De La Salle University

About: De La Salle University is a education organization based out in Manila, Philippines. It is known for research contribution in the topics: Population & Computer science. The organization has 2951 authors who have published 4374 publications receiving 49567 citations. The organization is also known as: Pamantasang De La Salle.

Comparing world regional sustainable supply chain finance using big data analytics: a bibliometric analysis

Abstract: Sustainable supply chain finance (SSCF) is a fascinated consideration for both academics and practitioners because the indicators are still underdeveloped in achieving SSCF This study proposes a bibliometric data-driven analysis from the literature to illustrate a clear overall concept of SSCF that reveals hidden indicators for further improvement,A hybrid quantitative and qualitative approach combining data-driven analysis, fuzzy Delphi method (FDM), entropy weight method (EWM) and fuzzy decision-making trial and evaluation laboratory (FDEMATEL) is employed to address the uncertainty in the context,The results show that blockchain, cash flow shortage, reverse factoring, risk assessment and triple bottom line (TBL) play significant roles in SSCF A comparison of the challenges and gaps among different geographic regions is provided in both advanced local perspective and a global state-of-the-art assessment There are 35 countries/territories being categorized into five geographic regions Of the five regions, two, Latin America and the Caribbean and Africa, show the needs for more improvement, exclusively in collaboration strategies and financial crisis Exogenous impacts of wars, natural disasters and disease epidemics are implied as inevitable attributes for enhancing the sustainability,This study contributes to (1) boundary SSCF foundations by data driven, (2) identifying the critical SSCF indicators and providing the knowledge gaps and directions as references for further examination and (3) addressing the gaps and challenges in different geographic regions to provide advanced assessment from local viewpoint and to diagnose the comprehensive global state of the art of SSCF

Government Performance Management and Evaluation in South Korea: History and Current Practices

Abstract: :This article discusses the history and features of South Korea’s government performance management and evaluation system. The Korean system was initially influenced by New Public Management and Reinventing Government as practiced in the United States, but it has developed distinct features that stem from South Korea’s institutional and cultural context. These features reflect a blend of Western institutions and Korean cultural influences that emphasize centralization, hierarchy, group harmony, and submission to higher authority. The institutionalized representation and involvement of civilians in the committee-type bodies that oversee performance evaluation at all levels, and the adoption of a comprehensive and advanced information technology platform, on the other hand, signify a desire to break from the past.

Vehicle detection and tracking using corner feature points and artificial neural networks for a vision-based contactless apprehension system

Abstract: Blocked intersections have been a contributing factor in the city-wide traffic congestion, especially in metropolitan cities. This research study aims to develop a better traffic violations management system in city-road intersections by using a machine vision system that automatically identifies and tags traffic violations committed in an intersection. The proposed system have three main sub-systems which are the video capture, video analysis, and output sub-systems. This study presents the development and results of a vehicle detection and tracking system using corner feature point detection and artificial neural networks for the vision-based contactless traffic violations apprehension system. This detection and tracking system serves as the front-end processing in the video analysis sub-system. Experiments were conducted for different corner feature-points detection algorithm: Harris, Shi-Tomasi, and Features from Accelerated Segment Test (FAST). The results showed that in the testing phase Harris-ANN have 89.09% accuracy, Shi-Tomasi-ANN have 88.48%, and FAST-ANN have 90.30% accuracy.

Clinical outcomes of mesh exposure/extrusion: presentation, timing and management.

Abstract: Background The Food and Drug Administration has recently highlighted an increase in reported complications associated with the use of transvaginal mesh. Aims To describe the clinical outcomes, presentation, timing and management of mesh exposure/extrusion Materials and Methods Retrospective study from December 2006 to March 2012. A total of 40 women had vaginal mesh exposure/extrusion secondary to prior transvaginal mesh (TVM) surgery. Descriptive statistics were used for demographics and pre-operative data. Paired-samples t-test was applied for comparison of pre- and postoperation. A P value of <0.05 was considered statistically significant. Results The mesh exposure/extrusion rate was noted to be 2.64% (17/642). Vaginal bleeding in 29 of 40 (72.5%) and hispareunia in 12 of 13 (92.3%) were identified as the most common symptoms for mesh exposure/extrusion. The onset of complications occurred in two peaks: between 3 and 4 months and after 1-year of follow-up. Initial conservative treatment was given for 12.5% (5/40) of women, while 87.5% (35/40) had undergone repair for mesh exposure/extrusion (21 outpatient and 14 inpatient cases). Among those who had conservative treatment, 80% (4/5) had persistent mesh exposure. Conclusion Persistent or new-onset abnormal vaginal bleeding and hispareunia after TVM surgery should be considered as ‘red flag’ symptoms for mesh exposure/extrusion. Frequent follow-up from the first 3–4 months up to 1 year postoperative may identify complications. Utilisation of mesh excision or trimming as the initial means of treatment may yield a better outcome.