Search Results (28)

Cybersecurity represents a critical challenge for data-sharing platforms involving multiple stakeholders, particularly within complex and decentralized systems such as livestock supply chain networks. These systems demand novel approaches, robust security protocols, and advanced data management strategies to address key challenges such as data consistency, transparency, ownership, controlled access or exposure, and privacy-preserving analytics for value-added services. In this paper, we introduced the Framework for Livestock Empowerment and Decentralized Secure Data eXchange (FLEX), as a comprehensive solution grounded on five core design principles: (i) enhanced security and privacy, (ii) human-centric approach, (iii) decentralized and trusted infrastructure, (iv) system resilience, and (v) seamless collaboration across the supply chain. FLEX integrates interdisciplinary innovations, leveraging decentralized infrastructure-based protocols to ensure trust, traceability, and integrity. It employs secure data-sharing protocols and cryptographic techniques to enable controlled information exchange with authorized entities. Additionally, the use of data anonymization techniques ensures privacy. FLEX is designed and implemented using a microservices architecture and edge computing to support modularity and scalable deployment. These components collectively serve as a foundational pillar of the development of a digital product passport. The FLEX architecture adopts a layered design and incorporates robust security controls to mitigate threats identified using the STRIDE threat modeling framework. The evaluation results demonstrate the framework’s effectiveness in countering well-known cyberattacks while fulfilling its intended objectives. The performance evaluation of the implementation further validates its feasibility and stability, particularly as the volume of evidence associated with animal identities increases. All the infrastructure components, along with detailed deployment instructions, are publicly available as open-source libraries on GitHub, promoting transparency and community-driven development for wider public benefit. Full article

This study investigates the application of network audio technology in performing arts and media art collaborations within virtual environments, analyzing its impact through four case studies. Employing a practice-based research methodology through using a variety of open-source software and communication protocols, it examines the cultural and social dynamics, creative workflows, and technical frameworks of ensembles leveraging network audio technology for remote recording and virtual production. These projects, recognized internationally within the electroacoustic music community, underscore the potential of network audio to transform virtual music performance, industry practices, and education. The research addresses challenges in internet-based production, particularly in real-time multichannel audio recording, mixing, and production with limited home setups. Insights into managing multiple audio networks effectively and capturing distinct tracks across virtual spaces are presented, offering both creative and technical strategies for virtual music performance and production in emerging digital environments. Full article

This paper presents an autonomous perfectly secure low-bit-rate voice communication system (APS-VCS) based on the mixed-excitation linear prediction voice coder (MELPe), Vernam cipher, and sequential key distillation (SKD) protocol by public discussion. An authenticated public channel can be selected in a wide range, from internet connections to specially leased radio channels. We found the source of common randomness between the locally synthesized speech signal at the transmitter and the reconstructed speech signal at the receiver side. To avoid information leakage about open input speech, the SKD protocol is not executed on the actual transmitted speech signal but on artificially synthesized speech obtained by random selection of the linear spectral pairs (LSP) parameters of the speech production model. Experimental verification of the proposed system was performed on the Vlatacom Personal Crypto Platform for Voice encryption (vPCP-V). Empirical measurements show that with an adequate selection of system parameters for voice transmission of 1.2 kb/s, a secret key rate (KR) of up to 8.8 kb/s can be achieved, with a negligible leakage rate (LR) and bit error rate (BER) of order ${10}^{-3}$ for various communications channels, including GSM 3G and GSM VoLTE networks. At the same time, by ensuring perfect secrecy within symmetric encryption systems, it further highlights the importance of the symmetry principle in the field of information-theoretic security. To our knowledge, this is the first autonomous, perfectly secret system for low-bit-rate voice communication that does not require explicit prior generation and distribution of secret keys. Full article

