Reviewerly/exHarmony huggingface dataset:
THE USE OF INTEGRATION IN THE TEACHING OF HIGHER MATHEMATICS IN THE FIELD OF CHEMISTRY

One of the leading methods of teaching mathematics is the method of mathematical modeling. The use of the modeling method allows us to show the versatility of the mathematical apparatus, it makes it possible to unify the description of processes that are diverse in nature. The use of concepts related to modeling, directly in the process of teaching mathematics, allows you to improve the methodology of teaching it, avoid a formal approach to teaching, and implement integration ties. Students develop ideas about the role of mathematical methods in transformative activities, about the nature of the reflection of the phenomena of the surrounding world by mathematics.
Freedom of speech in the university context

In 2018, the federal government, commissioned a review of free speech in universities because it was felt certain views were being shut down on campus. But Universities Australia has questioned why...
THE EFFECT OF GIVING CONVERSATION PRACTICE TOWARDS STUDENTS’ SPEAKING ABILITY AT THE EIGHTH GRADE OF SMP NEGERI 4 SIPOHOLON IN ACADEMIC YEAR 2020/2021

This study aims to find out the effect of giving conversation practice toward students' speaking ability. The population of the study was grade of junior high school (SMP N.4 Sipoholon) The sample of the study was two classes. The sample was divided into two groups, the first group is 22 students, (Grade VIII.1) which was the experimental group. The second group is 22 students, (Grade VIII.2) which as the control group. The data of this study was recorded by using tape recorder. It was applied in pre-test and post-test. Then the score of data were analyzed by using t-test formula. The result of the analysis showed that t-observed value is higher than t-table value (4,33>2,021) with the degree of freedom (df) (42). The result of the analysis showed that the hypothesis of the study was accepted. It means that there was a significant effect to improve giving conversation practice towards students’ speaking ability.
Singularity and Similarity Detection from Signals Using Wavelet  Transform

The wavelet transform and related techniques are used to analyze singular and fractal signals. The normalized wavelet scalogram is introduced to detect singularities including jumps, cusps and other sharply changing points. The wavelet auto-covariance is applied to estimate the self-similarity exponent for statistical self-affine signals.
Robust method for fringe demodulation under rapid phase and amplitude fluctuations

In this article, an optimization framework using non convex, non smooth total generalized variation based regularization using surrogate principle is presented to mitigate the affects of fast varying phases and corruption of interferogram with noise and sudden amplitude changes.
Learning Optimal Decision Trees Using MaxSAT

We present a Combinatorial Optimization approach based on Maximum Satisfiability technology to compute Minimum Pure Decision Trees (MPDTs) for the sake of interpretability. We show that our approach outperforms clearly in terms of runtime previous approaches to compute MPDTs. We additionally show that these MPDTs can outperform on average the DT classifiers generated with sklearn in terms of accuracy. Therefore, our approach tackles favourably the challenge of balancing interpretability and accuracy.
Deep Multi-Illumination Fusion for Low-Light Image Enhancement

In recent years, improving the visual quality of low-light images has attracted tremendous attention. Most of the existing deep learning approaches estimate the single illumination and then obtain the enhanced result according to the Retinex theory. However, only estimating the single illumination limits the solution space of the enhanced result, causing the unideal performance, e.g., color distortion, details loss, etc. To overcome the issues, we design a new Deep Multi-Illumination Fusion (denoted as DMIF) network to effectively handle low-light image enhancement. Specifically, we first construct an illumination estimation module to generate multiple illuminations to enlarge the solution space. We fuse these illuminations and aggregate their advantages by an illumination fusion algorithm to produce a final illumination. Finally, the enhanced result is obtained according to the Retinex theory. Plenty of experiments are conducted to fully indicate our effectiveness and superiority against other state-of-the-art methods.
A unique approach of person reidentification using auto track regression framework

