Generic qualitative dissertations in counselor education: A content analysis

We conducted a content analysis of generic qualitative counseling dissertations (GQR; N = 70), examining their methodological justifications, coherence, and trustworthiness. Dissertations authors often presented vague methodological justifications. Findings have implications for constructing methodological justifications, integrating relevant literature, and awareness of how GQR compares to other qualitative methodologies.     

Barriers to domestic violence education in Northern Ireland: Pupils' views and experiences

Domestic violence (DV) in adult and young people's intimate partner relationships is a social and public health problem across the globe. Education can play an important and unique role in addressing DV; however, it remains relatively under-investigated. The aim of this qualitative study set in Northern Ireland, the first of its kind, was to explore young people's views and experiences of DV education. Focus groups were conducted with 188 pupils (97 males and 91 females) aged 16 to 18 attending post-primary school. The data were analysed using thematic analysis and reveal five barriers to DV education: (1) absence of DV teaching and learning; (2) DV is a taboo topic; (3) lack of teacher training and expertise on DV; (4) religious influence; (5) prioritisation of academic achievement over pupil wellbeing. The results demonstrate that changes are needed in schools to improve the role of schools in addressing DV. From this qualitative study, we make recommendations for how school-based DV education may help prevent and protect young people against intimate partner violence.     

Relationship of executive functioning and memory to autism symptomology and adaptive functioning: Implications for reducing future underemployment

Understanding the relationship between executive functioning and its connection to working memory and adaptive functioning can inform planning and employment efforts. This study explored the relationship between memory and adaptive functioning with a sample of Autistic youths/young adults. Participant mean age was 21.3 (SD = 3.0). Of the 22 participants, 17 were male, and 19 white, non-Hispanic/Latina/o/x. All but one lived with their parent(s). Participants were administered a full battery assessing cognitive ability (WAIS-IV), memory and executive functioning (WMS-IV and DKEFS), autism symptomatology (ADOS-II), and adaptive functioning (SIB-R). A multivariate lasso regression model was used. Memory, especially as measured on the WMS-IV, was found to be significantly related to adaptive functioning and autism symptomatology. There appears to be continuing evidence that memory is highly related to adaptive functioning and autism symptomatology. Interventions involving auditory and immediate memory could be helpful in promoting more mutually effective social interactions necessary for positive employment outcomes.     

Strategic interactions in public R&D across European countries: A spatial econometric analysis

The paper adds to the existing literature on the determinants of government spending in Research and Development (R&D) by considering the role of strategic interactions among countries as one of the possible competing explanations, within a spatial econometric framework. We account for several factors affecting national levels of public R&D spending, including (i) the international context – i.e. Lisbon strategy; (ii) country characteristics – level of private R&D, GDP, trade openness and the National System of Innovation; (iii) countries’ similarities in relation to (a) trade and economic size and (b) sectoral specialization. The analysis is carried out on 14 European countries. First, we find that factors traditionally affecting the level of public R&D expenditure, such as the scale of the national economy, trade openness, sectoral specialization and private R&D, significantly influence the level of public R&D in European countries between 1994 and 2006. Interestingly, the introduction of the Lisbon strategy does not seem to have affected changes in the levels of public R&D spending. Second, by using different weight matrices, we confirm the existence of strategic interactions in relation to R&D spending among European countries with similar economic, international trade and sectoral structure characteristics, though not geographically close.     

Revisiting Cross-document Structure Theory for multi-document discourse parsing

Multi-document discourse parsing aims to automatically identify the relations among textual spans from different texts on the same topic. Recently, with the growing amount of information and the emergence of new technologies that deal with many sources of information, more precise and efficient parsing techniques are required. The most relevant theory to multi-document relationship, Cross-document Structure Theory (CST), has been used for parsing purposes before, though the results had not been satisfactory. CST has received many critics because of its subjectivity, which may lead to low annotation agreement and, consequently, to poor parsing performance. In this work, we propose a refinement of the original CST, which consists in (i) formalizing the relationship definitions, (ii) pruning and combining some relations based on their meaning, and (iii) organizing the relations in a hierarchical structure. The hypothesis for this refinement is that it will lead to better agreement in the annotation and consequently to better parsing results. For this aim, it was built an annotated corpus according to this refinement and it was observed an improvement in the annotation agreement. Based on this corpus, a parser was developed using machine learning techniques and hand-crafted rules. Specifically, hierarchical techniques were used to capture the hierarchical organization of the relations according to the proposed refinement of CST. These two approaches were used to identify the relations among texts spans and to generate multi-document annotation structure. Results outperformed other CST parsers, showing the adequacy of the proposed refinement in the theory.     

Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application

Understanding the main determinants of Internet banking adoption is important for banks and users; our understanding of the role of users’ perceived risk in Internet banking adoption is limited. In response, we develop a conceptual model that combines unified theory of acceptance and use of technology (UTAUT) with perceived risk to explain behaviour intention and usage behaviour of Internet banking. To test the conceptual model we collected data from Portugal (249 valid cases). Our results support some relationships of UTAUT, such as performance expectancy, effort expectancy, and social influence, and also the role of risk as a stronger predictor of intention. To explain usage behaviour of Internet banking the most important factor is behavioural intention to use Internet banking.     

Analysis and design for continuous-time string-connected Takagi–Sugeno systems

Distributed systems consist of interconnected, lower-dimensional subsystems. For such systems, distributed analysis and design present several advantages, such as modularity, easier analysis and design, and reduced computational complexity. A special case of distributed systems is when the subsystems are connected in a string. Applications include distributed process control, traffic and communication networks, irrigation systems, hydropower valleys, etc. By exploiting such a structure, in this paper, we propose conditions for the distributed stability analysis of Takagi–Sugeno fuzzy systems connected in a string. These conditions are also extended to observer and controller design and illustrated on numerical examples.     

算法谜题

正出版社:人民邮电出版社出版时间:2014-03-01ISBN:9787115338440所属分类:图书计算机与互联网操作系统算法是计算机科学领域最重要的基石之一。算法谜题,就是能够直接或间接地采用算法来加以解决的谜题。求解算法谜题是培养和锻炼算法思维能力一种最有效和最有乐趣的途径。《算法谜题》是一本经典算法谜题的合集。书中包括了一些古已有之的谜题,数学和计算机科学有一部分知识就发源于此。《算法谜题》中还有一些较新的谜题,其中有一部分谜题     

Harmonization of pre-analytical quality indicators

Quality indicators (QIs) measure the extent to which set targets are attained and provide a quantitative basis for achieving improvement in care and, in particular, laboratory services. A body of evidence collected in recent years has demonstrated that most errors fall outside the analytical phase, while the pre- and post-analytical steps have been found to be more vulnerable to the risk of error. However, the current lack of attention to extra-laboratory factors and related QIs prevent clinical laboratories from effectively improving total quality and reducing errors. Errors in the pre-analytical phase, which account for 50% to 75% of all laboratory errors, have long been included in the ‘identification and sample problems’ category. However, according to the International Standard for medical laboratory accreditation and a patient-centered view, some additional QIs are needed. In particular, there is a need to measure the appropriateness of all test request and request forms, as well as the quality of sample transportation. The QIs model developed by a working group of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) is a valuable starting point for promoting the harmonization of available QIs, but further efforts should be made to achieve a consensus on the road map for harmonization.