Search results for: passive optical networks (PONs)

Authors: Gulfam Haider, sana danish

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Convolutional Neural Networks (CNNs) have emerged as powerful tools for image classification, and the choice of optimizers profoundly affects their performance. The study of optimizers and their adaptations remains a topic of significant importance in machine learning research. While numerous studies have explored and advocated for various optimizers, the efficacy of these optimization techniques is still subject to scrutiny. This work aims to address the challenges surrounding the effectiveness of optimizers by conducting a comprehensive analysis and evaluation. The primary focus of this investigation lies in examining the performance of different optimizers when employed in conjunction with the popular activation function, Rectified Linear Unit (ReLU). By incorporating ReLU, known for its favorable properties in prior research, the aim is to bolster the effectiveness of the optimizers under scrutiny. Specifically, we evaluate the adjustment of these optimizers with both the original Softmax activation function and the modified ReLU activation function, carefully assessing their impact on overall performance. To achieve this, a series of experiments are conducted using a well-established benchmark dataset for image classification tasks, namely the Canadian Institute for Advanced Research dataset (CIFAR-10). The selected optimizers for investigation encompass a range of prominent algorithms, including Adam, Root Mean Squared Propagation (RMSprop), Adaptive Learning Rate Method (Adadelta), Adaptive Gradient Algorithm (Adagrad), and Stochastic Gradient Descent (SGD). The performance analysis encompasses a comprehensive evaluation of the classification accuracy, convergence speed, and robustness of the CNN models trained with each optimizer. Through rigorous experimentation and meticulous assessment, we discern the strengths and weaknesses of the different optimization techniques, providing valuable insights into their suitability for image classification tasks. By conducting this in-depth study, we contribute to the existing body of knowledge surrounding optimizers in CNNs, shedding light on their performance characteristics for image classification. The findings gleaned from this research serve to guide researchers and practitioners in making informed decisions when selecting optimizers and activation functions, thus advancing the state-of-the-art in the field of image classification with convolutional neural networks.

Keywords: deep neural network, optimizers, RMsprop, ReLU, stochastic gradient descent

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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Authors: Le Zhao, Alain Nogaret

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We have built universal Central Pattern Generator (CPG) hardware by interconnecting Hodgkin-Huxley neurons with reciprocally inhibitory synapses. We investigate the dynamics of neuron oscillations as a function of the time delay between current steps applied to individual neurons. We demonstrate stimulus dependent switching between spiking polyrhythms and map the phase portraits of the neuron oscillations to reveal the basins of attraction of the system. We experimentally study the dependence of the attraction basins on the network parameters: the neuron response time and the strength of inhibitory connections.

Keywords: central pattern generator, winnerless competition principle, artificial neural networks, synapses

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Authors: Aishrith Rao

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COVID 19 is a pandemic which has resulted in thousands of deaths around the world and a huge impact on the global economy. Testing is a huge issue as the test kits have limited availability and are expensive to manufacture. Using deep learning methods on radiology images in the detection of the coronavirus as these images contain information about the spread of the virus in the lungs is extremely economical and time-saving as it can be used in areas with a lack of testing facilities. This paper focuses on binary classification and multi-class classification of COVID 19 and other diseases such as pneumonia, tuberculosis, etc. Different deep learning methods such as VGG-19, COVID-Net, ResNET+ SVM, Deep CNN, DarkCovidnet, etc., have been used, and their accuracy has been compared using the Chest X-Ray dataset.

Keywords: deep learning, computer vision, radiology, COVID-19, ResNet, VGG-19, deep neural networks

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Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

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The paper is focused on the operational model for transport the single wagon consignments on railway network by using two different models of train formation. The paper gives an overview of possibilities of improving the quality of transport services. Paper deals with two models used in problematic of train formatting - time continuously and time discrete. By applying these models in practice, the transport company can guarantee a higher quality of service and expect increasing of transport performance. The models are also applicable into others transport networks. The models supplement a theoretical problem of train formation by new ways of looking to affecting the organization of wagon flows.

