Reviewerly/exHarmony huggingface dataset:
KAJIAN PENERAPAN PRINSIP KERJA SAMA DAN PRINSIP KESOPANAN DALAM TUTURAN IR. JOKO WIDODO PADA VIDEO DEBAT PILPRES 2019

AbstractThis qualitative descriptive research aimed to describe (1) the application of cooperative principle in speech Ir. Joko Widodo in 2019 Presidential Election debate video and (2) the application of the principle of politeness in the speech of Ir. Joko Widodo in 2019 Presidential Election debate video. The subject of this study was Ir. Joko Widodo, while the objects were the cooperative principle and the principle of politeness. This research used a data collection method in the form of documentation of the 2019 Presidential debate video with the technique of listening and note taking. The instrument used in this study was data card. The data analysis method was carried out in three stages, namely data reduction, data display, and conclusion. The results showed that cooperative principle had been applied in the speech of Ir. Joko Widodo in the 2019 Presidential Election debate video. In the statement there are four maxims contained in the cooperative principle, namely maxim of quantity, maxim of quality, maxim of relevance, and maxim of manner. In addition, the principle of politeness has also been applied in the speech of Ir. Joko Widodo on the 2019 Presidential Election debate video. In the speech there were six maxims contained in the principle of politeness, namely the maxim of wisdom, maxim of generosity, maxim of appreciation, maxim of humility, maxim of compatibility, and maxim of sympathy. Keywords: cooperative principle, principle of politeness, debate
RETRACTED: The Analysis of Higher Vocational Education Informationization Teaching and Training Mode Based on Computer Technology

Abstract With the increasing strength of the national economy, more and more attention has been paid to the development and training of talents, especially the training of talents in higher vocational education. It is the school’s unremitting efforts and pursuit to cultivate professional and skilled talents. Therefore, in order to output more application-oriented talents to the society, higher vocational colleges will actively use the computer information teaching and training model, greatly improve students’ interest in learning, to help students develop in an all-round way. This paper mainly studies and analyzes the elements and development trend of the practical training teaching mode in higher vocational colleges under the condition of computer information technology.
Attention-Based Encoder-Decoder Model for Photovoltaic Power Generation Prediction

Abstract The weather factors that affect the output of photovoltaic power generation systems have great volatility and discontinuities. Thus how to accurately predict the output of photovoltaic power generation has become a crucial issue. In this paper, we propose an attention-based Encoder-Decoder model for photovoltaic power generation. Filtered data based on maximum information coefficient is used as one of the features to reconstruct the experiment data. Then the attention mechanism is introduced to the Encoder-Decoder model, which constructed by Long Short-Term Memory (LSTM) neurons. We implement this experiment based on actual photovoltaic power plant examples and experimental results confirm the accuracy and applicability of the proposed model in predicting photovoltaic power generation
Improving Retrieval Efficiency of Person Re-Identification Based on Resnet50

In recent years, the issue of person re-identification has become more and more popular, which is an important research subject in the field of computer vision, and many models or methods for different predicaments have been proposed successively. However, there are often differences between theory and practice. As a matter of fact, while collecting a large number of pedestrian images, retrieval efficiency becomes one of the significant evaluation indicators. Therefore, how to maintain high precision and quickly respond to retrieval requirements is a very important issue. This thesis explores many proposed person re-identification methods and improves retrieval time under the premise of maintaining a high precision rate. In this paper, we select Resnet50 as the feature output model, and use not only K-means Clustering to filter out the preliminary candidates but also Hierarchical Comparison to reduce the number of feature comparisons. The final experimental result shows the average retrieval time is improved dramatically with a speed-up ratio closed to 8, whereas the precision loss is under 3%.
ЕФЕКТИВНІСТЬ МЕТОДУ ГРАФІЧНОЇ ФАСИЛІТАЦІЇ ПІД ЧАС ВДОСКОНАЛЕННЯ КОМУНІКАТИВНИХ УМІНЬ МАЙБУТНІХ МЕНЕДЖЕРІВ

the publication highlights the role of communication skills of managers in their future professional activities. An analysis of modern teaching methods used by teachers in the United States, Ukraine and other European countries. The expediency of using methods of information visualization in the educational process, in particular the method of graphic facilitation, was substantiated. The expediency and efficiency of using the method of graphic facilitation in the conditions of the 2020 pandemic in order to increase the efficiency of distance learning was analyzed.
RETRACTED: Research and Planning of Smart City Based on Computer Big Data Participation

