bluuebunny/crossref_metadata_2025 huggingface dataset:
Sustainable ecosystem of business models: experience and lessons of the development project
Authors: Nekrasova M. A. , Palagin V. S.
Published: October 2024

The article considers an example of expanding the area of interest of the project to the sphere of pre-project activities aimed at solving the tasks of business planning and forming the concept of the future product. The main objective of the study is to review current and propose effective approaches to project business planning in the National Park—Development Region system.

To develop an effective, sustainable ecosystem of national park business models that make a positive contribution to the regional gross product (RGP) of the region, the current approaches to assessing the contribution of economic and other activities, including project activities, to the socio-economic development of regions and the country as a whole were analyzed. The analysis uses methodological recommendations for the development and adjustment of development strategies, as well as national indicators of socio-economic, sustainable, low-carbon development, climate change adaptation of the region’s economy. As a result of application of the considered approaches to business planning of the project in the system ‘National Park — Development Region’ a  list of measures to increase the investment attractiveness of the national park was developed. All activities are successfully compatible with the main objectives of the national park, such as preservation of biodiversity and cultural values (code) of the region. Business models are proposed for the effective contribution of national parks to the socio-economic development of the development region, taking into account the natural-resource and recreational potential of the park, interests of the local population, participants of internal and external tourism.

The sustainable ecosystem of business models for national park development considered in this article is not limited to the framework of a unique study for one region. The super task of this study was to create a prototype for sustainable socio-economic development of regions that include a network of regional protected areas and national parks.
Research on the creation concept of "beautiful material and skillful workmanship" in modern product design
Authors: Wu Ying dong , Shajinbat Ariunaa
Published: October 2024

In contemporary society, product design is no longer limited to simple functional considerations, but has gradually evolved into a comprehensive discipline that integrates art, technology and humanities. As the three core elements of product design, material, aesthetics and technology play a vital role in shaping product shape, improving user experience and transmitting cultural connotation. This paper aims to deeply explore the creation concept of "material beauty and workmanship" in product design, through the analysis of Chinese traditional creation concept and pragmatic aesthetics, as well as the study of the post-industrial era and personalized consumption trend, combined with the relationship between materials, aesthetics and technology in modern product design, to explore its application value in contemporary product design. It is hoped that these studies can provide useful inspiration and reference for the development and innovation of product design field.
Cognitive technologies in the process of influencing the preparation of journalistic text in the digital media field
Authors: Doroschuk Elena Sergeevna
Published: October 2024

The author considers the features of cognitive technologies in the social space of digital communications as an element of modern journalist activity. Based on the modeling of the processes of creating a journalistic text, the specific features of the use of cognitive technologies and their functional potential in the media space of regional media are highlighted. The potential of cognitive technologies in relation to the development of modern digital media as a social phenomenon has been determined.
Building waste caring character: School-based waste management training at SMP Muhammadiyah 10 Yogyakarta
Authors: Muttaqien Muhammad , Rizqi Muhammad Arif , Nooresa Alifya Fathiyyah , Indahsari Dewi Ayu , Febri I Wayan Nain
Published: October 2024

Since 2010, Muhammadiyah has recognized that waste materials such as plastic, paper, cans, and aluminum still contain energy. One of Muhammadiyah schools that utilizes plastic waste is SMP Muhammadiyah 10 Yogyakarta (Muhdasa) through its "sedekah sampah" (charity waste) task force. However, the task force members are active students who change every year, requiring continuous education. Additionally, there was no centralized collection point for plastic bottles. This community service aimed to enhance students' knowledge about waste types and management, as well as cultivate their environmental consciousness. The method employed involved initial observation followed by socialization in collaboration with the environmental communities Hero Trash Yogyakarta and Akshi UMY. The results show that students gained a better understanding of waste classification and management, as evidenced by their participation in plogging activities (picking up litter while jogging). The activity concluded with the donation of a metal bin for collecting plastic bottles.
Optimization of Wae Bobok based on community based tourism through green products and digitalization
Authors: Dewi Luh Komang Candra , Arini Ni Nyoman , Priastana I Ketut Andika
Published: October 2024

This activity aims to empower local communities in Wae Bobok Area through a community based tourism approach that integrates the concept of green products and digitalization. The method used in this activity is training and mentoring. The results of this activity show that the community based tourism approach by integrating the concept of green products and digitalization is able to empower local communities in the Wae Bobok Area significantly. Through mapping the potential of tourism and MSME products, it has succeeded in designing attractive tour packages by utilizing the uniqueness and beauty of nature and local culture. Assistance in packaging MSME products and green product innovation has encouraged the development of sustainable and environmentally friendly tourism products. Assistance in creating virtual tours have succeeded in increasing the exposure of Wae Bobok tourist destinations and MSMEs. By using digital technology, this destination can be reached by a wider community. Waste management assistance using the TPS3R system has succeeded in improving the cleanliness and comfort of tourist destinations. By continuing to develop this program and involving all stakeholders, it is hoped that Wae Bobok can continue to develop sustainably.
Addressing students' mental health through peer counseling at SMK Muhammadiyah 4 Surakarta
Authors: Hamidah Rista Nur , Santinintyas Widya Yuli , Kristanto Ichsan , Daliman Daliman
Published: October 2024

