Reviewerly/exHarmony huggingface dataset:
PERBEDAAN HASIL BELAJAR SISWA DENGAN MENGGUNAKAN MODEL STUDENT TEAM ACHIVEMENT DIVISION (STAD) DAN NUMBERED HEAD TOGETHER (NHT) PADA MATERI STRUKTUR DAN FUNGSI JARINGAN TUMBUHAN KELAS VIII DI SMP N 6 LANGSA TAHUN PELAJARAN 2019/2020

Abstract&#x0D; Education is the process of changing the attitudes and behavior of a person or group who in an effort to mature themselves through teaching and education efforts, when talking about education people will tend to think about school or tertiary education, even though the notion of education is not only related to school, but also regarding grades students. This study aims to determine differences in student learning outcomes and which model is better for learning outcomes using the Student Team Achievement Division (STAD) and Numbered Head Together (NHT) models on the structure and function material of plant networks in class VIII at SMP N 6 Langsa. 2019/2020 lessons. The method used is an experimental method with instruments in the form of written tests. The results obtained prove that there is a comparison of the Student Team Achievement Division (STAD) model with Numbered Head Together on the learning outcomes of class VIII students at SMP N 6 Langsa in the 2019/2020 school year, with the testing criteria -t_ (1-1 / 2 α) &lt;t &lt;t_ (1-1 / 2 α) with a value of -2.008 - 0.025≤ 5.97 ≤ 2.008 - 0.025 is the same as -2.033 ≤ 5.79 ≤ 1.983. With a difference in the comparison of learning outcomes of 2.46. Material for the structure and function of plant tissue for class VIII at SMP N 6 Langsa in the 2019/2020 school year.
Perbandingan Estimasi Radar Cuaca Dopler Baron Terhadap Data Observasi Kejadian Hujan Di Kota Kupang

Radar is able to provide information about extreme weather observations in the form of heavy rain, so it is important to find the level of accuracy of the radar in providing extreme weather information. So that with accurate data disaster mitigation can be done by creating an early warning system using radar data in order to minimize the impact that will occur. Comparative analysis of the estimated rainfall events on the radar with surface observation data shows a good level of accuracy, but the blankness of the data on the radar due to damage thus influences the decision making of the forecasters when providing extreme weather information quickly to the public. By knowing the radar accuracy level is quite good in estimating rain events, BMKG can provide weather information in the form of appropriate early warning so that people can anticipate extreme weather events
Reinforcement learning using associative memory networks

It is shown that associative memory networks are capable of solving immediate and general reinforcement learning (RL) problems by combining techniques from associative neural networks and reinforcement learning and in particular Q-learning. The modified model is shown to outperform native RL techniques on a stochastic grid world task by developing correct policies. In addition, we formulated an analogous method to add feature extraction as dimensional reduction and eligibility traces as another mechanism to help solve the credit assignment problem. The network contrary to pure RL methods is based on associative memory principles such as distribution of information, pattern completion, Hebbian learning, and noise tolerance (limit cycles, one to many associations, chaos, etc). Because of this, it can be argued that the model possesses more cognitive explanative power than other RL or hybrid models. It may be an effective tool for bridging the gap between biological memory models and computational memory models.
Foldscope as a diagnostic tool: A case study in Lakhimpur district of Assam

Microscope provides a beneficial instrument for visualization of microorganisms.Its cost is very high which is not affordable for rural based educational institutes.For enhancing scientific temperament among rural children Manu Prakash introduced an ultra-low-cost origami-based approach for large-scale manufacturing of microscope, specifically demonstrating bright field, darkfield and fluorescence microscopes.Introduction of low cost microscopy would reduce quality analysis costing and also one can have a better understanding about the surface microstructure of foods by using the foldscope.Future scope lies in development of simple methods for common people, who could also used this instrument to rapidly determine the microscopic quality of food before consumption.We had organized some awareness cum demonstration programme regarding foldscope and its applications in the field of science education in different educational institute of Lakhimpur district, Assam.
Improving 9th Grade Students’ Writing Competency Using Card Lottery Games Media

The current study was intended to use Card Lottery Games Media to improve writing ability. The design of the study is action research. The sample of the study was IX grade students in one selected school. It was found that after implementing Card Lottery Game Media in two cycles, it could be concluded that Card Lottery Games Media was effective to improve the students’ competency in writing report text There were five aspects that should be full field by the students in writing report text, there are; developing ideas (content), organizing ideas, vocabulary, grammar, and mechanics. The students’ improvement could be seen from the mean score of the pre-test (56,25), post-test 1 (74) and post-test 2 (84,25). During the implementation of Card Lottery Games Media, the students were looked serious, enthusiastic, motivated and interested.
Dynamic Simulation of Tilted Rotor Quadcopter