Automatic Person Re-identification by video surveillance is commonly used in different applications. Perhaps the human uniqueness criteria for tracking the presence of the same person across multiple camera views and a person’s growth identification is extremely challenging. To solve the above problem, we propose an efficient Auto Track Regression System (ATRF) based on a deep learning technique that uses an eminent representation strategy along with recognition. In this work, the Auto Wiley Detective (AWD) approach is proposed for the representation of features that can collect valuable information by monitoring individuals. After obtaining important information on the characteristics, it is possible to define the personal growth identity of the generation. The OPVC (Original Pick Virtual Classifier) is used for accurate classification of the queried person from a dense area by utilizing features of a person’s growth identity extracted from feature extraction by the Auto Wiley Detection Method. The proposed Originated Pick Virtual Classifier (OPVC) uses Platt scaling (originated pick) on probit regression (virtual) to train the featured data set for accurate person re-identification, which is boosted by the Karush–Kuhn–Tucker (KKT) conditions to reduce false re-identification. Since the gallery information is trained using the Backpropagation method and smoothened analysis through approximated output, the Auto Wiley Detection Method proficiently detects the required information automatically. This also helps to detect the person query image from the database, which contains a vast collection of video images based on the similarity features identified in the query image and the detailed features extracted from the query image. The classification is completed automatically, and then the Person Re-Identification from the databases is performed accurately and efficiently. Henceforth, the proposed work effectively extracts reliable height and age estimates with improved flexibility and individual re-identifying capabilities.
Evaluation of Information Technology-Based Inclusive Education’s Policies in DIY for the 2017/2018 Academic Year

This study aims to reveal and explain the results of the evaluation of information technology-based inclusive education policies in DIY for the 2017/2018 academic year conducted by researchers in 16 high school inclusion schools in DIY. In this study the authors use two major concepts in evaluating this policy, namely: Policy Design and Policy Implementation. The method used in this research is Mix-Method, which combines two qualitative and quantitative research methods, so that more comprehensive, valid, reliable, and objective data are obtained. The results of this study are the policy design obtained a value of 3.12 and was included in the fairly good category, the implementation of the policy obtained a score of 2.77 and was included in the good enough category so that the results of the evaluation of information technology-based inclusive education policies in DIY for the 2017/2018 academic year were in the fairly good category.
LibGuides: Landing Your Dream Job: Helpful Internet Sites

This guide is based on information provided by Jan-Marie Lanuzza, Experiential Education Coordinator and Jean Moats, Director of Library Services.
Pembuatan handout mobile learning berbasis android untuk pembelajaran fisika pada materi gerak parabola dan gerak melingkar di kelas X SMA/MA

This research was conducted because the learning process in the classroom was not yet using smartphone technology based on the curriculum 2013 revision. Each student has a smartphone device which is most are android, but they did not use it in the learning process, the teaching system using speech method, while the printed books still existing in the class. The usage ICT such as text, picture, sound, animation,and video in the class are in separated form yet. Therefore, the purpose of this research is to produce Handout based mobile learning assisted by android aplication and to know the validity criteria of the product. This variety of research is a mixed method. The research uses a validity test instrument that contains 4 aspects as follows; substances; language; graphic and utilization of software. The result are presented in the table,diagram and then analyzed to determine the advisability criteria of handout. Based on the research conducted, there are two results research obtained, first is the handout product are consisted of text, sound, picture, animation, and video while the second is the results of the validity test conducted twice, with an average value of the first validity is 86.93% with high valid criteria and the average value of the second validity is 94.49% with high valid criteria. Based on the results, it can be concluded that the product of handout mobile learning on parabolic and circular motion material assisted by the android class X SMA/MA is feasible to be used in the learning process.
A Novel PageRank-Based Fault Handling Strategy for Workflow Scheduling in Cloud Data Centers

Unexpected faults result in unscheduled cloud outage, which negatively affects the completion of workflow tasks in the cloud. This paper presents a novel PageRank-based fault handling strategy to rescue workflow tasks at the faulty data center. The proposed approach uses a holistic view and considers the task attributes, the timeline scenario, and the overall cloud performance. A priority assignment system is developed based on the modified PageRank algorithm to prioritise workflow tasks. A min-max normalization method is applied to select the target data center and match the timeline at this data center. Additionally, a dynamic PageRank-constrained task scheduling algorithm is proposed to generate the task scheduling solution. The simulation results show that the proposed approach can achieve better fault handling performance, measured by task resilience ratio, workflow resilience ratio, and workflow continuity ratio in both the traditional 3-replica and the image backup cloud environment.
PENERAPAN DATA MINING UNTUK KLASIFIKASI SELEKSI CALON ANGGOTA HMIF AMIKOM YOGYAKARTA MENGGUNAKAN METODE ALGORITMA DECISION TREE C4.5

Members of the Amikom HMIF Organizational Committee then have the authority to carry out their vision and mission or main objectives at Amikom Yogyakarta University, one of which is the implementation of recruitment and placement according to requirements and procedures that have been determined by the Chairperson and other authorized members according to the needs of the formation in each organizational unit or body. Many cases have been found that the selection of members from the same year and during the interview.&#x0D; In the case of the initial C4.5 algorithm, in determining whether or not candidates are eligible to use graduation parameters, namely oral and written interviews, enthusiasm and achievement in organization in the history of education that has been followed. Data mining benefits can be implemented in data parts that contain data in large quantities. The technique used in data mining is a decision tree with a C45 decision tree. The results of the study used 80 data from prospective members who had registered. Producing experimental and evaluation results that C4.5 decision tree algorithm is accurate in determining whether or not prospective members pass.
Implementation of an efficient super resolution algorithm for game images using sparse matrix multiplication

