Reviewerly/exHarmony huggingface dataset:
Intelligent Data Selection in Autonomous Robot Movement

Autonomous mobile robots have been discovering recently a wide range of applications in various areas of human activities. A robot uses many data sources (sensors) to recognize its current situation, including video, inertial, acoustic, mechanical stress. The data flows from such sources are redundant, error prone, delivered with a rather high rate, and contain considerable information as for the ongoing events so present measurement noise, errors and insignificant data about minor fluctuations of the environment and the device. They present a source information for the inference modules such as navigation, localization, path planning, scheduling etc. The total number of the ongoing events can be large. They have different importance for the movement control. In this paper, we consider a method for intelligent data selection. The method is based on the Additive Increase Multiplicative Decrease (AIMD) algorithm. The effect is in filtering the most significant information to forward to the robot movement control.
Game Edukasi Math & Trash Berbasis Android dengan Menggunakan Scirra Construct 2 dan Adobe Phonegap

Educational games can be used as an effective learning method, especially for children, because children can gainknowledge in a fun way. Here the game is designed for young children to practice arithmetic and knowledge to separateorganic and inorganic wastes. This game is based on Android using Construct 2 software, design using UML and GameDevelopment Life Cycle (GDLC). At the end of the manufacturing process, software tests or tests consist of unit tests,integration tests and system tests. From the test results, the game Math & Trash can be run on several versions of Androidwith a variety of different screen sizes. The educational game Math & Trash is expected to have a positive impact onchildren on the importance of math subjects and the importance of protecting the surrounding environment.
Rating of Various Indian Airlines on various parameters using Twitter Data

Abstract In today’s world, e-commerce markets runs on the sentiments of the customers as they provides real feedback of the products or services. In such scenario, the companies tries to collect data from different social media platform like instagram, Facebook, twitter, and other sites where customers places their reviews and feedback about their experience on various parameters. These organizations analyze these data as per their requirements for market analysis, recommendation systems, feedback of the product/service, sentimental analysis etc. In this proposed work, feedback/reviews of various Indian airlines like Air-India, Indigo, Go-Air, Jet airways, Spice-Jet.is collected from twitter to rate the airlines services on various parameters like food quality, staff, delay in time, turbulence, aircraft condition and value for money parameters.
Computational Reconstruction of the Human Nasal Airway

Reconstructing the human airways begins with image acquisition which involves the procurement of medical images typically from computed tomography (CT) or magnetic resonance (MR) imaging. This produces a 3D matrix of a series of 2D cross-sections, that contains information about tissues and anatomic structures. Reconstructing the airway from the medical scans involves segmentation of the region of interest. The segmentation step extracts a contiguous airway region which is ready for 3D model processing. This chapter discusses CT and MR scan imaging, followed by some common segmentation algorithms based on thresholding, edge detection, and region characteristics.
The Effect of Using Free Writing Technique on Students’ Writing Recount Text Ability in An Islamic Boarding School

This study aims to find out whether there is a significant effect of using free writing technique on students’ ability in writing recount text. It was carried out in the design of quasi-experimental research. The sample of this research was tenth-grade EFL students which were divided into control class and experimental class. Each class was provided with pre-test, treatment, and post-test. In collecting the data the researcher used writing test to measure the students’ ability to write recount text. Two professional raters were involved to score the students’ writings. The collected data were analyzed through T-test formula. Based on the findings, it can be concluded that the students’ ability in writing recount text is significantly improved after being taught by using free writing technique. Thus, teaching EFL students by using free writing technique is one of the solutions for the English teachers who want to improve their students’ ability in writing, especially for recount genre.
Attention-Based End-to-End Named Entity Recognition from Speech

Named entities are heavily used in the field of spoken language understanding, which uses speech as an input. The standard way of doing named entity recognition from speech involves a pipeline of two systems, where first the automatic speech recognition system generates the transcripts, and then the named entity recognition system produces the named entity tags from the transcripts. In such cases, automatic speech recognition and named entity recognition systems are trained independently, resulting in the automatic speech recognition branch not being optimized for named entity recognition and vice versa. In this paper, we propose two attention-based approaches for extracting named entities from speech in an end-to-end manner, that show promising results. We compare both attention-based approaches on Finnish, Swedish, and English data sets, underlining their strengths and weaknesses.
Enhanced Privacy With Disrupted Data By Choosing Features

