Reviewerly/exHarmony huggingface dataset:
INDUCTION TO​MOGRAPHY IN ELECTRICAL EXPLORATION

The main provisions of the tomographic approach in pulsed electrical exploration are considered. The proposed approach is based on a multi-angle observation system where the object is irradiated from differentsides at a high density of the observation network. At the same time, two statements of inverse problems are considered, they are closely related to the tomographic approach. The first problem is searching andvisualization of medium inhomogeneities. The second problem is determination of electrical characteristicsof the identified inhomogeneities. The article considers examples of solving these problems. generating rocks. It is concluded that the lithification asynchrony of the fluid seal clay deposits predetermined the time diversity of the HC accumulation generation in the Malyshevka Formation in geological past.
Perbandingan Dosis Radiasi Pemeriksaan Radiografi Thoraks PA Menggunakan Faktor Eksposi: Standar dan High kVp Berdasarkan Database DRL Si-INTAN BAPETEN

The usage of high kV has yet to be debated, so it is not fully used in PA chest radiographic examinations. However, The World Health Organization (WHO) and the Commission of European Communities (CEC) recommend using high kV, which can reduce the radiation dose to a minimum while maintaining the quality of the radiographic image. This study aimed to analyze the radiation dose for posterior-anterior (PA) chest radiography examinations using exposure factors: standard and high kV. This research method uses a retrospective study of the results of PA chest radiography examinations database diagnostic reference level (DRL) BAPETEN between 2018-2022. The PA chest examination data are the procedure, patient position, age, body weight, exposure factors (kVp and mAs), and ESAK dose (mGy). Then, use a standard exposure factor between 60-75 kVp and tube current-time of 6-12 mAs, while the exposure factor is high kV between 90-109 kVp and tube current-time of 0.7-4 mAs. After that, statistical analysis was carried out using IBM SPSS version 26 and Microsoft Excel. Determination of the average value and percentage difference in radiation dose of standard exposure factors and high kV. Then, proceed with statistical tests mann-whitney to determine the difference in the average radiation dose value between standard and exposure factors high kVp. The study showed that the average radiation dose for the standard kV exposure factor for the PA chest radiography examination was 0.179 mGy, while the high kV was 0.146 mGy. The dose difference between standard kV and high kV is 18.43%, with exposure factor radiation dose high kV lower than the standard exposure factor. For statistical test results, mann-whitney results p-value &lt; 0,000. High kV could be a procedure to optimize exposure factors for PA chest radiography examination. Keywords: Exposure factors, High kV, Optimization, DRL, Chest PA
588: ACCURACY OF A MACHINE-LEARNING ALGORITHM IN DETECTING STATUS EPILEPTICUS ON POINT-OF-CARE EEG

Copyright © 2023 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.
Topic Identification in Voice Recordings

Abstract The paper shows the understanding of a topic recognition problem like the speech recognition system based on Natural Language Processing (NLP) and the steps of its implementation of a rules-based approach, which is able to classify given audio materials based on predefined topics in real-time. During implementation, a statistical vocabulary was developed. Google Speech API ( Application Programming Interface ) was employed for subtitling audio materials, and the most ideal time frame for reception was identified through several experiments. The motivation of this work is based on the deficiency of similar simple systems for Hungarian topic recognition, even though numerous international languages already utilize multiple Automatic Sound Recognition (ASR) systems.
Development of Pop-Up Book Media to Teach Reading Skill for Tenth Grade Students at SMK Annur Bululawang

This Study aim For developing learning media in the form of pop-up book narrative text and know How to level the feasibility of the media. Research is done on student class 10 SMK An-Nur Bululawang. The method of research used is Research and Development (R&amp;D) which uses the ADDIE model. The stages include (1) Analysis needs, (2) Development product (3) Product design (4) Implementation product (4) Product evaluation. Determination feasibility is carried out with validation expert learning, validation media expert, and validation expert language. After That researcher does testing the product. Research And Development produce pop-up book media that is feasible to use based on a study from (1) Media expert validator get 90% rating (2) Expert validators learning get an evaluation by 90%. Expert validator Language gets evaluation by 85%. Assessment response students get a percentage evaluation of 88% which means the media can be received by the student. Reason choose study This is Because development previously different in place variable And object study as well as No exists Validation expert language..
Flashcards as Media to Students’ Achieve Vocabulary: Process and Role of Flashcard in Vocabulary Class

This study aims to analyze the process in class with flashcards and the role of flashcards in learning vocabulary. The method of this research is the qualitative descriptive method that uses random sampling. This research was conducted in Senior High School in Karawang. The instruments of this research used observation and interviews to collect data. Other information, in analyzing the data of this study using the Interactive Model. The results obtained from this study are that flash cards make the class more productive, increase student motivation, increase student response rates, increase student participation, make students active and participatory enthusiastic in the learning process, increase students’ pronunciation, increase students’ fluency and increase students’ comprehension.
Mediating effect of Ocuupational Value in the relationship between University Students Major Selection Motivation and career preparation behavior

