Reviewerly/exHarmony huggingface dataset:
Design and prototyping of dual axis solar tracking system for performance enhancement of solar photo-voltaic power plant

Increase in the world energy demand has made renewable energy source as one of the best option. It is finding wide utility in comparison with the other sources of energy. Solar energy is one of the major source of renewable energy. The abundance of solar energy in India makes it highly desirable to exploit but due to the limitations of technology, only a fraction of the energy can be extracted and used. This paper describes a concept for solar detection sensor implementation in Photo-Voltaic (PV) dual-axis solar tracking systems. The system uses only three units of identical light-detecting- resistors (LDR) arranged on the three sides of tetrahedron geometry and is able to track the light source position at the strongest intensity of visible light. On the basis of comparative study of outputs of all the three LDRs, the panel will tilt so as to get maximum output from the system. This system results in a wide field of view with minimum error and also has advantages in terms of sensor quantity, size of the system, accuracy and effectiveness.
Analyzing of Quantum Entanglement with Concurrence in the Deep Lamb-Dicke Regime

The entangled states of three-level of trapped ion and two phonons (into coherent state) in Lambda configuration forming a Hilbert space of 12-dimensional (D) are analyzed. The concurrence is considered "such as a quantum measure" in trapped ion-coherent state system. Four values of Lamb-Dicke parameter (LDP), eta=0.005, 0.07, 0.08$ and $0.09 are investigated by the worths of concurrence. We demonstrate that as eta is increased, sudden birth of entangled states in the system is increased. Thus, establishing of entangled states can be tuned by LDP.
PENERAPAN STRATEGI PEMBELAJARAN TASK BASED LANGUAGE LEARNING DALAM MENINGKATKAN KETERAMPILAN MENULIS TEKS DESKRIPTIF BAHASA PERANCIS

Today there are so many learning strategies to support teaching and learning activities. One of the learning strategies that can be applied in writing skills is Task Based Language Learning. This research aims to measure the level of student mastery of descriptive text writing skills before and after the use of Task Based Language Learning strategies; measure the effectiveness of the implementation of Task Based Language Learning, and; obtain information about the implementation of Task Based Language Learning. The method used in this research was a pre-experimental. Meanwhile, the research design was one group pre-test and post-test design. The research findings explained that the use of Task Based Language Learning can improve students’s descriptive text writing skills. This is proven by an increase in the average value obtained by students. The average score in the pre-test was 60.8 while the post-test average score increased by 74.88. Then based on the overall questionnaire data analysis, the application of this learning strategy contributed positively to the learning of descriptive French writing skills.
A Bi-Level Probabilistic Path Planning Algorithm for Multiple Robots with Motion Uncertainty

For improving the system efficiency when there are motion uncertainties among robots in the warehouse environment, this paper proposes a bi-level probabilistic path planning algorithm. In the proposed algorithm, the map is partitioned into multiple interconnected districts and the architecture of proposed algorithm is composed of topology level and route level generating from above map: in the topology level, the order of passing districts is planned combined with the district crowdedness to achieve the district equilibrium and reduce the influence of robots under motion uncertainty. And in the route level, a MDP method combined with probability of motion uncertainty is proposed to plan path for all robots in each district separately. At the same time, the number of steps for each planning is dependent on the probability to decrease the number of planning. The conflict avoidance is proved, and optimization is discussed for the proposed algorithm. Simulation results show that the proposed algorithm achieves improved system efficiency and also has acceptable real-time performance.
Quickest Multiple User Active Authentication

In this chapter, we investigate how to detect intruders with low latency for Active Authentication (AA) systems with multiple-users. We extend The Quickest Change Detection (QCD) framework is extended to the multiple-user case and the Multiple-user Quickest Intruder Detection (MQID) algorithm is formulated. Furthermore, the algorithm is extended to the data-efficient scenario where intruder detection is carried out with fewer observation samples. The effectiveness of the method is evaluated on two publicly available AA datasets on the face modality.
Blockchain based Architecture for Digital-right Management in Scientific Data Sharing

Abstract The data integration and copyright protection are the essential requirements in promoting the scientific data sharing. We present a blockchain-based architecture for digital-right management in scientific data sharing. The main innovations are the multiple parallel sub-chains based block structure, and the on-chain/off-chain hybrid storage. This leads to an efficient and scalable data management platform for the large-scale scientific data and still maintains the tamper-proof and traceability features of blockchain. The qualitative analysis shows that the parallel sub-chain based architecture can improve the throughput and scalability of the original Hyperledger Fabric chain by up to 10 x.
PODCAST USAGE: EXPANDING ENGLISH LEARNING OF UNDERGRADUATE STUDENT AT UNIVERSITAS AHMAD DAHLAN

