bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial Intelligence in Education: An Exploration into the University Teachers’ Perspectives about Opportunities and Challenges
Authors: Sohail Humayun , Zaman Muhammad Shokat , Zaidi Muhammad Hussain Raza
Published: September 2024

This was a qualitative endeavor to explore the university teachers' perspectives on opportunities and challenges regarding Artificial Intelligence in higher education. For this purpose, there were eight university teachers (from both public and private) who were sampled conveniently from the social sciences disciplines. The data have been collected with the help of a Semi-structured protocol that has been developed by the investigator(s). It comprises 10 items including one introductory and one closing question. The collected data have been analyzed with the help of the Thematic analysis. Based on the results, it is concluded that, while AI has the potential to significantly transform education, there is a clear need for more targeted support and training for educators. Addressing these challenges is crucial to fully leveraging the benefits of AI and ensuring that its integration into education enhances, rather than complicates, the teaching and learning experience.
History of Hindutva Ideology: Massive Violations of Minority's Rights in India
Authors: Shahid Muneeba , Ishfaq Uroosa , Ashfaq Kashif
Published: September 2024

Hindutva, commonly indicated as the nationalism of Hindus, is a thought based on extremism that expects toward destruction of India's common structure and change the nation into a Hindu state. Hindutva isn't something very similar to the religion of Hinduism., both Hindutva and Hinduism are modern concepts, Hindutva is an ethnic-nationalist or religious-patriot philosophy that derives from the old Indian conventions that have been organized together today under the umbrella of "Hinduism". This article explores the history of Hindutva and the different associations that advocate this ideology. V.D. Savarkar and M.S. Golwalkar who played their role in the promotion of Hindutva ideology Hindu extremism against Muslim minorities and different historical incidents happened to Muslims in the past that how in a pluralistic society of India many individuals are deprived of their fundamental rights are also discussed in the following research.
Social Media as a Helping Tool for Journalists: A Study on the Use of Facebook, X, and Instagram by Mardan-Based Journalists
Authors: Shahid Muhammad
Published: September 2024

This study investigates how Mardan-based journalists utilize Facebook, X, and Instagram. It focuses on how useful social media is for them in carrying out their professional duties. The study intends to investigate how often and how journalists use Facebook, which particular features and functions they find most helpful, what kinds of content are shared, and how the pros and cons of using Facebook for professional journalism are perceived. Thirty journalists in Mardan were surveyed using the study's convenient sampling method and quantitative approach. The findings show that although journalists use a variety of social media sites, Facebook stands out as a particularly helpful resource for information collecting and distribution. The results provide credence to the theory that social media, particularly Facebook, helps journalists fulfill their professional obligations.
Formation of richterite in the enstatite–diopside system in the presence of the K2CO3–Na2CO3–CO2–H2O fluid in application to the processes of mantle metasomatism
Authors: Limanov E. V. , Butvina V. G. , Safonov O. G. , Spivak A. V. , Van K. V. , Vorobey S. S.
Published: September 2024

The paper presents results of studying the formation reaction of K–Na-richterite in the enstatite + diopside association with the participation of the K2CO3–Na2CO3–CO2–H2O fluid at 3 GPa and 1000°C, simulating the formation of this mineral in peridotites of the upper mantle. Richterite formation depends on the (H2O + CO2) / (K2CO3 + Na2CO3) and K2CO3 / Na2CO3 ratios in the starting material. A high concentration of alkaline components in the fluid leads to the decomposition of clinopyroxene, the formation of olivine, as well as a change in the component composition of pyroxene and amphibole. Fluids with a high concentration of the potassium component are responsible for the formation of K-richterite, similar in composition to that formed in metasomatized peridotites of the upper mantle. In some cases, such a fluid leads to the decomposition of amphibole and stabilization of the alkaline melt. With an increase in the activity of the sodium component, the fluid contains richterite, which is similar in composition to richterite from lamproites. The obtained patterns can be used to assess the activities of fluid components and the conditions for the formation of K-richterite. To replenish the data bank of Raman spectra of minerals, the largest and most homogeneous amphibole crystals of different compositions were studied.
Features of crystallization of andesite melt at moderate hydrogen pressures (experimental study)
Authors: Persikov E. S. , Bukhtiyarov P. G. , Shaposhnikova O. Y. , Aranovich L. Y. , Nekrasov A. N.
Published: September 2024

Important problems of magma differentiation, formation of native metals and ore formation processes in the earth's crust are increasingly associated with the active participation of hydrogen. In this paper, new experimental data on the crystallization of andesite melts at high temperatures (900–1250°C) and hydrogen pressures (10–100 MPa) have been obtained, which clarify the possible role of hydrogen in the processes occurring in andesite melts in the earthʼs crust and during volcanism under strongly reduced conditions (f(O2) = 10–17–10–18). In crystallization experiments, it was found that the crystal compositions (pyroxenes and plagioclases) formed in experiments on crystallization of andesite melt under hydrogen pressure closely correspond to the crystal compositions of lava flows of Avacha volcano in Kamchatka. This result can be considered as an experimental confirmation of the participation of hydrogen in the volcanic process.
Features of loparite dissolution in aluminosilicate melts (experimental investigation)
Authors: Suk N. I. , Kotelʹnikov A. R. , Viryus A. A.
Published: September 2024

