Reviewerly/exHarmony huggingface dataset:
Semantic Relationship between Abbreviations and the Original Words Based on Word Vectors

Based on word vectors, this paper studies the semantic relationship between abbreviations and the original words from a quantitative perspective. First, we train word vectors according to the corpus of the People's Daily. Then, from the perspectives of intrinsic evaluation and extrinsic evaluation, the research on the relationship between abbreviations and the original words is carried out. In the intrinsic evaluation, after vectorizing the abbreviations and their original words, we measure their semantic similarity, and compare with the semantic similarity of synonym collection; In the extrinsic evaluation, we propose an abbreviation recognition task, like named entity recognition. Through this task, the degree of mutual substitution between abbreviations and the original words can be described. The above experiments show that after the abbreviations and their original words are expressed by word vectors, there is still a strong semantic relationship between them.
Improving Efficiency of CBIR by using Color, Texture and Fusion Features with Bit Pattern

Digital graphic offers many advantages for processing and distributing image and other types of understanding.A single color image have more information of the different situations and object scenario and each color and texture have own characteristics.Geometrical and color information extraction are the key issue.CBIR finds and show images alike to one given as query image and another are similar images.In the earlier work, most of the researchers used low level features but there are some challenges like distortion of image, color imbalance, semantic gap between low level features etc.The challenges, be that as it may, is in planning a system with the capacity to retrieve best possible matches when there is an occurrence of all kind of images as query without using some other relevant information, for example, metadata, keywords and labels etc, and using only content of the images.The system proposed in this approach aim to retrieve the most relevant images using color, edge histogram descriptor with bitmap by using fusion based feature.Applications of the proposed system are climate forecast, crime prevention, military imaginary etc.
Development of a Disaster Safety Sentiment Index via Social Media Mining

People use social media platforms such as Twitter to record their personal thoughts and opinions.Social media platforms reflect people's sentiments as they are, and an accurate understanding of sentiments on social media could be useful and significant for disaster management.In this research, sentiment type modeling and sentiment quantification are proposed to understand the sentiments presented on social media platforms.Sentiment types are primarily analyzed based on the three major sentiments of affirmation, caution, and observation.Then, for a detailed understanding of sentiment progress according to the progress of a disaster or accident and the government's response, negative sentiments are categorized into anxiety, disappointment, depression, sadness, and displeasure to enhance the analysis, while positive sentiments are categorized into pleasure, happiness, and relief; Russell's circumplex model is used to develop a model of eight primary sentiments to acquire an overall understanding of the public's sentiments.Then, the sentiment index of each sentiment is quantified.Based on the results, the overall sentiment status of the public is monitored, and in the event of a disaster, the public's sentiment fluctuation rate can be quantitatively observed.Moreover, the influence of disasters and accidents on public sentiments, or the sentiment indices of different accidents, can be compared to identify the accidents that affect public sentiment and public needs after a disaster, and the insights can be used for policy-making.
Invisible watermarking framework that authenticates and prevents thevisualization of anaglyph images for copyright protection

In this work, a watermarking framework to authenticate and protect the copyright that prevents the visualization of nonauthorized anaglyph images is proposed. Designed scheme embeds a binary watermark and the Blue channel of the anaglyph image into the discrete cosine transform domain of the original image. The proposed method applies the quantization index modulation-dither modulation algorithm and a combination of Bose-Chaudhuri-Hocquenghem with repetition codes, which permit to increase the capability in recovering the watermark. Additionally, Hash algorithm is used to scramble the component where the watermark should be embedding, guaranteeing a higher security performance of the scheme. This new technique prevents the visualization of 3D content to unauthorized users. Additionally, its high robustness against the most common image processing attacks, such as JPEG compression, impulsive and Gaussian noises, etc. has been demonstrated in this study.
Disorder indicator for nonstationary stochastic processes

The properties of a statistic called a self-consistent stationarity level of nonstationary time series are examined in this work. It is shown that a change in this statistic can be treated as a disorder in the nonstationarity properties of the series. The significance level of decision making is estimated, characteristic periods in a non-stationary stochastic process are detected, and an optimal sample size for constructing indicators in stochastic control problems is determined. A disorder indicator for electroencephalogram data from epilepsy patients is studied as a practical application.
Sistem Pendukung Keputusan Kelayakan Penerima Subsidi Kepemilikan Rumah Menggunakan Adaptive Neuro-fuzzy Inference System

The development of the world of Information Technology is so fast that the technology that has just become a trend has become obsolete in a short time. so that the existence of accurate, fast and reliable information is needed in various aspects of life. Armed with the problems arising from previous research, that is the result of not implementing government regulations properly so that the ownership of RSH is not exactly the target for this research is carried out so that the developer can make decisions to determine the feasibility of recipients of House ownership ready, decent or inappropriate which is required by grant recipients from low-income communities. As well as with the criteria used to help the developer or developer determine the feasibility of the recipient of the Ready to Own House (RSH) subsidy by applying the ANFIS method in developing its decision support system.
SIMULASI PEMILAH BENDA BERDASARKAN WARNA (HITAM-PUTIH) MENGGUNAKAN SENSOR WARNA BERBASIS MIKROKONTROLER AT89S51

