Reviewerly/exHarmony huggingface dataset:
Special issue on analysis and mining of social media data

This Editorial introduces the PeerJ Computer Science Special Issue on Analysis and Mining of Social Media Data. The special issue called for submissions with a primary focus on the use of social media data, for a variety of fields including natural language processing, computational social science, data mining, information retrieval and recommender systems. Of the 48 abstract submissions that were deemed within the scope of the special issue and were invited to submit a full article, 17 were ultimately accepted. These included a diverse set of articles covering, inter alia, sentiment analysis, detection and mitigation of online harms, analytical studies focused on societal issues and analysis of images surrounding news. The articles primarily use Twitter, Facebook and Reddit as data sources; English, Arabic, Italian, Russian, Indonesian and Javanese as languages; and over a third of the articles revolve around COVID-19 as the main topic of study. This article discusses the motivation for launching such a special issue and provides an overview of the articles published in the issue.
CuentosIE: can a chatbot about “tales with a message” help to teach emotional intelligence?

In this article, we present CuentosIE (TalesEI: chatbot of tales with a message to develop Emotional Intelligence), an educational chatbot on emotions that also provides teachers and psychologists with a tool to monitor their students/patients through indicators and data compiled by CuentosIE. The use of "tales with a message" is justified by their simplicity and easy understanding, thanks to their moral or associated metaphors. The main contributions of CuentosIE are the selection, collection, and classification of a set of highly specialized tales, as well as the provision of tools (searching, reading comprehension, chatting, recommending, and classifying) that are useful for both educating users about emotions and monitoring their emotional development. The preliminary evaluation of the tool has obtained encouraging results, which provides an affirmative answer to the question posed in the title of the article.
A discrete component in visual working memory encoding.

Working memory (WM) is a central cognitive bottleneck, which has primarily been attributed to its well-known storage limit. However, relatively little is known about the processing limit during the initial memory encoding stage, which may also constrain various cognitive processes. The present study introduces a novel method using dynamic stimulus presentation and hierarchical Bayesian modeling to quantitatively estimate visual WM encoding speed. Participants performed a delayed-estimation task with two memory items continuously changing color hues in perceptually unnoticeable steps. Across three experiments, the recall errors systematically shifted toward the direction of color change, providing a proxy measure of encoding speed. Importantly, the observed shifts were best characterized by a temporal lag during the encoding of different items, supported by a mixture of two distributions with credibly distinct encoding times. A supplementary model-free analysis further confirmed the discrete encoding component in visual WM for multiple items. These findings shed light on the temporal dynamics of WM encoding processes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Pendidikan Karakter dalam Anime: Analisis Psikologi Tokoh Naruto pada Serial Anime Naruto

Naruto anime is one of the anime that can be used as an educational watch that supports us in teaching character education to the younger generation. The purpose of this study is to analyze the psychology of the main characters of Naruto anime and find out the influence of Naruto anime in shaping characters and values in the audience. This study used a qualitative approach with data collection techniques, watch-listen-record and read-record. From this research, it can be found that there are several psychological aspects of Naruto characters, namely 1) loneliness and rejection, 2) social care, 3) motivation and determination, 4) self-development, 5) courage and confidence, 6) empathy, and the influence of the anime in shaping the character and values in the audience, namely 1) inspiration to overcome obstacles, 2) the importance of friendship, 3) face conflict peacefully, 4) courage to oppose injustice. The conclusion obtained is that the character Naruto shows a rich journey in terms of psychology, from a difficult childhood to strong self-development. In addition, Naruto Anime can inspire and shape characters and values in its audience.
Restoration of UAV-Based Backlit Images for Geological Mapping of a High-Steep Slope

Unmanned aerial vehicle (UAV)-based geological mapping is significant for understanding the geological structure in the high-steep slopes, but the images obtained in these areas are inevitably influenced by the backlit effect because of the undulating terrain and the viewpoint change of the camera mounted on the UAV. To handle this concern, a novel backlit image restoration method is proposed that takes the real-world application into account and addresses the color distortion issue existing in backlit images captured in high-steep slope scenes. Specifically, there are two main steps in the proposed method, which consist of the backlit removal and the color and detail enhancement. The backlit removal first eliminates the backlit effect using the Retinex strategy, and then the color and detail enhancement step improves the image color and sharpness. The author designs extensive comparison experiments from multiple angles and applies the proposed method to different engineering applications. The experimental results show that the proposed method has potential compared to other main-stream methods both in qualitative visual effects and universal quantitative evaluation metrics. The backlit images processed by the proposed method are significantly improved by the process of feature key point matching, which is very conducive to the fine construction of 3D geological models of the high-steep slope.
EXPRESS: Processing Wh-filler-gap Dependencies

