Evaluation Plan Research Articles

Model construction and empirical of urban characteristic planning evaluation index system

With accelerated urbanisation, the importance of urban characteristic planning has become increasingly prominent. It has been a focus on how to conduct scientific urban characteristic planning evaluation to ensure high quality and sustainable development of urban characteristic planning. Therefore, this study proposed an urban characteristic planning evaluation index system based on support vector machine (SVM). The process uses hierarchical analysis to determine the relative weight values, calculates fuzzy values for indicators that cannot be directly and objectively evaluated and then introduces SVM for precise processing of interval data. The test results showed that the accuracy of the research method was 0.9760, 0.9600 and 0.9750 when taking the maximum bias value of 0.5 in the three datasets. The optimisation time of the research method for the parameters of the UCI (University of California Irvine) dataset remained within 650–750 ms. The evaluation results of the research method fit well with the expert evaluation results. The above results show that the research method has high data accuracy and operational efficiency in the evaluation of urban characteristic planning, which can make reasonable evaluation of urban characteristic planning. This method can provide reliable reference basis for government decision making.

An ontology‐based digital test and evaluation master plan (dTEMP) compliant with DoD policy

AbstractTest and evaluation (TE) planning is a critical part of systems engineering. However, it has not received as much attention from digital engineering efforts as early‐stage design and analysis. Digital engineering has the potential to reduce the risk and effort associated with TE, while leveraging existing digital capabilities to add value. One aspect in particular that may benefit from such attention is the Department of Defense's Test and Evaluation Master Plan (TEMP). The purpose of the TEMP is to identify the key processes with respect to the TE of a product, and to specify the roles and responsibilities of key personnel and organizations. Concerns have been raised regarding the document‐based nature of the TEMP and the increased risk and reduced reward that this entails. In this paper, we investigate the potential benefits of digitalizing the TEMP and outline an incremental approach for achieving this. We also present a set of ontologies, collectively known as the Digital TEMP (dTEMP), and investigate potential benefits and limitations by applying the dTEMP to an example test program.

A Study on Impact of Accounting Information system in Financial Performance

This research examines the connection between accounting data performance; the research uses statistical examination of financial statements and key performance indicators, while qualitative interviews with industry experts and stakeholders provide insights into the subjective aspects of accounting information utilization. The findings show a noteworthy association between the quality, timeliness, and pertinence of accounting information additionally financial performance metrics like profitability, liquidity, solvency, and shareholder value. Elements that impact the effectiveness of accounting data include regulatory frameworks, technological advancements, managerial competence, and organizational culture. The study emphasizes the importance of transparency, accuracy, and reliability in financial reporting practices, enhancing investor confidence, facilitating informed decision-making, and fostering sustainable growth. Accounting information is also crucial in risk management, strategic planning, and performance evaluation, highlighting its value as a strategic asset for organizations in today’s dynamic business environment. This study broadens our comprehension by providing a thorough grasp. of the interplay between accounting information and financial performance, offering valuable insights for practitioners, policymakers, and researchers.

Matching the scales of planning and environmental risk: an evaluation of Community Wildfire Protection Plans in the western US

Theory predicts that effective environmental governance requires that the scales of management account for the scales of environmental processes. A good example is community wildfire protection planning. Plan boundaries that are too narrowly defined may miss sources of wildfire risk originating at larger geographic scales whereas boundaries that are too broadly defined dilute resources. Although the concept of scale (mis)matches is widely discussed in literature on risk mitigation as well as environmental governance more generally, rarely has the concept been rigorously quantified. We introduce methods to address this limitation, and we apply our approach to assess scale matching among Community Wildfire Protection Plans (CWPPs) in the western US. Our approach compares two metrics: (1) the proportion of risk sources encompassed by planning jurisdictions (sensitivity) and (2) the proportion of area in planning jurisdictions in which risk can originate (precision). Using data from 852 CWPPs and a published library of 54 million simulated wildfires, we demonstrate a trade-off between sensitivity and precision. Our analysis reveals that spatial scale match—the product of sensitivity and precision—has an n-shaped relationship with jurisdiction size and is maximal at approximately 500 km2. Bayesian multilevel models further suggest that functional scale match—via neighboring, nested, and overlapping planning jurisdictions—may compensate for low sensitivity. This study provides a rare instance of a quantitative framework to measure scale match in environmental planning and has broad implications for risk mitigation as well as in other environmental governance settings.

