Reviewerly/exHarmony huggingface dataset:
Soda Machine and User Experience: A Study of Icon Display

Touch-screen GUIs have become a key feature of modern consumer electronics. The purpose of this study is to investigate the effect that reducing the number of icons on the GUI of a popular soda machine has on drink selection time and user satisfaction. Twenty subjects participated in the study, with 10 assigned to the control and experimental groups respectively. Time to make a drink selection was recorded and compared between groups using unpaired t-test. User satisfaction was measured using a five-point scale questionnaire. The results suggested that user satisfaction, except for the display dependability category, is not affected by the reduction of the number of icons on the soda machine GUI and no change was observed in drink selection time.
PERBANDINGAN MODEL JARINGAN SYARAF TIRUAN DENGAN ALGORITMA LEVENBERG-MARQUADT DAN POWELL-BEALE CONJUGATE GRADIENTPADA KECEPATAN ANGIN RATA-RATA DI KOTA SEMARANG

Wind is one of the most important weather components. Wind is defined as the dynamics of horizontal air mass displacement measured in two parameters, namely speed and direction. Wind speed and direction depend on the air pressure conditions around the place. High wind speed intensity can cause high sea water waves. To estimate wind speed intensity required a study of wind speed prediction. One of method that can be used is Artificial Neural Network (ANN). In ANN there are several models, one of which is backpropagation. Thepurpose of this researchis to compare between backpropagation model with Levenberg-Marquadt and Powell-Beale Conjugate Gradient algorithms. The results of this researchshowing that Powell-Beale Conjugate Gradient better than Levenberg-Marquadtalgorithms. The best model architecture obtained is a network with two input layer neurons, six hidden layer neurons, and one output layer neuron. The activation function used are the logistic sigmoid in the hidden layer and linear in the output layer. MAPE value based on the chosen model is 0,0136% in training process and 0,0088% in testing process.
Sign-Regularized Multi-Task Learning

Multi-task learning is a framework that enforces different tasks to share their knowledge to improve the generalization performance. It is a long-standing active domain that strives to handle several core issues including which tasks are correlated and similar and how to share the knowledge among correlated tasks. Existing works usually do not distinguish the polarity and magnitude of feature weights and commonly rely on linear correlation, due to three major technical challenges in: 1) optimizing the models that regularize feature weight polarity, 2) deciding whether to regularize sign or magnitude, 3) identifying which tasks should share their sign and/or magnitude patterns. To address them, this paper proposes a new multi-task learning framework that can regularize feature weight signs across tasks, beyond the conventional framework for feature weight regularization. We innovatively formulate such sign-regularization problem as a biconvex inequality constrained optimization upon the multiplications among feature weights with slacks. We then propose a new efficient algorithm for the optimization with theoretical guarantees on generalization performance and convergence. Extensive experiments on multiple datasets show the proposed methods’ effectiveness, efficiency, and reasonableness of the regularized feature weighted patterns.
STUDI KEGAGALAN INSTRUKSI KELAS DI KURSUS BAHASA INGGRIS ESSENTIAL MEDAN

The purpose of this study was to determine and analyse the fault instruction or explanation given by an English guru at school, causing interpretation or response that does not comply with the guru's expectations. The objective of this research is to evaluate the classroom instruction failure at English Course Medan. This study was applied descriptive qualitative design. In the classroom interaction, researcher found four guru failures; two of them are giving instruction, and others are explaining topic failure.There are several factors that led to the failure of the guru in the learning process. The first, guru failure may be the caused by the unpreparedness of gurus in teaching. Gurus should well-prepared teaching scenario well so that failures can be minimized. Another factor is the guru was too overestimating the ability of siswa. Gurus expect siswa to know phrasal verb before the guru explained what it was. This could have an impact on frustrating siswa themselves who do not know anything.
What’s next for Amazon after Jeff Bezos? No dramatic changes, just more growth and optimisation

Jeff Bezos has announced he will stand down as chief executive of Amazon in the third quarter of 2021. The founder of the online retail behemoth will hand the reins to Andy Jassy, who currently leads Amazon’s cloud computing wing. The announcement comes after an enormously successful 2020 for Amazon despite (or perhaps because of) the COVID-19 pandemic, with operating cashflow up 72% from the previous year to US$66.1 billion, and net sales increasing 35% to US$386.1 billion. Amazon has its share of detractors, with critics highlighting concerns around working conditions, tax minimisation, anti-competitive practices and privacy. But its enormous size and continuing phenomenal growth make it a force to be reckoned with. How did Amazon get to this position, and what does the future hold under new leadership?
Perancangan Sistem Manajemen Sekolah Berbasis Progressive Web Apps