SMK Muhammadiyah 4 Surakarta recognizes the importance of enhancing students' awareness of peer counseling to support their psychological well-being. This community service aimed to improve students' understanding of peer counseling roles and skills through activities including materials provision, Focus Group Discussions (FGDs), and peer counseling practice. Post-test results indicated a significant increase in students' comprehension of peer counseling concepts, including emotional support provision. FGDs offered a platform for students to discuss and share experiences, while peer counseling practice provided firsthand experience as both counselor and client. This community service successfully enhanced students' understanding of peer counseling.
Oral health education and methods for detecting the replacement of deciduous teeth with permanent teeth
Authors: Arini Roro Ambar , Fitriani Rahmania Ade , Novildan Naufal Hanif Syah , Saleh Edwyn , Nugroho Aji , Utami Sri , Puspita Sartika
Published: October 2024

Indonesian people's awareness of oral health is still relatively low, as evidenced by the number of people who seek dental treatment and check-ups only when experiencing dental problems. Based on this issue, promotive and preventive efforts are needed through oral health education. The oral health status of the people in Dusun Botokan shows that many people do not have their teeth and mouths checked. Therefore, the purpose of this community service activity is to improve the knowledge and healthy behaviors of the people of Dusun Botokan regarding oral health. The method used is education as a promotive and preventive effort, as well as medical services as a curative effort. The success of the activity is seen from the short-term results in the form of an increase in pre-test and post-test scores by 12.74%. Thus, this activity has succeeded in increasing the knowledge of tooth replacement detection and awareness of oral care in the community of Dusun Botokan.
Enhancement of packaging quality and digital marketing management for SuleMu soy milk
Authors: Rahayu Triastuti , Nurcahyanto Guntur , Aryani Ima , Maimun Muhammad Halim , Ripdianti Arum Dyah
Published: October 2024

SuleMu is a soy milk product produced by KL LazisMu SMP Muhammadiyah 7 (SMP MUTU) Colomadu, Karanganyar Regency, Central Java Province. Although SuleMu packaging has a label, it lacks nutritional information. Additionally, its marketing strategy is still traditional. Therefore, this community service aims to add nutritional information to SuleMu packaging and create a digital marketing platform. The implementation of this program began with coordination, nutritional analysis, packaging label redesign, digital marketing training, the creation of a SuleMu digital marketing platform, and evaluation. The results of the nutritional analysis of SuleMU per 100g were: protein (3.4g), fat (3.3g), sugar (5.1g), crude fiber (2.6g), and calcium (40mg). This data has been added to the new SuleMu label. For digital marketing training, the average pre-test scores for WhatsApp Business and Instagram materials were 72.57 and 73.14, respectively, while the average post-test scores were 87.43 and 81.43. SuleMu also now has digital marketing accounts on Instagram and WhatsApp Business.
Museos y tecnología: El caso del MACA y su interacción con el público
Authors: Guijarro Sánchez Rocío , Iglesias-García Mar
Published: October 2024

Introducción: Los museos deben adaptarse a la era digital para mejorar la interacción con su público. El Museo de Arte Contemporáneo de Alicante (MACA) ha implementado las TIC para enriquecer la experiencia de sus visitantes. Este estudio investiga el impacto de las TIC en la interacción del público con el MACA, evaluando su conocimiento del museo, uso de recursos digitales y percepciones sobre la tecnología. Metodología: Se encuestaron 150 visitantes del MACA durante seis semanas en octubre y noviembre de 2023, con preguntas sobre perfil del público, conocimiento del museo, uso de recursos digitales y experiencia con las TIC. Resultados: La mayoría de personas visitaban el museo por primera vez, principalmente mujeres de 46 a 65 años, que conocieron el MACA a través de Google Maps. Pocas personas utilizaron recursos digitales como códigos QR, aunque hubo interés en más recursos digitales, especialmente audioguías multilingües. Discusión: Los resultados muestran una actitud positiva hacia la integración de las TIC, resaltando la necesidad de mejorar la visibilidad y funcionalidad de los recursos digitales. Conclusiones: El estudio destaca la importancia de mejorar las estrategias de comunicación y servicios digitales del MACA para enriquecer la experiencia del público y aumentar la participación con el arte contemporáneo.
Competencias para la promoción de una educación inclusiva en el aula universitaria: un análisis de las habilidades y conocimientos docentes
Authors: García Leiva Silvia , Romero López M.ª Asunción
Published: October 2024

