bluuebunny/crossref_metadata_2025 huggingface dataset:
Leveraging Convolutional Neural Networks for Face Mask Detection
Authors: Adhikari Smita
Published: January 2025

In response to the widespread use of face masks for safety, security, and health reasons, the development of automated systems for face mask detection has garnered significant attention. This research addresses binary face mask detection by leveraging Convolutional Neural Networks (CNNs) to create a specialized model. Using a Kaggle dataset, preprocessing steps including image resizing and color space conversion are applied for standardized data. The method entails a purpose-built CNN architecture comprising multiple convolutional layers with ReLU (Rectified Linear Unit) activations and max pooling for efficient feature extraction and spatial information capture. Further bolstering the architecture, fully connected layers coupled with dropout layers mitigate overfitting risks, enhancing generalization. The final sigmoid-activated output layer facilitates precise binary classification, distinguishing individuals with or without masks. Training guided by the Adam optimizer ensures parameter optimization based on accuracy metrics. This work contributes a meticulously designed CNN architecture optimized for face mask detection, showcasing robust feature extraction, spatial complexity handling, and overfitting mitigation, thereby presenting a potent solution with broad implications across industries for safety and public health measures. By aligning technology with societal needs, the research aids diverse industries in integrating automation and Artificial Intelligence for mask-wearing compliance. The findings underscore mask detection's pivotal role in overcoming challenges for safer environments.
Analyzing the Accessibility of Trolley Bus Stops in the City of Salzburg
Authors: Subedi Sushmita , Pandit Roman
Published: January 2025

Public transport promotes sustainable mobility by enhancing connectivity, safety, comfort and health. The location, type, condition and spacing of stops play a pivotal role in determining the accessibility to public transport. Poor accessibility to public transport can lead to increased cost and time of travel, poor mobility, traffic congestion and social exclusion. This study uses Multi Criteria Analysis to provide a holistic measure of accessibility in terms of Transit Accessibility Index (TAI) for all the trolley bus stops in the city of Salzburg. Five quantitative indicators are combined and weighted appropriately to obtain the final accessibility score. An overall accessibility assessment is performed to further classify the bus stops into five performance categories based on their final accessibility score. Ideal Point Method is employed to determine the values of indicators for the ideal bus stop and compare the values with those of the existing stops. The result from the analysis shows that the most accessible trolley bus stops are located in the core region of Salzburg city near the city center and the main train station. This kind of analysis is crucial for sustainable transport planning and thus helps to promote smart mobility and better habitability of the city.
The Influence Of Perceived Transformational Leadership Style And Job Satisfaction On Organizational Commitment In Teacher
Authors: Previarzya Realita Sereen , Thamrin Winny Puspasari
Published: January 2025

Teachers play an important role in the success and sustainability of the organization. Thus, teachers are required to have a work attitude that plays an active role in achieving school goals and a high commitment to school organizations. Commitment to the organization is an attitude that describes an individual's orientation to the organization as indicated by loyalty, self-identification and involvement in the goals of the organization. Transformational leadership and job satisfaction are predicted to have a role in influencing organizational commitment to teachers. This study aims to empirically prove the effect of transformational leadership style and job satisfaction on organizational commitment in teachers. The research sample was 238 high school teachers in Bogor Regency. The data analysis technique in this study used multiple linear regression analysis. The results of this study show that transformational leadership and job satisfaction have a 55.7% influence on organizational commitment with a significance level of p=0.000. This shows that transformational leadership and job satisfaction have a very significant influence on organizational commitment. The results of this study also show that organizational commitment, perceived of transformational leadership style, and job satisfaction among high school teachers in Bogor Regency are in the high category.
Peningkatan Perkembangan Kognitif Anak Usia Dini (AUD) Melalui Alat Permainan Edukatif (APE) Papan Berhitung
Authors: Arumsari Andini Dwi , Setyawan Dedi , Dzulkifli Dzulkifli , Marini Marini
Published: January 2025

Abstrak: Alat permainan edukatif (APE) diberikan kepada anak usia dini (AUD) untuk membantu anak-anak belajar, salah satunya adalah mengoptimalkan perkembangan kognitifnya melalui pembelajaran berhitung. Alat permainan edukatif (APE) Papan berhitung dirancang secara khusus untuk menarik minat anak dan membantu mereka belajar berhitung dengan cara yang menyenangkan dan mudah dimengerti. Tujuan dalam penelitian ini adalah untuk mengetahui peningkatan perkembangan kognitif anak usia dini (AUD) melalui alat permainan edukatif (APE) Papan berhitung. Subyek dalam penelitian ini adalah siswa TK A di TK Aisyiyah Surabaya. Penelitian ini menggunakan metode penelitian pre eksperimen dengan model one group pretest post-test design. Pre dan post tes dilakukan menggunakan 10 indikator dalam Standar Tingkat Pencapaian Perkembangan Anak usia dini (STPPA) usia 5-6 tahun. Hasil dari penelitian ini adalah ada peningkatan perkembangan kognitif anak usia dini (AUD) melalui alat permainan edukatif (APE) Papan Berhitung dengan skor sig Uji beda dilakukan dengan menggunakan SPSS versi 29, dan mendapatkan hasil nilai signifikansi (Sig) sebesar 0.03.Kata Kunci: Alat Permainan Edukatif, Anak Usia Dini, Perkembangan Kognitif, siswa TK A  Abstract : Educational game tools (APE) are given to early childhood (AUD) to help children learn, one of which is optimizing their cognitive development through learning to count. Educational game tools (APE) Counting boards are specifically designed to attract children's interest and help them learn to count in a fun and easy-to-understand way. The purpose of this study was to determine the increase in cognitive development of early childhood (AUD) through educational game tools (APE) Counting boards. The subjects in this study were students of Kindergarten A at Aisyiyah Kindergarten Surabaya. This research used pre experiment method with one group pre-test post-test design model. Pre and post tests were conducted using 10 indicators in the Early Childhood Development Achievement Level Standards (STPPA) aged 5-6 years. The results of this study are that there is an increase in cognitive development of early childhood (AUD) through educational game tools (APE) Counting boards with a sig score. The difference test was conducted using SPSS 29th version, and obtained a significance value (Sig) of 0.03. Keywords: Educational Game Tools, Early Childhood, Cognitive Development, Kindergarten students
Dynamic Connectedness across Equity, Currency, and Commodity Markets in South Asia: A Time- Varying Parameter Vector Autoregressive Approach
Authors: S.M.N.N. Sarathkumara  , S.M.R.K. Samarakoon
Published: January 2025