Application of quadcopter unmanned aerial vehicle (UAV) has already become common today. As the name suggests, quadcopter has four rotors and these rotors can be classified into two types: fixed and tilted rotors. The maneuvering of quadcopter using the fixed rotor is achieved through the thrust differential. On contrary, a tilted rotor can be rotated or tilted and the resultant thrust component will move the quadcopter longitudinally. In this study, the dynamic behavior of HMF SL300 tiltrotor quadcopter is analyzed through simulation. The study is limited to longitudinal behavior of the HMF SL300 tiltrotor quadcopter in z- and x-axis. A Simulink model has been developed based on the longitudinal dynamic model of the quadcopter and acceleration, velocity and displacement of the quadcopter in z- and x-axis when the tilt angle is varied are presented. Based on the findings from the simulation, it can be concluded that the higher the tilt angle, the higher the rate of motion in x-axis but the lower the rate of motion in z-axis.
"Analysis of Face Recognition Methods "

Face recognition has emerged as a promising field in computer-based applications in recent years, owing to the wide range of applications that it has found in a variety of fields. Due to the obvious wide variety of variances across people's faces, face recognition utilizing database photos, actual data, record images, and sensor photographs is a tough task. Image segmentation, cognition, and data analysis, to mention a few areas of research, all have ties to facial identification. The development of new techniques associated with face authentication technologies is an ongoing process that contributes to the development of more long-lasting face recognition algorithms. Many facial recognition techniques are often divided into two categories: feature-based approaches and holistic methods. At the present, there is a relatively small number of research that have been conducted that have linked both of these techniques. Face recognition algorithms have been developed in large numbers over the course of the past few decades. The purpose of this article is to provide a systematic evaluation of a wide variety of facial recognition methods that are currently on the market. This includes neural networks, fuzzy-based methodologies, and the eigenvalues approach, among other things.
A professional image’s formation philosophy

The study relevance lies in the fact, that the prestige and success functioning of the high education national system depends on both the teacher and the high education institution. Such requirements make it necessary to purposefully prepare future high school teachers for creating their own effective professional and pedagogical image. Modern society perceives image as a political and socio-cultural category. Image acts as a link between the individual and the audience. At the same time, it serves as a reflection of both the audience interests and the professional interests, seeking to combine these interests, to move away from the unilateral pressure from above, typical of a totalitarian state. A recent research’s and publications’ analysis. In the study we consider the essence of a specialist’s professional image and his effective self-presentation features, which are presented in the works of I. Alekhin, V. Bebik, M. Vudkoka, F. Genov, F. Kuzina, N. Skripachenko, E. Utkin, D. Francis. The scientific achievements in the pedagogical image formation and a high school teacher’s "professional image" of such scholars as I. Volodarska, N. Guzy, A. Morozov, S. Panchuk, V. Khoroshikh, O. Chebikin, I. Chertikova deserve attention. An unexplored parts of a common problem selection - regularities in the development of the educational personnel pedagogical skills and a formation of professionally important qualities in future managers. The study foundation - the basic scheme for the individual image formation, is represent a novelty. The professional and pedagogical teacher image ensures a high social prestige and success of national system, which is simultaneously based on the strict requirements that the target audience puts forward. The study’s aim is to analyze the influence of personality characteristics on a professional image formation. The main material presentation. The modern image perception analysis is carried out not only in economic, but also in political and socio-cultural categories; presents the "image" definition; it was found that the image can be divided into two types: the ideal (to which they aspire) and the real (present) analyzed sign systems, contribute to the image’s creation; highlighted the main image management types, which has a positive effect on the leader image and the whole team work’s result; selected elements in the individual with the personalization strategy of building a favorable image; it is established that the image has a very clear attachment to this time, reflecting even the nuances of changes in public opinion. The research methodology was made by methods of analysis and generalization. Conclusions - a concept has been formed in which a person must clearly maintain his image and the corresponding actions and actions
Uncertainty handling using Improvised Intuitionistic fuzzy ANN based Voice Disorder Detection

The voice pathology detection is one of the essential process which has to be determined in the earlier stages because it is a sign for raising health related problems. The aim of this paper is to handle the uncertainty in voice dataset due to inconsistency in extracting potential features and vagueness in dealing voice signals. The raw voice signals are preprocessed by feature extraction using meyer wavelet and potential features involved in voice disorder detection are done using sequential forward feature selection methods as voice preprocessing. This research work introduced an improvised intuitionistic fuzzy artificial neural network which enhances the process of voice disorder detection is SVD database by using analytical hierarchical processing for assigning weights and thus the complete neural network performance was fine tuned instead of assigning the weights randomly. The simulation results proved the performance of the proposed model as best by producing more promising result while comparing with ANN, PANN and Fuzzy ANN models.
Indian Handwritten Script Identification System Based on Random Forest Tree Ensembles

