Search results for: double layered fuzzy graph

Authors: Ali Ates, Sadık Ata, Kevser Dincer

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In this study, performance of the driver seat‘s localized cooling and heating in a standard car air conditioning system was experimentally investigated and modeled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modeling technique. Climate function at automobile is an important variable for thermal comfort. In the experimental study localized heating and cooling performances have been examined with the aid of a mechanism established to a vehicle. The equipment’s used in the experimental setup/mechanism have been provided and assembled. During the measurement, the status of the performance level has been determined. Input parameters revolutions per minute and time; output parameters car seat cooling temperature, car back cooling temperature, car seat heating temperature, car back heating temperature were described by RBMTF if-the rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between experimental data and RBMTF is done by using statistical methods like absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF could be successfully used in standard car air conditioning system.

Keywords: air conditioning system, cooling-heating, RMBTF modelling, car seat

Procedia PDF Downloads 350

Authors: M. Karthigayan, M. Rizon, Sazali Yaacob, R. Nagarajan, M. Muthukumaran, Thinaharan Ramachandran, Sargunam Thirugnanam

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In this paper, using a set of irregular and regular ellipse fitting equations using Genetic algorithm (GA) are applied to the lip and eye features to classify the human emotions. Two South East Asian (SEA) faces are considered in this work for the emotion classification. There are six emotions and one neutral are considered as the output. Each subject shows unique characteristic of the lip and eye features for various emotions. GA is adopted to optimize irregular ellipse characteristics of the lip and eye features in each emotion. That is, the top portion of lip configuration is a part of one ellipse and the bottom of different ellipse. Two ellipse based fitness equations are proposed for the lip configuration and relevant parameters that define the emotions are listed. The GA method has achieved reasonably successful classification of emotion. In some emotions classification, optimized data values of one emotion are messed or overlapped to other emotion ranges. In order to overcome the overlapping problem between the emotion optimized values and at the same time to improve the classification, a fuzzy clustering method (FCM) of approach has been implemented to offer better classification. The GA-FCM approach offers a reasonably good classification within the ranges of clusters and it had been proven by applying to two SEA subjects and have improved the classification rate.

Keywords: ellipse fitness function, genetic algorithm, emotion recognition, fuzzy clustering

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

Procedia PDF Downloads 275

Authors: Ahmet Kayabasi, Ali Akdagli

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In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: a-shaped compact microstrip antenna, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM)

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Authors: M. Abbasi Layegh, S. Haghipour, K. Athari, R. Khosravi, M. Tafkikialamdari

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An approach to find the optimum mel-frequency cepstral coefficients (MFCCs) for the Radif of Mirzâ Ábdollâh, which is the principal emblem and the heart of Persian music, performed by most famous Iranian masters on two Iranian stringed instruments ‘Tar’ and ‘Setar’ is proposed. While investigating the variance of MFCC for each record in themusic database of 1500 gushe of the repertoire belonging to 12 modal systems (dastgâh and âvâz), we have applied the Fuzzy C-Mean clustering algorithm on each of the 12 coefficient and different combinations of those coefficients. We have applied the same experiment while increasing the number of coefficients but the clustering accuracy remained the same. Therefore, we can conclude that the first 7 MFCCs (V-7MFCC) are enough for classification of The Radif of Mirzâ Ábdollâh. Classical machine learning algorithms such as MLP neural networks, K-Nearest Neighbors (KNN), Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and Support Vector Machine (SVM) have been employed. Finally, it can be realized that SVM shows a better performance in this study.

Keywords: radif of Mirzâ Ábdollâh, Gushe, mel frequency cepstral coefficients, fuzzy c-mean clustering algorithm, k-nearest neighbors (KNN), gaussian mixture model (GMM), hidden markov model (HMM), support vector machine (SVM)

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Authors: Wenjun Hou, Marek Perkowski

