Reviewerly/exHarmony huggingface dataset:
Designing Synchronous and Asynchronous Activities for Interactive Learning

This study aims to develop a model of interactive learning media by focusing on online activities with synchronous and asynchronous models to improve the quality of English learning. The study provides some discussion about preparing an interactive online learning by deploying various types of activities which group into synchronous and asynchronous activities. The method used in the research is research and development method which follows ADDIE model. The data collected from English skill class which include Elementary Reading and Writing and Elementary Listening and Speaking. The result of the study shows effective model for developing interactive medias for teaching English skill. It is very important to design learning activities aligned with the learning outcomes and learning objectives. To create an effective online learning environment, teachers should consider about the interactivity of the learning activities and the mode of content delivery. Both synchronous and asynchronous activities have benefits and drawback. Hence to get a maximum benefit of online learning, teachers need to combine synchronous and asynchronous activities and design which activities should be delivered in each mode.
ÇOCUKLARDA YÜZ İFADESİ TANIMLAMA İÇİN YENİ VERİ SETİ ÖNERİLMESİ VE VERİ SET ÜZERİNDE DERİN ÖĞRENME MODELLERİNİN KARŞILAŞTIRILMASI

With the developing technology, smart systems have started to take place in our daily lives. Accordingly, it is very important for the systems that will actively participate in social life to adapt to social life properly. One of the most important steps of adapting to social life is communication. Facial expressions are one of the most important parts of communication that usually supports verbal communication. For this reason, many studies have been carried out on identifying facial expressions. The vast majority of these studies were carried out using datasets containing only adult faces. Conducting studies that do not involve the elderly and children may lead to the creation and development of highly biased smart systems. Therefore, this article focuses on detecting children's facial expressions. In order to detect facial expressions in children, a data set was prepared with images collected from search engines using keywords. By using the transfer learning method, the success of VGG16, ResNet50, DenseNet121, InceptionV3, InceptionResNetV2 and Xception models were evaluated and compared on this prepared data set. According to the evaluation results, the best result was obtained with the InceptionV3 model with an accuracy rate of 76.3% and an F1 score of 0.76.
A Systematic Review of LRD (Listen-Read-Discuss) Strategy to Teaching Reading

This research aimed to determine the LRD strategy’s contribution to teaching reading comprehension. This study applied a systematic review method using google scholar to observe the data. The subject of studies was selected by Zotero software with inclusion and exclusion criteria. The results of five journals related to the strategy included inclusion criteria. They focused on finding the contribution of the LRD strategy on students’ reading comprehension using the same level of education to get results that are more significant than the contribution of using the LRD strategy for students’ reading comprehension. The LRD strategy improves reading comprehension, activating students’ background knowledge, building prior knowledge, establishing a purpose for reading, and making students more active and enthusiastic in learning. LRD positively influences students’ reading comprehension skills, and it can also use this strategy to help teachers facilitate the process of teaching reading comprehension. It can conclude that the LRD strategy contributes to teaching reading comprehension.
Pengembangan Lembar Kerja Mahasiswa Mata Kuliah Praktek Tata Teknik Pentas Dan Cahaya

Based on observations. Some lecturers have used MFIs and other lecturers not to use MFIs because the use of printed books is enough to be used by students in understanding the material taught. Seeing the facts, all lecturers from the concentration in the department stated that there was a need for the development of MFIs. This is the basis of the problem statement 1) How is the Development Process of Eye and Light Engineering MFIs? 2) How is the Quality of Development of Eye MFIs for Stage and Light Engineering? The research method used in the development of this MFI is research and development or Research and Development (R &amp; D). Sukmadinata (2015) states that research and development or Research and Development (R &amp; D) is a research method or approach to produce new products or improve existing products. Based on the results of the process of developing stage and light engineering MFIs for the 6th semester students of the 2015 UNESA FBS study program, the percentage scale obtained was 90%, 85% and 74%. The percentage scale obtained belongs to the good category. Quality aspects consist of: the accuracy of the contents of the book validator I gets a scale of 92% and validator II gets a scale of 83%. For the benefit aspect the book validator I got a scale of 83% and validator II got a scale of 83%. For completeness aspects, validator I gets a scale of 100% and validator II gets 93%. For linguistic aspects, validator I got a scale of 100% and validator II got a scale of 93%. With the scale obtained from these 4 aspects, it can be concluded that the product does not need to be revised. The researcher hopes that this product can be disseminated and used by lecturers and students extensively to improve the ability of lecturers in the arts, especially the practice of TTPC.
Feature Extraction and Classification Techniques for Wireless Endoscopy Images: A Review

