Reviewerly/exHarmony huggingface dataset:
Search Data Structure Learning

In our modern world, an enormous amount of data surrounds us, and we are rarely interested in more than a handful of data points at once. It is like searching for needles in a haystack, and in many cases, there is no better algorithm than a random search, which might not be viable. Previously proposed algorithms for efficient database access are made for particular applications such as finding the min/max, finding all points within a range or finding the k-nearest neighbours. Consequently, there is a lack of versatility concerning what we can search when it comes to a gigantic database. In this work, we propose Search Data Structure Learning (SDSL), a generalization of the standard Search Data Structure (SDS) in which the machine has to learn how to search in the database. To evaluate approaches in this field, we propose a novel metric called Sequential Search Work Ratio (SSWR), a natural way of measuring a search's efficiency and quality. Finally, we inaugurate the field with the Efficient Learnable Binary Access (ELBA), a family of models for Search Data Structure Learning. It requires a means to train two parametric functions and a search data structure for binary codes. For the training, we developed a novel loss function, the F-beta Loss. For the SDS, we describe the Multi-Bernoulli Search (MBS), a novel approach for probabilistic binary codes. Finally, we exhibit the F-beta Loss and the MBS synergy by experimentally showing that it is at least twice as better than using the alternative loss functions of MIHash and HashNet and twenty times better than with another SDS based on the Hamming radius.
The Architectonics of Musical Sound

At the turn of the 20th and 21st centuries there appeared a new trend in musical composition and musical pedagogy conditioned by the fast development of electronic musical instruments: from the simplest synthesizers to powerful musical computers. In the wide range contemporary electronic musical instrument the accumulated informational technologies in music and the art of music making have manifested themselves in the fullest and most perfect manner. The current and the subsequent issues of the journal shall provide a consecutive presentation of four lectures, compiling the basis of the discipline “Informational Technologies in Music” and a set of programs of advanced training, which include “Informational Technologies in Music,” “Informational Technologies in Musical Education,” “Computer Musical Composition,” etc. The first lecture, “The Architectonics of Musical Sound” shall disclose themes connected with the study of the physical characteristics of musical sounds, the means of their recording and reproduction; explanation is given to the aural perception of sound by the human being, and the basic principles of computer generation of musical sound are examined. The material elucidated in the lection possesses a theoretical and practical directedness and contains information in which the technological aspects of contemporary perceptions of music, about the musical instrument range (including computer musical instruments); without knowledge of these aspects a competent interpretation of musical instruments is impossible.
Aplikasi Sistem Pakar Untuk Diagnosa Penyakit Diabetes Melitus dengan Algoritma Certainty Factor Berbasis Web

Information technology is currently very rapidly developing. information technology can be used in all aspects, including for the world of health. currently an expert system application has been developed by researchers with a variety of methods. The expert system itself is a system that adopts the way of thinking of an expert into a computer system. expert systems for diagnosing a disease make it easy for people to consult about their health and illness without having to meet directly with an expert or doctor. the results of the expert system diagnosis can be used as a reference if you want to consult a doctor when conducting a health test. The method used in the system is certainty factor. Certainty factor is an algorithm used when facing a problem for which the answer is uncertain. This uncertainty can be a probability. Certainty Factor states confidence in an event (or facts or hypotheses) based on expert evidence or judgment. application of an expert system with this certainty factor method successfully diagnoses well according to the weight value given by the expert or doctor. This expert system will also be very useful for the community as an educational medium so that people are more aware of diabetes, the symptoms of diabetes and solutions that must be done from diabetes.
Growth Effects of Remittance: A Case of Turkey Diaspora

In the age of globalization, remittances are an essential part of human life. This analysis's key objective is to examine the effect of remittances in developing economies like Turkey on economic development. The 1980 to 2020 time-series data used in this analysis which use numerous time series estimating techniques. Sending data is given by the Banks of Turkey and in a million dollars. Simultaneously, economic development or GDP data are provided by world economic indicator, the World Bank, and the new US dollar. The findings indicated that there are both short-term and long-term ties between transactions and economic development in Turkey. Therefore, results indicate that Turkey's transition flows positively affect Turkey's person and Turkey's macroeconomic scenario. The government should implement policies that allow Turkey in overseas countries to submit transmissions through official channels.
Straight to the Gradient: Learning to Use Novel Tokens for Neural Text Generation