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The Traveling Salesman problem is famous in computing and graph theory. In short, it asks for the Hamiltonian cycle of the least total weight in a given graph with N nodes. All variations on this problem, such as those with K-bounded-degree nodes, are classified as NP-complete in classical computing. Although several papers propose theoretical high-level designs of quantum algorithms for the Traveling Salesman Problem, no quantum circuit implementation of these algorithms has been created up to our best knowledge. In contrast to previous papers, the goal of this paper is not to optimize some abstract complexity measures based on the number of oracle iterations, but to be able to evaluate the real circuit and time costs of the quantum computer. Using the emerging quantum programming language Q# developed by Microsoft, which runs quantum circuits in a quantum computer simulation, an implementation of the bounded-degree problem and its respective quantum circuit were created. To apply Grover’s algorithm to this problem, a quantum oracle was designed, evaluating the cost of a particular set of edges in the graph as well as its validity as a Hamiltonian cycle. Repeating the Grover algorithm with an oracle that finds successively lower cost each time allows to transform the decision problem to an optimization problem, finding the minimum cost of Hamiltonian cycles. N log₂ K qubits are put into an equiprobablistic superposition by applying the Hadamard gate on each qubit. Within these N log₂ K qubits, the method uses an encoding in which every node is mapped to a set of its encoded edges. The oracle consists of several blocks of circuits: a custom-written edge weight adder, node index calculator, uniqueness checker, and comparator, which were all created using only quantum Toffoli gates, including its special forms, which are Feynman and Pauli X. The oracle begins by using the edge encodings specified by the qubits to calculate each node that this path visits and adding up the edge weights along the way. Next, the oracle uses the calculated nodes from the previous step and check that all the nodes are unique. Finally, the oracle checks that the calculated cost is less than the previously-calculated cost. By performing the oracle an optimal number of times, a correct answer can be generated with very high probability. The oracle of the Grover Algorithm is modified using the recalculated minimum cost value, and this procedure is repeated until the cost cannot be further reduced. This algorithm and circuit design have been verified, using several datasets, to generate correct outputs.

Keywords: quantum computing, quantum circuit optimization, quantum algorithms, hybrid quantum algorithms, quantum programming, Grover’s algorithm, traveling salesman problem, bounded-degree TSP, minimal cost, Q# language

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Authors: H. Ahmed, A. Schlenkhoff, R. Rousta, R. Abdelaziz

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Vertical slotted walls can be used as permeable breakwaters to provide economical and environmental protection from undesirable waves and currents inside the port. The permeable breakwaters are partially protection and have been suggested to overcome the environmental disadvantages of fully protection breakwaters. For regular waves a semi-analytical model is based on an eigenfunction expansion method and utilizes a boundary condition at the surface of each wall are developed to detect the energy dissipation through the slots. Extensive laboratory tests are carried out to validate the semi-analytic models. The structure of the physical model contains two walls and it consists of impermeable upper and lower part, where the draft is based a decimal multiple of the total depth. The middle part is permeable with a porosity of 50%. The second barrier is located at a distant of 0.5, 1, 1.5 and 2 times of the water depth from the first one. A comparison of the theoretical results with previous studies and experimental measurements of the present study show a good agreement and that, the semi-analytical model is able to adequately reproduce most the important features of the experiment.

Keywords: permeable breakwater, double vertical slotted walls, semi-analytical model, transmission coefficient, reflection coefficient, energy dissipation coefficient

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Authors: Shahin A. Abdel-Naby, James P. Colgan, Michael S. Pindzola

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A time-dependent close-coupling method is developed to calculate a total, double and triple autoionization rates for hollow atomic ions of four-electron systems. This work was motivated by recent observations of the four-electron Auger process in near K-edge photoionization of C+ ions. The time-dependent close-coupled equations are solved using lattice techniques to obtain a discrete representation of radial wave functions and all operators on a four-dimensional grid with uniform spacing. Initial excited states are obtained by relaxation of the Schrodinger equation in imaginary time using a Schmidt orthogonalization method involving interior subshells. The radial wave function grids are partitioned over the cores on a massively parallel computer, which is essential due to the large memory requirements needed to store the coupled-wave functions and the long run times needed to reach the convergence of the ionization process. Total, double, and triple autoionization rates are obtained by the propagation of the time-dependent close-coupled equations in real-time using integration over bound and continuum single-particle states. These states are generated by matrix diagonalization of one-electron Hamiltonians. The total autoionization rates for each L excited state is found to be slightly above the single autoionization rate for the excited configuration using configuration-average distorted-wave theory. As expected, we find the double and triple autoionization rates to be much smaller than the total autoionization rates. Future work can be extended to study electron-impact triple ionization of atoms or ions. The work was supported in part by grants from the American University of Sharjah and the US Department of Energy. Computational work was carried out at the National Energy Research Scientific Computing Center (NERSC) in Berkeley, California, USA.

Keywords: hollow atoms, autoionization, auger rates, time-dependent close-coupling method

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Authors: Chan Ka Lok Sobel

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Recently, several famous Asian films have been remade in North America, set in the context of U.S. society and with the financial and cultural scale of Hollywood cinema. Notably, the practice of remaking films is interactive, with famous Hollywood films also being remade in Asia; for example, Charlie’s Angels (McG, 2002) was remade as So Close (Yuen, 2002), Seven (Fincher, 1995) was remade as Double Vision (Fu, 2002), and Cellular (Ellis, 2004) was remade as Connected (Chan, 2008). Conversely, Asian films such as Infernal Affairs (Lau & Mak, 2002), il Mare (Lee, 2000), and Bangkok Dangerous (Pang, 2000) were remade into Hollywood blockbuster films The Departed (Scorsese, 2006), The Lake House (Agresti, 2006), and Bangkok Dangerous (Pang, 2007), respectively. This research examined Asian cinema and Hollywood remakes from the perspective of cultural hybridization and partition in the context of global capitalism and postmodernism. Using Infernal Affairs and The Departed as a case study, key concepts such as crosscultural adaptation, intercultural and global communication competence, and cultural identity and authorship were compared and analyzed.