This study examines the dynamic return spillovers among major South Asian financial markets, including equity indices from India (NIFTY50R), Pakistan (KSER), and Sri Lanka (SLASPIR), as well as key global commodities such as Brent crude oil (BrentR) and gold (GoldR), and the relevant exchange rates (USDINR, USDPKR, and USDLKR). Using the Time-Varying Parameter Vector Autoregressive (TVP- VAR) connectedness approach, the analysis covers the period from March 2, 2005, to February 29, 2024, providing insights into how financial shocks propagate across these interconnected markets over nearly two decades. The findings reveal that the Indian equity market (NIFTY50R) and the Indian Rupee exchange rate (USDINR) serve as significant transmitters of shocks within the South Asian region, influencing other regional markets. Conversely, the Sri Lankan (SLASPIR) and Pakistani (KSER) equity indices are identified as net receivers of shocks, indicating their vulnerability to external financial disturbances. The study also highlights the pivotal role of Brent crude oil prices (BrentR) in driving spillovers, particularly affecting the Indian financial markets. The study's findings have significant implications for understanding the complexities of market interconnectedness in South Asia, particularly in the context of global economic integration.
COMPLIANCY TO LEVOTHYROXINE TREATMENT AND THE RATE OF DISEASE CONTROL FOR PATIENTS WITH HYPOTHYROIDISM IN DUHOK CITY
Authors:   Department of Internal Medicine, College of Medicine, University of Duhok, Kurdistan Region – Iraq, SARBAST SIPAN
Published: January 2025

ABSTRACT

Background: Hypothyroidism is one of the most prevalent endocrine diseases, affecting nearly 200 million people globally, with around 60% of those affected remaining undiagnosed. The incidence of hypothyroidism has been shown to have increased recently, becoming a worldwide health problem. It accounts for 30-40% of the patients seen in endocrinology departments and clinics. Iodine deficiency is the most prevalent cause of hypothyroidism, with data showing that around 2 billion people suffer from insufficient iodine intake.ke
Materials and Methods: In this cross-sectional study, we enrolled 309 adults with hypothyroidism who had been receiving Levothyroxine for 8 weeks or more at Azadi General & Teaching Hospital from July 10, 2023, to August 25, 2023. The planned sample size was chosen to facilitate accurate estimates of the rate of control and adherence to treatment. No formal study visits were conducted, and patients were approached for participation during their routine clinic visits.
Results: In our study of 309 hypothyroidism patients treated with levothyroxine for 8 weeks to 25 years, we found that 54.37% achieved optimal disease control, 37.22% did not achieve control, and 8.41% were overcorrected. Patients with full adherence to levothyroxine had significantly better TSH control compared to those with poor adherence (p < 0.001).
Conclusions: In this study, we observed poor treatment compliance rates, with only around half of the patients achieving disease control. Additionally, a significant proportion of patients were found to be overweight or obese.
Dinâmica das assimetrias na distribuição de renda segundo os arranjos familiares no Brasil
Authors: Silva Terra Taís Maria , Hermeto Ana Maria
Published: January 2025

O trabalho explora o papel das mudanças dos arranjos familiares na distribuição de renda brasileira, utilizando microdados da Pesquisa Nacional por Amostra de Domicílios Contínua (PNADC) no período de 2012 a 2023.  Os arranjos familiares serão distribuídos em 5 grupos: casal com filhos, casal sem filhos, monoparentais femininos, unipessoais e outros arranjos. Observa-se tendências modestas, mas relevantes, como diminuição de casais com filhos e aumento de famílias unipessoais e casais sem filhos. Nota-se quedas recentes na desigualdade de renda, acentuadas em 2020, devido ao empobrecimento geral, intensificado com a pandemia. Por fim, resultados da regressão quantílica sugerem que há assimetrias estatisticamente significativas entre os percentis ao longo da distribuição de renda em todos os arranjos familiares e resultados da decomposição do índice de Theil indicam que a distância “dentro dos grupos” é mais relevante na distribuição da renda familiar, embora o peso da desigualdade “entre grupos” esteja aumentando desde 2019.
Autoencoder Artificial Neural Network Model for Air Pollution Index Prediction
Authors: Basir Nor Irwin , Tan Kathlyn Kaiyun , Djarum Danny Hartanto , Ahmad Zainal , Vo Dai-Viet N. , Jie Zhang
Published: January 2025

