Reviewerly/exHarmony huggingface dataset:
Rancang Bangun Sistem Informasi Penjualan Bahan Baku Gypsum dan Baja Berbasis Web

Abstract - CV Gypsum Griya Indah is a market leader distributor company in the industry of gypsum and mild steel raw materials. The sales system at this company is still manually felt to be less effective in attracting customers. By implementing information systems at Griya Indah CV Gypsum which is engaged in sales and wants to expand its marketing area through an E-commerce website. Aside from being a means of promotion, E-commerce websites can simplify the process of ordering and purchasing goods. E-commerce websites do not only act as information media but can also expand sales areas to reach all of Indonesia and internationally. For consumers, websites simplify the process of purchasing goods needed. In this study the method used is the waterfall method which describes a systematic and sequential approach to software development, starting with the specification of user needs and then continuing through several stages as follows planning, modeling, construction, and the delivery of the system to customers / users, then end with complete software support generated. By using webset as a media. &#x0D; Keywords: E-commerce Website, Gypsum Raw Material, Light Steel
Memory-Efficient Adaptive Optimization

Adaptive gradient-based optimizers such as Adagrad and Adam are crucial for achieving state-of-the-art performance in machine translation and language modeling. However, these methods maintain second-order statistics for each parameter, thus introducing significant memory overheads that restrict the size of the model being used as well as the number of examples in a mini-batch. We describe an effective and flexible adaptive optimization method with greatly reduced memory overhead. Our method retains the benefits of per-parameter adaptivity while allowing significantly larger models and batch sizes. We give convergence guarantees for our method, and demonstrate its effectiveness in training very large translation and language models with up to 2-fold speedups compared to the state-of-the-art.
PEMBELAJARAN MENULIS PUISI DENGAN MENGGUNAKAN METODE OUTDOOR STUDY PADA SISWA KELAS X SMAN 1 KATAPANG

The subject of this study is the results of evaluating poetry writing for students who do not reach the indicators of learning success in the curriculum so that the researcher offers a solution that is a recognized learning method that is more effective in improving students' ability to write poetry using the Outdoor study method. The formulation of the problem formulated in this study is about how the results of poetry writing skills using the outdoor study method? This study aims to determine the results of poetry writing skills using the outdoor study method. The method used in this study is the experimental method. The instrument for collecting data in this study uses the initial test sheet and the final test. Based on the results of the research, the students' ability to write poetry texts obtained an average initial test score of 43,0 and after using the outdoor method the study of poetry writing learning obtained an average value of 64,5. So, it can be concluded that the application of the outdoor study method to learning poetry text writing in class X SMAN 1 Katapang is able to improve student learning outcomes.
A Knowledge Transfer Framework for Differentially Private Sparse Learning

We study the problem of estimating high dimensional models with underlying sparse structures while preserving the privacy of each training example. We develop a differentially private high-dimensional sparse learning framework using the idea of knowledge transfer. More specifically, we propose to distill the knowledge from a "teacher" estimator trained on a private dataset, by creating a new dataset from auxiliary features, and then train a differentially private "student" estimator using this new dataset. In addition, we establish the linear convergence rate as well as the utility guarantee for our proposed method. For sparse linear regression and sparse logistic regression, our method achieves improved utility guarantees compared with the best known results (Kifer et al., 2012; Wang and Gu, 2019). We further demonstrate the superiority of our framework through both synthetic and real-world data experiments.
Principal Component Analysis on Mixed Data For Deep Neural Network Classifier in Banking System

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Towards Evaluating and Understanding Robust Optimisation under Transfer

In this work, we evaluate adversarial robustness in the context of transfer learning from a source trained on CIFAR 100 to a target network trained on CIFAR 10. Specifically, we study the effects of using robust optimisation in the source and target networks. This allows us to identify transfer learning strategies under which adversarial defences are successfully retained, in addition to revealing potential vulnerabilities. We study the extent to which features learnt by a fast gradient sign method (FGSM) and its iterative alternative (PGD) can preserve their defence properties against black and white-box attacks under three different transfer learning strategies. We find that using PGD examples during training on the source task leads to more general robust features that are easier to transfer. Furthermore, under successful transfer, it achieves 5.2% more accuracy against white-box PGD attacks than suitable baselines. Overall, our empirical evaluations give insights on how well adversarial robustness under transfer learning can generalise.
Analysis of Knowledge Innovation Capability of High-tech Service Enterprises Based on the Perspective of Book Knowledge Spillover

