Search results for: simulation techniques

Authors: Joseph C. Chen

Abstract:

Machine vision system provides automatic inspection to reduce manufacturing costs considerably. However, only a few principles have been found to optimize machine vision system and help it function more accurately in industrial practice. Mostly, there were complicated and impractical design techniques to improve the accuracy of machine vision system. This paper discusses implementing the Six Sigma Define, Measure, Analyze, Improve, and Control (DMAIC) approach to optimize the setup parameters of machine vision system when it is used as a direct measurement technique. This research follows a case study showing how Six Sigma DMAIC methodology has been put into use.

Keywords: DMAIC, machine vision system, process capability, Taguchi Parameter Design

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Authors: I. L. Kim, J. Y. Lee, A. K. Tekile

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In consequence of the very high urbanization rate of Korea, the number of traffic noise damages in areas congested with population and facilities is steadily increasing. The current environmental noise levels data in major cities of the country show that the noise levels exceed the standards set for both day and night times. This research was about comparative analysis in search for optimal soundproof panel shape and design factor that can minimize sound reflection noise. In addition to the normal flat-type panel shape, the reflection noise reduction of swelling-type, combined swelling and curved-type, and screen-type were evaluated. The noise source model Nord 2000, which often provides abundant information compared to models for the similar purpose, was used in the study to determine the overall noise level. Based on vehicle categorization in Korea, the noise levels for varying frequency from different heights of the sound source (directivity heights of Harmonize model) have been calculated for simulation. Each simulation has been made using the ray-tracing method. The noise level has also been calculated using the noise prediction program called SoundPlan 7.2, for comparison. The noise level prediction was made at 15m (R1), 30 m (R2) and at middle of the road, 2m (R3) receiving the point. By designing the noise barriers by shape and running the prediction program by inserting the noise source on the 2nd lane to the noise barrier side, among the 6 lanes considered, the reflection noise slightly decreased or increased in all noise barriers. At R1, especially in the cases of the screen-type noise barriers, there was no reduction effect predicted in all conditions. However, the swelling-type showed a decrease of 0.7~1.2 dB at R1, performing the best reduction effect among the tested noise barriers. Compared to other forms of noise barriers, the swelling-type was thought to be the most suitable for reducing the reflection noise; however, since a slight increase was predicted at R2, further research based on a more sophisticated categorization of related design factors is necessary. Moreover, as swellings are difficult to produce and the size of the modules are smaller than other panels, it is challenging to install swelling-type noise barriers. If these problems are solved, its applicable region will not be limited to other types of noise barriers. Hence, when a swelling-type noise barrier is installed at a downtown region where the amount of traffic is increasing every day, it will both secure visibility through the transparent walls and diminish any noise pollution due to the reflection. Moreover, when decorated with shapes and design, noise barriers will achieve a visual attraction than a flat-type one and thus will alleviate any psychological hardships related to noise, other than the unique physical soundproofing functions of the soundproof panels.

Keywords: reflection noise, shaped noise barriers, sound proof panel, traffic noise

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Authors: Eui-Hak Lee, Jae-Hyun Ro, Hyoung-Kyu Song

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In internet of things (IoT) system, the communication scheme with reliability and low power is required to connect a terminal. Cooperative communication can achieve reliability and lower power than multiple-input multiple-output (MIMO) system. Cooperative communication increases the reliability with low power, but decreases a throughput. It has a weak point that the communication throughput is decreased. In this paper, a novel scheme is proposed to increase the communication throughput. The novel scheme is a transmission structure that increases transmission rate. And a decoding scheme according to the novel transmission structure is proposed. Simulation results show that the proposed scheme increases the throughput without bit error rate (BER) performance degradation.

Keywords: cooperative communication, IoT, STBC, transmission rate

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Authors: Masoumeh Mofarrah, Amir NahanMoghadam

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Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise, and improve EOR methods and their application. Recently, Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic, and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization infeasible and effective way.

