bluuebunny/crossref_metadata_2025_split huggingface dataset:
Guiding reading club members to build better reading skills using directed reading thinking activities (DRTA)
Authors: Iftanti Erna 
Published: September 2024

[Bahasa]: Menindaklanjuti hasil wawancara dengan anggota klub membaca di UIN Tulungagung yang menggambarkan bahwa sebagian besar dari mereka mengaku mempunyai berbagai permasalahan membaca, terutama membuat referensi dan inferensi. Kedua keterampilan tersebut sangat dibutuhkan untuk memperoleh pemahaman bacaan yang baik. Oleh karena itu, untuk mengatasi permasalahan tersebut, maka perlu dilakukan pengabdian kepada masyarakat melalui metode Community Based Research (CBR). Teknik mengajar membaca Directed Reading Thinking Activity (DRTA) diimplementasikan untuk meningkatkan keterampilan membaca mereka khususnya keterampilan membuat referensi dan inferensi. Pengabdian masyarakat berbasis penelitian ini dilaksanakan pada bulan Juni 2023 kepada 47 anggota Klub Baca UIN Sayyid Ali Rahmatullah Tulungagung melalui penelitian tindakan. Nilai rata-rata pre-test yang diberikan sebelum dilakukan perlakuan adalah 52,23 dan hanya 10,6% yang memperoleh nilai ketuntasan minimal 75 dari total nilai 90. Sedangkan nilai post-test setelah perlakuan adalah 72,75, dan terdapat 75 % peserta mencapai nilai ketuntasan minimum. Hasil pengabdian berbasis penelitian ini menunjukkan bahwa penerapan teknik mengajar membaca DRTA dapat membantu pembelajar bahasa Inggris sebagai bahasa asing untuk meningkatkan keterampilan mereka dalam membuat referensi dan inferensi. Hal ini dapat mengarahkan mereka untuk mencapai pemahaman membaca yang lebih baik
Kata Kunci: keterampilan membaca, teknik DRTA, klub membaca
[English]: In response to the interview results with the reading club members at the State Islamic University of Tulungagung, most of them claim to have various reading problems, mainly in making references and inferences. Those two skills are significantly needed to achieve good reading comprehension. Therefore, it is essential to address the problem through a community service program with Community Based Research (CBR) method. The Directed Reading Thinking Activities (DRTA) technique of teaching reading was implemented to improve their reading skills, specifically in making references and inferences. This research-based community service was carried out in June 2023 to 47 members of the Reading Club at the State Islamic University of Tulungagung. The mean score of the pre-test before the treatment was 52,23 and only 10,6% got the minimum passing score of 75 out of the total score of 90. Meanwhile, the post-test score after the treatment was 72,75, and 75% of the participants reached the minimum passing score. The result of this CBR indicates that implementing the DRTA technique of teaching reading helps EFL learners improve their skills in making references and inferences. This further leads them to achieve better reading comprehension.
Keywords: reading skills; DRTA technique; reading club
PEMENUHAN HAK ANAK OLEH PANTI ASUHAN DI KABUPATEN JOMBANG
Authors: Abdalloh Feri , Kusumawati Ita Rahmania 
Published: September 2024

Ada banyak panti asuhan di Kabupaten Jombang yang mengurusi anak yang kurang beruntung tidak memiliki orang tua. Muncul keingintahuan peneliti untuk mengetahui bagaimana Panti Asuhan di Kabupaten Jombang memenuhi hak-hak anak asuh, apa hambatan dan solusi pemenuhan hak anak oleh Panti Asuhan di Kabupaten Jombang. Pendekatan yang digunakan dalam penelitian ini adalah metode pendekatan kualitatif. Jenis penelitian ini adalah penelitian lapangan (field reseach) yang digunakan untuk memperoleh data yang diperlukan dalam mengkaji tentang pemenuhan hak anak oleh panti asuhan di Kabupaten Jombang lalu dianalisis dengan kacamata maqashid syariah. Penelitian ini menyimpulkan bahwa panti asuhan di Kabupaten Jombang menerapkan strategi pemenuhan hak anak, termasuk kebutuhan dasar, pendidikan, kesehatan, perlindungan, dan keadilan. Kendala yang dihadapi melibatkan konflik antar anak, kekurangan tenaga pengasuh, latar belakang yang beragam, dan keterbatasan finansial. Upaya penanganan mencakup mediasi, pembinaan, koordinasi dengan dinas sosial, dukungan psikologis, dan kerjasama dengan instansi sejenis. Strategi pemenuhan hak anak di panti asuhan Kabupaten Jombang, perspektif Maqasid Syariah, bertujuan memperkuat tanpa bertentangan dengan hukum Islam. Pendekatan holistik diterapkan untuk memenuhi kebutuhan fisik, spiritual, emosional, intelektual, dan sosial anak-anak di panti asuhan.
Structural Evolution and Correlation Characteristics of Carbon Emissions in China's Industrial Sector
Authors: zhao Jiali , Dong Jiangfeng , Wu Rong , Guo Chenzi 
Published: September 2024

