bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of the SAMRY Model (Mahfudzat Adaptation Stress and Guided Imagery) on Nurse Work Stress
Authors: Kurniawati Ayu Khuzaimah , Pramana Cipta , Pohan Vivi Yosafianti , Hartiti Tri , Soesanto Edy , Astuti Rahayu
Published: December 2024

Nurses’ work stress must be managed well. Work stress can affect nurses’ performance, reduce service quality, and cause turnover intention. The 2018 PPNI survey showed that 50.9% of Indonesian nurses experienced work stress. A preliminary study at K.R.M.T Wongsonegoro Hospital Semarang of 10 nurses in special units stated that 90% experienced work stress. The SAMRY (Stress Adaptation and Guided Imagery) model can reduce nurses’ work stress. This technique combines the application of the concepts of mahfudzat and guided imagery so that it can create relaxation distractions and increase adaptive coping patterns. This research aims to determine the effect of the SAMRY model on nurses’ work stress. The research method uses a pre-experiment with a pre-post-test one-group design. The population is 223 nurses who work in special units. Sample of 35 respondents using a purposive random sampling technique. Data collection was carried out by assessing work stress pre and post-intervention. The research instrument used the Expanded Nursing Stress Scale (ENSS) questionnaire. The results of the study reported an average pre-intervention work stress score of 114 and post-intervention 78.26. Data analysis using the paired sample t-test obtained p-value=0.000 (p0.05). It can be concluded that there is an influence of the SAMRY model on nurses’ work stress.
Design Laboratory for Developing Students Competencies: Physical Education for Elementary School
Authors: Raharjo Hermawan Pamot , Kurniawan Wahyu Ragil , Wijayanti Dwi Gansar Santi
Published: December 2024

Attention to student competence as prospective physical education teachers is very important. Physical education is not only learning about how to maintain health but also how to provide space for students to learn movement skills. Analysis in 2023 shows no laboratory that facilitates a special space for microteaching practice for prospective physical education teacher students at the elementary school level. This research aims to develop a basic physical education movement learning laboratory design for elementary school physical education study program students in 2023. The method used in this research is the research and development method. This type of development research is carried out to produce certain products and test the effectiveness of these products. The results of this research found that the suitability, safety, and usability of the products developed for users received a good response. Five questions addressed to lecturers and students as potential design users showed that on the first question, respondents gave a good response with an average of 72% regarding the placement and use of spatial layout. Next, regarding basic movement coverage, the result was 68.3%. Questions related to the suitability of material outcomes obtained a result of 65.1%. The percentage regarding aspects of ease and safety in use obtained a value of 55%, and regarding the usability and usefulness of the product, a response of 56.5% was obtained. This response concludes that the development product received a good response and support from the lecturers and students of the elementary school physical education study program. Suggestions for further research are the development of a laboratory with the concept of game activities by including elements of tactics and strategy.
Application of the Tonnis Game Branch of Sports in Improving Physical Fitness
Authors: Ragil Setiawan  , Hartati  , Herri Yusfi
Published: December 2024

This research investigates the impact and correlation of tennis games on the physical fitness of students at State Elementary School 11 Tanjung Batu. The study employs a quantitative descriptive approach to analyze data collected in percentage form, which is then discussed descriptively using a solid theoretical framework. The research involved 40 students from Tanjung Batu State Elementary School during the academic year 2023-2024. The findings reveal a robust relationship between the application of tennis games and improvements in physical fitness among students. The correlation coefficient (r) of 0.774 indicates a strong relationship, highlighting the effectiveness of tennis games in enhancing physical fitness levels. This is particularly evident in fostering creativity and skill development in small ball sports within the physical education curriculum. The implications drawn from this research underscore the practical benefits of incorporating tennis games into educational settings to bolster students’ physical fitness. The successful implementation of tennis games as a means to enhance physical fitness outcomes underscores its viability and relevance in educational practices. This research contributes valuable insights into the positive outcomes of integrating sports like tennis into physical education programs, emphasizing its role in promoting overall health and skill development among school children. In conclusion, the study substantiates the significance of tennis games not only as a recreational activity but also as a structured approach to improving physical fitness and fostering motor skill development among elementary school students. The findings encourage further exploration and adoption of tennis and similar activities within educational curricula to optimize physical education outcomes.
Efficiency of Coach Training in Turkey and Its Assessment Specific to Shooting Sport
Authors: Abiş Mehmet , Taşkıran Mehmet Yavuz
Published: December 2024

The primary aim of this study is to assess the efficiency of the coach training system in Turkey, with a specific focus on shooting coaches, and to gather the views of working, retired and volunteer coaches working in this field regarding this training. The research follows a correlational survey model and targets shooting coaches, encompassing both air and firearms disciplines, who possess coaching certificates and were actively engaged in coaching roles in Turkey during the year 2023, whether voluntarily or on a tenured or non-tenured basis. The research sample comprises 307 coaches, selected through simple random sampling from the larger population. Data for the study were collected through questionnaires. To this end, the researcher developed a questionnaire consisting of two parts, drawing on the existing literature and expert opinions. Quantitative methods, facilitated by the SPSS 25 program, were employed for data analysis. Results indicate that the overall sentiments of coaches in Turkey regarding the adequacy of coaching education in terms of content, duration, and facilities, as well as its impact on athletes’ skills and performance, and the coaches’ personal development through education, tended to be negative. Conversely, there were very strong (0.900.05).
Paranasal Sinus Mucoceles and their Ocular Impacts: A case report
Authors: Li Ziqing
Published: December 2024

