Reviewerly/exHarmony huggingface dataset:
Culture And The Spiritual World Of Man

This article is the result of the study of the following problem -the role of culture in the formation and spiritual development of the individual.To assess the significance of culture, the author considers various interpretations of the "culture" concept, the nature of culture as a means of accumulation, storage, transmission of human experience, its multitasking, as well as the process of spiritual development of the individual in the triunity of "body-soul-spirit" in the cultural space.The author analyzes the humanitarian culture that contributes to the spiritual growth and perfection of the individual.The conclusion is made about the relationship between culture and spirituality: the possibility of developing and educating the spirit, soul and body at different levels of influence -spiritual, intellectual, cultural, moral, labor, physical, aesthetic, etc.An important emphasis in the article is placed on the problems of spiritual and moral guidelines of the modern generation, brought up in the conditions of digitalization of everyday life, the predominance of contactless (correspondence, network) ways of communication.At the same time, the education of universal and national cultural values is an integral part of a harmonious personality development, which is emphasized by both teachers and psychologists, and is reflected, in the state approach to education, patriotism and national identity promoted in society.General cultural humanitarian values should become the basis for the development of the spiritual world of a person, regardless of the technological structure and the prevailing norms of behavior, country, race, and religion.
Distribution Based Crowd Abnormality Detection

The complications of abnormal behavior and behavior identification are very eminent problems in the video processing. Abnormal behavior detector can be designed by choosing the region of interest through feature detector and by tracking them over the short time period. Therefore, the detector shows the trade-off among the object tracking and optical flow. Since, various regions normally display the various types of motion pattern, we introduce Distribution Based Crowd Abnormality Detection (DCAD) which catches the statistics of object trajectories which are passing via the Spatio-temporal cube. This technique directly provides the distribution to define the frame. Also clustering is not required to build the dictionary. Besides, we exploited the motion trajectories to calculate the “power potentials” in the pixel space which defines the amount of interaction among the people. Furthermore, utilize the standard method for classification by considering SVMs (Support Vector Machines) discriminative learning method to recognize the abnormalities.
Efficient user authentication, server allocation and secure data storage in cloud

With the increased popularity and the need to store the sensitive data over the cloud, the security of stored data is a very big challenge. This work has not only investigated and rectified the susceptibility of the data in the cloud, but also proposed the technique for user authentication and server allocation efficiently. Cuckoo search algorithm (CSA) is applied for efficiently allocating the server. For maintaining the privacy of client's data over the cloud, improved attribute-based encryption (IABE) can effectively do attribute adjunction/revocation, reduce the time complexity as well as safeguard from collusion attacks. The minimum set generation, proxy key generation, file updation, and secret key updation, is modified for efficient attribute revocation/adjunction. The combination of IABE with CSA achieves the security objective and the process is enhanced efficiently.
Some results on an encryption method using subset-sums of pseudo-recursive sequences

Let Aη := { 2 n η : n = 0, 1, 2, . . .}, where 1 ≤ η < 2. In the recent paper [Discrete Math.Lett. 4 (2020) 31-36], the authors examined the subset-sums of the set Aη and then presented an encryption algorithm.The basics of the latter part is that the encoded message is a public natural number N and everyone is allowed to query for the set (Aη Aη) ∩ [1, N ] until they find an element of it.Using the results about P (Aη), the set of subset-sums of Aη, it was shown that with the secret key γ the message can be decoded in logarithmic time, but for an eavesdropper without the key it takes on average more than N/log 2 N time.In this article, we show that the eavesdropper essentially can not figure out the codeword from the found element of S, even if she got that element from the query sequence in a relatively short time.
Contributions to the automatic processing of the user-generated Tunisian dialect on the social web

With the growing use of social media in the Arab world, Arabic dialects are rapidly spreading on the web, leading to a growing interest from NLP researchers. These dialects are however, still under-resourced languages which is a major obstacle to their study and processing. In this paper, we focus on the automatic processing of the user-generated Tunisian dialect (TD) on the social web and propose an approach that aids to automatically generate TD language resources. This approach exploits the large amounts of textual productions on the social web to extract and generate dialectal content. It is based on two main NLP components, namely the TD identification and the TD transliteration. A machine learning approach using conditional random fields is proposed for implementing these two components and reached an accuracy of 87.45 for the TD identification and 90.49 for the automatic generation of dialectal contents by transliteration.
Modified Salp Swarm Algorithm based Energy-Efficient Resource Allocation in Cloud-Computing Data Centers

