bluuebunny/crossref_metadata_2025 huggingface dataset:
Critical edition of texts: analyzing the editions of Toá by César Uribe Piedrahita
Authors: Carvajal Córdoba Edwin , Taborda Sánchez Juan Fernando
Published: May 2023

This text presents the philological analysis of the different editions of the novel Toá:Narraciones de Caucherías (1933) by Colombian writer César Uribe Piedrahita. This analysis is essentially based on the theory of textual criticism, which presents a derivation of a philological methodology for the execution of the critical edition of the text, which implies an edition faithful to the original or closer to the will of the writer. In this way, the analysis of the editions of Toá allowed the identification and selection of them, the exposition of their editorial characteristics and the execution of the comparison from the first edition, and then continuing with the process of textual fixation; process that finally allowed the execution of the critical edition of the novel with their respective philological variants and explanatory notes. Lastly, it is concluded that the editorial process of the five editions of the novel Toá showed inconsistencies of all kinds, inconsistencies that this critical edition aims to correct.
Stated vS. enacted beliefS: looking at pre-Service teachers’ pedagogical beliefS through classroom interaction
Authors: Fajardo Alberto
Published: May 2023

This article explores the relationship between pedagogical beliefs and classroom practice. Two Colombian pre-service primary school language teachers in the final stage of their five-year training programme were the research participants. Interview and classroom observation were the methods used, and content analysis was the analytical approach. It is argued in this study that by comparing the stated beliefs (as articulated in interviews) and enacted beliefs (as manifested in classroom interaction), it is possible to gain a fine-grained understanding of the relationship between beliefs and teaching practice. The findings suggested that while there were significant cases of coherence between beliefs and classroom action, there was also evidence of some incongruent relationships.
Translations as Sources for the Press in the Nineteenth Century: The Case of the Gaceta de Caracas
Authors: Navarro Aura
Published: May 2023

This article studies the influence of translations published in the Gaceta de Caracas during the Independence and the First Republic of Venezuela. The study consisted of three stages: 1) identification of translations; 2) comparati­ve analysis between source texts (STs) and target texts (TTs); and 3) analysis of translation strategies. As a result, English is the most translated language in the gazette, given that the majority of source texts were taken from American and British newspapers. The content of the translations is largely political; all translations are anonymous. We observed the use of summary and peri­phrasis; literal translation was also a frequently used translation technique. Notably, appropriation was utilized as a translation strategy in half of the translations. To sum up, translation in the Gaceta de Caracas contributed to the consolidation of Venezuelan independence and the creation of the First Republic of Venezuela due to the use of appropriation combined with the political purposes of the translators.

Received: 06-09-09 /Accepted: 19-11-09

How to reference this article:

Navarro, A. (2010) Las traducciones como fuentes para la prensa en el siglo XIX: el caso de la Gaceta de Caracas. Íkala 15(1), pp.15-43.
The meaning of a word cannot be expressed in one sentence: The meaning of terminology for technical communication and the translation of technical texts.
Authors: Schmitz Klaus-Dirk
Published: May 2023

This article refers to a statement of the Austrian-British philosopher Lud­wig Wittgenstein related to words and sentences. The goal is to analyze and discuss the relevance of Wittgenstein's statement for terminology work nee­ded in the framework of technical communication and technical translation. In addition to the basic concepts of terminology theory such as concept, term and object, the article concentrates on definitions as a means of con­cepts description and on criteria for the formation and selection of scientific terms. In conclusion, Wittgenstein's statement can be interpreted in diffe­rent ways. But for technical communication and translation, the definition (sentence) has to illustrate the concept behind the term (word), and transpa­rent and well motivated terms can clarify the concept without a definition.

Received: 31-03-10 / Accepted: 30-04-10

How to reference this article:

Schmitz, K.-D. (2010). Was ein Wort bedeutet, kann ein Satz nicht sagen: Zur Bedeutung der Terminologiearbeit für die Technische Kommunikation und das Fachtextübersetzen. Íkala, 15(2), pp.189-197
From terminologies to recurrent constructions: a study of specialized languages
Authors: Bocorny Maria José , Evers Aline , De Oliveira Cybele Margareth , Alencar Silva Maria Cristina
Published: May 2023

Objective: To report researches carried out by the TEXTQUIM/TEXTECC project between 2002 and 2010 about Brazilian Portuguese scientific discourse in Chemistry and Pediatrics. Methodology: By using Corpus Linguistics, we observed: a) causality expressed by verbs and connectors; b) patterns of collocation with recurrent terminologies. As translations from English into Portuguese are common, we contrasted original texts and compared data with French texts. Results: The findings show higher frequency of causal connectors than causal verbs, low frequency of PORQUE and CAUSAR, recurrent associations around typical terminologies in Brazilian texts and influence of translations from English in the causal patterns observed in the Portuguese texts. Publications were produced, as well as presentations and free on-line tools for public access of our corpora. These resources are available at www.ufrgs.br/textquim.

