Reviewerly/exHarmony huggingface dataset:
Field Experiment System “VoiceTra”

This chapter introduces “VoiceTra,” a speech-to-speech translation system which utilizes the technologies introduced in the previous chapters. VoiceTra’s client application has been released as to the public as a field experiment and has marked a total of 3,921,186 downloads and has collected as many as 178,054,211 speech utterances (as of August 31st, 2019), allowing the system to make continuous improvements. The following sections will cover the system overview, the communications protocols used between the client and server, the user interface of the client application, how the utterances are processed on the speech translation server, and finally the statistical data based on user downloads and logs.
Implrmrntasi Policy Base Routing Dan Failover Menggunakan Router Mikrotik Untuk Membagi Jalur Akses Inter Di Fakultas Komputer Universitas Bina Insan Lubuklinggau

ABSTRACT The problem in this study is that more and more internet users in the Bina Insan Lubuklinggau University building specifically the Faculty of Computer internet connection often experience problems, the internet network is still unstable, and ways to divide internet access points in the Computer Faculty. This study uses data collection methods by observing and recording directly at the research site (Observation), conducting question and answer directly to the source (Interview), and documentation by reading literature books. The results showed that the internet is often experiencing constraints and unstable internet networks and ways to divide internet access points at the Computer Faculty of the University of Bina Insan Lubuklinggau by using Policy Base Routing and Failover Implementation using a Mikrotik Router. It can be concluded that the internet network connection is stable and shows the results of the distribution of internet access points at the Faculty of Computer Bina Insan Lubuklinggau. Keywords: Mikrotik, Policy Base Routing, Failover
Papers we should be reading

This issue's recommended paper comes from Axel Hübl (Lawrence Berkeley National Laboratory). Among other distinctions, Axel received the ACM/IEEE-CS George Michael Memorial High Performance Computing Fellowship in 2016.
Modern Drum Solos Over Ostinatos

Abstract Improvised drum solos by Steve Gadd, Vinnie Colaiuta, Dave Weckl, Trilok Gurtu, and Jojo Mayer are examined in the context of interactive frameworks comprising three distinct rhythmic elements: meter, ostinato, and drums. Meter and background ostinato provide complementary recurring cycles—one implicit, the other explicit—that the drummer uses as referents to create shifting contrapuntal configurations. These configurations can be understood in terms of degrees of synchrony between the three elements in the drums/meter/ostinato network, from full three-way convergence to total divergence and including intermediary states where one of the three elements is distinct from the other two. The chapter pays special attention to polymetric phrasing, an effective way for drummers to not only affirm their independence from meter and ostinato but also infuse the solo with playfully complex qualities.
Towards a Trusted Virtual Smart Cities Operation Center Using the Blockchain Mirror Model

The article proposes a new vision for the smart city operation center combining blockchain and virtual reality. The objective is to achieve high synchronization among the different operators, an enhanced operator performance and the creation of a trustworthy communication layer to record all the decisions taken in the virtual environment and to share data among the operators securely.
Modern Search Engine Techniques

To be at the top in the world of www, every website needs to be standardized and well format as per standards defined. SEO has many new algorithms &amp; indexing ways that helps user to get best results for their searches. Search Engine Optimization (SEO) is important for websites to improve the rank for search results and get more page views resulting into large user traffic. The search engine ranks provide the better and optimized result to user's query, which help them to view the exact contents they are looking for from list of popular web pages among the number of pages available on the web. My case study will focus on some advanced techniques that are helpful to the website owner for better page rank in search result. This will focus on simple modern SEO techniques that can be add on to your website designing which will indirectly help into SEO page rank.
Fuzzy Reasoning and Decisions in Primary School

The work starts from the idea that the natural instrument of communication in a class is constituted by linguistic propositions, called fuzzy propositions, which are grammatically and syntactically correct statements, but which often can not be classified either completely true or completely false. The truth value of a linguistic proposition depends on the opinions of a decision maker that are conditioned by the circumstances that occur. In this order of ideas the linguistic proposition is called a fuzzy event. A problem of decisions under conditions of uncertainty can be seen as attributing truth values to fuzzy events for each of the states of nature. Using the classic logical operations on events we can define the logical reasoning methods. We consider also an extension to fuzzy events, highlighting the fact that this leads to having to make choices of a subjective nature, on which to open interesting debates in the classroom.
Development of Independent Learning System Arabic Letters For Blind People