Introduction: Paranasal sinus mucoceles are the build-up of mucous-containing, epithelium-lined, cystic lesions within the air-filled cavities in the bones surrounding the nasal cavity. An accumulation of mucous can occur in the sinus cavity when the normal drainage pathways are blocked, resulting in an increased volume of mucous.
Case report: A 56-year-old Hispanic male complained of proptosis, periorbital edema, and pain in the right eye, accompanied by cluster headaches persisting for the past six months. Initial examination demonstrated uncorrected visual acuity of 20/20 in both eyes at distance and near. Clinical assessments further revealed Hertel exophthalmometry measurements of 21 mm in the right eye and 19 mm in the left (base of 108 mm), along with resistance to manual pressure in the affected right eye. Subsequent computed tomography imaging of the head and orbits identified a sizable, well-defined mass originating from the right nasal cavity, extending into multiple paranasal sinuses, and inducing structural alterations in the medial wall of the maxillary sinus, consistent with paranasal sinus mucoceles.
Conclusion: Proptosis and lid edema can arise from various etiologies, encompassing intracranial masses, autoimmune disorders, or impaired venous return. This case report adds another consideration of a diagnosis in a patient with a history of sinus surgery. Comprehensive history gathering and meticulous clinical examination are paramount to discerning pathological manifestations in establishing an accurate diagnosis.
La narrativa romántico-sentimental y las pedagogías afectivo-emocionales: diálogos entre pasado y presente
Authors: Abramowski Ana
Published: December 2024

El artículo parte de constatar la actual proliferación de pedagogías afectivo-emocionales de diverso signo y, para comprender este fenómeno, establece relaciones entre estas iniciativas y la narrativa romántico-sentimental configurada en los albores de los sistemas educativos modernos. La hipótesis sostenida es que el entramado precedente funciona de sostén de las actuales pedagogías afectivo-emocionales, al configurar un terreno propicio para su instalación. Luego de presentar el papel que jugaron los sentimientos en la configuración de las subjetividades modernas hacia los siglos XVIII y XIX, y de describir la trama romántico-sentimental que se fue tejiendo en los orígenes del sistema educativo argentino, el artículo se detiene en las críticas formuladas hacia el sustrato romántico-sentimental, en particular, aquella que focaliza en el sentimentalismo.
Educación Emocional en la Ciudad de Buenos Aires: una política pública para la individualización de los procesos pedagógicos
Authors: Feldfeber Myriam , Rodrigo Lucrecia , Kesler Axel , Pantoja Cecilia
Published: December 2024

Este artículo examina la incorporación de la perspectiva de la educación emocional en las políticas educativas para el nivel secundario en la Ciudad Autónoma de Buenos Aires. Se pone atención en las intervenciones relacionadas con la reforma curricular, la evaluación y la formación docente, así como en su institucionalización dentro de la estructura burocrática del Estado y en el ámbito legislativo. El estudio se basa en el análisis de documentos oficiales, normativas, proyectos legislativos y entrevistas semiestructuradas a funcionarios del área de educación de la ciudad. Los hallazgos principales indican que las políticas que promueven la educación emocional en la ciudad se sustentan en una perspectiva instrumental, que atribuye al individuo y a la regulación de sus emociones la solución a los problemas socioeducativos. Este enfoque, no obstante, tiende a relegar las condiciones sociales que afectan los procesos pedagógicos a un plano secundario.
Formación para dirigentes sociales como herramienta para el desarrollo de gobernanza territorial
Authors: Rosas-Leutenegger Marco , Dougnac-Quintana Paulette , Vivallo-Urra Oscar Gabriel , Muñoz-Valenzuela Catherine , Castro-Machuca Yasna
Published: December 2024

El presente artículo analiza la experiencia de la Escuela para la Gobernanza y las Políticas Públicas (EGPP) de la Región de La Araucanía (Chile), ejecutada por la Universidad de La Frontera, a través del Instituto de Desarrollo Local y Regional. El diseño de investigación fue de carácter descriptivo-exploratorio de tipo cualitativo, con el objetivo de conocer las percepciones y experiencias de dirigentes sociales respecto de la contribución de la EGPP. Los resultados identifican aportes en términos del conocimiento adquirido por los participantes para su gestión como dirigentes sociales, el desarrollo de capacidades para la gobernanza territorial, y la generación y fortalecimiento de redes en el contexto de su participación en la Escuela.
Assessment of Weight Change and All-Cause Mortality Based on Body Mass Index Intervals in South Korea: A 12-Year Follow-Up of the Korean Longitudinal Study of Aging
Authors: CHO DaHye , LEE Jae Hyuck , HONG Seung Wan , SUH Young Sung , KIM Dae Hyun
Published: December 2024