Air pollution, a significant global challenge driven by industrialization, urbanization, and population growth, is caused by the emission of harmful gases, particulates, and biological molecules into the atmosphere, posing serious risks to health and the environment. Key sources include power plants, industrial activities, vehicles, and residential heating. Thus, effective air quality monitoring and forecasting are crucial to mitigating the adverse impacts of pollution. This paper presents shallow and deep sparse autoencoder artificial neural network models to improve the prediction of the Air Pollution Index (API) in Perak Darul Ridzuan, Malaysia, as a case study. The results show that the deep sparse autoencoder achieves better prediction accuracy with  and  values of 0.1474 and 0.8331, respectively, compared to 0.1515 and 0.8300 for the shallow sparse autoencoder. The performance of these autoencoder models is also compared with other models, such as feedforward artificial neural networks (FANN) and principal component analysis (PCA). The findings confirm that both autoencoder models enhance API prediction accuracy, with the deep sparse autoencoder emerging as the optimal model, highlighting the potential of deep learning in improving air quality prediction.
ABSTRAK: Pencemaran udara, merupakan satu cabaran global yang didorong oleh perindustrian, urbanisasi pesat, dan pertumbuhan populasi, adalah disebabkan oleh pelepasan gas, partikel, dan molekul biologi merbahaya ke atmosfera, menimbulkan risiko serius kepada kesihatan dan alam sekitar. Sumber utama termasuk loji janakuasa, aktiviti industri, kenderaan, dan pemanasan kediaman. Oleh itu pemantauan dan ramalan kualiti udara penting bagi mengurangkan kesan buruk pencemaran. Kajian ini membentangkan model rangkaian neural tiruan pengauto kod jarang ‘cetek’ dan pengauto kod jarang ‘dalam’ memperbaiki ramalan Indeks Pencemaran Udara (API) di negeri Perak Darul Ridzuan, Malaysia sebagai kes kajian. Dapatan kajian menunjukkan bahawa pengautokod jarang ‘dalam’ mencapai ketepatan ramalan lebih baik, dengan nilai MSE dan R2 masing-masing sebanyak 0.1474 dan 0.8331, berbanding 0.1515 dan 0.8300 bagi pengautokod jarang ‘cetek’. Prestasi model pengautokod ini juga dibandingkan dengan model lain, seperti rangkaian neural tiruan suapan hadapan (FANN) dan analisis komponen utama (PCA). Hasil kajian mengesahkan bahawa kedua-dua model pengautokod meningkatkan ketepatan ramalan API, dengan pengautokod jarang ‘dalam’ muncul sebagai model paling optimum, menonjolkan potensi pembelajaran mendalam ‘dalam’ meningkatkan ramalan kualiti udara.
Map Floodwater Radar Imagery using Machine Learning Algorithms
Authors: Doan Thanh-Nghi , Le-Thi Duc-Ngoc
Published: January 2025

Flooding is a widespread and costly natural disaster around the world. Accurately assessing the extent of flooding in near real-time is crucial for governments and humanitarian organizations. This information strengthens early warning systems, evaluates risks, and guides effective relief efforts. Therefore, precise flood mapping is essential for saving lives through improved early warning systems and targeted emergency responses. In this study, radar imagery available on the Planetary Computer Data was utilized to train a U-Net model specifically designed to label flood-affected pixels in an image from a flood event. Different blocks of the U-Net encoder architecture were fine-tuned to identify the most efficient fine-tuned model, and their results were compared. As a result, the model with blocks 1 and 2 being fine-tuned demonstrated the highest Intersection over Union (IoU) score of 78.904%, an increase of 8.663% over the baseline methods.
ABSTRAK: Banjir merupakan bencana alam yang meluas dan mahal di seluruh dunia. Penilaian yang tepat terhadap skala banjir secara hampir masa nyata adalah penting bagi kerajaan dan organisasi kemanusiaan. Maklumat ini memperkukuhkan sistem amaran awal, menilai risiko, dan membimbing usaha bantuan yang lebih berkesan. Oleh itu, pemetaan banjir yang tepat adalah penting untuk menyelamatkan nyawa melalui sistem amaran awal yang lebih baik dan respons kecemasan yang disasarkan. Dalam kajian ini, imej radar yang tersedia pada Planetary Computer Data digunakan untuk melatih model U-Net yang direka khas untuk melabelkan piksel yang terjejas oleh banjir dalam imej daripada kejadian banjir. Bagi mengenal pasti model ditala-halus yang paling cekap, blok-blok berlainan dalam arkitektur pengekod U-Net telah ditala-halus, dan hasilnya dibandingkan. Hasilnya, model dengan blok 1 dan 2 yang ditala-halus menunjukkan skor Intersection over Union (IoU) tertinggi sebanyak 78.904%, iaitu peningkatan sebanyak 8.663% berbanding kaedah asas.
Model Predictive Control-Based Energy Management System with Load Curtailment for Standalone Microgrid
Authors: Mohd Yunus Muhammad Sharir Fathullah , Yusoff Siti Hajar , Mohd Sapihie Siti Nadiah , Abu Hanifah Mohd Shahrin , Gunawan Teddy Surya , Suriza Ahmad Zabidi
Published: January 2025

