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A fully integrated sensor microsystem for blue/ultraviolet radiation detection is presented. The photosensitive part combines a blue/UV selective stripe‐shaped photodiode with a small compensation infrared photodiode. A transimpedance amplifier with 1 GΩ feedback resistor is integrated on the same silicon chip. The main features of the op amp are a low offset (<0.5mV) and fail‐safe operation. This sensor has a maximal responsivity of 150 mV/nW at λ = 420 nm, corresponding to 43 percent quantum efficiency. A ratio of the responsivities at 420 nm and 1 μm as large as 560 is achieved. The system has a noise equivalent power of 5 10^‐13 W. The 2.2 mm² microsystem is realized in a standard CMOS 0.5 μm process.

The results showed that the use of a magnetic marker could relatively accurately reflect the fracture pattern inside the rock-like material (RLM).

This study investigated the internal structure and fracture pattern of a fractured RLM. Magnetized iron oxide powder, which was used as a magnetic marker, was mixed with water and glue to form a magnetic slurry, which was subsequently injected into a fractured RLM. After the magnetic slurry completely filled the cracks inside the RLM and became cemented, the distribution and magnitude of the magnetic field inside the RLM were determined using a three-dimensional (3D) magnetic field imaging system.

A model for determining the magnetic field strength was developed using MATLAB.

This model of 3D magnetic will further be used as a finite element tool to simulate and image cracks inside the rock.

As a type of angular displacement sensor, the Hall-effect magnetic encoder incorporates many advantages. While compared with the photoelectric encoder, the magnetic encoder nevertheless has lower precision and lower resolution. So, the purpose of this essay is to find a way to increase the precision and resolution of the magnetic encoder.

By combining a single-pole magnetic encoder and a multi-pole AlNiCo magnet, the precision and resolution of this combined magnetic encoder are increased without increasing its volume or complicating its structure. A special algorithm system is developed to ensure faithful encoding and decoding.

Tests show that the combined magnetic encoder, with a diameter of 67.12 mm (including shaft) and thickness of 6.9 mm, has a precision of ±6′, compared with a 15-bit photoelectric encoder and a static resolution of ±0.6′.

This new kind of magnetic encoder could be used in specialized fields which need high-precision servo-control systems that are small, have ultra-low-speed and high-speed ratios and are non-oil-polluting or shock-resistant.

The purpose of this paper is to present gait analysis for five different terrains: level ground, ramp ascent, ramp descent, stair ascent and stair descent.

Gait analysis has been carried out using a combination of the following sensors: force-sensitive resistor (FSR) sensors fabricated in foot insole to sense foot pressure, a gyroscopic sensor to detect the angular velocity of the shank and MyoWare electromyographic muscle sensors to detect muscle’s activities. All these sensors were integrated around the Arduino nano controller board for signal acquisition and conditioning purposes. In the present scheme, the muscle activities were obtained from the tibialis anterior and medial gastrocnemius muscles using electromyography (EMG) electrodes, and the acquired EMG signals were correlated with the simultaneously attained signals from the FSR and gyroscope sensors. The nRF24L01+ transceivers were used to transfer the acquired data wirelessly to the computer for further analysis. For the acquisition of sensor data, a Python-based graphical user interface has been designed to analyze and display the processed data. In the present paper, the authors got motivated to design and develop a reliable real-time gait phase detection technique that can be used later in designing a control scheme for the powered ankle-foot prosthesis.

The effectiveness of the gait phase detection was obtained in an open environment. Both off-line and real-time gait events and gait phase detections were accomplished for the FSR and gyroscopic sensors. Both sensors showed their usefulness for detecting the gait events in real-time, i.e. within 10 ms. The heuristic rules and a zero-crossing based-algorithm for the shank angular rate correctly identified all the gait events for the locomotion in all five terrains.

This study leads to an understanding of human gait analysis for different types of terrains. A real-time standalone system has been designed and realized, which may find application in the design and development of ankle-foot prosthesis having real-time control feature for the above five terrains.

The noise-free data from three sensors were collected in the same time frame from both legs using a wireless sensor network between two transmitters and a single receiver. Unlike the data collection using a treadmill in a laboratory environment, this setup is useful for gait analysis in an open environment for different terrains.

The purpose of this paper is to present a magnetic contactless displacement sensor with liftoff compensation. The sensor consists of two‐axis Hall sensor, moving permanent magnet (PM) and ferromagnetic substrate which is considered as a magnetic flux concentrator.

The two Hall‐effect sensors are used to detect the B_X and B_Y induced by the moving PM. The B_X and B_Y curves reflect the nature of the liftoff and the displacement of the inducing PM, respectively. Then the model of the displacement sensor, based on the facing current method, is constructed. Finally, the finite element method is used to compute the characteristics of B_X and B_Y.

