The Case for Data Driven Strategic Decision Making

The study examines the case for data driven strategic decision making. The quality of strategic decision making and effectiveness of implementing the selected strategies is increasing becoming more important in organizational developments. This calls for the adoption and usage of data driven decision making process in strategy management. Strategic data-driven decision making involves collecting data, analyzing that data, getting the data into the hands of the people who need it, using the data to increase efficiencies and improve performance and communicating data-driven decisions to key stakeholders. The elements of data driven strategic decision making and the various models are outlined. An application is considered of usage of data in strategic decision making in schools. This powerful tool in the education sector facilitates data collection, data analysis and application into the improvement plans. Its premium value is in facilitating informed decision making, boosting overall school performance and improved student achievement. A proactive leader who understands the vision and able to champions the cause is required in creating momentum behind any data-driven decision making tasks.  Strategic decision making is an indispensable tool in moving organization on a sustainable success drive. Keywords: Data, strategic, decisions, models, quality, performance, tools, analysi

Multiwavelength Observations of Gamma-ray Binary Candidates

A rare group of high mass X-ray binaries (HMXBs) are known that also exhibit MeV, GeV, and/or TeV emission ("gamma-ray binaries"). Expanding the sample of gamma-ray binaries and identifying unknown Fermi sources are currently of great interest to the community. Based upon their positional coincidence with the unidentified Fermi sources 1FGL J1127.7-6244c and 1FGL J1808.5-1954c, the Be stars HD 99771 and HD 165783 have been proposed as gamma-ray binary candidates. During Fermi Cycle 4, we have performed multiwavelength observations of these sources using XMM-Newton and the CTIO 1.5m telescope. We do not confirm high energy emission from the Be stars. Here we examine other X-ray sources in the field of view that are potential counterparts to the Fermi sources.Comment: 2012 Fermi Symposium proceedings - eConf C12102

New Measure of the Dissipation Region in Collisionless Magnetic Reconnection

A new measure to identify a small-scale dissipation region in collisionless magnetic reconnection is proposed. The energy transfer from the electromagnetic field to plasmas in the electron's rest frame is formulated as a Lorentz-invariant scalar quantity. The measure is tested by two-dimensional particle-in-cell simulations in typical configurations: symmetric and asymmetric reconnection, with and without the guide field. The innermost region surrounding the reconnection site is accurately located in all cases. We further discuss implications for nonideal MHD dissipation

Supervision experiences of postgraduate research students at one South African higher education institution

This paper is based on a study that was conducted at a university based in the Eastern Cape, South Africa. The research aimed to explore and describe challenges that are likely to limit the success of postgraduate research students, mostly focusing on the relationship between students and supervisors. The study adopted a case study design with qualitative data. A self-constructed interview guide with open-ended questions was utilised as the main data collection tool from a sample of 34 postgraduate students from one faculty of the university in question. The study findings revealed that communication breakdown, poor feedback, non-availability of some supervisors and lack of ethical consideration were some of the major factors that contributed to negative supervisory experiences of the students who participated in the study.  Based on the findings, the study recommended a number of intervention strategies that could be put in place for both students and supervisors to improve the supervision experience. Among these are the adoption of collaborative cohort model, supervisor training and communication guidelines

Fixed-Point Approximations of Bandwidth-Sharing Networks with Rate Constraints

Bandwidth-sharing networks are important flow level models of communication networks. We focus on the fact that it takes a signicant number of users to saturate a link, necessitating the inclusion of individual rate constraints. In particular we extend work of Reed & Zwart on fluid models of bandwidth sharing with rate constraints under Markovian assumptions: we consider a bandwidth sharing network with rate constraints, where job sizes and deadlines have a general joint distribution. We introduce a fluid model and investigate several of its properties. In particular we show that its invariant point approximates the invariant distribution of the bandwidth sharing network if capacities are large