Received: 22-01-10 / Accepted: 09-04-10

How to reference this article:

Bocorny Finatto, M. J.; Evers, A.; De Oliveira, C. M. & Alencar Silva, M. C. (2010). From terminologies to recurrent constructions: a study of specialized languages. Íkala, 15(2), pp.223-258.
Current status of audiovisual translation in Colombia
Authors: Orrego Jefferson David , Alarcón Natalia , Olaya Claudia Lorena , Pérez Katherin
Published: May 2023

This article has two objectives: to present the general view of the current market of Audio Visual Translation (AVT) in Colombia and to highlight the importance of developing further studies in this area. The methodolo­gy used included research and reading literature related to the subject, the implementation of surveys to different groups related to AVT and subse­quent analysis. The results showed the general lack of knowledge in this discipline and the preferences for AVT modalities of the surveyed groups. It was observed that each group has a marked preference for subtitling due to specific reasons. It was concluded that Colombian translators need AVT training to meet the market demands and the importance of developing fur­ther and deeper studies focused on the development of AVT in Colombia is highlighted. Received: 17-01-2010 / Accepted: 22-10-2010 How to reference this article: Orrego, J. D., Alarcón, N., Olaya, C. L. & Pérez, K. (2010). Situación actual de la traducción audiovisual en Colombia. Íkala, 15(3), 17 – 39.
An Approach to Terminology Teaching. A Methodological Proposal Adapted to the Training Needs of Translators
Authors: Schnell Bettina , Rodríguez Nadia
Published: May 2023

The aim of this article is to provide methodological reflections about lear­ning and teaching terminology in the context of translator training. These reflections are based on the premise that the professional reality determines what we teach and how we teach, that is to say, the type of terminological and terminographic competences future translators should acquire and the training methodology we should adopt in order to develop these competen­ces. We outline the contextual framework in which terminology training for translators is situated and we address the relation between terminology and specialized translation, taking a closer look at the concept of terminological competence on the basis of Cabré's and Alcina's approaches. The article concludes with a methodological proposal focused on the learning process. Recieved: 29-01-2010 / Accepted: 28-04-2010 How to reference this article: Schnell, B. & Rodríguez, N. (2010). Aproximación a la enseñanza de la terminología. Una propuesta metodológica, adaptada a las necesidades formativas de los traductores. Íkala, 15(3), 181 – 203.
Colección Termisul: un estudio de los patrones de lenguaje jurídico, normativo y científico
Authors: Bevilacqua Cleci Regina , Ramos Reuillard Patrícia Chittoni
Published: May 2023

The objective of this paper is to present an overview of the Termisul re­search group work and report some results of its latest initiative of studies on specialized languages patterns from 2006 up to now. The method used is the description of the Project Termisul Collection: patterns of legal, re­gulatory and scientific languages and some of the related sub-projects. The new stage at Termisul is mainly characterized by corpus-based research and by the publication of the results on the web page www.ufrgs.br/termisul. Finally, the corpus based research approach of the work and the on-line presentation of its outcomes have been a strong contribution to terminology teaching and translation. 

Recieved: 20-01-10 /Accepted: 09-04-10

How to reference this article:

Bevilacqua, C. R. & Ramos Reuillard, P. C. (2010). Acervo Termisul: estudo dos padrões da linguagem legal, normativa e científica. Íkala, 15(3), 207 – 233.
Thematic categorization of cultural analysis: a proposal for translation
Authors: Igareda Paula
Published: May 2023

This article analyzes the cultural referents of various literary texts and their translation from Spanish to German and English based on the development of a methodological tool for cultural analysis. Firstly, it makes a brief tour of the state of the art in relation to the translation of cultural elements, the main existing classifications and theories in order to develop the tool to, finally, present some examples of how cultural references have been translated into the study corpus. One of the main conclusions is the tendency to neutralize or search for a functional equivalent in the translation work of this type of works.
Phase Transitions in the Reduction of the Traveling Salesman Problem and the Two-Level Cooperative Assignment Problem
Authors:   Saint Petersburg Electrotechnical University, Saint Petersburg, 197022, Russian Federation, Sheveleva A. M. , Belyaev S. A. ,   Saint Petersburg Electrotechnical University, Saint Petersburg, 197022, Russian Federation
Published: May 2023

The paper considers algorithms for reducing the NP-hard traveling salesman problem to a two-level cooperative assignment problem and vice versa. The accuracy of the information of both algorithms is demonstrated by an example. Using the known conditions of the phase transition in the traveling salesman problem, copies of the problem were created, on which a computational experiment was subsequently carried out. The experiment is aimed at demonstrating the conservation of the phase transition when reducing one problem to another.
The Pareto Principle in the Functions Approximating Processing the Results of Psychological and Sociological Research
Authors:   St. Petersburg State University of Telecommunications named prof. M. A. Bonch-Bruevich, Dvornikova O. F. , Tatarnikova I. M. ,   St. Petersburg State University of Telecommunications named prof. M. A. Bonch-Bruevich, Dvornikov S. V. ,   St. Petersburg State University of Aerospace Instrumentation, Military Academy of Communications
Published: May 2023