In a cloud data centre the consolidation of the virtual machines (VMs) assist to optimize the resources need and diminish the energy consumption. In the consolidation of the VMs the VM placement acts an important role. By considering optimized energy consumption the researchers have developed various algorithms for VM placement. However, these algorithms be deficient in the exploitation mechanism use resourcefully. This paper attend to VM placement issues by offering meta-heuristic algorithms that is, the Modified Salp Swarm Algorithm (MSSA) presenting the comparative analysis relating to energy optimization. The comparison are made adjacent to the existing particle swarm optimization (PSO), and salp swarm algorithm (SSA) and the energy consumption results of all the contributing algorithms confirm that the proposed MSSA is more efficient than the other algorithms. The simulation result demonstrates that MSSA outperforms effectively than other presented approaches in optimal VM placement in cloud computing environment with maximal resource use, minimal energy consumption, minimum SLA violation and reduced migration cost.
Calibrating rhythms in L1 Japanese and Japanese accented English

Japanese and Japanese-accented English utterances produced by native Japanese speakers were classified using rhythm spectra automatically derived from the speech signals. Results of a stepwise discriminant function analysis revealed an overall classification rate of 81.9% (chance = 50%) for Japanese and 85.9% for English utterances. Two parameters extracted from the spectra emerged as the strongest predictors: normalized amplitude modulation rate above 4 Hz in the 1,000 Hz octave band frequency and normalized amplitude modulation rate between 3-6 Hz in the 4,000 Hz octave band. These results suggested that native Japanese speakers produce Japanese and English with different patterns of temporal regularities in the amplitude envelope of the speech waveform.
Against complementizers

In this paper we investigate the syntax of complement clauses in some Romance and Germanic languages by focusing on word order asymmetries and extraction phenomena. We argue that complement clauses are relative clauses, as proposed in Manzini &amp; Savoia (2003, 2011) and Kayne (2010). However, differently from the previous proposals, we claim that as in relative clauses (see Poletto &amp; Sanfelici 2018a), the ‘complementizer’ partially spells out either the nominal element internal to the relative/complement clause, resulting thus into a raising derivation of the relative/complement clause, or the external nominal modified by the relative/complement clause itself, leading to a matching derivation. This difference in the raising vs. matching derivation accounts for a series of well-known asymmetries between some Romance and Germanic languages. In addition, we show that this proposal may be suitable to derive the different extraction patterns exhibited in ‘traditional’ relative clauses and complement clauses.
An Efficient Gesture Recognition with ABC-ANN Classification and Key-Point Features Extraction for Hand Images

With the advent of an electronic device in humanization, there has been various usage of easing human-computer interface. However, novel methods and techniques have been developed for boosting the HCI interface. In the world of technology, including gestures in the human-computer interface, become a crucial exploration field. The gesture has become a communication approach with the computer interface and users. Hand Gesture works as a natural boundary for serving as an inspiring strength for investigating gesture classifications. The hand gesture is used in a wide variety of applications like as recognition technology, controlling of system, computer system, electronic device, home appliances, flying equipment controlling, and so forth. The hand gesture is described as the production of the motion or the gestures by hands; it determines the expression through a signature pattern that leads to the interface between the system and individuals. However, hand gesture plays the main role in the establishment of the novel human and system interface. In this research, a classification technique with ABC –ANN is developed to enhance the detection rate and the SIFT algorithm has been implemented to extract features of hand images. Features are described as - i) Assignment (ii) Localization (iii) Orientation and (iv) SIFT key-points. The extraction of features is done through the key point format. Along with that, classification and selection of the specific features of gesture image acquired based on categories. Experimental analysis is done based on parameter metrics (testing rate, validation rate, recognition rate) to improve the detection rate.
Location big data differential privacy dynamic partition release method

Aiming at the privacy protection requirements in real-time statistical publishing process of location big data, a dynamic partition method is proposed based on differential privacy mechanism. The temporal redundancy between adjacent data snapshots has been eliminated by sampling and differential processing of dynamic location big data, and the spatial redundancy of location big data has been reduced by adaptive density meshing and uniformity heuristic quadtree partitioning. Differential privacy protection has been realised by adjusting partition structures of the current dataset on the spatial structure of previous moment and adding Laplace noise. Experiments carried out on the cloud computing platform and real location big datasets show that the proposed algorithm can meet the dynamic partition release requirements of real-time location big data, and the query precision of single-released location big data is better than other similar methods.
The Use of Open and Distance Learning For Correctional Education: The Views of Prison Inmates of Nsawam Medium Security Prison (NMSP), Ghana.

