This paper introduces an agent-based approach that semantically integrates the Building Information Model (BIM), Geographical Information System (GIS), and the Environmental Data Agent (EDA)-based optimization interface between Information and Operational Technology (IT/OT) for more trusted and resilient data centers. Using the cybersecurity-aware BIM-GIS-IoT data model facilitates the exchange of requirements and forecasts to optimize energy use, environmental impact, availability, and costs in data centers. At the core of this solution, the EDA securely mediates data exchange between IT and OT, translating IT resource consumption into energy metrics for effective optimization.

The OPtimization of Electric Vehicle Autonomy (OPEVA) project enhances data aggregation for Electric Vehicles (EVs) by collecting critical real-time data (i.e., vehicle performance, battery health, charging behaviours) through heterogeneous data acquisition devices built on robust HW and integrated with Internet of Things (IoT) protocols. By combining internal sensor data and driver-specific behaviours with external information (e.g., road conditions, charging station availability), OPEVA maximizes vehicles performance, establishing secure and seamless data communication between EVs and the infrastructure, and using IoT and cloud computing tools alongside Vehicle-to-Everything (V2X) devices and networks. This paper focuses on the extensible data model ensuring semantic data integrity considering in- and out-vehicle factors, presenting data acquisition solutions dealing with OPEVA's semantic data model and their use in various Artificial Intelligence (AI)-powered use cases (e.g., range prediction, route optimization, battery management).

Traditional "2nd Wave (2WAI)" AI algorithms are highly specialized in narrowly-defined tasks in the transportation and mobility domain, however, quite hardly explainable and unable to cover the needs of unbiased and trusted decision-making in the CCAM domain. There is a strong need to accelerate the shift towards human-like "3rd Wave AI (3WAI)" to overcome the challenges of road transport to make autonomous vehicles and driving safe, cleaner and more efficient. This paper aims to shed light on ambitious pathways toward more trustworthy and explainable AI by presenting a strategic approach envisioning the requirements of 5 main audience profiles in the CCAM context (developers, decision-makers, regulators, end-users, and CCAM Service providers). The presented approach envisages a 6-dimensional concept that brings features of i) Transparent and explainable; ii) Fair and impartial; iii) Responsible and accountable; iv) Robust and Reliable; v) Respectful of Privacy; vi) Safe and Secure, transportation. To achieve the transition towards 3WAI a model-based n-sprint V methodology is introduced that is enriched with continuous validation by putting ethics at the centre of all potential innovations. The paper presents a review of the recently funded European projects within the concept of AI-powered CCAM.

Metaverse was recently introduced as an online virtual world or world of worlds that incorporates the augmented/virtual/mixed/extended reality (AR/VR/MR/XR), Internet of Things (IoT), personalization with virtual avatars, interaction and communication interlinking real and/or virtual “things” with “things”. Metaverse users are supposed to live in a digital realm in which such living universes are created either as imaginative or realistic environments. This brings a new creative space for architects in the Architecture-Engineering-Construction (AEC) sector to design new buildings and cities in a semi-realistic digital world as they can be inspired by actual urban settings and augment these real or realistic environments towards a cyber environment. This paper aims to present such a cyber environment, called BIMyVerse, that blends IoT-enabled situational awareness, VR-supported integrated semantic digital twin models incorporating Building Information Model (BIM), Geographical Information System (GIS) and sensory cyberspace and explainable interpretations for better interaction with buildings and urban contexts. The proof of concept studies demonstrate how BIMyVerse can be used for i) situational fire regulation check and monitoring the maintenance status (building-scale); ii) circular economy provisioning through the digital twin of an urban transformation area (urban-scale).

This paper introduces a robust random number generator that based on Bernoulli discrete chaotic map. An eight bit SAR ADC is used with discrete time chaotic map to generate random bit sequences. Compared to RNGs that use the continuous time chaotic map, sensitivity to process, voltage and temperature (PVT) variations are reduced. Thanks to utilizing switch capacitor circuits to implement Bernoulli chaotic map equations, power consumption decreased significantly. Proposed design that has a throughput of 500 Kbit/second is implemented in TSMC 180 nm process technology. Generated bit sequences has successfully passed all four primary tests of FIPS-140-2 test suite and all tests of NIST 820–22 test suite without post processing. Furthermore, data rate can be increased by sacrificing power consumption. Hence, proposed architecture could be utilized in high speed cryptography applications.

