Reviewerly/exHarmony huggingface dataset:
Direct tracking of noncircular sources for multiple arrays via improved unscented particle filter method

Abstract Direct tracking problem of moving noncircular sources for multiple arrays is investigated in this study. Here, we propose an improved unscented particle filter (I‐UPF) direct tracking method, which combines system proportional symmetry unscented particle filter and Markov Chain Monte Carlo (MCMC) algorithm. Noncircular sources can extend the dimension of sources matrix, and the direct tracking accuracy is improved. This method uses multiple arrays to receive sources. Firstly, set up a direct tracking model through consecutive time and Doppler information. Subsequently, based on the improved unscented particle filter algorithm, the proposed tracking model is to improve the direct tracking accuracy and reduce computational complexity. Simulation results show that the proposed improved unscented particle filter algorithm for noncircular sources has enhanced tracking accuracy than Markov Chain Monte Carlo unscented particle filter algorithm, Markov Chain Monte Carlo extended Kalman particle filter, and two‐step tracking method.
File System Organizer

According to development requirements, a standardized management system is mainly used in basic information management files, file statistics and query management, file lending management. Development files for standardized management system that school personnel more efficient file management functions within the scope of work documents, files, archiving and management, promoting the school to improve the level of records management staff, increase their strength, and speed up the school on the pace of information technology to make the management more standardized and efficient. This paper introduces The Design and Development of a School File Management System for Standardized. Keywords- file; management system; standardization. In order to better manage the school’s archives, in order to better ensure the integrity of the archives, to standardize the school to the records management standard, my company decided to develop school file standardized management system. Therefore, the file management system from unit files management practice, in accordance with national standards and relevant industry standards at the same time, in the “people-oriented” principle, suitable for the development of the middle and primary school of the characteristics of the actual file management software Key Words: Files, organized, Management, Data, Storage, System
Public Speaking Anxiety among College Students at St. Paul University Surigao

Public speaking is the act of making speeches in public or the art of effective oral communication with an audience. Fear of public speaking is common among students and the general population. The National Institute of Mental Health Report stated that public speaking anxiety is considered a social anxiety disorder (Brewer, 2001). This research aimed to find out the public speaking anxiety among college students of St. Paul University Surigao. It sought to answer the participants’ anxiety levels as Trait Anxiety, Context Anxiety, Audience Anxiety, and Situation Anxiety. The data were tested for the significant difference when grouped according to their profile. The researchers utilized the quantitative descriptive survey design using a researcher-made questionnaire that was subjected for validity and reliability checking and was administered to 81 education students. The findings revealed that students experienced very high Audience Anxiety while only high Trait, Context and Situation Anxieties. Furthermore, the findings found no significant difference in the participants’ level of anxiety when grouped according to profile. This means that anxiety level remains the same regardless of age, sex, and year level. Hence, it is recommended that public speaking should be offered as a subject to all degree programs at the tertiary level especially for teacher education programs. Also, the school administrators should encourage more public speaking activities in and out of the school where students would participate in such public speaking events to hone skills, thus, minimizing public speaking anxieties.
Text Encryption with Improved Elliptic Curve Cryptography

The security of data encrypted with an encryption algorithm should be guaranteed such that it is never easy for a third party to recover the message from the encrypted data. To this effect, ECC has been a reliable option. However, the base equation that defines the security of Elliptic Curve Cryptography (ECC) is in the form of a linear equation with one unknown which is easy to solve. The ease with which this equation can be solved is a weak point in the algorithm. Thus, the aim of this research work is to improve the security of ECC by improving the nature of its base linear equation.&#x0D; Elliptic curve arithmetic was used to develop the improved model. The encryption process was specifically targeted and improved from single to double encryption using separate encryption constant for each round of encryption. Simulation was done using a 256 bits key size on selected number of character inputs. Java programming language was used to simulate the model on Net Beans IDE. Results of the research show that despite a longer key size of 256 bits and double encryption process, the improved ECC performed better than the existing ECC model in both encryption and decryption times, but compared to RSA, the encryption is higher while the decryption time is lower. Generally, this shows that the improved ECC out – performed the existing systems and is therefore better.
Effectiveness of a Training Program Based on Infographic Technique in Providing Corona Virus Prevention Skills (COVID-19) for Children with intellectual disabilities (Educable)

