bluuebunny/crossref_metadata_2025 huggingface dataset:
Pengaruh Pembelajaran Daring terhadap Minat Belajar Siswa yang Beragama Buddha pada Masa Covid-19 di Sekolah Dasar Maitreyawira Kelas VI Tahun 2020/2021
Authors: Diana Diana , Lamirin Lamirin , Siu Ong Cin
Published: December 2024

Penelitian ini bertujuan untuk mendeskripsikan kendala-kendala yang dialami oleh guru dan siswa dalam pelaksanaan pembelajaran secara daring dan solusi mengatasi kendala-kendala yang dialami tersebut selama masa pandemi COVID-19. Munculnya problematika pembelajaran daring terjadi karena peralihan proses pembelajaran yang mulanya dilaksanakan secara tatap muka menjadi online, ini merupakan sebuah adaptasi baru yang mau tidak mau harus dilaksanakan oleh semua orang yang terlibat dalam proses pendidikan. Proses pembelajaran daring secara mendadak mengharuskan semua guru, siswa, bahkan orang tua untuk beralih menggunakan teknologi dan memanfaatkan jaringan internet. Dalam pelaksanaannya pasti banyak kendala dan harus dicari solusinya. Penelitian ini dilakukan di Sekolah Maitreyawira, Deli Serdang pada Tahun Ajaran 2020/2021. Dengan jenis penelitian kuantitatif deskriptif dengan menggunakan angket atau kuisioner tertutup yang dijawab oleh 30 siswa SD Kelas VI. Teknik analisis data menggunakan bantuan aplikasi SPSS 24. Hasil penelitian menunjukkan bahwa terdapat beberapa faktor yang memengaruhi pembelajaran daring terhadap minat belajar siswa yaitu guru, orang tua, media pembelajaran yang digunakan dan fasilitas yang baik.    Kesimpulan yang didapat dari penelitian ini bahwa pembelajaran daring berpengaruh positif terhadap peningkatan minat belajar siswa secara signifikan. Pengaruh tersebut disebabkan kepiawaian guru SD Maitreyawira dalam merencanakan, mempersiapkan, menyampaikan materi pembelajaran dengan menggunakan media pembelajaran yang menarik dan tidak membosankan. Faktor pendukung lainnya adalah partisipasi aktif dari orang tua yang mendukung proses pembelajaran dan mendampingi siswa belajar di rumah.
Pengaruh Pola Asuh Orang Tua Terhadap Perilaku Belajar Peserta Didik TK A yang Beragama Buddha di TK Maitreyawira Deli Serdang Tahun Pelajaran 2020/2021
Authors: Jumiati Jumiati , Dewi Citra , Darsono Darsono
Published: December 2024

Perkembangan zaman membuat orang tua zaman sekarang semakin efisien dalam mengasuh anak sehingga anak yang seharusnya tumbuh sesuai tahap perkembangan usianya menjadi masalah pada perilaku belajar anak di sekolah. Pembelajaran etika adalah pembelajaran yang memasukkan pendidikan karakter untuk membentuk karakter anak sejak dini sesuai dengan aspek yang ada dalam tahap perkembangan anak. Untuk itu, usaha yang harus dilakukan untuk mendidik anak agar berbakti kepada orangtua yaitu mendidik anak dengan pola asuh yang tepat sehingga anak dapat memiliki perilaku belajar sesuai dengan capaian perkembangan di sekolah yaitu dari aspek nilai agama dan moral, aspek fisik motori, aspek kognitif, aspek bahasa, aspek social emosional, dan aspek seni. Penelitian kuantitatif ini menggunakan jenis penelitian korelasi. Subjek penelitian ialah Anak TK A di TK Maitreyawira Deli Serdang Tahun Pelajaran 2020/2021 yang terdiri dari 43 siswa. Instrumen yang digunakan adalah angket dengan skala likert. Data dianalisis dengan menggunakan pendekatan analisis regresi linier sederhana. Berdasarkan hasil analisis data yang telah dilakukan maka disimpulkan ada pengaruh signifikan Pola asuh orang tua terhadap perilaku belajar anak TK A  di TK Maitreyawira Deli Serdang. Besarnya pengaruh tersebut adalah 62.2%. Sedangkan 38,8% Perilaku belajar dipengaruhi oleh faktor lain.
Pengaruh Metode Pembiasaan Terhadap Kemandirian Anak Di TK B Sekolah Maitreyawira Deli Serdang Tahun Pelajaran 2020/2021
Authors: Liuriana Reni , Lamirin Lamirin , Darsono Darsono
Published: December 2024

