Plans For Future Improvements Research Articles

Mapping sidewalks on a neighborhood scale from street view images

Although reliable and accurate inventorying of sidewalks is time consuming, it can aid urban planners in decision making for infrastructure development. Recent advancements in computer vision and machine learning algorithms have improved the reliability and accuracy of automated inventorying. This research uses a deep learning architecture-based semantic segmentation model (i.e., HRNet + OCR) to automate sidewalk identification using Google Street View (GSV) images. The results show that retraining the model using local training images yields 114.16% and 178.11% higher performance in terms of intersection over union (IoU) metric compared to pretrained model using Cityscapes and Mapillary datasets, respectively. The developed model showed excellent performance in predicting the presence of sidewalks in an image by achieving high accuracy (0.9557), precision (0.9447), recall (0.9900), and F1- score (0.9668). Further, in comparison with EfficientNet, a computationally efficient image classification model, the present model showed superior performance in predicting sidewalk presence at the image level. Therefore, integrating local training images containing minimum required labels (in this study, roads, sidewalks, buildings, and walls) with publicly available training datasets can help increase the performance of the semantic segmentation model for extracting the required features (in this study, roads and sidewalks) from GSV images, especially in developing countries like Bangladesh. This study generates sidewalk maps on a neighborhood scale, which can be useful visualization tools for researchers and practitioners to understand the existing pedestrian infrastructure and plan for future improvements.

Flexible Pavement Design Analysis Using Bina Marga 2017 Method for the Road Section from Banjang-Pulau Nyiur to Batu Mandi, Hulu Sungai Utara

The Banjang, Pulau Nyiur, Batu Mandi road is one of the provincial roads in South Kalimantan located in the Hulu Sungai Utara. This road falls under the jurisdiction of the South Kalimantan Provincial Government and has a total length of 12.5 km. Some parts of this road still lack asphalt pavement, and there are plans for future improvements to enhance driving comfort and facilitate inter-regional transportation. Therefore, there is a need for appropriate pavement thickness planning that aligns with the field conditions and regulations. This study employs the flexible pavement thickness planning method according to the Bina Marga 2017 guidelines, with a design life of 20 years and a traffic growth rate of 3.5%. The surface thickness planning utilizes Asphalt Concrete (AC) with a wearing course (AC WC), and an AC Base layer with LPA Class A aggregate gradation. The results of this study indicate that the calculated flexible pavement thickness using the Bina Marga 2017 method is 58 cm, comprising a 10 cm AC WC layer, an 18 cm AC Base layer, and a 30 cm LPA Class A aggregate layer

문화재 활용정책의 평가

The purpose of this study is to evaluate the performance of the Local cultural heritage utilization project and to seek future improvement plans. this study applied Vedung (2010)'s policy evaluation system model to empirically evaluate the local cultural heritage utilization project, which is a representative project of cultural heritage utilization policy. First of all, the evaluation model was set up in the steps of input-implementation-result. The results were more specified as outputs and impacts. The evaluation was based on project statistical data, related reports, work plans or performance reports of the Cultural Heritage Administration. Finally, through the evaluation results, this study suggested improvement directions in terms of business continuity, institutional arrangements, and program planning and capacity building.

Learning Culture in a Virtual Classroom

The study reports how “A Glimpse of China,” a cultural course that had been typically conducted offline for cultural immersion, adapted to the COVID-19-imposed challenges of an online transition. The teaching team sought the guidance of social constructivism and the WisCom Framework, made adaptations in the instructional design, assessed the learning outcomes and course effects, and proposed a plan for future improvements. Content analysis of the course reports of 10 students from Class 2020 and 2021 confirmed the success of the online transition, and yet indicated that experiential learning and interactive collaboration should be strengthened for better learning experience and outcomes. As an improvement for future students, a set of experiential projects is developed. Each project constitutes a collaborative inquiry cycle that aims to build a more desirable wisdom community for both the learners and the instructor.

