Reviewerly/exHarmony huggingface dataset:
A Semantic Image Retrieval Method Based on Interest Selection

There is a semantic gap between people’s understanding of images and the underlying visual features of images, which makes it difficult for image retrieval results to meet the needs of individual interests. To overcome the semantic gap in image retrieval, this paper proposes a semantic image retrieval method based on interest selection. This method analyses the interest points of individual selections and gives the weight of the interest selection in different regions of an image. By extracting the underlying visual features of different regions, this paper constructs two feature vector methods after users’ interest point weighting. The two methods are called interest weighted summation and interest weighting. Finally, this paper compares the accuracy of different image classification methods using a support vector machine classification algorithm. The experimental results show that the target classification accuracy of the classification algorithm based on interest weighted summation is higher than that of the traditional and interest weighted methods. The classification algorithm based on interest weighted summation has the highest overall effect on target object classification in the four experimental scenarios. Therefore, the interest point selection method can effectively improve the overall satisfaction of image recommendation and can be used as a novel solution to overcome the semantic gap.
Preface

Vasireddy Venkatadri Institute of Technology was established under the aegis of Social Educational Trust, Guntur in the year 2007. It has become an autonomous college from the academic year 2019-2020. All six departments are accredited by NBA, New Delhi and accredited by NAAC with A Grade. Todayalmost 4300 students, 285 teaching staff and 315 non-teaching staff strive to fulfill the vision of VVIT. The college has professionally qualified and experienced faculty with 48 doctorates. Siemens Centre of Excellence with 15 high technology laboratories including robotics laboratory has been set up to provide training to the students including neighboring colleges. VVIT has many student chapters like IUCEE (EWB), IE(I), IETE, IEEE. In the Private or self-financed Colleges category, VVIT has been ranked under Band-A (Rank between 6th - 25th) across the entire country by Atal Ranking of Institutions on Innovation Achievement, MHRD, Govt of India. VVIT stood first in Times of Indian Ranking-2020. It is the youngest Engineering College in the state to achieve this recognition. MoUs with Google Inc. USA for establishing Google Code labs, Stanford University USA under University Innovative Fellowship (UIF) program and 3D Experience Lab established by Dassault Systems, France signify our commitment to update quality technical education. Realizing the slogan that “Everyone Counts,” VVIT has the unique achievement of having placed most of its students in MNCs like Amazon, DBS bank, Tech Mahindra, Infosys, TCS, Wipro, Athena Health Care, Open Text, Genpact, Sutherlands, CSS Corp, Convergys, Apps Associates, etc. (about 95 companies) every year. About Conference New Technologies are emerging every day that may radically transform the future of engineering. Vision of this conference is to promote excellence in scientific knowledge and innovations in the field of Civil and Mechanical engineering and related disciplines to motivate young researchers. It also provides a premier interdisciplinary platform for faculty members, students’ researchers, practitioners and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the practical fields. We welcome technical papers presenting research and experimental results, position papers addressing the pros and cons of specific proposals, such as those being discussed in the standard or in industry consortia, survey papers addressing the key problems and solutions on any of the topics or research papers on work in progress List of Conference themes, Organizing Committee, Conference Committees and Editors are available in this Pdf.
Writer adaptation for E2E Arabic online handwriting recognition via adversarial multi task learning

The importance of online handwriting recognition has been rapidly increasing over recent years due to the rapid technological advances in handheld devices and communication software with handwriting interfaces. Deep learning end-to-end (E2E) models have provided high recognition rates as part of online handwriting recognition systems. However, attaining even higher performance levels requires supplementing these models with adaptation techniques that cater to individual penmanship. This study proposes a writer adaptation technique for Arabic online handwriting recognition systems that employs adversarial Multi-Task Learning (MTL). Adversarial training and MTL modify the deep-features distribution of the Writer Dependent (WD) model, leading its output to closely resemble that of the Writer Independent (WI) model. The design of the proposed method entails two tasks: label classification (primary task) and model features discrimination (secondary task). Our method was designed to jointly optimize both sub-networks. The proposed technique was tested against the E2E Connectionist Temporal Classification (CTC) based model, a combination of both Convolutional Neural Networks (CNNs) and Bidirectional Long Short-term Memory (BiLSTM). The proposed models were trained and evaluated against two large datasets (the Online-KHATT and CHAW). In supervised adaptation, it achieved an absolute Character Error Rate (CER) of up to 1.83% and an absolute Word Error Rate (WER) reduction of 11.71% over the WI model. Additionally, supervised adaptation achieved an absolute CER of up to 0.84% and an absolute WER reduction of 6.77% over the fine-tuned model. In unsupervised adaptation, the proposed method achieved an absolute CER of up to 0.5% absolute and an absolute WER reduction of 1.74% absolute (WER) reduction over the WI. Our experimental results indicate that our proposed supervised writer adaptation can achieve significant improvements in recognition accuracy compared with the baseline models: WI and fine-tuned models.
APLICAÇÃO DE TÉCNICAS DE INTELIGÊNCIA ARTIFICIAL NA DETECÇÃO DE EVASÃO FISCAL: UMA REVISÃO SISTEMÁTICA

