Analysis of Hepatitis C Viral Dynamics Using Latin Hypercube Sampling

We consider a mathematical model comprising of four coupled ordinary differential equations (ODEs) for studying the hepatitis C (HCV) viral dynamics. The model embodies the efficacies of a combination therapy of interferon and ribavirin. A condition for the stability of the uninfected and the infected steady states is presented. A large number of sample points for the model parameters (which were physiologically feasible) were generated using Latin hypercube sampling. Analysis of our simulated values indicated approximately 24% cases as having an uninfected steady state. Statistical tests like the chi-square-test and the Spearman's test were also done on the sample values. The results of these tests indicate a distinctly differently distribution of certain parameter values and not in case of others, vis-a-vis, the stability of the uninfected and the infected steady states

SYSTEM IDENTIFICATION AND PARAMETRIC ESTIMATION OF INFERENTIAL CORIOLIS

Metering technology offers a number of possible options for the measurement of compressible natural gas (CNG). However, the accuracy of these measurements is dependent on various dynamic factors and fluid parameters. To avoid flow measurement from such dynamic errors, a new technique or novel concept of flowmeter is needed for measuring CNG. One of the options is to use natural force phenomenon that could be derived from fundamental physics, a force known as coriolis. It is used in mass flowmeter design that uses vibration tubes to guide and measure fluid or gas based on coriolis force. The motivation behind the research is to develop and apply coriolis in an embedded FieldPoint controller proclaimed as an inferential coriolis. The major challenge is to find a suitable algorithm for coriolis in the form of a mathematical model that could measure mass and mass flowrate of CNG with maximum permissible error. To define such system, an experimental approach known as System Identification (SYSID) theory is used. Performance of inferential coriolis is tested on experimental natural gas test rig which could be summarized into three areas: single pressure flow; continuous pressure flow; multi pressure flow with disturbances. When experiment was conducted, mass flowrate was measured using inferential coriolis and a commercial flowmeter from a manufacturer i.e., Micro Motion. To validate both methods, a load cell was used as the reference. Details evaluations of three pressure flow scenarios namely the single pressure flow, the continuous pressure flow, and the multi pressure flow for a CNG refueling system are presented. From percentage error analyses, it shows that in all measurements the inferential coriolis have less error compares to commercial coriolis manufactured by Micro Motion. The findings demonstrate the viability of the SYSID approach to provide a solution to the modeling of an inferential coriolis, and confirm the qualitative behavior of the inferential coriolis in response to the different flow measurements

Switching Time Optimization via Time Optimal Control for Natural Gas Vehicle Refueling

The implementation of Natural Gas Vehicle (NGV) refueling system using multipressure storage source requires a suitable controller to be developed. In this thesis, a refueling algorithm using Time Optimal Control (TOC) technique is proposed as a basis for determining the optimal switching time in NGV refueling using the mass and mass flowrate as the state variables, measured using Coriolis flowmeter. In order to implement TOC in actual NGV refueling process, a fully instrumented NGV laboratory test facility was designed and commissioned which includes three main parts: the NGV test rig, the Data Acquisition (DAQ) & Control System using FieldPoint, and the LabVIEW programming model. Performance measurements for experiments conducted at NGV test rig are based on two criteria, i. e., the refueling time and the total mass of natural gas stored. These become the performance measurements used to evaluate the performance of TOC and other NGV controller currently applied in the commercial NGV dispenser i. e., Kraus refueling algorithm. The performance of the refueling algorithms are evaluated based on three experiments: the first experiment is the performance of valves switching and refueling time transitions; the second experiment is the performance of refueling when the storage pressures are set to 3600 psig while the receiver tank is varied from 20 to 2000 psig; and the third experiment is the performance of refueling when the storage pressures are set to different pressures while the receiver tank is maintained at 20 psig. In conclusion, the results from the third experiment verifies the viability of TOC refueling compared to Kraus refueling to be used in NGV refueling using multi-pressure storage source, which average difference for refueling time and total mass loss are 25.33 seconds and 0.95 kg, respectively. By implementing the refueling algorithm in actual NGV refueling stations, it is expected to provide saving in term of the energy consumed by the compressor and contributing to the reduction in the NGV station congestion problem in the country

