Search results for: point of maximum convergence

Authors: Bhim Singh

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Due to increased pressure from global competitors, manufacturing organizations are switching over to lean philosophies from traditional mass production. Lean manufacturing is a manufacturing philosophy which focuses on elimination of various types of wastes and creates maximum value for the end customers. Lean thinking aims to produce high quality products and services at the lowest possible cost with maximum customer responsiveness. Indian Industry is facing lot of problems in this transformation from traditional mass production to lean production. Through this paper an attempt has been made to identify various lean implementation hurdles in Indian industries with the help of a structured survey. Identified hurdles are grouped with the help of factor analysis and rated by calculating descriptive statistics. To show the effect of lean implementation hurdles a hypothesis “Organizations having higher level of lean implementation hurdles will have poor (negative) performance” has been postulated and tested using correlation matrix between performance parameters of the organizations and identified hurdles. The findings of the paper will be helpful to prepare road map to identify and eradicate the lean implementation hurdles.

Keywords: factor analysis, global competition, lean implementation, lean hurdles

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Authors: Magdalena Twaruzek, Karolina Ropejko

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Mycotoxins are secondary metabolites of molds. Ochratoxin A (OTA) is the most common in the Polish climate. It is produced by fungi of the genera Aspergillus and Penicillium. It is produced as a result of improper food storage. It is present in many products that are consumed both by humans and animals: cereals, wheat gluten, coffee, dried fruit, wine, grape juice, spices, beer, and products based on them. OTA is nephrotoxic, hepatotoxic, potentially carcinogenic, and teratogenic. OTA mainly enters an organism by oral intake. The aim of the study was to detect the presence of OTA in milk, urine, and serum of lactating women. A survey was also conducted regarding the daily diet of women. The research group consisted of 32 lactating women (11 were the donors from the Milk Bank in Toruń, the other 21 were recruited for this study). Results of the analysis showed the occurrence of OTA only in 3 milk samples (9.38%). The minimum level was 0.01 ng/ml, while the maximum 0.018 ng/ml and the mean 0.0013 ng/ml. Twenty-six urine samples (81.25%) were OTA positive, with minimum level 0.013 ng/ml, maximum level 0.117 ng/ml and mean 0.0192 ng/ml. Also, all 32 serum samples (100%) were contaminated by OTA, with a minimum level of 0.099 ng/ml, a maximum level of 2.38 ng/ml, and a mean of 0.4649 ng/ml. In the case of 3 women, OTA was present in all tested body fluids. Based on the results, the following conclusions can be drawn: the breast-milk of women in the study group is slightly contaminated with ochratoxin A. Ten samples of urine contained ochratoxin A above its average content in tested samples. Moreover, serum of 8 women contains ochratoxin A at a level above the average content of this mycotoxin in tested samples. The average ochratoxin A level in serum in the presented studies was 0.4649 ng/ml, which is much lower than the average serum ochratoxin A level established in several countries in the world, i.e., 0.7 ng/ml. Acknowledgment: This study was supported by the Polish Minister of Science and Higher Education under the program 'Regional Initiative of Excellence' in 2019 - 2022 (Grant No. 008/RID/2018/19).

Keywords: breast-milk, urine, serum, contamination, ochratoxin A

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: one-class classification, outlier detection, generative adversary networks, semi-supervised learning

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Authors: Bo Kampmann Walther

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This essay examines the narratives of the Book of Genesis through the lens of game theory, a mathematical framework for analyzing strategic interactions among rational actors. By treating key figures in Genesis as players in a game, this analysis sheds light on their decisions and the resulting consequences. Focusing primarily on the story of Adam and Eve, the essay utilizes concepts such as game state, saddle point, optimal strategy, and Nash equilibrium to explore the dynamics at play and scrutinize the existence of two kinds of game rules in Genesis: one being global and post-Fall oriented, the other being local and relegated to life in the Garden. The serpent's intervention and the subsequent actions of Adam and Eve are modeled as strategic moves, revealing the complexities and shifts in the game state from harmony in Eden to a world marked by toil and mortality post-Fall.

Keywords: game theory, Genesis, strategy, saddle point, nash equilibrium, New Game State

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Authors: Sihem Bazid, Meriem El Kolli, Aicha Medjahed

