Search results for: morphology optimization

Authors: Dessie Tibebe, Yeshifana Ayenew, Marye Mulugeta, Yezbie Kassa, Zerubabel Moges, Dereje Yenealem, Tarekegn Fentie, Agmas Amare, Hailu Sheferaw Ayele

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Electrochemical treatment technology is a technique used for wastewater treatment due to its ability to eliminate impurities that are not easily removed by chemical processes. The objective of the study is the treatment and characterization of textile wastewater by an electrochemical process. The results obtained at various operational parameters indicated that at 20 minutes of electrochemical process at ( pH =7), initial concentration 10 mg/L, current density 37.5 mA/cm², voltage 9 v and temperature 25⁰C the highest removal efficiency was achieved. The kinetics of removal of selected metal by electrochemical treatment has been successfully described by the first-order rate equation. The results of microscopic techniques using SEM for the scarified electrode before treatment were uniform and smooth, but after the electrochemical process, the morphology was completely changed. This is due to the detection of the adsorbed aluminum hydroxide coming from adsorption of the conducting electrolyte, chemicals used in the experiments, alloying and the scrap impurities of the anode and cathode. The FTIR spectroscopic analysis broad bands at 3450 cm-¹ representing O-H functional groups, while the presence of H-O-H and Al-H groups are indicated by the bands at 2850-2750 cm-¹ and 1099 representing C-H functional groups.

Keywords: electrochemical, treatment, textile wastewater, kinetics, removal efficiency

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Authors: Shunsuke Miyoshi, Yasuyuki Nogami, Takuya Kusaka, Nariyoshi Yamai

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Elliptic curve discrete logarithm problem (ECDLP) is one of problems on which the security of pairing-based cryptography is based. This paper considers Pollard's rho method to evaluate the security of ECDLP on Barreto-Naehrig (BN) curve that is an efficient pairing-friendly curve. Some techniques are proposed to make the rho method efficient. Especially, the group structure on BN curve, distinguished point method, and Montgomery trick are well-known techniques. This paper applies these techniques and shows its optimization. According to the experimental results for which a large-scale parallel system with MySQL is applied, 94-bit ECDLP was solved about 28 hours by parallelizing 71 computers.

Keywords: Pollard's rho method, BN curve, Montgomery multiplication

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Authors: Andreas D. Jansson

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The availability of inexpensive, yet competent hardware allows for increased level of automation and self-optimization in the context of Industry 4.0. However, such agents require high quality information about their surroundings along with a robust strategy for collision avoidance, as they may cause expensive damage to equipment or other agents otherwise. Manually defining a strategy to cover all possibilities is both time-consuming and counter-productive given the capabilities of modern hardware. This paper explores the idea of a model-free self-optimizing obstacle avoidance strategy for multiple autonomous agents in a simulated dynamic environment using the Q-learning algorithm.

Keywords: autonomous vehicles, industry 4.0, multi-agent system, obstacle avoidance, Q-learning, simulation

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Authors: Ali Fattahi Bafghi, Abolghasem Siyadatpanah, Farzaneh Mirzaei, Fahimeh Pournasir, Roghayeh Norouzi, Maria De Lourdes Pereira

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Leishmaniasis caused by Leishmania major is one of the main infectious diseases that affect populations in developing countries around the world. We assessed the effectiveness of berberine chloride nano-liposome (BcNLs) against L. major promastigotes in vitro. Nano-liposomal berberine chloride was prepared using the thin-film hydration method and characterized based on encapsulation efficiency, size, and zeta potential. Anti-Leishmania effect of different concentrations (0.05-60 µg/ml) of BcNLs as studied in L. major [MRHO/IR/75/ER] at 24, 48, and 72 h using the hemocytometer technique. Berberine chloride was successfully loaded into nano-liposomes with an encapsulation efficiency of 85.54%. The surface charge of nanoparticles is neutral, and the morphology of nano-liposomal berberine chloride is spherical without any agglomeration. Cell viability assay was performed on the HFF cell line to show the biocompatibility of liposome nanoparticles. IC50 of BcNPs at 24, 48, and 72 h against L. major were found to be 7.6, 5.96, and 3.19 µg/ml, respectively. BcNLs showed a significant anti-Leishmania effect and induced a better and more tangible effect on the survival of L. major promastigotes and could be suitable candidates for further investigation. The results showed that the BcNLs agent is effective against L. major promastigotes and may be a promising alternative to current treatments.