Keywords: train formation, wagon flows, marshalling yard, railway technology

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Authors: Kais Manai

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The main part of this work focuses on the study of pion/muon separation at low energy using a nuclear Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The work consists of two parts: particle reconstruction algorithm and a Neural Network that assigns to each reconstructed particle the probability to be a muon or a pion. The pion/muon separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data. The algorithm allows to achieve a 60% muon identification efficiency with a pion misidentification smaller than 3%.

Keywords: nuclear emulsion, particle identification, tracking, neural network

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Authors: Reyhan Özdoğan, Özgür Ceylan, Mehmet Arif Kaya, Mithat Çelebi

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Food packaging is important for the food industry. Bioplastics have been used as food packaging materials. According to the European Bioplastics organization, bioplastics can be defined as plastics based on renewable resources (bio-based) or as plastics which are biodegradable and/or compostable. Poly(lactic acid) (PLA) has an industrially importance of bioplastic polymers. PLA is a family of biodegradable thermoplastic polyester made from renewable resources. It is produced by conversion of corn, or other carbohydrate sources, into dextrose, followed by fermentation into lactic acid through direct polycondensation of lactic acid monomers or through ring-opening polymerization of lactide. The processing possibilities of this transparent material are very wide, ranging from injection molding and extrusion over cast film extrusion to blow molding and thermoforming. In this study, PLA films were prepared by solution casting method. PLAs which are different molecular weights were plasticized with glycerol and the morphology of films was monitored by optical microscopy. Properties of mechanical and film of PLA were researched with the mechanical testing machine.

Keywords: biodegradable, bioplastics, morphology, solution casting, poly(lactic acid)

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Authors: Filimonova Alexanra

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Inviscid incompressible fluid flows are considered. The object of the study is a vortex parquet – a structure consisting of distributed vortex spots of different directions, occupying the entire plane. The main attention is paid to the study of advection processes of passive particles in the corresponding velocity field. The dynamics of the vortex structures is considered in a rectangular region under the assumption that periodic boundary conditions are imposed on the stream function. Numerical algorithms are based on the solution of the initial-boundary value problem for nonstationary Euler equations in terms of vorticity and stream function. For this, the spectral-vortex meshless method is used. It is based on the approximation of the stream function by the Fourier series cut and the approximation of the vorticity field by the least-squares method from its values in marker particles. A vortex configuration, consisting of four vortex patches is investigated. Results of a numerical study of the dynamics and interaction of the structure are presented. The influence of the patch radius and the relative position of positively and negatively directed patches on the processes of interaction and mixing is studied. The obtained results correspond to the following possible scenarios: the initial configuration does not change over time; the initial configuration forms a new structure, which is maintained for longer times; the initial configuration returns to its initial state after a certain period of time. The processes of mass transfer of vorticity by liquid particles on a plane were calculated and analyzed. The results of a numerical analysis of the particles dynamics and trajectories on the entire plane and the field of local Lyapunov exponents are presented.

Keywords: ideal fluid, meshless methods, vortex structures in liquids, vortex parquet.

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Authors: Rakesh Kumar, Shashi Janeoo, Ankit Dhiman, Siddharth Chopra

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Arynes are versatile reactive intermediates that offer broad opportunities in green organic synthesis. Arynes are potential aryl group surrogates for the transition metal-free environment friendly arylation reactions. Regioselective arylations of quinolines were achieved by the reactions of quinoline N-oxides with aryne intermediates generated in situ from the Kobayashi precursors. Various 2-substituted quinolines provided 3-arylated-2-substituted quinolines under ambient conditions. Acridine N-oxides also reacted well and provided unusual 4-arylacridines. Various fluorine containing 2,3-diarylquinaolines prepared using this approach were evaluated for antibacterial activity and two compounds inhibited the drug-resistant strains of S-aureus with a good selectivity index. Further, the 2,3-diarylquinolines as the potential optoelectronic materials were prepared by the aryne chemistry approach and their optical and electronic properties for such applications are under study. The aryne intermediates provide an effective Green Chemistry tool to achieve versatile arylated heteroarenes for diverse applications.

Keywords: arynes, arylation, quinolines, acridines.