유아특수교육기관의 조직문화에 대한 유아특수교사의 경험과 요구

The purpose of this study is to examine the experiences and needs of early childhood special education teachers for the organizational culture of early childhood special education institutions. A focus group interview was conducted with 11 early childhood special education teachers working for special classes in kindergarten and special education kindergartens. As a result of the study, 3 themes, 11 subcategories, and 30 main concepts were derived. Specific research results are as follows. First, early childhood special education teachers presented four types of organizational culture experiences according to the differences in the method of pursuing values and flexibility of institutions. In other words, it is a relationship-oriented culture, a performance-oriented culture, a hierarchy-oriented culture, and a chaotic organizational culture that is difficult to be explained by the preceding three models. Second, early childhood special education teachers presented negative experiences with respect to organizational fairness such as mutual fairness, procedural fairness, and distribution fairness. Third, early childhood special education teachers said that it is necessary to make an active effort on their own to realize the unique identity of early childhood special education teacher along with the improvement of democratic and organizational culture. In addition, they emphasized the need for awareness-raising training for institutional members and securing fairness in the promotion system for early childhood special education teacher. Based on the results of this study, future improvement plans for the organizational culture of early childhood special education institutions were suggested.

미래사회 대비 2015 개정 중학교 기술과 교육과정의 진단과 개선 방안에 관한 연구

The purpose of this study is to diagnose the 2015 revised middle school technology education curriculum by examining the curriculum requirements related to the expansion of the proportion of technology education in preparation for the future society, and to suggest future improvement plans for nurturing science and engineering talents and cultivating technological literacy. To this end, as an improvement plan to diagnose the problem of the 2015 revised middle school technology education curriculum, and to expand the proportion, about 1,000 opinions from elementary and secondary school teachers, university professors and researchers, college students, and parents, etc. was investigated to derive implications. Firstly, technology education should be prioritized among the subjects that should be treated with importance in the future society in school education. And when considering future social changes, natural science and engineering fields with a high degree of job and employment creation were 907, accounting for 86.8% of the total respondents, showing high results. Secondly, as for the current technology education, the lower the school level, the more familiar the subject is, and the higher the school level, the more friendly the subject. However, it can be seen that it needs to be reflected in the future curriculum due to the lack of practice time and facilities and facilities for practice. Thirdly, it is recognized that the natural science and engineering field group lacks practical time and facilities and facilities for practice compared to the non-science and engineering field group. On the other hand, the non-science and engineering field group perceives that technology subjects are tied to home subjects compared to the natural science and engineering fields, preventing them from advancing into the science and engineering fields. Fourthly, compared to other subject majors, technology majors are suggesting two-fold improvement in the introduction of long-term projects, linked with STEAM education, use of digital equipment, and technology and home education. On the other hand, students majoring in other subjects had a higher degree of agreement than those majoring in technology about replacing the theoretical explanation part of technology education with cyber learning.

Review the status of Korean geoid model development since 2000s and future improvement plan

Korean geoid models have been continuously developed for more than 20 years. However, the precision of previous models was approximately 8–15 cm according to evaluations based on newly obtained Global Navigation Satellite System (GNSS)/Leveling data because of irregular distribution and low precision of the gravity and GNSS/Leveling data. Therefore, in 2008, NGII began to obtain new terrestrial gravity and GNSS/Leveling data and collected more than 12,000 points of gravity data and 4492 points of GNSS/Leveling data by the end of 2017. As a result, the newest model, Korean National Geoid 2018 (KNGeoid18), achieved a degree of fit (DOF) of 2.3 cm. The precision was significantly improved compared to previous models including KNGeoid14, but precision in the mountainous areas remained still lower than that of the plain areas. Also, inconsistent differences between the GNSS/Leveling data and KNGeoid18 remained as a problem that should be solved. Through KNGeoid project, the NGII observed a positive effect of supplementing fundamental data, so NGII is obtaining new terrestrial gravity data. Regarding GNSS/Leveling data, the installation of 3D control points was completed in 2019 and the adjustment of GNSS and leveling data is ongoing to allow for the application of verified and adjusted GNSS/Leveling data in the future. Therefore, a new geoid model will be developed until the end of 2023 by applying new terrestrial gravity and GNSS/Leveling data. Overall, it is expected that the precision will be improved to approximately 1–1.5 cm, except in the mountainous areas, owing to new data gathering efforts and the maintenance of the fundamental data.

