bluuebunny/crossref_metadata_2025 huggingface dataset:
AiShifu: AI Karate Pose Trainer Using Human Pose Estimation
Authors: Lu Frederick
Published: February 2024

One application of the artificial intelligence (AI) technology is self-guided physical activities where a computing device acts as a trainer. One key challenge for these applications is how to measure the performance of such an AI trainer, especially when the AI trainer is run on a generic PC or a mobile device. In the spirit of the Turing test, an AI trainer should mimic the behavior of a human trainer. A good human trainer generally considers the training history and the level of the trainee when providing feedback, which requires more than body position analysis. In this work, we built a Martial Art trainer application called AIShifu that helps users practice martial art poses using Human Pose Estimation (HPE). We chose an open-source neural network called HRNET trained with MS-COCO dataset as the core of the HPE. The joint coordinates and angles were used to identify the pose being practiced by the trainee, whether the active side is left or right, and how close is the key joint angle to that from a “golden” image. We collected data from both a black belt martial artist and a novice trainee and on three Karate poses. Based on the data, it is clear that the blackbelt performed the poses more consistently. A much larger sample size was required to test how well an AI trainer can discern the difference between trainees with different levels of proficiency. This understanding forms the foundation to customize AI trainer softwares for different users.
How Genetic and Sociocultural Factors Interact with Mental Health Disorders and Epigenetics to Predispose and Reinforce Substance Use Disorder
Authors: Borodulin Natalia , Holmberg Jennifer
Published: February 2024

The recent drug epidemics occurring nationally and globally have called for questions of “nature vs. nurture” with regard to what predisposes for addiction. What has a more significant impact on drug risk? Biological or environmental factors? The understanding of different impacts can fundamentally change how people treat substance use disorder (SUD). However, SUD is a lot more complex and requires the interaction of many risk factors. While nature may predispose addiction, your environment must aid the predisposition to facilitate and reinforce SUD. This project will show how genetic, social, and mental health risk factors interact to cause addiction as well as how SUD is reinforced through social pressures and epigenetics. Here we review literature on the different risk factors that contribute to addiction and how they interact. Specifically, we investigate the impact of genetic factors, sociocultural influences, mental health disorders, and epigenetics on SUD. Knowing what can assist a predisposal to SUD would not only further our understanding of addiction but could also help people who struggle with SUD by reinforcing social policies and health infrastructures that help with treatment and recovery from SUD. It could also help parents protect their kids from growing up in environments that may influence them and push them to develop SUD in the future. The understanding of risk factors can lower the number of people with SUD in the future and help people currently trying to recover from SUD by interrupting addiction cycles.
Effect of High School Math skills on the Types of Professions
Authors: Yea Brandon , Kaci Rachael
Published: February 2024

In the 21st century, the importance of STEM professions has increased. Simultaneously, the interest to acquire these STEM professions has also increased among high school students. For high school students desiring to acquire a STEM profession, this paper attempts to find the relationship between high school math skills and the likelihood of acquiring a STEM profession in the future. Furthermore, this paper attempts to explain the effect that high school math skill has on average wages which are indicated in other related papers. This paper collected secondary sources from a renowned math summer program for high school students which contained tracked data of past alumni. After analyzing 121 alumni data, it was clear that high school students who were skilled at math indeed had a higher chance of acquiring STEM professions such as engineering and computer science. However, STEM jobs related to science did not have high percentages. This indicated that high school math proficiency had a profound effect on the probability of acquiring heavily math integrated professions whereas this was not the case for STEM professions requiring a mix of other STEM knowledge besides math. In addition, the high percentage of computer science and engineering jobs explained how proficient high school math skills led to high average salaries as these are one of the highest paying jobs. Overall, it is clear after reviewing the data that although proficiency in high school math skill does not necessarily lead to higher probability of acquiring all types of STEM jobs, it still has a noticeable impact on the probability of acquiring a math-heavy STEM profession and is likely to be one of the major elements in determining the future salaries.
Bullied, Blamed, Broken: The Impact of Victim Blame on Bullied Adolescents’ Ego Establishment
Authors: Zhang Estelle , Wang Wanting , Hu Lingping
Published: February 2024

School bullying is widely recognized as a significant social issue. Past studies have discovered a potential connection between school bullying and identity crisis, drawing from Erik Erikson’s theory about psychological developmental stages. However, there is a dearth of research examining the possible influence of victim blame on bullied students’ identity formation during adolescence, especially with sufficient quantitative evidence. Addressing this research gap, the current study aims to investigate the correlation between victim blame and bullied students' identity crisis with quantitative measures. To comprehensively analyze the relationship between these three factors, this research focuses on the following question: How does victim blame impact the establishment of ego in bullied adolescents? To answer this question, data was collected from participants with high school experience and classifying them into control and treatment group. research tools were employed simultaneously: James E. Cote’s identity crisis modality model, Erik Erikson’s theory about psychological growth phases, and a quantitative survey consisting of close-ended questions. The findings reveal that most participants in the treatment group exhibited a sharp increase in identity crisis levels during adolescence, accompanied by frequent acute fluctuations in identity crisis level. This period also coincides with their experience of both victim blame and school bullying. Furthermore, the results demonstrate a positive correlation between victim blame and bullied students’ identity crisis. This research offers fresh insight to the psychology of bullied adolescent students, and future studies should aim to expand the scope of inquiry into the process of identity formation.
The Implications of Using Artificial Intelligence (AI) for Facial Analysis and Recognition
Authors: Saluja Simran , Douglas Trevor
Published: February 2024