Background: Obesity and weight loss are associated with increased mortality. Understanding the association between weight change and mortality is critical and can help inform effective prevention and intervention strategies. Therefore, this study aimed to investigate the association between weight change and mortality based on body mass index (BMI) intervals using data from a 12-year follow-up survey in Korea.Methods: We used data from the Korean Longitudinal Study of Aging from 2006 to 2018. Individuals aged 45–69 years without a history of malignancy and chronic obstructive pulmonary disease at baseline were selected. Cox regression analysis was used to compare mortality based on body mass index and weight change.Results: Compared with individuals with a body mass index of 20.0–25.0 kg/m2 and an increase in body weight of <5 kg, mortality was 3.8 times higher in the group with a body mass index of <20.0 kg/m2 and a weight loss of <5 kg, two times higher in the group with a body mass index of 20.0–25.0 kg/m2 and weight loss of >10 kg, and 4.3 times higher in the group with a body mass index of ≥25.0 kg/m2 and weight gain of ≥10 kg. Conclusions: Weight loss in underweight or normal-weight individuals and weight gain in individuals with obesity increased the mortality rate compared with individuals with normal weight and less weight change. This suggests that body weight and the changes in the weight of individuals are crucial, and weight loss in patients with underweight and weight gain in patients with obesity are closely related to increased mortality.
Risk Factors for Dysfunctional Thinking about COVID-19 among Nurses Caring for Patients with COVID-19
Authors: CHOI Hye-Ran , PARK Yeon-Hwan
Published: December 2024

Background: This study aims to identify factors influencing dysfunctional thinking about coronavirus disease 2019 (COVID-19) among nurses who have experience caring for COVID-19 patients.Methods: A survey was conducted on a total of 152 nurses nationwide from March 11 to March 19, 2024. Data were analyzed using descriptive statistics, independent t-test, χ2-test, or Fisher’s exact test. Logistic regression analysis was performed to identify risk factors for dysfunctional thinking about COVID-19.Results: There were 23 respondents (15.1%) with dysfunctional thinking about COVID-19. The posttraumatic growth score was 3.37±1.14. Risk factors influencing dysfunctional thinking about COVID-19 were age of 31 years or older (odds ratio [OR]=4.39, 95% confidence interval [CI]=1.30–14.87), chronic diseases of co-living family (OR=13.60, 95% CI=1.39–133.06), and nursing for confirmed patients within 1 month (OR=3.34, 95% CI=1.08–10.32).Conclusions: This study identified risk factors that affect dysfunctional thinking about COVID-19 among nurses working in various-sized medical institutions in Korea. This is expected to be helpful for improving healthcare workers’ psychosocial and environmental intervention during infectious disease pandemics in the future.
The Motivation to Volunteer and Change of Attitudes Towards Volunteering in a Post-Soviet Country
Authors: Pranaitytė Irma
Published: December 2024

The paper explores the attitudes towards volunteering and the change of attitudes towards volunteering in a Post-Soviet country after the collapse of the Soviet regime. The aim of the paper is to reveal what are the factors which keep individuals away from joining voluntary organizations, how the attitude towards volunteering has been changing over 30 years and what motivates individuals to get involved in voluntary organizations. A qualitative research method has been chosen – 60 interviews with individuals who have been born in 1945–1965 and have been living under the Soviet regime. The results reveal the change of attitudes towards volunteering in five periods and how the understanding about volunteering has been changing. Voluntary organizations can use the results of the research for the attraction of potential volunteers to volunteering.
Diversity in Education and Its Social Implications: Predictors of Diversity Competence of the Future Teachers
Authors: Andronache Daniel , Stănescu Mirona-Horiana
Published: December 2024

This study explores the factors influencing the development of diversity competence in future primary and preschool teachers, focusing on age, religiosity, background, and sexual orientation. Diversity competence refers to the ability to interact effectively with diverse groups across various dimensions, such as culture, gender, religion, and socioeconomic status, allowing educators to create inclusive classroom environments that respect and value each student’s unique background. Using the DiKo rating scale, data were collected from 170 student teachers at Babeș-Bolyai University. The analysis employed Pearson correlation and regression models to assess the relationship between these demographic factors and diversity competence. The results indicate that religiosity and age have a significant, though modest, influence on diversity competence, with intrinsic religiosity linked to greater openness to diversity. Conversely, sexual orientation and background were found to have no significant impact on diversity competence. These findings have important implications for teacher education programs, particularly the need to promote empathy, self-reflection, and critical engagement with diverse groups. The study also highlights the importance of future research to further investigate the influence of sexual orientation and background on diversity competence, considering the limitations of the current sample size.
Analysis of Targeting Accuracy of Sembako Programme in Rangkasbitung Sub-district through Logical Framework Approach (LFA)
Authors: Maulana Asep , - Harianto , - Sumardjo
Published: December 2024

