Arkansas is a major producer of a commodity that is tough to live without: electricity. From electronics engineering and
EPC has introduced an evaluation board implementing a 40Arms (60A peak) three-phase inverter that will run from 30V to 130V. Called EPC91200, it is
Join Erwin Eimers of Sumitomo Chemicals Americas to discover how AI-driven NDR enhances SIEM, closing visibility gaps in IT/OT environments.
Geopolitisch motivierte, KI-gesteuerte DDoS-Angriffe nehmen zu, so Karl Heuser, Manager Security Enterprise (DACH, EUR & Nordics) NETSCOUT.
This research introduces a novel hybrid cryptographic framework that combines traditional cryptographic protocols with advanced methodologies, specifically Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP) and Genetic Algorithms (GA). We evaluated several cryptographic protocols, including AES-ECB, AES-GCM, ChaCha20, RSA, and ECC, against critical metrics such as security level, efficiency, side-channel resistance, and cryptanalysis resistance. Our findings demonstrate that this integrated approach significantly enhances both security and efficiency across all evaluated protocols. Notably, the AES-GCM algorithm exhibited superior performance, achieving minimal computation time and robust side-channel resistance. This study underscores the potential of leveraging machine learning and evolutionary algorithms to advance cryptographic protocol security and efficiency, laying a robust foundation for future advancements in cybersecurity.
(Bild: Dall-E / KI-generiert) Erfahren Sie, wie eine unsichere OAuth-Implementierung in Perl Cyberkriminelle Zugang zu sensiblen Systemen erlaubt und wie man es absichern kann.
AI is evolving at a rapid pace, and the uptake of Generative AI (GenAI) is revolutionising the way humans interact and leverage this technology. GenAI is
We often interact with untrusted parties. Prioritization of privacy can limit the effectiveness of these interactions, as achieving certain goals necessitates sharing private data. Traditionally, addressing this challenge has involved either seeking trusted intermediaries or constructing cryptographic protocols that restrict how much data is revealed, such as multi-party computations or zero-knowledge proofs. While significant advances have been made in scaling cryptographic approaches, they remain limited in terms of the size and complexity of applications they can be used for. In this paper, we argue that capable machine learning models can fulfill the role of a trusted third party, thus enabling secure computations for applications that were previously infeasible. In particular, we describe Trusted Capable Model Environments (TCMEs) as an alternative approach for scaling secure computation, where capable machine learning model(s) interact under input/output constraints, with explicit information flow control and explicit statelessness. This approach aims to achieve a balance between privacy and computational efficiency, enabling private inference where classical cryptographic solutions are currently infeasible. We describe a number of use cases that are enabled by TCME, and show that even some simple classic cryptographic problems can already be solved with TCME. Finally, we outline current limitations and discuss the path forward in implementing them.
onsemi today announced that it has completed its acquisition of the Silicon Carbide Junction Field-Effect Transistor (SiC JFET) technology business, including the United Silicon Carbide subsidiary, from Qorvo for $115 million in cash.
The new MOTIX™ family of full-bridge ICs is designed for smart brushed DC motor applications, enhancing comfort and convenience in vehicles.The post Infineon Introduces the New BTM90xx Family of Full-Bridge ICs for Brushed DC Motor Applications appeared first on Power Electronics News.
WASHINGTON (dpa-AFX) - Wednesday, onsemi (ON) announced the completion of its acquisition of the Silicon Carbide Junction Field-Effect Transistor business, including the United Silicon Carbide
Czech cybersecurity firm Wultra, known for its advanced post-quantum authentication solutions, has raised €3m in a Seed+ funding round.
Global Automotive Power MOSFET Drivers Market size was valued at USD 400 million in 2023 and is poised to grow from USD 430 million in 2024 to USD 766 90 million by 2032 growing at a CAGR of 7 5 ...
Global Lithium Ion Battery Capacitor Market Research Report: By Capacity, By Voltage, By Chemistry, By End User and By Regional - Forecast to 2032.
ISO 26262-ready Motorsteuer-ICs der BTM90xx-Serie für Anwendungen wie Tür-, Spiegel-, Karosserie- und Zonensteuerungsmodule.
