Reviewerly/exHarmony huggingface dataset:
Basic Programming Training in Python for Junior High School Students at Al Fitrah Islamic Boarding School

This research discusses the implementation of basic programming training using the Python programming language for junior high school (SMP) students at Al Fitrah Islamic Boarding School. The aim of this study is to provide an overview of the training experience and its impact on students' understanding of programming and their proficiency in using Python. The research method used is qualitative with a case study approach. The participants of the study consist of students from the seventh and eighth grades at Al Fitrah Islamic Boarding School. Data was collected through observations, interviews, and tests of students' learning outcomes. The results of the research show that the basic programming training with Python effectively improves students' understanding of programming concepts and develops their computational skills. Additionally, the students demonstrate high interest and enthusiasm in programming activities, indicating strong potential for developing technological skills in the future. This research concludes that basic programming training with Python can be well integrated into the junior high school curriculum to enhance digital literacy and prepare students to face the challenges of an increasingly advanced technological world.
GM-Ledger: Blockchain-Based Certificate Authentication for International Food Trade

Maritime transportation plays a critical role for many Arab countries and their food security and has evolved into a complex system that involves a plethora of supply chain stakeholders spread around the globe. This inherent complexity brings huge security challenges, including cargo loss and high burdens in cargo document inspection. The emerging blockchain technology provides a promising tool to build a unified maritime cargo tracking system critical for cargo security. This is because blockchains are a tamper-proof distributed ledger technology that can store and track data in a secure and transparent manner. Using the State of Qatar as a case study, this research introduces the Global Maritime Ledger (GM-Ledger), which will aid authorities in verifying, signing and transacting food certificates in an efficient manner. The methodology of this research includes reviewing past publications, identifying the requirements of various players in the Qatari food import–export industry and then creating a smart contract framework that will efficiently manage the work with necessary human intervention as and when required. The result of this work is the formation of a solid framework that can be employed in future works. This work realized that employing web3 solutions for the food import sector is highly viable and that with the right social, economic and policy reforms, it is possible to transform the entire food system to bear healthy transparency and power balance in global supply chains. In conclusion, this study argues that BCT has the ability to assist the government and other players to minimize fraud and maximize food supply chain stakeholder participation.
Viscissitudes in the Transition from the Presential to the Educational Virtuality Caused by Covid-19 in the Mixteca Region

This study examined the psychosocial impacts and management of the CORONA virus from triple perspectives; negative socialization, dehumanization, and de-individuation. The literature of the study was focused around the following schools of thought; social psychology, cognitive psychology, psychodynamic theory, and behaviorism.
Architecture Considerations for a Decision Support System in Cyber Risk Management

In this paper we will elaborate on specific architectural elements for designing a decision support system for cyber risks management in critical infrastructures. The development of any information system follows standard steps, from the design to the market ready product. The design phase is critical as it ensures that the final system is adjusted to the needs and requirements of the customer. The paper starts with the identification of architecture elements of a decision support system. Throughout the paper we will focus on the input and output elements of a decision support system. We will propose categories of data that are required managing cyber risks in the critical infrastructure domain. We will identify the critical design aspects these two elements. In conclusion we will elaborate on the implications of context and human element on the architecture for the DSS, as well as future propose future research activities in this area.
Interactive Powerpoint Media in Grade IV Elementary School

The teacher as a facilitator must be able to present interesting material and learning for students. There are still many teachers who have not used learning tools that can assist teachers in conveying learning to students which can cause the learning process to be less than optimal. The media that will be used will make students more active in the learning process. One example of learning media that can be used by teachers is multimedia using Powerpoint. This research aims to develop interactive PowerPoint media for thematic learning in grade IV elementary school. This study uses research and development (R&amp;D) methods using the 4D models. Data collection in this study used a questionnaire to determine the validity test and practicality test of the media. The effectiveness test is done by testing. The expert's validation on the material, media, and language aspect scored in Very Valid category. The results of the practicality test by the teacher obtained score in Very Practical category, and results of practicality test by students obtained score \in Very Practical category. The results of effectiveness test on aspect knowledge with the pretest at elementary school obtain very good predicate. Assessment of skills aspects at elementary school found Very Good predicate. From the research can be concluded that interactive PowerPoint media in class IV of elementary school is practical and effective for use in class IV of elementary school.
Enhancing The Adsorption Capacity of Commercial Kaolin for Efficient Removal of Lead Ions from Aqueous Solutions