The solubility of loparite (Na, Ce, Ca)2(Ti, Nb)2O6) in aluminosilicate melts of various compositions was experimentally studied at T = 1200 and 1000°C and P = 2 kbar under dry conditions and in the presence of 10 wt. % H2O in a high gas pressure vessel with a duration of 1 day. The initial material was previously melted glasses of malignite, urtite and eutectic albite-nepheline composition, as well as natural loparite of the Lovozero massif. The dependence of the solubility of loparite on the composition of the aluminosilicate melt (Ca/(Na + K), (Na + K)/Al) has been revealed. Partition coefficients of a number of elements (Ti, Nb, Sr, REE) between silicate melt and loparite crystals (Ki = Cimelt/Cilop) were estimated.
Electricity spot price dynamics comparison in the European and Siberian price zones of Russia using a stochastic volatility model
Authors: Kasianova K. A.
Published: September 2024

In the literature on forecasting electricity spot prices, it is noted that the empirical distribution of the growth rates of equilibrium prices for electricity is characterized by the presence of heavy ‘tails’, so they can be described as a jump-diffusion process. However, electricity prices are associated with a variety of observable factors that can be included in the model. Within the framework of this article, a flexible model, that allows taking into account statistical features of electricity prices (multilevel seasonality, stochastic volatility), as well as fundamental price factors that directly or indirectly affect equilibrium price indices (weather factors, resource prices, industrial production index, or IPI), was developed. Using methods of Bayesian inference, it was shown that the developed two-level specification of the stochastic volatility model, which separates the factors influencing the deterministic and stochastic components of the series, fits the data best, among the considered alternatives. As a result, differences in the price dynamics between the European and Siberian price zones were revealed: the influence of the weather factor in the price zones is not the same; there are also differences in the weekly price dynamics and the effect of holidays. The effect of low-frequency economic factors (resource prices, IPI) on prices was not revealed. This model is a useful tool for analyzing short-term and long-term electricity price dynamics, building scenario forecasts, and it also can potentially be used in risk-management and electricity derivatives pricing.
Biodiversity of Ethiopian aquatic ecosystems
Authors: Golubtsov A. S. , Levin B. A. , Neretina A. N. , Kotov A. A. , Mina V. V. , Dgebuadze Yu. Yu.
Published: September 2024

For 40 years, Russian scientists have investigated the biodiversity of the aquatic ecosystems of the Ethiopian Highlands (Ethiopia), a unique hydrological and hydrobiological region. The expeditions took place in all six main river basins of Ethiopia, which made it possible to describe the species composition and distribution of fish and other aquatic organisms. The discovery of the so-called “species flock” of cyprinid fish, consisting of 4–6 morphotypes, was outstanding. For representatives of these flocks (including the previously discovered flock of lakeTana). Information on the ecology of reproduction, development, age, growth, morphology, nutrition and genetics was obtained for the first time. Methods of artificial reproduction of a number of commercial fishes of Ethiopia have been developed. In addition, knowledge about aquatic crustaceans has been significantly expanded.
IMPLEMENTASI NILAI-NILAI PANCASILA OLEH GURU PKN DALAM UPAYA MEMBENTUK KARAKTER KEBANGSAAN SISWA DI SMP NEGERI 1 EMPANANGKAPUAS HULU TAHUN PELAJARAN 2020/2021
Authors: Mardawani Mardawani , Juri Juri , Santi Dominika
Published: September 2024

Dalam Upaya Membentuk Karakter Kebangsaan Siswa Di SMP Negeri 1 Empanang Kapuas Hulu Tahun Pelajaran 2020/2021. Untukmendeskripsikan implementasi nilai-nilai Pancasila di masa Pandemi Covid-19 melalui pembelajaran Pendidikan Kewarganegaraan dan pembinaan di luar jam pelajaran seperti kegiatan ekstrakulikuler, untuk mendeskripsikan faktor pendukung dan faktor penghambat, serta mendeskripsikan upaya yang dilakukan guru PKn dalam membentuk karakter kebangsaan siswa. Metode yang digunakan dalam penelitian ini adalah deskriptif kualitatif dengan bentuk penelitian deskriptif. Teknik pengumpulan data menggunakan teknik observasi, wawancara, dan dokumentasi. Hasil dalam penelitian ini menunjukan bahwa: 1) Implementasi nilai-nilai Pancasila oleh guru PKn dilakukan melalui kegiatan pembelajaran PKn dan pembinaan di luar jam pelajaran dengan mengupayakan penerapan setiap sila-sila Pancasila dalam setiap materi sesuai dengan RPP 2) faktor pendukung mewujudkan visi misi sekolah, mewujudkan program 9 K, serta melaksanakan kebijakan yang sudah ditentukan kepala sekolah. Faktor penghambat kurangnya sarana dan prasarana, aktivitas pembelajaran berkurang, kurangnya ketersediaan buku/sumber belajar di perpustakaan sekolah, masih banyak siswa yang tidak memiliki HP serta keterbatasan akses internet dalam mengikuti pembelajaran di masa pandemi Covid-19. 3) menanamkan nilai-nilai Pancasila dalam membentuk karakter kebangsaan siswa melalui ikut kegiatan sekolah seperti pengarahan dari Kepala sekolah dan ikut memperingati hari besar nasional. Kata Kunci: nilai-nilai Tujuan dalam penelitian ini untuk mendeskripsikan Implementasi Nilai-Nilai Pancasila Oleh Guru PKn pancasila, peran guru PKn, karakter kebangsaan
EFEKTIVITAS SEKOLAH RUJUKAN TERHADAP PENINGKATAN MUTU PENDIDIKAN DI SMA NEGERI 9 BANDAR LAMPUNG
Authors: Amin Ahmad Fatkhul , Adha Muhammad Mona , Nurmalisa Yunisca
Published: September 2024

