Multiple Representation Models Research Articles

Estimation of the Total Soil Nitrogen Based on a Differential Evolution Algorithm from ZY1-02D Hyperspectral Satellite Imagery

Precise fertilizer application in agriculture requires accurate and dependable measurements of the soil total nitrogen (TN) concentration. Henan Province is one of the most important grain-producing areas in China. In order to promote the development of precision agriculture in Henan Province, this study took the high-standard basic farmland construction area in central Henan Province as the research area. Using single-phase images acquired from the ZY1-02D satellite hyperspectral sensor on 28 January 2021 (with a spatial resolution of 30 m × 30 m, a spectral range that covered 400–2500 nm, and a revisit period of 3 days) for spectral reflectance transformation and feature spectral band extraction. Based on multiple representation models, such as multiple linear regression, partial least squares regression, and support vector machine (SVM), all bands, feature bands, feature band combinations, and differential evolution (DE) algorithms were used to extract the secondary characteristic variables of the combination of characteristic bands, which were used as model inputs to estimate the content of TN in the study area. It was found that (1) the spectral reflectance transformation could help to improve the accuracy of prediction by reducing the interference from noise in the model, but the optimal spectral transformation method differed between different models and even between the training and test sets of the same model; (2) the estimation accuracy of the TN content model based on the minimum shrinkage and feature selection operator of the feature band was usually better than that of the full band, the feature combination band contained more effective information related to the TN content, and the combination of the DE algorithm and the SVM model achieved a better estimation accuracy for secondary feature extraction and TN content estimation of the feature combination band; and (3) ZY1-02D hyperspectral satellite data have the potential for the dynamic and non-destructive monitoring of regional TN content.

Discovery Learning using Multiple Representation model for enhancing scientific processing and critical thinking skills of the students

This study aims to reveal: (1) the feasibility of the developed Discovery Learning using Multiple Representations (DLMRs) model on the subject matter “Substance Pressure and its Application in Daily Life” for grade 8 students of SMP, (2) the practicality of the developed DLMRs model for science teachers and grade 8 students of SMP, and (3) the effectiveness of the developed DLMRs model in improving the science process and critical thinking skills of grade 8 students of SMP. This research is research and development adapting the development procedures by Borg & Gall which consisted of 10 steps: (1) research and information collection, (2) planning, (3) developing the preliminary form of product, (4) preliminary field testing, (5) main product revision, (6) main field testing, (7) operational product revision, (8) operational field testing, (9) final product revision, and (10) dissemination and implementation. The limited trial subjects consist of 15 students of class VIII.4 SMPN 1 Watopute. The subjects of the field trial in the experimental class consist of 31 students of class VIII.1 and those in the control class consist of 32 students of class VIII.3 SMPN 1 Watopute. The used sampling technique is cluster sampling. The instrument of data collection is an essay test to measure critical thinking skills, observation sheets to measure science process skills, questionnaires to determine the readability of the DLMRs student worksheet, and questionnaires to determine student and teacher responses to DLMRs model. The data analysis technique used is the MANOVA test with a significance level of 0.05. The results showed that: (1) the developed DLMRs model was feasible to implement based on experts judgment, (2) the DLMRs model is practical for teaching science based on responses given by teachers and students, (3) the DLMRs model is effective for improving students' science process skills, (4) the DLMRs model is effective for enhancing students' critical thinking skills.

Using multiple representations model to enhance student’s understanding in magnetic field direction concepts

The magnetic field direction is one of the concepts in physics that need good representation ability to understand. This article presents an application of multiple representation models to help the student understand this concept. The sample that was taken using a purposive random sampling technique consisted of 62 high school students from 3 senior high schools in Purworejo. The analysis focused on the effectiveness of multiple representation models to enhance student understands in magnetic field direction concepts and level of students’ understanding. We used drawing representation (magnetic force lines and magnetic pole) and mathematics representation. Based on the analysis it can be concluded that learning by using multiple representation models effectively to enhance students’ understanding. By CRI scale also found that students did not understand the concept more than misconception.

Legitimate actors of international law-making: towards a theory of international democratic representation

ABSTRACTThis article addresses the identity of the legitimate actors of international law-making from the perspective of democratic theory. It argues that both states or state-based international organisations, and civil society actors should be considered complementary legitimate actors of international law-making. Unlike previous accounts, our proposed model of representation, the Multiple Representation Model, is based on an expanded, democratic understanding of the principle of state participation: it is specifically designed to palliate the democratic deficits of more common versions of the Principle of State Consent. Second, it endorses a qualified version of the Principle of Civil Society Participation, one that is much more restrictive and more critical of the democratic defects of civil society actors than most of its current supporters. Finally, it reveals how the democratic strengths and deficits of both models are best approached as mirroring one another and need to be combined in a complex account of representation.