Keywords: Leishmania major, berberine chloride, nano-liposomes, cutaneous leishmaniasis

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Authors: Lei Lei, Hongbo Zhang, Donald J. Bergstrom, Bing Zhang, K. Y. Song, W. J. Zhang

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This paper presents a model for a modified T-junction device for microspheres generation. The numerical model is developed using a commercial software package: COMSOL Multiphysics. In order to test the accuracy of the numerical model, multiple variables, such as the flow rate of cross-flow, fluid properties, structure, and geometry of the microdevice are applied. The results from the model are compared with the experimental results in the diameter of the microsphere generated. The comparison shows a good agreement. Therefore the model is useful in further optimization of the device and feedback control of microsphere generation if any.

Keywords: CFD modeling, validation, microsphere generation, modified T-junction

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Authors: Gulfam Haider, sana danish

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

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

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Authors: Riccardo Loggia, Francesca Pizzimenti, Francesco Lelli, Luigi Martirano

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Recent air emission regulations point toward the complete electrification of road vehicles. An increasing number of users are beginning to prefer full electric or hybrid, plug-in vehicle solutions, incentivized by government subsidies and the lower cost of electricity compared to gasoline or diesel. However, it is necessary to optimize charging stations so that they can simultaneously satisfy as many users as possible. The purpose of this paper is to present optimization algorithms that enable simultaneous charging of multiple electric vehicles while ensuring maximum performance in relation to the type of charging station.

Keywords: electric vehicles, charging stations, sharing model, fast charging, car park, power profiles

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Authors: Nona Mirzamohammadi, Bahram Nasernejad

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This work mainly focuses on studying the mechanism governing the adsorption of tetraethylammonium bromide, a short-chain quaternary ammonium salt, on the surface of natural zeolite and to characterize modified and raw zeolites in order to study the removal of nitrate anions from water. Natural clinoptilolite, as the most common zeolite, was chosen and modified in an ultrasonication process using tetraethylammonium bromide, subsequent to being contacted with NaCl solutions. FT-IR studies indicated a peak attributed to the stretching vibrations of the –CH₂ group in the molecule of tetraethylammonium bromide in the spectrum of the modified sample. Moreover, the SEM images showed some obvious changes in the surface morphology and crystallinity of clinoptilolite after being modified. Batch adsorption experiments show that the modified zeolite is capable of removing nitrate anions, and the predominant removal mechanism is suggested to be a combination of electrostatic attraction and ion exchange since the results from the zeta potential analysis showed a decrease in the net negative charge of clinoptilolite after modification, while bromide ions were detected in the modified sample in the µXRF analysis.

Keywords: adsorption, clinoptilolite, short-chain quaternary ammonium salt, tetraethylammoniumbromide, ultrasonication

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Authors: R. Ouafi, F. Ouafi

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We study the problem of cutting a rectangular material entity into smaller sub-entities of trapezoidal forms with minimum waste of the material. This problem will be denoted TCP (Trapezoidal Cutting Problem). The TCP has many applications in manufacturing processes of various industries: pipe line design (petro chemistry), the design of airfoil (aeronautical) or cuts of the components of textile products. We introduce an orthogonal build to provide the optimal horizontal and vertical homogeneous strips. In this paper we develop a general heuristic search based upon orthogonal build. By solving two one-dimensional knapsack problems, we combine the horizontal and vertical homogeneous strips to give a non orthogonal cutting pattern.