Introducción: Las organizaciones internacionales destacan la importancia de que la Educación Superior sea accesible para todos, sin importar origen social, raza, etnia, género o discapacidad. La capacitación de profesores en educación inclusiva es esencial para lograr una enseñanza equitativa y de calidad. Metodología: Este estudio cualitativo interpretativo analiza las competencias inclusivas de los docentes mejor evaluados de la Universidad Tecnológica de Chile Inacap, Valdivia, mediante entrevistas a 12 docentes destacados. Sus relatos permitieron identificar categorías emergentes sobre factores relevantes para una enseñanza inclusiva y centrada en el aprendizaje. Resultados: Los resultados muestran que los docentes tienen competencias como adaptarse a la diversidad del estudiantado ofrecer estrategias de enseñanza personalizadas y ser sensibles a las necesidades individuales. También valoran la motivación y la experiencia previa en el aprendizaje, adoptan prácticas inclusivas en la evaluación y refuerzan el aprendizaje. No obstante, enfrentan desafíos como la adaptación a diversos perfiles de estudiantes y la necesidad de más recursos, capacitación y apoyo institucional. Conclusiones: En conclusión, las competencias inclusivas de los docentes promueven la participación y el éxito de todos los estudiantes. Fortalecer estas competencias mediante capacitación docente y soporte institucional es crucial para mejorar la inclusión en la Educación Superior.
Решение двумерного нелинейного параболического уравнения теплопроводности при краевом режиме, заданном на подвижном многообразии
Authors: Казаков А. Л. , Нефедова О. А. , Спевак Л. Ф.
Published: October 2024

Статья посвящена исследованию вырождающегося параболического уравнения теплопроводности с нелинейностями общего вида при наличии источника (стока) в случае двух пространственных переменных. Рассмотрена задача об инициировании тепловой волны, распространяющейся по холодному (нулевому) фону с конечной скоростью, краевым режимом, заданным на подвижном многообразии — замкнутой линии. Для нее доказана новая теорема существования и единственности и предложен численный алгоритм построения решения, основанный на методе граничных элементов, методе коллокаций и разностной аппроксимации по времени, при этом использована специальная замена переменных типа преобразования годографа. Найдены новые точные решения рассматриваемого уравнения в случае нелинейностей степенного вида. Численный алгоритм реализован в виде программы, проведен комплексный вычислительный эксперимент. Сравнение построенных численных решений с точными (как найденными в работе, так и ранее известными) показало хорошее соответствие, установлена численная сходимость относительно шага по времени и числа точек коллокации. Библ. 28. Фиг. 3. Табл. 4.
Локальная вейвлетная адаптация декартовых сеток в вычислительных задачах газовой динамики
Authors: Афендиков А. Л. , Никитин В. С.
Published: October 2024

Представлен метод динамической локальной адаптации градуированных декартовых деревьев для численного решения задач газовой динамики. Локальный вейвлетный анализ газодинамического поля на базе неравномерных B-сплайнов применяется независимо к каждой ячейке расчетной сетки и позволяет выделить негладкие или существенно нелинейные участки решения (или наоборот, достаточно гладкие и линейные) и модифицировать сетку для расчета следущего шага по времени так, чтобы у разномасштабных особенностей течения было адекватное сеточное разрешение. В комбинации с другими методами вычислительной газовой динамики, такими как метод свободный границы, представленный метод позволяет эффективно решать нестационарные задачи с обтеканием движущихся тел. На ряде таких задач продемонстрирована работа предложенного варианта вейвлетной адаптации. Библ. 37. Фиг. 5.
Brazil’s new economic policy
Authors: Simonova L. N , Ponomarev E. A
Published: October 2024

The article presents a critical analysis of the main economic programs adopted in Brazil in the first year and a half of Lula da Silva's rule (2023 – the first half of 2024), and which will determine the country's development strategy for the next decade. Particular attention is paid to diagnosing the current state of industry and infrastructure in Brazil, analyzing the causes of deindustrialization, assessing the opportunities and risks of strengthening the role of the state in the modernization of industry and the implementation of large-scale infrastructure projects. The success of new development programs and their geopolitical impact will depend on the effectiveness of public resource management, improved planning and implementation of projects, and increased interaction and control at the federal and sub-regional levels.
Brazil: new guidance for cultural policy
Authors: Konstantinova N. S
Published: October 2024

The article is devoted to the new guidelines for the cultural policy of Brazilian President Luiz Inacio Lula da Silva and his government for the period since the 2023 elections. The main tasks set in this area immediately after coming to power are outlined, the algorithms and deadlines for their implementation are specified. The primary role of the recreated Ministry of Culture in achieving its goals is highlighted. Particular attention is paid to the formation of a legislative framework on the basis of which a new cultural policy will be carried out in line with the democratic model of state power. An assessment of the results achieved during the first hundred days of the reign is given. A chronology of the most significant events in the field of cultural policy in the current year, 2024, is presented. The final part examines both the positive aspects of the work done and the risks that must be taken into account in the further successful implementation of the assigned tasks.
НОВИЙ МЕТОД ДЕШИФРУВАННЯ ДІАГНОСТИЧНОЇ ІНФОРМАЦІЇ НА ОСНОВІ ІНТЕРВАЛЬНИХ ОЦІНОК
Authors: БАРАБАШ Олег , МАКАРЧУК Андрій
Published: October 2024