This paper presents a wake-up & shut-down ring oscillator based Random Number Generator (RNG) together with a new method of duty cycle correction circuit for cryptographic applications more specifically irregular sampling of regular waveform method based True Random Number Generators (TRNGs). The proposed circuit is composed of fully digital elements and contains only one D type flip-flop, one inverter, one buffer, and one XOR gate. The bias at the one-zero balance that occurs in irregular sampling of regular waveform based RNGs due to the regular clock's duty cycle is avoided by discarding the sampled data at the problematic duty cycle regions. The improvement provided with the proposed circuit is shown by applying the method to a Random Number Generator based on irregular sampling of regular waveform method. The irregular clock is generated by employing wake-up and shut-down ring oscillators. The speed of the sampling is reduced by downsampling the irregular signal. All of the circuits mentioned in this paper are implemented in Xilinx Zynq7000 FPGA. Furthermore, NIST 800-22 test suite is used to test all of the designs. Data sets of one million bits are collected with a UART module. All the NIST 800-22 test suite requirements are satisfied with the duty cycle correction applied RNG. The proposed circuit improves the throughput of the wake-up&shut-down RNG 12.3 times. Furthermore, the proposed circuit can be used with any RNG based on irregular sampling of regular waveform method.

Cybernetic technologies enhanced with Augmented/Virtual Reality (AR/VR) present many opportunities for surgeon training in plastic surgery. There is an increasing need for a controlled feedback mechanism that should encounter three aspects: trainees’ performance, the effective assessment of the training program by trainers, and the evidence-based realistic cases dealing with the patient’s health status considering the pre-/peri-/post-operational steps. This paper aims to present a triangular cybernetic approach that melts the need of the trainees’, trainers’ and patients’ needs in the same pot over an AR/VR-based virtual environment. The proposed AR/VR solution enables active interaction with the 3D medical and face/head data of the patient, utilization of patient health record and health status IoT data and trainer-trainee-patient interaction for better training. The solution experiments on otoplasty, cheek reshaping and jaw filling.

An FPGA-based chaotic “true” random number generator (RNG) is targeted. In the demonstration, the target system encrypts an image using keys generated by the chaotic system. A new response system using auto-synchronization method is suggested. It tries to decrypt the encrypted image without knowing the secret key. Experimental results prove that it is possible to estimate secret key generated by the target system by only monitoring limited scalar time series from the chaotic RNG.

This paper presents the FPGA (Field Programmable Gate Array) implementation and the coupling analysis of a metastability-based random number generator (RNG). The metastability is acquired through exploiting transient effect ring oscillators (TEROs) and the random bit generation is accomplished through irregular sampling of regular waveform method. As the proposed RNG is made up of only digital logic gates, it is prototyped on a Xilinx ZedBoard Zynq-7000 evaluation platform. It is demonstrated that the RNG output bitstream satisfies NIST 800-22 statistical tests of randomness without any need for post-processing and the proposed RNG can provide high data throughput. Furthermore, the proposed RNG uses less number of components compared to previously reported TERO based RNGs, thus enabling lower power consumption and smaller footprint. Additionally, the proposed RNG is subjected to correlation based cryptanalysis study. In classical ring oscillator (RO) based RNGs, the ring oscillators are required to be placed at a distance from each other to avoid locking phenomenon that may occur due to coupling between adjacent ROs. This study demonstrates that unlike classical RO based RNGs, the proposed RNG is insensitive to locking phenomenon and TERO structures are not required to be placed way from each other. Therefore, the proposed method lead to a more compact RNG design compared to classical RO based RNGs.

This brief presents a random number generator (RNG) based on irregular sampling of regular waveform method where the irregular signal is obtained by combining Fibonacci-Galois ring oscillators with an XOR gate. The RNG is implemented on a FPGA (field-programmable gate array). The regular waveform generated by the digital clock manager of the FPGA, is sampled at times corresponding to certain number of rising edges of the irregular signal, and the resulting bit stream is subjected to statistical tests of randomness. It is demonstrated that the resulting bit sequence from the proposed RNG satisfies NIST 800-22 test suit and Rabbit and SmallCrush batteries from TestU01 library without any need for post-processing such as Von Neumann or XOR. A comparison between the methods regular sampling of irregular waveform and irregular sampling of regular waveform is given in terms of robustness against external interference. The impact of selection of Fibonacci-Galois polynomials is discussed. Using digital design flow for TSMC 65nm process, an asic implementation of the proposed RNG is given having 1115 gates and 4.811 mW estimated power.

A new response system is suggested to show the security vulnerabilities of an FPGA-based chaotic “true” random number generator (RNG). The auto-synchronization method is used to justify the success of the response system. The hidden parameter of the chaotic RNG is revealed when the design of the RNG is open to everyone and a limited scalar time series can be monitored from the chaotic RNG. Experimental results prove the applicability of the response system in a way of estimating next bit while the same bit stream of the RNG can be reproduced.