Keywords: remake and originality, double cultural identity, studio system, genre and authorship

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Authors: Sindhu S Nair, Atul Thakur, Preeti Thakur, Trukhanov Alex

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Perovskite-based absorbing materials that are organic, inorganic, or hybrid have gained interest as an appealing candidate for the development of solar cell devices. Lead-based perovskites are among the most promising materials, but their application is plagued with toxicity and stability concerns. Most of the perovskite solar cell consists of conventional (n-i-p) structure with organic or inorganic charge transport materials. The commercial application of such device is limited due to higher J-V hysteresis and the need for high temperature during fabrication. This numerical analysis primarily directs to investigate the performance of various inorganic lead-free valency ordered double perovskite absorber materials and to develop an inverted perovskite solar cell device structure. Simulation efforts using SCAPS-1D was carried out with various organic and inorganic charge transport materials with absorber layer materials, and their performance has been evaluated for various factors of thickness, absorber thickness, absorber defect density, and interface defect density to achieve the optimized structure.

Keywords: perovskite materials, solar cell, inverted solar cell, inorganic perovskite solar cell materials, cell efficiency

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Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Kyeong Hoon Park, Taiji Mazuda

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High damping rubber (HDR) bearings are dissipating devices mainly used in seismic isolation systems and have a great damping performance. Although many studies have been conducted on the dynamic model of HDR bearings, few models can reflect phenomena such as dependency of experienced shear strain on initial history. In order to develop a model that can represent the dependency of experienced shear strain of HDR by Mullins effect, dynamic loading test was conducted using HDR specimen. The reaction of HDR was measured by applying a horizontal vibration using a hybrid actuator under a constant vertical load. Dynamic program analysis was also performed after dynamic loading test. The dynamic model applied in program analysis is a bilinear type double-target model. This model is modified from typical bilinear model. This model can express the nonlinear characteristics related to the initial history of HDR bearings. Based on the dynamic loading test and program analysis results, equivalent stiffness and equivalent damping ratio were calculated to evaluate the mechanical properties of HDR and the feasibility of the bilinear type double-target model was examined.

Keywords: base-isolation, bilinear model, high damping rubber, loading test

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Authors: Mohamed Ahmed Gesraha, Amany Ramadan Ebeid

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Aphids are noxious and serious persistent pests in the open fields worldwide. Many authors studied the possibility of aphid control by applying Ladybirds and Lacewings at different releasing rates under open-field conditions. Results clarify that releasing 3rd instar larvae of Coccinella undecimpunctata at the rate of 1 larva:50 aphid was more effective than 1:100 or 1:200 rates for controlling Aphis gossypii population in Okra field; reflecting more than 90% reduction in the aphid population within 15 days. When Chrysoperla carnea 2nd larval instar were releasing at 1:5, 1:10, and 1:20 (predator: aphid), it was noticed that the former rate was the most effective one, inducing 98.93% reduction in aphid population; while the two other rates reflecting less reduction. Additionally, in the case of double releases, the reduction percentage at the 1:5 rate was 99.63%, emphasize that this rate was the most effective one; the other rates induced 97.05 and 95.64% reduction. Generally, a double release was more effective in all tested rates than the single one because of the cumulative existence of the predators in large numbers at the same period of the experiment. It could be concluded that utilizing insect predators (Coccinella undecimpunctata or Chrysoperla carnea) at an early larval stag were faire enough to reduce the aphids’ populations under open fields conditions.

Keywords: releasing predators, lacewings, ladybird, open fields

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Authors: Muhammad Bahrul Ilmi

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The purpose of this research is to analyze the influence of Islamic financing and work relation founding simultaneously and partially towards non-performing financing in Islamic banks. This research was regression quantitative field research, and had been done in Muammalat Indonesia Bank and Islamic Danamon Bank in 3 months. The populations of this research were 15 account officers of Muammalat Indonesia Bank and Islamic Danamon Bank in Surakarta, Indonesia. The techniques of collecting data used in this research were documentation, questionnaire, literary study and interview. Regression analysis result shows that Islamic financing and work relation founding simultaneously has positive and significant effect towards non performing financing of two Islamic Banks. It is obtained with probability value 0.003 which is less than 0.05 and F value 9.584. The analysis result of Islamic financing regression towards non performing financing shows the significant effect. It is supported by double linear regression analysis with probability value 0.001 which is less than 0.05. The regression analysis of work relation founding effect towards non-performing financing shows insignificant effect. This is shown in the double linear regression analysis with probability value 0.161 which is bigger than 0.05.

