Hasil untuk "Technology (General)"

Benjamin Leroy, Davi Marim, El Ghali Benjelloun et al.

We explore a quantitative approach to emerging technological sovereignty and geoeconomic power by assessing the relative positioning of countries with economic complexity methods applied to the structure of national venture-capital (VC) portfolios and their associated Revealed Venture Advantage (RVA) metrics. Using Crunchbase firm- and deal-level data, we map venture-backed startups to 18 emerging technology domains via a probabilistic multi-label large-language-model classifier, and construct an RVA-based country-technology specialization matrix for the 17 countries with the highest aggregate VC funding. From this matrix, we derive two eigenvector-based measures: a Geoeconomic Complexity Index (GCI) that ranks countries by the composition of their venture specializations, and an Emerging Technology Geoeconomic Complexity Index (ETGCI) that ranks domains by the extent to which specialization is concentrated among high-GCI countries. Empirically, Cloud Computing, Cybersecurity Tools, and Medtech exhibit the highest ETGCI values, reflecting concentration of specialization in a small set of leading countries. The United States and Israel consistently occupy a marked "high-diversity/low-ubiquity" position and lead the GCI ranking, followed by China, France, Japan, and Germany; both country and domain rankings are stable from 2021-2024. Finally, relatedness-based simulations identify, when it exists, for each country the Simplest Single Sovereignty Enhancing Technology (SSSET), i.e., the most feasible single new technological direction associated with the largest expected improvement in relative geoeconomic positioning.

Michelle L. Ding, Harini Suresh, Suresh Venkatasubramanian

The last decade has witnessed a rapid advancement of generative AI technology that significantly scaled the accessibility of AI-generated non-consensual intimate images (AIG-NCII), a form of image-based sexual abuse that disproportionately harms women and girls. There is a patchwork of commendable efforts across industry, policy, academia, and civil society to address AIG-NCII. However, these efforts lack a shared, consistent mental model that situates the technologies they target within the context of a large, interconnected, and ever-evolving technological ecosystem. As a result, interventions remain siloed and are difficult to evaluate and compare, leading to a reactive cycle of whack-a-mole. We contribute the first comprehensive AIG-NCII technological ecosystem that maps and taxonomizes 11 categories of technologies facilitating the creation, distribution, proliferation and discovery, infrastructural support, and monetization of AIG-NCII. First, we build and visualize the ecosystem through a synthesis of over a hundred primary sources from researchers, journalists, advocates, policymakers, and technologists. Next, we demonstrate how stakeholders can use the ecosystem as a tool to 1) understand new incidents of harm via a case study of Grok and 2) evaluate existing interventions via three more case studies. We conclude with three actionable recommendations, namely that stakeholders should 1) use the ecosystem to map out state, federal, and international laws to produce a clearer policy landscape, 2) collectively develop a database that dynamically tracks the 11 technologies in the ecosystem to better evaluate interventions, and 3) adopt a relational approach to researching AIG-NCII to better understand how the ecosystem technologies interact.

Lanbo Lai, Xiaolin Wang, Gholamreza Kefayati et al.

The indirect evaporative cooling system, which exploits the water evaporation process to generate cooling loads without introducing additional moisture, has been recognised as a viable alternative to conventional air-conditioning systems. This acknowledgment is due to its attributes of energy efficiency and environmental friendliness. The meticulous selection of wetting materials for an indirect evaporative cooler is of paramount importance as it significantly influences the heat and mass transfer performance of the system. Therefore, this paper experimentally examined a novel material produced by laser-resurfaced technology, and this material was compared with four other distinct materials (kraft paper, cotton fibre, polyester fibre, and polypropylene + nylon fibre) while considering the wicking ability, water-holding capacity, and thermal response performance. The results revealed that the fabric materials, specifically cotton fibre and polyester fibre, exhibited outstanding water-wicking ability, with a vertical wicking distance exceeding 16 cm. Cotton fibre also demonstrated an exceptional water-holding ability, registering a value of 0.0754 g/cm². In terms of thermal response performance, polypropylene + nylon fibre and the laser-resurfaced polymer achieved stable conditions within one minute, which could be attributed to the absence of a mechanical support plate and adhesive layer. All five materials attained stability after 4.2 min. Cotton and polyester fibres exhibited advantages in the duration of the evaporation process, maintaining stable conditions for 24 and 90 min, respectively. Based on the experimental results, appropriate water-spray strategies are proposed for each material.

