Reviewerly/exHarmony huggingface dataset:
The perceptions of university students' professional socialization process

The purpose of this study is to determine the perceptions of university student’s professional socialization process. The study adopted the qualitative research design. Easily accessible case sampling method, was used to determine the participants of the study group. The study group consisted of 16 students. The data were collected through two focus groups. The data of the study were analysed using the content analysis method. According to the findings of the content analysis the themes “adaptation to society”, “professional role achievements”, and “adoption of the profession”, and relevant sub-themes were identified. The results of the study revealed that students who were studying at both faculties expressed the concept of ‘professional socialization’ in a multidimensional way. In the light of the findings obtained from the research, it is proposed to make new curriculum arrangements that will provide the development of professional socialization for students.
Michael Guihot and Lyria Bennett Moses (2020). Artificial Intelligence, Robots and the Law, LexisNexis Australia

Nicholas Korpela reviews Michael Guihot and Lyria Bennett Moses (2020). Artificial Intelligence, Robots and the Law
Model of Methods and Approaches for the Formation of School Readiness and Qualities of the XXI Century in 6-7 Year Old Children

The authors share experience in the educational process with 6-7 year olds on a tested model with elementssemiotic approach, competence approach, team approach, methods "mirror training", "mind map" and "design thinking" in 6-7 year olds.children in their educational and practical activities for acquiring creative thinking; solving problems; finding solutions in order to obtain a constructive result.The tested methods and approaches help to: tolerate the expression of the personal position; concentration and promotion of children's independence; team interaction; equality of the organization and self-organization in the training; to respect the experiences of children in pedagogical interaction; and others with which 6-7 year old children to acquire the necessary competencies for the new social role "student".Through the applied model the children mastered three main types of intelligence necessary for the transition kindergarten-school: abstract (or conceptual) intelligence, characterized by the ability to use verbal and symbolic material, practical intelligence with which children feel comfortable in the specific environment when they have to deal with objects, social intelligence, which implies communication with others and the ability to dialogue with them.The stability of the model is expressed in its universality -it can be applied by children, parents, teachers, in all regime moments and in the next age period -school age.
The Use Of Listen Read Discuss (LRD) Strategy To Improve Student’s Reading Comprehension

The objective of this research is to find out whether the use of LRD Strategy can improve reading comprehension of grade ten students particularly in descriptive text. This researcher applied a quasi-experimental research design. The population of this research was grade ten students of SMK Negeri 6 Palu which consist of 108 students. The sample of this research was 36 students of class X TKJ 2 and considered as the experimental class while 36 students of class X TKJ 3 as the control class. The sample was selected using cluster random sampling technique. The technique of data collection was test that includes pre-test and post-test. While the mean score of pre-test in experimental class was about 49.71, the control class is 58.09. In post-test, experimental class got 64.76. On the other hand, the control class got 61.13. By applying 0.05 level of significance and 28 degree of freedom (df), as seen tha table that the value of t-counted is (2.12) and t-table is (1.703). The t-counted value is higher than t-table, which means that the research hypothesis is accepted. Therefore, the use of LRD Strategy can improve students’ reading comprehension in descriptive text.
Activating students’ cognitive perspective using problem based learning in Efl speaking class

Speaking is one of the skills in mastering English that must be taught and learned in senior high school. The problem based learning (PBL) is an appropriate strategy to assist the students in their speaking skills learning. Cognitive perspective also takes accountability on this research due to students’ perspective toward the PBL that moreover influences their speaking skills. The purpose of the research is to explore students’ perception about problem based learning also to discover the phase in PBL that delivers students’ cognitive aspect in the speaking classroom at the second year students of SMAN 1 Karawang. Qualitative research was used as the research approach with descriptive research as the method of this research. This research took place at SMAN 1 Karawang by taking the XI IPA 5 class as the sample with six research participants. They were chosen by purposive sampling. All of the data was gathered through observation, student’s reflection journals, and documentation. It was found that the use of PBL technique was able to assist the constraints of students in solving a problem along the way with their cognitive perspective while speaking it out. Moreover, the researcher also discovers that PBL and cognitive perspective hold strong intercourse between each other, the phase in PBL goes along with human mental processes particularly in cognitive views. Furthermore, it shows how PBL assists students in their problem-solving skills with their cognitive views and how it triggered them so they can elaborate on it in front of the class. PBL and speaking activity were two items that always go right together.
The Implication of Covid-19 on Educational Disparity Between the Developed and the Developing Countries, Urban and Rural Dwellers and, on ICT in Nigeria

