Reviewerly/exHarmony huggingface dataset:
Research Growth of Engineering Faculty Universitas Negeri Padang: A Bibliometric Study of Journal

This research aimed to conduct a comprehensive literature review of all papers from the beginning of time published by the Faculty of Engineering at Universitas Negeri Padang and indexed in the SINTA database using bibliometrics analysis. It started with a query to the DOI (Digital Object Identifier) database. The papers from this scholarly publication may be accessed here. A total of 1094 papers from 7 journals were collected. Each paper published by the Engineering Faculty at Universitas Negeri Padang receives an average of 0.42 citations. Given the insignificance of this average, it seems likely that the publication's contribution has yet to be fully recognized and has only had a little effect on the global state of knowledge. According to the findings, Universitas Negeri Andalas researchers collaborate the most with their peers around the country. Contrast this with the declining frequency with which multinational teams work together. With 38 articles published and ten citations obtained, Ahmaddul Hadi of the Informatics Department stood out as the most productive author. Research conducted by this faculty has been widely disseminated due to its publication in the reputable academic journal Inovasi Vokasi Dan Teknologi (INVOTEK).
Comparison of Korean Speech De-identification Performance of Speech De-identification Model and Broadcast Voice Modulation

In broadcasts such as news and coverage programs, voice is modulated to protect the identity of the informant. Adjusting the pitch is commonly used voice modulation method, which allows easy voice restoration to the original voice by adjusting the pitch. Therefore, since broadcast voice modulation methods cannot properly protect the identity of the speaker and are vulnerable to security, a new voice modulation method is needed to replace them. In this paper, using the Lightweight speech de-identification model as the evaluation target model, we compare speech de-identification performance with broadcast voice modulation method using pitch modulation. Among the six modulation methods in the Lightweight speech de-identification model, we experimented on the de-identification performance of Korean speech as a human test and EER(Equal Error Rate) test compared with broadcast voice modulation using three modulation methods: McAdams, Resampling, and Vocal Tract Length Normalization(VTLN). Experimental results show VTLN modulation methods performed higher de-identification performance in both human tests and EER tests. As a result, the modulation methods of the Lightweight model for Korean speech has sufficient de-identification performance and will be able to replace the security-weak broadcast voice modulation.
Abstract 5437: Vision transformers for breast cancer human epidermal growth factor receptor 2 (HER2) expression staging without immunohistochemical (IHC) staining

Abstract Purpose: Staging of human epidermal growth factor receptor 2 (HER2) expression is crucial for evaluating the effectiveness of breast cancer treatment. However, it involves an expensive and challenging immunohistochemical (IHC) staining in addition to hematoxylin and eosin (H&amp;E) staining. Here, we argue that customized vision transformers are effective in breast cancer HER2 expression staging using only H&amp;E-stained images. Methods: Our algorithm has three modules: a localization module to weakly localize the necessary features of an image via spatial transformers, an attention module to learn global features from the image using vision transformers, and a loss module that determines the closest one to a HER2 expression level from input images by calculating the ordinal loss. We utilized a publicly available breast cancer HER2 expression dataset, the breast cancer immunohistochemical image (BCI) dataset, which contains paired H&amp;E and IHC stained images. Results were calculated with 95% confidence intervals and t-test was used to evaluate the significance of the proposed model against other models. Results: Our approach achieved area under receiver operating characteristics curve (AUC), precision, sensitivity, and specificity of 0.9202±0.01, 0.922±0.01, 0.876±0.01, and 0.959±0.02, respectively, averaged over five-fold cross-validation, in staging HER2 expression. The proposed method showed better performance than the conventional vision transformer model and state-of-the-art convolutional neural network models with statistical significance of p&amp;lt;0.01 in all cases. Conclusion: Our findings are important in assisting HER2 expression staging in breast cancer treatment, while avoiding the need for an expensive and time-consuming IHC staining procedure. Comparison of the proposed model with state-of-the-art models. CNN-convolutional neural network Study Neural network Model AUC Couture et al. (2018) CNN VGG16 0.75 Shamai et al. (2019) CNN ResNet50 0.74 Yang et al. (2021) CNN ResNet50 0.76 Naik et al. (2020) CNN ResNet50 0.78 Khater et al. (2021) CNN ShuffleNet 0.75 Conde-Sousa et al. (2022) CNN EfficientNet 0.88 Farahmand et al. (2022) CNN InceptionV3 0.90 Proposed Vision transformer vitb_16 0.92 Citation Format: Gelan Ayana, Eonjin Lee, Se-woon Choe. Vision transformers for breast cancer human epidermal growth factor receptor 2 (HER2) expression staging without immunohistochemical (IHC) staining. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5437.
Development of domestic information technologies: new products of the Russian market