Innovation plays an important role in economic growth, and book knowledge plays a pivotal role in technological progress and innovation. With the arrival of the book knowledge economy, the eyes of scholars not only stay in the technological progress in the region. People gradually realize the importance of book knowledge in promoting innovation and national development, and innovation has gradually shifted from the traditional way to the innovative way of creating and flowing book knowledge. Compared with the traditional service industry, high-tech service enterprises emphasize the characteristics of book knowledge and technology intensiveness. It is a human resource-intensive industry and highlights the important role of innovation. Based on the perspective of book knowledge spillover, this study selects two indicators of innovation ability output type and input type index for the analysis index of high-tech service enterprise innovation ability. And the five secondary indicators and 17 third-level indicators under the first-level indicators evaluate the innovation ability of high-tech service industry from the perspective of book knowledge spillover. Based on the perspective of book knowledge spillover, this study selects three levels of indicators to evaluate the knowledge innovation ability of high-tech service enterprises to the knowledge innovation ability of high-tech service industry.
THE MODERATING ROLE OF JOB SATISFACTION ON THE RELATIONSHIP BETWEEN HUMAN RESOURCE MANAGEMENT PRACTICES AND EMPLOYEE PERFORMANCEAMONG TELECOMMUNICATION EMPLOYEES

This study was aimed at identifying the relationship between human resource practices and employee performance among employees in Yemeni Telecommunication Public companies. It also aimed to examine the moderating role of job satisfaction on the relationship between human resource practices such as (work environment, reward, fairness and job performance). The study population included employees from Public Telecommunication Corporation (PTC) located in Sana'a, Yemen. The researcher used Raosoft to determine the required sample. The sample size refers to the total number of employees in PTC, where the numbers of employees in Sana’a branch are 800 employees. The sample size is 260, which was randomly selected. The questionnaires were distributed to 365 employees, from which 262 were retrieved. The study reached the following results: There is a significant relationship between work environment and employees performance. There is a significant relationship between reward and employees' performance. There is a significant relationship between fairness and employees' performance. Job satisfaction has a significant impact on the relationship between work environment and fairness and employees' performance. However, it does not have the effect on the relationship between reward and employees' performance. Based on the research findings, some practical and theoretical implications were discussed.
Fast transcription of speech in low-resource languages

We present software that, in only a few hours, transcribes forty hours of recorded speech in a surprise language, using only a few tens of megabytes of noisy text in that language, and a zero-resource grapheme to phoneme (G2P) table. A pretrained acoustic model maps acoustic features to phonemes; a reversed G2P maps these to graphemes; then a language model maps these to a most-likely grapheme sequence, i.e., a transcription. This software has worked successfully with corpora in Arabic, Assam, Kinyarwanda, Russian, Sinhalese, Swahili, Tagalog, and Tamil.
Quality Cluster Generation Using Random Projections

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Reservoir-Size Dependent Learning in Analogue Neural Networks

The implementation of artificial neural networks in hardware substrates is a major interdisciplinary enterprise. Well suited candidates for physical implementations must combine nonlinear neurons with dedicated and efficient hardware solutions for both connectivity and training. Reservoir computing addresses the problems related with the network connectivity and training in an elegant and efficient way. However, important questions regarding impact of reservoir size and learning routines on the convergence-speed during learning remain unaddressed. Here, we study in detail the learning process of a recently demonstrated photonic neural network based on a reservoir. We use a greedy algorithm to train our neural network for the task of chaotic signals prediction and analyze the learning-error landscape. Our results unveil fundamental properties of the system’s optimization hyperspace. Particularly, we determine the convergence speed of learning as a function of reservoir size and find exceptional, close to linear scaling. This linear dependence, together with our parallel diffractive coupling, represent optimal scaling conditions for our photonic neural network scheme.
Implementation of Collaborative Filtering for Product Recommendation in E-Commerce to Enhance Scalability and Performance

