The next wave of Business Intelligence

Syftet med uppsatsen är att undersöka nästa våg av Business Intelligence - Corporate Performance Management - och vilka typ av möjligheter detta koncept kan bidra med när det kommer till uppföljning av projekt i ett kunskapsföretag som vi kan kalla ”Kusten AB”. Kusten AB finner nämligen utmaningar att i sina leveransprojekt identifiera problem och risker innan de får negativa konsekvenser för projektets budget, tidplan eller leveranskvalitet. Till hjälp i vårat arbete hade vi vår akademiska handledare Magnus Bergquist samt vår handledare på Kusten AB. Det praktiska arbetet bestod av prototypbyggande samt laborationer med hjälp av Microsofts verktyg PerformancePoint Server. När det kom till valet av metodologi valde vi ett kvalitativt tillvägagångssätt som bestod av fyra intervjuer, en enkät samt evaluering av ovannämnda prototyp. Detta var det som bidrog till den största delen av vår empiri. Den huvudsakliga slutsatsen som vi kom fram till är att snabbare och effektivare uppföljning av projekt, när det kommer till tid och budget, är fullt möjligt i den studerade organisationen

NUMERICAL SOLUTIONS OF SINGULAR NONLINEAR ORDINARY DIFFERENTIAL EQUATIONS USING SAID-BALL POLYNOMIALS

In this article, the collocation method based on Said-Ball polynomials have been used to solve the singular nonlinear ordinary differential equations of various orders numerically. An operational matrix forms of these ordinary differential equations are obtained from Said-Ball polynomial with variated relations of solution and different derivatives. The presented method reduces the given problem to a system of nonlinear algebraic equations, which removed the singularity of ordinary differential equations. Resulting system is solved using Newton\u27s iteration method to get the coefficients of Said-Ball polynomials. We obtained approximate solutions of the problem under study. Numerical results have been obtained and compared with exact and other works. The presented method gives impressive solutions, that show the accuracy and reliability of the proposed method

Demand modeling for mobile app stores

Smartphones have reached a relatively high market share of the mobile market, creating new market opportunities. As a result, different stakeholders are investing in the mobile industry attempting to generate a higher revenue share. Hence, competition between various mobile device manufacturers has increased, as they compete for customers. These device manufacturers have created their own ecosystems, trying to lock-in their customers. These ecosystems include the application (app) stores providing services for mobile users. Currently, the two leading app stores are the Apple App Store and Google Play. Similarly, the competition exists among app developers of both stores. Therefore, it is vital to understand the user demands to design a successful app is popular in these stores. This thesis identifies successful app categories for both app stores from the perspective of an app developer. It adopts basic descriptive analysis for the dataset provided during September and October 2013 regarding the US and Finnish markets. Furthermore, it introduces a probabilistic graphical model based on Bayesian Network, aiming to understand the dynamics of mobile app stores. The thesis defines the success indicator for each category of apps, and then compares the results of both app stores. The top successful app categories in the US market include Social Networking, Productivity, Music, Finance, Education, Sports, Entertainment, and Travel. The corresponding app categories in Finland include Social Networking, Finance, Education, Music, Productivity, Entertainment, Photos and Video, Lifestyle, Games, and News. The thesis concludes that Google Play has higher success indicators than Apple App Store both in US and Finnish markets. Additionally, the success indicator is higher for free apps compared to paid apps. The results of this research contribute to recommendations for developers, during the development and publishing stages of an app, as well as building marketing strategies for mobile apps. Furthermore, it suggests a framework to identify successful apps in mobile app stores

Identifying Venous Thromboembolism in Cancer Patients Using Veterans Affairs Administrative Data