Education as an agent of socialization started in Iraq located in Asia and later in Egypt located in Africa and proceeded to the European countries where it grew and overshadowed that of the originators in Asia and in Africa through industrial revolution in Europe which became intensely magnified with the development of the computers leading to information and communication technology (ICT), though, the application of ICT to education had been Known for many decades, its overwhelming significance has not come to bare as it is today with the rise of Covid-19 pandemic, the researcher therefore set out to investigate: the implication of: covid-19 on educational disparity between the developed and the developing countries, urban and rural dwellers, the rich and the poor, and on Information and Communication Technology (ICT) using an open-ended survey questionnaire and found out that: the onset of Covid-19 unfolds the latent potentials and significance of ICT which will further widen the educational gaps between the developed and the developing countries, the urban and rural dweller, the rich and the poor, especially in Nigeria and in Africa as a whole, in the light of the above findings the researcher recommended among others that Nigeria should improve on internet connectivity and electricity, provide ICT devices for learners, and above all provides free e-learning educational site(s) for all categories of learners Keywords: Implication, Covid-19, Disparity, Developed, Developing, Urban, Rural, ICT. DOI: 10.7176/JEP/12-30-06 Publication date: October 31 st 2021
DOCUMENTING THE CATALOGING PRACTICES AND POLICIES AMONG SELECTED LIBRARIES IN KAZAKHSTAN

Objective. A survey was conducted among selected librarian catalogers in Kazakhstan to determine the current cataloging practices and policies being employed in their respective libraries. Methods. Responses suggested that cataloging is still one of the important aspects of the library work even with the emergence of electronic resources. Results. While many were still applying traditional standards such as MARC, AACR, LC and DDC in their descriptive cataloging and authority works, catalogers were interested in new standards such as RDA and BIBFRAME. Conclusions. Finally, interests in having a unified online catalog as well as more trainings on the field of cataloging and metadata librarianship in the future has also been considered by these libraries to improve the quality of their cataloging work.
Apatite as a tracer for magmatic-hydrothermal ore-forming processes

This project focuses on the trace element chemistry of igneous apatite in various magmatic systems with the use of in situ analytical techniques. The composition of apatite may possibly be used as a tracer for various magmatic-hydrothermal processes due to the breadth of chemical substitutions possible within the structure. Apatite is found in many mineralized layered intrusions as a minor phase. Apatite may be utilized in the tracking of metasomatic fluids in layered intrusions or in geochronological studies in the absence of other commonly used phases i.e. zircon. Apatite accumulations can be exploited economically for phosphorus and possibly for rare earth elements as well.
AN ANALYSIS OF DIRECTIVE SPEECH ACTS PRODUCED BY TEACHERS IN EFL CLASSROOM

&lt;p&gt;The teaching and learning process entails several encounters in which the teacher and students exchange a variety of utterances, particularly in language classes. Understanding language involves an understanding of pragmatics. Teaching and learning will be more successful if appropriate speech acts are used. Directive Speech Acts are a type of speech act that is frequently employed in classroom interactions. It is used by the teacher to give instruction, command the students to do something, limit the students’ bad behavior, etc. This study aims at investigating the types of directive speech acts and analyzing the functions of the acts used by English teachers at SMKN 1 Sawan. The theory of directive acts classification adopted in this study is the theory proposed by Ibrahim (1993). Ibrahim’s theory classified directive acts into six major types. They are &lt;em&gt;requestive, question, requirement, prohibitive, permission &lt;/em&gt;and&lt;em&gt; advisory&lt;/em&gt;. This research also focused on the functions of directive acts based on Amalsaleh, Yamini, and Yarmohammadi's (2004) theory. They are &lt;em&gt;elicitation, instruction, advice, threat, &lt;/em&gt;and &lt;em&gt;attention-getter. &lt;/em&gt;This research was a descriptive study with two teachers as the subjects of this research. Observation and recording were used as the technique in collecting the data. The validity of the data used is source and theory of triangulation. The results showed that the most frequent type of directive speech acts used by the teachers was &lt;em&gt;question directive&lt;/em&gt; with occurance of 185 utterances (46.95%). Teachers that employ the question directive encourage students to be interested in the world around them, to enhance their abilities and attitudes toward science, and to enhance their speech communication and critical thinking. The other functions of the acts were also identified in various types of the acts.&lt;/p&gt;
Conditional Noise Filter for MRI Images with Revised Theory on Second-order Histograms