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Authors: Parul Johri, Mala Trivedi

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Major Intrinsic proteins (MIPs), actively involved in the passive transport of small polar molecules across the membranes of almost all living organisms. MIPs that specifically transport water molecules are named aquaporins (AQPs). The permeability of membranes is actively controlled by the regulation of the amount of different MIPs present but also in some cases by phosphorylation and dephosphorylation of the channel. Based on sequence similarity, MIPs have been classified into many categories. All of the proteins are made up of the 20 amino acids, the only difference is there in their orientations. Again all the 20 amino acids are made up of the basic five elements namely: carbon, hydrogen, oxygen, sulphur and nitrogen. These elements are responsible for giving the amino acids the properties of hydrophilicity/hydrophobicity which play an important role in protein interactions. The hydrophobic amino acids characteristically have greater number of carbon atoms as carbon is the main element which contributes to hydrophobic interactions in proteins. It is observed that the carbon level of proteins in different species is different. In the present work, we have taken a sample set of 150 aquaporins proteins from Uniprot database and a dynamic programming code was written to calculate the carbon percentage for each sequence. This carbon percentage was further used to barcode the aqauporins of animals and plants. The protein taken from Oryza sativa, Zea mays and Arabidopsis thaliana preferred to have carbon percentage of 31.8 to 35, whereas on the other hand sequences taken from Mus musculus, Saccharomyces cerevisiae, Homo sapiens, Bos Taurus, and Rattus norvegicus preferred to have carbon percentage of 31 to 33.7. This clearly demarks the carbon range in the aquaporin proteins from plant and animal origin. Hence the atom level analysis of protein sequences can provide us with better results as compared to the residue level comparison.

Keywords: aquaporins, carbon, dynamic prgramming, MIPs

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Authors: C. Jameke

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During the cognitivist era in cognitive psychology, a theory of internal rules and symbolic representations was posited as an account of human cognition. This type of cognitive architecture had its heyday during the 1970s and 80s, but it has now been largely abandoned in favour of subsymbolic architectures (e.g. connectionism), non-representational frameworks (e.g. dynamical systems theory), and statistical approaches such as Bayesian theory. In this presentation I describe this changing landscape of research, and comment on the increasing influence of neuroscience on cognitive psychology. I then briefly review a few recent developments in connectionism, and neurocomputation relevant to cognitive psychology, and critically discuss the assumption made by some researchers in these frameworks that higher-level aspects of human cognition are simply emergent properties of massively large distributed neural networks

Keywords: connectionism, emergentism, postocgnitivist, representations, subsymbolic archiitecture

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Authors: Renu Kumari, Jyotsna Dutta Majumdar

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In the present study, composite coating consisting of hydroxyapatite (HA) + 50 wt% TiO2 has been developed on Ti-6Al-4V substrate by plasma spray deposition technique. Followed by plasma spray deposition, detailed surface roughness and microstructural characterization were carried out by using optical profilometer and scanning electron microscopy (SEM), respectively. The composition and phase analysis were carried out by energy-dispersive X-ray spectroscopy analysis, and X-ray diffraction (XRD) technique, respectively. The bio-activity behavior of the uncoated and coated samples was also compared by dipping test in Hank’s solution. The average surface roughness of the coating was 10 µm (as compared to 0.5 µm of as-received Ti-6Al-4V substrate) with the presence of porosities. The microstructure of the coating was found to be continuous with the presence of solidified splats. A detailed XRD analysis shows phase transformation of TiO2 from anatase to rutile, decomposition of hydroxyapatite, and formation of CaTiO3 phase. Standard dipping test confirmed a faster kinetics of deposition of calcium phosphate in the coated HA+50% wt.% TiO2 surface as compared to the as-received substrate.

Keywords: titanium, plasma spraying, microstructure, bio-activity, TiO2, hydroxyapatite

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Authors: Ahmed S. Afifi, Ahmed Magdy

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Satellite monitoring is an essential tool to study, understand, and map large-scale environmental changes that affect humans, climate, and biodiversity. The Sentinel-1 Synthetic Aperture Radar (SAR) instrument provides a high collection of data in all-weather, short revisit time, and high spatial resolution that can be used effectively in flood management. Floods occur when an overflow of water submerges dry land that requires to be distinguished from flooded areas. In this study, we use global flood mapper (GFM), a new google earth engine application that allows users to quickly map floods using Sentinel-1 SAR. The GFM enables the users to adjust manually the flood map parameters, e.g., the threshold for Z-value for VV and VH bands and the elevation and slope mask threshold. The composite R:G:B image results by coupling the bands of Sentinel-1 (VH:VV:VH) reduces false classification to a large extent compared to using one separate band (e.g., VH polarization band). The flood mapping algorithm in the GFM and the Otsu thresholding are compared with Sentinel-2 optical data. And the results show that the GFM algorithm can overcome the misclassification of a flooded area in An Giang, Vietnam.

