bluuebunny/crossref_metadata_2025 huggingface dataset:
Sosialisasi Dalam Mengoptimalisasi Pelayanan Rekam Medis Elektronik (ERM) Rawat Inap di Rumah Sakit Siaga Al Munawwarah Samarinda
Authors: Zanetti Nazarani Kezia , M. Ardan M. Ardan
Published: November 2024

Latar Belakang: Rumah Sakit sebagai institusi pelayanan kesehatan harus terus meningkatkan mutu layanan, salah satunya penerapan teknologi Rekam Medis Elektronik (ERM) yang dapat meningkatkan efisiensi administratif dan keamanan data pasien, serta memfasilitasi proses diagnosis. Tujuan: Tujuan kegiatan ini untuk meningkatkan efesiensi pelayanan kesehatan melalui implementasi ERM. Metode: Metode ini menggunakan deskriptif kualitatif dengan pendekatan Fishbone untuk mengidentifikasi penyebab permasalahan, termasuk faktor Man, Material, Machine, dan Methode. Hasil: Berdasarkan hasil observasi dan wawancara yang dilakukan di Rumah Sakit Siaga Al Munawwarah Samarinda, ditemukan Rekam Medis Rawat Inap belum berbasis elektronik. Meskipun rumah sakit memiliki perencanaan , hal tersebut mengalami keterlambatan karena programer memiliki tugas dibeberapa rumah sakit. Selain itu, banyaknya file rekam medis yang harus diinput dan belum tersediannya sistem ERM Rawat Inap memperlambat digitalisasi. Kesimpulan: Rekomendasi tambahan mencakup audit infrastruktur, pelatihan staf, dan pemantauan rutin setelah implementasi.
Edukasi Penerapan Keselamatan dan Kesehatan Kerja Pada Proyek Konstruksi Bangunan Rumah Ibadah di Minahasa
Authors: Marthinus Adrian Philip , Malingkas Grace Yoyce , Tjakra Jermias
Published: November 2024

Latar Belakang: Berdasarkan data Prioritas Ketenagakerjaan SDI, jumlah kecelakaan kerja di Indonesia mencapai 162.327 kasus dari Januari hingga Mei 2024. Tingginya angka kecelakaan kerja sebagian besar disebabkan oleh kelemahan sistem manajemen keselamatan dan kesehatan kerja yang diterapkan oleh perusahaan-perusahaan tidak dilakukan peningkatan berkelanjutan (continual improvement). Tujuan: PKM ini bertujuan untuk meningkatkan kesadaran dan pemahaman mengenai penerapan K3 dalam proyek konstruksi, khususnya pada proyek pembangunan rumah ibadah di Minahasa. Metode: PKM menggunakan metode ceramah dan tanya jawab. PKM dilaksanakan pada tanggal 20 Juli 2024 di area direksi kitt. Hasil: Hasil PKM edukasi penerapan keselamatan dan kesehatan kerja meningkat sebanyak 96,5% (Post Test) dari 86% (Pre Test). Kesimpulan: Hal ini menunjukkan peserta menyadari pentingnya menerapkan K3 saat melakukan pekerjaan.
Profil Faktor Risiko Penyakit Tidak Menular Pada Masyarakat Negeri Mahia, Ambon
Authors: Mus Rosdiana , Asmin Elpira , Abbas Mutmainnah , Astuty Eka , Tamalsir Dylan , Esmeraldine Genevieva , Agustina Titin
Published: November 2024

Latar Belakang: Penyakit tidak menular (PTM) sebagai salah satu penyebab kematian. Deteksi dini di fasilitas kesehatan kurang efektif Sehingga perlu meningkatkan kesadaran masyarakat dengan melakukan pemeriksaan langsung melalui kegiatan pengabdian masyarakat. Tujuan: Tujuan kegiatan ini dilakukan untuk mengkaji faktor risiko PTM pada masyarakat di Mahia. Ambon. Metode: Metode pelaksanaan terdiri dari pra pelaksanaan, pelaksanaan dan evaluasi. Kegiatan ini dilaksanakan di mahia GPM. Hasil: Hasil kegiatan menunjukkan sebagian besar responden berusia 45-60 tahun. Pada pemeriksaan tekanan darah, kolesterol dan lingkar pinggang ditemukan lebih dari 50% responden mempunyai hasil yang tidak normal atau tinggi. Hasil pemeriksaan gula darah dan asam urat menunjukkan lebih dari 50% responden memiliki kadar normal. Kesimpulan: Pemeriksaan kesehatan seperti tekanan darah, kolesterol, gula darah dan asam urat didapatkan beberapas responden hasilnya tinggi sehingga perlu untuk dilakukan pemeriksaan berkala dan edukasi.
Pengaruh Metode Bil Qolam dalam Meningkatkan Kemampuan Membaca Al-Qur’an Siswa di SMP Khadijah Surabaya
Authors: Ningsih Dessi Fitria
Published: November 2024