The standalone microgrid emerges as an economical solution for providing electricity to remote areas disconnected from the main grid. However, the intermittent nature of renewable energy sources (RES) and unpredictable load demands can disrupt its balance. Diesel generators are commonly used to supply auxiliary power and serve as a backup for the microgrid. Nevertheless, inefficient utilization of diesel generators can lead to high operational costs, shortened lifespan, and environmental pollution. An energy management system (EMS) is implemented to optimize the operational cost and reliability of the microgrid by incorporating model predictive control (MPC), which has grown in popularity in recent years due to its ability to support multiple inputs and multiple outputs. The MPC-based EMS is developed using MATLAB/Simulink software, with the optimization problem formulated using mixed integer quadratic programming (MIQP). A comparative analysis is conducted between the MPC-based EMS with and without load curtailment capability, revealing a significant improvement of 52.21% in diesel fuel cost savings with the inclusion of load curtailment capability.
ABSTRAK: Grid mikro berdiri sendiri muncul sebagai penyelesaian ekonomi untuk menyediakan perkhidmatan elektrik kepada kawasan terpencil yang jauh daripada grid utama. Walau bagaimanapun, ciri-ciri ketidaktentuan sumber tenaga boleh diperbaharui (RES) dan permintaan beban yang tidak dapat diramalkan boleh mengganggu keseimbangan dalam grid mikro. Jentera diesel selalunya digunakan untuk menyediakan kuasa tambahan dan berfungsi sebagai sandaran untuk grid mikro. Namun begitu, penggunaan jentera diesel yang tidak cekap boleh menyebabkan kos operasi yang berlebihan, pengurangan jangka hayat dan pencemaran alam sekitar. Pengurusan tenaga (EMS) dilaksanakan untuk mengoptimumkan kos operasi grid mikro dan kebolehpercayaan dengan menggunakan kawal perkiraan model (MPC) yang semakin popular kerana keupayaannya dalam menyokong input dan output yang pelbagai. EMS berasaskan MPC dibangunkan menggunakan perisian MATLAB/Simulink, dengan masalah pengoptimuman diformulasikan menggunakan pengaturcaraan kuadratik berbilangan campuran (MIQP). Analisis perbandingan dijalankan antara EMS berasaskan MPC dengan dan tanpa keupayaan pemangkasan beban, yang mendedahkan pengurangan yang signifikan sebanyak 52.21% dalam penjimatan kos bahan api diesel dengan penambahan keupayaan pemangkasan beban.
4D Radar Imaging and Camera Fusion for Road Crossing Detection and Classification Using Deep Learning
Authors: Wan Abd Aziz Liyaana Shahirah , Mohd Isa Farah Nadia , Abd Rahman Faridah , Narayanan Arvind Hari , Alghooneh Ahmad Reza , Shaker George
Published: January 2025

This paper presents the development of an object detection and classification system for road crossing areas, integrating 4D radar imaging and a mono-camera dataset with a deep-learning neural network. The system utilizes deep neural networks implemented via Keras and TensorFlow to detect and classify multiple targets, including pedestrians, cars, buses, and trucks. At the core of this work is Retina-4F, a multi-chip radar imaging system developed by Smart Radar System, which offers high-resolution object detection and localization capabilities. Retina-4F provides real-time 4D information on detected objects, operating in a cascading architecture with three transmitters and four receivers per chip. Two road-crossing scenes were simulated to collect data, generating a point cloud dataset labeled with target classes for neural network training and testing. Data from two main sensors—Retina-4F and a mono-camera—were pre-processed using DBSCAN and YOLOv7 for enhanced accuracy. Operating at 77 GHz, Retina-4F was tested in two road environments, generating a dataset with approximately 10,000 frames. The deep learning model demonstrated an accuracy of 84% in classifying multiple targets, including cars, pedestrians, buses, and trucks. The fusion of radar point cloud data with visual sensor data proved effective, showing strong results in distinguishing target types.
ABSTRAK: Kertas ini membentangkan pembangunan sistem pengesanan dan pengelasan objek untuk kawasan lintasan jalan raya, menggabungkan pengimejan radar 4D dan set data mono-kamera dengan rangkaian neural pembelajaran mendalam. Sistem ini menggunakan rangkaian neural mendalam yang dilaksanakan melalui Keras dan TensorFlow untuk mengesan dan mengelaskan pelbagai sasaran, termasuk pejalan kaki, kereta, bas, dan trak. Inti daripada kajian ini adalah Retina-4F, sistem pengimejan radar berbilang cip yang dibangunkan oleh Smart Radar System, yang menawarkan keupayaan pengesanan objek dan penentuan lokasi resolusi tinggi. Retina-4F menyediakan maklumat 4D masa nyata mengenai objek yang dikesan, beroperasi dengan tiga pemancar dan empat penerima bagi setiap cip dalam seni bina kaskad. Dua adegan lintasan jalan disimulasikan untuk mengumpul data, menghasilkan set data awan titik yang dilabel dengan kelas sasaran untuk latihan dan ujian rangkaian neural. Data daripada dua sensor utama—Retina-4F dan mono-kamera—dipra-proses menggunakan DBSCAN dan YOLOv7 untuk meningkatkan ketepatan. Beroperasi pada 77 GHz, Retina-4F diuji dalam dua persekitaran jalan yang berbeza, menghasilkan set data dengan kira-kira 10,000 bingkai. Model pembelajaran mendalam menunjukkan ketepatan sebanyak 84% dalam mengelaskan pelbagai sasaran, termasuk kereta, pejalan kaki, bas, dan trak. Penggabungan data awan titik radar dengan data sensor visual terbukti berkesan, menunjukkan hasil yang kuat dalam membezakan antara jenis sasaran.
Utilizing MFCCs and TEO-MFCCs to Classify Stress in Females Using SSNNA
Authors: Zainal Nur Aishah , Asnawi Ani Liza , Ibrahim Siti Noorjannah , Mohamed Azmin Nor Fadhillah , Harum Norharyati , Mat Zin Nora
Published: January 2025

