Reviewerly/exHarmony huggingface dataset:
Analysis of the Resolution in Basic Health Units in the City of Curitiba Using Data Mining

The E-Saúde system manages data related to the health care provided to patients in the public health system in the city of Curitiba. We applied data mining in the public database derived from E-Saúde, in order to identify attributes that determine the resolution prescribed by physicians working in Basic Health Units, specifically with regard to the quantity of laboratory tests requested and referrals to specialized care. For this, the decision tree classification algorithms of rule generators were applied on the 15 thousand records generated during one month in one of the sanitary districts of the city. The decision tree algorithm used was J48, which displays the nodes with the weights of the predictive attributes. The rule generator algorithm used, the JRip, displays sets of rules that can be easily interpreted allowing basic unit managers to monitor and determine the training and recycling needs of the professionals working in their units.
A Re-look into the Information in Multimedia Design and Animation Theme Presentation

Human factors and ergonomics involves the “fit” amongst the user, tools, and surroundings is to take into account the user’s abilities and limits that can be used to look for, to confirm that jobs, purposes, information, and the surroundings that can be the fit that a user can be provided with. An experience of hand rendering was used effectively, using the final frame of the hand render, to be used to design a moving visual. The frames used to design a moving visual through a stop-motion animation technique showing the abstract display of the refinement in the design. The design student learns the fineness of the technique to communicate imaginative exquisiteness. The procedure was used to bring the behind the scene technique forward, such that it is useful for users to assume the technique after inputs of their peers, such as to allow students’ to imagine and enrich to provide an experience.
A multi Ability CP-ABE access control scheme for public cloud storage

Abstract The main personality of the cryptography structure based on communication with writings of stable figures and private keys [1-4]. Our development is a key encapsulation mechanism (KEM), so long messages can be coded under a short symmetric key. In our response, the writings of the figures and the private keys have stable dimensions and the people in general are directly in the maximum estimate of s. Furthermore, in our plan, the private key generator (PKG) can potentially include new people without modifying the already widespread data (as in the EIB’s plans). We also note that there is no chain of importance between the characters, despite HIBE. The income of the general population is directed at the maximum size of S, and not in the amount of decoding keys that can be transmitted, which is the amount of conceivable characters. In this case, use a simple situation to find out about the group classification and main administration test problems. Think about a source that sends information to a provision of beneficiaries in a multicast session. Session security is supervised by two principles of useful substances: a Group Controller (GC) responsible for confirmation, approval and control and a Key Server (KS). To ensure classification in the middle of the multicast session, the sender (source) shares a mysterious symmetric key with all the individuals in the legitimate collection, called the Traffic Encryption Key (TEK). To multicast a mysterious message, the source encodes the message with the TEK using a symmetric encryption calculation. From previous documents, we look at how to share protected information in the cloud without losing keys. In this article, we present a new digital brand, an SSH key, hash functionality, and major escrow calculations.
AL4LA: Active Learning for Text Labeling Based on Paragraph Vectors

Nowadays, despite the huge amount of digitized information, the biggest drawback to use machine learning in text mining is the lack of availability of a set of tagged data due to mainly, that it requires a great user effort that it is not always viable. In this paper, with the aim of reducing the great workload required to manually processing the contents of large volumes of documents, we present a methodology based on probabilistic inference and active learning to label documents in Spanish using a semi-supervised approach. First, a vector representation of the documents is generated, and then an interactive learning process to apply both, automatic and manual labeling is proposed. To evaluate the accuracy of the predictions and the efficiency of the methodology, different configurations regarding the automatic and manual labeling processes have been studied. The proposed methodology reduces the need for a large corpus of manually labeled texts by introducing a self-labeling process during training. We have shown that both tagging approaches can be combined maintaining accuracy and reducing user intervention.
A Personalized Blood Pressure Prediction Model Using Recurrent Kernel Extreme Reservoir Machine

Hypertension is becoming a global epidemic for the developing world and continuous blood pressure monitoring and early diagnosis is vital for the prevention of this disease. However, in real life, patients are usually unable to maintain frequent monitoring because of reasons that include forgetfulness, human error and/or machine error. This paper presents a personalized prediction model for blood pressure using Recurrent Kernel Extreme Reservoir Machine (RKERM). This technique combines reservoir computing with RKELM to perform multistep ahead prediction. We use RKERM for blood pressure prediction and its performance is evaluated with other ELM based prediction algorithms. To evaluate our model, we use real world blood pressure data collected from Malaysian population consisting of hypertensive and non-hypertensive patients. The experimental results show that the proposed prediction mechanism has higher prediction accuracy than existing ELM methods.
Calmness in Virtual Environments Enhance User’s Spatial Presence Experience