ChatGPT is a generative artificial intelligence (AI) based chatbot developed by OpenAI and has attracted great attention since its launch in late 2022. This study aims to provide an overview of ChatGPT research through a CiteSpace-based bibliometric analysis. We collected 2465 published articles related to ChatGPT from the Web of Science. The main forces in ChatGPT research were identified by examining productive researchers, institutions, and countries/regions. Moreover, we performed co-authorship network analysis at the levels of author and country/region. Additionally, we conducted a co-citation analysis to identify impactful researchers, journals/sources, and literature in the ChatGPT field and performed a cluster analysis to identify the primary themes in this field. The key findings of this study are as follows. First, we found that the most productive researcher, institution, and country in ChatGPT research are Ishith Seth/Himel Mondal, Stanford University, and the United States, respectively. Second, highly cited researchers in this field are Tiffany H. Kung, Tom Brown, and Malik Sallam. Third, impactable sources/journals in this area are ARXIV, Nature, and Cureus Journal of Medical Science. Fourth, the most impactful work was published by Kung et al., who demonstrated that ChatGPT can potentially support medical education. Fifth, the overall author-based collaboration network consists of several isolated sub-networks, which indicates that the authors work in small groups and lack communication. Sixth, United Kingdom, India, and Spain had a high degree of betweenness centrality, which means that they play significant roles in the country/region-based collaboration network. Seventh, the major themes in the ChatGPT area were “data processing using ChatGPT”, “exploring user behavioral intention of ChatGPT”, and “applying ChatGPT for differential diagnosis”. Overall, we believe that our findings will help scholars and stakeholders understand the academic development of ChatGPT. Full article

Renewable energy communities (RECs) are widely regarded as a transformative opportunity to enhance the management of electricity distribution networks, benefiting the system as a whole and its participants through local energy production, increased self-consumption, and empowering citizens. However, their proliferation introduces significant challenges for distribution system management, particularly at the low-voltage (LV) level, where participants are primarily located. Despite its critical role, the LV network is often overlooked in favor of studies focusing on the system-level impacts. This paper addresses this gap by evaluating the impact of RECs on LV networks and the broader distribution system. The study analyzes various LV networks representative of the Italian context, encompassing both rural and urban areas. By leveraging the software tool OpenDSS and Monte Carlo simulations over an entire year, the analysis captures the inherent variability of load demand and photovoltaic generation, as well as the resulting network imbalances under diverse policy scenarios. The findings reveal that the increasing level of self-consumption could significantly challenge distribution network operation, limiting also the sourcing of flexibility. These results underscore the necessity for advanced management strategies and targeted investments in grid flexibility to ensure the reliability and efficiency of distribution networks integrating RECs. Full article

Revolutionary advances in technology have been seen in many industries, with the IIoT being a prime example. The IIoT creates a network of interconnected devices, allowing smooth communication and interoperability in industrial settings. This not only boosts efficiency, productivity, and safety but also provides transformative solutions for various sectors. This research looks into open-source IIoT and edge platforms that are applicable to a range of applications with the aim of finding and developing high-potential solutions. It highlights the effect of open-source IIoT and edge computing platforms on traditional IIoT applications, showing how these platforms make development and deployment processes easier. Popular open-source IIoT platforms include DeviceHive and Thingsboard, while EdgeX Foundry is a key platform for edge computing, allowing IIoT applications to be deployed closer to data sources, thus reducing latency and conserving bandwidth. This study seeks to identify potential future domains for the implementation of IIoT solutions using these open-source platforms. Additionally, each sector is evaluated based on various criteria, such as development requirement analyses, market demand projections, the examination of leading companies and emerging startups in each domain, and the application of the International Patent Classification (IPC) scheme for in-depth sector analysis. Full article

