Reviewerly/exHarmony huggingface dataset:
Design and Implementation for BIC Code Recognition System of Containers using OCR and CRAFT in Smart Logistics

The BIC (Bureau International des Containers et du Transport Intermodal) Code is the identification code for ocean shipping containers and is crucial for logistics, transportation, and security. Accurate recognition of container BIC Code is essential for efficient import and export processes, authorities' ability to intercept illegal goods and safe transportation. Nevertheless, the current practice of employees recognizing and manually entering container BIC codes is inefficient and prone to error. Although automated recognition efforts have been made, challenges remain due to the aging of containers, manufacturing differences between companies, and the mixing of letters and numbers in the 11-digit combination. In this paper, we propose the design and implementation of a BIC Code recognition system using an open source-based OCR engine, deep learning object detection algorithm, and text detector model. In the logistics industry, various attempts are being made to seamlessly link the data required at each stage of transportation between these systems. If we can secure the stability and consistency of BIC Code recognition that can be used in the field through our research, it will contribute to overcoming the instability caused by false positives.
The remote work of the high school teacher linked to the regional education center of Ponta Grossa during the pandemic of the novel Coronavirus

This article consists of an analysis of the remote work of high school teachers, linked to the Regional Education Center of the city of Ponta Grossa, State of Paraná, Brazil, in the context of the coronavirus (COVID-19) pandemic, with a view to identifying the possible occurrence of existential damage as a result of the violation of the right to disconnection. Lo and behold, one of the first sanitary measures implemented by the authorities to contain the spread of the COVID-19 virus was the suspension of face-to-face school activities, and with the prolongation of such measures, in the face of the rampant increase in the number of cases of the disease, it was decided to establish a new model for the continuity of classes and compliance with the school calendar, making use of virtual resources that allowed the teaching of remote classes. This reality had significant effects on the work routine and on the private lives of these professionals who, suddenly, were compelled to adapt to this new format of work, carried out from within their homes, using their own resources. There were several transformations and difficulties resulting from this new way of working, notably in relation to time and intensification of work, shortening of rest periods, damage to social, family and professional relationships, as well as several other mishaps felt and reported by professionals, through this research, conducted through a questionnaire made available through a virtual tool. The data obtained with the research pointed to the existence of elements that can characterize the existential damage, as well as well-founded indications that the work in such conditions is capable of causing the worker existential damage, by violating the right to disconnection.
BibPat: Quantum k-means clustering with incremental enhancement

Background: One of the main areas of study within the broader paradigm of quantum machine learning is quantum clustering (QC). Considering the potential time and cost savings that solutions to real-world issues employing QC algorithms bring, in comparison to their classical methods, researchers have recently developed a keen interest in QC. With new algorithms and their applications being invented virtually every other day, this is still a highly young and fascinating area of research. Based on the background information provided, this work aims to analyze research and patent databases spanning twelve years (2010 to mid-2022) to identify and understand the publishing and patent trends in the field of QC. Objective: This study aims to study the topological analyses, important study areas, relationships, and collaboration patterns that distinguish traditional and developing research clusters. The graphical representation of the progress of publications and patents over time depends on such rigorous field mapping. This paper presents a comprehensive list of all the sources through the network, bibliometric and patentometric (BibPat) analysis, and future research scope in the QC. Method: The top authors, universities, and research fields were listed after the primary and secondary keywords connected to the quantum K-means clustering algorithm in the analysis design. Reviewing the articles and then delving into the specifics of the patents will help us evaluate the total body of work on the quantum K-means clustering technique. Using the thorough BibPat tools and numerous research and patent databases like Scopus, IEEE, ACM, Google Scholar, Lens, Google Patents, and Espacenet, the analysis design displays the patents and journal papers that have been published. Conclusion: Additionally, it is crucial for later research because it aids in the identification of areas for current research interests and possible avenues for future study. QC offers various studies in disciplines from computer science to psychology. The Ministry of Education, China, produced most publications. Since 2014, the trend has been up, and experts continue studying the issue. The BibPat analysis shows that the Chinese National Natural Science Foundation has facilitated funding for cutting-edge research. In order to open the door for future research and investigation on the substantial amount of unstructured real-time data, the report concluded by proposing an incremental QC approach.
Eyeing the Visitor’s Gaze for Artwork Recommendation

