Reviewerly/exHarmony huggingface dataset:
The effect of library exterior design building on increasing student’s personal branding through selfie

Background of the study: The exterior design of the library building is an alternative in attracting visitors to come and visit. However, in reality this is not only limited as a means of promotion, it can even be a means of enhancing personal branding. This situation is currently happening to student of IPII UIN Sayyid Ali Rahmatullah Tulungagung who like to take selfies with the exterior view of the library building Purpose: This research aims to explain the effect of the exterior design of the UIN Sayyid Ali Rahmatullah library building on increasing student personal branding through selfies Method: This research uses quantitative methods with explanative approach. Data collection techniques through questionnaires, literature study, and observation. The population and sample were 50 students of IPII at UIN Sayyid Ali Rahmatullah Tulungagung who took selfies with the exterior background of the library building and used quota sampling for sampling. Findings: The results explain that there is an influence between the exterior design of the library building on student personal branding through selfies with a significance value of 0.000&lt;0.005 and an influence value of 35.3%. Conclusion: The exterior design of the UIN Sayyid Ali Rahmatullah Tulungagung library building had a significant impact on the personal branding of IPII students in the form of an increase in the number of likes, followers, comments, viewers. Some even got Paid Promote offers and endorsements
A Study of Attitudes, Skills, and Barriers Among the Special Education Hearing Impairment Teachers in the Use of Assistive Technology in Teaching

In the context of special education, most of the special education hearing impairment (SEHI) teachers understand that the use of assistive technology (AT) is a necessity in teaching and providing opportunities for SEHI students to control and improve their learning. However, the question of the acceptance of SEHI teachers use of AT in teaching is not much discussed. The objective of this study is to examine the attitudes, skills, and barriers of SEHI teachers to the use of AT in teaching. This study was conducted in special education secondary schools (SESS) in Selangor, Penang, Pahang, and Kedah. The sampling used was a purposive sampling of four respondents, consisting of two male teachers and two female teachers. The design of this study uses qualitative approaches, and interviews are the methods used as research instruments. The result of the study was an analysis of content (content analysis) by presenting the exact sentence of the respondent. The findings show the SEHI teachers have moderate attitudes and moderate skills towards the use of assistive technology in teaching, while the lack of cost, infrastructure, and resources for assistive technology is a barrier to the use of assistive technology in SESS. Discussions on the findings and recommendations to stakeholders have been raised to enhance the application of the assistive technology elements in the teaching of SEHI teachers in Malaysia.
A Creative Approach to Preparing Inclusive Music Lessons: The Role of Neuropedagogy in Inclusive Music Education

The article discusses the issue of music education for children with special needs in children’s art schools. It highlights the most relevant problem, namely, insufficient knowledge among music school teachers and art school teachers about the peculiarities of development and learning of such children. Besides, a significant gap in today’s music education is the lack of appropriate methods and techniques of music instruction that are suitable for learners with special educational needs. The article shows the most common disorders that allow for education in children’s music schools, reveals the difficulties encountered in teaching children with developmental delays and provides corresponding recommendations. The authors of this article believe that principles widely applied in corrective pedagogy can contribute to music education in children’s art schools. These principles include minimization, accessibility, cyclicity, intensification and comprehensiveness. When adapted to music pedagogy, they can be successfully incorporated into the educational process. Also, the article defines the category of children with special needs and describes a creative approach to preparing inclusive music lessons. Finally, it characterizes inclusion in music for children with developmental delays in mental and language abilities and identifies the role of neuropedagogy in inclusive music education.
STTA: enhanced text classification via selective test-time augmentation

Test-time augmentation (TTA) is a well-established technique that involves aggregating transformed examples of test inputs during the inference stage. The goal is to enhance model performance and reduce the uncertainty of predictions. Despite its advantages of not requiring additional training or hyperparameter tuning, and being applicable to any existing model, TTA is still in its early stages in the field of NLP. This is partly due to the difficulty of discerning the contribution of different transformed samples, which can negatively impact predictions. In order to address these issues, we propose Selective Test-Time Augmentation, called STTA, which aims to select the most beneficial transformed samples for aggregation by identifying reliable samples. Furthermore, we analyze and empirically verify why TTA is sensitive to some text data augmentation methods and reveal why some data augmentation methods lead to erroneous predictions. Through extensive experiments, we demonstrate that STTA is a simple and effective method that can produce promising results in various text classification tasks.
Novel approach for quantitative and qualitative authors research profiling using feature fusion and tree-based learning approach