Sekolah rujukan didefinisikan sebagai sekolah acuan bagi sekolah lain di sekitarnya dalam penerapan penjaminan mutu pendidikan secara mandiri, memenuhi Standar Nasional Pendidikan (SNP), memiliki  atau mencapai indikator-indikator pendidikan yang lebih dari SNP, dan memiliki prestasi atau keunggulan baik dalam bidang akademik maupun non akademik. Tujuan dari penelitian ini untuk menjelaskan efektivitas sekolah rujukan terhadap peningkatan mutu pendidikan di SMA Negeri 9 Bandar Lampung. Metode penelitian yang digunakan dalam penelitian ini adalah metode deskriptif dengan pendekatan kuantitatif. Sampel dalam penelitian ini adalah 50 orang. Analisis data menggunakan teknik analisis presentase dan teknik pengumpulan data menggunakan angket. Hasil penelitian menunjukan bahwa pelaksanaan sekolah rujukan terhadap peningkatan mutu pendidikan di SMA Negeri 9 Bandar Lampung sudahefektif. Hal ini menunjukan bahwa SMA Negeri 9 Bandar Lampung telah melaksanakan dan meningkatkan mutu pendidikan dalam upaya membantu pemerintah melaksanakan program sekolah rujukan. Kata kunci: Efektivitas, Sekolah rujukan, Peningkatan mutu
PENGEMBANGAN APLIKASI GOOGLE SITES SEBAGAI PENGUATAN LITERASI PEMBELAJARAN TEMATIK SISWA KELAS IV SDN 3 KARANGANYAR
Authors: Pratomo Wachid , Nadziroh Nadziroh , Chairiyah Chairiyah
Published: September 2024

Penelitian ini bertujuan untuk mengetahui (1) Untuk pengembangan Google Sites pada pembelajaran PPKn di kelas IV SDN 3 Karanganyar. (2) Untuk mengetahui kelayakan materi & informasi yang menggunakan Google Sites pada  pembelajaran PPKn di kelas IV SDN 3 Karanganyar. Metode penelitian ini adalah Reseach and Development (R&D) dengan metode pengembangan Borg & Gall yang disederhanakan menjadi 5 langkah prosedur. Penelitian dilakukan di IV SDN 3 Karanganyar, waktu penelitian dilakukan pada tahun pembelajaran 2020/2021. Instrument pengumpulan data yang digunakan adalah  observasi, wawancara & angket/kuisoner. Analisis data hasil kelayakan dilakukan dengan analisis data kualitatif & kuantitatif. Subjek  penelitian yaitu fokus dengan siswa kelas  IV SDN 3 Karanganyar. Tahap uji coba produk yang dilaksanakan yaitu uji coba lapangan secara terbatas dan uji coba lapangan secara luas. Sampel yang di gunakan menggunkan random sampling. Hasil penelitian menunjukan bahwa (1) dalam mengembangkan sistem informasi menggunakan aplikasi Google Sites sebagai penguatan literasi pembelajaran Tematik, dengan menyiapkan bahan dasar materi, perangkat pembelajaran, dan sumber refenrensi yang didapatkan di website resmi dan video edukatif menggunakan aplikasi dasar dari produk Google sites & fitur Google.inc lalu di integrasikan setiap langkah pembuatanya di inputkan kedalam produk website yang disusun oleh peneliti. Aplikasi pendukung dari pihak kedua dan ketiga yaitu  Corel Draw,Adobe Photoshop. Pixellab, Video Director, Freepik. (2) produk aplikasi Google Sites sebagai penguatan literasi pembelajaran tematik siswa baik/layak digunakan dengan  prosentase tertinggi setiap penilaiannya, ahli materi persentase nilai sebesar 93% dengan kriteria Sangat Baik, ahli media persentase nilai sebesar 76,7% dengan kriteria Baik, kepuasan guru persentase nilai sebesar 80 % dengan kriteria Baik. Selain itu persentase respon siswa setelah menggunakan prosuk website yakni 93,75% dengan kriteria Sangat Baik. Kata Kunci: Google Sites, Literasi, Pengembangan, PPKn
PENGARUH PENDIDIKAN PANCASILA DAN KEWARGANEGARAAN TERHADAP SIKAP NASIONALISME SISWA SMA DI PERBATASAN INDONESIA-MALAYSIA
Authors: Purnomo Sapto
Published: September 2024

Penelitian ini bertujuan untuk mengetahui pengaruh Pendidikan Pancasila dan Kewarganegaraan (PPKn) terhadap sikap nasionalisme siswa Sekolah Menengah Atas di perbatasan Indonesia dengan Malaysia. Pada penelitian ini menggunakan metode Ex Post Facto. Sampel penelitian berjumlah 372 yang ditentukan menggunakan teknik cluster random sampling  pada 15 sekolah di 5 Kabupaten yaitu Kabupaten Sintang, Kabupaten Sanggau, Kabupaten Sambas, Kabupaten Bengkayang dan Kabupaten Kapuas Hulu. Pengumpulan data menggunakan instrument angket skala likert. Analisis data yang digunakan meliputi: Uji normalitas, uji linieritas, uji heteroskedastisitas dan uji regresi sederhana. Hasil penelitian menunjukan bahwa Pendidikan Pancasila dan Kewarganegaraan (PPKn) mempunyai pengaruh positif terhadap sikap nasionalisme siswa Sekolah Menengah Atas di perbatasan Indonesia dengan Malaysia. Pendidikan Pancasila dan Kewarganegaraan (PPKn) merupakan salah satu faktor yang bisa memberikan dasar penguatan sikap nasionalisme siswa melalui proses implementasi pembelajarannyaKata Kunci: Pendidikan Pancasila dan Kewarganegaraan, Sikap Nasionalisme Siswa, Perbatasan Negara
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PRESTASI BELAJAR SISWA PADA MASA PANDEMI COVID-19 MATA PELAJARAN PENDIDIKAN KEWARGANEGARAAN KELAS VII C DI SMP NEGERI 2 TEMPUNAK TAHUN PELAJARAN 2020/2021
Authors: Suparno Suparno , Hartini Agnesia , Susila Ardianti
Published: September 2024