Keywords: artificial intelligence, EOR, neural networks, expert systems

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Authors: Jung Hyun Kim, Gyo Woo Lee

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In this study, the enhancement of the heat release performance of an extruded-type heat sink to prepare the large-capacity solar inverter thru the flow holes in the base plate near the heat sources was investigated. Optimal location and number of the holes in the baseplate were determined by using a commercial computation program. The heat release performance of the shape-modified heat sink was measured experimentally and compared with that of the simulation. The heat sink with 12 flow holes in the 18-mm-thick base plate has a 8.1% wider heat transfer area, a 2.5% more mass flow of air, and a 2.7% higher heat release rate than those of the original heat sink. Also, the surface temperature of the base plate was lowered 1.5°C by the holes.

Keywords: heat sink, forced convection, heat transfer, performance evaluation, flow holes

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Authors: Ibrahim A. Aref, Tarek El-Mihoub, Khadiga Ben Musa

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This paper presents Carrier Sense Multiple Access (CSMA) communication model based on SoC design methodology. Such model can be used to support the modelling of the complex wireless communication systems, therefore use of such communication model is an important technique in the construction of high performance communication. SystemC has been chosen because it provides a homogeneous design flow for complex designs (i.e. SoC and IP based design). We use a swarm system to validate CSMA designed model and to show how advantages of incorporating communication early in the design process. The wireless communication created through the modeling of CSMA protocol that can be used to achieve communication between all the agents and to coordinate access to the shared medium (channel).

Keywords: systemC, modelling, simulation, CSMA

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Authors: Erin M. Durke, Monica L. McEntee, Meilu He, Suresh Dhaniyala

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Aerosols are one of the most important and significant surfaces in the atmosphere. They can influence weather, absorption, and reflection of light, and reactivity of atmospheric constituents. A notable feature of aerosol particles is the presence of a surface charge, a characteristic imparted via the aerosolization process. The existence of charge can complicate the interrogation of aerosol particles, so many researchers remove or neutralize aerosol particles before characterization. However, the charge is present in real-world samples, and likely has an effect on the physical and chemical properties of an aerosolized material. In our studies, we aerosolized different materials in an attempt to characterize the charge imparted via the aerosolization process and determine what impact it has on the aerosolized materials’ properties. The metal oxides, TiO₂ and SiO₂, were aerosolized expulsively and then characterized, using several different techniques, in an effort to determine the surface charge imparted upon the particles via the aerosolization process. Particle charge distribution measurements were conducted via the employment of a custom scanning mobility particle sizer. The results of the charge distribution measurements indicated that expulsive generation of 0.2 µm SiO₂ particles produced aerosols with upwards of 30+ charges on the surface of the particle. Determination of the degree of surface charging led to the use of non-traditional techniques to explore the impact of additional surface charge on the overall reactivity of the metal oxides, specifically TiO₂. TiO₂ was aerosolized, again expulsively, onto a gold-coated tungsten mesh, which was then evaluated with transmission infrared spectroscopy in an ultra-high vacuum environment. The TiO₂ aerosols were exposed to O₂, H₂, and CO, respectively. Exposure to O₂ resulted in a decrease in the overall baseline of the aerosol spectrum, suggesting O₂ removed some of the surface charge imparted during aerosolization. Upon exposure to H₂, there was no observable rise in the baseline of the IR spectrum, as is typically seen for TiO₂, due to the population of electrons into the shallow trapped states and subsequent promotion of the electrons into the conduction band. This result suggests that the additional charge imparted via aerosolization fills the trapped states, therefore no rise is seen upon exposure to H₂. Dosing the TiO₂ aerosols with CO showed no adsorption of CO on the surface, even at lower temperatures (~100 K), indicating the additional charge on the aerosol surface prevents the CO molecules from adsorbing to the TiO₂ surface. The results observed during exposure suggest that the additional charge imparted via aerosolization impacts the interaction with each probe gas.