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Proteins and polysaccharides are the two types of biopolymers most frequently used in the food industry to control the mechanical properties and structural stability and organoleptic properties of the products. The textural and structural properties of these two types of blend polymers depend on their interaction and their ability to form organized structures. From an industrial point of view, a better understanding of mixtures protein / polysaccharide is an important issue since they are already heavily involved in processed food. It is in this context that we have chosen to work on a model system composed of a fibrous protein mixture (gelatin)/anionic polysaccharide (sodium carboxymethylcellulose). Gelatin, one of the most popular biopolymers, is widely used in food, pharmaceutical, cosmetic and photographic applications, because of its unique functional and technological properties. Sodium Carboxymethylcellulose (NaCMC) is an anionic linear polysaccharide derived from cellulose. It is an important industrial polymer with a wide range of applications. The functional properties of this anionic polysaccharide can be modified by the presence of proteins with which it might interact. Another factor may also manage the interaction of protein-polysaccharide mixtures is the triple helix of the gelatin. Its complex synthesis method results in an extracellular assembly containing several levels. Collagen can be in a soluble state or associate into fibrils, which can associate in fiber. Each level corresponds to an organization recognized by the cellular and metabolic system. Gelatin allows this approach, the formation of gelatin gel has triple helical folding of denatured collagen chains, this gel has been the subject of numerous studies, and it is now known that the properties depend only on the rate of triple helices forming the network. Chemical modification of this system is quite controlled. Observe the dynamics of the triple helix may be relevant in understanding the interactions involved in protein-polysaccharides mixtures. Gelatin is central to any industrial process, understand and analyze the molecular dynamics induced by the triple helix in the transitions gelatin, can have great economic importance in all fields and especially the food. The goal is to understand the possible mechanisms involved depending on the nature of the mixtures obtained. From a fundamental point of view, it is clear that the protective effect of NaCMC on gelatin and conformational changes of the α helix are strongly influenced by the nature of the medium. Our goal is to minimize the maximum the α helix structure changes to maintain more stable gelatin and protect against denaturation that occurs during such conversion processes in the food industry. In order to study the nature of interactions and assess the properties of mixtures, polarimetry was used to monitor the optical parameters and to assess the rate of helicity gelatin.

Keywords: gelatin, sodium carboxymethylcellulose, interaction gelatin-NaCMC, the rate of helicity, polarimetry

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Authors: C. Bunsanit

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This paper presents the refinement method for two beams formation of wideband smart antenna. The refinement method for weighting coefficients is based on Fully Spatial Signal Processing by taking Inverse Discrete Fourier Transform (IDFT), and its simulation results are presented using MATLAB. The radiation pattern is created by multiplying the incoming signal with real weights and then summing them together. These real weighting coefficients are computed by IDFT method; however, the range of weight values is relatively wide. Therefore, for reducing this range, the refinement method is used. The radiation pattern concerns with five input parameters to control. These parameters are maximum weighting coefficient, wideband signal, direction of mainbeam, beamwidth, and maximum of minor lobe level. Comparison of the obtained simulation results between using refinement method and taking only IDFT shows that the refinement method works well for wideband two beams formation.

Keywords: fully spatial signal processing, beam forming, refinement method, smart antenna, weighting coefficient, wideband

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Authors: Lami Mohammed, Hussain J. Al Faifi, Abdel Aziz Al Bassam, Osama M. K. Kassem

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The Neoproterozoic basement rocks of the Ar Rayn terrane have been identified as parts of the Eastern Arabian Shield. It focuses on the petrological and finite strain properties to display the tectonic setting of the Al Amar suture for high deformed volcanic and granitoids rocks. The volcanic rocks are classified into two major series: the eastern side cycle, which includes dacite, rhyodacite, rhyolite, and ignimbrites, and the western side cycle, which includes andesite and pyroclastics. Granitoids rocks also contain monzodiorite, tonalite, granodiorite, and alkali-feldspar granite. To evaluate the proportions of shear contributions in penetratively deformed rocks. Asymmetrical porphyroclast and sigmoidal structural markers along the suture's strike, namely the Al Amar, are expected to reveal strain factors. The Rf/phi and Fry techniques are used to characterize quartz and feldspar porphyroclast, biotite, and hornblende grains in Abt schist, high deformed volcanic rock, and granitoids. The findings exposed that these rocks had experienced shape flattening, finite strain accumulation, and overall volume loss. The magnitude of the strain appears to increase across the nappe contacts with neighboring lithologies. Subhorizontal foliation likely developed in tandem with thrusting and nappe stacking, almost parallel to tectonic contacts. The ductile strain accumulation that occurred during thrusting along the Al Amar suture mostly includes a considerable pure shear component. Progressive thrusting by overlaid transpression and oblique convergence is shown by stacked nappes and diagonal stretching lineations along the thrust axes. The subhorizontal lineation might be the result of the suture's most recent activity. The current study's findings contradict the widely accepted model that links orogen-scale structures in the Arabian Shield to oblique convergence with dominant simple shear deformation. A significant pure shear component/crustal thickening increment should have played a significant role in the evolution of the suture and thus in the Shield's overall deformation history. This foliation was primarily generated by thrusting nappes together, showing that nappe stacking was linked to substantial vertical shortening induced by the active Al Amar suture on a massive scale.