Pendidikan karakter bukan mengajarkan mana yang benar dan salah, lebih dari itu pendidikan karakter menanamkan kebiasaan tentang hal yang baik sehingga peserta didik menjadi paham (kognitif) tentang mana yang benar dan salah, mampu merasakan (afektif) nilai yang baik dan biasa melakukannya (psikomotor). Pendidikan karakter merupakan pendidikan yang penting dan bisa diterapkan melalui beberapa metode, salah satunya yaitu metode pembiasaan Untuk menjadi pribadi yangmandiri, anak harus diberi latihan terus menerus dan dilakukan sejak dini. Danlatihan yang diberikan harus dikerjakan oleh anak itu sendiri tanpa dibantuorangtua. Kemandirian memberi dampak yang baik bagi perkembangan anak,maka sebaiknya kemandirian dilatih sejak usia dini, dan kemandirian anakdisesuaikan dengan kemampuan anak. Anak yang kurang mandiri biasanyaselalu meminta bantuan dari orantua, guru maupun teman. Hal tersebutmerusak kemampuan dan kepercayaan diri dalam mencapai segalakebutuhanya. Penelitian kuantitatif ini menggunakan jenis penelitian lapangan. Subjek penelitian ialah Anak di TK B Sekolah Maitreyawira Deli Serdang Tahun Pelajaran 2020/2021yang terdiri dari 48 siswa. Instrumen yang digunakan adalah angket dengan skala likert. Data dianalisis dengan menggunakan pendekatan analisis regresi linier sederhana. Berdasarkan hasil analisis data yang telah dilakukan maka disimpulkan ada pengaruh signifikan Metode Pembiasaan terhadap Kemandirian Anak di TK B Sekolah Maitreyawira Deli Serdang. Besarnya pengaruh tersebut adalah 84.2%. Sedangkan 15,8% Kemandirian Anak oleh faktor lain.
The Opening of Albanian Schools in Albanian Territories in 1908-1909
Authors: Mehmeti Nevila
Published: December 2024

Purpose: This paper aims to highlight the efforts of Albanian patriots to open schools in the Albanian language throughout the Albanian territory in the years 1908-1909. The objective of the study is to argue, through facts and evidence from archival sources, monographs, and contemporary press, that despite difficulties and obstacles, Albanians managed to open a significant number of Albanian schools from the north to the south. Method: The methodology used for this paper is an analysis of archival sources, publications by Albanian and foreign authors, as well as publications from the contemporary press, focusing specifically on the issues of opening schools across the Albanian territory. By defining research questions and utilizing document analysis, the aim is to reach accurate conclusions. Results: In the years 1908-1909, the spread of Albanian schools was one of the most important events for the development of the Albanian national identity. This period marked the beginning of a movement for the education of Albanians, which was essential for preserving the Albanian language and culture. This study shows that the period of 1908-1909 was a significant step in establishing an Albanian educational infrastructure, which would have a profound impact on the further development of Albanian culture and society. Conclusions: The spread of Albanian schools demonstrates the widespread commitment of Albanians to support education, viewing it as an instrument for social and political development. Despite the achievements, Albanian schools faced numerous challenges, including economic and political obstacles that required sustainable solutions.
 
 
Received: 2 August 2024 / Accepted: 10 November 2024 / Published: 3 December 2024
The Impact of the “Regulations on the Governance of Online Violence Information” on User Behavior in Chinese Social Media Platforms
Authors: Zhang Ruiqing
Published: December 2024

The rise of social media platforms in China, such as Weibo, Douyin, and WeChat, has transformed communication but also led to the proliferation of online violence, including cyberbullying, harassment, and doxxing. These harmful behaviors have serious psychological impacts on victims and disrupt the digital ecosystem by creating toxic environments. In response, the Chinese government implemented the “Regulations on the Governance of Online Violence Information” in 2024. This study examines the effectiveness of these regulations in shaping user behavior and promoting safer online interactions. The regulations impose responsibilities on social media platforms to implement content monitoring, provide reporting mechanisms, and cooperate with law enforcement. Through case studies and user analysis, this paper explores the regulations’ impact on reducing harmful behaviors, fostering self-regulation, and addressing challenges such as technical difficulties in moderation and concerns over freedom of expression. The findings highlight the regulations’ role in improving digital governance and contributing to a healthier online ecosystem.
The Role of Vocational Education in Addressing Labor Shortages in Aging China
Authors: Wu Qianyan
Published: December 2024

China’s rapidly aging population presents significant challenges to its labor market, with acute shortages threatening economic growth and industrial productivity. This paper explores the critical role of vocational education as a strategic solution to address these labor shortages. By equipping workers with industry-relevant skills, vocational education enhances workforce competitiveness, supports the reskilling of older workers, and reduces regional disparities in economic opportunities. The paper delves into the challenges facing vocational education, including societal perceptions, curriculum modernization, and regional access inequalities, while highlighting opportunities for systemic reform and collaboration with industry stakeholders. It argues that vocational education is not merely a response to immediate labor shortages but a cornerstone for China’s long-term economic transformation and sustainability. By embracing vocational education as a forward-looking strategy, China can mitigate the impacts of demographic shifts and build a resilient, inclusive, and future-ready economy.
Preventive and Responsive Intervention Strategies of Teachers in School Bullying
Authors: Seong Doyoung
Published: December 2024

School bullying is a persistent issue that negatively impacts students’ psychological well-being, academic performance, and social development. In South Korea, where societal hierarchies and academic pressures are prevalent, addressing bullying requires a comprehensive approach involving both preventive and responsive strategies. This paper examines the pivotal role of teachers in combating school bullying, focusing on their preventive and intervention tactics. Preventive strategies emphasize fostering a positive school climate, enhancing teacher-student relationships, and promoting empathy among students. Responsive strategies, meanwhile, involve immediate and effective intervention through restorative practices, behavioral counseling, and emotional support for victims. Additionally, the paper highlights the critical influence of school climate and leadership in shaping the efficacy of anti-bullying measures. Strong leadership provides the necessary framework for consistent policy enforcement and resource allocation, empowering teachers to act confidently. This study underscores the importance of integrating prevention, intervention, and leadership to create a safer and more supportive educational environment. By analyzing current practices and offering evidence-based recommendations, this research aims to guide schools in reducing bullying and fostering a nurturing atmosphere conducive to learning and personal growth.
The Effectiveness of China’s Anti-Food Waste Campaign on University Canteens
Authors: Chen Weihao
Published: December 2024