The use of the bil qolam method applied at Khadijah Middle School in Surabaya is very important to study because this method is effective and has been proven to be able to produce a generation that is able to read the Al-Qur'an. The research method uses a quantitative approach, using percentage analysis techniques and Pearson product moment correlation. The population in this study were students in grades IX-X-XII, totaling 439 students. The sampling technique in this research used the Quota Porposive Random Sampling technique which was taken randomly from 439 students so that 20% was taken, namely 439 x 20%, namely 88. For data collection, questionnaires, observation and documentation were used. The location of this research is Khadijah Middle School, Surabaya. The results of the research show that the use of the bil qolam method at Khadijah Middle School Surabaya is in the very good category, namely reaching 89.20% which is in the 80%-100% interval. Meanwhile, the ability to read the Al-Qur'an at Khadijah Middle School Surabaya is categorized as very good, reaching 91.25%, which is in the 80%-100% interval. And there is an influence between the bil qolam method on the ability to read the Al-Qur'an of Khadijah Surabaya Middle School students, this is proven in the product moment analysis with a value of rxy = 0.603 which is included in the correlation coefficient interval of 0.60-0.799 which is classified as having a strong influence. There is a significant influence between the bil qolam method on students' ability to read the Al-Qur'an at Khadijah Middle School Surabaya, this is proven by tcount > ttable, namely 0.0097 > 1.66623.
Pengaruh Metode (SQ3R) Berbantuan Pohon Literasi Terhadap Peningkatan Hasil Belajar Siswa Kelas V
Authors: Amin H. , Julkifli Julkifli
Published: November 2024

Survey, Question, Read, Recite, And Review (SQ3R) Method. This method is a reading plan consisting of surveying the content, making questions, reading the content, telling the reading content, and reviewing the reading. Also, the SQ3R method is an integrated study plan to understand and master the reading content. This study aims to determine the effect of using the SQ3R method assisted by literacy trees on improving the learning outcomes of grade V students of SDN Inpres Padende in the 2023/2024 academic year. This type of research is pre-experimental with a quantitative approach. The population is all students from grades I to VI totaling 113 students. The sample used was grade V students totaling 17 students involving one class as the experimental class only. The sampling technique used a purposive sample. Data were obtained through pretest and posttest then analyzed using the t-test. Based on the initial test at the time of the pretest, an average of 65 was obtained, the final test results at the time of the posttest showed an average of 95. The final test data were analyzed using the t-test, the results of the t-test obtained a t-count of 61.36 and a t-table of 86.33. The t-count was obtained to be greater than the t-table at an error level of 5% and a dk of 16. Based on the proposed hypothesis, there is an effect of using the SQ3R method assisted by literacy trees on improving the learning outcomes of class V students of SDN Inpres Padende in 2023/2024.
Implementasi Edupreneurship Melalui Business Center di SMKN 1 Kaligondang
Authors: Muginah Muginah , Kusumawardhana Ap Massri M , Winarso Didik , Suwardi Suwardi , Kuat Tri
Published: November 2024

This research aims to describe and analyze the implementation of edupreneurship through the business center at SMKN 1 Kaligondang and how to foster an entrepreneurial spirit in students through this program. The research method used is a qualitative method, which aims to understand the implementation of edupreneurship and business center in the school. The research was conducted by observation and interviews with informants who were directly involved in edupreneurship activities. The results of this study show that: 1) the implementation of education is carried out through the business center, 2) Learning in the business center is carried out through business practices involving Accounting students in market observation activities, inventory of consumer needs, ordering/purchasing from the business center, determining selling prices, recording transactions and making reports, as well as managing their own finances. This activity succeeded in fostering an entrepreneurial spirit which included confidence, the courage to take risks, focus on tasks and results, as well as honesty and thoroughness.
Integrasi Etika AI dalam Pendidikan Agama Kristen: Tantangan dan Peluang
Authors: Nenomataus Ade Epatri , Rantung Djoys Anneke , Naibaho Lamhot
Published: November 2024

AI ethics is a branch of ethics that focuses on moral principles in the development and use of AI technologies. This research aims to integrate AI ethics in Christian religious education and explore the opportunities and challenges in the process, as well as strategies to overcome these challenges. The method used is a descriptive qualitative approach with literature studies from various sources such as books, national and international journals, and websites. The results show the importance of integrating AI ethics in Christian religious education to shape students' characters, prepare their future, and improve the quality of learning. Challenges faced include limited resources, digital divide, lack of understanding of AI ethics, and the need for adequate supervision and regulation. Strategies to address these challenges include improving technological infrastructure, training for teachers, and developing policies that support the integration of AI ethics in Christian religious education.
Implementasi Profil Pelajar Pancasila Berbasis Budaya Literasi dalam Mata Pelajaran Pendidikan Pancasila di SMA Negeri 5 Semarang
Authors: Asyhar Rifky Latieful , Haryati Titik , Wahyuni Endang Sri , Sudrajat Rahmat
Published: November 2024

Implementation of the Pancasila Student Profile based on literacy culture in Pancasila Education subjects at SMA Negeri 5 Semarang. This research was motivated by the lack of interest and awareness of students in promoting literacy culture, but something different was shown by SMA Negeri 5 Semarang by making various efforts to foster literacy culture through the Pancasila Student Profile. The aim of this research is to obtain data regarding the implementation of the Pancasila Student Profile based on literacy culture in Pancasila Education subjects at SMA Negeri 5 Semarang. The method used in this research is qualitative research using a descriptive approach. After carrying out research with various respondents, the researcher then processes the data and conclusions can be drawn in the form of data analysis results. The research results show that the implementation of the Pancasila Student Profile based on literacy culture in Pancasila Education subjects has been carried out well. This is realized in various kinds of activities that support literacy activities and are adapted to the six dimensions in the Pancasila Student Profile. The problems obtained are lack of student attention, lack of communication and collaboration. The solution that can be taken to overcome these problems is to increase communication and collaboration, involve related parties, and carry out monitoring and evaluation activities.
Strategi Efektif dalam Manajemen Kelas untuk Meningkatkan Keterlibatan Siswa
Authors: Sudharsono Muhamad , Rahayu Sri , Damayanti Sherli , Rahmah Laila
Published: November 2024