Keywords: petrology, finite strain analysis, al amar region, ar-rayn terrane, Arabian shield

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Authors: Auwal Garba, Rabiu Maijama’a, Abdullahi Muhammad Jalam

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Variability in climate has affected the agricultural production all over the globe. This concern has motivated important changes in the field of research during the last decade. Climate variability is believed to have declining effects towards rice production in Nigeria. This study examined climate variability and its impact on rice productivity in Dass Local Government Area, Bauchi State, by employing Linear Trend Model (LTM), analysis of variance (ANOVA) and regression analysis. Annual seasonal data of the climatic variables for temperature (min. and max), rainfall, and solar radiation from 1990 to 2015 were used. Results confirmed that 74.4% of the total variation in rice yield in the study area was explained by the changes in the independent variables. That is to say, temperature (minimum and maximum), rainfall, and solar radiation explained rice yield with 74.4% in the study area. Rising mean maximum temperature would lead to reduction in rice production while moderate increase in mean minimum temperature would be advantageous towards rice production, and the persistent rise in the mean maximum temperature, in the long run, will have more negatively affect rice production in the future. It is, therefore, important to promote agro-meteorological advisory services, which will be useful in farm planning and yield sustainability. Closer collaboration among the meteorologist and agricultural scientist is needed to increase the awareness about the existing database, crop weather models among others, with a view to reaping the full benefits of research on specific problems and sustainable yield management and also there should be a special initiative by the ADPs (State Agricultural Development Programme) towards promoting best agricultural practices that are resilient to climate variability in rice production and yield sustainability.

Keywords: climate variability, impact, productivity, rice

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Authors: Fares Khalfallah, Zakaria Boumerzoug, Selvarajan Rajakumar, Elhadj Raouache

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The ceramic-aluminum bond is strongly present in industrial tools, due to the need to combine the properties of metals, such as ductility, thermal and electrical conductivity, with ceramic properties like high hardness, corrosion and wear resistance. In recent years, some joining techniques have been developed to achieve a good bonding between these materials such as brazing, diffusion bonding, ultrasonic joining and friction welding. In this work, AA1100 aluminum alloy rods were welded with Alumina 99.9 wt% ceramic rods, by friction welding. The effect of friction pressure on mechanical and structural properties of welded joints was studied. The welding was performed by direct friction welding machine. The welding samples were rotated at a constant rotational speed of 900 rpm, friction time of 4 sec, forging strength of 18 MPa, and forging time of 3 sec. Three different friction pressures were applied to 20, 34 and 45 MPa. The three-point bending test and Vickers microhardness measurements were used to evaluate the strength of the joints and investigate the mechanical properties of the welding area. The microstructure of joints was examined by optical microscopy (OM), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The results show that bending strength increased, and then decreased after reaching a maximum value, with increasing friction pressure. The SEM observation shows that the increase in friction pressure led to the appearance of cracks in the microstructure of the interface area, which is decreasing the bending strength of joints.

Keywords: welding of ceramic to aluminum, friction welding, alumina, AA1100 aluminum alloy

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Authors: Zian Cheak Tiu, Harith Ahmad, Sulaiman Wadi Harun

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A simple multi-wavelength passively Q-switched Erbium-doped fiber laser (EDFL) is demonstrated using low cost multi-walled carbon nanotubes (MWCNTs) based saturable absorber (SA), which is prepared using polyvinyl alcohol (PVA) as a host polymer. The multi-wavelength operation is achieved based on nonlinear polarization rotation (NPR) effect by incorporating 50 m long photonic crystal fiber (PCF) in the ring cavity. The EDFL produces a stable multi-wavelength comb spectrum for more than 14 lines with a fixed spacing of 0.48 nm. The laser also demonstrates a stable pulse train with the repetition rate increases from 14.9 kHz to 25.4 kHz as the pump power increases from the threshold power of 69.0 mW to the maximum pump power of 133.8 mW. The minimum pulse width of 4.4 µs was obtained at the maximum pump power of 133.8 mW while the highest energy of 0.74 nJ was obtained at pump power of 69.0 mW.

Keywords: multi-wavelength Q-switched, multi-walled carbon nanotube, photonic crystal fiber

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Authors: M. R. Zaman, M. S. Bari, M. Kajal