The purpose of this study is to investigate the mediating effect of ocuupational value in the relationship between University students motivation for choosing a major and career preparation behavior. To this end, a survey was conducted on 337 university students in the first, second, and third grades of the university, of which 264 valid questionnaires were used for the study. The data collected through the survey were statistically analyzed using the IBM SPSS 26.0 program, and mediated regression analysis was performed using Hayes' process macro model 4 to verify the research hypothesis. As a result, first, it was confirmed that the motivation for selecting a major had a significant positive (+) effect on ocuupational values. Second, the total effect of major selection motivation on career preparation behavior was confirmed without considering ocuupational value, and as a result, major selection motivation had a positive (+) effect on career preparation behavior. Third, the mediating effect according to the sub-factors of ocuupational value was confirmed in the effect of major selection motivation on career preparation behavior. To this end, the effect of major selection motivation and job value on career preparation behavior was confirmed by inputting both major selection motivation and job value, and as a result, it was found that major selection motivation had a positive (+) effect on career preparation behavior, but job value did not. In other words, as a result of bootstrap verification to verify the mediating effect of ocuupational value, it was found that ocuupational value did not mediate the effect of major selection motivation on career preparation behavior. However, as a result of verifying the mediating effect of the sub-factors of job value, it was found that intrinsic ocuupational value (attitude, achievement, ability) mediates the influence of intrinsic motivation (attitude, interest, talent, and future) on career preparation behavior. This indicated that intrinsic ocuupational value can make specific career decisions and active career preparation actions by improving career search activities. As a result of this study, it was found that when intrinsic ocuupational value are satisfied, the motivation for choosing a major leads to career preparation behavior more. Therefore, people in charge of the university field need to diversify the direction of career education and support according to the students' personal characteristics and motivation for choosing a major. Therefore, it is expected that this study will be used as basic data for counseling and education that can establish ocuupational value and increase career confidence for students' active career preparation behavior from the lower grades of university.
Exploring Challenges in Implementing Non-face-to-Face (blended) Class: A Case Study of Teacher Education College

The objective of this study was to understand the challenges experienced during the implementation of blended learning at University A and to explore factors for improving its effectiveness in the future. Data was collected through semi-structured interviews with 12 undergraduates at University A.&#x0D; From the university’s viewpoint, findings indicated a lack of procedural validity in decision-making for blended learning implementation and a forced application of blended learning without considering prerequisites for its effectiveness. Students were found to exploit virtual classes to improve hiring exam pass rates, select courses that are easy to earn credits, and engage in behaviors such as not watching recorded lectures.&#x0D; On the teaching aspect, there was intensified polarization in class quality compared to face-to-face classes, with methods chosen for the convenience of time utilization rather than learning effectiveness. Based on these findings, we propose practical implications for University A to better leverage the advantages of non-face-to-face (blended) classes in the future.
Analysis of Phonological Errors in Reading Qasidah Burdah at Darul Falah Islamic Boarding SchoolTambak Sumur Sidoarjo Indonesia

This study aims to describe the phonological errors of students of the Salafiyah Islamic boarding school, Darul Falah 42, Tambak Sumur, Sidoarjo. In addition to explaining the error, it also seeks the underlying causes or factors for the errors in the pesantren students to provide solutions to help improve the following learning process. In collecting data, researchers used listening, note-taking and recording techniques. In addition, researchers also use observation techniques, interviews, and also documentation. The research method uses a qualitative descriptive method. The phonological errors of the students were found in two groups of sounds, namely the group of throat sounds (الحلق) and the group of sounds of the tongue (اللسان). In this study, two causes or factors of error were found, namely linguistic factors and non-linguistic factors—the different alphabetical characters between Arabic and Indonesian caused the error. The non-linguistic factors include lack of self-confidence, reading comprehension, and mother tongue interference. Then, the researchers provide several solutions to help improve the subsequent learning process, namely that students should increase their enthusiasm for learning and improve their reading, teachers should pay special attention to students who are not fluent in reading Arabic literature, and teachers should provide recitation reviews for every student's mistakes.
An Enhanced Snake Optimizer Algorithm for Feature Selection