Previous research by the author has the theory that histograms of second-order derivatives are capable of determining differences between pixels in MRI images for the purpose of noise reduction without having to refer to ground truth. However, the methodology of the previous research resulted in significant false negatives in determining which pixel is affected by noise. The theory has been revised in this article through the introduction of an additional Laplace curve, leading to comparisons between the histogram profile and two curves instead of just one. The revised theory is that differences between the first curve and the histogram profile and the differences between the second curve and the profile can determine which pixels are to be selected for filtering in order to improve image clarity while minimizing blurring. The revised theory is tested with a modified average filter versus a generic average filter, with PSNR and SSIM for scoring. The results show that for most of the sample MRI images, the theory of pixel selection is more reliable at higher levels of noise but not as reliable at preventing blurring at low levels of noise.
INTRAHEPATIC CHOLANGIOCARCINOMA DETECTION AND SEGMENTATION OF IMAGES USING DEEP LEARNING TECHNIQUES

Intrahepatic cholangiocarcinoma is a form of cancer that forms in the cells of the bile ducts, both inside and outside of the liver. Cholangiocarcinoma and bile duct cancer are two words that are often used interchangeably to describe the same disease. Therefore, we have proposed an intelligent Hepatoma detection system. So, the main purpose of this research is to develop and implement an automated method that will help to detect and classify the Liver Cancer disease by processing hepatomic images. We have used liver-tumor-segmentation dataset for the testing our proposed methodology, it contains 130 images of Liver Cancer patients. We have applied pre-processing techniques on these images such as morphological filtering, in order to enhance images from input data for post processing. After obtaining the resultant image we have applied slicing. We have used UNets (modified form of convolutional Neural Network) for classification purpose with ResNet34, 50 and 100 architecture for downsampling and upsampling of shifted pixels. The proposed technique provides a sophisticated diagnosis and classification accuracy when compared with previous techniques. The parameter we used to validate the performance of our proposed technique is Top-N accuracy. Our proposed method shows the accuracy of about 99.8%.
To What Extent Can English-as-a-Second Language Learners Read Economic News Texts?

In decision making in the economic field, an especially important requirement is to rapidly understand news to absorb ever-changing economic situations.Given that most economic news is written in English, the ability to read such information without waiting for a translation is particularly valuable in economics in contrast to other fields.In consideration of this issue, this research investigated the extent to which non-native English speakers are able to read economic news to make decisions accordingly -an issue that has been rarely addressed in previous studies.Using an existing standard dataset as training data, we created a classifier that automatically evaluates the readability of text with high accuracy for English learners.Our assessment of the readability of an economic news corpus revealed that most news texts can be read by intermediate English learners.We also found that in some cases, readability varies considerably depending on the knowledge of certain words specific to the economic field.
Correction to: Feedback through emotion extraction using logistic regression and CNN

The publication of this article unfortunately contained mistakes. The name of one of the authors was not correct. The corrected name is given below.
Precise characterization of the prior predictive distribution of deep ReLU networks

Recent works on Bayesian neural networks (BNNs) have highlighted the need to better understand the implications of using Gaussian priors in combination with the compositional structure of the network architecture. Similar in spirit to the kind of analysis that has been developed to devise better initialization schemes for neural networks (cf. He- or Xavier initialization), we derive a precise characterization of the prior predictive distribution of finite-width ReLU networks with Gaussian weights. While theoretical results have been obtained for their heavy-tailedness, the full characterization of the prior predictive distribution (i.e. its density, CDF and moments), remained unknown prior to this work. Our analysis, based on the Meijer-G function, allows us to quantify the influence of architectural choices such as the width or depth of the network on the resulting shape of the prior predictive distribution. We also formally connect our results to previous work in the infinite width setting, demonstrating that the moments of the distribution converge to those of a normal log-normal mixture in the infinite depth limit. Finally, our results provide valuable guidance on prior design: for instance, controlling the predictive variance with depth- and width-informed priors on the weights of the network.
APLIKASI MANAJEMEN SISTEM INFORMASI BERBASIS TIK DALAM UPAYA MENINGKATKAN PRODUKTIFITAS SEKOLAH

The objectives to be achieved in this study include efforts to identify, decipher, and analyze planning, implementation, implementation evaluation and control mechanisms, as well as efforts to increase the productivity of University of Education Indonesia Laboratory Schools through information system management applications.The research method used in this study is a descriptive method with a qualitative approach.The results show that the planning done in the School Governing Body Laboratory University of Education Indonesia can be classified into several activities: (1) Determining the vision and mission of the School Governing Body Laboratory University of Education Indonesia made for adoption by schools under its construction.(2) Schools have not optimally analyzed the internal and external environment.(3) The making of activity plans is oriented on cultural change, especially in the use of websites, multimedia, and computer -based information systems.
Domain-Specific Japanese ELECTRA Model Using a Small Corpus