The possibilities of approximating functions in the processing of large data arrays of the results of psychological and sociological research are analyzed. An approach to the processing of areas limited by approximating functions is substantiated in accordance with the Pareto principle. Threshold values are obtained that ensure the division of areas in the ratio 1/4 for the most frequently used for approximating the results of studies of approximating functions. The conformity of the law of distribution of histograms of scientific achievements of scientists, approximating them with curves, according to Pearson's goodness-of-fit criterion is checked.
Ensuring Information Security of OLAP-Containing Distributed Electronic Systems using Blockchain Technology
Authors:   Institute of Information Technology of The Ministry of Science and Education of the Azerbaijan Republic, Baku, Azerbaijan, Nabibayova G. Ch.
Published: May 2023

The article outlines the properties of blockchain technology, according to which the content of blockchain blocks is immutable and the use of a peer-to-peer (P2P) network implies decentralized management. It describes the essence and meaning of smart-contracts and smart-views derived from them, which are involved in the process of data analysis and decision making. The article considers the papers devoted to various approaches to the problem of integration of blockchain technology and data storage. To ensure all three key aspects of information security — the integrity, availability and confidentiality of information, which is important for both government and corporate structures, the article proposes to use a private blockchain, instead of a public one. A modification of the model of an electronic decision support system containing an OLAP block, which includes a private blockchain, is developed. It is shown that this DSS model can be used as an electronic demographic DSS, which is an infrastructure for solving state problems in this area, since many of the characteristics of this model correspond to the multisectoral nature of demography.
nline Tutoring System "Kak Eto Rabotaet: Algoritmy"
Authors:   Volgograd State Technical University, Volgograd, 400005, Russian Federation, Denisov M. E. , Sychev O. A. ,   Volgograd State Technical University, Volgograd, 400005, Russian Federation, Terekhov G. V. ,   Volgograd State Technical University, Volgograd, 400005, Russian Federation
Published: May 2023

The article describes the features and architecture of intelligent online tutor "Kak eto rabotaet: Algoritmy", which is based on modelling subject-domain concepts on the comprehension level of Bloom's taxonomy. It is designed for learning basic algorithmic structures — sequences, selection statements, and loops — using the task of building an execution trace of the given algorithm. The tutor analyzes the student's solution step by step and displays explanatory messages for every error right after it happens; the error messages include the violated domain rules and their consequences in the specific situation. It can also hint the next correct step with textual explanation of why it is correct. It allows reliable learning of new concepts without control of each exercise from the human teachers which significantly increases the number of exercises learners can perform during a course. A control-flow diagram of the algorithm can be visualized; when the student makes an error, it is displayed with a red line on the diagram. The tutor is based on the formal model of subject domain implement using Apache Jena rules over RDF graph. Teachers can create learning problems using block-based interface and them, receiving links that can be sent to their students. Students can also use the tutor on their own to explore examples of interest to them.
Experiencing Political Advertising Through Social Media Logic: A Qualitative Inquiry
Authors: Echeverría Martin
Published: May 2023

<span style="font-size: 10.0pt; mso-bidi-font-size: 11.0pt; line-height: 107%; font-family: 'Calibri',sans-serif; mso-fareast-font-family: Calibri; mso-bidi-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US">The allocation of political advertising in social media is rising in Western campaigns. Yet audiences, unlike those of television advertising, are no longer isolated and passive consumers of linear discourses from politicians; users can now interact, share, and merge political advertising with other messages. Literature has dealt with the effects of such affordances separately, yet not in an integrative, holistic way that makes it possible to observe how they interact with each other. Hence, this article explores qualitatively how users experience, engage with, and make sense of political advertising in social media, and how its affordances mediate the attitudes, responses, and meanings users bring to political advertising and its sponsors. Under the lenses of the theory of social media logic, which points out the properties of social media—popularity, programmability, datafication, and connectivity—that structure users’ experiences, we conducted six focus group sessions with Mexican users (n = 34) during the 2021 federal campaigns. Findings show the fuzziness of digital advertising for users, which blurs with other formats like infographics or memes, the crucial role of individual linkages for advertising attention and attitude formation, a mismatch between the platform’s political feed and citizens’ information needs, and the tactics users perform to tame or avoid political content, disengaging them from campaigns.
Formation of the "security" phenomenon: features of mytho-religious contexts
Authors:   Taras Shevchenko national University of Kyiv, Predko Olena , Predko Denys ,   Taras Shevchenko national University of Kyiv, Nesterova Mariia ,   Taras Shevchenko national University of Kyiv
Published: May 2023

