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In forensic document analysis, the authenticity of a document must be properly checked in the context of suspected forgery. Hyperspectral Imaging (HSI) is a non-invasive way of detecting fraudulent papers in a multipage document. The occurrence of a forged paper in a multi-page document may have a substantial difference from rest of the papers in its age, type, color, texture, and so on. Each pixel in an HSI data can be used as the material fingerprint for the spatial point it corresponds to. Hence, hyperspectral data of paper samples made of the same substance have similar characteristics and can be grouped into a single cluster. Similarly, paper samples made of different substances have different spectral properties. This paper relies on this heuristic and proposes a tensor based clustering framework for hyperspectral paper data, with an application to detect the forged papers in multi-page documents. Information embedded in the hyperspectral patches of the papers to be clustered is arranged into individual lateral slices of a third-order tensor in this framework. Further, this work employs the self-expressiveness property of submodules and an objective function is formulated to extract self-expressive representation tensor with low multirank and f-diagonal structure. Objective function of the proposed method incorporates $l_{\frac {1}{2}}$ -induced Tensor Nuclear Norm (TNN) and $l_{\frac {1}{2}}$ regularization to impart better low rankness and f-diagonal structure to the representation tensor. Experimental results of the proposed method were compared to the state-of-the-art subspace clustering approaches. The results demonstrate improved performance of the proposed method over the existing clustering algorithms.

Mineral oil has traditionally been used as a cooling fluid in power transformers, but its low biodegradability and low fire point have motivated the search of alternatives. In this work, six different dielectric fluids have been studied, including four vegetable liquids, from sunflower, rapeseed, soybean, and palm, one synthetic ester and a mineral oil used for comparison. These oils were subjected to an accelerated thermal ageing in glass vessels at 150°C for four weeks (672 hours) in presence of Kraft insulating paper. Different oils parameters were measured during the ageing, i.e. breakdown voltage, dielectric dissipation factor, permittivity, DC resistivity, density, kinematic viscosity, flash and fire points, interfacial tension, acidity, and dissolved gases; additionally, the degree of polymerisation (DP) of the paper was measured. Results showed that the changes of the natural esters properties, except for the palm oil, were similar along the ageing time. Palm oil results were similar to those of the mineral oil, whereas synthetic ester showed a behaviour similar to natural esters. The kraft paper degradation was higher in the mineral oil, followed by the synthetic ester and the palm oil. No significant differences were found in the ageing with the natural esters. This work was supported in part by the European Union’s Horizon 2020 Research and Innovation Program, through the Marie Sklodowska-Curie, under Grant 823969, and in part by the Ministry of Economy, through the National Research Project: Gestión del Ciclo de Vida de Transformadores Aislados con Fluidos Biodegradables, under Grant PID 2019-107126RBC22.

Temperature compensation occupies a significant function in the insulation condition evaluation of converter transformer bushings based on the Frequency Domain Spectroscopy (FDS), which could influence the accuracy of its insulation diagnosis. In order to accurately obtain the variation law of FDS at different temperature, a Resin Impregnated Paper (RIP) insulation bushing for converter transformer was designed by the equivalence of maximum electric field, coaxial cylinder structure and RIP materials. The increment law of dielectric parameters both dissipation factor and capacitance at wideband frequency (1mHz ~ 10kHz) was measured for a quality RIP insulation samples at the temperature from 30°C to 100°C. 1) Under the uniform temperature, it was found that the value of dissipation factor was rising with the frequency from 10 Hz to 0.001Hz, while the tendency was reversed at the frequency from 100Hz to10kHz. 2) The minimum value of tan $\delta $ from 0.001Hz to 10kHz could be driven to higher frequency moving (10Hz to 10kHz) by the action of temperature rising 30°C to 100°C.3) The effect of temperature on the lower frequency 0.001Hz ~ 1Hz tan $\delta $ of RIP insulation closely conformed to the index law of Arrhenius equation, while it was in accordance with the linear decrease at higher frequency 1kHz ~ 10kHz. The effect of temperature on dissipation factor could be eliminated by curve segment shifting based the experiment equation, which it at 0.001Hz dissipation factor could be eliminated by curve shifting based the index equation originated Arrhenius equation. The method is beneficial to eliminate the influence of temperature on the dielectric spectroscopy test results, and then to eliminate the influence of temperature on the dielectric spectroscopy diagnosis of RIP bushings.

