Reviewerly/exHarmony huggingface dataset:
Real-time Karaoke Recommendations : Session-based Multi-Task Recommendations with Multivariate RNNs

There are more than 2,000 Karaoke stores in Japan and approximately 50 million users visit every year for a singing experience. For Karaoke, recommendations of the next songs play a significant role in leading customers to explore more songs and make the most of time in Karaoke. However, few recommendation functions are provided due to the difficulty and uniqueness of the Karaoke environment, in which unknown groups choose songs based on with whom they are sharing the Karaoke experience and the group mood; solid information of these factors is not available. In this paper, we propose a session-based multivariate recurrent neural network (RNN) to consider an occasion for a Karaoke store visit and any possible mood changes; these factors are assumed to be embedded in the sequential data. The model uses metadata from previously played songs, the conditions present, and performs several tasks that predict the songs and artists to be played at time t to t+n. It outperformed the item-kNN algorithm for prediction tasks (offline) of the next song by 127.94% regarding MAP@20 and the next artist by 142.8% regarding MAP@10. In addition, we analyzed the performance of the model for three types of groups, namely individuals, older groups, and younger groups that were manually categorized from played songs, and it outperformed the item-kNN algorithm by 89.59%, 483.11%, and 50.88% regarding MAP@20 respectively. The model also outperformed the baselines for all positions in a session, which demonstrates that it has the potential to quickly capture the preferences of a target group and to recognize mood changes from the sequence. We have launched a recommender system that is designed for Japanese Karaoke stores. The system has demonstrated that the model used in this system is also appliable to business applications due to its ability to handle vast numbers of requests in a reasonable time and enhance user experience by helping to choose more diverse songs faster.
Measuring the morpho-syntactic ambiguity using the edit distance functions

This paper presents the application of edit distance functions for the measuring of morphological ambiguity and similarity between the natural languages. We propose sequence and tree edit distance functions for the Universal dependencies framework, which compare both morphological and syntactical annotations of the words in the sentences. The experiments were performed with the Slovak as a reference language and set of Slavic languages for comparison.
PENGARUH PENGGUNAAN MODEL PEMBELAJARAN THINK PAIR SHARE TERHADAP KETERAMPILAN MENULIS SURAT PRIBADI SISWA KELAS VII SMP NEGERI 5 KOTA JAMBI

This research is intended to find out the effect of using think pair share learning model towards students’ writing ability at class VII SMP Negeri 5 Kota Jambi. The method used in this research is quasi experimental design by using the randomized posttest only control design. The sample is taken by using purposive sampling technique. The sample of this research is 72 students; 36 students of control class without think pair share learning model and 36 students of experimental class with think pair share learning model. The requirement test is done by using normality test and homogenity test. The normality test of the postest is done by using Liliefors test. The result of normality which is taken from the control test is L0 &lt; Lt (0,115 &lt; 0,147) while the result of normality test in experimental class is L0 &lt; Lt (0,135 &lt; 0,147) and homogenity test in which Fcount &lt; Ftable (1,054&lt;1,74). It means that in normal and homogenity test, so the hypothesis can be tested. The hypothesis test is done by using t-test formula. The result of the research shows that the value of tcount = 6,25 which is higher than ttable = 1,665. In the level of significancy α = 0,05 with dk is 70. The mean of posttest which is required from the experimental class is 88,61 and the mean of posttest which is required from the control class is 73,61. Thus, it can be concluded that the think pair share learning model has a significant effect towards students’ writing ability at class VIIA and VIIC SMP Negeri 5 Kota Jambi. Keywords: Think Pair Share Model, Writing, Personal Letter
Forensic Audit Practices to Reduce Financial Frauds

International markets are highly competitive these days due to the globalization of the industry. Companies might manipulate this competition to gain some advantages. Also, technology has been the main force behind business growth in the past decade. The widespread use of technology and globalization also increased financial crimes. Accordingly, the auditing profession has entered into the process of institutionalization and embedded itself within institutions due to the enhanced complexity of frauds, corruption, and manipulations. One of the developments that have been happened in the field of auditing is the emergence of the “forensic auditing” profession. This chapter discusses the conceptual framework of the forensic audit and its essential role in preventing frauds and corruption.
Investigation of Awareness for Evaluation Factors of Fire Response Capability to Apartment Residents