Wireless Capsule Endoscopy (WCE) is one of the convenient ways to observe human digestive system, like esophagus, stomach, duodenum, small intestine, large intestine, liver, gallbladder and pancreas which are involved in metabolism.There are no incision-related injuries, no anaesthetic complications, and no negative effects on the patient.The researchers started this investigation because early detection of abnormalities is essential.Through WCE imaging data, polyps, ulcers, and cancers can be identified early.Feature extraction and selection, classification, and image pre-processing are the next three main procedures used to handle the WCE images.One of the crucial phases that can gauge the efficacy of WCE picture classification and, ultimately, the disease, is the feature extraction and selection.This study investigates three feature selection approaches and nine feature extraction methods for classifying WCE photos.It also examines the benefits and drawbacks of each technique.Both of these are taken into account while deciding which approach to use in various situations.A table with a synopsis of each technique is supplied as supporting documentation.This study demonstrates that the suitable feature extraction technique for the civic DVC dataset is Local Binary Pattern combined with GLRLM (Gray Level Run-Length Matrix), ZM (Zero Shot Manipulation Net), PHOG (Pyramid Histogram of Oriented Gradients) and GLCM (Gray-Level Co-Occurrence Matrix), while the best feature selection and extraction techniques for general knowledge bases is CSRN (Cellular Simultaneous Recurrent Networks) and DELM (Deep Extreme Learning Machine) and the classification accuracy achieved is 96.5%.
Psykholohichni resursy profesiynoho samozdiysnennya maybutnikh fakhivtsiv sotsionomichnykh spetsialʹnostey

The article examines the issue of psychological resources for professional self-realization of future specialists in socionomic specialties. It is noted that professional self-realization is a form of life self-realization, which is characterized by a high level of revealing the personal potential of a specialist in the chosen profession, the development of his abilities, professional qualifications, and extensive use of professional experience. Selected types of professional self-fulfillment (extra-professional and intra-professional). The signs of personal self-fulfillment are outlined: the presence of one's own project (strategy) of life and a firm intention to implement it; the need for self-improvement; achievement of set life goals and disclosure of her personal potential; recognition of a person's personal achievements by the social environment; constant setting of new goals. Indicators of professional self-realization include: extra-professional and intra-professional. Methods of professional self-realization are outlined, such as self-expression, self-determination, self-realization, self-transcendence. The article defines the structural elements of a person's professional self-realization: organizational, activity-creative, subject-personal, result-professional. Generalized indicators and criteria of professional self-realization of future specialists in socionomic specialties are formulated, and the levels of professional self-realization are characterized: adaptive-reproductive, activity-creative, subject-personal. The personal qualities that determine the success of professional self-improvement are singled out. The existence of a relationship between personal characteristics and the success of professional self-improvement is confirmed. The opinion is expressed that self-realization of the individual takes place during all stages of professional development: selection, educational and professional training, professional adaptation, primary and secondary professionalization, and the stage of professional mastery. It is characterized by professional destruction in the structure of professionogenesis, which leads to changes in the formed structure of activity, negatively affects work productivity and interaction with other participants of this process, as well as the development of the individual himself. The characteristics of the levels of professional destruction of the personality (general professional, special professional, professional-typological destruction and individual deformations) are given. Types of professional and typological destruction of specialists in socionomic specialties are outlined and their causes are determined. The article suggests ways to prevent the emergence of professional destruction of specialists in socionomic specialties.
NeRBERT- A Biomedical Named Entity Recognition Tagger

Biomedical named entity recognition is a popular research topic in the Biosciences domain as number of biomedical articles getting published are increasing rapidly.Generic models using machine learning and deep learning techniques have been proposed for extracting these entities in the past, however there is no clear verdict on which techniques are better and how these generic models perform in a domain-specific big data scenario.In this paper, we evaluate three baseline models using the most complex BioNLP 2013 cancer genetics dataset addressing the cancer domain.A classifier ensemble, bidirectional long short-term memory (Bi-LSTM) model and the bidirectional encoder representations from transformers (BERT) model are implemented.We propose NeRBERT, a domain-specific, graphical processing unit (GPU) pre-trained language model using extra biomedical corpora extending BERTBASE.Experimental results prove the efficacy of NeRBERT as it outperforms the other three models with an F1-score gain of 12.18 pp, 8.59 pp and 5.43 pp over the ensemble, Bi-LSTM and BERT models respectively.GPUs reduce the model training time to less than half.Comparing it to existing state-of-the-art models, it performs 1.57 pp higher than the next best existing model compared, emerging as a robust biomedical and cancer phenotyping NER tagger.
Content-Based Image Retrieval Using Adaptive CIE Color Feature Fusion

