Reviewerly/exHarmony huggingface dataset:
An Efficient Machine Learning Technique for Prediction of Consumer Behaviour with High Accuracy

Consumers choose to purchase a given item by looking at these evaluations and surveys. Such substance can be positive or negative audits made by consumers who have recently utilized the item. The Machine Learning Calculation can help us to visual portrayal of the information and vectorize the information. This paper presents the Naive Bayes and Logistic Regression method to investigate the consumer behavior. The logistic regression strategies improved preferred performance over others. The current issues are examined, and afterward, current answers for these issues are introduced and talked about. The trial results show that the proposed strategy has higher precision, recall and F1 score. The strategy is end up being effective with high accuracy on remarks. The reproduction and analysis is finished utilizing the python spyder 3.7 software.
Predicting Calibration Parameter Values for Constitutive Models using Genetic Programming

In material science, models are derived to describe emergent properties (e.g. elasticity, strength, conductivity, ...) and their relations to the material and processing conditions. Constitutive models are models that describe the behaviour of materials for instance deformation processes through applied forces. We describe a general method for the extension of constitutive white-box models using genetic programming (GP). The method is demonstrated for a constitutive model which is used in computational mechanics to describe the material response to various thermo-mechanical loading conditions. This model operates with internal material variables such a dislocation density and contains a number of parameters. Among them there are three calibration parameters, which are usually fit to measured data since the relations to the processing conditions (e.g. deformation temperature, strain rate) are not fully understood. Our proposed GP-based method identifies these relations and generates short expressions which can be plugged into the constitutive model instead of the calibration parameters. This would enable interpolation as well as extrapolation which is crucial for constitutive modelling. Our results show that evolving extensions for the constitutive model implicitly with GP leads to better predictive accuracy than explicitly learning independent formulas for predicting calibration parameters with symbolic regression.
Pelatihan Analisis Data Hasil Penelitian Bagi Mahasiswa Program Studi Pendidikan Bahasa Inggris STKIP PGRI Bandar Lampung

Training on Data Analysis of Research Results for Students of the English Language Education Study Program of STKIP PGRI Bandar Lampung aims to provide knowledge to students so they can analyze research data. This activity was carried out because of the limited knowledge of students in analyzing research data, namely quantitative research, qualitative research, PTK (classroom action research) and experimental research, so that students were unable to analyze data and interpret the research results in their thesis. The solution offered is to provide training in data analysis of research results to students of the English Language Education Study Program of STKIP PGRI Bandar Lampung, especially in making it easier for students to carry out experimental research on their thesis. The results of the training that had been carried out were seen when monitoring and evaluation were held by STKIP PGRI Bandar Lampung lecturers that the students of the English Language Education Study Program at STKIP PGRI Bandar Lampung were able to analyze research data on their respective theses.
Face Mask Detection– A Machine Learning Approach

The COVID-19 is an unmatched emergency inciting an immense number of incidents and security issues. To reduce the spread of Covid, individuals regularly wear shroud to promise themselves. This makes the face attestation an especially infuriating undertaking since unequivocal pieces of the face are hidden. A basic mark of the intermingling of specialists during the progressing Covid pandemic is viewed as plans to deal with this issue through fast and suitable strategies. Face Detection has made a remarkable issue in Image preparation and Computer Vision. Different new figurings are being envisioned utilizing convolutional developments to make the most of them as exact as could be viewed as ordinary. These convolutional models have made it conceivable to eliminate even the pixel subtleties. We desire to plan an equivalent face classifier that can perceive any face present in the bundling paying little psyche to its course of action. Beginning from the RGB picture of any size, the method utilizes Predefined Training Weights of Architecture with arranging is performed through Fully Convolutional Networks. This is to correspondingly set up to see an unmistakable facial cover in a solitary edge.
Enrichment Of Color Image Using Random Transfer Functions

Image enrichment might be a way of improvising an image quality in terms of upper insight of the knowledge present within the image. Enrichment of color images is more burdensome compared to the enrichment of gray scale images. Several methods are preferred for enriching the color images. variety of these methods are furnished during this seminar. One method supported enrichment in HSV space is described intimately . The results and comparison of those methods are also proposed.
OUTDOOR LEARNING-BASED THEMATIC LEARNING