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A field experiment was conducted at the Agroforestry and Environment Research Field, Hajee Mohammad Danesh Science and Technology University, Dinajpur during 2013 to investigate the potentiality of three napier fodder varieties under Litchi orchard. The experiment was consisted of 2 factors RCBD with 3 replications. Among the two factors, factor A was two production systems; S1= Litchi + fodder and S2 = Fodder (sole crop); another factor B was three napier varieties: V1= BARI Napier -1 (Bazra), V2= BARI Napier - 2 (Arusha) and V3= BARI Napier -3 (Hybrid). The experimental results revealed that there were significant variation among the varieties in terms of leaf growth and yield. The maximum number of leaf plant -1 was recorded in variety Bazra (V1) whereas the minimum number was recorded in hybrid variety (V3).Significantly the highest (13.75, 14.53 and14.84 tha-1 at 1st, 2nd and 3rd harvest respectively) yield was also recorded in variety Bazra whereas the lowest (5.89, 6.36 and 9.11 tha-1 at 1st, 2nd v and 3rd harvest respectively) yield was in hybrid variety. Again, in case of production systems, there were also significant differences between the two production systems were founded. The maximum number of leaf plant -1 was recorded under Litchi based AGF system (T1) whereas the minimum was recorded in open condition (T2). Similarly, significantly the highest (12.00, 12.35 and 13.31 tha-1 at 1st, 2nd and 3rd harvest respectively) yield of napier was recorded under Litchi based AGF system where as the lowest (9.73, 10.47 and 11.66 tha-1 at 1st, 2nd and 3rd harvest respectively) yield was recorded in open condition i.e. napier in sole cropping. Furthermore, the interaction effect of napier variety and production systems were also gave significant deviation result in terms of growth and yield. The maximum number of leaf plant -1 was recorded under Litchi based AGF systems with Bazra variety whereas the minimum was recorded in open condition with hybrid variety. The highest yield (14.42, 16.14 and 16.15 tha-1 at 1st, 2nd and 3rd harvest respectively) of napier was found under Litchi based AGF systems with Bazra variety. Significantly the lowest (5.33, 5.79 and 8.48 tha-1 at 1st, 2nd and 3rd harvest respectively) yield was found in open condition i.e. sole cropping with hybrid variety. In case of the quality perspective, the highest nutritive value (DM, ASH, CP, CF, EE, and NFE) was found in Bazra (V1) and the lowest value was found in hybrid variety (V3). Therefore, the suitability of napier production under Litchi based AGF system may be ranked as Bazra > Arusha > Hybrid variety. Finally, the economic analysis showed that maximum BCR (5.20) was found in the Litchi based AGF systems over sole cropping (BCR=4.38). From the findings of the taken investigation, it may be concluded that the cultivation of Bazra napier varieties in the floor of Litchi orchard ensures higher revenue to the farmers compared to its sole cropping.

Keywords: potentiality, Litchi, fodder, agroforestry

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Authors: Olusola Ezekiel Abolarin, Gift E. Noah

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This research work considered an innovative procedure to numerically approximate higher-order Initial value problems (IVP) of ordinary differential equations (ODE) using the Legendre polynomial as the basis function. The proposed method is a half-step, self-starting Block integrator employed to approximate fourth and fifth order IVPs without reduction to lower order. The method was developed through a collocation and interpolation approach. The basic properties of the method, such as convergence, consistency and stability, were well investigated. Several test problems were considered, and the results compared favorably with both exact solutions and other existing methods.

Keywords: initial value problem, ordinary differential equation, implicit off-grid block method, collocation, interpolation

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Authors: Aydin Sipahioglu, Gokhan Celik

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Helicopter routing problem (HRP) is finding good tours for helicopter so as to pick up and deliver personnel or material among specified nodes, mutually. It can be encountered in case of being lots of supply and demand points for different commodities and requiring delivering commodities with helicopter. For instance, to deliver personnel or material from shore to oil rig is a good example. In fact, HRP is a branch of vehicle routing problem with pickup and delivery (VRPPD). However, it has additional constraints such that fuel capacity, performance of helicopter in different altitude and temperature, and the number of maximum takeoff and landing allowed. This kind of pickup and delivery problems can be classified into 3 groups, basically. 1-1 (one to one), M-M (many to many) and 1-M-1 (one to many to one). 1-1 means each commodity has only one supply and one demand point. M-M means there can be more than one supply and demand points for each kind of commodity. 1-M-1 means commodities at depot are delivered to demand points and commodities at customers are delivered to depot. In this case helicopter takes off from its own base, complete its tour and return to its own base. In this study, we define 1-M-M-1 type HRP. That means helicopter takes off from its home base, deliver commodities among the nodes as well as between depot and customers and return to its home base. These problems have NP-hard nature. Therefore, obtaining a good solution in a reasonable time is not easy. In this study, a model is offered for 1-M-M-1 type HRP. It is shown on small scale test instances that the model can find the optimal solution.

Keywords: helicopter routing problem, vehicle routing with pickup and delivery, integer programming

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Authors: Hsien-Tsen Wang

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Business Intelligence (BI) has long helped organizations make informed decisions based on data-driven insights and gain competitive advantages in the marketplace. In the past two decades, businesses witnessed not only the dramatically increasing volume and heterogeneity of business data but also the emergence of new technologies, such as Artificial Intelligence (AI), Semantic Web (SW), Cloud Computing, and Big Data. It is plausible that the convergence of these technologies would bring more value out of business data by establishing linked data frameworks and connecting in ways that enable advanced analytics and improved data utilization. In this paper, we first review and summarize current BI applications and methodology. Emerging technologies that can be integrated into BI applications are then discussed. Finally, we conclude with a proposed synergy framework that aims at achieving a more flexible, scalable, and intelligent BI solution.

Keywords: business intelligence, artificial intelligence, semantic web, big data, cloud computing

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Authors: Dražen Cvitanić, Biljana Maljković

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This paper presents models for predicting operating speeds on tangent sections of two-lane rural roads developed on continuous speed data. The data corresponds to 20 drivers of different ages and driving experiences, driving their own cars along an 18 km long section of a state road. The data were first used for determination of maximum operating speeds on tangents and their comparison with speeds in the middle of tangents i.e. speed data used in most of operating speed studies. Analysis of continuous speed data indicated that the spot speed data are not reliable indicators of relevant speeds. After that, operating speed models for tangent sections were developed. There was no significant difference between models developed using speed data in the middle of tangent sections and models developed using maximum operating speeds on tangent sections. All developed models have higher coefficient of determination then models developed on spot speed data. Thus, it can be concluded that the method of measuring has more significant impact on the quality of operating speed model than the location of measurement.