Privacy shows a key role in data mining applications. This has sparked the expansion of several data mining procedures to protect privacy. In order to facilitate the preservation of privacy in data mining algorithms over generally consist of together horizontal and vertical data Collection, a variety of procedures have been recommended using SMC and different protected structure blocks. Earlier work concentration on maintaining privacy by adjusting a separately adaptable disruption perfect that allows persons to select their individual degree of secrecy. The weakness, however, is that the computational findings for privacy are not adequately discovered. This paper suggested the collection of privacy features in a multi-partitioned dataset. Information can be wrapped for confidentiality by disruptive method as a alias name. In a multi-stakeholder data assessment, the arrangement of data and the collection of features for the data mining conclusion model that builds the fundamental model evidence popular this paper are established. The aim of the improvement ratio technique used in this work is to improve privacy in a multi-part data collection. Not completely features need the security of sensitive data for the top classical. Documents Representation for Privacy Protection Data Mining has occupied measures to improve techniques to create the best classical without breaking the confidentiality of characters. An investigational assessment is performed to evaluation the efficiency of the future Enhanced Privacy with Disrupted Data by Choosing Features [EPDDCS] in multi-partitioned datasets proved by various experimentations on together simulated and actual datasets.
Using an Experimental Framework to Support Variables Selection: An Exploratory Study

The selection of variables in a given experiment is crucial, since it is the theoretical foundation that guides how data should be collected and analyzed. However, selecting variables is an intricate activity, especially considering areas such as Software Engineering and Education, whose studies should also consider human-related variables in the design. In this scenario, we aim to investigate how a support mechanism helps in the variables selection activity of the experiment process. To do so, we conducted a preliminary study on the use of an experimental framework composed of a catalog of variables. We explored the domain of the integration of software testing into programming education. Participants were divided into two groups (ad hoc and framework support) and asked to select variables for a given experiment goal. We analyzed the results by identifying threats to validity in their experimental design drafts. Results show a significant number of threats of type inadequate explication of constructs for both groups. Nonetheless, the framework helped to increase the clarity of concepts selected as variables. The cause of most raised threats, even with the framework support, was an inaccuracy in selecting the values of such variables (i.e. treatments and fixed values).
The scientific and poetic creativity: knowledge in the culture

This article describes the role of apperception and imagination (scientific and poetic) in scientific and poetic creativity in order to compare with each other. It demonstrates the importance of imagination for scientific creativity and highlights typological features of ideal objects (according to V.S. Stepin) that are common to scientific ideal objects and poetic images. The article discusses the concept of scientific and poetic meaningfulness and scientific and poetic meanings. According to the definition of N.M. Smirnova creativity is understood as the process of creation of new cultural meanings. The scientific imagination is analyzed as a necessary factor of scientific activity. The role of imagination in the apperception of the results of scientific and poetic creativity is demonstrated. It’s shown that in term of phenomenology, human culture appears as the horizon where the meanings circulate as ideal objects of culture. Special attention is paid to the concepts of intersubjectivity of scientific and poetic contents. The reasons and the sources of special reliability of scientific and poetic knowledge are presented. Poetic creativity is considered as a kind of spiritual activity that has cognitive meaning. It’s demonstrated that poetic creativity as well as scientific one has its own object and subject. From this perspective the analysis of poetic seems heuristic for theory of knowledge.
Research on the Boundary Identification Method of Concealed Geological Bodies Based on Non-seismic Geophysical Data—— Taking Benxi-Xiuyan Area as an Example

In the process of deep geological structure research, gravity and aeromagnetic anomaly data are often used to invert the distribution law of concealed geological bodies. In order to reveal the boundaries of concealed geological bodies and divide structural divisions, this paper adopts fuzzy control simulated annealing genetic algorithm () to superimpose the gravity and aeromagnetic anomaly data in Benxi-Xiuyan area and classify the patterns, and identify the main geological body boundaries and fractures. Comparing the relationship with known geological maps, the two have a higher degree of matching. Experiments show that the application of SAGAFcm algorithm can quickly identify the boundaries of concealed geological bodies and provide a new means for field geological mapping.
Visualizing Prediction Correctness of Eye Tracking Classifiers

Eye tracking data is often used to train machine learning algorithms for classification tasks. The main indicator of performance for such classifiers is typically their prediction accuracy. However, this number does not reveal any information about the specific intrinsic workings of the classifier. In this paper we introduce novel visualization methods which are able to provide such information. We introduce the Prediction Correctness Value (PCV). It is the difference between the calculated probability for the correct class and the maximum calculated probability for any other class. Based on the PCV we present two visualizations: (1) coloring segments of eye tracking trajectories according to their PCV, thus indicating how beneficial certain parts are towards correct classification, and (2) overlaying similar information for all participants to produce a heatmap that indicates at which places fixations are particularly beneficial towards correct classification. Using these new visualizations we compare the performance of two classifiers (RF and RBFN).
Proof-directed program transformation: A functional account of efficient regular expression matching

