Reviewerly/exHarmony huggingface dataset:
Convolutional Time Delay Neural Network for Khmer Automatic Speech Recognition

Convolutional Neural Networks have been proven to successfully capture spatial aspects of the speech signal and eliminate spectral variations across speakers for Automatic Speech Recognition. In this study, we investigate the Convolutional Neural Net-work with Time Delay Neural Network for an acoustic model to deal with large vocabulary continuous speech recognition for Khmer. Our idea is to use Convolutional Neural Networks to extract local features of the speech signal, whereas Time Delay Neural Networks capture long temporal correlations between acoustic events. The experimental results show that the suggested net-work outperforms the Time Delay Neural Network and achieves an average relative improvement of 14% across test sets.
Linguistic Analysis on Cursive Characters

Document Analysis has major importance in Information Retrieval Systems. Dredged with vaults of paper and material documents, to protect very important information and the summaries, without losing their meaning and importance, each document need to be properly curated and processed. Ancient written documents possess many types of cursive language character sets, which are very tedious to discriminate the characters and subsequently the right meaning. To overcome the difficulties of reading the cursive language characters and prevent misunderstanding the meaning and the importance of documents, an improvised CNN [6] model to work on OCR and Tesseract API has been proposed in this work. The documents are scanned, curated and preprocessed in the forms of images. CNN are the best algorithms, hitherto in the existing AI and Deep Learning arena. CNN with OCR API could contribute to the development of efficient strategies of character recognition even with complex cursive styles. A method which is adaptable to the classification and segmentation of the text images with cursive styles is proposed I this article. Tesseract is the popular and effective OCR library with rich API that can enrich the CNN-OCR model
Statistical and clustering validation analysis of primary students' learning outcomes and self-awareness of information and technical online security problems at a post-pandemic time

The authors decided to investigate the impact of the pandemic period and the resulting limitations in Polish primary school online security education. The first part of the study investigates the impact of the COVID-19 pandemic on students' educational learning outcomes in information and Internet security. The study has been performed via a student-oriented survey of 20 questions. The statistical analysis confirms the significant difference before and after the pandemic in several questions at most. Nevertheless, this justifies the statement that pandemics had a positive impact on post-pandemic Internet-related security education. The second part of the study has been focused on students' perception and self-awareness of cyberspace problems. For this purpose, the authors used novel majority-based decision fusion clustering validation methods. The revealed results illustrate the positive tendency toward the students' self-awareness and self-confidence of online security problems and e-threats before, during and after the challenging pandemic period. Moreover, the presented validation methods show the appealing performance in educational data analysis, and therefore, the authors recommended these methods as a preprocessing step that helps to explore the intrinsic data structures or students' behaviors and as a postprocessing step to predict learning outcomes in different educational environments.
The Future of Education-A Survey of Current Scientific Research Trends

Today, the field of education is the subject of various reforms at several levels, either pedagogical, didactic or technological, especially with the rapid and continuous evolution of ICT which means information and communication technologies, the resulting constraints and the challenges of the Covid-19 epidemic, as well as the new understanding of the teaching-learning process and the psychology of learning. In this regard, the present study aims to collect the most requested research topics in doctoral studies centers, indexed conferences and journals, related to this field, and then analyze them to determine their categorization, as well as define the current trends and the lines of research necessary to meet the needs of the educational field. To do this, a bibliometric approach, taking advantage of the univariate indicators development method and relational indicators development method, is implemented to effectively achieve the objectives of the study.
Novel Framework for Children’s Bilingual Pronunciation Correction based on Abnormal Speech Recognition Algorithm

Novel framework for the children’s bilingual pronunciation correction based on abnormal speech recognition algorithm is designed and implemented in this study. The key innovation aspect of the designed study is the abnormal speech recognition algorithm. The designed speech recognition sub-flow chart is used to recognize human speech signals, create a speech library and store the speech library in the single-chip microcomputer. get a recognizable voice signal. According to Shannon sampling theorem, the periodic movement of the spectrum in the frequency domain with the sampling rate as the interval will cause the high-frequency part to overlap, hence, the novel processing unit is used to achieve the goal of correcting children’s bilingual pronunciation. Through the systematic testing, the performance is validated.
Question-Answering System over Knowledge Graphs Using Analogical-Problem-Solving Approach