This research is a research on developing a test instrument for higher-order thinking skills based on outdoor learning for fifth grade elementary school students. This study aims to 1) develop a test instrument for higher order thinking skills based on outdoor learning in elementary schools; 2) validate the test instrument through expert validation and empirical validity. Expert validation is carried out by consulting the product development design with expert lecturers. Empirical validity was carried out using the product moment correlation formula, while the determination of reliability used the Cronbach Alpha formula. The research method uses Design Based Research. The development of this model is carried out in stages 1) identification and problem analysis by researchers and practitioners collaboratively 2) developing solutions based on theoretical benchmarks, existing design principles and technological innovations 3) carrying out an iterative process to test and improve practical solutions 4) reflection to produce design principles and improve implementation of practical solutions. The results of the study are 1) 22 items of higher order thinking skills; 2) validation by experts states that this assessment instrument is suitable for use as an assessment tool, while in empirical validation it is stated that the overall results of the test using the product moment formula of the items have been declared valid. Determination of reliability using Cronbach's alpha formula has a reliability value of 0.935 which is categorized as high reliable. Overall, in this development research, this higher-order thinking ability assessment instrument is valid and reliable as a form of assessment.
COVID-19 Transition to Online: Quick! Bring the Fun!.

The need to quickly transition from face-to-face teaching using engaging, content-based activities to a new, online platform in just two weeks during the COVID-19 pandemic, made it necessary to try to migrate familiar activities that the students enjoyed into a virtual classroom. The activity that proved to be the most successful in maintaining a sense of community, engaging students, and reviewing content was playing Quizlet Live while in Breakout Rooms in Zoom.Keywords: online teaching, gaming, pandemic, student participation, active learning, learner engagement, collaboration, educational technology, Distance Education.
COMPENDIO INTERPRETATIVO VIVENCIAL DE LA COMUNICACIÓN EN PANDEMIA

he following essay aims to outline an interpretive vision from the perspective of the experience of communication, its relevance and importance to be handled effectively and assertively in each process of our lives, according to each role to assume, situation and event to our around, with a view that glides through the necessary changes and transformations that we have suffered since the beginning of the Covid 19 pandemic, at the beginning of 2020. This compendium invites us to rethink our neuro-affective processes (sensations, emotions and experiences) in accordance with rational thinking, with the understanding that recognizing and interpreting effective communication strategies will allow us to better adapt to our environment. Taking this interpretive journey to the internalization of neurocommunication as a viable alternative for the readjustment of our way of communicating from the understanding and understanding of learning to listen, to interpretation, analysis and response to our environment; developing the ability to change those aspects that we must improve to achieve a conciliation in our mind, words and actions, from the respect, posture and acceptance of the opinion of others. Without losing the essence that characterizes our being from the complementarity of logical criteria
Comparative Analysis of Distance Metrics using Face Recognition

Researchers are using various distance metric standards in evaluation of face recognition methods. In past decades, the Eigenfaces and Fisherfaces face recognition methods were generally evaluated using the Euclidean distance (ED) metric that have shown better performance in cooperative environments, but poorly performed in non-cooperative environments. This paper presents a comparative analysis of distance metrics through face recognition methods i.e., Eigenfaces and Fisherfaces in both cooperative environments and non-cooperative environments. The recognition accuracies of these methods is critically evaluated using ED and Bray Curtis Dissimilarity (BCD) metrics in the face recognition under different conditions on publicly available face databases such as ORL and extended Yale B (EYB). The experimental results show significant improvement in recognition accuracies of Eigenfaces and Fisherfaces methods under BCD.
FAKTOR-FAKTOR YANG MEMENGARUHI AKTIVITAS BELAJAR SISWA DALAM PEMBELAJARAN SPREADSHEET KELAS X AKUNTANSI DI SMK