Keywords: combinatorial optimization, cutting problem, heuristic

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Authors: Amine Rezzoug, Said Abdi, Nadjet Bouhelal, Ismail Daoud

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This paper investigates the application of metallic coatings on high fiber volume fraction carbon/epoxy polymer matrix composites. For the grip of the metallic layer, a method of modifying the surface of the composite by introducing a mixture of copper and steel powder (filler powders) which can reduce the impact of thermal spray particles. The powder was introduced to the surface at the time of the forming. Arc spray was used to project the zinc coating layer. The substrate was grit blasted to avoid poor adherence. The porosity, microstructure, and morphology of layers are characterized by optical microscopy, SEM and image analysis. The samples were studied also in terms of hardness and erosion resistance. This investigation did not reveal any visible evidence damage to the substrates. The hardness of zinc layer was about 25.94 MPa and the porosity was around (∼6.70%). The erosion test showed that the zinc coating improves the resistance to erosion. Based on the results obtained, we can conclude that thermal spraying allows the production of protective coating on PMC. Zinc coating has been identified as a compatible material with the substrate. The filler powders layer protects the substrate from the impact of hot particles and allows avoiding the rupture of brittle carbon fibers.

Keywords: arc spray, coating, composite, erosion

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Authors: S. Srinivasan, E. Cretu

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The information flow (e.g. block-diagram or signal flow graph) paradigm for the design and simulation of Microelectromechanical (MEMS)-based systems allows to model MEMS devices using causal transfer functions easily, and interface them with electronic subsystems for fast system-level explorations of design alternatives and optimization. Nevertheless, the physical bi-directional coupling between different energy domains is not easily captured in causal signal flow modeling. Moreover, models of fundamental components acting as building blocks (e.g. gap-varying MEMS capacitor structures) depend not only on the component, but also on the specific excitation mode (e.g. voltage or charge-actuation). In contrast, the energy flow modeling paradigm in terms of generalized across-through variables offers an acausal perspective, separating clearly the physical model from the boundary conditions. This promotes reusability and the use of primitive physical models for assembling MEMS devices from primitive structures, based on the interconnection topology in generalized circuits. The physical modeling capabilities of Simscape have been used in the present work in order to develop a MEMS library containing parameterized fundamental building blocks (area and gap-varying MEMS capacitors, nonlinear springs, displacement stoppers, etc.) for the design, simulation and optimization of MEMS inertial sensors. The models capture both the nonlinear electromechanical interactions and geometrical nonlinearities and can be used for both small and large signal analyses, including the numerical computation of pull-in voltages (stability loss). Simscape behavioral modeling language was used for the implementation of reduced-order macro models, that present the advantage of a seamless interface with Simulink blocks, for creating hybrid information/energy flow system models. Test bench simulations of the library models compare favorably with both analytical results and with more in-depth finite element simulations performed in ANSYS. Separate MEMS-electronic integration tests were done on closed-loop MEMS accelerometers, where Simscape was used for modeling the MEMS device and Simulink for the electronic subsystem.

Keywords: across-through variables, electromechanical coupling, energy flow, information flow, Matlab/Simulink, MEMS, nonlinear, pull-in instability, reduced order macro models, Simscape

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Authors: Ayed S. Al-Shihri, Abul Kalam, Abdullah G. Al-Sehemi, Gaohui Du, Tokeer Ahmad, Ahmad Irfan

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We report here the synthesis of nickel oxide (NiO) nanoparticles by microwave-assisted method, using a common precipitating agent followed by calcination in air at 400°C. The effect of the microwave and pH on the crystallite size, morphology, structure, energy band gap and surface area of NiO have been investigated by means of powder X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), high resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR), ultraviolet visible spectroscopy (UV-vis) and BET surface area studies. X-ray diffraction studies showed the formation of monophasic and highly crystalline cubic NiO. TEM analysis led to decrease the average grain size of NiO nanoparticles from 16.5 nm to 14 nm on increasing the amount of NaOH. FTIR studies also confirm the formation of NiO nanoparticles. It was observed that on increasing the volume of NaOH, the optical band gap energy (2.85 eV to 2.95 eV) and specific surface area (33.1 to 39.8 m2/g) increases, however the average particles size decreases (16.5 nm to 14 nm). This method may be extended to large scale synthesis of other metal oxides nanoparticles and the present study could be used for the potential applications in water treatment and many other fields.

