Hybrid pixel radiation detectors with a direct photon-to-charge conversion working in a single photon counting mode have gained increasing attention due to their high dynamic range and noiseless imaging. Since sensors of different materials can be attached to readout electronics, they enable work with a wide range of photon energies. The charge-sharing effect observed in segmented devices, such as hybrid pixel detectors, is a phenomenon that deteriorates both spatial resolution and detection efficiency. Algorithms that allow the detection of a photon irrespective of the charge-sharing effect are proposed to overcome these limitations. However, the spatial resolution of the detector can be further improved beyond the resolution determined by the pixel size if information about the charge proportions collected by neighbouring pixels is used to approximate the interaction position. In the article, an approach to achieve a subpixel resolution in a hybrid pixel detector working in the single photon counting mode is described. Requirements and limitations of digital inter-pixel algorithms which can be implemented on-chip are studied. In the simulations, the factors influencing the detector resolution are evaluated, including size of a charge cloud, number of virtual pixel subdivisions, and detector parameters.
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Fano resonance is an optical effect that emerges from the coherent coupling and interference (constructive and destructive) between the continuous state (background process) and the Lorentzian state (resonant process) in the plasmonic waveguide-resonator system. This effect has been used in the applications like optical sensors. These sensors are extensively used in sensing biochemicals and gases by the measurement of refractive index changes as they offer high sensitivity and ultra-high figure of merit. Herein, we surveyed several plasmonic Fano sensors with different geometries composed of metal-insulator-metal waveguide(s). First, the resonators are categorized based on different architectures. The materials and methods adopted for these designs are precisely surveyed and presented. The performances are compared depending upon the characterization parameters like sensitivity and figure of merit. Finally, based on the survey of very recent models, the advances and challenges of refractive index sensing deployed on Fano resonances are discussed.
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This research paper discusses an analytical approach to designing the active region of light emitting diodes to enhance its performance. The layers in the active region were modified and the effects of changing the width of quantum well and barrier layers in a multi-quantum light emitting diode on the output power and efficiency have been investigated. Also, the ratio of the quantum well width to the B layer width was calculated and proposed in this research paper. The study is carried out on two different LED structures. In the first case, the width of the quantum well layers is kept constant while the width of the B layers is varied. In the second case, both the quantum well and B layer widths are varied. Based on the simulation results, it has been observed that the LED power efficiency increases considerably for a given quantum well to B layers width ratio without increasing the production complexity. It is also seen that for a desired power efficiency the width of quantum well should be between 0.003 µm and 0.006 µm, and the range of B width (height) should be 2.2 to 6 times the quantum well width. The proposed study is carried out on the GaN-AlGaN-based multi-quantum well LED structure, but this study can be extended to multiple combinations of the semiconductor structures.
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In this paper, the effect of an indoor visible light communication channel is studied. Moreover, the analysis of the received power distribution of the photodiode in the line of sight and the first reflection of the channel without line of sight with several parameters is simulated. Two different waveforms are explained in detail. Orthogonal frequency division multiplexing has been widely adopted in radio frequency and optical communication systems. One of the most important disadvantages of the orthogonal frequency division multiplexing signal is the high peak-to-average power ratio. Therefore, it is important to minimize the peak-to-average power ratio in the visible light communication systems more than in radio-frequency wireless applications. In the visible light communication systems, the high peak-to-average power ratio produces a high DC bias which reduces power efficiency of the system. A discrete Fourier transform spread orthogonal frequency division multiplexing is proposed to be used in wireless communication systems; its ability to minimize peak-to-average power ratio has been tested. The analysis of two different subcarrier allocation methods for the discrete Fourier transform-spread subcarriers, as well as the examination of two distinct subcarrier allocation strategies, distributed and localized mapping, are investigated and studied. The effects of an accurate new sub-band mapping for the localized discrete Fourier transform spread orthogonal frequency division multiplexing scheme are presented in this paper. The light-fidelity system performance of the orthogonal frequency division multiplexing and discrete Fourier transform spread orthogonal frequency division multiplexing with different sub-mapping techniques are simulated with Matlab™. A system performance size of bit error rate and peak-to-average power ratio are obtained, as well.