The article is devoted to understanding the idea of security in mytho-religious beliefs, as well as the search for theoretical interpretations of the transformation of the mask phenomenon, from its original meaning to the present in terms of COVID-19. It is revealed that in the primitive era characteristic notions of security were formed, which was due to a certain type of worldview. Primitive man, mastering the environment and being in conditions of a threatening reality, tried to protect himself by creating a kind of amulet, through which he tried to preserve its integrity. At the same time, certain codes of conduct were formed. Mythological and religious ideas testify to the formation of the idea of security, which originated by performing a protective function, regulating interpersonal relations and the life of society. Acting as a kind of worldview, mytho-religious ideas reflected a certain level of human identification, its ability to protect himself as integrity. In fact, mythology reflects the harmony between man and the world around him, between society and nature. In this sense, it serves as a means of protecting man from negative influences. Particular attention is paid to the application of various theoretical approaches, those discourses that have constructed mythological meanings, religious accents. This study can be considered an analytical comparison of two strategic vectors of security thinking, which are directly related. First, the vector associated with the emergence of various gods, forces, which, despite all their contradictions and various spheres of influence, "increased" their protective function. The second trajectory is the emergence of various mytho-religious factors, the emergence of certain means as an auxiliary factor in human protection. There is also no linear growth in this movement, phenomena and situations arise that do not have an unambiguous definition – religion and culture. These phenomena intertwine and show that they, or society, are already dealing with some other semantic mode of protection. Reconstruction of the mytho-religious context allowed to establish the functional features of the mask, which are considered in relation to the meaning of life orientations of man. The mask is associated with the formulation of meanings in the context of reflections on oneself, the Other and the world as a whole.
Hypervolume Sen Task Scheduilng and Multi Objective Deep Auto Encoder based Resource Allocation in Cloud
Authors: George Neema , B. K. Anoop
Published: May 2023

Cloud Computing (CC) environment has restructured the Information Age by empowering on demand dispensing of resources on a pay-per-use base. Resource Scheduling and allocation is an approach of ascertaining schedule on which tasks should be carried out. Owing to the heterogeneity nature of resources, scheduling of resources in CC environment is considered as an intricate task. Allocating best resource for a cloud request remains a complicated task and the issue of identifying the best resource – task pair according to user requirements is considered as an optimization issue. Therefore the main objective of the Cloud Server remains in scheduling the tasks and allocating the resources in an optimal manner. In this work an optimized task scheduled resource allocation model is designed to effectively address  large numbers of task request arriving from cloud users, while maintaining enhanced Quality of Service (QoS). The cloud user task requests are mapped in an optimal manner to cloud resources. The optimization process is carried out using the proposed Multi-objective Auto-encoder Deep Neural Network-based (MA-DNN) method which is a combination of Sen’s Multi-objective functions and Auto-encoder Deep Neural Network model. First tasks scheduling is performed by applying Hypervolume-based Sen’s Multi-objective programming model. With this, multi-objective optimization (i.e., optimization of cost and time during the scheduling of tasks) is performed by means of Hypervolume-based Sen’s Multi-objective programming. Second, Auto-encoder Deep Neural Network-based Resource allocation is performed with the scheduled tasks that in turn allocate the resources by utilizing Jensen–Shannon divergence function. The Jensen–Shannon divergence function has the advantage of minimizing the energy consumption that only with higher divergence results, mapping is performed, therefore improving the energy consumption to a greater extent. Finally, mapping tasks with the corresponding resources using Kronecker Delta function improves the makespan significantly. To show the efficiency of Multi-objective Auto-encoder Deep Neural Network-based (MA-DNN) cloud time scheduling and optimization between tasks and resources in the CC environment, we also perform thorough experiments on the basis of realistic traces derived from Personal Cloud Datasets. The experimental results show that compared with RAA-PI-NSGAII and DRL, MA-DNN not only significantly accelerates the task scheduling efficiency, task scheduling time but also reduces the energy usage and makespan considerably.
An Ensemble Classification and Hybrid Feature Selection Approach for Fake News Stance Detection
Authors: Vaideghy A. , Thiyagarajan C.
Published: May 2023

The developments in Internet and notions of social media have revolutionised representations and disseminations of news. News spreads quickly while costing less in social media. Amidst these quick distributions, dangerous or seductive information like user generated false news also spread equally. on social media. Distinguishing true incidents from false news strips create key challenges. Prior to sending the feature vectors to the classifier, it was suggested in this study effort to use dimensionality reduction approaches to do so. These methods would not significantly affect the result, though. Furthermore, utilising dimensionality reduction techniques significantly reduces the time needed to complete a forecast. This paper presents a hybrid feature selection method to overcome the above mentioned issues. The classifications of fake news are based on ensembles which identify connections between stories and headlines of news items. Initially, data is pre-processed to transform unstructured data into structures for ease of processing. In the second step, unidentified qualities of false news from diverse connections amongst news articles are extracted utilising PCA (Principal Component Analysis). For the feature reduction procedure, the third step uses FPSO (Fuzzy Particle Swarm Optimization) to select features. To efficiently understand how news items are represented and spot bogus news, this study creates ELMs (Ensemble Learning Models). This study obtained a dataset from Kaggle to create the reasoning. In this study, four assessment metrics have been used to evaluate performances of classifying models.
IoT-based Secure Data Transmission Prediction using Deep Learning Model in Cloud Computing
Authors: Chinthamu Narender , Gooda Satheesh Kumar , Venkatachalam Chandrasekar , S. Swaminathan , Malathy G.
Published: May 2023

