Reviewerly/exHarmony huggingface dataset:
Knowledge and practice of bovine tuberculosis among occupational workers in abattoirs in Abuja

Zoonotic tuberculosis particularly those caused by Mycobaterium bovis is increasingly of importance especially since the emergence of HIV/AIDS, posing a serious public health threat to human population. The aim of the study was to determine the knowledge and practice of Bovine tuberculosis among occupational workers in abattoir in Abuja. A total of 389 questionnaire were administered to butchers and meat sellers in the randomly selected abattoir in four selected area councils. Data were analysed using Chi-square at a ρ&lt;0.05 level of significant and descriptive statistics such as percentages. Out of 384 of the respondents, 95.1% were males while 4.9% were females; 96.9% were between that of 18-45; 57% had secondary education; 61.2% had 1 to 10 years working experience. Based on knowledge, 67.4% knew bovine tuberculosis to be zoonotic; 20.1% and 36.2% knew transmission could be from infected milk and meat respectively; 53.9% and 49.0% knew emaciation and respiratory distress as signs in cattle respectively; 72.1% and 54.9% of the respondents knew tuberculosis lesions to be of pulmonary and extrapulmonary regions respectively. Based on practice, 34.9% do nothing when they see abnormal lesions while 24.5% call the veterinarian; 31.0% and 9.9% of respondent use boot and mask as protective clothing respectively; 43.2% wash their hands and knife with water and soap while 10.9% use disinfectant. The findings of this study revealed that butchers and meat sellers have acquired knowledge about the nature of tuberculosis lesions through repeated meat inspection carried out by veterinarians in Abuja abattoirs.
3-Dimensional Object Recognition Using 1-Dimensional Capsule Neural Networks

Currently, indoor home object recognition systems lack the degree of accuracy required for reliable automated operations. In this paper, a 3-Dimensional (3D) object recognition deep neural network system, capable of recognizing indoor objects from 3D images with a view to assisting indoor robotic devices in performing home tasks, is presented. Almost invariably such systems drastically increase the number of total parameters which must be trained leading to very time-consuming training processes. Furthermore, the lack of suitably large annotated datasets for indoor objects adds to the training difficulties. To address these challenges a 3D dataset arranged in a 1D array format along with new architectures of 1D CapsNet is proposed. This effectively reduces the total number of parameters, resulting in faster and more accurate training of a neural network. Using the proposed architecture also appears to improve the training accuracy even when the datasets are relatively small. For this work, ModelNet-10 and the ModelNet-40 datasets are used. They have indoor home object images in 3D, which are few when compared to other datasets.
Dynamic Image-Based Visual Servoing of Unmanned Aerial Vehicles under Disturbances

In this paper, a novel image-based visual servoing (IBVS) approach based on a second-order image dynamics model is proposed to realize the positioning of unmanned aerial vehicles (UAVs) under disturbances. Specifically, the mathematical relationship between the image motion and the UAV accelerations is described by a second-order image dynamics model, which decouples the image motions and the UAV dynamics. Based on this model, a sliding-mode observer is implemented to estimate the external disturbances. Then, the output of the observer is exploited in the dynamic IBVS controller designed. As a result, the proposed dynamic IBVS controller can be applied in environments under uncertain disturbances without position and translational velocity measurements. The Lyapunov analysis is provided demonstrating the global asymptotic stability of the proposed dynamic IBVS controller and the exponential convergence of the image errors. Finally, a visual positioning experiment is implemented to verify the feasibility and effectiveness of the proposed IBVS method.
DEFINITION OF PSYCHOPHYSICAL THE STATE OF HIGH SCHOOL CHILDREN AGE IN REMOTE CONDITIONS EDUCATION DURING WARTIME

AnnotationsIntroduction.Ukraine has recently been experiencing many problems related to the education system.The reasons for these problems lie in the epidemiological situation that emerged in 2020, which entailed the transition of educational institutions to distance learning, and the aggravation of the situation was facilitated by the military actions currently taking place on the territory of Ukraine.Distance learning initially raised many questions, both for teachers and students, as they had no previous experience of this form of learning.All participants in the educational process had to assimilate in a very short time the new achievements of information technology, necessary for human entry into the global information space.The changes connected with the introduction of quarantine, not only in our country, but all over the world have affected the quality of education, as well as the psychophysical state of all participants of the educational process.As noted by experts in the field of education, distance learning has both advantages and negative consequences, which are expressed in the deterioration of the physical and psychological condition of children of all ages.The article deals with the determination of psychophysical state of 14-15 year old teenagers under wartime distance learning conditions.The hypothesis of the study is that the determination of the psychophysical state of middle school age children will allow to develop methodological recommendations for the organization of independent physical education classes with teenagers in the conditions of distance learning during wartime to improve their psychophysical state.The purpose of the research: to determine the psychophysical state of children of secondary school age in the conditions of distance learning during wartime.Material and methods: theoretical analysis and generalization of scientific and methodological literature data, questionnaires, pedagogical testing, functional research methods, psychodiagnostic methods, methods of mathematical statistics.The study involved 100 adolescents aged 14-15 who studied in the conditions of distance learning during wartime on the basis of communal educational institution "Lyceum No1" of Kamenka City Council.Results: as a result of the study it was determined that in the conditions of distance education during wartime teenagers aged 14-15 have: different signs of stress, an increased level of anxiety, decreased indicators of happiness, the motor mode does not meet the biological needs of the child's body in physical activity, reduced motivation for physical education classes, physical fitness indicators of almost 50% of teenagers are at a low and below average level.Conclusions.1. thanks to the use of modern technologies during distance learning, the participants of the educational process can learn information skills which may be required in future work.But psychological and intellectual load, distance
Technological Unemployment, Meaning in Life, Purpose of Business, and the Future of Stakeholders