The AlphaZero algorithm achieved superhuman levels of play in chess, shogi, and Go by learning without domain-specific knowledge except for game rules. This paper targets stochastic games and investigates whether AlphaZero can learn theoretical values and optimal play. Since the theoretical values of stochastic games are expected win rates, not a simple win, loss, or draw, it is worth investigating the ability of AlphaZero to approximate expected win rates of positions. This paper also thoroughly studies how AlphaZero is influenced by hyper-parameters and some implementation details. The analyses are mainly based on AlphaZero learning with lookup tables. Deep neural networks (DNNs) like the ones in the original AlphaZero are also experimented and compared. The tested stochastic games include reduced and stronglysolved variants of Chinese dark chess and EinStein würfelt nicht!. The experiments showed that AlphaZero could learn policies that play almost optimally against the optimal player and could learn values accurately. In more detail, such good results were achieved by different hyper-parameter settings in a wide range, though it was observed that games on larger scales tended to have a little narrower range of proper hyper-parameters. In addition, the results of learning with DNNs were similar to lookup tables.

Publisher Copyright: Author In this paper, a single source five-level boost inverter has been proposed and analyzed. The proposed structure includes a five-level inverter and a single-input multi-output (SIMO) boost converter. In this structure, the DC link voltage has been controlled by controlling the implemented DC-DC boost converter. In addition, the inverter switching pattern has been obtained based on the pick current control (PCC) method. In order to test and prove the performance of the proposed structure, this system is tested with the local grid. Since the active and reactive powers have been controlled based on the PCC method, the generated energy in a renewable energy source can be transferred to the local grid with a controlled and high-quality current. In this paper, the proposed structure has been introduced and its operation in different modes has been analyzed completely. Furthermore, the design considerations of the required elements have been investigated. Also, the power loss analysis and the comparison results of the proposed converter with other similar structures have been presented. Finally, in order to test the practical performance of the proposed structure and prove the theoretical analysis, a 620 W laboratory prototype of this structure has been assembled and its performance with the local grid has been tested.

This paper presents an efficient control allocation (CA) strategy which significantly improves the flight performance of a planar hexacopter. This allocation maps the desired control vector composed of the thrust and torques in roll, pitch, and yaw axis, respectively, to propellers' speed. This paper shows that a CA strategy based on the classical approach of pseudo-inverse matrix only exploits a limited range of the vehicle capabilities to generate thrust and moments. A novel approach is presented, which is based on a weighted pseudo-inverse matrix method, called WCA, capable of exploiting a much larger domain in the control vector. The three weights involved in WCA are adapted online according to nonlinear laws which are analytically derived by solving symbolically the equivalent constraint least-squares problem, thus removing the need for online-optimization calculations. This solution allows for very fast real-time operations, suitable for autopilots with limited computing resources. This paper provides 1) a detailed analysis of the limitations of the classical control allocation scheme, 2) the mathematical development of the WCA algorithm, 3) simulations and real experiments which show that this WCA strategy outperforms the classical CA approach in terms of a) capability to generate the maximum roll and pitch torques possible, without generating undesired yaw torques, b) prioritizing the generation of thrust over attitude torques, thus achieving better altitude tracking despite aggressive maneuvers or the presence of a payload, and c) better behavior in case of actuator saturation, faults or even failures., IEEE Access, 11, ISSN:2169-3536

