Semantic Modeling of Analytic-based Relationships with Direct Qualification

Successfully modeling state and analytics-based semantic relationships of documents enhances representation, importance, relevancy, provenience, and priority of the document. These attributes are the core elements that form the machine-based knowledge representation for documents. However, modeling document relationships that can change over time can be inelegant, limited, complex or overly burdensome for semantic technologies. In this paper, we present Direct Qualification (DQ), an approach for modeling any semantically referenced document, concept, or named graph with results from associated applied analytics. The proposed approach supplements the traditional subject-object relationships by providing a third leg to the relationship; the qualification of how and why the relationship exists. To illustrate, we show a prototype of an event-based system with a realistic use case for applying DQ to relevancy analytics of PageRank and Hyperlink-Induced Topic Search (HITS).Comment: Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015

SNOMED CT standard ontology based on the ontology for general medical science

Background: Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT, hereafter abbreviated SCT) is acomprehensive medical terminology used for standardizing the storage, retrieval, and exchange of electronic healthdata. Some efforts have been made to capture the contents of SCT as Web Ontology Language (OWL), but theseefforts have been hampered by the size and complexity of SCT. Method: Our proposal here is to develop an upper-level ontology and to use it as the basis for defining the termsin SCT in a way that will support quality assurance of SCT, for example, by allowing consistency checks ofdefinitions and the identification and elimination of redundancies in the SCT vocabulary. Our proposed upper-levelSCT ontology (SCTO) is based on the Ontology for General Medical Science (OGMS). Results: The SCTO is implemented in OWL 2, to support automatic inference and consistency checking. Theapproach will allow integration of SCT data with data annotated using Open Biomedical Ontologies (OBO) Foundryontologies, since the use of OGMS will ensure consistency with the Basic Formal Ontology, which is the top-levelontology of the OBO Foundry. Currently, the SCTO contains 304 classes, 28 properties, 2400 axioms, and 1555annotations. It is publicly available through the bioportal athttp://bioportal.bioontology.org/ontologies/SCTO/. Conclusion: The resulting ontology can enhance the semantics of clinical decision support systems and semanticinteroperability among distributed electronic health records. In addition, the populated ontology can be used forthe automation of mobile health applications

Technology assessment of advanced automation for space missions

Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology

FESTivE: an information system method to improve product designers and environmental experts information exchanges

Effective collaboration between product designers and environmental experts is an important driver for the ecodesign practice in industry. This paper investigates the principal functions required for such an e ective collaboration and aims at facilitating them. Product designers should be able to integrate the environmental parameters into their activities, and to exchange information dynamically with the environmental expert whenever needed during the design process. Therefore, the IT system should be in itself dynamic and exible to the integration of new concepts (knowledge, software). Recent developments in Model Driven Engineering (MDE) are showing some interesting results to gain exibility and dynamism in the IT system. Combining software interoperability using model federation based on MDE with the speci city of ecodesign practice in industry this paper proposes the FESTivE method for Federate EcodeSign Tool modEls. Experimented in two different industrial contexts the practical feasibility of FESTivE has been validated with practitioners. Results on the e ects of using FESTivE in industry shows that product designers and environmental experts are more equipped to anticipate and to respond to each other's needs at each stage of the design process of product or service

Contribution structures

The invisibility of the individuals and groups that gave rise to requirements artifacts has been identified as a primary reason for the persistence of requirements traceability problems. This paper presents an approach, based on modelling the dynamic contribution structures underlying requirements artifacts, which addresses this issue. We show how these structures can be defined, using information about the agents who have contributed to artifact production, in conjunction with details of the numerous traceability relations that hold within and between artifacts themselves. We describe a scheme, derived from work in sociolinguistics, which can be used to indicate the capacities in which agents contribute. We then show how this information can be used to infer details about the social roles and commitments of agents with respect to their various contributions and to each other. We further propose a categorisation for artifact-based traceability relations and illustrate how they impinge on the identification and definition of these structures. Finally, we outline how this approach can be implemented and supported by tools, explain the means by which requirements change can be accommodated in the corresponding contribution structures, and demonstrate the potential it provides for "personnel-based" requirements traceability