Evaluating the use of three-dimensional reconstruction visualization technology for precise laparoscopic resection in gastroesophageal junction cancer.

Laparoscopic gastrectomy for esophagogastric junction (EGJ) carcinoma enables the removal of the carcinoma at the junction between the stomach and esophagus while preserving the gastric function, thereby providing patients with better treatment outcomes and quality of life. Nonetheless, this surgical technique also presents some challenges and limitations. Therefore, three-dimensional reconstruction visualization technology (3D RVT) has been introduced into the procedure, providing doctors with more comprehensive and intuitive anatomical information that helps with surgical planning, navigation, and outcome evaluation. To discuss the application and advantages of 3D RVT in precise laparoscopic resection of EGJ carcinomas. Data were obtained from the electronic or paper-based medical records at The First Affiliated Hospital of Hebei North University from January 2020 to June 2022. A total of 120 patients diagnosed with EGJ carcinoma were included in the study. Of these, 68 underwent laparoscopic resection after computed tomography (CT)-enhanced scanning and were categorized into the 2D group, whereas 52 underwent laparoscopic resection after CT-enhanced scanning and 3D RVT and were categorized into the 3D group. This study had two outcome measures: the deviation between tumor-related factors (such as maximum tumor diameter and infiltration length) in 3D RVT and clinical reality, and surgical outcome indicators (such as operative time, intraoperative blood loss, number of lymph node dissections, R0 resection rate, postoperative hospital stay, postoperative gas discharge time, drainage tube removal time, and related complications) between the 2D and 3D groups. Among patients included in the 3D group, 27 had a maximum tumor diameter of less than 3 cm, whereas 25 had a diameter of 3 cm or more. In actual surgical observations, 24 had a diameter of less than 3 cm, whereas 28 had a diameter of 3 cm or more. The findings were consistent between the two methods (χ2 = 0.346, P = 0.556), with a kappa consistency coefficient of 0.808. With respect to infiltration length, in the 3D group, 23 patients had a length of less than 5 cm, whereas 29 had a length of 5 cm or more. In actual surgical observations, 20 cases had a length of less than 5 cm, whereas 32 had a length of 5 cm or more. The findings were consistent between the two methods (χ2 = 0.357, P = 0.550), with a kappa consistency coefficient of 0.486. Pearson correlation analysis showed that the maximum tumor diameter and infiltration length measured using 3D RVT were positively correlated with clinical observations during surgery (r = 0.814 and 0.490, both P < 0.05). The 3D group had a shorter operative time (157.02 ± 8.38 vs 183.16 ± 23.87), less intraoperative blood loss (83.65 ± 14.22 vs 110.94 ± 22.05), and higher number of lymph node dissections (28.98 ± 2.82 vs 23.56 ± 2.77) and R0 resection rate (80.77% vs 61.64%) than the 2D group. Furthermore, the 3D group had shorter hospital stay [8 (8, 9) vs 13 (14, 16)], time to gas passage [3 (3, 4) vs 4 (5, 5)], and drainage tube removal time [4 (4, 5) vs 6 (6, 7)] than the 2D group. The complication rate was lower in the 3D group (11.54%) than in the 2D group (26.47%) (χ2 = 4.106, P < 0.05). Using 3D RVT, doctors can gain a more comprehensive and intuitive understanding of the anatomy and related lesions of EGJ carcinomas, thus enabling more accurate surgical planning.

Mental Health Programs for the UK-Based LGBTQ Community Through Education and Employment Opportunities

Background: This study explores mental health programs designed for the LGBTQ community, focusing on education and employment opportunities as a way to improve mental wellbeing. Methods: This Systemic Review evaluate existing mental health programs for LGBTQ individuals in the UK. It consider factors such as economic disparities, social inequalities, and communication barriers faced by LGBTQ individuals. They will draw on demographic data and scholarly research to highlight the importance of inclusive education policies and job opportunities. Results: The evaluation plan outlined in this study emphasizes a research design incorporating observational methods and measurement of various factors, such as social behaviour, job satisfaction, and skill enhancement. The researchers will also involve relevant stakeholders, including government agencies and NGOs, for the successful implementation of these mental health programs. Conclusions: By prioritizing the needs of the LGBTQ community and collaboration among stakeholders, this study aims to contribute to the advancement of mental health initiatives that promote inclusivity and equity by maintaining equal opportunities.