A Gitbash-Generative Model for an Enhanced Query Processing In a Distributed Database System

This research study is directly focused on an enhanced query processing system using GitBash- Deep Generative Model, it is use to improve the performance of big data. Due to Poor query execution plan and absence of an improved aggregate query method which impose threats to qualities of good query processing in distributed databases which also cause memory pressure in a database, inflated central processing unit (CPU) and an overall reduction in concurrency. Also the volume of data use in any organization is progressively increasing in it seize, thereby resulting or demand a large storage location or space system. The availability of intended software that will confront the problem of storage contents and execution plan for query processing is a vital challenge facing big data in a processing system, which can prompt to information loss and missing record of vital document in an enterprises. The study will boost solution and addresses the problem of latencies, inability to transform and store queries, and poor query processing plans for future improvement of distributed databases, using an unsupervised learning approach such as deep generative model. The adopted methodology is dynamic system development method (DSDM). php programming language and mongoDB database is adopted for implementation. The datasets used for the proposed system was generated from e-library server/data.json (query) and is inserted into MongoDB database json format. The datasets are all trained and recognized by the Deep Generative algorithm through the Git Bash server. The proposed system result shows highly increase in the efficiency of management of big data and improved query processing. General Term Query Processing System Keywords Big Data, Deep Generative Model, Query Processing System, Information Management, Gitbash.

Reconciling Simulations and Experiments With BICePs: A Review.

Bayesian Inference of Conformational Populations (BICePs) is an algorithm developed to reconcile simulated ensembles with sparse experimental measurements. The Bayesian framework of BICePs enables population reweighting as a post-simulation processing step, with several advantages over existing methods, including the proper use of reference potentials, and the estimation of a Bayes factor-like quantity called the BICePs score for model selection. Here, we summarize the theory underlying this method in context with related algorithms, review the history of BICePs applications to date, and discuss current shortcomings along with future plans for improvement.

BioMolViz: A Community Devoted to the Assessment of Biomolecular Visual Literacy

Educators in the molecular life sciences rely heavily on visual representations of biological molecules. The explicit instruction of visual literacy of the representations, however, is frequently overlooked, leaving students confused about what information is being communicated and/or assessed. The BioMolViz learning community was developed to bring attention to the need for visual literacy instruction and assessment distinct from the interpretation of these representations. Over the past several years, BioMolViz has organized interactive workshops devoted to enhancing instructor skillsets through the collaborative development of biomolecular visualization (BMV) assessments. In response to the pandemic, this year the workshops were moved online. In these workshops, participants engage with like minded scientists to design and peer review BMV assessments and share BMV resources, tools, and activities. Using the BioMolViz Framework (biomolviz.org), a tool that unpacks twelve overarching themes of BMV into a collection of learning goals and objectives, participants produce high-quality assessment instruments for evaluating visual literacy skills, which will be made broadly available to the molecular life sciences community through an online repository. We have found that our process encourages collaboration while developing assessment strategies, which has the added benefit of enriching the pedagogy of our growing community of educators. We will present our strategies for creating engaging workshops, the translation of these meetings to effective online experiences, and challenges resulting from the shift to online format. Guided by participant surveys, we have modified the online experience, and will share our plans for future improvements to increase interactivity and sense of community. We invite the members of ASBMB to join our community of practice, providing an opportunity to expand their engagement with our growing and evolving network of collaborating educators.

