Hasil untuk "Technology"

L. Krychkovska, M. Bobro, G. Birta et al.

High-quality, naturally protected seeds prior to sowing, along with growth activation of seedlings, represent a promising approach to stabilising crop yield and quality. Enhancing plant resistance to dynamic environmental stresses, including harmful organisms, is one of the strategies for realising the biological potential of crop yields in breeding and seed production. This research aimed to experimentally evaluate a preparation based on humic substances, film formers, a nanocomposite, succinic acid, and microbiological carotene. Experiments were conducted using spring barley and wheat seeds. A seed encrustation technology employing a functional preparation was applied. Laboratory and field experiments were conducted at V. Dokuchaev Kharkiv National Agrarian University, Department of Plant Growing, over two years. The experimental design and economic efficiency assessment of the functional preparation in enhancing yield was carried out according to established methodologies. Pre-sowing seed treatment with the preparation resulted in improved field germination, synchronised seedling emergence, and increased yield. Comprehensive studies revealed that the preparation was compatible with fungicides, demonstrating a synergistic effect of their joint protective effect. Experimental results confirmed that seed incrustation with protective and stimulating formulations based on water-soluble polymers is an effective method for protecting plants from seed- and soil-borne infections while reducing the level of environmental pollution. The extended and enhanced fungicidal activity of film-forming protective and stimulating compositions was also demonstrated. Agricultural production tests indicated that the developed preparation was user-friendly, environmentally safe, and economically efficient, contributing to increased crop yields. The positive test results support practical recommendations for its application in both seed encrustation and grain crop spraying during the tillering and milky-wax ripeness phases

Ran Wang, Caibo Tang, Yuge Ma et al.

Building-integrated photovoltaics (BIPVs) represent a pivotal technology for enhancing the utilization of renewable energy in buildings. However, challenges persist, including the lack of integrated design models, limited analytical dimensions, and insufficient consideration of climate change impacts. This study proposes a comprehensive performance assessment framework for BIPV that incorporates global climate change factors. An integrated simulation model is developed using EnergyPlus8.9.0, Optics6, and WINDOW7.7 to evaluate BIPV configurations such as photovoltaic facades, shading systems, and roofs. A multi-criteria evaluation system is established, encompassing global warming potential (GWP), power generation, energy flexibility, and economic cost. Future hourly weather data for the 2050s and 2080s are generated using CCWorldWeatherGen under representative climate scenarios. Monte Carlo simulations are conducted to assess performance across variable combinations, supplemented by sensitivity and uncertainty analyses to identify key influencing factors. Results indicate (1) critical design parameters—including building orientation, wall thermal absorptance, window-to-wall ratios, PV shading angle, glazing optical properties, equipment and lighting power density, and occupancy—significantly affect overall performance. Equipment and lighting densities most influence carbon emissions and flexibility, whereas envelope thermal properties dominate cost impacts. PV shading outperforms other forms in power generation. (2) Under intensified climate change, GWP and life cycle costs increase, while energy flexibility declines, imposing growing pressure on system performance. However, under certain mid-century climate conditions, BIPV power generation potential improves due to altered solar radiation. The study recommends integrating climate-adaptive design strategies with energy systems such as PEDF (photovoltaic, energy storage, direct current, and flexibility), refining policy mechanisms, and advancing BIPV deployment with climate-resilient approaches to support building decarbonization and enhance adaptive capacity.

Xinyue Wang, Weifan Lin, Weiting Zhang et al.