All individuals are susceptible to experiencing stress in their everyday lives. Nevertheless, stress has a greater influence on females due to both biological and environmental factors. This study utilized female speeches to detect and classify stress and no stress in women. Using speech, composed of non-invasive and non-intrusive approaches, helps to identify stress better in females. A comparative analysis was conducted between Mel-frequency Cepstral Coefficients (MFCCs) and Teager Energy Operator- MFCCs (TEO-MFCCs) to determine the best speech feature for classifying emotions associated with stress and no-stress conditions for female voices. With the assistance of the Stress Speech Neural Network Architecture (SSNNA), an improved accuracy of 93.9% was achieved. This research showed that MFCCs enhanced higher-frequency components in stressed speech, distinguishing between stress and no-stress classes. This study shows that SSNNA achieved high accuracy with 14 female voices, confirming its ability to function independently of speaker identity.
ABSTRAK: Semua individu terdedah kepada stres dalam kehidupan seharian mereka. Walau bagaimanapun, stres memberi pengaruh yang lebih besar terhadap wanita akibat faktor biologi dan persekitaran. Kajian ini menggunakan ucapan untuk mengesan dan mengklasifikasikan stres dan tiada stres dalam kalangan wanita. Penggunaan ucapan, yang merupakan pendekatan tidak invasif dan tidak mengganggu, membantu mengenal pasti tekanan dengan lebih baik dalam kalangan wanita. Analisis perbandingan telah dijalankan antara Mel-frequency Cepstral Coefficients (MFCCs) dan Teager Energy Operator-MFCCs (TEO-MFCCs). Tujuannya adalah untuk menentukan ciri ucapan terbaik bagi mengklasifikasikan emosi yang berkaitan dengan keadaan stres dan tiada stres bagi suara wanita. Dengan bantuan Stress Speech Neural Network Architecture (SSNNA), metrik prestasi yang lebih tinggi dengan ketepatan 93.9% telah dicapai. Penyelidikan ini menunjukkan bahawa MFCCs meningkatkan komponen frekuensi tinggi dalam ucapan yang stres, secara efektif membezakan antara kelas stres dan tiada stres. Kajian ini menunjukkan bahawa SSNNA mencapai ketepatan tinggi dengan 14 suara wanita, mengesahkan ia berfungsi secara bebas daripada identiti penutur.
Uporaba metod strojnega učenja za klasifikacijo nalog po prioritetah v IT-projektih
Authors: Unuchak Tatyana , Kljajić Borštnar Mirjana , Unuchak Yauhen
Published: January 2025

Določanje prioritet in razvrščanje nalog še vedno predstavlja izziv pri učinkovitem vodenju projektov. Obstaja veliko pristopov za določanje prioritet, kot so MoSCoW, drevo binarnega iskanja in drugi. Vendar so vse te tehnike delovno intenzivne, subjektivne in neprilagodljive. V prispevku obravnavamo pristope, ki temeljijo na strojnem učenju za samodejno določanje prioritet nalog. Glavni cilj našega dela je raziskati, kako lahko z uporabo tehnik strojnega učenja pomagamo projektnim vodjem pri bolj učinkovitem razvrščanju nalog v IT-projektih. V ta namen smo na množici 600000 zapisov razvili klasifikacijski model za samodejno določanje prioritet po korakih procesa CRISP-DM. Večina nalog v IT-projektih je označenih z najvišjo prioriteto, kar predstavlja izziv pri modeliranju, kot tudi pri učinkovitosti izvedbe projekta. Pokažemo, da je smiselno naloge razvrstiti v manj skupin prioritet, kar posledično prispeva k večji natančnosti klasifikacijskega modela.
СТРАТЕГІЧНЕ БАЧЕННЯ ЄВРОПЕЙСЬКОГО ДЕРЖАВОТВОРЕННЯ ТА РЕСУРСНОЕКОЛОГІЧНА СКЛАДОВА ЗГУРТОВАНОСТІ ПУБЛІЧНОГО УПРАВЛІННЯ В УКРАЇНІ
Authors: Воротін Валерій , Проданик Василь
Published: January 2025

Наразі в Україні відбувається процес формування нової державної регіональної політики, зокрема, на засадах використання саме екологічних механізмів публічного управління та законодавчого забезпечення в умовах воєнного стану та впровадження європейських норм (регламентів) у цій сфері суспільних відносин за умов воєнного стану. Метою такого формування є створення умов для збереження чи відновлення якості життя людини, екологізації та додержання гарантованих державою соціальних стандартів для кожного громадянина незалежно від його місця проживання, через забезпечення територіально цілісного та збалансованого розвитку України, інтеграції регіонів в єдиний економічний, політичний, правовий, інформаційний та культурний простір, максимально повного використання їх потенціалу з урахуванням природних, політичних, історичних, культурних, соціальних і інших особливостей, підвищення конкурентоспроможності регіонів і реалізації дієвого самоуправління.
У статті обґрунтовано, що еколого-ресурсний розвиток неможливо здійснити без реальної децентралізації, зміцнення самоврядування в Україні та залучення територіальних громад до формування, впровадження політики (стратегічного бачення) регіонального та місцевого розвитку, зокрема, в сфері екології та ресурсів відновлення.
Державна стратегія регіонального розвитку на 2021–2027 рр. (зі змінами), яка затверджена постановою Кабінету Міністрів України від 13 серпня 2024 р. № 940, лишається основним планувальним документом для реалізації секторальних стратегій розвитку, координації державної політики в різних сферах. Стратегія визначає певні досягнення ефективності використання державних ресурсів у територіальних громадах і регіонах в інтересах людини, єдності держави, сталого розвитку історичних населених місць та збереження традиційного характеру історичного середовища, збереження навколишнього природного середовища та сталого використання природних ресурсів для нинішнього та майбутніх поколінь українців після Перемоги.
Доведено, що найбільш суттєвими викликами, на які держава має реагувати шляхом вироблення та реалізації державної регіональної політики, є неспроможність більшості територіальних громад самостійно вирішувати питання, віднесені до їх повноважень. В цілому, передавати повноваження та відповідальність за екологічність регіонального розвитку на органи місцевого самоврядування не можна допоки не буде створена дієва і ефективна система місцевого самоврядування і, у першу чергу, дійсно спроможна та економіко-екологічна стійка територіальна громада.
СУЧАСНІ АСПЕКТИ СОЦІАЛЬНОГО ЗАХИСТУ ОСІБ З ІНВАЛІДНІСТЮ: ЗАКОРДОННІ ПРАКТИКИ ТА ДОСВІД ДЛЯ УКРАЇНИ
Authors: Пархоменко-Куцевіл Оксана
Published: January 2025