The lack of manpower in education field and the ever growing number of students who are seeking knowledge in school makes the education workforces find it difficult to handle. That’s why there are demands for school management system which can handle school’s academics efficiently. A progressive web apps based school management system can provide the easiness in processing academics matter for teachers and education workforces according to the stage of education that the students are taking which include the daily assessment, mid-term assessment, and the end of semester assessment. What makes the progressive web apps based application great is that the teachers and students can access the application anywhere using mobile web or even desktop web. The system can do self-calculation based on the daily assessment the teachers have entered. The system can give the report to each student accordingly through the applications. To summarize it all, the school management system which based on progressive web apps can be used to ease the assessment of each students efficiently.
Tingkat Kesiapsiagaan Mahasiswa Universitas Negeri Padang Terhadap Bencana Gempa Bumi Dan Tsunami

This purpose of this reaserch is to know the level of preparedness of Padang State University students against the earthquake and tsunami disaster. Preparedness parameters in dealing with earthquake and tsunami disasters, namely knowledge related to earthquake and tsunami disasters, disaster emergency response plans, and early warning systems. This type of research is quantitative descriptive. The population of this researcher were students of Padang State University, totaling 30,965 students.. The research sample was determined by proportional random sampling technique, totaling eight faculties. sampling of respondents using the Slovin formula with a eror tolerance of 10% so that there are 100 people. Data analysis used is descriptive data analysis. The results of this research show that 1) the level of preparedness related to the knowledge of earthquakes and tsunamis in the high category is found at (75.00%) FIS, (78.33%) FIP, (80.95%) FIK, (72.22%) FE, (75.00%) FT, FMIPA (79.48%,) and FPP (72.22%), while FBS (68.88%) are classified as medium. 2) The level of preparedness related to disaster emergency response in the high category is found in FIS (79.76%), FIP (72.85%,) FE (78.57%), FT (72.61%), FBS (81.90%), FMIPA (72.52%) and FPP (83.33%), while FIK (63.26%) is classified as medium. 3) The level of preparedness related to the early warning system in the high category is found in FIS (70.83%), FIP (71.25%), FIK (80.35%, FE (78.12%), FT (83.33%), FBS (70.00%), while FMIPA (67.30%), and FPP 58.33% are classified as medium.
Sistem Pakar Tes Kepribadian Menggunakan Metode Dempster-Shafer

Personality is a pattern of human behavior that comes from within someone's self. personality sometimes needs to be adapted to the context in the world of employment, personality is often identified with the attitude and character of someone in the world of work and everyday life. Women who are considered to have a good personality can be seen from the way he walks, how to speak, and how to behave properly. The term personality comes from the Latin word persona which means mask or mask, which is the face cover which is often used by stage players, whose purpose is to describe a person's behavior, character, or personality. Some types of personality based on big five personality personality are classified into several types of personality, namely: Neuroticism, Extraversion, Openness To Experience, Conscientiousness, Agreeableness. Expert systems are computer-based systems that use knowledge, facts, and reasoning techniques in solving problems that can usually only be solved by an expert in a particular field. Expert systems provide added value to technology to help experts determine a person's personality based on the characteristics and characteristics of individual eating to need to be studied again with certain methods. Dempster shafer method - is an expert system method used by experts (experts) to determine relevant and accurate decisions. by applying the dempster shafer method to the expert system the personality test can determine the type of individual or individual servitude based on each characteristic so that it can be based on the type of personality.
Unified Principles For Multi-Source Transfer Learning Under Label Shifts

We study the label shift problem in multi-source transfer learning and derive new generic principles. Our proposed framework unifies the principles of conditional feature alignment, label distribution ratio estimation, and domain relation weights estimation. Based on inspired practical principles, we provide a unified practical framework for three multi-source label shift transfer scenarios: learning with limited target data, unsupervised domain adaptation, and label partial unsupervised domain adaptation. We evaluate the proposed method on these scenarios by extensive experiments and show that our proposed algorithm can significantly outperform the baselines.
A Probabilistic Approach to Constrained Deep Clustering

Clustering with constraints has gained significant attention in the field of semi-supervised machine learning as it can leverage partial prior information on a growing amount of unlabelled data. Following recent advances in deep generative models, we derive a novel probabilistic approach to constrained clustering that can be trained efficiently in the framework of stochastic gradient variational Bayes. In contrast to existing approaches, our model (CVaDE) uncovers the underlying distribution of the data conditioned on prior clustering preferences, expressed as pairwise constraints. The inclusion of such constraints allows the user to guide the clustering process towards a desirable partition of the data by indicating which samples should or should not belong to the same class. We provide extensive experiments to demonstrate that CVaDE shows superior clustering performances and robustness compared to state-of-the-art deep constrained clustering methods in a variety of data sets. We further demonstrate the usefulness of our approach on challenging real-world medical applications and face image generation.
Farsi Conceptual Text Summarizer: A New Model in Continuous Vector Space