Recently, domain shift, which affects accuracy due to differences in data between source and target domains, has become a serious issue when using machine learning methods to solve natural language processing tasks.With additional pretraining and fine-tuning using a target domain corpus, pretraining models such as BERT 1 can address this issue.However, the additional pretraining of the BERT model is difficult because it requires significant computing resources.The efficiently learning an encoder that classifies token replacements accurately (ELECTRA) pretraining model replaces the BERT pretraining method's masked language modeling with a method called replaced token detection, which improves the computational efficiency and allows the additional pretraining of the model to a practical extent.Herein, we propose a method for addressing the computational efficiency of pretraining models in domain shift by constructing an ELECTRA pretraining model on a Japanese dataset and additional pretraining this model in a downstream task using a corpus from the target domain.We constructed a pretraining model for ELEC-TRA in Japanese and conducted experiments on a document classification task using data from Japanese news articles.Results show that even a model smaller than the pretrained model performs equally well.
Smart System for Elderly Wandering Person

Nowadays wandering became one of the frequent, ticklish and deleterious behaviors of elders suffering from dementia. The same may lead to consequences like getting lost or falling down. The proposed system concentrates on problems related to wandering. In this system, we are planning a security support system focused on android for identifying the location of a wandering elder person. This system is employed with the GPS that can detect the position of the individual within and around buildings, and transmit the location to the server device. It can also detect the sound of the drifting elder person and identify the accurate position. There will be an accelerometer which detects when a person falls. This model informs the caregiver by sending the notification.
Analysis of watermarking techniques in multimedia communications

Multimedia information is critical of examining, information perceived and which are illustrated by the human cerebrum. In our brain, 33% of the cortical area concentrates only on visual information processing. Digital watermarking technology is being received to guarantee and encourage such kinds of digital data authentication, security, and copyright. These algorithms permit the expandable values of different techniques to prevent the problems of copyright issues during the transmission. This paper discusses the detailed about the point by point investigation of watermarking definition and different watermarking applications and strategies used to improve information security.
Template-aware Attention Model for Earnings Call Report Generation

Earning calls are among important resources for investors and analysts for updating their price targets. Firms usually publish corresponding transcripts soon after earnings events. However, raw transcripts are often too long and miss the coherent structure. To enhance the clarity, analysts write well-structured reports for some important earnings call events by analyzing them, requiring time and effort. In this paper, we propose TATSum (Template-Aware aTtention model for Summarization), a generalized neural summarization approach for structured report generation, and evaluate its performance in the earnings call domain. We build a large corpus with thousands of transcripts and reports using historical earnings events. We first generate a candidate set of reports from the corpus as potential soft templates which do not impose actual rules on the output. Then, we employ an encoder model with margin-ranking loss to rank the candidate set and select the best quality template. Finally, the transcript and the selected soft template are used as input in a seq2seq framework for report generation. Empirical results on the earnings call dataset show that our model significantly outperforms state-of-the-art models in terms of informativeness and structure.
PettingZoo: Gym for Multi-Agent Reinforcement Learning

OpenAI's Gym library contains a large, diverse set of environments that are useful benchmarks in reinforcement learning, under a single elegant Python API (with tools to develop new compliant environments) . The introduction of this library has proven a watershed moment for the reinforcement learning community, because it created an accessible set of benchmark environments that everyone could use (including wrapper important existing libraries), and because a standardized API let RL learning methods and environments from anywhere be trivially exchanged. This paper similarly introduces PettingZoo, a library of diverse set of multi-agent environments under a single elegant Python API, with tools to easily make new compliant environments.
What Metadata? Defining Different Types of Digital Assets as Application Targets of Metadata in Clinical Research Informatics

The term 'metadata' is mentioned in every one of the FAIR principles. Metadata is without question important for findability, accessibility, and reusability, but essential for interoperability. Standardized schemas have been developed by various stakeholders for decades, but too rarely come to practical use. The reason for this is that the application domain is not clearly understood. In many bio-medical research projects, the need for metadata is recognized at some point, but there is not only a lack of overview of existing standards, but also a lack of correct assessment of what individual metadata schemas were actually made for. This paper differentiates different application scenarios for metadata in clinical research.