Developing quality heathcare software using quality function deployment: A case study based on Sultan Qaboos University Hospital

Development of software is one of the most expensive projects undertaken in practice. Traditionally, the rate of failure in software development projects is higher compared to other kinds of projects. This is partly due to the failure in determining software users’ requirements. By using Quality Function Deployment (QFD), this research focuses on identification and prioritization of users’ requirements in the context of developing quality health-care software system for Sultan Qaboos University Hospital (SQUH) in Oman. A total of 95 staff working at eight departments of SQUH were contacted and they were requested to provide their requirements in using hospital information systems. Analytic Hierarchy Process has been integrated with QFD for prioritizing those user requirements. Then, in consultation with a number of software engineers, a list consisting of 30 technical requirements was generated. These requirements are divided into seven categories and all of them are purported to satisfy the user needs. At the end of QFD exercise, continuous mirror backup from backup category, multi-level access from the security and confidentiality category, linkage to databases from application category emerge as technical requirements having higher weights. These technical requirements should receive considerable attention when designing the health-care software system for SQUH.Software quality; Quality function deployment; Healthcare software; Analytic Hierarchy Process

Citizens Adoption and Intellectual Capital Approach

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 협동과정 기술경영·경제·정책전공, 2019. 2. Hwang, Junseok .The emergence of knowledge intensive industries gave rise to the issue of intellectual capital management which is used as an instrument to identify and measure the hidden sources of value creation at the firm, regional and national level. Knowledge-intensive companies are rated much higher than their book value suggests, and thus need to identify the intangible valuables of the company for the improvement and sustainability of their learning and capitalization system. Intellectual capital components are the key resources that can be leveraged for smart city development which intends to use information and communication technologies in order to bring efficiency and sustainability to the urban functions. The role of intellectual capital components in smart city implementation needs to be studied due to the fact that attributes of intellectual capital components would have a distinguished impact on value creation and the increase in productivity and performance. Despite the existence of a significant number of literatures on intellectual capital, the role of its components in the success of smart city implementation has not been examined. This research aims to investigate the role of intellectual capital components towards smart city success using an analysis of experts preferences for human capital and structural capital. The research also includes the demand-side perspective towards smart city information services characteristics that influences the adoption decision. The analysis is performed using two methodologies: Analytics Hierarchy Process (AHP) for human capital and structural capital and discrete choice analysis using a mixed logit model for the adoption of smart city information services. The first study employs a multidimensional approach to the development of a model for human capital using individual-level characteristics and the collective behavior. The identification of the sources of value in human capital is critical to the success of smart city implementations as these capabilities can be leveraged and upgraded to improve productivity and performance. Human capital components have been categorized into personal qualifications, personal traits, culture and social factors. The findings reveal that the most important category is personal qualifications followed by culture. Moreover, the overall priority weights estimation shows that the existence of domain-specific tacit knowledge gained through experience, the multi-disciplinary scope of education and the density of R&D personnel are the top-three ranked attributes of human capital towards smart city success. The study on the structural capital examined 24 smart city cases across the globe to identify the structural capital elements valuable in the smart city development process. The different orchestration of these structural capital elements can influence the outcome of the development process and its impact on the efficiency of the urban systems. The identified structural capital elements have been categorized into process, relational and infrastructural