In this paper, the Merkle-Transformer model is introduced as an innovative approach designed for financial data processing, which combines the data integrity verification mechanism of Merkle trees with the data processing capabilities of the Transformer model. A series of experiments on key tasks, such as financial behavior detection and stock price prediction, were conducted to validate the effectiveness of the model. The results demonstrate that the Merkle-Transformer significantly outperforms existing deep learning models (such as RoBERTa and BERT) across performance metrics, including precision, recall, accuracy, and F1 score. In particular, in the task of stock price prediction, the performance is notable, with nearly all evaluation metrics scoring above 0.9. Moreover, the performance of the model across various hardware platforms, as well as the security performance of the proposed method, were investigated. The Merkle-Transformer exhibits exceptional performance and robust data security even in resource-constrained environments across diverse hardware configurations. This research offers a new perspective, underscoring the importance of considering data security in financial data processing and confirming the superiority of integrating data verification mechanisms in deep learning models for handling financial data. The core contribution of this work is the first proposition and empirical demonstration of a financial data analysis model that fuses data integrity verification with efficient data processing, providing a novel solution for the fintech domain. It is believed that the widespread adoption and application of the Merkle-Transformer model will greatly advance innovation in the financial industry and lay a solid foundation for future research on secure financial data processing.

Katarzyna Grabowska, Łukasz Januszkiewicz, Ewelina Pabjańczyk-Wlazło

This study explores the electromagnetic properties of flat textile products enhanced with carbon nanotube (CNT) threads used as the weft. CNT threads, fabricated via dry-spinning, were integrated into fabrics by wrapping them around steel threads to form a solenoid-like structure. To further improve electromagnetic attenuation, the CNT yarn was coated with graphene oxide and silver nanoparticles. The research assessed the impact of these modifications on the fabric’s ability to attenuate alternating electromagnetic fields across a range of frequencies. Results showed enhanced attenuation at 30 MHz and 500 MHz. CNT yarn wrapped around steel threads achieved attenuation efficiencies of 18 dB at 30 MHz and 22 dB at 500 MHz, with a notable 10 dB improvement at 30 MHz over the reference. Fabrics with CNT yarn coated with graphene oxide demonstrated similar performance to the reference fabric at 500 MHz and an 8 dB increase at 30 MHz. Similarly, CNT yarn with silver nanoparticles showed comparable performance at higher frequencies but matched the reference at 30 MHz. These results indicate significant enhancement at lower frequencies, with benefits diminishing at higher. This study underscores the potential of integrating CNTs and metal nanoparticles into textiles to improve electromagnetic shielding, especially across specific frequencies.

Freddy Tuxworth, Adnan Aijaz

The global energy landscape is experiencing a significant transformation driven by increased awareness of climate change and rapid technological advancements in renewable energy and electric vehicles (EVs). Packetized energy management (PEM) schemes are gaining attention as a potential solution for power management for effective load control. This study presents the development of a co-simulation platform to investigate integration of vehicle-to-grid (V2G) with packetized energy trading (PET) in microgrid scenarios. The platform facilitates the interaction between EVs and prosumers, with a focus on responsive loads, and solar photovoltaic (PV) as intermittently available resources. Using the developed co-simulation, this study evaluates how V2G-capable EVs can enhance the stability and efficiency of PET-based microgrids. The results demonstrate the capability of V2G EVs to act as an energy reservoir, effectively managing demand-side load, thus mitigating its fluctuation from available supply while maintaining quality-of-service.

Xiangyu Wu, Hailiang Zhang, Yang Yang et al.

In this paper, we present our champion solution to the Global Artificial Intelligence Technology Innovation Competition Track 1: Medical Imaging Diagnosis Report Generation. We select CPT-BASE as our base model for the text generation task. During the pre-training stage, we delete the mask language modeling task of CPT-BASE and instead reconstruct the vocabulary, adopting a span mask strategy and gradually increasing the number of masking ratios to perform the denoising auto-encoder pre-training task. In the fine-tuning stage, we design iterative retrieval augmentation and noise-aware similarity bucket prompt strategies. The retrieval augmentation constructs a mini-knowledge base, enriching the input information of the model, while the similarity bucket further perceives the noise information within the mini-knowledge base, guiding the model to generate higher-quality diagnostic reports based on the similarity prompts. Surprisingly, our single model has achieved a score of 2.321 on leaderboard A, and the multiple model fusion scores are 2.362 and 2.320 on the A and B leaderboards respectively, securing first place in the rankings.