Keywords: SAR backscattering, Sentinel-1, flood mapping, disaster

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Authors: Shih-Hao Chen, Chi-Wai Chow

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Multiple-input and multiple-output (MIMO) scheme can extend the transmission capacity for the light-emitting-diode (LED) visible light communication (VLC) system. The MIMO VLC system using the popular mobile-phone camera as the optical receiver (Rx) to receive MIMO signal from n x n Red-Green-Blue (RGB) LED array is desirable. The key step of decoding the received RGB LED array signals is detecting the direction of received array signals. If the LED transmitter (Tx) is rotated, the signal may not be received correctly and cause an error in the received signal. In this work, we propose and demonstrate a novel hierarchical transmission scheme which can reduce the computation complexity of rotation detection in LED array VLC system. We use the n x n RGB LED array as the MIMO Tx. A novel two dimension Hadamard coding scheme is proposed and demonstrated. The detection correction rate is above 95% in the indoor usage distance. Experimental results confirm the feasibility of the proposed scheme.

Keywords: Visible Light Communication (VLC), Multiple-input and multiple-output (MIMO), Red-Green-Blue (RGB), Hadamard coding scheme

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Authors: Benallou Yassine, Amara Kadda, Bouazza Boubakar, Soudini Belabbes, Arbouche Omar, M. Zemouli

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The study of the pressure effect on the materials, their functionality and their properties is very important, insofar as it provides the opportunity to identify others applications such the optical properties in the alkaline earth chalcogenides, as like the SrS. Here we present the first-principles calculations which have been performed using the full potential linearized augmented plane wave method (FP-LAPW) within the Generalized Gradient Approximation developed by Perdew–Burke–Ernzerhor for solids (PBEsol). The calculated structural parameters like the lattice parameters, the bulk modulus B and their pressure derivative B' are in reasonable agreement with the available experimental and theoretical data. In addition, the elastic properties such as elastic constants (C11, C12, and C44), the shear modulus G, the Young modulus E, the Poisson’s ratio ν and the B/G ratio are also given. The treatments of exchange and correlation effects were done by the Tran-Blaha modified Becke-Johnson (TB-mBJ) potential for the electronic. The pressure effect on the electronic properties was visualized by calculating the variations of the gap as a function of pressure. The obtained results are compared to available experimental data and to other theoretical calculations

Keywords: SrS, GGA-PBEsol+TB-MBJ, density functional, Perdew–Burke–Ernzerhor, FP-LAPW, pressure effect

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Authors: Kalyani Kulkarni, Bharat Chaudhari

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This paper addresses the issue of resource allocation in the emerging cognitive technology. Focusing the quality of service (QoS) of primary users (PU), a novel method is proposed for the resource allocation of secondary users (SU). In this paper, we propose the unique utility function in the game theoretic model of Cognitive Radio which can be maximized to increase the capacity of the cognitive radio network (CRN) and to minimize the interference scenario. The utility function is formulated to cater the need of PUs by observing Signal to Noise ratio. The existence of Nash equilibrium is for the postulated game is established.