With the advancement of technology and the Internet facilities, e-commerce business is growing very fast. E-commerce is trending across geographical boundaries. A user can place order sitting at home, and the product is delivered to the given address within the specified time period. At the same time, user is given a variety of options to choose from, thus making e-commerce a much convenient way of shopping. E-commerce applications nowadays have millions of users worldwide and billions of products to offer. Thus, it becomes difficult for a user to find a product of their choice from millions of available choices. Recommendation plays an important role in e-commerce applications. A recent study on the concerned topic has advocated for a recommendation system which can be a potential solution to the mentioned problem. This system uses various parameters such as users’ purchase history, products in the cart, users’ ratings and review to recommend an item to the target user. A good recommendation system is one which helps the user to find the appropriate product and also helps the organization to grow vertically as well as horizontally. Further, collaborative filtering is an algorithm which may be applied to product recommendation which successfully satisfies customer’s needs and at the same time also helps in organization’s growth. One of the biggest challenges these days is to provide efficiency and scalability while handling a large number of users and products. The research work studies and discusses different approaches of implementation of collaborative filtering for product recommendation system. The study also shows how to overcome the drawbacks of user-based collaborative filtering by implementing item-based collaborative filtering. This research work also demonstrates how collaborative filtering can be implemented for big data using Hadoop, to overcome scalability problem and enhance performance.
The Role of Investment in Reducing Dependence on Borrowing an Exploratory Study of the Views of a Sample of Academics

It is clear that investment is an important and effective means in the economies of many countries, especially limited resources, because it is a tool to help support and revitalize the economy and achieve social welfare by reducing the unemployment rates and the development of levels of production through the introduction of modern technologies and improve the quality of the product. Better than the public loans that weigh heavily on the state by committing to repayment of the principal of the loan and its benefits as well as the risks that may accompany that, which require the intervention of donors in the formulation of the financial and economic policy of the state by reducing public expenditure The study seeks to achieve a set of objectives, the most important of which is to clarify the nature of investment and the benefits of its importation and its great role in achieving economic and social development as it is the best alternative to borrowing. , As well as to define the concept of borrowing and associated risks and its negative effects on the national economy in the foreseeable and long term.
DESIGN AND ANALYSIS OF SELF STABILIZED PLATFORM

Nowadays, stabilization is the most important this paper presents a development self-stabilized platform. Self-stabilizing platform mechanism is specially design for establishing communication without any kind of distraction. The purpose of the mechanism is to stay in stable position even the vehicle on which it is mount upon is in constant state of motion. The self-stabilizing platform has a very unique application which make it compatible for both space and ground station. This type of platform is used in military application, hospital stretcher, hand held camera, SOTM etc. In this project a mechanism is to be prepared that continues to maintain its communication with any of its transmitter (satellite). Self-stabilized mechanism working principle is same as gimbal mechanism which is stabilized platform on individual axis rotation.
KEEFEKTIFAN MODEL PEMBELAJARAN CONTEKTUAL TEACHING AND LEARNING UNTUK MENINGKATKAN HASIL BELAJAR IPS SISWA KELAS III SD NEGERI 30 MANDAU

This research is motivated by the low student social studies learning outcomes. this research was carried out at 30 Mandau Public Elementary School. The purpose of this study was to improve the learning outcomes of class III students at SD Negeri 30 Mandau. This study uses classroom action research. The study was conducted in 2 cycles, each through the stages of planning, implementation, observation, and reflection. The results showed that, in the initial data of students who were completed by 11 (45.8%) people while those who did not complete 13 (54.2%) people with incomplete categories. In the second cycle, students who completed completed increased to 18 (75%) while those who did not complete were 6 (25%) with complete categories. In the second cycle, the total number of students completed was 21 (87.5%) while the incomplete students were 3 (12.5%) people in the category of institutions. Based on these results it can be concluded that by applying the contextual teaching and learning (CTL) learning model can improve social studies learning outcomes of class III students of 30 Mandau Public Elementary School.
Quantum Multiplexing