Article citation creates a link between the cited and citing articles and is used as a basis for several parameters like author and journal impact factor, H-index, i10 index, etc ., for scientific achievements. Citations also include self-citation which refers to article citation by the author himself. Self-citation is important to evaluate an author’s research profile and has gained popularity recently. Although different criteria are found in the literature regarding appropriate self-citation, self-citation does have a huge impact on a researcher’s scientific profile. This study carries out two cases in this regard. In case 1, the qualitative aspect of the author’s profile is analyzed using hand-crafted feature engineering techniques. The sentiments conveyed through citations are integral in assessing research quality, as they can signify appreciation, critique, or serve as a foundation for further research. Analyzing sentiments within in-text citations remains a formidable challenge, even with the utilization of automated sentiment annotations. For this purpose, this study employs machine learning models using term frequency (TF) and term frequency-inverse document frequency (TF-IDF). Random forest using TF with Synthetic Minority Oversampling Technique (SMOTE) achieved a 0.9727 score of accuracy. Case 2 deals with quantitative analysis and investigates direct and indirect self-citation. In this study, the top 2% of researchers in 2020 is considered as a baseline. For this purpose, the data of the top 25 Pakistani researchers are manually retrieved from this dataset, in addition to the citation information from the Web of Science (WoS). The self-citation is estimated using the proposed model and results are compared with those obtained from WoS. Experimental results show a substantial difference between the two, as the ratio of self-citation from the proposed approach is higher than WoS. It is observed that the citations from the WoS for authors are overstated. For a comprehensive evaluation of the researcher's profile, both direct and indirect self-citation must be included.
Oversampling Method Based Covariance Matrix Estimation in High-Dimensional Imbalanced Classification

Class imbalance is a common problem in (binary) classification problems. It appears in many application domains, such as text classification, fraud detection, churn prediction and medical diagnosis. A widely used approach to cope with this problem at the data level is the Synthetic Minority Oversampling Technique (SMOTE) which uses the K-Nearest Neighbors (KNN) algorithm to generate new, artificial instances in the minority class. It is however known that SMOTE is not ideal for high-dimensional data. Therefore, we propose an alternative oversampling strategy for imbalanced classification problems in high dimensions. Our approach is based on the sparse inverse covariance matrix estimated trough the Ledoit-Wolf method for high-dimensional data. The results show that our proposal has a competitive performance with respect to popular competitors.
A New Proposal for Detection and Location of Cyberattacks in Industrial Processes

In the Industry 4.0 paradigm, the cybersecurity is a key aim to obtain high levels of performance of the industries based on the use of the IoT technology and the Big Data analysis. To achieve this objective, the cyberphysical industrial plants must be equipped with cybersecurity systems for early detection and location of cyberattacks. This paper presents a robust approach of an industrial cybersecurity system by using non-standard Pythagorean membership grades. The proposed scheme was validated using the Two-Tanks benchmark with excellent results. The proposal was compared with other computational intelligence tools recently presented in the scientific literature, and the results showed the best performance of the proposed scheme.
Web Alert: Microbes and plastics: An annotated selection of World Wide Web sites relevant to the topics in environmental microbiology

Environmental MicrobiologyVolume 25, Issue 12 p. 3771-3772 Web Alert Web Alert: Microbes and plastics: An annotated selection of World Wide Web sites relevant to the topics in environmental microbiology Lawrence P. Wackett, Lawrence P. Wackett McKnight Professor Department of Biochemistry, Molecular Biology & Biophysics, BioTechnology Institute, University of Minnesota, St. Paul, MN, 55108 USASearch for more papers by this author Lawrence P. Wackett, Lawrence P. Wackett McKnight Professor Department of Biochemistry, Molecular Biology & Biophysics, BioTechnology Institute, University of Minnesota, St. Paul, MN, 55108 USASearch for more papers by this author First published: 19 December 2023 https://doi.org/10.1111/1462-2920.16071Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume25, Issue12December 2023Pages 3771-3772 RelatedInformation
Audio-Instructional Strategy as A Panacea to Listening Challenges Among Primary Pupils in Ikere Local Government Area of Ekiti State

Listening is one of the language skills that poses challenges to learners most especially second language learners. The study finds out how audio-instructional strategy can be used to help learners: to discriminate English sounds, to improve listening comprehension and spelling abilities of learners. A sample of three hundred and twenty (320) are purposely selected across all public and private primary schools in urban and rural areas of Ikere Local Government of Ekiti State. There are two groups: experimental and control groups that are given pretest and posttest through an instrument tagged. “Effective Audio- Instructional Strategy Test” (EAIST). Three hypotheses were formulated and tested at 0.05 level of significance. The data collected are analyzed through t-test inferential statistics and the study finds out that those samples that are treated with audio-instructional strategy perform better than those not so treated in their abilities to discriminate English sounds, respond correctly listening comprehension questions and write correct spellings. The study recommends the use of audio- instructional strategy to ameliorate pupils’ listening challenges.
The English Learning Motivation of Chinese High School Students: Cross-grade Survey Analysis