We offer a precautionary account of why business managers should proactively rethink about what kinds of automation firms ought to implement, by exploring two challenges that automation will potentially pose. We engage the current debate concerning whether life without work opportunities will incur a meaning crisis, offering an argument in favor of the position that if technological unemployment occurs, the machine age may be a structurally limited condition for many without work opportunities to have or add meaning to their lives. We term this the axiological challenge. This challenge, if it turns out to be persuasive, leads to a second challenge, to which managers should pay special attention: the teleological challenge, a topic especially relevant to the broad literature about corporate purpose and governance. We argue that both the shareholder profit-maximization model and its major alternative, stakeholder theory, are insufficient to address the meaning crisis. Unless rebutted, the two challenges compel business leaders to proactively rethink the purpose of business for future society. Otherwise, businesses will be contributors to a major ethical crisis and societal externality in the coming society.
Implementation and Analysis of Service-Based Integrated Platform for Research Center Using Thomas Erl Method

The process of developing a platform is a process that consists of various stages. Still, until now, there has been no awareness in utilizing available data and information sources to serve as the basis for developing or creating a platform that can improve the quality of an integrated system. For this reason, a Platform as a Service (PaaS) architecture was built that provides application development and deployment services to process data and information obtained from relevant agencies at Telkom University to monitor the performance achievements of units within Telkom University, especially the Human Centric Engineering Research Center (HUMIC RC). This requires a service-oriented system platform design that can integrate various diverse information systems into a single unit. In this study, the Service Oriented Architecture (SOA) method from Thomas Erl was used to design a service-oriented system platform, where every business process is built in the form of services. REST Service Modeling Process technology is used in modeling services, which produces an integrated service design. In making the platform architecture this time, the API gateway is one of the middleware used on a microservice-based platform. The service-oriented platform that has been built can assist the Institutional Planning, Development, Control or Perencanaan, Pengembangan, Pengendalian Institusi (P3I) unit of Telkom University in monitoring the performance achievements of units within Telkom University so that there is no duplication of data, facilitates the storage of evidence of accomplishments, and reduces the stage and time of the process of searching for proof of performance achievements.
Music and Time

How does music manifest through time and, simultaneously, how does time manifest through music?
The Precursors of High Rainfall Intensity During June in Southern Central Java: A Case Study of Flash Floods 18 June 2016 in Purworejo

High rainfall intensity during the dry season can cause floods and landslides that cause a lot of loss of property and life as happened in Purworejo. Generally, the dry season with little rainfall, heavy rain in June is very rare, therefore disaster anticipation will be better if the precursor can be identified. This research aims to obtain high-intensity rain precursors in the south of Central Java, especially Purworejo. Identification used classifying rainfall for 10 years and related to atmospheric phenomena that impact to Indonesian rainfall variability. The results show that if there are very heavy rainfall and evenly distributed, precursors, can be identified in 3 days before the incident such as low OLR which value of &lt;150 Wm-2. Moreover, an analysis of the average 3 days before the incident, the value of the OLR anomaly in the Central Java region is between –20 to –60 Wm-2. Meanwhile, the vertical humidity profile with more than 80% reached the 500 mb level, as well as spots where the temperature was more than 30.20C, three to four days before the incident with a value of more than 30.20C in the Indian Ocean adjacent to the southern part of Java Island. Existing low air pressure in the northern part of Kalimantan and in the southern part of Java, which persists for a long time, can support very heavy rains in June in Purworejo. Especially if the wind speed decreases to less than 4 m/s and occurs in phases 3 and 4 of the MJO.
Parasitic Covert Adversarial Attack on Deep Learning based Modulation Recognition