Активний розвиток обчислювальних систем та, як наслідок, збільшення сфер їх застосування ставить перед науково-технічним прогресом ряд нових задач, однією з найважливіших з яких є організація діагностування систем. Оскільки габарити та складність обчислювальних систем постійно зростає, то логічною є спроба організувати їх діагностування в автономному режимі, при мінімальному, а то й взагалі без участі людини.
На даний момент, такий спосіб діагностування можна реалізувати, наприклад, програмно в два етапи: збір діагностичної інформації та її дешифрування. З деякими проблемами можна стикнутися саме на етапі дешифрування, оскільки багато запропонованих на даний момент дешифрування діагностичної інформації вимагають досить багато обчислень. В силу того, що сучасні обчислювальні системи можуть містити дуже велику кількість елементів, об’єм діагностичної інформації може бути досить великим. В наслідок цього застосування деяких існуючих методів дешифрування діагностичної інформації може займати багато часу. Це пов’язано з тим, що, на відміну від збору діагностичної інформації, розроблені на даний момент методи її дешифрування вимагають велику кількість обчислень: деякі з них мають експоненційну складність відносно кількості елементів системи. А даний фактор може бути критичним при розробці, наприклад, великих інформаційних систем чи систем критичної інфраструктури. Це породжує необхідність в розробці нових, більш швидких методів дешифрування.
В даній роботі пропонується новий метод дешифрування діагностичної інформації, який є дещо швидшим від багатьох існуючих. Даний факт досягається завдяки поєднанню інтервальних оцінок та розподілу Бернуллі, які не вимагають надмірної кількості обчислень. Також коротко описано особливості даного методу, одна з яких наглядно демонструється на двох конкретних прикладах інформаційних систем.
АЛГОРИТМ ПЕРЕХОДУ ВІД МОНОЛІТНОЇ ДО МІКРОСЕРВІСНОЇ АРХІТЕКТУРИ ІЗ ЗАСТОСУВАННЯМ МЕТОДІВ КЛАСТЕРИЗАЦІЇ ГРАФІВ
Authors: КОРНАГА Ярослав , ГУБАРЄВ Олександр
Published: October 2024

У даній статті представлений підхід до трансформації монолітної архітектури в мікросервісну з використанням bottom-up стратегії декомпозиції. В данному підході використовується статичний аналіз коду для представлення монолітної системи у вигляді зв’язного графа. На другому етапі, використовуючи алгоритми кластеризаціїї, відбувається кластеризація графа. На третьому — оптимізація отриманих кластерів.
ІНСТРУМЕНТИ СТИМУЛЮВАННЯ МІСЦЕВОГО ЕКОНОМІЧНОГО РОЗВИТКУ УКРАЇНИ В УМОВАХ НЕСТАБІЛЬНОСТІ
Authors: ВАСИЛЬЦІВ Тарас , ЛЕВИЦЬКА Ольга , КРАВЧИК Юрій
Published: October 2024

The research emphasizes the objectively existing need, as well as the problems of ensuring local economic development in Ukraine, in particular under conditions of critically acute economic and social instability caused by a full-scale war and its consequences. The purpose of the study is to determine the scientific justification of the tools for stimulating and ensuring the local economic development of Ukraine under the instability. It is shown that in the conditions of a full-scale war, the regional socio-economic systems of Ukraine faced such challenges as large-scale external and internal migrations of the population, deepening of depopulation problems, reduction of employment and the number of jobs due to the cessation of activities or relocation of enterprises, the growth of precarization in the labor market and social and labor insecurity of vulnerable categories of the population, the development of sectoral and structural imbalances and the strengthening of personnel problems in the labor markets. Accordingly, the latest challenges have become the main causes of destabilization of the spatial development of Ukraine's economy. The results of the analysis made it possible to identify, firstly, the significant typicality of existing problems, secondly, the significant resource limitations of local self-government bodies, thirdly, the need to involve innovative solutions, fourthly, the relevance of developing practices of intermunicipal socio-economic cooperation and integration of efforts in this way, fifthly, the need for a systemic and strategic approach, when based on visions, strategies and development programs, investment passports of territorial communities, a single coordinated regional master plan of industry specialization and development will be formed. The basic principles of two regional policy strategies in terms of stimulating local economic development are substantiated: (1) stabilization, (2) proactive. The strategic goal of each of these approaches is indicated, as well as a set of tools is defined, the implementation of which allows to activate the processes of local economic development in Ukraine under current conditions of instability.
Pengembangan Model Bimbingan Kelompok dengan Teknik Proyeksi dalam Peningkatan Resiliensi Diri Siswa Korban Kekerasan Seksual
Authors: Asri Robbi , Ifdil Ifdil , Karneli Yeni , Netrawati Netrawati , Amora Rendy
Published: October 2024