Abstract. Sembako programme is a government programme in reducing poverty, in practice the sembako programme often faces problems, one of which is target accuracy. The inaccuracy of targeting in the sembakoprogramme often results in food assistance that is not appropriate and does not touch the people who really need it, thus hampering the success of the programme. Therefore, this study analysed the Sembako program in Rangkasbitung Sub-district with a focus on the accuracy of targeting using the Logical Framework Approach (LFA). The main objectives of this study were to find the problems of targeting for the Sembako program and to make an improvement plan to improve the accuracy of the targeting of the Sembako program. The results showed that targeting accuracy in the kecamatan was affected by low data quality and weak verification. To ensure that the targeting accuracy is met, this study suggests creating clearer poverty indicators and training human resources. There is also a need for updated and connected data. The results of this study are expected to have an impact on the improvement of the Sembako programme so that it can target the people who really need it. Keywords: Sembako Program, Targeting Accuracy, Logical Framework Approach (LFA), Data Quality, Verification, Human Resources (HR). Abstrak. Program sembako merupakan program pemerintah dalam mengurangi kemiskinan pada praktiknya program sembako sering menghadapi masalah salah satunya adalah ketepatan sasaran. Ketidaktepatan sasaran dalam program sembako sering kali mengakibatkan bantuan sembako tidak tepat guna dan tidak menyentuh masyarakat yang benar-benar membutuhkan sehingga menghambat keberhasilan program. Oleh karena itu Penelitian ini menganalisis program Sembako di Kecamatan Rangkasbitung dengan fokus pada ketepatan sasaran menggunakan pendekatan Logical Framework Approach (LFA). tujuan utama penelitian ini adalah untuk menemukan masalah tepat sasaran untuk program Sembako dan untuk membuat rencana perbaikan untuk meningkatkan ketepatan sasaran program Sembako. Hasil penelitian menunjukkan bahwa ketepatan sasaran di kecamatan dipengaruhi oleh kualitas data yang rendah dan verifikasi yang lemah. Untuk memastikan tepat sasaran terpenuhi, penelitian ini menyarankan pembuatan indikator kemiskinan yang lebih jelas serta pelatihan sumber daya manusia. Selain itu diperlukan juga penyempurnaan data yang diperbarui dan terkoneksi. Hasil penelitian ini diharapkan dapat berdampak pada perbaikan program Sembako yang tepat sasaran sehingga sembako dapat menyasar masyarakat yang benar-benar membutuhkan. Kata Kunci: Program Sembako, Ketepatan Sasaran, Logical Framework Approach (LFA), Kualitas Data, Verifikasi, Sumber Daya Manusia (SDM).
K-Drama Excessive Watching Behavior and Loneliness of Parasocial Interaction in College Students
Authors: Saptari Saptari , Suhesty Aulia , Rasyid Miranti , Handayani Nanik
Published: December 2024

Abstract. The emergence of the Korean Wave, encompassing K-dramas and K-pop, has garnered significant interest, particularly among college students. This research investigates how excessive viewing and feelings of loneliness impact social interactions. Utilizing a quantitative research design, the study involved 83 students from the Faculty of Social and Political Sciences at X University, selected through probability sampling methods. Data collection methods included scales measuring parasocial interactions, excessive viewing habits, and loneliness levels. The analysis employed multiple linear regression techniques. Key findings indicate that: (1) excessive viewing and loneliness significantly affect parasocial interactions, with an F-value of 3.992 exceeding the F-table value of 3.18 and a p-value of 0.001, contributing an influence of 42.1% (R²); (2) excessive viewing positively correlates with parasocial interactions, shown by a beta coefficient (β) of 0.377, a t-value of 2.071 surpassing the t-table value of 2.008, and a p-value of 0.044 (p < 0.05); (3) however, loneliness does not significantly impact parasocial interactions, evidenced by a beta coefficient (β) of 0.156, a count of 0.156.859 falling below the t-table value of 2.008, and a p-value of 0.395 (p < 0.05). Keywords: Social interaction, excessive watching, loneliness. Abstrak. Perkembangan fenomena Korean Wave, yang mencakup K-Drama dan musik K-Pop, telah menarik perhatian yang luas, khususnya di kalangan mahasiswa. Penelitian ini bertujuan untuk mengeksplorasi dampak dari menonton secara berlebihan dan perasaan kesepian terhadap interaksi parasosial. Metode yang digunakan dalam penelitian ini adalah pendekatan kuantitatif. Subjek penelitian terdiri dari 83 mahasiswa Fakultas Ilmu Sosial dan Ilmu Politik Universitas X yang dipilih melalui teknik probability sampling. Pengumpulan data dilakukan dengan menggunakan skala untuk mengukur interaksi parasosial, tingkat menonton berlebihan, dan kesepian. Analisis data dilakukan menggunakan regresi linier berganda. Hasil penelitian menunjukkan bahwa: (1) terdapat pengaruh signifikan antara menonton berlebihan dan kesepian terhadap interaksi parasosial, dengan nilai F hitung sebesar 3.992 yang lebih besar dari F tabel 3.18 dan nilai p sebesar 0.001, serta kontribusi pengaruh (R²) mencapai 42.1%; (2) terdapat pengaruh positif yang signifikan dari menonton berlebihan terhadap interaksi parasosial dengan nilai koefisien beta (β) sebesar 0.377, t hitung 2.071 lebih besar dari t tabel 2.008, dan nilai p sebesar 0.044 (p < 0.05); (3) tidak ditemukan pengaruh signifikan dari kesepian terhadap interaksi parasosial dengan nilai koefisien beta (β) sebesar 0.156, t hitung 0.859 lebih kecil dari t tabel 2.008, dan nilai p sebesar 0.395 (p < 0.05).Kata Kunci: Interaksi parasosial, menonton berlebihan, kesepian.
The Policy Formation Process of Inclusivity PEKKA Foundation with Australian DFAT
Authors: Jihan Nur , Yudono Raden Maisa
Published: December 2024