Ein neuer Gesetzesentwurf sieht vor, dass öffentliche Einrichtungen und Betreiber kritischer Infrastrukturen künftig keine Lösegeldzahlungen mehr an Cyberkriminelle leisten dürfen.
Check Point Software Technologies geht nun mithilfe künstlicher Intelligenz gegen Dynamic-Link-Library (DLL) -Bedrohungen vor. "DeepDLL" ist ein neues,
AI is evolving at a rapid pace, and the uptake of Generative AI (GenAI) is revolutionising the way humans interact and leverage this technology. GenAI is
Eine Hackergruppe missbraucht eine Verschlüsselungsfunktion von AWS, um Kunden des Cloudanbieters zu erpressen. Ein permanenter Datenverlust droht. (Ransomware, Storage)
Für Linux Kernel wurde ein Update für den IT-Sicherheitshinweis zu einer bekannten Schwachstelle veröffentlicht. Was betroffene User tun können, erfahren Sie hier.
Für GNU Emacs wurde ein Update zur IT-Sicherheitswarnung einer bekannten Schwachstelle veröffentlicht. Wie sich betroffene Anwender verhalten sollten, erfahren Sie hier.
AI is evolving at a rapid pace, and the uptake of Generative AI (GenAI) is revolutionising the way humans interact and leverage this technology. GenAI is
AI and ML are revolutionizing fraud detection in digital banking, enhancing security by enabling real-time, accurate, and adaptive solutions.
54 % der großen Organisationen bezeichnen die Abhängigkeiten in der Lieferkette als größtes Hindernis für die Erreichung von Cyber-Resilienz. + Geopolitische Unruhen haben die Wahrnehmung von Risiken beeinflusst, wobei jeder dritte CEO Cyberspionage und den Verlust sensibler Informationen/Diebstahl geistigen Eigentums als seine größte Sorge nennt. + Die wachsende Komplexität verschärft die Cyber-Ungleichheit weiter, vertieft die Kluft zwischen Industrie- und Schwellenländern, vergrößert die sektoralen Unterschiede und die Kluft zwischen großen und kleinen Organisationen.
Die Bedrohungen im Cyberraum entwickeln sich schneller, als viele Unternehmen reagieren können: Sie stehen einer Vielzahl neuer Herausforderungen gegenüber – von KI-unterstützten Angriffen bis hin zu Deepfake-Technologien. Andreas Müller, Vice President Enterprise Sales Central and Eastern Europe bei Delinea, beleuchtet die wichtigsten Cybersicherheitstrends und -herausforderungen für das Jahr 2025. Cybersicherheit der Zukunft: Frühe Erkennung erweitert…
Cyber Threat Intelligence (CTI) is critical for mitigating threats to organizations, governments, and institutions, yet the necessary data are often dispersed across diverse formats. AI-driven solutions for CTI Information Extraction (IE) typically depend on high-quality, annotated data, which are not always available. This paper introduces 0-CTI, a scalable AI-based framework designed for efficient CTI Information Extraction. Leveraging advanced Natural Language Processing (NLP) techniques, particularly Transformer-based architectures, the proposed system processes complete text sequences of CTI reports to extract a cyber ontology of named entities and their relationships. Our contribution is the development of 0-CTI, the first modular framework for CTI Information Extraction that supports both supervised and zero-shot learning. Unlike existing state-of-the-art models that rely heavily on annotated datasets, our system enables fully dataless operation through zero-shot methods for both Entity and Relation Extraction, making it adaptable to various data availability scenarios. Additionally, our supervised Entity Extractor surpasses current state-of-the-art performance in cyber Entity Extraction, highlighting the dual strength of the framework in both low-resource and data-rich environments. By aligning the system's outputs with the Structured Threat Information Expression (STIX) format, a standard for information exchange in the cybersecurity domain, 0-CTI standardizes extracted knowledge, enhancing communication and collaboration in cybersecurity operations.
Source: www.infosecurity-magazine.com - Author: A new ransomware group dubbed FunkSec, which emerged in late 2024, has
Samsung hat ein wichtiges Sicherheitsupdate für acht seiner Smartphones veröffentlicht. Fünf davon stufen Experten als besonders gefährlich ein.