&lt;p&gt;&lt;em&gt;At present the company is always trying to replace the work done by humans, replaced by machines in order to improve the efficiency and quality of production. In other words, many companies automate their production. For example, production processes that were initially carried out manually as in the process of sorting their products. In the industry this process is done manually with human effort and requires a large amount of labor and makes the production process longer. To overcome this problem, companies that want more effective and efficient production processes to change production patterns by applying automation in their production systems. This is realized by the construction of a packing system for goods, where the system usually consists of goods distribution in the form of a mechanical conveyor system and packaging of goods. As in the case of items based on the color sorting system, you will need a tool that can automatically sort this product. This system consists of object sensors, color sensors, conveyor belts, and means of dividing goods. Mechanical systems are built using acrylic, plastic and PVC. The control system in this simulation uses the AT89s51 IC microcontroller.&lt;/em&gt;&lt;em&gt;&lt;/em&gt;&lt;/p&gt;&lt;strong&gt;&lt;em&gt;Keyword &lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: Augmented Reality, &lt;/em&gt;Satya Negara Indonesia&lt;em&gt; University, Virtual Reality, 3D&lt;/em&gt;
NEW METHOD OF USING MOBILE ROBOTS FOR IMPLEMENTING WAREHOUSE OPERATIONS

The new patented method of movements of packaged cargoes at the warehouse is proposed in this article.The proposed method of loading is superior in economic efficiency, reliability, cheapness, simplicity of construction and use, to all other methods of loading implemented by robots.The method allows the mobile robot to load a cargo which is three times as heavy as this mobile robot, wherein almost no electrical energy is consumed during loading.In implementing the method, two mobile robots are used, each of which contains a mobile platform, an omnidirectional mobile wheel-type mechanism and a transport suspension with independent suspension for each wheel.Actually, mobile robots help each other to load cargo on the first mobile robot, through robot cooperation.Loading of the container with the load on the first mobile robot is carried out by actuating a two-arm lever, which is carried out through the impact of the bottom of the mobile platform of the second mobile robot on the longer arm of the two-arm lever by lowering the mobile platform of the second mobile robot due to the operation of the transport suspension of the mobile platform of the second mobile robot.For example, if the length of the longer arm of the two-arm lever is three times longer than the shorter arm of the two-arm lever then the second mobile robot of weight 50 kg is capable of loading a container with a load of weight 150 kg on the first mobile robot.
Pengembangan Bahan Ajar Pembelajaran Matematika Untuk Mahasiswa PGSD Semester 6

The purpose of this study was produce a mathematics learning companion book that was feasible to use and to measure the student's response to the teaching material. This study uses the Research and Development (R &amp; D) method with a 4D model, which includes needs analysis, design, development, and dissemination. The feasibility was measured with the validity test from material and the design expert. The effectiveness was measured with the test to one class of PGSD FKIP UMM students, then the second test was conducted in 2 classes. The results of the research obtained are the validity values of teaching materials worthed 91.6%, and the validation test the material experts scored 78.8%, all are in ‘valid’ criteria. The effectiveness of the teaching materials were also shown from positive responses obtained from lecturers and students as product users. After revision, the effectiveness of teaching materials reached 86.93%, in the ‘effective’ criteria. Lecturers and students concluded that the use of teaching materials companion book was effective for learning
Towards Automatically Generating a Sound and Complete Dataset for Evaluating Static Analysis Tools

Binary static analysis has seen a recent surge in interest, due to a rise in analysis targets for which no other method is appropriate, such as, embedded firmware.This has led to the proposal of a number of binary static analysis tools and techniques, handling various kinds of programs, and answering different research questions.While static analyis tools that focus on binaries inherit the undecidability of static analysis, they bring with them other challenges, particularly in dealing with the aliasing of code and data pointers.These tools may tackle these challenges in different ways, but unfortunately, there is currently no concrete means of comparing their effectiveness at solving these central, problem-independent aspects of static analysis.In this paper, we propose a new method for creating a dataset of real-world programs, paired with the ground truth for static analysis.Our approach involves the injection of synthetic "facts" into a set of open-source programs, consisting of new variables and their possible values.The analyses' goal is then to evaluate the possible values of these facts at certain program points.As the facts are injected randomly within an arbitrarily-large set of programs, the kinds of data flows that can be measured are widely-varied in size and complexity.We implemented this idea as a prototype system, AUTOFACTS, and used it to create a ground truth dataset of 29 programs, with various types and number of facts, resulting in a total of 2,088 binaries (with 72 versions for each program).To our knowledge, this is the first dataset aimed at the problem-independent evaluation of static analysis tools, and we contribute all code and the dataset itself to the community as open-source.
A Theoretical Model for Cloud Computing Adoption Saudi Arabia For Small and Medium Size Enterprise (SMEs) in ICT Sector