The sorption of lead ions (Pb+2) from aqueous solutions using commercial kaolin (KC) was investigated. The effects of various factors such as dosage, different pH media, different concentration, and temperature on the adsorption process were investigated. The Langmuir model was determined to fit the Pb+2sorption model on KC. Langmuir model parameters qm, KL, and R2, were found to be 31.2, 0.0014, and 0.9908 mg.g-1 respectively. The qmax of the Pb+2 on KC was 31.2 mg.g-1 at pH 5.7, 500 mg of KC, and 25?C. Free energy (?G), enthalpy (?H), and entropy (?S) were calculated to understand the nature of the sorption process. Negative ?G, negative ?H, and positive ?S were found to indicate the adsorption process is non-spontaneous, exothermic, and random, respectively. A pseudo-second-order (PSO) model was followed for the adsorption process. The percentage extractions (%ER) found ranged from 102.5- 90.8 % for stimulation mineral water and tap water samples. This research provides valuable insights for the development of efficient and sustainable methods for water treatment and environmental remediation.
Medical Image Compression Techniques Comparison Using Open-Source Libraries

Digital Imaging and Communications in Medicine (DICOM) has become the de facto standard for the exchange and storage of medical images. With the increasing use of imaging modalities and the growing size of image datasets, efficient compression techniques have become essential to address storage, transmission, and processing requirements. This paper provides an overview of DICOM image compression, particularly based on MRI cases, discussing the various techniques and challenges associated with it. It explores both lossless and lossy compression methods (like FIT, that was developed by this group), their impact on image quality, and the trade-offs between compression ratio and performance. Furthermore, it highlights the importance of considering regulatory requirements, interoperability, and the potential impact on clinical workflows when implementing DICOM image compression solutions .
Meningkatkan Keterampilan Membaca Peserta Didik Kelas Rendah Melalui Media Flashcards

Language skills are important for all individuals, especially in the first grade of elementary school students, reading skills are the main focus. Teachers have an important role in improving the reading skills of learners, and to achieve this, the application of an effective approach becomes very important. This study aims to evaluate the learning strategies used by teachers in improving the reading ability of students in grade 1, as well as identify inhibiting factors in the development of students' reading skills. The method used in this study is descriptive qualitative method, with data collection involving interview and observation techniques. This research was carried out in SD Negeri Cikande 1. The results showed that teachers use various strategies in improving students' reading skills, including spelling, sound, and syllabic strategies as an effective learning approach. In this context, the approach helps learners in understanding and mastering reading skills well. By using this strategy, teachers also use flashcards learning media. Factors that can inhibit students' reading in the classroom are cognitive factors, environmental factors, lack of encouragement from parents, and low interest in reading.
Study of Psychological Defense Mechanisms, Motivation and Success of Professional Activity of Entrepreneurs

Analysis of psychological defense mechanisms, motivation and success of professional activity of entrepre-neurs provides relevant data for using in the development of programs of psychological support of personal development, psychological assistance in adapting a traumatic situation and coping with stress in entrepre-neurs. The aim of the present study is to identify psychological defense mechanisms and reveal psychological features in entrepreneurs with high and low professional success. The relevant concepts on the stated topic in psychological research are interpreted. Based on the evaluation of the total index on the questionnaire ques-tions characterizing these life spheres, the degree of subjective success of entrepreneurs’ professional activity was assessed. Two groups of entrepreneurs with high and low professional success were singled out. In the presented groups, the results of a study of self-efficacy, personal characteristics, psychological defense mech-anisms, motivation for success, and willingness to take risks were analyzed. Significant differences in the indi-cators of self-efficacy; emotional instability, dominance, suspiciousness, self-control, tension; psychological defense mechanisms “regression” and “intellectualization”, “tension of psychological defense”; motivation for success; readiness to risk were determined.
Interactions Among Declarative and Procedural Memory Systems, Different Linguistic Structures, and the Efficacy of Different Corrective Feedback Types