Radiotherapy Plan Quality Assurance in NRG Oncology Trials for Brain and Head/Neck Cancers: An AI-Enhanced Knowledge-Based Approach.

The quality of radiation therapy (RT) treatment plans directly affects the outcomes of clinical trials. KBP solutions have been utilized in RT plan quality assurance (QA). In this study, we evaluated the quality of RT plans for brain and head/neck cancers enrolled in multi-institutional clinical trials utilizing a KBP approach. The evaluation was conducted on 203 glioblastoma (GBM) patients enrolled in NRG-BN001 and 70 nasopharyngeal carcinoma (NPC) patients enrolled in NRG-HN001. For each trial, fifty high-quality photon plans were utilized to build a KBP photon model. A KBP proton model was generated using intensity-modulated proton therapy (IMPT) plans generated on 50 patients originally treated with photon RT. These models were then applied to generate KBP plans for the remaining patients, which were compared against the submitted plans for quality evaluation, including in terms of protocol compliance, target coverage, and organ-at-risk (OAR) doses. RT plans generated by the KBP models were demonstrated to have superior quality compared to the submitted plans. KBP IMPT plans can decrease the variation of proton plan quality and could possibly be used as a tool for developing improved plans in the future. Additionally, the KBP tool proved to be an effective instrument for RT plan QA in multi-center clinical trials.

Automated glioblastoma patient classification using hypoxia levels measured through magnetic resonance images

IntroductionThe challenge of treating Glioblastoma (GBM) tumors is due to various mechanisms that make the tumor resistant to radiation therapy. One of these mechanisms is hypoxia, and therefore, determining the level of hypoxia can improve treatment planning and initial evaluation of its effectiveness in GBM. This study aimed to design an intelligent system to classify glioblastoma patients based on hypoxia levels obtained from magnetic resonance images with the help of an artificial neural network (ANN).Material and methodMR images and PET measurements were available for this study. MR images were downloaded from the Cancer Imaging Archive (TCIA) database to classify glioblastoma patients based on hypoxia. The images in this database were prepared from 27 patients with glioblastoma on T1W + Gd, T2W-FLAIR, and T2W. Our designed algorithm includes various parts of pre-processing, tumor segmentation, feature extraction from images, and matching these features with quantitative parameters related to hypoxia in PET images. The system’s performance is evaluated by categorizing glioblastoma patients based on hypoxia.ResultsThe results of classification with the artificial neural network (ANN) algorithm were as follows: the highest sensitivity, specificity, and accuracy were obtained at 86.71, 85.99 and 83.17%, respectively. The best specificity was related to the T2W-EDEMA image with the tumor to blood ratio (TBR) as a hypoxia parameter. T1W-NECROSIS image with the TBR parameter also showed the highest sensitivity and accuracy.ConclusionThe results of the present study can be used in clinical procedures before treating glioblastoma patients. Among these treatment approaches, we can mention the radiotherapy treatment design and the prescription of effective drugs for the treatment of hypoxic tumors.

Protocol for the Support Application for Food PAntrieS trial: design, implementation, and evaluation plan for a digital application to promote healthy food access and support food pantry operations.

Food-insecure households commonly rely on food pantries to supplement their nutritional needs, a challenge that was underscored during the COVID-19 pandemic. Food pantries, and the food banks that supply them, face common challenges in meeting variable client volume and dietary needs under normal and emergency (e.g., pandemic, natural disaster) conditions. A scalable digital strategy that has the capacity to streamline the emergency food distribution system, while promoting healthy food options, managing volunteer recruitment and training, and connecting to emergency management systems in times of need, is urgently required. To address this gap, we are developing a working mobile application (app) called the Support Application for Food PAntrieS (SAFPAS) and will evaluate its feasibility and impact on food pantry staff preparedness, stocking, and client uptake of healthful foods and beverages in two urban United States settings. This paper describes the protocol for a randomized controlled trial of the SAFPAS mobile application. We will conduct formative research in Baltimore, Maryland and Detroit, Michigan to develop and refine the SAFPAS app and increase scalability potential to other urban settings. Then we will test the app in 20 food pantries in Baltimore randomized to intervention or comparison. The impact of the app will be evaluated at several levels of the emergency food system, including food pantry clients (n = 360), food pantry staff and volunteers (n = 100), food pantry stock, and city agencies such as the local food bank and Office of Emergency Management. The primary outcome of the SAFPAS trial is to improve the healthfulness of the foods received by food pantry clients, measured using the Food Assessment Scoring Tool (FAST). Post-trial, we will conduct additional formative research in Detroit to prepare the app for scale-up. We anticipate that SAFPAS will improve alignment in the supply and demand for healthy foods among food pantry clients, food pantries, and city agencies which supply food in Baltimore. Real-time, bidirectional communication between entities across the system allows for increased situational awareness at all levels during normal and emergency operations. By conducting formative research in Detroit, we hope to increase the scalability of the SAFPAS app to additional settings nationwide. NCT87654321. https://classic.clinicaltrials.gov/ct2/show/NCT05880004.