Keywords: Syariah financing, work relation founding, non-performing financing (NPF), Islamic Bank

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Authors: Wei-Chou Hsu, Ching-Sung Lee, Han-Yin Liu

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This work uses H2O2 oxidation technique to improve the pH sensitivity of the AlGaN/GaN-based ion-sensitive field-effect transistors (ISFETs). 10-nm-thick Al2O3 was grown on the surface of the AlGaN. It was found that the pH sensitivity was improved from 41.6 mV/pH to 55.2 mV/pH. Since the H2O2-grown Al2O3 was served as a passivation layer and the problem of Fermi-level pinning was suppressed for the ISFET with the H2O2 oxidation process. Hysteresis effect in the ISFET with the H2O2 treatment also became insignificant. The hysteresis effect was observed by dipping the ISFETs into different pH value solutions and comparing the voltage difference between the initial and final conditions. The hysteresis voltage (Vhys) of the ISFET with the H2O2 oxidation process was improved from 8.7 mV to 4.8 mV. The hysteresis effect is related to the buried binding sites which are related to the material defects like threading dislocations in the AlGaN/GaN heterostructure which was grown by the hetero-epitaxy technique. The H2O2-grown Al2O3 passivate these material defects and the Al2O3 has less material defects. The long-term stability of the ISFET is estimated by the drift effect measurement. The drift measurement was conducted by dipping the ISFETs into a specific pH value solution for 12 hours and the ISFETs were operating at a specific quiescent point. The drift rate is estimated by the drift voltage divided by the total measuring time. It was found that the drift rate of the ISFET was improved from 10.1 mV/hour to 1.91 mV/hour in the pH 7 solution, from 14.06 mV/hour to 6.38 mV/pH in the pH 2 solution, and from 12.8 mV/hour to 5.48 mV/hour in the pH 12 solution. The drift effect results from the capacitance variation in the electric double layer. The H2O2-grown Al2O3 provides an additional capacitance connection in series with the electric double layer. Therefore, the capacitance variation of the electric double layer became insignificant. Generally, the H2O2 oxidation process is a simple, fast, and cost-effective method for the AlGaN/GaN-based ISFET. Furthermore, the performance of the AlGaN/GaN ISFET was improved effectively and the non-ideal effects were suppressed.

Keywords: AlGaN/GaN, Al2O3, hysteresis effect, drift effect, reliability, passivation, pH sensors

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Authors: Krzysztof Skiba, Zdzislaw Kaminski

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Wind power is based on a variety of construction solutions to convert wind energy into electrical energy. These constructions are constrained by the correlation between their energy conversion efficiency and the area they occupy. Their energy conversion efficiency can be improved by wind tunnel tests of a rotor as a diffuser to optimize shapes of aerodynamic elements, to adapt these elements to changing conditions and to increase airflow intensity. This paper discusses the results of computer simulations and aerodynamic analyzes of this innovative diffuser design. The research aims at determining the aerodynamic phenomena triggered by the airflow inside this construction, and developing a design to improve the efficiency of the wind turbine. The research results enable us to design a diffuser with a double Venturi nozzle and specially shaped blades. The design of this type uses Bernoulli’s law on the behavior of the flowing medium in the tunnel of a decreasing diameter. The air flowing along the tunnel changes its velocity so the rotor inside such a decreased tunnel diameter rotates faster in this airflow than does the wind outside this tunnel, which makes the turbine more efficient. Additionally, airflow velocity is improved by applying aerodynamic rings with extended trailing edges to achieve controlled turbulent vortices.

Keywords: wind turbine, renewable energy, cfd, numerical analysis

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Authors: Buse T. Aydin, Enver Ozdemir

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An automatic dependent surveillance-broadcast (ADS-B) system has serious security problems. In this study, a double layer authentication scheme between the aircraft and ground station, aircraft to aircraft, ground station to ATC tower is designed to prevent any unauthorized aircrafts from introducing themselves as friends. This method can be used as a solution to the problem of authentication. The method is a combination of classical cryptographic methods and new generation physical layers. The first layer has employed the embedded key of the aircraft. The embedded key is assumed to installed during the construction of the utility. The other layer is a physical attribute (flight path, distance, etc.) between the aircraft and the ATC tower. We create a mathematical model so that two layers’ information is employed and an aircraft is authenticated as a friend or unknown according to the accuracy of the results of the model. The results of the aircraft are compared with the results of the ATC tower and if the values found by the aircraft and ATC tower match within a certain error margin, we mark the aircraft as friend. As a result, the ADS-B messages coming from this authenticated friendly aircraft will be processed. In this method, even if the embedded key is captured by the unknown aircraft, without the information of the second layer, the unknown aircraft can easily be determined. Overall, in this work, we present a reliable system by adding physical layer in the authentication process.