Evaluation and Lessons Learned from a Campus as a Living Lab Program to Promote Sustainable Practices

Any group that creates challenging goals also requires a strategy to achieve them and a process to review and improve this strategy over time. The University of British Columbia (UBC) set ambitious campus sustainability goals, including a reduction in its greenhouse gas emissions to 33% below the 2007 level by 2015, and 100% by 2050 (UBC, 2006). The University pursued these goals through a number of specific projects (such as major district energy upgrade and a bioenergy facility) and, more generally, through a “Campus as a Living Lab” (CLL) initiative to marry industry, campus operations, and research to drive innovative solutions. The CLL program has achieved significant successes while also demonstrating many opportunities for improvements and lessons learned. The aim of this study was to examine the UBC CLL program, to identify and formalize its operations, to extract key transferable characteristics, and to propose replicable processes that other universities and municipalities can follow to expand their sustainable practices in similar ways. There was a learning curve with implementing a CLL program at UBC; thus, the goal of this study was to potentially shorten this learning curve for others. The research involved an ethnographic approach in which researchers participated in the CLL process, conducted qualitative analysis, and captured the processes through a series of business process models. The research findings are shared in two parts: 1. generalized lessons learned through key transferrable characteristics; 2. a series of generic organizational charts and business process models (BPMs) culminated with learned strategies through defined processes that illustrate what was required to create a CLL program at UBC. A generalized future improvement plan for UBC CLL programs is defined, generic BPMs about CLL projects are evaluated, and the level of engagement of multiple stakeholders through phases of project life cycle given in the conclusion for future use of other Living Lab organizations.

Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit

The Liquid Argon Time Projection Chamber (LArTPC) technology plays an essential role in many current and future neutrino experiments. Accurate and fast simulation is critical to developing efficient analysis algorithms and precise physics model projections. The speed of simulation becomes more important as Deep Learning algorithms are getting more widely used in LArTPC analysis and their training requires a large simulated dataset. Heterogeneous computing is an efficient way to delegate computationally intensive tasks to specialized hardware. However, as the landscape of compute accelerators quickly evolves, it becomes increasingly difficult to manually adapt the code to the latest hardware or software environments. A solution which is portable to multiple hardware architectures without substantially compromising performance would thus be very beneficial, especially for long-term projects such as the LArTPC simulations. In search of a portable, scalable and maintainable software solution for LArTPC simulations, we have started to explore high-level portable programming frameworks that support several hardware backends. In this paper, we present our experience porting the LArTPC simulation code in the Wire-Cell Toolkit to NVIDIA GPUs, first with the CUDA programming model and then with a portable library called Kokkos. Preliminary performance results on NVIDIA V100 GPUs and multi-core CPUs are presented, followed by a discussion of the factors affiecting the performance and plans for future improvements.

Speech Recognition Based Prescription Generator

Lots of cases have been recorded that are caused by misinterpretation of illegible handwritten prescriptions. In this paper, we propose a mobile device-based speech recognition approach to help doctors utter prescription and get the prescription in tabularized format rather than writing it manually. We start with data collection for the task at hand, which is a Natural Language Processing task. This is followed by its preprocessing and further, we use the Stack-Propagation approach to address the joint task of intent detection and slot filling. After refining our dataset and model parameters as well as the training parameters we finally achieve acceptable results. The scope of this paper is discussed, and future improvement plans are laid.