dimensions. The findings reveal that the infrastructural dimension comprising communication and information system is most critical towards the smart city success, followed by the process category with the most dominant component of policy. The overall ranking of these elements suggest that the decision makers need to focus on city-level policies and the development and enforcement of procedures for innovation generation. Finally, the citizens preferences analysis was performed for the case of Islamabad city in Pakistan which is at the early stage of smart city development and can benefit from a better understanding of the demand-side perspective. The characteristics of smart city information services considered in the study comprise language, access mode, service ownership, interoperability and security. Willingness-to-pay was used to observe the price sensitivity of the end users choices. The findings reveal that citizens in Islamabad have a higher utility towards the use of the English language, a mobile access mode and a high level of security. In conclusion, the study provides guidelines for policy makers who are concerned with the early stage of smart city development. The demand-side study of Islamabad city provides valuable insights in to existing trends that affect the rapid adoption of smart city services.국문초록 지식집약적 산업의 출현으로 기업, 지역 및 국가 차원에서 가치 창출의 숨겨진 출처를 파악하고 측정하는 도구로 사용되는 지적 자본 관리가 쟁점으로 떠올랐다. 지식집약적 기업은 순자산보다 훨씬 높은 평가를 받고 있기 때문에 그들의 학습과 자본화 시스템의 개선과 지속 가능성을 위해 회사의 무형 가치를 확인할 필요가 있다. 지적 자본요소는 정보통신 기술을 이용해 도시 기능에 효율성과 지속성을 높이는 스마트 시티 개발에 활용될 수 있는 핵심 자원이다. 지적 자본 요소의 속성은 가치 창출과 생산성 및 성능 향상에 가변적인 영향을 미칠 수 있기 때문에 스마트 시티 구현에서의 지적 자본 요소의 역할을 연구할 필요가 있다. 지적 자본에 관한 중요한 연구 문헌들이 있지만 스마트 시티의 성공적인 구현을 위한각 요소들의 역할은 검토되지 않았다. 이 연구는 인적자본과 구조자본에 대한 전문가의 선호도 분석을 사용하여 스마트 시티의 성공을 위한 지적 자본 요소의 역할 조사를 목적으로 한다. 또한 수용 의사 결정에 영향을 미치는 스마트 시티 정보 서비스 특성에 대한 수요 측면의 관점도 조사한다. 분석은 인적 자본 및 구조적 자본을 위한 분석 계층 프로세스(AHP)와 스마트 시티 정보 서비스 채택을 위한 혼합 로짓 모델을 이용한 이산 선택 분석이라는 두 가지 방법을 사용한다. 첫 번째 연구는 다차원적 접근법을 사용해 개인 수준의 특성과 집단 행동을 이용한 인적 자본에 대한 모델을 개발한다. 인적 자본의 가치의 근원을 식별하는 것은 스마트 시티 구현 성공에 매우 중요하다. 이러한 능력들이 활용되고 개선되어 생산성과 성능을 향상시킬 수 있기 때문이다. 인적 자본 요소는 개인의 자격, 성격, 문화, 사회적 요인으로 분류되었다. 그 결과, 첫번째로 중요한 것은 개인의 자격요건이며 두번째는 문화임을 밝혀냈다. 또한, 전체적인 우선순위 가중치 추정은 경험을 통해 얻은 도메인 고유의 암묵적 지식의 존재, 다분야의 교육 범위 및 R&D 인력의 밀도는 스마트 시티 성공을 위한 인적 자본의 상위 3대 속성임을 보여준다. 구조적 자본에 관한 연구는 전 세계 24개 스마트 시티 사례를 조사해 스마트 시티 개발 과정에서 가치 있는 구조적 자본의 요소를 확인했다. 서로 다른 구조적 자본 요소의 조정은 개발 프로세스의 결과와 도시 시스템의 효율성에 영향을 미칠 수 있다. 확인된 구조적 자본 요소는 프로세스, 관계 및 기반 구조 차원으로 분류되었다. 이는 통신과 정보 시스템을 구성하는 기반 구조의 차원이 스마트 시티의 성공에 가장 중요하며 그 다음으로 정책의 가장 우세한 구성 요소를 가진 프로세스 범주가 중요하다는 것을 보여준다. 이들 요소의 전체 순위는 의사결정자들이 혁신 생성을 위한 도시 수준의 정책과 절차 개발과 집행에 초점을 맞출 필요가 있음을 시사한다. 마지막으로, 스마트 시티 개발의 초기 단계에 있으며 수요 측면 관점에서 유용할 수 있는 파키스탄의 이슬라마바드 도시에 대한 시민의 선호 분석이 이루어졌다. 본 연구에서 고려한 스마트 시티 정보 서비스의 특성은 언어, 접근 모드, 서비스 소유권, 상호운용성 및 보안으로 구성된다. 지불 의지는 최종 사용자의 선택에 따른 가격 민감도를 관찰하기 위해 사용되었다. 연구 결과는 이슬라마바드 시민들이 높은 수준의 보안과 함께 영어 사용에 더 높은 효용을 가지고 있다는 것을 보여준다. 결론적으로, 이 연구는 특별히 스마트 시티 개발의 초기 단계에 있는 정책 입안자들을 위한 지침을 제공한다. 이슬라마바드시에 대한 수요 측면 연구는 스마트 시티 서비스의 신속한 채택을 지원하는 기존 추세에 대한 귀중한 통찰력을 제공한다. 주요 단어: 스마트 시티, 지적 자본, 인적 자본, 구조적 자본, 정보 서비스Chapter 1 Introduction 1 1.1 Overview 1 1.2 Purpose of the Research 9 1.3 Contribution of the Research 12 1.4 Research Outline 15 Chapter 2 Literature Review 18 2.1 Smart Cities 18 2.1.1 Smart City Definitions 19 2.1.2 Smart City Components 22 2.1.3 Smart City Systems Architecture 28 2.2 Intellectual Capital 30 2.2.1 Existing Studies on Intellectual Capital 32 2.2.2 Intellectual Capital and Smart Cities 37 2.2.3 Intellectual Capital Components 39 Chapter 3 Study on the Role of Human Capital for Smart City Success 50 3.1 Model 52 3.1.1 Personal Qualifications 54 3.1.2 Personal Traits 57 3.1.3 Culture 58 3.1.4 Social Factors 59 3.2 Methodology 60 3.2.1 Survey for Analytic Hierarchy Process 63 3.3 Estimation of Results 66 Chapter 4 Study on Structural Capital Role for Smart City Success 74 4.1 Model 77 4.1.1 Process Elements 77 4.1.2 Relational Elements 81 4.1.3 Infrastructural Elements 82 4.2 Methodology 85 4.2.1 Survey for Analytic Hierarchy Process 85 4.3 Estimation of Results 87 Chapter 5 Adoption of Smart City Information Services 95 5.1 Citizens Preferences Analysis towards the Adoption of Smart City Information Services 95 5.2 Model 97 5.3 Methodology 101 5.3.1 Random Utility Model 101 5.3.2 Willingness to Pay 104 5.4 Survey Design and Data 105 5.4.1 Survey for Discrete Choice Analysis 105 5.5 Estimation of Results 109 Chapter 6 Discussion and Conclusion 115 6.1 Discussion and Implications 115 6.2 Conclusion 128 6.3 Limitations and Future Work 131 References 134 Appendix A: Description of Attributes for AHP Survey 152 Appendix B: Survey Questionnaire for AHP 155 Appendix C: Conjoint Survey for Citizens Preference Analysis 163 국문초록 166 Acknowledgments 169Docto