Keywords: operating speed, continuous speed data, tangent sections, spot speed, consistency

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Authors: J. Constanzo, B. Paquette, G. Charest, L. Masson-Côté, M. Guillot

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Targeted and whole-brain irradiation in humans can result in significant side effects causing decreased patient quality of life. To adequately investigate structural and functional alterations after stereotactic radiosurgery, preclinical studies are needed. The first step is to establish a robust standardized method of targeted irradiation on small regions of the rat brain. Eleven euthanized male Fischer rats were imaged in a stereotactic bed, by computed tomographic (CT), to estimate positioning variations regarding to the bregma skull reference point. Using a rat brain atlas and the stereotactic bregma coordinates assessed from CT images, various regions of the brain were delimited and a treatment plan was generated. A dose of 37 Gy at 30% isodose which corresponds to 100 Gy in 100% of the target volume (X = 98.1; Y = 109.1; Z = 100.0) was set by Leksell Gamma Plan using sectors number 4, 5, 7, and 8 of the Gamma Knife unit with the 4-mm diameter collimators. Effects of positioning accuracy of the rat brain on the dose deposition were simulated by Gamma Plan and validated with dosimetric measurements. Our results showed that 90% of the target volume received 110 ± 4.7 Gy and the maximum of deposited dose was 124 ± 0.6 Gy, which corresponds to an excellent relative standard deviation of 0.5%. This dose deposition calculated with the Gamma Plan was validated with the dosimetric films resulting in a dose-profile agreement within 2%, both in X- and Z-axis,. Our results demonstrate the feasibility to standardize the irradiation procedure of a small volume in the rat brain using a Gamma Knife.

Keywords: brain irradiation, dosimetry, gamma knife, small-animal irradiation, stereotactic radiosurgery (SRS)

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Authors: Karima Bourenane, Aissa Keffous

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In this paper, we present an experimental method on the etching reaction of p-type 6H-SiC, etching that was carried out in HF/K₂Cr₂O₇ solutions. The morphology of the etched surface was examined with varying K₂Cr₂O₇ concentrations, etching time and temperature solution. The surfaces of the etched samples were analyzed using Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR) and Photoluminescence. The surface morphology of samples etched in HF/K₂Cr₂O₇ is shown to depend on the solution composition and bath temperature. The investigation of the HF/K₂Cr₂O₇ solutions on 6H-SiC surface shows that as K₂Cr₂O₇ concentration increases, the etch rate increases to reach a maximum value at about 0.75 M and then decreases. Similar behavior has been observed when the temperature of the solution is increased. The maximum etch rate is found for 80 °C. Taking into account the result, a polishing etching solution of 6H-SiC has been developed. In addition, the result is very interesting when, to date, no chemical polishing solution has been developed on silicon carbide (SiC). Finally, we have proposed a dissolution mechanism of the silicon carbide in HF/K₂Cr₂O₇ solutions.

Keywords: silicon carbide, dissolution, Chemical etching, mechanism

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Authors: Mohamed Raouf Benmakrelouf, Joseph Rynkiewicz

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Targeted maximum likelihood estimation (TMLE) is well-established method for causal effect estimation with desirable statistical properties. TMLE is a doubly robust maximum likelihood based approach that includes a secondary targeting step that optimizes the target statistical parameter. A causal interpretation of the statistical parameter requires assumptions of the Rubin causal framework. The causal effect of binary variable, E, on outcomes, Y, is defined in terms of comparisons between two potential outcomes as E[YE=1 − YE=0]. Our aim in this paper is to present an adaptation of TMLE methodology to estimate the causal effect of a non-binary categorical variable, providing a large application. We propose coding on the initial data in order to operate a binarization of the interest variable. For each category, we get a transformation of the non-binary interest variable into a binary variable, taking value 1 to indicate the presence of category (or group of categories) for an individual, 0 otherwise. Such a dummy variable makes it possible to have a pair of potential outcomes and oppose a category (or a group of categories) to another category (or a group of categories). Let E be a non-binary interest variable. We propose a complete disjunctive coding of our variable E. We transform the initial variable to obtain a set of binary vectors (dummy variables), E = (Ee : e ∈ {1, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when its category is not present, and the value of 1 when its category is present, which allows to compute a pairwise-TMLE comparing difference in the outcome between one category and all remaining categories. In order to illustrate the application of our strategy, first, we present the implementation of TMLE to estimate the causal effect of non-binary variable on outcome using simulated data. Secondly, we apply our TMLE adaptation to survey data from the French Political Barometer (CEVIPOF), to estimate the causal effect of education level (A five-level variable) on a potential vote in favor of the French extreme right candidate Jean-Marie Le Pen. Counterfactual reasoning requires us to consider some causal questions (additional causal assumptions). Leading to different coding of E, as a set of binary vectors, E = (Ee : e ∈ {2, ..., |E|}), where each vector (variable), Ee, takes the value of 0 when the first category (reference category) is present, and the value of 1 when its category is present, which allows to apply a pairwise-TMLE comparing difference in the outcome between the first level (fixed) and each remaining level. We confirmed that the increase in the level of education decreases the voting rate for the extreme right party.

