Reviewerly/exHarmony huggingface dataset:
A Novel Machine Learning-based Strategy for Agricultural Time Series Analyzing and Forecasting: a Case Study in China's Table Grape Price

Applications of data science for agriculture has been widely discussed, this study attempts to construct a novel machine learning-based strategy for products price analyzing and forecasting. To do this, we follow the framework of "divide and conquer" to strategically integrate the Ensemble Empirical Mode Decomposition (EEMD), reconstruction algorithms, evolutionary Least Squares Support Vector Machine (LSSVM) and Extreme Learning Machine (ELM) to realize numerical forecasting and qualitative analysis. In the price prediction scenario of table grape, which is a typical perishable fruit in China's fruit market, the performance of the proposed method is verified. This paper is committed to provide a reference for the univariate time series price analysis of perishable agricultural products when the conditions are not enough to analyze the influencing factors, free it from the tedious process of data collection, and realize the accurate prediction and qualitative analysis of the target series.
Pengembangan LKPD Berbasis Contextual Teaching and Learning (CTL) Berbantuan Media Powtoon di SDN Sukun 1 Malang

Abstract: This research aimed to produce printed teaching materials is a LKPD based on Contextual Teaching and Learning (CTL) assisted by powtoon media to support the learning process and to determine the feasibility and practicality of LKPD based on Contextual Teaching and Learning (CTL) as teaching materials. This study uses a research and development (R&D) method with the ADDIE model. The test subjects for this product consisted of material experts, linguists, media experts, teachers, and students. The data collection instrument used a validation sheet and questionnaire guidelines. Data analysis techniques used qualitative and quantitative data. The results of the LKPD based on Contextual Teaching and Learning (CTL) by material experts obtained a percentage of 86.36% with the very valid category, linguists obtained a percentage of 91.7% with the very valid category, Media experts obtained a percentage of 87.5% with the category very valid. In addition, the teacher's response to the LKPD in the limited trial obtained a percentage of 97.5% and student responses obtained a percentage of 92.91% in the very practical category. So it can be concluded that the LKPD based on Contextual Teaching and Learning (CTL) developed using the ADDIE model is suitable for use as teaching material for grade III students in elementary schools.
Mobile payment systems in the Covid-19 era: security, privacy and digital trust

Mobile payment systems are based on many technologies. This paper builds on a fairly comprehensive review of the scientific literature, relative to the recent development of mobile payment systems. It presents the main current solutions and some implementations. However, many issues remain open, including the security of personal data, which raises ethical concerns related to privacy, among other concerns. The article shows how, in the Covid-19 era, ethics are an asset for improving digital trust in mobile payment systems that have become essential tools in the lives of citizens.
Analysis of Control Strategies of Leakage Power Considering Decoder Optimization

This paper discusses the factor of power dissipation and its influence on VLSI Design .It alsodiscusses the basics of power dissipation and the variety of techniques available to make it work. Decoderbased optimization in terms of power is the order of the day and these have been implemented in this paperwith results. Consequently the speed of the processor also gets a boost via this implementation.
Application of Naïve Bayes in Document Categorization

Document Categorization can be very helpful in organizing a company’s file. In this research, NaiveBayes methodology was implemented in the developed application. There are four categories that can becategorized by the system. For the evaluation processes, a company’s main document were identifies and trainedthe data for its major type of document. Four hundred sample documents were used for training the system, sinceNaive Bayes is dependent to the number of training data and another one hundred documents for the evaluationprocess. The accuracy of the system were evaluated and the overall accuracy of the system is 83.05 which is ratedas Satisfactory.
AN ANALYSIS ON THE GRAMATICAL ERROR OF PROCEDURE TEXT WRITEN BY THE THIRD GRADE OF SMPN 286 JAKARTA

The objective of this research is to find out the empirical evidence of the English examination test content validity made by the English lecturer for the even semester of the first grade SMPN 26 Jakarta administered at the SMPN 26 Jakarta. Having analysis of the findings of this assessment, can be conclude that omission is the type mostly found in writing procedure text followed by mis formation, mis ordering and addition.  These findings indicated that every learner’s expression need article but the learner’s misform and omitted the required articles.   Based on the analysis of the erroneous sentences written by the students in their composition, can be interpreted that the factor which is influences student to make grammatical error is the different grammatical system of L1 and English.  As we understand, Indonesian Bahasa does not have “to be” in construction sentences.
An Applied Model’s Capability of Suppervision for Social-Pedagigical Experts in the Field of Social Serveces and Education