Food waste in university canteens is a significant issue in China, contributing to environmental degradation and financial inefficiencies. In response, the Chinese government and universities have implemented comprehensive anti-food waste campaigns aimed at reducing waste volumes and promoting sustainable consumption practices. This paper examines the effectiveness of these measures, focusing on their impact on student behavior, operational efficiencies, and broader environmental benefits. Key initiatives include the introduction of portion control options, educational programs, and advanced waste monitoring technologies. Through case studies and comparative data analysis, the study highlights significant reductions in food waste, cost savings, and improved environmental outcomes. The findings underscore the importance of combining technological innovation with behavioral change to achieve long-term sustainability in campus dining.
Pengabdian Kepada Masyarakat di Desa Wisata Penghasil Strawberi Lebakmuncang, Kabupaten Ciwidey, Propinsi Bandung
Authors: Satiawati Listiana , Abdillah Ridho
Published: December 2024

Kegiatan Pengabdian kepada Masyarakat (PKM) ini adalah merupakan kegiatan PKM kolaborasi yang diadakan oleh Universitas Persada Indonesia (YAI) pada tanggal 6-7 September 2024 dengan judul PKM Kolaborasi IV Pengabdian Masyarakat untuk UMKM, Pokdarwis, Petani, Kader Posyandu, Guru dan Peternak di Desa Wisata Lebakmuncang Kecamatan Ciwidey Kabupaten Bandung. Kegiatan ini adalah merupakan kegiatan yang sudah terjadwal dan sudah berlangsung 4 kali. Program PKM ini melibatkan kolaborasi lintas perguruan tinggi ini diikuti oleh 137 dosen dan 9 panitia dari berbagai perguruan tinggi, baik negeri maupun swasta, yang berada di lingkungan LLDIKTI wilayah 3 dan 4, serta perwakilan dari kota-kota lain seperti Padang, Semarang, Surabaya, Banjarmasin, dan Makassar. Jumlah Perguruan Tinggi peserta dalam kegiatan adalah 47 kampus. Peserta akan dibagi menjadi beberapa kelompok. Para peserta berinteraksi langsung dengan berbagai kelompok masyarakat yang terdiri dari petani sayur-mayur, pembudidaya stroberi, peternak sapi dan lebah madu, kader posyandu, Usaha Mikro Kecil dan Menengah (UMKM), guru, pelaku bank sampah, serta pembudidaya ikan air tawar. Kegiatan ini bertujuan untuk meningkatkan keterampilan, pengetahuan, dan kesejahteraan masyarakat desa melalui berbagai program edukatif dan inovatif. Selain dari pada itu kegiatan ini juga menambah pengetahuan peserta PkM dengan cara mencari ilmu dari ketrampilan yang sudah dipunyai oleh penduduk terutama dalam bidang pertanian dan peternakan. Kegiatan ini menghasilkan berbagai luaran termasuk publikasi media massa (youtube, tiktok, instagram maupun facebook), artikel pengabdian masyarakat untuk jurnal nasional dan book chapter hasil karya para peserta. Selain itu, dokumentasi kegiatan telah disebarluaskan melalui berbagai platform media sosial, memperluas jangkauan dampak positif program ini untuk memperkenalkan desa wisata ini kepada para pelancong dari dalam dan luar negeri. Kolaborasi ini juga memperkuat hubungan antara perguruan tinggi dengan kelompok sadar wisata (Pokdarwis) dan pemerintah desa setempat. Diharapkan, kegiatan ini dapat menjadi landasan untuk mendorong keberlanjutan program pemberdayaan masyarakat di masa mendatang.
Edukasi Metode Food Diary Sebagai Upaya Pencegahan Stunting Pada Siswa TK Permata Hati Aisyiyah Kota Tasikmalaya
Authors: Astuti Yani Sri , Wardani Yusrima Syamsina , Srigustini Astri , Husnul Nisatami , Ningsih Mega Prani
Published: December 2024

Kasus stunting merupakan permasalahan yang bisa dijumpai baik pada wilayah baik kategori pedesaan, maupun perkotaan. Demikian juga di Kelurahan Kahuripan yang merupakan bagian dari wilayah Kota Tasikmalaya, menurut data Puskesmas Kahuripan tahun 2023, masih terdapat 33 kasus stunting yang membutuhkan upaya penanganan secara komprehensif. Berdasarkan permasalahan faktual inilah, mendorong perencanaan Pengabdian Pada Masyarakat dengan Skema Program Peningkatan Kesehatan Masyarakat bertema Stunting. Kegiatan Edukasi Metode Food Diary kepada Persatuan Orangtua Murid dan Guru TK Permata Hati Aisyiyah Kota Tasikmalaya bertujuan untuk memberikan pemahaman tentang pentingnya Gizi untuk tumbuh kembang anak dan unsur gizi apa saja yang harus terpenuhi agar tumbuh kembang anak bisa optimal. Kegiatan ini akan dilaksanakan dengan metode 1) Edukasi Metode Food Diary pada mitra sasaran yang melibatkan Siswa TK, orangtua, dan guru di tempat kegiatan, 2) Demo memasak menu sehat gizi seimbang bagi anak, 3) penjelasan pengisian Food Diary, 3) evaluasi bersama dari hasil pengisian Food Diary. Kegiatan pengabdian kepada masyarakat ini dilakukan di di TK Permata Hati Aisyiyah, Kelurahan Kahuripan, Kecamatan Tawang. Tahapan kegiatan dilakukan dalam beberapa tahapan, yaitu 1) tahap persiapan (sosialisasi), 2) pelaksanaan (pelatihan dan penerapan teknologi Food Diary), 3) tahap pendampingan dan evaluasi program dan 4) keberlanjutan program pengabdian kepada masyarakat. Adapun hasil yang di dapatkan dalam pengabdian kepada masyarakat ini antara lain: 1) peserta mendapatkan edukasi food diary, 2) peserta mendapatkan informasi tentang cara mengolah makanan sehat, 3) pembagian menu makanan sehat gizi seimbang bagi siswa TK Permata Hati, dan 4) evaluasi hasil food diary.
Phytochemical Analysis of Dried Hevea brasiliensis (Will. Ex Adr. De Juss.) Muell. et Arg Leaves Collected from the Ovitrap with Mosquito Larvae
Authors: Blessy P. , Marin E. Grace
Published: December 2024