The expected acceleration in sea level rise (SLR) throughout this century poses significant threats to coastal cities and low-lying regions. Since the early 1990s, high-precision multi-mission satellite altimetry (SA) has enabled the routine measurement of sea levels, providing a continuous 30-year record from which the mean sea level rise (global and regional) and its variability can be computed. The latest reprocessed product from CMEMS span the period from 1993 to 2020, and have enabled the acquisition of accurate sea level data within the coastal range of 0–20 km. In order to fully utilize this new dataset, we establish a global virtual network consisting of 184 virtual SA stations. We evaluate the impact of different stochastic noises on the estimation of the velocity of the sea surface height (SSH) time series using BIC_tp information criterion. In the second step, the principal component analysis (PCA) allows the common mode noise in the SSH time series to be mitigated. Finally, we analyzed the spatiotemporal characteristics and accuracy of sea level change derived from SA. Our results suggest that the stochasticity of the SSH time series is not well described by a combination of random, flicker, and white noise, but is best described by an ARFIM/ARMA/GGM process. After removing the common mode noise with PCA, about 96.7% of the times series’ RMS decreased, and most of the uncertainty associated with the computed SLR decreased. We confirm that the spatiotemporal correlations should be accounted for to yield trustworthy trends and reliable uncertainties. Our estimated SLR is 2.75 ± 0.89 mm/yr, which aligns closely with recent studies, emphasizing the robustness and consistency of our method using virtual SA stations. We additionally introduce open-source software (SA_Tool V1.0) to process the SA data and reduce noise in surface height time series to the community. Full article

The Geysers geothermal field in California is experiencing land subsidence due to the seismic and geothermal activities taking place. This poses a risk not only to the underlying infrastructure but also to the groundwater level which would reduce the water availability for the local community. Because of this, it is crucial to monitor and assess the surface deformation occurring and adjust geothermal operations accordingly. In this study, we examine the correlation between the geothermal injection and production rates as well as the seismic activity in the area, and we show the high correlation between the injection rate and the number of earthquakes. This motivates the use of this data in a machine learning model that would predict future deformation maps. First, we build a model that uses interferometric synthetic aperture radar (InSAR) images that have been processed and turned into a deformation time series using LiCSBAS, an open-source InSAR time series package, and evaluate the performance against a linear baseline model. The model includes both convolutional neural network (CNN) layers as well as long short-term memory (LSTM) layers and is able to improve upon the baseline model based on a mean squared error metric. Then, after getting preprocessed, we incorporate the geothermal data by adding them as additional inputs to the model. This new model was able to outperform both the baseline and the previous version of the model that uses only InSAR data, motivating the use of machine learning models as well as geothermal data in assessing and predicting future deformation at The Geysers as part of hazard mitigation models which would then be used as fundamental tools for informed decision making when it comes to adjusting geothermal operations. Full article

As an emerging product innovation model, open-source innovation has undergone rapid development in recent years. The sustainability and stability of the open-source product community (OSPC) is crucial for product innovation, and the effect that users have on the OSPC’s robustness is an important and closely scrutinized topic. This paper explores the robustness of the OSPC from the aspect of user knowledge contribution. We first construct an OSPC network and analyze its characteristics. An improved node evaluation method is then proposed to identify different types of knowledge contribution nodes. Further, seven node- and edge-based attack strategies are designed to simulate network robustness changes, with evaluation indicators being proposed for structural robustness and knowledge robustness. The results reveal that our proposed node evaluation method can effectively identify nodes of different knowledge contribution types. Additionally, the network is found to have different robustness performance when facing multiple deliberate attacks on three important knowledge contribution node types. Moreover, the network shows different robustness characteristics when facing deliberate attacks on betweenness and weight edges. Our findings can benefit product innovation and OSPC managers by enhancing the robustness of the OSPC network. Full article