There has been an unfortunate increase in gastronomy-related diseases especially due to today's urban living style with less physical activity and unhealthy nutrition. Obesity and diabetes have become climbing threats to human life more than ever before. Besides, combating with diabetes and obesity leads serious economic bottlenecks. Aligned with such a socio-economic state-of-play, technology-enhanced solutions are coming to forward. However, there is still a big need to develop holistic solutions considering the entire food value chain where food and health stakeholders meet in consensus. This paper presents an innovative reflection of this holistic approach with specific interest on two aspects: (1) Combat with diabetes and (2) Food, but especially dessert, design and production processes; considering patient's or eater's preferences and health constraints cordially for better personalized medicine and nutrition. The proposed case study presents an integrated solution that is composed of a combined food, diabetes and dessert design ontology for more comprehensive and structured data analysis, IoT-enabled diabetes monitoring, VR-enabled dessert design and production for better cognitive enjoyment and participative virtual market for diversified access to food stakeholders.

Building Information Modelling (BIM) is set to revolutionize not only the planning and construction of buildings, but the entire process of urban planning and facilitation. This paper addresses the effective use of BIM in urban context based on the Geographical Information Systems (GIS) for training, planning and utilizing crisis management activities. The proposed solution integrates the domain ontologies associated with BIM and GIS at building and urban level to filter the useful data and use that filtered data to increase the public awareness for better crisis and disaster preparedness by interactive gaming. The proposed proof of concept study presents an IoT-enabled Virtual Reality (VR) environment that relies on the visual data obtained from the BIM and GIS and also sensory inputs accumulated from the building or urban layout. Such visual layouts of buildings and their surrounding areas are presented in a layered format, considering the security and privacy concerns, to identify the safe and dangerous zones on the evacuation route starting from a person's private residential area, e.g. home, and ends at a crisis gathering point (e.g. Points of Interest, PoI). The use case presented in this study simulates an earthquake and fire scenario in a VR environment.

Use of cybernetic technologies in data-driven surgery simulation is a trendy topic. Although there exist promising studies in virtual simulation of surgery operations there exist relatively little effort in plastic surgery domain. This paper aims to present a data-driven interactive virtual reality simulation environment that is built on a novel surgical operational context taxonomy. The proposed taxonomy is used to develop a data model covering pre-surgery, peri-surgery, and post-surgery operations enabling effective monitoring of the surgery steps. The data model helps users to filter the useful data about surgery steps and health data. Such a data-driven filtering mechanism will also assist the training of surgeon candidates to get more prepared for real-life surgery operations. The suggested solution also enables health data flow over an IoT backbone which augments the ambient-assisted reality of the surgery operation environment.

A novel predicting system is proposed to find out the security weaknesses of a chaotic random number generator (RNG). Convergence of the predicting system is proved using auto-synchronization. Secret parameter of the target chaotic RNG is revealed where the public information are the design of the chaotic RNG and a scalar time series observed from the target chaotic system. Simulation and numerical results verifying the feasibility of the predicting system are given such that, next bit can be predicted while the same output bit sequence of the chaotic RNG can be regenerated.

With the recent advancements in industry 4.0 new concepts like “Digital Twin” has been rising also for the gastronomy sector. Gastronomic processes like cooking, serving, presenting, and preparing food have evolved with the new trends utilizing Internet of Things (IoT), Augmented Reality (AR) and Virtual Reality (VR). This paper presents an innovative concept of digital cloning of gastronomic devices, named as eGastronomic things, to monitor their functions and simulate their operations. Here, eGastronomic things have both real physical appearances and their digital counterparts presenting them as a living 3D model augmented with its real incorporating data. Such live data can be any sensory or instant data observed while the device is working, or any catalogue data, like the model name and the owner information, stored in a database. In order to prove the concept, a case study where the digital twin of an industrial ice cream machine (as an example of an eGastronomic thing) is presented. The ice cream machine and its 3D digital twin can be visualized in a 3D virtual environment which enables interaction through AR or VR. The digital twin of the machine is secured with an electronic IoT gateway embedded in the machine and incorporated with a data acquisition board. Thus, the device is protected against unauthenticated use by realizing a secure access control mechanism.

The new Industry 4.0 era has opened a new gateway having the capacity to be applied in gastronomy sector in order to provide clever solutions to its critical challenges or emerging needs like: Energy consumption; Process optimization; Healthy and personalized nutrition; and Effective maintenance and refinement of entire portfolio of gastronomic services. The proposed food technology, which is mainly based on so-called magnetic induction, is enabled as an embedded solution. The holistic solution, namely ERINOKS, has an Internet-of-Things (IoT) background enabling distributed and connected food processes, adaptive power control according to the amount of food (by weight control) and a recommendation system for effective nutrition of individuals or group of people having special preferences. ERINOKS supports statistical methods like bootstrapping to analyze the parameters affecting the food processes and energy efficiency. Such a statistical analysis can be used to model the food consumption rates according to age, gender, origin, daily or seasonal factors and individual preferences or health status. ERINOKS utilizes a virtual assistant simulating food preparation steps or just for sharing information about ingredients for the use of cookers and consumers, i.e. selecting or cooking the healthiest food.

