bluuebunny/crossref_metadata_2025 huggingface dataset:
La logistique d'importation du bois tropical africain en France
Authors: Chauvin Jean-Paul
Published: January 2025

L'objet de cet article est de souligner l'importance de la fonction logistique dans le commerce des bois tropicaux entre l'Afrique et la France. Cette logistique comprend le transport maritime des bois en provenance d'Afrique, la gestion du port d'entrée à l'arrivée en France et le transport terrestre jusqu'aux locaux de l'importateur. Sur la base d'exemples concrets et de chiffres, l'auteur souligne l'importance du transport maritime dans les coûts logistiques et l'avantage du transport routier à terre. Toutefois, il est difficile d'établir une règle générale en ce qui concerne le choix d'un port. L'auteur conclut qu'en raison de son importance, la fonction logistique doit être prise en compte dans toute étude sur les avantages de l'importation de bois tropicaux en France.
Lettre à l’éditeur. Réponse de M. B. Rollet, auteur de l'article : La régénération naturelle dans les trouées
Authors: Rollet Bernard
Published: January 2025

Pas de résumé
Can green technologies serve as a pathway for women's socioeconomic inclusion in Africa?
Authors: Donald Djatcho Siefu , Orfe Chouafi Nguekam , Merime Aguekam Ngako , Chretien Nzomo Tchuenta Joseph
Published: January 2025

This study aims to evaluate the effects of green technology innovations on the socio-economic integration of women in Africa from 2014 to 2023. To achieve this goal, a quantitative analysis of longitudinal data has been utilized through econometric techniques such as fixed effects models, Lewbel 2SLS (Two Stage Least Square) 2SLS estimates, and panel quantile models to address and mitigate potential endogeneity bias. The findings show a direct impact on women’s employment in high- and middle-income countries, particularly in renewable energy generation and sustainable agriculture, as a result of increased use of green technologies. Additionally, in these countries, better availability of renewable energy is related to the advancements made by women's education and household health. Yet, access to the economic opportunities that this technology enables for many women in lower-income parts of the world remains scarce. Hence, it is necessary to mainstream gender and institutional issues more into the green technology policies in Africa. It would lead to a fairer sharing of the socio-economic gains arising out of green technology adoption and help in promoting sustainable development.
PENGEMBANGAN BAHAN AJAR PEMBELAJARAN IPA BERORIENTASI LEARNER AUTONOMY UNTUK MENINGKATKAN KETERAMPILAN PROSES SAINS MATERI CAHAYA DAN ALAT OPTIK
Authors: Anggryani Anggryani , Suryajaya Suryajaya , Rusmansyah Rusmansyah , Fahmi Fahmi
Published: January 2025

Rendahnya keterampilan proses sains peserta didik dikarenakan kurangnya penggunaan metode percobaan dalam proses pembelajaran serta kegiatan pembelajaran masih didominasi oleh guru. Oleh karena itu, penelitian ini bertujuan untuk menghasilkan bahan ajar berorientasi learner autonomy yang valid, praktis dan efektif, sehingga layak untuk melatihkan keterampilan proses sains peserta didik. Subjek penelitian ini yaitu kelas VIII A SMP Negeri 10 Banjarmasin sebanyak 23 peserta didik menggunakan desain model pengembangan ADDIE meliputi analyze, design, develop, implement, dan evaluate. Pengumpulan data penelitian menggunakan lembar validasi akademisi dan praktisi, lembar pengamatan RPP, lembar pengamatan keterampilan proses sains, dan hasil tes peserta didik. Data selanjutnya dianalisis secara deskriptif, kualitatif, dan kuantitatif. Hasil penelitian menunjukkan: (1) bahan ajar berorientasi learner autonomy termasuk valid karena komponen validitas RPP dengan rerata 3,35; materi ajar dengan rerata 3,19; LKPD dengan rerata 3,16; dan THB dengan rerata 3,08 dalam kategori valid; (2) bahan ajar berorientasi learner autonomy termasuk praktis, karena komponen keterlaksanaan RPP diperoleh rerata sebesar 3,69 dalam kategori sangat praktis; (3) bahan ajar berorientasi learner autonomy termasuk efektif karena gain score kognitif sebesar 0,81 dalam kategori tinggi. Diperoleh kesimpulan bahan ajar berorientasi learner autonomy layak untuk meningkatkan keterampilan proses sains.
Development of Virtual Laboratory Based on Mobile Learning in Bromo Tengger Semeru National Park Area
Authors: Bashith Abdul , Amin Saiful , Kurniawan Muchammad Akbar , Dewi Sari
Published: January 2025