UNDERGRADUATE STUDENTS’ MISCONCEPTION ON ACID-BASE AND ARGENTOMETRIC TITRATIONS: A CHALLENGE TO IMPLEMENT MULTIPLE REPRESENTATION LEARNING MODEL WITH COGNITIVE DISSONANCE STRATEGY

The study was conducted to map the misconception pattern of chemistry prospective teachers who learned acid-base and argentometric titration. Further, it attempts to minimize misconception through a multiple representation model of learning chemistry with cognitive dissonance strategy. The first treatment was done on acid-base titration and the second treatment on argentometric titration materials. The multiple choice test with open reasons was administered to 30 undergraduate students. The finding shows that 28.6% students have the same pattern of misconception while learning in both of the courses. After the treatment, misconception decreased to 9.5% on the first treatment, and 9.4% on the second treatment. The model was found to be suitable to decrease the misconception, but could not change the misconception into “zero misconception”, especially for microscopic and symbolic representations.

Receptor Dependent Multidimensional QSAR for Modeling Drug - Receptor Interactions

Quantitative Structure Activity Relationship (QSAR) is an approach of mapping chemical structure to properties. A significant development can be observed in the last two decades in this method which originated from the Hansch analysis based on the logP data and Hammett constant towards a growing importance of the molecular descriptors derived from 3D structure including conformational dynamics and solvation scenarios. However, molecular interactions in biological systems are complex phenomena generating extremely noisy data, if simulated in silico. This decides that activity modeling and predictions are a risky business. Molecular recognition uncertainty in traditional receptor independent (RI) m-QSAR cannot be eliminated but by the inclusion of the receptor data. Modeling ligand-receptor interactions is a complex computational problem. This has limited the development of the receptor dependent (RD) m-QSAR. However, a steady increase of computational power has also improved modeling ability in chemoinformatics and novel RD QSAR methods appeared. Following the RI m-QSAR terminology this is usually classified as RD 3/6D-QSAR. However, a clear systematic m-QSAR classification can be proposed, where dimension m refers to, the static ligand representation (3D), multiple ligand representation (4D), ligand-based virtual or pseudo receptor models (5D), multiple solvation scenarios (6D) and real receptor or target-based receptor model data (7D).

Three-Layered Source-Code Modelling

Models of software must serve many roles; storage management, information representation and information interchange. A model tailored to a specific role is often inadequate for, and incapable of, supporting other roles. For this reason, we advocate a multi-layered approach, where each successive layer fulfils a specific role. Our current experience with a 3-layered implementation indicates that the use of a storage layer decreases the demands upon conceptual and interchange representation models. Furthermore, we believe that a sufficiently general storage layer can support the simultaneous use of multiple conceptual models. In this approach, the storage layer and its associated database is an enabling technology for the integration of multiple representation models.

整合操作に着目した企画設計CADの開発研究

Designers generally develop their designs as processes of adjusting and reconciling design decisions explored using various types of representation models that were developed, in parallel fashion, to study varying subjects such as space planning, building bulk, or structural system. Though the most CAD allow users to define multiple representation models, they have lacked utilities that support adjusting operations among them. It is the objective of this study to propose a model of design process and a prototype CAD for schematic design stage. Reviewing a case study, the authors assessed the advantages of the system use and subjects for the future studies.

Traumatic memory characteristics: A cross-validated mediational model of response to rape among employed women.

In a cross-validated mediational model, the authors examined characteristics of memories formed in response to rape and other intense unpleasant and pleasant experiences. Data were responses to a mailed survey of women medical center and university employees. Measurement models of memory and symptom factors and a structural model with pathways among cognitive appraisal, emotional valence, memory characteristics, and health outcomes were developed in Sample 1 (N = 1,307) and confirmed in Sample 2 (N = 2,142). Rape had substantial direct effects on 2 memory factors (Clarity and Affect) and indirect effects through the construal of victimization. Rape was associated with memories described as more emotionally intense but less clear and coherent and less often thought of or talked about. Most effects on physical symptoms were nonsignificant. Implications of findings for neurohormonal and multiple representation models of emotional memory and to cognitive avoidance are discussed.

Traumatic memory characteristics: a cross-validated mediational model of response to rape among employed women.

In a cross-validated mediational model, the authors examined characteristics of memories formed in response to rape and other intense unpleasant and pleasant experiences. Data were responses to a mailed survey of women medical center and university employees. Measurement models of memory and symptom factors and a structural model with pathways among cognitive appraisal, emotional valence, memory characteristics, and health outcomes were developed in Sample 1 (N = 1,307) and confirmed in Sample 2 (N = 2,142). Rape had substantial direct effects on 2 memory factors (Clarity and Affect) and indirect effects through the construal of victimization. Rape was associated with memories described as more emotionally intense but less clear and coherent and less often thought of or talked about. Most effects on physical symptoms were nonsignificant. Implications of findings for neurohormonal and multiple representation models of emotional memory and to cognitive avoidance are discussed.