Stephen Fox, Charla Griffy-Brown

A. V. Zamkovaya

Modern technology is expanding the possibilities of classes and determining the need for new forms of learning. The study of multimedia technology is currently developing in an academic way. Visuals in general play a huge, sometimes decisive role in digital communication. The article is devoted to the usage of video materials in the foreign language classes, the author considers the methods of video resources usage in the process of teaching foreign languages, aimed at forming communicative competence of the students. The author analyses psycho-didactic possibilities of audiovisual teaching materials. Particular attention is paid to the peculiarities of clip thinking, the level of visual literacy and the typology of video resources for teaching foreign languages. The aim of the article is to develop a methodology of applying teaching and authentic video resources in the process of foreign language teaching aimed at forming audiovisual literacy and communicative competence of students. The author concludes that the rational use of video materials and video resources contributes to a deeper involvement of students in learning a foreign language, stimulates the development of creative thinking, social skills, contributes to the mastery of knowledge, skills and abilities of understanding, speaking and writing.

Farshid Danesh, Samaneh Kesht Karan, Lili Banihashemi et al.

Editorial board members (EBMs) of journals play a pivotal role in authentic international scientific journals. Editorial Board Interlocking (EBI) phenomenon reflects the effectiveness and importance of the scholarly journal's editorial boards in various scientific fields. The primary purpose of this paper is to conduct a Social Network Analysis (SNA) of EBI phenomena from the perspective of astronomy and astrophysics journals. The present study is applied research based on EBI, SNA, and the descriptive-analytical approach. The statistical population of this study consists of the editorial board members of all journals of astronomy and astrophysics indexed in the JCR and official journal websites. There are 1597 job positions in 67 astronomy and astrophysics journals occupied by the 1394 scholars. Data analysis shows EBI for 95 scholars and 79 organizations. "Aleksei A. Starobinsky" from Russia and the Russian Academy of Sciences, "Daniel J. Scheeres" from the United States, and the University of Colorado Boulder have the highest EBI contributions in five journals. "Daniel J. Scheeres," with a centrality of 39, has the highest degree of centrality measurement among the EBMs. The presence of more than five times as many men as women indicates that astronomy and astrophysics journals are considered "masculine" by the editorial board. The EBI phenomenon is observed in astronomy and astrophysics journals due to the limited number of peop le eligible for the editorial board. Due to EBI, a limited number of famous scholars are made macro-policies such as publishing the articles, referees selections, and the reviewing process. Astronomy and astrophysics journals have "elite" academic networks. Gender inequality exists among EBMs, and the majority of them are male. Accordingly, these journals are "men's journals."

Soonil Hong, Byoungwook Park, Chandran Balamurugan et al.

Efforts to commercialize organic solar cells (OSCs) by developing roll-to-roll compatible modules have encountered challenges in optimizing printing processes to attain laboratory-level performance in fully printable OSC architectures. In this study, we present efficient OSC modules fabricated solely through printing methods. We systematically evaluated the impact of processing solvents on the morphology of crucial layers, such as the hole transport, photoactive, and electron transport layers, applied using the doctor blade coating method, with a particular focus on processability. Notably, deposition of charge transport layer using printing techniques is still a challenging task, mainly due to the hydrophobic characteristic of the organic photoactive layer. To overcome this issue, we investigated the solvent effect of a well-studied cathode interlayer, bathocuproine (BCP). We were able to form a uniform thin BCP film (∼10 nm) on a non-fullerene based organic photoactive layer using the doctor bladed coating method. Our results showed that the use of volatile alcohols in the BCP processing required a delicate balance between wettability and vaporization, which contrasted with the results for spin-coated films. These findings provide important insights into improving the efficiency of printing techniques for depositing charge transport layers. The fully printed OSC modules, featuring uniform and continuous BCP layer formation, achieved an impressive power conversion efficiency of 10.8% with a total area of 10.0 cm2 and a geometrical fill factor of 86.5%.

Wei Zhou, Guilin Zeng, Haotian Jin et al.