In recent years, deep learning (DL) models have demonstrated remarkable achievements on non-trivial tasks such as speech recognition and natural language understanding. One of the significant contributors to its success is the proliferation of end devices that acted as a catalyst to provide data for data-hungry DL models. However, computing DL training and inference is the main challenge. Usually, central cloud servers are used for the computation, but it opens up other significant challenges, such as high latency, increased communication costs, and privacy concerns. To mitigate these drawbacks, considerable efforts have been made to push the processing of DL models to edge servers. Moreover, the confluence point of DL and edge has given rise to edge intelligence (EI). This survey paper focuses primarily on the fifth level of EI, called all in-edge level, where DL training and inference (deployment) are performed solely by edge servers. All in-edge is suitable when the end devices have low computing resources, e.g., Internet-of-Things, and other requirements such as latency and communication cost are important in mission-critical applications, e.g., health care. Firstly, this paper presents all in-edge computing architectures, including centralized, decentralized, and distributed. Secondly, this paper presents enabling technologies, such as model parallelism and split learning, which facilitate DL training and deployment at edge servers. Thirdly, model adaptation techniques based on model compression and conditional computation are described because the standard cloud-based DL deployment cannot be directly applied to all in-edge due to its limited computational resources. Fourthly, this paper discusses eleven key performance metrics to evaluate the performance of DL at all in-edge efficiently. Finally, several open research challenges in the area of all in-edge are presented., 21 pages

Steer-by-wire systems represent a key technology for highly automated and autonomous driving. In this context, robust steering control is a fundamental precondition for automated vehicle lateral control. However, there is a need for improvement due to degrees of freedom, signal delays, and nonlinear characteristics of the plant which are unconsidered in the design models for the design of current steering controls. To be able to design an extremely robust steering control, suitable optimal models of a steer-by-wire system are required. Therefore, this paper presents an innovative nonlinear detail model of a steer-by-wire system. The detail model represents all characteristics of a real steer-by-wire system. In the context of a dominance analysis of the detail model, all dominant characteristics of a steer-by-wire system, including parameter dependencies, are identified. Through model reduction, a reduced model of the steer-by-wire system is then developed that can be used for a subsequent robust control design. Furthermore, this paper compares the steer-by-wire system with a conventional electromechanical power steering and shows similarities as well as differences.

With the development of Information and Communication Technologies, trust has been applied more and more in various scenarios. At the same time, different organizations have published a series of trust frameworks to support the implementation of trust. There are also academic paper discussing about these trust standards, however, most of them only focus on a specific application. Unlike existing works, this paper provides an overview of all current available trust standards related to communication networks and future digital world from several main organizations. To be specific, this paper summarizes and organizes all these trust standards into three layers: trust foundation, trust elements, and trust applications. We then analysis these trust standards and discuss their contribution in a systematic way. We discuss the motivations behind each current in forced standards, analyzes their frameworks and solutions, and presents their role and impact on communication works and future digital world. Finally, we give our suggestions on the trust work that needs to be standardized in future., 7 pages, 3 figures, Magazine paper under review

This paper investigates facilitating remote collection of a patient’s data in distributed system while protecting the security of the data, preserving the privacy of the patient’s ID, and preventing inference attack. The paper presents a novel framework called SPID stand for a Secure, ID Privacy, and Inference Threat Prevention Mechanisms for Distributed Systems. In designing this framework, we make the following novel contributions. The SPID presents a novel architecture that supports the use of a distributed set of servers owned by different service providers. The SPID allows the patient to access these servers using certificates generated by the patient. The SPID allows the patient to select one server to be the home server, and select a number of servers to be the foreign servers. The patient uses the foreign servers to upload data. The home server is responsible for collecting the patient’s data from the foreign servers and sending them to the healthcare provider. The SPID proposes a method for efficient verification of each request from the patient without searching in the server’s database for the verification key. This is done by using some of the Elliptic Curves Cryptography (ECC) properties. The SPID has been analyzed using a bench-marking tool and evaluated using queuing theory. The evaluation results indicate an efficient performance when the number of servers increases. We uses Shannon entropy method to measure the likelihood of the inference attack.

Non-linearity of wireless transceivers, specifically power amplifier (PA) non-linearity, could pose major limitations towards having high throughput, and cost and energy efficient wireless communication systems. Such limitations from the PA is typically compensated in the transmitter, e.g. by applying power back-off or performing digital-pre-distortion (DPD) aiming to linearize the transmitter. However, applying PA power back-off leads to lower energy efficiency, and lower output power, and hence lower coverage; and performing DPD results in higher complexity of the transmitters. This paper presents an alternative approach based on a receiver method to perform signal detection in the presence of distortions due to PA non-linearity. We propose a receiver technique using artificial neural networks (ANN) to compensate for the PA non-linearity at the receiver side. The paper presents link-level simulation results using pre-trained neural network models based on synthesized training data. The simulation results confirm that the designed receiver can tolerate higher distortions, hence allow the PA output power back-off to be reduced, leading to higher output power improving coverage, spectral efficiency, energy efficiency, and throughput.

