Reviewerly/exHarmony huggingface dataset:
RNE: A Scalable Network Embedding for Billion-Scale Recommendation

Nowadays designing a real recommendation system has been a critical problem for both academic and industry. However, due to the huge number of users and items, the diversity and dynamic property of the user interest, how to design a scalable recommendation system, which is able to efficiently produce effective and diverse recommendation results on billion-scale scenarios, is still a challenging and open problem for existing methods. In this paper, given the user-item interaction graph, we propose RNE, a data-efficient Recommendation-based Network Embedding method, to give personalized and diverse items to users. Specifically, we propose a diversity- and dynamics-aware neighbor sampling method for network embedding. On the one hand, the method is able to preserve the local structure between the users and items while modeling the diversity and dynamic property of the user interest to boost the recommendation quality. On the other hand the sampling method can reduce the complexity of the whole method theoretically to make it possible for billion-scale recommendation. We also implement the designed algorithm in a distributed way to further improves its scalability. Experimentally, we deploy RNE on a recommendation scenario of Taobao, the largest E-commerce platform in China, and train it on a billion-scale user-item graph. As is shown on several online metrics on A/B testing, RNE is able to achieve both high-quality and diverse results compared with CF-based methods. We also conduct the offline experiments on Pinterest dataset comparing with several state-of-the-art recommendation methods and network embedding methods. The results demonstrate that our method is able to produce a good result while runs much faster than the baseline methods.
A social engineering és a manipulációs technikák és módszerek

In the first, theoretical part of our two-part study, we review all or most of the manipulation methods and techniques related to the human soul, psychology, and interpersonal communication, which also appear in the field of information security. In describing the techniques and methods, we present, among other things, shoulder surfing, asking for and providing help, personalization, phishing, image and video forgery, fake security applications, and fraudulent calls. In the latter case, we also point out the criminal law implications of the perpetrators ’act. Fraudsters have also taken advantage of the psychological effects of the coronavirus, as mentioned in several examples. We hope that we can contribute to the personal and organizational development of information security by reviewing the theory, presenting examples, and then presenting our research results in the next section.
Development of a Method for Measuring Resource Efficiency for Product Lifecycle

In recent years, increasing the efficient use of material resources by circulating them (through reuse, refurbishment, remanufacturing, and recycling) has become an important global goal. However, quantitative methods of measuring resource efficiency during the product life cycle have not previously been established. In this study, we built a framework for a measurement method with two features. The first feature concerns the change in a product’s value due to the reuse, refurbishing, and remanufacturing of products. The second feature is the difference in environmental impact based on the type of material used. As a case study, we formulated five scenarios for refrigerated showcases. In our presentation, we review existing methods for measuring the resource efficiency of products and present our proposed method. Then, we introduce the refrigerated showcase product business of Panasonic Corporation. Next, we describe the baseline and four alternative scenarios developed for our analysis, and we present the results as calculated using different methods. Finally, we discuss the effectiveness of the various measurement methods.
The relationship between genre-based English learning material to Indonesian learner’s motivation and achievement

Achieving an effective learning activity requires appropriate teaching materials in the learning process. Yet, there are some problems in the preparation of learning materials to teach that affect delivering the materials in the learning process. This paper is aimed to examine the impact genre-based as a learning material which is able to motivate learners in learning with interesting activity for learning process to improve learners’ writing achievement. The finding of this study shows that the learner’s motivation and achievement were improved. Also, there were a strong relationship between the usability of Genre-based learning materials to learner’s motivation and achievement. The result of this study is expected going to be applicable for teachers who want to shift their teacher-centered learning style to be learner-centered style in writing activities. Also, it is for the reader who is concerning to English learning media and learners motivation.
Factors Affecting the Study Habits of Senior High School Students of the Science, Technology, Engineering and Mathematics (STEM) Curriculum

A descriptive-comparative research design was used in determining the factors affecting the study habits of senior high school students of the Science, technology, Engineering and Mathematics (STEM) curriculum. The respondents of the study were 300 senior high school students under the STEM curriculum. The Slovin's formula was used to determine the ideal number of respondents with 0.05 level of significance. A parametric statistical test particularly the t-test was used to test the difference on the study habits of the STEM students particularly time management, study environment and academic skills when grouped according to sex and type of school graduated from. Results showed that, the test of significance conducted and revealedthat the male students' study habits on test preparation, note taking skills and reading skills are better than the study habits of the female students on the aforementioned variables.Further, the study habits specifically on time management, study environment, test preparation, note taking skills and writing skills of the STEM students graduated from the public schools are better than the study habits of the students graduated from the private schools.
Discrete solution pools and noise-contrastive estimation for predict-and-optimize.