Cloud computing technology provides different solutions to organizations on demand in order to improve their performance and to lower hardware and software procurement and maintenance cost.There is a rich body of literature on its benefits for SMEs, however, studies that investigate the factors influencing the adoption by SMEs in developing countries especially Saudi Arabia and particularly in Information and Communication Sector (ICT) are still lacking.To fill this gap, this study examines the factors that influence the adoption of cloud computing by Saudi Arabian SMEs.This study seeks to develop a research framework that integrates the innovation characteristics as well as the Technology-Organization-Environment (TOE) perspectives that underlie its adoption.Primarily, the adoption factors for cloud computing are identified and classified into different dimensions using the Technology, Organization and Environment (TOE) framework.This study therefore presents a more holistic assessment of the factors of cloud computing adoption than earlier studies.The study contributes to the wider body of scientific knowledge that, so far, has not studied the adoption of cloud computing in this sector.The findings confirm a high potential for use of the cloud computing market within developing countries and further recommend cloud computing vendors to focus on cloud computing knowledge.
Penerapan Pelatihan Partisipatif Pada Kegiatan Penulisan Dan Publikasi Karya Ilmiah Bagi Guru SD

The problems that will be solved in Community Engagement (CE) activities for elementary school teachers in Kecamatan Tingkir is the low ability to write scientific paper among teachers. This CE activity was held at SD Tingkir Lor 2 Salatiga. The participants of the CE were 54 elementary school teachers/principals from the Gugus Joko Tingkir. The model of the CE is a participatory training model. The training activities were carried out for three days from April 23-25, and continued online coaching for 2 weeks. Training material covers the Basics of Writing; Problems in Scientific Paper Writing; Searching materials; Introduction of Online Journals, Introduction to Style Guide and How to Submit in Online Journal. Instruments to measure the success of the process and results of training using questionnaires and evaluation sheets. Data analysis techniques used percentage analysis techniques and categorical descriptive. The results of CE is: teacher knowledge about writing increases; skills in writing papers have been shown to increase from a number of articles published successfully; teacher professionalism has increased, proven to be successful in writing scientific articles; and a close relationship between KKG Gugus Joko Tingkir with PGSD-FKIP UKSW.
Optimal Sequential Planning for Communicative Actions: A Bayesian Approach

We build on the Interactive POMDP (IPOMDP) framework, which extends POMDPs to multi-agent settings, and include communication which can take place between the agents. While IPOMDPs endow the agents with models of their environments and models of other agents, we supplement IPOMDPs with communicative acts available to the agents to formulate Communicative IPOMDPs (CIPOMDPs). We treat communication as a type of action; hence decisions regarding communicative acts should be based on decision-theoretic planning using Bellman optimality principle, just as they are for all other actions. As in any form of planning, the results of actions need to be precisely specified. We use Bayes update to derive how agents update their beliefs in CIPOMDPs; updates are due to their actions, observations, messages they send to other agents, and messages they receive from others. Without communication, CIPOMDPs reduce to IPOMDPs. Without other agents they all become classical POMDPs.
CrowdGuard: Characterization and Early Detection of Collective Content Polluters in Online Social Networks

Recently, content polluters post malicious information in Online Social Networks (OSNs), which is a more and more serious problem that poses a serious threat to the privacy information, account security, user experience, etc. They continuously simulate the behaviors of legitimate accounts in various ways, and evade detection systems against them. In this paper, we focus on one kind of content polluter, namely collective content polluter (hereinafter referred to as CCP). Existing works either focus on individual polluters or require long periods of data records for detection, making their detection methods less robust and lagging behind. It is thus necessary to analyze the characteristics of collective content polluters and study the methods for early detection. This paper proposes a CCP early detection method called CrowdGuard. It analyzes the crowd behaviors of collective content polluters and legitimate accounts, extracts distinctive features, and leverages the Gaussian Mixture Model (GMM) method to cluster the two groups of accounts (legitimate users and polluters) to achieve early detection. Using the public dataset including thousands of collective content polluters on Twitter about a political election, we design an experimental scenario simulating early detection and evaluate the performance of CrowdGuard. The results show that CrowdGuard outperforms existing methods and is adequate for early detection.
Can additional spectral bands be estimated from aerial color images?