Advanced large-scale neural language models have led to significant success in many natural language generation tasks. However, the most commonly used training objective, Maximum Likelihood Estimation (MLE), has been shown to be problematic, where the trained model prefers using dull and repetitive phrases. In this work, we introduce ScaleGrad, a modification straight to the gradient of the loss function, to remedy the degeneration issues of the standard MLE objective. By directly maneuvering the gradient information, ScaleGrad makes the model learn to use novel tokens during training. Empirical results show the effectiveness of our method not only in open-ended generation, but also in directed generation. With the simplicity in architecture, our method can serve as a general training objective that is applicable to most of the neural text generation tasks.
PENGGUNAAN MEDIA EXPLOSION BOX TERHADAP KETERAMPILAN MEMBACA NYARING SD NEGERI 69 BANDA ACEH

Based on information obtained from the second grade teachers of SD Negeri 69 Banda Aceh, the reading skills of the loud students of class II are still low, because in the learning process in class students pay less attention to the teacher when explaining in front of the class in other words the use of methods does not vary so that it does not attract students' attention and the lack of use of media which results in students becoming bored with learning becoming ineffective. This makes students less motivated in learning activities which results in low reading skills. Observing the existence of these problems, it is necessary to use media as a learning facility that can improve students' reading skills aloud. One of the learning media that can be used to improve students' reading skills is the explosion box. Based on the above problems, the problem formulation in this study is whether there is an increase in the ability to read aloud through the explosion box media in class II students of SD Negeri 69 Banda Aceh. This study aims to determine the increase in reading skills through the media explosion box in class II students of SD Negeri 69 Banda Aceh. The population used in this research is class IIA and IIB elementary school, while the sample used is class IIA 69 elementary school Banda Aceh. This research is an experimental study, the experimental design used is true experimental designs with the form of pretest-posttest control design. Data collection methods in observation research and skills tests. From the data analysis it is known that the significance is 0,000. The significance value indicates 0,000 <0.05 so Ho is rejected. This is also supported by the mean value of the experimental class of 35.07 which is greater than the control class of 17.24. Based on the above analyst results it can be concluded that there is an increase in reading skills through the use of media explosion box.
Aspekty lingwistyczne [Kołysanki Madonny] części poematu w dialekcie kalabryjskim „Noc Bożonarodzeniowa” ks. Vincenza Padula (1819-1893)

The aim of this article is to present a language analysis of one of the most beautiful dialectal poem of Fr. V. Padula. The dialect used by Fr. V. Padula is to be called the Acrian dialect (spoken in the city of Acri, Cosenza Province), which belongs to the group of northern Calabrian dialects. The lullaby [Ninna-nanna di Madonna], sung by Holy Mary, is the second part of the poem La Notte di Natale. No one ever was capable as Fr. V. Padula, to carry the Acrian dialect a such high summits of lyricism and piety. The Acrian dialect served him to know and testify the Calabrian society and culture. [Ninna-nanna di Madonna] includes in itself some biblical references to the main truths of the faith of Christianity.
Marketing Strategy to Enhance New Book Reading

This paper tries to use marketing strategy to change school teacher and student’s stereotype perception of the library, so as to effectively improve new book loan, further cultivate good reading aura for the school, and build a more perfect reading environment for students.
Systemic Thought as a Necessity in Post Pandemic Age

In this editorial, the author reflects on the importance of systemic thinking in the post-pandemic age, in the midst of the general and normalized crisis and between the technical dichotomy of care, its relationship with nursing care, based on some theoretical references as Jared Diamond, Martin Heiddeger and Michel Foucault
Quantum simulation via randomized product formulas: Low gate complexity with accuracy guarantees

Quantum simulation has wide applications in quantum chemistry and physics. Recently, scientists have begun exploring the use of randomized methods for accelerating quantum simulation. Among them, a simple and powerful technique, called qDRIFT, is known to generate random product formulas for which the average quantum channel approximates the ideal evolution. This work provides a comprehensive analysis of a single realization of the random product formula produced by qDRIFT. The main results prove that a typical realization of the randomized product formula approximates the ideal unitary evolution up to a small diamond-norm error. The gate complexity is independent of the number of terms in the Hamiltonian, but it depends on the system size and the sum of the interaction strengths in the Hamiltonian. Remarkably, the same random evolution starting from an arbitrary, but fixed, input state yields a much shorter circuit suitable for that input state. If the observable is also fixed, the same random evolution provides an even shorter product formula. The proofs depend on concentration inequalities for vector and matrix martingales. Numerical experiments verify the theoretical predictions.
On the Concept of the Author’s Media Text Translation in the Era of Digitalization and Commercialization of Art