Mobile learning-based digital field laboratories have not been widely developed in the learning process. Currently, the development of mobile learning-based virtual laboratories needs to be done to assist learning both online and offline. This study aims to explain the process of developing mobile learning-based virtual laboratories and also discuss the effect of using mobile learning-based virtual laboratories on student learning outcomes. This study uses the Borg & Gall Research and Development (R&D) model. The suitability of the product has been tested by expert validators on media and learning materials. Product effectiveness data has been tested on students using normality tests, homogeneity tests and independent sample t-tests. The increase in Gain score in the experimental group using mobile learning-based virtual laboratories was 39.04 (from 46.22 to 85.26), while the control group without a virtual laboratory increased by 25.70 (from 42.37 to 68.07). The results of the study indicate that 1) mobile learning-based virtual laboratories are feasible to use in learning with a very effective category and 2) the use of mobile learning-based virtual laboratories is effective in improving student learning outcomes in the topic of Economic Behavior of the Tengger Mountain Slope Community. This research has a positive impact on the development of knowledge of social studies education students in utilizing virtual laboratories based on mobile learning. Suggestions for further research are that the results of the development of mobile learning-based learning media products should be distributed through the app market
Research on Bearing Fault Diagnosis Based on Optimized CNN and Information Fusion
Authors: Zhang Mengke , Xu Yanwei , Wang Liuyang , Zhu Yongshuai , Xie Tancheng , Wang Junhua , Cai Haichao
Published: January 2025

Aiming at the problem of the low recognition rate of a bearing fault under a single sensor condition, an intelligent detection method of a bearing fault based on an optimized convolutional neural network (CNN) and information fusion is proposed. Firstly, a NU216 bearing is selected as the research object to prefabricate fault defects. Then, the orthogonal test method is used to design the test scheme, and the vibration signal and acoustic emission signal of the NU216 bearing are collected; Secondly, the mutual feature fusion method of convolutional neural network is used to fuse the vibration signal and the acoustic emission signal. Then, the fused one-dimensional data is converted into a two-dimensional image dataset by continuous wavelet transform. Finally, the three datasets are divided into training sets and test sets, and input into the optimized convolution neural network model for training and testing. The test results show that the accuracy of fault diagnosis based on vibration signal is 95.76%, the accuracy of fault diagnosis based on acoustic emission signal is 92.33%, and the accuracy of fault diagnosis based on fusion signal is 98.59%.
Insights to the Transition Regimes of Flow-Induced Vibration for Three Tandem Cylinders
Authors: Guo Kai , Cheng Yuxuan , Zhang Hongsheng , Fan Xiantao , Wang Yang , Tan Wei
Published: January 2025

Flow-induced vibration (FIV) is a complex phenomenon influenced by the interplay between flow dynamics and structural vibrations. Traditionally, it has been perceived as a threat to structures, but FIV has recently emerged as a promising method for highly efficient energy harvesting. This study focuses on the FIV of three tandem cylinders with varying spacing ratios (L/D) ranging from 1.3 to 4.0 with Reynold number Re of 5800-70000. Three distinct vibration states are identified: separated vortex-induced vibration (VIV) and wake-induced galloping (WIG) at L/D =1.3, continuous VIV-WIG at L/D =1.5, and partially separated VIV-WIG at L/D =2.0. To assess the coupling strength between the cylinders, the concept of vibration coherence is introduced and quantitatively analyzed. For L/D < 2, strong coherence is observed at the natural frequency ({f_{n), resulting in equal interference between the tandem cylinders across all reduced velocities. Conversely, for L/D >= 2, coherence becomes apparent at the vortex shedding frequency (f_v and 2 f_v), indicating linear interference with the reduced velocity. The transaction between the regimes is also accompanied with phase change. The establishment of these regimes, characterized by quantitative coherence, enhances our understanding of FIV in tandem cylinders, facilitating the efficient design of process industrial structures.
Estimation of the Acoustic Field in a Uniform Duct with Mean Flow using Neural Networks
Authors: Veerababu D. , Quasim Namra , Ghosh Prasanta K.
Published: January 2025

The study of sound propagation in a uniform duct having a mean flow has many applications, such as in the design of gas turbines, heating, ventilation, and air conditioning ducts, automotive intake and exhaust systems, and the modeling of speech. In this paper, the convective effects of the mean flow on the plane wave acoustic field inside a uniform duct were studied using artificial neural networks. The governing differential equation and the associated boundary conditions form a constrained optimization problem. It is converted to an unconstrained optimization problem and solved by approximating the acoustic field variable to a neural network. The complex-valued acoustic pressure and particle velocity were predicted at different frequencies and validated against the analytical solution and the finite element models. The effect of the mean flow is studied in terms of the acoustic impedance. A closed-form expression that describes the influence of various factors on the acoustic field is derived.
Research on Fault Feature Extraction of Rolling Bearing Based on Adaptive DFIF and CYCBD
Authors: Ge Hongping , Liu Huaying , Zhang Xin , Mei Xuwen
Published: January 2025