After radical development of city from 1970 to 1980 took place in Korea, most of cities experience deterioration of city’s infrastructure. Also, safety ignorance among Korean is another serious problem, which make citizen vulnerable to disaster particularly in dense urban areas. As most apartment houses are being worn out, safety problem caused deterioration of facility and equipment is being serious. In such a place, when unexpected disaster occurs, degree of damage is hard to predict because of characteristic of apartment house, and types of damage could happen in a variety of aspects. Disaster usually occurs when accumulated dangerous factors can be intolerable state from sudden shock, so responsive ability to various types of disaster is required through cooperation with community of apartment house to prevent accumulation of dangerous factors before disaster happens.
Division algebras and MRD codes from skew polynomials

Abstract Let $D$ be a division algebra, finite-dimensional over its center, and $R=D[t;\;\sigma,\delta ]$ a skew polynomial ring. Using skew polynomials $f\in R$ , we construct division algebras and maximum rank distance codes consisting of matrices with entries in a noncommutative division algebra or field. These include Jha Johnson semifields, and the classes of classical and twisted Gabidulin codes constructed by Sheekey.
An Indented Level-Based Tree Drawing Algorithm for Text Visualization

Level-based tree drawing is a common algorithm that produces intuitive and clear presentations of hierarchically structured information. However, new applications often introduces new aesthetic requirements that call for new tree drawing methods. In this paper, we propose an indented level-based tree drawing algorithm for visualizing parse trees of English language. This algorithm displays a tree with an aspect ratio that fits the aspect ratio of the newer computer displays, while presenting the words in a way that is easy to read. We discuss the design of the algorithm and its application in text visualization for linguistic analysis and language learning. An efficient and practical implementation of the algorithm is also presented.
Haze Visibility Enhancement of Image Using Dark Channel Prior

Images taken in hazy weather are often utterly degraded by scattering of atmospheric particles, which decreases the contrast, deviations the color. This makes the thing features difficult to spot by human vision and by some outdoor embedded systems used for image processing. Conventional methods are intended to perform in clear weather. In the end, embedded systems used for weather image processing need to provide mechanisms to allow them to play its role within the presence of haze. Therefore, image dehazing is a crucial issue and has been widely addressed within the field of computer vision. The role of image dehazing is to get rid of the influence of weather factors so as to enhance the visual effects of the image and supply benefit to subsequent image processing stages. In this study, we propose haze removal technique using dark channel prior. Proposed technique is found effective to remove haze from input images; its upheld key perception that, in one shading channel neighbouring pixel in haze free picture have low intensity. Utilizing proposed model, we will straightforwardly appraise the thickness of the haze and recuperate a top-notch fog free picture. Results on a spread of cloudy pictures show the impact of the proposed earlier.
To Solve the Coronavirus Crisis: Click Here

Abstract Human beings are technical beings. From the clothes we wear to the spaceships we fire into the sky, all these technologies are developed with the aim to protect ourselves, improve ourselves, and control the fickle world in which we live. Therefore, it should not come as a surprise that when hit with one of the biggest health crises of the last century, all over the world, governments have turned to technology to contain this life-threatening event. Most of these proposed—or already developed—technological solutions are data-driven. Just as the turn to technology to solve this crisis does not come as a surprise, neither does the protest it has caused. Critical citizens and civil rights organizations worry about the possibility of personal data being shared with private parties, about governments ending up using the collected information against citizens, and they fear an overall loss of privacy and freedom if these applications became widely used. Overall, they suspect that what is introduced as a temporary instrument to counter this crisis will have long-lasting effects on society.
Insegnare italiano L2 ad adulti migranti di livello pre A1. Un’indagine sul territorio lombardo

In this paper we present the results of a survey, conducted in the Italian region of Lombardy, on teaching Italian as a second language to adult migrants at Pre A1 level of competence, i.e. in the case of semi-literate learners. The first purpose of this research was to describe the characteristics of the teaching practices of Italian as a second language in Pre A1 level courses for migrants, collecting data through a questionnaire addressed to teachers in adult education centres in Lombardy. Then, a broader objective was to encourage the teachers’ metacognitive thinking, in order to enhance and disseminate existing good practices and promote methodological innovation, with particular attention to the role of grammatical reflection in the case of semi-literate learners. After showing the theoretical framework and the methodology of the research, we analyse the collected data, which allow to outline some implications for teaching practice and teacher training.
A version of the voting protocol based on blockchain technology

Abstract The paper describes a generalized version of the voting protocol based on blockchain technology. The analysis of the proposed protocol is also carried out. The proposed protocol is based on such cryptographic primitives as digital signatures, asymmetric ciphers, and zero knowledge proof protocol. Safety analysis was carried out using the AVISPA software package. Anonymity was analyzed separately as part of this protocol by analyzing differential privacy.
Efficient Neural Architecture Search for Long Short-Term Memory Networks