Keywords: aerosols, charge, reactivity, infrared

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Authors: Mohammed H. Rasheed, Hussein Nadhem Fadhel, Mohammed M. Siddeq

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In this paper we suggested image quality measuring metrics tools that can provide an accurate and close to the perceived quality sense of the tested images. Such tools give metrics that can be used to compare the performance of image compression algorithms. In this paper, two new metrics to measure the quality of decompressed images are proposed. The metric measurement based on combined data (CD) between an originals and decompressed images. Compared with other e.g., PSNR and RMSE, the proposed metrics gives values with the closest reflection of image quality perception by the human eye.

Keywords: RMSE, PSNR, image quality metrics, image compression

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Authors: A. Keshavarz, Z. Roosta

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In this paper, propagation of cos-Gaussian beam in strongly nonlocal nonlinear media has been stimulated by using paraxial group transformation. At first, cos-Gaussian beam, nonlocal nonlinear media, critical power, transfer matrix, and paraxial group transformation are introduced. Then, the propagation of the cos-Gaussian beam in strongly nonlocal nonlinear media is simulated. Results show that beam propagation has periodic structure during self-focusing effect in this case. However, this simple method can be used for investigation of propagation of kinds of beams in ABCD optical media.

Keywords: paraxial group transformation, nonlocal nonlinear media, cos-Gaussian beam, ABCD law

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Authors: Priti Kumari, Tricha Anjali

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Body Area Networks (BANs) have emerged as the most promising technology for pervasive health care applications. Since they facilitate communication of very sensitive health data, information leakage in such networks can put human life at risk, and hence security inside BANs is a critical issue. Safe distribution and periodic refreshment of cryptographic keys are needed to ensure the highest level of security. In this paper, we focus on the key distribution techniques and how they are categorized for BAN. The state-of-art pre-shared key distribution algorithms are surveyed. Possible attacks on algorithms are demonstrated with examples.

Keywords: attacks, body area network, key distribution, key refreshment, pre-shared keys

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Authors: Pandurang Balwant, Ashutosh Mishra, Jyothi V., Abhay Soni, Padmakar C., Rafat Quamar, Ramesh J.

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The sea water intrusion in the coastal aquifers has become one of the major environmental concerns. Although, it is a natural phenomenon but, it can be induced with anthropogenic activities like excessive exploitation of groundwater, seacoast mining, etc. The geological and hydrogeological conditions including groundwater heads and groundwater pumping pattern in the coastal areas also influence the magnitude of seawater intrusion. However, this problem can be remediated by taking some preventive measures like rainwater harvesting and artificial recharge. The present study is an attempt to identify suitable sites for rainwater harvesting in salt intrusion affected area near coastal aquifer of Jafrabad town, Amreli district, Gujrat, India. The physico-chemical water quality results show that out of 25 groundwater samples collected from the study area most of samples were found to contain high concentration of Total Dissolved Solids (TDS) with major fractions of Na and Cl ions. The Cl/HCO3 ratio was also found greater than 1 which indicates the salt water contamination in the study area. The geophysical survey was conducted at nine sites within the study area to explore the extent of contamination of sea water. From the inverted resistivity sections, low resistivity zone (<3 Ohm m) associated with seawater contamination were demarcated in North block pit and south block pit of NCJW mines, Mitiyala village Lotpur and Lunsapur village at the depth of 33 m, 12 m, 40 m, 37 m, 24 m respectively. Geospatial techniques in combination of Analytical Hierarchy Process (AHP) considering hydrogeological factors, geographical features, drainage pattern, water quality and geophysical results for the study area were exploited to identify potential zones for the Rainwater Harvesting. Rainwater harvesting suitability model was developed in ArcGIS 10.1 software and Rainwater harvesting suitability map for the study area was generated. AHP in combination of the weighted overlay analysis is an appropriate method to identify rainwater harvesting potential zones. The suitability map can be further utilized as a guidance map for the development of rainwater harvesting infrastructures in the study area for either artificial groundwater recharge facilities or for direct use of harvested rainwater.