Increasing student participation is one of the main goals in education.Effective classroom management plays a key role in achieving this goal. This overview describes some effective classroom management strategies to increase student participation. Create a positive and informative learning environment. This can be achieved by building positive relationships with students, setting clear rules and expectations, and positively reinforcing desired behaviors. Implement active learning that is student-centered.This can be done by using various learning methods, such as collaborative learning, project-based learning and problem-based learning. Provide effective feedback and evaluation. Effective feedback and assessment help students understand their progress and learn from their mistakes. Parent and community involvement. Parents and the community can play an important role in supporting student learning.
Effectiveness of Physical Activity Intervention during Music Lessons
Authors: Kopačin Barbara , Ovčjak Petra , Volmut Tadeja
Published: November 2024

There are many previously published studies that examine the integration of children’s physical activity into various school subjects. However, studies that integrate children’s physical activity into music lessons are very rare. Therefore, we decided to use an accelerometer to measure the amount and intensity of individual physical activity phenotypes of first graders during a music-only lesson, with and without a physical activity intervention. One hundred and eight children, aged six to seven, from two Slovenian elementary schools in the coastal region wore the accelerometer during two music lessons. We compared the physical activity phenotypes during music lessons with and without an intervention. On average, children were more physically inactive during music lessons without an intervention than during music lessons with an intervention (p = 0.001, d = 2.8) and spent a higher proportion of time doing moderate (p = 0.001, d = 5.9) and vigorous (p = 0.001, d = 30) physical activity during music lessons with an intervention than during regular music lessons. During regular music lessons, children spent 39 % more time being physically inactive than during music lessons with a physical activity intervention programme. We recommend that future studies include a larger sample of children and that they wear the accelerometers for at least five consecutive days.
Interplay of Personality, Self-Efficacy and Willingness to Communicate
Authors: Šafranj Jelisaveta , Bogdanović Vesna , Gak Dragana
Published: November 2024

This research examines how Willingness to Communicate (WTC) in learning English is conditioned by personality traits and linguistic self-efficacy. The sample consists of 216 students at the University of Novi Sad. Three instruments were used: the Big Five Plus Two questionnaire, the Willingness to Communicate Questionnaire, and the Questionnaire of English Self-Efficacy. Students showed self-efficacy at a slightly above-average level and were willing to speak at a slightly higher than moderate level. Self-efficacy and WTC are in positive correlation. Extraversion and Positive valence contribute significantly to WTC. Positive valence and Openness to experience are significant traits in relation to self-efficacy. Females have higher Extraversion,Conscientiousness and Openness to experience, whereas males have higher Negative valence. Gender has no direct effect on WTC and self-efficacy, but moderates the relationship with Conscientiousness, Openness to experience, Extraversion, and Negative valence. Females have higher Extraversion, Conscientiousness and Openness to experience, while males have higher Negative valence. In addition, some pedagogical implications are proposed.
Sekundarna analiza podatkov in masovni podatki v pedagoškem raziskovanju
Authors: Štemberger Tina
Published: November 2024

Prispevek se usmerja v dva koncepta, ki se tudi na področju raziskovanja vzgoje in izobraževanja vse pogosteje pojavljata v strokovnih razpravah, nista pa bila znotraj tega področja pri nas še deležna dovoljšne pozornosti, zato sta manj poznana in razširjena ter skromno implementirana. V prvem delu prispevka se usmerjamo v sekundarno analizo podatkov, pri čemer najprej opredelimo sam koncept sekundarne analize podatkov, nato pa analiziramo potencial in zadržke pri rabi tovrstnih podatkov. V nadaljevanju predstavimo pojem masovni podatki, ki z vse večjo digitalizacijo, tudi v šolskem prostoru, postajajo vse pomembnejši vir podatkov, ki predstavlja pomembno osnovo za načrtovanje sprememb za višjo kakovost izobraževanja. Hkrati predstavimo tudi pomembne slabosti rabe masovnih podatkov, med katerimi se zlasti usmerimo v problem varnosti podatkov na spletu ter pomanjkanja kompetentnih strokovnjakov za analizo tovrstnih podatkov. Oba koncepta skušamo tudi smiselno umestiti v polje pedagoškega raziskovanja.
Preschool Teachers’ Job Satisfaction
Authors: Jurčević Lozančić Anka , Tot Daria , Kudek Mirošević Jasna
Published: November 2024