In this paper, an Enhanced Snake Optimizer for Feature Selection (ESOFS) algorithm is proposed, which improve the shortcomings of original Snake Optimizer (SO) algorithm. Specifically, chaos mapping and opposition-based learning are added to the population initialization process to improve initial population diversity and efficient search; in the search phase, a restart strategy is invoked to jump out of the local optimum based on extreme value detection, and differential evolution is used to improve the exploitation capability; due to the duality of the feature selection problem, a transfer function is introduced to map search space to the value domain of 0 and 1. ESOFS algorithm is tested on eight datasets of different dimensions, and its performance is compared to other meta-heuristic feature selection algorithms. The experimental results show that ESOFS algorithm outperforms other algorithms in terms of fitness and classification accuracy.
A Thorough Examination of the Influence of Drug Addiction on Youth and the Efficacy of Legal Measures in its Prevention

Drug addiction is essentially a condition or disorder characterized by the impact of substances on an individual's brain, resulting in a diminished ability to control drug or medication usage. Whether legal or illegal, excessive reliance on any substance is detrimental. Presently, a concerning trend is the increasing susceptibility of young individuals to drug addiction. Various factors contribute to this phenomenon, including easy access to drugs, depression, peer pressure, lack of family involvement, and low self-esteem. The study aims to explore the heightened vulnerability of youth to drug addiction, identify the reasons behind their susceptibility, investigate the influence of adults on youth drug consumption, analyze the role of peer pressure in drug addiction rates, and discuss strategies for overcoming drug addiction. The empirical research methodology employed in this study reveals that drugs are readily available in society, making it easier for youngsters to access them. However, the findings emphasize that individuals hold the key to preventing drug addiction by altering their mindset. Recommendations include seeking diversions such as engaging in physical activities like going to the gym or playing sports, practicing mindfulness through activities like meditation, seeking professional assistance, maintaining a well-balanced lifestyle, listening to music, and surrounding oneself with positive influences. Ultimately, the study underscores the importance of individual initiative in breaking the cycle of drug addiction
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The article analyses the existing international approaches in the field of cooperative learning strategy. It is also discussed the possibilities of their application in educational institutions in our republic, based on results of analysis.
Response of Inclusive Growth to Development Aid in Africa and the Role of ICT Diffusion

Over the years, some regions of Africa have witnessed stable economic growth, which could not be considered pro-poor or inclusive given the region’s high rate of poverty and income inequality. Development aid flow, on the other hand, has been contended to be a pro-poor strategy, which could play a key role in the drive towards the achievement of sustainable, inclusive growth in Africa. Thus, the purpose of this paper is to evaluate the role of development aid, which has been argued to be welfare-enhancing, especially in developing countries, taking into account digitalization. The research hypothesis is that development aid in the form of foreign aid and remittances promotes inclusive growth, especially in the face of digitalization in Africa. Premised on the inclusive growth-aid nexus, the study carried out panel data analysis using the common correlation effect technique for 50 African countries from 1996 to 2021. The main findings reveal that remittances have a welfare-enhancing effect through improving inclusive growth. Foreign aid, on the other hand, had a positive effect but was not significant, which was attributed to the weak institutional framework in the region. Digitalization was observed to have an adverse effect attributed to its high affordability. The theoretical contribution of the study is the incorporation of structural systems such as digitalization in the nexus between inclusive growth and development aid, which has been identified as a facilitator in the drive for inclusive growth. In terms of practical significance, the study highlights the need for digital reforms and investment in this sector as well as the need to address the institutional gap to mitigate the inefficiencies of development aid performance.
Towards Interpretability in Fintech Applications via Knowledge Augmentation

The financial industry is a major player in the digital landscape and a key driver of digital transformation in the economy. In recent times, the financial sector has come under scrutiny due to emerging financial crises, particularly in high-risk areas like credit scoring models where standard AI models may not be fully reliable. This highlights the need for greater accountability and transparency in the use of digital technologies in Fintech. In this paper, we propose a novel approach to enhance the interpretability of AI models by knowledge augmentation using distillation methods. Our aim is to transfer the knowledge from black-box models to more transparent and interpretable models, e.g., decision-trees, enabling a deeper understanding of decision patterns. We apply our method to a credit score problem and demonstrate that it is feasible to use white-box techniques to gain insight into the decision patterns of black-box models. Our results show the potential for improving interpretability and transparency in AI decision-making processes in Fintech scenarios.
Dynamic Governance: Utilization of Waste Methane Gas as Renewable Energy (Case Study at Puuwatu Kendari Landfill)

The use of new renewable energy (EBT) sources to meet the needs of electricity and gas in Indonesia is increasing but has not been optimally realized. Therefore, government support is needed in the use of NRE to help the community in the availability of electricity and gas. This study aims to find o
The Application of Causal Inference Algorithms in Federated Recommender Systems