Keywords: analytical hierarchy process, groundwater quality, rainwater harvesting, seawater intrusion

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Authors: Elabed Saud

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This paper introduces the new ability of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neutrals are training by Levenberg-Marquardt back-propagation algorithm. ANNs are the standard three layers feed-forward neural network with sigmoid activation functions in the input and hidden layers and purelin in the output layer. Simulation results are presented to demonstrate the effectiveness of this neural and advantage of the control system DC motor with ANNs in comparison with the conventional scheme without ANNs.

Keywords: Artificial Neural Network (ANNs), excited DC motor, convenional controller, speed Controller

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Authors: D. B. Gohil

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Closed die forging is a very complex process, and measurement of actual forces for real material is difficult and time consuming. Hence, the modelling technique has taken the advantage of carrying out the experimentation with the proper model material which needs lesser forces and relatively low temperature. The results of experiments on the model material then may be correlated with the actual material by using the theory of similarity. There are several methods available to resolve the complexity involved in the closed die forging process. Finite Element Method (FEM) and Finite Difference Method (FDM) are relatively difficult as compared to the slab method. The slab method is very popular and very widely used by the people working on shop floor because it is relatively easy to apply and reasonably accurate for most of the common forging load requirement computations.

Keywords: experimentation, forging, process modeling, strain distribution

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Authors: Irati Barandiaran, Xabier Velasco-Iza, Galder Kortaberria

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Hybrid inorganic/organic nanostructured materials based on block copolymers are of considerable interest in the field of Nanotechnology, taking into account that these nanocomposites combine the properties of polymer matrix and the unique properties of the added nanoparticles. The use of block copolymers as templates offers the opportunity to control the size and the distribution of inorganic nanoparticles. This research is focused on the surface modification of inorganic nanoparticles to reach a good interface between nanoparticles and polymer matrices which hinders the nanoparticle aggregation. The aim of this work is to obtain a good and selective dispersion of Fe3O4 magnetic nanoparticles into different types of block copolymers such us, poly(styrene-b-methyl methacrylate) (PS-b-PMMA), poly(styrene-b-ε-caprolactone) (PS-b-PCL) poly(isoprene-b-methyl methacrylate) (PI-b-PMMA) or poly(styrene-b-butadiene-b-methyl methacrylate) (SBM) by using different grafting strategies. Fe3O4 magnetic nanoparticles have been surface-modified with polymer or block copolymer brushes following different grafting methods (grafting to, grafting from and grafting through) to achieve a selective location of nanoparticles into desired domains of the block copolymers. Morphology of fabricated hybrid nanocomposites was studied by means of atomic force microscopy (AFM) and with the aim to reach well-ordered nanostructured composites different annealing methods were used. Additionally, nanoparticle amount has been also varied in order to investigate the effect of the nanoparticle content in the morphology of the block copolymer. Nowadays different characterization methods were using in order to investigate magnetic properties of nanometer-scale electronic devices. Particularly, two different techniques have been used with the aim of characterizing synthesized nanocomposites. First, magnetic force microscopy (MFM) was used to investigate qualitatively the magnetic properties taking into account that this technique allows distinguishing magnetic domains on the sample surface. On the other hand, magnetic characterization by vibrating sample magnetometer and superconducting quantum interference device. This technique demonstrated that magnetic properties of nanoparticles have been transferred to the nanocomposites, exhibiting superparamagnetic behavior similar to that of the maghemite nanoparticles at room temperature. Obtained advanced nanostructured materials could found possible applications in the field of dye-sensitized solar cells and electronic nanodevices.

Keywords: atomic force microscopy, block copolymers, grafting techniques, iron oxide nanoparticles

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Authors: R. Nasrin, M. Ferdows

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Among the renewable energy sources, photovoltaic (PV) is a high potential, effective, and sustainable system. Irradiation intensity from 200 W/m2 to 1000 W/m2 has been considered to observe the performance of PV module. Generally, this module converts only about 15% - 20% of incident irradiation into electrical energy and the rest part is converted into heat energy. Finite element method has been used to solve the problem numerically. Simulation has been performed by considering the ambient temperature 30°C. Higher irradiation increase solar cell temperature and electrical power. The electrical efficiency of PV module decreases with the variation of solar radiation. The efficiency of PV module can be increased if cell temperature is reduced. Thus the effect of irradiation is significant to enhance the efficiency of PV module if the solar cell temperature is kept at a certain level.