We introduce an analogical-problem-solving based question-answering system, LingTeQA. It generates templates from known pairs $$\langle $$ question-SPARQL query $$\rangle $$ and uses generated templates to answer newly asked questions. These questions can be of regular/usual form and can contain imprecise concepts represented by linguistic terms. The system works over open-domain Knowledge Graphs on the Web. In addition, LingTeQA can generate linguistic summaries to answer questions whose answers contain large amounts of numerical values. This system is accessible at https://www.lingteqa.site .
CSRB's opus one

Comments on the Cyber Safety Review Board Log4j Event Report.
Pioneers of the Korean Society of Mission Studies

The Korea Society of Mission Studies was established in October 1992. However, early formation began in 1990, In the fall of 1991, the mission theologians who first gathered for the founding of the Society petitioned the Korean Christian Association for the establishment of the Mission Theology Society. At the inaugural general meeting of the following year, Pres. Jung-won Seo, V. Pres. Jae-Oak Chun, and General Secretary Kwang-soon Lee were elected. The first Pres. Jung-won Seo, emphasized the status of mission theology, and Prof. Jae-Oak Chun emphasized the weakness of mission theology that should support the vitalization of missions. Prof. Kwang-soon Lee helped them and took on practical roles, from preparatory meetings to establishment, registering for conferences, and publishing academic journals. They served as the 1st, 2nd, and 3rd presidents side by side, and their term of office lasted 2 years each. This article introduces the early activities of the KSMS. We must not forget the hard work of Prof. Soo-il Chai(1994) and Prof. Ki-young Hong(1996) increasing the few dozen members to 300 members in the Society today.
The Origin and Early History of the Korean Society of Mission Studies

This is a study of the early historic development of the Korean Society of Mission Studies (KSOMS). The KSOMS was established in 1992 and celebrated its 30th anniversary this year. In this regard, this study summarizes the development of early history in the past 30 years from three perspectives. First, the origin of KSOMS is described and the development process of its early academic conference is summarized. Next, the origin and historic development of the journal Theology of Mission is described. Although the journal was first published in 1997, it did not become officially authorized by the Korea Research Foundation until 2007, Finally, this study arranges the development of interdisciplinary cooperation and academic exchange in chronological order.
Virtual Reality, Film Marketing, and Value

This chapter examines Virtual Reality (VR) marketing content for several high-profile Hollywood films released between 2015 and 2019, focusing on the notion of value creation in this emerging and evolving area of promotion. It applies Atkinson and Kennedy's (2018) collaborative VR production ecosystem model to these case studies and questions how shared values might be constructed across complex multi-stakeholder collaborations, looking beyond consumer/producer binaries. More importantly, it asks whether there is really room for co-creation of value/meaningful brand engagement for the consumer, given the alleged centrality of the consumer in such an immersive experience and VR's reputation for increased empathy/affective involvement. Finally, it considers the ethical implications of immersing consumers in a piece of advertising in this way, as well as the data privacy implications for an emerging technology market dominated by social media giants like Meta and TikTok. The chapter concludes by identifying some of the key issues that need to be resolved at the industry-level and some practical steps that could be taken going forwards.
Reasoning with Quantified Modal Premises: Some Everyday Inferences May Be Logically Invalid

We present a theory of quantified modal reasoning, and four studies of individuals’ spontaneous conclusions that test its predictions. From premises, such as: All of those artists are businessmen, Paulo is possibly one of those artists, participants tended to conclude: Paulo is possibly a businessman (Experiment 1). This inference follows as necessary from an intuitive mental model that represents, say, three artists who are each businessmen, and Paulo as one of the artists. Deliberation can lead to a model in which Paulo is not an artist, which is consistent with the presupposition of the premise about him, but a possibility follows provided it holds in at least one correct model. Individuals tend to infer the model theory’s predicted conclusions about possibilities even when standard modal logics evaluate them as invalid (Experiment 2). The theory also predicts common errors, such as inferences of categorical conclusions from premises about possibilities (Experiment 3) and even from premises for modal syllogisms (Experiment 4). The paper concludes with a general account of quantified modal reasoning.
Comparison of machine learning classifiers for differentiating level and sport using movement data