Many individuals have ethical concerns related to newer biometric facial recognition technologies (FRT), along with how it is being integrated into various fields of study. This paper highlights the importance of understanding the positives and negatives of this technology in today's world, particularly in terms of privacy infringement and unintentional biases in machine learning models. FRT has significant applications in healthcare, law, security, and finance. However, it raises concerns regarding privacy, data protection, and potential biases in the data and analysis. The integration of AI and machine learning in FRT introduces the risk of biased decisions and discriminatory outcomes. Overall, the implications of this research suggest that while BFRT offers valuable advantages, proper legislation is necessary to address ethical concerns and ensure the safety and privacy of individuals.
Establishing Nitric Oxide Levels as a Biomarker for Fibromyalgia and Rheumatoid Arthritis Diagnosis
Authors: Wong Lauren , Joykutty Leya , Caulkins Juliana
Published: February 2024

Fibromyalgia (FM) is a chronic, hyperalgesic disorder leaving musculoskeletal pain throughout the body without tissue damage, ultimately affecting about 1 in 25 to 1 in 50 people in the United States. Although prevalent, its diagnosis is complicated and long due to its ambiguity of official signs of its presence. Patients wait an estimated 2.3 years and see about 3.7 physicians on average before being diagnosed with this disorder. But in recent years, the FM/a blood test, which analyzes unusual patterns of immune responses has allowed for more accurate and timely diagnosis, boasts a 93% sensitivity rate and 89% specificity rate. Although an advancement, the FM/a test was found to have a false positive rate of 29% and 31% for patients with SLE and RA, respectively. To combat the lack of secure physiological ways to determine Fibromyalgia in patients, measuring nitric oxide (NO) levels in the body and exhaled breath appears to be a promising biomarker to distinguish RA from FM upon diagnosis. Nitric oxide works as a vasodilator and signal for localized inflammation. FM is a non-inflammatory disorder, so NO levels are heightened in both the blood and exhaled breath due to a lack of arginase, a competitive inhibitor of NO production. On the other hand, RA is an inflammatory autoimmune disorder that presents similarly in behavior to FM, but it leaves less NO in the blood because of the increased activity of arginase.
Egy váratlan bejelentés: Megvalósulhat-e az EU bővítése 2030-ra?
Authors: Németh Ferenc , Orosz Anna
Published: February 2024

Charles Michel bejelentése, miszerint 2030-ra a tagjelölt országoknak és az EU-nak is késznek kell lennie új tagok fogadására, meglehetősen ambiciózus. Az Európai Tanács elnökének kijelentése egyelőre csak politikai keretek között értelmezhető; a bővítéspolitika folytatásához elengedhetetlen az EU működési-intézmény struktúrájának átalakítása, valamint a csatlakozni kívánó országok belső reformfolyamatainak véghezvitele. Ukrajna integrálásának kérdése, illetve a kül- és biztonságpolitikai kérdésekben minősített többségi szavazásra való áttérés körüli viták ezt a meglehetősen bonyolult mátrixot még bonyolultabbá teszik. Az elkövetkező hónapokban szükséges lesz megtenni az első lépéseket a 2030-ra történő felkészüléshez, mielőtt a 2024-es európai és amerikai „szuperválasztási év” több hónapra elvonná ezen kérdésekről a figyelmet.
Penerapan Metode K-Means Clustering Dalam Pengembangan Strategi Promosi Berbasis Data Penerimaan Mahasiswa Baru (Studi Kasus :Universitas Nurul Huda)
Authors: Indra Indra Irawan , Rizki Uli , Jakak Pamuji M. , Prayogi M. Bagus , Rahman Miftakhul
Published: February 2024

The admission of new students is a key element in the success of a university. In its effort to enhance efficiency in admitting new students, Nurul Huda University proposes applying the K-Means Clustering method as a solution to manage candidate student data more effectively and intelligently. The data used in this research is derived from the Admission of New Students process for the academic years 2021/2022 and 2022/2023, totaling 1275 entries, which will then be processed using data mining techniques to generate analysis. The goal is to determine promotional strategies based on the origin of profiles of newly enrolled students. The method applied is clustering with the K-Means algorithm. After data processing, analysis is conducted using the Knowledge Discovery in Databases (KDD) technique, consisting of five stages: selection, preprocessing, transformation, data mining, and evaluation. The implementation in this research utilizes Rapidminer software, resulting in three data clusters: Cluster 1 with 345 entries, covering 27% of the total; Cluster 2 with 86 entries (7%); and Cluster 3 with 835 entries (66%). For promotion, the marketing team is deployed to districts dominant in the East OKU region and potential areas outside the East OKU District. They conduct direct visits to introduce Nurul University to students, distribute brochures, display pamphlets, and adapt strategies using a promotion mix strategy
PENDEKATAN SAINTIFIK DALAM PEMBELAJARAN IPA SEBAGAI UPAYA MENINGKATKAN AKTIFITAS DAN HASIL BELAJAR SISWA KELAS IX B SMPN 6 REJANG LEBONG
Authors: Handayani Fitri
Published: February 2024

Jenis penelitian ini adalah penelitian tindakan kelas (Classroom Action Researct). Subjek penelitian adalah siswa kelas IX B SMP Negeri 6 Rejang Lebong sebanyak 32 orang dengan jumlah siswa laki-laki 15 orang dan siswa perempuan 17 orang. Kelas tersebut adalah kelas reguler pada umumnya yaitu kelas yang diselenggarakan tanpa perlakuan khusus seperti kelas unggul dan sebagainya. Lokasi penelitian yaitu di kelas IXB SMP Negeri 6 Rejang Lebong yang berada di Desa Kesambe Lama Kecamatan Curup Timur Kabupaten Rejang Lebong Propinsi Bengkulu. Waktu pelaksanaan penelitian tindakan kelas dilaksanakan pada bulan Januari sampai dengan Maret 2023 selama 3 bulan. Teknik pengumpulan data dengan teknik observasi, dokumentasi dan tes. Teknik analisis data menggunakan analisis data observasi dan data tes. Hasil penelitian adalah Pendekatan saintifik dapat meningkatkan aktifitas belajar IPA Siswa kelas IX SMPN 6 Rejang Lebong Hal ini terlihat dari pengamatan ketrampilan saintifik siswa yang meningkat yaitu pada siklus I rata-rata keaktifan siswa sebesar 45%, siklus II sebesar 63,75% dan siklus III sebesar 80,65%. Pendekatan saintifik dapat meningkatkan hasil belajar IPA Siswa kelas IX SMPN 6 Rejang Lebong Hal ini terlihat dari pengamatan ketuntasan hasil belajar pada siklus I sebesar 43,75%, siklus II sebesar 62,5% dan siklus III sebesar 87,5%.
MODEL PEMBELAJARAN KOOPERATIF TIPE BAMBOO DANCING UNTUK MENINGKATKAN HASIL BELAJAR MATEMATIKA SISWA KELAS VIII D SMP NEGERI 4 REJANG LEBONG
Authors: Husnety Husnety
Published: February 2024