In the modern culture the paddy fields are converted into rubber plantations and its plays a good breeding source for mosquitoes especially during rainy seasons. Our present investigation is to find out the phytochemical constituents present in Hevea brasiliensis dried leaves collected from the ovitrap as a preliminary study to find out the mosquito repellent activity. The obtained result suggests that the control showed the presence of terpenoid, phenol, alkaloid and tannin. Similarly methanol extract showed the presence of phenol, tannin and steroid; chloroform extract showed the presence of terpenoid, flavonoid, tannin and steroid; acetone extract showed the presence of alkaloid, tannin, steroid and aminoacid and aqueous extract showed the presence of steroid and aminoacid. Moreover, the results suggest that the dried leaf collected from the ovitrap contains various phytoconstituents which can be utilized for industrial use.
Macrophytes and Odonata of Man-made Lakes: Biodiversity Assessment in Raniganj-Asansol Belt, West Bengal, India
Authors: Mukherjee Snigdha , Sarkar Sanchari , Bhattacharya Tapajit , Mukherjee Aloke Kumar , Chakrabarty Moitreyee , Biswas Rajib
Published: December 2024

The ecological interplay between macrophytes and odonata in the pit lakes of the Raniganj-Asansol belt, West Bengal, was assessed for five (5) months. The study recorded a diverse array of 15 aquatic and 62 terrestrial macrophyte species from various families, as well as 23 Odonata species. Analysis of Variance (ANOVA), revealed significant disparities in macrophyte density and abundance among the pit lakes. Notably, one lake was devoid of macrophytes, reason not assessed, as indicated by significant density variance (f = 3.340, P = 0.020), and abundance variance (f = 4.046, P = 0.008). The findings highlight the presence of macrophyte diversity along with Odonata and suggest that reclaimed pit lakes can harbour such biodiversity. Non- inclusion of water quality assessment is the major limitation of this study.
Poultry Farms and Their Waste Disposal Techniques in Virudhunagar District, India: Issues and Challenges
Authors: Bhastina J. Jasmine , Kumar M.J. Senthil , P.Arumugapandi  , M.Ishwarya  , Sathana T.
Published: December 2024

The poultry industry in Virudhunagar district, Tamil Nadu, significantly contributes to the region’s economy and food security. However, the rapid growth of poultry farming has resulted in considerable waste management issues, leading to environmental harm, contamination of groundwater, and public health concerns. This study examines the waste disposal methods utilized by poultry farms in Virudhunagar, with a particular emphasis on sustainable approaches like composting, anaerobic digestion, and organic fertilizer production. Using a descriptive research design and a mixed-methods approach, the study surveyed 75 poultry farmers to assess their waste disposal practices, awareness levels, and challenges faced. The findings suggest that landfilling and open-area disposal continue to be the primary waste management practices, with minimal adoption of more sustainable alternatives. The study identifies several barriers to the adoption of environmentally friendly practices, including financial limitations, lack of technical knowledge, and insufficient resources. The research emphasizes the urgent need for increased awareness, financial assistance, and technical training to promote sustainable waste management in the poultry sector of Virudhunagar.
Sex Dependent Comparative Study of Hematological Parameters and Blood Cell Characteristics of Three Ornamental Teleosts
Authors: A Jothika , Vijay Anupama , R Sivalakshmi , M Madhavi , L Mohanasundari
Published: December 2024

Aquaculture is one of the rapidly increasing food production sectors in the world. Ornamental fish culture also plays a vital role. hematological parameters serve as a tool to indicate the health of the fish. The present research investigated to acquire basic information on the importance of the size of blood cells, morphology, and hematological parameters in teleost fishes of Devil cichlid (Amphilophus labiatus), Black moor (Carassius auratus), and Koi carp (Cyprinus rubrofuscus). Blood samples from the caudal vein of fish were collected. Standard protocols were used to analyze the hematological investigations such as RBC, WBC, PCV, HB, MCV, MCH, and MCHC. The morphological characteristics of the blood cells were examined using a bright field microscope. A diverse variety of blood cell measurements were executed using a stage and an ocular micrometer. The results showed significant differences between the male and female and also between the species. But the lymphocytes of male and female, C. rubrofusus exhibited no significant difference and the blood indices showed a significant difference of (p<0.05). Therefore, the current study provides baseline information on the hematology of A, labiatus, C. auratus, and C. rubrofuscus in the assessment of these species for proper maintenance and welfare.
ChatGPT Practices: Finance and Banking Domain
Authors: Hassan Md Khalid , Parvin Shahnaz , Siddikee Jahangir Alam
Published: December 2024