У статті проаналізовані інноваційні закордонні практики щодо соціального захисту осіб з інвалідністю. Зазначено, що реалізація права даних осіб вести самостійний спосіб життя здійснюється за допомогою його соціального захисту, мета якого – компенсація наявних у осіб з інвалідністю обмежень життєдіяльності, і вирівнювання, таким чином, його можливостей у порівнянні з іншими людьми. Зазначена мета досягається за допомогою створення доступного середовища, реабілітації, матеріального забезпечення, соціального обслуговування, надання пільг та ін. Таким чином, аналізована діяльність носить багатоаспектний характер і потребує комплексного регулювання різними галузями публічного управління.
Проведений аналіз дає підстави зазначити, що державна політика щодо осіб з інвалідністю має на меті: по-перше, забезпечити їх максимальну участь в економічному та соціальному житті суспільства та особливо стимулювати їх працевлаштування та участь на ринку праці; по-друге: забезпечити гарантований дохід, так, щоб люди з інвалідністю не позбавлялися можливості жити гідно через свою інвалідність. Основним завданням політики, що проводиться більшістю економічно розвинених країн, стало поєднати цих багато в чому несумісних цілей. Оскільки грошова допомога не завжди сприяє участі інваліда в суспільстві, не завжди стимулює його до активного пошуку роботи, то в законодавстві багатьох країн крім грошових виплат передбачаються заходи, що гарантують участь особи в економічному та соціальному житті.
У багатьох країнах застосовуються державні субсидії підприємствам, що використовують працю інвалідів. Субсидії, як правило, надаються тільки тоді, коли людина з інвалідністю гарантовано отримує таку ж заробітну плату, як і працівник без інвалідності на аналогічній посаді і має довгостроковий трудовий контракт. В основному субсидії надаються на робоче місце для людини з інвалідністю, придбання спеціалізованого обладнання та ін. У деяких країнах роботодавці отримують пільги щодо внесків у фонди соціального страхування.
У багатьох країнах люди з інвалідністю мають переваги за участю в різних тренінгах та програмах професійного навчання, що реалізуються на підприємствах. Також люди з інвалідністю можуть брати участь у державних програмах професійного навчання, без необхідності мати статус безробітного протягом певного мінімального періоду. У більшості країн існують спеціалізовані підприємства, які використовують працю інвалідів. Проте такі підприємства розцінюються не як місце роботи для людини з інвалідністю, а як «запасний варіант» працевлаштування, коли не вдається знайти місце роботи на загальних для всіх умовах. Також такі підприємства використовують працю людей, які мають серйозні порушення, для яких фізично неможливо або надзвичайно важко створити необхідні умови праці на звичайному підприємстві.
Method for Effective Increasing the Decomposition Rate of Ammonium Perchlorate in Solid Rocket Fuel
Authors: Moldosanov К.А. , Lelevkin V.M.
Published: January 2025

Ammonium perchlorate (AP) is a common oxidizer in solid rocket propellants. For devices, the most im- portant parameter of which is the speed of movement, the key correlation is between the jet thrust and the combustion rate of fuels and, consequently, the rate of thermal decomposition of the AP. To increase the de- composition rate of AP, fuel, aluminum powder, is used in the form of nanoparticles. The aim of this work is to identify the decomposition mechanism of AP molecules under conditions where aluminum nanoparticles, in addition to acting as a fuel, also act as catalysts for the decomposition of AP. The result of spraying alumi- num nanoparticles into multiple nanoclusters in the fuel combustion zone due to the melting of nanoparticle cores and the destruction of aluminum oxide shells is considered. In this case, aluminum nanoclusters become sources of terahertz (THz) radiation. Since the frequencies of vibrational and rotational oscillations in AP molecules are in the THz range, irradiation of AP molecules with THz photons promotes their decomposition. It is proposed to use emission of THz photons by aluminum nanoclusters, increasing its intensity by introduc- ing 3d impurities into aluminum, which increase the density of electron states near the Fermi level of alumi- num.
Análise estatística da produção de cana-de-açúcar em diferentes espaçamentos de plantio
Authors: Pádua Guilherme Hungria Nicos de , Ferreira Nathan , Melo Aurélio Ferreira , Bessa Stephanie Vicente de , Moreira Juracy Mendes , Silva Junior Elielton Olimpio da
Published: January 2025

Sugarcane (Saccharum officinarum spp.) is a cultivar from the Poaceae family, and its cultivation is a very important socioeconomic factor, with most of its production destined for ethanol and sugar, as well as organic fertilizers and animal feed. The experiment was implemented and conducted between April 2022 and April 2023 in an area located on BR 020, Km 18, where the climate is classified as seasonal tropical, characterized by two well-defined seasons: dry and rainy. The experimental area was prepared for conventional planting, with harrowing and subsoiling. Planting was carried out manually on April 18, 2022; for pre-plant fertilization, a dose of 600 kg ha-1 of NPK was applied to the 04-30-16 formulation throughout the experimental area. The experiment was carried out with 5 varieties of sugar cane as the main treatment, 2 planting spacings being the secondary treatments, and 4 replications in a completely randomized block design (BDC) in a split-plot arrangement. The tested varieties were: V1 - RB867515; V2 - RB966928; V3 - TC4; V4 - RB92579 and V5 - CTC9001. The spacings were E1 - 1.50m x 0.9m and E2 - 1.40m x 0.5m. For varieties, the value of the F statistic (32.83) exceeds the critical value at the 1% probability level (5.41) it is significant at this level (P < 0.01), so we reject the null hypothesis and conclude that the variety effect differs from the productivity effect of the cultivar. For spacing, the value of the F statistic (10.79) exceeds the critical value at the 1% probability level (8.68) it is significant at this level (P < 0.01), so we reject the null hypothesis and conclude that the spacing effect differs from the cultivar productivity effect. For the Interaction (Spacing x Variety), the value of the F statistic (0.70) was lower than the critical value at the 5% probability level (3.06) it is not significant at this level (P > 0.05), therefore the null hypothesis cannot be rejected and we conclude that the effect of the factors spacing and variety act independently on the productivity of the cultivar.
Pengembangan Modul Ajar Berbasis Inkuiry Terbimbing
Authors: Gumay Ovilia Putri Utami , Syabawaihi Syabawaihi
Published: January 2025