Keywords: PV module, solar radiation, efficiency, cell temperature

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Authors: M. A. Sohaly, M. A. Elfouly

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Parkinson's disease (PD) is a heterogeneous movement disorder that often appears in the elderly. PD is induced by a loss of dopamine secretion. Some drugs increase the secretion of dopamine. In this paper, we will simply study the stability of PD models as a nonlinear delay differential equation. After a period of taking drugs, these act as positive feedback and increase the tremors of patients, and then, the differential equation has positive coefficients and the system is unstable under these conditions. We will present a set of suggested modifications to make the system more compatible with the biodynamic system. When giving a set of numerical examples, this research paper is concerned with the mathematical analysis, and no clinical data have been used.

Keywords: Parkinson's disease, stability, simulation, two delay differential equation

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Authors: C. C .D. Kulathilake, M. Jayatilake, T. Takahashi

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The myocardium is composed of specialized muscle which relies mainly on fatty acid and sugar metabolism and it is widely contribute to the heart functioning. The changes of the cardiac energy-producing system during heart failure have been proved using autoradiography techniques. This study focused on evaluating sugar and fatty acid metabolism in myocardium as cardiac energy getting system using heart-accumulated radiopharmaceuticals. Two sets of autoradiographs of heart cross sections of Lewis male rats were analyzed and the time- accumulation curve obtained with use of the MATLAB image processing software to evaluate fatty acid and sugar metabolic functions.

Keywords: autoradiographs, fatty acid, radiopharmaceuticals, sugar

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Authors: Svebor Secak

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This four-year artistic research project hosted by the University of New England, Australia has set the goal to experiment with non-conventional ways of presenting a language-based narrative in dance using insights of recent theoretical writing on performance, addressing the research question: How to transform an archival recording of a neoclassical ballet performance into a new artistic dance video by implementing postmodern philosophical concepts? The Creative Practice component takes the form of a dance video Hamlet Revisited which is a reworking of the archival recording of the neoclassical ballet Hamlet, augmented by new material, produced using resources, technicians and dancers of the Croatian National Theatre in Zagreb. The methodology for the creation of Hamlet Revisited consisted of extensive field and desk research after which three dancers were shown the recording of original Hamlet and then created their artistic response to it based on their reception and appreciation of it. The dancers responded differently, based upon their diverse dancing backgrounds and life experiences. They began in the role of the audience observing video of the original ballet and transformed into the role of the choreographer-performer. Their newly recorded material was edited and juxtaposed with the archival recording of Hamlet and other relevant footage, allowing for postmodern features such as aleatoric content, synchronicity, eclecticism and serendipity, that way establishing communication on a receptive reader-response basis, thus blending the roles of the choreographer, performer and spectator, creating an original work of art whose significance lies in the relationship and communication between styles, old and new choreographic approaches, artists and audiences and the transformation of their traditional roles and relationships. In editing and collating, the following techniques were used with the intention to avoid the singular narrative: fragmentation, repetition, reverse-motion, multiplication of images, split screen, overlaying X-rays, image scratching, slow-motion, freeze-frame and simultaneity. Key postmodern concepts considered were: deconstruction, diffuse authorship, supplementation, simulacrum, self-reflexivity, questioning the role of the author, intertextuality and incredulity toward grand narratives - departing from the original story, thus personalising its ontological themes. From a broad brush of diverse concepts and techniques applied in an almost prescriptive manner, the project focuses on intertextuality that proves to be valid on at least two levels. The first is the possibility of a more objective analysis in combination with a semiotic structuralist approach moving from strict relationships between signs to a multiplication of signifiers, considering the dance text as an open construction, containing the elusive and enigmatic quality of art that leaves the interpretive position open. The second one is the creation of the new work where the author functions as the editor, aware and conscious of the interplay of disparate texts and their sources which co-act in the mind during the creative process. It is argued here that the eclectic combination of the old and new material through constant oscillations of different discourses upon the same topic resulted in a transmodern integrationist recent work of art that might be applied as a model for reconsidering existing choreographic creations.