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In perovskite solar cells, series of symmetrical and asymmetrical imino-naphthalimides were tested as hole-transporting materials. The compounds exhibited high thermal stability at the temperature of the beginning of thermal decomposition above 300 °C. Obtained imino-naphthalimides were electrochemically active and their adequate energy levels confirm the application possibility in the perovskite solar cells. Imino-naphthalimides were absorbed with the maximum wavelength in the range from 331 nm to 411 nm and emitted light from the blue spectral region in a chloroform solution. The presented materials were tested in the perovskite solar cells devices with a construction of FTO/b-TiO2/m-TiO2/perovskite/ HTM/Au. For comparison, the reference perovskite cells were also performed (without hole-transporting materials layer). Of all the proposed materials tested as hole-transporting materials, the bis-(imino-naphthalimide) containing in core the triphenylamine structure showed a power conversion efficiency at 1.10% with a short-circuit current at 1.86 mA and an open-circuit voltage at 581 mV.
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The technology of manufacturing silicon solar cells is complex and consists of several stages. The final steps in succession are the deposition of antireflection layer and discharge contacts. Metallic contacts are usually deposited by the screen printing method and then, fired at high temperature. Therefore, this article presents the results of a research on the effect of heat treatment on the properties of the Al2O3 thin film previously deposited by the atomic layer deposition method. It works well as both passivating and antireflection coating. Moreover, heat treatment affects the value of the cell short-circuit current and, thus, its efficiency. The surface morphology, optical and electrical properties were investigated, describing the influence of heat treatment on the properties of the deposited layers and the manufactured solar cells.
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Scientific and Didactic Laboratory of Nanotechnology and Material Technologies, Faculty of Mechanical Engineering, Silesian University of Technology, 7 Towarowa St., 44-100 Gliwice, Poland
Department of Engineering Materials and Biomaterials, Faculty of Mechanical Engineering, Silesian University of Technology, 18a Konarskiego St., 44-100 Gliwice, Poland
The research and analysis of the bactericidal properties of the spacer knitted fabric with the UV-C system are presented in this paper. The disintegration factor affecting the bacteria in the knitted fabric is the UV-C radiation in the range of 265–270 nm distributed via woven optical fibres. The way of integrating elements of the system generating the UV-C radiation in the structure of the spacer knitted fabric was designed, as well as various configurations of optical fibres arrangement, fibre density, number of radiation sources, and diode types were tested. The material was contaminated with selected microorganisms indicative of sanitary contamination and important in terms of nosocomial infections. The scope of the research included microbiological (quantitative and qualitative) analyses of selected taxonomic groups of microorganisms (mesophilic bacteria, fungi, actinomycetes) before and after the irradiation process. The analysis of the research results and the applied modification of the knitted fabric turned out to be effective in reducing the amount of potentially pathogenic microorganisms.
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Advances in photonic technologies, with new processes and scopes of photonic integrated circuits, have generated a lot of interest as the field allows to obtain sensors with reduced size and cost and build systems with high interconnectivity and information density. In this work, answering the needs of photonic sensors that must be portable, more energy-efficient, and more accurate than their electrical counterparts, also with a view to the emerging field of neuromorphic photonics, a versatile device is presented. The proposed device makes use of the well-known advantages provided by optical bistability. By combining two distributed feedback-multi quantum well semiconductor laser structures, this new optical multiple inputs - digital output device offers various essential purposes (such as logic gates, wavelength detector and monitoring) with no need for specific manufacturing for each of them. Through a commercial computer-aided design tool, VPIphotonics™, the necessary characterization of proposed device is also described.
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The present review is mainly focused on the extended analysis of the results obtained from coupled measurement techniques of a thermal imaging camera and chronoamperometry for imines in undoped and doped states. This coupled technique allows to identify the current-voltage characteristics of thin films based on imine, as well as to assess layer defects in thermal images. Additional analysis of results provides further information regarding sample parameters, such as resistance, conductivity, thermal resistance, and Joule power heat correlated with increasing temperature. As can be concluded from this review, it is possible not only to study material properties at the supramolecular level, but also to tune macroscopic properties of -conjugated systems. A detailed study of the structure-thermoelectrical properties in a series of eight unsymmetrical and symmetrical imines for the field of optoelectronics and photovoltaics has been undertaken. Apart from this molecular engineering, the imines properties were also tuned by supramolecular engineering via protonation with camphorsulfonic acid and by creation of bulk-heterojunction compositions based on poly(4,8-bis[(2-ethylhexyl)oxy]benzo[1,2-b:4,5-b′]dithiophene-2,6-diyl-alt-3-fluoro-2-[(2-ethylhexyl)carbonyl]thieno[3,4-b]thiophene-4,6-diyl) and/or [6,6]-phenyl-C71-butyric acid methyl ester, poly(3,4-ethylenedioxythiophene) towards the analysed donor or acceptor ability of imines in the active layer. The use of coupled measurement techniques of a thermal imaging camera and chronoamperometry allows obtaining comprehensive data on thermoelectric properties and defects indicating possible molecule rearrangement within the layer.