Keywords: ADS-B, authentication, communication with physical layer security, cryptography, identification friend or foe

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Authors: Krunal Thakar

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Wire ropes combine high tensile strength and flexibility as compared to other general steel products. They are used in various application areas such as cranes, mining, elevators, bridges, cable cars, etc. The earliest reported use of wire ropes was for mining hoist application in 1830s. Over the period, there have been substantial advancement in the design of wire ropes for various application areas. Under operational conditions, wire ropes are subjected to varying tensile loads and bending loads resulting in material wear and eventual structural failure due to fretting fatigue. The conventional inspection methods to determine wire failure is only limited to outer wires of rope. However, till date, there is no effective mathematical model to examine the inter wire contact forces and wear characteristics. The scope of this paper is to present a computational simulation technique to evaluate inter wire contact forces and wear, which are in many cases responsible for rope failure. Two different type of ropes, IWRC-6xFi(29) and U3xSeS(48) were taken for structural strength evaluation and wear prediction. Both ropes have a double helix twisted wire profile as per JIS standards and are mainly used in cranes. CAD models of both ropes were developed in general purpose design software using in house developed formulation to generate double helix profile. Numerical simulation was done under two different load cases (a) Axial Tension and (b) Bending over Sheave. Different parameters such as stresses, contact forces, wear depth, load-elongation, etc., were investigated and compared between both ropes. Numerical simulation method facilitates the detailed investigation of inter wire contact and wear characteristics. In addition, various selection parameters like sheave diameter, rope diameter, helix angle, swaging, maximum load carrying capacity, etc., can be quickly analyzed.

Keywords: steel wire ropes, numerical simulation, material wear, structural strength, axial tension, bending over sheave

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Authors: Amine.Harbia, Hicham. Moutaabbidb, Yann. Le Godecb, Said. Benmokhtara, Mouhammed. Moutaabbida

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This study explores the structural and magnetic characteristics of newly synthesized double perovskite oxides, La₂NiₓCo1-xMnO₆, with x ranging from 0.2 to 0.8. Utilizing X-ray powder diffraction and SQUID magnetometry, we analyzed the compounds that consistently exhibit a monoclinic structure with the P21/n space group at ambient temperature. it findings reveal that as Ni2+ is progressively substituted by Co2+, there is a corresponding decrease in cell parameters, attributable to the smaller ionic radius of Ni2+ (0.69 Å) compared to Co2+ (0.74 Å). The crystal structure features octahedrally coordinated (Co/Ni)2+ and Mn4+ cations with oxygen, forming (Co/Ni)O6 and MnO6 octahedra linked via oxygen atoms along different crystallographic axes. Magnetic characterization conducted over a temperature range of 2 to 300 K in both DC and AC magnetic fields, showed a predominant paramagnetic to ferromagnetic transition between 232 K and 260 K, with the Curie temperature notably increasing with higher x values. Samples with x=0.2, 0.25, and 0.5 exhibited a secondary PM-FM transition between 200 K and 208 K. Cation ordering was quantitatively assessed, indicating a higher ordering in Ni2+-rich samples (x=0.75 and 0.8) at over 96%, whereas the sample with x=0.25 showed minimal ordering. Furthermore, the out-of-phase component of the AC susceptibility displayed frequency-dependent transitions between 65 K and 110 K, suggesting the presence of superparamagnetic domains across all samples.

Keywords: double perovskite oxides, magnetic transitions, cation ordering, squid magnetometry

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Authors: Priyanka Jain, Ashish K. Sharma, Esha Shukla, K. J. Mukherjee