Fluid limits for bandwidth-sharing networks with rate constraints

Bandwidth-sharing networks as introduced by Massouli\'e~\& Roberts (1998) model the dynamic interaction among an evolving population of elastic flows competing for several links. With policies based on optimization procedures, such models are of interest both from a~Queueing Theory and Operations Research perspective. In the present paper, we focus on bandwidth-sharing networks with capacities and arrival rates of a large order of magnitude compared to transfer rates of individual flows. This regime is standard in practice. In particular, we extend previous work by Reed \& Zwart (2010) on fluid approximations for such networks: we allow interarrival times, flow sizes and patience times to be generally distributed, rather than exponentially distributed. We also develop polynomial-time computable fixed-point approximations for stationary distributions of bandwidth-sharing networks, and suggest new techniques for deriving these types of results

Entrepreneurship development; a step towards achieving the economic and social goals of fisheries: (Explanation and ranking of effective environmental factors using fuzzy Delphi and FAHP approach)

The purpose of the present research was to identify and rank the effective environmental (background) indices on OE process in Mazandaran Fisheries Organization. In terms of data collection, the method used in this study was the descriptive-survey method and in terms of research purposes, it was an applied research. Statistical population included experts and leading experts of Mazandaran fisheries organization in 2014. After literature review, the effective environmental (background) indices on OE were identified. Data were collected using Delphi and paired comparisons questionnaires, and analyzed using fuzzy Delphi method and FAHP. The results showed that the effective environmental (background) indices on OE, in order of priority, were the economic environments, legal-political environment, social-cultural environment, technological environment, administrative environment and international environment

The relationships between accessibility and crash risk from social equity perspectives: A case study at the Rotterdam-The Hague metropolitan region

Traflic safety and accessibility have been two important subjects in transportation research. On the one hand traffic crashes bring about high societal costs and serious health risks for urban road users. The cost oftraffic crashes is estimated to be 17 billion euros per year only in the Netherlands while over 600 people were killed in traffic, of whom 229 were cyclists and 195 were car users [l, 2]. Accessibility, on the other band, is regarded as one of the indicators of the quality of the transport system serving the public. There is comprehensive literature investigating the relationship between traffic crashes and factors associated with traffic, roadway design, built environment, and human factors. Similarly, several studies assessed and evaluated accessibility levels of individuals, communities, and regions by utilizing the aforementioned. factors. Nevertheless, there is a scarcity ofliterature investigating the relationships between accessibility and traffic safety. This is especially surprising considering that both subjects are associated with a similar set of factors, including land use and transport systems, as weil as individual and temporal factors [3-7]. The relationships between accessibility and traffic safety can be an adverse one; for example, improved accessibility by increasing the travel speeds (i.e., declining travel time) intensifies the crash risks which also deteriorates equity. Furthermore, levels ofboth accessibility and traffic safety are not homogeneous throughout urban areas and among different population groups. Based on the literature, it is obvious that accessibility is associated with economic equity [8]. lt is revealed that accessibility of lower-income groups is substantially worse than the higher-income groups as these groups have less mobility [9]. Previous studies also showed. that lower-income groups usually suffer from traffic safety problems more than other socio-economic groups [10-12]. Therefore, this research aims to address the aforementioned gap in the literature in understanding the relationships between accessibility levels and traffic safety with a focus on social equity perspecti.ves. For this purpose, a Gravity model and risk exposure evaluation approaches are utilix.ed to analyze traffic safety and accessibility to jobs by bicycle via extending the traditional definition of accessibility based on only travel time or proximity to a location

Legal Judgement Prediction for UK Courts

Legal Judgement Prediction (LJP) is the task of automatically predicting the outcome of a court case given only the case document. During the last five years researchers have successfully attempted this task for the supreme courts of three jurisdictions: the European Union, France, and China. Motivation includes the many real world applications including: a prediction system that can be used at the judgement drafting stage, and the identification of the most important words and phrases within a judgement. The aim of our research was to build, for the first time, an LJP model for UK court cases. This required the creation of a labelled data set of UK court judgements and the subsequent application of machine learning models. We evaluated different feature representations and different algorithms. Our best performing model achieved: 69.05% accuracy and 69.02 F1 score. We demonstrate that LJP is a promising area of further research for UK courts by achieving high model performance and the ability to easily extract useful features