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A compact temperature measuring device using a weakly coupled multi-core fibre in the Michelson interferometer structure is proposed and experimentally demonstrated. The device is manufactured by an easy and simple splicing approach which consists of a multi-core fibre segment and an in-fibre coupler. In-fibre coupler is made of a cascaded single-mode fibre and multi-core fibre balls. It enhances the interference phenomenon of light energy between the central core and the outer cores of a multi-core fibre. The sensor shows a high quality fringe visibility of about 14–18 dB in the wavelength spectrum. Multi-core structure presents multi-path interferences and exhibits a maximum temperature sensitivity of 70.6 pm/°C in the range of 20–90°C with an insensitive response to the refractive index in the range of 1.334 to 1.354. The device has the advantages of compact size, easy manufacturing, and it solves cross-sensitivity between temperature and refractive index making it an authentic real-time temperature monitoring solution.
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High power fibre lasers need to be cooled efficiently to avoid their thermal damage. Temperature distribution in fibre should be estimated during the fibre laser design process. The steady-state heat equation in a cylindrical geometry is solved to derive a practical formula for temperature radial distribution in multi-layered optical fibres with arbitrary number of the layers. The heat source is located in one or more cylindrical domains. The validity of the analytical formula is tested by comparison with static heat transfer simulations of typical application examples including octagonal double clad fibre, air-clad fibre, fibre with nonuniform, microstructured core. The accuracy sufficient for practical use is reported even for cases with not exactly cylindrical domains.
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Department of Fiber Lasers and Nonlinear Optics, Institute of Photonics and Electronics, Czech Academy of Sciences, 1014/57 Chaberská St., 18251 Praha 8, Czech Republic
The paper analyses the operation of different types of electronic colour sensors based on the light spectrum analysis. The application goal was to detect the type of the airport lamp based on differences in colour components of the light emitted by luminaires with specific spectral characteristics. Recognition of airport lamps is based on the analysis of the light spectrum. Proposed solution allows for an automatic software selection of appropriate conversion factors and comparison with specific standards necessary for this type of measurements. Various types of sensors were discussed and the AS7262 sensor was examined in detail. The colour sensor and the light intensity sensor were used in the mobile control device for examining elevated airport lamps and in the measurement platform for quality testing of embedded airport lamps. Two additional aspects were investigated: 1) influence of an additional acrylic glass cover; 2) distance between airport lamps and the spectrum sensor.
European Aviation Safety Agency. Certification Specifications (CS) and Guideline Material (GM) for Aerodrome Design. Edition 3, Annex to Decision No. 2016/027/R of the EASA Executive Director. (2016).
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Division of Signal Processing and Electronic Systems, Institute of Automation and Robotics, Poznan University of Technology, 24 Jana Pawła II Ave., 60-965 Poznań, Poland
Object tracking based on Siamese networks has achieved great success in recent years, but increasingly advanced trackers are also becoming cumbersome, which will severely limit deployment on resource-constrained devices. To solve the above problems, we designed a network with the same or higher tracking performance as other lightweight models based on the SiamFC lightweight tracking model. At the same time, for the problems that the SiamFC tracking network is poor in processing similar semantic information, deformation, illumination change, and scale change, we propose a global attention module and different scale training and testing strategies to solve them. To verify the effectiveness of the proposed algorithm, this paper has done comparative experiments on the ILSVRC, OTB100, VOT2018 datasets. The experimental results show that the method proposed in this paper can significantly improve the performance of the benchmark algorithm.
Aiming at the problems of low accuracy, low efficiency and low stability of traditional methods and recent developments in advanced technology incite the industries to be in sync with modern technology. With respect to various available techniques, this paper designs a fuzzy comprehensive evaluation model of the manufacturing industry for transferring risk based on economic big-data analytics. The big-data analysis method is utilized to obtain the data source of fuzzy evaluation of the manufacturing industry to transfer risk using data as the basis of risk evaluation. Based on the risk factors, the proposed model establishes the risk index system of the manufacturing industry and uses the expert evaluation method to design the scoring method of the evaluation index system. To ensure the accuracy of the evaluation results, the manufacturing industry's fuzzy comprehensive model is established using the entropy weight method, and the expert evaluation results are modified accordingly. The experimental results show that the highest efficiency of the proposed method is 96%, the highest accuracy of the evaluation result is 75%. The evaluation result's stability is higher than the other existing methods, which fully verifies the effectiveness and can provide a reliable theoretical basis for enterprise risk evaluation research.