The report is devoted to the media text editorial methods in the aspect of author’s and traditional translation. The strategies used to recreate the original in a foreign language are considered, some topical problems of authorship in the era of digitalization and commercialization of art are analyzed.
Development of computationally eﬀicient biorthogonal wavelets

Daubechies 5-tap/3-tap (Daub 5/3) wavelet and Kale 5-tap/3-tap (Kale 5/3) wavelet are computationally efficient wavelets which can be implemented by bitwise shifts and additions in the lifting scheme. In this work, presented is a formulation for computationally efficient wavelet prediction (P) and update (U) filters of two-channel lifting structures. Their subband decomposition scheme counterparts are also given. This research bases itself on the Daub 5/3 and Kale 5/3 wavelets and develops a formula for wavelets (which can be implemented with bitwise shifts and additions) that are derived from these two wavelets. The proposed wavelets are tried on 16 test images for three-level wavelet decompositions and better decorrelation results are achieved for the proposed wavelets for higher-level decompositions.
PENGALAMAN PUSTAKAWAN DALAM MELAKUKAN ANALISIS KEBUTUHAN PENGGUNA LIBRARY EXPERIENCE IN DOING ANALYSIS OF USER NEEDS

Users in collection development activities are very important elements. There are two things that emphasize the user as a central part in collection development activities, the first stage in developing collection must begin with user analysis, secondly almost all stages in collection development require library staff to always see who the user community is. Therefore the research aims to raise the library experience in analyzing user needs. The location of the study was conducted at the library center of IAIN Syeh Nurjati Cirebon. This study uses a quantitative approach to the type of phenomenological research. Data collection techniques are carried out through interviews, observations, and through library studies. As for the data analysis, it is carried out through three stages, namely data reduction, data presentation and data verification. Based on the results of the study note that in the view of librarians of the IAIN library center Syeh Nurjati the user aspect is an element that must be the center of attention in the development of collections, because the purpose of providing collections in the library is to meet user needs. While relating to the experience of librarians in analyzing user needs, it is known that librarians conduct needs analysis both formally and informally. There are several aspects seen in the analysis of user needs, such as the characteristics of library users, curriculum and the implementation of the tri dharma of higher education at IAIN Syeh Nurjati.
Perancangan Program Aplikasi Sistem Informasi Akuntansi Laporan Keuangan Menggunakan Microsoft Access 2016 (Studi Kasus Pada CV Mitra Tani Farm - Bogor)

CV Mitra Tani Farm is a livestock company located in Bogor. The main activity of  CV Mitra Tani Farm is buying and selling livestock to customers for aqiqah and qurban. However, the accounting records at CV Mitra Tani Farm are still manual and semi-manual so that there are several problems in the financial reporting process, such as a lack of employee knowledge about accounting so that financial recording and reporting are still unstructured and there a delay in submitting financial reports to the company owners. With these problems, the authors provide solutions by designing an application of financial report accounting information systems. The author uses qualitative methods with a case study approach and development. The author also conducts data observations and interviews to collect the required data. The results of this research is the design of a financial report application using Microsoft Access 2016 with flowchart and DFD in designing the system. The output from this application is containing general journal reports, ledgers, trial balance, income statement, capital change, balance sheet, cash flows,  and sales report. This design is expected to solve the problems contained in financial reports accounting information system at CV Mitra Tani Farm.
Sign Language Recognition System Using Cnn

In this study, we have built an automatic sign language translation system for deaf and dumb persons to communicate with ordinary people. According to the Statistics Department of the Taiwan Ministry of Health and Welfare, there are 119,682 hearing impaired persons, and 14,831 voice function or language dysfunctions. The Deaf and dumb persons’ account for 11.7% of the population with physical and mental disabilities. However, there are only 488 qualified people with the sign language translation skill certificate, which shows the importance of automatic sign language translation systems. This system collects 11 signals including five fingers’ curvature, 3-axis gyroscope and 3-axis accelerometer from left and right hand separately. In addition, a total of 22 signals are collected by the two sensors, Flex sensor and GY-521 six-axis with single-board computer Arduino MEGA 2560; and then uploaded to server via ESP-01S Wi-Fi module. While server receives the 22 signals, it converts to a RGB picture using PHP program. As a result, we can compare the picture with the model trained by TensorFlow and the compared result is stored in the database. Meanwhile, the comparison stored in database which can be accessed by APP programs would be displayed on the screen of the mobile device and be read aloud. The TensorFlow training model collects 25 sign language gestures, each based on 100 training gesture pictures, and a sign language recognition training model is Convolutional Neural Network (CNN). In this study, the results of the sign language recognition training model are further confirmed by 10 people other than those in training database. So far, the indeed recognition rate of sign language is about 84.4%, and the system response time is about 2.243 seconds.
Creation of Temporal Model for Prioritized Transmission in Predictive Spatial-Monitoring Using Machine Learning