The research has a qualitative and quantitative nature and is characterized as descriptive research. Data revealed that 44% of respondents comprised older people (over 50 years), and 66% of these were adolescents and adults (18-49 years); Regarding the level of education, the data showed that 27% had not completed high school, while 6% had not completed high school. Stands out that other research in this thematic should be performed out so that one can have a better comprehension of the accounting sciences, leadership and entrepreneurship inserted at the traditional populations.
Bots, Fraud, and Careless Responding: Challenges of Bad-faith Responses in Survey Research

This symposium is aimed at bringing together a panel of scholars to discuss the prevalence and challenges associated with bad faith responses as well as opportunities to improve the quality of responses in survey research. Bad faith responding is defined as a) intentionally careless responses (e.g., participants responding without reading items or randomly), b) fraudulent participants (e.g., individuals lying about who they are or completing multiple surveys), and c) bots (computer programs) completing one or more surveys and producing fake data. The panel discussion will focus on the trends of bad faith responding in organizational research, the challenges associated with gathering survey data, and the opportunities for preventing, detecting, and mitigating bad faith responses. The primary goals of this panel symposium are to build awareness of bad faith responding, the costs of convenience sampling, and to inform researchers of ways to resolve issues that can arise. By bringing together researchers who have examined these issues with practitioners working for platforms that help manage the survey research process (e.g. – Qualtrics, MTurk), we provide a unique perspective on the prevalence and impact of bad faith survey responding in management research.
Reviewer Acknowledgements

Applied Economics and Finance (AEF) would like to acknowledge the following reviewers for their assistance with peer review of manuscripts for this issue. Many authors, regardless of whether AEF publishes their work, appreciate the helpful feedback provided by the reviewers. Their comments and suggestions were of great help to the authors in improving the quality of their papers. Each of the reviewers listed below returned at least one review for this issue.Reviewers for Volume 9, Number 1 Abdulaziz Abdulahman, Marmara University, USAAlbert Henry Ntarmah, Jiangsu University, GhanaAli Massoud, Sohag University, EgyptFahri ÖZSUNGUR, Adana Science and Technology University, TurkeyIulia Lupu, Victor Slavescu” Centre for Financial and Monetary Research, Romanian Academy, RomaniaLiao Zhu, Cornell University, USAMagdalena Radulescu, University of Pitesti, RomaniaMahmoud Mohammed Sabra, Al Azhar University-Gaza, PalestineOlena Sokolovska, St. Petersburg State University, RussiaOmer Allagabo Omer Mustafa, Sudan Academy for Banking and Financial Sciences., SudanPayal Chadha, University of Wales Prifysgol Cymru, KuwaitRajeev Rana, APB Govt. P.G. College, IndiaRamona Orastean, Lucian Blaga University of Sibiu, RomaniaRomeo Victor Ionescu, Dunarea de Jos University, RomaniaShahram Fattahi, Razi University, IranSzabolcs Blazsek, Universidad Francisco Marroquín, GuatemalaY. Saidi, M’sila University, AlgeriaZi-Yi Guo, Wells Fargo Bank, N.A., USA Nikki GibbsEditorial AssistantOn behalf of,The Editorial Board of Applied Economics and FinanceRedfame Publishing9450 SW Gemini Dr. #99416Beaverton, OR 97008, USAURL: http://aef.redfame.com
An Android-Based Image Steganography System for Concealing Data and Information Transmission Using Adaptive Image Steganography

The growth in the volume of information transmission and transaction over the internet has necessitated the development and enhancement of measures and techniques required to ensure the safety of critical information during transmission. with developments in mobile technologies and the adoption and diffusion of android mobile devices, research must therefore continue to explore more secured media in which information can be hidden. One of such medium is the use of image carriers referred to as steganography. In tis paper, we provide insughts into the development of an android-based Image Steganography System for concealing data and information using adaptive image steganography. The Least Significant Bit (LSB) algorithm was employed as the algorithmic sequence for the development. Preliminary results from implementation and testing showed promising results Keywords: Android, image steganography, data, information, transmission, images, security
Consistent Sparse Deep Learning: Theory and Computation