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We propose a paradigm shift in our approach to design improved platforms for recombinant protein production, by addressing system level issues rather than the individual steps associated with recombinant protein synthesis like transcription, translation, etc. We demonstrate that by controlling and modulating the cellular stress response (CSR), which is responsible for feedback control of protein synthesis, we can generate hyper-producing strains. We did transcriptomic profiling of post-induction cultures, expressing different types of protein, to analyze the nature of this cellular stress response. We found significant down-regulation of substrate utilization, translation, and energy metabolism genes due to generation CSR inside the host cell. However, transcription profiling has also shown that many genes are up-regulated post induction and their role in modulating the CSR is unclear. We hypothesized that these up-regulated genes trigger signaling pathways, generating the CSR and concomitantly reduce the recombinant protein yield. To test this hypothesis, we knocked out the up-regulated genes, which did not have any downstream regulatees, and analyzed their impact on cellular health and recombinant protein expression. Two model proteins i.e., GFP and L-Asparaginase were chosen for this analysis. We observed a significant improvement in expression levels, with some knock-outs showing more than 7-fold higher expression compared to control. The 10 best single knock-outs were chosen to make 45 combinations of all possible double knock-outs. A further increase in expression was observed in some of these double knock- outs with GFP levels being highest in a double knock-out ΔyhbC + ΔelaA. However, for L-Asparaginase which is a secretory protein, the best results were obtained using a combination of ΔelaA+ΔcysW knock-outs. We then tested all the knock outs for their ability to enhance the expression of a 'difficult-to-express' protein. The Rubella virus E1 protein was chosen and tagged with sfGFP at the C-terminal using a linker peptide for easy online monitoring of expression of this fusion protein. Interestingly, the highest increase in Rubella-sGFP levels was obtained in the same double knock-out ΔelaA + ΔcysW (5.6 fold increase in expression yield compared to the control) which gave the highest expression for L-Asparaginase. However, for sfGFP alone, the ΔyhbC+ΔmarR knock-out gave the highest level of expression. These results indicate that there is a fair degree of commonality in the nature of the CSR generated by the induction of different proteins. Transcriptomic profiling of the double knock out showed that many genes associated with the translational machinery and energy biosynthesis did not get down-regulated post induction, unlike the control where these genes were significantly down-regulated. This confirmed our hypothesis of these genes playing an important role in the generation of the CSR and allowed us to design a strategy for making better expression hosts by simply knocking out key genes. This strategy is radically superior to the previous approach of individually up-regulating critical genes since it blocks the mounting of the CSR thus preventing the down-regulation of a very large number of genes responsible for sustaining the flux through the recombinant protein production pathway.

Keywords: cellular stress response, GFP, knock-outs, up-regulated genes

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Authors: M. Kessi

Abstract:

We investigated the effect of the magnetic field on carrier transport phenomena in the transistor channel region of Double-Gate Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET). This explores the Lorentz force and basic physical properties of solids exposed to a constant external magnetic field. The magnetic field modulates the electrons and potential distribution in the case of silicon Tunnel FETs. This modulation shows up in the device's external electrical characteristics such as ON current (ION), subthreshold leakage current (IOF), the threshold voltage (VTH), the magneto-transconductance (gm) and the output magneto-conductance (gDS) of Tunnel FET. Moreover, the channel doping concentration and potential distribution are obtained using the numerical method by solving Poisson’s transport equation in 3D modules semiconductor magnetic sensors available in Silvaco TCAD tools. The numerical simulations of the magnetic nano-sensors are relatively new. In this work, we present the results of numerical simulations based on 3D magnetic sensors. The results show excellent accuracy comportment and good agreement compared with that obtained in the experimental study of MOSFETs technology.

Keywords: single-gate MOSFET, magnetic field, hall field, Lorentz force

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Authors: Y. Lu, L. Liu, J. Guo

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Monolayer graphene and dichaclogenide semiconductor materials attract extensive research interest for potential nanoelectronics applications. The ultimate scaling limit of double gate MoS2 Field-Effect-Transistors (FETs) with a monolayer thin body is examined and compared with ultra-thin-body Si FETs by using self-consistent quantum transport simulation in the presence of phonon scattering. Modelling of phonon scattering, quantum mechanical effects, and self-consistent electrostatics allows us to accurately assess the performance potential of monolayer MoS2 FETs. The results revealed that monolayer MoS2 FETs show 52% smaller Drain Induced Barrier Lowering (DIBL) and 13% Smaller Sub-Threshold Swing (SS) than 3 nm-thick-body Si FETs at a channel length of 10 nm with the same gating. With a requirement of SS<100mV/dec, the scaling limit of monolayer MoS2 FETs is assessed to be 5 nm, comparing with 8nm of the ultra-thin-body Si counterparts due to the monolayer thin body and higher effective mass which reduces direct source-to-drain tunnelling. By comparing with the ITRS target for high performance logic devices of 2023; double gate monolayer MoS2 FETs can fulfil the ITRS requirements.

Keywords: nanotransistors, monolayer 2D materials, quantum transport, scaling limit

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Authors: Sašo Pečnik, Borut Žalik

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This paper presents a real-time visualization technique and filtering of classified LiDAR point clouds. The visualization is capable of displaying filtered information organized in layers by the classification attribute saved within LiDAR data sets. We explain the used data structure and data management, which enables real-time presentation of layered LiDAR data. Real-time visualization is achieved with LOD optimization based on the distance from the observer without loss of quality. The filtering process is done in two steps and is entirely executed on the GPU and implemented using programmable shaders.