Due to the fact that the fault features of rolling bearing is easily drowned out by strong noise, it is difficult to exploit the impact components which contain fault information, a combination method based on snake optimizer (SO), direct fast iterative filtering (DFIF) and maximum second order cyclostationary blind deconvolution (CYCBD) is proposed, namely, SO-DFIF-CYCBD, for rolling bearing fault features extraction. Firstly, the fault vibration signal is adaptively decomposed employing parameter optimized DFIF to acquire several intrinsic mode function (IMF) components. Secondly, the sensitive components are screened for reconstruction based on the kurtosis-correlation coefficient criterion. Finally, the reconstructed vibration signal is deconvoluted utilizing the CYCBD method to reinforce the fault shock components, and obvious frequency components are extracted using envelope demodulation to distinguish the fault type. The reliability of the proposed approach are verified through simulation vibration signals and actual rolling bearing signals. In addition, compared to other combination model techniques in this article, the proposed approach can extract richer fault feature information and has stronger fault feature extraction capabilities.
A Probabilistic Model-Based Framework for Damage Detection in Beam-Like Structures Considering Temperature Effects
Authors: Altammar Hussain
Published: January 2025

To improve the assessment outcomes of structural health monitoring systems, it has been acknowledged that the damage diagnostics process is associated with a considerable amount of uncertainties from operational and environmental sources such as temperature. This study presents a probabilistic framework for structural health monitoring aimed at identifying common defects such as cracks and corrosion in beam-like structures under varying temperature conditions. The framework utilizes optimization methods integrated with a probabilistic approach, comprising two levels of damage identification: first, determining the optimal probability mass function for the damage location ratio, followed by the optimal conditional for the damage depth ratio. A simply supported beam divided into four segments was modeled to evaluate the effectiveness of the proposed algorithm across various damage scenarios using frequency response signals. Structural damage was simulated by manipulating the length and depth ratios of specific beam segments. The modeling procedure for defects in the simply supported beam was validated through comparison with experimental measurements, achieving a maximum difference of less than 1%. The proposed algorithm consistently yielded improved damage detail outcomes in the second level, characterized by higher probabilities and lower uncertainties for both damage location and depth ratios. Identifying cracks and corrosion with a 0.1 depth ratio at low temperatures proved challenging, but the algorithm effectively addressed such scenarios, achieving identification probabilities exceeding 90%. The analysis outcomes demonstrate the advantages of the proposed framework for structural health monitoring that accounts for temperature effects, thereby improving the fidelity of damage assessment in real-world conditions.
Dynamics and Modal Analysis of Slurry Pump Rotor Based on Bidirectional Fluid-Structure Interaction
Authors: Peng Guangjie , Yin Qi , Ma Lie , Hong Shiming , Ji Guangchao , Chang Hao
Published: January 2025

Slurry pumps are widely used in complex media and harsh operating conditions due to their good transport performance and non-blocking characteristics. This paper takes a slurry pump as the research object, intending to analyze the impeller's structural characteristics and ensure the rotor's safe operation. By combining theoretical analysis and numerical simulation, the dynamic stress characteristics and vibration characteristics of the slurry pump structure are systematically analyzed using the bidirectional fluid-structure interaction research method, and the dry and wet modes of the pump rotor are analyzed. The results show that: the equivalent stress and deformation are the most severe under small flow conditions, and decrease with the increase of flow rate; the maximum equivalent stress occurs at the junction of the trailing edge of the suction surface of the blade and the back cover plate; the maximum deformation occurs at the intersection of the outlet of the impeller flow passage and the back cover plate; the wet mode has a lower inherent frequency than the dry mode; the rotor's inherent frequencies have some equal values of adjacent orders; the rotor's critical speed is $3408.4$ r/min, far higher than the rotor's actual speed of $1480$ r/min, and will not cause resonance.
Vehicle Subframe Effects on Frontal Collision
Authors: Limouei Mahtab , Hasani Shahin , Marzbanrad Javad
Published: January 2025

Ensuring passenger safety is a crucial consideration in designing vehicles. Forces that are transmitted to the passenger compartment, particularly during collisions, can jeopardize the safety of the passengers. Hence, minimizing forces in the vehicle body and chassis plays a crucial role in enhancing passenger safety. Many vehicles with a unibody chassis feature a subframe as a supplementary element. The primary contribution of the subframes to the performance of the vehicle is the reduction of noise and vibration. However, subframes can also improve factors such as suspension stiffness, vehicle handling, and vehicle stability. This paper examines the effect of the presence and design modifications to the subframe on vehicle body forces. To achieve this, five subframe designs with different dimensions and materials are modeled. They are then installed on a full-scale vehicle model, and frontal collisions with a barrier and a pole are simulated. The vehicle body forces during various cases of frontal collisions are studied by measuring the acceleration and acceleration magnitude of three points on the B-pillar in the time domain and frequency domains. The results indicate that a subframe can reduce vehicle body forces, with the subframe's design influencing the extent of this effect.
Diagnosing Belt Conveyor Idler Faults with STFT and CNN
Authors: Milovančević Miloš
Published: January 2025