Keywords: cognitive networks, game theory, Nash equilibrium, resource allocation

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Authors: Vadim Kulikov

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The classical Stroop effect is the phenomenon that it takes more time to name the ink color of a printed word if the word denotes a conflicting color than if it denotes the same color. Over the last 80 years, there have been many variations of the experiment revealing various mechanisms behind semantic, attentional, behavioral and perceptual processing. The Stroop task is known to exhibit asymmetry. Reading the words out loud is hardly dependent on the ink color, but naming the ink color is significantly influenced by the incongruent words. This asymmetry is reversed, if instead of naming the color, one has to point at a corresponding color patch. Another debated aspects are the notions of automaticity and how much of the effect is due to semantic and how much due to response stage interference. Is automaticity a continuous or an all-or-none phenomenon? There are many models and theories in the literature tackling these questions which will be discussed in the presentation. None of them, however, seems to capture all the findings at once. A computational model is proposed which is based on the philosophical idea developed by the author that the mind operates as a collection of different information processing modalities such as different sensory and descriptive modalities, which produce emergent phenomena through mutual interaction and coherence. This is the framework theory where ‘framework’ attempts to generalize the concepts of modality, perspective and ‘point of view’. The architecture of this computational model consists of blocks of neurons, each block corresponding to one framework. In the simplest case there are four: visual color processing, text reading, speech production and attention selection modalities. In experiments where button pressing or pointing is required, a corresponding block is added. In the beginning, the weights of the neural connections are mostly set to zero. The network is trained using Hebbian learning to establish connections (corresponding to ‘coherence’ in framework theory) between these different modalities. The amount of data fed into the network is supposed to mimic the amount of practice a human encounters, in particular it is assumed that converting written text into spoken words is a more practiced skill than converting visually perceived colors to spoken color-names. After the training, the network performs the Stroop task. The RT’s are measured in a canonical way, as these are continuous time recurrent neural networks (CTRNN). The above-described aspects of the Stroop phenomenon along with many others are replicated. The model is similar to some existing connectionist models but as will be discussed in the presentation, has many advantages: it predicts more data, the architecture is simpler and biologically more plausible.

Keywords: connectionism, Hebbian learning, artificial neural networks, philosophy of mind, Stroop

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Authors: Sheam-Chyun Lin, Wei-Kai Chen, Hung-Cheng Yen, Yung-Jen Cheng, Yu-Cheng Chen

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Result from the constant dwindle in natural resources, the alternative way to reduce the costs in our daily life would be urgent to be found in the near future. As the ancient technique based on the theory of solar chimney since roman times, the double-skin façade are simply composed of two large glass panels in purpose of daylighting and also natural ventilation in the daytime. Double-skin façade is generally installed on the exterior side of buildings as function as the window, so there’s always a huge amount of passive solar energy the façade would receive to induce the airflow every sunny day. Therefore this article imposes a domestic double-skin window for residential usage and attempts to improve the volume flow rate inside the cavity between the panels by the frame geometry design, the installation of outlet guide plate and the solar energy collection system. Note that the numerical analyses are applied to investigate the characteristics of flow field, and the boundary conditions in the simulation are totally based on the practical experiment of the original prototype. Then we redesign the prototype from the knowledge of the numerical results and fluid dynamic theory, and later the experiments of modified prototype will be conducted to verify the simulation results. The velocities at the inlet of each case are increase by 5%, 45% and 15% from the experimental data, and also the numerical simulation results reported 20% improvement in volume flow rate both for the frame geometry design and installation of outlet guide plate.

Keywords: solar energy, double-skin façades, thermal buoyancy, fluid machinery

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Authors: Isam M. Arafa, Mazin Y. Shatnawi, Yaser A. Yousef, Batool Zaid Al-Momani

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The present work describes the preparation, characterization, and luminescence of a series of fluorenone (FL) based luminophores grafted onto modified cellulose microfibers. The FL is condensed onto cellulose aldehyde using three diamine spacers (H₂N-NH₂, H₂N(CH₂)₂NH₂ and H₂N(CH₂)₃NH₂) to afford Cell=Spacer=FL. The obtained products were characterized by spectroscopic (FT-IR, UV–Vis), thermal gravimetric analysis (TGA), and microscopic (Optical, SEM) techniques. The UV-Vis spectra of the FL=N(CH₂)ₓNH₂ (x = 0, 2, 3) moieties show that they are transparent in the 375- 800 nm region while they exhibit intense absorption band below 350 nm attributed to n-π* and π-π* transitions. The solid-state photoluminescence (PLs-s) of the cold-pressed pellets of the FL=N(CH₂)ₓNH₂ and Cell=Spacer=FL placed in a quartz cuvette show strong emission in the 500-550 nm region upon irradiation with Xe lamp light (λex = 320 nm). The PLs-s green emission of the grafted Cell=Spacer=FL was evaluated relative to that of the FL-based precursor. These grafted conjugated products have the potential to be used as analyte sensors for typical nitroaromatics/aromatic amines and be further extended to immunoassay studies for aromatic amino acids such as phenylalanine and histidine.