Recommender systems (RSs) are increasingly present in our everyday lives for business and pleasure. The Cultural Heritage domain is no exception. In the research literature, several RSs have been proposed to enhance the fruition of artistic and cultural resources. In this paper, we present some of our research activities aimed at realizing a RS for suggesting personalized itineraries to exhibit and museum visitors. More specifically, we describe the collection and use of eye-tracking data to understand if there are any correlations between the visitors’ gaze patterns and their degree of appreciation of the viewed artworks. If such correlations exist, they could be used as implicit feedback in the recommendation engine. The preliminary results are interesting and encourage us to pursue our research activities.
Various Feature Extraction and Selection Techniques for Lexicon Based and Machine learning Sentiment Classification

Introduction: Natural Language Processing (NLP) is a kind of software that gives computers the ability to comprehend human languages. Words are often used as the fundamental unit for grammatical and semantic analysis on a deeper level, and the major objective of most natural language processing (NLP) projects is word segmentation&#x0D; Objectives: Proposed System uses the feature extraction method for generating the hybrid feature to get good accuracy for classification in order to solve the practical problem of huge structural differences between different data modalities in a multi-modal environment, where traditional machine learning methods cannot be directly applied to solve the problem.&#x0D; Methods: In order to do so, this paper introduces the method for generating the hybrid feature. In this System, we utilise a various feature extraction and selection technique from large text. The data has collected from students’ feedback and these feature extraction techniques has applied&#x0D; Results: Each technique provides different feature extraction while NLP based dependency features provides homogeneous feature set with relationship.&#x0D; Conclusions: In extensive experimental analysis NLP based features obtains higher precision over the other feature extraction techniques in classification.
Dynamic CDN Switching - DASH-IF Content Steering in dash.js

This paper overviews the content steering specification currently being developed in DASH Industry Forum and first implemented in the dash.js reference player.
Common Media Server Data (CMSD) – Update on Implementations and Validation of Key Use Cases

The CTA-5006 (Common Media Server Data, CMSD) specification establishes a uniform method for media servers to exchange data with each media object response. The aim is to enhance distribution efficiency, performance, and ultimately, the user experience. We provide an overview of CMSD implementations and focus on integrating CMSD into the dash.js reference player. Three use cases are evaluated to demonstrate the advantages of CMSD, including leveraging edge server throughput estimates to improve initial bitrate selection and low-latency live streaming, prefetching manifests and segments to improve startup delay, and allowing an edge server to suggest a playback bitrate to improve the collective experience. The outcomes from the initial implementations confirm the benefits of using CMSD.
Implementation of an Algorithm for Extracting Information about Structural Elements of Text Documents in ODT Format

The dependence of the XML markup of a digital document in the ODT format on the tool that was used to create it is considered. Not only specialized tools are used in comparison, but also those that do not directly work with the ODT format to identify the most vulnerable spots. The features of extracting data from the structural elements of the document, such as tables, lists and images, are also described. The implementation of an algorithm for obtaining style attributes used to create a system for automated normative control of digital documents is proposed and described. It is revealed that the non-strict standard of the ODT format led to the dependence of XML markup on the text editor that was used to create the document. And, as a result, to a limited number of tags that can be relied upon when developing document parsing algorithms. However, the task is feasible, as demonstrated in the article. Likewise, the default values, the description of the algorithm for bypassing the document in blocks and structural elements form the basis for preparing data for the subsequent creation of a classifier and automation of the process of normative control. Thus, the algorithm proposed in the article and the analysis of XML markup performed are effective tools for solving the problem of creating an automated document standard control system, and the algorithm has the potential for further improvement.
Basic Cryptographic Concepts and Open Problems in Hash Function Security

JOHNNA SMITH, Dept of Mathematics, Shepherd University, Shepherdstown, WV, 25443, and DONALD MILLS, Dept of Computer Sciences, Mathematics, and Engineering, Shepherd University, Shepherdstown, WV, 25443. Analysis of basic cryptographic concepts and recent open problems in hash function security. &#x0D; &#x0D; The objectives of this study are to show an understanding of cryptographic concepts as well as highlight recent open problems involving hash function security. The method of study used included reading the first five chapters of Cryptography: Theory and Practice by Stinson and Paterson as well as a recent paper that outlined open problems in hash function security. Then, written reports were delivered on the information learned which included selected proofs and solved examples. The essentials of the opening report introduce the basic elements of cryptography: cryptosystems, cryptographic tools, message integrity, protocols, and security approaches. Chapter 2 of “Cryptography” describes various types of ciphers including Shift, Substitution, Affine, Vigenère, Hill, Permutation, and Stream Ciphers, as well as how to cryptanalyze them. The third report focuses on the One-time Pad, entropy, perfect security, and cryptographic security, specifically unconditional security, as introduced by Claude Shannon in his work on information theory. Throughout the fourth report, block and stream ciphers, including substitution-permutation networks, attacks such as linear and differential cryptanalysis, and modes of operation are discussed. In the fifth report, basic concepts of cryptography, hash function and message authentication are discussed, including iterated hash function, sponge construction, and unconditionally secure MACS. Using the information learned from the previous reports, current problems in hash functions were then researched. In conclusion, open problems in hash function security include collision resistance, preimage resistance, and resistant to length extension attacks. The project was sponsored by the NSF S-STEM Grant (DUE-2130267).
IoT Based Surveillance and Health Monitoring System for Elderly and Physically Challenged People