The development of adversarial examples poses a serious threat to deep learning (DL). In the field of communication, DL-based neural networks are used for modulation recognition. The subtle perturbations of the adversarial examples that are imperceptible in the time domain are possible to form abnormal bumps in the frequency domain, which can be detected by the receiver. Therefore, this paper proposes a parasitic concealment adversarial method to avoid anomaly detection by the receiver. We firstly generate changes according to the gradient direction of the loss function to effectively reduce the recognition accuracy of the intelligent recognition system. Pseudo-random noise is then generated to conceal the interfering signal by means of cross-spreading. Finally, the generated concealed interference signal is sent to the electromagnetic space and parasitic on the channel signal. The proposed method effectively realizes the confrontation of intelligent signal recognition and maintains good robustness.
Development of Virtual Support Application for Sexual and Gender-Based Violence Victims

Sexual and Gender-Based Violence (SGBV) is an issue of a serious global concern. SGBV affects everyone and has severe implications on an individual's physical, mental, emotional, and sexual health. Cases of Sexual and Gender-based violence (SGBV) rise especially during pandemic. There was an increased domestic violence due to women being trapped with a perpetrator, often without the means of accessing support (Wendoh, 2020). Due to heightened restrictions to leave homes, many victims have limited means to seek social and professional care and support. Moreover, government and non-government services could not also prioritize their SGBV responses due to lockdown. Thus, this study aimed to develop a Virtual Support Web Application that would inform and guide victims using SGBV -related educational materials and aid victims in reaching out to organizations and law enforcement agencies for help and assistance. The proposed application is a digital-enabled multifunctional SGBV response tool called TARA. It also utilizes web analytics to create data maps on SGBV and intends to assist by providing access to Self-Care and Psycho-Social Services. TARA aims to become the key instrument for raising awareness, providing a directory and direction to law enforcement agencies to deal with new and future SGBV cases. The evaluation shows positive responses from IT and non-IT professional respondents. Evaluating the functionality, usability, and efficiency, users were satisfied with the application as the mean average of the evaluation result is interpreted as strongly agree, which is deemed satisfactory in becoming a platform for SGBV in the Philippines.
Introduction

R is a functional programming language with a focus on statistical analysis. It has built-in support for model specifications that can be manipulated as first-class objects, and an extensive collection of functions for dealing with probability distributions and model fitting, both built-in and through extension packages.
Mini Magazine as an Elicitor to Enhance Students’ Creativity in Writing

Expressing ideas in the form of written expression is usually challenging for many students in ESL/EFL classes. Along with the acquisition of the second language (L2), to write in L2 students might experience some social and cognitive challenges. For instance, Students may have little confidence to write in L2 compared to that of their first language. Moreover, language proficiency in L2 adds on to the quality of good writing. Some quandaries may contribute for this situation, in writing; students may face common issues such as: grappling with grammar aspects, choosing the appropriate vocabularies, copping with punctuation and mechanics, making coherence and cohesion, and generating ideas (Al Badi, 2015; Younes &amp; Albalawi, 2015). T hus, the researchers are going to stimulate thdents' creativity in writing via mini magazines to help students in generating their ideas and sharpen their writing skills. B y assigning the students to make mini-magazines, the researchers believe that it will have a positive impact on the students' writing skills and language proficiency.
EXPECTATIONS OF SOFTWARE DEVELOPMENT EDUCATION: STUDENTS VS PROFESSIONALS

ICT departments at universities are challenged to provide software development education that meets the expectations of both the students and the industry to deliver students with applicable professional competencies and behaviours. The question is
Visualization Tools for Monitoring and Debugging a Cognitive Architecture using CST

In this work we address the use of visualization tools for developing intelligent agents built with Cognitive Architectures (CAs). Unfortunately, there are just a few discussions about this issue in the CAs literature. We start by bringing a summary on how this topic is currently being addressed within the community and further introduce our efforts in building visualization tools for both debugging and aiding the understanding of the inner mechanisms of a CA. For this, we propose the MindViewer, a visualization tool for monitoring and debugging CAs constructed with CST, the Cognitive Systems Toolkit. MindViewer encompasses a variety of charts that are used to monitor the inner details of the agents’ mind. Its Web version allows inspect even complex data structures and customize their generated graphics. We exemplify their capabilities through a experimental application based on a robot simulation inspired in Iowa Gambling Task.
Discriminant Variance Criterion for Sentiment Analysis