In terms of new-generation energy-storing devices, aqueous zinc-ion batteries (AZIBs) are becoming the prime candidates because of their inexpensive nature, inherent safety, environmental benignity and abundant resources. Nevertheless, due to a restrained selection of cathodes, AZIBs often perform unsatisfactorily under long-life cycling and high-rate conditions. Consequently, we propose a facile evaporation-induced self-assembly technique for preparing V₂O₃@carbonized dictyophora (V₂O₃@CD) composites, utilizing economical and easily available biomass dictyophora as carbon sources and NH₄VO₃ as metal sources. When assembled in AZIBs, the V₂O₃@CD exhibits a high initial discharge capacity of 281.9 mAh g⁻¹ at 50 mA g⁻¹. The discharge capacity is still up to 151.9 mAh g⁻¹ after 1000 cycles at 1 A g⁻¹, showing excellent long-cycle durability. The extraordinary high electrochemical effectiveness of V₂O₃@CD could be mainly attributed to the formation of porous carbonized dictyophora frame. The formed porous carbon skeleton can ensure efficient electron transport and prevent V₂O₃ from losing electrical contact due to volume changes caused by Zn²⁺ intercalation/deintercalation. The strategy of metal-oxide-filled carbonized biomass material may provide insights into developing high-performance AZIBs and other potential energy storage devices, with a wide application range.

Jan-Peter Glock, Julia Gerlach

Abstract Cars are dominating urban traffic in cities around the world, even though daily trips in many cities are often realized with active modes of transportation or public transport. Urban transport planning processes need to adapt to this reality and the necessity of climate change mitigation. Against this background, the research project “Mobility Reporting”, a joint undertaking of the district Pankow in Berlin and researchers from TU Berlin and TU Dresden, established a new, goal-driven, and participative planning process. The process identified local mobility as one of the central planning goals. The 15-min city (FMC) was thus adduced as a benchmark to analyze the district’s current mobility system and development potential. We conducted extensive accessibility analyses to examine the status quo concerning the FMC. We calculated travel times to essential destinations in daily life by foot, public transport, and car. This analysis was accompanied by a mixed online and paper–pencil survey conducted to evaluate the perceived accessibility of people in Pankow. The survey results shed light on the question of which walking time thresholds constitute a “very good” or “good” accessibility. Further analyses included environmental and social variables, allowing us to check whether areas with different accessibility levels also differ regarding the socio-economic characteristics of their inhabitants. For example, do socially advantaged neighborhoods have better local accessibility? Is there a trade-off between exposure to environmental pollution and good accessibility? With this contribution, we shed light on what an FMC is and ought to be. Results from the survey support the normative and political vision of the FMC. Pankow generally offers the merits of a walkable city, showing the expected travel time differences between the dense inner city and the outskirts. Socially disadvantaged neighborhoods are not consistently less accessible. However, there seems to be a trade-off between good accessibility (especially PT accessibility) and correlated externalities of transport, namely air pollution and noise.

CHANG Kai, LIU Zhigeng, YUAN Xiaoming et al.

