Reviewerly/exHarmony huggingface dataset:
A Tabulation method for Character Recognition using Haar wavelet in 2D images

Character perception is a unique way to diagnostic the unidentifiable character into understandable text. Nowadays, with the increasing urge of getting information digital media has been roped in because of its convenient use. Hence the printed media needs to get into digital format but the printed text needs to get recognized by the computer this difficulty is solved by the pattern matching technique and haar wavelet method to recognize the character ,decompose it and frame it into understandable format keeping its prototype in mind this method can turn boon for the unidentifiable text also it can overcome the problems of printed text character perception system help human ease and reduce their jobs of manually handling and processing of document. The proposed method showed that the recognition of text is reliable and significantly accelerates data processing. Evaluation is executed as a collection of degraded documents which are images, indicates the proposed work will be well suited to reduce the noise by improving the pixel quality in which it will be rendered. The result analysis performed by using image quality matrix which are Mean Squared Error, Signal to Noise ratio, Structural Content, Normalized Cross Correlation, Maximum Difference, Normalize Absolute Error, Average difference. All the parameter shows effective results. Keywords — Character Perception, Haar Wavelet, Image Quality Matrix, Pattern Matching, Recognition of Text.
Implementation of Fuzzy Inference System with Sugeno Method for Marketing Performance Assessment

The Witel Business Service Division is a division that is responsible for the operational sector of PT Telkom Telekomunikasi Indonesia.One of the operational areas in the Witel division is customer service.The task of contacting customer needs in the ICT field as well as the disruption that the customer is experiencing is the task of the marketing department.The marketing department visits or prospects to customers through visits, calls, emails, to each predetermined customer data.If the customer agrees with what marketing offers, a memorandum of understanding is made.Furthermore, marketing will report its activities to the manager.Manager has one of his duties to evaluate marketing performance.There are several parameters / criteria for evaluating marketing performance based on reports received.In this study, to assess marketing performance using the Fuzzy Inference System (FIS) Sugeno method, namely the process of making a mapping system from the input given to the output using fuzzy logic.Fuzzy variables are obtained from the criteria for Existing Customer Management, Acquisition of Subscription Contracts and PBC is Acquisition of Billing Complete which is then used as fuzzy input.The results of this study resulted in the Sugeno method of Fuzzy Interference System which can be applied at the calculation stage of the marketing performance assessment, where the value of each input variable is subject to fuzzification first.Furthermore, inference is made to the rules used and ends with the defuzzification stage in the form of calculating the score using the weighted average method.With the average weight value is in the range 41-89, and is in the good category in general, although there is a low value.
Design and Implementation of Solar Tree

The paper is related to the solar energy power generation, more specifically the paper revolves around the topic of solar tree. This paper shows how efficient and important is the solar tree for this generation. This presents how solar trees converts the solar energy into electrical energy. Sunlight irradiates daily and blasts out an enormous amount of solar energy towards the earth, the total energy that is received from the sun is more than enough for humanity to run for many years, still the received solar energy is not harnessed properly and hence there is not sufficient energy production in the world. Since solar panels are the efficient method nowadays for generating electrical energy from the solar energy, but solar panels requires lot of space to install. Hence this paper solve this problem by using solar tree that is mounting of solar panels on artificial tree..
cv

Certain owners wish to permanently relinquish those rights to a Work for the purpose of contributing to a commons of creative, cultural and scientific works ("Commons") that the public can reliably and without fear of later claims of infringement build upon, modify, incorporate in other works, reuse and redistribute as freely as possible in any form whatsoever and for any purposes, including without limitation commercial purposes. These owners may contribute to the Commons to promote the ideal of a free culture and the further production of creative, cultural and scientific works, or to gain reputation or greater distribution for their Work in part through the use and efforts of others.
Logical language of description of polynomial computing

An expansion of the term concept and, accordingly, the formula due to new operators were constructed. These extensions of the language preserve the expressiveness of S-formulas, and at the level of D0-formulas and terms, they ensure the polynomiality of algorithms for calculating the value of a term and the truth of a D0-formula.
Administrasi Keuangan

This article explains about financial administration. In this article, researchers use the literature method. financial management is an act of managing or administering finance which includes planning, implementing and recording, accountability and financial reporting. Thus, school financial management is a series of activities regulating school finance ranging from planning, bookkeeping, learning, supervision, accountability and school financial reporting.
Go the Extra Mile to Publicize Your Radiothon