Microsoft hat rechtliche Schritte gegen drei Personen eingeleitet, die beschuldigt werden, ein "Hacking-as-a-Service"-System betrieben zu haben. Dieses war darauf ausgelegt, Sicherheitsmaßnahmen der KI-Plattform des Unternehmens zu umgehen.
Global energy consumption has increased steadily over the past few decades and is expected to increase further in the future…The post Unlocking a Greener Future: GaN Technology Leads the Energy Efficiency Revolution appeared first on Electronic Engineering Issue.
Silicon Carbide SIC Power Semiconductors Market Report by Key Insights Trends and In depth Overview The new report on the Silicon Carbide SIC Power Semiconductors Market research report provides a comprehensive analysis of the current market landscape imports segmentation key ...
Wide band gap (WBG) semiconductors, such as silicon carbide (SiC), provide substantial advantages over traditional power devices, such as IGBTs, previously used in numerous applications, such as vehicle chargers electrical Read the full article on EO Power 36The post Reducing development time of SiC-based power converters in automotive applications appeared first on Elettronica Plus.
Artificial intelligence is the greatest investment opportunity of our lifetime. The time to invest in groundbreaking AI is now, and this stock is a steal! The whispers are turning into roars. Artif…
Q-Day is coming like a thief in the night. The day when quantum computers with their immense computing power turn everything upside down may be just around the corner. All kinds of computer systems are suddenly no longer safe, state secrets are on the street, parts of society are collapsing. At least if we don't do anything. Intelligence and security service AIVD, together with other parties, released a new manual to turn the tide, because it is two to twelve.
Publication date: 1 March 2025Source: Journal of Power Sources, Volume 631Author(s): Tianqing Yuan, Feng Gao, Jing Bai, Hao Sun
Unlike batteries, capacitors are charge-based devices for the storage of electricity. A segment may include a range of chemicals, heavy
According to a new report published by IMR Market Reports titled Silicon Carbide Boat Market by Solution Services Application Global Opportunity Analysis and Industry Forecast 2024 2032 The global Silicon Carbide Boat market was valued at US 109 21 million ...
Renesas Electronics Corporation, a premier supplier of advanced semiconductor solutions, today introduced new 100V high-power N-Channel MOSFETs that deliver industry-leading high-current switching performance for applications such as motor control, batt
Toyoda Gosei Co ( ($JP:7282) ) has shared an announcement. Toyoda Gosei has achieved a significant breakthrough in enhancing power device performan...
We have extended the entry deadline to the Electronics Weekly Women Leaders In Electronics Awards to ensure no one misses out! The deadline is: Friday 24 January 2025
Toyoda Gosei in Japan has developed a 200mm single crystal wafer of gallium nitride (GaN) for vertical transistors.
Multilevel converters are not a technological novelty, but researchers and engineers are still exploring new configurations and control strategies to improve their performance and adaptability.The post Power Converters from High Voltage to EV Applications: Analysis of NPC Multilevel Inverters appeared first on Power Electronics News.
Anreicherungsmodus-GaN-Transistor Markttrends und Wachstumsanalyse 2031
Power GaN Device Market Size & Growth Report The Power GaN Device Market is witnessing significant growth due to its increasing adoption in EVs, solar inverters, and high-efficiency power applications. AUSTIN, TX, UNITED STATES, January 7, 2025 /EINPresswire.com/ — Market Size & Industry Insights As Per the SNS Insider,“The Power GaN Device Market was USD […]
New Report Forecasts Substantial Growth in the Global Market for Passive Devices in High-Power Electronics Over the Next Decade New Report Forecasts Substantial Growth in the Global Market for Passive Devices in High-Power Electronics Over the Next Decade
The research used bacterial biosensors containing bacterial luciferase genes to monitor changes in the environment in real-time. In this work to express four different gene constructs: recA:luxCDABE, soxS:luxCDABE, micF:luxCDABE, and rpoB:luxCDABE in Escherichia coli SM lux biosensor after exposure to three different antibiotics (nalidixic acid, ampicillin, kanamycin) and diclofenac was determined. It was found that incubation of the E. coli SM strain in various concentrations of analytes results in differentiation in gene expression at each of the tested concentrations (from 0.625 to 10 µg/mL) and during all three measurements, in “time 0”, after 30 min. and after 1 h. The measurable signal is created as a result of the action of reporter genes (bacterial luciferase genes luxCDABE), present in genetically modified bacterial cells. E. coli luminescent bioreporters in the stationary phase were used. In the analysis of the induction of the promoter (regulatory proteins) to the control (0 µg/ml), the highest biosensor response was shown in the case of kanamycin concentration equal to 0.625 µg/mL after 1-h incubation. The highest increase express gene construct was found for micF:luxCDABE in E. coli SM343 lux biosensor, where the micF promoter induction relative to the control at a concentration of 0.625 µg/mL is 73.9%.