Penelitian ini adalah Penelitian Tindakan Kelas (PTK) atau Classroom Action Research (CAR). Subyek penelitian yang akan dilakukan peneliti adalah siswa kelas VIII D SMP Negeri 4 Rejang Lebong Tahun Ajaran 2022/2023 yang berjumlah 32 siswa. Obyek dalam penelitian ini adalah strategi pembelajaran Bamboo Dancing dalam meningkatkan hasil belajar Matematika di kelas VIII D SMP Negeri 4 Rejang Lebong Tahun Ajaran 2022/2023. Data yang digunakan dalam penelitian ini berupa data hasil observasi dan data hasil belajar siswa. Hasil penelitian adalah model pembelajaran kooperatif tipe bamboo dancing dapat meningkatkan motivasi belajar matematika siswa kelas VIII D SMP Negeri 4 Rejang Lebong, hal ini terlihat pada pembelajaran pra siklus kriteria motivasi sedang, siklus I motivasi baik dan siklus II amat baik. Model pembelajaran kooperatif tipe bamboo dancing dapat meningkatkan hasil belajar matematika siswa kelas VIII D SMP Negeri 4 Rejang Lebong, hal ini terlihat dimana rata-rata hasil belajar pada pra siklus sebesar 56,75 meningkat pada siklus I sebesar 67,5 dan siklus II sebesar 75,5.
UPAYA MENINGKATKAN KETERAMPILAN PROSES SAINS DAN HASIL BELAJAR SISWA MELALUI PENERAPAN MODEL PEMBELAJARAN GUIDED DISCOVERY DI KELAS IV SDN 43 REJANG LEBONG
Authors: Sulastri Sulastri
Published: February 2024

Latar belakang pada penelitian ini adalah ketertarikan peneliti untuk meningkatkan kualitas pembelajaran IPA di dalam kelas. Penelitian ini bertujuan untuk membuktikan apakah penerapan model pembelajaran guided discovery dapat meningkatkan keterampilan proses sains dan hasil belajar siswa. Penelitian ini menggunakan desain penelitian tindakan kelas dengan empat tahapan penelitian, yakni tahap perencanaan, tahap pelaksanaan, tahap observasi, dan tahap refleksi. Subjek penelitian ini adalah siswa kelas IV SD Negeri 43 yang terdiri dari 29 orang siswa. Hasil penelitian menunjukkan bahwa penerapan model pembelajaran guided discovery terbukti mampu meningkatkan keterampilan proses sains siswa dimana pada fase prasiklus, persentase tingkat keterampilan proses sains siswa sebesar 31,03%, meningkat di siklus I sebesar 55,17% dan meningkat pada siklus II sebesar 82,76%. Penerapan model pembelajaran guided discovery juga terbukti mampu meningkatkan hasil belajar siswa dimana pada fase prasiklus, tingkat ketuntasan klasikal siswa sebesar 34,48%, meningkat pada siklus I menjadi sebesar 62,07% dan pada siklus II meningkat menjadi sebesar 86,21%.
PENERAPAN MODEL PEMBELAJARAN QUANTUM LEARNING UNTUK MENINGKATKAN MINAT BELAJAR DAN HASIL BELAJAR PJOK SISWA KELAS V SD NEGERI 43 REJANG LEBONG
Authors: Misbahayati Misbahayati
Published: February 2024

Jenis penelitian yang digunakan dalam penelitian ini adalah penelitian tindakan kelas. Desain penelitian yang digunakan dalam penelitian tindakan mengacu pada model penelitan yang dikembangkan oleh Kemmis & Taggart. Penelitian ini dilaksanakan sebanyak 3 siklus dan masing-masing siklus dilaksanakan melalui tahap-tahap perencanaan, pelaksanaan, observasi, dan refleksi. Subjek penelitian ini adalah siswa kelas V SD Negeri 43 Rejang Lebong dengan jumlah siswa sebanyak 22 orang. Waktu penelitian dilaksanakan selama 3 bulan dari bulan Agustus 2022 hingga bulan Oktober 2022. Hasil penelitian penerapan model pembelajaran Quantum Learning dapat meningkatkan minat belajar siswa dimana siswa yang memiliki tingkat minat tinggi meningkat pada siklus I sebesar 40,91%, pada siklus II sebesar 63,64% dan pada siklus III sebesar 90,91%. Model pembelajaran Quantum Learning juga dapat meningkatkan hasil belajar PJOK siswa kelas V SD Negeri 43 Rejang Lebong dimana ketuntasan belajar klasikal meningkat yaitu pada siklus I sebesar 45,45%, pada siklus II sebesar 63,64%, dan pada siklus III sebesar 90,91%.
MODEL PENGEMBANGAN PERMAINAN BOLA BASKET DENGAN MENGGUNAKAN POLA KONSEP CIRCUIT TRAINING BALL DI SMPN 1 REJANG LEBONG
Authors: Dermawansyah Dermawansyah
Published: February 2024