Penelitian ini bertujuan menganalisis pengembangan model bimbingan kelompok dengan teknik proyeksi dalam peningkatan resiliensi diri siswa korban kekerasan seksual. Penelitian ini menggunakan metode kuantitatif dan kualitatif dengan Research and Development (R&D). Subjek penelitian ini adalah 10 siswa korban kekerasan seksual untuk kelompok eksperimen di SMA N 15 Padang. Data diperoleh melalui observasi, wawancara, dokumen dan instrumen penelitian resiliensi diri. Data dianalisis dengan menggunakan Wilcoxon Signed Ranks Test dan SPSS versi 21.00. Hasil penelitian mengungkapkan bahwa (1) model bimbingan kelompok dengan teknik proyeksi berbasis user website dinilai layak digunakan oleh Guru BK/Konselor dalam peningkatan resiliensi diri siswa korban kekerasan seksual, (2) tingkat keterpakaian model bimbingan kelompok dengan teknik proyeksi dinilai sangat baik digunakan dalam layanan bimbingan dan konseling. Maka dapat diketahui prototype model bimbingan kelompok dengan teknik proyeksi dalam peningkatan resiliensi diri siswa korban kekerasan seksual dinyatakan layak dan dapat dimanfaatkan oleh Guru BK/Konselor dalam meningkatkan resiliensi diri siswa korban kekerasan seksual.
DEM Analysis of Ballast Particle Direct Shear Tests: Exploring the Influence of Varying Particle Size Distributions on Shear Stress
Authors: Chalabii Jafar , Movahedi Rad Majid
Published: October 2024

The dimension of particles can significantly influence the load response and the performance of uniformly graded ballast layers in railway track structures in real-world conditions. Yet, the micromechanical behavior of the unbound aggregate ballast layer assembly, particularly affected by particle size, remains largely unexplored. In this study, the distinct element model of a direct shear test was initially simulated using friction coefficients of 0.8, 0.9, and 1, and particle size distribution No.4A. The dimensions of the shear test box were 300 mm in width, 300 mm in length, and 180 mm in height. Additionally, a constant normal force of 333 kPa was applied to the sample during the simulation. Subsequently, this model was compared with experimental results, revealing a close correspondence between simulated and experimental shear stress-displacement curves, particularly for the friction coefficient of 1. Following this verification, the validated model was employed to investigate three other particle size distributions: No.4, No.5, and No.57. The results demonstrated a reduction in shear stress for particle size distributions No.4, No.5, and No.57 compared to No.4A, with quantified decreases of 11.9%, 38.2%, and 56.7%, respectively.
Experiments of Time-Periodic Control During Run-Up of a Flexible Rotor
Authors: Fasih Muhammad Saad , van Baren Johannes , Dohnal Fadi
Published: October 2024

Flexible rotors must pass through at least one critical speed before reaching its nominal or working speed. During passage through this resonance, transient vibrations are introduced in the rotor. For a better performance of the machinery, these vibrations must be kept below a certain threshold to keep a small clearance between the rotor and the stator. Modal coupling by periodic control is a modern approach which is capable of transferring kinetic energy between two selected modes. By introducing a time-periodic variation of the bearing characteristics, a modal energy transfer is induced in a flexible rotor during run-up and run-down. This concept reduces the main resonance peak during passage through resonance compared to the nominal run-up. By the application of this technique, we were able to reduce the maximum amplitude response during the run-up to 25.4 percent and during the run-down to 27.1 percent.
An Alternative Mooney-Rivlin Material Model for Finite Strain Plasticity
Authors: Écsi Ladislav , Jančo Roland
Published: October 2024

Contemporary hyperelastic-based material models for finite strain plasticity use a multiplicative split of the deformation gradient into an elastic part and a plastic part to imitate the inelastic behaviour of hyperelastic materials. The models have several serious disadvantages originating from the multiplicative split. This paper presents an alternative Mooney-Rivlin material model for finite strain plasticity, which uses a variant of the additive split of the strain rate tensor into elastic and plastic parts and has none of the disadvantages of the related multiplicative plasticity model. The underlying theory allows for expressing the multiplicative split of the deformation gradient in the proper form, thus providing a framework for developing a universal continuum theory for finite elastoplastic deformations of solids.
Improved Equations of the Classic Hunting Problem of Railway Wheelsets
Authors: Finta Ervin , Antali Mate
Published: October 2024

In this paper, the equations of motion are derived for a railway wheelset by the systematic linearisation of the full nonlinear description. Compared to the standard approximate equations of the literature, the new form of differential equations improves the values of some coefficients and also adds the correct values of terms from gravity and gyroscopic forces. The resulting model can be used to describe the stability loss called hunting motion, and can be included in models of whole railway vehicles.
Novel Technique for Reducing Geometrical Inaccuracies of Clamped Workpiece During Machining: A Hybrid Method
Authors: Ledenyák Dániel , Rosta Tamás , Hargitai Hajnalka
Published: October 2024