Abstract We show how to systematically derive an efficient regular expression (regex) matcher using a variety of program transformation techniques, but very little specialized formal language and automata theory. Starting from the standard specification of the set-theoretic semantics of regular expressions, we proceed via a continuation-based backtracking matcher, to a classical, table-driven state machine. All steps of the development are supported by self-contained (and machine-verified) equational correctness proofs.
USING OF CONTENT ANALYSIS IN DEVELOPING STRATEGIC PLANNING IN THE EDUCATION

The purpose of the research is to identify the degree of knowledge of scientific publications in the planning of the activities of institutions in the field of education using quantitative methods and content analysis. Methodology – a content analysis was conducted for the main keywords in indexed international scientific publications and journals. Graphical and statistical methods of analysis are applied. The originality / value of the research is the identification of a low degree of study using the method of content analysis of international scientific publications and the use of the results in the strategic improvement of academic activities in the long term. Findings . The using of content analysis in the strategic planning of education reflected the little-studied scientific publications in the development of strategic planning. This analysis requires the need for a comprehensive study and research of this problem in the field of education. The source of the study was the data of the study and activity in the international indexed scientific articles in the journal Scopus in the field of education.
Representation Matching For Remote Quantum Computing

Many quantum computational tasks have inherent symmetries, suggesting a path to enhancing their efficiency and performance. Exploiting this observation, we propose representation matching, a generic probabilistic protocol for reducing the cost of quantum computation in a quantum network. We show that the representation matching protocol is capable of reducing the communication or memory cost to almost minimum in various tasks, including remote execution of unitary gate arrays, permutation gates and unitary conjugation, as well as the storage and retrieval of unitary gates.
REyeker: Remote Eye Tracker

Eye tracking allows us to shed light on how developers read and understand source code and how that is linked to cognitive processes. However, studies with eye trackers are usually tied to a laboratory, requiring to observe participants one at a time, which is especially challenging in the current pandemic. To allow for safe and parallel observation, we present our tool REyeker, which allows researchers to observe developers remotely while they understand source code from their own computer without having to directly interact with the experimenter. The original image is blurred to distort text regions and disable legibility, requiring participants to click on areas of interest to deblur them to make them readable. While REyeker naturally can only track eye movements to a limited degree, it allows researchers to get a basic understanding of developers’ reading behavior.
Markov Model-Based Smart Home Assistance for Geriatric Care

Geriatric care is one of the most important needs in the present scenario. The location tracking of geriatric people inside the smart home has to be predicted to give a better living environment. The better living environment can ease their lifestyle and can possibly enhance their lifetime. This paper mainly discusses about the Markov-based model of presence of geriatric people inside a smart environment. The predictions were judged and this model can possibly help in making decisions to the people on their actuator. The state transition matrix is derived and its saturation at nth state is calculated. The entire scenario is simulated in MATLAB to understand the working of the proposed model.
Integration Information Systems Design of Material Planning in the Manufacturing Industry using Service Oriented Architecture

PT XYZ has an Enterprise Resource Planning application that is used by the Planning Department to view stocks and plan production materials.Currently calculation of production materials takes more than 30 seconds just to export to Excel then a few minutes to adjust the data format to the planning form and the data used is not real-time.Each item needs to be calculated one by one per period, then the size of the Excel file used varies according to the time period and requires more storage.To support real-time integration and process efficiency planning and storage reduction, an integration between Enterprise Resource Planning application and web applications has been made using a Service Oriented Architecture approach.The Web service uses RESTful and has been tested using Quality of Service and the Vulnerability Test.Based on the test results using the Jmeter simulation with 10 users, it is obtained Latency 1.2 seconds and Load Time 1.2 seconds with an average amount of data sent 1280.73 bytes.The test results using OWASP ZAP show vulnerability to the web service header made from the web server version used by PHP version 5.6.40.With the results of these tests, the web service is able to replace the export and import process as well as create real-time data connectivity and replace storage media with databases, thereby reducing the time needed for planning activities.
WITHDRAWN: The intelligent methods of novel the disappeared intersexuality