Keywords: filtering, graphics, level-of-details, LiDAR, real-time visualization

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Authors: Maria Luisa de la Torre, Javier Aroba, Jose Miguel Davila, Aguasanta M. Sarmiento

Abstract:

Steel is one of the most widely used materials in polymetallic sulfide mining installations. One of the main problems suffered by these facilities is the economic losses due to the corrosion of this material, which is accelerated and aggravated by the contact with acid waters generated in these mines when sulfides come into contact with oxygen and water. This generation of acidic water, in turn, is accelerated by the presence of acidophilic bacteria. In order to gain a more detailed understanding of this corrosion process and the interaction between steel and acidic water, a laboratory experiment was carried out in which carbon steel plates were introduced into four different solutions for 27 days: distilled water (BK), which tried to assimilate the effect produced by rain on this material, an acid solution from a mine with a high Fe2+/Fe3+ (PO) content, another acid solution of water from another mine with a high Fe3+/Fe2+ (PH) content and, finally, one that reproduced the acid mine water with a high Fe2+/Fe3+ content but in which there were no bacteria (ST). Every 24 hours, physicochemical parameters were measured, and water samples were taken to carry out an analysis of the dissolved elements. The results of these measurements were processed using an explainable AI model based on fuzzy logic. It could be seen that, in all cases, there was an increase in pH, as well as in the concentrations of Fe and, in particular, Fe(II), as a consequence of the oxidation of the steel plates. Proportionally, the increase in Fe concentration was higher in PO and ST than in PH because Fe precipitates were produced in the latter. The rise of Fe(II) was proportionally much higher in PH, especially in the first hours of exposure, because it started from a lower initial concentration of this ion. Although to a lesser extent than in PH, the greater increase in Fe(II) also occurred faster in PO than in ST, a consequence of the action of the catalytic bacteria. On the other hand, Cu concentrations decreased throughout the experiment (with the exception of distilled water, which initially had no Cu, as a result of an electrochemical process that generates a precipitation of Cu together with Fe hydroxides. This decrease is lower in PH because the high total acidity keeps it in solution for a longer time. With the application of an artificial intelligence tool, it has been possible to evaluate the effects of steel corrosion in mining environments, corroborating and extending what was obtained by means of classical statistics.

Keywords: acid mine drainage, artificial intelligence, carbon steel, corrosion, fuzzy logic

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Kyonghoon Kim, Wonyoung Park, Taeil Park

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In 1994, Korea experienced a national tragedy of Seongsu Bridge collapse. The accident was severe enough to alert governmental officers to the problem of existing management policy for national infrastructures. As a result, government legislated the ‘Guidelines for the safety inspection and test of infrastructure’ which have been utilized as the primary tool to make decision for the maintenance and rehabilitation of infrastructure for last twenty years. Although it is clear that the guideline established a basics how to evaluate and manage the condition of infrastructures in systematic manner, it is equally clear that the guideline needs improvements in order to obtain reasonable investment decisions for budget allocation. Because its inspection and evaluation procedures mainly focused on the structural condition of infrastructures, it was hard to make decision when the infrastructures were in same level of structural condition. In addition, it did not properly reflect various aspects of infrastructures such as performance, public demand, capacity, etc., which were more valuable to public. Regardless of the importance, these factors were commonly neglected in governmental decision-making process, because there factors were somewhat subjective and difficult to quantify in rational manner. Thus, this study proposes a framework to properly evaluate the serviceability indicators using AHP and Fuzzy approach. The framework is expected to assist governmental agency in establishing effective investment strategies for budget planning.

Keywords: infrastructure, evaluation, serviceability, fuzzy

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Authors: Karan Bhandari

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Almost quarter region of Indian terrain is covered by grasslands. Grass being a low maintenance perennial crop is in abundance. Farmers are well acquainted with its nature, yield and storage. The aim of this paper is to study and identify the applicability of grass as a source of bio fuel. Anaerobic break down is a well-recognized technology. This process is vital for harnessing bio fuel from grass. Grass is a lignocellulosic material which is fibrous and can readily cause problems with parts in motion. Further, it also has a tendency to float. This paper also deals with the ideal digester configuration for biogas generation from grass. Intensive analysis of the literature is studied on the optimum production of grass storage in accordance with bio digester specifications. Subsequent to this two different digester systems were designed, fabricated, analyzed. The first setup was a double stage wet continuous arrangement usually known as a Continuously Stirred Tank Reactor (CSTR). The next was a double stage, double phase system implementing Sequentially Fed Leach Beds using an Upflow Anaerobic Sludge Blanket (SLBR-UASB). The above methodologies were carried for the same feedstock acquired from the same field. Examination of grass silage was undertaken using Biomethane Potential values. The outcomes portrayed that the Continuously Stirred Tank Reactor system produced about 450 liters of methane per Kg of volatile solids, at a detention period of 48 days. The second method involving Leach Beds produced about 340 liters of methane per Kg of volatile solids with a detention period of 28 days. The results showcased that CSTR when designed exclusively for grass proved to be extremely efficient in methane production. The SLBR-UASB has significant potential to allow for lower detention times with significant levels of methane production. This technology has immense future for research and development in India in terms utilizing of grass crop as a non-conventional source of fuel.