This paper presents a comprehensive study of radio channels related to capsule endoscopy communications in ultra wideband wireless body area networks (UWB-WBAN) utilizing multiple antenna systems. The research includes 363 channel realizations, obtained through simulations using an anatomically realistic human voxel model and a capsule model. A capsule position is modelled in such a way that it moves throughout the entire intestinal tract. The study examines the frequency and time domain characteristics of the channels in various capsule locations, including the most challenging positions deep inside the tissues or far away from most of the antennas. Additionally, the propagation characteristics inside the abdominal tissue are studied by calculating the most obvious propagation paths based on power flow illustrations and reflecting the results with the channel impulse response analysis. The impact of capsule rotation is also studied. It is shown how small changes in capsule location can greatly impact on the channel characteristics if the thickness of the tissues between the capsule and the on-body antenna changes significantly. The paper concludes with statistical analysis of the channel data, including path loss and root mean square (RMS) delay spread. The results provide valuable insight into how the signal propagates inside different parts of the gastrointestinal tract. They show that channel attenuation remains moderate along most of the gastrointestinal tract, and that even the deepest locations in the small intestine area can be resolved with the use of directional on-body antennas and receivers with higher sensitivity.

Publisher Copyright: Author This paper focuses on the design aspects of the key components for a scalable phased-array system over the 200 GHz frequency range. A high-gain phase shifter chain for 220 to 240 GHz frequency range and a high-gain power amplifier (PA) with a high output power are designed in a 0.13-μm SiGe BiCMOS technology. The phase shifter chain includes a low-noise amplifier (LNA), a vector modulator phase shifter (PS), and a gain-enhancing amplifier. The LNA is a five-stage cascode design. The vector modulator core is realized by two variable gain amplifiers based on the Gilbert cell architecture. A four-stage cascode design is used for the gain-enhancing amplifier. The phase shifter chain shows a measured gain of 18 dB at 230 GHz with a 360° phase tuning range and more than 10 dB of gain control. The chip achieves a minimum measured noise figure of 11.5 dB at 230 GHz and shows a wideband noise characteristic. The complete phase shifter chain chip consumes a dc power of 153 mW and occupies a 1.41 mm2 area.A high-power PA that is critical for a large phased-array system is designed. This paper presents a unique 4-way power combining technique utilizing a differential quadrature coupler. The realized balanced PA occupies an area of 0.67 mm2 and shows a measured peak gain of 21 dB at 244 GHz. The PA consumes 819 mW of dc power and delivers a maximum saturated output power (Psat) of 7.1 dBm at 244 GHz and more than 4.3 dBm of Psat from 230 to 255 GHz.

In the process of digital image acquisition, color inconsistency is a common issue due to the influence of photographic conditions. The inconsistency of color affects the quality of digital orthophoto products and subsequent applications significantly, and this issue remains challenging both in the academia and industry. This paper proposes a color equalization method for aerial image based on block adjustment and an improved color balance model based on the analysis of causes for color deviation. Two nonlinear functions are used to simulate the process of color deviation and correct the color of images. Due to the existence of error, the color corrected images still have minor deviations in the color of the overlapped regions. Therefore, this research introduces an error equation to address this issue and uses the least square principle to calculate the adjustment. The simulation experiments and real experiments are carried out on several groups of aerial image data respectively. The results show that the method not only achieves better visual effect but also has a higher adjustment precision. Finally, the rationality and parameters of the model proposed in this paper are discussed.