Abstract With the rapid development of domestic economy, the process of urbanization is accelerating. According to the national unification and the national economic operation data released by the Planning Bureau in 2015, the urbanization population accounts for the total population 56.1% of the total. The rapid development of urbanization has promoted the economic and social development of the city. However, the development of urbanization brings about a series of urban problems as well as urban economy. For example, urban resources are increasingly tense, urban environment is becoming worse, and urban livelihood issues are becoming more and more serious. The more complicated. It is everyone’s wish to promote the harmony of life and improve the quality of life. How to reasonably apply computer big data technology to the construction of smart city has become an important topic for researcher significance to improve the employment rate to give full play to the role of counselors in employment guidance.
How to Improve the Immersiveness in VR by Changing the Time Expansion Coefficient

We introduce Time Expansion Coefficient (that is, α), which refers to the ratio of the actual time to the VR image time, in this paper. VR film designers adjust time expansion coefficient according to different narrative types in VR films to optimize users’ immersive perception. We evaluated five types of narrative which include linear narrative with fixed shot, linear narrative with moving shot, circular narrative, multi-view narrative and interactive narrative. The results show that circular narrative and multi-view narrative are most affected by the time expansion coefficient. Interactive narrative and multi-view narrative are almost equally affected while linear narrative is less affected. In addition, when time expansion coefficient is greater than 1 (that is, α > 1), immersion in all five narrative types we refer to is improved.
Information System of Agricultural Commodities Mapping Based on Machine Learning

Abstract Climate change that occurs from year to year affects the agricultural sector. People who work in agriculture need to know the compatibility of plants with climate conditions in the region. Back Propagation Neural Network (BPNN) is a multilayer Artificial Neural Network (ANN) that is used to train neural networks with input in the form of precipitation, relative humidity, and temperature data. The training produced a model that was able to classify climate data based on plant growth requirements. The model for Soybean got the highest average accuracy of 96.53% and 90.87% for Rice. Variables that influence training include the number of neurons in the hidden layer, the value of learning rate, the number of folds, and the number of epochs. Prediction results generated from the model are used as a reference to display markers on maps that can be accessed by users.
A NOVEL ITERATIVE DEMOSAICING ALGORITHM USING FUZZY BASED DUAL TREE WAVELET TRANSFORM

In this research paper, an efficient demosaicking algorithm for Color Filter Array (CFA) is proposed to overcome the problem of reconstructing the correlated signals from the down sampled samples. The aim of this work is reconstruction of a full color image from the spatially under sampled color channels. The demosaicing is done by an iterative methodology for finding the values of missing pixels. The Dual Tree Complex Wavelet Transform (DTCWT) is used with the combination of fuzzy if-then rule to refine the color plane values. The DTCWT has shift invariance and directionality property that achieves the perfect reconstruction of images and improves quality of the image. The new iterative interpolation algorithm uses color difference domain model and reduces false coloring by using an effective stopping criteria. The research work shows result as, the explicated interpolation method yields better psnr values than bilinear interpolation technique, edge based method, subband based method, and other iterative based demosaicing methods.
A Minimal River Crossing Task to Aid the Explainability of Evolutionary Agents

Evolving agents to learn how to solve complex, multi-stage tasks to achieve a goal is a challenging problem. Problems such as the River Crossing Task are used to explore how these agents evolve and...
Using intelligent algorithms on singlesweeps to evaluate thresholds and waveforms of brainstem evoked response audiometry (BERA) on animal model

Introduction Unrecognized changes in hearing perception and their processing pose a serious barrier to integration into our society. The threshold of hearing level from the averaged measurements of brain stem potentials is visually determined in clinical practice. If in addition to the hearing threshold, questions arise in regard of wave morphology , it is not possible to quantify these features objectively without having, concrete references and evaluation algorithms.
RETRACTED: The Construction of an Evaluation System for the Post Competence of College Foreign Language Teachers Based on Computer Big Data Technology

Abstract This paper plans to comprehensively evaluate the post capacity of college English teachers by combining the computer big data technology with the equivalent multi-level weighted index method. Through the analysis, this paper constructs the post competency index of teachers in colleges and universities, and integrates the teaching achievements, scientific research achievements, attendance results and the subjective evaluation results of students and colleagues, so as to realize the comprehensive evaluation of teachers. Teacher comprehensive working ability price. This index applies not only to college English teachers, but also to the evaluation of other college teachers.
Optimizing Virtual Reality Eye Tracking Fixation Algorithm Thresholds Based on Shopper Behavior and Age

Eye tracking (ET) is becoming a popular tool to study the consumer behavior. One of the significant problems that arise with ET integrated into 3D virtual reality is defining fixations and saccades, which are essential part of feature extraction in ET analysis and have a critical impact on higher level analysis. In this study, the ET data from 60 subjects, were recorded. To define the fixations, Dispersion Threshold Identification algorithm was used which requires to define several thresholds. Since there are multiple thresholds and extracted features, a Multi-Objective Reinforcement Learning (MORL) algorithm was implemented to solve this problem. The objective of the study was to optimize these thresholds in order to improve accuracy of classification of the age based on different visual patterns undertaken by the subject during shopping in a virtual store. Regarding the nature of the classification, the objective for this optimization problem was to maximize the differences between the averages of each feature in different classes and minimize the variances of the same feature within each class. For the current study, thresholds optimization has shown an improvement in results for the accuracies of classification between age groups after applying the MORL algorithm. In conclusion, the results suggest that the optimization of thresholds is an important factor to improve feature extraction methods and in turn improve the overall results of an ET study involving consumer behavior inside virtual reality. This method can be used to optimize thresholds in similar studies to provide improved accuracy of classification results.
Exploring Earth Science Applications using Word Embeddings