With the increase in global life expectancy and the advance of technology, the creation of age-friendly environments is a priority in the design of new products for elderly people healthcare. This paper presents a proposal for a real-time health monitoring system of older adults living in geriatric residences. This system was developed to help caregivers to have a better control in monitoring the health of their patients and have closer communication with their patients’ family members. To validate the feasibility and effectiveness of this proposal, a prototype was built, using a biometric bracelet connected to a mobile application, which allows real-time visualization of all the information generated by the sensors (heart rate, body temperature, and blood oxygenation) in the bracelet. Using these data, caregivers can make decisions about the health status of their patients. The evaluation found that the users perceived the system to be easy to learn and use, providing initial evidence that our proposal could improve the quality of the adult’s healthcare.
Generation of Regular Expression from Aligned Sequences of Text Snippets

Introduction: Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Vitae sapien pellentesque habitant morbi tristique senectus et netus. Dignissim cras tincidunt lobortis feugiat vivamus at augue eget arcu. At risus viverra adipiscing at in. Cras semper auctor neque vitae tempus quam. Sed cras ornare arcu dui. Turpis massa sed elementum tempus. Risus commodo viverra maecenas accumsan lacus vel facilisis volutpat est.&#x0D; Objectives: Effective data management has become an absolute necessity in today's world as a direct result of the widespread adoption of electronic medical records for patients. For medicine and healthcare domains, particularly effective web healthcare providers, computer-assisted categorization of such information into functional classifications such as medical issues or illnesses may save time and efforts. However, a substantial volume of data in the healthcare domain is still unstructured.&#x0D; Methods: The utilization of unstructured text datasets is a challenge in comparison with structured text datasets. Many researchers in various domains have proposed to convert unstructured text into structured text. The text needs to be built in a fixed and aligned pattern for easy comparison, matching, and classification. In the text classification process, accuracy is one of the challenges when text is unstructured. The text with a fixed pattern is easy to classify. The regular expressions are sequences of characters with fixed patterns of text. This strength of regular expression is used in the proposed text classification. Finding patterns in unstructured text is possible with the use of sequence alignment. Basically, sequence alignment is a concept of biomedical research, but the same concept is used to align text snippets that are not perfectly similar to each other.&#x0D; Results: The sequence alignment technique detects the similarity score assigned to each potential alignment in order to choose among the numerous local alignments of sequences. The proposed local pairwise alignment method is used to get sequence alignments, which are useful to generate regular expressions.&#x0D; Conclusions: A regular expression is a string of characters used to describe a text pattern. The regular expressions are typically created manually by the domain experts. The proposed work is the automatic generation of regular expressions from aligned sequences with a bottom up approach. The generated regular expressions are used as a dataset on which various machine learning algorithms are applied for text classification.
Innovative ML-based Methods for Automated On-board Spacecraft Anomaly Detection

Spacecraft health monitoring is an important task to assure the mission operational life. For this purpose, a variety of telemetry data are analyzed to detect anomalies that can lead to failures and cause irreversible damage to on-board devices. In this paper we propose and analyze different ML-based methods that contribute to the generation of an intelligent anomaly detector capable of identifying anomalies in spacecraft telemetries, with a particular attention to the memory footprint of each method. Finally, we investigated how to model the abnormal behaviors during the validation/test phase, exploiting different families of possible configurations for anomaly injection. The achieved results, after several tuning setups, suggest that all of the adopted methods are suitable for implementation when observing relatively short intervals of time. Instead, when longer time windows are used, the score-based detectors outperform the proximity/density-based ones, despite being more resource hungry.
The Students’ Ability In Comprehending English Descriptive Text of The Eighth Grade Students at SMPN 28 Tanjung Jabung Timur

Tujuan Penelitian: This research has a purpose to analyze the students’ ability in comprehending English descriptive text of the eighth grade students at SMPN 28 Tanjung Jabung Timur.&#x0D; Metodologi: This research is classified as a descriptive research type using quantitative methods. The population of this study were students of class VIII SMPN 28 Tanjung Jabung Timur. The samples used were class 8A and class 8B, totaling 42 people. The research instrument used was a reading test to measure or analyze their ability to understand English descriptive texts. The data analysis technique used was tabulated data obtained from the reading test, calculated in the assessment classification, calculated in the percentage of data within the range of 0% - 100%, explained the results, and concluded from the research results.&#x0D; Temuan Utama: The findings of this study indicate that the students' ability in understanding English descriptive texts is low.&#x0D; Keterbaruan/Keaslian dari Penelitian: The novelty of this research is to analyze students' ability to understand English descriptive text.
EdTech in humanitarian contexts: whose evidence base?