Keywords: statistical inference, causal inference, super learning, targeted maximum likelihood estimation

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: Hao Chen, Bo Guo, Ping Jiang

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Residual life (RL) estimation based on multi-phase nonlinear Wiener process was studied in this paper, which is significant for complicated products with small samples. Firstly, nonlinear Wiener model with random parameter was introduced and multi-phase nonlinear Wiener model was proposed to model degradation process of products that were nonlinear and separated into different phases. Then the multi-phase RL probability density function based on the presented model was derived approximately in a closed form and parameters estimation was achieved with the method of maximum likelihood estimation (MLE). Finally, the method was applied to estimate the RL of high voltage plus capacitor. Compared with the other three different models by log-likelihood function (Log-LF) and Akaike information criterion (AIC), the results show that the proposed degradation model can capture degradation process of high voltage plus capacitors in a better way and provide a more reliable result.

Keywords: multi-phase nonlinear wiener process, residual life estimation, maximum likelihood estimation, high voltage plus capacitor

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Authors: Wei Zhao, Yuxuan Yao, Hao Chen

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In order to find out the mechanical properties and failure behavior of lithium-ion batteries, drop hammer impact experiments and finite element simulations are carried out on batteries with different packed angles. Firstly, a drop hammer impact experiment system, which is based on the DHR-1808 drop hammer and oscilloscope, is established, and then a drop test of individual batteries and packed angles of 180 ° and 120 ° are carried out. The image of battery deformation, force-time curve and voltage-time curve are recorded. Secondly, finite element models of individual batteries and two packed angles are established, and the results of the test and simulation are compared. Finally, the mechanical characteristics and failure behavior of lithium-ion battery modules with the packed arrangement of 6 * 6 and packing angles of 180 °, 120 °, 90 ° and 60 ° are analyzed under the same velocity with different battery packing angles, and the same impact energy with different impact velocity and different packing angles. The result shows that the individual battery is destroyed completely in the drop hammer impact test with an initial impact velocity of 3m/s and drop height of 459mm, and the voltage drops to close to 0V when the test ends. The voltage drops to 12V when packed angle of 180°, and 3.6V when packed angle of 120°. It is found that the trend of the force-time curve between simulation and experiment is generally consistent. The difference in maximum peak value is 3.9kN for a packing angle of 180° and 1.3kN for a packing angle of 120°. Under the same impact velocity and impact energy, the strain rate of the battery module with a packing angle of 180° is the lowest, and the maximum stress can reach 26.7MPa with no battery short-circuited. The research under our experiment and simulation shows that the lithium-ion battery module with a packing angle of 180 ° is the least likely to be damaged, which can sustain the maximum stress under the same impact load.

Keywords: battery module, finite element simulation, power battery, packing angle

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Authors: Somnath Karmakar, S. Chakraverty

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This work investigates the vibration of nonhomogeneous Timoshenko nanobeam resting on the Winkler-Pasternak foundation. Eringen’s nonlocal theory has been used to investigate small-scale effects. The Differential Quadrature method is used to obtain the frequency parameters with various classical boundary conditions. The nonhomogeneous beam model has been considered, where Young’s modulus and density of the beam material vary linearly and quadratically. Convergence of frequency parameters is also discussed. The influence of mechanical properties and scaling parameters on vibration frequencies are investigated for different boundary conditions.

Keywords: Timoshenko beam, Eringen's nonlocal theory, differential quadrature method, nonhomogeneous nanobeam

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Authors: Xiaodong Gao, Pingchuan Dong, Qichao Gao

Abstract:

There has been lots of published work focused on asphaltene deposited on the smooth pipe under steady conditions, while particle deposition on the blockage wellbores under transient conditions has not been well elucidated. This work attempts to predict the deposition rate of asphaltene particles in blockage tube through CFD simulation. The Euler-Lagrange equation has been applied during the flow of crude oil and asphaltene particles. The net gravitational force, virtual mass, pressure gradient, saffman lift, and drag forces are incorporated in the simulations process. Validation of CFD simulation results is compared to the benchmark experiments from the previous literature. Furthermore, the effect of blockage location, blockage length, and blockage thickness on deposition rate are also analyzed. The simulation results indicate that the maximum deposition rate of asphaltene occurs in the blocked tube section, and the greater the deposition thickness, the greater the deposition rate. Moreover, the deposition amount and maximum deposition rate along the length of the tube have the same trend. Results of this study are in the ability to better understand the deposition of asphaltene particles in production and help achieve to deal with the asphaltene challenges.