The key role of preschool teachers relates to using their professional and personal competencies in daily practice. Depending on the teachers’ assessment, their job satisfaction reflects either a positive or a negative response to specific aspects of teaching. This research aims to provide insight into preschool teachers’ perception of their job role and job satisfaction. A total of 536 teachers participated in the survey and answered two open-ended questions in which they were asked to list three of the most and least satisfying experiences at work. The results obtained by the method of qualitative analysis have shown that preschool teachers see the main sources of job satisfaction in their direct work with children, in the success and progress of children, and in their relations with fellow teachers, expert staff and parents. The biggest sources of dissatisfaction include inadequate working conditions, low status in society, and the attitude of society toward the teaching profession. The results obtained contribute to the professional development of preschool teachers with the aim of improving their work quality and personal development.
Moral (Dis)engagement among Higher Education Student-Bystanders in Cyberbullying
Authors: Pirc Tina , Pečjak Sonja
Published: November 2024

In our study, we aimed to determine how different demographic variables (gender, age, free time spent online) and mechanisms of moral (dis)engagement (justification, disregarding or misrepresenting injurious consequences, diffusion of responsibility, dehumanization) predict perceptions of cyberbullying among student bystanders, according to the Bystander Intervention Model. The model proposes that a bystander must take five steps in order to intervene: notice the event, interpret the event as an emergency requiring help, accept responsibility for intervening, know how to intervene or provide help, and implement decisions to intervene (Latané and Darley, 1970). Our sample included 205 student-bystanders in cyberbullying. The most variance (27 %) was explained in the second step – to interpret the event as an emergency and help. Older students and students with less pronounced dehumanization were more likely to perceive cyberbullying as serious and to help. Our findings suggest a need for greater interest and intervention in the group of cyber-bystanders among this age group of students as well.
Mechanisms for the Formation of Empathic Culture of Students
Authors: Akhtyamovna Kamalova Lera , Novgorodtseva Irina Vladimirovna
Published: November 2024

The relevance of this study is caused by the insufficient methodological development of the mechanisms and methods for empathy formation in students of pedagogical and medical universities, which is an important professional competence of future teachers and doctors. The empathic culture of teachers and doctors is an integral part of personal culture, a component of professional skills that requires targeted training and development. The aim of the study is to theoretically justify and experimentally test the mechanisms of empathic culture formation in students of pedagogical and medical universities. The main research method is based on the selected diagnostics. We have proved that empathy is an important professional trait in the profession of doctors and teachers. Most students of pedagogical and medical universities showed an average level of empathic culture. The emotional and active channels of empathy are more prominent in teachers, and the cognitive channels are more prominent in physicians. The results of the study can be used in the professional training of students of pedagogical and medical universities.
Seca como fenômeno geográfico: letramento literário com os estudantes do ensino médio
Authors: Silva Maria Camila Siqueira Santos , Moura Marcelo de Oliveira , Tonini Ivaine Maria
Published: November 2024

O artigo propõe analisar como o letramento literário contribui para aprender o fenômeno da seca no ensino da Geografia. A construção do problema da pesquisa se apresentou através das dificuldades que os estudantes manifestaram concernente à compreensão das características e dos impactos relevantes para o entendimento da temática evidenciadas ao longo das aulas. Em termos metodológicos, foi desenvolvida uma pesquisa-ação com os estudantes de uma turma de 3º ano do ensino médio de uma escola pública situada no município de Afogados da Ingazeira – Pernambuco. A pesquisa-ação foi constituída por três sequências didáticas realizadas de maneira contextualizada com os estudantes. Alinhada a essa metodologia, foi proposto o uso do texto literário O Quinze, da escritora Rachel de Queiroz, como principal fonte de investigação dos conhecimentos geográficos. E fazendo uso da abordagem qualitativa, as ações planejadas, desenvolvidas e analisadas valorizaram a participação entre professora-estudantes e estudantes-estudantes, proporcionando um processo de ensino-aprendizagem mais dinamizador e contextualizado. Dito isso, acreditamos que o uso do letramento literário para o entendimento do fenômeno da seca nas aulas de Geografia demonstra ser mais uma forma de tencionar as diferentes dimensões e os danos socioambientais deflagrados pela seca meteorológica na região do Semiárido brasileiro.
Variabilidade da temperatura do ar na bacia hidrográfica do rio Paraíba do Norte, no estado da Paraíba
Authors: Nascimento Maxsuel Bezerra do , Nascimento Gabriel Victor Silva do , Medeiros José Ludemario da Silva , Santos Laércio Leal dos
Published: November 2024

Eventos extremos de tempo ou clima são anormalidades que ocorrem em escalas de tempo que podem variar de dias a milênios. Os eventos extremos de curta duração têm tido maior interesse para os cientistas na área de climatologia, devido aos modelos climáticos. O objetivo principal deste trabalho é avaliar a variabilidade da Temperatura do ar da Bacia Hidrográfica do Rio Paraíba no Estado da Paraíba (BHRPB), através da análise espaço-temporal mensal e anual da sua Temperatura mínima do ar (TMín), Temperatura máxima do ar (TMáx) e Temperatura média do ar (TMéd), identificando-se assim suas oscilações que impactam no período seco ou chuvoso. Os dados meteorológicos utilizados nesse estudo foram disponibilizados por um projeto conjunto entre a Universidade do Texas (EUA) e Universidade Federal do Espírito Santo (Brasil). A análise temporal anual da TMín, TMáx e TMéd demostrou similaridades entre todas três, constatou-se m aumento em todas as variáveis com destaque para a TMáx, atingindo picos de 36°C. Os resultados ajudam a compreender como a Temperatura do ar se comporta no decorrer dos anos, projetando-se assim cenários futuros, ajudando no planejamento ambiental de cada município, em políticas ambientais e climáticas.
Pharmacokinetics and metabolism of ketoconazole after single ocular instillation in Sprague-Dawley rats
Authors: Pu Jiang , He Jingsong , Xue Ru , Gao Ruiqi , Yu Yaoming , Feng Wanyong
Published: November 2024