Keywords: Ballet Hamlet, intertextuality, transformation, transmodern dance video

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Authors: Natalia Efremova, Sergey Tarasenko

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We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

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Authors: Saurabh Rawat, Anushree Sah

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K Maps are generally and ideally, thought to be simplest form for obtaining solution of Boolean equations. Cubical Representation of Boolean equations is an alternate pick to incur a solution, otherwise to be meted out with Truth Tables, Boolean Laws, and different traits of Karnaugh Maps. Largest possible k- cubes that exist for a given function are equivalent to its prime implicants. A technique of minimization of Logic functions is tried to be achieved through cubical methods. The main purpose is to make aware and utilise the advantages of cubical techniques in minimization of Logic functions. All this is done with an aim to achieve minimal cost solution.r

Keywords: K-maps, don’t care conditions, Boolean equations, cubes

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Authors: Jared Beard, Ali Baheri

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As autonomous systems become more prominent in society, ensuring their safe application becomes increasingly important. This is clearly demonstrated with autonomous cars traveling through a crowded city or robots traversing a warehouse with heavy equipment. Human environments can be complex, having high dimensional state and action spaces. This gives rise to two problems. One being that analytic solutions may not be possible. The other is that in simulation based approaches, searching the entirety of the problem space could be computationally intractable, ruling out formal methods. To overcome this, approximate solutions may seek to find failures or estimate their likelihood of occurrence. One such approach is adaptive stress testing (AST) which uses reinforcement learning to induce failures in the system. The premise of which is that a learned model can be used to help find new failure scenarios, making better use of simulations. In spite of these failures AST fails to find particularly sparse failures and can be inclined to find similar solutions to those found previously. To help overcome this, multi-fidelity learning can be used to alleviate this overuse of information. That is, information in lower fidelity can simulations can be used to build up samples less expensively, and more effectively cover the solution space to find a broader set of failures. Recent work in multi-fidelity learning has passed information bidirectionally using “knows what it knows” (KWIK) reinforcement learners to minimize the number of samples in high fidelity simulators (thereby reducing computation time and load). The contribution of this work, then, is development of the bidirectional multi-fidelity AST framework. Such an algorithm, uses multi-fidelity KWIK learners in an adversarial context to find failure modes. Thus far, a KWIK learner has been used to train an adversary in a grid world to prevent an agent from reaching its goal; thus demonstrating the utility of KWIK learners in an AST framework. The next step is implementation of the bidirectional multi-fidelity AST framework described. Testing will be conducted in a grid world containing an agent attempting to reach a goal position and adversary tasked with intercepting the agent as demonstrated previously. Fidelities will be modified by adjusting the size of a time-step, with higher-fidelity effectively allowing for more responsive closed loop feedback. Results will compare the single KWIK AST learner with the multi-fidelity algorithm with respect to number of samples, distinct failure modes found, and relative effect of learning after a number of trials.

Keywords: multi-fidelity reinforcement learning, multi-fidelity simulation, safety validation, falsification

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Authors: Kyoung-il Do, Byung-seok Lee, Hee-guk Chae, Jeong-yun Seo Yong-seo Koo

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In this paper, a Silicon Controlled Rectifier (SCR)-based Electrostatic Discharge (ESD) protection circuit with high holding voltage and high robustness characteristics is proposed. Unlike conventional SCR, the proposed circuit has low trigger voltage and high holding voltage and provides effective ESD protection with latch-up immunity. In addition, the TCAD simulation results show that the proposed circuit has better electrical characteristics than the conventional SCR. A stack technology was used for voltage-specific applications. Consequentially, the proposed circuit has a trigger voltage of 17.60 V and a holding voltage of 3.64 V.