Quick development of computer techniques and increasing computational power allow for building high-fidelity models of various complex objects and processes using historical data. One of the processes of this kind is an air traffic, and there is a growing need for traffic mathematical models as air traffic is increasing and becoming more complex to manage. This study concerned the modelling of a part of the arrival process. The first part of the research was air separation modelling by using continuous probability distributions. Fisher Information Matrix was used for the best fit selection. The second part of the research consisted of applying regression models that best match the parameters of representative distributions. Over a dozen airports were analyzed in the study and that allowed to build a generalized model for aircraft air separation in function of traffic intensity. Results showed that building a generalized model which comprises traffic from various airports is possible. Moreover, aircraft air separation can be expressed by easy to use mathematical functions. Models of this kind can be used for various applications, e.g.: air separation management between aircraft, airports arrival capacity management, and higher-level air traffic simulation or optimization tasks.
High-speed switching capabilities of SiC MOSFET power modules allow building high power converters working with elevated switching frequencies offering high efficiencies and high power densities. As the switching processes get increasingly rapid, the parasitic capacitances and inductances appearing in SiC MOSFET power modules affect switching transients more and more significantly. Even relatively small parasitic capacitances can cause a significant capacitive current flow through the SiC MOSFET power module. As the capacitive current component in the drain current during the turn-off process is significant, a commonly used method of determining the switching power losses based on the product of instantaneous values of drain-source voltage and drain current may lead to a severe error. Another problem is that charged parasitic capacitances discharge through the MOSFET resistive channel during the turn-on process. As this happens in the internal structure, that current is not visible on the MOSFET terminals. Fast switching processes are challenging to measure accurately due to the imperfections of measurement probes, like their output signals delay mismatch. This paper describes various problems connected with the correct determination of switching power losses in high-speed SiC MOSFET power modules and proposes solutions to these problems. A method of achieving a correct time alignment of waveforms collected by voltage and current probes has been shown and verified experimentally. In order to estimate SiC MOSFET channel current during the fast turn-off process, a method based on the estimation of nonlinear parasitic capacitances current has also been proposed and verified experimentally
The iterative learning fault-tolerant control strategies with non-strict repetitive initial state disturbances are studied for the linear discrete networked control systems (NCSs) and the nonlinear discrete NCSs. In order to reduce the influence of the initial state disturbance in iteration, for the linear NCSs, considering the external disturbance and actuator failure, the iterative learning fault-tolerant control strategy with impulse function is proposed. For the nonlinear NCSs, the external disturbance, packet loss and actuator failure are considered, the iterative learning fault-tolerant control strategy with random Bernoulli sequence is provided. Finally, the proposed control strategies are used for simulation research for the linear NCSs and the nonlinear NCSs. The results show that both strategies can reduce the influence of the initial state disturbance on the tracking effect, which verifies the effectiveness of the given method.
In the era of smart manufacturing and Industry 4.0, the rapid development of modelling in production processes results in the implementation of new techniques, such as additive manufacturing (AM) technologies. However, large invest-ments in the devices in the field of AM technologies require prior analysis to identify the possibilities of improving the production process flow. This paper proposes a new approach to determine and optimize the production process flow with improvements made by the AM technologies through the application of the Petri net theory. The existing produc-tion process is specified by a Petri net model and optimized by AM technology. The modified version of the system is verified and validated by the set of analytic methods safeguarding against the formal errors, deadlocks, or unreachable states. The proposed idea is illustrated by an example of a real-life production process.
The aim of the article is to present an exemplary system for recording and analyzing quality costs and to demonstrate that it is helpful in planning and assessing the effectiveness of continuous improvement processes at the operational and strategic level. Various approaches to defining quality costs are described, followed by indicators for assessing effectiveness and tools to collect data on the values of individual groups of quality costs and compare them with financial indicators. The practical part presents a case study on the quality cost accounting system in a medical company and the possibility of using quality cost accounting to plan and evaluate continuous improvement processes and make managerial decisions.