This paper reviews the practice of ChatGPT in the field of finance and banking through a natural language processing (NLP) system developed by OpenAI. We also discuss applications of ChatGPT in finance and banking, such as the detection of fraud, risk management, forecasting and analysis of the market, management of investments, chatbots for customer service, personal financial management, impact investing, and asset management along with its challenges, limitations and extremely encouraging future potentials. We also recommend taking necessary steps by the authorities to create and enhance ChatGPT-related legislation and regulations to avoid illegal and criminal offences. The paper concludes that ChatGPT will perform better and offer a better user experience for a variety of banking and finance sectors. It is worth remembering that in a relatively short period of time, ChatGPT has garnered significant attention from research, industry, and academia. This study will be helpful for policy makers, practitioners, and researchers.
The Impact of BigBlueButton vs. Skype on Communication Anxiety and Oral Communication Skills
Authors: Mohammadzadeh Hajar , Rahimpour Sepideh
Published: December 2024

The present study, following a sequential mixed-methods design, aimed at examining whether internet-based applications, including Big-BlueButton and Skype online instruction differ in terms of communication anxiety and oral communication skills for EFL learners. A pool of 32 Iranian pre-intermediate EFL students participated in the quantitative phase of the study based on convenience sampling and a pool of nine students participated in the qualitative phase of the study based on purposive sampling. The results of one-way ANCOVA confirmed that there was a significant difference between the Skype group and the BigBlueBottom group in terms of communication anxiety and oral communication skills. Following inter-coder reliability, the most common themes (i.e., novel, challenging, motivating, less stressful, helpful, low internet speed, lack of equipment, and time-consuming) emerged from the students’ responses to the interview questions regarding the role of online learning on oral communication skills. Finally, some practical impli-cations were offered for EFL students and teachers, and some suggestions were made for conducting further studies.
A Systematic Review of ESL/EFL Learners’ Communication Preferences for Written Corrective Feedback
Authors: Daşer Zeynep
Published: December 2024

Fuelled by the advent of process-oriented approaches to writing instruction, written corrective feedback (WCF) has garnered popularity, as a written communication skill, in second and foreign language writing research. Despite the prior reviews on WCF so far, no attempt has been made to synthesize existing research evidence on students’ communication preferences for it. Driven by the gap, the present study seeks to systematically review empirical research on learners’ WCF preferences published between 2013 and 2023 to examine their trends and major findings. The review was conducted according to the PRISMA 2020 Statement Guidelines, and three electronic databases including Web of Science, ERIC, and Scopus were searched. Thirty studies were evaluated based on their relevance and quality. Content analysis indicated that the majority of these primary articles were mixed-method studies, using mostly questionnaires to gather data. Three major groups of research foci were identified. The publications mostly recruited adult, intermediate-level, EFL university students. Students expressed a strong preference for teacher-initiated, direct, comprehensive WCF, targeting grammar errors, and were provided with a red pen.
Los beneficios de la inteligencia artificial en el desarrollo de actividades contables: una revisión de la literatura reciente (últimos 10 años)
Authors: Córdova Morán María
Published: December 2024

Este artículo presenta una revisión a los trabajos desarrollados en relación a los beneficios que ofrece la inteligencia artificial para el desarrollo de las actividades contables.  El objetivo es demostrar cómo la Inteligencia Artificial (IA) permite el desarrollo y mejora del proceso contable, para lo cual se efectuó una revisión sistemática de literatura utilizando la base de Scopus mediante el establecimiento de una ecuación de búsqueda.  Se aplicaron técnicas bibliométricas para analizar la revisión de la literatura, utilizando enfoques tanto cuantitativos como cualitativos.  Los principales hallazgos demuestran un mayor interés por el tema a partir del año 2018.  Se concluyó que el desarrollo de las tecnologías de información y comunicación permiten a su vez, un mejor uso y aplicación de la inteligencia artificial en beneficio de los procesos contables; lo cual maximiza el crecimiento de una empresa, debido a que le permite tener una mejor toma de decisiones.
Mobile Lives: The Quotidian Use Of Mobile Phone
Authors:   Bangladesh Institute of Development Studies, Mozumder Mohammad Golam Nabi
Published: December 2024

Technologies that we habitually use in everyday life play a crucial role in making what we come to be or (en) act in social life (Doron, 2012). Marginalised groups of people appropriate technologies to combat the prevalent modes of domination (Eglash, 2004). This study focuses on a less studied issue, i.e., the quotidian use of mobile phones, particularly among the under-privileged segments of the populace in Bangladesh.
This qualitative study investigates what makes mobile technology a popular tool in (re)constituting the users as social subjects. Do the users redefine the device itself, i.e., a mobile phone? In-depth interviews of mobile users were conducted from all of the eight administrative divisions of the country, with particular focus on young users of 15-35 years of age. More than half of the respondents were female. The interviews were recorded, transcribed, and translated into English. We collected supplementary evidence, such as browsing history, activity log, social media posts, messages, images, and audio-video records. In addition, we conducted a tone analysis of selected portions of a few interviews.
The study finds that the little digital machine known as the mobile phone is not merely a device that they find themselves in awe with; “the little phone” often appears to be vital, the lack of which makes mobile users immobile, hapless, and “lifeless.” Four major types of use of mobile phones are the following: regular use, cultivating attachment, addictive use, and professional use. Users make 11 types of phone calls; they plan, initiate, execute, admonish, punish, and even imagine and outdo what we used to know as phone-calling. The un(der)educated young users of mobile phones invented their own language, which we call “vernography.” Extensive users frequently become addicted to the device; only in rare cases, users might overcome that seductive habit. Access to mobile phones does not always lift them to a higher status; female users from the disadvantaged sections strategise to bypass the seemingly invincible patriarchal barriers to access mobile phones.
In theorising the findings of this study, we argue that society is technology made invisible, which is an extension of Latour’s (1990) famous observation: “Technology is society made durable.” The device that comes to life with the social actuation of human bodies is critical to materialising the vitality of social beings. Digital devices facilitate building “mesh connections”; these connections are vital for underprivileged youth. Mobile is life! Mobile phones engender invisible yet unavoidable connections.
Boas práticas de fabricação para a produção do material de referência para ensaios sorológicos no Instituto Adolfo Lutz
Authors: Jorge Castejon Márcia , Lopes de Oliveira Elaine
Published: December 2024