Keywords: ESD, SCR, latch-up, power clamp, holding voltage

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Authors: Kyeong-Ri Ko, Seong Bong Bae, Jang Sik Choi, Sung Bum Pan

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A simple method for testing the posture imbalance of the human body is to check for differences in the bilateral shoulder and pelvic height of the target. In this paper, to check for spinal disorders the authors have studied ways to establish a motion capture system to obtain and express motions of 4-joints, and to acquire data based on this system. The 4 sensors are attached to the both shoulders and pelvis. To verify the established system, the normal and abnormal postures of the targets listening to a lecture were obtained using the established 4-joint based motion capture system. From the results, it was confirmed that the motions taken by the target was identical to the 3-dimensional simulation.

Keywords: inertial sensor, motion capture, motion data acquisition, posture imbalance

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Authors: Ahmed Abbou, Ali Mousmi, Rachid El Akhrif

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This research paper aims to reduce the chattering phenomenon due to control by sliding mode control applied on a wind energy conversion system based on the doubly fed induction generator (DFIG). Our goal is to offset the effect of parametric uncertainties and come as close as possible to the dynamic response solicited by the control law in the ideal case and therefore force the active and reactive power generated by the DFIG to accurately follow the reference values which are provided to it. The simulation results using Matlab / Simulink demonstrate the efficiency and performance of the proposed technique while maintaining the simplicity of control by first order sliding mode.

Keywords: correction of the equivalent command, DFIG, induction machine, sliding mode controller

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Authors: Suruchi Saini, Hitender Kumar Tyagi

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With the rapid progress of the nanotechnology industry, it is becoming increasingly important to have compact semiconductor devices to function and offer the best results at various technology nodes. While performing the scaling of the device, several short-channel effects occur. To minimize these scaling limitations, some device architectures have been developed in the semiconductor industry. FinFET is one of the most promising structures. Also, the double-gate 2D Fin field effect transistor has the benefit of suppressing short channel effects (SCE) and functioning well for less than 14 nm technology nodes. In the present research, the MuGFET simulation tool is used to analyze and explain the electrical behaviour of a double-gate 2D Fin field effect transistor. The drift-diffusion and Poisson equations are solved self-consistently. Various models, such as Fermi-Dirac distribution, bandgap narrowing, carrier scattering, and concentration-dependent mobility models, are used for device simulation. The transfer and output characteristics of the double-gate 2D Fin field effect transistor are determined at 10 nm technology node. The performance parameters are extracted in terms of threshold voltage, trans-conductance, leakage current and current on-off ratio. In this paper, the device performance is analyzed at different structure parameters. The utilization of the Id-Vg curve is a robust technique that holds significant importance in the modeling of transistors, circuit design, optimization of performance, and quality control in electronic devices and integrated circuits for comprehending field-effect transistors. The FinFET structure is optimized to increase the current on-off ratio and transconductance. Through this analysis, the impact of different channel widths, source and drain lengths on the Id-Vg and transconductance is examined. Device performance was affected by the difficulty of maintaining effective gate control over the channel at decreasing feature sizes. For every set of simulations, the device's features are simulated at two different drain voltages, 50 mV and 0.7 V. In low-power and precision applications, the off-state current is a significant factor to consider. Therefore, it is crucial to minimize the off-state current to maximize circuit performance and efficiency. The findings demonstrate that the performance of the current on-off ratio is maximum with the channel width of 3 nm for a gate length of 10 nm, but there is no significant effect of source and drain length on the current on-off ratio. The transconductance value plays a pivotal role in various electronic applications and should be considered carefully. In this research, it is also concluded that the transconductance value of 340 S/m is achieved with the fin width of 3 nm at a gate length of 10 nm and 2380 S/m for the source and drain extension length of 5 nm, respectively.