Special Events GaloreVolume 19, Issue 3 p. 3-3 Articles Go the Extra Mile to Publicize Your Radiothon First published: 13 February 2019 https://doi.org/10.1002/speg.31053Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume19, Issue3March 2019Pages 3-3 RelatedInformation
Method for Measuring the Semantic-similarity of Textual Document and Web-pages

In this article, the process of semantic comparison of web pages in the global network is addressed. Comparing process is done based on set of words in text. Google Ajax Search and Yandex-API services are used to search and find web pages in global network. The local database is used for the determination of synonyms of the words. For the experiment, we took a document from Global network and its text was exchanged to synonyms and generated new document. The generated document compared with the given algorithm and it showed 90-95% similarity. The developed system with this algorithm used in Tashkent University of Information Technologies named after Muhammad Al-Khwarizmi for verifying students Graduation Qualification works for plagiarism.
Generating of Fuzzy Rule Bases with Gaussian Parameters Optimized via Fuzzy C-Mean and Ordinary Least Square

The fuzzy rule bases has a central role in the fuzzy inference system. Generating of rule bases based on input-output data pairs by using Fuzzy C-Mean clustering (FCM) requires parameters setting of the membership function (mf). In the Gaussian mf, the mean and spread parameters must be determined. The outputs of FCM clustering include the cluster center and the partition matrix of each object. The value of cluster center can be used as the center parameter, but the spread parameter is usually determined as a constant value. The research proposes a method to determine spread parameter of Gaussian mf by using Ordinary Least Square (OLS) approach with using the partition matrix as the membership degree of each object in the cluster. The magnitude of cluster centers (n) of 3, 5, and 7 are considered as FCM input to cluster the weekly price of soybeans in East Java, Indonesia on the period of January 2014 to December 2017. Based on each cluster center, the optimal spread value of a Gaussian mf is obtained via OLS. This research succeeded in getting a spread values that could approach almost perfectly each element of the partition matrix
Administrasi Sarana dan Prasarana

Administration of educational facilities and infrastructure is a series of activities and all components that help the effectiveness and performance to be effective and efficient in accordance with the desired educational goals. In teaching and learning activities facailities and infrastructure is needed in order to support the smooth process of its activities , so that the management of facilities and infrastructure is needed by every agency , especially schools. Besides that, the teacher plays an important role in the administration of facilities and infrastructure, such as being involved in the planning process of teaching aids, involved in the use and maintenance of teaching aids used by the teacher during the teaching and learning process, supervision in the use of practical tools by students. Facilities and infrastructure become an important part in supporting learning , because without the supporting facilities and infrastructure , the learning process cannot run optimally , therefore management of facilities and infrastructure is needed to realize effective learning.
An Incentivization Mechanism with Validator Voting Profile in Proof-of-Stake-Based Blockchain

The Proof of Stake (PoS) protocol is one of the consensus algorithms for blockchain, in which the integrity of a new block is validated according to voting by nodes called validators. However, due to validator-oriented voting, voting results are likely to be false when the number of validators with wrong votes increases. In the PoS protocol, validators are motivated to vote correctly by reward and penalty mechanisms. With such mechanisms, validators who contribute to correct consensuses are rewarded, while those who vote incorrectly are penalized. In this paper, we consider an incentivization mechanism based on the voting profile of a validator, which is estimated from the voting history of the validator. In this mechanism, the stake collected due to the penalties are redistributed to validators who vote correctly, improving the incentive of validators to contribute to the system. We evaluate the performance of the proposed mechanism by computer simulations, investigating the impacts of system parameters on the estimation accuracy of the validator profile and the amount of validator's stake. Numerical results show that the proposed mechanism can estimate the voting profile of a validator accurately even when the voting profile dynamically changes. It is also shown that the proposed mechanism gives more reward to validators who vote correctly with high voting profile.
A Relative Method of Video Coding using Different Wavelets with SPIHT

Lossy or lossless data compression is needed to Bring down the storage size and greater transmission rate. Wavelet transform is one of the ideal methods used for video compression. Different types of wavelet transforms are now available. In this paper, video is compressed by different wavelets and modified version of SPIHT. Totally seven types of wavelets are used here to compress the video, MSPIHT is used as encoding technique. They are (i) Video coding using duabechies wavelet and MSPIHT (VDM) (ii) Video coding using haar wavelet and MSPIHT (VHM) (iii) video coding using bi orthogonal wavelet and MSPIHT (VBM) (iv) video coding using symlet wavelet and MSPIHT (VSM) (v) video coding using coiflet wavelet and MSPIHT (VCM) (vi) video coding using demeyer wavelet and MSPIHT (VDMM) and (vii) video coding using Mexican hat wavelet and MSPIHT (VMHM). Then we calculate the PSNR and compression ratio for knowing the performance of the system.
Encoding Circuit, Entropy and Error Correction