Presence has been described to be crucial in several virtual reality (VR) applications.Among the factors influencing presence, realistic virtual environment has been examined extensively from the angle of geometry-based virtual reality (GBVR) application.The visual of the applications has been manipulated by altering numerous technological characteristics or by adding more sensory information (such as touch and smell).However, realistic virtual environment in GBVR application often required complex programming and takes longer time to develop.As such GBVR application is not acceptable for the application that needs to have a collection of realistic panoramic virtual environments.An alternative solution for above statement is image-based virtual reality (IBVR) application.IBVR refers to photo-based images, stitched together to develop a realistic panoramic virtual environment.Based on this method, many realistic virtual environments can be created in much less time but with limited interaction function.Despite this limitation, realistic virtual environment in image-based virtual reality is expected to enhance user's spatial presence experience, which is supported by spatial presence theoretical model.There a few levels in this theoretical model before the formation of spatial presence, and the most important part in this theoretical model is primary egocentric reference frames (PERF), adapting calmness to produce spatial presence experience.Thus, this chapter describes the summary on adapting calmness as PERF.
Mining Specific Content Search using Clustering Algorithm

Abstract Overdue problems in information recovery are diagnosed with records in casual corporations and wealthy media content fabric. inside the ones cases, the substance is associated with multilingual, purchaser created views and substance, adaptability, strength and flexibility to mistakes. The graphical model learns is possibly a hopeful term is to be an difficulty term simply as how likely phrases are to be assembled collectively in an inquiry function, and catches the situations among the two elements. Proposed framework upgraded the past work to live faraway from duplication of comparative internet site on line via way of net page parsing and examination of web web page content material fabric. We suggest a bunching calculation is correctly have an effect on the two wonders to therefore mine the foremost subtopics of questions wherein each subtopic is spoken to via a set containing diverse URLs and key terms.moreover brief and gifted ordering and looking administrations are required, for you to scale advanced substance dissemination and video on interest, in which excellent degree of inquiries and substance related errands are done via customers. to assess the span of a hid database, on instinctive concept is to perform topple checking out.
A Real Time Approach for Detecting Mobile Malicious WebPages

Abstract Transportable specific web page pages comparison altogether from their work place partners in substance, format and usefulness. Likewise, current processes to apprehend malevolent websites are possibly no longer going to work for such pages. In this paper, we structure and actualize kayo, a machine that acknowledges pernicious and amiable portable webpage. we makes this warranty dependent on static highlights of a website web page going from the amount of iframes to the nearness of found out deceitful Smartphone numbers. Within the first vicinity, we tentatively display the requirement for transportable express structures and in a while recognize a scope of recent static highlights that profoundly relate with flexible malignant WebPages. We then observe to a dataset of extra than 350,000 known favorable and noxious versatile web page pages and showcase 90% precision in characterization. Additionally, we find, describe and document numerous internet site pages missed through Google secure browsing and virus general subsequently, we construct a application augmentation utilizing to defend clients from pernicious flexible web sites steadily. In doing as such, we give the primary static investigation strategy to differentiate malevolent transportable pages.
Use of amplified expenditure expenses using the calculation services scheme

Abstract An information analyst can study the ability of social achievement according to countless user site records by evaluating multiple circular range queries. More specifically, the zeros of the previous search, especially dealing with system comparisons or encrypting command-saving files, can be expanded and exploited to allow exploration of spatial data between axes and rectangular parallels. While most search file encryption schemes focus on common SQL queries, for example, keyword queries and logical queries, two searches have been achieved in particular from the search for geometric range to encrypted spatial data. Our main contribution to the fact that our design is in fact a general approach, can support several types of to the axis. With the rapid development of social systems and location-based services and travel using a laptop, the amount of data that people create every day continues to grow dramatically. It is no longer easy or profitable for companies to keep a large amount of data in their area. More specifically, it lacks a general approach, which can accept various types of engineering queries on a large scale in encrypted spatial data, regardless of their specific geometric shapes. Our design has great potential for use and application in large applications, for example, location-based services and spatial databases, requiring the use of sensitive spatial data based on robust privacy.
Protected and Flexible Multi-Keyword Score Search model over Encoded Cloud Data