The effectiveness of supervision for professionals from helping professions is indisputable. In our country, the activities for children and youth with disabilities are undertaken by professionals employed in two main areas - education and social services. The last one, participates in supervision partly, for the others there is no such activity. Regarding the interventions related to children and youth with disabilities, there is professional differentiation outside of Bulgaria. A clinical aspect of supervision emerges. These circumstances raise the question of whether a general approach to supervision affects these professionals equally and in the same extent. The answer reveals the significant circumstances and points out the aspects and influence of supervision to the specialists from the fields - education and social services, who work with children and youth people with disabilities.
Guide 9: Creating a Business Around TYPO3

TYPO3 is a professional-grade web publishing platform, and a perfect starting point to build—or expand—a professional web agency business.
THE ASSESSMENT OF TRANSLATION QUALITY IN BOUND NOVEL

The objectives of this study were to describe the translation quality in Bound novel. This study followed the theory of Nababan et.al (2012) about the three aspects of translation quality namely (1) accuracy; (2) acceptability; and (3) readability. This research uses descriptive qualitative method as the research design. The data of this study were gathered by using the documents and questionnaire by the raters. The results analysis from the raters showed that translation quality in Bound novel were less accurate with the average points around 2.75, acceptable with the average points around 2.92 and readable with the average points around 3.0. It means, the quality of translation in Bound novel was good quality. Keywords: Translation Quality, Bound Novel . Assessment, Aspects of Translation
PELATIHAN PEMANFAATAN APLIKASI MANAJEMEN REFERENSI ZOTERO DALAM MENINGKATKAN KUALITAS PEMAHAMAN GURU-GURU SD DALAM MEMBUAT KARYA TULIS ILMIAH

In today's era, teachers are required to have more abilities related to the use of technology as a tool in writing scientific papers. This is because there are still a lot of teachers who are still confused in finding reference applications in writing scientific papers. One application that is used to make it easier for teachers to write scientific papers, especially in managing references is the Zotero application. The purpose of this program of activity is to provide training and guidance for teachers who are required to write scientific papers as demand for self-quality improvement and learning in order to increase class in teaching positions. The method used in this Community Service is through the workshop approach method, lectures, questions and answers, and guidance on the use of the application, with the guidance process is expected to provide opportunities for teachers according to the training theme. This community service activity can provide direct benefits to partners in increasing understanding and skills related to reference management applications in the preparation of scientific papers in the form of CAR, indicators of the success of community service activities marked by the enthusiasm of the teachers in participating in training activities.
The Human Rights Challenges of Digital COVID-19 Surveillance.

Digital technologies offer huge potential to improve the accuracy, breadth, reliability, and speed of contact tracing and other public health surveillance measures. However, in the absence of appropriate global governance frameworks, the usage of digital technologies during health emergencies presents multidimensional challenges. The article by Sharifah Sekalala and colleagues in this issue analyzes the human rights implications of tools used for outbreak surveillance and suggests concrete recommendations to mitigate risks to human rights. This commentary discusses the technological and governance challenges associated with their recommendations. It incorporates a technological feasibility viewpoint into some of the recommendations and proposes one additional recommendation to strengthen the governance and accountability of technology developers, regulators, and evaluators. As Sekalala and colleagues note, several countries now use digital COVID-19 surveillance technologies for symptom tracking and contact tracing to enable rapid case identification and integration into public health databases. Most technologies use location or GPS services (for example, China's Health Code and Ghana's COVID-19 Tracker) or Bluetooth (for example, France's TousAntiCovid and Singapore's TraceTogether).
Learning Contextual Perturbation Budgets for Training Robust Neural Networks

Existing methods for training robust neural networks generally aim to make models uniformly robust on all input dimensions. However, different input dimensions are not uniformly important to the prediction. In this paper, we propose a novel framework to train certifiably robust models and learn non-uniform perturbation budgets on different input dimensions, in contrast to using the popular l∞ threat model. We incorporate a perturbation budget generator into the existing certified defense framework, and perform certified training with generated perturbation budgets. In comparison to the radius of l∞ ball in previous works, the robustness intensity is measured by robustness volume which is the multiplication of perturbation budgets on all input dimensions. We evaluate our method on MNIST and CIFAR-10 datasets and show that we can achieve lower clean and certified errors on relatively larger robustness volumes, compared to methods using uniform perturbation budgets. Further with two synthetic datasets constructed from MNIST and CIFAR-10, we also demonstrate that the perturbation budget generator can produce semantically-meaningful budgets, which implies that the generator can capture contextual information and the sensitivity of different features in input images.
A STUDY OF THE FIRST-YEAR STUDENTS PERCEPTIONS REGARDING THE STRATEGY OF IIB DARMAJAYA’S MARKETING COMMUNICATION APPROACH DURING COVID-19 PANDEMIC