Abstract The purpose of this study describes the design of the instrument which aims to help blind people learn hijaiyah letters. For blind people, of course there will be difficulties in learning hijaiyah letters. The research method used was the process of making tools in designing a system block diagram consisting of three main parts, namely the design of input modules, the controller / processor design, and the output design. Based on the results of the study found that an independent system that can teach hijaiyah letters to the blind, this instrument can be used independently by the blind because it provides a special braille button to represent hijaiyah letters. There are two modes provided in this learning tool, namely tutorial mode and practice mode. For tutorial mode, if a blind person presses the braille button on one of the hijaiyah letters, the letter will come out. As for the practice mode, if a blind person reads hijaiyah letters, the tool will provide a voice response to the user whether the pronunciation of the letters is correct or wrong in pronunciation. With this instrument, it is expected to help make it easier for blind people to learn hijaiyah letters.
Deep CNN for Single Image Super Resolution Using Skip Connections

With the current progress in deep learning domain, quite a few deep learning based models have been developed to address the challenges of Single Image Super Resolution (SISR) task. Recent trend in SISR models is towards increasing the depth of the model to achieve a high accuracy through multiple contexts learned at various depth of the network. Skip connections between different layers of the deep network help in utilising multi-context features and also help to address the issue of vanishing gradients but at the cost of increased computational complexity. In this paper, a deep CNN with a minimum number of skip connections is devised to derive a High-Resolution (HR) image from a Low-Resolution (LR) image. A detailed experimental analysis is carried out on skip connection parameters for a given depth to optimise network parameters. The proposed model gives better results compared to existing methods for multiple scales on benchmark data-sets.
Research on the Propagation Characteristics of Social Events in the Context of Micro-media

Abstract With the great development of information science and technology, a variety of communication tools have come out, which enormously improved efficiency and speed of social communication, and people’s living conditions have endured a great change. The social events has always drawn mass attention and reflected publice focus, and people will soon get together, talking about social events by micro-media, such as QQ, Wechat, micro-blogs. The way people talked and publicized by micro-media, as well as the outcome, are all things we are going to research on.
Impact of therapeutic riding on motor function

"Impact of therapeutic riding on motor function." Journal of Physical Education, Recreation & Dance, 90(9), pp. 61–62
User-trained activity recognition using smartphones and weak supervision

With many people now carrying some form of smart device, the feasibility of capturing movement data has never been so practical. Current methods of activity recognition use complex sensor arrangements or potentially biased questionnaires. This paper presents a method of activity recognition which is trained by the user on their own device, reducing the requirement for laboratory-based data capture experiments. Requests will be made to the user to provide labelling information at fixed intervals and a classifier is trained using these user-captured labels. These requests will come in the form of notifications on their smart device. Many activity recognition systems are limited to capturing the activities they are pre-trained with. However, allowing the user to provide their own sparse labels provides an opportunity to capture a larger range of activities. The novel contributions of this paper are in the combination of experience sampling with multiple instance learning and a clustering method to provide a simpler method of data capture for activity recognition.
Segmentation of Leukemia Cells Using Clustering

Leukemia is a blood cancer which is defined as an irregular augment of undeveloped white blood cells called “blasts.” It develops in the bone marrow, which is responsible for blood cell generation including leukocytes and white blood cells. The early diagnosis of leukemia greatly helps in the treatment. Accordingly, researchers are interested in developing advanced and accurate automated techniques for localizing such abnormal blood cells. Subsequently, image segmentation becomes an important image processing stage for successful feature extraction and classification of leukemia in further stages. It aims to separate cancer cells by segmenting the microscopic image into background and cancer cells that are known as the region of interested (ROI). In this article, the cancer blood cells were segmented using two separated clustering techniques, namely the K-means and Fuzzy-c-means techniques. Then, the results of these techniques were compared to in terms of different segmentation metrics, such as the Dice, Jac, specificity, sensitivity, and accuracy. The results proved that the k-means provided better performance in leukemia blood cells segmentation as it achieved an accuracy of 99.8% compared to 99.6% with the fuzzy c-means.
Multiple-Disease Risk Predictive Modeling Based on Directed Disease Networks

This paper studies multiple-disease risk predictive modelsPredictive modeling to assess a discharged patient’s future disease risks. We propose a novel framework that combines directed disease networksDirected disease network and recommendation system techniques to substantially enhance the performance of multiple-disease risk predictive modelingPredictive modeling . Firstly, a directed disease networkDirected disease network considering patients’ temporal information is developed. Then based on this directed disease network, we investigate different disease risk score computing approaches. We validate the proposed approaches using a hospital’s dataset. Promisingly, the predictive results can be well referenced by healthcare professionals who provide healthcare guidance for patients ready for discharge.
Generating Topical and Emotional Responses Using Topic Attention