We present a super resolution algorithm that increases the resolution of game scenes. Since game scenes are required to be rendered in real time, rendering high-resolutional game scenes in real time is very challenging. Therefore, increasing the resolution of game scenes rendered in low resolution is very promising. In order to present a fast super resolution algorithm, we implement our super resolution algorithm using a sparse matrix operation that can be accelerated through a matrix multiplication unit (MMU). Since many open source GPUs present an acceleration environment, our MMU-based approach can be implemented in many open source GPUs. As a baseline of our approach, we present a sparse matrix multiplication formula of bilinear interpolation and bicubic interpolation. We furthermore present a sparse matrix multiplication form of a convolution operation, which is necessary for deep learning-based super resolution algorithms. The filters employed in the convolution operations are converted to a series of sparse matrices, which are multiplied to complete the deep learning-based super resolution model. We demonstrate the performance of our approach by measuring peak signal-to-noise ratio (PSNR) and mean opinion score (MOS) of the result images generated by our approach and by the existing methods.
Hybrid Adversarial Imitation Learning.

Extrapolating beyond-demonstrator (BD) performance through the imitation learning (IL) algorithm aims to learn from and outperform the demonstrator. Most existing BDIL algorithms are performed in two stages by first inferring a reward function before learning a policy via reinforcement learning (RL). However, such two-stage BDIL algorithms suffer from high computational complexity, weak robustness, and large performance variations. In particular, a poor reward function derived in the first stage will inevitably incur severe performance loss in the second stage. In this work, we propose a hybrid adversarial imitation learning (HAIL) algorithm that is one-stage, model-free, generative-adversarial (GA) fashion and curiosity-driven. Thanks to the one-stage design, the HAIL can integrate both the reward function learning and the policy optimization into one procedure, which leads to many advantages such as low computational complexity, high robustness, and strong adaptability. More specifically, HAIL simultaneously imitates the demonstrator and explores BD performance by utilizing hybrid rewards. Extensive simulation results confirm that HAIL can achieve higher performance as compared to other similar BDIL algorithms.
ELECTRONIC BENEFIT TRANSFER REDEMPTION: AN INTERACTIVE EXERCISE

This exercise is an interactive participation process that emulates using an Electronic Benefit Transfer (EBT) card, the distribution method that has replaced paper food stamp coupons. EBT is a delivery option that at first glance might easier, faster, and safer for administrators and recipients alike, but EBT must be looked at from the users’ perspective to see the problems. -- I am a person with a disability who receives food stamp benefits. I created the exercise to show what it is like for me and 19 million other food stamp recipients (Health and Human Services, 2000) to use EBT. I can no longer get food coupons and have no choice in delivery method. EBT is like a debit card, swiped at checkout terminals with the amount deducted from my food stamp balance.
Theories of Blockchain

With the huge advancements in the field of blockchain, it becomes necessary to understand how it evolved to be an essential part of all emerging technologies. From cryptocurrencies, healthcare to Internet of Things implementation, there is no field left where blockchain’s applicability is not suitable. Blockchain has been widely adapted due to its various principles and types, which can fulfill a lot of purposes. In this context, the progress of blockchain has been reviewed to determine if it can be proved as a way of providing security, privacy and reliable services in various applications. Based on the review of a variety of literature resources, the chapter provides a quick view of its history, evolution and in-depth analysis of blockchain while keeping the factors such as security, privacy and trust management in consideration. Based on research done, it is believed that blockchain will be seen in various applications in future. The question is still unanswerable if it can be successful in various domains or not, but it might certainly affect the functioning of various financial industries. A lot of further research is still required to search out all the factors which can affect its implementation in various ways.
Research Guides: Understanding Predatory Publishing: Database Sources and Lists

This guide is designed to increase awareness of Predatory Publishing practices, guidelines on how to avoid, and how to seek assistance from information experts.
A Study on Remote Instruction of Studio Art and Design Pedagogy

