Device Fingerprinting with Magnetic Induction Signals Radiated by CPU Modules

With the widespread use of smart devices, device authentication has received much attention. One popular method for device authentication is to utilize internally measured device fingerprints, such as device ID, software or hardware-based characteristics. In this article, we propose DeMiCPU , a stimulation-response-based device fingerprinting technique that relies on externally measured information, i.e., magnetic induction (MI) signals emitted from the CPU module that consists of the CPU chip and its affiliated power-supply circuits. The key insight of DeMiCPU is that hardware discrepancies essentially exist among CPU modules and thus the corresponding MI signals make promising device fingerprints, which are difficult to be modified or mimicked. We design a stimulation and a discrepancy extraction scheme and evaluate them with 90 mobile devices, including 70 laptops (among which 30 are of totally identical CPU and operating system) and 20 smartphones. The results show that DeMiCPU can achieve 99.7% precision and recall on average, and 99.8% precision and recall for the 30 identical devices, with a fingerprinting time of 0.6~s. The performance can be further improved to 99.9% with multi-round fingerprinting. In addition, we implement a prototype of DeMiCPU docker, which can effectively reduce the requirement of test points and enlarge the fingerprinting area.

Wireless Underground Sensor Network for Monitoring Various Fields Using Magnetic Induction

The frequent accidents of mining safety caused severe losses and massive cost losses. The global mining sector urgently needs to improve operational efficiency and the overall safety of mines. This article suggests a WUSN based mining safety monitoring. The monitoring system collects temperature, moisture, soil vibration and gas values around the mine, and then transmits the data through wireless underground sensor network. Here Transmission based on magnetic induction (MI) is being suggested, in this approach soil is medium for communication so based on the soil conductivity the measured information are transferred. It is also an early warning system, which will help all miners in the mine to save their lives before a victim happens.

Real-time database of the subsystem of monitoring the process of growing vegetable products in the greenhouse

When choosing systems for automatic control of the microclimate of the greenhouse should take into account the requirements that affect the process itself. In the process of growing different crops in the greenhouse, it is necessary to maintain the temperature and humidity according to the technology for the comfortable development of the plant, which will further affect the quality of the crop. An important factor is the fixation of all measured values for further processing of the results, and in paper and mostly unstructured form it is not so convenient to do. That is why information control systems provide constant fixation of measured values and maintain indicators that will be comfortable for a particular variety grown in the greenhouse. The aim of the study is to create software for an automated subsystem for monitoring technological parameters, which will allow in real time to obtain indicators of the microclimate of the greenhouse. To effectively manage the parameters of greenhouse cultivation and rapid processing of measured data, it is proposed to improve automated software management systems for creating databases. An automated subsystem for monitoring technological parameters has been developed, which allows to obtain real-time indicators of the greenhouse microclimate, control their values, process them statistically and demonstrate them to the staff. An application for reading and outputting measured information from the Arduino hardware platform has also been created. Key words: human-machine interface, monitoring, air temperature, microclimate, greenhouse

Holographic optical field recovery using a regularized untrained deep decoder network

Image reconstruction using minimal measured information has been a long-standing open problem in many computational imaging approaches, in particular in-line holography. Many solutions are devised based on compressive sensing (CS) techniques with handcrafted image priors or supervised deep neural networks (DNN). However, the limited performance of CS methods due to lack of information about the image priors and the requirement of an enormous amount of per-sample-type training resources for DNNs has posed new challenges over the primary problem. In this study, we propose a single-shot lensless in-line holographic reconstruction method using an untrained deep neural network which is incorporated with a physical image formation algorithm. We demonstrate that by modifying a deep decoder network with simple regularizers, a Gabor hologram can be inversely reconstructed via a minimization process that is constrained by a deep image prior. The outcoming model allows to accurately recover the phase and amplitude images without any training dataset, excess measurements, or specific assumptions about the object’s or the measurement’s characteristics.