Belt conveyors are widely used for transporting bulk commodities, and idlers are essential components prone to frequent failures. The timely and accurate fault diagnosis of idlers is critical for ensuring the safe and efficient operation of belt conveyors. This paper proposes a method for diagnosing idler faults by combining Short-Time Fourier Transform (STFT) and Convolutional Neural Networks (CNN). The STFT is used to convert one-dimensional vibration signals into time-frequency representations, which are then processed by the CNN to classify the operational state of idlers. The proposed method is tested on vibration signals collected under various working conditions, including normal operation, bearing damage, and cylinder skin fracture. The CNN model, trained and validated using MATLAB, achieves high diagnostic accuracy, demonstrating its effectiveness in identifying different fault types. This approach enhances the reliability of belt conveyor systems by enabling prompt detection and maintenance of idlers.
A Multi Parameter Synchronous Identification Method for Stiffness and Damping of Single Fixed Clamp Based on Pareto Algorithm
Authors: Xu Kunpeng , Xu Cheng , Liu Yicheng , Wang Bo , Shi Yan , Wang Shaoyang
Published: January 2025

As a composite structure, the single fixed clamp (SFC) is an important supporting component of the aeroengine piping system. The dynamic parameters (stiffness and damping) of SFC have significant differences in bolt direction and opening direction. Accurately identifying the dynamic parameters of an SFC in both directions is of great significance for the study of pipeline system dynamics. At present, there is very little research on the identification of dynamic parameters for such SFC. Therefore, an SFC-straight pipe structure for identifying the dynamic parameters of an SFC is proposed in this paper. In this structure, one end of the straight pipe is completely fixed, and the other end is supported by an SFC. This structure can better reflect the working state of the SFC. A dynamic model of this structure is established based on the finite element method for parameter identification of SFC. In the finite element model (FEM), the constraint effect of the SFC is simplified into two identical spring-damping groups. Considering the structural asymmetry, spring and damping parameters for bolt direction and opening direction are separately set in each spring damping group. Next, based on the Pareto multi-objective genetic algorithm, an identification algorithm and procedure for the stiffness and damping of the SFC using modal test data as input parameters are proposed. Through experimental testing, parameter identification is carried out for DK8 type SFC, and a straight pipe experimental structure completely supported by two SFCs is constructed to verify the correctness of the identification results.
A identidade docente e as concepções de professores no uso das tecnologias educacionais
Authors: Mendonça Ana Cláudia Sousa
Published: January 2025

Este artigo apresenta a construção da identidade docente e as concepções de professores no uso das tecnologias educacionais em uma escola da rede pública de ensino no município de Aracaju-SE/Brasil. Tem como principal objetivo identificar a base epistemológica na construção da identidade docente e as concepções de professores no uso das tecnologias educacionais. Metodologicamente, trata-se de uma pesquisa de natureza qualitativa com viés descritivo, caracterizada como estudo de caso. A produção de dados se deu a partir de entrevistas semiestruturadas online, que contou com a participação de 12 (doze) professores pertencentes ao quadro efetivo de funcionários da rede estadual, atuantes em escolas da capital Aracaju. Os resultados revelaram uma identidade docente alicerçada na Pedagogia Relacional professor/aluno/conhecimento, em que o professor atua como mediador, assim como a necessidade da aplicabilidade das tecnologias educacionais para práticas pedagógicas interativas, com sentido, inovadoras e que dão dinamicidade ao ensino-aprendizagem.
Educação e práticas escolares riberinhas: apontamentos da literatura sobre aspectos socioculturais, dificuldades e a valorização das comunidades ribeirinhas nas práticas educativas
Authors: Leite Nanci Costa , Manske George Saliba , Oliveira Paulo Rogério Melo de
Published: January 2025

Inseridos no campo dos Estudos Culturais buscamos compreender como se relacionam as práticas educativas escolares de populações ribeirinhas com os aspectos culturais destas comunidades. A partir de uma pesquisa bibliográfica de revisão da literatura no site periódicos CAPES no período de 2017 a 2022 se estabeleceu o material empírico composto de 12 artigos para análise. Utilizando a análise de temática se organizou as discussões em 6 subcategorias, quais sejam: Práticas educativas e os aspectos socioculturais das comunidades ribeirinhas; Dificuldades das práticas educativas nas comunidades ribeirinhas; Valorização das comunidades ribeirinhas nas práticas educativas; A cultura ribeirinha os Saberes populares e os Conhecimentos empíricos; A docência, a educação inclusiva, ambiental e o multisseriado das escolas ribeirinhas; e Proposta curricular. Ao fim, se percebeu que as práticas educativas são aspectos tangenciados por elementos de ordem financeira e sociocultural, articuladas as possibilidades de uma educação a partir da realidade do território.
Radiographic Image of Fracture Healing with Bone Graft Equine Hydroxyapatite (BGEH) Implantation in Rabbits
Authors: Muhammad Zulfadillah Sinusi  , Fatmawati Dian , Amriani Rini , Liding Ulfa Desianti , Gifardi Muhammad Dirga
Published: January 2025