The aim of this paper is to provide a novel technique in production technology, which ensures the adequate tightening torque of workpiece by a vise connector to minimize the effect of elastic deformation, therefore geometrical inaccuracies roughness, during machining process. This effect emerges if the clamping force is excessively high, resulting in a deformed workpiece with a slightly convex surface. Once this surface is machined and the clamping force is released, the material returns to its initial shape and the newly machined flat surface will be concaved, resulting geometrical inaccuracy. The method is based on a simple workpiece, where the elastic deformation is numerically modelled and experimentally measured as a function of different clamping heights and tightening forces. During the experiments, the workpiece is tightened by bolts, step by step, and in each step, the deformation of the surface is measured with a coordinate measuring machine equipped with a Touch Probe Measurement system. This measurement process is followed by finite element modelling, where the same system, with identical boundary conditions (load, constraints, material properties), are computationally created to compare the numerically and experimentally obtained results. As a result of evaluating various cases, a user-friendly database was established that provides recommendations for specific geometry, position, and capture height. Our model can also propose a minimum clamping height if geometry, position, and maximum force(s) are specified during machining.
Application of Bored Pile Technology Under Complex Geological Conditions
Authors: Hou Xiangyang , Miao Xin , Yi Xiaoli , Wang Zhenjun , Chen Yongle , Zhang Xu , Hui Bin
Published: October 2024

The paper systematically explores the application and optimization strategy of bored pile construction technology in light of the intricate and dynamic surrounding environment, challenging geological conditions, and significant potential damage, based on extensive research conducted for a subway station construction project. The entire process, from lofting measurement to final hole formation, hole clearing, steel cage fabrication, underwater concrete pouring, and post-grouting construction, is comprehensively detailed. Furthermore, the key control points of bored pile construction are further extracted and summarized. In-depth analysis and discussion are conducted on the two core technical challenges in this project case: reasonable mud proportion control to ensure hole wall stability and prevent the risk of collapse; as well as scientific installation and arrangement of grouting pipes to guarantee grouting quality and subsequent effectiveness. Through comprehensive case analysis and in-depth exploration of key technologies, this paper aims to provide meticulous and practical construction strategies as well as a solid reference framework for similar underground projects, thereby enhancing the quality and efficiency of bored pile construction under complex environmental conditions.
A Sustainable Approach for Reversing the Structural Design Process of Steel Structures: From the Traditional Minimum-Weight Approach to the Cutting Losses Minimization
Authors: Cucuzza Raffaele , Movahedi Rad Majid , di Bari Roberta , Domaneschi Marco , Marano Giuseppe Carlo
Published: October 2024

In this research, a Genetic Algorithm (GA) has been developed and the well-known one-dimensional bin packing problem (BPP) has been implemented within the structural optimization process. The Objective Function formulation lies in a marked change of the paradigm in which the target function is represented by the amount of steel required by the factory instead of the structural cost (e.g. weight). The best design is obtained by varying the geometry properties of the members and the cross-section assignation ensuring optimal stock of existing elements. Finally, the structural cost and the Carbon emission are calculated for a spatial reticular dome. The mass of the waste with respect to the mass of the stock, Mwaste/Mstock, is evaluated by adopting both the cutting Stock approach and the traditional approach. The former leads to a waste saving that is almost twice that obtained from the latter. However, no significant differences in terms of carbon emission can be observed by comparing the two approaches.
Comparison of Mechanical Properties of PLA-Based Biocomposites Filled with Different Agricultural By-Products
Authors: Jakab Sándor Kálmán , Singh Tej , Lendvai László
Published: October 2024

In this study, biopolymer composites were developed using poly(lactic acid) (PLA) as a polymer matrix. Various agricultural by-products, including flax seed meal, rapeseed straw, and mustard seed meal, were added as a reinforcement. The research aimed to provide insight into the valorization of cheap, readily available residues generated in the agricultural industry and assess the mechanical properties of composites prepared using them. The experimental fabrication was conducted by compounding PLA with agro-waste particles in 10 and 20 wt% concentrations. These components were melt mixed with a twin-screw extruder and injection molded into standardized forms. The resulting fabricated composites were tested for tensile and flexural mechanical properties and hardness. Through scanning electron microscopy, images of the natural particles were taken to better understand their structure, geometry, and possible ways of interaction between them and the PLA matrix. The results of quasi-static mechanical tests suggest that using agricultural by-products can effectively improve Young’s modulus and flexural modulus of PLA but at the cost of tensile and flexural strength, which decreased with the by-products’ introduction. Of the three agro-waste options, rapeseed straw emerged as the superior choice because it only marginally reduced the mechanical strength of the PLA and enhanced its stiffness the most. Hardness was the least affected property, test results showed that the added fillers did not substantially change the polymer matrix’s hardness.
Effect of Waist Strap Reinforcement in Backpacks on Children Gait Parameters During Walking and Running: A Randomized Cross-Over Prospective Study
Authors: Huang Li , Xu Yining , Fekete Gusztáv , Gu Yaodong
Published: October 2024