The work proposal addresses to introduce a methodology for Indian unconstrained handwritten script identification by practicing distinct features and classifiers. By utilizing classifiers like RF, SVM, k-NN, and LDA for Indian script identification using statistical, geometric, and structural features. To preserve all the information present on handwritten documents such as historical, medieval, inscription, financial administration, public records, government archives, letters, land councils, various agreements, etc. in digitalize form needs textual document processing system (e.g. OCR). To build a precise and productive multi-script/language textual document processing system must have script identification. For this study use, total 1288 (line wise) samples of ten scripts use in India are collected from different persons of different gender, age, education and region (rural or urban). After successful training and testing, 81.8% and 0.252 accuracies and the OOB error rate are achieved by Random Forest respectively. And 77.8%, 73.5%, and 65.5% accuracy is achieved in SVM, k-NN and LDA classifiers respectively.
Detection of Breast Cancer in the Bio Medical Image using Supervised Machine Learning

The detection of disease for diagnosis in the medical image becomes easier, when the machine learning concept is used. In this article, the Breast cancer is detected from the biomedical image using supervised machine learning technique. The bio medical image is acquired from the image sensors and that acquired image is pre processed for further processing. From that pre-processed image, the object detection is performed. The next processes are segmentation and feature extraction. Finally, the supervised learning is implemented in the image for image classification. With the help of machine learning, the different cases of cells are also detected, differentiated and spotted for the further diagnosis.
Service-based Architecture for SLA Management in Cloud Computing

Service Level Agreements (SLAs) have proven their added value in the modern distributed computing era.Well-established systems for managing SLAs represent a challenging aspect in cloud computing.Certainly, proper design of such systems can save a lot of costs that are spent in paying SLA violation penalties.A managed SLA can be accomplished through several stages (i.e.life cycle): Definition and Awareness, Negotiation, Design, Implementation, and Monitoring and Compliance.In this work, a reliable service-based architecture for managing the SLA life cycle in cloud computing is proposed.The introduced architecture is composed of five main layers: Infrastructure Layer, SLA Layer, Provider Layer, Consumer Layer, and Security and Privacy Layer; each layer in turn consists of multiple components that provide certain management functionalities (e.g.violation detection and recovery).This paper focuses on the design and implementation of the SLA layer and its components, in addition to a monitoring system that observes the SLA performance, detects any violations by determining a particular calculated compliance value, and diagnoses and recovers from such violations by taking the proper actions.
Binary Search In Linked List

This paper is based on an approach to implement Binary Search in Linked List. Binary Search is divide and conquer approach to search an element from the list of sorted element. In Linked List we can do binary search but it has time complexity O(n) that is same as what we have for linear search which makes Binary Search inefficient to use in Linked List. The main problem that binary search takes O(n) time in Linked List due to fact that in linked list we are not able to do indexing which led traversing of each element in Linked list take O(n) time. In this paper a method is implemented through which binary search can be done with time complexity of O(log2n). This is done with the help of auxiliary array. Auxiliary array helps in indexing of linked list through which one can traverse a node in O(1) complexity hence reducing the complexity of binary search to O(log2n) hence increasing efficiency of binary search in linked List.
Public Response to Online Public Debate in the 2020 Regional Head Election of Ponorogo Regency

This year, regional head elections were held in the midst of the Covid-19 pandemic so that social media can be used as a means of online campaigns to reduce mass gathering. This research was conducted to see the response of the Ponorogo community in participating in online public debates and to assess people's political participation by analyzing public comments on public debate shows on YouTube and Facebook. The data is processed using the Nvivo12 plus application by using cross tabulation data analysis techniques with manual coding then the results of the data obtained are described and analyzed in accordance with the theory of response and political participation. The data obtained on Facebook and YouTube were 772 responses with details of 357 responses on Facebook and 415 responses on YouTube. The responses given are in the form of positive, negative, and neutral responses. The process of obtaining data on public response is in accordance with the S-O-R response theory (Stimulus, Organism, Response) and the stage of response formation, as well as the political participation of the Ponorogo community is high enough to see the debate shows but the level of activeness in giving responses is less active.
Implementation of Artificial Intelligence to Predict Threats in Social Media Based on User’s Behavior