Podcast is an audio or video program which can be downloaded via the Internet to your mobile phone or computer in the form of an audio or video material. It is an interesting media that some people use to provide and share information. The use of podcast is another enjoyable way to expand the learning of English, as well as the use of movies or music as a mother tongue. This allows both students and teachers to develop their quality of learning. The style can also be more interesting and fun, as students and teachers can explore new ways of learning. This study aims to analyze the benefit of using podcast to enhance English skill for the undergraduate students at Universitas Ahmad Dahlan. The method used in this research is a qualitative approach. The objects of this research are the undergraduate students of Universitas Ahmad Dahlan who have been using a podcast in their daily life. The instruments used in this research are direct observations and semi-structured interview. The process of data analysis is started by collecting data from direct observation and semi-structured interviews. Then, the results of data analysis are integrated into the form of descriptive. The results showed that Podcast's benefits are that it can be downloaded and heard any time and wherever they want. It can be a media to get entertained besides enhancing English skills. Moreover, podcast can develop listening, speaking, pronunciation, as well as vocabulary.
Equivalence classes of coherent projectors in a Hilbert space with prime dimension: <i>Q</i> functions and their Gini index

Coherent subspaces spanned by a finite number of coherent states are introduced, in a quantum system with Hilbert space that has odd prime dimension $d$. The set of all coherent subspaces is partitioned into equivalence classes, with $d^2$ subspaces in each class.The corresponding coherent projectors within an equivalence class, have the `closure under displacements property' and also resolve the identity. Different equivalence classes provide different granularisation of the Hilbert space, and they form a partial order `coarser' (and `finer'). In the case of a two-dimensional coherent subspace spanned by two coherent states, the corresponding projector (of rank $2$) is different than the sum of the two projectors to the subspaces related to each of the two coherent states. We quantify this with `non-addditivity operators' which are a measure of quantum interference in phase space, and also of the non-commutativity of the projectors. Generalized $Q$ and $P$ functions of density matrices, which are based on coherent projectors in a given equivalence class, are introduced. Analogues of the Lorenz values and the Gini index (which are popular quantities in Mathematical Economics) are used here to quantify the inequality in the distribution of the $Q$ function of a quantum state, within the granular structure of the Hilbert space....
Sustainable Development of University as a Prerequisite of Region’s and Country’s Prosperity

The article by the rector of the Kazan Innovation University named after V.G. Timiryasov (KIU) shows the development path of one of the strongest non-governmental universities in the Volga region, recognized as a university that makes a great contribution to the development of the region and the country. This academic year, KIU celebrated its 25th anniversary. The demand for a university among the population is evidenced by the fact that, according to the ranking of the demand for universities in the Russian Federation, published by the Social Navigator project of MIA Russia Today, the university takes the 15th place in the group “Universities of management area” (Economics, Finance, Law). The share of graduates of KGU named after V.G. Timiryasov who received a job placement is 88,9%. The share of funds from the commercialization of intellectual products is 10,9%. Also, the ranking shows a high citation index of the works of faculty. The development of the university is comparable to the development of the largest universities in the world, which, by training personnel in popular specialties, provide the future for the country.
Conditioning and Dilation with Coherent Nearly-Linear Models

In previous work [1] we introduced Nearly-Linear (NL) models, a class of neighbourhood models obtaining upper/lower probabilities by means of a linear affine transformation (with barriers) of a given probability. NL models are partitioned into more subfamilies, some of which are coherent. One, that of the Vertical Barrier Models (VBM), includes known models, such as the Pari-Mutuel, the $$\varepsilon $$ -contamination or the Total Variation model as special instances. In this paper we study conditioning of coherent NL models, obtaining formulae for their natural extension. We show that VBMs are stable after conditioning, i.e. return a conditional model that is still a VBM, and that this is true also for the special instances mentioned above but not in general for NL models. We then analyse dilation for coherent NL models, a phenomenon that makes our ex-post opinion on an event A, after conditioning it on any event in a partition of hypotheses, vaguer than our ex-ante opinion on A.
Improvements in the Utterance Database for Enhancing System Utterances in Chat-oriented Dialogue Systems