Penelitian ini adalah penelitian dengan metode pengembangan. Menurut Borg dan Gall (1983) dalam buku Punaji Setyosari, penelitian pengembangan adalah suau proses yang digunakan untuk mengembangkan atau memvalidasi produk yang digunakan dalam pendidikan. Subjek penelitian adalah siswa kelas VII B SMPN 1 Rejang Lebong yang berjumlah 34 siswa. Analisis data yang digunakan dalam penelitian pengembangan ini adalah menggunakan teknik analisis berbentuk deskriptif presentase. Sedangkan data yang berupa saran dan alasan dalam memilih jawaban dianalisis menggunakan teknik analisis kualitatif. Pengembangan model permainan bola basket dengan model pembelajaran circuit basketball pada siswa kelas VII B SMPN 1 Rejang Lebong dapat memenuhi kriteria baik dan layak untuk siswa hal ini dapat dilihat pada hasil analisis data uji coba lapangan pada skala kecil sebanyak 10 siswa rata-rata sebesar 85,00 (%), skala besar rata-rata sebesar 88,25(%) peningkatan progresif sebesar 0,25(%). Pengembangan model permainan bola basket dengan model pembelajaran circuit basketball pada siswa kelas VII B SMPN 1 Rejang Lebong layak memenuhi aspek kognitif dan psikomotor dimana hasil analisis data uji coba tim ahli yaitu aspek kognitif sebesar 85,00(%),aspek psikomotor sebesar 81, 36(%) peningkatan progresif sebesar 3,59(%).
PENINGKATAN KEMAMPUAN GURU DALAM MEMANFAATKAN LINGKUNGAN SEKOLAH SEBAGAI SUMBER BELAJAR MELALUI KELOMPOK KERJA GURU DI SD NEGERI 25 REJANG LEBONG SEMESTER I TAHUN PELAJARAN 2022/2023
Authors: Hasanah Hasanah
Published: February 2024

Penelitian ini bertujuan untuk mendeskripsikan proses Memanfaatkan Lingkungan Sekitar Sebagai Sumber Belajar Melalui Diskusi Kelompok Kerja Guru Semester I Tahun Pelajaran 2022/2023 di SD Negeri 25 Rejang Lebong . Penelitian ini didasari oleh karena selama ini semua guru kelas dan guru mata pelajaran di SD Negeri 25 Rejang Lebong jarang dan bahkan tidak pernah memanfaatkan alam sekitar sebagai sumber belajar, hal ini disebabkan oleh kurangnya pemahaman dan kemampuan guru untuk memanfaatkan alam sekitar sebagai sumber belajar. Setelah diberikan tindakan pada pelaksanaan penelitian ini melalui siklus I, ada peningkatan kemampuan guru-guru di SD Negeri 25 Rejang Lebong . dalam memanfaatkan alam sekitar sebagai sumber belajar. Dari 8 orang guru yang terlibat, 1 orang guru sudah mendapat skor dengan katagori “baik” dan 4 orang dengan katagori “cukup” sedangkan 3 orang dengan katagori “kurang”. Oleh karena itu dilanjutkan dengan tindakan siklus II yang hasilnya secara umum ada peningkatan ke arah yang lebih baik yaitu 100% guru sudah mendapatkan katagori baik dengan skor rata-rata 80–100. Hal ini sudah sesuai dengan kriteria keberhasilan yang ditetapkan. Secara rinci perolehan nilai rata-rata peningkatan kemampuan guru memanfaatkan alam sekitar sebagai sumber belajar yaitu nilai rata-rata observasi hasil kegiatan diskusi 66 di siklus I menjadi 85 di siklus II ada peningkatan 19%, kegiatan penyusunan skenario pembelajaran nilai rata-rata 73,13 di siklus I menjadi 93,75 di siklus II ada peningkatan 20,62%, kegiatan pembelajaran atau dalam proses belajar mengajar nilai rata-rata 72,88 di sklus I menjadi 95 di siklus II, ada peningkatan 22,12%. Penelitian ini membuktikan kebenaran hipotesis bahwa: Melalui diskusi kelompok dapat meningkatkan kemampuan guru SD Negeri 25 Rejang Lebong dalam memanfaatkan alam sekitar sebagai sumber belajar di SD Negeri 25 Rejang Lebong.
Ilmuan Kimia Dalam Sejarah Islam Terhadap Perkembangan Sains
Authors: Jami' Jami'
Published: February 2024

Perkembangan ilmu kimia yang sampai sekarang masih terus dikembangkan dengan berbagai manfaatnya. Cendekiawan Islam tidak kalah dengan cendekiawan Barat dalam menyumbangkan berbagai penemuannya sebagai sebuah kontribusi yang sangat penting dalam dunia kimia. Jabir Ibnu Hayyan salah satu cendekiawan Muslim dalam bidang Kimia dengan berbagai penemuannya salah satunya teori hukum perbandingan tetap. Selain Jabir ibnu Hayyan ada beberapa cendekiawan Muslim yang berpengaruh dengan perkembangan ilmu sains lainnya seperti Ibnu Sina dan Al- Zahrawi bidang Kedokteran, Al-Khawarizmi di bidang Matematika, Ibnu Haitham bidang Optik, Al Battani bidang Astronomi, dan masih banyak cendekiawan lainnya. Penting sekali untuk menelusuri sejarah keilmuan oleh tokoh-tokoh Islam sebagai motivasi dalam melanjutkan kontribusi mereka dibidang keilmuan masing-masing.
Urgensi Literasi dalam Pembelajaran Bahasa Indonesia Era Industri 4.0 di MTSN 2 Tanjung Jabung Timur
Authors: Sargiyo Sargiyo
Published: February 2024