The high dimensionality and sparsity of text data are major obstacles for sentiment analysis. These obstacles may be removed by using some technology such as feature selection. In this paper, we propose a filter feature selection method, called Discriminant Variance Criterion (DVC), for sentiment analysis. DVC utilizes feature and class variances to select discriminative features. Statistically, the feature variance of a feature is its total scatter. Apart from it, DVC also takes into account the class variance of a feature in each class, i.e., class scatter, by introducing the class information of data. As a result, DVC selects terms with a higher total scatter and a lower class scatter as the optimal feature subset. The effectiveness and efficiency of DVC is demonstrated by experimental results on five sentiment datasets using three widely used classifiers including Support Vector Machine (SVM), Multinomial Naive Bayes (MNB) and Logistic Regression (LR).
Espaço formativo para editoria científica na Revista Baiana de Enfermagem: uma experiência de gestão e planejamento de fontes indexadoras

The indexing of scientific journals in indexing bases is essential for scientific qualification and dissemination, as well as national and international prominence and visibility. Indexing is a potential means for nursing to be projected as a science. In this sense, the objective is to report the experience of students and professors in the Formative Space for the management of indexing bases in the Revista Baiana de Enfermagem. This is an experience report. The experience resulted in joint activities between editors and graduate students to build planning on the main databases, update and monitoring flow, workshops and meetings through remote meetings on a digital platform.
Learning Uncertainty-Aware Label Transition for Weakly Supervised Solar Panel Mapping with Aerial Images

Weakly supervised solar panel mapping has shown its advantages in automatically detecting solar panels from remote sensing images with low annotation costs. Considering the noisy nature of pseudo labels (PLs), which are frequently employed in weakly supervised methods, we propose to introduce uncertainty measure to guide the estimation of noise levels in PLs and develop a novel method based on uncertainty-aware label transition (UALT). The proposed method consists of three parts: uncertainty estimation network, uncertainty-aware label transition network, and target mapping network with forward correction. We first generate heteroscedastic uncertainty by learning an estimator under Bayes formalism. Then, with the uncertainty as guidance, a label transition network is trained to learn the mapping between clean labels, and Bayes optimal labels and predict the instance-dependent transition matrix. Finally, the transition matrix is employed in the forward correction process, where the target mapping network produces clean predictions for solar panels. Comparative experiments with six state-of-the-art weakly supervised methods on an aerial image data set show the superiority of the proposed UALT, especially in mapping accuracy and dis-covering small-scale objects.
Implementasi Algoritma K-Medoids Dengan Evaluasi Davies-Bouldin-Index Untuk Klasterisasi Harapan Hidup Pasca Operasi Pada Pasien Penderita Kanker Paru-Paru

Lung Cancer is a disease in which there are cells that grow in the lungs by a collection of carcionogens uncontrollably. Lung Cancer can be treated with surgery, chemotherapy and radiotherapy. Early treatment that needs to be done to reduce the mortality rate in patients with lung cancer after performing thoracic surgery, by collecting data from each patients regarding this information causes a new problem, including the data obtained including high-dimensional data and has many attributes so that it can produce less accurate information. So it is necessary to calculate data mining clustering. In general, the methods for performing clustering are grouped into four parts, namely partitioning, hierarchial, grid-based and model-based. This study used the k-medoids algorithm because it is able to handle data sensitive to outliers and has high accuracy and efficiency in processing large numbers objects. The results of the k-medoids calculation were evaluated using the euclidean distance Davies Bouldin Index which resulted in a DBI value of 0.93543 indicating that the k-medoids algoritm achieves good grouping because the final result of the calculation is less than 0. From the results of the evaluation using DBI it shows that the k-medoids algorithm has an average accumulation average at the time of execution is quite fast and the cluster quality is good.
A Study on Rabindranath Tagore Sahaj Path’ in the light of Child psychology

Arpan DasAssistant Professor, Katwa College, Katwa, Purba Bardhaman-713130. Prof. (Dr.) Swami TattwasaranandaPrincipal, Probationers’ Training Centre, Belur-711202. Former Principal, Ramakrishna Missian Sikshanamandira, Belur Math, Belur711202. DOI: https://doi.org/10.52756/ieldps.2022.e01.001 Keywords: Primer, Assimilation, Accommodation, Cathexis. Abstract:Modern Education has incorporated several theories and concepts of Learning – a learning approach is a life-long process that can be developed within a … A Study on Rabindranath Tagore Sahaj Path’ in the light of Child psychology Read More »
Keterampilan Berbicara Bahasa Jerman Melalui Media Zoom

Abstract. This study aims to know the planning, process, and results of the German speaking skills of class XI IPA 1 SMAN 8 Gowa students through Zoom media. This research was a class action research consists of two cycles. The data of this research consists of two data types: qualitative and quantitative data. Qualitative data were obtained through teacher and student observations and quantitative data from the German speaking skill test. The data were analyzed using the percentage technique. The results showed that speaking skills with an average score obtained by students in the first cycle reached 54% and the second cycle reached 82%. These results indicate that the Zoom media can improve the German speaking skills of class XI IPA 1 SMAN 8 Gowa students.Keyword: Speaking Skills, Zoom, German