This study investigated the interactions among different cognitive abilities, linguistic structures, and the efficacy of different corrective feedback (CF) types. The cognitive abilities examined were declarative and procedural memory. The target linguistic structures were English regular and irregular past tense forms. In terms of the relationships between English past tense forms and the two memory systems, the declarative and procedural (D/P) model (Ullman, 2020) posits that regular past tense forms are learned in procedural memory while irregular past tense forms are learned in declarative memory. However, these relationships have not been investigated for second language learners. The participants were divided into recast, explicit correction, metalinguistic prompt groups. Second language learning was measured using an untimed grammaticality judgment task (UGJT) and an elicited imitation task (EIT). The results showed that procedural memory significantly predicted the UGJT posttest scores for regular past tense forms in the metalinguistic prompt group, while declarative memory significantly predicted the EIT posttest scores for irregular past tense forms in the recast group. These results were consistent with the predictions of the D/P model that the learning of regular past tense forms is related to procedural memory, whereas that of irregular past tense forms is related to declarative memory, although relationships were not observed for all the treatment groups.
Material Development Promoted By English For Specific Purposes Teacher

English has been considered as the most international language used in the world. As the effect of that, English becomes the global language for worldwide communication in which people are required to acquire the language orally or in written. In Indonesia, English is perceived as one of the important subjects that must be tough at any level of education. ESPecially for the university level, English specifies its purposes and develops its concept of teaching under-aimed at bridging students major to their future competences. Therefore, to achieve the goal, the material for ESP is designed properly by the teacher there. This study aims to unlock the principles of developing the material and the procedures on how it is maintained to develop. Depth interview, observation, and document analysis were occupied in order to drag out the answer of statement problems - the result announced that nine principles found inside the material, the task, the topic, and the level of difficulties are the under-development unit, and the procedure covers the evaluation, design, and implementation.
Motives for Employment of College Graduates: Analysis of Changes

In the context of large-scale import substitution, improving the training of workers for all sectors of the national economy in the system of secondary vocational education becomes an urgent problem. It is necessary to cre-ate conditions that ensure the formation of motivation among college graduates for the implementation of the entire volume of competencies acquired during the study in the specialty or associated with it. In this regard, there is a need to investigate the motivations that determine the employment of current academic graduates. Based on the materials of three sociological studies conducted by the Ural Federal University in 2018, 2021, 2023, the main factors influencing the choice of a future place of work by senior students of different colleges of the Middle Urals are revealed. The article shows changes in assessment of the level of the desired salary, prospects of realization of abilities, professional and career growth when making a decision to work in a pro-fession or adjacent to it.
DECISION-MAKING SUPPORT SYSTEM FOR DETERMINING THE FITNESS OF SCIENTIFIC AND EDUCATIONAL ACTIVITY OBJECTS TO SCIENTIFIC AND EDUCATIONAL FIELDS AND SPECIALTIES

The task of assigning the object of scientific and educational activity (teacher, department, student group, etc.) to a certain scientific and educational field of knowledge or specialty is considered. It is noted that solving this problem is important during the accreditation of educational programs, when choosing a reviewer for a scientific article or a student competitive scientific paper, sometimes - when choosing a supervisor for a qualification work, etc. The task of creating an information system (decision-making support system) was set and solved, which would contribute to the formation of performance indicators and check the compliance of these indicators with the fields of educational activity or scientific specialties. At the same time, the list of results of the object's activity can be contained in scientific publications, in keywords used by the scientist to describe his scientific interests, or in the topics of qualifying student papers. The main information resources are the database of categorized scientific publications from the Dimensions system and information about scientists in the Google Scholar system. The classification systems ANZSRC-2008, ANZSRC-2020, ISCED-F and the standard adopted in Ukraine are used. Examples of the work of the developed system are described, the calculation of indicators according to various formulas (absolute values of the number of occurrences found; the share of each value in relation to the sum of all indicators of the object under study; the frequency of entry into the thematic collection for each field or specialty; the share of each frequency of entry to the sum of all particles of the object under study); analysis of the results of calculations both in each position (keyword pair or scientific publication) of the researched object, and the general indicator (which, in turn, can be calculated either as an arithmetic average or as a sum of values); "reduction" of the results ("cutting off the tails") either by the minimum level or by the maximum number of positions, with the possibility of normalizing the total (bringing the sum to one); translation of the distribution by branches and specialties of the ANZSRC to the ISCED-F table or to the standard adopted in Ukraine; calculation of indicators for the entire group of objects and ranking of objects in this group by the chosen industry or specialty.
An Active Contour Model Based on Edge and Region Information for Image Segmentation