Abstract. This research discusses the inclusion policy formulation process conducted by Pemberdayaan Perempuan Kepala Keluarga (PEKKA) Foundation and the Australian Department of Foreign Affairs and Trade (DFAT). This research background is the social and economic vulnerability experienced by female-headed households in Indonesia. This research examines multi-stakeholder collaboration and the process of formulating inclusive policies in Indonesia. The research method is descriptive qualitative, with interview techniques and non-participant observation. The results show that policy-making involves five stages: agenda setting, policy formulation, policy adoption, policy implementation, and policy evaluation. At each stage, both PEKKA and DFAT play their respective roles through collaboration using the multi-stakeholder partnership (MSP) approach, resulting in empowerment programs such as the Klinik Layanan Informasi dan Konsultasi (KLIK PEKKA) and the Paradigta Academy, which have increased access to basic services and political participation of the female-headed family. Keywords: Policy; female- headed family; PEKKA; DFAT; MSP Abstrak. Penelitian ini membahas proses perumusan mengenai kebijakan inklusivitas yang dilakukan oleh Yayasan Pemberdayaan Perempuan Kepala Keluarga (PEKKA) bersama dengan Australian Department of Foreign Affairs and Trade (DFAT). Latar belakang penelitian ini adalah isu kerentanan sosial dan ekonomi yang dialami oleh perempuan kepala keluarga di Indonesia. Penelitian ini bertujuan untuk mengkaji kolaborasi multi-stakeholder serta proses perumusan kebijakan inklusivitas di Indonesia. Metode penelitian yang digunakan adalah kualitatif deskriptif, dengan teknik wawancara dan observasi non-partisipan. Hasil penelitian menunjukkan bahwa proses pengambilan kebijakan melibatkan lima tahap, yaitu agenda setting, formulasi kebijakan, adopsi kebijakan, implementasi kebijakan, dan evaluasi kebijakan. Dalam setiap tahap, baik PEKKA maupun DFAT memainkan perannya masing-masing melalui kolaborasi menggunakan pendekatan multi-stakeholder partnership (MSP) yang menghasilkan program-program pemberdayaan seperti Klinik Layanan Informasi dan Konsultasi (KLIK) PEKKA dan Akademi Paradigta yang berhasil meningkatkan akses layanan dasar dan partisipasi politik perempuan kepala keluarga.  Kata Kunci: Kebijakan; perempuan kepala keluarga; PEKKA; DFAT; MSP
Emotion and Gender
Authors: Salvo Irene
Published: December 2024

At times of war and violence in more than one region, being able to write and publish in 2024 seems like a privilege. I open the present issue of the Journal of Cognitive Historiography with an acknowledgement of such privilege and with a message of solidarity to all scholars currently suffering adverse political conditions and being forced to stop researching.
Development of a neural network approach for risk management in helicopter technical condition diagnostics
Authors: Koshekov Kayrat , Pirmanov Ildar , Kenbeilova Saltanat , Koshekov Abay , Togambayev Rustam , Toiganbayev Beglan
Published: December 2024

The object of the study is the quality of helicopter maintenance based on digital diagnostic tools. To ensure the required quality, quantitative risk assessment models for the in-depth and express diagnostics system of helicopter gas turbine engines in a neural network environment are proposed. The assessment of diagnostic efficiency is based on the analysis of probable control risks by standard deviations, which distinguishes the proposed approach from the traditional one. Two diagnostic modes are considered: rapid diagnostics exemplified by vibration diagnostics, and in-depth diagnostics, including both vibration diagnostics and pyrometric control. These diagnostic methods make it possible to implement a remote monitoring system at aircraft repair facilities, which significantly reduces maintenance labor intensity. As a result, it was found that control risks depend not only on the metrological level of measuring instruments but also on a combination of the statistical nature of control agents in their system composition according to the following characteristics: statistical parameters of the controlled indicator, distribution laws, and values of uncertainty of measuring instruments, as well as the uncertainty of control standards (tolerances). In the modeling process, risks were assessed as a function of the ratio of uncertainties of measuring instruments to the uncertainty of the controlled parameter, with varying values of the standard (tolerance). This approach will allow, in practice, the creation of a more effective system for monitoring and collecting statistical information on the operational reliability of the Mi-8 helicopter engine, where the quality of control is predicted to a greater extent based on the metrological indicators of the measuring instruments and methods
Developing an early detection model for skin diseases using a hybrid deep neural network to enhance health independence in coastal communities
Authors: Harumy Tengku Henny Febriana , Br Ginting Dewi Sartika , Manik Fuzy Yustika , Alkhowarizmi Alkhowarizmi
Published: December 2024