Existing literature indicates that motivation is the most powerful determining factor that influences the rate and success of second language learning (Jiang, 2016; Kramsch &amp; Yin, 2018; Li &amp; Edwards, 2017; Liu et al., 2016; Liu, 2016; You &amp; Dörnyei, 2016; Zhi &amp; Wang, 2019). Currently, there is a growing body of empirical research indicating the changes in second language learning motivation in different grades at the same or different schools (Chambers, 1999; Kim, 2011, 2012a, b; Lamb, 2007; Williams et al., 2002). The findings of previous studies have mostly shown that student second language learning motivation increases with increasing school grades. Do¨rnyei (2000) suggested that concentrating on the time dimension of second language motivation is crucial for comprehending the second language motivation of students. However, the temporal variations of second language motivation, particularly motivational changes at different Chinese high school grades, have not been sufficiently emphasized by second language motivation researchers, therefore, this quantitative research investigated the changes in Chinese high school students’ English learning motivation from Grade 10 to Grade 12. An English learning motivation questionnaire was used and administered to 3000 students from Grades 10 to 12 in public high schools across mainland China, and employed the reliability analysis and analysis of variance to analyze quantitative data. The statistical results revealed that Grade 12 students ranked highest in English learning motivation, followed by Grade 11 and Grade 10 students. Furthermore, the college entrance examination had a positive impact on Grade 12 students' motivation to learn English.
PENGARUH PENGUASAAN DIKSI TERHADAP KEMAMPUAN MENULIS TEKS EKSPLANASI OLEH SISWA KELAS XI SMA NEGERI 1 SIABU

The purpose of this study was to determine the mastery of diction, the ability to write explanatory texts and the influence of diction mastery on the ability of explanatory texts of grade XI students of SMA Negeri 1 Siabu for the 2022-2023 academic year. The type of research used is quantitative with experimental design. The sampling technique was carried out randomly (random sampling) so that class XI IPA-3 was obtained as a research sample with a total of 31 students. The research Instrumens used are tests consisting of multiple choice to measure mastery of diction and essay tests to measure students' ability to write explanatory texts. Hypothesis testing is carried out through the "r" product moment correlation technique with the help of the SPSS Statistic program version 26. The results showed that the mastery of diction and explanatory text skills of grade XI students of SMA Negeri 1 Siabu for the 2022-2023 school year were still lacking with average scores of 45.48 and 40.16, respectively. The correlation test results show the value of r = 0.412 (medium) and the value of sig. 0.02 &lt; 0.05 so that the hypothesis is acceptable. The conclusion is that there is a significant influence of mastery of diction on the ability to write explanatory texts for grade XI students of SMA Negeri 1 Siabu for the 2022-2023 school year.
Method of influencing a student's attestation results through extracurricular activities

The article systematically analyzes, systematizes the impact of extracurricular activities of students on educational indicators and identifies the main characteristics. A methodology for assessing the impact of students' extracurricular activities on educational indicators using the Bayesian approach has been developed. Using the proposed methodology, reports were compiled based on a priori data and the impact of students' extracurricular activities on their success rates was assessed. Based on the a priori data obtained, it was determined that this effect does not exceed 30%.
The Influence of Virtual Banking on Operational Efficiency

This study investigates the integration of artificial intelligence (AI) into business processes and its effects on operational efficiency and customer satisfaction, focusing on two AI platforms, Zenith’s Virtual Banker, ZIVA and UBA’s Virtual Banker, LEO. Data were collected from respondents using a well-designed Google Form and were analysed using regression analysis. It was discovered that the major attractive features of LEO and ZIVA to customers included 24/7 availability for interaction, transaction processing, natural language processing (NLP) capabilities, personalized customer interactions. These features enhanced efficiency, customer engagement, and decision-making in business processes. Approximately 46% of respondents were satisfied that LEO improved customer satisfaction, while 50% were satisfied with ZIVA. Both platforms demonstrated a substantial positive impact on customer satisfaction, emphasizing their ability to enhance user experiences. Respondents showed a positive belief in the potential of both LEO and ZIVA to impact organizational processes positively, enhance decision-making, reduce response times for customer issues, and streamline business processes. While some skepticism exists, a substantial proportion held positive views, highlighting the importance of careful AI implementation. Analyses revealed that organizational processes had a significant positive impact on perceived improvement in operational efficiency for both LEO and ZIVA. Hypotheses were supported by statistical tests, indicating that both LEO and ZIVA improve customer experience and satisfaction, enhance operational efficiency, and contribute to revenue generation and business growth. In conclusion, the integration of AI, represented by LEO and ZIVA, offers substantial benefits in terms of improving customer satisfaction and operational efficiency. While some caution is warranted, these findings emphasize the transformative potential of AI in modern banking processes and underscore the need for continued research and development in the banking industry.
The Application of Artificial Intelligence Technology in Public Library Information Retrieval

