Reviewerly/exHarmony huggingface dataset:
TDOA Time Delay Estimation Algorithm Based on Cubic Spline Interpolation

In order to solve the fence effect caused by the fixed number of sampling points in the passive time difference positioning system in practical applications, a TDOA time delay estimation algorithm based on cubic spline interpolation is proposed. The algorithm uses cubic spline interpolation to interpolate the spectral peak curve of the cross-correlation function. While ensuring the stability and convergence, the spectral peak curve is smoother, the accuracy of the peak value is improved, and the accurate time delay estimation of the signal source is further obtained. The measured results show that the TDOA time delay estimation method based on cubic spline interpolation can solve the fence effect well and obtain the time delay estimation value accurately. This method can use the algorithm to improve the time delay estimation accuracy under the condition that the hardware sampling rate is fixed, thus reducing the dependence of passive time difference positioning on the system hardware.
Study of Disappearing ink Writings on Different Types of Documents

Disappearing inks are used in textile industry such as dressmaking crafts and as a kind of teaching material; for example, printed questions are visible and the spaces for an answer exhibit invisible disappearing ink. The answers only become visible using a coloring assistant. This research was conducted on the preparation of disappearing inks using different concentrations of thymolphthalein (Th-ph) and O-Cresolphthalein (O-Cph). The prepared inks were applied to different types of handwriting papers. It was found that the handwriting stability increased by increasing thymolphthalein (Th-ph) and O-Cresolphthalein (O-Cph), or alkali concentration. Deciphering of the faded documents was evaluated by different methods. Commercial paper C2 surfaces gave the more handwriting stability than other paper, the order of stability were C2 ≥ C1 > Azhar >Xerox > C3 >C4 > Edfo. All the faded documents were visible when treated with alkaline solution. When the faded documents surfaces are exposed to the thermal effect there is no change in all the faded documents. Disappearing inks have been used in different fields, but it may be abused in forgery and counterfeiting.
PSYCHO-PEDAGOGICAL FEATURES OF DESIGNING THE EDUCATIONAL ENVIRONMENT OF THE GYMNASIUM

The article is devoted to the problem of designing the educational environment of school in General and the question of the definition of psycho-pedagogical features of this process in particular. The article highlights the urgency of the problem, due to the need of development of scientific-methodical support of process of reforming of the General secondary education, which will allow reaching adequate quality of basic secondary education in the public schools through the creation of the effective current educational environment. The aim of the article is the emphasis on the potential aspects and factors that relate to psychological and pedagogical features of the educational process students and are influential in the design process of the educational environment of the gymnasium with the aim of improving the quality of basic education. The result is a generalidation and systematization of psychological and pedagogical features of the educational process that have potential impact on the efficiency of the design process of the educational environment of the school. Research methods are the analysis, synthesis and generalization of psycho-pedagogical features of process of designing of the educational environment of the school. The article says that the design of the educational environment can be carried out with the purpose of its creation, modernization or maintenance in a changing environment the process of reforming the education system. The project of the educational environment provides for its structural-systemic view, which shows the relationship of the main components, driven by purpose, goals and objectives of the educational process. Organizational-pedagogical bases of designing of the educational environment the article deals with the definition of structural organization and efficient use of pedagogical forms, means, methods, techniques and material-technical conditions, functional structures, designed to meet the requirements of the compulsory educational outcomes of students and the demands of subjects of the educational environment. The article focuses on the fact that a significant role in the design process of the educational environment of the gymnasium as an educational institution providing students acquire the basic level of secondary education, plays records of psycho-pedagogical features of the educational process. In particular, the effectiveness of educational activity of students depends on several key interrelated components: resources, motivation and satisfaction of the results. Their objective assessment and the trends in the formation and development will allow the most efficient design an educational environment of high school and to create the necessary conditions for the formation of student’s personality in this age period.
SINAI at SemEval-2019 Task 3: Using affective features for emotion classification in textual conversations

Detecting emotions in textual conversation is a challenging problem in absence of nonverbal cues typically associated with emotion, like facial expression or voice modulations.However, more and more users are using message platforms such as WhatsApp or telegram.For this reason, it is important to develop systems capable of understanding human emotions in textual conversations.In this paper, we carried out different systems to analyze the emotions of textual dialogue from SemEval-2019 Task 3: EmoContext for English language.Our main contribution is the integration of emotional and sentimental features in the classification using the SVM algorithm.
A Chinese Remainder Theorem Based Enhancements of Lempel-ziv-welch and Huffman Coding Image Compression