We present experimental evidence showing that different wh-filler-gap dependencies are processed differently, depending on their syntactic licensors. Our studies compared the active storage profiles for why, how, and who (serving as subject or object of the verb). The results of offline and online experiments revealed that these wh-fillers are stored in memory for different durations, and predictably so based on the hypothesized structural distance between each wh-filler and the licensor which determines its grammatical and interpretive functions. Furthermore, the results showed that once the wh-filler is licensed, it is integrated to the current structure, and no longer engenders additional memory costs. Based on these findings, we argue that the mechanism of online sentence processing may employ both storage and integration components in memory.
Evaluation of a Deep Learning Model for Metastatic Squamous Cell Carcinoma Prediction From Whole Slide Images

Squamous cell carcinoma (SCC) is a histologic type of cancer that exhibits various degrees of keratinization. Identifying lymph node metastasis in SCC is crucial for prognosis and treatment strategies. Although artificial intelligence (AI) has shown promise in cancer prediction, applications specifically targeting SCC are limited.To design and validate a deep learning model tailored to predict metastatic SCC in radical lymph node dissection specimens, using whole slide images (WSIs).Using the EfficientNetB1 architecture, a model was trained on 6587 WSIs (2413 SCC and 4174 nonneoplastic) from several hospitals, encompassing esophagus, head and neck, lung, and skin specimens. The training exclusively relied on WSI-level labels without annotations. We evaluated the model on a test set consisting of 541 WSIs (41 SCC and 500 nonneoplastic) of radical lymph node dissection specimens.The model exhibited high performance, with receiver operating characteristic curve areas under the curve between 0.880 and 0.987 in detecting SCC metastases in lymph nodes. Although true positives and negatives were accurately identified, certain limitations were observed. These included false positives due to germinal centers, dust cell aggregations, and specimen-handling artifacts, as well as false negatives due to poor differentiation.The developed artificial intelligence model presents significant potential in enhancing SCC lymph node detection, offering workload reduction for pathologists and increasing diagnostic efficiency. Continuous refinement is needed to overcome existing challenges, making the model more robust and clinically relevant.
Identification of Fencing Athletes Based on Anthropometric Measurements Using MediaPipe Pose

Over time, numerous developments in digital technology have benefited people, including anthropometric measurements that provide information on an athlete’s ability in sports. The use of digital technology in sports must continue, particularly in the National Sports Committee of Indonesia (Komite Olahraga Nasional Indonesia, KONI) of Bandung City. This study proposed a technique for classifying and identifying fencing athletes’ talents. This work developed a methodology for evaluating sports talent based on anthropometric measurements of athletes’ bodies using the posture detection approach. Fencing and nonfencing athletes in KONI Bandung City were categorized using this talent identification. This study used 36 datasets of body posture images from various skills of the sport. These images were in JPEG or JPG format with a resolution of 3,024 × 4,032 and were acquired using a Canon EOS 1300D camera. This study utilized four points landmarks, which are usually used as measurement components in KONI, to categorize fencing athletes. The four points are shoulder (S), elbow (E), index (I), and hip (H) landmarks. The testing was done using three different dataset settings. According to the test results of all scenarios, scenario 2 had the highest accuracy. This scenario was able to categorize fencing and nonfencing athletes with an accuracy rate of 89% and an average processing time of less than 3 s per image.
Methods and means of developing the pedagogical skill of teachers of general education disciplines in vocational education institutions