This paper introduces the development and application status of intelligent auxiliary transportation technology in open-pit coal mine and underground coal mines at home and abroad. The intelligent auxiliary transportation system of open-pit coal mine has realized the functions of unmanned driving, automatic loading, automatic unloading, active obstacle avoidance and intelligent dispatching of mining trucks in fixed sections. And the system has achieved good application results in engineering practice. At present, the auxiliary transportation intelligence of underground coal mine is still in the development stage of single machine intelligence of equipment. The intelligent auxiliary transportation system integrating vehicle scheduling, operation status monitoring, traffic command, material control and other functions has not yet been formed. The main problems of intelligent auxiliary transportation system in underground coal mine are analyzed. The underground positioning system has low precision and poor real-time performance. The dispatching system function lacks effective integration. The driving assistance system module is not perfect. The unmanned driving technology lags behind and the test conditions are lacking. Based on the relevant requirements of intelligent auxiliary transportation in Coal Mine Intelligent Construction Guide (2021 edition), this paper puts forward the overall goal of the construction of intelligent auxiliary transportation. According to the overall goal, the intelligent coal mine auxiliary transportation system framework is designed. ① Coding and centralized loading transportation of materials realizes the whole process information management and control of materials from storage, coding, loading, transportation, unloading and recycling. ② Automatic loading and unloading and automatic connection realizes the automatic transfer and connection of materials among rail locomotives, monorail cranes, trackless and other different auxiliary transportation modes. ③ Accurate positioning and intelligent navigation achieves accurate real-time positioning, route planning and real-time navigation of personnel and transportation equipment. ④ Intelligent vehicle dispatching realizes the functions of auxiliary transportation comprehensive information display, data transmission, status monitoring, dispatching command and health management. ⑤ Driving assistance system builds several intelligent subsystems, such as anti fatigue driving warning, 360° panoramic look around monitoring, collision prevention, traffic sign identification, auxiliary braking for downhill driving, adaptive lighting, etc. Driving assistance system improves the safety of locomotive operation. ⑥ The auxiliary operation robot realizes the robot automatic operation of underground auxiliary operation scenes. The auxiliary operation robot reduces the number of personnel and improves the overall automation level of auxiliary operation. ⑦ Unmanned driving realizes the normal unmanned driving operation of locomotives in underground coal mine. The research can provide reference for the construction and development of intelligent auxiliary transportation system.

Aletta Lucia Meinsma, Sanne Willemijn Kristensen, W. Gudrun Reijnierse et al.

Researchers point to four potential issues related to the popularisation of quantum science and technology. These include a lack of explaining underlying quantum concepts of quantum 2.0 technology, framing quantum science and technology as spooky and enigmatic, framing quantum technology narrowly in terms of public good and having a strong focus on quantum computing. To date, no research has yet assessed whether these potential issues are actually present in popular communication about quantum science. In this content analysis, we have examined the presence of these potential issues in 501 TEDx talks with quantum science and technology content. Results show that while most experts (70%) explained at least one underlying quantum concept (superposition, entanglement or contextuality) of quantum 2.0 technology, only 28% of the non-experts did so. Secondly, the spooky/enigmatic frame was present in about a quarter of the talks. Thirdly, a narrow public good frame was found, predominantly by highlighting the benefits of quantum science and technology (found in over 6 times more talks than risks). Finally, the main focus was on quantum computing at the expense of other quantum technologies. In conclusion, the proposed frames are indeed found in TEDx talks, there is indeed a focus on quantum computing, but at least experts explain underlying quantum concepts often.

Ghassan Samara, Abla Hussein, Israa Abdullah Matarneh et al.

The Internet of Robotic Things (IoRT) is a new domain that aims to link the IoT environment with robotic systems and technologies. IoRT connects robotic systems, connects them to the cloud, and transfers critical information as well as knowledge exchange to conduct complicated and intricate activities that a human cannot readily perform. The pertinent notion of IoRT has been discussed in this paper, along with the issues that this area faces on a daily basis. Furthermore, technological applications have been examined in order to provide a better understanding of IoRT and its current development phenomenon. The study describes three layers of IoRT infrastructure: network and control, physical, and service and application layer. In the next section, IoRT problems have been presented, with a focus on data processing and the security and safety of IoRT technological systems. In addition to discussing the difficulties, appropriate solutions have been offered and recommended. IoRT is regarded as an essential technology with the ability to bring about a plethora of benefits in smart society upon adoption, contributing to the generation and development of smart cities and industries in the near future.

Muhammad K. Shehzad, Luca Rose, M. Majid Butt et al.

With the deployment of 5G networks, standards organizations have started working on the design phase for sixth-generation (6G) networks. 6G networks will be immensely complex, requiring more deployment time, cost and management efforts. On the other hand, mobile network operators demand these networks to be intelligent, self-organizing, and cost-effective to reduce operating expenses (OPEX). Machine learning (ML), a branch of artificial intelligence (AI), is the answer to many of these challenges providing pragmatic solutions, which can entirely change the future of wireless network technologies. By using some case study examples, we briefly examine the most compelling problems, particularly at the physical (PHY) and link layers in cellular networks where ML can bring significant gains. We also review standardization activities in relation to the use of ML in wireless networks and future timeline on readiness of standardization bodies to adapt to these changes. Finally, we highlight major issues in ML use in the wireless technology, and provide potential directions to mitigate some of them in 6G wireless networks.