SMP Negeri 2 Tempunak pada masa pandemi covid-19 tidak melaksanakan proses belajar mengajar secara tatap muka setiap harinya tetapi hanya melalui penugasan seperti pemberian soal yang setiap 2 minggu siswa harus mengambil dan menyerahkan tugasnya ke sekolah, dengan demikian tentunya proses pembelajaran tidak berjalan secara efektif. Hal tersebut akan mempengaruhi prestasi belajar siswa. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi prestasi belajar siswa pada masa pandemi covid-19 mata pelajaran Pendidikan Kewarganegaraan kelas VII C di SMP Negeri 2 Tempunak tahun pelajaran 2020/2021. Penelitian ini menggunakan pendekatan kualitatif dan metode penelitian kualitatif dengan bentuk penelitian studi kasus. Hasil penelitian ini menunjukkan bahwa faktor-faktor yang mempengaruhi prestasi belajar siswa pada masa pandemi covid-19 mata pelajaran Pendidikan Kewarganegaraan kelas VII C di SMP Negeri 2 Tempunak terdiri dari faktor internal dan eksternal. Prestasi belajar siswa juga mengalami penurunan pada masa pandemi covid-19 karena proses belajar mengajar tidak berjalan secara efektif. Guru berperan penting dalam mengatasi faktor-faktor yang mempengaruhi prestasi belajar siswa. Peran guru yaitu memberikan motivasi kepada siswa agar lebih giat untuk belajar, guru  memberikan teguran dan bimbingan kepada siswa yang prestasi belajarnya mengalami penurunan, guru memberikan buku paket kepada siswa dan siswa diberikan keringanan waktu oleh guru jika telat mengumpulkan tugas. kata Kunci : Faktor-faktor prestasi belajar, pandemi covid-19, mata pelajaran pendidikan                     Kewarganegaraan.
ANALISIS DAMPAK PEMBERIAN BANTUAN LANGSUNG TUNAI DANA DESA BAGI MASYARAKAT DI DESA MEKAR MANDIRI KECAMATAN KAYAN HILIR KABUPATEN SINTANG TAHUN ANGGARAN 2020
Authors: Juri Juri , Ades Teodorus
Published: September 2024

Penelitian ini dilatarbelakangi adanya Pemberian Bantuan Langsung Tunai Dana Desa Bagi Masyarakat Tahun Anggaran 2020. Tujuan dalam penelitian ini untuk mengetahui bagaimana kondisi masyarakat Desa Mekar Mandiri, untuk mengetahui bagaimana proses pemberian Bantuan Langsung Tunai Dana Desa di Desa Mekar Mandiri, untuk mengetahui bagaimana dampak Bantuan Langsung Tunai Dana Desa bagi masyarakat Desa Mekar Mandiri. Metode penelitian yang digunakan dalam penelitian ini adalah deskriptif kualitatif dan bentuk penelitian ini adalah deskriptif. Teknik pengumpulan data menggunakan teknik observasi, wawancara, dan dokumentasi. Hasil penelitian ini menunjukan bahwa:1) kondisi masyarakat Desa Mekar Mandiri yaitu masih banyak ekonomi dalam keluarga tidak mampu pada masyarakat Desa Mekar Mandiri sehingga menimbulkan keadaan sosial ekonomi masyarakat masih ada warga yang miskin. 2) pemberian bantuan langsung tunai dana desa di Desa Mekar Mandiri masih kurang efektif untuk mengentas angka kemiskinan. 3) dampak pemberian bantuan langsung tunai dana desa bagi masyarakat di Desa Mekar Mandiri ada terdapat dua dampak yaitu dampak positif masyarakat merasa terbantu dalam memenuhi kebutuhan pokok sehari dan negatifnya merupakan terjadi kenaikan biaya hidup masyarakat dan kecemburuan sosial. Kesimpulan awal tahun 2020 keadaan masyarakat terdampak oleh pandemi Covid-19 sehingga berpengaruh pada ekonomi dalam keluarga tidak mampu masyarakat Desa Mekar Mandiri, untuk mengatasi peristiwa tersebut pemerintah desa membuat kebijakan berupa program bantuan langsung tunai yang bersumber dari dana desa. Saran untuk pemerintah desa diharapkan bisa mengambil kebijakan yang tepat, cepat dan bersikap adil bagi seluruh masyarakat Desa Mekar Mandiri dan lebih mengefektifkan lagi dalam pemberian berbagai bantuan agar bisa diberikan kepada warga yang benar-benar layak mendapatkannya. Kata Kunci: BLT, Dana Desa.
IMPLEMENTASI PENDIDIKAN MORAL MELALUI IMTAQ OLEH GURU DALAM MEMBENTUK KARAKTER SISWA DI SMA NEGERI 1 DEDAI
Authors: Suparno Suparno , Juri Juri , Paulinus Paulinus
Published: September 2024

