A Study on Developing the Kadazandusun Commercial and Industrial Community (KCIC) in Sabah, Malaysia

The creation of a Bumiputera Commercial and Industrial Community was formulated to achieve the second strategy of the New Economic Policy, which was removing the identification of race with major economic function. Through this concept an exploratory research on the creation of a Kadazandusun Commercial and Industrial Community was made to enable the Kadazandusun community to be at par with other communities by the year 2020. The first two objectives of this study determined the current level of involvement of the Kadazandusun in commercial and industrial activities and identifying current entrepreneurship development programmes. From the secondary data, the Kadazandusun controls less than 17 percent of the 9 economic sectors used as a basis for comparison for current economic performance and were not aware of entrepreneurship development programmes. In accessing the strengths, wealmesses, opportunities and threats facing the community a questionnaire survey was cond ucted . Data processing included both qualitative and quantit.ative method. Five groups representing the cultural community characteristics namely awareness, information: psychological> culture and manpower development were identified through factor analysis and acted as independent variables towards community's information awareness, knowledge regarding available loans, administration and management, networking, market share, manpower development and financial management in the regression analysis. Using situational analysis, Strategic factors Analysis Summary Matrix revealed strategic factors for the development of Kadazandusun community. Strategic strength factors were "Bumiputera Status", "Largest Bumiputera Group" and "Government Development Programmes", while the major weaknesses were "Motivation", "Access to Business Information", and "Management Skills". Whereas opportunities were represented by "Kota Kinabalu Industrial Park", "Access to Loans" and "Government Policies". The threat factors were "Competition from Other Communities", and "poatics".An "lnformation Center" was recommended to be set-up by the Kadazandusun Chamber of Commerce and lndustry to help entrepreneurs in terms of management skills, financial management, information management, quality development, strategic networking, business development, technology development and fulfilling human resources needs. Institutions dealing in business consultancy, entrepreneurship development programme, information technology, training and funding were also recommended in the proposed model. These key factors will- produced genuine entrepreneurs of quality and resilient to challenges, competitive in all potential area of economic growth, able to cultivate entrepreneurship culture, and capable of developing and nurturing the Kadazandusun community's capabilities in businesses and pursue the nation's industrialisation's goals as envisaged in Vision 2020

Semantic Federation of Musical and Music-Related Information for Establishing a Personal Music Knowledge Base