Keywords: BET surface area analysis, electron microscopy, optical properties, X-ray techniques

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Authors: Y.Galerkin, O. Solovieva

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Flow parameters are calculated in vaneless diffusers with relative width 0,014 – 0,10 constant along radii. Inlet flow angles and similarity criteria were varied. Information about flow structure is presented – meridian streamlines configuration, information on flow full development, flow separation. Polytrophic efficiency, loss and recovery coefficient are used to compare diffusers’ effectiveness. The sample of narrow diffuser optimization by conical walls application is presented. Three tampered variants of a wide diffuser are compared too. The work is made in the R&D laboratory “Gas dynamics of turbo machines” of the TU SPb.

Keywords: vaneless diffuser, relative width, flow angle, flow separation, loss coefficient, similarity criteria

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Authors: Marcelle Muriel Domkam Tchunkam, Rolin Feudjio

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This work investigates the ultrastructure, physicochemical and thermal properties evaluation of Palm Kernel Shells (PKS). PKS Tenera waste samples were obtained from a palm oil mill in Dizangué Sub-Division, Littoral region of Cameroon, while PKS Dura waste samples were collected from the Institute of Agricultural Research for Development (IRAD) of Mbongo. A sodium hydroxide solution was used to wash the shells. They were then rinsed by demineralised water and dried in an oven at 70 °C during 72 hours. They were then grounded and sieved to obtained powders from 0.04 mm to 0.45 mm in size. Transmission Electron Microscopy (TEM) and Surface Electron Microscopy (SEM) were used to characterized powder samples. Chemical compounds and elemental constituents, as well as thermal performance were evaluated by Van Soest Method, TEM/EDXA and SEM/EDS techniques. Thermal characterization was also performed using Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA). Our results from microstructural analysis revealed that most of the PKS material is made of particles with irregular morphology, mainly amorphous phases of carbon/oxygen with small amounts of Ca, K, and Mg. The DSC data enabled the derivation of the materials’ thermal transition phases and the relevant characteristic temperatures and physical properties. Overall, our data show that PKS have nanopores and show potential in 3D printing and membrane filtration applications.

Keywords: DSC, EDXA, palm kernel shells, SEM, TEM

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Authors: H. Yousefnia, MS. Mousavi-Daramoroudi, S. Zolghadri, F. Abbasi-Davani

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High expression of somatostatin receptors on a wide range of human tumours makes them as potential targets for peptide receptor radionuclide tomography. A series of octreotide analogues were synthesized while [DOTA-DPhe1, Tyr3]octreotide (DOTATOC) indicated advantageous properties in tumour models. In this study, 177Lu-DOTATOC was prepared with the radiochemical purity of higher than 99% in 30 min at the optimized condition. Biological behavior of the complex was studied after intravenous injection into the Syrian rats. Major difference uptake was observed compared to 177LuCl3 solution especially in somatostatin receptor-positive tissues such as pancreas and adrenal.

Keywords: Biodistribution, 177Lu, Octreotide, Syrian rats

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Authors: Francis O. Nwawuru

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The convergence analysis of split monotone inclusion problems and fixed point problems of certain nonlinear mappings are investigated in the setting of real Hilbert spaces. Inertial extrapolation term in the spirit of Polyak is incorporated to speed up the rate of convergence. Under standard assumptions, a strong convergence of the proposed algorithm is established without computing the resolvent operator or involving Yosida approximation method. The stepsize involved in the algorithm does not depend on the spectral radius of the linear operator. Furthermore, applications of the proposed algorithm in solving some related optimization problems are also considered. Our result complements and extends numerous results in the literature.

Keywords: fixedpoint, hilbertspace, monotonemapping, resolventoperators

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Authors: Qinglin Shu

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Based on the analysis of the structural vibration comfort of a domestic bridge, this paper studies the vibration reduction control principle of TMD, the derivation process of design parameter optimization and how to simulate TMD in the finite element software ANSYS. The research shows that, in view of the problem that the comfort level of a bridge exceeds the limit in individual working conditions, the vibration reduction control design of the bridge can effectively reduce the vibration of the structure by using TMD. Calculations show that when the mass ratio of TMD is 0.01, the vibration reduction rate under different working conditions is more than 90%, and the dynamic displacement of the TMD mass block is within 0.01m, indicating that the design of TMD is reasonable and safe.