Automated machine learning (AutoML) is a technique which helps to determine the optimal or near-optimal model for a specific dataset and has been a focused research area during the last years. The automation of model design opens doors for non-machine learning experts to utilize machine learning models in several scenarios, which is both appealing for a wide range of researchers and for cloud services as well. Neural Architecture Search is a subfield of AutoML where the optimal artificial neural network model's architecture is generally searched with adaptive algorithms. This paper proposes a method to apply Efficient Neural Architecture Search (ENAS) to LSTM-like recurrent architecture, which uses a gating mechanism an inner memory. Using this method, the paper investigates if the handcrafted Long Short-Term Memory (LSTM) cell is an optimal or near-optimal solution of sequence modelling for a given dataset, or other, automatically defined recurrent structures outperform. The performance of vanilla LSTM, and advanced recurrent architectures designed by random search, and reinforcement learning-based ENAS are examined and compared. The proposed methods are evaluated in a text generation task on the Penn TreeBank dataset.
Analysis of the Main Trends and Directions of Automation in the Formation of the “Smart Archives” System

The article examines the current trend in the development of information technology in the Republic of Uzbekistan. Several approaches to the creation of an automation system and the intellectualization of the activities of organizations and enterprises are analyzed. On the example of the archival activities of the Republic, it is proposed to create and implement SMART technologies – “Smart Archive” covering the full range of automation of the issues of packaging, storage, digitization and use of archive documents. The system and subsystems Smart Archive, its functional diagram, main elements are proposed and the effectiveness of using such systems in modular application is analyzed. The rapid development of modern information and communication technologies and integrated automation systems in all areas of human activity, has served as a great impetus for the creation of innovative intellectualized, so-called “Smart systems” in many areas of the economy.
Practical Range Counting over Data Streams

In applications such as network monitoring and sensor measurements, massive amounts of data arrive as a high-rate stream and real-time analytic over the stream data is required. Maintaining a succinct sketch over the data stream has been a dominant approach to support analysis in those applications. Recent applications, however, demand more sophisticated types of analytics such as range-counting. Unfortunately, state-of-the-art sketches perform poorly when facing range-counting as none of them was designed to support range-counting at the outset. In this paper, we aim to fill the gap and present RC-Sketch, a sketch that supports range-counting over rapid data stream. Empirical results show that RC-Sketch outperforms the state-of-the-art in range-count accuracy with comparable throughput.
An Alternative Method for Evaluating the Risk of Cyberattack Over the Management of a Smart House with Intuitionistic Fuzzy Estimation

The development of digital technologies has led to their introduction into all scopes of life, including people’s homes. The need for effective management and control of a Smart House has also increased. With the remote-control capabilities that give the user extreme freedom, there is also the danger of hacking and taking control of the Smart House by people with malicious intents. This chapter is a follow-up to the Modelling of Smart Home Cyber System with Intuitionistic Fuzzy Estimation article, which focuses on cyber-threats in the so-called Smart House, which use fuzzy estimations for analysing possible ways and places to penetrate the security system and intervene in the functioning of the Smart House control systems.
Controllable phase-dependent Wigner-function negativity at steady state via parametric driving and feedback

Generating the negative Wigner functions where the corresponding Wigner states are nonclassical has been recognized as a powerful tool for successfully performing quantum information and computing protocols beyond the scope of classical computers. Here, we present the possibility to generate and engineer the negative Wigner function at a steady state using parametric (two-photon) driving and homodyne-based feedback in a quantum van der Pol (vdP) oscillator. Specifically, we employ a quantum master equation approach for calculating the Wigner function of the vdP oscillator field in phase space and, furthermore, quantifying its negativity content. We clearly show that the negative-value magnitudes, regions, and shapes of the Wigner function can be effectively tuned by the parametric driving phase and the parametric driving amplitude, as well as the feedback coefficient within a large range. We identify different contributions of these involved parameters to the Wigner-function negativity. In the present scheme, more complex quantum coherence and interference phenomena are introduced via the parametric driving and feedback, which stabilizes the phase of the vdP oscillator field and renders the capability to generate the negative Wigner function. Therefore, the enhanced Wigner-function negativity can be achieved under these optimized system parameters. Our in-depth study provides insight into the formation and in situ control of the desirable Wigner nonclassical states. The obtained results are not limited to the vdP oscillator systems and should be generally applicable to other coherent coupled systems within the reach of modern experimental facilities.
Productizing an Artificial Intelligence Solution for Intelligent Detail Extraction—Synergy of Symbolic and Sub-Symbolic Artificial Intelligence Techniques