The security of Internet of Things (IoT) networks has become highly significant due to the growing number of IoT devices and the rise in data transfer across cloud networks. Here, we propose Generative Adversarial Networks (GANs) method for predicting secure data transmission in IoT-based systems using cloud computing. We evaluated our model’s attainment on the UNSW-NB15 dataset and contrasted it with other machine-learning (ML) methods, comprising decision trees (DT), random forests, and support vector machines (SVM). The outcomes demonstrate that our suggested GANs model performed better than expected in terms of precision, recall, F1 score, and area under the receiver operating characteristic curve (AUC-ROC). The GANs model generates a 98.07% accuracy rate for the testing dataset with a precision score of 98.45%, a recall score of 98.19%, an F1 score of 98.32%, and an AUC-ROC value of 0.998. These outcomes show how well our suggested GANs model predicts secure data transmission in cloud-based IoT-based systems, which is a crucial step in guaranteeing the confidentiality of IoT networks.
Integrating the EGC, EF, and ECS Trio Approaches to Ensure Security and Load Balancing in the Cloud
Authors: Abraham Abin T. , Fredrik E. J. Thomson
Published: May 2023

According to data protection studies, "Distributed Denial-of-Service (DDoS)" threats have cost governments and businesses throughout the globe a large number of financial resources. Despite this, the existing practices fall short of the standards set by "Cloud Computing (CC)" monitoring technology. They ignore the "Intrusion Detection Systems (IDS)" techniques, which take advantage of the CC's multiple tenants and elasticity qualities, and also the hardware limitations. Attackers are finding increasing ways to effectively exploit them because of their rising complexity. DDoS assaults of this scale have never been observed online before 2018. As online services get more popular, so does the amount of DDoS assaults and malevolent hackers leading to terrible. Numerous IDS for DDoS are already in place to address this problem. One of the most challenging aspects of virtualization is establishing a "Trust Model (TM)" between the many "Virtual Machines (VMs)". The lack of a standard formulation for generating a TM would be the primary reason. As a consequence, the integrity of every VM might not have been recognized by an independent trust, which might lead to a decrease in trust value. In this research for TM creation, "Enhanced Graph Based Clustering (EGC)" is proposed, while "Enhanced Fuzzy (EF)" is used for detecting attacks, and the "Enhanced Cuckoo Search (ECS)" method is used to find the ideal "Load Balancing (LB)" distribution. By creating a new TM, the proposed (EGC-EF-ECS) system strengthens trust value. To expand the CC model's stability, it optimizes attacker recognition percentage and makes better use of resources by restricting each VM's processing, bandwidth, and storage requirements. The proposed EGC-EF-ECS outperformed the previously used BPA-SAB, and DCRI-RI approaches in terms of the "Intrusion-Detection-Rate (IDR)", "Load-Balancing-Efficiency (LBE)", and "Data-Accessing-Time (DAT)" evaluation metrics.
Detecting the Anti-Social Activity on Twitter using EGBDT with BCM
Authors: Chinthamu Narender , Gooda Satheesh Kumar , Shenbagavalli P. , Krishnamoorthy N. , Selvan S. Tamil
Published: May 2023

The rise of social media and its consequences is a hot topic on research platforms. Twitter has drawn the attention of the research community in recent years due to various qualities it possesses. They include Twitter's open nature, which, unlike other platforms, allows visitors to see posts posted by Twitter users without having to register. In twitter the sentiment analysis of tweets are used for detecting the anti-social activity event which is one of the challenging tasks in existing works. There are many classification algorithms are used to detect the anti-social activities but they obtains less accuracy. The EGBDT (Enhanced Gradient-Boosted Decision Tree) is used to optimize the best features from the NSD dataset and it is given as input to BCM (Bayesian Certainty Method) for detecting the anti-social activities. In this work, tweets from NSD dataset are used for analyzing the sentiment polarity i.e. positive or negative. The efficiency of the proposed work is compared with SVM, KNN and C4.5. From this analysis the proposed EGBDT and BCM obtained better results than other techniques.
Enlightening Network Lifetime based on Dynamic Time Orient Energy Optimization in Wireless Sensor Network
Authors: Priya S. , Suganthi P.
Published: May 2023