ABSTRACT The objective of this research is to study factors affecting students’ learning activities in Spreadsheet learning at Vocational High School. It used the descriptive qualitative research method. Its population was all of the students as many as 214 of Accounting Department. Purposive sampling was used to determine its samples. They consisted of 71 students in Grade X. The data of the research were collected through questionnaire. The instrument was validated with Spearman’s Product Moment at the significance level of 5%. The reliability coefficient was calculated with the Cronbach’s Alpha method. The analysis prerequisite test of the research used the KMO Test dan Barlett’s Test. The data of the research were analyzed by using the Exploratory Factor Analysis (EFA) aided with the computer software of SPSS Version 22 for Windows. The result of the research shows that there were 8 factors affecting the students’ learning activities, namely:(1) encouragement to learn; (2) learning attitude; (3) interest and talent; (4) intellectual intelligence; (5) learning habit; (6)social environment; (7) family; and verbal intelligence. The factor which most dominantly affected the students’ learning activities was that of encouragement to learn with the variance percentage of 26.251%, whereas the factor which least affected the students’ learning activities was that of verbal intelligence with the variance percentage of 4.036%. Keywords: factor analysis, students’ learning activities, spreadsheet learning ABSTRAK Tujuan penelitian ini untuk mengkaji faktor-faktor yang memengaruhi aktivitas belajar siswa dalam pembelajaran spreadsheet di SMK. Penelitian ini merupakan penelitian deskriptif kuantitatif. Populasi dalam penelitian adalah seluruh siswa kelas akuntansi yang berjumlah 214 siswa. Pengambilan sampel menggunakan teknik purposive sampling. Sampel penelitian adalah siswa akuntansi kelas X yang berjumlah 71 siswa. Teknik pengumpulan data menggunakan metode angket. Teknik uji validitas instrumen menggunakan rumus product moment dengan taraf signifikansi 5%. Perhitungan koefisien reliabilitas dalam penelitian ini menggunakan metode Cronbach’s Alpha. Uji prasyarat analisis yang digunakan adalah pengujian KMO dan Barlett’s. Teknik analisis data yang digunakan adalah Exploratory Factor Analysis (EFA) dengan bantuan software SPSS Versi 22 for Windows. Hasil penelitian menunjukkan bahwa terdapat delapan faktor yang memengaruhi aktivitas belajar siswa yaitu: (1) faktor dorongan belajar, (2) faktor sikap belajar, (3) faktor minat dan bakat, (4) faktor kecerdasan intelektual, (5) faktor kebiasaan belajar, (6) faktor lingkungan sosial, (7) faktor keluarga, dan (8) faktor kecerdasan verbal. Faktor yang paling dominan dalam memengaruhi aktivitas belajar siswa adalah faktor dorongan belajar dengan persentase variansi 26,251%, sedangkan faktor yang paling lemah dalam memengaruhi aktivitas belajar adalah faktor kecerdasan verbal dengan persentase variansi 4,036%. Kata kunci: analisis faktor, aktivitas belajar siswa, pembelajaran spreadsheet
Whole Foods launches free online cooking classes

Whole Foods enlisted a team of experts and social media influences to teach the Home Ec 365 classes.
4차 산업혁명 시대를 대비한 고객 중심의 신제품 개발 필요성 인식 제고

It is expected that the Fourth Industrial Revolution will have a great impact on the manufacturing industry, especially as it will cause big changes in industry, economy as well as socio-cultural. To cope with this situation, each country is promoting the policy of cultivating its manufacturing. This study derives the effect of the fourth industrial revolution on product lifecycle management for smart manufacturing through expert’s cognitive analysis. The knowledge area of product lifecycle management is divided into Project Portfolio Management, Collaborative Product Design, Customer Needs Management, Direct Material Sourcing, Product Data Management, Digital Manufacturing & Engineering, R&D Foundation, New Product Development through academic research. The expert survey was conducted in five different perspectives: Importance, Insufficiency. Then, using the results of the survey and the academic research the implication about Product Lifecycle Management were derived. The significance of this study is that it derives the change areas and factors of the product life cycle management knowledge domain in preparation for the fourth industrial revolution according to the perspective of importance and insufficiency.
한국어 인명의 러시아어 번역·표기의 문제점 고찰

This paper investigates the current state of Russian Cyrillic orthography of Korean names. With the rise of Hallyu or the Korean wave, an accurate translation and orthography of the names of Korean actors, singers and literary writers is an important issue. Different Cyrillization of the same name only exacerbates confusion.There are two types of Russian Cyrillic orthography to transcribe Korean words - the Holodovich System and the Kontsevich system. There exists controversy on some of the issues between the two systems. Among the differences in opinions among researchers, this paper categorizes the most urgent issues in Cyrillization of Korean proper nouns into four groups. Examples where such issues arise are collected and analyzed. Although there are various arguements around each of the types of Cyrillization, this paper attempts to narrow the differences in arguements and proposes alternatives that are believed to be more appropriate. Findings in this paper may contribute to developing a standard for Cyrillization of the Korean language.
A REVIEW OF ALTERNATIVE SECURITY EQUITY MARKET FINANCING AND BUSINESS GROWTH OF LISTED SMEs IN NIGERIA

Small and Medium Enterprises (SMEs) has been recognized globally as a useful tool for development. However, financing in this regard has posed a major challenge to Africa and Nigeria in particular as developing country. The need to attain self-sufficiency through development cannot be over emphasised. Therefore, this study is aimed at examining the Alternative Security Equity Market (ASEM) introduced recently by the Nigerian Stock Exchange (NSE) to serve as alternative means for equity fund raising only to listed SMEs in the nation’s Stock Exchange for business growth. This paper looks at the uniqueness of this platform under which listed SMEs can raise funds for business expansion, improved technology, adding a new product line, improving the work force to mention but few. It will also uncover the criteria under which SME can be listed at the NSE in other to be fit for raising such funds. Relevant literatures were consulted to advance the hidden importance of ASEM as a financing options for listed SMEs. Consequently, this paper sought to explain the need for SMEs to embrace this development in Nigeria considering its enormous contributions to growth and development and how unpredictable the world economy is in the 21 st century and Nigeria in particular.
The Formal-Language-Constrained Graph Minimization Problem