Insufficient Effort Responding

The quality of self-report data has long been a concern, with increasing attention to the issue of insufficient effort responding (IER). Researchers have made considerable progress in developing techniques for handling IER (Meade & Craig, 2012; Huang, Bowling, Liu, & Li, 2014). This dissertation examines the use of IER best practices in survey research within the management literature through a series of essays. The results of the first study indicate that there is a lack of methodological transparency regarding how IER is addressed in the management literature. Simply stated, few authors report addressing IER in their manuscripts; thus, no conclusions could be drawn regarding management researchers use of IER best practices. Based on the findings of Study 1, the aim of Study 2 was to investigate this lack of reporting through a job performance lens. The essay explored several potential reasons for low methodological transparency regarding IER practices, including (1) insufficient KSAs (i.e., understanding or awareness of IER best practices), thus IER was not addressed nor reported, and (2) a lack of extrinsic motivation to report how IER was addressed in studies (i.e., reviewer requirements and page limitations). The results of Study 2 indicate that though management researchers do not report utilizing IER technique, IER is being addressed in various ways by management researchers. The most common techniques management researchers use to address IER are employing infrequency technique items to detect IER and deleting respondents flagged by the detection method from samples. Taken as a whole, these findings suggest there is room for improvement regarding how IER is addressed in management research using self-report survey data. Subsequently, Study 3 introduces a technique for examining and addressing the effects of IER on data quality that does not require researchers to delete respondent data, which may inadvertently bias samples or eliminate otherwise “good” data. Specifically, the final essay demonstrates how to create an IER method factor that can be used to examine the effects of IER detected in a sample and control for the effects of IER if it appears to bias research conclusions