The author analyzed the creation of new domestic technologies in the field of IT directory services. The history of the appearance of this technology on the market is noted, the problems of creating a domestic catalog service are evaluated.
Non-English Majors’ Use of Canvas-based Language Learning Activities at Dong Nai Technology University

Currently, the foremost embraced and excellent way of advancing scholastics in presumed informative set up worldwide is online learning and due to the COVID-19 epidemic with its effects on most of the world; therefore, applying new E-learning methods to bring knowledge to all of the students is necessary than ever. This study, consequently, attempts to investigate the effect of Canvas-based language learning activities on non-English major students’ use. It involved seventy second-year students at Dong Nai Technology University in Bien Hoa City where the current study was conducted. Both quantitative and qualitative data were obtained through two instruments, namely questionnaires, and interviews. Descriptive statistics were employed for data analysis by using SPSS 20.0 and 3-interview questions were used to ask fifteen students. The results revealed that classroom Canvas-based language learning activities had an effect on non-English majors. This study is expected to point out Canvas’s advantages in efficaciously helping students with their language learning.
The Impact of Human Resource Training on Employee Turnover in London

Purpose: The study aims to investigate the effect of human resource training on employee turnover in London.&#x0D; Methodology: The study adopted a desktop methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low-cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.&#x0D; Results: The literature review indicates that human resource training can significantly impact employee turnover in London. Specifically, research suggests that training programs can improve employee job satisfaction, increase employee engagement, and enhance organizational commitment, all of which can contribute to reducing turnover rates. Furthermore, the review highlights the importance of training program design, delivery, and evaluation in achieving positive outcomes. Effective training programs should be tailored to the specific needs of employees and organizations, utilize a variety of training methods, and be regularly evaluated to ensure their effectiveness. Additionally, the review suggests that factors such as organizational culture, leadership, and employee motivation may influence the impact of training programs on turnover rates. Overall, the findings suggest that human resource training can be a valuable tool for reducing employee turnover in London, but more research is needed to determine the optimal training strategies for different types of organizations and employees.&#x0D; Unique Contribution to Theory, Practice and Policy: This study shows that human resource training programs can reduce employee turnover rates in London. Effective program design, delivery, and evaluation are important, and factors like organizational culture, leadership, and employee motivation can influence their impact. Organizations should invest in tailored, diverse, and regularly evaluated training programs. Policy makers should prioritize training policies that promote well-being and organizational performance.
Research on Developing Project Teaching Method in Computer Course Teaching

This article focuses on the research and analysis of project-based teaching methods in the teaching of computer courses. Based on the existing problems in traditional education of computer courses and the application methods of project-based teaching methods in computer course teaching, it conducts in-depth discussions and analysis from the following aspects: student-oriented teaching, building a complete teaching system, and building a complete evaluation mechanism, Its purpose is to strengthen the value of project-based teaching methods in computer course teaching. This article focuses on the research and analysis of project-based teaching methods in computer course teaching, combining the existing problems in traditional education of current computer courses and the application methods of project-based teaching methods in computer course teaching as the main basis, from student-oriented teaching to building a complete teaching system The purpose of in-depth discussion and analysis on the construction of a complete evaluation mechanism is to strengthen the value of project based teaching methods in computer course teaching,
A.N. Parshin (1942–2022): Volunteer of the Best

The article is dedicated to the memory of Alexey Nikolaevich Parshin (1942–2022), an outstanding mathematician, academician of the Russian Academy of Sciences, a scientist with universal interests, who devoted a lot of attention to general problems of science and culture. The author of the article uses the rich philosophical and theoretical heritage of A.N. Parshin, archival materials and personal memories. Initiator of the seminar on Russian philosophy, A.N. Parshin in his works on Russian philosophy traced in particular the theme of its inter­action with natural and exact sciences. The article shows that the axis of A.N. Parshin’s Weltanschauung was Christian Platonism, like that of Pavel A. Flo­rensky, whose work made an indelible impression on him and introduced him to the world of philosophy. The author of the article reveals the specifics of A.N. Parshin’s approach to the humanities, to the problem of the unity of knowl­edge and religious culture. Special author’s attention is paid to such a problem as that of cycles and rhythms in the structure of time, which combines the ideas of various sciences and cultural traditions. This problem was of particular interest to A.N. Parshin. The article also gives the general characteristic of the creative personality of A.N. Parshin, which is based on the concept of heroic philoso­phy, referring to the later stage of the philosophical evolution of F. Ravaisson, the French spiritualist, the predecessor of H. Bergson.
DIGITAL TRANSFORMATION OF THE HIGHER EDUCATION SYSTEM