Predictive spatial-monitoring, which predicts spatial information such as road traffic, has attracted much attention in the context of smart cities. Machine learning enables predictive spatial-monitoring by using a large amount of aggregated sensor data. Since the capacity of mobile networks is strictly limited, serious transmission delays occur when loads of communication traffic are heavy. If some of the data used for predictive spatial-monitoring do not arrive on time, prediction accuracy degrades because the prediction has to be done using only the received data, which implies that data for prediction are ‘delay-sensitive’. A utility-based allocation technique has suggested modeling of temporal characteristics of such delay-sensitive data for prioritized transmission. However, no study has addressed temporal model for prioritized transmission in predictive spatial-monitoring. Therefore, this paper proposes a scheme that enables the creation of a temporal model for predictive spatial-monitoring. The scheme is roughly composed of two steps: the first involves creating training data from original time-series data and a machine learning model that can use the data, while the second step involves modeling a temporal model using feature selection in the learning model. Feature selection enables the estimation of the importance of data in terms of how much the data contribute to prediction accuracy from the machine learning model. This paper considers road-traffic prediction as a scenario and shows that the temporal models created with the proposed scheme can handle real spatial datasets. A numerical study demonstrated how our temporal model works effectively in prioritized transmission for predictive spatial-monitoring in terms of prediction accuracy.
WITH KNOWLEDGE TO BETTER FUTURE

Innovation in education technology, under the influence of the modern information and communication complex, has allowed the development, modernization and rationalization of education, thus creating completely new paradigms in the field of knowledge transfer. New technologies provide efficient, diversified and autonomous access to knowledge, and this significantly changes the organization of the teaching or educational process as a whole. In addition, the complexity and multidimensionality of modern communication transmits the educational process into a simulated environment. By the way, the condition in such a way of simulated - virtual reality is interaction. Contemporary educational processes require new studies, as well as teaching and upbringing through modern means of communication and modern expression, which become an integral part of a specific and autonomous field of knowledge process in pedagogical theory and practice. The use of information and communication technologies in education is the future, which all speaks in favor of Serbian enlightenment and how they want new knowledge and discussion about how the future of the future will look. And exactly in this virtual space, outside the classroom, and actually in the classroom, the biggest changes are taking place. Because of the enormous amount of information from modern media (TV, radio, computer networks), the teacher of the future becomes more and more difficult to teach young people why it is important to be able to read, write. Indeed, the media, TV, radio, and computers were created by people with literacy skills, not people from the media. In order to filter the enormous amount of information that students will encounter inside and outside the school, using multimedia computer networks, the teacher of the future must act as a measure, perspective of the provider. The simplest way to provide this perspective in the context of a curriculum is to learn from where information came from: History of technology, history of science, history of mathematics, history of language, art history, history of history (including the history of the "future"!). In other words, regardless of the subject to be taught, the teacher will in the future have to give the students a sense of evolution of the subject in order to provide a reason for thinking in the continuous flow of information, not in parts. " The School of the Future will be moved from classrooms to parks and museums, students will learn to meditate, and the main assistant teachers will be artificial intelligence. It is time for pedagogy to catch up with technology. Since recently, computer networks are paradise literacy, the textual state is rapidly passing, and computer network research quickly moves to multimedia This means that digital images (moving images, audio, graphics) will become the biggest influence on these networks.
Collision-Free Robot Coordination and Visualization Tools for Robust Cycle Time Optimization

Abstract This paper presents novel algorithms and visualization tools for avoiding collisions and minimizing cycle time in multi-robot stations by velocity tuning of robot motions. These tools have the potential to support product/manufacturing engineers in the practical task of adding synchronization instructions to robot programs to overcome the challenges in terms of product design, cycle time, quality control, and maintenance including re-usability of coordination schemes. We propose a range of techniques to achieve that, when additional requirements make the best coordination strategy hard to be chosen. Indeed, our main contributions are (i) considering and minimizing delays introduced by limitation in hardware synchronization mechanisms, (ii) highlighting insights on the relationship between a 3D working space and a path coordination space, and (iii) a computational tool for visualization of shared areas in both work space and path coordination space. Different strategies based on the developed algorithms are evaluated by successfully automatically solving industrial test cases from inspection measurement applications in the automotive industry. A study about how cycle time robustness is significantly influenced by variation in the robot motion execution times is also given.