Identifying Venous Thromboembolism in Cancer Patients Using Veterans Affairs Administrative Data Noah Ravenborg1, Najeebah A. Bade, M.D.2, Dalia Abdelaziz Mobarek, M.D.1, 2, 3 1 George Washington University School of Medicine and Health Sciences, Washington, D.C. 2 Department of Medicine, Section of Hematology, Veterans Affairs Medical Center, Washington, D.C., 3 Department of Medicine, Section of Hematology & Medical Oncology, George Washington University Medical Center, Washington, D.C. Noah Ravenborg Cell phone: (310)-804-0848, Email: [email protected], MS2 IMPORTANCE: The validity of administrative data in identifying diagnoses within the Veterans Affairs (VA) database, including viral hepatitis, cirrhosis, H. pylori, and cancer metastasis has been reported. International Classification of Diseases-9 (ICD-9) validity for venous thromboembolism (VTE) in cancer patients within the VA database is unknown. OBJECTIVES: Determine the validity of ICD-9 codes for VTE in cancer patients in a local VA database. DESIGN: We conducted a retrospective study utilizing data from the Washington, DC VA Cancer Registry and the Electronic Health Records (EHR). VTE diagnosis was identified using the ICD-9 codes for Pulmonary Embolism and Thrombosis, with subsequent confirmation via comprehensive chart reviews. SETTING: Veterans Affairs Medical Center, Washington, DC. PARTICIPANTS: 6,678 patients with cancer were identified from 1999-2015 using the cancer registry. We applied the algorithms above and identified subjects with VTE in the database. EXPOSURES: N/A MAIN OUTCOME(S) AND MEASURE(S): The primary outcome study measurement was the validity of ICD-9 for VTE in cancer patients. Positive (PPV), negative predictive (NPV) values, sensitivity, specificity, and likelihood ratios were calculated. Our hypothesis, that ICD-9 codes alone are not predicative of VTE diagnosis in our cancer registry, was formulated during data collection after initial chart reviews yielded false positives. RESULTS: Initial application of ICD-9 codes for VTE among 6,678 subjects yielded 616 VTE. Chart reviews confirmed the presence of VTE among 403/616. The ICD-9 codes had a 65% PPV, 95% NPV, 57% sensitivity and 96.4% specificity. Estimated prevalence of VTE in 6,678 subjects is 10.6%. Positive and negative likelihood ratios were 15.8 and 0.45, respectively. CONCLUSIONS AND RELEVANCE: Within our local VA database, ICD-9 codes for VTE are not sensitive for identifying patients with VTE. Accurate ICD coding by physicians is paramount for patient care and research purposes. There is a lack of data on physician coding education. A systematic literature review revealed variable ICD-9 code validity based on the population of interest making larger studies challenging with added need for manual abstraction for validation. Provider education on proper use of ICD code is important for health outcomes research perspective and would allow for more accurate retrospective research. REGISTRATION: N/

Revisiting the impact of ESG on financial performance of FTSE350 UK firms: Static and dynamic panel data analysis

This study re-examines the impact of ESG (economic, environmental, social, and corporate governance performance) on the financial performance of UK firms. Most recent sample of 351 firms from FTSE350 for the time period 2002–2018 is used. The study estimates the impact of total ESG and individual dimensions of ESG on corporate financial performance using static and dynamic panel data techniques, and it also examines the impact of high and low ESG on firm financial performance. Further, the study investigates the role of firm size as a moderator in the relationship between ESG and firm financial performance. The results of total ESG performance indicate that ESG has a positive and significant impact on firm financial performance. However, in the case of the individual ESG performance, the results are mixed. Overall, the results confirm that high ESG firms show high financial performance as compared to low ESG firms. Results indicate that firm size moderates the relationship between ESG performance and firm financial performance

A numerical and experimental study of near surface ground energy systems including the use of adaptable insulation layer