The subject of the study is the digital transformation of the higher education system. The purpose of the study is to assess the impact of the development of digital and information technologies on the educational services market. The objectives of the study are to analyze current economic and technological trends affecting the transformation of the educational services market; to assess the impact of the development of digital information technologies on the quality of educational services of higher education; to identify changes in the nature and forms of education, requirements for professional skills and abilities; to identify the risks of digitalization for the higher education system. The novelty of the research lies in the author's approach to the definition of the concept "digital educational environment" and it essence. Conclusions: identified trends in the development of the education system allowed us to identify a number of problems associated with an insufficient level of infrastructure, disrupted communication between higher education institutions and employers, slow introduction of technologies into the digital activities of higher education institutions, etc.
Geochemical distribution in residual soils of Iberian Pyrite Belt (Spain)

Abstract The Iberian Pyrite Belt (IPB) is a volcanic- and shale-hosted massive sulfides world-class province of the Upper Paleozoic age that includes some supergiant ore deposits with a unique mining operations history. An extensive soil (multi-element) geochemical survey in the IPB has been performed to create a geochemical database to increase the knowledge of the studied area. Both univariate and multivariate treatments have been done to manage a large amount of new data. The studied area shows higher background concentrations of several elements (e.b. Cu, Pb, Zn, Cd, Sn, In, Bi, As, or Sb) than in other terrains in Spain due to the IPB volcano-sedimentary ore deposits and their associated mining wastes. Mapping chemical elements help understand their behavior, controls and associations in natural environments. According to this, the mono-elemental contour maps show single-element distributions with geological control (e.g., Na), ore deposit control (e.g., Cu) or a mixture of both. On the other hand, multivariate analysis has been applied to reduce the large geochemical database maintaining the same information. We have chosen Factorial Analysis (FA) and obtained six factors that explain approximately 70% of the variability. Four of these factors (F1, F2, F4 and F5) show an intense geological control that improves the geological information of the IPB, while the other two (F3 and F5) show an ore deposit control. These factors allow distinguishing between different types of deposits in the IPB and help discover new possible exploration targets for future studies.
Lineament Patterns and Structural, Tectonic, and Neotectonic Control in the Relief of the Pancas Region (Espírito Santo, Southeast Brazil)

The main objective of this research is to investigate the lithostructural, tectonic, and neotectonic control on the relief of the Pancas region (Espírito Santo, Southeastern Brazil). The methodology was organized into computer and field analyses. In a computer, lineament and structural trend maps were generated from the manual extraction technique using editing tools of ArcGIS 10.3.1™ software (ESRI, 2012) over a Digital Elevation Model (DEM) with different artificial illumination (scale 1:110.000) and orientation rosettes were generated. The geological and geomorphological maps were organized/elaborated with ArcGIS from the Geographic Information System (GIS). The cartographic bases were configured in the UTM projection system, and DATUM SIRGAS 2000, zone 24S, and later analyzed and compared with the data of the orientations of the dedicated lineaments, with the orientation of the studied outcrop failures and with the existing literature. The results presented NW-SE/NNW-SSE and NE-SW/NNE-SSW orientations, with the predominance of NNW-SSE and NW-SE orientations identified in the analysis of the lineaments and structural trends, similar to the orientations of the geological faults and neotectonic faults present in the studied area, reflecting the regional structuring of the area, presenting the same orientations as the Colatina Belt. The secondary orientations of the Araçuaí Orogen (NE-SW), the identification of morphotectonic features, the presence of abrupt topographic differences (topographic profiles), and the identification of tectonic regions (base surface map) and tectonic blocks (scanning profile) demonstrate the tectonic control in the relief of the Pancas-ES region, achieving the objective of this research.
An Adaptive Fusion Feature Extraction Algorithm Based on CNN

Keypoint feature extraction algorithms based on manual feature rely on the professional domain knowledge of the designer, and usually perform well in depicting the detail of an image. However, these manual feature-based feature extraction algorithms tend to fail in obtaining the abstract information of the image, which results in low robustness of the algorithms. In view of this, this paper proposes an image feature extraction algorithm that adaptively integrates the low layer feature of CNN and the high layer feature of CNN. The proposed algorithm makes use of fact that the low layer feature can detect the detail of an image and the high layer feature can detect the abstract information of the image. Meanwhile, the similarity between the area descriptors of two feature points is employed to adaptively determine the weight of the high layer feature and that of the low layer feature in the integrated feature, so as to realize the trade-off between distinguishability and invariance of features, and make the integrated feature more robust. Experiments on HPatches, Oxford, and RDNIM datasets show that the proposed algorithm is not only robust to illumination changes, but also shows superior performance when it comes to challenging scenes such as large viewing angle changes and day and night matching.
A Channel-level Neural Network Compression Method Based on K-order Statistics