As an indispensable influencing factor of human-computer interaction experience, emotional cognitive behaviors in dialogues have aroused spread concern of researchers. However, existing emotional dialogue generation models tend to generate generic and universal responses. To address this problem, this paper proposes a topical and emotional chatting machine (TECM) that generates not only high-quality but also emotional responses. TECM utilizes the information obtained by the topic model as a prior knowledge to guide the generation of the responses, and the topic information is used as the input of the topic attention mechanism to improve the quality of responses. TECM also adopts a method of emotion category embedding to generate emotional responses. The empirical study on automatic evaluation metrics shows that TECM can generate diverse, informative and emotional responses.
Collaborative adaptive scheduling scheme for multi-source big data tasks in the cloud

With the arrival of big data age, workflow applications are transferring from original infrastructure to more efficient, reliable and affordable cloud computing platforms. Focusing on fine-grained big data tasks schedule in cloud computing environment, we proposed a novel collaborative adaptive algorithm based on reinforcement learning in this paper. Experiment results demonstrate the efficiency of the collaborative adaptive scheduling scheme.
Sensitive Data Encoding in Blockchain-Based P2P Trading System

With the rapid development and application of information technology, blockchain technology has become one of the important means to promote the integration of the real economy and the digital economy. However, for the application of blockchain technology in P2P transactions, existing technology provide no reasonable framework. This paper proposes a framework of P2P trading system based on blockchain technology. The proposed framework can ensure the security of data and establish trust among entities. It can also reduce business divergence and costs. In order to prevent the leak of sensitive data in the trading process, we also propose an encoding method of sensitive data. This guarantees the data from being stolen or tampered. The calculations on matrixes of this method can use the computing resources of all nodes in the blockchain to calculate in parallel, and then summarize the results. This makes full use of massive GPU resources in the blockchain, and makes the calculation valuable. The proposed framework and method realize transactions without the intervention of a centralized platform. It not only establishes the trust relationship among entities well, but also realizes safe and reliable P2P transactions.
Web-Based Culture Information System of Literature Besemah City of Pagar Alam

The purpose of this research is to create a Web-based Literature Culture Information System Besemah Pagar. Besemah Literary Culture comes from the besemah tribe that grew up in Kota Pagar Alam. Besemah literature is now rarely heard by the Pagar Alam people inside and outside the City of Pagar Alam and is also almost unknown to the public, especially Pagar Alam among young people today. The system development method used is Rapid Application Development. With the web-based information system program, the public will gain knowledge about the literary culture that is weak in the City of Pagar Alam, and also help disseminate information in the introduction of the culture and literature to the public at large to increase outside tourists in supporting the City of Pagar Alam program. Tests carried out using Black Box Testing with no error results. The results of research in the form of Web-based Literature Culture Information System Weak Besagar Pagar that can be implemented and used by the general public.
Reversible Image Watermarking for Health Informatics Systems Using Distortion Compensation in Wavelet Domain

Commencing the watermarked image replacement of related inventive cover and watermark symbol is assured by Reversible image watermarking. Two fold significant consideration sin reversible watermarking are Capability and distortion of the image. Concentrating on improving the implanting capability plus decreasing the distortion in medicinal images, a reversible watermarking is explored in this paper. Intended for implanting single bit of watermark in a transform factor, we practice numeral wavelet transform. The formed distortion is recompensed in the succeeding repetition as soon as a constant is altered in single repetition and this has been formulated using a novel methodology. Condensed alteration proportion is produced using Distortion Compensation technique. Upon 4 varieties of medical images comprising MRI of the brain, cardiac MRI, MRI of breast and intestinal polyp images, the anticipated scheme is verified. Through a single-stage wavelet transform, the extreme capability of 1.5 bpp is attained. With reference to capability and alteration, the anticipated scheme is greater to the state of-the-art mechanisms which are validated using Investigational outcomes.
Adaptation of Parameters with Binary Cat Swarm Optimization Algorithm of Controller for a Mobile Autonomous Robot

This paper describes a method to solve optimization problems based on the binary cat swarm optimization (BCSO) algorithm to optimize the trajectory of a mobile unicycle autonomous robot, with the aim of following an established trajectory with the lowest possible margin of error. Simulation results show that the proposed method achieves good results.
Evaluating the Comprehensiveness of VR PLAY Guidelines Using Elder Scrolls: Skyrim VR