The faith and devotion of students is the goal of national education where school educational institutions are one of the most effective vehicles for achieving educational goals. However, the problem in the study of the implementation of moral education through faith and piety (imtaq) by teachers to shape the character of students at SMA Negeri 1 Dedai, the condition of moral behavior and personality of students is very concerned, this is indicated by the existence of cases such as students being late when the lesson starts, students do not pay attention to the teacher when delivering the material and there are many students who skip or run away during school hours. The purpose of the research is to describe the implementation of moral education through Imtaq by teachers to shape student character at SMA Negeri 1 Dedai. Researchers used qualitative methods, the subjects and objects of research were teachers of Islamic Religion, Catholic Religion and Islamic Religion Students and Catholic Religion Students. The data analysis technique used is a qualitative approach in this study, data collection techniques through observation, interviews (interviews), and documentation. The results showed that: (1) The purpose of the imtaq program at SMA Negeri 1 Dedai is to instill good character values in students, besides that it also familiarizes students so that students have faith and devotion to Allah SWT. (2) The implementation of the imtaq program in instilling student character at SMA Negeri 1 Dedai has been going well and with this imtaq program students have reflected good character. The conclusion is that the implementation of moral education through imtaq is very good for shaping student character. Keywords:Moral Education and Imtaq
PENINGKATAN HASIL BELAJAR PESERTA DIDIK MELALUI MEDIA ULAR TANGGA PADA MATA PELAJARAN IPS KELAS VIII SMP NUSANTARA INDAH SINTANG
Authors: Pelipa Emilia Dewiwati , Relita Dessy Triana , Wulandari Wulandari
Published: September 2024

The purpose of this study was to describe the use of snakes and ladders learning media in improving student learning outcomes in social studies subjects in Class VIII of Nusantara Indah Sintang Junior High School in the 2023/2024 academic year. The method used in this research is qualitative research method. The subjects in this study were all students in class VIII of Nusantara Indah Junior High School Sintang in the 2023/2024 academic year, totalling 13 students, including 10 female students and 3 male students. The data collection techniques used were observation, interviews, documentation and test questions. Based on data analysis, the research results are as follows: (1) the application of snakes and ladders learning media is in accordance with the steps specified on the observation sheet. Judging from the results of teacher activity observations in cycle I was 90% and in cycle II was 100% with the assessment criteria for teacher activity observation results very well. (2) the improvement of students' learning outcomes can be seen from the test results, average scores, and classical completeness of each cycle. Where the average value of cycle I was 63.07 and the classical completeness was 53.84%, while the average value of cycle II was 88.46 and the classical completeness was 92.30%, meaning that snakes and ladders learning media can improve student learning outcomes. (3) Students' responses to the snakes and ladders learning media expressed positive responses based on statements on the students' interview sheets. It can be concluded that through snakes and ladders media can improve the learning outcomes of students in social studies class VIII SMP Nusantara Indah Sintang in the 2023/2024 academic year. Keywords: Learning Outcomes, Snakes and Ladders Learning Media
MEMBENTUK KARAKTER PELAJAR BEBAS NARKOBA DI SMPN 2 SINTANG
Authors: Suseka Septha , Fingky Winarto , Anjela Tersia
Published: September 2024

The purpose of this article is to provide an overview of the phenomenon of drug abuse among teenagers and the efforts made to prevent it. This study was conducted with a qualitative approach and is descriptive in nature. Meanwhile, there are several steps that need to be taken to deal with the problem of drug abuse among teenagers. This includes prevention and education, anti-drug campaigns, and massive enforcement actions starting from families, schools, and communities. Therefore, parents must act democratically by treating their children or teenagers well and giving them enough attention. To prevent drug abuse among teenagers, schools must provide education and various information about the dangers of drugs. In society, every member of society must act firmly and consistently as social control to prevent drug abuse. The research results show that drugs have spread in Indonesia today, especially among teenagers. There is already a drug emergency in Indonesia, and everyone must pay attention to this. Meanwhile, there are several steps that need to be taken to deal with the problem of drug abuse among teenagers. This includes prevention and education, anti-drug campaigns, and massive enforcement actions starting from families, schools, and communities. Therefore, parents must act democratically by treating their children or teenagers well and giving them enough attention. To prevent drug abuse among teenagers, schools must provide education and various information about the dangers of drugs. In society, every member of society must act firmly and consistently as social control to prevent drug abuse.Keywords: Preventing Drug Abuse, Drug Abuse, Teenager
Tod im digitalen Zeitalter
Authors: Frei Nula , Zlatescu Petru Emanuel , Naedele Robert
Published: September 2024

Während ihres Lebens häufen Menschen zahllose Daten in digitalen Umgebungen an. Was damit nach dem Tod geschieht ist nicht in allen Fällen klar. Welche digitalen Persönlichkeitsrechte stehen einer verstorbenen Person zu und welche Ansprüche haben Erben auf die virtuellen Hinterlassenschaften? Die zunehmende Digitalisierung des Todes wirft zahlreiche Rechtsfragen auf, die nicht nur Erblasser und Erben betreffen, sondern auch Technologiefirmen und Onlinedienste. Die vorliegende Studie blickt auf das schweizerische Recht und die bestehenden Vorschriften, welche auf die Folgen des digitalen Todes anwendbar sind. Zudem versucht sie aufzudecken, welche Lücken existieren und wie der Gesetzgeber sie schliessen könnte. Damit schafft sie die juristische Ergänzung zur Studie "La mort à l’ère numérique. Chances et risques du Digital Afterlife", welche sich auf die technischen, sozialen, ökonomischen, psychologischen und philosophischen Aspekte der Thematik bezieht.
Exploring the elastocaloric effect of Shape Memory Alloys for innovative biomedical devices: a review
Authors: Costanza Girolamo , Porroni Ilaria , Tata Maria Elisa
Published: September 2024