This study introduces the application of causal inference algorithms in federated recommender systems through a framework called FedCIRec. The framework utilizes two key causal inference methods: Instrumental Variable (IV) and Counterfactual Inference (CF). IV helps identify and address confounding biases, improving recommendation accuracy. CF addresses data loss issues in federated learning, enabling the inference of possible scenarios and outcomes. Experimental results on the MIND and Adressa datasets demonstrate excellent performance in evaluation metrics. The FedCIRec framework has advantages over centralized storage and user privacy protection methods. Further exploration of causal inference methods and optimization of recommendation effects while protecting user privacy are areas for future research. Introducing causal inference techniques in federated recommendation systems has broad research and practical application prospects.
Accelerating Robust-Object-Tracking via Level-3 BLAS Based Sparse Learning

The sparse collaborative tracking (SCT) method has been developed for object tracking recently, and it is very efficient and robust to various occlusions. In SCT, sparse representation (SR) plays an essential role because it needs to perform several manipulations of sparse matrix representation (SMR) or nonnegative SMR in each iteration. So one of the most challenging problems in SCT is how to efficiently solve the SMR. However, existing SR algorithms are solely developed for the vectors-based SR. They partition SMR into a set of vector-based SR problems and solve them in the level-2 BLAS (Basic Linear Algebra Subprograms) manner, i.e., matrix-vector operations, which is computationally much less efficient than the direct level-3 BLAS (direct matrix-matrix operations). To solve this problem, by extending the standard SR algorithm from the vector version to the matrix for SMR and nonnegative SMR, BLAS3-based Sparse Learning (BLAS3-SpaL) is first developed, and then the corresponding BLAS3-SpaL-based SCT method (FastSCT-BLAS3SpaL) is further developed for fast robust-object-tracking in this paper. The experiments verified that it achieves robust object tracking by reducing accumulation errors and speeds up tracking with more than double speed.
Assessment of Seasonal Variation in Heavy Metal Status of a Lotic Ecosystem in Federal Capital Territory, Abuja, North Central Nigeria

The concentrations of Cu, Zn, Fe, Cd, Co, Cr, and Mn and their seasonal variations in water samples from the Wupa River, Abuja, Nigeria, were studied through the atomic absorption spectrophotometric method to determine the suitability of the water for domestic usage and identify potential sources of contamination. Sixty samples were collected during both dry and wet seasons. The respective metal concentrations (in mg/dm3) in the dry and wet seasons were as follows: Cu (0.023 ± 0.022, 0.023 ± 0.026), Zn (0.104 ± 0.039, 0.158 ± 0.085), Fe (0.350 ± 0.097, 0.3630.103), Cd (not detectable), Co (not detectable), Cr (0.003 ± 0.003, 0.004 ± 0.004), and Mn (0.120 ± 0.132, 0.110 ± 0.099). Among these metals, Cu, Zn, Cr, and Mn occurred in concentrations below the tolerable limits recommended by Nigeria Standard for Drinking Water Quality and WHO, whereas Fe exceeded these limits, and Cd and Co were not detectable. The calculated heavy metal pollution index values (68.22 in the dry season and 63.78 in the wet season) were lower than the critical value (100), indicating low pollution levels in both seasons. The metal index values for both seasons (1.50 for the dry season and 1.55 for the wet season) suggest that the water from the Wupa River was slightly affected by heavy metals. Moreover, no significant differences in metal concentrations existed between the dry and wet seasons. A strong positive correlation occurred between Zn and Fe only during the wet season. Water from the river was polluted with Fe and unsuitable for domestic use. Potential sources of contamination include agricultural areas, industrial effluents, and domestic waste in the wet season, and industrial and domestic sewage in the dry season. To make the river water safe for use, it should be treated and regularly monitored for metal contents, and sources of contamination should be managed appropriately.
Perancangan User Interface Dan User Experience Pada Customer Interface Website Perusahaan Transportasi Menggunakan Metode Usability Testing

Ordering transportation services through customer service requires a long time for negotiations re-garding prices, types of fleets and the amount of goods transportation services. The negotiations took a long time until agreed to order. From these problems, a safe interface is created where customers can find out the price per route and type of fleet as well as the number of goods transport services in-dependently and can be considered by customers regarding the prices that can be offered. The user in-terface (UI) page is made to facilitate website-based implementation. User interface pages are created with figma software using the usability testing method. The results of the analysis show that there are 4 UI/UX including User interface (UI) customer page, user interface (UI) check delivery page, user interface (UI) page stepper 1, user interface (UI) page stepper 2, user interface ( UI) page stepper 2, user interface (UI) page-safe stepper 3. The results of usability testing using aspects of the indicators of learnability, memorability, efficiency, errors, and satisfaction have been calculated to produce an average value above 0.78% per indicator. The results of this value show a large value and show that the UI/UX page of the customer interface is very good.