Numerous real-life decision-making processes involve solving a combinatorial optimization problem with uncertain input that can be estimated from historic data. There is a growing interest in decision-focused learning methods, where the loss function used for learning to predict the uncertain input uses the outcome of solving the combinatorial problem over a set of predictions. Different surrogate loss functions have been identified, often using a continuous approximation of the combinatorial problem. However, a key bottleneck is that to compute the loss, one has to solve the combinatorial optimisation problem for each training instance in each epoch, which is computationally expensive even in the case of continuous approximations. We propose a different solver-agnostic method for decision-focused learning, namely by considering a pool of feasible solutions as a discrete approximation of the full combinatorial problem. Solving is now trivial through a single pass over the solution pool. We design several variants of a noise-contrastive loss over the solution pool, which we substantiate theoretically and empirically. Furthermore, we show that by dynamically re-solving only a fraction of the training instances each epoch, our method performs on par with the state of the art, whilst drastically reducing the time spent solving, hence increasing the feasibility of predict-and-optimize for larger problems.
Aspect-category based Sentiment Analysis on Dynamic Reviews

The emergence of social media has generated huge amounts of datawhich has led researchers to study the possibility of their exploration in order to identify their hidden knowledge. Two areas are being used for this: opinion mining and sentiment analysis. Sentiment analysis identifies and extracts subjective information in social material. In this paper we propose a method to process the user reviews and categorize them based on their aspects after which the aspect categories are recognized. Following this, the polarity of the reviews based on these categories are calculated, depending on the tone and adjectives used. In the proposed method, a Convolutional Neural Network (CNN) is trained and used for the task of aspect term extraction, which gives an f-measure of 88.97%. This CNN model uses general embeddings as well as domain specific embeddings for training purposes which are created using Word2Vec. Aspect term list and review pairs are processed to identify their aspect categories. Then the polarity of the review is detected using TextBlob. An aspect-category based summary is generated for the dynamic reviews input by the users using the deep neural network model.
Replica-Exchange Nos\'e-Hoover Dynamics for Bayesian Learning on Large Datasets

In this paper, we present a new practical method for Bayesian learning that can rapidly draw representative samples from complex posterior distributions with multiple isolated modes in the presence of mini-batch noise. This is achieved by simulating a collection of replicas in parallel with different temperatures and periodically swapping them. When evolving the replicas' states, the Nose-Hoover dynamics is applied, which adaptively neutralizes the mini-batch noise. To perform proper exchanges, a new protocol is developed with a noise-aware test of acceptance, by which the detailed balance is reserved in an asymptotic way. While its efficacy on complex multimodal posteriors has been illustrated by testing over synthetic distributions, experiments with deep Bayesian neural networks on large-scale datasets have shown its significant improvements over strong baselines.
A Lightweight Speaker Recognition System Using Timbre Properties

Speaker recognition is an active research area that contains notable usage in biometric security and authentication system. Currently, there exist many well-performing models in the speaker recognition domain. However, most of the advanced models implement deep learning that requires GPU support for real-time speech recognition, and it is not suitable for low-end devices. In this paper, we propose a lightweight text-independent speaker recognition model based on random forest classifier. It also introduces new features that are used for both speaker verification and identification tasks. The proposed model uses human speech based timbral properties as features that are classified using random forest. Timbre refers to the very basic properties of sound that allow listeners to discriminate among them. The prototype uses seven most actively searched timbre properties, boominess, brightness, depth, hardness, roughness, sharpness, and warmth as features of our speaker recognition model. The experiment is carried out on speaker verification and speaker identification tasks and shows the achievements and drawbacks of the proposed model. In the speaker identification phase, it achieves a maximum accuracy of 78%. On the contrary, in the speaker verification phase, the model maintains an accuracy of 80% having an equal error rate (ERR) of 0.24.
For a Dynamic Web Services Discovery Model for Open Ecosystems of Software Providers

With the increasing adoption of business models relaying on Cloud Computing, digital platforms and servitization, IT providers have been trans-forming their solutions into services-based, having as a goal facilitating their binding to clients' applications. In this formed wide and open service-oriented environment, classical static services binding approaches are limited to support the business dynamics of Virtual Organizations (VO). As services would assure VO members' systems operation, a bad services selection may hazard that. We argue, though, that services selection criteria, largely based on QoS and costs, are not enough to provide higher confidence to VO members when selecting services from such open ecosystem of service providers. In this line, this paper proposes a more comprehensive and multi-criteria decision-making model for dynamic services discovery. A prototype has been implemented and results are discussed.
The Influence of Guided Questions Technique with Inside outside Circle toward Students’ Ability in Writing Descriptive Text (A Quasi-experimental Research of MTsN 2 Pandeglang)