Business Intelligent Grading System Of Graduate Students

Not long ago, a corporate executive was adequate to justify a strategic business decision. Organizations such as educational institutions now are wrestling with larger and increasingly more complex databases. They are struggling to manage and update the wealth of information stored in departmental and schools databases. And today, executive management realizes that information from these databases needs to be streamlined to support the strategic business decision. Data analysis is required for both short- and long-term actions, and organizations want to be able to get that information from their databases easily and quickly. Without the proper tools, however, organizations will not be able to leverage one of their most important assets i.e. information. In this case, business intelligent technology can help an organization to overcome the above mention problem. Business intelligent is designed to improve an enterprise's ability to make good decisions. It makes necessary information available to all levels of the enterprise, from senior management to the knowledge worker. This project, "Business Intelligent Grading System of Graduate Students", has make use the technology of business intelligent to extract the data from grading system of graduate students for Master of Science (IT) by coursework program to capture the important solution i.e. useful information in form of chart/report with capability to make queries. The Groupware Business Intelligence has been used in implementing this project

Professional development among academic staff at selected Malaysian public universities: preliminary findings of the impact of the Basic Teaching Methodology Course (BTMC)

Despite the growing number of research findings that indicate the importance of professional development in academic teaching and learning, the visible impact of staff participation in professional development on effective teaching practices in Higher Education is not significant. As such, the Ministry of Higher Education of Malaysia has strongly urged the universities to sonduct the Basic Teaching Methodology Course (BTMC) for new academic staff. A self-administered questionnaire survey was carried out in four selected universities offering the BTMC. It was found that participants of the BTMC had positive perceptions about the course. They were happy for the oppurtunities offered by their respective universities to improve their knowledge and skills. They believed that the BTMC is useful in developing their academic potential. However, the study also found that the impact of the BTMC on actual teaching practices is minimal. This paper is a report of the findings of the study, and discusses the benefits and the extent to which the academic staff utilized the knowledge and skills learned from the BTMC

SYSTEM IDENTIFICATION AND PARAMETRIC ESTIMATION OF INFERENTIAL CORIOLIS

Metering technology offers a number of possible options for the measurement of compressible natural gas (CNG). However, the accuracy of these measurements is dependent on various dynamic factors and fluid parameters. To avoid flow measurement from such dynamic errors, a new technique or novel concept of flowmeter is needed for measuring CNG. One of the options is to use natural force phenomenon that could be derived from fundamental physics, a force known as coriolis. It is used in mass flowmeter design that uses vibration tubes to guide and measure fluid or gas based on coriolis force. The motivation behind the research is to develop and apply coriolis in an embedded FieldPoint controller proclaimed as an inferential coriolis. The major challenge is to find a suitable algorithm for coriolis in the form of a mathematical model that could measure mass and mass flowrate of CNG with maximum permissible error. To define such system, an experimental approach known as System Identification (SYSID) theory is used. Performance of inferential coriolis is tested on experimental natural gas test rig which could be summarized into three areas: single pressure flow; continuous pressure flow; multi pressure flow with disturbances. When experiment was conducted, mass flowrate was measured using inferential coriolis and a commercial flowmeter from a manufacturer i.e., Micro Motion. To validate both methods, a load cell was used as the reference. Details evaluations of three pressure flow scenarios namely the single pressure flow, the continuous pressure flow, and the multi pressure flow for a CNG refueling system are presented. From percentage error analyses, it shows that in all measurements the inferential coriolis have less error compares to commercial coriolis manufactured by Micro Motion. The findings demonstrate the viability of the SYSID approach to provide a solution to the modeling of an inferential coriolis, and confirm the qualitative behavior of the inferential coriolis in response to the different flow measurements

The Joint Effects of Personality and Behavioural Intentions on Academic Knowledge Productivity Behaviours