Keywords: pedestrian bridges, human-induced vibration, comfort, tuned mass dampers

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Authors: A. S. Walkey, N. P. Patidar

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It is not always economical to provide reactive power using synchronous alternators. The cost of reactive power can be minimized by optimal placing of FACTS devices in power systems. In this paper a Particle Swarm Optimization- Sequential Quadratic Programming (PSO-SQP) algorithm is applied to minimize the cost of reactive power generation along with real power generation to alleviate the bus voltage violations. The effectiveness of proposed approach tested on IEEE-14 bus systems. In this paper in addition to synchronous generators, an opportunity of FACTS devices are also proposed to procure the reactive power demands in the power system.

Keywords: reactive power, reactive power cost, voltage security margins, capability curve, FACTS devices

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Authors: Shaban Guma, Naim Bajcinca

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We propose an event-triggered algorithm for the solution of a distributed optimization problem by means of the projected subgradient method. Thereby, we invoke an OFDMA resource allocation scheme by applying an event-triggered sensitivity analysis at the access point. The optimal resource assignment of the subcarriers to the involved wireless nodes is carried out by considering the sensitivity analysis of the overall objective function as defined by the control of vehicle clusters with respect to the information exchange between the nodes.

Keywords: consensus, cross-layer, distributed, event-triggered, multi-vehicle, protocol, resource, OFDMA, wireless

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Authors: Mourad Makhlouf, Bouabdellah Benaicha, Zoubir Benmaamar, Didier Villemin

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The addition of combustion catalysts to ammonium perchlorate-based composite fuels can indeed significantly enhance their performance. In this work, a nanocomposite was synthesized using graphene oxide (GO) and hematite nanoparticles grafted onto graphene oxide as a catalyst support.To characterize the nanocomposite, several experimental techniques were employed, including Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, and scanning electron microscopy (SEM). FTIR is useful for analyzing chemical bonding and functional groups, while Raman spectroscopy provides information about the vibrational modes of the materials. SEM allows for visualizing the surface morphology and structure.The thermal analysis of two mixtures, one based on AP/GO and the other on AP/GO-Fe2O3, was conducted with varying percentages. The results indicated that the nanocomposite GO-Fe2O3 acted as a catalyst, significantly accelerating the thermal decomposition process of AP. This catalytic effect ultimately led to an improvement in the energy performance of the composite fuel.Overall, the synthesis and characterization of the nanocomposite, as well as the thermal analysis, demonstrated the effectiveness of GO-Fe2O3 as a combustion catalyst in enhancing the performance of ammonium perchlorate-based composite fuels.

Keywords: composite propellants, ammonium perchlorate, nanocomposite, catalytic support, hematite nanoparticles, graphene oxide, thermal decomposition

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Boris Melnikov, Ye Zhang, Dmitrii Chaikovskii

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This study explores the pseudo-geometric version of the extensively researched Traveling Salesman Problem (TSP), proposing a novel generalization of existing algorithms which are traditionally confined to the geometric version. By adapting the "onion husk" method and introducing auxiliary algorithms, this research fills a notable gap in the existing literature. Through computational experiments using randomly generated data, several metrics were analyzed to validate the proposed approach's efficacy. Preliminary results align with expected outcomes, indicating a promising advancement in TSP solutions.

Keywords: optimization problems, traveling salesman problem, heuristic algorithms, “onion husk” algorithm, pseudo-geometric version

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Authors: Saeed Ahmed, Muhammad Imran, Yasir Allah Ditta, Shahid Mehmood, Zahid Rasool

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A study was conducted to investigate the effect of different levels of microencapsulated butyric (MEB) on growth performance, gut health and immunity in commercial broiler chickens. In total, 336 day-old Hubbard classic broilers chicks were randomly assigned to 4 dietary treatments (Control, 0.25, 0.35 and 0.45g/kg of butyric acid) under completely randomized design. Each treatment was replicated 3 times with 28 birds in each replicate. Feed intake, body weight gain, feed conversion ratio, intestinal morphology, apparent ileal digestibility of protein and immunity parameters were evaluated. At the end of the experiment (35-d) 3 birds/replicate in each group were randomly selected and slaughtered to collect blood, duodenal samples and ileal digesta. The data were analyzed by using ANOVA technique. The results indicated improved body weight gain (P = 0.0222), feed conversion ratio (P = 0.0056), duodenal villus height (P = 0.0512), AID (P = 0.0098) antibody titer against Newcastle disease improved (P = 0.0326). Treatments remained unresponsive with respect to feed intake (P = 0.9685).