Music is perceived and described very subjectively by every individual. Nowadays, people often get lost in their steadily growing, multi-placed, digital music collection. Existing music player and management applications get in trouble when dealing with poor metadata that is predominant in personal music collections. There are several music information services available that assist users by providing tools for precisely organising their music collection, or for presenting them new insights into their own music library and listening habits. However, it is still not the case that music consumers can seamlessly interact with all these auxiliary services directly from the place where they access their music individually. To profit from the manifold music and music-related knowledge that is or can be available via various information services, this information has to be gathered up, semantically federated, and integrated into a uniform knowledge base that can personalised represent this data in an appropriate visualisation to the users. This personalised semantic aggregation of music metadata from several sources is the gist of this thesis. The outlined solution particularly concentrates on users’ needs regarding music collection management which can strongly alternate between single human beings. The author’s proposal, the personal music knowledge base (PMKB), consists of a client-server architecture with uniform communication endpoints and an ontological knowledge representation model format that is able to represent the versatile information of its use cases. The PMKB concept is appropriate to cover the complete information flow life cycle, including the processes of user account initialisation, information service choice, individual information extraction, and proactive update notification. The PMKB implementation makes use of SemanticWeb technologies. Particularly the knowledge representation part of the PMKB vision is explained in this work. Several new Semantic Web ontologies are defined or existing ones are massively modified to meet the requirements of a personalised semantic federation of music and music-related data for managing personal music collections. The outcome is, amongst others, • a new vocabulary for describing the play back domain, • another one for representing information service categorisations and quality ratings, and • one that unites the beneficial parts of the existing advanced user modelling ontologies. The introduced vocabularies can be perfectly utilised in conjunction with the existing Music Ontology framework. Some RDFizers that also make use of the outlined ontologies in their mapping definitions, illustrate the fitness in practise of these specifications. A social evaluation method is applied to carry out an examination dealing with the reutilisation, application and feedback of the vocabularies that are explained in this work. This analysis shows that it is a good practise to properly publish Semantic Web ontologies with the help of some Linked Data principles and further basic SEO techniques to easily reach the searching audience, to avoid duplicates of such KR specifications, and, last but not least, to directly establish a \"shared understanding\". Due to their project-independence, the proposed vocabularies can be deployed in every knowledge representation model that needs their knowledge representation capacities. This thesis added its value to make the vision of a personal music knowledge base come true.:1 Introduction and Background 11 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.2 Personal Music Collection Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2 Music Information Management 17 2.1 Knowledge Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.1.1 Knowledge Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.1.1.1 Knowledge Representation Models . . . . . . . . . . . . . . . . . 18 2.1.1.2 Semantic Graphs . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.1.1.3 Ontologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.1.1.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.1.2 Knowledge Management Systems . . . . . . . . . . . . . . . . . . . . . . . 19 2.1.2.1 Information Services . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.1.2.2 Ontology-based Distributed Knowledge Management Systems . . 20 2.1.2.3 Knowledge Management System Design Guideline . . . . . . . . 21 2.1.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.2 Semantic Web Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.2.1 The Evolution of the World Wide Web . . . . . . . . . . . . . . . . . . . . . 22 Personal Music Knowledge Base Contents 2.2.1.1 The Hypertext Web . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.2.1.2 The Normative Principles of Web Architecture . . . . . . . . . . . 23 2.2.1.3 The Semantic Web . . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.2.2 Common Semantic Web Knowledge Representation Languages . . . . . . 25 2.2.3 Resource Description Levels and their Relations . . . . . . . . . . . . . . . 26 2.2.4 Semantic Web Knowledge Representation Models . . . . . . . . . . . . . . 29 2.2.4.1 Construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.2.4.2 Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.2.4.3 Context Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 2.2.4.4 Storing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 2.2.4.5 Providing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 2.2.4.6 Consuming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 2.2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 2.3 Music Content and Context Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.3.1 Categories of Musical Characteristics . . . . . . . . . . . . . . . . . . . . . 37 2.3.2 Music Metadata Formats . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 2.3.3 Music Metadata Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 2.3.3.1 Audio Signal Carrier Indexing Services . . . . . . . . . . . . . . . . 41 2.3.3.2 Music Recommendation and Discovery Services . . . . . . . . . . 42 2.3.3.3 Music Content and Context Analysis Services . . . . . . . . . . . 43 2.3.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 2.4 Personalisation and Environmental Context . . . . . . . . . . . . . . . . . . . . . . 44 2.4.1 User Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 2.4.2 Context Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 2.4.3 Stereotype Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 3 The Personal Music Knowledge Base 48 3.1 Foundations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.1.1 Knowledge Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.1.2 Knowledge Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3.2 Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.3 Workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.3.1 User Account Initialisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.3.2 Individual Information Extraction . . . . . . . . . . . . . . . . . . . . . . . . 53 3.3.3 Information Service Choice . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 3.3.4 Proactive Update Notification . . . . . . . . . . . . . . . . . . . . . . . . . . 55 3.3.5 Information Exploration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 3.3.6 Personal Associations and Context . . . . . . . . . . . . . . . . . . . . . . . 56 3.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 4 A Personal Music Knowledge Base 57 4.1 Knowledge Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 4.1.1 The Info Service Ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 4.1.2 The Play Back Ontology and related Ontologies . . . . . . . . . . . . . . . . 61 4.1.2.1 The Ordered List Ontology . . . . . . . . . . . . . . . . . . . . . . 61 4.1.2.2 The Counter Ontology . . . . . . . . . . . . . . . . . . . . . . . . . 62 4.1.2.3 The Association Ontology . . . . . . . . . . . . . . . . . . . . . . . 64 4.1.2.4 The Play Back Ontology . . . . . . . . . . . . . . . . . . . . . . . . 65 4.1.3 The Recommendation Ontology . . . . . . . . . . . . . . . . . . . . . . . . 69 4.1.4 The Cognitive Characteristics Ontology and related Vocabularies . . . . . . 72 4.1.4.1 The Weighting Ontology . . . . . . . . . . . . . . . . . . . . . . . 72 4.1.4.2 The Cognitive Characteristics Ontology . . . . . . . . . . . . . . . 73 4.1.4.3 The Property Reification Vocabulary . . . . . . . . . . . . . . . . . 78 4.1.5 The Media Types Taxonomy . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 4.1.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.2 Knowledge Management System . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 5 Personal Music Knowledge Base in Practice 87 5.1 Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.1.1 AudioScrobbler RDF Service . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.1.2 PMKB ID3 Tag Extractor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 5.2 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 5.2.1 Reutilisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 5.2.2 Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 5.2.3 Reviews and Mentions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 5.2.4 Indexing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 5.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 6 Conclusion and Future Work 93 6.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 6.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Sport Fish Research in Illinois: A Look Inside Sport Fish Restoration Fund Project F-69-R