Abstract Disbursed computing is contemporary innovation as any other processing model in wide variety of business organization areas. Expansive portions of sizeable scale divisions are startingto pass the information on to the cloud situation. With the benefit of functionality as an management numerous undertakings are shifting their worthwhile facts to the cloud, since it costs much less, correctly adaptable and may be gotten to from anywhere on every occasion. advanced dynamic multi-watchword positioning inquiry plot with fine key by the use of encoded cloud records that all the whilst underpins dynamic refresh responsibilities as erasing and embeddings information. eager profundity first experiment calculation is accommodated effectiveness multi catchphrases on spot and listing shape. Cryptography is one of the building up believe fashions. on hand protection is a cryptographic technique to provide protection. In variety of scientists have been taking a shot at growing protection and effective on hand encryptiontypes. We take new possible cryptographic techniques relying on statistics structures like CRSA and BTree to improve the size of safety. We advise new multi-watchword are in search of for inquiry over encoded cloud records in recovering nice okay scored files.The vector area model and TFIDF display are applied to carry collectively document and question age. This paper facilities spherical multi catchphrase are looking for dependent on positioning over an encoded cloud facts. The pursuit utilizes the element of evaluation and internal item closeness coordinating. We advocate to assist the super ok Multi-full-content material search for safety and execution examination show off that the proposed model guarantees a immoderate health and not unusual sense and dynamic refresh activities, for example, erasing and such as files. The exploratory results show that the overhead in calculation and correspondence is low.
Reconstructing Objects from Noisy Images at Low Resolution

We study the problem of reconstructing small objects from their low-resolution images, by modelling them as r-regular objects. Previous work shows how the boundary constraints imposed by r-regularity allows bounds on estimation error for noise-free images. In order to utilize this for noisy images, this paper presents a graph-based framework for reconstructing noise-free images from noisy ones. We provide an optimal, but potentially computationally demanding algorithm, as well as a greedy heuristic for reconstructing noise-free images of r-regular objects from images with noise.
Machine Learning Approach for Face Recognition from 3D Models Generated by Multiple 2D Angular Images

We propose a machine learning approach for face recognition from 3D models generated by multiple 2D angular images that recognizes faces from multiple angle of a 3D face model. The proposed system uses SFM algorithm with SIFT detector, Approximate Nearest Neighbors (ANN) algorithm and RANSAC algorithm to reconstruct 3D from multiple RGB images. Again, it includes AdaBoost Learning algorithm that is used to train model to recognize faces and we used Local Binary Pattern Histogram (LBPH) which marks the pixels of a picture. The proposed system successfully recognizes faces with a deviation angle up to 120°, (i.e., 60° left and 60° right). Additionally, it gives an accuracy of 80% to 100% depending on angular deviation of up to from 0° to 60°. Nevertheless, the rate of accuracy of our proposed system is reversely proportional to the Angular Deviation.
Artificial Speech Corpus in Japanese for Anti-spoofing Automatic Speaker Recognition

In this paper, we introduce an artificial speech corpus in Japanese designed for anti-spoofing automatic speaker recognition. This speech corpus contains the speech data which are generated by a voice conversion method and a text-to-speech synthesizer. Using this speech corpus, we conduct speaker recognition experiments. Experimental results show that it is possible to spoof the automatic speaker recognizer using the artificial speech. Especially, it is difficult to distinguish the synthesis speech from the genuine speech compared with the voice conversion speech.
Performance study of cloud computing for scientific applications

Abstract I propose the primary visualization of the cost estimate to evaluate the costs of the cloud database in simple and codified cases from the point of view of an occupant in a intermediate term period. Consider the variability of cloud costs and the chances that the database workload will vary in the evaluation time frame. The proposed model is instantiated in relation to some offers of cloud service providers and related authentic costs. Obviously, adaptable encryption affects the costs recognized with the capacity size and system usage of a database advantage.
Sparse Least Squares Support Vector Machines Based on Genetic Algorithms: A Feature Selection Approach

This paper presents a new approach for pruning dataset features (i.e., feature selection) based on genetic algorithms (GAs) and sparse least squares support vector machines (LSSVM) for classification tasks. LSSVM is a modified version of standard Support Vector Machine (SVM), which is in general faster to train than SVM since the training process of SVM requires the solution of a quadratic programming problem while the LSSVM demands only the solution of a linear equation system. GAs are applied to solve optimization problems without the assumption of linearity, differentiability, continuity or convexity of the objective function. There are some works where GAs and LSSVM work together, however, mostly to find the LSSVM kernel and/or classifier parameters. Nevertheless, our new proposal combines LSSVM and GAs for achieving sparse models, in which each support vector has just a few features in a feature selection sense. The idea behind our proposal is to remove non-relevant features from the patterns by using GAs. Removing a pattern has less impact than removing a feature since the training dataset has in general more patterns than features. On the basis of the results, our proposal leaves non-relevant features out of the set of features and still maintains or even improves the classification accuracy.
Customer Critique Analysis System for PT. KCI’s Twitter