This work proposes a novel content-based image retrieval framework using adaptive weight feature fusion in the International Commission on Illumination (CIE) color space.To enhance the weights of the saliency region features of an image, an adaptive wrapper model is proposed for the adaptive feature selection.Initially, the images are transferred to the CIE color space, i.e., the L*, a*, b* color space.The local binary model (LBP) texture features of all four channels are analyzed class-wise.For each class, the weights of the LBP features for a* and b* axis are calculated dynamically as per their class variance.The weighted LBP features along a* and b* axis are merged, which is referred to as the LBPCW feature in the CIE color space.To test the performance of the proposed LBPCW feature we developed a CBIR system, here two standard classifiers i.e.Support Vector Machine (SVM), and Naï ve Bayes (NB) is used for classification and Euclidian distance measure is used for image retrieval.The model is tested with two public datasets Wang-1K and Corel-5K.It is observed that our proposed LBPCW feature outperforms LBP and local binary pattern with saliency map (LBPSM) features.
Fusion of RNCNN-BRHA for Recognition of Telugu Word from Handwritten Text

With the increasing proliferation of digital pictures, word retrieval (WR) algorithms have been intensively investigated.In general, WR service is relatively costly in terms of computing and storage resources.However, retrieving telugu words from handwritten text is difficult due to the wide range of curves and strokes in handwritten words.Deep learning for handwritten word identification from photos is an ongoing research topic with promising results.In this paper, thinning the words is performed, which helps in extraction of sharp features.After performing thinning operation for given input word, features are extracted using residual network (RN) structure in CNN, BRISK and HARRIS algorithms to identify the word from the handwritten text.These three are combined and termed as RNCNN-BRHA model.The features are evaluated to check the performance of proposed RNCNN-BRHA technique in retrieval of telugu words.The CNN utilized has various innovative features, such as the utilization of several completely linked branches.When applied to all regularly used handwriting recognition criteria, our technique surpasses all current algorithms by a wide margin.The PSNR value obtained using the proposed model is 26.94 which is far better compared to techniques like hilditch algorithm and morphological operation.
Mobile Technology-Powered Education in Developing Countries

Mobile learning, which is supported by mobile applications and devices such as smartphones and tablets, has gained significant popularity due to the widespread adoption of mobile technology and continuous improvements in internet infrastructure. This trend is reflected in the growing use of mobile learning worldwide. Research has shown that smartphones play a crucial role in promoting student development, particularly in learning and research (Esechie et. al., 2022). Compared to traditional learning approaches, mobile technology-powered learning is more flexible and convenient, as it can be conducted at any time and in any places. Students can access learning resources via mobile devices, complete assignments and tests online, and more. Existing studies suggest that most students are receptive to mobile device-assisted learning, and student attitudes, strategies, and preferences are the main factors influencing their mobile learning experience (Tang et al., 2019).
Translation Strategies of the Terminologies in the Thesis Abstracts of the Faculty of Industrial Technology

This study examines the translation strategies of the terminologies in the eighty thesis abstracts of the Faculty of Industrial Technology. There are twenty abstracts from the Industrial Engineering Department, twenty-one abstracts from the Mechanical Engineering and Design, twenty abstracts from the Business Information System, and nineteen abstracts from the Electrical Engineering Department. The writer uses Baker’s (2018) eight translation strategies as theory. This study applies a descriptive qualitative methodology for the research. The result shows that five of eight translation strategies were used in translating terminologies in the thesis abstracts. The strategies are general word, cultural substitution, loan word/ loan word with explanation, paraphrase using related word, paraphrase using unrelated word. This study shows that loan word is the strategy that is used the most in translating terminologies. This strategy is used because a lot of terminologies from the abstracts of the faculty of Industrial Technology comes from English words.
The Effect of Product Branding

Social media is currently very influential on the activities of today's life and includes all people, both young and old. The purpose of this research is to find out how much influence the information system has on the branding of a product. This research method uses descriptive method, to present an overview of the influence of information systems on a product brand by observing and through interviews with brands that use information systems and those that do not use information systems. The results obtained from this study indicate that the information system has a major effect on the brand of a product. Product brands that use information systems are more widely known by consumers compared to brands that do not use information systems. It is also known that social media is very influential on the introduction of a branding. This research shows that the importance of information systems on a product brand to be more widely known in the market, so that sales will increase.
A novel image segmentation utilizing FUZZY-based LBP and active contour model