Heuristic evaluation is a useful tool for non-usability experts to evaluate their product for usability and produce lists of guidelines for product designers to avoid usability problems early in the development process. However, Nielsen’s 10 original us ability heuristics (Nielsen, 1990) only showed to help users find slightly over 50% of the usability problems found by experts. This highlights the need for domain-specific heuristic lists. An example of one of these domain-specific lists is VR PLAY (Desurvire &amp; Kreminski, 2018), a heuristic list to help virtual-reality game developers evaluate their games and adhere to usability principles. The current research evaluated Elder Scrolls: Skyrim VR for usability problems that were then categorized using VR PLAY. Results showed some missing usability principles in VR PLAY, including guidelines for control design, user interface elements, and navigation. This study proposes changes to VR PLAY to include the principles.
K-means algorithm for mapping by utilizing google maps imagery

Abstract In several cases, data mapping that is available today has not much done digitally yet. Too much data that is involved in data filling process causing a long mapping process. The purpose of this research is to design the system by implementing K-Means Clustering Algorithm for data mapping using Google Maps imagery. The object of system design in this research is the plantation area in Sukabumi Regency, Indonesia. The system design methodology that used is the UML (Unified Modelling Language) approach. Based on the results of system testing, K-Means Clustering algorithm can determine and cluster the plantation area with potency of commodity with three level, among others high level, medium level, and low level, which is further indicated by spatial data.
The Construction of a Domain Knowledge Graph and Its Application in Supply Chain Risk Analysis

Domain knowledge graphs, which compose scattered information about domain entities, are expressive when organizing information for enterprise systems in the decision-making process. Such knowledge graphs can give us semantically-rich information which can later be applied to fuel different graph mining services to conduct analytical work. In this paper, we discuss a subject-oriented domain knowledge graph based on multi-source heterogenous data consisting of dynamic data generated from daily transactions among companies in interlacing supply-chains and relatively static data demonstrating the basic properties of these enterprises to assist with analytical work. Such high-dimensional graph with strong heterogeneity is rich in semantics and is casted into lower dimensions to be used as inputs for graph mining services, giving us various enterprise correlation chains, aiming to support upper-level application like credit risk assessment. The framework has been testified in real-life information systems.
Swarm Based Algorithms for Neural Network Training

The purpose of this paper is to compare the abilities and deficiencies of various swarm based algorithms for training artificial neural networks. This paper uses seven algorithms, seven regression problems, sixteen classification problems, and four bounded activation functions to compare algorithms in regards to loss, accuracy, hidden unit saturation, and overfitting. It was found that particle swarm optimization is the top algorithm for regression problems based on loss, firefly algorithm was the top algorithm for classification problems when examining accuracy and loss. The ant colony optimization and artificial bee colony algorithms caused the least amount of hidden unit saturation, with the bacterial foraging optimization algorithm producing the least amount of overfitting.
A Semi-supervised Fuzzy Clustering Approach via Modifications of the DBSCAN Algorithm

In the data mining context, semi-supervised learning is applicable in circumstances where only a scarce amount of information on the intrinsic structure of a dataset is available. This information may be in the form a few labelled instances or a relatively small set of constraints on the pairwise memberships of particular instances. In this study we are providing a semi-supervised fuzzy clustering model which modifies versions of conventional DBSCAN algorithm in order to generate soft clusters which foreclose the noise points. The employed modifications are mostly related to the control parameters of the algorithm intending to utilize the additional information (which in our case is in the form of a few labelled instances) and adaptations towards the fuzzy clustering approach. Finally, several experimental procedures have been conducted on synthetic and real-world benchmark datasets in order to assess the accuracy of our employed model and to compare it to the conventional algorithms of the respective domain.
Confidence Value: A Novel Evaluation Index of Side-Channel Attack

The side-channel attacks (SCAs) use the correlation between the power leakage information and the key to implement the attack process. The result of SCAs has a certain probability. If guessing an 8-bit key, there is a probability of 1/256 that the key will be guessed coincidentally, resulting in false positive. Therefore, the reliability of result key also needs an index to measure. Thereby, this paper proposes a novel evaluation index based on confidence value (CV). The CV of result key is divided three levels, low false positive, medium false positive and high false positive. CV provides a new reference index for the designers, suppliers and users of cryptographic devices to evaluate the security of devices.
Analysis of Project Documentation Based on the Search for Frequent Subgraphs

The problem of the analysis of project documentation are considered. Various ways of presenting documentation are described. The task of finding frequent subgraphs is presented. An algorithm for searching for documentation based on the search for frequent subgraphs is proposed.