Keywords: current on-off ratio, FinFET, short-channel effects, transconductance

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Authors: E. Ramprasath, P. Manojkumar, P. Veena

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Proposed paper dealt with the modelling and analysis of induction motor based on the mathematical expression using the graphical programming environment of Laboratory Virtual Instrument Engineering Workbench (LabVIEW). Induction motor modelling with the mathematical expression enables the motor to be simulated with the various required parameters. Owing to the invention of variable speed drives study about the induction motor characteristics became complex.In this simulation motor internal parameter such as stator resistance and reactance, rotor resistance and reactance, phase voltage, frequency and losses will be given as input. By varying the speed of motor corresponding parameters can be obtained they are input power, output power, efficiency, torque induced, slip and current.

Keywords: induction motor, LabVIEW software, modelling and analysi, electrical and mechanical characteristics of motor

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Authors: F. Rahmani, F. Razaghian, A. R. Kashaninia

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This article proposes a new method for application in communication circuit systems that increase efficiency, PAE, output power and gain in the circuit. The proposed method is based on a combination of switching class-E and class-J and has been termed class-EJ. This method was investigated using both theory and simulation to confirm ~72% PAE and output power of > 39 dBm. The combination and design of the proposed power amplifier accrues gain of over 15dB in the 2.9 to 3.5 GHz frequency bandwidth. This circuit was designed using MOSFET and high power transistors. The load- and source-pull method achieved the best input and output networks using lumped elements. The proposed technique was investigated for fundamental and second harmonics having desirable amplitudes for the output signal.

Keywords: power amplifier (PA), high power, class-J and class-E, high efficiency

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Authors: Younghoon Kim, Seoung Bum Kim

Abstract:

One-class classification plays an important role in detecting outlier and abnormality from normal observations. In the previous research, several attempts were made to extend the scope of application of the one-class classification techniques to statistical process control problems. For most previous approaches, such as support vector data description (SVDD) control chart, the design of the control limits is commonly based on the assumption that the proportion of abnormal observations is approximately equal to an expected Type I error rate in Phase I process. Because of the limitation of the one-class classification techniques based on convex optimization, we cannot make the proportion of abnormal observations exactly equal to expected Type I error rate: controlling Type I error rate requires to optimize constraints with integer decision variables, but convex optimization cannot satisfy the requirement. This limitation would be undesirable in theoretical and practical perspective to construct effective control charts. In this work, to address the limitation of previous approaches, we propose the one-class classification algorithm based on the mixed integer programming technique, which can solve problems formulated with continuous and integer decision variables. The proposed method minimizes the radius of a spherically shaped boundary subject to the number of normal data to be equal to a constant value specified by users. By modifying this constant value, users can exactly control the proportion of normal data described by the spherically shaped boundary. Thus, the proportion of abnormal observations can be made theoretically equal to an expected Type I error rate in Phase I process. Moreover, analogous to SVDD, the boundary can be made to describe complex structures by using some kernel functions. New multivariate control chart applying the effectiveness of the algorithm is proposed. This chart uses a monitoring statistic to characterize the degree of being an abnormal point as obtained through the proposed one-class classification. The control limit of the proposed chart is established by the radius of the boundary. The usefulness of the proposed method was demonstrated through experiments with simulated and real process data from a thin film transistor-liquid crystal display.

Keywords: control chart, mixed integer programming, one-class classification, support vector data description

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Authors: Okba Belahssen, Lazhar Torchane, Said Benramache, Abdelouahed Chala

Abstract:

This paper presents corrosion behavior of the plasma-nitrided 32CrMoV13 steel. Different kinds of samples were tested: non-treated, plasma nitrided samples. The structure of layers was determined by X-ray diffraction, while the morphology was observed by scanning electron microscopy (SEM). The corrosion behavior was evaluated by electrochemical techniques (potentiodynamic curves and electrochemical impedance spectroscopy). The corrosion tests were carried out in acid chloride solution (HCl 1M). Experimental results showed that the nitrides ε-Fe2−3N and γ′-Fe4N present in the white layer are nobler than the substrate but may promote, by galvanic effect, a localized corrosion through open porosity. The better corrosion protection was observed for nitrided sample.

Keywords: plasma-nitrided, 32CrMoV13 steel, corrosion, EIS

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Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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