Mobile Ad-hoc Networks (MANET) are a set of Large-scale infrastructure and mobile device networks that build themselves without centralized control to provide various services through mobile. However, the quality of service of MANET is highly dependent on multiple parameters. Many routing schemes in literature use hop count, mobility speed, direction, etc. Similarly, the flow-based approach chooses long routes, which increases latency and reduces throughput efficiency. However, not all methods work well with all Quality of Service (QoS) parameters. To introduce a Dynamic Time Orient Energy Optimization (DTOEO) algorithm to construct the energy-based tree formation to achieve the minimum energy consumption network. Energy-based Dynamic Tree Routing to provide higher energy node and shortest route estimation that help to better transmission quality. In this proposed DTOEO method, perform three stages, there are i). Source node discovery process, ii). Time-orient density estimation, and iii). Energy-based Dynamic Tree Routing. In this stage, orient density estimation evaluates the data transmission size for each window period. To assess the consuming energy in the overall network. The proposed method of performance evaluation using various QoS matrices and its comparison to the existing process provides better performance.
A Novel Approach for Optimization of Convolution Neural Network with Particle Swarm Optimization and Genetic Algorithm for Face Recognition
Authors: P Kalaiarasi , Rani P. Esther
Published: May 2023

Convolutional neural networks are contemporary deep learning models that are employed for many various applications. In general, the filter size, number of filters, number of convolutional layers, number of fully connected layers, activation function and learning rate are some of the hyperparameters that significantly determine how well a CNN performs.. Generally, these hyperparameters are selected manually and varied for each CNN model depending on the application and dataset. During optimization, CNN could get stuck in local minima. To overcome this, metaheuristic algorithms are used for optimization. In this work, the CNN structure is first constructed with randomly chosen hyperparameters and these parameters are optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. A CNN with optimized hyperparameters is used for face recognition. CNNs optimized with these algorithms use RMSprop optimizer instead of stochastic gradient descent. This RMSprop optimizer helps the CNN reach global minimum quickly. It has been observed that optimizing with GA and PSO improves the performance of CNNs. It also reduces the time it takes for the CNN to reach the global minimum.
Crime Prediction and Analysis against women Using LRSRI-Missing Value Imputation and FIPSO - Optimum Feature Selection Methods
Authors: Tamilarasi P. , Rani R. Uma
Published: May 2023

Data investigation is the method of considering crude measurements in arrange to draw conclusions around them. Many statistics evaluation techniques and tendencies had been automated into mechanical techniques and algorithms in such a manner that they provided raw statistics for human consumption. Machine learning could be a portion of artificial intelligence that permits computer frameworks to "analyze" their own statistics and improve them over time without being explicitly programmed. Machine learning algorithms can understand patterns in statistics and analyze them to make their own predictions. Lost esteem ascription is one of the foremost vital procedures in data pre-processing and it is additionally the most prepare of information examination. Ascription of lost information for a variable replaces lost information with a esteem inferred from an assess of the dispersion of that variable. Basic accusation employments as it were one suspicion. Numerous ascriptions employments diverse gauges to reflect the instability in evaluating this dispersion. In this article, The proposed method LRSRI used for impute the missing values on Crime against Women Data-set(CAW).The Linear Regression Imputation and Stochastic regression imputations are used in this method.Feature selection is another important data preprocessing techniques.This is often called attribute selection or feature selection. The most important problem in predictive modeling is the mechanical selection of features in the data. In this work,the proposed method FIPSO implemented for feature selection.This is feature importance and Particle Swarm Optimization based method.The main objective of this work is predict the crime rate against women in India based on 2001 to 2021 crime recorded against women in India.This Data set is collected from Data.gov.in.Finally The predicted result is compared with recent NCRB crime report.The proposed method LRSRI and FIPSO has given 98.34% accuracy of crime prediction.In feature,This outcome will be valuable for the crime office to control the CAW in India.
Power Loss Minimization in a Radial Distribution Network by Optimal Sizing and Placement of Energy Storage Units
Authors: Maddina Suresh Babu. , Thirunavukkarasu R. , Karthik N.
Published: May 2023

It is possible to reduce distribution losses by strategically placing and sizing DG and BESS sources. Assuring low loss requires strategically placing the aforementioned devices; otherwise, the system may experience either under- or overvoltage. It is preferable to choose bus stations with less risk for loss. The proposed approach tries to pinpoint the optimal BESS size and placement to cut down on investment and operating expenses while still achieving the desired level of energy reduction. The development of optimisation algorithms for finding and scaling BESS units is the fundamental focus of this study. Two such strategies are being explored here: the Genetic Algorithm (GA) and the Ant Colony Optimization Algorithm (ACOA). The goal function, like the original issue, seeks to minimise system-wide power losses while adhering to specified levels of equality and inequality. This article explores the appropriate capacity and placement of the DGs in a 33-bus radial distribution grid to reduce power dissipations. Matlab code is used to perform a simulation, and the results are put to use gauging the method's sturdiness.
Enhancing Feature Extraction through G-PLSGLR by Decreasing Dimensionality of Textual Data
Authors: Chinthamu Narender , Venkatachalam Chandrasekar , Pillai.N Muthuvairavan , Appaji Setti Vidya Sagar , Murali M.
Published: May 2023