Publication date: 15 January 2025Source: Chemical Engineering Journal, Volume 504Author(s): Gagan Bahadur Pradhan, Kumar Shrestha, Md. Assaduzzaman, Sagar Sapkota, SeungJae Lim, Md Selim Reza, Jae Yeong Park
Due to their inherent advantages, optical fiber sensors (OFSs) can substantially contribute to the monitoring and performance enhancement of energy infrastructure. However, optical fiber sensor systems often are standalone solutions and do not connect to the main energy infrastructure control systems. In this paper, we propose a solution for the digitalization of an optical fiber sensor system realized by the Open Platform Communications Unified Architecture (OPC UA) protocol and the Internet of Things (IoT) platform Insights Hub. The optical fiber sensor system is based on bidirectional incoherent optical frequency domain reflectometry (biOFDR) and is used for the interrogation of fiber Bragg grating (FBG) arrays. To allow for an automated sensor identification and thus measurement procedure, an optical sensor identification marker based on a unique combination of fiber Bragg gratings (FBGs) is established. To demonstrate the abilities of the digitalized sensor network, a field test was performed in a power plant test facility of Siemens Energy. Temperature measurements of a packaged FBG sensor fiber were performed with a portable demonstrator, illustrating the system’s robustness and the comprehensive data processing stream from sensor value formation to the cloud. The realized network services promote sensor data quality, fusion, and modeling, expanding opportunities using digital twin technology.
Due to their inherent advantages, optical fiber sensors (OFSs) can substantially contribute to the monitoring and performance enhancement of energy infrastructure. However, optical fiber sensor systems often are standalone solutions and do not connect to the main energy infrastructure control systems. In this paper, we propose a solution for the digitalization of an optical fiber sensor system realized by the Open Platform Communications Unified Architecture (OPC UA) protocol and the Internet of Things (IoT) platform Insights Hub. The optical fiber sensor system is based on bidirectional incoherent optical frequency domain reflectometry (biOFDR) and is used for the interrogation of fiber Bragg grating (FBG) arrays. To allow for an automated sensor identification and thus measurement procedure, an optical sensor identification marker based on a unique combination of fiber Bragg gratings (FBGs) is established. To demonstrate the abilities of the digitalized sensor network, a field test was performed in a power plant test facility of Siemens Energy. Temperature measurements of a packaged FBG sensor fiber were performed with a portable demonstrator, illustrating the system’s robustness and the comprehensive data processing stream from sensor value formation to the cloud. The realized network services promote sensor data quality, fusion, and modeling, expanding opportunities using digital twin technology.
Frequent glucose monitoring is essential for effective diabetes management. Currently, glucose monitoring is done using invasive methods such as finger-pricking and subcutaneous sensing. However, these methods can cause discomfort, heighten the risk of infection, and some sensing devices need freque …
IoT Revolutionizes Asset Management in Oil and Gas Industry, Enhancing Efficiency and … transform asset management in the oil and gas industry. The Challenge: … Managing Aging Infrastructure For many oil and gas companies, managing aging infrastructure …
Dublin, Dec. 27, 2024 (GLOBE NEWSWIRE) -- The
Technological advancements in mechanized food production have expanded markets beyond geographical boundaries. At the same time, the risk of contamination has increased severalfold, often resulting in significant damage in terms of food wastage, economic loss to the producers, danger to public health, or all of these. In general, governments across the world have recognized the importance of having food safety processes in place to impose food recalls as required. However, the primary challenges to the existing practices are delays in identifying unsafe food, siloed data handling, delayed decision making, and tracing the source of contamination. Leveraging the Internet of Things (IoT), 5G, blockchains, cloud computing, and big data, a novel framework has been proposed to address the current challenges. The framework enables real-time data gathering and in situ application of machine learning-powered algorithms to predict contamination and facilitate instant decision making. Since the data are processed in real time, the proposed approach enables contamination to be identified early and informed decisions to be made confidently, thereby helping to reduce damage significantly. The proposed approach also throws up new challenges in terms of the implementation of changes to data collection across all phases of food production, onboarding various stockholders, and adaptation to a new process.