This paper discusses Shape Memory Alloys’ (SMA) elastocaloric effect (EC) and underscores its potential use in substituting conventional cooling systems, for future and innovative applications in the biomedical sector, where temperature has a significant influence on the structure and function of crucial macromolecules and cells. After an introduction on SMA’s EC and its relevance for medical and biomedical field, the authors examine the principles and mechanisms at the base of this particular property, with a focus on main keys essential to evaluate performances and the differences characterizing most used elastocaloric alloys, also exploring strategies currently in place to improve performances. Thereafter, the discussion moves on the current design and development of instruments exploiting this innovative behavior, introducing thermal microdevices made of elastocaloric materials in biomedical applications. It concludes by analyzing future directions of elastocaloric cooling and heating for biomedical applications, including possible upcoming medical and biomedical devices, evaluating challenges that researchers still need to address for the adoption of SMA’s EC in the biomedical field.
Spatio-temporal deep learning framework for pedestrian intention prediction in urban traffic scenes
Authors: Monika  , Singh Pardeep , Chand Satish
Published: September 2024

Pedestrian intent prediction is an essential task for ensuring the safety of pedestrians and vehicles on the road. This task involves predicting whether a pedestrian intends to cross a road or not based on their behavior and surrounding environment. Previous studies have explored feature-based machine learning and vision-based deep learning models for this task but these methods have limitations in capturing the global spatio-temporal context and fusing different features of data effectively. To address these issues, we propose a novel hybrid framework HSTGCN for pedestrian intent prediction that combines spatio-temporal graph convolutional neural networks (STGCN) and long short-term memory (LSTM) networks. The proposed framework utilizes the strengths of both models by fusing multiple features, including skeleton pose, trajectory, height, orientation, and ego-vehicle speed, to predict their intentions accurately. The framework’s performance have been evaluated on the JAAD benchmark dataset and the results show that it outperforms the state-of-the-art methods. The proposed framework has potential applications in developing intelligent transportation systems, autonomous vehicles, and pedestrian safety technologies. The utilization of multiple features can significantly improve the performance of the pedestrian intent prediction task.
Detecting and Mitigating the Weakest Cybersecurity Link in an Information System
Authors: Sadeghian Ali , Mejri Mohamed
Published: September 2024

In today’s digital landscape, the prevention of cyber attacks has become exceptionally crucial. This is especially true for safety-critical systems, where safeguarding against these threats is of paramount importance. To address this concern, the MITRE Corporation has developed ATT&CK, an extensive framework comprising data matrices. This framework serves the purpose of assessing a company’s security preparedness and pinpointing vulnerabilities that may exist within its infrastructure. By leveraging the capabilities of MITRE ATT&CK, including its tactics and techniques, in conjunction with the LDA4CPS tool, we have devised a novel approach to identify the most critical vulnerabilities in a susceptible system. Furthermore, incorporating MITRE ATT&CK mitigations tailored to the discovered vulnerability empowers the blue team (defensive side) with tangible, practical measures to fortify their security posture. This approach enhances their capability to effectively counter cyber threats, bolstering their overall defensive capabilities.
Data Hiding Components for Solving Information Security Issues in DICOM Medical Images
Authors: Mosco-Garcia Juan Eduardo , Cedillo-Hernandez Manuel
Published: September 2024

In the field of medical image management, the security and privacy of patient data are of utmost importance. This research focuses on the application of the Jarvis halftone technique for image reconstruction aimed at enhancing data hiding capabilities. We employed data hiding in binary image with high payload method to embed binary characters into the modified contours of Jarvis halftone images, thereby increasing the bandwidth for data hiding. To enhance the hiding capacity, the original patient image was modified by adding an artificial contour that creates vectors in selected pixels, thus optimizing the halftone technique used. The processed images were embedded into DICOM medical images using a pseudo-random walk technique, which allowed the generation of two keys for concealment, embedded in layers 12 and 16 of the image. This resulted in a modified DICOM image with a Structural Similarity Index measure. Subsequently, data were extracted using the generated keys, thus retrieving the Jarvis halftone image with modified contours. This process was followed by a conversion of the halftone image to grayscale for patient authentication, highlighting the effectiveness of the Jarvis halftone in preserving image quality after the data hiding and extraction process. This study not only demonstrates the feasibility of integrating advanced halftone and data hiding techniques in the medical field but also opens ways to future research on security in the transmission and storage of medical images, ensuring the confidentiality and integrity of patient information.
URL Phishing Detection by Using Natural Language Processing and Deep Learning Model
Authors: Lai Clive ,   University of Hradec Kralove, Selamat Ali , Ibrahim Roliana , Quang D.N. , Fujita Hamido , Krejcar Ondrej
Published: September 2024