Abstract

The deterioration of the global environment and the intensification of the greenhouse effect are increasingly severe issues, making the pursuit of a green and sustainable development path, characterized by low carbon emissions, the primary direction for global economic progress. A thorough understanding of the dynamic changes in the structure of industrial carbon emissions and the relationships between them is crucial for the strategic planning of industries and the effective development of energy conservation and emission reduction policies. This paper constructs a comparable input-output industry table for China and employs an input-output model combined with a complex network analysis method to examine the trends, correlation characteristics, and evolutionary patterns of carbon emissions across various industrial sectors in China. Notably, the metal smelting and rolling processing, construction, and chemical industries exhibit the highest carbon emissions, while the non-metallic mineral products industry and the metal smelting and rolling processing industry show the highest direct carbon emission intensity. Additionally, the financial products industry and the electrical machinery and equipment manufacturing industry have significant indirect carbon emission intensity. The network characteristics of associated carbon emissions reveal that the industrial carbon emissions network exhibits small-world properties with closely linked nodes. Metal smelting and the chemical industry hold central positions in the carbon emissions network, marking them as critical sectors for energy conservation and emissions reduction. The optimal emissions path analysis indicates that the oil processing and electric power production industries are key to stable emissions, highlighting the need for focused efforts on promoting energy conservation and emissions reduction.
Multi-Stage BiLinear Self-Attention Network for Multi-Sensor Industrial Time Series Classification
Authors: Huang HaoLang , Pang Xiongwen , Zou ChunYa , Li Xiangru , AI JUN 
Published: September 2024

Abstract

Available deep learning models have shortcomings in processing some industrial time datasets, as these models often ignore the importance of various stages in industrial time-series data and fail to capture the complex relations between multiple series from different sensors. This paper introduces MMITNet, a novel Multi-Stage Multi-Sensor Industrial Time-series Network, designed to emphasize the importance of various stages within industrial time-series data and the fusion of multi-sensor data. In our study, we utilize time-series embedding techniques, incorporating stages-based segmentation and BiLinear Self- attention Embedding, to effectively highlight pivotal stages within time-series data. This embedding methodology employs a parallel structure, which accounts for both inter-stage relationships within a time- series and the dynamics across various stages. Subsequently, the Multi-Sensor Fusion Network leverages a graph attention mechanism to integrate data from multiple sensors, capturing non-linear correlations among features. Our experiments demonstrate that our model attains state-of-the-art performance on an authentic industrial spot-welding time-series dataset and exhibits a good performance across several baseline datasets. Further investigation reveals that MMIPNet consistently achieves promising results when handling time series characterized by distinct stage changes and fluctuations.
InfoFlow: A Transformer-based Time Series Anomaly Detection Model with Information Bottleneck and Normalizing Flows
Authors: Mo Yuhua , Fu Hongzhu , Bai Sen , Deng Chao , Tang Tiantian , Lang Jian , Zhou Fan 
Published: September 2024

