Plant Biology Experimental Courses in Universities: Status Quo, Limitations and Prospects

Plant biology, as a significant compulsory course for biological science students, is intuitive and practical, which plays a unique role in improving students' comprehensive quality and cultivating their innovation ability. Because of its strong practical characteristics, the experimental course is of great necessity in the study of this course. This paper analyzes the traditional teaching mode of plant biology experiment, as well as its shortcomings in modern teaching, and puts forward diversified reform methods based on the development of contemporary plant biology to promote the teaching mode of plant biology experiment to meet the needs of contemporary students on this subject. Based on the rapid development of modern science and technology, this paper includes the teaching contents, teaching methods, and assessment system of plant biology experiments, and discusses them respectively. This paper aims to improve the teaching efficiency of modern plant biology experiments and help to achieve the goal of efficiently improving students' innovation and scientific research ability.

Advanced eNose-Driven Pedestrian Tracking Pipeline for Intelligent Car Driver Assisting System: Preliminary Results

From a biological point of view, alcohol human attentional impairment occurs before reaching a Blood Alcohol Content (BAC index) of 0.08% (0.05% under the Italian legislation), thus generating a significant impact on driving safety if the drinker subject is driving a car. Car drivers must keep a safe driving dynamic, having an unaltered physiological status while processing the surrounding information coming from the driving scenario (e.g., traffic signs, other vehicles and pedestrians). Specifically, the identification and tracking of pedestrians in the driving scene is a widely investigated problem in the scientific community. The authors propose a full, deep pipeline for the identification, monitoring and tracking of the salient pedestrians, combined with an intelligent electronic alcohol sensing system to properly assess the physiological status of the driver. More in detail, the authors propose an intelligent sensing system that makes a common air quality sensor selective to alcohol. A downstream Deep 1D Temporal Residual Convolutional Neural Network architecture will be able to learn specific embedded alcohol-dynamic features in the collected sensing data coming from the GHT25S air-quality sensor of STMicroelectronics. A parallel deep attention-augmented architecture identifies and tracks the salient pedestrians in the driving scenario. A risk assessment system evaluates the sobriety of the driver in case of the presence of salient pedestrians in the driving scene. The collected preliminary results confirmed the effectiveness of the proposed approach.

A Diagnostic Framework for the Empirical Evaluation of Learning Maps

Learning progressions and learning map structures are increasingly being used as the basis for the design of large-scale assessments. Of critical importance to these designs is the validity of the map structure used to build the assessments. Most commonly, evidence for the validity of a map structure comes from procedural evidence gathered during the learning map creation process (e.g., research literature, external reviews). However, it is also important to provide support for the validity of the map structure with empirical evidence by using data gathered from the assessment. In this paper, we propose a framework for the empirical validation of learning maps and progressions using diagnostic classification models. Three methods are proposed within this framework that provide different levels of model assumptions and types of inferences. The framework is then applied to the Dynamic Learning Maps® alternate assessment system to illustrate the utility and limitations of each method. Results show that each of the proposed methods have some limitations, but they are able to provide complementary information for the evaluation of the proposed structure of content standards (Essential Elements) in the Dynamic Learning Maps assessment.

Integrative Smart Grids’ Assessment System

The COVID-19 pandemic has significantly affected the energy sector. The new behavior of industrial and non-commercial consumers changes the energy consumption model. In addition, the constraints associated with the coronavirus crisis have led to environmental effects from declining economic activity. The research is based on evidence from around the world showing significant reductions in emissions and improved air quality. This situation requires rethinking the energy development strategy, particularly the construction of smart grids as a leading direction of energy development. Evaluating the efficiency of smart grids is a vital tool for disseminating successful experience in improving their management. This paper proposes an approach to a comprehensive assessment of smart grids based on a comparative analysis of existing methods, taking into account the changes that need to be considered after the experience gained from the COVID-19 pandemic. The approach provides an accurate set of efficiency indicators for assessing smart grids to account for the direct and indirect effects of smart grids’ implementation. This evaluation approach can be helpful to policymakers in developing energy efficiency programs and implementing energy policy.

SISTEM SELF ASSESMENT, DAN PENGETAHUAN MEKANISME DALAM PEMUNGUTAN WAJIB PAJAK DI INDONESIA

Semua negara pasti memliki sistem perpajakan yang beda. Pajak sendiri berfungsi sebagai guna membiayai pengeluaran – perngeluaran, pajak juga bermanfaat untuk digunakan dalam melakukan pembangunan hingga membayar gaji pegawai negeri. Tujuan dari penelitian ini adalah guna mengedukasi masyarakat tentang sistem yang ada dalam pemungutan pajak serta mekanisme dalam pemungutan pajak tersebut. Jenis penelitian yang digunakan berdasarkan masalah yang diteliti adalah penelitian kualitatif. Pajak sendiri merupakan sumber penerimaan negara yang utama. Semakin hari peranan penerimaan pajak bagi pembiayaan umum atau negara semakin besar. Maka sistem pemungutan pajak adalah suatu cara yang dipakai untuk menghitung besarnya pajak yang perlu dibayarkan kepada negara. Hasil penelitian ini sistem pemungutan pajak di Indonesia sepenuhnya bersifat self assesment system. Serta Masalah sistem perpajakan yang berlaku di Indonesia dapat ditelusuri kembali ke rendahnya kesadaran hukum masyarakat Indonesia. Wajib pajak memanfaatkan peluang yang ditawarkan oleh sistem self-assessment ini. Undang-undang yang memperlakukan wajib pajak secara self assessment system kurang kesadaran hukum wajib pajak, lemahnya pengawasan, dan belum optimalnya penerapan sanksi bagi wajib pajak yang melanggarnya. Pengawasan sebelumnya belum berjalan maksimal, dan sanksi bagi Wajib Pajak yang ternyata melakukan atau melakukan pelanggaran perpajakan masih sangat lemah.