Keywords: luminescence, cellulose, fluorenone, grafting, solid state

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Authors: Zouhour Neji Ben Salem

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Microscopic evacuation focuses on the evacuee behavior and way of search of safety place in an egress situation. In recent years, several models handled microscopic evacuation problem. Among them, we have proposed Artificial Neural Network (ANN) as an alternative to mathematical models that can deal with such problem. In this paper, we present two ANN models: SOM map and Hopfield Network used to predict the evacuee behavior in a disaster situation. These models are tested in a real case, the second floor of Tunisian children hospital evacuation in case of fire. The two models are studied and compared in order to evaluate their performance.

Keywords: artificial neural networks, self-organization map, hopfield network, microscopic evacuation, fire building evacuation

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Authors: Jana Djounova

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The World Health Organization proposes an average annual reference level of 100 Bq/m³ to minimize health risks due to radon exposure in buildings. However, if this cannot be achieved under the country's specific conditions, the chosen reference level should not exceed 300 Bq/m³. The World Health Organization recognized the relationship between indoor radon exposure and lung cancer, even at low doses. Radon in buildings is one of the most important indoor air pollutants, with harmful effects on the health of the population and especially children. This study presents the assessment of indoor radon concentration as air pollution and analyzes the exposure to radon of children and workers. Assessment of air pollution and exposure to indoor radon concentrations under the National Science Fund of Bulgaria, in the framework of grant No КП-06-Н23/1/07.12.2018 in kindergartens in two districts of Bulgaria (Razgrad and Silistra). Kindergartens were considered for the following reasons: 1these buildings are generally at the ground and/or the first floor, where radon concentration is generally higher than at upper floors; 2these buildings are attended by children, a population generally considered more sensitive to ionizing radiation, although little data is available for radon exposure. The measurements of indoor radon concentrations were performed with passive methods (CR-39 track detectors) for the period from February to May 2015. One hundred fifty-six state kindergartens on the territories of two districts in Bulgaria have been studied. The variations of radon in the children's premises vary from 9 to 1087 Bq/m³. The established arithmetic mean value of radon levels in the kindergartens in Silistra is 139 Bq/m³ and in Razgrad 152 Bq/m³, respectively. The percentage of kindergarteners, where the radon in premises exceeds the Bulgarian reference level of 300 Bq/m³, was 19%. The exposure of children and workers in those kindergartens is high, so remediation measures of air pollution had been recommended. The difference in radon concentration in kindergartens in two districts was statistically analyzed to assess the influence of geography and geology and the difference

Keywords: air pollution, radon, kindergartens, detectors

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Authors: Vassilios Moussas, Dimos N. Pantazis, Panagioths Stratakis

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The aim of this paper is to present the optimization methodology developed in the frame of a Coastal Transport Information System. The system will be used for the effective design of coastal transportation lines and incorporates subsystems that implement models, tools and techniques that may support the design of improved networks. The role of the optimization and decision subsystem is to provide the user with better and optimal scenarios that will best fulfill any constrains, goals or requirements posed. The complexity of the problem and the large number of parameters and objectives involved led to the adoption of an evolutionary method (Genetic Algorithms). The problem model and the subsystem structure are presented in detail, and, its support for simulation is also discussed.

Keywords: coastal transport, modeling, optimization

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Authors: M. Sneha Reddy, M. Arun Kumar, V. Kameswara Rao

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Chromites are binary transition metal oxides with a general formula of ACr₂O₄, where A = Mn²⁺, Fe²⁺, Co²⁺, Ni²⁺, and Cu²⁺. Chromites have a normal-type spinel structure with interesting applications in the areas of applied physics, material sciences, and geophysics. They have attracted great consideration because of their unique physicochemical properties and tremendous technological applications in nanodevices, sensor elements, and high-temperature ceramics with useful optical properties. Copper chromite is one of the most efficient spinel oxides, having pronounced commercial application as a catalyst in various chemical reactions like oxidation, hydrogenation, alkylation, dehydrogenation, decomposition of organic compounds, and hydrogen production. Apart from its usage in chemical industries, CuCr₂O₄ finds its major application as a burn rate modifier in solid propellant processing for space launch vehicles globally. Herein we synthesized the nanoparticles of copper chromite using the co-precipitation method. The synthesized nanoparticles were characterized by XRD, TEM, SEM, BET, and TG-DTA. The synthesized nanoparticles of copper chromites were used as a catalyst for the thermal decomposition of various high-energy materials.