&amp;lt;p&amp;gt;Word embedding are numeric representations of text which capture meanings and semantic relationships in text. Embeddings can be constructed using different methods such as One Hot encoding, Frequency-based or Prediction-based approaches. Prediction-based approaches such as&amp;amp;#160; Word2Vec, can be used to generate word embeddings that can capture the underlying semantics and word relationships in a corpus. Word2Vec embeddings generated from domain specific corpus have been shown in studies to both predict relationships and augment word vectors to improve classifications. We describe results from two different experiments utilizing word embeddings for Earth science constructed from a corpus of over 20,000 journal papers using Word2Vec.&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The first experiment explores the analogy prediction performance of word embeddings built from the Earth science journal corpus and trained using domain-specific vocabulary. Our results demonstrate that the accuracy of domain-specific word embeddings in predicting Earth science analogy questions outperforms the ability of general corpus embedding to predict general analogy questions. While the results are as anticipated,&amp;amp;#160; the substantial increase in accuracy, particularly in the lexicographical domain was encouraging. The results point to the need for developing a comprehensive Earth science analogy test set that covers the full breadth of lexicographical and encyclopedic categories for validating word embeddings.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The second experiment utilizes the word embeddings to augment metadata keyword classifications. Metadata describing NASA datasets have science keywords that are manually assigned which can lead to errors and inconsistencies. These science keywords are controlled vocabulary and are used to aid data discovery via faceted search and relevancy ranking. Given the small size of the number of metadata records with proper description and keywords, word embeddings were used for augmentation. A fully connected neural network was trained to suggest keywords given a description text. This approach provided the best accuracy at ~76% as compared to other methods tested.&amp;lt;/p&amp;gt;
The Exploration of Progressive Experimental Training Teaching Mode Based on O2O

Abstract In view of the current situation that the experimental teaching hours are few and the task is heavy, the offline progressive experimental teaching, online micro class teaching and online progressive practical training breakthrough teaching mode are adopted, the experimental teaching contents with progressive logical relationship are designed, the difficult and in-depth practical training tasks are allocated, and the trainees’ practical training results are mastered openly, fairly and fairly in real time on the training platform It is proved that this method can improve the quality of practical teaching.
Improvements on the Inland Transportation of Cold Chain Pharmaceuticals in Korea: Focused on the Qualification and Institutional Improvements for Temperature Controlled Packaging

본 연구의 목적은 온도관리 포장을 중심으로 국내 콜드체인 의약품 운송에 대한 개선방안을 결정하고 제안하기 위한 것이다. 콜드체인 의약품 시장이 성장함에 따라서 국내에서도 콜드체인 의약품 운송을 위해서 온도관리 포장을 이용하는 것은 계속 증가 할 것으로 전망된다. 그러나 현재 우리나라에서는 적격성 평가가 제대로 되지 않은 온도관리 포장이 콜드체인 의약품의 국내 운송 을 위해서 사용되고 있어서 콜드체인 의약품의 품질을 운송 중에 유지하는 것에 어려움이 있는 상황이다. 이에 본 연구에서는 온 도관리 포장을 이용하는 콜드체인 의약품 운송 관련 국내외 요구사항을 고찰하고 국내 주요 제약업체 소속인 물류 관리자들과의 인터뷰를 통해서 온도관리 포장을 이용하는 국내 콜드체인 의약품 운송의 문제점을 파악하였다. 그리고 운송 중 측정된 실제 온도 자료의 분석 및 구성을 통해서 온도관리 포장의 적격성 평가를 위한 과학적 기준을 수립하고 관련 문헌, 정보, 가이드라인의 고찰 을 통해서 온도관리 포장을 이용하는 국내 콜드체인 의약품 운송 관련 구체적 제도 개선방안을 제안하였다. 본 연구 결과가 온도 관리 포장을 이용하는 국내 콜드체인 의약품 운송의 개선과 이해관계자의 인식전환을 위한 방향을 제시해 줄 것으로 기대한다.The purpose of this study is to determine and propose improvements on the inland transportation of cold chain pharmaceuticals in Korea focusing on temperature controlled packaging. The use of temperature controlled packaging is expected to continue increasing for the inland transportation of cold chain pharmaceuticals in Korea as the market for cold chain pharmaceuticals grows. However, temperature controlled packaging that is not properly qualified is currently used for t he inland t ransportation o f cold chain pharmaceuticals in Korea, which makes it difficult to preserve the quality of cold chain pharmaceuticals during transportation. In this study, the domestic and overseas requirements for cold chain pharmaceutical transportation using temperature controlled packaging were considered, and problems on the inland cold chain pharmaceutical transportation using temperature controlled packaging in Korea were identified through interviews with logistics managers belonging to leading pharmaceutical companies. In addition, the scientific standards for the qualification of temperature controlled packaging were established by analyzing and organizing actual temperature data which were measured during t ransportation, and the specific institutional improvement plans for the inland cold chain pharmaceutical transportation using temperature controlled packaging were proposed through the consideration of relevant literature, information and guidelines. The results of this study are expected to provide directions to improve the inland cold chain pharmaceutical transportation using temperature controlled packaging and to change the awareness of interested parties.
A Model to Support Collective Reasoning: Formalization, Analysis and Computational Assessment