The current study aims to study the effectiveness of a training program based on infographic technique in providing Corona Virus Prevention Skills (COVID- 19) for children with intellectual disabilities (Educable). Ten children with intellectual disabilities (Educable) and their caregivers are cohesion as a sample for this study, with an average age of (12.9) years, and average intelligence (69). Corona Virus Prevention Skills Scale was applied to the sample, then the program was applied to them. After that the telemetry and tracking were applied on the sample. The results show that: there are statistically significant differences between the mean levels of the group members ’scores in the pre and post procedural measurements on the Corona virus prevention skills scale for people with intellectual disabilities at the level (0.01) in the direction of the post measurement. Moreover, there is no statistically significant differences between the mean scores of the group members ’scores in the two-dimensional and consecutive measurements (one month after the end of the program) on the Corona Virus Prevention Skills for Persons with Intellectual Disabilities scale. The study recommends the need to train people with intellectual disabilities in skills to prevent viruses and infectious diseases, and the use of infographic techniques in various training programs. Key words: Infographic - Prevention Skills - Corona Virus (COVID- 19) - Intellectual Disabled (Educable).
EXPLORATORY DATA ANALYSIS ON ASIA CUP CRICKET DATA

The Asia Cup is a cricket tournament featuring teams from all over Asia.Analyzing Asian Cup data can provide valuable insights into the performance of individual teams and players.By analyzing data on batting and bowling statistics, team strategies, and player performance, it is possible to identify trends and patterns that can be used to inform future decisions related to team selection, game strategy, and player development.As well, data analysis can help determine each team's strengths and weaknesses, which can be used to inform game plans and improve overall performance.Overall, data analysis of the Asia Cup can provide valuable insights into the performance of teams and players, and can help to inform future decisions related to game strategy and player development.
Effects of Covid-19 pandemic on organizational transformation and employee’s performance

This study explored 'Effects of Covic-19 Pandemic on Organizational Transformation and Employees Performance' with specific focus on Veritas University Abuja, Nigeria.Corona Virus is a pandemic of monumental consequences to health, world economy and well-being of individual that changes our ways of life.The goal of this investigation was to ascertain the degree to which Covid-19 driven change impact positively on employees' and organizational performance.Literatures were reviewed and a survey and descriptive research design was adopted.438 questionnaires were dispersed via expediency sampling technique to staff from different programmes.Nevertheless, only 394 questionnaires which were properly filled and retuned were used for the analysis.Quantitative approach, which involved using the ranking data's Spearman rank correlation coefficient for data analysis.The findings posit that Covid-19 driven transformations have both positive and negative connection with the employees' performance and job satisfaction.This shows that Covid-19 driven transformations does not encourage staff to deliver better work, and the result thus, is high employees' turnover.Finding further depict that, the Covid-19 motivated transformations have positive relationship with organizational performance as per the level of expectations.The researchers recommended that, institutions or firms should embrace the conventional 'new normal' behavior of performing task and responsibility, build hi-tech capability and show flexibility and desire to embrace changes in technology.
Self-supervised Guided Hypergraph Feature Propagation for Semi-supervised Classification with Missing Node Features

Graph neural networks (GNNs) with missing node features have recently received increasing interest. Such missing node features seriously hurt the performance of the existing GNNs. Some recent methods have been proposed to reconstruct the missing node features by the information propagation among nodes with known and unknown attributes. Although these methods have achieved superior performance, how to exactly exploit the complex data correlations among nodes to reconstruct missing node features is still a great challenge. To solve the above problem, we propose a self-supervised guided hypergraph feature propagation (SGHFP). Specifically, the feature hypergraph is first generated according to the node features with missing information. And then, the reconstructed node features produced by the previous iteration are fed to a two-layer GNNs to construct a pseudo-label hypergraph. Before each iteration, the constructed feature hypergraph and pseudo-label hypergraph are fused effectively, which can better preserve the higher-order data correlations among nodes. After then, we apply the fused hypergraph to the feature propagation for reconstructing missing features. Finally, the reconstructed node features by multi-iteration optimization are applied to the downstream semi-supervised classification task. Extensive experiments demonstrate that the proposed SGHFP outperforms the existing semi-supervised classification with missing node feature methods.
3M3D: Multi-view, Multi-path, Multi-representation for 3D Object Detection