Data size minimization is the focus of data compression procedures by altering representation and reducing redundancy of information to a more effective kind. In general, lossless approach is favoured by a number of compression methods for the purpose of maintaining the content integrity of the file afterwards. The benefits of compression include saving storage space, speed up of data transmission and high quality of data. This paper observes the effectiveness of Chinese Remainder Theorem (CRT) enhancement in the implementation of Lempel-Ziv-Welch (LZW) and Huffman coding algorithms for the purpose of compressing large size images. Ten images of Yale database was used for testing. The outcomes revealed that CRT-LZW compression saved more space and speedy compression (or redundancy removal) of original images to CRT-Huffman coding by 29.78% to 14.00% respectively. In terms of compression time, CRT-LZW approach outperformed CRT-Huffman approach by 9.95 sec. to 19.15 sec. For compression ratio, CRT-LZW also outperformed CRT-Huffman coding by 0.39 db to 4.38 db, which is connected to low quality and imperceptibility of the former. Similarly, CRT-Huffman coding (28.13db) offered better quality Peak-Signal-to-Noise-Ratio (PSNR) for the reconstructed images when compared to CRT-LZW (3.54db) and (25.59db) obtained in other investigated paper.
On addition-subtraction chains of numbers with low Hamming weight

An addition chain is a sequence of integers such that every element in the sequence is the sum of two previous elements.They have been much studied, and generalized to additionsubtraction chains, Lucas chains, and Lucas addition-subtraction chains.These various chains have been useful in finding efficient exponentiation algorithms in groups.As a consequence, finding chains of minimal length is critical.The main objective of this paper is to extend results known for addition chains to addition-subtraction chains with Lucas addition-subraction as a tool to construct such minimal chains.Specifically, if we let -(n) stand for the minimal length of all the Lucas addition-subtraction chains for n, we prove | -(2n) --(n)| ≤ 1 for all integers n of Hamming weight ≤ 4. Thus, to find a minimal addition-subtraction chains for low Hamming weight integers, it suffices to only consider odd integers.
Compromiso social y político de los universitarios en la esfera digital. Usos de las redes sociales para la participación ciudadana

Anàlisi is a science journal published by the Journalism and Communication Sciences Department of the Autonomous University of Barcelona (UAB). The journal has been published by the UAB Journalism Department since 1980. Anàlisi publishes science articles in the fields of the communication sciences: journalism, advertising and public relations, audiovisual communication, internet, multimedia and similar areas, always from the social and cultural viewpoint and following the theoretical and methodological approaches of the media studies disciplines. Anàlisi will especially value articles from competitive research projects, with a clear articulation of theory and methodology, a well-defined and up-to-date theoretical framework, and proposed as a significant contribution to their subject area and field.
Implicational Logic, Relevance, and Refutability

The goal of this paper is to analyse Implicational Relevance Logic from the point of view of refutability. We also correct an inaccuracy in our paper “The RM paraconsistent refutation system” (DOI: http://dx.doi.org/10.12775/LLP.2009.005).
Convolutional Neural Networks in Predicting Missing Text in Arabic

Missing text prediction is one of the major concerns of Natural Language Processing deep learning community's attention.However, the majority of text prediction related research is performed in other languages but not Arabic.In this paper, we take a first step in training a deep learning language model on Arabic language.Our contribution is the prediction of missing text from text documents while applying Convolutional Neural Networks (CNN) on Arabic Language Models.We have built CNN-based Language Models responding to specific settings in relation with Arabic language.We have prepared our dataset of a large quantity of text documents freely downloaded from Arab World Books, Hindawi foundation, and Shamela datasets.To calculate the accuracy of prediction, we have compared documents with complete text and same documents with missing text.We realized training, validation and test steps at three different stages aiming to increase the performance of prediction.The model had been trained at first stage on documents of the same author, then at the second stage, it had been trained on documents of the same dataset, and finally, at the third stage, the model had been trained on all document confused.Steps of training, validation and test have been repeated many times by changing each time the author, dataset, and the combination author-dataset, respectively.Also we have used the technique of enlarging training data by feeding the CNN-model each time by a larger quantity of text.The model gave a high performance of Arabic text prediction using Convolutional Neural Networks with an accuracy that have reached 97.8% in best case.
Stepwise fuzzy correction of the algorithm filters of random signals

The task of estimating the information contained in random signals from various sources – meters. It is assumed that the gauges are discrete and are described, like the original process assessed, by a discrete mathematical model in the form of difference equations. As an estimation algorithm, we consider a discrete Kalman filter, which, in the general case, when mathematical models are inadequate to real processes, can give distorted information. To improve the accuracy of estimation, it is proposed to apply the integration of all possible meters with the introduction of additional a priori information using a fuzzy logic system. At the same time, it is proposed to make a transition from the obtained probability characteristics of the estimated process to the membership functions of fuzzy logic based on the output filter parameters using the normalization of the posterior probability density. This approach allows to increase the accuracy of estimation, as it takes into account additional information and its complex processing.
Implementation of a Web based Weather Monitoring Station and Data Storage System

Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA), being the country's weather bureau, is the one presently monitoring weather conditions.PAGASA has many observation sites and one is the Science Garden which is located in Agham Road, Quezon City.The present system in the Science Garden requires an observer to go to the instrument shelter to take readings and then translate it to weather parameters.Due to the different environmental conditions, readings could be affected as it is taken manually.Safety concerns also pose a threat as observers are required to take readings in the open field.An AWS was made to address such problems as it is automated.Being automated, the weather parameters are sent automatically to the observers PC via SMS.This ensures that during harsh weather conditions, the safety and well-being of the observers are taken care of.Given that technology will drive towards AWS in the future, our system could be considered as an extra node that can be deployed to any part of the country.The hardware and software components of this study include a GSM module, Sensor modules and software such as Apache Web server, MySQL Database and PHP Scripts.
A Collaborative Filtering Recommender System Model for Recommending Intervention to Improve Elderly Well-being

In improving elderly well-being nowadays, people at home or health care centre are mostly focusing on guarding and monitoring the elderly using tools, such as CCTV, robots, and other appliances that require a great deal of cost and neat fixtures to prevent damage.Elderly observations using the recommender system are found to be implemented, but only focusing on one aspect such as nutrition and health.However, it is important to give interventions to an elderly by concentrating more on the multiple aspects of successful ageing such as social, environment, health, physical, mental and other so that it can help the elderly people in achieving successful ageing as well as improving their well-being.In this paper, two recommender system models are proposed to recommend interventions for improving elderly well-being in the multiple aspects of successful ageing.These models using a Collaborative Filtering (CF) technique to recommend interventions to an elderly based on the interventions given to other elderly who have similar conditions with the user.The process of recommending interventions involves the generation of user profiles presenting the elderly conditions in multiple aspects of successful ageing.It also applying the k-Nearest Neighbor (kNN) method to find users with similar conditions and recommending interventions based on the interventions given to the similar user.The experiment is conducted to determine the performance of the proposed Collaborative Filtering (CF) recommender system and Collaborative Filtering and Profile Matching (CFS) compared to the Basic Search (BS).The results of the experiment showed that Collaborative Filtering (CF) recommender system and Collaborative Filtering and Profile Matching (CFS) outperformed Basic Search (BS) in terms of precision, recall and F1 measure.This result showed that the proposed models are efficient to recommend interventions using elderly profiles based on many aspects of successful ageing.
Exploiting the Interplay among Products for Efficient Recommendations

Recommender systems are built with the aim to reduce the cognitive load on the user.An efficient recommender system should ensure that a user spends minimal time in the process.Conversational Case-Based Recommender Systems (CCBR-RSs) depend on the feedback provided by the user to learn about the preferences of the user.Our goal is to use the feedback provided by the user effectively by exploiting the interplay among the products to build an efficient CCBR-RS.In this work, we propose two ways towards achieving that goal.In the first method, we utilize the higher order similarity and tradeoff relationship among the products to propagate the evidence obtained through user feedback.In our second method, we utilize the diversity among cases/products along with the similarity and trade-off relationship to make the best use of the feedback provided by the user.
PEMODELAN WAKTU TUNGGU PENUMPANG PADA JALUR ANGKUTAN DALAM KOTA PALU MENGGUNAKAN ALJABAR MAX-PLUS

Passenger waiting time is the time required by passengers starting from the stops until getting transport. The purpose of this research is to get the model of waiting time passengers on the freight line in the Palu city. The first step is the preparation of directed graphs based on the existring routes, then calculate the mileage and travel time using synchronization rules and power algorithm with initial vector 𝑥 = 0 obtained the value 𝑝 = 2, 𝑞 = 1 and 𝑐 = 102by using the appplication rock Scilab 5.5.2 and Map-Plus Toolbox obtained eigenvalues as the departure period of 102 and eigenvektor as the initial departure time.Keywords : Eigenvalues, Eigenvectors, Max-Plus Algebra, Waiting Time.
Abnormal Vehicle Load Identification Method Based on Genetic Algorithm and Wireless Sensor Network