Present status of portfolio based training and assessment in postgraduate residency program in Bangabandhu Sheikh Mujib Medical University (BSMMU): A quantitative approach

Since 2009, the portfolio has been a prerequisite for the evaluation of postgraduate residency programs at BSMMU. This descriptive cross-sectional study was conducted with the aim of investigating the current status of portfolio-based training and assessment in BSMMU`s postgraduate training program. Total 264 residents and 30 faculty members selected conveniently and completed the Likert scale-based questionnaire. A checklist was used for reviewing portfolios (n=33) those were preserved by residents. Study revealed that most of the respondents were male (68.6% of residents and 93.3% of faculty members). About 60% of residents have given positive views on presence of instruction and purpose about maintaining the portfolio. Several participants expressed concerns because the portfolio content is self-reported; it may include bias or inaccuracy. Regarding opinions of respondents on characteristics of portfolio, both of the respondents perceived high satisfaction on portfolio based learning, reasonable contents, and practicable and feasible use of portfolio (p<0.05) except regular updating (p<0.05) and comprehensiveness of portfolio. In line with ownership and motivation, faculty members (4.03) highly assumed that the portfolio completed by residents as requirement of the university than residents (3.22) and p<0.05). Residents did not agree that they worked on the portfolio during university deadline (2.89) whereas faculty members ((3.73) showed vary positive views in this regard. Concerning commitments to use the portfolio, both respondents have conveyed high expression (mean >3.5) on the relationship between residents and supervisors so the role of an available supervisor in direct observations of the residents and dedicated educational meetings, giving feedback and support, cannot be exaggerated. Relating to assessment of portfolio, overall views of the respondents have expressed poor to moderate views and faculty members (2.37 to 4.23) have less satisfaction than residents (2.88 to 3.73). Though there are so many constraints such as the lack of clear purposes and instructions, poor understanding regarding ownership, assessment issues, and confusion about educational impact in future, but the portfolio as a feasible and acceptable tool to train and assess clinical competence and clinical specialization. Study recommended for generic format of portfolio based training and assessment to be considered in Bangladesh context. All Stakeholders should be well oriented at the beginning for utilizing the portfolio (supervision, monitoring and assessment system). Bangladesh Journal of Medical Education Vol.13(1) January 2022: 69-78

Development and use of a computerized system to track the competency development of family medicine residents: analysis of the convergence between system proposals and assessor decisions

In recent decades, a number of training environments have moved toward program approaches targeting the development of competencies. Because of their complexity, monitoring the development of those competencies is a considerable challenge. Our hypothesis is that a computerized system could help overcome this challenge if it is well accepted by its users. We first summarize the context surrounding the implementation of such approaches. Next, we present a computerized assessment system established in the Family Medicine Residency Program of Laval University (Québec, Canada) that we have developed for tracking the development of residents’ competencies. We then present the analysis of interactions between the system and users and the various proposals that were made to improve the system and longitudinal tracking of the development of the targeted competencies. We consider that this research provides useful guidelines for the computerized monitoring of learners' competencies development and for the design of such systems.

Validation of an Aesthetic Assessment System for Commercial Tasks

Automatic prediction of the aesthetic value of images has received increasing attention in recent years. This is due, on the one hand, to the potential impact that predicting the aesthetic value has on practical applications. Even so, it remains a difficult task given the subjectivity and complexity of the problem. An image aesthetics assessment system was developed in recent years by our research group. In this work, its potential to be applied in commercial tasks is tested. With this objective, a set of three portals and three real estate agencies in Spain were taken as case studies. Images of their websites were taken to build the experimental dataset and a validation method was developed to test their original order with another proposed one according to their aesthetic value. So, in this new order, the images that have the high aesthetic score by the AI system will occupy the first positions of the portal. Relevant results were obtained, with an average increase of 52.54% in the number of clicks on the ads, in the experiment with Real Estate portals. A statistical analysis prove that there is a significant difference in the number of clicks after selecting the images with the AI system.

Multi-GNSS Combined Orbit and Clock Solutions at iGMAS

Global navigation services from the quad-constellation of GPS, GLONASS, BDS, and Galileo are now available. The international GNSS monitoring and assessment system (iGMAS) aims to evaluate the navigation performance of the current quad systems under a unified framework. In order to assess impact of orbit and clock errors on the positioning accuracy, the user range error (URE) is always taken as a metric by comparison with the precise products. Compared with the solutions from a single analysis center, the combined solutions derived from multiple analysis centers are characterized with robustness and reliability and preferred to be used as references to assess the performance of broadcast ephemerides. In this paper, the combination method of iGMAS orbit and clock products is described, and the performance of the combined solutions is evaluated by various means. There are different internal precisions of the combined orbit and clock for different constellations, which indicates that consistent weights should be assigned for individual constellations and analysis centers included in the combination. For BDS-3, Galileo, and GLONASS combined orbits of iGMAS, the root-mean-square error (RMSE) of 5 cm is achieved by satellite laser ranging (SLR) observations. Meanwhile, the SLR residuals are characterized with a linear pattern with respect to the position of the sun, which indicates that the solar radiation pressure (SRP) model adopted in precise orbit determination needs further improvement. The consistency between combined orbit and clock of quad-constellation is validated by precise point positioning (PPP), and the accuracies of simulated kinematic tests are 1.4, 1.2, and 2.9 cm for east, north, and up components, respectively.