As academic demands increase, school-aged children and adolescents often carry heavy backpacks, impacting their posture and musculoskeletal health. This study examines how backpack carriage affects children’s gait, focusing on the influence of waist strap design. In this study, twelve children underwent biomechanical tests while walking and running with and without backpacks, with weights adjusted based on daily habits. It can be found that waist strap-equipped backpacks significantly increased load response (F = 58.031, P < .001) and pre-swing phases (F = 58.031, P < .001) during both activities. In running, these backpacks also prolonged load response (F = 3.10, P = 0.004) and pre-swing phases (F = 3.10, P = 0.004). The study concludes that waist strap-equipped backpacks alter gait dynamics in children, affecting phases and contact times without impacting symmetry. This underscores the importance of waist straps in enhancing stability and reducing fatigue during backpack carriage.
The World is a Multi-Objective Multi-Agent System: Now What?
Authors: Rădulescu Roxana
Published: October 2024

Most complex problems of social relevance, such as climate change mitigation, traffic management, taxation policy design, or infrastructure management, involve both multiple stakeholders and multiple potentially conflicting objectives. In a nutshell, the majority of real world problems are multi-agent and multi-objective in nature. Artificial intelligence (AI) is a pivotal tool in designing solutions for such critical domains that come with high impact and ramifications across many dimensions, from societal and economic well-being, to ethical, political, and legal levels. Given the current theoretical and algorithmic developments in AI, it is an opportune moment to take a holistic approach and design decision-support tools that: (i) tackle all the prominent challenges of such problems and consider both the multi-agent and multi-objective aspects; (ii) exhibit vital characteristics, such as explainability and transparency, in order to enhance user agency and alignment. These are the challenges that I will discuss during the Frontiers in AI session at ECAI 2024, together with a brief overview of my work and next steps for this field. This paper summarises my contribution to the session.
Zero-Waste Machine Learning
Authors: Trzcinski Tomasz , Twardowski Bartłomiej , Zieliński Bartosz , Adamczewski Kamil , Wójcik Bartosz
Published: October 2024

Today, both science and industry rely heavily on machine learning models, predominantly artificial neural networks, that become increasingly complex and demand more computing resources to be trained. In this paper, we will look holistically at the efficiency of machine learning models and draw the inspirations to address their main challenges from the green sustainable economy principles. Instead of constraining some computations or memory used by the models, we will focus on reusing what is available to them: computations done in the previous processing steps, partial information accessible at run-time, or knowledge gained by the model during previous training sessions in continually learned models. This new research path of zero-waste machine learning can lead to several research questions related to efficiency of contemporary neural networks - how machine learning models can learn better with less data? How they select relevant data samples out of many? Finally, how can they build on top of already trained models to reduce the need for more training samples? Here, we explore all the above questions and attempt to answer them.
Contributions to the Journal Track
Authors: Behnke Gregor
Published: October 2024

The journal track of the 27th European Conference on Artificial Intelligence (ECAI-2024) offered the authors of papers recently accepted for publication by either one of the two leading discipline-wide journals in AI, Artificial Intelligence (AIJ) and the Journal of Artificial Intelligence Research (JAIR), the opportunity to present their work at the conference without undergoing an additional round of reviewing. Papers were eligible only if no part had previously been presented at a conference with archival proceedings. Traditionally, the authors of such papers would have missed out on the opportunity to present their work to a broader research audience. This limitation tends to discourage the submission of original work to journals without prior conference publications on the same topic. The intention of the journal track is to encourage a “journal-first” publication strategy–by giving authors the option to present their work at a suitable conference venue such as ECAI. On the following pages, for each paper presented at the journal track, we list bibliographic information and the abstract of the original publication.
Detect Closer Surfaces That Can be Seen: New Modeling and Evaluation in Cross-Domain 3D Object Detection
Authors: Zhang Ruixiao , Wu Yihong , Lee Juheon , Cai Xiaohao , Prugel-Bennett Adam
Published: October 2024

The performance of domain adaptation technologies has not yet reached an ideal level in the current 3D object detection field for autonomous driving, which is mainly due to significant differences in the size of vehicles, as well as the environments they operate in when applied across domains. These factors together hinder the effective transfer and application of knowledge learned from specific datasets. Since the existing evaluation metrics are initially designed for evaluation on a single domain by calculating the 2D or 3D overlap between the prediction and ground-truth bounding boxes, they often suffer from the overfitting problem caused by the size differences among datasets. This raises a fundamental question related to the evaluation of the 3D object detection models’ cross-domain performance: Do we really need models to maintain excellent performance in their original 3D bounding boxes after being applied across domains? From a practical application perspective, one of our main focuses is actually on preventing collisions between vehicles and other obstacles, especially in cross-domain scenarios where correctly predicting the size of vehicles is much more difficult. In other words, as long as a model can accurately identify the closest surfaces to the ego vehicle, it is sufficient to effectively avoid obstacles. In this paper, we propose two metrics to measure 3D object detection models’ ability of detecting the closer surfaces to the sensor on the ego vehicle, which can be used to evaluate their cross-domain performance more comprehensively and reasonably. Furthermore, we propose a refinement head, named EdgeHead, to guide models to focus more on the learnable closer surfaces, which can greatly improve the cross-domain performance of existing models not only under our new metrics, but even also under the original BEV/3D metrics. Our code is available at https://github.com/Galaxy-ZRX/EdgeHead.
Segmentation-Driven Image Enhancement Based on Deep Reinforcement Learning
Authors: Liu Yihong , Chen Zishang , Cui Yukang , Li Piji
Published: October 2024