Stereoscopic visualization plays a significant role in the detailed and accurate interpretation of various geometric features on the surface of archaeological artifacts, which can be challenging to perceive using conventional two-dimensional visualizations. Moreover, virtual 3D models can be shared with other archaeologists for interpretation and the exchange of opinions. The hardware requirements for rendering stereoscopic 3D models are often readily available on desktop computers, or require only a minimal investment for implementation. This article focuses on creating stereoscopic visualizations of a stylized dove-shaped cult vessel for a virtual museum project. The term “visualization” is defined, emphasizing its significance and everyday applications. The camerawork techniques and processes involved in stereoscopic image production, including anaglyph imaging and polarization, are described. Blender (community-driven project under the GNU General Public License (GPL), Blender Foundation is a member of Open Invention Network, Khronos, Linux Foundation and the Academy Software Foundation) and StereoPhoto Maker (Muttyan, Japan) are reviewed as they relate to the production process of stereoscopic visualizations using open-source software. A series of static stereoscopic visualizations, along with two dynamic stereoscopic examples, are created, one using the anaglyph process, and the other using polarization. Lastly, the article discusses the contribution of stereoscopic visualizations to the interpretation of archaeological artifacts and suggests the optimal parameters for creating stereoscopic visualizations. Full article

Understanding greenhouse gas–climate processes and feedbacks is a fundamental step in understanding climate variability and its links to greenhouse gas fluxes. Chemical transport models are the primary tool for linking greenhouse gas fluxes to their atmospheric abundances. Hence, accurate simulations of greenhouse gases are essential. Here, we present a new simulation in the GEOS-Chem chemical transport model that couples the two main greenhouse gases—carbon dioxide (CO${}_2$) and methane (CH${}_4$)—along with the indirect greenhouse gas carbon monoxide (CO) based on their chemistry. Our updates include the online calculation of the chemical production of CO from CH${}_4$ and the online production of CO${}_2$ from CO, both of which were handled offline in the previous versions of these simulations. In the newly developed coupled (online) simulation, we used consistent hydroxyl radical (OH) fields for all aspects of the simulation, resolving biases introduced by inconsistent OH fields in the currently available uncoupled (offline) CH${}_4$, CO and CO${}_2$ simulations. We compare our coupled simulation with the existing v12.1.1 GEOS-Chem uncoupled simulations run the way they are currently being used by the community. We discuss differences between the uncoupled and coupled calculation of the chemical terms and compare our results with surface measurements from the NOAA Global Greenhouse Gas Reference Network (NOAA GGGRN), total column measurements from the Total Carbon Column Observing Network (TCCON) and aircraft measurements from the Atmospheric Tomography Mission (ATom). Relative to the standard uncoupled simulations, our coupled results suggest a stronger CO chemical production from CH${}_4$, weaker production of CO${}_2$ from CO and biases in the OH fields. However, we found a significantly stronger chemical production of CO${}_2$ in tropical land regions, especially in the Amazon. The model–measurement differences point to underestimated biomass burning emissions and secondary production for CO. The new self-consistent coupled simulation opens new possibilities when identifying biases in CH${}_4$, CO and CO${}_2$ source and sink fields, as well as a better understanding of their interannual variability and co-variation. Full article

IP-PBX have grown considerably in the telecoms and IT industries in recent times due to their low cost, high customizability, open source and hardware-independent nature. Unlike traditional PBX systems that are TDM-based and require a separate wired infrastructure to operate, an IP PBX can be attached to the local LAN and uses SIP with RTP over Internet Protocol (IP) for signaling and data transport, respectively. Asterisk-based IP PBX has become a de facto standard for open-source low-to-medium calling capacity requirements. Single Board Computers (SBCs) are attracting considerable attention from academics, hobbyists and the industry, due to their compact size, low cost, low power, portability and fair processing ability. Raspberry Pi series SBCs are the pioneer in the field, having Pi, Pi2, Pi3 and Pi Zero in production, supporting different processing and storage capabilities. An IP PBX embedded on the raspberry Pi SBC can serve an adequate number of users and provide a tiny platform that can fit in a pocket and be transported anywhere while preserving the functionality of a complete IP PBX. Such systems can be phenomenally successful in situations where large infrastructures cannot be taken, for instance, in warzones or disaster-affected areas where communication networks are damaged, necessitating an immediate requirement for an ad hoc-based communication system. In this paper, we aim to explore the performance of an Asterisk^®-based IP PBX installed on a Raspberry Pi 3 (model B) platform in terms of concurrent call handling using different codecs. Full article