The technology of big data has become highly popular in numerous industries owing to its various characteristics such as high value, large volume, rapid velocity, wide variety, and significant variability. Nevertheless, big data presents several difficulties that must be addressed, including lengthy processing times, high computational complexity, imprecise features, significant sparsity, irrelevant terms, redundancy, and noise, all of which can have an adverse effect on the performance of feature extraction. The objective of this research is to tackle these issues by utilizing the Partial Least Square Generalized Linear Regression (G-PLSGLR) approach to decrease the high dimensionality of text data. The suggested algorithm is made up of four stages: Firstly, gathering featured data in vector space model (VSM) and training it with bootstrap technique. Second, grouping trained feature samples using a Pearson correlation coefficient and graph-based technique. Third, getting rid of unimportant features by ranking significant group features using PLSGR. Lastly, choosing or extracting significant features using Bayesian information criterion (BIC). The G-PLSGLR algorithm surpasses current methods by achieving a high reduction rate and classification performance, while minimizing feature redundancy, time consumption, and complexity. Furthermore, it enhances the accuracy of features by 35%.
An Automated Framework for Detecting Change in the Source Code and Test Case Change Recommendation
Authors: Sivaji U. , Mahalakshmi V. , Sivakumar G S , R Sasirekha. , Venkataramana R
Published: May 2023

Improvements and acceleration in software development have contributed towards high-quality services in all domains and all fields of industry, causing increasing demands for high-quality software developments. The industry is adopting human resources with high skills, advanced methodologies, and technologies to match the high-quality software development demands to accelerate the development life cycle. In the software development life cycle, one of the biggest challenges is the change management between the version of the source codes. Various reasons, such as changing the requirements or adapting available updates or technological upgrades, can cause the source code's version. The change management affects the correctness of the software service's release and the number of test cases. It is often observed that the development life cycle is delayed due to a lack of proper version control and due to repetitive testing iterations. Hence the demand for better version control-driven test case reduction methods cannot be ignored. The parallel research attempts propose several version control mechanisms. Nevertheless, most version controls are criticized for not contributing toward the test case generation of reduction. Henceforth, this work proposes a novel probabilistic rule-based test case reduction method to simplify the software development's testing and version control mechanism. Software developers highly adopt the refactoring process for making efficient changes such as code structure and functionality or applying changes in the requirements. This work demonstrates very high accuracy for change detection and management. This results in higher accuracy for test case reductions. The outcome of this work is to reduce the development time for the software to make the software development industry a better and more efficient world.
Efficacy of Decentralized CSS Clustering Model Over TWDP Fading Scenario
Authors: Dobaria Ankit D. , Vora Vishal S.
Published: May 2023

Cognitive Radio technology, which lowers spectrum scarcity, is a rapidly growing wireless communication technology. CR technology detects spectrum holes or unlicensed spectrums which primary users are not using and assigns it to secondary users. The dependability of the spectrum-sensing approach is significantly impacted from two of the most critical aspects, namely fading channels and neighboring wireless users. Users of non-cooperative spectrum sensing devices face numerous difficulties, including multipath fading, masked terminals, and shadowing. This problem can be solved using a cooperative- spectrum-sensing technique. For the user, CSS enables them to detect the spectrum by using a common receiver. It has also been divided into distributed CSS and centralized CSS. This article compares both ideas by using a set of rules to find out whether a licensed user exists or not. This thought was previously used to the conventional fading channels, such as the Rician, Rayleigh and the nakagami-m models. This work focused on D-CSS using clustering approach over TWDP fading channel using two-phase hard decision algorithms with the help of OR rule as well as AND rule. The evaluation of the proposed approaches clearly depicted that the sack of achieve a detection-probability of greater than 0.8; the values SNR varies between -14 dB to -8 dB. For all two-phase hard decision algorithms using proposed approach and CSS techniques, the detection probability is essentially identical while the value of signal to noise ratio is between -12 dB to -8dB. Throughout this work, we assess performance of cluster-based cooperative spectrum-sensing over TWDP channel with the previous findings of AWGN, Rayleigh, and wei-bull fading channels. The obtained simulation results show that OR-AND decision scheme enhanced the performance of the detector for the considered range of signal to noise ratios.
A Novel Method of Enhancing Security Solutions and Energy Efficiency of IoT Protocols
Authors: Prasad KDV , Palanikkumar D , V Dankan Gowda , Hussain Naziya , Pazhani A. Azhagu Jaisudhan , N Anil Kumar
Published: May 2023