This study explored the views of the Inmates of Nsawam Medium Security Prison (NMSP) in Ghana about using Open and Distance learning building their human resource while serving their jail terms.The study employed qualitative research methodology which made use of semi-structured interviews to collect qualitative data.Fifteen final year students of two formal education programmes in the prison were purposively selected to participate in the study.The study found among others that prisoners in NMSP possess adequate knowledge and understanding of potential benefits of ODL in equipping them with knowledge and skills they will need to live a meaningful life after prison.The inmates were also able to identify the financial and logistical support they will need to embark on a successful ODL programme.The author recommended that government should provide financial support and logistical support for effective correctional educational through ODL.
Interdisciplinary Approach As The Basis Of The Scientific And Technological Policy

The article substantiates and describes the foundations of an interdisciplinary approach, which has become a defining direction in many branches of modern science.The importance of this approach is noted as a principle that provides a comprehensive analysis of the problem and guarantees the possibility of considering the maximum number of its components.Particular attention is paid to the reflection of interdisciplinarity in modern state documents of the Russian Federation, in state strategies for the development of science and technology.The study reveals that in the conditions of globalization of the socio-economic space, interdisciplinarity becomes multidisciplinarity, linking the results of disciplinary research and allowing scientists to expand the range of their research and find new characteristics of the studied subject areas.It sums up the prospects and importance of multidisciplinary research carried out in various branches of modern Russian science.It studies the issue of the spontaneous nature of these studies and the need for further understanding of the essence and methods of multidisciplinary research.
Corpora Based Classification to Perform Sentiment Analysis in Kannada Language

In this modern era, the users’ opinions play an uncanny role in understanding how well a product has satisfied the customer requirements, so that the producer can change the product to suit the customers’ demands and these reviews also help the new consumers to decide on whether to purchase the product or not. Analysis of a particular entity's feelings in terms of positive, negative or neutral polarization is known as ‘Sentiment Analysis’. SentimentAnalysis is a sub-domain of opinion mining.Here the analysis is focused on the mining of emotions and opinions of the people towards a specific topic. The emotions and opinions are collected in the form of organized, semi-organized or amorphous data. As the world is slowly progressing towards regional languages, this article talks about extracting the opinions of a product in Kannada and performing analysis about these reviews and classifying them accordingly. The dataset or the corpus is scarce as it is not English. The limited corpus is being collected via website – https://gadgetloka.com through an API. However, extracting inclusive opinion manually from huge amorphous data would be a tedious task. An automated system called 'Sentiment Analysis or Opinion Mining' can solve this problem, which can analyze and extract the observation of the user throughout the reviews. In this classifier of review analysis, the process classifies the review via corpus, which is a huge collection of pre-defined data. The API that has been used is Python-Beautiful Soup via utf-8 text recognition method to parse Kannada characters. The reviews are converted to text sentence and each word of the sentence are broken down. Data mining task is done to find the sentiment of each word by comparing it with two stored files named as good.txt and bad.txt. Further, the analyzed result is given through text output as Positive, Negative or Neutral sentiments based on their weights.
Challenges and Difficulties in Social Media Analytics

Web 2.0 tools and the appearance of social media seem to have redefined the marketing strategy, research and practice, broadening marketing's potential.These potentials go beyond customers' information and expand on commitment and engagement levels.Since an ever-increasing part of the population makes use of social media in their day-to-day lives, social media data is being analyzed in many different disciplines.Social media produce a vast amount of measurable useful data to analysts and marketers whose goal is to monitor and analyze behavioral targeting, brand loyalty and further marketing performance indicators, rendering these data effective.Social media can serve as an effective marketing tool in business, valuable for both consumers and companies, offering a wide range of opportunities.Therefore, social media show an unprecedented increase of use inside business.Even though, understanding social media is a crucial, but not a simple procedure.The social media analytics process involves four distinct steps, data discovery, collection, preparation, and analysis.While there is a great deal of literature on the challenges and difficulties involving specific data analysis methods, there hardly exists research on the stages of data discovery, collection, and preparation.This study analyzes the Challenge and Difficulties in Social Media Analytics.
A Rule Based Stemmer