In our commercial chat-oriented dialogue system, we have been using an utterance database created from a massive amount of predicate-argument structures extracted from the web for generating utterances. However, because the creation of this database involves several automated processes, the database often includes non-sentences (ungrammatical or uninterpretable sentences) and utterances with inappropriate topic information (called off-focus utterances). Additionally, utterances tend to be monotonous and uninformative because they are created from single predicate-argument structures. To resolve these problems, we propose methods for filtering non-sentences by using neural network-based methods and utterances inappropriate for their associated foci by using co-occurrence statistics. To reduce monotony, we also propose a method for concatenating automatically generated utterances so that the utterances can be longer and richer in content. Experimental results indicate that the non-sentence filter can successfully remove non-sentences with an accuracy of 95% and that our focus filter can filter utterances inappropriate for their foci with high recall. We also examine the effectiveness of our filtering methods and concatenation method through an experiment involving human participants. The experimental results indicate that our methods significantly outperform a baseline in terms of understandability and that the concatenation of two utterances leads to higher familiarity and content richness while retaining understandability.
Inductive Bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters

The problem of scheduling of workloads onto heterogeneous processors (e.g., CPUs, GPUs, FPGAs) is of fundamental importance in modern data centers. Current system schedulers rely on application/system-specific heuristics that have to be built on a case-by-case basis. Recent work has demonstrated ML techniques for automating the heuristic search by using black-box approaches which require significant training data and time, which make them challenging to use in practice. This paper presents Symphony, a scheduling framework that addresses the challenge in two ways: (i) a domain-driven Bayesian reinforcement learning (RL) model for scheduling, which inherently models the resource dependencies identified from the system architecture; and (ii) a sampling-based technique to compute the gradients of a Bayesian model without performing full probabilistic inference. Together, these techniques reduce both the amount of training data and the time required to produce scheduling policies that significantly outperform black-box approaches by up to 2.2x.
Task approach to robotics training using the TRIK Studio environment in school informatics course

The purpose of the article is to analyze, generalize the experience and describe ways to include robotics issues in the school course of computer science. Analyzing the existing copyrighted educational and methodological sets on computer science, it is proposed to use the task approach for parallel study of algorithmic issues and the basics of robotics using the educational constructor and the TRIK Studio environment. An example of using the system of I. G. Semakin’s tasks and the implementation of their solutions in the environment of TRIK Studio is presented. The article considers the advantages of using the TRIK Studio environment, suggests methods of studying robotics and algorithmization issues in the conditions of various availability of educational robotic designers.
A recurrent construction of irreducible polynomials of fixed degree over finite fields

Abstract In this paper we consider in detail the composition of an irreducible polynomial with $$X^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>X</mml:mi> <mml:mn>2</mml:mn> </mml:msup> </mml:math> and suggest a recurrent construction of irreducible polynomials of fixed degree over finite fields of odd characteristics. More precisely, given an irreducible polynomial of degree n and order $$2^rt$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msup> <mml:mn>2</mml:mn> <mml:mi>r</mml:mi> </mml:msup> <mml:mi>t</mml:mi> </mml:mrow> </mml:math> with t odd, the construction produces $$ord_t(2)$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>o</mml:mi> <mml:mi>r</mml:mi> <mml:msub> <mml:mi>d</mml:mi> <mml:mi>t</mml:mi> </mml:msub> <mml:mrow> <mml:mo>(</mml:mo> <mml:mn>2</mml:mn> <mml:mo>)</mml:mo> </mml:mrow> </mml:mrow> </mml:math> irreducible polynomials of degree n and order t . The construction can be used for example to search irreducible polynomials with specific requirements on its coefficients.
A Study on Measuring the Relationship Between the Library and Quality of Life of Local Residents

Abstract In this study, we explore a strategy to strengthen the library’s role of enhancing the quality of life for residents by identifying relationships between user satisfaction with library services and their quality of life. Questionnaires were distributed to public library users and normal distribution (skewness and kurtosis) and reliability of the measurement tools were validated. The results of this study show that satisfaction with the library staff has a positive influence on the participants’ living satisfaction, self-efficacy, and emotional stability. Second, an evaluation of their satisfaction with the library overall showed a significantly positive influence on their living satisfaction as well positive thinking. In conclusion, investment in libraries leads the public to be satisfied with their overall life, think of their future positively, have confidence to perform their roles successfully, and gain a sense of freedom with continuing stability.
A Blockchain Approach to Social Responsibility

As blockchain technology matures, more sophisticated solutions arise regarding complex problems. Blockchain continues to spread towards various niches such as government, IoT, energy, and environmental industries. One often overlooked opportunity for blockchain is the social responsibility sector. Presented in this paper is a permissioned blockchain model that enables enterprises to come together and cooperate to optimize their environmental and societal impacts. This is made possible through a private or permissioned blockchain. Permissioned blockchains are blockchain networks where all the participants are known and trust relationships among them can be fostered more smoothly. An example of what a permissioned blockchain would look like is described in this paper as well as its implementation, achieved using Hyperledger Fabric, which is a business-oriented blockchain framework. This study touches on the benefits available for companies that are willing to engage in socially responsible causes through blockchain. It states in what ways a permissioned blockchain can bring together businesses on common ground to increase their reach and provide better customer service. Finally, a use case is provided to bring to life a real-world situation where blockchain use improves service quality for all the parties involved, both the companies and their customers.
Research on Radar Signal Recognition Technology Based on Deep Learning