Pendidikan 4.0 sebuah program untuk mendukung terwujudnya pendidikan cerdas melalui peningkatan dan pemerataan kualitas pendidikan, perluasan akses,dan relevansi memanfaatkan teknologi dalam mewujudkan pendidikan kelas dunia. Tujuannya untuk menghasilkan siswa yang memiliki keterampilan kolaborasi, komunikasi, berpikir kritis, dan kreatif. Di era ini diperlukan kemampuan literasi, baik literasi lama maupun literasi baru. Tujuan utama pembelajaran literasi mengembangkan kompetensi siswa sebagai komunikator yang kompeten dalam konteks multiliterasi, multikultural,dan multimedia melalui pemberdayaan multiintelegensi. Guru dalam pembelajaran bahasa Indonesia harus mampu mendesain proses pembelajaran menjadi kekinian, kontekstual, dengan menekankan pada penguatan kompetensi literasi lama, namun harus berwawasan pada penguatan literasi baru yang menyatu dalam penguatan empat keterampilan berbahasa. Pembelajaran bahasa Indonesia yang berwawasan literasi baru dengan penguatan literasi lama akan berhasil dengan baik bila guru dan dosen bahasa Indonesia berwawasan literasi baru. Ada lima kualifikasi dan kompetensi guru yang dibutuhkan di era 4.0. yaitu educational competence, kompetensi mendidik/pembelajaran berbasis internet of thing sebagai basic skill, competence for technological commercialization,competence in globalization, competence in future strategies, dan conselor competence.
Urgensi Pendidikan Akhlak Budi Pekerti Sebagai Pondasi dalam Perspektif Islam
Authors: Asih Sri
Published: February 2024

Menanamkan pendidikan Islam pada anak sejak dini berarti ikut mempersiapkan generasi bangsa yang berkarakter, anak-anak adalah calon generasi bangsa yang diharapkan mampu memimpin bangsa dan menjadikan negara yang berperadaban, menjunjung tinggi nilai-nilai luhur bangsa dengan berakhlak mulia serta menjadi generasi yang berilmu pengetahuan dan bertakwa kepada Tuhan Yang Maha Esa.. Oleh karena itu pembelajaran pendidikan agama Islam di sekolah sebagai salah satu upaya pembentukan karakter siswa sangatlah penting. Pembentukan karakter anak akan lebih baik jika muncul dari kesadaran keberagamaan bukan hanya karena sekedar berdasarkan prilaku yang membudaya dalam masyarakat. Dalam mengacu pada perilaku, sikap, dan moralitas seseorang. Akhlak mencakup aspek etika, moralitas, dan tata krama yang diatur oleh ajaran agama Islam. Akhlak adalah bagian penting dari ajaran Islam yang melibatkan hubungan antara manusia dengan Allah dan hubungan antara manusia dengan sesama manusia. Caranya adalah terus berusaha untuk selalu ber-akhlakul karimah sebagaimana sudah dicontohkan oleh Rasulullah seperti tawadlu, lemah lembut, sabar, berbuat berbuat baik kepada orang yang berbuat buruk, dan lain sebagainya. Akhlak yang baik akan menjadi benteng, akan menjadi perisai atau pelindung dalam setiap langkah kehidupan. Sehingga, manusia tidak akan berbuat dosa. Hasilnya, pembangunan disemua bidang akan stabil.
Peran Bahasa Inggris dan Bahasa Indonesia Sebagai Alat yang Penting di Era Globalisasi
Authors: Supena Supena
Published: February 2024

Bahasa di era global menjadi alat komunikasi yang sangat penting begitu juga dalam bidang ilmu pengetahuan. Bahasa Indonesia berfungsi sebagai bahasa nasional. Selain itu, bahasa Indonesia juga berfungsi sebagai bahasa ilmu sehingga digunakan sebagai bahasa pengantar disemua lembaga pendidikan di Indonesia. Bahasa Inggris sebagai bahasa internasional dengan pengguna terbanyak juga turut andil dalam pertukaran ilmu pengetahuan global. Penggunaan bahasa Inggris dalam penulisan berbagai sumber pustaka dan karya ilmiah menjadikan bahasa Inggris bahasa yang penting dalam bidang IPTEK. Penggunaan bahasa Indonesia tidak lepas dari adanya tantangan. Tantangan tersebut berasal dari dalam maupun dari luar. Starategi yang dilakukan untuk mengatasi tantangan ialah menumbuhkan sikap positif terhadap bahasa Indonesia. Masyarakat secara emosional sadar bahwa perilaku berbahasa tidak terkait dengan nasionalisme sehingga banyak orang lebih gemar menggunakan bahasa asing. Tantangan lainnya ialah persoalan tata istilah dan ungkapan ilmiah yang lebih sering mengadopsi bahasa asing. Strategi untuk mengatasi tantangan tersebut antara lain garis haluan kebahasaan; pengembangan bahasa; dan pembinaan bahasa; serta cakupan perencanaan bahasa. Adanya sikap positif terhadap bahasa Indonesia pun perlu ditingkatkan guna mentasi masalah tersebut yaitu (1) sikap kesetiaan berbahasa Indonesia dan (2) sikap kebanggaan berbahasa Indonesia.
Актуальность концепции «Цифровой университет»: литературный обзор отечественных и зарубежных исследований
Authors: Маматова Г. Д. , Кучкаров Т. С.
Published: February 2024