Este trabalho relata os procedimentos seguidos pelo Laboratório de Material de Referência do Centro de Imunologia – Instituto Adolfo Lutz na produção de materiais de referência (MR) com a qualidade e eficácia para assegurar a confiabilidade dos resultados sorológicos pelos laboratórios participantes nos Programas de Controle de Qualidade do Instituto Adolfo Lutz (PCQ/IAL). A produção do MR envolve um conjunto de medidas para verificar e controlar todo processo, desde a entrada do plasma no laboratório até o produto final.  O intuito é assegurar a máxima qualidade, prevenindo e identificando qualquer possível variação durante o processo. As amostras de controle de qualidade são fundamentais em laboratórios clínicos para maximizar a eficácia dos testes laboratoriais e minimizar custos desnecessários.
Depresión post-parto en madres solteras: una revisión teórica
Authors: Ruiz Malca Raquel Irayda , Sanjinez Atoche Luhana Clarita , Barreto Espinoza Marilú Elena
Published: December 2024

Durante el embarazo, la mujer vivencia diferentes cambios tanto físicos como psicológicos; algunas de ellas experimentan sentimientos de miedo, angustia o ansiedad cuando se aproximan a la etapa del parto; ocurriendo diversos procesos de adaptación a nivel socioemocional y hormonal en la madre, que unidos a las demandas que deberá enfrentar luego del parto, pueden influir significativamente a nivel psicológico, representado posibles factores de riesgo para desencadenar una depresión posparto. Este trastorno que afrontan las mujeres después de dar a luz, depende de la vulnerabilidad de la madre: son más propensas a padecerlo aquellas mujeres con antecedentes de algún trastorno mental, madres muy jóvenes o de edad avanzada, con menor nivel educativo, de condición económica baja, o que estén desempleadas o también su cónyuge, sin embargo la condición de su estado civil como madres solteras o que están pasando por un proceso de divorcio, constituye una condición muy peculiar en esta enfermedad; ya que la condición de que no contar con el apoyo de la pareja, predispone a que las mujeres experimenten sentimientos de soledad, no tengan un soporte emocional e incluso no logren un buen descanso. Incrementando la probabilidad de que las mujeres presenten la depresión postparto.
Análisis de sentimientos y opiniones en expertos sobre inteligencia artificial aplicada a la planificación estratégica ante la pandemia
Authors: Aldana Balderas Wilfrido Isidro , Aguilar Fuentes José Alfonso , Bermúdez Ruíz Gilberto
Published: December 2024

En el contexto de la pandemia, el incremento del uso de la Inteligencia Artificial se debió a las políticas de distanciamiento y confinamiento social. En este sentido, los planificadores estratégicos edificaron un sistema basado en la IA, aunque la exploración y el análisis de las dimensiones se ha realizado desde las razones y motivos de uso, el objetivo del presente trabajo fue establecer los sentimientos y opiniones entorno a la alianza estratégica en la IA y la planificación. Se realizó un estudio documental, transversal y exploratorio con una muestra de 20 expertos, seleccionados por su índice de impacto H reportado en Google Scholar. Los resultados sugieren la prevalencia de cuatro dimensiones relativas a once categorías concernientes a la IA y su relación con la PE en el contexto de la pandemia.
3D Human Pose Estimation Based on Monocular RGB Images and Domain Adaptation
Authors: Manesco João Renato Ribeiro , Berretti Stefano , Marana Aparecido Nilceu
Published: December 2024

Human pose estimation in monocular images is a challenging problem in Computer Vision. Currently, while 2D poses find extensive applications, the use of 3D poses suffers from data scarcity due to the difficulty of acquisition. Therefore, fully convolutional approaches struggle due to limited 3D pose labels, prompting a two-step strategy leveraging 2D pose estimators, which does not generalize well to unseen poses, requiring the use of domain adaptation techniques. In this work, we introduce a novel Domain Unified Approach called DUA, which, through a unique combination of three modules on top of the pose estimator (pose converter, uncertainty estimator, and domain classifier), can improve the accuracy of 3D poses estimated from 2D poses. In the experiments carried out with SURREAL and Human3.6M datasets, our method reduced the mean per-joint position error (MPJPE) by 44.1 mm in the synthetic-to-real scenario, a quite significant result. Furthermore, our method outperformed all state-of-the-art methods in the real-to-synthetic scenario.
Text-driven Video Acceleration
Authors: Ramos Washington L. S. , Marcolino Leandro Soriano , Nascimento Erickson R.
Published: December 2024