3D visual perception tasks based on multi-camera images are essential for autonomous driving systems. Latest work in this field performs 3D object detection by leveraging multi-view images as an input and iteratively enhancing object queries (object proposals) by cross-attending multi-view features. However, individual backbone features are not updated with multi-view features and it stays as a mere collection of the output of the single-image backbone network. Therefore we propose 3M3D: A Multi-view, Multi-path, Multi-representation for 3D Object Detection where we update both multi-view features and query features to enhance the representation of the scene in both fine panoramic view and coarse global view. Firstly, we update multi-view features by multi-view axis self-attention. It will incorporate panoramic information in the multi-view features and enhance understanding of the global scene. Secondly, we update multi-view features by self-attention of the ROI (Region of Interest) windows which encodes local finer details in the features. It will help exchange the information not only along the multi-view axis but also along the other spatial dimension. Lastly, we leverage the fact of multi-representation of queries in different domains to further boost the performance. Here we use sparse floating queries along with dense BEV (Bird's Eye View) queries, which are later post-processed to filter duplicate detections. Moreover, we show performance improvements on nuScenes benchmark dataset on top of our baselines.
Masked Gradient-Based Causal Structure Learning

This paper studies the problem of learning causal structures from observational data. We reformulate the Structural Equation Model (SEM) with additive noises in a form parameterized by binary graph adjacency matrix and show that, if the original SEM is identifiable, then the binary adjacency matrix can be identified up to super-graphs of the true causal graph under mild conditions. We then utilize the reformulated SEM to develop a causal structure learning method that can be efficiently trained using gradient-based optimization, by leveraging a smooth characterization on acyclicity and the Gumbel-Softmax approach to approximate the binary adjacency matrix. It is found that the obtained entries are typically near zero or one and can be easily thresholded to identify the edges. We conduct experiments on synthetic and real datasets to validate the effectiveness of the proposed method, and show that it readily includes different smooth model functions and achieves a much improved performance on most datasets considered.
Complexity of Maker-Breaker Games on Edge Sets of Graphs

We initiate the study of the algorithmic complexity of Maker-Breaker games played on the edge sets of general graphs. We mainly consider the perfect matching game and the $H$-game. Maker wins if she claims the edges of a perfect matching in the first, and a copy of a fixed graph $H$ in the second. We prove that deciding who wins the perfect matching game and the $H$-game is PSPACE-complete, even for the latter in small-diameter graphs if $H$ is a tree. Toward finding the smallest graph $H$ for which the $H$-game is PSPACE-complete, we also prove that such an $H$ of order 51 and size 57 exists. We then give several positive results for the $H$-game. As the $H$-game is already PSPACE-complete when $H$ is a tree, we mainly consider the case where $H$ belongs to a subclass of trees. In particular, we design two linear-time algorithms, both based on structural characterizations, to decide the winners of the $P_4$-game in general graphs and the $K_{1,\ell}$-game in trees. Then, we prove that the $K_{1,\ell}$-game in any graph, and the $H$-game in trees are both FPT parameterized by the length of the game, notably adding to the short list of games with this property, which is of independent interest. Another natural direction to take is to consider the $H$-game when $H$ is a cycle. While we were unable to resolve this case, we prove that the related arboricity-$k$ game is polynomial-time solvable. In particular, when $k=2$, Maker wins this game if she claims the edges of any cycle.
Amplitude-dependent modal coefficients accounting for localized nonlinear losses in a time-domain integration of woodwind model

This article develops the design of a sound synthesis model of a woodwind instrument by modal decomposition of the input impedance, taking into account viscothermal losses as well as localized nonlinear losses at the end of the resonator. This formalism has already been applied by Diab et al. [ Journal of Sound and Vibration 528 (2022) 116892] to the study of forced systems. It is now implemented for self-oscillating systems. The employed method extends the definition of the input impedance to the nonlinear domain by adding a dependance on the RMS acoustic velocity at a geometric discontinuity. The poles and residues resulting from the modal decomposition are fitted as a function of this velocity. Thus, the pressure-flow relation defined by the resonator is completed by new equations which account for the dependence with the velocity at the end of the tube. To assess the ability of the model to reproduce a real phenomenon, comparisons with the experimental results of Atig et al. [PhD thesis, Université du Maine (2004)] and Dalmont and Frappé [ Journal of the Acoustical Society of America 122(2) (2007) 1173–1179] were carried out. Simulations show that the model reproduces these experimental results qualitatively and quantitatively.
A Critical Evaluation of Google Translation: The Case of English-Sorani Kurdish Translation