Quantum communication, our ability to transmission quantum information between remote locations, is a primitive operation necessary for any future quantum internet. At its heart quantum communication relies on establishing entangled links between remote locations which can then be used to teleport quantum data. The ultimate performance of such approaches is limited by photon losses in the optical fiber channels. We introduce the concept of quantum multiplexing, which allows us to both minimize the number of photons needed in the entanglement distribution processing while at the same time enhancing the quality of the entangled pairs generated. Our approach should improve the performance of quantum communication systems and repeater networks. © 2019 The Author(s)
Information processing by coordinated neuronal ensembles in the primary auditory cortex

Author(s): See, Jermyn | Advisor(s): Schreiner, Christoph; Sohal, Vikaas | Abstract: The primary auditory cortex (AI) is made up of highly interconnected populations of neurons that are responsible for integrating bottom-up auditory information from the lemniscal auditory pathway and top-down inputs from higher-order cortical areas. Despite that, most studies of information processing in AI focus on either single-unit spectro-temporal receptive field (STRF) estimation, or paired neuronal correlation analyses, and assume that AI neurons filter auditory information either as individual entities or pairs. Meanwhile, some recent studies have also shown how populations of AI neurons can also encode auditory behavior. Determining how AI encodes information will hence require an integrated approach that combines receptive field and multi-neuronal ensemble analyses. In this dissertation, I show that I can accurately detect coordinated neuronal ensembles (cNEs), which we define as groups of neurons that have reliable synchronous activity, in AI. These cNEs are meaningful constructs that are active in both spontaneous and evoked activity, and their synchronous evoked activity cannot be trivially explained by receptive field overlap. cNEs also come in two flavors – one of them enhances stimulus representation over single neurons or simultaneously recorded random groups of neurons of the same size, while the other does not represent spectro-temporal features at all, and might reflect internally generated neuronal activity. Since single neurons can participate in multiple cNEs over the course of a recording, I also show that neurons can multiplex information, and encode slightly different spectro-temporal information, if they encode spectro-temporal information at all, when associated with different cNEs. Meanwhile, the enhancement of information processing and the reliability of representation of the stimulus by cNEs suggest that cNEs should be considered the principal unit of information processing in AI.
Peer Review Jurnal dengan judul Enhancing students' learning motivation through bibliocounseling technique

The present study aimed at enhancing students' learning motivation using bibliocounseling technique. This was a pre-experimental study with one group pretest-posttest design. The subjects of the study were 11th grade students of a Senior High School. They were selected through purposive random sampling. The instrument of the study consisted of learning motivation scale and observation guide. The data of the study were analyzed by descriptive analysis and Wilcoxon test. The result of the study showed that there was a difference between the score of pre-test and post-test, there was a 37% increase from the category of intermediate into high. While, the result of statistical analysis on the Wilcoxon test exhibited the significance value of 0.011 < 0.05, in other words, there is differences between pre- and post- treatment, therefore, the proposed hypothesis was accepted. The result of the study showed that the subjects experienced learning motivation improvement because he/she implemented bibliocounseling. Therefore, it could be concluded that bibliocounseling technique is effective to improve students’ learning motivation.
Microworld_57. Unsolved Problems of Physics_ 17 Xxvii. Hydrogen Superfluidity

Internet reports that the Harvard University physicists derived metal hydrogen having superconducting properties. Below it is shown that they, in fact, experimentally discovered the existence of superfluid hydrogen rather than superconducting one.
Perancangan Aplikasi Perbaikan Reduksi Salt Dan Pepper Noise Pada Citra Menggunakan Metode Discrete Wavelet Transform

Digital imagery may experience degradation or disruption. The noise in the digital image is called noise. A low-quality image caused by noise requires corrective measures to improve image quality without compromising more image detail quality. One of image improvement technique is image filtering method. The method that will be used in this final project to improve the image containing noise is Wavelet Transformation. The method will be applied to an image containing impulse noise (salt & pepper). Wavelet transformation is a development of noise detection algorithm based on simple concept that if pixel belongs to uniform region, then it is near its color with neighboring pixel, hence uncorrected, if nothing close to neighboring pixel, then noise is detected then pixel value is replaced with value of the window being evaluated
Risk-Based Authentication using Autoencoders

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.