Covid-19 has brought some negative impact globally, including the declining interest to register in universities due to economic unaffordability. This study will obtain information about how students perceive Darmajaya in the middle of this Covid-19 spread. For the marketing area, this information might give an additional strategy on how to attract new students in a new different way in increasing the number of total new admissions. This study used the approach of qualitative phenomenological study. To acquire the data, the researcher used the deep-interview method. A sample of 14 students of Darmajaya’s first year-students and a number of selection criteria were identified. From the informants, it was obtained that Darmajaya had built a good perception among the students regarding the service quality, accreditation, lecturers’ quality, achievements, web, and social media accessibilities as well as popular events and competitions but it needed an improvement in scholarship socialization, needed to expose more of the students’ organizations (UKM) in social media and needed to enrich the major/courses in order to attract the new enrollers to register. Keyword: Students, Education, Pandemic Covid 19, Perceptions, Marketing strategy
User Authentication Approaches in Different Applications

Abstract:This paper represents importance of user authentication over the applications, user authentications in different type of applications either it is web-based applications or mobile based applications or window-based applications it has been our protections by acting to prevent one’s data from unauthorized access. With the achievement of new technologies, the way we have been using User Authentication has been changed and transformed into ample safe yet more easily than they were ever been in the past few years. This paper discusses the different approaches for developing user authentication for web based and mobile based applications [1][2].
Characterization of Breast Masses in Mammography using First Order Statistic

This study concern to characterize the breast masses in mammography were defining the breast tissues to tumor, gland, fat and connective tissue, at cancer diagnostic medical center and carried out using Interactive Data Language [IDL] program as platform for the generated codes.The texture analysis technique used to find the gray level variation in mammography images.Analyzing the image with Interactive Data Language IDL software to measure the grey level variation of mammography images.The result of the classification showed that the breast areas were classified well from the rest of the tissues although it has characteristics mostly similar to surrounding tissue.Several texture features are introduced from first order statistics and the classification score matrix generated by linear discriminate analysis and the classification accuracy of breast tissues classified to Tumor 96.8%, gland 57.9%, fat 98.9,While the connective tissue showed a classification accuracy 98.5%.The overall classification accuracy of breast area 94.0%.These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new mammography images with the appropriate breast area names.
A Simple Approach To Define Curricula For Training Neural Networks

In practice, sequence of mini-batches generated by uniform sampling of examples from the entire data is used for training neural networks. Curriculum learning is a training strategy that sorts the training examples by their difficulty and gradually exposes them to the learner. In this work, we propose two novel curriculum learning algorithms and empirically show their improvements in performance with convolutional and fully-connected neural networks on multiple real image datasets. Our dynamic curriculum learning algorithm tries to reduce the distance between the network weight and an optimal weight at any training step by greedily sampling examples with gradients that are directed towards the optimal weight. The curriculum ordering determined by our dynamic algorithm achieves a training speedup of ∼45% in our experiments. We also introduce a new task-specific curriculum learning strategy that uses statistical measures such as standard deviation and entropy values to score the difficulty of data points in natural image datasets. We show that this new approach yields a mean training speedup of ∼43% in the experiments we perform. Further, we also use our algorithms to learn why curriculum learning works. Based on our study, we argue that curriculum learning removes noisy examples from the initial phases of training, and gradually exposes them to the learner acting like a regularizer that helps in improving the generalization ability of the learner.
Disguised Face Verification Using Inverse Disguise Quality

Research in face recognition has evolved over the past few decades. With initial research focusing heavily on constrained images, recent research has focused more on unconstrained images captured in-the-wild settings. Faces captured in unconstrained settings with disguise accessories persist to be a challenge for automated face verification. To this effect, this research proposes a novel deep learning framework for disguised face verification. A novel Inverse Disguise Quality metric is proposed for evaluating amount of disguise in the input image, which is utilized in likelihood ratio as a quality score for enhanced verification performance. The proposed framework is model-agnostic and can be applied in conjunction with existing state-of-the-art face verification models for obtaining improved performance. Experiments have been performed on the Disguised Faces in Wild (DFW) 2018 and DFW 2019 datasets, with three state-of-the-art deep learning models, where it demonstrates substantial improvement compared to the base model.
Style Analysis of Argumentative Texts by Mining Rhetorical Devices

Using the appropriate style is key for writing a high-quality text. Reliable computational style analysis is hence essential for the automation of nearly all kinds of text synthesis tasks. Research on style analysis focuses on recognition problems such as authorship identification; the respective technology (e.g., n-gram distribution divergence quantification) showed to be effective for discrimination, but inappropriate for text synthesis since the “essence of a style” remains implicit. This paper contributes right here: it studies the automatic analysis of style at the knowledge-level based on rhetorical devices. To this end, we developed and evaluated a grammar-based approach for identifying 26 syntax-based devices. Then, we employed that approach to distinguish various patterns of style in selected sets of argumentative articles and presidential debates. The patterns reveal several insights into the style used there, while being adequate for integration in text synthesis systems.
Drivable Road Area Detection with Regression Output CNN