Keywords: butyric acid, broilers, gut health, ileal digestibility

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Authors: Sandra C. L. Dorea, Joann K. Whalen, Yixin Shao, Oumarou Savadogo

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The major challenge for industries that rely on fossil fuels in manufacturing processes or to provide goods and services is to lower their CO2 emissions, as the case for the manufacture of Portland cement. Feasible materials for this purpose can include agro-industrial or agricultural wastes, which are termed 'biosilica' since the silica was contained in a biological matrix (biomass). Corn cob (CC) has some characteristics that make it a good candidate as biosilica source: 1) it is an abundant grain crop produced around the world; 2) more production means more available residues is left in the field to be used. This work aims to evaluate the CC collected from different farms in Canada during the corn harvest in order to see if they can be used together as a biosilica source. The characterization of the raw CC was made in the physical, chemical, and thermal way. The moisture content, the granulometry, and the morphology were also analyzed. The ash content measured was 2,1%. The Thermogravimetric Analysis (TGA) and its Derivative (DTG) evaluated of CC as a function of weight loss with temperature variation ranging between 30°C and 800°C in an atmosphere of N2. The chemical composition and the presence of silica revealed that the different sources of the CC do not interfere in its basic chemical composition, which means that this kind of waste can be used together as a source of biosilica no matter where they come from. Then, this biosilica can partially replace the cement Portland making sustainable cementitious mixtures and contributing to reduce the CO2 emissions.

Keywords: biosilica, characterization, corn cob, sustainable cementitious materials

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Authors: Asiful Hossain Seikh, Mohammad Asif Alam, Ubair Abdus Samad, Jabair A. Mohammed, S. M. Al-Zahrani, El-Sayed M. Sherif

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In this current investigation, aliphatic amine-cured diglycidyl ether of bisphenol-A (DGEBA) based epoxy coating was mixed with certain weight % hardener polyaminoamide (1:2) and was coated on carbon steel panels with and without 1% nano crystalline Al powder. The corrosion behavior of the coated samples were investigated by exposing them in the salt spray chamber, for 500 hours. According to ASTM-B-117, the bath was kept at 35 °C and 5% NaCl containing mist was sprayed at 1.3 bars pressure. Composition of coatings was confirmed using Fourier-transform infrared spectroscopy (FTIR). Electrochemical characterization of the coated samples was also performed using potentiodynamic polarization technique and electrochemical impedance spectroscopy (EIS) technique. All the experiments were done in 3.5% NaCl solution. The nano Al coated sample shows good corrosion resistance property compared to bare Al sample. In fact after salt spray exposure no pitting or local damage was observed for nano coated sample and the coating gloss was negligibly affected. The surface morphology of coated and corroded samples was studied using scanning electron microscopy (SEM).

Keywords: epoxy, nano aluminium, potentiodynamic polarization, salt spray, electrochemical impedence spectroscopy

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Authors: Atakan Efe Akpınar, Zeynep Demir

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Seed priming technologies are frequently used nowadays to increase the germination potential and stress tolerance of seeds. These treatments might be beneficial for native species as well as crops. Different priming treatments can be used depending on the type of plant, the morphology, and the physiology of the seed. Moreover, these may be various physical, chemical, and/or biological treatments. Aiming to improve studies about seed priming, ideas need to be brought into this technological sector related to the agri-seed industry. This study addresses the question of whether seed priming with plant extracts can improve seed vigour and germination performance. By investigating the effects of plant extract priming on various vigour parameters, the research aims to provide insights into the potential benefits of this treatment method. Thus, seed priming was carried out using some plant extracts. Firstly, some plant extracts prepared from plant leaves, roots, or fruit parts were obtained for use in priming treatments. Then, seeds of Common zinnia (Zinnia elegans) were kept in solutions containing plant extracts at 20°C for 48 hours. Seeds without any treatment were evaluated as the control group. At the end of priming applications, seeds are dried superficially at 25°C. Seeds of Common zinnia (Zinnia elegans) were analyzed for vigour (normal germination rate, germination time, germination index etc.). In the future, seed priming applications can expand to multidisciplinary research combining with digital, bioinformatic and molecular tools.