Keywords: copper chromite, coprecipitation method, high energy materials, catalytic thermal decomposition

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Authors: Malgorzata Sekulowicz, Krystyna Boron-Krupinska, Paulina Morga, Blazej Cieslik

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Burnout is highly prevalent in health care employees, especially in physicians. It significantly reduces the efficiency of these employees, which can have negative consequences for both physicians and patients. Resilience and mindfulness enhancing positive emotions, leading to sustainable development and personal commitment, can have a significant impact on burnout. Therefore, the aim of this study was to determine the relationship between burnout symptoms and mindfulness and resilience among physicians. The authors conducted a cross-sectional survey study among seventy-four polish physicians. Participants filled out the following psychometric tools: the Maslach Burnout Inventory - Human Services Survey (MBI-HSS), Five Facet Mindfulness Questionnaire (FFMQ), Areas of Work-Life Survey (AWS), International Personality Item Pool (IPIP), the Resilience Assessment Scale (SPP-25) and the Mini-COPE Inventory. The relationship between burnout and resilience and mindfulness was assessed with path analysis. Analyzing the relationship between MBI-HSS components and mindfulness, a significant negative correlation of the FFMQ score with emotional exhaustion (-0.50, p < 0.05) and depersonalization (-0.43, p < 0.05) and a positive correlation with personal accomplishment (0.50, p < 0.05) was demonstrated. Analyzing resilience, a statistically significant relationship of SPP-25 with all tested components of MBI-HSS was demonstrated: emotional exhaustion (-0.54, p < 0.05), depersonalization (-0.31, p < 0.05) and personal accomplishment (0.35, p < 0.05). In the group of medical doctors, the higher the level of mindfulness and resilience, the lower the risk of burnout. Furthermore, the more frequently used active coping strategies (planning, acceptance), the lower the risk of burnout, while the use of passive, evasive strategies increases the risk of burnout. It may be worth considering implementing mindfulness intervention to effectively manage burnout symptoms in this group.

Keywords: burnout, medical doctors, mindfulness, physicians, resilience

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Authors: Samai'la Abdullahi

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A graph is a pair of two set and so that a graph is a pictorial representation of a system using two basic element nodes and edges. A node is represented by a circle (either hallo shade) and edge is represented by a line segment connecting two nodes together. In this paper, we present a circuit network in the concept of graph theory application and also circuit models of graph are represented in logical connection method were we formulate matrix method of adjacency and incidence of matrix and application of truth table.

Keywords: euler circuit and path, graph representation of circuit networks, representation of graph models, representation of circuit network using logical truth table

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Authors: André Lages, Victor Dmitriev, Juliano Bazzo, Gianni Portela

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This work evaluates the feasibility of the graphene application to perform as a wideband reconfigurable material for lens antennas in 5G/6G and satellite applications. Based on transformation optics principles, the electromagnetic waves can be efficiently guided by modifying the effective refractive index. Graphene behavior can range between a lossy dielectric and a good conductor due to the variation of its chemical potential bias, thus arising as a promising solution for electromagnetic devices. The graphene properties and a lens antenna comprising multiples layers and periodic arrangements of graphene patches were analyzed using full-wave simulations. A dipole directivity was improved from 7 to 18.5 dBi at 29 GHz. In addition, the realized gain was enhanced 7 dB across a 14 GHz bandwidth within the Ka/5G band.