The object of study is a solution for early skin disease diagnosis by integrating hybrid deep neural networks – EfficientNetB7 for Classification and YOLOv8 for detection. The system is designed to classify five skin conditions: Melanoma, Basal Cell Carcinoma (BCC), melanoma is a type of skin cancer that originates from melanocytes, the cells that produce skin pigment, Melanocytic Nevi (NV) Melanocytic nevus is a mole or dark spot on the skin formed due to the accumulation of melanocytes, Benign Keratosis-like Lesions (BKL) is a term for a group of skin changes that resemble keratosis but are non-cancerous, and Seborrheic Keratoses and other benign tumors to enhance the health diagnostics. The problem to be solved in this study revolves around improving early and accurate skin disease diagnosis, particularly in resource-limited or underserved areas and the lack of Accessible Diagnostic Tools and Low Efficiency of Current Diagnostic Methods. The study highlights EfficientNetB7's classification accuracy at 94 % and YOLOv8's means average precision (mAP) of 0.812 for detection. This hybrid system processes skin images efficiently, providing classification and detection outcomes with consistent performance in multiple tests. The results demonstrate that the EfficientNetB7 model achieved an accuracy of 94 % on test data, while YOLOv8 delivered a detection performance with a mean average precision (mAP) of 0.812. The web-based system efficiently processed skin images and provided classification and detection outcomes.
Furthermore, integrating EfficientNetB7 and YOLOv8 allowed the skin disease detection system to classify five different diseases and assess malignancy risk. The systems are portable and can be used with minimal setup, making them practical for real-world diagnostic use. The Scope and Practical applications are designed for accessibility in resource-limited settings. The website-based skin disease detection tool provides a user-friendly platform accessible to the public and healthcare providers, especially in underserved areas. Each application's high accuracy and ease of use make them viable aids in early diagnosis, potentially improving healthcare access
Rationale for choosing the airfoil of a UAV wing using a dynamic ground effect principle
Authors: Dreus Andrii , Kravets Olena
Published: December 2024

Vehicles that use the principle of dynamic ground effect principle are innovative vehicles that have prospects for use as high-speed unmanned vehicles. It is known that when an aircraft moves near the ground, the phenomenon of increasing lift occurs, which allows for contactless movement at high speeds. However, the effectiveness of this ground effect depends on the airfoil shape. The object of this study is the aerodynamic processes that occur during the movement of an unmanned aerial vehicle near the ground. The influence of the effect of approaching the ground on the aerodynamic characteristics of four airfoil of different shapes has been considered: Clark YH-12, NACA-M6, USA-35B, TsAGI-721, which are used in subsonic high-speed aircraft, including unmanned aerial vehicles. The aim of the work is to evaluate the performance of these aerodynamic airfoils in near-surface operation and to determine the most promising shape for use in small unmanned WIGs. CFD modeling methods were used as a research tool. The pressure and velocity fields around the wing airfoils were determined and the influence of the distance to the ground and the angle of attack on the aerodynamic characteristics was established. It was found that the best aerodynamic quality for all airfoils is achieved at angles of attack of 4–6°. It is not recommended to use airfoils with angles of attack close to 0° as the ground may have a negative effect on lift. The USA-35B airfoil demonstrated the greatest increase in aerodynamic quality when approaching the surface, with a maximum increase of 67 %. This makes it possible to recommend USA-35B as small unmanned aerial vehicles with a dynamic ground effect principle
Advancing real-time echocardiographic diagnosis with a hybrid deep learning model
Authors: Bolshibayeva Aigerim , Rakhmetulayeva Sabina , Ukibassov Baubek , Zhanabekov Zhandos
Published: December 2024

This research focuses on developing a novel hybrid deep learning architecture designed for real-time analysis of ultrasound heart images. The object of the study is the diagnostic accuracy and efficiency in detecting heart pathologies such as atrial septal defect (ASD) and aortic stenosis (AS) from ultrasound data.
The problem is the insufficient accuracy and generalizability of existing models in real-time cardiac image analysis, which limits their practical clinical application. To solve this, the convolutional neural networks (CNNs), combining local feature extraction was integrated with global contextual understanding of cardiac structures. Additionally, a YOLOv7 for precise segmentation and detection was utilized.
The results demonstrate that the hybrid model achieves an overall diagnostic accuracy of 92 % for ASD detection and 90 % for AS detection, representing a 7 % improvement over the standard YOLOv7 model. These improvements are attributed to the hybrid architecture's ability to simultaneously capture fine-grained anatomical details and broader structural relationships, enhancing the detection of subtle cardiac anomalies.
The findings suggest that combination of CNNs enhances pattern recognition and contextual analysis, leading to better detection of cardiac anomalies. The key features contributing to solving the problem include the hybrid architecture's ability to capture detailed local features and broader structural context simultaneously.
In practical terms, the model can be applied in clinical settings that require real-time cardiac assessment using standard medical imaging equipment. Its computational efficiency and high accuracy make it suitable even in resource-constrained environments, reducing analysis time for clinicians, supporting personalized treatment plans, and potentially improving patient outcomes in cardiology
Development of a magnetic activator to protect an electric water heater against scale formation
Authors: Mekhtiyev Ali , Sarsikeyev Yermek , Gerassimenko Tanya , Alkina Aliya , Mekhtiyev Ruslan , Neshina Yelena , Kirichenko Lalita
Published: December 2024