The Internet of Things (IoT) has seen remarkable advancements in recent years, leading to a paradigm shift in the digital landscape. However, these technological strides have introduced new challenges, particularly in cybersecurity. IoT devices, inherently connected to the internet, are susceptible to various forms of attacks. Moreover, IoT services often handle sensitive user data, which could be exploited by malicious actors or unauthorized service providers. As IoT ecosystems expand, the convergence of traditional and cloud-based systems presents unique security threats in the absence of uniform regulations. Cloud-based IoT systems, enabled by Platform-as-a-Service (PaaS) and Infrastructure-as-a-Service (IaaS) models, offer flexibility and scalability but also pose additional security risks. The intricate interaction between these systems and traditional IoT devices demands comprehensive strategies to protect data integrity and user privacy. This paper highlights the pressing security concerns associated with the widespread adoption of IoT devices and services. We propose viable solutions to bridge the existing security gaps while anticipating and preparing for future challenges. This paper provides a detailed survey of the key security challenges that IoT services are currently facing. We also suggest proactive strategies to mitigate these risks, thereby strengthening the overall security of IoT devices and services.
Infrared Sensor Market Size & Trends The global infrared sensor market size was estimated at USD 711.4 million in 2023 and is expected to grow at a CAGR
LoRa-based sensor nodes may provide a reliable solution for wireless communication in orchard cultivation and smart farming, facilitating real-time environmental monitoring. However, the signal strength and data integrity can be affected by several factors, such as trees, terrain, weather, and nearby electrical devices. The objective of this study is to evaluate the impact of orchard trees on the performance of a LoRa sensor node under orchard conditions. A sensor node, built with a commercial LoRa transceiver and microcontroller unit (MCU), was paired with a single-channel gateway linked to an orchard irrigation system. Performance metrics such as the packet delivery ratio (PDR), received signal strength indicator (RSSI), and signal-to-noise ratio (SNR) were measured over a range of 20 to 120 m under open field conditions and in an orchard with trees averaging 3.12 and 4.36 m in height. Data were sent every 20 s using three spreading factors (SF8, SF10, and SF12) and stored as a CSV file in the MCU via a Python program. The results showed that the PDR remained consistently high (100%) under non-vegetative (open field) conditions. In the orchard under vegetative conditions, the PDR dropped significantly, with SF12 maintaining 100% only up to 120 m. For SF10, the packet delivery rates dropped to 45% at 80 m, while SF8 achieved 100% at 20 m but decreased to 52% at 40 m. SNR values also declined with an increase in distance, becoming largely undetectable beyond 40 m for SF8. These findings indicate that vegetation greatly impacts LoRa sensor node performance, reducing packet delivery and signal quality in orchards.
This paper unveils an innovative wireless piezoresistive sensor designed to operate autonomously without batteries, addressing the critical challenge …
There are more than 60 radio-frequency identification (RFID) technologies in common use worldwide, along with mobile technologies based on Bluetooth Low Energy (BLE) or Near-Field Communication (NFC). In addition, there are a wide array of communication standards and protocols, connection
NXP's Trimension SR250 integrates UWB radar and ranging, enhancing autonomous systems and IoT with improved performance and efficiency, while offering comprehensive support for easier deployment.The post Innovative IoT Solutions: NXP’s Trimension SR250 Combines UWB Radar and Secure Ranging appeared first on EE Times Asia.
The Latest research report on the Wearable Biosensors Market 2024 provides a comprehensive analysis of the current market landscape with forecasts extending to 2031 This study combines qualitative and quantitative insights to highlight significant market developments challenges competitive dynamics and ...
Smart cities are getting more popular But how might smart cities enhance people s lives and be useful First and foremost technology contribute to a city s economic growth by bringing new business models cutting energy costs and improving quality ...