Traditional methods of summarization were very costly and time-consuming. This led to the emergence of automatic methods for text summarization. Extractive summarization is an automatic method for generating summary by identifying the most important sentences of a text. In this paper, two innovative approaches are presented for summarizing the Persian texts. In these methods, using a combination of deep learning and statistical methods, we cluster the concepts of the text and, based on the importance of the concepts in each sentence, we derive the sentences that have the most conceptual burden. In the first unsupervised method, without using any hand-crafted features, we achieved state-of-the-art results on the Pasokh single-document corpus as compared to the best supervised Persian methods. In order to have a better understanding of the results, we have evaluated the human summaries generated by the contributing authors of the Pasokh corpus as a measure of the success rate of the proposed methods. In terms of recall, these have achieved favorable results. In the second method, by giving the coefficient of title effect and its increase, the average ROUGE-2 values increased to 0.4% on the Pasokh single-document corpus compared to the first method and the average ROUGE-1 values increased to 3% on the Khabir news corpus.
Enhancement of Library Services into Mobile-based Library Services in Select University Libraries in Delhi (India): users' perspective

The overwhelming growth of mobile devices has created new challenges of providing access to online content in mobile-accessible formats and providing opportunities to learn anytime and anywhere and also facilitate the practice of bring your own device (BYOD) and accessing library resources The primary purpose of the study discussed in the present article was first to understand the problems of users they face due to the unavailability of mobile-based library services and then figure out user perception of how to enhance the existing library services to mobile-based library services. The findings of the study show that all the surveyed universities/institutions are yet to exploit the full potential of mobile technology. By contrast, other universities/institutions in developed countries are advancing in terms of providing information access/retrieval to the library users through mobile devices. Therefore, considering the possibility of fast information access, mobile computing provides myriad opportunities for libraries to provide access anytime and anywhere. The responses collected indicate that the respondents are willing to access library services through their mobile devices. The study is significant because it represents one of the earliest works to shed light on the current level of use of mobile technology and mobile-based library services in university libraries, which are in primitive nature. The findings of the study can provide guidance to the students, research scholars, faculty members, and others to identify popular mobile library services and access them on the go. The study also provides some practical suggestions for the studied institutions and their libraries to enhance the existing library services into mobile-based library services so that they can be accessed through mobile devices based on the perception of respondents.
Development of nonsense sentence corpus (O'Neill et al., 2020)

Purpose: The goal of this study was to develop and validate a new corpus of sentences without semantic context to facilitate research aimed at isolating the effects of semantic context in speech perception.Method: The newly developed corpus contains nonsensical sentences but is matched in vocabulary and syntactic structure to the existing Basic English Lexicon (BEL) corpus. It consists of 20 lists, with each list containing 25 sentences and each sentence having four keywords. Each new list contains the same keywords as the respective list in the original BEL corpus, but the keywords within each list are scrambled across sentences to eliminate semantic context within each sentence, while maintaining the original syntactic structure. All sentences in the original and nonsense BEL corpora were recorded by the same two male and two female talkers.Results: Mean intelligibility scores for each list were estimated by calculating the mean proportion of correct keywords achieved by 40 normal-hearing listeners for one male and one female talker. Although small but significant differences were found between some pairs of lists, mean performance for all 20 lists fell within the 95% confidence intervals of the mean.Conclusions: Lists in the newly developed nonsense corpus are reasonably well equated for difficulty and can be used interchangeably in a randomized experimental design. Both the original and nonsense BEL sentences, all recorded by the same four talkers, are publicly available.Supplemental Material S1. Complete list of all 500 nonsense sentences. Supplemental Material S2. List of the original words along with the words that were accepted as having a similar semantic meaning. O'Neill, E. R., Parke, M. N., Kreft, H. A., & Oxenham, A. J. (2020). Development and validation of sentences without semantic context to complement the Basic English Lexicon sentences. Journal of Speech, Language, and Hearing Research. Advance online publication. https://doi.org/10.1044/2020_JSLHR-20-00174
Analysis of Contamination Characteristics in The Hand Function Evaluation Process