Penelitian ini bertujuan untuk mengembangkan modul ajar berbasis inkuiri terbimbing yang dapat meningkatkan kemampuan berpikir kritis dan pemahaman konsep siswa. Metode penelitian yang digunakan adalah Research and Development (R&D) dengan model pengembangan ADDIE (Analysis, Design, Development, Implementation, Evaluation). Modul yang dikembangkan disesuaikan dengan kebutuhan peserta didik dan kurikulum yang berlaku, serta divalidasi oleh ahli materi dan ahli media. Uji coba dilakukan pada siswa sekolah menengah pertama dengan pendekatan kuasi-eksperimen. Hasil penelitian menunjukkan bahwa modul ajar berbasis inkuiri terbimbing yang dikembangkan memenuhi kriteria valid, praktis, dan efektif. Modul ini mampu meningkatkan keterlibatan siswa dalam proses pembelajaran, melatih kemampuan bertanya, dan memecahkan masalah secara mandiri. Berdasarkan temuan ini, modul ajar berbasis inkuiri terbimbing direkomendasikan untuk digunakan sebagai salah satu alternatif bahan ajar dalam upaya meningkatkan kualitas pembelajaran di sekolah.
Reading Achievement of Chilean Second-Grade Students after Covid-19
Authors: Claro Susana , Orellana Pelusa , Valenzuela Juan Pablo , Fantoni Dominga
Published: January 2025

Background: Low levels of reading comprehension have remained persistent in South America, as evidenced by third-grade results from the ERCE. A deeper understanding of the underlying reading subprocesses is essential to addressing reading comprehension lags in the region. Methods: We conducted a diagnostic study to assess the reading skills of a representative sample of Chilean second-grade students from a large metropolitan area. Results: for 60% of students reading comprehension was below  the level expected by the end of first-grade. These results cannot be explained by language comprehension alone, since most of those students (63%) had above second grade listening comprehension skills. Instead, low reading comprehension levels seem to be more strongly associated       with deficits      in frequent word recognition and vocabulary knowledge. Specifically, 88% and 58% of these students, respectively, performed below end-of-first-grade levels. Conclusions: strengthening these specific reading subprocesses is crucial to prevent comprehension deficits as reading tasks become more complex.
Political Violence and Terrorism from the Belle Epoque to Vichy
Authors: Nicholls Julia
Published: January 2025

The articles in this special issue originated as a panel on political violence and terrorism in modern France at the Society for the Study of French History conference in summer 2021. Taken together, they help deepen our understanding of these two issues, and particularly the ways in which they intersected with gender and race in interwar and wartime France. In his classic lecture Politics as a Vocation, the German sociologist Max Weber famously defined a monopoly on the legitimate use of physical force as the defining characteristic of the modern state. Weber's maxim cannot have been based on French history. From the eruption of the French Revolution in 1789 to the crushing of the Paris Commune in 1871, France was gripped by constitutional uncertainty and political violence. Monarchies, empires, and republics rose and fell with alarming speed as different factions competed to claim power and remake the country in their image. This uncertainty was brought to an end by the establishment of the Third Republic, which would go on to last for seventy years until its abolition after France's defeat to Nazi Germany in 1940.
“A New Era in the Progress of Liberty and Independence”
Authors: Scherr Arthur
Published: January 2025

Historians have tended to conclude that North American attitudes were hostile toward the Haitian Revolution in the early nineteenth century. This article argues that, after Haiti was unified under President Jean-Pierre Boyer in 1820, public opinion expressed in various newspapers across the United States accepted and even applauded events in Haiti. Impressed by the apparent stability Boyer's regime brought to Haiti, North Americans even recommended that government authorities consider laws to emancipate enslaved Blacks in the United States and send them to Haiti. Evidence drawn from periodicals published in Virginia, Maryland, North Carolina, and the Northern states shows support for the independent Black and mixed-race Haitian government. It challenges the conventional view of public hostility in the United States toward Black rule in Haiti.
STRATEGI PEMASARAN BERKELANJUTAN UNTUK MENINGKATKAN DAYA SAING PT. SUN POWER CERAMICS DI ERA DIGITAL : PENDEKATAN INOVATIF DAN PRAKTIS
Authors: Damayanti Vidya
Published: January 2025

Penelitian ini mengkaji strategi pemasaran berkelanjutan berbasis digital yang diterapkan oleh PT. Sun Power Ceramics dalam upaya meningkatkan daya saing di pasar global. Dengan menggunakan pendekatan kualitatif deskriptif melalui wawancara mendalam, observasi, dan analisis dokumen, penelitian ini berfokus pada integrasi teknologi digital, penerapan prinsip keberlanjutan dalam rantai pasokan, tantangan implementasi, serta evaluasi langkah-langkah penanganannya. Hasil penelitian menunjukkan bahwa PT. Sun Power Ceramics telah berhasil mengadopsi teknologi big data, artificial intelligence (AI), dan otomatisasi pemasaran untuk meningkatkan efektivitas kampanye dan loyalitas konsumen. Penerapan prinsip keberlanjutan dalam seluruh rantai pasokan, seperti penggunaan bahan baku ramah lingkungan dan pengurangan emisi karbon, memperkuat citra perusahaan di pasar internasional. Tantangan utama yang dihadapi meliputi keterbatasan infrastruktur digital, resistensi budaya kerja, dan alokasi anggaran yang terbatas. PT. Sun Power Ceramics telah mengambil langkah-langkah strategis, termasuk penguatan infrastruktur digital, pelatihan karyawan, dan peningkatan anggaran teknologi untuk mengatasi kendala tersebut. Kesimpulannya, meskipun masih terdapat beberapa hambatan, perusahaan menunjukkan komitmen kuat terhadap pemasaran berkelanjutan berbasis digital yang diproyeksikan akan terus meningkatkan daya saingnya di pasar global.
A Quasilinear Algorithm for Computing Higher-Order Derivatives of Deep Feed-Forward Neural Networks
Authors: Chickering Kyle R.
Published: January 2025