Executive Summary: For over 75 years, the Federal Aid in Sport Fish Restoration Fund has worked with state partners to conserve, protect, and enhance fish and their habitats, along with the sport fishing and recreational boating opportunities they provide. During more than a third of the existence of this important conservation program, Project F-69-R has been the cornerstone for collection and analysis of Illinois fisheries data, with a specific focus through much of its existence on understanding the interface between recreational anglers and the recreational fisheries on which they depend. F-69-R has produced a wide array of groundbreaking research findings, supported modern advancements in fisheries management, and implemented state-of-the-art technologies for fisheries data management. Most recently, this project has opened the door to connect resource users with data-driven information about Illinois fisheries through the use of emergent Internet technologies.In its first few years, Project F-69-R was tasked with developing an efficient method for conducting regular creel surveys on inland lakes in Illinois. Additionally, several research studies led to improvements in sampling design and a better understand-ing of how the efficiency of sampling gear used by fisheries managers is affected by environmental conditions. The design and implementation of creel surveys and more effective sampling was supported by what was, at the time, a cutting-edge computer-ized system for storing and analyzing fisheries data, the Fisheries Analysis System (FAS). This system became the single tool used by fisheries managers and researchers alike to tap into valuable information about sport fish populations across the state. Illinois emerged as a leader in fisheries data management through the development of FAS, serving as a model for other states to develop their own systems.From 1992 – 2009, Project F-69-R was focused on the execution of inland creel surveys, producing 334 lake and river creel surveys that have played a major role in fisheries management decisions, such as setting size and bag limits, informing supple-mental stocking strategies, and identifying needs for habitat improvement. Data from those creel surveys has been utilized by other Federal Aid Projects as well. For example, a project evaluating the effectiveness of stocking largemouth bass at certain sizes and anther project evaluating the regulation and stocking strategies designed to improve stunted bluegill populations were among the many projects that utilized creel survey data on study lakes. The combination of managing long-term fisheries data and addressing emerging research needs continues to be the corner-stone of Project F-69-R today. In the last three years, the breadth of research topics has expanded to include an evaluation of urban stream restoration on the DuPage River (p. 4–5), an in-depth investigation into largemouth bass recruitment dynamics as affected by spring angling (p. 6–7), an assessment of land-use practices and their impacts through the Fishes of Champaign County study (p. 8), and an investigation into natural reproduction of lake trout in southern Lake Michigan (p. 10). Bringing this information back to the angler has been a key component of Project F-69-R for the last 10 years through the creation of IFishIllinois.org and its social media counterparts (p. 9).A bright and exciting future is unfolding for the Sport Fish Restoration Program, and F-69-R is a central piece of that future in Illinois. Within these pages is a snapshot of the many contributions this project has made to sustaining sport fish populations in Illinois. As this project evolves to answer more complex, data-driven research questions to inform fisheries management decisions, anglers in Illinois will have access to a wide array of sustainable fisheries for generations to come.Good Fishing! Dr. Jeffrey A. Stein, Project LeaderSenior Research ScientistIllinios Natural History SurveyUS Fish and Wildlife Service/IL Department of Natural ResourcesOpe