Competences of teachers of natural-physical sciences. An analysis from the perception of the students

This article arises as a proposal in view of the need to evaluate the scientific competences promoted by teachers of the subject of physics at the level of basic secondary and secondary technical education. A valid questionnaire was designed from the application of scalar analysis, factorial analysis and content analysis, which is composed of 49 items evaluated by means of a Likert scale with five levels of response. It was applied in a sample of 249 students enrolled in a public educational institution during 2019, characterized by their good results in the area of physics in state tests. The results allowed the identification of strengths in the four dimensions proposed by the Ministerio de Educación Nacional, Colombia (pedagogical, didactic, disciplinary and behavioural), in contrast with some weaknesses within which the evaluation process stands out as the one with the greatest impact, since the students state that this process is assumed by the teacher as a mechanism of pressure and control. When investigating the teachers in a complementary way, positions were determined that were totally opposite to those held by the students, then it is suggested for future research to consider both the students and the teachers as informants and a supervision of the students’ notes as the end of triangulating the results to refine the conclusions, on which future improvement plans will depend.

중학교 스포츠강사에 대한 구조화 분석

The purpose of this study is to present basic data and realistic policy directions for future improvement plans through the survey on the employment and system of school instructors. In order to investigate the perception of the members, I visited the unit school and interviewed the physical education teachers. The interview was conducted for five month in June 2019, and an in-depth interview was conducted with a total of six people. The main issues of regular teachers and school officials derived through in-depth interviews were job security and treatment of instructor occupations. Assessing the ability and quality of instructors to teach students, budgeting for school sports clubs at government level for effective sports club activities, It was suggested to establish various systems for the activation of school sports club activities, such as reflection on career and college entrance.<BR> First, there are major revisions to administrative and policy reinforcement, such as securing the budget, This is a reality where the budget for sports instructors is very low and the population of sports instructors must be increased for better teaching quality. In addition, sports instructors are new jobs created by job creation and are hired as contract workers, which puts them in jeopardy every year. In this situation, sports instructors increase job insecurity and job insecurity, which can affect job satisfaction and quality of instruction. Therefore, a rational improvement plan such as employment stability through the contract of arms and the transition to public service is needed.<BR> Second, institutional support measures include reflecting the career and academic system of sports club activities, and expanding the facilities such as classrooms, equipment, and tools. There are still many students and parents who feel that the major subjects in Korea, English, and Sue are important, and that sports activities are a waste of time. In addition, sports club activities are receiving more enthusiasm because they have no experience in school records. For this reason, awards and participation events through sports club activities should remain in the history and be reflected in the career and college system, and should be introduced in the university entrance system. In addition, school sports activities are conducted at the same time and in the same place as other sports, which affects the class a lot. In addition, as the number of students per sports instructor is large, there is a lack of equipment and class tools necessary for the class, so some students are waiting and some students are participating. Therefore, the expansion of facilities, such as separate places and lacking teaching equipment and tools, should be improved for each event.<BR> Third, there are ways to improve the instructor"s work, such as their own teaching methods, curriculum planning, and reinforcement of their leadership capacity through training activities. Sports instructors are expected to teach various sports and develop sports club activities so that students can participate with interest. To do this, you need to create your own teaching methods and course plans so that students can experience a variety of sports activities. In addition, various trainings are underway to revitalize school sports and strengthen leadership skills. Through these trainings, students will have to learn their teaching techniques and instructional know-how to strengthen their competences and make quality lessons.

Current status of slow extraction from J-PARC Main Ring

A 30 GeV proton beam accelerated in the J-PARC Main Ring (MR) is slowly extracted by the third integer resonant extraction and delivered to the hadron experimental facility. A dynamic bump scheme under achromatic condition drastically reduces beam hit rate on the septa devices, and we have attained 51 kW SX operation at 5.2 s cycle with high slow extraction efficiency of 99.5%. A spill duty factor indicating a uniformity of the time structure of the extracted beam is typically 50%. The current SX performance and future plans for improvements will be presented.

국내 열린관광지에 대한 인식 조사 연구: IPA분석을 활용하여

The purpose of this study is to compare and analyze the recognition and importance of selected tourist attractions in Korea using IPA (Importance Performance Analysis). This study is to investigate the basic perceptions of tourists in the open tourist resort development project in Korea and to suggest future improvement plans and suggest policies. Based on the results of this study, it can be concluded that the establishment of accessible tourism destinations and the development of courses will provide the necessary information for tourists without restrictions. In the future, if it is possible to develop a scale capable of measuring accessible tourism on the basis of tourist awareness survey, it will be able to provide a basis for managing tourist attractions as well as accessible tourism destinations.