The online social network users are with faced multiple vulnerabilities threats that are strategically implementing the social engineering mechanisms.Cybercriminals targeting the social engineering technique often investigate the environment in which a user is subjected.However, current research is pegged on the technical measurement of how threats can be neutralized or prevented completely in the online social network environment.It, therefore, follows that the online social networks systems create characteristics and elements which can be investigated further to produce relevant models.Facebook in the recent past has worked so hard and invested heavily in developing algorithms that are able to determinate an imminent cyber-attack based on user's behavior and characteristics on the platform.As much as Facebook has done relevant technical measures to ensure that threats are minimized as much as possible there is still a gap of further investigations which seek to harness the automated algorithmic prediction using artificial intelligence to determine the possibility of an attack or a threat.This research uses the machine learning techniques to show how an AI-based algorithm of the user's behavioral characteristics, perceptions, and socio-emotions that would help in identifying features that further become very relevant in determining an individual's vulnerability to social engineering threats and attacks.The aim is to primarily study the habitual perspective and perpetual perspective reactions towards socially engineered threats daily.This research uses a comparative analysis of the theories and the findings from the primary data to show that certain behaviors of Facebook users are a threat to other users.Through machine learning techniques, the results have shown how A.I. algorithms work in identifying scamming messages and scammers.
The Effect of Auditor Cybersecurity Expertise on Audit Fees and Cyber Incidents.

This study focuses on local audit offices' cybersecurity expertise and examines the effect of such expertise on non-breached clients' audit fees and future cyber incidents.Using data on cyber incidents from the Audit Analytics cybersecurity database and the Privacy Rights Clearinghouse for the period from 2006 to 2017, we observe a positive and significant association between auditor's cybersecurity experience and non-breached clients' audit fees.This suggests that auditors with greater cybersecurity experience consider cyber risk before any cyber incident has occurred.In addition, we find evidence that the increased audit fees charged by cybersecurityexperienced auditors are negatively associated with non-breached clients' future breaches and auditor's IT capability strengthens the association.Collectively, this finding suggests that auditor's cybersecurity experience is effective in helping clients preventing future cyber incidents and auditor's IT capability strengthens the effectiveness.Our results remain robust after a battery of sensitivity tests.
Data Mining Menggunakan Rough Set dalam Menganalisa Modal Upah Produksi pada Industri Seragam Sekolah

In a fund industry is a very important factor, mismanagement or unavailability of funds can have a negative impact on the industry, the successful shop still uses internal capital that is capital from the sale of the store itself, the sales results are not always sufficient to pay the production wage money cause late payments which adversely affect the performance of workers and the industry itself, production wage data on successful stores can be utilized by using the rough set method to find solutions to predict future production wages, The results found 57 rules of 8 reducts from 11 Equivalence Classes that provide new information that is the cause factor of not achieving capital production wages, the main factor is income followed by sewing wages, cut wages.
Pemanfaatan Media Pembelajaran Lectora Inspire Dalam Upaya Peningkatan Kualitas Pembelajaran (Pengabdian Masyarakat di SLTPN 7 Kota Payakumbuh)

A qualify learning process that is fullfill the needs of students is urgent for a teacher, so that the expected learning objectives can be achieved. Implementation of multi-media in learning is one of alternative method. Lectora inspire is a program that can be used by teachers in designing multi-media learning. Lectora inspire can be used to combine flash, record video, combine images and screen capture. Lectora Inspire has the advantage of being user friendly, because it does not require understanding of complex programming languages. The design and manufacture of multi- media using the Lectora Inspire program is carried out by providing integrated training to teachers of SLTPN 7 Payakumbuh City. Training methods are provided by providing information, discussion, guided practice, independent practice and ending with evaluation.Keywords : media, instructional, lectora inspire
Exploration of the Compilation of English Learning Materials for Chinese College Students Based on Big Data under the Guidance of Complex Dynamic Theory

With the help of big data and Citespace software, this research makes a statistical analysis of the journals and dissertations on College English teaching and learning materials collected by CNKI from 2011 to 2020. This paper, based on the knowledge map drawn by the visualized analysis of literatures volume, authors, research institutions and keywords clustering, analyzes the current research status and hotspots in the compilation of China’s College English textbooks. It is found that there are six problems in the compilation. Because of the complexity of teaching and learning materials and the dynamic progress of language learning, the nature of English teaching and learning materials is bound to turn from a learning tool to learning resources. Thus, this research, from the perspective of Complex Dynamic System Theory, attempts to develop big data-based College English learning materials with digital, individual and multi-dimensional characteristics by three paths: the establishment of big data-based English learning behaviors index system, the development of big data-based College English learning materials and the application of big data-based College English learning materials. This paper will explore a new way of developing China’s College English learning materials, improve and optimize the compilation and development of College English learning materials in China.