Model Simulation for the Spread of Rabies in Sarawak, Malaysia

There is a growing concern over the ongoing rabies epidemic in Sarawak that has remain unresolved ever since the outbreak began in July 2017. As of today, there has been 18 positive human rabies cases reported, which includes 17 fatalities, and one survivor who is now on life support after a severe neurological complications. Subsequently, the death rate now stands at approximately 94%. This paper is a preliminary report on the simulation of rabies transmission dynamics in Sarawak. At present, research is still lacking on the disease dynamics of rabies in Malaysia particularly in the state of Sarawak. We propose here a deterministic, compartmental model with SEIRS framework to fit actual data on the number of human infected rabies cases in Sarawak from June 2017 to January 2019. The simulation predicts that rabies in Sarawak will persist even with the current outbreak management and control efforts. Further, sensitivity analysis showed that dog vaccination rate is the most influential parameter and the basic reproduction number is estimated to be higher than 1. Henceforth, there is a need to increase the access to dog vaccines especially in remote rural areas with lack of health facilities. Our findings also suggest that controlling dog births could prevent the spread of  rabies from perpetuating in the state. Neutering or using other fertility control methods would reduce the input of new susceptible domestic dogs into the population while Trap-Neuter-Vaccinate-Release (TNVR) method can be implemented to control new births of free-roaming strays. In summary, increasing the coverage of dog vaccination and reducing the number newborn dogs would be the more effective strategies to manage the current rabies outbreak in Sarawak

Measuring usability for application software using the quality in use integration measurement model

User interfaces of application software are designed to make user interaction as efficient and as simple as possible. Market accessibility of any application software is determined by the usability of its user interfaces. A poorly designed user interface will have little value no matter how powerful the program is. Thus, it is significantly important to measure usability during the system development lifecycle in order to avoid user disappointment. Various methods and standards that help measure usability have been developed. However, these methods define usability inconsistently, which makes software engineers hesitant in implementing these methods or standards. The Quality in Use Integrated Measurement (QUIM) model is a consolidated approach for measuring usability through 10 factors, 26 criteria, and 127 metrics. It decomposes usability into factors, criteria, and metrics, and it is a hierarchical model that helps developers with no or little background of usability metrics. Among 127 metrics of QUIM, essential efficiency (EE) is the most specific metric used to measure the usability of user interfaces through an equation. This study involves a comparative analysis between three case studies that use the QUIM model to measure usability in terms of EE for three case studies: (1) Public University Registration System, (2) Restaurant Menu Ordering System, and (3) ATM system. A comparison is made based on the percentage of EE for each element of the use cases in each use case diagram. The results obtained revealed that the user interface design for Restaurant Menu Ordering System scored the highest percentage of EE, thus proving to be the most user-friendly application software among its counterparts

Grounded Theory as an approach to studying students’ uses of learning management systems

This paper presents the first phase of a qualitative study of students’ use of a Learning Management System (LMS). A group of students at Kingston University with experience of two different systems were afforded the opportunity to study the relationship between the interface to an LMS and the usability of the system

The Medicare Physician Group Practice Demonstration: Lessons Learned on Improving Quality and Efficiency in Health Care

Discusses the experiences of ten large practices earning performance payments for improving the quality and cost-efficiency of health care delivered to Medicare fee-for-service beneficiaries

Generating Aspect-oriented Multi-document Summarization with Event-Aspect Model

In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sentences into aspects. We then use extended LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Programming for sentence selection. Key features of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantitative evaluation based on Rouge metric demonstrates the effectiveness and advantages of our method.