Search results for: EB thermal processing

Authors: Rajpal Kaur, Pooja Choudhary

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Biometrics, which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capabilities to the reliably distinguish between an authorized person and an imposter. The Signature recognition systems can categorized as offline (static) and online (dynamic). This paper presents Surf Feature based recognition of offline signatures system that is trained with low-resolution scanned signature images. The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. However the signatures of human can be handled as an image and recognized using computer vision and HMM techniques. With modern computers, there is need to develop fast algorithms for signature recognition. There are multiple techniques are defined to signature recognition with a lot of scope of research. In this paper, (static signature) off-line signature recognition & verification using surf feature with HMM is proposed, where the signature is captured and presented to the user in an image format. Signatures are verified depended on parameters extracted from the signature using various image processing techniques. The Off-line Signature Verification and Recognition is implemented using Mat lab platform. This work has been analyzed or tested and found suitable for its purpose or result. The proposed method performs better than the other recently proposed methods.

Keywords: offline signature verification, offline signature recognition, signatures, SURF features, HMM

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Authors: Naser Safdarian, Nader Jafarnia Dabanloo

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In this paper we used four features i.e. Q-wave integral, QRS complex integral, T-wave integral and total integral as extracted feature from normal and patient ECG signals to detection and localization of myocardial infarction (MI) in left ventricle of heart. In our research we focused on detection and localization of MI in standard ECG. We use the Q-wave integral and T-wave integral because this feature is important impression in detection of MI. We used some pattern recognition method such as Artificial Neural Network (ANN) to detect and localize the MI. Because these methods have good accuracy for classification of normal and abnormal signals. We used one type of Radial Basis Function (RBF) that called Probabilistic Neural Network (PNN) because of its nonlinearity property, and used other classifier such as k-Nearest Neighbors (KNN), Multilayer Perceptron (MLP) and Naive Bayes Classification. We used PhysioNet database as our training and test data. We reached over 80% for accuracy in test data for localization and over 95% for detection of MI. Main advantages of our method are simplicity and its good accuracy. Also we can improve accuracy of classification by adding more features in this method. A simple method based on using only four features which extracted from standard ECG is presented which has good accuracy in MI localization.

Keywords: ECG signal processing, myocardial infarction, features extraction, pattern recognition

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Authors: Yan Yue

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Huang Di Nei Jing (HDNJ) is one of the significant traditional Chinese medicine (TCM) classics which lays the foundation of TCM theory and practice. It is an important work for the world to study the ancient civilizations and medical history of China. Language in HDNJ is highly concise and vague, and notably challenging to translate. This paper investigates the translatability of one particular vagueness in HDNJ: the conceptual vagueness which carries the Chinese philosophical and cultural connotations. The corpora tool Sketch Engine is used to provide potential online contexts and word behaviors. Selected two English translations of HDNJ by TCM practitioner and non-practitioner are used to examine frequency and distribution of linguistic features of the translation. It was found the hypothesis about the universals of translated language (explicitation, normalisation) is true in one translation, but it is on the sacrifice of some original contextual connotations. Transliteration is purposefully used in the second translation to retain the original flavor, which is argued as a violation of the principle of relevance in communication because it yields little contextual effects and demands more processing effort of the reader. The translatability of conceptual vagueness in HDNJ is constrained by source language context and the reader’s cognitive environment.

Keywords: corpus-based translation, translatability, TCM classics, vague language

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Authors: Ching-Sung Lee, Wei-Chou Hsu, Han-Yin Liu, Hung-Hsi Huang, Si-Fu Chen, Yun-Jung Yang, Bo-Chun Chiang, Yu-Chuang Chen, Shen-Tin Yang