Keywords: asphaltene deposition rate, blockage length, blockage thickness, blockage diameter, transient condition

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Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

Abstract:

Carefully scheduling the operations of pumps can be resulted to significant energy savings. Schedules can be defined either implicit, in terms of other elements of the network such as tank levels, or explicit by specifying the time during which each pump is on/off. In this study, two new explicit representations based on time-controlled triggers were analyzed, where the maximum number of pump switches was established beforehand, and the schedule may contain fewer switches than the maximum. The optimal operation of pumping stations was determined using a Jumping Particle Swarm Optimization (JPSO) algorithm to achieve the minimum energy cost. The model integrates JPSO optimizer and EPANET hydraulic network solver. The optimal pump operation schedule of VanZyl water distribution system was determined using the proposed model and compared with those from Genetic and Ant Colony algorithms. The results indicate that the proposed model utilizing the JPSP algorithm outperformed the others and is a versatile management model for the operation of real-world water distribution system.

Keywords: JPSO, operation, optimization, water distribution system

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Authors: Taylan Kabbani, Ekrem Duman

Abstract:

The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

Procedia PDF Downloads 178

Authors: A. O. Glazkov, A. S. Krylova, G. G. Nadareishvili, A. S. Terenchenko, S. I. Yudin

Abstract:

The topic of the presented materials concerns the design of the exhaust system for a certain internal combustion engine. The exhaust system can be divided into two parts. The first is the engine exhaust manifold, turbocharger, and catalytic converters, which are called “hot part.” The second part is the gas exhaust system, which contains elements exclusively for reducing exhaust noise (mufflers, resonators), the accepted designation of which is the "cold part." The design of the exhaust system from the point of view of acoustics, that is, reducing the exhaust noise to a predetermined level, consists of working on the second part. Modern computer technology and software make it possible to design "cold part" with high accuracy in a given frequency range but with the condition of accurately specifying the input parameters, namely, the amplitude spectrum of the input noise and the acoustic impedance of the noise source in the form of an engine with a "hot part". Getting this data is a difficult problem: high temperatures, high exhaust gas velocities (turbulent flows), and high sound pressure levels (non-linearity mode) do not allow the calculated results to be applied with sufficient accuracy. The aim of this work is to obtain the most reliable acoustic output parameters of an engine with a "hot part" based on a complex of computational and experimental studies. The presented methodology includes several parts. The first part is a finite element simulation of the "cold part" of the exhaust system (taking into account the acoustic impedance of radiation of outlet pipe into open space) with the result in the form of the input impedance of "cold part". The second part is a finite element simulation of the "hot part" of the exhaust system (taking into account acoustic characteristics of catalytic units and geometry of turbocharger) with the result in the form of the input impedance of the "hot part". The next third part of the technique consists of the mathematical processing of the results according to the proposed formula for the convergence of the mathematical series of summation of multiple reflections of the acoustic signal "cold part" - "hot part". This is followed by conducting a set of tests on an engine stand with two high-temperature pressure sensors measuring pulsations in the nozzle between "hot part" and "cold part" of the exhaust system and subsequent processing of test results according to a well-known technique in order to separate the "incident" and "reflected" waves. The final stage consists of the mathematical processing of all calculated and experimental data to obtain a result in the form of a spectrum of the amplitude of the engine noise and its acoustic impedance.

Keywords: acoustic impedance, engine exhaust system, FEM model, test stand

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Authors: Magdalena Wilk-Kozubek, Magdalena Rowińska, Krzysztof Rola, Joanna Cybińska

Abstract:

Leuco dye-based thermochromic systems are classified as intelligent materials because they exhibit thermally induced color changes. Thanks to this feature, they are mainly used as temperature sensors in many industrial sectors. For example, placing a thermochromic material on a chemical reactor may warn about exceeding the maximum permitted temperature for a chemical process. Usually two components, a color former and a developer are needed to produce a system with irreversible color change. The color former is an electron donating (proton accepting) compound such as fluoran leuco dye. The developer is an electron accepting (proton donating) compound such as organic carboxylic acid. When the developer melts, the color former - developer complex is created and the termochromic system becomes colored. Typically, the melting point of the applied developer determines the temperature at which the color change occurs. When the lactone ring of the color former is closed, then the dye is in its colorless state. The ring opening, induced by the addition of a proton, causes the dye to turn into its colored state. Since the color former and the developer are often solid, they can be incorporated into polymer films to facilitate their practical use in industry. The objective of this research was to fabricate a leuco dye-based termochromic system that will irreversibly change color after reaching the temperature of 100°C. For this purpose, benzofluoran leuco dye (as color former) and phenoxyacetic acid (as developer with a melting point of 100°C) were introduced into the polymer films during the drop casting process. The film preparation process was optimized in order to obtain thin films with appropriate properties such as transparency, flexibility and homogeneity. Among the optimized factors were the concentration of benzofluoran leuco dye and phenoxyacetic acid, the type, average molecular weight and concentration of the polymer, and the type and concentration of the surfactant. The selected films, containing benzofluoran leuco dye and phenoxyacetic acid, were combined by mild heat treatment. Structural characterization of single and combined films was carried out by FTIR spectroscopy, morphological analysis was performed by optical microscopy and SEM, phase transitions were examined by DSC, color changes were investigated by digital photography and UV-Vis spectroscopy, while emission changes were studied by photoluminescence spectroscopy. The resulting thermochromic system is colorless at room temperature, but after reaching 100°C the developer melts and it turns irreversibly pink. Therefore, it could be used as an additional sensor to warn against boiling of water in power plants using water cooling. Currently used electronic temperature indicators are prone to faults and unwanted third-party actions. The sensor constructed in this work is transparent, thanks to which it can be unnoticed by an outsider and constitute a reliable reference for the person responsible for the apparatus.