The paper is dedicated to the research and development of a magnetic activator for the prevention of scale formation in electric water heaters, which is a pressing problem in regions with hard water, typical for Сentral Kazakhstan. During the operation of water heaters, salt deposits on heating elements lead to increased energy consumption and reduced efficiency. The developed activator uses powerful neodymium magnets that change the structure of the hardness salts in the water, preventing their deposition in the form of scale. Research has shown that the use of a magnetic activator can reduce water hardness by 15–20 %, resulting in a significant reduction in scale formation. In particular, under normal operating conditions, the thickness of the scale layer can reach 2–4 mm, but with the use of the magnetic activator this indicator is reduced to less than 1 mm. Descaling the heating elements not only extends the life of the water heater, but also reduces energy costs. Energy consumption is reduced by 10–15 %, as water heaters with less scale work more efficiently without requiring additional energy for heating. The paper also discusses the design features of the magnetic activator, the principles of its operation and the results of laboratory and field tests. Economic analysis has shown that the installation of the magnetic activator pays for itself within 1–2 years due to the reduction in limescale and energy costs. This makes it an attractive solution for private households as well as for industrial companies that use water heaters in their production process, as the proposed magnetic activator is an effective solution for protecting water heaters from the negative effects of hard water
Big data analytics for seasonal crop patterns: integrating machine learning techniques
Authors: Yunis Roni , Halim Arwin , Pardosi Irpan Adiputra
Published: December 2024

This study addresses the challenge of predicting rice growing season lengths, crucial for agricultural planning in tropical regions. Climate variability and season timing create uncertainties in decision-making, and while machine learning is widely used in agriculture, a gap persists in integrating spatial-temporal data for accurate season length prediction and region-specific pattern analysis influenced by rainfall. Using a combination of Random Forest algorithms with hyperparameter optimization (grid search), and clustering techniques such as PCA, K-Means, and Hierarchical Clustering, this study analyzes key features such as the start of the season (SOS), end of the season (EOS), and their significance indicators (sig_sos and sig_eos). The findings reveal a strong correlation (0.98) between SOS and EOS, with an optimal growing season ranging from day 93 to day 207 (113.82 days). The Random Forest model, optimized with Grid Search, achieved a MSE of 28.9474 and an R2 of 0.8636, showing an outstanding predictive result. SHAP and LIME analyses identified sos and eos as the most influential predictors, while cluster analysis highlighted three distinct growing season groups characterized by variations in rainfall and seasonal stability. These results underscore the importance of understanding localized agricultural conditions and provide actionable insights for optimizing planting schedules, resource allocation, and climate adaptation strategies. By integrating advanced machine learning techniques with spatial-temporal data, this study establishes a foundation for improving agricultural resilience and sustainability in the face of climate variability
Devising investment strategies as a source of financial support to the development of territorial communities in the era of digitalization
Authors: Radynskyy Serghiy , Ratynskiy Vadym , Lobodina Zoryana , Shpylyk Svitlana , Pohrishchuk Halyna , Dobizha Nataliia , Bei Snizhana , Diachenko Nataliia , Diachenko Valentyn , Piniak Iryna
Published: December 2024

The object of this study is the process of financial support to the development of territorial communities under the conditions of digitalization. The task addressed was insufficient financial support to territorial communities, which, in turn, limits their development under the conditions of digitalization. The need to devise and implement an investment strategy as a basis of financial support to the development of territorial communities has been identified. The interpretation of the research results demonstrates the significant impact of digitalization on the directions and technologies of the investment strategy of territorial communities. This makes it possible to choose the most popular sources of funding for investment strategies of territorial communities under conditions of digitization. An example of sources of funding for the strategic goals of the digital development of the urban territorial community was given, among which the local budget funds and grant funds prevail. The results prove that the successful development of territorial communities in the era of digitalization depends on their ability to determine target orientations and diversify their funding sources. A distinctive feature of the research results is the construction of a model for the development of territorial communities under conditions of digitalization based on an investment strategy. In order to increase the effectiveness of the process of development and implementation of the investment strategy of territorial communities, the implementation of two-level filtering has been  envisaged – according to goals and financial resources. The use of the proposed model would create prerequisites for the further development of territorial communities under the conditions of digitalization. The domain of practical use of the results extends to the management of regional investment development, which involves increasing the size of financial investments and improving the well-being of residents of territorial communities
Estimating the influence of the rigidity of support assemblies on the resonance phenomena and the vibration state of a hydraulic unit
Authors: Tretiak Oleksii , Kovryga Anton , Kravchenko Stanislav , Shpitalnyi Denys , Zhukov Anton , Serhiienko Serhii , Arefieva Mariia , Penkovska Nataliia , Madonych Andrii
Published: December 2024