Mobile Ad-hoc Networks (MANET’s) are wireless networks that are capable of operating without any fixed infrastructure. MANET routing protocols must adhere to strict secrecy, integrity, availability and non-repudiation criteria. In MANETs, attacks are roughly categorised into two types: active and passive. An active attack attempts to modify or remove data being transferred across a network. On the other hand, passive attack does not modify or erase the data being sent over the network. The majority of routing protocols for MANETs were built with little regard for security and are therefore susceptible to a variety of assaults. Routing technologies such as AODV and dynamic source routing are quite common. Both however are susceptible to a variety of network layer attacks, including black holes, wormholes, rushing, byzantine, information disclosure. The mobility of the nodes and the open architecture in which the nodes are free to join or leave the network keep changing the topology of the network. The routing in such scenarios becomes a challenging task since it has to take into account the constraints of resources of mobile devices. In this an analysis of these protocols indicates that, though proactive routing protocols maintain a route to every destination and have low latency, they suffer from high routing overheads and inability to keep up with the dynamic topology in a large sized network. The reactive routing protocols in contrast have low routing overheads, better throughput and higher packet delivery ratio. AODVACO-PSO-DHKE Methodology boosts throughput by 10% while reducing routing overhead by 7%, latency by 8% and energy consumption by 5%. To avoid nodes always being on, a duty cycle procedure that's also paired with the hybrid method is used ACO-FDR PSO is applied to a 100-node network and NS-3 is used to measure various metrics such as throughput, latency, overhead, energy consumption and packet delivery ratio.
Real-time Monitoring and Evaluation of the Vax Cash Program: A Case Study from Columbus, Ohio
Authors: Hyder Ayaz , Graffagnino Cheryl , French Gavin , Maloney John A. , DeJesus Ben , Cowen Kathleen , Iversen Jane , Bennett Suellen
Published: May 2023

Background: The prevention of severe outcomes due to SARS-CoV-2 infection among vulnerable populations is an important public health goal. The purpose of our study was to report on the implementation and evaluation of an innovative public health prevention program. This program aimed to reduce the projected gap in COVID-19 vaccine uptake between more and less vulnerable neighborhoods by addressing issues around access and trust among communities at high risk for COVID-19 positive cases, hospitalization, and death.
Methods: Columbus Public Health implemented the Vax Cash program in Columbus, Ohio, from July 6, 2021, to August 22, 2021, based on regular community feedback and using a data-driven approach. The program provided a financial incentive to eligible individuals upon receiving their first dose of a COVID-19 vaccine. A time-series model was used to create short-term forecasts for COVID-19 vaccine uptake for neighborhoods in and around the 10 clinics in the program. These projections were compared with the observed uptake as the program was implemented over a 6-week period.
Results: Seven out of ten sites showed an increase in the observed COVID-19 vaccine uptake in and around the sites compared to projected uptake values. We observed a rapid increase in uptake among Black residents and a reduction in the Black-White vaccine uptake gap in and around the Vax Cash sites.
Conclusion: Vaccination rates increased in areas of high social vulnerability through the Vax Cash program. Similarly designed programs could be applied to achieve other public health prevention goals.
Adaptation of Pansori “Sarang-ga(Love Song)” in Chunhyang-ga and its meaning: Focusing on K-pop music since the 2000s
Authors: Lee Chae eun
Published: May 2023

This study investigated the cases and types of Pansori “Sarang-ga(Love Song)” in Chunhyang-ga adaptation into popular music works since the 2000s, and what adaptation could mean. The adaptation of Pansori “Love Song” can be divided into three types based on the response of the adaptation to the original story world. First, there was a type of adaptation that elicited dependent changes to the existing story world through “retelling.” Second, there was a type that extended the existing story world while “revising” the original and ezamining it reflectively. Lastly, there was a type of creation of an alternative narrative that deviated from the existing story world by “expansion” of the original. All three types are “repeated and not reproduced” in terms of the original. There is a power struggle between traditional norms, cultural ideologies, and symbols, and the desire to create new things by raising or dismantling problems. This also occurs while the audience appreciates the work while exchanging or comparing the original and the adaptation. In the dual perception of having to perceive the original and the adaptation at the same time, Pansori’s popular music adaptation provieds novelty in familiarity as a recombinant tradition and reinterprets classics in a way that meets the expectations and needs of the modern public as a present-day past. In addition, listeners who do not have extensive knowledge of Pansori can enjoy interactive play and enjoy through the process of finding Pansori elements used in music. The tradition that the public takes over through the popular musical adaptation of Pansori may be an imaginary element that has been selected and recombined and created, that is, a recombined tradition from the current viewpoint. However, the positive side can be found in that today’s pop music audiences independently accept the contents of traditional Pansori and attract them into their lives and savor them. On the other hand, the adaptations that preserve Pansori have the potential to induce reactions and curiosity about Pansori and make it more prosperous. As such, the popular music adaptation of Pansori exhibits a multi-layered orientation and three-dimensionality as much as the adaptation of video content or narrative that has been widely dealt with in academia. Considering that popular music has a strong influence on people living in modern society, it is necessary to continue to pay attention to the popular music adaptation of Pansori and analyze it from a delicate perspective.