A Magnetic Measurement Model for Real-Time Control of Synchrotrons

In this paper, we present a measurement model for estimating the magnetic field of a synchrotron-type particle accelerator, based on sensors installed in a reference magnet. The model combines the calibration of the individual sensors with the experimental characterization of the magnets to infer, in absolute terms, the value of the average field in the ring, as needed for the real-time feedback control of the accelerator. Implementation of this model at the extra low energy antiproton (ELENA) ring at the European Organization for Nuclear Research (CERN) is used as a case study. We describe first the measurement setup and method, followed by the detailed definition of the model, along with its parameters and an evaluation of their value and uncertainty. Next, we assess the combined uncertainty of the whole measurement chain. Finally, we discuss the results obtained so far during the machine commissioning phase and outline our plans for future improvement.

Regional Climate Model Evaluation System powered by Apache Open Climate Workbench v1.3.0: an enabling tool for facilitating regional climate studies

Abstract. The Regional Climate Model Evaluation System (RCMES) is an enabling tool of the National Aeronautics and Space Administration to support the United States National Climate Assessment. As a comprehensive system for evaluating climate models on regional and continental scales using observational datasets from a variety of sources, RCMES is designed to yield information on the performance of climate models and guide their improvement. Here, we present a user-oriented document describing the latest version of RCMES, its development process, and future plans for improvements. The main objective of RCMES is to facilitate the climate model evaluation process at regional scales. RCMES provides a framework for performing systematic evaluations of climate simulations, such as those from the Coordinated Regional Climate Downscaling Experiment (CORDEX), using in situ observations, as well as satellite and reanalysis data products. The main components of RCMES are (1) a database of observations widely used for climate model evaluation, (2) various data loaders to import climate models and observations on local file systems and Earth System Grid Federation (ESGF) nodes, (3) a versatile processor to subset and regrid the loaded datasets, (4) performance metrics designed to assess and quantify model skill, (5) plotting routines to visualize the performance metrics, (6) a toolkit for statistically downscaling climate model simulations, and (7) two installation packages to maximize convenience of users without Python skills. RCMES website is maintained up to date with a brief explanation of these components. Although there are other open-source software (OSS) toolkits that facilitate analysis and evaluation of climate models, there is a need for climate scientists to participate in the development and customization of OSS to study regional climate change. To establish infrastructure and to ensure software sustainability, development of RCMES is an open, publicly accessible process enabled by leveraging the Apache Software Foundation's OSS library, Apache Open Climate Workbench (OCW). The OCW software that powers RCMES includes a Python OSS library for common climate model evaluation tasks as well as a set of user-friendly interfaces for quickly configuring a model evaluation task. OCW also allows users to build their own climate data analysis tools, such as the statistical downscaling toolkit provided as a part of RCMES.

Tingkat Kepuasan Mahasiswa Terhadap Kualitas Pelayanan Angkot di Kota Medan

In general, urban transportation experiences similar problem, which is the low level of public transport occupancy. There are numerous factors that can cause such condition, of which can be summarized in the form of service quality shortcoming. Service quality of such public facility is measured and evaluated based on user experience, and planners utilize it to plan for future improvements. Importance-Performance Analysis is used in this research to identify aspects of service that are expected to be on top of enhancement priority list. Based on 159 students’ responses, it was found that six service criterias are in high-priority-quadrant. These are crowding, sitting comfort, hygiene, driver behavior, driver cleanliness, and security. Specifically, driver behavior aspect is regarded as highly prioritized, whereas on the contrary angkot fare and operating time are considered good enough and thus placed on low-priority list.