Abstract

Time series anomaly detection aims to identify unusual samples that significantly deviate from the majority of the data. The greatest challenge lies in endowing models with the ability to learn effective differentiation criteria. Previous methods have focused on learning intricate, sophisticated representations to overcome these difficulties. However, these approaches are often hindered by spurious correlations, which limit their potential for further improving model performance and causality.To solve the problem, we propose a novel approach, called InfoFlow, which accurately extracts and identifies pertinent details within sequences while excluding anomalous entries. This is achieved by utilizing information bottleneck constraints throughout a transformer-based model. Our primary discovery suggests that anomalous data are rare and unevenly distributed within the observed points, resulting in the phenomenon of anomaly concentration, which complicates the identification. To mitigate this issue, we employ normalizing flows to adjust the sequence distribution to a more uniform range. This approach accentuates subtle variations in the data and enhances the algorithm's sensitivity to anomalies, thereby facilitating easier detection of outlier points. Extensive experiments on real-world datasets demonstrate that our InfoFlowapproach outperforms state-of-the-art benchmarks.
Enhancing Wi-Fi Security by Preventing Backward Compatibility Attacks on WPA3 Protocols
Authors: Tareef Aya , ABADLEH AHMAD , Alkasasbeh Anas A. , Alghamdi Mansoor 
Published: September 2024

Abstract

The widespread adoption of the Wi-Fi Protected Access III (WPA3) standard has been critical in wireless network security. However, the inherent vulnerability of wireless communication to unauthorized access presents a significant challenge. A critical concern is the potential for downgrade attacks, which can force the network's security protocol from WPA3 to WPA2, exploiting known vulnerabilities in the older standard. To mitigate this issue, many intrusion detection systems depend on fixed-threshold statistical approaches. However, these statistical approaches may prove inefficient in adapting to dynamic network conditions and attack behaviors. Therefore, adaptive selection and thresholding methods are required to compromise with the downgrade attack on WPA3. The proposed approach provides a hybrid adaptive approach for feature selection and thresholding with the goal of classifying incoming traffic containing downgrade attacks. It consists of three stages: (1) preprocessing, (2) baseline adaptive feature selection, and (3) real-time detection and prevention. The findings reveal that the developed approach, using a specially generated dataset, successfully detects downgrade attacks in WPA3 networks. Evaluation of the Naive Bayes classifier performance in both WPA3 modes demonstrates a high accuracy rate of approximately 99.8%. This result confirms the approach's effectiveness in detecting and mitigating wireless network security breaches.
Clinical Evaluation of a Polarization-Based Optical Noninvasive Glucose Sensing System
Authors: Leung Ho Man Colman , Gong Chengyue , Geiser Luke , Fivekiller Emily E. , Bui Nam , Vu Tam , Prioleau Temiloluwa , Forlenza Gregory P. , Liu Qiang , Zhou Xia 
Published: September 2024

Abstract

Diabetes affects millions in the US, causing elevated blood glucose levels that could lead to complications like kidney failure and heart disease. Recent development of a continuous glucose monitors has enabled a minimally invasive option, but the discomfort and social factors highlight the need for noninvasive alternatives in diabetes management. We propose a portable noninvasive glucose sensing system based on the glucose's optical activity property where it rotates linearly polarization light depending on its concentration level. To enable a portable form factor, a light trap mechanism is used to capture unwanted specular reflection from the palm and the enclosure itself. We fabricate four sensing prototypes and perform a multi-session clinical evaluation where 30 participants are provided with a prototype for a 5-day home monitoring study, collecting on average 8 data points per day. We identify the error caused by differences between the sensing boxes and the participants' improper usage. We utilize a machine learning pipeline together with Bayesian Ridge Regressor models and multiple-step data processing techniques to deal with the noisy data. Over 95% of the predictions fall in either Zone A (clinically accurate) or B (clinically acceptable) of the Consensus Error Grid with a 0.24 mean absolute relative differences.
Impact of Environmental Award &amp; Financial Performance on Environmental Disclosure Quality: A Case Study of Listed Companies in Pakistan
Authors: Munir Muhammad Badar Ul , Ishfaq Muhammad 
Published: September 2024