The rewrite the experiences of those who lived it, urging readers to look over the epic, tragic, and offensive facet of their history. The purpose of this study is to show how and why authors used the traumatic history of their countries as settings for their novels. By using historiographical metafiction as a device for investigating both novels; Novel without a Name 1995 and The Disappeared 2008 this study would be able to prove that these novelists re- write and re-present history by enfolding it into fiction to generate together accessibility and reasonability for recovering and reforming the history of minorities, which have been suppressed long ago. These texts can be considered as historiographic metafiction since they combine historical personage parody and metafictional self-reflexivity to present what the recorded history fails to present.
A Face Changing Animation Framework Based on Landmark Mapping

In this paper, we study on a face animation framework based on landmark mapping. We present an implementation pipeline, which can be realized and improved independently in each connecting stages. In the pre-processing phase, face image normalization is obtained, and then landmark points are notated as a series of corresponding pixel coordinates of two images. Based on the corresponding landmarks, the image morphing is adopted to realize the deformation and fusion of facial images, which involves triangulation build on landmark points, deformation of triangulation, reconstruction of face identity, and synthesis of intermediate results. Final animation is realized by a finite number of intermediate results. In our experiment, we use the image dataset containing landmarks to achieve efficient face changing animation. In the future, we will combine face detection, scaling, alignment, and landmark detection modules to further improve the efficiency of animation and the quality of image generation.
Detection of Malicious Spatial-Domain Steganography Over Noisy Channels

Steganographic channels can be abused for malicious purposes, thus raising the need to detect malicious embedded steganographic information (steganalysis). This chapter will cover the little-studied problem of steganography and steganalysis over a noisy channel, providing a detailed modeling for the special case of spatial-domain image steganography. It will approach these issues from both a theoretical and a practical point of view. After a description of spatial-domain image steganography, the impact of Gaussian noise and packet loss on the steganographic channel will be discussed. Characterization of the substitution-insertion-deletion (SID) channel parameters will be performed through experiments on a large number of images from the ALASKA database. Finally, a steganalysis technique for error-affected spatial-domain image steganography using a convolutional neural network (CNN) will be introduced, studying the relationship between different types and levels of distortions and the accuracy of malicious image detection.
The Literature Review of Teacher Exchange and Rotation Policy

This chapter involves the literature review of the teacher exchange and rotation policy. Both the study of school district system and the study on the problems and countermeasures of school district system have been explored in this chapter.
Prediction of In-Hospital Mortality from Administrative Data: A Sequential Pattern Mining Approach

Study of trajectory of care is attractive for predicting medical outcome. Models based on machine learning (ML) techniques have proven their efficiency for sequence prediction modeling compared to other models. Introducing pattern mining techniques contributed to reduce model complexity. In this respect, we explored methods for medical events’ prediction based on the extraction of sets of relevant event sequences of a national hospital discharge database. It is illustrated to predict the risk of in-hospital mortality in acute coronary syndrome (ACS). We mined sequential patterns from the French Hospital Discharge Database. We compared several predictive models using a text string distance to measure the similarity between patients’ patterns of care. We computed combinations of similarity measurements and ML models commonly used. A Support Vector Machine model coupled with edit-based distance appeared as the most effective model. Indeed discrimination ranged from 0.71 to 0.99, together with a good overall accuracy. Thus, sequential patterns mining appear motivating for event prediction in medical settings as described here for ACS.
Tighter Reduction for Lattice-Based Multisignature

Multisignatures enable multiple users to sign a message interactively. Many instantiations are proposed for multisignatures, however, most of them are quantum-insecure, because these are based on the integer factoring assumption or the discrete logarithm assumption. Although there exist some constructions based on the lattice problems, which are believed to be quantum-secure, their security reductions are loose. In this paper, we aim to improve the security reduction of lattice-based multisignature schemes concerning tightness. Our basic strategy is combining the multisignature scheme proposed by El Bansarkhani and Sturm with the lattice-based signature scheme by Abdalla, Fouque, Lyubashevsky, and Tibouchi which has a tight security reduction from the Ring-LWE (Ring Learning with Errors) assumption. Our result shows that proof techniques for standard signature schemes can be applied to multisignature schemes, then we can improve the polynomial loss factor concerning the Ring-LWE assumption. Our second result is to address the problem of security proofs of existing lattice-based multisignature schemes pointed out by Damgård, Orlandi, Takahashi, and Tibouchi. We employ a new cryptographic assumption called the Rejected-Ring-LWE assumption, to complete the security proof.