The purposes of this study were to determine if 1) recurrent neural networks designed for multivariate, time-series analyses outperform traditional linear and non-linear machine learning classifiers when classifying athletes based on competition level and sport played, and 2) athletes of different sports move differently during non-sport-specific movement screens. Optical-based kinematic data from 542 athletes were used as input data for nine different machine learning algorithms to classify athletes based on competition level and sport played. For the traditional machine learning classifiers, principal component analysis and feature selection were used to reduce the data dimensionality and to determine the best principal components to retain. Across tasks, recurrent neural networks and linear machine learning classifiers tended to outperform the non-linear machine learning classifiers. For all tasks, reservoir computing took the least amount of time to train. Across tasks, reservoir computing had one of the highest classification rates and took the least amount of time to train; however, interpreting the results is more difficult compared to linear classifiers. In addition, athletes were successfully classified based on sport suggesting that athletes competing in different sports move differently during non-sport specific movements. Therefore, movement assessment screens should incorporate sport-specific scoring criteria.
Navigating the narrative: An eye‐tracking study of readers' strategies when Reading comic page layouts

Abstract In multimedia stimuli (e.g., comics), the reader must follow a narrative in which text and image both contribute information, and artists may use more irregular layouts which must still be followed correctly. While previous work has found that the external structure (outlines) of panels is a major contributor to navigation decisions in comics, other studies have shown that panel content can affect reading order. The present studies use eye‐tracking to investigate these contributions further. In Experiment 1, the reading behaviors on six layout variations were compared. The influence of the external structure was replicated, but an effect of text location was also found for one layout type. Experiment 2 focused on variations of this particular layout, manipulating the location of text within critical panels. Panel content was a consistent effect for all variations. While most navigation decisions are made using the external structure, content becomes key when resolving ambiguous layouts.
BIO MATERIAL MODELING QUANTUM CIRCUIT COMPRESSION

Bioelectronics is a perspective future of electronics. The modelling of the protein is an important part that allows to search the appropriate folding structure with applicable conductivity properties. The classical computers struggle from modelling large structures because of number degrees of freedom. The mathematical modelling inside the quantum programming paradigm is a possible way to overcome this factor. This work describes a simplification algorithm of bio material (protein) model used in bioelectronics
Refinement method for compressive hyperspectral data cubes based on self-fusion

Compressive hyperspectral images often suffer from various noises and artifacts, which severely degrade the imaging quality and limit subsequent applications. In this paper, we present a refinement method for compressive hyperspectral data cubes based on self-fusion of the raw data cubes, which can effectively reduce various noises and improve the spatial and spectral details of the data cubes. To verify the universality, flexibility, and extensibility of the self-fusion refinement (SFR) method, a series of specific simulations and practical experiments were conducted, and SFR processing was performed through different fusion algorithms. The visual and quantitative assessments of the results demonstrate that, in terms of noise reduction and spatial-spectral detail restoration, the SFR method generally is much better than other typical denoising methods for hyperspectral data cubes. The results also indicate that the denoising effects of SFR greatly depend on the fusion algorithm used, and SFR implemented by joint bilateral filtering (JBF) performs better than SRF by guided filtering (GF) or a Markov random field (MRF). The proposed SFR method can significantly improve the quality of a compressive hyperspectral data cube in terms of noise reduction, artifact removal, and spatial and spectral detail improvement, which will further benefit subsequent hyperspectral applications.
Digital image correlation based on the pre-deformation assist strategy and an optimized checkerboard-like speckle pattern for large deformation measurement

Large deformation measurement is one of the main issues faced by the digital image correlation method, and the specially designed speckle pattern offers a promising solution. This Letter suggests an extremely simple method to fabricate an optimized speckle pattern for large deformation problems. It demonstrates a more effective large deformation initial estimation capability and measurement accuracy when combined with the pre-deformation assist strategy. A series of simulated and real experiments are used to test the effectiveness of the proposed method, and the results reveal that it performs significantly better than the traditional method in large deformation problems.
Autonomous Logistic Transportation System for Smart Healthcare System

The operations of complex traffic conditions of connected automated vehicles and the perception of the road environment can be developed, due to the improvement in the accuracy and functions of the controller. Autonomous technology is a common research area in computer science in which artificial intelligence and machine learning are only a few of the subjects covered. In recent years, DL also displayed its enormous processing capacity by expanding its capabilities into increasingly complex areas. The information gathered from the literature survey below can be used in a variety of ways to progress the work. Similarly, each paper has its own set of advantages and disadvantages, as well as suggestions for overcoming the disadvantages. The Arduino platform seems to be a free and open-source electronics platform. It has simple hardware and software. A series of instructions can be written on the microcontroller using the Arduino programming language, which is based on Wiring, and the Arduino Software.
A Security Approach to Manage a Smart City's Image Data on Cloud