This study reports on the design and development of a methodological toolbox prototype for evaluating EdTech deployed in the contexts of fragility and crisis. The project adopted a bottom-up approach: training EdTech users in participatory action research approaches was followed by a comprehensive mapping of problems in the Azraq refugee camp that might be addressed through the chosen EdTech installed in a local Makerspace. Students as researchers used a developmental evaluation approach to deepen their understanding of evaluation as a concept and as a process and proceeded to match the results of their Azraq camp problem-tree analysis with evaluation questions related to the EdTech tools available in the Makerspace. The study concludes with a proposed methodological toolbox prototype, a set of approaches and processes that include research capacity building in fragile contexts, and user-led evaluation that emphasizes the notion of evaluation as a learning process driven by those designed to benefit from EdTech in fragile contexts.
Impacto de una Intervención Virtual en Lectura en Niños Disléxicos: ¿Es Distinta la Eficacia Respecto de una Intervención Presencial?

As a result of the COVID-19 pandemic situation, the psychoeducational work was forced to carry out virtual interventions. In this work, progress in reading skills was compared in face-to-face vs. virtual intervention in patients with dyslexia. The evolution of 26 patients from 1st to 3rd grade exposed in both formats to the same reading intervention with a cognitive program, was analyzed. The results showed that both in the virtual and face-to-face modalities, an improvement was achieved in phonological skills, reading fluency and decoding, with no significant difference across modalities. In conclusion, virtual interventions can be effective if an explicit and systematic treatment is carried out, with an evidencebased program and based on an initial faceto-face bond.
Environment for the Safe Execution of Computer Programs and Communications in the Activities of an Additional Education Institution

To solve the problems of developing software solutions in educational and project activities, a dedicated environment for the safe execution of computer programs was designed and investigated, which allowed students to solve educational and project tasks for developing software solutions both remotely and inside the institution, maintaining direct communication with the teacher and not requiring additional software and hardware resources. This article describes the concept of a dedicated environment for the safe execution of computer programs, describes technical solutions and testing of the environment.
Student's Literacy and Numeracy Skills in ombok Island, West Nusa Tenggara : Baseline Survey Innovation Based Gender Equality, Disability, and Social

This research aims to analyze the literacy and numeracy skills of students in ombok Island, West Nusa Tenggara based on gender, disability and social equality. The research approach uses a Mixed Method between qualitative and quantitative research with a survey method (cross-sectional). Data collection was carried out involving 2639 respondents from SD and MI students, school principals, teachers, parents, village representatives, and from TTIs. Survey data were obtained through questionnaires, document recording, and interviews. Furthermore, the data were analyzed qualitatively. This study's results show the lowest achievement is the numeration of female respondents in East Lombok Regency, 59.41. Achievements in the same aspect for Central Lombok Regency were higher, namely 62.97. For literacy skills, female respondents in Central Lombok also obtained a higher average (68.91) than female respondents in East Lombok Regency (66.93). The achievement of male respondents in Central Lombok Regency for literacy (69.08) looks lower than male respondents in East Lombok Regency (69.44). The same thing also happened to the average achievement in the numeracy aspect; Central Lombok Regency only got an average of 66.00, while East Lombok reached 66.44. In general, male literacy achievements were higher than women, while numeracy achievements were superior to female respondents from men's.
Pengaruh Kondisi Sosial Ekonomi Keluarga Dan Motivasi Belajar Terhadap Minat Melanjutkan Studi Mahasiswa Angkatan 2022.

This research employed a quantitative approach with the Ex-post facto research method. The data used were primary data obtained by distributing questionnsires to economics education students in the class of 2022, with a total sample of 70 respondents. At the same time, the data analysis technique technique used was multiple linear regressions. The results of data analysis and discussion denoted that family socioeconomic status and learning motivation had a positive and significant effect on interest in pursuing education. This result signified that good family socioeconomic status and learning motivation could increase students’ interest in pursuing education at the department of economics education, faculty of economics, universitas negeri gorontalo. It could be concluded that the research finding could answer the problems formulated in this research.