that the perpetrators are authorised users and that the insider misuse activities do not violate system level controls makes detection of insider abuse more complicated than detection o f attacks by outsiders. The overall aim o f the research is to determine novel methods by which monitoring and detection may be improved to enable successful detection of insider IT abuse. The discussion begins with a comprehensive investigation o f insider IT misuse, encompassing the breadth and scale of the problem. Consideration is then given to the sufficiency of existing safeguards, with the conclusion that they provide an inadequate basis for detecting many o f the problems. This finding is used as the justification for considering research into alternative approaches. The realisation of the research objective includes the development of a taxonomy for identification o f various levels within the system from which the relevant data associated with each type of misuse can be collected, and formulation of a checklist for identification of applications that requires misfeasor monitoring. Based upon this foundation a novel architecture for monitoring o f insider IT misuse, has been designed. The design offers new analysis procedures to be added, while providing methods to include relevant contextual parameters from dispersed systems for analysis and reference. The proposed system differs from existing IDS in the way that it focuses on detecting contextual misuse of authorised privileges and legitimate operations, rather than detecting exploitation o f network protocols and system level \ailnerabilities. The main concepts of the new architecture were validated through a proof-of-concept prototype system. A number o f case scenarios were used to demonstrate the validity of analysis procedures developed and how the contextual data from dispersed databases can be used for analysis of various types of insider activities. This helped prove that the existing detection technologies can be adopted for detection o f insider IT misuse, and that the research has thus provided valuable contribution to the domain

Efficient Labelling of Pedestrian Supervisions

Object detection is a fundamental goal to achieve intelligent visual perception by computers due to the fact that objects are the basic building blocks to achieve higher level image understanding. Among the numerous categories of objects in the real-world, pedestrians are among the most important due to several potential benefits brought about by successful pedestrian detection. Often, pedestrian detectors are trained in state-of-the-art systems using supervised machine learning algorithms which necessitates costly and often tedious manual annotation of pedestrians in the form of precise bounding boxes. In this paper, a novel weakly supervised learning algorithm is proposed to train a pedestrian detector that requires, instead of bounding boxes, only annotations of estimated centres of pedestrians. The algorithm makes use of a pedestrian prior learnt in an unsupervised way from the video and this prior is fused with the given weak supervision information in a systematic manner. By evaluating on publicly available datasets, we demonstrate that our weakly supervised algorithm reduces the cost of manual annotation of pedestrians by more than four times while achieving similar performance to a pedestrian detector trained with standard bounding box annotations

Prevalence of job stress among non-academic staff of International Islamic University Malaysia (IIUM) Kuantan campus

Objective: Job stress is one of the most important health issues concerning globally and locally. Job stress affects both physical and mental wellbeing and also effects to work output. The aim of this study was to measure prevalence of job stress among non-academic staff of International Islamic University Malaysia, Kuantan Campus. Methods: Cross sectional study design was used with sample size of 222 non-academic staffs. Participants were identified through multistage stratified random sampling and face-to-face interviewed by using validated self-administered questionnaire that includes background characteristics such as age, gender, smoking, occupational level and marital status; and job using stress identified Job Content Questionnaire (JCQ) in bilingual version. Univariate analyses were conducted using the prevalence and 95% CI. Results: Prevalence of job stress among IIUM Kuantan Campus’ non-academic staffs was 18.5% (95% CI: 13.8-24.0). The mean age for job stress was 32.5 (7.9) years old. Prevalence of job stress was found higher in female (20.7%), non-smoker (19.0%) and those who are single (19.7%). As for occupational level, respondents who were categorized under Grade C have the highest prevalence of job stress which was 20.0%. Conclusion: Prevalence of job stress among IIUM non-academic staffs was lower compared to other studies in Malaysia

Essays on Carbon Dioxide Emissions

内容の要約博士(学術)Doctor of Philosophy広島大

Efficient non-iterative domain adaptation of pedestrian detectors to video scenes

Pedestrian detection is an essential step in many important applications of Computer Vision. Most detectors require manually annotated ground-truth to train, the collection of which is labor intensive and time-consuming. Generally, this training data is from representative views of pedestrians captured from a variety of scenes. Unsurprisingly, the performance of a detector on a new scene can be improved by tailoring the detector to the specific viewpoint, background and imaging conditions of the scene. Unfortunately, for many applications it is not practical to acquire this scene-specific training data by hand. In this paper, we propose a novel algorithm to automatically adapt and tune a generic pedestrian detector to specific scenes which may possess different data distributions than the original dataset from which the detector was trained. Most state-of-the-art approaches can be inefficient, require manually set number of iterations to converge and some form of human intervention. Our algorithm is a step towards overcoming these problems and although simple to implement, our algorithm exceeds state-of-the-art performance

Comparison On Knowledge, Attitude And Practice Of Betel Nut Chewing Habit Between Blind And Normal People In Yangon, Myanmar

Originated from the Southeast Asia region, the betel nut chewing habits prevailed through immigration to other regions such as India, Taiwan, southern China, South Pacific Islands, and even to the Europe. The use of smokeless tobacco as betel nut with tobacco is highly prevalent in Myanmar compared with other countries. The misconception of smokeless tobacco use is less dangerous than tobacco smoking is a big challenge to the tobacco control measures. Then, a crosssectional study on comparison of knowledge, attitude and practice of betel chewing habit with structured questionnaire to two groups: normal group and blind group (n = 78) in Yangon, Myanmar is conducted. The selection criteria is having a history of taking betel quid regardless of race, sex, marital status in School for the Blind and normal individuals in Yangon region. 87% of male and 12.8% of female gender ranging from age 18 to 35 years participated in the study. The results show that there is no strong significantly difference in knowledge, attitude and practice on betel chewing habit of two groups even though they are different in learning a behavior according to their different physical abilities. However, the study assures that their knowledge on betel quid has been satisfactory and they are still addicting to this habit due to their favorable surrounding environment like betel quid shops, family member users and socialization by friends. Therefore the supply of betel quid ingredients especially tobacco should be regulated strictly by government procedure and specific health promotion plan for disabled person as well as the social support system like behavioral therapy to already addicted one should be promoted

Adapting pedestrian detectors to new domains: A comprehensive review.

Successful detection and localisation of pedestrians is an important goal in computer vision which is a core area in Artificial Intelligence. State-of-the-art pedestrian detectors proposed in literature have reached impressive performance on certain datasets. However, it has been pointed out that these detectors tend not to perform very well when applied to specific scenes that differ from the training datasets in some ways. Due to this, domain adaptation approaches have recently become popular in order to adapt existing detectors to new domains to improve the performance in those domains. There is a real need to review and analyse critically the state-of-the-art domain adaptation algorithms, especially in the area of object and pedestrian detection. In this paper, we survey the most relevant and important state-of-the-art results for domain adaptation for image and video data, with a particular focus on pedestrian detection. Related areas to domain adaptation are also included in our review and we make observations and draw conclusions from the representative papers and give practical recommendations on which methods should be preferred in different situations that practitioners may encounter in real-life