Many factors affect the vibration of the hydraulic unit, including the natural oscillation frequencies of the structural elements, which in some cases may contribute to an increase in vibration because of the occurrence of resonance phenomena.
In this work, the case of design optimization of the support assemblies of the shaft pipeline of the hydrogenerator-motor was considered, installed at HSPP during its reconstruction in order to improve vibration parameters. The effect of increasing the stiffness of the upper crosspiece and reducing the weight of the rotating parts on the value of the first and second critical rotation frequencies was analyzed. Based on the results of computations, operability of the proposed new reinforced structure of the upper crosspiece of the hydrogenerator-motor with increased rigidity was confirmed. Using this design could increase the first critical rotation frequency from 9 Hz (540 rpm) to 17.6 Hz (1056 rpm). This would lead to the avoidance of resonance phenomena caused by the proximity of the first critical rotation frequency of the rotor to the rated rotation frequency (600 rpm).
The computations were performed in a three-dimensional setting in two stages for each of the considered design cases. At the first stage, the supporting elements rigidity of the shaft line of the hydrogenerator-motor were studied by determining the structural element elastic deformations when it was loaded by a transverse force. At the second stage, these determined stiffnesses of the support elements were used as input data for calculating the critical rotation frequencies of the hydraulic unit rotor
Development a set of mathematical models for anomaly detection in high-load complex computer systems
Authors: Meleshko Yelyzaveta , Yakymenko Mykola , Mikhav Volodymyr , Shulika Yaroslav , Davydov Viacheslav
Published: December 2024

The subject of this study is the process of anomaly detection in high-load complex computer systems (HLCCSs). The task addressed in the paper is the lack of real-time anomaly detection models in HLCCS with a specified accuracy. A set of mathematical models for real-time anomaly detection has been built and investigated. This set includes a mathematical model for detecting anomalous connections between components of computer system (DACCCSs) and a mathematical model for assessing current state of computer system (CSACS).
The results of models tests showed the following efficiency metrics. For a DACCCS model: accuracy – 84 %, positive predictive value – 87 %, recall – 74 %, and weighted average accuracy (WAA) – 78 %. For a CSACS model: accuracy – 91 %, positive predictive value – 82 %, recall – 68 %, and WAA – 67 %.
The positive results of the study can be attributed to the following factors. A DACCCS model uses projection matrices and orthogonal vector functions to analyze anomalies. This enables the creation of spatial decompositions that reveal complex interrelationships between system components using only eigenvalues and eigenvectors. A CSACS model applies the singular value decomposition method, which implies solving a system of scalar equations to determine the current state of the system. This approach minimizes computational costs compared to methods requiring the solution of complex matrix equations. Thus, the model could be applied for real-time data analysis and anomaly detection under conditions of limited resources and high system load.
The practical application scope includes HLCCS, such as banking transaction servers and cloud platforms, in which it is essential to enable stable operation under high request amount and to minimize the risk of data loss or service failure
Design and application of CNN for emission detection through thermal imagery
Authors: Yuniardi Doddi , Madenda Sarifuddin , Ridwan Ridwan , Prihandoko Prihandoko , Abdillah Abdul Azis , Permana Sulaksana
Published: December 2024

Motorcycle exhaust emissions (EE) that do not meet regulatory standards present a significant environmental and public health issue, particularly given the rising number of motorcycles in densely populated areas. These emissions release pollutants such as carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx), which contribute to poor air quality and have adverse effects on human health. Traditional emission testing methods using gas analyzers, while commonly used, face limitations such as sensitivity to environmental fluctuations, the necessity for frequent recalibration, and an intensive testing process requiring specialized expertise. This study addresses these issues by developing an innovative method for emission detection using Convolutional Neural Networks (CNN) applied to thermal images of motorcycle exhausts. The research method involves five key stages: data acquisition, dataset formation, CNN model design and training, model testing, and validation. Thermal images were gathered from 27 motorcycles, representing various brands and engine configurations common in Indonesia, and each image set included 100 samples for both emission-compliant and non-compliant categories. By analyzing thermal patterns, the CNN model was trained to accurately detect combustion patterns indicative of emission status based on the lambda value. This approach enables the model to generalize across different motorcycle models, offering practical adaptability for widespread implementation. The results demonstrate that the CNN model delivers high predictive accuracy, precision, recall, and F1-score, making it a robust tool for assessing motorcycle emission compliance. This CNN-based approach provides a practical solution for real-time, large-scale emission monitoring and regulatory enforcement, reducing dependency on conventional methods. Its scalability and adaptability position it as a valuable advancement in emission monitoring technology, with significant potential for supporting environmental standards and improving air quality management