SOSIALISASI PEMBUATAN DETERJEN CAIR DI LINGKUNGAN ANGGOTA KOPERASI SUMBER REZEKI KOTA BINJAI

Empowering housewives as members of society and still being classified as productive workers is very important, aimed at increasing awareness and independence in business, as well as expanding employment opportunities to increase family income in an effort to achieve a happy and prosperous family. In this regard, this can be done through various alternative activities, including training in making liquid detergent. Soap is a commodity that cannot be separated from household needs. It can be said that part of the routine expenses for housewives each month is allocated to purchasing washing soap. The methods used in this community service activity are socialization, discussion and practice or demonstration regarding raw materials, work procedures and calculation of production costs for making liquid detergent. The training participants are members of the Sumber Rezeki Cooperative in Sumber Mulyo Rejo Village with a total of 20 training participants. This activity was carried out in Sumber Mulyo Rejo Village, Binjai City on February 24 2024. The evaluation plan for service activities is that the target number of training participants is achieved, the training objectives are achieved well, the planned material targets are achieved and the participants are able to understand the training material. The result of this training activity in making liquid detergent is that members of the Sumber Rezeki cooperative in Binjai city have knowledge of making liquid detergent and provide innovation to improve the economy.

Advances in 3D Inner Ear Reconstruction Software for Cochlear Implants: A Comprehensive Review.

Auditory impairment stands as a pervasive global issue, exerting significant effects on individuals' daily functioning and interpersonal engagements. Cochlear implants (CIs) have risen as a cutting-edge solution for severe to profound hearing loss, directly stimulating the auditory nerve with electrical signals. The success of CI procedures hinges on precise pre-operative planning and post-operative evaluation, highlighting the significance of advanced three-dimensional (3D) inner ear reconstruction software. Accurate pre-operative imaging is vital for identifying anatomical landmarks and assessing cochlear deformities. Tools like 3D Slicer, Amira and OTOPLAN provide detailed depictions of cochlear anatomy, aiding surgeons in simulating implantation scenarios and refining surgical approaches. Post-operative scans play a crucial role in detecting complications and ensuring CI longevity. Despite technological advancements, challenges such as standardization and optimization persist. This review explores the role of 3D inner ear reconstruction software in patient selection, surgical planning, and post-operative assessment, tracing its evolution and emphasizing features like image segmentation and virtual simulation. It addresses software limitations and proposes solutions, advocating for their integration into clinical practice. Ultimately, this review underscores the impact of 3D inner ear reconstruction software on cochlear implantation, connecting innovation with precision medicine.

Estimation of shale adsorption gas content based on machine learning algorithms

Shale gas is a clean and low-carbon natural gas resource. It mainly exists in both adsorbed and free states in pores and fractures. To accurately estimate the in-situ adsorption gas content (AGC), which is helpful in resource evaluation and development planning, methane isothermal adsorption data and geological parameters have been collected, such as total organic carbon (TOC) content, thermal maturity (Ro), siliceous mineral content (VQF), total clay content (VTC), water content (VWC), and temperature (T). Using machine learning (ML) methods, the in-situ AGC estimation models were constructed and optimized. Various geological factors affecting methane adsorption were evaluated, and an application was conducted in the Wufeng-Formation shale. The results reveal that the four ML models have higher accuracy in predicting Langmuir volume (VL) and Langmuir pressure (PL) than empirical formulas and linear regression models. Among the four ML models, the Random Forest Regression (RFR) and eXtreme Gradient Boosting Regression (XGBR) models perform the best, with R2 higher than 0.85. TOC and T are the main factors affecting methane adsorption, followed by Ro and VQF, while the importance of VTC and VWC is relatively low. According to different combinations of geological parameters, there are three schemes for ML model construction. Among them, scheme 1 based on all six geological parameters has the highest accuracy and is most beneficial to predicting AGC. Gradually reducing VWC, VTC, and VQF results in a slight decrease in accuracy, with R2 decreasing by at most about 6%, scheme 2 is suitable for rougher estimation of AGC. Further removal of T and Ro results in a significant decrease in accuracy, with R2 decreasing by up to 50% and MRE exceeding 30%, rendering scheme 3 unavailable for AGC prediction. The AGC of Wufeng-Longmaxi shale is successfully predicted based on XGBR model, with AGC mainly in 1.0 m3/ton-4.0 m3/ton. Overall, the ML models based on multiple geological parameters can simulate the real reservoir environment and achieve rapid and accurate estimation of in-situ AGC.