This systematic literature review explores the intersection of AI-driven digital twins and IoT in creating a sustainable building environment. A comprehensive analysis of 125 papers focuses on four major themes. First, digital twins are examined in construction, facility management, and their role in fostering sustainability and smart cities. The integration of IoT and AI with digital twins and energy optimization for zero-energy buildings is discussed. Second, the application of AI and automation in manufacturing, particularly in Industry 4.0 and cyber-physical systems, is evaluated. Third, emerging technologies in urban development, including blockchain, cybersecurity, and EEG-driven systems for sustainable buildings, are highlighted. The study underscores the role of data-driven approaches in flood resilience and urban digital ecosystems. This review contributes to sustainability by identifying how digital technologies and AI can optimize energy use and enhance resilience in both urban and industrial contexts.
Developing and managing complex IoT–Edge–Cloud Continuum (IECC) systems are challenging due to the system complexity and diversity. Internet of Things (IoT), Edge, and Cloud components combined with artificial intelligence (AI) in data processing systems must ensure strong security and privacy for data sources. The approach of the IECC Data Management Framework (DMF) introduces a novel combination of multiple easy-to-configure plugin environments using data visualization features. These contributions collectively address the critical challenges inherent in heterogeneous environments such as scalability, data privacy, and configuration management by standardizing data flow configurations and increasing stakeholder trust in sensitive applications, particularly in critical infrastructure monitoring.
Biological cells have many vital functions in the organism. For example, they produce proteins, carbohydrates and fats. But they are also responsible for detoxifying harmful molecules and transmitting signals and immune defense steps. A so-called redox potential is required to drive these processes. It depends on the ratio of NADPH (nicotinamide adenine dinucleotide phosphate in negatively charged, “reduced” form) to its oxidized form NADP⁺. A team led by plant biotechnologist Prof Markus Schwarzländer from the University of Münster and biochemist […]
Temperature and pressure variations are the key early warnings for the thermal runaway safety monitoring of lithium batteries. Although flexible tempe…
This study presents a blockchain-based traceability system designed specifically for the olive oil supply chain, addressing key challenges in transparency, quality assurance, and fraud prevention. The system integrates Internet of Things (IoT) technology with a decentralized blockchain framework to provide real-time monitoring of critical quality metrics. A practical web application, linked to the Ethereum blockchain, enables stakeholders to track each stage of the supply chain via tamper-proof records. Key functionalities include smart contracts that automate quality checks, ensuring data integrity and providing immediate verification of product authenticity. Initial user feedback highlights the system’s potential to enhance transparency and reduce fraud risks in the olive oil market, supporting consumer trust and regulatory compliance. This approach offers a scalable solution adaptable to other high-value agricultural products, demonstrating the blockchain’s transformative potential for secure and transparent food traceability.
Advance Market Analytics published a new research publication on IoT in Construction Market Insights to 2030 with 232 pages and enriched with self explained Tables and charts in presentable format In the Study you will find new evolving Trends Drivers ...
CEA-Leti Device Integrates Light Sensing & Modulation, Bringing Key Scalability, Compactness and Optical-Alignment Advantages First-Report...
Brady Corporation has released an RFID-based solution to help prevent fires from lithium-ion batteries used on e-vehicles and warehouses.
Although many electronics businesses are aware of the upcoming Ecodesign for Sustainability Products Regulation (ESPR), many have yet to begin preparations because of uncertainty about where to start.
Nowadays, indoor positioning using ultra-wideband (UWB) signals is actively being developed with the aim of implementing existing ideas and solutions, improving their performance, and searching for new measurement schemes. This paper proposes an approach to estimating the distance between wireless nodes by measuring radio signal propagation time using UWB chaotic radio pulses and UWB transceivers. This type of signal is a simple and practically interesting alternative to radio carriers of other types of UWB signals, which are based on packets of pulses (usually ultra-short pulses). The practical interest is caused by the noise-like nature of chaotic radio pulses, as well as their immunity to multipath fading and ease of generation. The aim of this work is to analyze such a system and identify the fundamental limitations inherent in the proposed approach. This paper describes a wireless system for measuring the signal propagation time based on the envelope of chaotic radio pulses using the SS-TWR (Single-Sided Two-Way Ranging) method. A difference scheme is used to determine the range. The characteristics of the proposed system are studied experimentally. The factors related to the threshold scheme for determining the time of arrival of a radio signal that introduce a systematic error into the measurement results are revealed, and approaches to correcting their influence are proposed.