Abstract Commuter Line is one of the main choices for users of public transport in Jakarta. Commuter Line in Indonesia is managed by PT. Kereta Commuter Indonesia (PT. KCI). PT. KCI has an official Twitter account @CommuterLine. The purpose of this research was built Customer Critique Analysis System for Twitter PT. Kereta Commuter Indonesia using Support Vector Machine (SVM). The software engineering method used in this research is Component-Based Software Engineering (CBSE). Applications built in this research uses some components/libraries, which are Tweetsharp, LibSVM, Metronic, Kendo UI and JQCloud. The results of this research is a useful analytics application to perform grabbing and tweet data analysis from Twitter account @CommuterLine, and a dashboard to display the results of the analysis in graphical form. The test results show that the system meets the functional and nonfunctional requirements from the user. Testing is done by installing the application on the server PT. KCI, then it was tested by user.. Non-functional testing was done by measuring application performance and usability. Performance measured is classification accuracy and running time of the program. Accuracy performance testing resulted in average sentence classification accuracy of 80.4%, and the accuracy of complaint classification type of 82.3%. The average running time is 3 minutes 25 seconds.
A Common Description and Measures for Attitude in Information Security for Organizations

Understanding employee's security behavior is required before effective security policies and training materials can be developed. The Anti-virus software, secure systems design methods, information management standards, and information systems security policies; which have been developed and implemented by many organizations; have not been successfully adopted. Information systems research is encompassing social aspects of systems research more and more in order to explain user behavior and improve technology acceptance. Theory of planned behavior (TPB) based on attitude, subjective norm, and perceived behavioral control constructs, considers intentions as cognitive antecedents of actions or behavior. This study reviews various research on attitude and finds the most common measures for attitude, which can be used in organizations to develop a method to influence employees' attitude positively with the goal of inducing positive security behavior. Further, a conceptual model for operationalizing the obtained measures for enhancing information security in organizations is presented.
Effect of an Optical Coating on In-Band and Out-of-Band Transmittance Wavefront Error Measurements

The Transmitted Wavefront Error (TWE) of an optical filter can be significantly different at the in-band and out-of-band wavelengths. TWE measurements and a method of predicting the inband TWE of an optical filter are presented.
Pirated Content Blocking and Copyright Protection on the Internet

Purpose of reseach. The study is aimed at identifying the types of liability for copyrights and related rights infringement as well as. distinguishing the key feature of the product, thanks to which the object can be registered as a result of the intellectual activity of a particular author. The peculiar features of patent law are emphasised. Methods. The article proposes a method and an algorithm for making decisions concerning blocking websites which takes into account the peculiarities of copyright infringement in Russia. The authors also propose ways to eliminate such violations: first, it is necessary to clearly define the terms used in the copyright law; secondly, it is important to protect the results of intellectual activity by the state; and, thirdly, it is appropriate to block and / or impose temporary bans on websites that violate legislation. Results. The analysis of the existing system of copyright showed the following shortcomings in the Copyright Law: - Unclear definition of the concept of ‘information mediator’; unjustified application of the law to bona fide owners of websites and webpages on the Internet; - There are no sanctions against such results of intellectual activities as photographs and trademarks in the legislation, which discriminate right holders and opens up wide possibilities for illegal activities of offenders; - The process of detecting ‘pirated’ products and website blocking is time consuming and too complicated; - Foreign citizens are ‘beyond Russian Copyright Law’, their punishments are not regulated by Russian legislation. Conclusion. Copyright Law was introduced in the Russian Federation not so long ago, therefore there are some shortcomings and inaccuracies in it, but all of them can be amended. Such a rapid development of information technology makes it more difficult to follow the changes; fraudsters invent more sophisticated ways of making a profit at the expense of other people’s products, which should be immediately prevented.
Alternative Nonvisual Web Browsing Techniques

People with vision impairments typically use screen readers to browse the Web. To facilitate nonvisual browsing, web sites must be made accessible to screen readers, i.e., all the visible elements in the web site must be readable by the screen reader. But even if web sites are accessible screen reader users may not find them easy to use and/or easy to navigate. For example, locating the desired information may require a tedious linear search of the webpage that involves listening to a lot of irrelevant content. These issues go beyond web accessibility and directly impact web usability. Several techniques have been reported in the accessibility literature for making Web usable for screen reading. This chapter is a review of these techniques.