This work presents an object recognition algorithm that combines local binary pattern (LBP) based on fuzzy logic approach and active contour model for segmenting different images to detect textured objects. Initially, images containing objects are segmented using the fuzzy logic-optimized LBP method. Then, we eliminate the image noise. Finally, utilizing a Chan-Vese active contour method, the target object of the image is highlighted. The segmentation has been compared with the classical LBP technique and the results indicated higher accuracy and quality for highlighting the object from the background. The classification of highlighted objects is performed with a convolution neural network (CNN). To authenticate the proposed approach, 140 images with the classification of 10 different objects were used. The simulation depicted that the proposed method has better results than other methods both in terms of segmentation error and performance. Significantly, CNN classification also showed a classification accuracy of 92.8%.
Pragmatic Communication with Embodied Agents

With the emergence of a new generation of embodied AI agents (e.g., cognitive robots), it has become increasingly important to empower these agents with the ability to learn and collaborate with humans through language communication. Despite recent advances, language communication in embodied AI still faces many challenges. Human language not only needs to ground to agents’ perception and action but also needs to facilitate collaboration between humans and agents. To address these challenges, I will introduce several efforts in my lab that study pragmatic communication with embodied agents. I will talk about how language use is shaped by shared experience and knowledge (i.e., common ground) and how collaborative effort is important to mediate perceptual differences and handle exceptions. I will discuss task learning by following language instructions and highlight the need for neuro-symbolic representations for situation awareness and transparency. I will further present explicit modeling of partners’ goals, beliefs, and abilities (i.e., theory of mind) and discuss its role in language communication for situated collaborative tasks.
‘Changing Tactile Intensity and Frequency Perception Via Autosuggestion’

Autosuggestion is the inner reiteration of an idea with the goal of actively influencing one’s own perception. Despite being an integral part of our modern life, autosuggestion has gained little scientific attention so far. Here, we challenge the concept of autosuggestion as a tool to bias perception, by testing its modulatory effects on touch while controlling for response biases. We took advantage of the known link between intensity and frequency perception in touch (‘Békésy effect’). Across three experiments, N = 77 participants tried to modulate the perceived intensity of tactile stimuli at the fingertip through autosuggestion, but they were asked to report the perceived frequency. We provide the first experimental demonstration that autosuggestion can alter participants' tactile perception using a response orthogonal to the suggested variable. Our results have implications for the establishment of future complementary medical treatments.
Redes sociales virtuales, como alternativas a los procesos de enseñanza aprendizaje del SENA Magdalena

This article refers to what is now considered as learning alternatives under the use of social networks in educational environments, where teachers and students relate formative activity in a context of interaction and virtual communication that benefits productivity and educational quality.While it is true that the inclusion of social networks in learning environments can lead to distractions that impede the development of individual and collaborative work and lean towards entertainment space, which can be built on a distracting element that limits participation and the relationship between teacher and student.This intrinsic aspect cannot be substantial to technological evolution in the teaching and learning processes, where virtual social networks are being optimally incorporated and integrated into the different academic activities inside and outside the classroom and in the generational prospect of new knowledge and skills that 21st century education has been offering.TIC in education has a dynamic and differential character in the teaching and learning processes, acquiring a new role between student and teacher in the development of critical and analytical thinking.Before this situation, it is evident in the study that virtual social networks are constituted in a support that adapts pedagogical and training strategies in the classroom, facilitating social cohesion between members of the academic community.Becoming an innovative and flexible proposal that promotes student autonomy and collaborative learning.
Contingency Access Control COVID-19

The main goal of this work is to show results obtained from a software called "Access Control by Contingency COVID-19" which allows the institution control the access to facilities after returning from COVID pandemic in order to avoid crowds of people, this software will help avoid COVID-19 infections .The methodology used for this project was Scrum ,since the development of the project required mainly a constant testing and delivery follow-up, prioritizing activities and adapting changes for greater flexibility to modifications to achieve the main objective in a established time. Currently web applications are being used as a resource in order to put together different projects, in this case health control and University access, applying a survey to generate a QR code with which people will be able to enter the university facilities, this code is read by a mobile application that sends data via wifi to a desktop application that is in charge for validating and recording student`s data, employees and external personnel accessing the institution facilities.