This study aims to investigate effective design pedagogy by remote instructions and tools through the virtual art and design studio class. Because of the sudden shift to online instruction due to the COVID-19 pandemic, the academic environment has been faced with difficulties of teaching and learning in terms of limited accessibilities, flexibilities, and interactivities. A few video conferencing applications replaced virtual classrooms, however, various disciplines in art and design education were not able to keep the same creativity as an in-person class due to the vacancy of the studio facilities and resources. However, some discipline, especially graphic design major, as dealing with digital media by individual creative tools appears as a new effective design pedagogy. This study analyzed the effectiveness of remote instruction in a new experimental design pedagogy through the UX/UI design studio. The pedagogical methods between synchronized and unsynchronized meetings were measured by collecting data and information from the survey and exit interviews at the end of the semester. Moreover, the students’ outcomes of the design solution were carefully reviewed along with the descriptive data and information. Collected various data and information were reorganized to measure the effective value of learning and teaching through the given remote instruction tools and methods. The findings from the analysis of the effective remote instructions answered for initial research questions. Even if limited interaction and communication in virtual learning and teaching environment is not effective and efficient, applying the digital/online instructional tools properly and efficiently on helping effective working progress for each student is significantly considered. Another significant finding is that well-managed and controlled remote instruction would be a new pedagogical initiative beyond the COVID-19 Pandemic situation. Various instructional models from other researches also provide great potential for face-to-face interaction as an effective virtual classroom and meeting. Even though this study has a few significant concerns for limitation to access design studio facilities and lacking students’ self-directed learning and motivation, the pedagogical objectives in UX/UI discipline have met with the satisfaction of students learning and teaching in comprehensive tasks. Therefore, findings from measured and analyzed students’ learning progress and outcomes through the virtual studio meetings will be significantly necessary to discuss for specifying tangible pedagogy as an effective and efficient remote instruction model in a further direction.
Indonesian-English Code-Mixing Used by Broadcasters in Rapma FM Radio Station at UMS

This study aims to find the types of code-mixing and describe the reasons for using code-mixing used by radio broadcasters. This type of research is descriptive qualitative research. The data of this research is in the form of utterances containing of code-mixing. The data collection technique uses observation with the following steps: recording the broadcasting, collecting the recording, listening the recording, transcribing the recording, classifying the types and reasons for using code-mixing, transcribing based on groups, then provide data coding. The data analysis technique for identifying the types of mixing code using Suwito's theory (1983); explaining the reasons for using Kim's (2006) code mixing. The results of this study are: Firstly, there are five types of code mixing which are ranked respectively from the highest of occurrence to the lowest, they are code-mixing in the word form, phrase form, repetition form, hybrid form, and clause form. The most dominant type of code-mixing used by broadcasters is the code mixing in the word form with a percentage of 60%. Secondly, there are five reasons for using code mixing which are ranked respectively from the highest of occurrence to the lowest, they are explaining factors, habitual factors, message intrinsic factors, participant roles and relationship, and situational factors. The most dominant reason of using code mixing used by broadcasters because of the explaining factors with a percentage of 43%.
Determine Material of the Gravity Particles and Understand the Mechanism of the Universe Gravity Fields: A Recent Study

The study analysing the issue of the gravity fields of universe through another corner depending upon previous theories and concepts to find the way that guide to determine the material of the gravity particles and understand the mechanism of the universe gravity fields, choosing the atomic and nuclear construction to investigate the issue of the gravity. Purpose: Determine the material of the gravity particles and understand the mechanism of the universe gravity fields. Method: Reverse engineering to determine the smallest sub-particles of material observing the results in the moment of crashing Neutrons in the materials accelerator to determine the smallest construction unit of the Neutron, then expect via the theory of the probabilities the model of sitting of Photons in the Neutrons through the concept of the theory of probabilities. Results: The material of the gravity particles are Photons and the mechanism of the universe gravity fields depends upon the magnetic fields of Electrons and Positrons of Photons of the gravity fields.
FEATURE SELECTION AND PARAMETER OPTIMIZATION FOR SUPPORT VECTOR MACHINES USING PARTICLE SWARM OPTIMIZATION AND HARMONY SEARCH

The present paper proposes a mechanism, Diverse Particle Swarm Optimization and Harmony Search (DPSO_HS), which finds feature subsets and parameter values for Support Vector Machines (SVM) when addressing classification problems by incorporating Particle Swarm Optimization (PSO) and Harmony Search (HS). Specifically, we introduced HS to enhance diversity in the PSO process since it has the advantage of providing diverse solutions as compared to other methodologies, as it considers all solutions in memory when improvising a new solution. For performance evaluation, various datasets with a wide range of features, instances, and classes were considered. DPSO_HS showed an increased diversity and classification accuracy as compared to PSO where statistical significance was found in most datasets. In addition, with two different hybridized approaches based on PSO, we observed that the proposed method showed higher accuracy for most datasets. We also reviewed the results of previous research with identical datasets and found that DPSO_HS achieved higher or equal accuracy rates for most datasets.