Inspired by the surprising performances of deep generative models, in this paper we present the preliminary results of an overly ambitious task: estimating computationally the additional spectral bands of a color aerial image. We have harnessed the expressive power of deep generative models to estimate the distribution of mostly infrared bands of aerial scenes, using only color RGB channels as input. Our approach has been tested from multiple aspects, including the reconstruction error of the additional bands and the effect of estimated bands on scene classification performance, as well as through the transfer potential of the trained network to a distinct dataset. To our surprise, the initial experiments have shown us that deep generative models can indeed learn to estimate additional bands up to a certain degree and can thus computationally reinforce datasets stemming from color-only sensors.
The effects of the global surface curvature on Makyoh-topogaphy imaging

The effects of the global curvature of the reflecting surface on Makyoh (magic-mirror) topography imaging is analysed based on a geometrical optical model. It is shown that the effects can be taken into account by introducing an equivalent screen-to-sample distance which is a function of the real screen-to-sample distance and the global curvature. The special limiting cases are discussed and analysed for practical applications. Full Text: PDF ReferencesK. Kugimiya, "“Makyoh”: The 2000 year old technology still alive", J. Cryst. Growth 103, 420 (1990). CrossRef P. Blaustein, S. Hahn, "Realtime inspection of wafer surfaces", Solid State Technol. 32, 27 (1989). CrossRef Z.J. Pei, G.R. Fisher, M. Bhagavat, S. Kassir, "A grinding-based manufacturing method for silicon wafers: an experimental investigation", Int. J. Machine Tools Manufacture 45, 1140 (2005). CrossRef F. Riesz, "Makyoh topography: a simple yet powerful optical method for flatness and defect characterization of mirror-like surfaces", Proc. SPIE 5458, 86 (2004). CrossRef T. Hirogaki, E. Aoyama, R. Machinaka, H. Sueda, K. Ogawa, J. Japan Soc. Precision Eng. 73, 96 (2007). CrossRef G. Saines, M.G. Tomilin, "Magic mirrors of the Orient", J. Opt. Technol. 66, 758 (1999). CrossRef W.E. Ayrton, J. Perry, "The Magic Mirror of Japan. Part I", Proc. Roy. Soc. London 28, 127 (1878). CrossRef M.V. Berry, "Oriental magic mirrors and the Laplacian image", Eur. J. Phys. 27, 109 (2006). CrossRef F. Riesz, "Sensitivity and detectability in Makyoh imaging", Optik 122, 2115 (2011). CrossRef Z.J. Laczik, "Quantitative Makyoh topography", Opt. Eng. 39, 2562 (2000). CrossRef F. Riesz, "Geometrical optical model of the image formation in Makyoh (magic-mirror) topography", J. Phys. D: Appl. Phys. 33, 3033 (2000). CrossRef F. Riesz, "Camera length and field of view in Makyoh-topography instruments", Rev. Sci. Instr. 72, 1591 (2001). CrossRef J. Szabó, F. Riesz, B. Szentpáli, "Makyoh Topography: Curvature Measurements and Implications for the Image Formation", Japan. J. Appl. Phys. 35, L258 (1996). CrossRef F. Riesz, "Non-linearity and related features of Makyoh (magic-mirror) imaging", J. Opt. 15, 075709 (2013). CrossRef A.V. Gitin, "System approach to image formation in a magic mirror", Appl. Opt. 48, 1268 (2009). CrossRef
Digital Language Mining Platform for Nigerian Languages (DLMP)

Effective communication occurs when the receiver and sender both understand and synchronize the flow of information across board.The utility of language extends beyond human to human interaction and includes also, the use of syntactically formed programming languages to interact with digital systems.Nigeria has an estimate of over 450 languages, which makes it cumbersome to harmonize and put all into a single large repository for data mining.The goal of this paper is to firmly establish the importance of Information Technology in galvanizing Nigerian Languages and Mining scientific data thereof.The purpose of applying Information and Communication Technology (ICT) is to codify the process of extracting various underlying meanings in a language, processing the various idioms, proverbs and quaint statements in such language with the view of bringing out the creativity behind them.The authors explore the developmental stages and techniques of applying an artificial Intelligence system that scans through a given indigenous linguistic system to bring out the hidden facts therein.It is recommended that stakeholders in the 'digital humanities' adopt such mining platforms which helps in achieving greater insight into the diverse cultures and languages, in turn, promoting easy learning experience for indigenous languages.
Author Correction: Perceptual straightening of natural videos

The original and corrected figures are shown in the accompanying Author Correction.
Learning Writing through Psychowriting Perspective

All this time, writing is widely viewed from various perspectives, such as fragmentary and/ or integrative (mono-disciplinary studies), interdisciplinary studies, and multidisciplinary studies. In this article, learning writing based on psychowriting in the Department of Indonesian Language and Literature, State University of Surabaya is presented. Based on the results of the study, it was found that psychowriting-based writing lesson improves students’ writing skill, writing effectiveness, and the understanding of students’ psychological personality.