From the dawn of the digital revolution until today, data has grown exponentially, especially in images and videos. Smartphones and wearable devices with high storage and long battery life contribute to continuous recording and massive uploads to social media. This rapid increase in visual data, combined with users’ limited time, demands methods to produce shorter videos that convey the same information. Semantic Fast-Forwarding reduces viewing time by adaptively accelerating videos and slowing down for relevant segments. However, current methods require predefined visual concepts or user supervision, which is costly and time-consuming. This work explores using textual data to create text-driven fast-forwarding methods that generate semantically meaningful videos without explicit user input. Our proposed approaches outperform baselines, achieving F1 Score improvements up to 12.8 percentage points over the best competitors. Comprehensive user and ablation studies, along with quantitative and qualitative evaluations, confirm their superiority. Visual results are available at https://youtu.be/cOYqumJQOY and https://youtu.be/u6ODTv7-9C4.
Digital Video Stabilization: Methods, Datasets, and Evaluation
Authors: Souza Marcos Roberto e , Maia Helena De Almeida , Pedrini Hélio
Published: December 2024

Our thesis addressed digital video stabilization, a process that removes unwanted shakes from videos via software. We performed a thorough review, which resulted in two survey papers. We also studied and proposed a new stability measure aligned with human perception and a novel method for evaluating 2D camera motion to assess video quality better. Next, we introduced NAFT, a semi-online DWS with a new neighborhood-aware mechanism. This method stabilizes videos without relying on an explicit definition of stability. To train NAFT effectively, we created SynthStab, a paired synthetic dataset. NAFT achieves stabilization quality comparable to non-DWS methods, with a significantly smaller model (a 14× reduction).
Pseudo Labeling and Classification of High-Dimensional Data using Visual Analytics
Authors: Benato Bárbara C. , Telea Alexandru C. , Falcão Alexandre X.
Published: December 2024

Machine learning (ML) works with data consisting of tens up to tens of thousands of measurements (dimensions) per sample. As the number of dimensions and/or samples grow, so does the difficulty of understanding such data and its ML pipelines. Visualization, and in particular Visual Analytics (VA) has emerged as one of the key approaches that helps practitioners with the understanding of high-dimensional data and with ML engineering tasks. In this paper, we investigate several novel approaches by which VA can help ML (and conversely). Our work focuses on a visualization technique called dimensionality reduction, or projection, and the task of training a classifier when only a small amount of ground-truth labels is available. As result, experiments show that projections can capture very well the data structure present in high dimensions to support the design of high-performance feature and classifier learning models. Also, experiments relate projection quality to data separation and classifier performance. Finally, we combine these two observations to assist users in manual labeling samples to show that both algorithms and humans can exploit projections to build better classifiers. We argue that the ability of pseudo labels in retain information from 2D projected spaces is the key idea that links all these contributions.
Efficient Deep Learning for Image Classification: Lighter Preprocessing and Fewer Parameters
Authors: Santos Samuel Felipe dos , Sebe Nicu , Almeida Jurandy
Published: December 2024

Convolutional neural networks have achieved state-of-the-art performance in several computer vision tasks recently, learning high-level representations directly from RGB images. However, using deeper architectures has led to high computational costs, hindering deployment on devices with limited resources. Additionally, models are usually specialized in a single domain/task while an increasing amount of real-world applications need to deal with multiple domains simultaneously. The computational cost of storing and running multiple instances of those costly models can limit their utilization even more. This Ph.D. thesis aims to reduce the computational burden of deep learning, focusing on two main aspects: reducing data preprocessing cost and sharing parameters across multiple domains/tasks. These contributions have led to the creation of efficient models with high classification performance and reduced costs, allowing them to be deployed in a wider array of devices.
Hierarchical Graph Neural Networks Based on Multi-Scale Image Representations
Authors: Batisteli João Pedro Oliveira , Patrocínio Jr Zenilton K. G.
Published: December 2024

Image representation as graphs can enhance the understanding of image semantics and facilitate multi-scale image representation. However, existing methods often overlook the significance of the relationship between elements at each scale or fail to encode the hierarchical relationship between graph elements. To cope with that, we introduce four novel approaches for graph construction from images. These approaches utilize hierarchical image segmentation techniques to generate segmentations at multiple scales, and one of them incorporates edges to encode the relationships at each scale. Leveraging these representations, we present two new models: the Hierarchical Graph Convolutional Network for Image Classification (HGCIC) and the Hierarchical Image Graph with Scale Importance (HIGSI). HGCIC uses an adaptive depth to capture significant features and patterns at different scales, while HIGSI employs a novel readout function that weighs the importance of each scale when generating a fixed-size graph representation. Experimental results with CIFAR-10 and STL-10 datasets show that the HIGSI model outperforms (or closely matches) state-of-the-art models. The model also utilizes smaller graphs, reaching the point of using graphs with 50% of the number of nodes compared to other approaches. Additionally, HIGSI outperforms models trained with only the base graph used to create the hierarchy, achieving up to 11.54% better performance while using fewer parameters.
A Graph Convolutional Network with Localized Convolution and Readout Operations for Diagnosing Chest X-Rays Using Radiologist Gaze Data
Authors: Lutfi Antonio Nascimento , Batista Neto João do Espírito Santo
Published: December 2024