The problem of developing the professionalism of teachers today belongs to the key directions of research in the field of modern pedagogical science. The high quality of teaching in the vocational education system depends on the level of knowledge, pedagogical skill of the teacher, and his/her professional maturity. On the basis of the conducted analysis, it is substantiated that the effectiveness of the development of the pedagogical skill of teachers of general education disciplines of vocational education institutions depends both on the correct definition of goals and content, and on the methods of achieving the goal - teaching methods.&#x0D; The purpose of the article is the theoretical justification of the main methods and means of developing the pedagogical skill of teachers of general education disciplines of vocational education institutions.&#x0D; The work characterizes the main functions of teaching methods, analyzes their main classifications, examines familiar, traditional methods (lecture method, story, explanation, training exercises, explanatory conversation, discussion, independent work, instruction, etc.), as well as innovative: simulation and game methods, brainstorming method, problem methods, project method, case method, master class, work in pairs, work in groups, consultations, portfolio, method of situational analysis, coaching, tutoring, etc.&#x0D; The study revealed that improving the professional skill of teachers of general education disciplines in vocational education institutions is a complex process. The professional skill of a teacher is an individual style, combined with high professional competence, which determines the ability to apply traditional and innovative technologies, to carry out professional activities regardless of the conditions of the social environment and the characteristics of students. That is why explanatory-illustrative, reproductive, and problem-based teaching methods (traditional and innovative) should gradually and purposefully implement cognitive activity, develop and improve professional skills within the framework of formal, non-formal, and informal continuous pedagogical education of teachers of general education disciplines of vocational education institutions
THE SPECIALIST AND APPLICABLE REQUIREMENTS IN THE CRIMINAL-PROCEDURAL LEGISLATION OF THE REPUBLIC OF UZBEKISTAN

It is perceptible that a number of requirements are stipulated regarding the specialist in the process of proof by virtue of analyzing the Criminal-procedural Code of the Republic of Uzbekistan. The disinterestedness and worthwhile elements of the profession in performing the tasks assigned to the specialists as indispensable part of these requirements are vitally important in the criminal procedural relations. Ultimately, the lack of special knowledge of the specialists involved in the case shows theirincompetence for their profession and inhibits them to participate in the proceeding.
Validasi Dokumen Pengajuan Kredit Nasabah Menggunakan Metode Simple Additiveweighting dan Rapid Application Development

Applying for credit to purchase goods is now very easy, just attach it personal and supporting data documents, your credit application can be approved in a matter of hours. These submission documents must have valid criteria and information prospective customer data, and fast and accurate validation methods are carried out in doing so document verification and validation. The Simple Additive Weighting method is used for validating documents and verification is carried out by checking the source of the document issued. This method, out of 100 credit applications that are approved, has a level success reached 97% and only 3% of customers experienced credit problems.
THE ROLE OF COPYRIGHT IN THE CONTEXT OF SOCIAL MEDIA

This article examines important aspects of the interaction between copyright and social networks in contemporary information society. The article emphasizes key elements of agreements between users and platforms, defining rules for content usage. The Digital Millennium Copyright Act (DMCA) is highlighted as an effective mechanism for protecting copyright in the online environment. Court decisions on copyright infringement in social networks serve as examples for understanding the complexities of balancing between freedom of information exchange and intellectual property protection. In conclusion, the importance of effective collaboration between authors and social platforms is emphasized to ensure fairness, diversity, and quality of content in the online space.
MEASURES TO ENSURE THE EFFECTIVENESS OF THE PREPARATION FOR THE INSPECTION OF THE CRIME SCENE

In this article, the nature of the investigative action of inspecting the scene of the incident, the concept of the stage of preparation for examining the scene of the incident. There has also been an attempt to improve the preparation for the survey in order to improve the effectiveness of the survey of the scene. To this end, in the practice of Investigation, measures have been developed that will be carried out precisely on the issue under consideration, in preparation for consideration in any situation. It has been proposed to strengthen the issue of preparing for the incident in the legislation in order to increase the responsibility of the participants in the survey of the scene, to ensure the effectiveness of the investigative action.
GENESIS OF CYBERCRIME AND ITS CONCEPT PECULIARITIES

The article deals with the history of the origin of cybercrime. It describes in detail the essence and peculiarities of cybercrimeterminology. At the same time, the article reveals types of cybercrime, as well as its goals and objects of influence.
THE SIGNIFICANCE OF AL'GOFLORA IN OPTIMIZING WATER TREATMENT PROCESSES

Water treatment facilities play a vital role in ensuring the availability of safe and clean water for human consumption and various industrial purposes. Among the innovative approaches in water treatment, the integration of Al'GOFLORA stands out as a promising method for optimizing the treatment process. Al'GOFLORA, a long water treatment facility utilizing algae and other flora, offers a sustainable and effective solution for water purification. This article explores the importance of Al'GOFLORA in optimizing water treatment processes, highlighting its benefits, mechanisms, and potential applications.
Groups of Non-Conventional Means Referring to Time in Literary Texts.