In this paper we propose a new model to represent human debates and methods to obtain collective conclusions from them. This model overcomes two drawbacks of existing approaches. First, our model does not assume that participants agree on the structure of the debate. It does this by allowing participants to express their opinion about all aspects of the debate. Second, our model does not assume that participants’ opinions are rational, an assumption that significantly limits current approaches. Instead, we define a weaker notion of rationality that characterises coherent opinions, and we consider different scenarios based on the coherence of individual opinions and the level of consensus. We provide a formal analysis of different opinion aggregation functions that compute a collective decision based on the individual opinions and the debate structure. In particular, we demonstrate that aggregated opinions can be coherent even if there is a lack of consensus and individual opinions are not coherent. We conclude with an empirical evaluation demonstrating that collective opinions can be computed efficiently for real-sized debates.
การพัฒนาชุดฝึกทักษะออนไลน์ เรื่อง ระบบแรงและการสมดุล สำหรับนักศึกษาวิศวกรรมโยธา มทร.ศรีวิชัย

The purpose of this research was 1) to develop the online skill training package on Force system and Equilibrium in subject code 04-411-101 Engineering Mechanics 1 and 2) to study and assess learning achievement. The samples selected by purposive random sampling comprised 2 groups of the 1st and 2nd year of civil engineering students, Faculty of Engineering, Rajamangala University of Technology Srivijaya divided into 2 groups; 33 students in experimental group and 27 students in control group. Research instruments for the study consisted of 1) a Pre-test 2) a Post-test and 3) an online skill training package. The collection data were analyzed by Percentage, Mean, Standard Deviation and t-test dependent. The results showed that, 1) the developed online skill training package included 44 questions of selection type and matching questions. 2) The developed online skill training package was an efficiency 83.6/63.0, which meets the 80/80 standard only the first set. 3) The experimental group had higher learning achievement than before learning at, but the achievement was not statistically significant different at the level .05 same as in the control group studied by normal methods. 4) The experimental group had higher post-learning achievement than the control group studied by normal methods, but the statistically significant different at the level .05.
Reimagining Russian Higher Education: Could an experiment in progressive education in Siberia help transform Russia's universities?

In Tyumen, a Siberian city located some 1,000 miles east of Moscow, a radical experiment in Russian higher education is taking place. The School of Advanced Studies (SAS) is an institute that is attempting to bring multidisciplinary, liberal arts-influenced education to Russia. Founded in 2017, SAS operates as an autonomous institution within the state-funded University of Tyumen (UTMN). This article will analyze SAS's current educational model through data and interviews with faculty, administration, and students. It is divided into five parts. The first section offers background information. We explain how SAS was founded, its source of funding, and why liberal education is an outlier in Russia. The middle three sections take a deeper look at the institution from the perspectives of the administration, students, and faculty. We document their observations about the SAS experiment, highlighting their differing views on what they believe the institute's mission should be. These sections also analyze which elements of the SAS model are working so far and which ones need further development. The final section sums up our findings: how is SAS, a progressive, liberal experiment, able to exist in a traditional, generally inflexible Russian education system? So far, what are the institution's successes and failures? And finally, is SAS a fluke experiment, or is there potential to create similar institutions throughout Russia?
Application of improved intelligent ant colony algorithm in protein folding prediction

While the single ant colony algorithm and the fish swarm algorithm have many advantages, they also have various shortcomings. After analyzing the advantages and disadvantages of the ant colony algorithm and the fish swarm algorithm, this paper uses the complementary principle of the two algorithms to effectively fuse the two population intelligent algorithms. The improved swarm intelligence algorithm is applied to the well-considered protein folding prediction problem, and the simplified protein structure Toy model is verified, and the ideal results are obtained. The improved algorithm enhances the search ability, and the computational efficiency is greatly improved, ensuring the accuracy of the operation.