In this work-in-progress report we propose a Graph Convolutional Network (GCN) capable of diagnosing chest x-rays using radiologist captured data for training. While other neural networks are capable of making inference on medical image exams with gaze data, the examples found in literature use architectures that combine this data with traditional CNNs that learn from the whole image. Our model, on the other hand, learns from a graph of gaze fixations as nodes, each accompanied by a feature vector describing only their region of observation. Such graph is, naturally, euclidean. Traditional convolution and readout operations in GCNs are not conceived to leverage local features and attributes of euclidean graphs, usually aggregating nodes and edges into a whole-graph representation. Our approach divides the graph in a grid, performing such operations in small regions as to preserve local features. With this we aim to prove two hypotheses: 1) a model can learn from specialist gaze data over an image without being paired with the image in its original structure and 2) it is possible to take advantage of euclidean graphs by not aggregating local features in graph convolution and readout layers.
Enhancing Fairness in Machine Learning: Skin Tone Classification Using the Monk Skin Tone Scale
Authors: Matias Vitor Pereira , Batista Neto João
Published: December 2024

In the machine learning era, unethical errors from poorly curated datasets are a pressing issue, especially in fields related to skin tone recognition in which imbalanced datasets lead to biased results. Developing a skin tone classification algorithm helps identify such imbalances. Existing methods range from classic computer vision pipelines to deep learning CNNs that typically employs controlled environment datasets with limited class diversity (two to six classes). Our work focuses on classifying skin tones using the 10-class Monk Skin Tone (MST) scale. To this end, we created the SkinTone in The Wild (STW) dataset by merging well-known face recognition datasets and labelling it according to the MST. This dataset comprises 39,605 images of 2,183 individuals, mostly captured in uncontrolled environments. To overcome this scenario, we evaluated different approaches which resulted in 74% accuracy and 92% off-by-one accuracy (OOAcc) with a RandomForest model, and 68% accuracy along with 86% OOAcc using a DenseNet121 CNN. Furthermore we discussed the sheer power of CNNs and showed that the DenseNet121 architecture learned to predict skin tones by focusing on the background of images. These results highlight the potential for accurate skin tone classification in machine learning which leads to better curated datasets.
Automating the Koedam Parietal Atrophy Scale for Alzheimer's Using MRI Features and Clustering Techniques
Authors: Oliveira Yasmin V. , Ferrari Ricardo J.
Published: December 2024

Early detection of Alzheimer’s disease (AD) is crucial for effective intervention, and imaging biomarkers are pivotal in this process. The search for imaging biomarkers is important in diagnosing AD, offering a non-invasive and potentially early method to identify brain changes associated with the disease. These biomarkers can provide valuable insights into the progression of AD and aid in differential diagnosis, enabling the application of more effective treatment strategies. In this context, the Koedam visual scale for parietal atrophy is a valuable tool for assessing structural changes in the parietal lobe associated with AD. This study proposes an automated approach for the Koedam scale using attributes extracted from T1-weighted magnetic resonance imaging (MRI) combined with clustering techniques. Initially, a preprocessing pipeline is applied to the images to skull stripping, to mitigate noise and bias field effects and to define the ROI (parietal region). Subsequently, a finite mixture model is applied to segment the images into gray matter, white matter, and cerebrospinal fluid. The volume of each tissue is then utilized as a feature for clustering, effectively simulating the visual categorization of the Koedam scale. Our method, tested on 103 MRI images, demonstrates potential for automating the assessment of parietal atrophy, providing a more objective and efficient evaluation tool.
Exploring Foundation Models for Synthetic Medical Imaging: A Study on Chest X-Rays and Fine-Tuning Techniques
Authors: Silva Davide Clode da , Bernardes Marina Musse , Ceretta Nathália Giacomini , Souza Gabriel Vaz de , Silva Gabriel Fonseca , Bordini Rafael Heitor , Musse Soraia Raupp
Published: December 2024

Machine learning has significantly advanced healthcare by aiding in disease prevention and treatment identification. However, accessing patient data can be challenging due to privacy concerns and strict regulations. Generating synthetic, realistic data offers a potential solution for overcoming these limitations, and recent studies suggest that fine-tuning foundation models can produce such data effectively. In this study, we explore the potential of foundation models for generating realistic medical images, particularly chest x-rays, and assess how their performance improves with fine-tuning. We propose using a Latent Diffusion Model, starting with a pre-trained foundation model and refining it through various configurations. Additionally, we performed experiments with input from a medical professional to assess the realism of the images produced by each trained model.
Desenvolvimento de um Modelo Convolucional Leve para Identificação de Doenças Foliares
Authors: Sousa Roney Nogueira de , Oliveira Saulo Anderson Freitas , Rebouças Filho Pedro Pedrosa
Published: December 2024

A produção agrícola enfrenta perdas significativas anualmente devido a doenças de plantas, com impactos econômicos superiores a 40 milhões de dólares e contribuindo para a fome aguda que afeta mais de 281,6 milhões de pessoas em 2023. A identificação de doenças de plantas por meio da análise de imagens de folhas é crucial para mitigar essas perdas. Este estudo propõe um modelo de Rede Neural Convolucional leve, inspirado na arquitetura MobileNet, para classificar diversas doenças em folhas de plantas. Utilizando um conjunto de dados público, esta pesquisa visa desenvolver um modelo que equilibre desempenho e eficiência computacional. O modelo proposto alcançou uma acurácia de 98,94%, com métricas de precisão, recall, F1-Score e AUC de 98,48%, 98,38%, 98,41% e 99,99%, respectivamente. A análise comparativa foi realizada com o MobileNetV2 e um modelo de referência de pesquisas anteriores, demonstrando a eficácia da arquitetura proposta em manter um alto desempenho com um número reduzido de parâmetros.