Abstract — An effective emergency response to accidents with chemical, biological, radiological, nuclear, or explosive materials (CBRNE) that represent highly dynamic situations needs immediate actions within limited time, information and resources. The aim of the study is to provide the foundation for division of unsafe area into risk zones according to the impact of hazardous parameters (heat radiation, thermal dose, overpressure, chemical concentrations). A decision on the boundary values for three risk zones is based on the vulnerability analysis that covered a variety of accident scenarios containing the release of a toxic or flammable substance which either evaporates, ignites and/or explodes. Critical values are selected for the boundary definition of the Red, Orange and Yellow risk zones upon the examination of harmful effects that are likely to cause injuries of varying severity to people and different levels of damage to structures. The obtained results provide the basis for creating a comprehensive real-time risk map for a decision support at CBRNE operations.
The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE). Keywords—DoA estimation, adaptive antenna array, Deep Neural Network, LS-SVM optimization model, radial basis function, MSE.
A technique for reconstruction of on-chip high frequency signals is demonstrated. The majority of the on-chip reconstruction methods based on subsampling technique are applicable to synchronized systems. This paper demonstrates a jitter-based subsampling technique for non-intrusive reconstruction of on-chip high frequency signals in non-synchronized systems. The proposed technique is demonstrated on a custom designed IC in 180 nm technology. The on-chip sensors are used for acquisition of high frequency signals as a response to the transmission line pulses (TLP) applied to the IC. The presented technique is also used to investigate the influence of the TLP on the internal nodes of the IC.
Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios. Keywords—Hybrid MAC protocol, data integrity, lightweight encryption, Neighbor based key sharing, Sensor node data processing, Z-MAC.
: At present, heterostructures are used for fabrication of almost all types of optoelectronic devices. Our research focuses on the optoelectronic properties of InAs(Sb) solid solutions that are widely used in fabrication of light emitting diodes (LEDs) operating in middle wavelength infrared range (MWIR). This spectral range (2-6 μm) is relevant for laser diode spectroscopy of gases and molecules, for systems for the detection of explosive substances, medical applications, and for environmental monitoring. The fabrication of MWIR LEDs that operate efficiently at room temperature is mainly hindered by the predominance of non-radiative Auger recombination of charge carriers over the process of radiative recombination, which makes practical application of LEDs difficult. However, non-radiative recombination can be partly suppressed in quantum-well structures. In this regard, studies of such structures are quite topical. In this work, electroluminescence (EL) of LED heterostructures based on InAs(Sb) epitaxial films with the molar fraction of InSb ranging from 0 to 0.09 and multi quantum-well (MQW) structures was studied in the temperature range 4.2-300 K. The growth of the heterostructures was performed by metal-organic chemical vapour deposition on InAs substrates. On top of the active layer, a wide-bandgap InAsSb(Ga,P) barrier was formed. At low temperatures (4.2-100 K) stimulated emission was observed. As the temperature increased, the emission became spontaneous. The transition from stimulated emission to spontaneous one occurred at different temperatures for structures with different InSb contents in the active region. The temperature-dependent carrier lifetime, limited by radiative recombination and the most probable Auger processes (for the materials under consideration, CHHS and CHCC), were calculated within the framework of the Kane model. The effect of various recombination processes on the carrier lifetime was studied, and the dominant role of Auger processes was established. For MQW structures quantization energies for electrons, light and heavy holes were calculated. A characteristic feature of the experimental EL spectra of these structures was the presence of peaks with energy different from that of calculated optical transitions between the first quantization levels for electrons and heavy holes. The obtained results showed strong effect of the specific electronic structure of InAsSb on the energy and intensity of optical transitions in nanostructures based on this material. For the structure with MQWs in the active layer, a very weak temperature dependence of EL peak was observed at high temperatures (>150 K), which makes it attractive for fabricating temperature-resistant gas sensors operating in the middle-infrared range.
This paper presents a wireless energy harvesting device formed by a meandered printed dipole antenna, which is resonant in the frequency bands Global System for Mobile Communication (GSM), Long Term Evolution (LTE) and Instrumentation, Scientific and Medical (ISM) and a serial topology rectifier circuit. This rectifier circuit features a broadband, which provides a double-band rectenna. This has been optimized to provide high output voltage and efficiency for very low levels of input power, the rectenna has been built on the FR4 substrate.