The present digital world generates enormous amount of data instantaneously. The need to effectively mine knowledge seems to be the need of the hour. Sentiment Analysis, a part of web content mining which is a subpart of web mining has gained momentum in the field of research. It analyses the opinion of variety of people all over the world. Sentiment Analysis encompasses preprocessing, feature selection, classification and sentiment prediction. Preprocessing is an important process and it deals with many techniques. Stop word removal, punctuation removal, conversion of numbers to number names are some of the basic techniques. Stemming is yet another important preprocessing technique that reduces the different words form to its root. There are basically three types of stemmers namely truncating, statistical and hybrid. The aim of this paper is to propose a rule based stemmer that is a truncating stemmer. It deals with rules for truncation and replacement. The data given as input passes through a series of rules. If the condition specified gets satisfied then the associated rule gets executed otherwise the input is checked with the next rule and the process continues further. The result of execution is stemmed words. The performance of the proposed rule based stemmer is compared with the existing stemmers under the same rule based category namely Porter and Lancaster. Various metrics have been used for evaluation. The observations reveal the fact that the proposed stemmer out performs the Porter and Lancaster stemmers in terms of correctly stemmed words factor and shows a good average conflation factor and lesser over stemming and under stemming errors.
Development of IEEE 802.11 Compliant Antenna with WLAN Mobile Multimedia Messaging Application for Emergency Communication Purposes

In emergency or disaster situations, when communications were interrupted due to damaged local network infrastructures, coordination are affected. Moreover, the deployment of specialized technologies such as satellite and shortwave communication network were found impractical. The objective of the study was first, to construct an improvised antenna that will be tested on an area with no cellular network and test the router’s operating range using it, and second, to design and develop a mobile multimedia messaging application that utilizes WLAN to send data. Results of the testing shows that improvised antenna achieved operating range of 192 meters, the range achieved 215 meters in area with no cellular network, and the application was capable of sending multimedia messages over WLAN.
Inovasi Sistem Informasi Pendaftaran Pasien Dengan Scanner Kib Dan Mesin Antrian Elektronik

Registration system at the Banjarsengon Community Health Center is still done manually starting from calling the queue number to the making of the MNH. Such a system would cause the patient registration process to be ineffective in terms of time while in the manufacture of MNH using paper material, it would not be durable or could be said to be damaged so that the writing could not be read. In addition, in looking for data on old patient visits, officers must search individual patients' names in the thick registration book. The purpose of this study is that all of the problems previously described can be resolved. The technology used in making the KIB scanner and the queue number uses RFID and sevent segment which is controlled by an Arduino microcontroller. Making the patient registration information system application using Microsoft Visual Studio 17. The results of this study are the patient registration information system with the MNH scanner and electronic queuing machine that can facilitate the registration officer in serving patients.
Blockchain Based Voting System

The Voting/Electoral system is that the backbone of Each and Every Country and Organization. The main goal of voting (in a scenario where the citizens have a right to vote) is to come up with their leader of their choice. At Present there are various voting is conducted in various methods such as Ballot Voting, E-Voting also known as Electronic Voting System, Missed Call Voting. Various problems are during Election Period as some of them include ridging votes/fake votes during election, insecure or inaccessible polling stations, inadequate materials and also inexperienced personnel.To overcome this problems we have used Blockchain Technology to make Unique ID’s for each vote.In this paper, we have tried to sort out issues faced by various voting systems.And make Voting more Secure by using various authentications.
Detection and Classification of Vehicles on Curved Roads

Detection of a vehicle is a very important aspect for traffic monitoring. It is based on the concept of moving object detection. Classifying the detected object as vehicle and class of vehicle is also having application in various application domains. This paper aims at providing an application of vehicle detection and classification concept to detect vehicles along curved roads in Indian scenarios. The main purpose is to ensure safety in such roads. Gaussian mixture model and blob analysis are the methods applied for the detection of vehicles. Morphological operations are used to eliminate noise. The moving vehicles are detected and the class of the vehicle is identified.