Background and purpose: Ketoconazole is limited to its conditioned oral use due to hepatic toxicity. Its ocular eye drop administration may be an option for mycotic keratitis treatment. Therefore, it is necessary to explore its pharmacokinetic and metabolic profile via topical ocular administration. Experimental approach: Nine rats were dosed at 300 µg/rat via topical ocular administration, and sacrificed at 5, 30, and 120 min with 3 rats/timepoint. Plasma, cornea, retina, and vitreous humour samples were collected, processed, and analysed. Key results: Ketoconazole was quantified with a mean peak plasma concentration of 445 ng/mL at 5 min post-dose. In the rat ocular tissue, the mean ketoconazole concentration at 5 min post-dose was 423 μg/g in the cornea, 4.96 μg/g in the retina, and 1.19 μg/g in the vitreous humour, respectively. The mean ketoconazole concentration in each matrix decreased from 5 to 120 min. The mean ketoconazole concentration at 120 min was 38.4 ng/mL in plasma, and 8.36, 0.0944, and 0.116 μg/g in the cornea, retina, and vitreous humour, respectively. Pooled plasma, cornea, retina, and vitreous humour homogenates were used for metabolite identification. Nine metabolites were identified in rat plasma, and O-dealkylated metabolite (M3) and dehydrogenated metabolite (M11) were the top two, accounting for 5.0 and 5.8 % of the relative mass abundance. The metabolic pathways were O-dealkylation, mono-oxygenation, and dehydrogenation. Eleven metabolites were identified in the rat cornea, and two metabolites were identified in the rat retina and vitreous humour, respectively. The O-dealkylated and hydrogenated metabolite (M2) was a dominant metabolite in the cornea, retina, and vitreous humour, while M3 and M11 were the dominant metabolites in plasma. Conclusion: Ketoconazole was a dominant component (≥ 98.5 %) in the cornea, retina, and vitreous humour, having higher concentrations in cornea than in plasma. M2 was identified as a dominant metabolite (1.1 - 1.2 %) in the cornea, retina, while M3 (5.0 %) and M11 (5.8 %) were identified as dominant metabolites in the plasma.
Combined approach of nanoemulgel and microneedle pre-treatment as a topical anticellulite therapy
Authors: Hameed Hiba Imad , Al-Mayahy Mohammed Hussain
Published: November 2024

Background and purpose: Cellulite is caused by changes in the metabolism of the fatty tissue beneath the skin. Methylxanthines and retinoids are commonly added to the different anticellulite products. However, their topical permeation into the dermis is limited. Thus, the objective of this research is to formulate a nanoemulgel (NEG) containing a triple therapy of caffeine, aminophylline, and tretinoin as a topical anticellulite product to improve their skin permeation. Furthermore, the influence of microneedles (MNs) as skin pre-treatment on the permeation of the NEG was investigated. Experimental approach: Various nanoemulsion (NE) formulations were prepared using high-energy ultrasonication with different compositions and sonication amplitudes. Several characterisation tests were employed to select the optimum NE formulation. Then, the optimised NE formulation was incorporated with hyaluronic acid to prepare the NEG, which was, in turn, subjected to various evaluations. An ex vivo permeation study using human skin was performed for the NEG compared to a control preparation of plain gel. Additionally, a microneedling pen was applied as a skin pre-treatment at varying lengths prior to NEG application to examine its impact on the NEG’s permeation. Key results: The selected NEG has a homogenous and consistent texture with no coarse particles, a droplet size of 175.8 nm and polydispersity index (PDI) of 0.19, an optimum pH value of 5.28, high drug content of caffeine, aminophylline, and tretinoin (99.35, 98.48 and 98.05 %, respectively), high drug release values of approximately 100 % within 6 hours, appro-priate viscosity, minimum skin irritation, and adequate short-term stability. The ex vivo permeation study showed that caffeine, aminophylline, and tretinoin permeated more and deposited in the skin with higher percentages from the NEG than plain gel. This skin deposition within the dermis was increased by applying the microneedling pen at varying lengths of 0.5, 1, and 2 mm as a skin pre-treatment. Conclusion: This combined approach of NEG formulation containing a triple therapy of caffeine, aminophylline, and tretinoin, along with MNs application, has the potential to serve as a topical anticellulite product, reducing cellulite formation and improving skin appearance.
Incorporación de Herramientas Digitales para Fortalecer el Aprendizaje en Áreas Interdisciplinarias
Authors: Pin-Alvarado Marliz Janice , Ortega-Lema Wilson Israel , Hidalgo-Salazar Mariuxi Celestina
Published: November 2024