We formally define the Formal-Language-Constrained Graph Minimization problem. The goal is to minimize the amount of data associated to the edges of a graph database, while preserving its utility, defined as a conjunctive path query. We show that the problem is NP-hard. A solution to this problem contributes to balancing the trade-off between privacy protection and utility when publishing a graph database.
Budaya Literasi Santri (Studi Kasus di Pondok Pesantren Nurul Islam Kecamatan Antirogo Kabupaten Jember)

Literacy is not just about a person's ability to recognize numbers and letters. Literacy is also about cultural activities that are closely related to reading and writing-competence, even now it is also interpreted with more comprehensive. While the discourse itself is related to various fields of science, ranging from religious studies, linguistics, arithmetic, psychology, politics, economics, social, literature and many more. Now the literacy culture is facing challenges, especially in the midst of changing times which results in a transformation in all fields to be stopless, non-stop. To achieve the missions of an advanced Indonesia, it cannot be separated from the role of literacy culture. In this case, pesantren as one of the influential institutions in the world of education in Indonesia needs to take the role of building people’s literacy culture. Santri is part of determining the future of Indonesia .This study aims to uncover the culture of literacy among students, as well as what are the supporting and inhibiting factors surrounding them.
Supplemental Material: Maturation experiments reveal bias in the chemistry of fossil melanosomes

Supplemental text and discussion, figures of scanning electron microscope photos of untreated and matured melanosomes, analysis of thickness, multichannel analysis of X-ray fluorescence, and datasets with melanosome geometry and chemistry.&lt;br&gt;
Attacks against Ranking Algorithms with Text Embeddings: a Case Study on Recruitment Algorithms

Recently, some studies have shown that text classification tasks are vulnerable to poisoning and evasion attacks. However, little work has investigated attacks against decision making algorithms that use text embeddings, and their output is a ranking. In this paper, we focus on ranking algorithms for recruitment process, that employ text embeddings for ranking applicants resumes when compared to a job description. We demonstrate both white box and black box attacks that identify text items, that based on their location in embedding space, have significant contribution in increasing the similarity score between a resume and a job description. The adversary then uses these text items to improve the ranking of their resume among others. We tested recruitment algorithms that use the similarity scores obtained from Universal Sentence Encoder (USE) and Term Frequency Inverse Document Frequency (TF IDF) vectors. Our results show that in both adversarial settings, on average the attacker is successful. We also found that attacks against TF IDF is more successful compared to USE.
Quantum engineering of non-Gaussian resources for continuous-variable quantum computing by photon-number-resolving detection

Continuous-variable quantum computing (CVQC) boasts, by way of quantum optics, one of the largest scalability potentials of all quantum computing platforms. In order to enable universal CVQC, i.e., exponential speedup as well as fault tolerance, one requires quantum resources (states and/or gates) with a non-Gaussian Wigner function. We present several state preparation techniques, using photon-number-resolving detection, that enable the generation of resource states such as GKP or binomial error encodings.
Preservice Teacher Trainees Attitudes towards E Learning and Satisfaction Factors Prior and During Covid-19: A Comparative Study

The present study aims to explore the attitudes about e-learning and its satisfaction factors (perceived interest, perceived usefulness, perceived ease of use, perceived confidence) among pre-service teacher trainees studied prior to Covid-19 and during the Covid -19 pandemic situation. The study also investigates whether there are any statistically significant differences among trainees' attitudes towards e-learning and its satisfaction factors concerning gender, habitat, stream, age, time spent (per day) in e-learning. In this present study, a sample of 174 trainees was selected using the convenience sampling technique. For collecting data Normative survey method and Dimpal Rani’s Attitude towards E-learning scale” was used. Results revealed there was a statistically significant difference found in perceived e-learning usefulness, perceived e-learning ease of use, perceived e-learning confidence and e-learning attitude in both intervals, but such difference was not found in perceived e-learning interest factors.  Gender wise analysis showed significant difference found in perceived e-learning interest, perceived e-learning usefulness, perceived e-learning ease of use in both the interval but statistically no difference found in the perceived e-learning confidence factor. Habitat and time spend in e-learning wise analysis revealed there was no significant difference in the attitude of trainees towards e-learning and its satisfaction factors studying in both the intervals. With regards to age and stream of study, a difference was found in the trainee's attitude and satisfaction factors studying prior to the Covid-19 interval, but no such difference was found during Covid-19.
Arrendale Library: Library & Research Skills Tutorials: Tutorial 1: Welcome to the Library

The contents of this guide show you some basics about the Library's website and how to use the online research services.