Background: Fractures refer to the obstruction of bone continuity due to trauma, stress, or pathological abnormalities. One method to accelerate fracture healing is through bone graft implantation. Horses are commonly utilized by society, but horse bones are difficult for decomposers to break down, resulting in waste. However, the calcium and phosphorus content in horse bones is quite high, making them a potential material for bone grafting due to their more compact and hard structure. Research Objective: Research Objective: To make a bone graft from horse bones called Bone Graft Equine Hydroxyapatites (BGEH) and evaluate its effectiveness for fracture healing. Research Method: The sample in this study used eight rabbits and divided into two groups. The first group was the control group by doing defect in femur rabbit without any implantation, while the second group was the treatment group with horse bone graft (BGEH) implantation. The research procedure consisted of two stages: the creation of horse bone grafts and testing on experimental animal. Results: In two weeks, the control group showed the formation of a soft callus characterized by low density at the edges of the fragments. In contrast, the treatment group with BGEH showed the formation of a thin callus distributed evenly across the entire bone defect area provided by high opacity in whole defect of bone. At six weeks, the control group showed that the bone area was not yet completely covered but had reduced in defect diameter, whereas the treatment group had achieved complete closure due to the formation of a more organized hard callus and new bone formation. The results indicated that the use of horse bone grafts could be an alternative for fracture management as it could accelerate bone healing.
 
Keywords: Fracture, bone graft, hydroxyapatite, BGEH, equine
Analysis of the Style Characteristics of Regional Folk Songs and Music Classification Algorithms
Authors: Liu Lin , Liang Hao
Published: January 2025

Regional folk songs have a rich history and are filled with cultural values. In this paper, first, the style characteristics of regional folk songs are briefly introduced. Using four regional folk songs from the northwest, northeast, southwest, and Hakka as examples, time domain, frequency domain, and mel-frequency cepstral coefficient (MFCC) features were extracted. Finally, the bidirectional long short-term memory (BiLSTM)-based music classification algorithm is used to realize the classification of folk songs from different regions. It was found that using the time-frequency domain + MFCC as features produced better results in music classification than using only the time-frequency domain or only MFCC features. The BiLSTM algorithm achieved an accuracy of 0.8339 and an F1 value of 0.8201 for the 10 s fragment set, both of which were better than those of the K-nearest neighbor, support vector machine, and other classification algorithms. The results show that the approach used in this study to categorize regional folk songs is reliable and that it can be applied to real folk songs.
Enhancing Individual Self-Efficacy Through a Self-Growing Memory Artificial Intelligence Agent Integrated with a Diary Application
Authors: Guo Yuchen , Siow Chyan Zheng , Chin Wei Hong , Hadžić Bakir , Yorita Akihiro , Obo Takenori , Rätsch Matthias , Kubota Naoyuki
Published: January 2025

This paper introduces an artificial intelligence (AI) interactive system featuring a self-growing memory network designed to enhance self-efficacy, reduce loneliness, and maintain social interaction among the elderly. The system dynamically analyzes and processes user-written diaries, generating empathic and personalized responses tailored to each individual. The system architecture includes an experience extraction model, a self-growing memory network that provides a contextual understanding of the user’s daily life, a chat agent, and a feedback loop that adaptively learns the user’s behavioral patterns and emotional states. By drawing on both successful and challenging experiences, the system crafts responses that reinforce the self-efficacy of the user, fostering a sense of accomplishment and engagement. This approach improves the psychological well-being of elderly users and promotes their mental health and overall quality of life through consistent interaction. To validate our proposed method, we developed a diary application to facilitate user interaction and collect diary entries. Over time, the system’s capacity to learn and adapt further refines the user experience, suggesting that AI-driven solutions hold significant potential for mitigating the effects of declining self-efficacy on mental health and social interactions. With the proposed system, we achieve an average system usability scale score of 77.3 (SD = 5.4) and a general self-efficacy scale score of 34.2 (SD = 3.5).
sEMG Signal-Based Human Lower-Limb Intention Recognition Algorithm Using Improved Extreme Learning Machine
Authors: Wu Shengbiao , Cheng Xianpeng , Li Huaning
Published: January 2025

To address the difficulty in identifying human lower-limb movement intentions, low accuracy of classification models, and weak generalization ability, this study proposes a motion intention recognition method that combines an improved pelican optimization algorithm (IPOA) and a hybrid kernel extreme learning machine (HKELM). First, we collect the surface electromyography (sEMG) signals of subjects in six motion modes and perform feature parameter extraction under non-ideal conditions. On this basis, we establish a dataset of the relationships between the feature parameters and gait movements. Second, we build a motion intention classification model based on relational data using the HKELM to solve the problems of low modeling accuracy and weak generalizability. Third, the IPOA is used to optimize the parameters related to the HKELM, and a differential evolution algorithm is introduced to improve the population quality and prevent the algorithm from falling into a local optimal solution. The experimental results show that the IPOA exhibits better optimization accuracy and convergence speed for four classical benchmark functions. Its average classification accuracy, average classification recall, and average F-value are 94.45%, 94.47%, and 94.46%, respectively, which are significantly higher than those of other intention recognition algorithms. Therefore, the proposed method has high classification accuracy and generalization performance.
An Ensemble Approach with Evolutionary Algorithm for Hand Posture Classification
Authors: Obo Takenori , Sato-Shimokawara Eri , Shibata Hiroki , Ho Yihsin , Kobayashi Ichiro
Published: January 2025