&lt;p&gt;This paper considers the entropy perspective on the problem of noise in the circuit where the quantum data is prepared before it is sent forward to the error correction encoder. Since the errors in the circuits before the data qubits are converted to logical qubits cannot be corrected, there will be residual qubit errors in the processing system. This constitutes a great challenge for developing useful, scalable quantum computers. &lt;/p&gt;
Handwriting Quality Analysis using Online-Offline Models

This work is part of an innovative e-learning project allowing the development of an advanced digital educational tool that provides feedback during the process of learning handwriting for young school children (three to eight years old). In this paper, we describe a new method for children handwriting quality analysis. It automatically detects mistakes, gives real-time on-line feedback for children’s writing, and helps teachers comprehend and evaluate children’s writing skills. The proposed method adjudges five main criteria: shape, direction, stroke order, position respect to the reference lines, and kinematics of the trace. It analyzes the handwriting quality and automatically gives feedback based on the combination of three extracted models: Beta-Elliptic Model (BEM) using similarity detection (SD) and dissimilarity distance (DD) measure, Fourier&lt;br&gt;Descriptor Model (FDM), and perceptive Convolutional Neural Network (CNN) with Support Vector Machine (SVM) comparison engine. The originality of our work lies partly in the system architecture which apprehends complementary dynamic, geometric, and visual representation of the examined handwritten scripts and in the efficient selected features&lt;br&gt;adapted to various handwriting styles and multiple script languages such as Arabic, Latin, digits, and symbol drawing. The application offers two interactive interfaces respectively dedicated to learners, educators, experts or teachers and allows them to adapt it easily to the specificity of their disciples. The evaluation of our framework is enhanced by a database collected in Tunisia primary school with 400 children. Experimental results show the efficiency and robustness of our suggested framework that helps teachers and children by offering positive feedback throughout the handwriting learning process using tactile digital devices.&lt;br&gt;
Spectral Differential Privacy: Application to Smart Meter Data

&lt;div&gt;We present Spectral Differential Privacy (SpDP), a novel form of differential privacy designed to protect the frequency content of time series data that come from wide sense stationary stochastic processes. This notion is motivated by privacy needs in applications with time series data over unbounded time, such as smart meters. First, a notion of differential privacy on the space of (discretized) spectral densities is introduced. A Gaussian-like mechanism for SpDP is then presented that provides differential privacy to the spectral density. Next, a novel streaming implementation is developed to enable real-time use of the proposed mechanism. The privacy guarantee provided by SpDP is independent of the time duration over which data is collected or shared. In contrast, time-domain trajectory-level differential privacy (TrDP) will require noise with large variance to provide privacy over an extended time duration. The technique is numerically evaluated using smart meter data from a single home to compare the utility of SpDP to that of time-domain trajectory-level differential privacy. The noise added by SpDP is substantially smaller than that added by time-domain TrDP, particularly when privacy over long time horizons is sought by TrDP.&lt;/div&gt;
The effectiveness of using Mind Mapping Technique to improve students’ reading comprehension in the Narrative Text

Abstract. The objectives of this research were to investigate if there was an improvement in students’ reading comprehension and to find out students’ attitudes toward the implementation of the mind mapping technique for teaching reading comprehension. The samples of this research were 30 students of first-year students of SMAN 1 Natar. The data were obtained through a pre-test and post-test in which the results were analyzed by using Paired Sample T-Test. The results of the research showed that there was a significant improvement in students’ reading comprehension since the t-value was 9.253 with the significance level of 0.00 and the student's attitude toward the implementation of the technique was positive. It can be concluded that the mind mapping technique enables students to improve their reading comprehension and they have a positive attitude toward the use of the strategy for teaching reading. Keywords: mind mapping technique, reading comprehension, students’ attitude
Star Topology Convolution for Graph Representation Learning