This current study investigates individual differences factors impacting the Knowledge Productivity Behaviour of academic. In this study academic knowledge productivity are defined as the capability with which individuals achieve creation and production of knowledge knowledge-based improvements, exploitation, and innovations through their knowledge activities. In this study the Big Five (B5) personality traits of openness, conscientiousness, extraversion, agreeableness and neuroticism are proposed to influence productivity. In addition, these personality traits are expected, at least in part, to have their effect mediated and moderate through variables associated with the Theory of Planned Behaviour (TPB). The methodology used in this study was quantitative in nature. A survey methodology was used with a Malaysian working academic sample. This study describes results to date from a pilot study, and the very beginning of analysis from main study, main study data (Time 1) and follow up data approximately a year after (Time 2) and a supplementary qualitative data. This study adopts a quantitative method and online questionnaires were used as the instruments for data collection. The on-line survey was administered by emailing potential respondents a link. Volunteer respondents were academics from Malaysia Public University (N=985). The descriptive analysis of the pilot, main data and one-year follow-up data was done using SPSS version 20. In particular, in main study and one-year follow-up data, estimating the path coefficients associated with specific hypotheses, indirect effects were estimated for the hypotheses which propose that TPB mediates personality effects on KPB, in order to determine whether the mediated effects are statistically significant. These were determined using path analysis conducted with an accepted SEM package such as MPlus. Overall in this study, all possible relationships among the set of five personalities (Big Five), the Theory of Planned Behaviour and Knowledge Productivity Behaviour (KPB), as well as KPB construct; Knowledge Acqusition (KA), Knowledge Sharing (KS) and Knowledge Transfer (KT) were estimated. These results support the preliminary hypotheses, however for the main study (Time 1 social science data) only openness, agreeableness and extraversion ii were reported significant with KPB. Meanwhile only Openness were reported significant with KPB in Time 2 social science data. As was reported in this study, all four of the TPB variables, i.e., Attitude, Norm Perceived Behavioural Control and Intention, have strong, positive, and statistically significant relationships with each other. However, Subjective Norms did not predict behavioural intentions for KPB. Moreover sub-models specified to test the Big Five relationship with TPB for their direct effects, predicting Emotional Stability and Openness traits on Attitude, both Time 1 and Time 2 models reported that only Openness variable had significant effects on Attitude. Furthermore, this study also estimated the interaction effects of Extraversion, Agreeableness and Conscientiousness with Subjective Norms and Perceived Behavioural Control on Intention. Nonetheless, these results indicate all of these hypotheses are not supported both in Time 1 and Time 2 models. Finally, a set of multi-group analyses performed to compare estimates from the two Time 1 samples (Social Science and Science Technology). The results show Openness to Social Norms path was significantly different in the two samples. In sum, based on the discussion of the outcomes, it is expected that this study will bring better understanding to the current knowledge and theoretically and empirically contribute to a bigger literature on Big Five personality traits and the Theory of Planned Behaviour. In addition, through this study, academics in Malaysia public university can take the opportunities to be more productive in Knowledge Productivity Behaviour. Apart from that, other theories such as understanding the concept of motivation can be added to this research. user satisfaction or university-industry-government relationships and measuring the effective of organisation as well for results of the academics KPB can be expanded to a further research and increased more details

Factors that influence parents' choice of pre-schools education in Malaysia: an exploratory study

The objective of this study is to identify the important factors contribute most to parents' choice of pre-school for their children. Parents' choice of pre-school is influenced by various factors that are mostly associated with the pre-school institution itself. Parent have different educational believes and preferences which puts them in a dilemma when making decision for their children pre-school education. it is important for pre-school businesses to meet the needs of both parents and children in order to attract and retain their customer. Data was collected using a survey questionnaire. The sample consisted of 162 parents who have pre-school children. Multiple regression analysis was used to identify the predictor variables that contributed to the choice of pre-schools. The main factors that influence parents' choice of pre-schools are branding, private-run institutions, safety and security, quality of teaching and hygiene. English medium and religion-based pre-schools are the preferred pre-schools chosen by these parents

Knowledge Level on Bagworm in Oil Palm and its Control Using Integrated Pest Management (IPM) Practices Among Independent Oil Palm Smallholders in Johor

Bagworm (Psychidae) and nettle caterpillars (Limacodidae) are among the major insect pests of oil palm in Malaysia. Bagworm from the species Metisa plana is the most destructive insect pests compared to nettle caterpillar in oil palm plantations. Outbreaks of bagworms were frequently occurred in various areas own by independent oil palm smallholders in Johor. At present, no scientific study has been conducted to indicate the level of knowledge among the independent oil palm smallholders on bagworm and its control, especially using the Integrated Pest Management (IPM) practices. Therefore, this study was conducted to determine knowledge level on bagworm and its control using IPM among 313 independent smallholders in three infestation areas in Johor, which are Mukim Chaah Bahru, Mukim Chaah, Mukim Paloh and Mukim Chamek. Data were collected by interview guided with a questionnaire consisting 23 questions regarding bagworm and its IPM practices. Most of the respondents are more than 51 years (61.1%), with 77.7% males and 22.3% females. They are mostly having primary (47.1%) and secondary (47.5%) school qualifications. This study found that most of the respondents have a basic understanding of bagworm in oil palm and its control measures using IPM practices, but their knowledge is still at a low level. Correlation analysis showed a significant relationship between the level of knowledge on bagworm and its control methods with race, education level and field management experience among the respondents. Therefore, more focus should be given by extension agents to enhance smallholder knowledge on bagworm management, especially in the potential and affected areas in Johor

Magnetic Analysis of Electromagnetic Microgenerator via Finite Element Analysis

In future, micro sensor system will be deployed throughout our environment for monitoring pur-pose. Powering system is becoming important factor for independent and long period deployment sensors in our environment (deploy and forgot)