Keywords: seed priming, plant extracts, germination, biology

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Authors: Chanhyuck Jeon, Jongho Park, Jinwoong Choi, Sungnam Hong, Sun-Kyu Park

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Many industries put emphasis on environmentally-friendliness as environmental problems are on the rise all over the world. Among themselves, the Modular Bridge research is going on. Also performing cross-section optimization and duration reducing, this research aims at developing the modular bridge with Environment-Friendliness and economic feasibility. However, the difficulty lies in verifying environmental effectiveness because there are no field applications of the modular bridge until now. Therefore, this thesis is categorized according to the form of the modular bridge superstructure and assessed CO₂ emission quantification per work types and materials according to each form to verify the environmental effectiveness of the modular bridge.

Keywords: modular bridge, CO2 emission, environmentally friendly, quantification, carbon emission factor, LCA (Life Cycle Assessment)

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Authors: Josef Brychta, Jiri Kratochvil, Marek Pagac

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The group of progressive cutting materials can include non-traditional, emerging and less-used materials that can be an efficient use of cutting their lead to a quantum leap in the field of machining. This is essentially a “superhard” materials (STM) based on polycrystalline diamond (PCD) and polycrystalline cubic boron nitride (PCBN) cutting performance ceramics and development is constantly "perfecting" fine coated cemented carbides. The latter cutting materials are broken down by two parameters, toughness and hardness. A variation of alloying elements is always possible to improve only one of each parameter. Reducing the size of the core on the other hand doing achieves "contradictory" properties, namely to increase both hardness and toughness.

Keywords: grained cutting materials difficult to machine materials, optimum utilization, mechanic, manufacturing

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Authors: Amar Khoukhi, Mohamed Shahab

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This paper presents the optimal control problem of mobile robot motion as a nonlinear programming problem (NLP) and solved using a direct method of numerical optimal control. The NLP is initialized with a B-Spline for which node locations are optimized using a genetic search. The system acceleration inputs and sampling periods are considered as optimization variables. Different scenarios with different objectives weights are implemented and investigated. Interesting results are found in terms of complying with the expected behavior of a mobile robot system and time-energy minimization.

Keywords: multi-objective control, non-holonomic systems, mobile robots, nonlinear programming, motion planning, B-spline, genetic algorithm

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Authors: Nurul Z. Sani, Amalina N. Ghazali, Azree Elmy, Lee C. Yuen, Zar C. Thent

Abstract:

Piper betel (P. betel) leaves is widely used in Asian countries for treating diabetes mellitus and its complication. In our previous study, we observed the positive effect of P.betel extract on diabetic wounds following 3 and 7 days of treatment. The aim of the present study was to determine the effect of P.betel leaves extract in the diabetic rats was observed in terms of body weight and wound contraction rates following 5 days of the treatment. Total 64 male Sprague-Dawley rats were used and the experimental rats received a single dose of 60mg/kg of Streptozotocin (STZ) injection, intraperitoneally. Four full thickness (6mm) cutaneous wounds were created on dorsum of each rat. The rats were divideid into (n=8): Non-treated Control (NC), Non-treated Diabetic (ND), diabetic treated with commercial cream (SN) and diabetic treated with 50mg/kg of P.betel extract (PB). The rats were sacrificed on day 0 and 5 post wounding. Significant increased in wound closure rate, body weight was observed in PB group compared to ND. Histological deterioration was restored in the P. betel extract treated wounds. It is concluded that topical application with P.betel extract for 5 days of post wounding offers positive scientific value in diabetic rats.

Keywords: diabetes, piper betel, wound healing, body weight, morphology

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