Development of Algorithms for Identifying Parameters of the Maritime Vessel Motion Model in Operating Conditions with Elements of Intellectual Analysis

The article examines the synthesis of algorithms for the estimation of the random parameters of ship movement models, based on measured information in field tests. In addition, accuracy analysis of the synthesized algorithms is provided. The derived algorithms are relatively simple and allow highly precise unknown parameters for estimation of ship motion models at the non-real-time scale to be obtained using the measurements recorded in field tests. The results can be used in the construction of automated ship control systems, or in the development of navigation simulators and the creation of ship models.

Holographic Optical Field Recovery Using a Regularized Untrained Deep Decoder Network

Image reconstruction using minimal measured information has been a long-standing open problem in many computational imaging approaches, in particular in-line holography. Many solutions are devised based on compressive sensing (CS) techniques with handcrafted image priors or supervised Deep Neural Networks (DNN). However, the limited performance of CS methods due to lack of information about the image priors and the requirement of an enormous amount of per-sample-type training resources for DNNs has posed new challenges over the primary problem. In this study, we propose a single-shot lensless in-line holographic reconstruction method using an untrained deep neural network which is incorporated with a physical image formation algorithm. We demonstrate that by modifying a deep decoder network with simple regularizers, a Gabor hologram can be inversely reconstructed via a minimization process that is constrained by a deep image prior. The outcoming model allows to accurately recover the phase and amplitude images without any training dataset, excess measurements, or specific assumptions about the object’s or the measurement’s characteristics.

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The spectra of absorption, luminescence, and lifetime of Yb3+ in SO2Cl2 – GaCl3 – Yb3+ solutions were measured. Information is obtained on the Stark splitting of energy levels, absorption and stimulated emission cross sections of Yb3+. An analysis of the spectral dependence of the gain cross sections indicates that the SOCl2 – GaCl3 – Yb3 solution is promising as the active medium of a diode-pumped liquid ytterbium laser.

The Association of Objective and Subjective Vision Impairment With Self-Reported Time Spent in Sedentary Behaviors in Low- and Middle-Income Countries

Background: There is a scarcity of studies on the relationship between visual impairment (VI) and time spent in sedentary behavior (SB), especially from low- and middle-income countries (LMICs). Thus, we investigated the association of objectively and subjectively measured VI with SB in adults aged ≥18 years across 6 LMICs. Methods: Cross-sectional data from the WHO Study on global AGEing and adult health (SAGE) were analyzed. Objective and subjective visual acuity were measured. Information on self-reported SB was also collected. Multivariable multinomial logistic regression analysis was conducted to assess associations with time spent in SB as the outcome. Results: The sample consisted of 42,489 individuals (mean age = 43.8 [14.4] y; 50.1% females). Only severe objective VI (vs no VI) was significantly associated with ≥11 hours per day of SB (vs <4 h/d) (odds ratio = 4.50; 95% confidence interval, 1.57–12.92). Increasing severity of subjective VI was associated with greater odds for ≥8 hours per day of SB (vs <4 h/d) dose dependently. Conclusions: The present study identified an association of both objectively and subjectively measured VI with time spent in SB in adults residing in LMICs, with subjectively measured VI being a stronger predictor of time spent in SB. Targeted interventions to decrease SB especially in those who perceive themselves to have VI are needed in LMICs.

The Integrated Statistical Control Method of Technical Condition of Radio-Electronic Equipment for Prototyping of Robotic Systems

In the article, the approach of integrated statistical control and diagnostics of the radio-electronic equipment, which is based on the analysis, integration of the measuring information arriving from the thermal imager, magnetic field sensors, tension and humidity of air and also statistical control of equipment parameters, is presented. The solution of a control and diagnostics problem is based on monitoring of changes in the average level of a multi-parameter process. Here, Hotelling control charts, integration and processing of the measured information are used to provide the analysis and decision-making on the influence of the operator. The algorithm implements a technique of integrated statistical control of the technical condition of the radio-electronic equipment and is capable to determine the level of its precritical condition. The proposed technique increases the reliability of the identification of technical conditions of radio-electronic equipment and expands the scope of technical means of control and diagnostics.