Wireless sensor network refers to a group of spatially dispersed and dedicated sensors for monitoring and recording the physical conditions of the environment and organizing the collected data at a central location.The current abnormal wireless sensor network vehicle load data recognition method is more complex, which leads to low recognition rate, false alarm rate and slow recognition speed.Based on the genetic algorithm, the accurate method for abnormal wireless sensor network vehicle load data recognition is proposed.The effective feature set of abnormal vehicle load data in the wireless sensor network is constructed, to remove irrelevant features and redundant features from existing abnormal wireless sensor network vehicle load data.The abnormal wireless sensor network vehicle load data in the effective feature set are coded, to reduce the recognition time of abnormal wireless sensor network vehicle load data.The adaptive fitness function, crossover operator and mutation operator are applied to genetic algorithm, which can improve the recognition rate, reduce the false alarm rate, and realize the recognition of abnormal vehicle load data wireless sensor network.The experimental results show that the recognition rate of this method is high, the false alarm rate is low, and the time of recognition is less.
NIT_Agartala_NLP_Team at SemEval-2019 Task 6: An Ensemble Approach to Identifying and Categorizing Offensive Language in Twitter Social Media Corpora

The paper describes the systems submitted to OffensEval (SemEval 2019, Task 6) on 'Identifying and Categorizing Offensive Language in Social Media' by the 'NIT Agartala NLP Team'.A Twitter annotated dataset of 13,240 English tweets was provided by the task organizers to train the individual models, with the best results obtained using an ensemble model composed of six different classifiers.The ensemble model produced macro-averaged F 1 -scores of 0.7434, 0.7078 and 0.4853 on Subtasks A, B, and C, respectively.The paper highlights the overall low predictive nature of various linguistic features and surface level count features, as well as the limitations of a traditional machine learning approach when compared to a Deep Learning counterpart.
Multi-Objective Optimization-Based Networked Multi-Label Active Learning

Along with the fast development of network applications, network research has attracted more and more attention, where one of the most important research directions is networked multi-label classification. Based on it, unknown labels of nodes can be inferred by known labels of nodes in the neighborhood. As both the scale and complexity of networks are increasing, the problems of previously neglected system overhead are turning more and more seriously. In this article, a novel multi-objective optimization-based networked multi-label seed node selection algorithm (named as MOSS) is proposed to improve both the prediction accuracy for unknown labels of nodes from labels of seed nodes during classification and the system overhead for mining the labels of seed nodes with third parties before classification. Compared with other algorithms on several real networked data sets, MOSS algorithm not only greatly reduces the system overhead before classification but also improves the prediction accuracy during classification.
The Impact Of New Technologies On The Instructive- Educational Process

I have taken into account the current requirements for student-centered education, based on direct and indirect activities. Contemporary society is a permanent and unique challenge to education. The new technologies have produced changes in all areas, and it was expected that at some point this progress would influence the teaching-learning process, with pupils having to learn to manage an impressive number of information, analyze it, make decisions, and develop their knowledge to meet the challenges of todays technology. The existence of each individual as well as of the entire society as a whole, hence, is becoming more and more alert, becoming increasingly marked by the need for immediate knowledge, complete and correct knowledge of the surrounding reality, so that decision-making can be made firmly and competently. The use of ICT means supports the development of critical thinking and creativity and develops a critical and reflective attitude towards information. The interdisciplinary approach is replaced by innovative ideas from everyday life, where the personal footprint will be an integrated approach to learning. I consider it necessary and I am going to assume that it is necessary to apply modern technology in teaching content to classes because the pupil has to take advantage of his / her abilities to interact with them and to have the necessary educational needs for the society we live in.
Using Web-based Intelligent Tutoring Systems in Teaching Physics Subjects at Undergraduate Level

The aim of the study is to draw attention to the importance of using web-based intelligent tutoring systems (WBITS), which have emerged as a result of artificial neural networks and technological developments (communication technology), in the teaching of physics subjects.A WBITS is an intelligent tutoring system that exhibits behavior similar to that of a teacher in the traditional educational process (classroom education), offers a flexible teaching process, defined according to user preferences, and adaptable for a specific purpose.WBITSs make important contributions to distance education and classroom education processes, because they can be used online and offline.The importance of using WBITSs in teaching physics at undergraduate level was subsumed under five headings: i).Developments in technology and artificial neural networks and the interest of young people in technology have made it important to use WBITSs in undergraduate physics education.ii) The use of WBITSs has become important in following scientific developments in traditional (classroom) physics education and eliminating problems related to individual perception capacity and insufficient class hours.iii).Online (remote) access to physics subjects via WBITSs contributes to equality of opportunity in education.iv).More time can be devoted to practice and the discussion of deeper (advanced) subjects in the classroom when basic physics subjects are taught at undergraduate (university) level using WBITSs.v).Limitations in distance physics education can be reduced using WBITSs.
DIGITAL ERA OF RFID IN LIBRARY AUTOMATION

In this paper we discuss about RFID uses in library automation.What is RFID?RFID technology in Libraries.Rfid for Libraires.Rfid advantage and disadvantage.The article saying about RFID that how can we effective uses of libraries serives with RFID systm.