Mengwen Gao, Yecui Hu, Xinwei Liu et al.

Spatial heterogeneity in the supply and demand of ecosystem services across multi spatiotemporal scales facilitates the formulation of ecosystem management policies at diverse administrative levels. We mapped the five ecosystem services (ESs) in China, analyzed the spatiotemporal evolution of ESs supply and demand pattern from 2000 to 2020, revealed the spatial distribution patterns and trade-off synergies of ecosystem services supply–demand ratio (ESDR) at multiple scales. Additionally, we explored ecosystem sustainable management pathways adapted to different scales of grid, city and basin. The results showed that, except for soil conservation, significant supply–demand imbalances existed in the other four ESs, with obvious deficits in food supply and water yield. Spatial clustering of ESDR slight variations in refinement level and regional synergy at different scales, with high-value predominantly observed in the southeast, low-value areas in the northwestern region. The increase of high-high (H-H) clustering units at the city and basin scales indicated an overall improvement in supply–demand imbalances on a larger scale. Moreover, the scale dependence of interactions between ESDRs was obvious. At the grid scale, most ESDRs exhibited a synergistic relationship with the strongest intensity. At the city scale, supply–demand ratio of food supply showed significant trade-offs with other types of ESDRs, and this effect was significantly weakened at the basin scale, even tended to shift toward synergistic effects. Consequently, this study suggested that the ESs supply–demand relationship should focus on multiple-scale dependence, enabling the effective design of refined ecosystem management strategies.

Qing Chen, Aihuang Guo, Yaodong Cui

To achieve the anticipated performance of massive multiple input multiple output (MIMO) systems in wireless communication, it is imperative that the user equipment (UE) accurately feeds the channel state information (CSI) back to the base station (BS) along the uplink. To reduce the feedback overhead, an increasing number of deep learning (DL)-based networks have emerged, aimed at compressing and subsequently recovering CSI. Various novel structures are introduced, among which Transformer architecture has enabled a new level of precision in CSI feedback. In this paper, we propose a new method named TransNet+ built upon the Transformer-based TransNet by updating the multi-head attention layer and implementing an improved training scheme. The simulation results demonstrate that TransNet+ outperforms existing methods in terms of recovery accuracy and achieves state-of-the-art.

О. P. Korzhova, D. S. Makashin, P. E. Popov et al.

The article focuses on the potential integration of the SFM digital control system into production. To achieve a more accurate implementation of the dSFM system, the article identifies its strengths and weaknesses. It evaluates and outlines the factors contributing to the successful implementation of the dSFM system in production. The article also analyses the traditional Lean manufacturing system, the analogue SFM system and its digital version. The study scrutinised the manner in which workers interact with the «System of Operations Management» with the purpose of refining its assimilation into manufacturing processes and enhancing employee output.

Alessandro Tavazzi, Dimitri Percia David, Julian Jang-Jaccard et al.

Identifying technological convergence among emerging technologies in cybersecurity is crucial for advancing science and fostering innovation. Unlike previous studies focusing on the binary relationship between a paper and the concept it attributes to technology, our approach utilizes attribution scores to enhance the relationships between research papers, combining keywords, citation rates, and collaboration status with specific technological concepts. The proposed method integrates text mining and bibliometric analyses to formulate and predict technological proximity indices for encryption technologies using the "OpenAlex" catalog. Our case study findings highlight a significant convergence between blockchain and public-key cryptography, evidenced by the increasing proximity indices. These results offer valuable strategic insights for those contemplating investments in these domains.

Linmi Tao, Ruiyang Liu, Donglai Tao et al.