Keywords: color developer, leuco dye, thin film, thermochromism

Procedia PDF Downloads 100

Authors: Masoud Gholam Ale Mohammad, Mojtaba Hafezi Birgani

Abstract:

An experimental study of saturated pool boiling on a single artificial nucleation site without and with the application of an electric field on the boiling surface has been conducted. N-pentane is boiling on a copper surface and is recorded with a high speed camera providing high quality pictures and movies. The accuracy of the visualization allowed establishing an experimental bubble growth law from a large number of experiments. This law shows that the evaporation rate is decreasing during the bubble growth, and underlines the importance of liquid motion induced by the preceding bubble. Bubble rise is therefore studied: once detached, bubbles accelerate vertically until reaching a maximum velocity in good agreement with a correlation from literature. The bubbles then turn to another direction. The effect of applying an electric field on the boiling surface in finally studied. In addition to changes in the bubble shape, changes are also shown in the liquid plume and the convective structures above the surface. Lower maximum rising velocities were measured in the presence of electric fields, especially with a negative polarity.

Keywords: single and double bubbles, electric field, boiling, rising

Procedia PDF Downloads 226

Authors: Mohammad Derakhshani, Saeed Reza Allahkarama, Michael Isakhani-Zakaria, Masoud Samadian, Hojjat Sharifi Rasaey

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In order to investigate the effects of stray current from DC traction systems (subway) on cathodically protected gas pipelines, the subway and the gas network maps in the city of Tehran were superimposed and a comprehensive map was prepared. 213 intersections and about 100150 meters of parallel sections of gas pipelines were found with respect to the railway right of way which was specified for field measurements. The potential measurements data were logged for one hour in each test point. 24-hour potential monitoring was carried out in selected test points as well. Results showed that dynamic stray current from subway on pipeline potential appears as fluctuations in its static potential that is visible in the diagrams during night periods. These fluctuations can cause the pipeline potential to exit the safe zone and lead to corrosion or overprotection. In this study, a maximum potential shift of 100 mv in the pipe-to-soil potential was considered as a criterion for dynamic stray current effective presence. Results showed that a potential fluctuation range between 100 mV to 3 V exists in measured points on pipelines which exceeds the proposed criterion and needs to be investigated. Corrosion rates influenced by stray currents were calculated using coupons. Results showed that coupon linked to the pipeline in one of the locations at region 1 of the city of Tehran has a corrosion rate of 4.2 mpy (with cathodic protection and under influence of stray currents) which is about 1.5 times more than free corrosion rate of 2.6 mpy.

Keywords: stray current, DC traction, subway, buried Pipelines, cathodic protection list

Procedia PDF Downloads 822

Authors: Jianfeng Hu

Abstract:

Personal authentication based on electroencephalography (EEG) signals is one of the important field for the biometric technology. More and more researchers have used EEG signals as data source for biometric. However, there are some disadvantages for biometrics based on EEG signals. The proposed method employs entropy measures for feature extraction from EEG signals. Four type of entropies measures, sample entropy (SE), fuzzy entropy (FE), approximate entropy (AE) and spectral entropy (PE), were deployed as feature set. In a silhouettes calculation, the distance from each data point in a cluster to all another point within the same cluster and to all other data points in the closest cluster are determined. Thus silhouettes provide a measure of how well a data point was classified when it was assigned to a cluster and the separation between them. This feature renders silhouettes potentially well suited for assessing cluster quality in personal authentication methods. In this study, “silhouettes scores” was used for assessing the cluster quality of k-means clustering algorithm is well suited for comparing the performance of each EEG dataset. The main goals of this study are: (1) to represent each target as a tuple of multiple feature sets, (2) to assign a suitable measure to each feature set, (3) to combine different feature sets, (4) to determine the optimal feature weighting. Using precision/recall evaluations, the effectiveness of feature weighting in clustering was analyzed. EEG data from 22 subjects were collected. Results showed that: (1) It is possible to use fewer electrodes (3-4) for personal authentication. (2) There was the difference between each electrode for personal authentication (p<0.01). (3) There is no significant difference for authentication performance among feature sets (except feature PE). Conclusion: The combination of k-means clustering algorithm and silhouette approach proved to be an accurate method for personal authentication based on EEG signals.

Keywords: personal authentication, K-mean clustering, electroencephalogram, EEG, silhouettes

Procedia PDF Downloads 285