La integración de las TIC en la educación escolar mejora la enseñanza y aprendizaje, pero enfrenta barreras como el acceso desigual a la tecnología, la falta de formación docente específica y la necesidad de adaptar estas herramientas a los diversos estilos de aprendizaje. A pesar de los avances impulsados por la pandemia de COVID-19, muchos docentes carecen de capacitación para utilizar eficazmente las TIC en el aula. Este estudio tiene como objetivo proponer estrategias para incorporar herramientas digitales en el aprendizaje interdisciplinario, mejorando la calidad educativa y el desarrollo de habilidades clave en los estudiantes. La investigación utilizó un enfoque mixto, combinando métodos cuantitativos y cualitativos. Se aplicaron análisis estadísticos descriptivos e inferenciales para examinar la relación entre los recursos digitales y el aprendizaje interdisciplinario. Se realizó una revisión de literatura en bases académicas como Scopus y Google Scholar. Se administró una encuesta estructurada a 30 estudiantes y entrevistas semiestructuradas a 3 docentes para explorar la percepción sobre el uso de TIC en la educación. Se empleó el software Jamovi para el análisis de datos, permitiendo generar resultados intuitivos y accesibles. Los resultados muestran que tanto estudiantes como docentes reconocen las ventajas de los recursos digitales, pero también enfrentan barreras como dificultades técnicas y resistencia al cambio. Las estrategias propuestas incluyen mejorar la infraestructura tecnológica y ofrecer capacitación continua. En conclusión, la integración de herramientas digitales en el aprendizaje interdisciplinario mejora la calidad educativa, contribuyendo al desarrollo de habilidades clave en los estudiantes.
KLASIFIKASI CITRA DIGITAL TULISAN TANGAN ANGKA MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK
Authors: Antonius Angga Kurniawan  , Rama Dian Syah  , Rizki Ariyani
Published: November 2024

Rapid technological advances have led to the development of computer vision science in various fields. This research aims to detect handwriting using deep learning technology with the Convolutional Neural Network (CNN) method. The research stages are data sample selection, data preprocessing, data training, data testing, and evaluation of results. This research succeeded in detecting handwriting with an accuracy value of 0.9800 and a loss value of 0.0665. There are several classification errors because images with numbers are less clear and almost look like numbers that they should not be. The more training data, the more the network will learn so that the accuracy will be better.
APLIKASI ENKRIPSI CITRA DIGITAL BERBASIS CHAOS MENGGUNAKAN ALGORITMA ARNOLD’S CAT MAP
Authors: Rama Dian Syah  , Antonius Angga Kurniawan  , Rizki Ariyani
Published: November 2024

The rapid development of technology can lead to vulnerabilities in data and information. Everyone can access that data and information and disseminate it easily through the internet. The data and information can be in the form of text, video, audio, and images that may be confidential. To prevent misuse and unauthorized access to this confidential data and information, a technique is needed to enhance the security of the data. One of these techniques is by encrypting data. This technique is used to encode data in such a way that the security of the information is maintained and it cannot be read without being decrypted first. The encryption technique that has been developed involves implementing chaos theory, one of which uses the Arnold’s Cat Map algorithm. This algorithm is applied in the process of encrypting and decrypting digital images with png and bmp extensions. The results of this trial show that the image files can be encrypted and decrypted properly. The time obtained is directly proportional to the size of the image.
Safeguarding Finances: State-of-the-Art Fraud Detection Methods for Credit Cards
Authors: Kant Vishnu , Gill Kanwarpartap Singh , Kumar Mukesh , Rawat Ruchira
Published: November 2024

This research primarily aims to shed light on the serious issue of credit card fraud, which has become much worse with the advent of internet shopping and, more specifically, the present COVID-19 epidemic. Developing a machine learning system capable of distinguishing between legitimate and fraudulent credit card transactions is the primary objective of this project, which aims to decrease an annual loss of $24 billion. Using data such as transformed numerical characteristics after PCA analyses, transaction time and amount, and Logistic Regression, Decision Tree Classifier, and K-Nearest Neighbours approaches are employed in the research study. The accuracy rates of these algorithms are demonstrated by the cross-validation score, ROC AUC score, and F1 score within the context of fraud detection. Improving the models' accuracy and resilience is as simple as using statistical tests like ANOVA when selecting features. To improve the detection of fraudulent behaviour and to accurately compare the results of various algorithms, balanced datasets are essential, as this shows. There was a 91% F1 score, 92.35% ROC AUC, and 98.01% cross-validation accuracy rate for fraud detection in the logistic regression model. Alternatively, a decision tree classifier's fraud detection cross-validation score was 96.67%, ROC AUC was 91.36%, and F1 was 90%. When it came to detecting fraud, K-Nearest Neighbours performed exceptionally well with scores of 97.63% for ROC AUC, 99.34% for cross-validation, and 97% for F1.
Deep Learning for Sign Language Recognition: Exploring VGG16 and ResNet50 Capabilities
Authors: Sharma Jatin , Gill Kanwarpartap Singh , Kumar Mukesh , Rawat Ruchira
Published: November 2024

For the deaf and hard of hearing to communicate with one another, sign language recognition (SLR) is an absolute must. The use of two popular deep learning models—VGG16 and ResNet50—for SLR-related tasks is examined in this study. We achieved remarkable success rates of 99.92% and 99.95% in sign language gesture recognition using the VGG16 and ResNet50 architectures, respectively. We found that these models worked well at accurately reading hand and gesture motions, which made it much easier for people to communicate with one another using sign language. With the use of cutting-edge deep learning methods, our study is making strides towards better SLR systems, which might lead to more accessible and inclusive communication.
Innovating Water Purity Analysis with Gradient Boosting Classification Techniques
Authors: Sharma Jatin , Gill Kanwarpartap Singh , Kumar Mukesh
Published: November 2024