Focusing on the current problem of sorting and recognition of radar signals, the application of the time- frequency analysis method to signal recognition was studied. Compared with other radar signal recognition methods, this method can effectively analyze non-stationary signals, and at the same time offer image processing and deep learning. Through comparison of simulation experiments, this method was found to effectively identify the radar signal recognition target. Through experiments, PWVD is an ideal time- frequency analysis method, and through image preprocessing and deep learning, it can finally achieve a high recognition accuracy rate.
NO IDLE SCHEDULING WITH FUZZY APPROACH

In this paper, we show that the power function of sub E-function f n (x) is sub E-function.Furthermore, we establish some new integral inequalities of Hadamard type involving sub E-functions and concave E-functions.
Analysis of Environmental Vulnerability Using Satellite Imagery and Geographic Information System in Coal Mining Area Planning at Banjar Regency

Abstract It has been done research of environmental vulnerability degradation in coal mining area planning using satellite imagery and Geographic Information System. Vulnerability of environmental degradation is the condition of areas that has potential to damage the environment because of human activities or activity that has potential to cause environmental impacts. Monitoring of environmental degradation can be done to determine the ecological vulnerabilities so as to predict and overcome the future events. The development of remote sensing technology and geographic information systems can facilitate the spatial analysis especially environmental degradation. This research was done to map the vulnerability of environmental degradation in coal mining area planning in Banjar regency and classify environmental damage in the area. The analysis based on scoring and weighting of each index resulting ecological vulnerability index (EVI). The results of the overlay and weighting using weighted summation model’s method in coal mining area planning was plotted into four types of zone, i.e., appropriate exploitation zone, optimized exploitation zone, needs to monitoring exploitation zone, and recommended not to be exploitation zone. Thus, the classification of environmental damage in the coal mining area planning of which are moderate to severe erosion, surface runoff in the watershed, moderate salinity resulting in soil degradation, vegetation does not grow well and loss of recharge area.
INVESTIGATING ARABIC CORPUS (KorSA) OF INDONESIAN UNDERGRADUATE THESIS ABSTRACTS

Purpose: This study was designed to unveil Arabic corpus written in the Indonesian undergraduate thesis abstracts.&#x0D; Methodology: Experimental and descriptive approaches were employed to elicit data which were in the forms of isim (noun), fi’il (verb), concordances, and idioms collected from 59 thesis abstracts written by undergraduate students of Universitas Negeri Malang UIN Maulana Malik Ibrahim Malang, both are state-owned universities based in East Java, Indonesia.&#x0D; Principal Findings: The results of this study informed that two steps were carried out to craft an Arabic corpus for undergraduate theses, such as enacting need analysis and designing the model of Arabic corpus. Furthermore, this study also uncovered that the main page of the corpus website was concordances and word frequency.&#x0D; Implications/Applications: If in the context of translating the Qur'an into English only, for example, there is not yet a parallel corpus model of the Qur'an. Furthermore, similar models in other languages, such as the Indonesian context are possible.&#x0D; Novelty/Originality of this study: This research is the first step towards the formation of the first model of the parallel Qur'an corpus and its translation in the Indonesian language. Besides, this model can later be used as a reference for the preparation of other identical corpus models in the context of bilingual bodies or more for the benefit of translation research.
Mobile Games for Negotiated-Play and Decision-Making in Health Literacy

The purpose of this qualitative case study study is to examine the ways in which mobile videogames can be used in non-formal educational environments, to support students to develop decision-making skills through negotiated play. In the context of this study, the health literacy mobile videogame, PlayForward: Elm City Stories developed at Yale University was implemented in an afterschool setting in southern Europe. In this study we explored how secondary school students negotiate meaning, make decisions, and interpret the consequences in a non-formal education context, through an interpretive symbolic-interactive framework. The data included individual interviews with students, field-notes, and video-based student-groups’ interactions. These were analyzed with the use of open coding techniques. The analysis of the data resulted in the following three assertions: (a) The technical affordances of the game such as sound, usability, rating system, and visuals, are vital features that defined the quality of play and learning experience; (b) The narrative of the game guided the learning game-play experience of the students; and, (c) Students perceived that their engagement in the game facilitated their collaboration and decision-making. These are discussed alongside recommendations for game design for supporting negotiated play and decision-making.