Siti rahayu. 161230087. 2020. “The Influence of Guided Questions Technique with Inside outside Circle toward Students’ Ability in Writing Descriptive Text” (A Quasi-experimental Research of MTsN 2 Pandeglang). This research investigates the use of guided questions technique with inside outside circle on writing descriptive text.. The objectives of this research are : 1) To know the students’ ability in writing descriptive text, and 2) To know the students’ ability in writing descriptive text using guided questions technique with inside outside circle. This research applied by quasi-experimental design and quantitative research method. The researcher took sample from class VIII i consist of 30 students as control class and VIII j consists of 30 students as experimental class. This research uses tetst and observation. Based on statistic calculation, the researcher got mean pre-test score 57,7 and post-test 62,06 from control class. While from experimental class the researcher get mean pre-test 61,53 and mean post-test 72,3 . The researcher get to (t observation) is higher than tt (t table) both at significance level 5% and 1%. to > tt = 3,26 > 1,67 at significance level 5%, to > tt = 3,26 > 2,39 at significance 1 %. It means that Ha (alternative hypothesis) is accepted and Ho (null hypothesis) is rejected. The conclusion of this research, there is an influence of guided questions technique with inside outside circle toward students’ ability in writing descriptive text.
Pengembangan Media Kotak Si Bolang Materi Muatan IPA dalam Meningkatkan Hasil Belajar Kelas 1 MI

The problem in this study is how to develop learning media for the box media, the material for the content of IPA, namely the material for grouping living and inanimate objects in order to improve the learning outcomes of class 1 students in MI MANSYAUL HUDA in each domain. The purpose of this study was to develop a valid, effective and practical learning media for the box media of living and inanimate objects. This research is R&amp;D according to Borg and Gall. Data sources were obtained from 2 individual students, 6 small group students and 12 large group students. Validation of development research involves learning validators, mat erial validators, design validators, language validators and learning practitioners. The results of the research on the development of Si Bolang box media met the attractive criteria with the results of the material expert's test reaching an eligibility level of 84.6%, learning experts reaching 82.5%, design experts reaching 75%, linguists reaching 85%, learning practitioners experts, and the results Student learning in each domain has increased as seen from the average value of the Pre-test and Post-test scores, namely the cognitive learning outcomes of 73.75 to 83 The average number of learning outcomes in the affective domain is 71.25 to 84.9. The average number of learning outcomes in the psychomotor domain was 70.8 to 82.1. This shows that the product developed has an attractive eligibility level because the concepts are in accordance with the characteristics of children, so this media is suitable for use in learning.
ENGINEERING WEB-BASED INFORMATION SYSTEMS FOR MANAGEMENT OF WOMEN AND CHILD PROBLEM HANDLING ACTIVITIES

The problem of violence against women and children, viewed from an individual as well as a social perspective, can have multiple effects. The effects such as psychological and individual health and the quality of public health. Women and children in everyday life often receive unpleasant treatment from close people and strangers. The constraints experienced are that often the two affairs are combined and handled by one sector, the number of officers is less than the cases handled, there is not enough budget to carry out follow-up actions and many residents do not want to disclose their problems directly to the authorities. There are many problems for women and children, so a "Task Force for Handling Women and Children Problems (Satgas PPA)", both at the central and regional levels. The activities of the PPA Task Force include: outreach, identification of conditions and services needed, protection of women and children at the scene (emergency assistance), placement and displacement of women and children who experience problems and referrals and / or recommendations. The research objective was to produce a management system for handling women and children activities in the village of Katekan, Gantiwarno, Klaten. The research method used consists of literature study, data collection and system development with the Waterfall method. The result of this research is a system capable of managing the activities of the task force handling women and children that can provide information in all variations to help make decisions. This system is built using PHP programming and MySQL DBMS.
PROSES PEMECAHAN MASALAH MATEMATIKA SISWA SMA BERDASARKAN KECERDASAN MAJEMUK