Der Krankenstand bei den UWB-Mitarbeitern ist hoch. Darum hatte sich die Abholung des Papiermülls immer wieder verschoben. Jetzt holt der Umweltbetrieb ab.
December the 20th, 2024 – Yet more innovation in the form of RFID tags is set to grace
Whole-body PET imaging is often hindered by respiratory motion duringacquisition, causing significant degradation in the quality of reconstructedactivity images. An additional challenge in PET/CT imaging arises from therespiratory phase mismatch between CT-based attenuation correction and PETacquisition, leading to attenuation artifacts. To address these issues, wepropose two new, purely data-driven methods for the joint estimation ofactivity, attenuation, and motion in respiratory self-gated TOF PET. Thesemethods enable the reconstruction of a single activity image free from motionand attenuation artifacts. The proposed methods were evaluated using data from the anthropomorphicWilhelm phantom acquired on a Siemens mCT PET/CT system, as well as 3 clinicalFDG PET/CT datasets acquired on a GE DMI PET/CT system. Image quality wasassessed visually to identify motion and attenuation artifacts. Lesion uptakevalues were quantitatively compared across reconstructions without motionmodeling, with motion modeling but static attenuation correction, and with ourproposed methods. For the Wilhelm phantom, the proposed methods delivered image quality closelymatching the reference reconstruction from a static acquisition. Thelesion-to-background contrast for a liver dome lesion improved from 2.0 (nomotion correction) to 5.2 (proposed methods), matching the contrast from thestatic acquisition (5.2). In contrast, motion modeling with static attenuationcorrection yielded a lower contrast of 3.5. In patient datasets, the proposedmethods successfully reduced motion artifacts in lung and liver lesions andmitigated attenuation artifacts, demonstrating superior lesion to backgroundseparation. Our proposed methods enable the reconstruction of a single, high-qualityactivity image that is motion-corrected and free from attenuation artifacts,without the need for external hardware.
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What the industry needs are RAIN RFID labels that meet the requirements of retailers for inventory taking while offering a higher level of waterproofing.
EPC Solutions Taiwan has developed a passive, RTLS system for data centers to provide equipment management and theft protection
The rise in electricity costs for households over the past year has driven significant changes in energy usage patterns, with many residents adopting smarter energy-efficient practices, such as improved indoor insulation and advanced home energy management systems powered by IoT and Digital Twin technologies. These measures not only mitigate rising bills but also ensure optimized thermal comfort and sustainability in typical residential settings. This paper proposes an innovative framework to facilitate the adoption of energy-efficient practices in households by leveraging the integration of Internet of Things technologies with Digital Twins. It introduces a novel approach that exploits standardized parametric 3D models, enabling the efficient simulation and optimization of home energy systems. This design significantly reduces deployment complexity, enhances scalability, and empowers users with real-time insights into energy consumption, indoor conditions, and actionable strategies for sustainable energy management. The results showcase that the proposed method significantly outperforms traditional approaches, achieving a 94% reduction in deployment time and a 98% decrease in memory usage through the use of standardized parametric models and plug-and-play IoT integration.
With the widespread adoption and increasing application of blockchain technology, cryptocurrency wallets used in Bitcoin and Ethereum play a crucial role in facilitating decentralized asset management and secure transactions. However, wallet security relies heavily on private keys, with insufficient attention to the risks of theft and exposure. To address this issue, Chaum et al. (ACNS’21) proposed a “proof of ownership” method using a “backup key” to prove ownership of private keys even when exposed. However, their interactive proof approach is inefficient in large-scale systems and vulnerable to side-channel attacks due to the long key generation time. Other related schemes also suffer from low efficiency and complex key management, increasing the difficulty of securely storing backup keys. In this paper, we present an efficient, non-interactive proof generation approach for ownership of secret keys using a single backup key. Our approach leverages non-interactive zero-knowledge proofs and symmetric encryption, allowing users to generate multiple proofs with one fixed backup key, simplifying key management. Additionally, our scheme resists quantum attacks and provides a fallback signature. Our new scheme can be proved to capture unforgeability under the computational indistinguishability from the Uniformly Random Distribution property of a proper hash function and soundness in the quantum random oracle model. Experimental results indicate that our approach achieves a short key generation time and enables an efficient proof generation scheme in large-scale decentralized systems. Compared with state-of-the-art schemes, our approach is applicable to a broader range of scenarios due to its non-interactive nature, short key generation time, high efficiency, and simplified key management system.