Unfortunately, the global conventional fuels in reserves are running out while the world energy consumption is increasing unruly. Therefore, innovative methods for providing sustainable heating and cooling through thermal energy storage (TES) have gained increasing attention. This study presents a numerical and experimental investigation of near surface ground energy systems including the use of adaptable insulation layers. The experimental set up involves the development of an innovative technique that is proposed to regulate the transfer of heat energy to the storage regions of the soil mass. Furthermore, a theoretical framework to represent the transient processes of such systems was developed and 1D and 2D numerical models were established to simulate ground energy system behaviour. The finite element method was utilised for spatial discretization and the finite difference method for time-stepping. The resulting model took into account conductive and convective heat transfer between the fluid inside pipe heat exchangers and the surrounding soil. Key additions were introduced to the recent model work which allowed it to take into account surface snow and ground freezing presence in the system, the amount of thermal energy available in the system and the ability to represent porous layer thermal properties of a multi layered system through considering its components (i.e. air, water and solids particles). The proposed new experimental setup was used to investigate the practical implementation of adaptable insulation layers with the experimental data then used to validate the numerical model. Further validation of the modelling of the surface snow and ground freezing was achieved via comparison against an experimental case study performed by others. In the analysis performed, particular attention was given to the energy balance at the soil surface and its impact on the performance of thermal energy storage devices in shallow regions of the ground. Additionally, the developed models were applied to explore the use of the adaptable insulation layer in different systems in comparison to typical designs. Three case scenarios were chosen to represent different type of systems, a comparisons analysis was then introduced which shows the potential effectiveness of using the adaptable insulation layer

Is the Force Awakened? Publication Trends in Oncology Big Data as Phase II CancerLinQ is Launched

Background: The American Society of Clinical Oncology launched CancerLinQ project in 2010 to provide real-time data collection, mining and visualization, clinical decision support, and quality feedback. Creation of a big data software platform is currently underway to power the CancerLinQ in the phase II of the project. This would allow for evidence driven practice and rapid learning for cancer care providers. Additionally, adequate knowledge about the utility of Big Data to encourage provider utilization in high Impact Factor (IF) journals is needed. We aimed to assess trends and quality of Big Data published in Oncology. Methods: Peer-reviewed English papers published between 2011 and 2015 reporting on cancer and Big Data were identified using PubMed. Manual review was conducted. Cohort construction and statistical analyses were performed utilizing SPSS v 21.0 Results: We identified 325 publications, 135 met inclusion criteria in 105 journals, of which 36% (n=38) are considered specialized hematology and/or oncology journals. Specialized journals published 29.62% (40/135). Equal distribution of publications was found in clinical and basic science journals; 54 (37%) and 50 (40%) respectively. There was a trend of increased publications in clinical journals from 2012 to 2015 (16.7% to 42.9%, P = 0.39). Of the available Impact factors (IF) – the median is 3.234 (range 0.00-41.456) with 25/125 (20.0%) of available IF being \u3e 5.00 and 12/125 (9.6%) being \u3e 10.00 with no difference in the proportion of IF \u3e 5.00 in clinical versus basic science journals; 11/51 (21%) versus 11/47 (23) % p = 1.00, respectively. Conclusions: The need for further publication of studies addressing Big Data use in furthering oncology research is being met by the research community in response to the CancerLinQ as demonstrated by the rapid increase in publications. We hypothesize that this will increase the likelihood of cancer providers using CancerLinQ in the future, although an increase in publication in specialized journals and in those with high impact factors is still necessary. Currently, despite the increased trend of publications addressing Big Data in oncology, less than one-third of these publications are in specialized journals

Improved Operational Matrices of DP-Ball Polynomials for Solving Singular Second Order Linear Dirichlet-type Boundary Value Problems

Solving Dirichlet-type boundary value problems (BVPs) using a novel numerical approach is presented in this study. The operational matrices of DP-Ball Polynomials are used to solve the linear second-order BVPs. The modification of the operational matrix eliminates the BVP\u27s singularity. Consequently, guaranteeing a solution is reached. In this article, three different examples were taken into consideration in order to demonstrate the applicability of the method. Based on the findings, it seems that the methodology may be used effectively to provide accurate solutions