В данном исследовании представлены основные направления совершенствования методологии использования передовых информационно-коммуникационных технологий в статистическом секторе Республики Узбекистан и других стран мира в условиях цифровой экономики. Исследование определяет степень использования цифровых технологий для развития учебно-методического процесса, а также эффективность внедрения цифровых технологий во всех высших учебных заведениях. В ходе исследования было изучено 120 статей из более 45 стран мира. Цель исследования заключается в проведении анализа современных теоретических подходов к раскрытию понятия и сущности цифровых университетов и демонстрации читателям актуальности концепции «Цифровой университет». Применяются методы систематического обзора литературы, руководствуясь исследовательскими вопросами, чтобы выделить исследования, посвященные моделям зрелости во всем мире, определить компоненты Цифрового университета и его влияние на рост эффективности цифровой экономики. Результаты исследования направлены на сокращение времени предоставления актуальных услуг, перевод образовательных услуг по многим дисциплинам в цифровой режим, снижение затрат и обновление материально-технических условий для осуществления основной деятельности вузов, обеспечение передачи знаний за счет создания единой среды, содействие занятости и повышение мотивации студентов. Научная новизна исследования заключается в том, что систематизация методологического подхода к выражению концепции «цифровой университет» в процессе анализа влияния времени на проектирование и исследование цифровых систем и стабильности цифровых технологий стала очевидной проблемой отсутствия целостного подхода с участием преподавателей, студентов и представителей цифровой среды трех университетов. Главная задача - сэкономить время читателя и познакомить с основными сведениями по данной тематике. Делается вывод о том, что в недалеком будущем традиционная университетская система полностью трансформируется в цифровую среду. Основные выводы и рекомендации обобщены в рекомендациях авторов.
Finite Element Analysis for the Free Vibration of a Rigid Pavement resting on a Non-uniform Elastic Foundation
Authors: Anh Bui Tuan , Hiep Nguyen Trong , Vinh An Le , Lap Nguyen Van
Published: February 2024

This paper presents a finite element analysis of the free vibration behavior of rigid pavements resting on non-uniform foundations. The rigid pavement was modeled using the Mindlin plate theory, while the supporting soil medium was approximated by a Winkler model with non-uniform stiffness. A finite element formulation was established to govern the equation of free vibration for rigid pavements. Subsequently, a computer program was developed based on the proposed algorithm, enabling the determination of natural frequencies and mode shapes. The accuracy of the proposed method was verified by comparing numerical examples of free vibration with analytical results. These numerical examples also demonstrate the significant influence of the foundation stiffness on natural frequencies and mode shapes.
Deep-Learning-based Cryptanalysis through Topic Modeling
Authors: Kumar Kishore , Tanwar Sarvesh , Kumar Shishir
Published: February 2024

Neural cryptography is a technique that uses neural networks for secure data encryption. Cryptoanalysis, on the other hand, deals with analyzing and decrypting ciphers, codes, and encrypted text without using a real key. Chosen-plaintext cryptanalysis is a subfield of cryptanalysis where both plain text and ciphertext are available and the goal is either to find the encryption technique, the encryption key, or both. This study addresses chosen plaintext cryptanalysis within public key cryptography, to categorize topics of encrypted text. Using a fixed encryption technique and key, the focus was placed on creating a framework that identifies the topic associated with ciphertext, using diverse plaintexts and their corresponding cipher texts. To our knowledge, this is the first time that chosen-plaintext cryptanalysis has been discussed in the context of topic modeling. The paper used deep learning techniques such as CNNs, GRUs, and LSTMs to process sequential data. The proposed framework achieved up to 67% precision, 99% recall, 80% F1-score, and 71% AUPR on a dataset, showcasing promising results and opening avenues for further research in this cryptanalysis subarea.
Making Different Topographic Maps with the Surfer Software Package
Authors: Ali Amal Mahdi
Published: February 2024

The main objective of this study is to describe the preparation of topographic maps using the Surfer software. A total of 159 regularly distributed Ground Control Points (GCPs) were collected with the use of the Differential Global Positioning System (DGPS). Seven methods (Contour Map, Post Map, 3D Surface Map, 3D Wireframe Maps, Grid Vector-1 Map, Color Relief Map, and Shaded Relief Maps) at the Surfer environment were used to prepare the topographic maps at the Mukhtar Village near the Al-Fallujah City. Contour lines with other features were superimposed on the DEM layer, which refers to the topography of the terrain inside this study area. The accuracy of the database's results was estimated, essential maps were given, and the results were efficient and effective. The most appropriate method to represent topographic maps was proposed, each of these techniques has been enough to provide us with a general understanding of the subject area.
Evaluation of Energy Renovation Measures for Hospital Buildings using the PSI Method
Authors: Kadric Dzana , Blazevic Rejhana , Bajric Hadis , Kadric Edin
Published: February 2024

This study investigated the potential for energy savings and reduction in CO2 emissions in hospital buildings in Bosnia and Herzegovina (B&H), through the implementation of energy renovation measures. The building sector in B&H is characterized by significant energy consumption, and hospitals account for a substantial portion of the total energy consumption in public buildings. This study analyzes certain energy renovation measures for selected hospital buildings, including the installation of thermal insulation on exterior walls and flat roofs, and the installation of a photovoltaic plant on the flat roof. The Preference Selection Index (PSI) multicriteria decision-making method was employed to evaluate and rank renovation scenarios based on energy, environmental, and financial criteria. The results indicate that the most preferred measure is the installation of a photovoltaic plant on a flat roof, resulting in significant primary energy and CO2 savings, with an acceptable discounted payback period. The findings emphasize the effectiveness of energy renovation measures in enhancing energy efficiency and reducing the environmental impact of hospital buildings in B&H.
Advancing Cloud Image Security via AES Algorithm Enhancement Techniques
Authors: Mohammed Zahraa A. , Gheni Hadeel Qasem , Hussein Zahraa Jabbar , Al-Qurabat Ali Kadhum M.
Published: February 2024