With the rapid development of Internet technology, the innovative value and importance of the open source product community (OSPC) is becoming increasingly significant. Ensuring high robustness is essential to the stable development of OSPC with open characteristics. In robustness analysis, degree and betweenness are traditionally used to evaluate the importance of nodes. However, these two indexes are disabled to comprehensively evaluate the influential nodes in the community network. Furthermore, influential users have many followers. The effect of irrational following behavior on network robustness is also worth investigating. To solve these problems, we built a typical OSPC network using a complex network modeling method, analyzed its structural characteristics and proposed an improved method to identify influential nodes by integrating the network topology characteristics indexes. We then proposed a model containing a variety of relevant node loss strategies to simulate the changes in robustness of the OSPC network. The results showed that the proposed method can better distinguish the influential nodes in the network. Furthermore, the network’s robustness will be greatly damaged under the node loss strategies considering the influential node loss (i.e., structural hole node loss and opinion leader node loss), and the following effect can greatly change the network robustness. The results verified the feasibility and effectiveness of the proposed robustness analysis model and indexes. Full article

Throughout history, many water conservation and management strategies have been employed, but only a few have proved successful. Stepwells were one such effective water management technologies used in India. Stepwells were constructed based on their geographical and topographical suitability, which revealed socio-cultural behaviors and beliefs. They form a unique, efficient system of hydraulic engineering that demonstrates the region’s traditional understanding of the sustainable use and management of its land, water, and agricultural biodiversity. Ancient water harvesting techniques integrated stepwells into agricultural and irrigation networks using prefabricated structures, to allow open channel flow, networked with surface water bodies. They demonstrated the use of Persian wheels, non-mechanized farm machinery, other agricultural implements, etc., and their structure utilized a vast array of local building materials, including granite, marble, sandstone, bricks, lime, mud, wood, etc. The utilization of agricultural wastes, such as rice husk, in the production of lakhori bricks is strongly associated with circular economy principles. They not only communicated and guided communities regarding water management and cleaner production, but also revealed historic knowledge regarding how ancient societies achieved social-ecological resilience. In addition to that, in almost all types of stepwells, aesthetics and ornamentation played an important role and served as a rich source of history to disseminate knowledge of governance, political ideas, social practices and lifestyle. Just a few studies on these stepwells have been published and they have generally focused on their history or on the construction materials of a specific stepwell, rather than offering a wide perspective. This review article will explore the scientific, architectural, artistic, and functional dimensions of all major stepwells in India that have either disappeared or lost their relevance owing to expanding human population and environmental stress. Additionally, this will provide an opportunity to rethink modern water engineering systems and redesign water infrastructure with less negative environmental impacts to achieve the Sustainable Development Goals and ensure water for all. Full article

Food security has become a topic of great concern in many countries. Global food security depends heavily on agriculture that has access to proper resources and best practices to generate higher crop yields. Crops, as with other plants, have a variety of strategies to adapt their growth to external environments and internal needs. In plants, the distal organs are interconnected through the vascular system and intricate hierarchical signaling networks, to communicate and enhance survival within fluctuating environments. Photosynthesis and carbon allocation are fundamental to crop production and agricultural outputs. Despite tremendous progress achieved by analyzing local responses to environmental cues, and bioengineering of critical enzymatic processes, little is known about the regulatory mechanisms underlying carbon assimilation, allocation, and utilization. This review provides insights into vascular-based systemic regulation of photosynthesis and resource allocation, thereby opening the way for the engineering of source and sink activities to optimize the yield performance of major crops. Full article