In the cloud environment, an enormous amount of the data is shared on the server for available access to the employees or customers related to the organization. Two main issues are generally faced when data is shared in a cloud environment: first is authenticating the user who can access the data, and second is securing the data itself. Seeing the concern, we proposed the hybrid concept, which involves role-based security and TPA-based security. By making use of role-based security, we have authenticated the users using the graphical authentication in which—first, the image required is selected, then the image gets segmented into image blocks, and when selected, then the pattern is formed, which is used for authentication. After that, when the user shares the file, then he/she specifies the role that can access the file.
FTX collapse will not spell end of crypto industry

Significance The firm’s lawyer has said that a "substantial amount" of FTX’s assets have been stolen or are missing; a cyber-crimes investigation has been opened. On November 18, US Commodity Futures Trading Commission (CFTC) commissioner Kristin Johnson urged crypto industry whistleblowers to come forward as Congress and regulatory agencies investigate FTX. The fallout is raising calls for greater regulation of a spottily regulated and opaque industry. Impacts Algorithms are proving no better than fallible humans in providing trust, transparency and accountability in financial transactions. Celebrity influencer marketing for cryptos will fall, since major US sports personalities will lose money invested in FTX. FTX's collapse will put at risk the Bahamas’ effort to become a digital currency trading hub. Concern over stifling crypto innovation will limit the guardrails that will be put in place.
Low-depth Circuit Implementation of Parity Constraints for Quantum Optimization

We present a construction for circuits with low gate count and depth, implementing three- and four-body Pauli-Z product operators as they appear in the form of plaquette-shaped constraints in QAOA when using the parity mapping. The circuits can be implemented on any quantum device with nearest-neighbor connectivity on a square-lattice, using only one gate type and one orientation of two-qubit gates at a time. We find an upper bound for the circuit depth which is independent of the system size. The procedure is readily adjustable to hardware-specific restrictions, such as a minimum required spatial distance between simultaneously executed gates, or gates only being simultaneously executable within a subset of all the qubits, for example a single line.
A Study on Kim Eun-seong’s Divisional Plays

This paper examines aspects of divisional plays appearing in Kim Eun-seong’s plays &lt;Yeonbyeon Mom&gt;(2011), &lt;Mokran Sister&gt;(2012), and &lt;Warriors of Sunshine&gt;(2016). There are two specific research goals. First, it is to argue that the author’s perspective on division is different from the previous division plays. Second, it examines the characteristics of the dramatic figuration of the target plays. As a result of the discussion, There are two common themes that appear in these plays. First, these plays imprison themselves in the harsh reality of this land. And critically reveal the loss of humanity that is being identified with the vulgar reality. Second, these plays call for reflection and cognitive transformation of the reader/ audience necessary to confront this reality and overcome it. These plays show several characteristics to dramatically shape the subject. To summarize, First, the characters show a certain comedy. And new perspectives can be found in points that cause comedy. Second, these plays is a characteristic that appears in the narrative composition. These plays shows a unique narrative composition and development in which the time and space of the narrative are mixed, and furthermore, the reality and the surreal are mixed. I considers these characteristics appearing in his plays are to be the basis for the popular success of his plays in matters of style. Third, The characteristic that appears in his plays is the power of narrative lead by the object. In particular, objects such as handkerchiefs/hammers/ notebooks/mirrors have unique meanings in the narrative. Also, they play a certain dramatic role. The author’s stories remain at the point of ‘pain and compassion’. There are also critical views. However, this paper paid attention to the fact that he introduces char-acters who reflect on their reality and strive to show the possibility of overcoming division in his works.
An exploratory study on the direction of writing-grammar integration education － Focusing on ‘accuracy’ and ‘appropriacy’

The purpose of this study is to find the direction of writing-grammar integration education by empirically exploring the understanding and application aspects of the concepts of accuracy and appropriacy required in the writing performance process. To this end, by analyzing previous discussions, we focused on accuracy and appropriacy as elements of intersection of writing education and grammar education, and examined how the national level curriculum treats them as educational content. In addition, in order to confirm the learner’s understanding of accuracy and appropriacy and practice of application, error correction items were developed and data were collected, and the results were analyzed by scoring and descriptive statistical analysis. Differences in learners’ understanding and performance of the concepts of accuracy and appropriacy and characteristics of each type were identified. This attempt will be able to provide the basis for the principle of educational contentization and the step-by-step educational content composition in that it captures the points to be considered first for the complete implementation of writing-grammar integrated education. In addition, it has significance as an empirical study to enhance the practicality of writing-grammar integrated education.