Communication system and internet dominance in our society, has made image security a matter of paramount concern. Cryptography involves encrypting data to protect information exchange between senders and receivers, establishing a foundation for secure communication. The Advanced Encryption Standard (AES) is an exceptional algorithm that plays a pivotal role in this area because of its ability to consistently transform plain data into cipher data using the same encryption key. This algorithm engages intricate encryption techniques, harnessing a variety of algorithms and transformations to ensure robust data security. This study introduces an image encryption technique to comprehensively address security requirements. The proposed method uses the AES algorithm to provide high reliability and unparalleled safety, effectively protecting precious images against any form of malicious attack. The sender's image is intelligently fragmented into multiple pieces to maximize data confidentiality, employing a sophisticated algorithm. Upon decryption by the intended recipient, these fragments seamlessly merge to reconstruct the original image. The suggested technique allows users to securely store their data in the cloud, mitigating concerns related to potential data leakage, damage, or corruption. Thus, by integrating a cloud-based storage system, and utilizing digital signatures through OpenSSL, this method guarantees airtight security and reliability for sensitive data.
Enhanced Skin Cancer Classification using Deep Learning and Nature-based Feature Optimization
Authors: Imran Talha , Alghamdi Ahmed S. , Alkatheiri Mohammed Saeed
Published: February 2024

This paper presents a skin cancer classification model that combines a pre-trained Convolutional Neural Network (CNN) with a nature-inspired feature optimization algorithm. A custom dataset comprising both malignant and benign skin cancer microscopic illustrations is derived from the ISIC dataset of dermoscopic images. Several preprocessing steps are performed on the input pictures, such as histogram equalization, gamma correction, and white balance adjustment, to improve visibility, quality, and make color corrections. Deep feature extraction and pattern recognition are conducted on both enhanced and original dataset images using the pre-trained CNN model EfficientNetB0. As a result of fusing these features, the model can capture rich details from both dataset versions at the same time. Ant Colony Optimization (ACO), a nature-inspired feature selection algorithm is applied to perform model optimization by keeping the most relevant features and discarding the unnecessary ones. The optimized feature vector is then used with various SVM classifier kernels for the skin cancer classification task. The maximum achieved accuracy of the proposed model exceeded 98% through CB-SVM while maintaining an excellent prediction speed and reduced training time.
Fracture Analysis of a Cycloidal Gearbox as a Yaw Drive on a Wind Turbine
Authors: Martins Jairo Aparecido , Romao Estaner Claro
Published: February 2024

Fast growth of renewable energies has required addressing challenges such as generating the largest energy production possible throughout the equipment's lifespan and between its preventive and corrective maintenance intervals. Actions such as preventive maintenance, and improvement of the main components, mainly when it comes to reliability and predictability are of extreme importance to reach maximum generation. Due to the importance of the yaw drives for wind turbines, this paper aims to evaluate a failure that occurred on a cycloidal gearbox used in a drive of this kind. For the evaluation of the yaw drive, all the components were analyzed to determine the incurred fracture mechanism. Such analysis was performed by mapping all components, conducting a hardness test to check the components' mechanical properties, analysis of the fractured surfaces of the cycloidal disc, and numerical simulation (linear elastic) via the Finite Element Method (FEM) to check the stress distribution on the fractured part (cycloidal disc) under load, and theoretical calculation of the cycloidal disc lifespan. In addition, the stress distribution by FEM was compared with the broken regions of the physical part. To sum up, after all the evaluations, it is possible to claim the results demonstrate there was a premature fracture of the cycloidal disc that occurred due to the phenomenon of high cycle fatigue.
Analyzing Embankment Displacement: PVD and Vacuum Consolidation with Sheet Pile Protection
Authors: Nguyen Trong Nghia , Nguyen Xuan Khanh , Vo Nguyen Phu Huan
Published: February 2024

The global widespread adoption of Prefabricated Vertical Drains (PVD) in conjunction with vacuum consolidation is driven by its robust and cost-efficient attributes. However, this construction method is not without challenges, as it has been linked to substantial displacements, posing risks to adjacent structures. Addressing such concerns in a Vietnamese road construction project, this study focuses on the innovative contribution of sheet pile protection as a highly effective solution. Utilizing numerical analysis with an anisotropic model, we examine the impact of sheet pile protection on embankment displacement. Through comparative analysis with field data, our study demonstrates the remarkable efficacy of the sheet pile method in significantly reducing both vertical and lateral settlements. Acting as a protective membrane, it effectively counters suction from the PVD vacuum zone. These findings make a substantial contribution to the field, providing engineers handling similar structural protection scenarios with invaluable insights and a novel approach to mitigating displacements associated with PVD and vacuum consolidation.
Optimal FLC-Sugeno Controller based on PSO for an Active Damping System
Authors: Nguyen Hoang Viet , Deng Feiqi , Nguyen Tien-Duy
Published: February 2024

In this paper, a method for the design of an optimal Sugeno model (FLC-Sugeno) fuzzy logic controller for the active suspension system of quarter-vehicle models is presented. The parameters of the FLC-Sugeno controller are optimally searched, using the Particle Swarm Optimization (PSO) algorithm. The 16 optimized parameters include 3 parameters for adjusting the domain of the input state variables and control variables at the controller’s output, 4 fuzzy set adjustment numbers of the linguistic variables, and 9 parameters as the fuzzy rule weights of the rule system control. To compare and evaluate the effectiveness of the optimal FLC-Sugeno controller, an optimal PID controller using PSO is also implemented. Simulation results of the active damping system with the controllers when affected by the same type and standard road surface excitation show that the FLC-Sugeno controller is optimal for the quick ending of the oscillations of vehicle body displacement. The result shows that the proposed controlling scheme can be extended and applied to more complex active damping system models.
Prediction of Vehicle-induced Air Pollution based on Advanced Machine Learning Models
Authors: Matara Caroline , Osano Simpson , Yusuf Amir Okeyo , Aketch Elisha Ochungo
Published: February 2024