Businesses are today moving from a data-driven focus for becoming ‘Insight-driven’ businesses. This paradigm shift hinges on the use of artificial intelligence technology. This shift needs accurate and smooth input of all pertinent details. This is facilitated by using artificial intelligence to provide intelligent detail extraction from documents and other sources. The techniques behind building an intelligent detail extraction product are discussed. The path from an initial solution through identifying and developing the characteristics that mark a product are described. A powerful synergy is created by appropriately using symbolic machine learning as well as deep learning techniques.
Introduction of Basic Core Concepts

A sound corpus of concepts, terms and definitions is needed to achieve relevant reliability assessments of safety and production systems. Some of the terms and concepts have been introduced a long time ago and have, little by little, drifted from their original definitions and this is a problem. The aim of this chapter is to identify the many specific concepts related to safety and dependability useful to reliability engineers and to explain, clarify and discuss them when needed. This encompasses the states (up/down, operating/non-operating, degraded, critical restoration), the failures and faults (definitions, classification, modes, common cause, critical), the maintenance (definitions, repair, restoration, repaired and non-repaired items) and the probabilistic concepts (random processes, reliability/availability, failure rate/intensity, maintainability). Acronyms (MUT/MDT, MTTF, MTTFF, MTBF) are analysed in detail specially these which, suffering from the biggest semantic drifts (MTTF and MTBF), have become meaningless. After a thorough analysis, more relevant acronyms (e.g. mean operating time to operating failures, MTTFO, and MTBF related to operating failures, MTBFO) and definitions are provided.
Analysis on Current Situation and Effect of Online Teaching Effect of Universities Based on Mobile Internet

Under the background of novel coronavirus pneumonia, all colleges and universities in China have carried out online teaching. In this special case, using case analysis method, this paper analyzed the situation and the effects of online teaching mode based on the data of a provincial university in southwest China, which is the study case. This paper puts forward some recommendations and prospects for the application of online teaching.
Computer technologies in the system of training specialists for the nuclear industry at ISPU

Abstract The article discusses the experience of effective application of computer technologies, trainers and simulators in the system of training specialists for the nuclear industry at ISPU. The necessity and relevance of using computer-based learning tools in the educational process is determined. The main stages of training specialists and the concept of multi-level training based on the wide use of computer technologies developed at ISPU are considered. The main advantages and features of using automated training systems, local computer simulators, functional analytical simulator, full-scale simulator, simulation tools, simulator of the basic principles of NPP operation, as well as packages of numerical and analytical methods of mathematical modeling in the educational process are shown. The directions for further improvement of the educational process at ISPU in order to increase the level of training of young personnel for the nuclear industry are shown.
Game-Based (Re)Habilitation via Movement Tracking

An international collaborative explorative pilot study is detailed between hospitals in Denmark and Sweden involving rehabilitation medical staff and children where the affordable, popular and commercially available Sony PlayStation 2 EyeToy® is used to investigate our goal in enquiring to the potentials of games utilizing mirrored user embodiment in therapy. Results highlight the positive aspects of gameplay and the evacuant potential in the field. Conclusions suggest a continuum where presence state is a significant interim mode toward a higher order aesthetic resonance state that we claim inherent to our interpretation of play therapy. Whilst this research is a few years ago the findings are still relevant and align to contemporary studies and in context of this book where cross-reference is made from another publication.
The price of anarchy in Tor latency reduction

The expected cell latency for multi-hop M/D/1 queueing networks in Wardrop equilibrium is calculated. The load is balanced such that no user can benefit from unilaterally changing its routes. The results are applied to a typical snapshot of the Tor anonymity network, for which an efficient approach is devised to calculate the equilibrium routing strategy. For this snapshot, latency in the Wardrop equilibrium is numerically compared with the globally optimal latency and the latency of the original routing method of Tor.
The Impact Adobe Flash Media in Learning Economics

Abstract This study aims to present the extent of the influence of Adobe Flash media on economic learning. The problem that exists is that there are still many schools that have not implemented varied learning media and the learning media used are less attractive so that they have a less than optimal impact on students. This research method is literature review study. The findings in this article present an increase in student motivation, creative thinking, critical thinking, literacy and student learning outcomes. The results of the literature review show that through the use of Adobe Flash media will have an effect on increasing student motivation, creative thinking, critical thinking, literacy and learning outcomes. The advantage of flash media is that it is one of the most popular web animation technologies, has good quality, and can be displayed on many media. However, Adobe Flash media has a drawback, namely that you have to memorize commands for beginners and only use them online. Literature study that examines Adobe Flash media in increasing the effectiveness of the economic learning process and students’ abilities in the economic learning process.