The selection between Deep Learning (DL) approaches is not easy for URL phishing due to the variety of attacks and scammers. There are various DL techniques to detect phishing URLs, and choosing the suitable algorithm and affecting the model formed is very important. Wrong-choosing DL techniques might lead to low maturity and produce bias. The trained model’s performance and accuracy would also be unsatisfactory if the wrong algorithms and methods were used. It often happens when the attackers change their phishing strategies frequently to target the system’s weaknesses and users’ naivety. The robust characteristics of DL algorithms have led the researchers to develop several URL phishing mitigation strategies. The techniques have been used to detect phishing attacks by using various URL features like URL length, URL domain, and other known features and further incorporating the new features. From the perspective of the Natural Language Processing (NLP) technique perspective, transformers are models designed to handle sequential text, such as summarizing and translating. One of the well-known transformers, called Keras Embedding, has a good application in detecting spam emails. As the transformers proved their usage in URL phishing detection, it is further hypothesized that the URLs can directly parse out the contextual meaning of the string and identify whether the website is benign or phishing. Therefore, this paper provides a URL phishing detection model with a combination of deep learning and natural language processing methods. As shown in the experiments, the result produces and improves with high performance and accuracy for URL phishing detection. We also examined and compared the findings of the proposed solution with deep learning only and NLP-only URL phishing detection approaches.
Extended Engineering Software Support for Multiphysical Research in Applied Informatics
Authors: Horváth László , Kovács Levente
Published: September 2024

This paper is about a special configuration of engineering model and modeling platform for model development that serves widely connected research in applied informatics considering demands by highly automated achievements. Initiative for this special application of engineering modeling platform was motivated by engineering purposed software development towards reactive, autonomous, and widely contextual solutions to accommodate tasks in extending variety of integrated issues. After characterizing the multiphysical way of multidisciplinary model powered engineering research, this paper introduces novel model mediated scenario in which research specific engineering software related activities are placed with the emphasis on flexible model and software configuration considering composition of complex multidisciplinary solutions for multiphysical engineering representations and simulations those are extended to human organ and other bioinspired issues. Additional contributions in this paper are about capabilities of reactive autonomous models, extended representation of behaviors, and novel experimental model for research in applied informatics. Finally, application of the above experimental model in research using scientifically renewable world level engineering modeling platform at the Virtual Research Laboratory, and evaluation and advantages of the proposed research are introduced.
Hands and Palms Recognition by Transfer Learning for Forensics: A Comparative Study
Authors: Fattahi Jaouhar , Fkiri Obeb , Mejri Mohamed , Ghayoula Ridha
Published: September 2024

In the realm of forensic science, precise identification of individuals holds paramount importance in both investigative procedures and legal proceedings. Hands and palms recognition has emerged as a valuable biometric modality within forensic applications, owing to the distinct and intricate features inherent to these anatomical regions. The elaborate patterns of veins, creases, and ridges present on palms and fingers serve as rich sources of biometric data, crucial for accurate identification purposes. Furthermore, given the frequent involvement of hands and palms in criminal activities such as theft and assault, their recognition becomes imperative for establishing links between suspects and crime scenes. However, developing robust recognition systems tailored for forensic applications poses notable challenges, including variations in hand poses, lighting conditions, and image quality. To address these hurdles, sophisticated deep learning techniques, notably transfer learning, have been employed. By harnessing pre-trained deep learning models namely NasNetLarge, NasNetMobile, and EfficientNet, initially trained on expansive datasets for general image recognition tasks, we can adapt these models to the specific task of hands and palms recognition in forensic contexts. Our findings reveal that all three models consistently achieved over 92% accuracy across all metrics evaluated, demonstrating their efficacy as strong contenders for the hands-and-palms recognition task. Notably, the EfficientNet model exhibited superior performance compared to its counterparts, boasting more than 95.8% accuracy, precision, F1-score and recall, along with more than 98.6% specificity and 99.4% AUC.
Machine Learning-Based Approach to Correct Saturated Flow Boiling Heat Transfer Correlations
Authors: Santiago Galicia Edgar , Hernandez Matamoros Andres , Miyara Akio
Published: September 2024

This study investigates the application of machine learning to enhance the accuracy of saturated flow boiling heat transfer correlations. Traditional correlations often exhibit limitations, motivating the exploration of alternative approaches. A comprehensive dataset encompassing 2770 experimental observations, compiled from over 15 published research papers, serves as the foundation for this research. The data incorporates flow boiling heat transfer for pure and mixture refrigerants in smooth tubes. The study compares three machine learning models including neural network, linear regression, and SVM. The data is strategically divided: 80% for training the models and 20% for testing. The wide neural network shows that the best-performing model achieves a Root Mean Square Error (RMSE) of 0.202, demonstrating exceptional prediction accuracy, followed by the linear regression, and SVM training models. Heat Transfer Coefficient (HTC) is predicted with an error of less than 5% for all refrigerants, further confirmed by a high coefficient of determination (0.99). This signifies a significant improvement in traditional experimental-based correlations. Furthermore, the study demonstrates the efficacy of machine learning models in predicting heat transfer enhancement methods. In conclusion, this work highlights the potential of machine learning for refining saturated flow boiling heat transfer predictions.
Optimizing Industrial Maintenance Scheduling Through Deep Reinforcement Learning and Simulation Integration
Authors: Marchesano Maria Grazia , Guizzi Guido , Converso Giuseppe , Salatiello Emma , Popolo Valentina
Published: September 2024