Andrew J Lohn, Krystal Alex Jackson

We aim to demonstrate the value of mathematical models for policy debates about technological progress in cybersecurity by considering phishing, vulnerability discovery, and the dynamics between patching and exploitation. We then adjust the inputs to those mathematical models to match some possible advances in their underlying technology. We find that AI's impact on phishing may be overestimated but could lead to more attacks going undetected. Advances in vulnerability discovery have the potential to help attackers more than defenders. And automation that writes exploits is more useful to attackers than automation that writes patches, although advances that help deploy patches faster have the potential to be more impactful than either.

Minqi Li, Xiangjian He, Kin‐Man Lam et al.

Abstract Face hallucination is a super‐resolution technique specially designed to reconstruct high‐resolution faces from low‐resolution faces. Most state‐of‐the‐art algorithms leverage position‐patch prior knowledge of human faces to better super‐resolve face images. However, most of them assume the training face dataset is sufficiently large, well cropped or aligned. This paper, proposes a novel example‐based face hallucination method, based on cluster consistent dictionary learning with the assumption that human faces have similar facial structures. In this method, the paired face image patches are firstly labelled as face areas including eyes, nose, mouth and other parts, as well as non‐face areas without requiring the training face images cropped and aligned. Then, the training patches are clustered according their labels and textures. The cluster consistent dictionary is learned to represent the low‐resolution patches and the high‐resolution patches. Finally, the high‐resolution patches of the input low‐resolution face image can be efficiently generated by using the adjusted anchored neighbourhood regression. As utilizing the labelled facial parts prior knowledge, the proposed method represents more details in the reconstruction. Experimental results demonstrate that the authors' algorithm outperforms many state‐of‐the‐art techniques for face hallucination under different datasets.

Hao Huang, Qunzhang Tu, Chengming Jiang et al.

This paper proposed control schemes to realize the collaborative control as well as enhance the control precision for the distributed driving electric vehicle (DDEV). Firstly, we suggested an electronic line-shafting (ELS) to realize the cooperative control for the Multi-Motor system which is installed in the DDEV. Secondly, we adopted a nonsingular terminal sliding mode control (NTSMC) method combined with a sliding mode observer (SMO) to quicken the response velocity and strengthen the robustness of the single motor controller. Finally, for the chattering value caused by the internal parameter variation and external disturbance, a fuzzy algorithm is proposed to obtain the controller parameters of NTSMC in real-time to eliminate the chattering value of DDEV. Through several simulations and experiments, the results demonstrate that the proposed strategies can realize ideal collaborative control for the Multi-Motor system, as well as improve the dynamic performance and anti-jamming ability for the whole control system of DDEV.

Masato Kikuchi, Shun Shiramatsu, Ryota Kozakai et al.

More than 80 civic tech communities in Japan are developing information technology (IT) systems to solve their regional issues. Collaboration among such communities across different regions assists in solving their problems because some groups have limited IT knowledge and experience for this purpose. Our objective is to realize a civic tech matchmaking system to assist such communities in finding better partners with IT experience in their issues. In this study, as the first step toward collaboration, we acquire relevant social issues and information technologies by association rule mining. To meet our challenge, we supply a questionnaire to members of civic tech communities and obtain answers on their faced issues and their available technologies. Subsequently, we match the relevant issues and technologies from the answers. However, most of the issues and technologies in this questionnaire data are infrequent, and there is a significant bias in their occurrence. Here, it is difficult to extract truly relevant issues--technologies combinations with existing interestingness measures. Therefore, we introduce a new measure called weighted casual confidence, and show that our measure is effective for mining relevant issues--technologies pairs.