At present, deep neural networks (DNNs) have been widely used, and the deployment of DNNs to resource-constrained devices becomes a popular trend, which leads to the problem of compression of deep neural networks. In this paper, we propose a channel-level deep neural network compression method, which aims to remove unimportant channels in the network, reduce the number of neural network parameters, and improve the performance of the compressed neural network. Specifically, to reduce channel redundancy more effectively, our approach introduces K-order statistics in the Batch Normalization (BN) layer, identifies and removes channels with low statistical values to generate a compact network, and improves the accuracy of the compressed network by fine-tuning. Our approach does not change the DNN architecture and does not require special hardware and software accelerators for the generated compression network. Our method was tested on CIFAR-10 image classification public dataset with various DNN models. By comparing with other model compression methods, the effectiveness of our method has been demonstrated.
DMobile-ELA: Digital Image Forgery Detection via cascaded Atrous MobileNet and Error Level Analysis

With the current developments in technology, not only has digital media become widely available, the editing and manipulation of digital media has become equally available to everyone without any prior experience.The need for detecting manipulated images has grown immensely as it can now cause false information in news media, forensics, and daily life of common users.In this work, a cascaded approach DMobile-ELA is presented to ensure an image's credibility and that the data it contains has not been compromised.DMobile-ELA integrates Error Level Analysis and MobileNet-based classification for tampering detection.It was able to achieve promising results compared to the state of the art on CASIAv2.0 dataset.DMobile-ELA has successfully reached a training accuracy of 99.79% and a validation accuracy of 98.48% in detecting image manipulation.
Hate Speech and Bad Language: The Ugly Face of Social Influencers and Its Impact on Brands: An Abstract

In light of the growing trend of influencer marketing, ample research has been conducted on its success factors (Lin et al., 2018). However, one success factor has rarely been considered: Influencers’ moral integrity, i.e., the absence of scandals. This is all the more surprising because the absence of scandals has been identified as the first and most important requirement for the success of any celebrity – above other much more frequently discussed requirements such as attractiveness, expertise or trustworthiness (Amos et al., 2015). As influencers’ main field of activity is the Internet, a major scandal may become a worldwide event in a matter of hours (Piazza & Jourdan, 2018). In addition, a scandal caused by an influencer is likely to become dangerous for an endorsed brand, which will be considered “guilty by association” (Appel et al., 2020; Kintu & Ben-Slimane, 2020). In the course of this work, we focus on five Hate Speech & Bad Language Scandals. These are: (1) Common use of Swearwords, (2) Gossiping, (3) Insulting followers, (4) Extremism and (5) Racist Slurs. Thereby we analyze the (a) perceived immorality and effects on (b) trust in the influencer, (c) liking of the influencer, (d) following the influencer and (e) purchase intention of the endorsed brand. We pose the following questions: Which scandals have the worst impacts on the influencer and brand? Are there some (minor) scandals that are not hazardous or may even be positive? To answer these questions, we examine and rank the effects of scandals on the influencer and endorsed brands through a survey employing 429 data sets analyzed by variance and cluster analyses in SPSS. In this way, we hierarchize influencer scandals. Some of the results are surprising. For example, even relatively small transgressions, such as the use of swearwords, can have detrimental effects on both the influencer and the brand – nevertheless it is the most minor scandal. Gossiping and insulting followers is of medium seriousness. The most serious scandals are extremism and racist slurs. Overall, a racist slur appears to be the most serious scandal, followed by extremism (except for the variable immorality, where insulting followers is the second worst). Finally, it should be noted that the impacts of the scandals on the five dependent variables were all similar, with differences in details only. At best, the small differences between immorality and the four other dependent variables are noteworthy. For example, immorality is the only variable for which gossiping does not differ significantly from extremism.
RANCANG BANGUN ROBOT LINE FOLLOWER PEMADAM API BERBASIS MIKROKONTROLLER ATMEGA 16

The fire area is not always in an easily accessible place, under certain conditions, there are times when it is not possible for humans to extinguish fires in the event of a fire, so certain smarter devices need to have the ability to detect and extinguish fires, namely Fire Extinguisher Robot. Robot Line Follower Fire Extinguisher designed by the author, works walking to find hotspots, if the sensor gets hot temperatures or hotspots, then the ic microcomtroller stops the dc motor, then another dc motor will be active to turn on the fan or fan. The method in this paper begins with designing a robot using the Proteus 8 simulator, making a robot, finally conducting a test and measurement. This study uses three dc motors, one dc motor to simulate the open lid or activate a fan or fan, two dc motorsto run the robot. The output of this robot is a line follower robot that serves to extinguish the fire