Ensuring water quality is crucial for protecting both human health and aquatic ecosystems. In this research, we delve into the effectiveness of gradient boosting classifiers for predicting water quality parameters. Our study evaluates the potential of this approach in assessing groundwater quality, comparing it against three other gradient boosting-based algorithms, and contrasts its performance with traditional machine learning methods. We also analyze feature importance to identify the key factors influencing water quality. The findings reveal an accuracy rate of approximately 78%. Moreover, the identified significant features provide valuable insights into the factors driving water quality changes. This research advances predictive modeling techniques in water quality assessment, aiding in proactive management strategies for sustainable water resource use and ecosystem conservation. These models hold significant implications for informed decision-making in agricultural water management and resource allocation within the region. As the population grows and the demand for resources increases, managing our lives becomes more challenging. In this struggle, we sometimes resort to using poor or contaminated water sources, endangering our health. According to a recent World Health Organization (WHO) survey, over 2.2 billion people in India suffer from issues related to unsafe drinking water, and 21% of diseases are linked to impure water.
Image Synthesis using Generative Adversarial Networks
Authors: Ahuja Kritika , Goyal Ekta , Satsangi Shikha , Patvardhan C.
Published: November 2024

In the past few years, significant progress has been made in artificial intelligence transforming many industries. Recently, the emergence and rapid adoption of advanced large language models like OpenAI's GPT, Google's PaLM, and Meta's Llama have shown great potential and sparked considerable global interest. However, there is a critical knowledge gap in the construction sector when it comes to the opportunities and challenges of implementing Generative AI, specifically in image-to-image generation tasks using Generative Adversarial Networks (GANs). By processing massive datasets of pictures, GAN models learn the essence of visual elements like color, shape, and color composition in the image. Within the world of artistic exploration, the generation of visual content opens the limitless potential for creativity. It also has the potential to generate an image in the style of Van Gogh or in the style of Raja Ravi Varma. Among these, CycleGAN has emerged as a powerful model for image-to-image translation tasks without requiring paired data. The following study explores the application of CycleGAN for preserving the content of input images while experimenting with various hyperparameters to enhance the model’s performance. The objective is to assess the efficacy of CycleGAN in maintaining the integrity of the original content and compare its results against established tools such as NightCafe, Neural Style Transfer and Deep Dream Generator. The results of the following study indicate the that with careful tuning of hyperparameters, CycleGAN can achieve superior content preservation while generating visually appealing transformations. Furthermore, the comparative analysis reveals the strengths and limitations of each tool, highlighting CycleGAN’s potential as a robust alternative for image transformation tasks.
Dynamic Transportation Problem
Authors: Singh Rahul Raj , Thakur Kartikesh , Kasaudhan Saurabh , Singh Gurwinder
Published: November 2024

Rising urbanisation and population expansion present difficulties for urban transportation networks. All of these constraints worsen traffic-related problems: unforeseen congestion, poor route planning, and underuse of resources. Dynamic Transportation Optimisation (DTO) technologies have consequently become intriguing means to increase the sustainability and efficiency of metropolitan transportation networks. Dynamic programming (DP), Simulated Annealing (SA), Ant Colony Optimisation (ACO), Swarm Intelligence (SI), Genetic Algorithms (GA), Reinforcement Learning (RL), Machine Learning Models (ML), Geographic Information Systems (GIS), and Integer Linear Programming (ILP) are just a few of the wide range of approaches DTO methods apply. These technologies generate complete traffic analysis and dynamic routing solutions by using real-time data from security cameras, traffic sensors, and GPS devices. This paper gives a complete evaluation of DTO approaches coupled with assessments of their usefulness, performance, and constraints in the framework of urban transportation. By way of a detailed comparison analysis, the study intends to highlight the advantages and disadvantages of every method, so supporting stakeholders in choosing and deploying DTO solutions customised to unique urban transport concerns. Furthermore highlighted in light of developments in artificial intelligence, big data analytics, and predictive modelling is the future prospects of DTO techniques. The integration of these technologies within present urban contexts aims to develop resilient transportation networks, thereby contributing to the continuing discourse on the evolution of urban mobility solutions. The subsequent sections of this article delve into the intricacy of each DTO technique, offering insights into their capabilities, actual implementations, and projected repercussions on urban transportation networks. By combining empirical evidence with theoretical frameworks, the research presents a holistic understanding of the role and significance of DTO techniques in defining the future of urban mobility.
Unlocking Dev Nagri: OCR with CNN
Authors: Maheshwari Saket , Sinha Sayantan , Upadhyayv Sachin
Published: November 2024