The rise of large models, often referred to as foundational models, has led to considerable progress in the field of artificial intelligence research. Our empirical findings indicate that the large models might struggle or deliver poor performance when it comes to specific surface segmentation challenges, including the identification and segmentation of defects on strip steel surfaces (S3D) and the detection of imperfections on magnetic tile surfaces. To apply the large model to defects segmentation, rather than fine-tuning the large model, we propose Segmentation-Driven Image Enhancement (SDIE), using several classic filters to enhance the input images. In this case, the weights of the filters in multiple layers are controlled by reinforcement learning. Then, we test our method on two S3D datasets with different few-shot settings. Our method accomplishes the task brilliantly compared with other methods for S3D such as CPANet. We believe that our work not only opens up opportunities for downstream tasks such as segmenting industrial defects using large models, but may also have potential applications in various fields in the future, including medical image processing, remote sensing image analysis, agriculture and more.
OmniCLIP: Adapting CLIP for Video Recognition with Spatial-Temporal Omni-Scale Feature Learning
Authors: Liu Mushui , Li Bozheng , Yu Yunlong
Published: October 2024

Recent Vision-Language Models (VLMs) e.g. CLIP have made great progress in video recognition. Despite the improvement brought by the strong visual backbone in extracting spatial features, CLIP still falls short in capturing and integrating spatial-temporal features which is essential for video recognition. In this paper, we propose OmniCLIP, a framework that adapts CLIP for video recognition by focusing on learning comprehensive features encompassing spatial, temporal, and dynamic spatial-temporal scales, which we refer to as omni-scale features. This is achieved through the design of spatial-temporal blocks that include parallel temporal adapters (PTA), enabling efficient temporal modeling. Additionally, we introduce a self-prompt generator (SPG) module to capture dynamic object spatial features. The synergy between PTA and SPG allows OmniCLIP to discern varying spatial information across frames and assess object scales over time. We have conducted extensive experiments in supervised video recognition, few-shot video recognition, and zero-shot recognition tasks. The results demonstrate the effectiveness of our method, especially with OmniCLIP achieving a top-1 accuracy of 74.30% on HMDB51 in a 16-shot setting, surpassing the recent MotionPrompt approach even with full training data. The code is available at https://github.com/XiaoBuL/OmniCLIP.
DCTAN: Densely Convolved Transformer Aggregation Networks for Monocular Dense Depth Prediction in Robotic Endoscopy
Authors: Fan Wenkang , Jiang Wenjing , Fang Hao , Shi Hong , Chen Jianhua , Luo Xiongbiao
Published: October 2024

Accurate dense depth prediction for 3-D reconstruction of monocular endoscopic images plays an essential role in expanding the surgical field in robotic surgery. However, it is generally a challenge to precisely estimate dense depth due to complex surgical fields with limited field of viewing, illumination variations, and variable texture structure. This work explores the performance of convolutional networks and transformer-based networks for endoscopic depth prediction, and proposes a new architecture called densely convolved transformer aggregation networks (DCTAN) that can aggregate local texture features and global spatial-temporal features for endoscopic dense depth recovery. Specifically, DCTAN creates a new hybrid encoder that combines dense convolution and scalable transformers to parallel extract local texture features and global spatial-temporal features from monocular endoscopic video sequences. Then, a local and global aggregation decoder is established to assemble the tokens of each frame to generate the global feature maps, that are integrated with the corresponding local feature maps to predict depth from coarse to fine. We trained and evaluated DCTAN through self-supervised learning on monocular synthesis (ground-truth) data and colonoscopic video images, with the experimental results demonstrating that our new architecture can extract more accurate local and global features for depth prediction and achieve more accurate depth range, more complete depth structure, and more sufficient texture information than other networks. In particular, all qualitative and quantitative assessment results of our method are better than current monocular dense depth estimation models.
Real-Time Indoor Object Detection Based on Hybrid CNN-Transformer Approach
Authors: Laidoudi Salah-eddine , Maidi Madjid , Otmane Samir
Published: October 2024

Real-time object detection in indoor settings is a challenging area of computer vision, faced with unique obstacles such as variable lighting and complex backgrounds. This field holds significant potential to revolutionize applications like augmented and mixed realities by enabling more seamless interactions between digital content and the physical world. However, the scarcity of research specifically fitted to the intricacies of indoor environments has highlighted a clear gap in the literature. To address this, our study delves into the evaluation of existing datasets and computational models, leading to the creation of a refined dataset. This new dataset is derived from OpenImages v7[14], focusing exclusively on 32 indoor categories selected for their relevance to real-world applications. Alongside this, we present an adaptation of a CNN detection model, incorporating an attention mechanism to enhance the model’s ability to discern and prioritize critical features within cluttered indoor scenes. Our findings demonstrate that this approach is not just competitive to existing state-of-the-art models in accuracy and speed but also opens new avenues for research and application in the field of real-time indoor object detection.