This study is to investigate characteristics of infection during hand function evaluation process by the difference in disinfection methods between hands and evaluation tools in order to find out how to manage effective disinfection of hand agility evaluation tools used in the occupational therapy service. The subjects of study were adults over 19 years of age, and methods was three groups by selecting the O’conner’s dexterity test and the Grooved peg board test, which are hand agility evaluation tools. In the first group (n=3), the subject's hands were sterilized with an alcohol swab and the evaluation tools were not sterilized, and an agility test was performed according to the existing method, and the degree of contamination of the hands was measured. In the second group (n=3), the evaluation tool was sterilized with an alcohol swab, and agility was evaluated  without disinfecting the hands of the subject, and the degree of contamination was measured. In the third group (n=3), the subject's hands and evaluation tools were sterilized with an alcohol swab, and the hand agility test was conducted and the degree of contamination was conducted. There was significant difference in frequency and size of contamination between 3 groups (p<0.05). In addition, contaminationbetween two group showed significant differences in thumb and index finger(p<0.05).In this study, disinfection and management of both hands and evaluation tools that are the main cause of contamination is the most effective for contamination control, and removing the source of infection by determining the disinfection method according to the contents of the hand function evaluation reduces the risk of infection and personal hygiene.
An Analysis of Using Duolingo Application in Improving Students’ Vocabulary Mastery at 10th Grade of SMA YADIKA Bandar Lampung

Pratiwi, (2020) An Analysis of Using Duolingo in Improving Students’ Vocabulary Mastery of 10th Grade at SMA YADIKA Bandar Lampung SMA YADIKA Bandar Lampung is one of the many schools in Bandar Lampung, researchers found several problems during observation. Some students said that they liked learning English but they found it difficult to express their skills due to lack of vocabulary, and the learning techniques used were still difficult to apply with this phenomenon. Teachers should use a lot of media, but in reality, the teacher only focuses on textbooks and manuals, teachers must be able to make students more eager to learn English and not make students stress when learning English. In this study, researchers used qualitative methods, precisely descriptive qualitative. The purpose of this study was to obtain evidence about how to use the Duolingo application in students' vocabulary mastery. The data source of this research is a video documentation of the learning process. The text is taken from interviews with students and students' opinions by distributing a list of questions. The results showed that the use of Duolingo Application as a Media in mastering the vocabulary of tenth-grade students at SMA YADIKA Bandar Lampung, it can be concluded that Duolingo Application has had a positive influence, this can be seen from the increased motivation, and students' Vocabulary Mastery; and the Duolingo Application has strengths namely Learning Through Technology, Language Courses, Duolingo Application Content, and Free registration and then its weaknesses, there are disadvantages of the Duolingo Application namely the Internet, Translations, and Features. So, it can be concluded that the Duolingo Application directly has a positive effect on tenth graders at Bandar Lampung YADIKA High School in vocabulary mastery.
Correction to: Recallable but not Recognizable: The Influence of Semantic Priming in Recall Paradigms

A Correction to this paper has been published: https://doi.org/10.3758/s13415-021-00872-2
Implementasi Metode Hungarian Dalam Penugasan Karyawan (Studi Kasus: PT. Jefrindo Consultant)

The assignment of employees in an office is one of the things that is complicated and often has difficulty in the division of tasks which causes instability in the performance of employees. Applications using POM Qm For Windows make the process of assigning employees very easy to get results as efficiently as possible. This employee assignment problem is solved by creating an employee assignment optimization model by maximizing the level of efficiency of the use of POM Qm For Windows software to minimize the level of employee dissatisfaction with the applicable tasks. The purpose of this study is to find out the minimization of employee assignment costs that must be applied by PT. Jefrindo Consultant. In looking for minimizing the cost of machining assignments the method used is the Hungarian Algorithm to find costs that are minimal in the placement of employees. After doing the calculation results using the Hungarian method, the company should implement this method in order to minimize the cost of assigning employees to be done
N-Bref : A High-fidelity Decompiler Exploiting Programming Structures

Binary decompilation is a powerful technique for analyzing and understanding software, when source code is unavailable. It is a critical problem in the computer security domain. With the success of neural machine translation (NMT), recent efforts on neural-based decompiler show promising results compared to traditional approaches. However, several key challenges remain: (i) Prior neural-based decompilers focus on simplified programs without considering sophisticated yet widely-used data types such as pointers; furthermore, many high-level expressions map to the same low-level code (expression collision), which incurs critical decompiling performance degradation; (ii) State-of-the-art NMT models(e.g., transformer and its variants) mainly deal with sequential data; this is inefficient for decompilation, where the input and output data are highly structured. In this paper, we propose N-Bref, a new framework for neural decompilers that addresses the two aforementioned challenges with two key design principles: (i)N-Bref designs a structural transformer with three key design components for better comprehension of structural data – an assembly encoder, an abstract syntax tree encoder, and a tree decoder, extending transformer models in the context of decompilation. (ii) N-Bref introduces a program generation tool that can control the complexity of code generation and removes expression collisions. Extensive experiments demonstrate that N-Bref outperforms previous neural-based decompilers by a margin of 6.1%/8.8% accuracy in datatype recovery and source code generation. In particular, N-Bref decompiled human-written Leetcode programs with complex library calls and data types in high accuracy.