Keywords: 5G/6G, graphene, lens, reconfigurable, satellite

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Authors: Joon Sang Kang, Ming Ke, Yongjie Hu

Abstract:

Controlling heat transfer and thermal properties of materials is important to many fields such as energy efficiency and thermal management of integrated circuits. Significant progress over the past decade has been made to improve material performance through structuring at the nanoscale, however a clear relationship between structure dimensions, interfaces, and thermal properties remains to be established. The main challenge comes from the unknown intrinsic spectral contribution from different phonons. Here, we describe our current progress on quantifying and controlling thermal spectra based on our recently developed technical approach using ultrafast optical spectroscopy. Our work brings further the promise of rational material design to achieve high performance through a synergistic experimental-modeling approach. This approach can be broadly applicable to a wide range of materials and energy systems. In particular, we demonstrate in-situ characterization and tunable thermal properties of 2D van der waals materials through ionic intercalations. The significant impacts of this research in improving the efficiency of thermal energy conversion and management will also be illustrated.

Keywords: energy, mean free path, nanoscale heat transfer, nanostructure, phonons, TDTR, thermoelectrics, 2D materials

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Authors: Hassiba Bougueria, Nesrine Benarous, Souheyla Chetioui

Abstract:

Azo dyes are one of the most widely used compounds in organic chemistry, primarily due to their relatively simple preparation methods. They have therefore been widely used, in particular as colorants for textiles, printing inks, cosmetics, and food additives. In addition to their use as dyes, azo compounds have attracted much attention from chemists as their potential applications are important in coordination chemistry, metal-organic frameworks (MOF) structures, COF (covalent-organic frameworks), and catalysis. Moreover, they have found many applications in different fields, such as nonlinear optics, optical storage, photoluminescence, and magnetism. The compound bis{(E)-1-[(2,4,6-tribromophenyl)diazenyl]naphthalen-2-olato}copper(II) dimethyl sulfoxide monosolvate, the CuII atom is tetracoordinate with a square-planar geometry, surrounded by two bidentate (E)-1-[(2,4,6-tribromophenyl)diazenyl]naphthalene-2-olate ligands via two N atoms and two O atoms. The O-Cu-O angles and N-Cu-N are of the order of 177.90(16)° and 177.8(2)°, respectively. The distances Cu-O and Cu- N are 1.892(4) Å and 1.976(4) Å, respectively. The cohesion of the crystal is ensured by hydrogen bonds of the C—H…O type and by π=π staking interactions [centroid–centroid distance = 3.679(4)Å]. The DMSO solvent molecule is disordered at two positions with occupancy rates of 0.70 and 0.30.

Keywords: azo dyes, DRX, structural characterization, biological activity

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Authors: Elena A. Outkina, Marina V. Meledina, Aliaksandr A. Khodin

Abstract:

Nanostructured thin films of SnSₓ, Cu₂ZnSnS₄ (CZTS) semiconductors were fabricated by chemical processing to produce thin-film photoactive layers for photocells as a prospective lowest-cost and environment-friendly alternative to Si, Cu(In, Ga)Se₂, and other traditional solar cells materials. To produce SnSₓ layers, the modified successive ionic layer adsorption and reaction (SILAR) technique were investigated, including successive cyclic dipping into Na₂S solution and SnCl₂, NaCl, triethanolamine solution. To fabricate CZTS layers, the cyclic dipping into CuSO₄ with ZnSO₄, SnCl₂, and Na₂S solutions was used with intermediate rinsing in distilled water. The nano-template aluminum/alumina substrate was used to control deposition processes. Micromorphology and optical characteristics of the fabricated layers have been investigated. Analysis of 2D-like layers deposition features using nano-template substrate is presented, including the effect of nanotips in a template on surface charge redistribution and transport.

Keywords: kesterite, nanotemplate, SILAR, solar cell, tin sulphide

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Authors: Shashank Gupta, Carlos Cid, William John Munro

Abstract:

Quantum distillation is the task of concentrating quantum correlations present in N imperfect copies to M perfect copies (M < N) using free operations by involving all P the parties sharing the quantum correlation. We present a threshold quantum distillation task where the same objective is achieved but using lesser number of parties (K < P). In particular, we give an exact local filtering operations by the participating parties sharing high dimension multipartite entangled state to distill the perfect quantum correlation. Later, we bridge a connection between threshold quantum entanglement distillation and quantum steering distillation and show that threshold distillation might work in the scenario where general distillation protocol like DEJMPS does not work.

Keywords: quantum networks, quantum distillation, quantum key distribution, entanglement distillation

Procedia PDF Downloads 38