Vehicle-induced air pollution is an important issue in the 21st century, posing detrimental effects on human health. Prediction of vehicle-emitted air pollutants and evaluation of the diverse factors that contribute to them are of the utmost importance. This study employed advanced tree-based machine learning models to predict vehicle-induced air pollutant levels, with a particular focus on fine particulate matter (PM2.5). In addition to a benchmark statistical model, the models employed were Gradient Boosting (GB), Light Gradient Boosting Machine (LGBM), Extreme Gradient Boosting (XGBoost), Extra Tree (ET), and Random Forest (RF). Regarding the evaluation of PM2.5 predictions, the ET model outperformed the others, as shown by MAE of 1.69, MSE of 5.91, RMSE of 2.43, and R2 of 0.71. Afterward, the optimal ET models were interpreted using SHAP analysis to overcome the ET model's lack of explainability. Based on the SHAP analysis, it was determined that temperature, humidity, and wind speed emerged as the primary determinants in forecasting PM2.5 levels.
Applying the Analytical Hierarchy Process to Identify the Challenges and Priorities of Reconstruction Projects in Iraq
Authors: Altaie Meervat R. , Dishar Marwaa D.
Published: February 2024

Reconstruction project management in the cities of Mosul, Anbar, and Tikrit, in Iraq still faces major obstacles that impede the comprehensive performance of these projects. It is thus necessary to improve the arising challenge estimation in the implementation of reconstruction projects and evaluate their components: time, cost, quality, and scope. This study used the Analytical Hierarchy Process (AHP) to prioritize major and minor criteria in the influential causes of challenges and formulate a mathematical model to help decision-makers estimate them. Using the Super Decisions software, the final results indicated that changes in scope reached 40.8%, which is the greatest difficulty, followed by changes in cost at 27.6%, changes in time at 13.5%, and changes in quality at 18.11%. The results of the essential subcriteria also indicated that underlying issues still exist in the Iraqi construction industry and that quick solutions are vital. Five mathematical equations were formulated to develop a model to estimate changes that introduce challenges in time, cost, quality, and scope and so to help decision-makers assess the level of these changes and identify challenges. This study recommended addressing these variables through realistic administrative and methodological strategies to consider changes, challenges, and available opportunities.
Optimizing Machine Learning Classifiers for Enhanced Cardiovascular Disease Prediction
Authors: Alanazi Sultan Munadi , Khamis Gamal Saad Mohamed
Published: February 2024

A key challenge in developing Machine Learning (ML) models for predicting or diagnosing Cardiovascular Disease (CVD), is selecting suitable algorithms and fine-tuning their parameters. In this study, we employed three ML techniques, namely Auto-WEKA, Decision Table/Naive Bayes (DTNB), and Multiobjective Evolutionary (MOE) fuzzy classifier to create diagnostic models using the Heart Disease Dataset from IEEE Dataport. Auto-WEKA generated a highly accurate model with a 100% success rate through optimal classifier selection and hyperparameter configuration. The DTNB classifier yielded a satisfactory 85.63% prediction accuracy concerning patients' risk levels. Further refinements, though, could help reduce possible misclassifications. Finally, the MOE fuzzy classifier achieved approximately 81.6% accuracy, indicating the potential for enhancing precision and recall values by adjusting classifier settings. Our findings underscore the promise of ML tools in CVD diagnosis and suggest further optimization of classifier parameters for superior performance.
CONCEPTUAL FOUNDATIONS OF THE GREEN AGENDA
Authors: Gostieva N. K. , Volkova K. S.
Published: February 2024

Solving environmental problems has been one of the most urgent tasks for both the scientific community and the world’s population in recent decades. Carbon emissions lead to climate change, which, along with environmental pollution, reduces biodiversity, leads to degradation of water and soil. The article discusses theoretical approaches to the green agenda and the resulting practical recommendations on regulating the activities of economic entities. Special attention is paid to the relationship between developed and developing countries, between which the environmental burden is distributed unevenly. Authors also propose ways of economic development aimed at increasing the welfare of the population and reducing the burden on the environment.
An Algorithm for Activity Recognition and Assessment of Adults Poststroke
Authors: Proffitt Rachel , Rasmussen Kial-Ann M. , Ma Mengxuan , Skubic Marjorie
Published: February 2024

Importance: Stroke is the leading cause of long-term disability in the United States. Providers have no robust tools to objectively and accurately measure the activity of people with stroke living at home.

Objective: To explore the integration of validated upper extremity assessments poststroke within an activity recognition system.

Design: Exploratory descriptive study using data previously collected over 3 mo to report on algorithm testing and assessment integration.

Setting: Data were collected in the homes of community-dwelling participants.

Participants: Participants were at least 6 mo poststroke, were able to ambulate with or without an assistive device, and self-reported some difficulty using their arm in everyday activities.

Outcomes and Measures: The activity detection algorithm’s accuracy was determined by comparing its activity labels with manual labels. The algorithm integrated assessment by describing the quality of upper extremity movement, which was determined by reporting extent of reach, mean and maximum speed during movement, and smoothness of movement.

Results: Sixteen participants (9 women, 7 men) took part in this study, with an average age of 63.38 yr (SD = 12.84). The algorithm was highly accurate in correctly identifying activities, with 87% to 95% accuracy depending on the movement. The algorithm was also able to detect the quality of movement for upper extremity movements.

Conclusions and Relevance: The algorithm was able to accurately identify in-kitchen activities performed by adults poststroke. Information about the quality of these movements was also successfully calculated. This algorithm has the potential to supplement clinical assessments in treatment planning and outcomes reporting.

Plain-Language Summary: This study shows that clinical algorithms have the potential to inform occupational therapy practice by providing clinically relevant data about the in-home activities of adults poststroke. The algorithm accurately identified activities that were performed in the kitchen by adults poststroke. The algorithm also identified the quality of upper extremity movements of people poststroke who were living at home.