The degree of implementing STEM practices among mathematics teachers at the middle school level from the teachers’ and educational supervisors’ perspectives

The current quantitative study aims to examine the degree of implementation of STEM practices among middle school mathematics teachers from the teachers’ and educational supervisors’ perspectives. The study also seeks to identify the statistical significance between the responses of teachers and supervisors regarding the degree of implementing STEM practices. STEM is an acronym for the integrative approach among science, technology, engineering and mathematics. The study used a questionnaire that was built based on a four-level Likert scale as a tool for collecting data using the descriptive survey method. Sixty-four middle school mathematics teachers and seven educational supervisors of mathematics participated in the study that took place in Al-Ahsa Governorate, Saudi Arabia. Findings revealed that the participating teachers implemented STEM practices moderately in their classrooms in the main three domains which are lesson evaluation, lesson implementation and lesson planning, respectively. In addition, there are statistically significant differences between the participating teachers and supervisors regarding the degree of implementing the STEM practices in favor of the teachers. The study recommends dedicating sufficient funds for STEM education, creating creative STEM websites and labs and obtaining access to STEM resources and materials. It is concluded that there is a great need for preparing mathematics teachers to apply STEM practices in their classrooms.

Management Analysis of the Uhamka Physics Laboratory in Jakarta: Evaluation of Planning, Organizing and Maintenance

This research aims to determine laboratory management in physics learning at FKIP UHAMKA Jakarta. This research is a qualitative descriptive study. This research was conducted at the UHAMKA Physics Laboratory, Jakarta. Data collection methods include observation, interviews and documentation. Data analysis techniques consist of data reduction, data presentation, and drawing conclusions. The results of the research show that laboratory planning is not yet good, because there are overlapping duties and responsibilities. From the results of interviews, the organization of the laboratory has not been carried out well because there is no laboratory assistant specifically assigned to take care of it, so far the person in charge of the laboratory also doubles as a lecturer so that the laboratory does not managed well, maintaining laboratory cleanliness has been said to be good. No dust sticks to the practice table and equipment. Students are involved in maintenance by cleaning practical equipment before and after learning. Maintenance of practical equipment is carried out periodically as stated by Mr. SG, the last stage is supervision, which aims to monitor and control laboratory management from various aspects, be it supervision of equipment and materials, laboratory users or supervision of human resources or management staff.

Comparing Video Head Impulse Testing With Rotary Chair in Pediatric Patients: A Controlled Trial.

To investigate the efficacy of video head impulse testing (VHIT) in detecting vestibular loss in pediatric patients with abnormal rotary chair testing, compared to a control group with normal rotary chair testing. Prospective, nonrandomized, controlled trial. Pediatric vestibular program at tertiary level children's hospital. Patients 3 to 18 years of age were recruited to undergo VHIT and rotary chair testing between September 2015 and November 2022. VHIT results were compared between an experimental group of 23 patients with vestibular symptoms and abnormal rotary chair testing results versus a control group of 14 patients without vestibular symptoms and with normal rotary chair testing results. The experimental group demonstrated reduced mean VHIT gain for the lateral semicircular canals (right = 0.83; left = 0.75) relative to the control group (right = 1.04, P = .005; left = 0.98, P < .001), but there was no significant difference between groups in superior and posterior canal responses. Among controls, there were no significant differences in mean gain values for each canal plane between age groups (3-7, 8-12, and 13-18 years) or between genders. A VHIT lateral canal gain value <0.85 and/or corrective saccades demonstrated 100% specificity and 100% positive predictive value for detecting vestibular loss on rotary chair, but only 69.6% sensitivity and 66.7% negative predictive value. VHIT is a useful test for detecting impairment of the lateral semicircular canals in children, though its sensitivity is limited relative to rotary chair. Its role in detecting vertical canal dysfunction in pediatric patients may be more limited and warrants further study.