In recent years, the field of machine learning has experienced significant advancements, and researchers have conducted extensive studies in various areas. One of the most exciting areas of research is image recognition, which has led to numerous breakthroughs in the field. Our research is focused on the development of a model that can recognize Devanagari characters with remarkable accuracy. Devanagari characters contain a unique set of characters with a rich history, and we chose it specifically for our research because of its importance. To achieve our goal, we utilized a convolutional neural network, a type of deep learning algorithm that is highly effective in image recognition. We trained our model using a vast dataset of Devanagari characters, which enabled it to recognize new characters with significant precision. Our research proposes an optical character recognition technique using a convolutional neural network, which has the potential to revolutionize the field of image recognition. This technique can be applied to other scripts and languages, making it an essential tool for various industries. With the development of our model, we believe we have contributed to the growing body of knowledge in machine learning and image recognition.
Transformative AI in Radiology: Convolutional Neural Networks for Pneumonia Diagnosis
Authors: Kant Vishnu , Gill Kanwarpartap Singh , Kumar Mukesh , Rawat Ruchira
Published: November 2024

Pneumonia, a severe bacterial infection primarily caused by Streptococcus pneumonia, can impact one or both lungs and poses a significant health threat to individuals worldwide. According to the World Health Organization (WHO), pneumonia is responsible for one-third of all deaths in India. Traditionally, chest X-rays are used to diagnose pneumonia, necessitating interpretation by skilled radiologists. Implementing an automated diagnostic system could significantly enhance early detection and treatment, particularly in remote areas. Convolutional Neural Networks (CNNs) have gained considerable attention for their ability to analyze medical images due to their deep learning capabilities. These CNN-based approaches offer notable advantages over traditional methods, including improved accuracy, scalability, and potential for automation. We propose leveraging deep learning techniques to uncover complex patterns in medical imaging data that are indicative of pneumonia, thereby improving diagnostic precision. Furthermore, pre-trained CNN models, which have been trained on large datasets, provide valuable features for image classification tasks. In this study, we evaluate the effectiveness of these models in differentiating between abnormal and normal chest X-rays by using them as feature extractors in conjunction with various classifiers. The research also includes a thorough analysis to identify the most effective CNN model for this diagnostic task
Mathematical Approaches to Securing Kubernetes: Analyzing Log Data Volume in a Complex Landscape
Authors: Karmakar Gobinda , Arri Harwant Singh
Published: November 2024

Kubernetes, the de facto standard for container orchestration, has revolutionized the deployment and management of applications at scale. However, the increasing complexity of Kubernetes environments has led to an exponential growth in the volume of logs generated by various components, including Kubernetes itself, containerized applications, and the underlying infrastructure. This paper presents a comprehensive exploration of the challenges associated with log management in complex Kubernetes environments. We introduce a mathematical model to quantify the volume of logs, represented as nV, where n is the number of components and V is the volume of logs per unit time. Effective log management, crucial for maintaining the security and operational integrity of Kubernetes clusters, becomes increasingly challenging as n increases. This paper proposes innovative strategies for navigating this deluge of logs, ensuring a secure and resilient Kubernetes deployment. Our findings provide valuable insights for organizations striving to maintain robust Kubernetes environments amidst escalating complexity.
Automate Code Refactoring for Enhanced Software Maintenance and Development
Authors: Ainapure Atman , Kharote Aditya , Agrawal Tarun , Dhage Sudhir
Published: November 2024

This paper unfolds a practical solution tailored to the intricate challenges faced by multinational corporations (MNCs) in the landscape of software development. The core emphasis of our research is on addressing the multifaceted aspects of maintaining code consistency, longevity, and achieving bug-free functionality. The crux of our proposed solution lies in the development of a sophisticated VS Code Extension built using TypeScript powered by LangChain and Flask that not only guides developers through the intricate process of code refactoring but also streamlines the often laborious task of generating comprehensive comments. This dual-pronged approach seeks to not only enhance the intrinsic quality of the codebase but also contribute significantly to the overall documentation and comprehensibility of the software.
Uso de los simuladores y modelos computacionales en el aprendizaje de la ingeniería
Authors: Roca García Jorge Luis , Olaya Gil Diana Gabriela , Guartatanga Faicán Moisés Danilo
Published: November 2024

La ingeniería como ciencia demanda un elevado nivel de aprendizaje por parte del estudiante, tanto desde una perspectiva teórica como práctica, de forma tal que les permita desarrollar habilidades analíticas y operativas en su futuro desempeño como ingeniero. El objetivo planteado se sustenta en indagar cómo el empleo de simuladores y modelos computacionales se articulan con el proceso de enseñanza-aprendizaje en la educación en ingeniería, dicho objetivo unido a la metodología empleada, permite plantear como principales resultados que la integración de simuladores y modelos computacionales le ha permitido a los estudiantes de ingeniería apropiarse de manera más rigurosa y dedicada a los conocimientos teóricos y prácticos complejos como la dinámica de sistemas, la mecánica de fluidos y la simulación de procesos industriales. El uso de herramientas de simulación permiten tambien, el desarrollo de  prácticas virtuales, mediante las cuales los estudiantes se apropian de habilidades técnicas antes de incorporarse a la realidad que enmarca a los laboratorios físicos, lo que resulta importante en escenarios donde la disponibilidad de equipos y recursos es restringida, optimizando el uso de la infraestructura y mejorando la preparación práctica de los futuros ingenieros. La enseñanza de la ingeniería que incorpora simuladores y modelos computacionales muestra mejor alineación con las demandas del mundo empresarial. Finalmente se plantea que el empleo de simuladores y modelos computacionales en la enseñanza de la ingeniería en Ecuador ha manifiesto trascendentales beneficios en la formación de los estudiantes, pero a la vez ha revelado  desafíos y áreas de mejora para el futuro.