Numerical difference computation is one of the cores and indispensable in the modern digital era. Tao general difference (TGD) is a novel theory and approach to difference computation for discrete sequences and arrays in multidimensional space. Built on the solid theoretical foundation of the general difference in a finite interval, the TGD operators demonstrate exceptional signal processing capabilities in real-world applications. A novel smoothness property of a sequence is defined on the first- and second TGD. This property is used to denoise one-dimensional signals, where the noise is the non-smooth points in the sequence. Meanwhile, the center of the gradient in a finite interval can be accurately location via TGD calculation. This solves a traditional challenge in computer vision, which is the precise localization of image edges with noise robustness. Furthermore, the power of TGD operators extends to spatio-temporal edge detection in three-dimensional arrays, enabling the identification of kinetic edges in video data. These diverse applications highlight the properties of TGD in discrete domain and the significant promise of TGD for the computation across signal processing, image analysis, and video analytic.

Lowri Williams, Eirini Anthi, Pete Burnap

While new technologies are expected to revolutionise and become game-changers in improving the efficiencies and practises of our daily lives, it is also critical to investigate and understand the barriers and opportunities faced by their adopters. Such findings can serve as an additional feature in the decision-making process when analysing the risks, costs, and benefits of adopting an emerging technology in a particular setting. Although several studies have attempted to perform such investigations, these approaches adopt a qualitative data collection methodology which is limited in terms of the size of the targeted participant group and is associated with a significant manual overhead when transcribing and inferring results. This paper presents a scalable and automated framework for tracking likely adoption and/or rejection of new technologies from a large landscape of adopters. In particular, a large corpus of social media texts containing references to emerging technologies was compiled. Text mining techniques were applied to extract sentiments expressed towards technology aspects. In the context of the problem definition herein, we hypothesise that the expression of positive sentiment infers an increase in the likelihood of impacting a technology user's acceptance to adopt, integrate, and/or use the technology, and negative sentiment infers an increase in the likelihood of impacting the rejection of emerging technologies by adopters. To quantitatively test our hypothesis, a ground truth analysis was performed to validate that the sentiment captured by the text mining approach is comparable to the results given by human annotators when asked to label whether such texts positively or negatively impact their outlook towards adopting an emerging technology.

Masaru Kuwabara, Ryota Kanai

In individuals afflicted with conditions such as paralysis, the implementation of Brain-Computer-Interface (BCI) has begun to significantly impact their quality of life. Furthermore, even in healthy individuals, the anticipated advantages of brain-to-brain communication and brain-to-computer interaction hold considerable promise for the future. This is attributed to the liberation from bodily constraints and the transcendence of existing limitations inherent in contemporary brain-to-brain communication methods. To actualize a comprehensive BCI, the establishment of bidirectional communication between the brain and the external environment is imperative. While neural input technology spans diverse disciplines and is currently advancing rapidly, a notable absence exists in the form of review papers summarizing the technology from the standpoint of the latest or potential input methods. The challenges encountered encompass the requisite for bidirectional communication to achieve a holistic BCI, as well as obstacles related to information volume, precision, and invasiveness. The review section comprehensively addresses both invasive and non-invasive techniques, incorporating nanotech/micro-device technology and the integration of Artificial Intelligence (AI) in brain stimulation.

Aydin Zaboli, Seong Lok Choi, Junho Hong

This study addresses critical challenges of cybersecurity in digital substations by proposing an innovative task-oriented dialogue (ToD) system for anomaly detection (AD) in multicast messages, specifically, generic object oriented substation event (GOOSE) and sampled value (SV) datasets. Leveraging generative artificial intelligence (GenAI) technology, the proposed framework demonstrates superior error reduction, scalability, and adaptability compared with traditional human-in-the-loop (HITL) processes. Notably, this methodology offers significant advantages over machine learning (ML) techniques in terms of efficiency and implementation speed when confronting novel and/or unknown cyber threats, while also maintaining model complexity and precision. The research employs advanced performance metrics to conduct a comparative assessment between the proposed AD and HITL-based AD frameworks, utilizing a hardware-in-the-loop (HIL) testbed for generating and extracting features of IEC61850 communication messages. This approach presents a promising solution for enhancing the reliability of power system operations in the face of evolving cybersecurity challenges.