UAV vision-based crack quantification and visualization of bridges: system design and engineering application

Accurately measuring visible cracks in bridges is crucial for their structural health diagnosis, damage detection, performance evaluation, and maintenance planning. The primary means of visual crack detection still relies heavily on manual visual inspection, an inefficient process that can pose significant safety risks. This article develops a unmanned aerial vehicle (UAV) vision-based surface crack measurement methodology and visualization scheme for the bridges that can detect and measure cracks automatically with improved efficiency. The surface crack measurement methodology is achieved by designing a three-stage crack sensing system including the You Only Look Once-based crack recognition, U-shaped network-based crack segmentation, and deep-vision-based crack width calculation. This workflow is integrated into a comprehensive UAV inspection system, which is intended for operation at the field. The surface crack visualization scheme is accomplished by taking advantage of time-series image fusion, GPS information migration, and three-dimensional (3D) point cloud technique to reconstruct the 3D geometrical model of the tested bridge, which is convenient for unveiling the crack information in the bridge. The proposed methodology was successfully validated by a case study on an arch bridge. The achievement of this article promotes the UAV vision-based bridge’s surface crack inspection technology to a new status that no preparation for pasting calibration marker is needed, and crack identification, segmentation, and width calculation are realized promptly during the UAV flying on-site, as well as damage evaluation for bridges is visually fulfilled based on the reconstructed digital-graphical 3D model. The working environments and influencing factors to the developed system are sufficiently discussed. Certain limitations in the current application are pointed out for future improvements.

An end-to-end deep convolutional neural network-based dose engine for parotid gland cancer seed implant brachytherapy.

Seed implant brachytherapy (SIBT) is a promising treatment modality for parotid gland cancers (PGCs). However, the current clinical standard dose calculation method based on the American Association of Physicists in Medicine (AAPM) Task Group 43 (TG-43) Report oversimplifies patient anatomy as a homogeneous water phantom medium, leading to significant dose calculation errors due to heterogeneity surrounding the parotid gland. Monte Carlo Simulation (MCS) can yield accurate dose distributions but the long computation time hinders its wide application in clinical practice. This paper aims to develop an end-to-end deep convolutional neural network-based dose engine (DCNN-DE) to achieve fast and accurate dose calculation for PGC SIBT. A DCNN model was trained using the patient's CT images and TG-43-based dose maps as inputs, with the corresponding MCS-based dose maps as the ground truth. The DCNN model was enhanced based on our previously proposed model by incorporating attention gates (AGs) and large kernel convolutions. Training and evaluation of the model were performed using a dataset comprising 188 PGC I-125 SIBT patient cases, and its transferability was tested on an additional 16 non-PGC head and neck cancers (HNCs) I-125 SIBT patient cases. Comparison studies were conducted to validate the superiority of the enhanced model over the original one and compare their overall performance. On the PGC testing dataset, the DCNN-DE demonstrated the ability to generate accurate dose maps, with percentage absolute errors (PAEs) of 0.67%±0.47% for clinical target volume (CTV) D90 and 1.04%±1.33% for skin D0.1cc. The comparison studies revealed that incorporating AGs and large kernel convolutions resulted in 8.2% (p<0.001) and 3.1% (p<0.001) accuracy improvement, respectively, as measured by dose mean absolute error. On the non-PGC HNC dataset, the DCNN-DE exhibited good transferability, achieving a CTV D90 PAE of 1.88%±1.73%. The DCNN-DE can generate a dose map in less than 10 ms. We have developed and validated an end-to-end DCNN-DE for PGC SIBT. The proposed DCNN-DE enables fast and accurate dose calculation, making it suitable for application in the plan optimization and evaluation process of PGC SIBT.