Google Translate is one of the most frequently and actively used machine translation services worldwide. Sorani Kurdish, otherwise known as Central Kurdish, was officially added to Google Translate in May 2022. At the onset of the launch of Sorani Kurdish translation services, it is crucial to evaluate the quality of the translation and pave way for improvements, if necessary. Taking into consideration both linguistic and cultural aspects, this paper aims to critically investigate the accuracy of English-Sorani Kurdish translations produced by Google Translate. For this purposes, the paper has adopted a textual analysis approach based on the notion of equivalence to critically analyze samples of translations generated by Google Translate. The results suggest that Google Translate is largely accurate at morphological and syntactic levels but improvements are needed to improve minor deficiencies detected in rendering ‘future perfect tense’, ‘third conditional sentences’ and passive tenses, especially in the case of ‘present progressive’ and ‘past progressive’ tenses. With regard to the semantic level, Google Translate has proved accurate in processing polysemous words, but it has assumed a total failure in translating idioms and proverbs. At the cultural level, in over third-fourths of instances Google Translate renders English cultural terms into Sorani Kurdish accurately, whereas in nearly one-fourth of instances it offers inappropriate translation. As far as English into Sorani Kurdish translation is concerned, Google Translate can be deemed effective as a supportive translation tool but it is far from being perfect, and continuous improvements will be needed to respond to the deficiencies unearthed in this study.
About the Challenges of Cybercrime in the Digital Age

With the COVID-19 pandemic and The Fourth Industrial Revolution: Digital Transformation, society is facing a global problem – cybercrime. Every single day, the management of different companies experiences more difficulties in ensuring prevention from hacker attacks. Prevention from cyberattacks is becoming an international problem for businesses, causing significant financial losses. For the aim of the article, some sectors were analyzed – the insurance and banking industry which face the challenge of “cybercrime” because their activities are almost completely digitalized. It is important to notice the arguments of the competent authorities investigating cybercrime. The whole digitalization of the business processes in enterprises requires additional resources for combating this kind of crime. The anonymous nature of these acts also threatens international security. Operational authorities also face these challenges. A change in international law regulation is necessary, in the management directed against digital risks and anomalies in IT security in administration and business.
Propagation Theories for Applied Logic

We examine logic in collaborative motion, as people communicate, find information and draw conclusions. We compare the timestamp traces of purely logical events with the timestamps of collaborative events and find a lawlike velocity ratio.
Investigation of processing test results based on knowledge similarity

The traditional scoring is based on the difficulty of the task. However, the same total score can be earned with different knowledge, hence it is difficult to create homogenous groups by only relying on the total score. In our work, we aim to present a new scoring method where such knowledge-based groups can be created, as opposed to the previous point-based method. For comparison of the test result done by the students, we utilized different distance measures. The main challenge with finding the similarities between the results is the high dimensionality of the data compared to the total number of observations. First, we used the traditional Minkowski distance with different p values, then we used local similarity hashes and high dimensional embedding techniques designed originally for natural language processing. With these never before used techniques, we were able to identify students with similar skillsets and knowledge. Furthermore, we utilized dimension reduction methods (t-SNE and UMAP) to make a lower dimension representation where we can cluster the data easier. These clusters and pairwise similarities were assessed by oral exam subjective scores. The teacher's subjective scores correlated more with this new metric-based method of scoring than the total test score itself. The presented procedures can not only be used effectively in research but can also help to get a more complete picture of the students' knowledge we teach in everyday practice.
THE USE OF THE DUOLINGO GUESSING GAME APPLICATION IN TEACHING SPEAKING ABILITY TOWARD 8TH - STUDENTS

The Use Of The Duolingo Guessing Game Application In Teaching Speaking Ability Toward 8th - Students. This study was aimed to analyze how students use the game application named Duolingo, as an English learning application, to evaluate its benefit to help students in learning English and to assess students' skills in speaking. The data for this research was collected by using post and pre-test methods in research techniques. The data source was students from SMP Muhammadiyah 1 Medan, focused on 8th grade by providing multiple-choice questions by using Duolingo Applications. The quantitative design was used in this study and the techniques for data analysis include (1) data collection procedures, (2) data analysis techniques, and (3) conclusions. Based on analysis findings, students provided improvements to English learning and they speak more smoothly with a better tone. However, learning English has a number of advantages, and since Duolingo is a form of multiple choice test so the students enjoy, and it help the problem of speaking and use repetition of words so the students can follow how to say or speak.