The use of neural networks for solving differential equations is practically difficult due to the exponentially increasing runtime of autodifferentiation when computing high-order derivatives. We propose \(n\)-TANGENTPROP , the natural extension of the TANGENTPROP formalism[1] to arbitrarily many derivatives. \(n\)-TANGENTPROP computes the exact derivative \({d^{n}/d}x^{n}f{(x)}\) in quasilinear, instead of exponential time, for a densely connected, feed-forward neural network \(f\) with a smooth, parameter-free activation function. We validate our algorithm empirically across a range of depths, widths, and number of derivatives. We demonstrate that our method is particularly beneficial in the context of physics-informed neural networks where \(n\)-TANGENTPROP allows for significantly faster training times than previous methods and has favorable scaling with respect to both model size and loss-function complexity as measured by the number of required derivatives. The code for this paper can be found at https://github.com/kyrochi/n_tangentprop. [https://github.com/kyrochi/n_tangentprop]
Feathered Icons: Drivers of Global Attention on Bird Species
Authors: Si Haozhong , Fu Changjian , Yu Fan , Li Zhongqiu
Published: January 2025

Global biodiversity faces profound threats. Efforts to slow biodiversity loss remain inadequate without greater public engagement. With challenges in the biases of species knowledge across taxa and regions, many endemic or threatened species receive insufficient attention. Birds, with their ecological importance and cultural visibility, present an ideal object for exploring biases in species knowledge. To understand factors driving scientific and public interest in birds, we compiled a comprehensive dataset to investigate how phenotypic, ecological, and cultural factors influence attention toward global bird species. Our analysis reveals that factors related to public familiarity and species charisma significantly shape public and scientific priorities. In contrast species that are threatened or have limited ranges often receive little public attention. IUCN status alone fails to sustain public interest in these species. To address this imbalance, we propose comprehensive strategies such as media campaigns and conservation education to better engage the public and scientific communities. These efforts are crucial for ensuring conservation efforts could encompass a sufficient range of species.
Introduction to Artificial Intelligence in Agriculture
Authors: Her Young Gu , Bliznyuk Nikolay , Ampatzidis Yiannis , Yu Ziwen , Bayabil Haimanote
Published: January 2025

This article is prepared to help Extension agents, farmers, farm managers, researchers, graduate students, and the general public better understand AI, associated terms, and technologies. Written by Young Gu Her, Nikolay Bliznyuk, Yiannis Ampatzidis, Ziwen Yu, and Haimanote Bayabil, and published by the UF/IFAS Department of Agricultural and Biological Engineering, September 2024.
Diez beneficios de los huertos urbanos: enfoque en las crisis socioeconómicas
Authors: Clarke Mysha
Published: January 2025

Esta publicación destaca los potenciales beneficios de los huertos urbanos tanto para los vecindarios cercanos como para la comunidad urbana en general, así como para las comunidades periféricas y visitantes de una ciudad. Los planificadores urbanos, residentes y miembros de la comunidad encontrarán muy útil esta información tanto para planificar nuevos huertos como para mantener los ya establecidos.
What Is in a Natural Resource Management Plan?
Authors: Demers Chris , Clausen Robert
Published: January 2025

This document outlines the essential components of a natural resource management plan for forest properties. It emphasizes the importance of clear objectives, property location and history, resource assessment, management recommendations, and an activity schedule. The plan serves as a “road map” to guide landowners in achieving their desired outcomes, such as timber production and wildlife habitat improvement. It also highlights the role of consulting foresters and the need for periodic reviews to adapt to changing conditions. The document provides practical advice for creating a flexible and effective management plan. First published August 2001.
Dypsis lutescens, Areca Palm
Authors: Friedman Melissa H. , Andreu Michael G. , McKenzie Mary
Published: January 2025

This document provides an overview of the Areca Palm (Dypsis lutescens), detailing its taxonomy, common names, and physical characteristics. Native to eastern Madagascar, this palm is endangered in its natural habitat but widely cultivated in Florida and the United States. It thrives in well-drained soils with ample water and can grow up to 35 feet tall. The article also discusses its horticultural applications, including its use as a landscape accent and natural fence, and offers care recommendations such as planting during the rainy season and regular fertilization to maintain its green color. Original publication date May 2010.
Quercus laevis, Turkey Oak
Authors: Andreu Michael G. , Friedman Melissa H. , McKenzie Mary , Quintana Heather V.
Published: January 2025

This document provides a comprehensive overview of Quercus laevis, commonly known as Turkey Oak. It details the tree’s taxonomy, physical characteristics, habitat, and uses. The article highlights its distinctive turkey-foot-shaped leaves, its adaptability to xeric environments, and its role in providing food for wildlife. Additionally, it discusses the tree’s allergenic properties, storm tolerance, and limited commercial value, primarily as firewood. The document also emphasizes Turkey Oak’s horticultural benefits, particularly its drought tolerance and aesthetic appeal in landscapes. Original publication date May 2010.