The B_Y curve can be corrected according to the liftoff distance of Hall‐effect sensor distinguished by the B_X trough value. Therefore, the influence of the liftoff on the output signal can be eliminated when B_Y curve is corrected.

The paper focused on the design of a contactless displacement sensor with compensated liftoff performance for the control measurement technology in general and for automotive engineering in particular.

The new developments in silicon Hall sensors are highlighted. First, basic components made by microelectronic technology are explained. They lead to the development of high accuracy vectorial magnetic probes. Then examples of new applications like angular position sensor and current measurements are illustrated. Finally, new concepts in order to increase the detectivity using magnetic chopping are demonstrated.

In November 2022, the commercial company, OpenAI, launched ChatGPT. Since then, university students have rapidly become regular users of this artificial intelligence (AI) platform. One reason for this is the powerful capability of this generative AI tool to produce textual content, which in many cases, is almost indistinguishable from human-generated content. Another reason is that ChatGPT easily gives anyone access to knowledge. However, there is a problem as the vast majority of its users have no idea how this AI platform works and thus overlook the importance of thinking critically about information communicated in ChatGPT. While some call for banning this generative AI tool, this study aims to provide evidence that science classrooms can become scenarios where students find explicit, concrete, and realistic opportunities to critically evaluate scientific information generated by ChatGPT.

An intervention study was conducted with 55 students (26 females and 29 males, 17–24 years old) during a university Spanish-English bilingual science course taught within an active learning environment. The data consist of the written critiques of the students about Spanish-English bilingual scientific texts produced by ChatGPT.

Results indicate that the intervention had a positive effect on students’ abilities to construct sound arguments in Spanish and in English while judging the quality of scientific texts produced by this AI bot. Moreover, the findings suggest that the intervention enriched students’ skills to make improvements to texts produced by this generative AI tool.

The evidence provided in this study contributes to the exploration of possibilities to help students become critical users of ChatGPT.

Existing deterministic models that predict the capacity of corroded reinforced concrete (RC) beams have limited applicability because they were based on accelerated tests that induce general corrosion. This research gap was addressed by performing a combined numerical and statistical analysis on RC beams, subjected to natural corrosion, to achieve a much better forecast.

Data of 42 naturally corroded beams were collected from the literature and analyzed numerically. Four constitutive models and their combinations were considered: the elastic-semi-plastic and elastic-perfectly-plastic models for steel, and two tensile models for concrete with and without the post-cracking stresses. Meanwhile, Popovics’ model was used to describe the behavior of concrete under compression. Corrosion coefficients were developed as functions of corrosion degree and beam parameters through linear regression analysis to fit the theoretical moment capacities with test data. The performance of the coefficients derived from different combinations of constitutive laws was then compared and validated.

The results showed that the highest accuracy (R² = 0.90) was achieved when the tensile response of concrete was modeled without the residual stresses after cracking and the steel was analyzed as an elastic-perfectly-plastic material. The proposed procedure and regression model also showed reasonable agreement with experimental data, even performing better than the current models derived from accelerated tests and traditional procedures.

This study presents a simple but reliable approach for quantifying the capacity of RC beams under more realistic conditions than previously reported. This method is simple and requires only a few variables to be employed. Civil engineers can use it to obtain a quick and rough estimate of the structural condition of corroding RC beams.

The study deals with key questions of Serbia’s economic development, including the regularities of transforming self-managed socialism to a standard capitalist system. It is based on the concept of endogenous growth and the general theory of market transition. In the empirical part of investigation, the main directions of economic development and transition in Serbia are analysed. Crucial issues of economic policy are also considered with a particular emphasis on the latest phase of transition. Concerning the problems of economic efficiency, an attempt is made to quantify the various types of technical progress and determine their contribution to its overall rate. The macroeconomic role of external factors is quantitatively shown through a globalisation effect related to inflows of FDI. The author believes that the Serbian economy, despite all its problems and difficulties, in principle has the potential necessary for finding adequate answers to the challenges of ‘neo-transition’. Of these challenges, he regards as most serious Serbia’s ability to comply with the standards of accession to the European Union, which, among others, requires closer regional cooperation.

The purpose of this paper is to provide a better understanding of the determinants of business intelligence system (BIS) adoption stages. It develops and empirically tests a conceptual model for assessing the determinants of BIS diffusion on the evaluation, adoption, and use stages in the context of small and medium enterprises (SMEs).

Drawing on data from 181 SMEs the influence of technological, organizational, and environmental factors on BIS adoption stages were analyzed using the PLS-SEM method.

The paper provides empirical insights about how technological, organizational, and environmental factors affect individual BIS adoption stages.

The paper includes implications for managers and solution providers to understand the influence of various determinants to more effectively conclude the adoption process.

This study represents important progress in the theoretical understanding of the role of technological, organizational, and environmental factors across the different BIS adoption stages.