Deep learning has been the engine powering many successes of data science.However, the deep neural network (DNN), as the basic model of deep learning, is often excessively over parameterized, causing many difficulties in training, prediction and interpretation.We propose a frequentist-like method for learning sparse DNNs and justify its consistency under the Bayesian framework: the proposed method can learn a sparse DNN with at most O(n/\log(n)) connections and nice theoretical guarantees such as posterior consistency, variable selection consistency and asymptotically optimal generalization bounds.In particular, we establish posterior consistency for the sparse DNN with a mixture Gaussian prior, show that the structure of the sparse DNN can be consistently determined using a Laplace approximation-based marginal posterior inclusion probability approach, and use Bayesian evidence to elicit sparse DNNs learned by an optimization method such as stochastic gradient descent in multiple runs with different initializations.The proposed method is computationally more efficient than standard Bayesian methods for large-scale sparse DNNs.The numerical results indicate that the proposed method can perform very well for large-scale network compression and high-dimensional nonlinear variable selection, both advancing interpretable machine learning.This talk is based on a joint work with Yan Sun and Qifan Song.
Learning with Privileged Tasks

Multi-objective multi-task learning aims to boost the performance of all tasks by leveraging their correlation and conflict appropriately. Nevertheless, in real practice, users may have preference for certain tasks, and other tasks simply serve as privileged or auxiliary tasks to assist the training of target tasks. The privileged tasks thus possess less or even no priority in the final task assessment by users. Motivated by this, we propose a privileged multiple descent algorithm to arbitrate the learning of target tasks and privileged tasks. Concretely, we introduce a privileged parameter so that the optimization direction does not necessarily follow the gradient from the privileged tasks, but concentrates more on the target tasks. Besides, we also encourage a priority parameter for the target tasks to control the potential distraction of optimization direction from the privileged tasks. In this way, the optimization direction can be more aggressively determined by weighting the gradients among target and privileged tasks, and thus highlight more the performance of target tasks under the unified multi-task learning context. Extensive experiments on synthetic and real-world datasets indicate that our method can achieve versatile Pareto solutions under varying preference for the target tasks.
A study on applying the living lab method to Korean language educations

The goal of this study is to understand the needs of international undergraduate learners and students from multicultural background, and to develop and evaluate a learner-centered Korean language education program based on the method of the living lab. The living lab activity implemented with members of a university Korean language and literature club, who were required to conduct a need analysis of international learners and, divided into four teams, create a living lab program. The goal of the four teams was 1) to develop Korean language material which included characteristics of the regional area, 2) foster cultural understanding through the development of a multicultural narrative collection, 3) create videos dealing with idiomatic expressions for advanced Korean language learners, and 4) run a counseling community for peers. Analysis and evaluation was conducted on two groups, and demonstrated that participants engaged in active and spontaneous learning. This study contributes to the literature in Korean language education by demonstrating a learner-centered approach based on the living lab method. Considerations on the program expansion and sustainability remain as future task.
Retraction: Predicting heart disease using hybrid machine learning model (J. Phys.: Conf. Ser. 1916 012208)

This article (and all articles in the proceedings volume relating to the same conference) has been retracted by IOP Publishing following an extensive investigation in line with the COPE guidelines. This investigation has uncovered evidence of systematic manipulation of the publication process and considerable citation manipulation. IOP Publishing respectfully requests that readers consider all work within this volume potentially unreliable, as the volume has not been through a credible peer review process. IOP Publishing regrets that our usual quality checks did not identify these issues before publication, and have since put additional measures in place to try to prevent these issues from reoccurring. IOP Publishing wishes to credit anonymous whistleblowers and the Problematic Paper Screener [1] for bringing some of the above issues to our attention, prompting us to investigate further. [1] Cabanac G, Labbé C and Magazinov A 2021 arXiv: 2107.06751v1 Retraction published: 23 February 2022
ERROR ANALYSIS ON THE STUDENTS’ CONSTRUCTION OF ENGLISH IRREGULAR PLURAL NOUNS

In English, the forms of singular nouns commonly different from those of the plural ones. Many students are confused with how to construct the irregular plural noun forms. The formation of irregular plural nouns has complex and unique patterns. This current study aims to get information about the types of errors commonly made by EFL learners in constructing irregular plural nouns and to know how the errors occurred. This study is descriptive qualitative applying error analysis theory. The data were collected by giving the respondents a test consisting of 28 questions on irregular plural construction. The result of analysis shows that the errors made by the respondents can be classified into three types: misformation, addition, and omission. Misformation was the kind of error most respondents made. The error specifically occurred with the nouns that had quite dissimilar plural forms from the singular ones (e.g., foot – feet, goose – geese).
Word Associations as a Source of Internet-Discourse Development