&lt;p&gt;We present a novel graph convolutional method called star topology convolution (STC). This method makes graph convolution more similar to conventional convolutional neural networks (CNNs) in Euclidean feature spaces. STC learns subgraphs which have a star topology rather than learning a fixed graph like most spectral methods. Due to the properties of a star topology, STC is graph-scale free (without a fixed graph size constraint). It has fewer parameters in its convolutional filter and is inductive, so it is more flexible and can be applied to large and evolving graphs. The convolutional filter is learnable and localized, similar to CNNs in Euclidean feature spaces, and can share weights across graphs. To test the method, STC was compared with state-of-the-art graph convolutional methods in a supervised learning setting on nine node properties prediction benchmark datasets: Cora, Citeseer, Pubmed, PPI, Arxiv, MAG, ACM, DBLP, and IMDB. The experimental results showed that STC achieved state-of-the-art performance on all these datasets and maintained good robustness. In an essential protein identification task, STC outperformed state-of-the-art essential protein identification methods. An application of using pretrained STC as the embedding for feature extraction of some downstream classification tasks was introduced. The experimental results showed that STC can share weights across different graphs and be used as the embedding to improve the performance of downstream tasks.&lt;/p&gt;
Sentiment Analysis of Online Product Reviews Using DLMNN and Future Prediction of Online Product Using IANFIS

Abstract Sentiment analysis or opinion mining is one of the major tasks of NLP (Natural Language Processing). It captures the user’s opinion, feelings, and belief regarding the respective product especially to determine whether the user’s attitude is positive, negative, or neutral. This analysis greatly helps the companies to make necessary changes in their product which in return can overcome the flaws that the product is facing and targets better customer satisfaction. Existing techniques for the sentiment analysis of online product reviews obtained low accuracy and also took more time for training. To overcome such issues in this paper, a DLMNN is proposed for sentiment analysis of online product review and IANFIS is proposed for future prediction of online product. Here, the sentiment analysis and future predictions are done on the products taken from the food review dataset. First, from the dataset, the data values are partitioned into GB, CB, and CLB scenarios and then the review analysis for each scenario is performed separately using DLMNN and they give the result as positive, negative, and neutral reviews for the product. After the process of review classification based on these three scenarios, the future prediction of the products is done by performing weighting factor and classification using IANFIS. Experimental results are compared with some existing techniques and the results show that the proposed method outperforms other existing algorithms.
A quality of experience-aware cross-layer architecture for optimizing video streaming services

The popularity of the video services on the Internet has evolved various mechanisms that target the Quality of Experience (QoE) optimization of video traffic. The video quality has been enhanced through adapting the sending bitrates. However, rate adaptation alone is not sufficient for maintaining a good video QoE when congestion occurs. This paper presents a cross-layer architecture for video streaming that is QoE-aware. It combines adaptation capabilities of video applications and QoE-aware admission control to optimize the trade-off relationship between QoE and the number of admitted sessions. Simulation results showed the efficiency of the proposed architecture in terms of QoE and number of sessions compared to two other architectures (adaptive architecture and non-adaptive architecture ).
Privacy Risks and Security Practices in Digital Technologies

Digital Technologies are getting worldwide popular. People are bounded with emerging technologies to make their life faster and smarter. Business organizations over the world taking this as an opportunity to launch more digital products to cover people. Users not aware of the importance of their private data. But the others know how to make use of it in favor of them. People need to be conscious and tailored to life in the digital age. This paper reveals the technical loop holes in variety of current digital applications that are familiar among the people. The aim is to create awareness among the people on security practices to safeguard from digital attacks.
SEEM: A Scalable Visualization for Comparing Multiple Large Sets of Attributes for Malware Analysis

Recently, the number of observed malware samples has rapidly increased, expanding the workload for malware analysts. Most of these samples are not truly unique, but are related through shared attributes. Identifying these attributes can enable analysts to reuse analysis and reduce their workload. Visualizing malware attributes as sets could enable analysts to better understand the similarities and differences between malware. However, existing set visualizations have difficulty displaying hundreds of sets with thousands of elements, and are not designed to compare different types of elements between sets, such as the imported DLLs and callback domains across malware samples. Such analysis might help analysts, for example, to understand if a group of malware samples are behaviorally different or merely changing where they send data.To support comparisons between malware samples’ attributes we developed the Similarity Evidence Explorer for Malware (SEEM), a scalable visualization tool for simultaneously comparing a large corpus of malware across multiple sets of attributes (such as the sets of printable strings and function calls). SEEM’s novel design breaks down malware attributes into sets of meaningful categories to compare across malware samples, and further incorporates set comparison overviews and dynamic filtering to allow SEEM to scale to hundreds of malware samples while still allowing analysts to compare thousands of attributes between samples. We demonstrate how to use SEEM by analyzing a malware sample from the Mandiant APT1 New York Times intrusion dataset. Furthermore, we describe a user study with five cyber security researchers who used SEEM to rapidly and successfully gain insight into malware after only 15 minutes of training.