The sharing of data is becoming increasingly important for the process and manufacturing industries that are using data-driven models and advanced analysis to assess production performance and make predictions, e.g., on wear and tear. In such environments, access to data needs to be accurately controlled to prevent leakage to unauthorized users while providing easy to manage policies. Data should further be shared with users outside trusted domains using encryption. Finally, means for revoking access to data are needed. This paper provides a survey on attribute-based approaches for access control to data, focusing on policy management and enforcement. We aim to identify key properties provided by attribute-based access control (ABAC) and attribute-based encryption (ABE) that can be combined and used to meet the abovementioned needs.We describe such possible combinations in the context of a proposed architecture for secure data sharing. The paper concludes by identifying knowledge gaps to provide direction to future research on attribute-based approaches for secure data sharing in industrial contexts. Validerad;2023;Nivå 2;2023-02-13 (hanlid);Funder: Arrowhead Tools Research Project (826452)

Koopman operator theory has proven to be a promising approach to nonlinear system identification and global linearization. For nearly a century, there had been no efficient means of calculating the Koopman operator for applied engineering purposes. The introduction of a recent computationally efficient method in the context of fluid dynamics, which is based on the system dynamics decomposition to a set of normal modes in descending order, has overcome this long-lasting computational obstacle. The purely data-driven nature of Koopman operators holds the promise of capturing unknown and complex dynamics for reduced-order model generation and system identification, through which the rich machinery of linear control techniques can be utilized. Given the ongoing development of this research area and the many existing open problems in the fields of smart mobility and vehicle engineering, a survey of techniques and open challenges of applying Koopman operator theory to this vibrant area is warranted. This review focuses on the various solutions of the Koopman operator which have emerged in recent years, particularly those focusing on mobility applications, ranging from characterization and component-level control operations to vehicle performance and fleet management. Moreover, this comprehensive review of over 100 research papers highlights the breadth of ways Koopman operator theory has been applied to various vehicular applications with a detailed categorization of the applied Koopman operator-based algorithm type. Furthermore, this review paper discusses theoretical aspects of Koopman operator theory that have been largely neglected by the smart mobility and vehicle engineering community and yet have large potential for contributing to solving open problems in these areas., Following a fruitful discussion with Professor Igor Mezic, the authors are providing a more detailed account of the roots of the modern-day engineering applications of the Koopman Operator Theory in this arXiv version

Interior permanent magnetic synchronous motors (IPMSMs) adopting concentrated windings have been widely used in industrial applications. To reduce operating costs, it is an important issue to enhance the efficiency of an IPMSM as much as possible while maintaining manufacturing costs. In general, an IPMSM used for an industrial application always operates in a specific operating area according to the required load. Therefore, this paper has two purposes. The first purpose is to propose a novel rotor structure which can enhance efficiency at the target wide-speed middle-torque operating area without additional manufacturing costs. The second purpose is to clarify the design method for a suitable rotor structure depending on its target operating area. Reducing losses is the key to enhancing efficiency. This paper first examines the effects of adopting large flux barriers and a disproportional airgap on copper and iron losses, and clarifies their merits and respective high-efficiency operating areas. Furthermore, to take advantage of the two rotor structures, a novel rotor structure which employs both large flux barriers and a disproportional airgap has been proposed. 2D-FEM (Finite-Element Method) is used for discussion first, and a prototype machine is manufactured to verify the 2D-FEM results. Both 2D-FEM and experimental results show that the proposed rotor structure can enhance the efficiency of an IPMSM most effectively at the target operating area. Moreover, for a low-speed high-torque operating area, adopting only large flux barriers is most suitable. And for a high-speed low-torque operating area, adopting only a disproportional airgap is most suitable.

As autonomous platforms become more advanced, it is useful to obtain more information about the environment. Classic vision sensors such as RGB-D cameras, LiDAR, or acoustical imaging cameras are capable of accurately displaying the location of an object in 3D space and are widely used for this purpose. However, a problem arises when the measurement environment becomes more complex and measurement data might begin to suffer in terms of accuracy. Imaging sonar sensors are developed specifically for these environments but are limited in terms of frame rate due to the inherent slow nature of sound. This paper will propose a method to increase the amount of useful information obtained from the available data from a single measurement in post-processing. Utilizing a signal in combination with a Doppler velocity-tuned matched-filter bank it is possible to estimate the radial velocity of an object with respect to the sensor’s location. This allows the robot to make better decisions when it comes to path planning and collision avoidance, as a rapidly approaching object requires a different action than a stationary object or one moving away from the sensor. Another advantage of this system is that a single seemingly-large object might be identified as two close lying objects with different speeds. This paper serves as a proof-of-concept with results from a realistic simulation environment using an imaging sonar sensor and shows that the proposed method is perfectly suitable for making accurate estimations of an object’s radial velocity.