대학 교양수업에서 학습자 중심의 팀기반 학습 경험

Objectives The purposes of this study were to explores the experiences that learners who participate in team-based learning experience during the learning process, examines the learners' experiences in team-based learning in a contextual setting through a qualitative approach, and seeks educational reflection and implications. Methods For this purpose, this study was conducted on 94 college students who participated in liberal arts classes. To achieve the purpose of the study, first, team-based learning was designed by selecting a ‘pedagogy-based lib-eral arts’ subject. Second, after analyzing the content covered in the selected subject, the instructor's lecture on the learning topic was conducted in advance in the first half of each lesson, and students studied individually through lectures on the learning topic. After watching various learning materials related to the learning topic, team-based learning related to the learning content was applied. Third, we analyzed individual and team activity sheets, study notes for each session, and reflection logs written by learners before and after learning. The response sheets used in the analysis were all qualitative data collected through classes, and were analyzed through the inter-action of categorization, coding, structuring, and interpretation during the data analysis process. Results In terms of learning motivation from the results of this study, first, the motivation for taking the course was participation due to obligation, accidental choice, and unclear expectations due to the nature of liberal arts subjects, and second, the topic and content of learning were based on their own real-life usefulness and career-related topics. Third, actively apply the cognitive information acquired through participation in learning to solve life problems. Fourth, setting learning goals shows educationally important information and context for converting extrinsic motivation into intrinsic motivation. In terms of cognition, learners showed the highest cognitive factors in motivation to take the course, personal learning goals, and learner needs. In terms of interaction, in the process of participating in team-based learning, learners placed first, the attitude of participants, including communication, participation, and courtesy among team members, as the most important, and second, they meaningfully experienced positive experi-ences and emotional support. In terms of teaching and learning, positive experiences such as self-expression, dis-cussion and presentation, initiative, and overcoming presentation anxiety were recognized through participation in team learning. On the other hand, negative aspects could act as a hindrance to positive interactions between team members. In particular, to overcome these obstacles in the early stages of learning, multifaceted efforts were need-ed, such as clear motivation, setting learning goals, setting learning content that suits the learner's needs and inter-ests, emotional support from the instructor, effective learning support materials, and evaluation plans. Conclusions Through this study, it can be seen that, due to the nature of the learning process in team-based classes where learners' interaction is the center, more active and interactive communication and voluntary and proactive participation are required than previous learning experiences.To achieve this, active and flexible re-sponses will be needed to improve the anxiety and dissatisfaction that learners may feel. Through this, the charac-teristics and diversity of individual learners can be mutually recognized and accepted at the beginning of learning, the strengths of team-based learning of emotional support and consideration through interaction between team members can be effectively demonstrated, and learners' expectations and demands for participation in learning can be improved.

Effect of Monitoring and Evaluation Practices and Urban Water Sustainability Project in Rwanda: A Case of WASAC Project in Kigali City

In Rwanda, projects failure is caused by lack of Monitoring and Evaluation staff trainings, technical expertise, design/approach, low level stakeholder involvement, lack of proper planning, lack of supportive supervision, insufficient financial management and poor leadership on feasibility and sustainability project. The general objective of the study is to assess monitoring and evaluation practices and urban water sustainability project in Rwanda. A case of WASAC project in Kigali city and the specific objectives of the study were to assess the influence of project monitoring and evaluation planning on urban water sustainability project in Rwanda, to assess the influence of monitoring and evaluation stakeholders involvement on urban water sustainability project in Rwanda and to determine the effect of monitoring and evaluation trainings on urban water sustainability project in Rwanda. The study was based on two theories such as theory of change and theory of constraints. In this study, a descriptive research design was used and the targeted population includes project management team, project monitoring and evaluation officials, project analysts and engineers. In total they were184 from whom a sample size of 126 was selected as representative of total population. Therefore, a simple sampling technique will be used and data will be collected using questionnaire, interview and documentation. The analysis of data will be done through SPSS version 21. The study findings showed that stakeholders’ involvement is essential in achieving urban water sustainability in the way that M&amp;E planning contribution is at the mean of 3.908 and standard deviation of 0.755, stakeholders involvement contributed to urban water sustainability at the mean of 3.275 and standard deviation of 0.642 while M&amp;E trainings has contributed to urban water sustainability at the mean of4.505 and standard deviation of 0.720 The study found that there are continuous M&amp;E trainings and development of the project staff to acquire skills to implement the project. The study recommended that effective project planning need to be put in place by the project team and managers. Project team should ensure their monitoring and evaluation control plan align with M&amp;E plan. The study recommends a sound stakeholders’ involvement at each phase of the project from initial phase to execution. Keywords: Monitoring and Evaluation, Urban Water Sustainability, WASAC, Project Management, Kigali City Infrastructure

Evaluating the Environmental Impact of Anthropogenic Activities on Human Health: A Systematic Review

Evaluating the Environmental Impact of Anthropogenic Activities on Human Health: A Systematic Review