This study aims to analyze the mathematics problem-solving process of high school students based on multiple intelligences. In research, multiple intelligence is divided into dominant linguistic intelligence, interpersonal and kinesthetic intelligence, dominant musical intelligence, logical-mathematical and naturalistic, existential, intrapersonal, and visual dominant intelligence. The type of research used in this research is descriptive exploratory, and the approach used is qualitative and quantitative approaches. Determination of research subjects was carried out using purposive sampling based on multiple intelligences, to obtain 3 high school students of class X as research subjects. The research instrument used was a multiple intelligence test and two problem-solving tests adopted from the American High School Math Exam (AHSME) Problems and the Provincial High School Mathematics National Science Olympiad questions. The data obtained were analyzed, utilizing data reduction. The research results show that students with multiple different intelligence bits have different ways of solving them, but there are also similarities in solving problems.
Quantum teleportation of an arbitrary three-qubit via three bell states

We report the three-qubit quantum teleportation scheme through channel six-qubit states which composed of three bell state. We apply arbitrary six-qubit state as measurement basis. This protocol can be done with classical communication of the appropriate measurement between the sender and receiver.
Speech Pathologist’s Positive Motivation is a Guaranty of Child’s Psychological Safety

The article examines the concept of speech pathologists’ positive motivation for their future professional work and the concept of psychological safety of the children with speech disorders, according to the analysis of psychological and pedagogical literature, and clarifies the relationship of these components. It also describes the essential educational conditions contributing to the formation of positive motivation of the future speech pathologists during educational process at their university, substantiates the urgency of the problem of developing this type of motivation in the students.
Problems and Reform Plan in Training Compound Talents of Economic Cooperation With Russia in Universities

As the main institution of professional talent training, universities play an active role in the training talents of economic cooperation and trade with Russia.However, universities still have problems such as insufficient total supply and imbalance between supply and demand of the economy and trade talents at present.Universities should establish an open and international school-running concept, reform professional schoolrunning models and teaching organization and management methods, and build a compound faculty by integrating internal and external resources in order to solve these existing problems and promote the sustained and rapid development of economy and trade cooperation between China and Russia.
DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference.

This paper proposes a dual-supervised uncertainty inference (DS-UI) framework for improving Bayesian estimation-based uncertainty inference (UI) in deep neural network (DNN)-based image recognition. In the DS-UI, we combine the classifier of a DNN, i.e., the last fully-connected (FC) layer, with a mixture of Gaussian mixture models (MoGMM) to obtain an MoGMM-FC layer. Unlike existing UI methods for DNNs, which only calculate the means or modes of the DNN outputs' distributions, the proposed MoGMM-FC layer acts as a probabilistic interpreter for the features that are inputs of the classifier to directly calculate the probability density of them for the DS-UI. In addition, we propose a dual-supervised stochastic gradient-based variational Bayes (DS-SGVB) algorithm for the MoGMM-FC layer optimization. Unlike conventional SGVB and optimization algorithms in other UI methods, the DS-SGVB not only models the samples in the specific class for each Gaussian mixture model (GMM) in the MoGMM, but also considers the negative samples from other classes for the GMM to reduce the intra-class distances and enlarge the inter-class margins simultaneously for enhancing the learning ability of the MoGMM-FC layer in the DS-UI. Experimental results show the DS-UI outperforms the state-of-the-art UI methods in misclassification detection. We further evaluate the DS-UI in open-set out-of-domain/-distribution detection and find statistically significant improvements. Visualizations of the feature spaces demonstrate the superiority of the DS-UI.
SISTEM DAN PERAWATAN MESIN KEMUDI DI KM. OTONG KOSASIHPT. PUPUK INDONESIA LOGISTIKJAKARTA

Steering or rudder is a system that serves to change the direction of movement of a ship. Ship steering system in the form of leaf / plate located on the back of the boat and use a hydraulic system to move the steering wheel right and left leaves, this study describes the working hydraulic system steering gears in steering the ship. Hydraulic system is a technology that utilizes liquid, usually oil, to perform a line of movement or rotation. This system works on the principle If a liquid subjected to pressure, then the pressure will propagate in all directions with no increase or decrease its power.Steering gears is a machine that uses a hydraulic system to move the leaves of steering the ship. The nature of the hydraulic system that is not noisy (silent operation), smooth movement, able to work on a variety of weather is suitable to be applied to the steering gears on ships. Hand Hydraulic machine used on non-propeller barges (barge no engine) and also used on lower tonnage ships and used to stand - by for a hydraulic machine is powered up.
Conjunctive and Disjunctive Limits: Abstract Logics and Modal Operators

Abstract Departing from basic concepts in abstract logics, this paper introduces two concepts: conjunctive and disjunctive limits. These notions are used to formalize levels of modal operators.