Grasping is a fundamental action in daily life and particularly evident during mealtime situations where various grasping actions occur with tableware such as chopsticks, spoons, forks, bowls, and cups, each serving specific purposes. While tableware usage varies across regions and cultures, recognizing grasping actions is crucial for assessing performance in daily activities. In this study, we focus on assessing grasping functionality in terms of tableware usage during meals and propose a method for identifying hand movements. In recent years, there has been a surge in developing approaches for hand pose estimation and gesture recognition using deep learning. However, these approaches encounter common challenges, including the need for large-scale datasets, hyperparameter tuning, significant time and computational costs, and limited applicability to incremental learning. To address these challenges, we propose an ensemble approach employing extreme learning machines to recognize grasp postures. In addition, we apply spatiotemporal modeling to extract the relationship between grasp postures and the surrounding tools during mealtimes.
User Action Recognition Using a Fabric Pressure Distribution Sensor in an Electric Wheelchair for Soil Cultivation
Authors: Matsuishi Takahiro , Takahashi Yasutake , Tsuichihara Satoki
Published: January 2025

Advancements in robotics technology and information and communication technology have significantly affected agriculture, especially systems that aid workers. Soil cultivation often requires prolonged bending, which results in physical strain. A commercially available work wheelchair reduces back strain, but lacks power assistance and relies on leg movements. In a previous study, we developed an electric wheelchair with a fabric pressure-distribution sensor on the seat. This sensor, combined with a fuzzy controller, aids movement by measuring the center of pressure fluctuations and reducing leg strain. However, it does not recognize user’s actions, such as standing or sitting, and requires the wheelchair to stop. This study introduced a user-action recognition system using a wheelchair seat pressure sensor. This system accurately recognizes user actions through deep learning time-series data. We evaluated data augmentation and multi-user data to enhance the performance. The results show improved prediction accuracy for action recognition in the test scenarios.
Relationship Between Intellectual Capital, Executive Motivation, and Corporate Innovation Level —Evidence from Chinese Listed Manufacturing Companies
Authors: Ren Junyi , Yu Yunhui
Published: January 2025

In the knowledge economy era, innovation is the main engine that drives high-quality development of the manufacturing industry. Exploring the mechanism behind intellectual capital, its constituent elements that stimulate innovation within manufacturing enterprises, and the influence of executive motivation emerges as a crucial imperative, considering intellectual capital as the sum of intangible assets of enterprises. Unraveling this intricate interplay becomes essential in comprehending the driving forces behind innovation in this sector. Based on this, the present study analyzed the relationship between intellectual capital, executive incentives, and corporate innovation level using a sample of manufacturing companies listed in Shanghai and Shenzhen A-shares from 2012–2021. The empirical findings demonstrate the positive impact of human capital, structural capital, and relational capital on the innovation levels of manufacturing firms. Moreover, executive compensation incentives and equity incentives also contribute positively to enhancing firm innovation. Notably, these executive incentives play a vital moderating role in strengthening the relationship between intellectual capital dimensions and firm innovation. Intellectual capital dimensions have a stronger impact on innovation levels in non-state-owned manufacturing enterprises than in their state-owned counterparts. Moreover, the positive influence of intellectual capital on innovation is more significant in highly marketized regions compared to regions with lower levels of marketization.
Research on Node Fault Diagnosis in Wireless Sensor Networks Based on a Constrained Data Maximum Entropy BN Parameter Learning Algorithm
Authors: Zhao Huiqin , Luo Jiang , Rong Li
Published: January 2025

Currently, power communication wireless sensor networks (WSNs) exhibit the characteristics of uncertainty and complexity. Furthermore, the application environment is more complex, resulting in nodes damaging easily, power communication breakdown, and economic losses. Dynamic monitoring of power communication WSN nodes is necessary. To this end, a constraint data maximum entropy Bayesian network (BN) parameter learning algorithm is used to solve the problem of small data sample size in monitoring and improve the quality of power communication WSN node fault diagnosis. After the latest verification, it is found that the correct rate of WSN node fault diagnosis under small data set is as follows: in normal conditions, the fault rate is 96%, the sensor fault is 94%, the power supply fault is 100%, the wireless communication fault is 90%, and the processor fault is 91%. It can be seen that even under small sample data sets, better diagnostic accuracy can be brought.
Research on the Measurement of Digitalization on the Integration of China’s Manufacturing Industry into the RCEP Regional Value Chain
Authors: Guo Xiaoyang , Chen Yijing , Yang Jingyi , Zhang Xiuwu
Published: January 2025