Abstract

As global environmental concerns have grown, so too have calls for more corporate environmental transparency and responsibility. Businesses are participating in programs such as earning environmental awards and improving their financial performance to promote their company image and demonstrate that they are effective environmental stewards. This research examines the nexus between environmental awards, environmental disclosure quality, and the firm performance of non-financial companies. This research aims to determine if environmental disclosure, indicative of accountability and transparency, is affected by awards for environmental success. The study incorporated quantitative information from 300 non-financial businesses selected randomly to serve as a sample and anticipate beginning operations between 2016 and 2020. The findings suggest a connection between environmental disclosures' quality and environmental awards' attainment. Similarly, environmental disclosure quality is not affected by financial performance. The conclusions of this study could stimulate more accountable and responsible business practices, which would enhance our collective efforts to create a more sustainable and environmentally friendly future.
SUBJECTS
Environmental Management; Environment & Business; Environmental Economics; Business, Management and Accounting
Mathematical modeling of water sorption isotherms in specialty coffee beans processed by wet and semi-dry post-harvest methods
Authors: Escobar Gentil Andrés Collazos , Cortés Valeria Hurtado , Monje Andrés Felipe Bahamón , Guzmán Nelson Gutiérrez 
Published: September 2024

Abstract

This article addresses the experimental evaluation and mathematical modeling of water sorption isotherms of dried specialty coffee beans that have been processed by wet and semi-dry post-harvest methods. The study analyzed different water activities ranging from 0.1 to 0.85 and temperatures of 25, 35, and 45°C. The experimental isotherms were obtained using the dynamic dew point method (DDI). To model water sorption isotherms, 11 empirical models, 4 machine learning, and the Guggenheim-Anderson-de Boer (GAB) equation were used. The experimental data were randomly split into 75% for model training and 25% for validation. The experimental results show a type II water sorption isotherm and a significant temperature influence. Additionally, the sorption shape of the isotherms suggests that the mucilaginous coating, which covers the beans obtained by the semi-dry method, modifies the curves and plays a protective role against water sorption. The SVM model was the most accurate predictor to describe the upward sigmoidal type II sorption trend. The impact of temperature and water activity, as well as the post-harvest method, on the equilibrium moisture content (ERM = 0.21% and R2ad = 99.8%) suggests that it could be a valuable tool for predicting and optimizing storage conditions for both types of specialty coffee beans.
SPM-FL: A Federated Learning Privacy Protection Mechanism Based on Local Differential Privacy
Authors: Chen Zhiyan , Zheng Hong 
Published: September 2024

Abstract

Federated learning (FL) is a popular distributed machine learning approach that avoids data transfer to third parties by sharing and computing model parameters through a central server, thereby protecting client privacy. However, model weights and other information can still be analyzed and leaked. Currently, many methods in FL apply local differential privacy (LDP) to protect model parameters, but model accuracy significantly declines with smaller privacy budgets and varying numbers of clients. To address this issue, we propose the Symmetric Piecewise Mechanism (SPM) to perturb local model weight parameters before aggregation. First, we design an LDP mechanism that satisfies ε-differential privacy to ensure algorithmic privacy. Second, we introduce a variance-constrained mechanism suitable for FL, maintaining effectiveness with smaller privacy budgets and different client numbers. Finally, we compare the proposed mechanism with other algorithms on three public datasets in terms of model accuracy, variance, and privacy protection. Theoretical proofs demonstrate that our mechanism achieves the minimum variance and highest model accuracy under any privacy budget, showing superior performance.
Front propagation accelerated by convection-driven symmetry breaking in frontal polymerization
Authors: Gao Yuan , Feng Yuqun , Yu Xiaotong , Chen Rong , Geubelle Philippe 
Published: September 2024

Abstract

Biological and chemical reaction-diffusion systems involving front propagation often experience symmetry-breaking events that enable the formation of topological patterns. Symmetry breaking is also used in some bio-inspired manufacturing methods to control spontaneous pattern formation in products. Here, we report how symmetry breaking caused by the buoyancy-driven convection in frontal polymerization, a reaction-diffusion-based manufacturing process, can increase the velocity of the front through a reaction-diffusion-convection process under typical processing conditions. Such a phenomenon can be captured by a multi-physics reaction-diffusion-convection model, which provides insight into the underlying physics and describes how symmetry breaking affects the local heat exchange and promotes the chemical reaction rates. The limit of the front acceleration regime is also explored under super-gravity conditions, where the fluid-induced convective heat dissipation limits the front velocity and quenches the polymerization. With various orientations of the frontal polymerization front with respect to gravity, the magnitude and vorticity of the buoyancy flow vary, generating different effects on the velocity, shape, and instability of the propagation front.
Changes in Temperature Extremes over Malawi during 1961 to 2015
Authors: Mtewa Thokozani Kachulu , Ngongondo Cosmo , Dulanya Zuze , Boyce Clement , Mtilatila Lucy 
Published: September 2024