The tremendous development of the Internet of Things (IoT) technology in the last decades has fostered advancement in automatic medical assistive devices to support the existing Electronic Health Record (EHR) system. As an integral part of the EHR electronic model, public cloud servers store medical data. Unfortunately, public cloud servers are prone to security and privacy breach. This paper introduces a novel non-cryptographic approach to preserve electrocardiograph (ECG) data confidentiality and integrity in the EHR environment. The main objective of the proposed anonymization algorithm is to obscure the patient’s cardiac information during transmission and to protect information stored in the cloud database. Although we focus on ECG data, generalization to other types of clinical data can be derived using the proposed method. Performance evaluation of the proposed scheme showed that the algorithm conceals both fiducial and non-fiducial features of the data. Therefore, confidentiality feature is preserved. This paper examined confidentiality of the anonymized data using the Percentage Residual Difference (PRD) and investigated the integrity of the reconstructed data in terms of cross-correlation. Security analysis carried out using the PRD, brute force attack, and performance comparison between the proposed algorithm and existing methods. Evaluation showed that the proposed scheme offers a secure non-cryptographic model for transmission and storing clinical data in the cloud. Moreover, in terms of processing time, the proposed algorithm is ten times faster than the existing wavelet packet method when processing long ECG data, 65,536 sample points. In a real-time experimental testbed, the implemented proposed system was successful.

International audience; This paper develops an original design method of high-pass (HP) negative group delay (NGD) integrated circuit (IC). The considered HP-NGD IC is based on a passive topology which is essentially composed of resistor-inductor (RL) network. The paper presents the first time that an unfamiliar HPtopology is designed in miniaturized circuit implemented in 130-nm CMOS technology. The theory of unfamiliar HP-NGD topology based on the voltage transfer function (VTF) analysis is elaborated. The design equations with synthesis formulas of the resistor and inductor are established. The HP-NGD IC CMOS design methodology is introduced. The feasibility of the miniature NGD IC implementation is approved by design rule check (DRC) and layout versus schematic (LVS) approaches. The HP-NGD passive IC is designed in 130-nm CMOS technology. The HP-NGD topology is constituted by RL-network based on CMOS high Ohmic unsalicided N + poly resistor and symmetrical high current spiral inductor. Then, the schematic and layout simulations are presented. The validity of the 130-nm CMOS HP-NGD design is verified by the investigation of 225 µm × 215 µm chip two different miniature circuit proofs-of-concept (POC). The HP-NGD behavior is validated by comparison between the calculated, and schematic and post-layout simulations of the HP-NGD POCs carried out by a commercial tool. As expected, the group delay and VTF magnitude diagrams are in very good correlation. HP-NGD optimal value, NGD cutoff frequency and attenuation, of about (−31 ps, 141 MHz, −3 dB) and (−47 ps, 204 MHz, −5 dB) are obtained from the miniature POCs. INDEX TERMS 130-nm CMOS technology, design method, negative group delay (NGD), high-pass (HP) NGD function, HP-NGD theory, integrated circuit (IC) design, synthesis equation, RL-network passive topology, miniature circuit.

Software code is present on multiple levels within current Internet of Things (IoT) systems. The quality of this code impacts system reliability, safety, maintainability, and other quality aspects. In this paper, we provide a comprehensive overview of code quality-related metrics, specifically revised for the context of IoT systems. These metrics are divided into main code quality categories: Size, redundancy, complexity, coupling, unit test coverage and effectiveness, cohesion, code readability, security, and code heterogeneity. The metrics are then linked to selected general quality characteristics from the ISO/IEC 25010:2011 standard by their possible impact on the quality and reliability of an IoT system, the principal layer of the system, the code levels and the main phases of the project to which they are relevant. This analysis is followed by a discussion of code smells and their relation to the presented metrics. The overview presented in the paper is the result of a thorough analysis and discussion of the author’s team with the involvement of external subject-matter experts in which a defined decision algorithm was followed. The primary result of the paper is an overview of the metrics accompanied by applicability notes related to the quality characteristics, the system layer, the level of the code, and the phase of the IoT project.