Malcolm Crowe, Fritz Laux

This paper reviews the changes for database technology represented by the current development of the draft international standard ISO 39075 (Database Languages - GQL), which seeks a unified specification for property graphs and knowledge graphs. This paper examines these current developments as part of our review of the evolution of database technology, and their relation to the longer-term goal of supporting the Semantic Web using relational technology.

Francisco Cejas Rodríguez, Elizabeth Roig Villariño, Dayniel Hernández Mestre et al.

A partir de la información extraída de la Base de datos de fanerógamas (plantas con flores) de Cuba, depositada en el Instituto de geografía Tropical, la presente investigación conformó una tabla en Excel que recoge la información sistemática detallada en cuanto a: familia botánica, género, especie, autor de la especie y sinonimia, entre otros, junto al nombre común, cuyo empleo facilita el reconocimiento de la especie a nivel del público en general. Con diferentes Macros implementadas sobre Visual Basic for Applications (VBA), que automatizaron la revisión del entorno, se procedió a un análisis de la información compilada. Se obtuvo una  aproximación al estado de conocimiento sobre la composición y distribución de las especies arbóreas en las formaciones boscosas naturales cubanas, señalándose las principales dificultades para acometer esta tarea y recomendaciones para llevarla a término felizmente.

Paolo Graniero, Paolo Graniero, Mark Khenkin et al.

Perovskite solar cells are the most dynamic emerging photovoltaic technology and attracts the attention of thousands of researchers worldwide. Recently, many of them are targeting device stability issues–the key challenge for this technology–which has resulted in the accumulation of a significant amount of data. The best example is the “Perovskite Database Project,” which also includes stability-related metrics. From this database, we use data on 1,800 perovskite solar cells where device stability is reported and use Random Forest to identify and study the most important factors for cell stability. By applying the concept of learning curves, we find that the potential for improving the models’ performance by adding more data of the same quality is limited. However, a significant improvement can be made by increasing data quality by reporting more complete information on the performed experiments. Furthermore, we study an in-house database with data on more than 1,000 solar cells, where the entire aging curve for each cell is available as opposed to stability metrics based on a single number. We show that the interpretation of aging experiments can strongly depend on the chosen stability metric, unnaturally favoring some cells over others. Therefore, choosing universal stability metrics is a critical question for future databases targeting this promising technology.

Shasha Zhao, Liuqingqing Liu, Chenguang Li et al.

IntroductionBiobased polymer blends have been recommended as an eco-friendly solution to abate plastic pollution in the environment. However, the formation of microplastics (MPs) by photodegradation of biobased polymer blends in the marine environment is still not well understood. In this study, we investigated the formation of MPs and the changes in the physicochemical properties of three types of biobased polymer blends after photodegradation in seawater.MethodsThe investigated materials included non-biodegradable polyethylene/ thermoplastic starch blends (PE/TPS) and polypropylene/thermoplastic starch blends (PP/TPS), as well as biodegradable polylactic acid/poly (butylene adipate-co-terephthalate)/thermoplastic starch blends (PLA/PBAT/TPS). The control groups were the corresponding neat polymers, including polyethylene (PE), polypropylene (PP), and polylactic acid (PLA).ResultsThe size distribution of the pristine and aged MPs indicated that the polymer blends were more likely to produce small-sized particles after photodegradation due to their poorer mechanical properties and lower resistance to UV irradiation than the neat polymers. Noticeable surface morphology alterations, including cracks, holes, and pits, were observed for polymer blends after photodegradation, while neat polymers were relatively resistant. After photodegradation, the attenuated total reflection Fourier transformed infrared spectroscopy (ATR-FTIR) spectrum of the polymer blends showed a significant decrease in the characteristic bands of thermoplastic starch (TPS), indicating depletion of their starch fractions. The C1s spectra of the polymer blends demonstrated that the aged MPs contained fewer -OH groups than the pristine MPs, further confirming the photodegradation of TPS. The molecular weight distribution curve of the polymer blends shifted significantly towards low molecular weight, suggesting the occurrence of chain scission during photodegradation. These results indicate that the polymer blends have a higher degree of photodegradation than neat polymers, and thereby generate more small-sized MPs than neat polymers. Photodegradation caused changes in the contact angle and surface charge of MPs derived from biobased polymer blends, which may affect the vector effects of MPs on any coexisting pollutants.DiscussionIn summary, polymer blends may pose a higher risk to the marine environment than neat polymers, and caution should be taken in promoting biobased polymer blends.