The paper is an extensive analysis of literary texts spanning different eras, genres, and languages (including the epic of Gilgamesh, Russian works by A. P. Chekhov, S. Dovlatov, G. G. Demidov, as well as English works by W. Shakespeare, R. P. Warren, W. Faulkner, K. Vonnegut). Through this analysis, the author identified a common poetic feature shared by these works: the utilization of both conventional and non-conventional means to convey the passage of time. The objective of the study was to examine and categorize these non-conventional means according to their respective referential spheres, as well as to elucidate their functions within literary texts. Four main groups were identified, encompassing references to food, human physiology, events or objects in the characters’ living spaces, and processes in nature. The study reveals that non-conventional methods of conveying time in literature are considered archaic; however, they are still widely employed to personalize characters’ perception of time and highlight its psychological aspect. The temporality of these methods is generally reinforced through the use of adverbs, prepositions, or grammatical structures that indicate time. In conclusion, it is established that due to the directional nature of time, its fluidity, and the inevitability of approaching death, authors strive to find ways to capture and define time, giving it tangible forms, and in doing so, the past becomes alive once more.&#x0D;
Penerapan Artificial Intelligence dalam Mendeteksi Batu Ginjal secara Otomatis pada Citra CT Scan

Background: Kidney stones are a clinical condition with the presence of stones along the urinary tract of varying sizes. The aim of this research is the need for a system to automatically detect kidney stones so that it can help radiologists in diagnosing kidney stones accurately, effectively and efficiently, and patients can immediately undergo further action to cure kidney stones.Methods: The difference in research carried out by researchers is the use of artificial intelligence which uses deep learning with a convolutional neural network (CNN) algorithm. This research uses images obtained from CT scan results from public data (Kaggle) and primary hospital data. The number of images used in the Augmentation training data was 2338 normal images and 2390 kidney stone images. The augmentation testing data used 540 normal images and 446 kidney stone images. The research also involved experts, namely radiology specialists, in determining images with abnormal and normal stone tones.Results: research obtained from CT Scan images of kidney stones with augmentation and original using public data/Kaggle images, obtained using augmentation obtained a high accuracy value of 99.69%. Meanwhile, in testing data using primary/hospital data images, augmented data obtained accuracy values that were still low at 45.43% and 45.23%, respectively.Conclusions: The use of deep learning with the CNN model in training data augmentation obtained high accuracy values, however in testing data using hospital CT scan images the accuracy value was still low, but it was able to recognize images of kidney stones, so it could help in automatically diagnosing kidney stones. For future work could involve refining the model to handle variations in hospital data or exploring additional features to improve generalizability.
Website-Based Employee Administration System at Tebing Tinggi City Regional Personnel Agency

Employee administration is a system that contains related information consisting of elements that are guided towards the target in order to achieve ideal results. For that, the system gets input containing information about employee needs. Often this staffing administration is done manually as written in a book. The problem makes the author interested in creating an employee administration site that is useful for making it easier to provide information related to employees. This administration system runs on localhost using the PHP programming language and MySQL as a database. With this administration system application, it can facilitate and speed up employees in getting information wherever and whenever just by accessing the employee administration system site.
The Internet of Things (IoT) in World Practice: Review and Analysis

This article explores the contemporary realm of the Internet of Things (IoT) and its influence on society and the economy. The primary emphasis lies in examining the principal patterns within the realm of IoT, encompassing the escalation of connected device quantities and the utilisation of 5G networks. The article encompasses various facets, including an overview of the evolution and possibilities of IoT, encompassing the advancement of intelligent urban areas and the influence of 5G networks. The analysis of threats and vulnerabilities related to this technology focuses on detecting common flaws, including weak passwords, unsecured network services, and inadequate privacy measures.&#x0D; Furthermore, the essay presents concrete hazards in diverse sectors that employ IoT technology. Particular emphasis is given to potential cybersecurity vulnerabilities in healthcare, manufacturing, agriculture, retail, transport and logistics, energy, and smart cities. These businesses have distinct challenges and hazards due to incorporating IoT technologies.&#x0D; The authors also analyse the substantial financial commitment to IoT and its profound influence on the worldwide economy, including data on the expansion of the IoT market and investments in IoT technologies and smart cities. The findings emphasise that the Internet of Things (IoT) substantially influences society and the economy. However, it necessitates meticulous consideration of cybersecurity and privacy concerns. The authors underscore the significance of creating efficacious cyber security policies to safeguard against the possible hazards presented by IoT technology.&#x0D; &#x0D; &#x0D;