Nowadays, many methods are developed on autonomous vehicles and driver assistance systems to prevent traffic accidents and support drivers. In this work, a drivable area detection method based on CNN and regression is proposed. In the proposed method, Cityscapes dataset, which is open to sharing on the Internet is used as dataset. The images in the dataset are cut into slices to obtain new input images. With those images, a CNN based deep learning network is trained. By applying linear regression on the characteristics of the output of the network, the road boundary points in the relevant slice are tried to be determined. Experimental results have shown that the developed method has real-time operating performance and the results can be improved.
Disclosing Cultural Contents in English Textbook Reading Passages for Junior High School

Textbooks have an important role in English language learning to provide information about the English language and interrelated cultures. This research aimed to find cultural contents which refer to cultural dimensions and cultural categories in 34 reading passages. Generating Qualitative Content Analysis, this research attempted to disclose the cultural dimensions and cultural categories embedded in the textbook reading passages. The coding system was done by means of QCAmap App. With regards to cultural dimensions, this research found patterns of the occurrence of the dimension were dominated by the dimension of Practices. Then it is followed by dimension of Perspectives, dimension of Products, dimension of Persons and dimension of Communities respectively. Furthermore, this study found that the highest percentage of cultural categories is Target Culture (35%). It is followed by Universality across Culture (26%), International Culture (24%) and Intercultural Interaction (15%). However, the researcher did not find the occurrence of Source Culture in the 34 reading passages in Next Move 1 Students’ Book.
The Communicative Approach In Teaching English Speaking Club (ESC)

The aim of this study was: to described and analyze the effect communicative approach in teaching English speaking club (ESC) based on the application of the communicative on order to teach them in master English speaking. The population is 1st semester STMIK Royal Kisaran and the sample is about 20 students. The data analysis technique was quantitative data. The qualitative data will be collected by students speaking performance. The data will be interpreted in term of instuctional events, and instructional modes and modes of acquisition strategies. Classroom mode of acquisition strategies depend on the extended to which the classroom lecturer was teaching. We took the pre -test and post-test. They got 5,65 for Students’ scores pre – test . and   7,95 for Students’ scores post – test. The diffrences of pre – test and post – test in the control group, there were 16 students (80 %) whose scores stayed the same, and 4 students (20%) whose score stayed not same. They gained 1 point difference from the others
Rancang Bangun Aplikasi Pemetaan Digital Pada Universitas Muhammadiyah Riau

The campus area is a place for students and teaching staff to carry out their routine activities. But there are times when campus visitors are not only focused on teaching staff or students who already know the ins and outs of the campus area. Some parties such as students' parents, new students, guests sometimes need a certain guide to find specific areas of interest in the campus area. The development of this application is carried out aiming to assist and alleviate these parties to search and find related areas. The design of the software is made with Adobe Edge Animation CC with Action Script 3.0. based on the results of this study it can be concluded that the Digital Mapping Application on the Muhammadiyah Riau Campus can overcome the problem of confusion among the parties when visiting the Muhammadiyah Riau campus.
Online Leave Information System Based On Website Case Study At Taman Mini Indonesia Indah

Along with the era development and the increasingly advanced technology, demanded speed and accuracy in obtaining information. The use of computers and Sistem-sistemnya has become a major necessity to facilitate human work. Taman Mini Indonesia Indah is an Indonesian culture-themed tourist park in East Jakarta. Leave is one of the employees ' rights. Leave can be used by employees to not be able to enter the work for a particular reason, e.g. refreshing, sick break, childbirth, performing religious obligations, and other purposes in accordance with the provisions of the leave of each organization/agency. Processing of leave data at Taman Mini Indonesia Indah is still done manually by using the leave paper to HRD which resulted in the approval process and the report has not been efficient. With the online website-based and make with method waterfall leave submission system, make it easier for employees to apply for leave and generate fast, precise and accurate data for HRD in obtaining and making employee leave reports.
FACTORS THAT INFLUENCE THE CHANGES OF STUDENTS’ WRITING

This paper is focused on factors that influence the changes in students’ writing ability. Several factors can affect students’ academic writing, it can come from culture, education, social aspects, and cognitive aspects. Those factors are too broad to be discussed in this paper. Finally, the author tries to describe the factors that are just related to the teaching process. They are materials, media, classroom activities, classroom management, teaching strategy, and teacher‘s approach.