This chapter addresses the role of word associations in developing spontaneous talk spurts – such as Internet discourses – as exemplified by commentaries in virtual mass media. The research deals with unique materials that involve four concurrent discourses of broad public interest in Runet. This chapter uses a discursive approach and lexical semantic analysis. It demonstrates that, with all their diversity and subjectivity, associations perform some stable functions in developing Internet discourse. The article also presents the typology of these functions: the upbuilding of discourse critical mass, its emotional enrichment, its semantic development and the establishment of links between concurrent discourses. The author reveals crosscutting associations in each Internet-discourse case and recognises the particular features of various Internet-discourse associations, which come after any newsworthy event. The study leads to the conclusion that certain rules of Internet users’ speech behaviour could be formulated despite the seemingly chaotic conduct of mass of people participating in Internet communications.
Retraction: Minimizing Rental Cost with Continuous Machine Operation Using Ginni Simpson Index (IOP Conf. Ser.: Mater. Sci. Eng. 1145 012087)

This article (and all articles in the proceedings volume relating to the same conference) has been retracted by IOP Publishing following an extensive investigation in line with the COPE guidelines. This investigation has uncovered evidence of systematic manipulation of the publication process and considerable citation manipulation. IOP Publishing respectfully requests that readers consider all work within this volume potentially unreliable, as the volume has not been through a credible peer review process. IOP Publishing regrets that our usual quality checks did not identify these issues before publication, and have since put additional measures in place to try to prevent these issues from reoccurring. IOP Publishing wishes to credit anonymous whistleblowers and the Problematic Paper Screener [1] for bringing some of the above issues to our attention, prompting us to investigate further. [1] Cabanac G, Labbé C and Magazinov A 2021 arXiv: 2107.06751v1 Retraction published: 23 February 2022
Design of National Sports Action Feature Extraction System Based on Convolutional Neural Network

Human action recognition is one of the hotspots in computer vision research. Its purpose is to detect and recognize target actions from videos, so that computer systems can understand human actions, and thus it has great research significance. Based on the action features of famous sports, this paper proposes an action recognition scheme based on RGB-D video compression to establish action features and deep learning as a means of recognition. By establishing the connection between the bone data of the three-dimensional data type and the depth image data, the depth sequence is analyzed and expressed as a three-level structure diagram sequence, which is the overall figure sequence, partial figure sequence, and joint point figure sequence, and then passes through the two-way pool. The sorting algorithm extracts the action features in the three picture sequences and compresses and generates three types of structured images of the corresponding picture sequences, and these three types of structured images are used as the feature expression of the video. When constructing a three-level structure diagram sequence, the innovation of this paper is to splice the extracted key unit image blocks to obtain a three-level structured moving image based on the three-key unit splicing, so that the image is not only retained. In addition to time-space information, the structure information of the depth image is also strengthened, and the amount of calculation is reduced at the same time. Finally, the three types of structured images are input into the convolutional neural network, respectively, and the judgment and recognition results obtained are multiplicatively fused to obtain the final recognition rate of the action.
Rancang Bangun Aplikasi Berbasis Android Untuk Pembelajaran Linux Centos

Centos is a Linux based framework commonly used by network supervisors. Given the educational plan of learning in the current PC innovation study program, students are familiar with this framework. In today's all-mechanical era, there are lots of learning media such as android applications. This application was created to offer a different convenience to the Java programming language. In addition, this application is also developed using the SDLC model. There are still some uses that can help with learning exercises, especially those related to the Centos linux framework, the basic explanation of application makers to create applications that can later help learn about Centos linux. Although not as popular as Windows and iOS frameworks, there are still many who use the Centos Linux framework, especially for framework needs with this application making it easier for users to learn because it is mobile based so that we can learn Centos anywhere and anytime.
The quest for myriad strains

In the era in which the web is fully demonstrating its archival potential, more and more composers make use of sound, melody and computer library repositories. It is a clear trend in popular music, which is increasingly being extended also to ‘academic’ composition: today authors can access and contribute to a vast array of audio materials, of procedures and languages, where historicity and innovation coexist in an eternal present. At first glance it may seem a revolution. However, a closer look reveals ancient roots in the history of music that audio reproduction has made only more evident: the fixation of music on tape, at first, has led some composers (e.g. Bruno Maderna) to create sound libraries to be reused in different works, thus blurring the borders of the Opera; later on, the dematerialization and atomization of procedures in IT have pushed towards a philosophy of sharing (e.g. libraries for Computer Assisted Composition systems) – exalted today by the capillarity of the lightning-fast web distribution – raising deep questions about the concept of author itself. Moving further backwards, to the re-uses in Rossini and Mozart, or to the anonymous formulas in Gregorian chant, could we not find the recurrence of a quest for that world of «myriad strains that once shall sound», where the composer can stretch forth a hand for a musical idea, so wonderfully glimpsed by Busoni in his Sketch for a New Esthetic of Music?