The food industry has been growing with the tremendous improvements in information technologies. The way of accessing foods has become diversified with innovative technologies based on new generation semantic frameworks and interaction technologies. The proposed web-based platform, namely KEBAP, is based on a semantic framework modeled by a food and food stakeholder combined ontology. The platform is presented by a case study that utilizes an innovative interaction facility based on Virtual Reality (VR). The online platform encounters gastronomic, cultural, personal, and nutritional factors affecting personal preferences, eaters' health status and regarding stakeholders in gastronomy sector. The proposed platform enables online promotion of food, conscious consumption and ordering of food over Internet, semantic filtering of food data and effective presentation and simulation of food and its environment with VR. The presented platform is designed by considering big data requirements that makes the proposed solution scalable to larger beverage and appetite data.

With the recent advancements in blockchain technology, it has become obvious that this technology is not just for crypto-currencies but instead can be used as a decentralized tool for better accountability. Blockchain has the capacity to transform the industries disruptively as it presents new features like smart contracts, tokenization of content, eliminating counterfeit products, supply chain improvement, digital twins, and end-to-end security. This paper presents a blockchain-based model for distributed and collaborative digital twin environments which is becoming indispensable in new “Any 4.0” era. The proposed model includes a public or private authority in the digital twin ecosystem providing non-repudiation of blockchain transactions, holistic security and privacy preservation. The proposed technique is based on the “X-by-design” and “X-as-a-service” principles which can be discussed as a novel model for better security, accountability and integrity in decentralized mechanisms. In order to elucidate, two case studies are described where the digital twin operations, stakeholders' activities and regarding transactions are stored on a blockchain.

This article describes vulnerability analysis of a chaos-based random number generator (RNG). An attack system has been proposed to reveal the security weaknesses of the chaosbased RNG. The master-slave synchronization is used to prove the convergence of the attack system. Future evaluation of the RNG output is derived where only the observable information is the structure of the RNG and a scalar time series obtained from the chaotic oscillator. Feasibility of the attack system is confirmed by simulation and numerical results. It has been verified that deterministic chaos can not be the true source of randomness.

A non-autonomous cross-coupled chaotic circuit is presented with its derivation mechanism. To guarantee robust chaotic behavior of the circuit against parameter variations, an ideal set of parameters is determined by constructing bifurcation diagrams. A truly random number generator (TRNG), which relies on generating non-invertible binary sequences according to regional distributions of underlying chaotic signal, is also introduced. Simulation and experimental results verifying the feasibility of the circuit are given. The proposed TRNG offers much higher and constant throughput rates, allows for offset compensation and fulfills the NIST-800-22 statistical test suite without further post-processing.

There is an increasing demand for fully digital, high speed Random Number Generators because of their speed compatibility and uncomplicated integration to digital platforms. To the best of our knowledge, this paper presents the first ASIC implementation of Random Number Generator based on ring oscillators. Prototypes have been designed and fabricated by using HHNEC's 0.25 /xm eFlash process with a supply voltage of 2.5V. The circuit occupies 0.043 mm2and dissipates minimum 0.011 W of power. IC design level experiences, measurements, analyses of measurements and statistical test results are also demonstrated. Instead of resilient function which decreases the throughput, we propose to use only a simple Von Neumann corrector, thus 4 times faster throughput can be obtained in comparison with the previous design in which resilient function is employed. We achieved fullfilled test results from NIST 800-22 test suit after Von Neuman corrector with 16.5 Mbps throughput which is the highest data rate to date with fullfiled test results. The results were repeatable numerous times.

A novel random number generator (RNG) based on an autonomous continuous-time chaotic oscillator is presented. In the proposed RNG, dual oscillator architecture is used with the chaotic oscillator in order to increase the throughput and to maximize the statistical quality of the output sequence. Mathematical model of the proposed design has been developed, and it has been numerically verified that the generated bit streams passed the four basic tests of FIPS-140-2 test suite. Finally, we have also verified that the bit streams, obtained from the hardware realization of the circuit in the same way, passed the full NIST-800-22 test suite without post processing. Simulation and experimental results, verifying the feasibility of the circuit, are given. The proposed RNG can be realized in integrated circuit.