In this paper, the industry classification of digital economy is determined, the comprehensive index framework of digital economy development level in China is constructed, and the input-output analysis method and index method are used to measure the digital investment status of manufacturing industry in China. At the same time, based on the realistic demand that China’s manufacturing industry needs to climb the regional value chain, this paper constructs the forward participation index, backward participation index, regional value chain position index, and regional value chain Balassa, and analyzes the current situation of China’s manufacturing industry in RCEP region. Construct a semi-parametric additive model to explore the impact of digital investment on China’s manufacturing industry’s participation in the RCEP regional value chain. In addition, this paper uses the community analysis method to build the RCEP regional manufacturing digital input trade network, and comprehensively evaluates the trade network pattern of digital input from multiple dimensions. The results show that: (1) the digital investment in China’s manufacturing industry is increasing year by year. (2) The indicators of manufacturing industry’s participation in RCEP regional value chain show a fluctuating situation, which is generally consistent with China’s economic development. (3) Within a certain range, digital investment will promote the participation of China’s manufacturing industry in the RCEP regional value chain. China is gradually becoming an important participant in RCEP regional trade. According to the corresponding measurement results, it provides policy suggestions for the deep integration of China’s manufacturing industry and digital economy.
A Knowledge Graph Summarization Model Integrating Attention Alignment and Momentum Distillation
Authors: Wang Zhao , Zhao Xia
Published: January 2025

The integrated knowledge graph summarization model improves summary performance by combining text features and entity features. However, the model still has the following shortcomings: the knowledge graph data used introduce data noise that deviates from the original text semantics; and the text and knowledge graph entity features cannot be fully integrated. To address these issues, a knowledge graph summarization model integrating attention alignment and momentum distillation (KGS-AAMD) is proposed. The pseudo-targets generated by the momentum distillation model serve as additional supervision signals during training to overcome data noise. The attention-based alignment method lays the foundation for the subsequent full integration of text and entity features by aligning them. Experimental results on two public datasets, namely CNN / Daily Mail and XSum, show that KGS-AAMD surpasses multiple baseline models and ChatGPT in terms of the quality of summary generation, exhibiting significant performance advantages.
Research on Cross-Border e-Commerce Supply Chain Prediction and Optimization Model Based on Convolutional Neural Network Algorithm
Authors: Zhao Yajie , Gong Bin , Huang Bo
Published: January 2025

Enhancing the precision of supply chain management and reducing operational costs are crucial for the development of the cross-border e-commerce market. However, existing research often overlooks the demand uncertainty caused by seasonal variations and the challenges of handling returns in logistics. Therefore, this paper proposes a SARIMA-CNN-BiLSTM prediction model that effectively captures both the seasonal and nonlinear characteristics of cross-border e-commerce supply chains. Additionally, by incorporating the returns process, a supply chain distribution optimization model is developed with the objective of minimizing total operational costs. The model is solved using an improved whale optimization algorithm. In validation with real-world data, the SARIMA-CNN-BiLSTM model achieved a mean absolute percentage error reduction of 6.479 and 7.703 compared to convolutional neural network (CNN) and BiLSTM models, respectively. Moreover, the chosen optimization algorithm reduced the cost by 231,310 CNY, 62,564 CNY, and 131,632 CNY compared to the whale optimization algorithm, genetic algorithm, and particle swarm optimization, respectively. The proposed approach provides robust support for cross-border e-commerce enterprises in reducing costs and enhancing efficiency in their operations.
Systematic Literature Review: Implementation of Online Learning Based on Education Levels in Indonesia
Authors: Dinata Vania , Wedi Agus , Fajarianto Otto
Published: January 2025

The COVID-19 pandemic has significantly accelerated the adoption of online learning, prompting extensive research on its implementation across various educational levels in Indonesia. This study employs the Systematic Literature Review (SLR) method, analyzing 13 articles from the GARUDA database, published between 2019 and 2023. The findings reveal diverse platforms utilized for online learning, including Google Classroom (3 mentions), Quizizz (2 mentions), Edmodo (3 mentions), WhatsApp (2 mentions), and custom-developed platforms. At the primary and secondary education levels, platforms like Quizizz and Edmodo were associated with improvements in student motivation (42.5% increase in motivation) and learning outcomes (up to 84% in comprehension improvement for specific materials). However, challenges such as limited internet access and reduced interaction hindered learning experiences. In higher education, Google Classroom was the most frequently cited platform, enhancing accessibility and learning independence. Despite these benefits, issues such as unstable internet connectivity, skill-based material comprehension, and limited engagement persisted. This study concludes that online learning has notably improved accessibility, motivation, and learning outcomes, with significant potential to enhance educational quality. However, addressing barriers such as technical limitations and fostering better interaction are essential for further optimization. These insights provide valuable guidance for refining online learning practices and policies in Indonesia.
Exploring High School Students' Mathematical Reasoning in Geometry Using GeoGebra-Assisted Problem-Based Learning
Authors: Nuralam Humam , Jupri Al , Alifulloh Wenda
Published: January 2025