Abstract

Changes in temperature and its extremes have widely been among key indicators in the global climate change discourse. In this study, we analysed the spatial and temporal trends of temperature extremes over Malawi in Southern Africa during 1961 to 2015. The analysis was based on observed daily maximum and minimum temperatures (Tmax and Tmean) from 25 stations across the country. We derived 17 extreme temperature indices based on the WMO/CLIVAR Expert Team on Climate Change Detection and Indices (ETCCDI). These indices were analysed for significance of trend using the non-parametric Mann-Kendal test at α = 0.05 while their slopes were quantified using linear regression. The results suggest a countrywide warming pattern, with statistically significant increases in warming indices: SU25 at 7.56 days/decade; TR20 at 17.81 days/decade; Tmin at 0.46 oC/decade; TXx at 2.72 oC/decade; TNx at 2.20 oC/decade; TXn at 0.84 oC/decade; TN90p at 5.17 days /decade,; TX90p at 5.11 days/decade; and WSDI at 14.26 days/decade. In addition, the countrywide pattern suggest significant decreases in cold spell indices: CSDI at -2.17 days/decade, TN10p at -3.53 days/decade at TX10p at -30.40 days/decade. No significant changes were found in Tmax, TNn and DTR. The lack of trends in the DTR and TNn, coupled with the significant trends in Tmin and TNx suggest that the Tmin increased more than the Tmax across the country. The spatial pattern of the warming over Malawi is typical of regions experiencing considerable deforestation and urbanization.
A Markov Chain-Based Multi-Criteria Framework for Dynamic Cloud Service Selection Using User Feedback
Authors: Latifi Faride , Nassiri Ramin , Mohsenzadeh Mehran , Mostafaei Hamidreza 
Published: September 2024

Abstract

As the variety of cloud services continues to expand, organizations increasingly struggle to select the best options. This task is made more challenging by the ever-changing nature of user preferences, which shift based on evolving needs and feedback from previous service experiences. This paper tackles these issues by presenting a comprehensive multi-criteria decision-making (MCDM) framework to aid in cloud service selection. The framework utilizes a Markov chain model to analyze and discern patterns in user feedback, facilitating the ranking of cloud services based on both quality and user satisfaction metrics. By employing a Markov chain approach, the framework can track changes in user preferences over time, providing a dynamic means of evaluating cloud services. This system aids users in making informed choices by offering personalized recommendations that meet their specific needs and preferences. It also provides cloud service providers (CSPs) with valuable insights into market trends and customer expectations, helping them enhance their services. The framework's efficacy is demonstrated through a detailed simulation using real-world quality of service (QoS) data. Furthermore, a comprehensive sensitivity analysis is performed to assess the robustness and reliability of the proposed approach, ensuring its consistency.
Surface modification of astralenes for obtaining optical composites based on photocurable acrylates
Authors: Tarasov Valentine E. , Burunkova Julia A. , Sitnikova Vera E. , Karpov Sergey A. , Ivanov Aleksey V. 
Published: September 2024

Abstract

Polymers are a promising matrix for creating optical materials due to the possibility of imparting new properties to the material by introducing additives. In particular, astralenes, which are multilayer toroidal nanostructures, known as structure modifiers for some medium and also have nonlinear optical properties. Hower, the creation of an optical composite requires modification of the particle surface for uniform distribution of particles in the matrix. The two-stage modification technique developed by the authors allows reducing the amount of disordered carbon in the astralenes, as well as making them compatible with photocurable acrylic monomers. As a result, a transparent optical composite was obtained by photopolymerization. The success of the modification process is confirmed by the results of Raman and FTIR spectroscopy, TG analysis. The TEM method showed that the toroidal structure of the particles is preserved after the modification process. The study compared composites with 0.01, 0.05, 0.10%wt. astralenes and the original copolymer. It was found that the introduction of particles into the reaction mass reduces the polymerization rate by more than 40%. At the same time, the conversion degree in samples with and without astralenes is comparable. The transparency of the obtained composites in the visible region and NIR is comparable to the copolymer and is equal to ~ 90%. The introduction of astralenes in the selected concentrations does not significantly affect the optical band gap of the material.