The aim of our research is to gain understanding about material flow related information sharing in the circular economy value network in the form of industrial symbiosis. We need this understanding for facilitating new industrial symbiosis relationships and to support the optimization of operations. Circular economy has been promoted by politics and regulation by EU. In Finland, new circular economy strategy raises the facilitation of industrial symbiosis and data utilization as the key actions to improve sustainability and green growth. Companies stated that the practical problem is to get information on material availability. Digitalization is expected to boost material flows in circular economy by data, but what are the real challenges with circular material flows and what is the willingness of companies to develop co-operation? This paper seeks understanding on how Industry 4.0 is expected to improve the efficiency of waste or by-product flows and what are the expectations of companies. The research question is: How Industry 4.0 technologies and solutions can fix the gaps and discontinuities in the Industrial Symbiosis information flow? This research is conducted as a qualitative case study research with three cases, three types of material and eight companies. Interview data were collected in Finland between January and March 2021. Companies we interviewed mentioned use-cases for sensors and analytics to optimize the material flow but stated the investment cost compared to the value of information. To achieve sustainable circular material flows, the development needs to be done in the bigger picture, for the chain or network of actors, and the motivation and the added value must be found for each of them.
In digital revolution, the appropriate IT infrastructure, technological knowledge are essential for the success of companies, where the success of the digital transformation depends on digital maturity. The aim of the study is to define the digital maturity, theoretical foundation of the digital maturity model and present a framework for small and medium-sized enterprises (SMEs) understanding where they are in digitalisation (how advanced their digital resource system and digital approach) to respond faster and efficiently to environmental changes. The model construction is based on theory of dynamic capabilities, graduation models, and SMEs management challenges. The model is a dynamic model to support management in strategic, digital and organizational developments, which is divided into IT and organizational dimensions, including 6 components and 28 subcomponents. The ultimate goal of the study is to determine the component weights to create a neurofuzzy model.
Technological progress is the driving force behind industrial development. It is a multidimensional and multi-level phenomenon. In this article we focus on its three manifestations: information and communication technologies (ICT), Industry 4.0 and agile manufacturing. The aim of this article is to analyse the relationship between these constructs as they are undoubtedly interrelated. ICT plays a key role, but it is not a goal itself. They are a prerequisite for the implementation of Industry 4.0, but together with it they serve to achieve agility by the manufacturing system and, as a result, achieve a competitive advantage by companies operating in turbulent and unpredictable environment. The literature findings in this paper are part of a broader study conducted on the impact of ICT on agility of SMEs operating in India. Therefore, we include also subsections showing the level of this relationship in Indian SMEs.
Enterprise innovation is currently becoming a recognized factor of the competitiveness, survival, and development of companies in the market economy. Managers still need recommendations on ways of stimulating the growth of innovation in their companies. The objective of this paper is to identify the strategic factors of enterprise innovativeness in the area of technology, defined as the most important internal factors positively impacting the innovativeness of enterprises in a strategic perspective. Empirical studies were conducted using the Computer-Assisted Web Interview (CAWI) method on a purposive sample of N = 180 small and medium-sized innovative industrial processing enterprises in Poland. Data analysis was performed using Exploratory Factor Analysis within the Confirmatory Factor Analysis framework (E-CFA) and Structural Equation Modeling (SEM). Empirical research shows that the strategic factor of enterprise innovativeness in the area of technology is technological activity. A technologically active company should (1) possess a modern machinery stock, (2) conduct systematic technological audits, and (3) maintain close technical cooperation with the suppliers of raw materials, consumables, and intermediates. The implementation of the indicated recommendations by managers should lead to increased innovativeness of small and medium-sized industrial companies. The author recommends the use of the presented research procedure and data analysis methods in further studies.
The present paper describes a methodological framework developed to select a multi-label dataset transformation method in the context of supervised machine learning techniques. We explore the rectangular 2D strip-packing problem (2D-SPP), widely applied in industrial processes to cut sheet metals and paper rolls, where high-quality solutions can be found for more than one improvement heuristic, generating instances with multi-label behavior. To obtain single-label datasets, a total of five multi-label transformation methods are explored. 1000 instances were generated to represent different 2D-SPP variations found in real-world applications, labels for each instance represented by improvement heuristics were calculated, along with 19 predictors provided by problem characteristics. Finally, classification models were fitted to verify the accuracy of each multi-label transformation method. For the 2D-SPP, the single-label obtained using the exclusion method fit more accurate classification models compared to the other four multi-label transformation methods adopted.