With the continuous innovation and development of social science and technology, artificial intelligence technology has been the focus of attention and research in more and more industries. Public library, as an important place in the society to provide mass education for the masses, should fully seize the development opportunity with artificial intelligence technology as the core idea in the operation and development, carry out intelligent, automatic and digital reform and innovation of the library, and optimize the links of information retrieval, book borrowing, information service and access to the library. Through Internet technology, artificial intelligence technology and other advanced technologies, the whole science and technology content of public libraries and public service quality is improved so as to meet the specific needs of the public for the use of public education resources. Based on this, this paper first briefly describes the basic concepts of human intelligence technology and information retrieval technology, and then studies the specific application of artificial intelligence technology in public library information retrieval link and related service applications, hoping to provide some reference for professionals.
Research On the Current Situation and Technical Exploration of Network Security in Power Monitoring System

This paper analyzes the current situation of the network security of the power monitoring system, and discusses the weak link in the network security protection of the power monitoring system from the perspective of technical exploration. From the perspective of application, the application of trusted computing technology and malicious code technology in the security protection system of power monitoring system is discussed, so as to further ensure the network security of power monitoring system.
A Nanosyntactic Approach to Event/Result Nominalization in English

The main concern of the present study is to shed light on nominalization in English adopting nanosyntactic approach (Starke, 2009, 2011; Caha, 2011; Taraldsen, 2010). This paper analyzes the semanticosyntactic contribution of some selected deverbal nominalizers such as {-ing, -ation, -ment and -ism}. In addition, the researchers use Ramchand’s (2008) classification of verbs to get a profound understanding for the process of nominalization. It is hypothesized that the nouns formed by the deverbal nominalizers are the carriers of the semanticosyntactic features of verbal root. These features are atomic parts of the semantic features that are decomposed by split vP. The study finds that the noun formed by adding {-ing} has a hierarchical structure composed of three features: Case, process and Referential and as a result of Superset Principle it can lexicalize three structures: gerundive nominal that bears all three features, mixed nominal which has lost its case marking capability as a result of losing Case feature, and result/referential nominal that carries just one feature namely Referential.
Performance Differences Between Keras Model and Deep Learning CNN in Implementing an Age Classification System

This paper discusses about the performance differences between the Keras model and the deep learning convolutional neural network (DCNN), which was utilized in this paper, in classifying age. Gender was included as one of the predictions in the previous study which made their system slow. Hence, Gender was not considered in this paper. Initially, Adience dataset was used to train the DCNN model. To assess the performances between the two model, FG-net dataset was utilized to train the DCNN model, since it was the same dataset used to train the Keras model. Mean absolute error (MAE) was used to determine the accuracy of each of the model. The Keras model provides a 6.61% AME for each age label, while the DCNN achieved a 16.86% AME in all age range. Consequently, the Keras model performs better compared to the DCNN model because the latter's accuracy is a result from a specific age label and not from age range.
Word Translation of Filipino Sign Language Under Various Backgrounds

Filipino Sign Language is the official language used by the Mute and Deaf community in the Philippines and has been an essential aspect of their lives. However, not everyone has a vocabulary of the whole Filipino Sign Language. It is also known that Filipino Sign language is not within the Philippines curriculum, making it difficult for non-signers to communicate with the deaf community. There is research on ways to close the gap, such as image recognition through the convolutional neural network, hand edge detection, and glove-based methods. However, it does not account for the complexity of a natural environment rather than a plain background. The study aims to train a CNN model to detect Filipino Sign Language on a Raspberry Pi 4, displaying the results on an LCD screen. In comparison to another model [17], the researchers found no significant difference; however, the model has a lower Standard Deviation which points to a more consistent detection rate. The overall performance of the proposed system shows a recognition rate is 92.33% which shows that the system is reliable in recognizing Filipino Sign language from different backgrounds. Therefore, the algorithm is reliable enough to be used as FSL word translator and may be of help as a medium of communication to Mute and Deaf community in the Philippines.