Marilena Cozzolino, Antonio De Simone, Vincenzo Gentile et al.

The application of non-invasive geophysical techniques and digital surveys to explore cultural heritage is becoming a very important research field. The capability to detect inner and superficial changes in the inspected surfaces allows for imaging spatial inhomogeneity and material features and planning targeted conservation and restoration interventions. In this work, the results of a research project carried out on the famous Battle of Issus Mosaic, also known as the “Alexander Mosaic”, are presented. It is a masterpiece of ancient art that was found in 1831 in the House of Faun, the most luxurious and spacious house in Pompeii. It is notable for its size (3.41 × 5.82 m), the quality of workmanship and the subject that represents the culminating phase of the battle between Alexander Magno’s army and the Persian one of Darius. In 1916, it was moved inside the National Archaeological Museum of Naples, where the original horizontal location was changed with a vertical arrangement supported by an inner wooden structure, whose exact manufacture is unclear. Today, the mosaic is affected by important instability phenomena highlighted by the appearance of the significant detachment of tiles, superficial lesions and swelling of the surface. Given the important need to preserve it, a high-detail diagnostic study was realized through a digital survey and non-invasive geophysical surveys using ground-penetrating radar (GPR). The investigation was repeated after two years, in 2018 and 2020, with the aim of verifying the evolution of degradation. The work provided a high-resolution estimate of the state of the health of the mosaic and allowed for obtaining a three-dimensional reconstruction of the internal mosaic structure, including the formulation of hypotheses on the engineering supporting works of the twentieth century; this provides an essential tool for the imminent conservation project, which also implies restoring the original horizontal position.

Andrew Myers, Catherine Ipsen, Krys Standley

IntroductionLack of transportation is a significant barrier to community participation for many disabled adults. Living in a rural area introduces additional transportation barriers, such as having to travel long distances to access services or socialize, and limited public transit options. While the importance of transportation access is clear, the mix of different transportation options used by people with disabilities to participate in their communities is less understood, particularly among those who do not or cannot drive.MethodsWe used data from the 2017 National Household Travel Survey to explore transportation behaviors among disabled adults in rural and urban areas and by four regions across the United States. We explored differences by transportation modalities (e.g., driver, passenger, public transportation, taxi/uber, walk) and trip purposes (e.g., social, independent living, healthcare, work). Our sample included 22,716 adults with travel-limiting disabilities.ResultsSeveral geographic differences emerged among non-drivers. Rural non-drivers were less likely to take any trip, particularly for social activities, and reported using less public transportation or walking/rolling than urban non-drivers. Further, respondents from the Northeast were more likely to report using public transportation and walking/rolling options, relative to the Midwest, South, and West. Overall, disabled rural adults reported lower odds of giving up driving, even after controlling for socio-demographic and health characteristics.DiscussionThese findings highlight the relative importance of different transportation modalities for participating in activities and the continued reliance upon personal vehicles, either as a driver or passenger, especially among rural disabled residents. Potential policy insights are discussed.

Yijing Chu, Ming Wu, Hongling Sun

Active noise and vibration control aims at attenuating unwanted sound or vibration by automatically generating an anti-sound or vibration [...]

Md Arquam, Ashish Patel, Parma Nand

The advent of blockchain technology by the Nakamoto group in 2008 has created a new trend on how to deal with various security issues and vulnerabilities. Blockchain systems have gained momentum in various spheres of technology deployment in business organizations. This paper presents a critical literature survey on the security strength of blockchains and security issues associated with blockchain technology deployment. Numerous studies have experimented with the various technical features of blockchain systems across various transaction domains. Findings obtained from the literature survey and thematic content analysis of the existing research studies indicate that blockchain systems provide unique capabilities that support processes and transactions across various sectors with a high level of integrity, transparency, confidentiality, and privacy. However, some loopholes and limitations associated with the deployment and use of blockchains have been highlighted in various studies. The present study cross-examined the security issues of the underlying scientific research evidence.