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In today’s expanding cities, pipeline networks are becoming an essential part of the industrial infrastructure. Monitoring these pipelines autonomously is becoming increasingly important. Inspecting pipelines for cracks is one specific task that poses a huge burden on humans. Undetected cracks may pose multi-dimensional risks. In this paper, we introduce the Pipeline Leak Identification Emergency Robot Swarm (PLIERS) system, an industrial system that deploys Internet-of-Things (IoT), robotics, and neural network technologies to detect cracks in emptied water and sewage pipelines. In PLIERS, a swarm of robots inspect emptied pipelines from the inside to detect cracks, collect images of them, and register their locations. When the images are taken, they are fed into a cloud-based module for analysis by a convolutional neural network (CNN). The CNN is used to detect cracks and identify their severity. Through extensive training and testing, the CNN model performance showed promising scores for accuracy (between 80% and 90%), recall (at least 95%), precision (at least 95%), and F1 (at least 96%). Additionally, through the careful design of a prototype for a water/sewage pipeline structure with several types of cracks, the robots used managed to exchange information among themselves and convey crack images to the cloud-based server for further analysis. PLIERS is a system that deploys modern technologies to detect and recognize cracks in pipeline grids. It adds to the efforts of improving instrumentation and measurement approaches by using robots, sensory, IoT principles, and the efficient analysis of CNNs.
Advanced Science, EarlyView.
The global temperature sensor market is set for explosive growth, with projections indicating a surge to $9.66 Billion by 2030. This remarkable expansion,...
Single-photon avalanche diodes (SPADs) are advanced sensors capable ofdetecting individual photons and recording their arrival times with picosecondresolution using time-correlated Single-Photon Counting detection techniques.They are used in various applications, such as LiDAR, and can capturehigh-speed sequences of binary single-photon images, offering great potentialfor reconstructing 3D environments with high motion dynamics. To complementsingle-photon data, they are often paired with conventional passive cameras,which capture high-resolution (HR) intensity images at a lower frame rate.However, 3D reconstruction from SPAD data faces challenges. Aggregatingmultiple binary measurements improves precision and reduces noise but can causemotion blur in dynamic scenes. Additionally, SPAD arrays often have lowerresolution than passive cameras. To address these issues, we propose a novelcomputational imaging algorithm to improve the 3D reconstruction of movingscenes from SPAD data by addressing the motion blur and increasing the nativespatial resolution. We adopt a plug-and-play approach within an optimizationscheme alternating between guided video super-resolution of the 3D scene, andprecise image realignment using optical flow. Experiments on synthetic datashow significantly improved image resolutions across various signal-to-noiseratios and photon levels. We validate our method using real-world SPADmeasurements on three practical situations with dynamic objects. First onfast-moving scenes in laboratory conditions at short range; second very lowresolution imaging of people with a consumer-grade SPAD sensor fromSTMicroelectronics; and finally, HR imaging of people walking outdoors indaylight at a range of 325 meters under eye-safe illumination conditions usinga short-wave infrared SPAD camera. These results demonstrate the robustness andversatility of our approach.
(Bild: Siemens) Entdecken Sie, wie ein Konsortium die Messqualität von Sensoren mit in Glas integrierten Lichtwellenleitern revolutioniert. Erfahren Sie mehr über Anwendungen in Leistungselektronik und Meeresforschung.
Global Wearable Inertial Sensors Market Poised for Significant Growth, Expected to Surpass USD 1 Billion by 2029...
The ST1VAFE3BX is ST’s newest biosensor. It combines and synchronizes biopotential inputs with an ST accelerometer and a machine learning core, thus
NXP's wireless ultra-wideband (UWB) battery management system simplifies the assembly of electric vehicles.
TDK has unveiled its new InvenSense SmartSonic ICU-10201 high-performance ultrasonic Time-of-Flight (ToF) sensor with an embedded processor and extended memory space.
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