The significance of mathematical reasoning in mathematics instruction and the substantial incidence of inadequate mathematical reasoning among high school students prompted this study. This study intends to explore the mathematical reasoning of high school students about three-dimensional geometry using the GeoGebra-assisted Problem-Based Learning (GPBL) model. This research applied a quasi-experimental design including a non-equivalent pretest and posttest control group. The subjects of this research were specifically 12th-grade students from an upper secondary school in Subang. The research contained two classes, with 27 students as the experimental group and 27 as the control group. Interviews were conducted to identify the factors that explain students' difficulties in solving mathematical reasoning problems concerning three-dimensional geometry. The findings indicated that (1) overall, the enhancement of mathematical reasoning among students utilizing the GPBL model was significantly higher than that of students implementing the conventional learning model; (2) referring to students' prior mathematical ability (PMA), the enhancement in mathematical reasoning for students in high, medium, and low PMA groups utilizing the GPBL model was significantly higher than that of students implementing the conventional learning model; (3) the main obstacle discovered by students to solving mathematical reasoning problems involving three-dimensional geometry is their struggle in visualizing problems in a three-dimensional context. GeoGebra assists students in visually constructing three-dimensional geometry problems and evaluating the outcomes of algebraic algorithms with 3D graphical representations.
Development of E-Books Oriented to Banten Culture Integrated with Challenge Based Learning to Improve Elementary School Students' Creative Thinking Skills in Science Learning
Authors: Putri Vina Karina , Ainulhaq Nurisa , Rahmadani Kurniati
Published: January 2025

Future demands are very complex, including the ability to generate new ideas, find unique solutions, and think flexibly and elaboratively. The purpose of this study is to develop students' creative thinking skills, especially in the subjects of Natural Sciences and Social Sciences (IPAS), which are often neglected in the learning process using e-books. This study uses the Research and Development (R&D) method with the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model. Data analysis was carried out using the one group pretest-posttest model. The subjects of the study were fifth grade students of SD Negeri 5 Banjarsari, Cipocok Jaya District, Serang City. The results of this study indicate that the developed E-Book is feasible and effective for use in the learning process, as evidenced by the assessment of learning design experts obtaining a score of 97.78% (very good), the assessment of content experts obtaining a score of 90.62% (very good), and the assessment of learning design and media experts obtaining a score of 97.50% (very good). The product effectiveness test also showed a significant difference between before and after using the E-Book. The results of the study concluded that the Banten Culture-oriented E-Book integrated with Challenge Based Learning (CBL) was able to improve students' creative thinking skills in science learning. The E-Book also received positive responses from both students and teachers, both in terms of content, design, and usability in the learning process. The recommendation is that this E-Book can be said to be an effective alternative learning media to improve the quality of education in elementary schools, especially in science learning.
Critical Portrait of Vocational High School Accounting Teachers Sustainable Awareness in Indonesia
Authors: Sri Sumaryati  , Ivada Elvia , Susanti Asri Diah , Nurhaini Lies
Published: January 2025

about their actions’ environmental and social impact, Education teaches students to think critically and responsibly towards the surrounding environment. Therefore, as the spearhead of education, teachers must be aware of sustainability education, so that they can teach it to their students Hence. This research explores the knowledge, attitudes, and behaviors towards sustainable awareness, especially in accounting teachers, and analyzes the interdimensional relationship to sustainable awareness.  This research uses a quantitative approach with a survey type of research. The data source for this study is 277 Vocational High School accounting teachers from the program of the institution's accounting and finance expertise, consisting of 239 females, and 38 males. They all participated in Teacher Professional Education at Universitas Sebelas Maret  Surakarta in 2023. The instrument used in this study is the Sustainability Consciousness Questionnaire (SCQ), developed by Gericke et al. in 2019. As a result of this study, teachers have knowledge about sustainable awareness that is followed up with sustainable attitudes and behaviors even though they are not optimal. This result can be seen from the high average score on knowledge of sustainable awareness, not followed by a high score on sustainable attitudes and behaviors. The study results show that each component's scores are 3.44, 3.17, and 3.13. This means that knowledge of sustainable awareness is not balanced with sustainable attitudes and behaviors.
STUDI ALIRAN 3-D NEAR ENDWALL PADA INTERAKSI AIRFOIL DAN PLAT DATAR
Authors: Rachman Arfidian , Yuana Dewi Arfita , Effendi Asnal
Published: January 2025

Kajian-kajian mengenai keberadaan struktur aliran sekunder ini didasarkan pada efek munculnya aliran sekunder didalam konfigurasi wing-body pada pesawat terbang, yaitu adanya wingtip-vortex pada tip region dan terciptanya beberapa unsur aliran vortex pada daerah sambungan (endwall region), keduanya bersama-sama akan menyebabkan blockage aliran utama. Adanya efek blockage ini akan mempengaruhi karakteristik aerodinamis lift dan drag, dimana hal ini secara langsung berpengaruh terhadap efektifitas dan efisiensi wing. Pada daerah endwall fenomena yang bisa diamati adalah terjadinya pergeseran posisi saddle point menuju pressure side. Sedangkan dari kontur isobar ditemukan pergerakan titik minimum pressure pada upper surface semakin mendekati leading edge, dan area maximum pressure pada lower surface bergerak menuju ke pressure side. Penelitian yang akan dilakukan dengan eksperimental pada sebuah variasi geometri wing yang dimodelkan pada flat plate dengan variasi angle of attack (α) = 0o. Hasil yang akan didapat berupa isobar contour pada endwall dan body serta flow visualization pada endwall dan body.