Maintenance scheduling is critical function across numerous industries, where the dynamic complexity of operations often challenge the systems efficiency. This study explores the application of Deep Reinforcement Learning (DRL) to refine scheduling decisions by integrating a simulation tool that replicates an industrial production line. This integration eases the modelling and simulation in real-time of machine operations, job flows, and maintenance activities, capturing the dynamics and complexities of a typical production environment. Our developed tool assesses various maintenance strategies and their direct impacts on productivity, leveraging DRL to enhance decision-making capabilities. We introduce an innovative job-sequencing rule that complements the DRL framework, systematically analysing its effectiveness against traditional heuristic methods. The comparative analysis confirms that our DRL-based approach, coupled with the job sequencing rule, significantly optimises maintenance timing and resource allocation in a flow shop setting. By synthesizing simulation with intelligent algorithms, our method not only optimize maintenance tasks but also boosts overall production efficiency.
ICERS: Intelligent Collaborative Emergency Response System
Authors: Yang Guoyin , Zhang Haotian , Yao Junfeng , Cai Chengyou , Song Jun , Xu Yuelin , Deng Bin
Published: September 2024

Advances in computer science and technology, coupled with the growing societal demand for enhanced safety, have paved the way for innovative smart home environments. While current smart home systems can send alarms and notify emergency contacts during a crisis, they do not provide timely and convenient on-site emergency assistance, potentially delaying critical aid and compromising user safety. This paper introduces the Intelligent Collaborative Emergency System (ICERS), which addresses this gap through three integrated subsystems: Fall Detection, Vital Signs Monitoring, and Central Dispatch. The Fall Detection module leverages camera video data to classify human positions and estimate potential falls. The Vital Signs Monitoring module employs millimeter-wave radar technology to provide non-contact, real-time health monitoring. The Central Dispatch system receives alert signals from on-edge devices and relays them to medical facilities and volunteer organizations for a coordinated emergency response. By utilizing multimodal data for collaborative efforts, the ICERS ensures that individuals receive timely notifications and coordinated emergency assistance during unforeseen situations.
Voice Gender Recognition Under Unconstrained Environments Using Fine-Tuned CNNs
Authors: Jorrin-Coz Jorge , Nakano Mariko , Flores-Monroy Jonathan , Perez-Meana Hector
Published: September 2024

Automatic voice gender recognition (VGR) offers several real-world applications, including recommender system, human-robot interaction, and forensic application. VGR systems become challenging when these operate under unconstrained environments. In this study, we evaluate the performance of VGR systems using different fine-tuned pretrained Convolutional Neural Networks (CNNs), in which the speech signals under unconstrained environments are introduced as input data. First, preprocessing is applied to the original speech signal, which consists of noise attenuation based on low-pass filter and silence part removal based on sound amplitude. Then, the time-frequency features, such as Spectrogram, Mel-Spectrogram and Mel Frequency Cepstral Coefficients (MFCC) are extracted, which are converted into RGB images and processed by CNN models. Our research utilizes the VoxCeleb dataset, which is the largest video-audio dataset recorded under unconstrained environments. The results obtained by several fine-tuned CNN models provide higher accuracy compared with the state-of-the-art techniques on this topic. The best accuracy achieved is 98.58% using fine-tuned MobileNet, which is higher than the best accuracy provided by previous works.
Adaptive WIP Control in Industry 4.0 Manufacturing via Deep Reinforcement Learning: A Case Study in Hybrid Control Architectures
Authors: Vespoli Silvestro , Mattera Giulio , Guizzi Guido , Santillo Liberatina Carmela , Nele Luigi
Published: September 2024

The advent of Industry 4.0 has revolutionised manufacturing systems, introducing unprecedented levels of customisation and variability. Traditional methods for controlling Work-In-Progress (WIP) often fall short in these dynamic environments, necessitating the development of adaptive and intelligent control strategies. This paper explores the application of Reinforcement Learning (RL) for adaptive WIP control in semi-heterarchical architectures for flow-shop production systems. We propose a novel framework that integrates RL, specifically Deep Q-Networks (DQN), with Discrete-Event Simulation (DES) to derive optimal control policies without relying on closed-form mathematical models. Preliminary simulation experiments demonstrate the effectiveness of the proposed approach in handling variations in job processing time variability and throughput reference targets, showcasing the merit and potential of RL for adaptive WIP control.
Topic Modeling in the Darknet via Semi-Supervised Learning and Linguistic Transformers
Authors: Hernandez-Suarez Aldo , Perez-Meana Hector Manuel , Sanchez-Perez Gabriel , Portillo-Portillo Jose , Olivares-Mercado Jesus , Toscano-Medina Linda Karina
Published: September 2024

In recent years, the darknet, a hidden part of the deep web associated with illicit activities, has been the subject of study due to the myths and mysteries surrounding it. Contemporary research aims to uncover the true topics hidden within this network using thematic analysis techniques, which are essential for cybercrime prevention and legal action. However, the dynamic and anonymous nature of the darknet poses the challenge of effectively navigating the TOR protocol to obtain and analyze samples from hidden sites. This paper presents an innovative approach to studying the darknet. Assuming limited prior knowledge of the original topics, a contextual relation-comparison technique with TinyBERT, a large language model, is used to generate super topics from previously identified hidden sites. From these super topics, keywords with contextual scores and weights are extracted, serving as input for a sensor that navigates the TOR network and aggregates new hidden sites. These sites are processed through semi-supervised learning to form clusters of sub-topics. Labels for each sub-topic propagate based on their similarity to the main topics and are ultimately classified in a fine-tuning layer of TinyBERT. The results demonstrate the identification of twelve classes of sub-topics in the darknet, related to drugs, hacking, marketplaces, pornography, and other areas, with a classification accuracy of 95.45%.