Keywords: biomethane potential values, bio digester specifications, continuously stirred tank reactor, upflow anaerobic sludge blanket

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Authors: Chuyi Ye, Minsang Kim, Cheol-Hee Moon

Abstract:

The organic light emitting diode(OLED), is a potential organic optical functional materials which is considered as the next generation display technology with the advantages such as all-solid state, ultra-thin thickness, active luminous and flexibility. Due to the development of polymer-inorganic substrate, it becomes possible to achieve the flexible OLED display. However the organic light-emitting material is very sensitive to the oxygen and water vapor, and the encapsulation requires water vapor transmission rate(WVTR) and oxygen transmission rate(OTR) as lower as 10-6 g/(m2.d) and 10-5 cm3/(m2.d) respectively. In current situation, the rigorous WVTR and OTR have restricted the application of the OLED display. Traditional epoxy/getter or glass frit approaches, which have been widely applied on glass-substrate-based devices, are not suitable for transparent flexible organic devices, and mechanically flexible thin-film approaches are required. To ensure the OLED’s lifetime, the encapsulation material of the OLED package is very important. In this paper, a low melting point alloy(LMPA)-epoxy mixture in the encapsulation process is introduced. There will be a phase separation when the mixture is heated to the melting of LMPA and the formation of the double line structure between two substrates: the alloy barrier has extremely low WVTR and OTR and the epoxy fills the potential tiny cracks. In our experiment, the PI film is chosen as a flexible transparent substrate, and Mo and Cu are deposited on the PI film successively. Then the two metal layers are photolithographied to the sealing pattern line. The Mo is a transition layer between the PI film and Cu, at the same time, the Cu has a good wettability with the LMPA(Sn-58Bi). At last, pattern is printed with LMPA layer and applied voltage, the gathering Joule heat melt the LMPA and form the double line structure and the OLED package is sealed in the same time. In this research, the double-line encapsulating structure of LMPA and epoxy on the PI film is manufactured for the flexible OLED encapsulation, and in this process it is investigated whether the encapsulation satisfies the requirement of WVTR and OTR for the flexible OLED.

Keywords: encapsulation, flexible, low melting point alloy, OLED

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Authors: Maria Nejjari, Michel Cloutier, Guylaine Talbot, Martin Lanthier

Abstract:

The fluorescence in situ hybridization (FISH) is a staining technique that allows the identification, detection and quantification of microorganisms without prior cultivation by means of epifluorescence and confocal laser scanning microscopy (CLSM). Oligonucleotide probes have been used to detect bacteria and archaea that colonize the cattle and swine digestive systems. These bacterial strains have been obtained from fecal samples issued from cattle manure and swine slurry. The collection of these samples has been done at 3 different pit’s levels A, B and C with same height. Two collection depth levels have been taken in consideration, one collection level just under the pit’s surface and the second one at the bottom of the pit. Cells were fixed and FISH was performed using oligonucleotides of 15 to 25 nucleotides of length associated with a fluorescent molecule Cy3 or Cy5. The double hybridization using Cy3 probe targeting bacteria (Cy3-EUB338-I) along with a Cy5 probe targeting Archaea (Gy5-ARCH915) gave a better signal. The CLSM images show that there are more bacteria than archaea in swine slurry. However, the choice of fluorescent probes is critical for getting the double hybridization and a unique signature for each microorganism. FISH technique is an easy way to detect pathogens like E. coli O157, Listeria, Salmonella that easily contaminate water streams, agricultural soils and, consequently, food products and endanger human health.

Keywords: archaea, bacteria, detection, FISH, fluorescence

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Authors: Pranitha Janapatla, Venkata Suman Gontla

Abstract:

The present paper investigates the effects of MHD, double dispersion and variable properties on mixed convection flow from a vertical surface in a power-law fluid saturated non-Darcy porous medium. The governing non-linear partial differential equations are reduced to a system of ordinary differential equations by using a special form of Lie group transformations viz. scaling group of transformations. These ordinary differential equations are solved numerically by using Shooting technique. The influence of relevant parameters on the non-dimensional velocity, temperature, concentration for pseudo-plastic fluid, Newtonian and dilatant fluid are discussed and displayed graphically. The behavior of heat and mass transfer coefficients are shown in tabular form. Comparisons with the published works are performed and are found to be in very good agreement. From this analysis, it is observed that an increase in variable viscosity causes to decrease in velocity profile and increase the temperature and concentration distributions. It is also concluded that increase in the solutal dispersion decreases the velocity and concentration but raises the temperature profile.

Keywords: power-law fluid, thermal conductivity, thermal dispersion, solutal dispersion, variable viscosity

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