In this paper, a novel active contour model for image segmentation is proposed, which comprises two components: edge energy and region energy. First, a preprocessing step is performed to obtain a denoised smooth image using an off-the-shelf denoiser, which effectively removes noise and unwanted edges. Then we calculate the gradient of the preprocessed image for the edge detection function. In addition, our model considers both local and global information of the image in the region energy. Specifically, we construct a constraint to minimize the differences between the denoised smooth image and the local fitted image, and design fitting terms of the image intensity inside and outside the target boundary. Extensive experiments indicate that our proposed model can effectively segment images even in the presence of noise and intensity inhomogeneity. Moreover, the segmentation accuracy and robustness of this model are better than those of relevant segmentation models.
Multidimensional stitching method with wavelength tuned interferometry and unconstrained support tooling for large-thin parallel plate

Limited by measurement methods, measuring the surfaces and thickness of large thin parallel plates has been challenging. In this paper, we propose a multi-dimensional stitching method using thickness alignment (MSuTA), which use the sub-aperture stitching method based on the phenomenon of parallel plate self-interference with wavelength-tuned interferometer (WTI) for measuring the surfaces and thickness of large thin parallel plates. We establish the stitching correction model based on Legendre polynomial to separate the aberrations caused by the elastic deformation of the thin plate in the unconstrained support tooling by analyzing the influence of the stress state of the thin plate with unconstrained three-point support. The stitching experiment has carried out on 6.3 mm thick, 6-inch parallel plates that the stitching residual is better than 0.35 nm RMS. Compared with 12-inch vertical interferometer, the surfaces and thickness deviation are better than 0.8 nm RMS, and the 36 standard Legendre polynomial coefficient deviation are better than 2.5 nm. Moreover, MSuTA can improves the lateral resolution of the measurement by nearly four times, allowing for a display of more comprehensive surface information. The stitching method proposed in this paper will be widely applied in the manufacture and measurement of large thin parallel plates, and provide reference for the elastic deformation analysis of the thin optical elements in the unconstrained support tooling.
Experimental demonstration of a reconfigurable free-space receiver implementing polarization routing and filtering for daytime quantum key distribution.

Free-space quantum key distribution (QKD) systems are often designed to implement polarization-encoding protocols. Alternatively, time-bin/phase-encoding protocols are considerably more challenging to perform over a channel experiencing atmospheric turbulence. However, over the last decade, new and improved optical platforms have revived the interest in them. In this paper, we present a free-space multi-protocol receiver designed to work with three different time-bin/phase-encoding protocols highlighting its interoperability with different systems and architectures for potential satellite-based communications. We also present a detailed analysis of different experimental configurations when implementing the coherent one-way (COW) protocol in a free-space channel, as well as a polarization filtering technique showing how time-bin/phase-encoding protocols could be used for QKD applications in daylight conditions. We demonstrate secret key rates of several kbps for channels with a total 30 dB attenuation even with moderately high QBERs of ≈3.5%. Moreover, a 2.6 dB improvement in the signal to noise ratio is achieved by filtering background light in the polarization degree of freedom, a technique that could be used in daylight QKD.
Research on point cloud matching algorithm based on point pair feature and improved ICP

A point cloud matching algorithm based on point pair features with improved ICP is proposed to address the problems of slow target recognition and low accuracy in complex scenes such as occlusion and overlap. In the offline training phase, the algorithm creates a global model description based on directed point pair features and uses hash table storage to speed up the finding time; in the online matching phase, the generalized Hoff voting strategy is used to complete the point pair matching and generate candidate poses; finally, the obtained candidate poses are clustered and filtered and the poses are optimized by the overlap rate between the field point cloud and the model point cloud and the improved ICP algorithm. In this paper, the proposed algorithm is experimented for different complex scenes, and the experimental results prove that the recognition rate and feature point matching rate of this paper are high and have good robustness for the point cloud data with large data volume and poor quality.
Gas data anomaly detection based on time-series ARIMA model

With the rise of artificial intelligence technology in recent years, combining artificial intelligence technology with industry has become a popular research direction, and safety issues in industry have gradually become important. Gas data can directly show the health condition of gas, and the research of anomaly detection on gas data is one of the important means to improve gas safety. To address the gas data problem, this paper proposes a gas data anomaly detection method based on a time-series ARIMA model. Firstly, the data in the SCADA system is pre-processed, then the features of the gas data are extracted, then a time-series model is established using ARIMA, and finally the anomaly is determined by the difference between the model prediction data and the real data. And the method proposed in this paper is verified in real data, and the results show that the average values of the indexes of true positive rate, false positive rate and accuracy rate of the method in this paper are 0.18%, 0% and 96.6% respectively, which verifies the effectiveness of the method in this paper.