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AlGaN/GaN high electron mobility transistors (HEMTs) have been intensively studied due to their intrinsic advantages of high breakdown electric field, high electron saturation velocity, and excellent chemical stability. They are also suitable for ultra-violet (UV) photodetection due to the corresponding wavelengths of GaN bandgap. To improve the optical responsivity by decreasing the dark current due to gate leakage problems and limited Schottky barrier heights in GaN-based HEMT devices, various metal-oxide-semiconductor HEMTs (MOS-HEMTs) have been devised by using atomic layer deposition (ALD), molecular beam epitaxy (MBE), metal-organic chemical vapor deposition (MOCVD), liquid phase deposition (LPD), and RF sputtering. The gate dielectrics include MgO, HfO2, Al2O3, La2O3, and TiO2. In order to provide complementary circuit operation, enhancement-mode (E-mode) devices have been lately studied using techniques of fluorine treatment, p-type capper, piezoneutralization layer, and MOS-gate structure. This work reports an Al2O3-dielectric Al0.25Ga0.75N/GaN E-mode MOS-HEMT design by using a cost-effective ozone water oxidization technique. The present ozone oxidization method advantages of low cost processing facility, processing simplicity, compatibility to device fabrication, and room-temperature operation under atmospheric pressure. It can further reduce the gate-to-channel distance and improve the transocnductance (gm) gain for a specific oxide thickness, since the formation of the Al2O3 will consume part of the AlGaN barrier at the same time. The epitaxial structure of the studied devices was grown by using the MOCVD technique. On a Si substrate, the layer structures include a 3.9 m C-doped GaN buffer, a 300 nm GaN channel layer, and a 5 nm Al0.25Ga0.75N barrier layer. Mesa etching was performed to provide electrical isolation by using an inductively coupled-plasma reactive ion etcher (ICP-RIE). Ti/Al/Au were thermally evaporated and annealed to form the source and drain ohmic contacts. The device was immersed into the H2O2 solution pumped with ozone gas generated by using an OW-K2 ozone generator. Ni/Au were deposited as the gate electrode to complete device fabrication of MOS-HEMT. The formed Al2O3 oxide thickness 7 nm and the remained AlGaN barrier thickness is 2 nm. A reference HEMT device has also been fabricated in comparison on the same epitaxial structure. The gate dimensions are 1.2 × 100 µm 2 with a source-to-drain spacing of 5 μm for both devices. The dielectric constant (k) of Al2O3 was characterized to be 9.2 by using C-V measurement. Reduced interface state density after oxidization has been verified by the low-frequency noise spectra, Hooge coefficients, and pulse I-V measurement. Improved device characteristics at temperatures of 300 K-450 K have been achieved for the present MOS-HEMT design. Consequently, Al2O3-dielectric Al0.25Ga0.75N/GaN E-mode MOS-HEMTs by using the ozone water oxidization method are reported. In comparison with a conventional Schottky-gate HEMT, the MOS-HEMT design has demonstrated excellent enhancements of 138% (176%) in gm, max, 118% (139%) in IDS, max, 53% (62%) in BVGD, 3 (2)-order reduction in IG leakage at VGD = -60 V at 300 (450) K. This work is promising for millimeter-wave integrated circuit (MMIC) and three-terminal active UV photodetector applications.

Keywords: MOS-HEMT, enhancement mode, AlGaN/GaN, passivation, ozone water oxidation, gate leakage

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Authors: Ved Kulkarni, Karthik Kini

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This experiment aims to understand how the media affects the power markets in the mainland United States and study the duration of reaction time between news updates and actual price movements. it have taken into account electric utility companies trading in the NYSE and excluded companies that are more politically involved and move with higher sensitivity to Politics. The scrapper checks for any news related to keywords, which are predefined and stored for each specific company. Based on this, the classifier will allocate the effect into five categories: positive, negative, highly optimistic, highly negative, or neutral. The effect on the respective price movement will be studied to understand the response time. Based on the response time observed, neural networks would be trained to understand and react to changing market conditions, achieving the best strategy in every market. The stock trader would be day trading in the first phase and making option strategy predictions based on the black holes model. The expected result is to create an AI-based system that adjusts trading strategies within the market response time to each price movement.

Keywords: data mining, language processing, artificial neural networks, sentiment analysis

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Authors: Shahriar Farzam, Maryam Rastgarpour

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Image denoising plays extremely important role in digital image processing. Enhancement of clinical image research based on Curvelet has been developed rapidly in recent years. In this paper, we present a method for image contrast enhancement for cone beam CT (CBCT) images based on fast discrete curvelet transforms (FDCT) that work through Unequally Spaced Fast Fourier Transform (USFFT). These transforms return a table of Curvelet transform coefficients indexed by a scale parameter, an orientation and a spatial location. Accordingly, the coefficients obtained from FDCT-USFFT can be modified in order to enhance contrast in an image. Our proposed method first uses a two-dimensional mathematical transform, namely the FDCT through unequal-space fast Fourier transform on input image and then applies thresholding on coefficients of Curvelet to enhance the CBCT images. Consequently, applying unequal-space fast Fourier Transform leads to an accurate reconstruction of the image with high resolution. The experimental results indicate the performance of the proposed method is superior to the existing ones in terms of Peak Signal to Noise Ratio (PSNR) and Effective Measure of Enhancement (EME).

Keywords: curvelet transform, CBCT, image enhancement, image denoising

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Authors: Krasimir I. Ivanov, Elitsa N. Kolentsova, Dimitar Y. Dimitrov, Georgi V. Avdeev, Tatyana T. Tabakova

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In recent research copper and manganese systems were found to be the most active in CO and organic compounds oxidation among the base catalysts. The mixed copper manganese oxide has been widely studied in oxidation reactions because of their higher activity at low temperatures in comparison with single oxide catalysts. The results showed that the formation of spinel CuxMn3−xO4 in the oxidized catalyst is responsible for the activity even at room temperature. That is why most of the investigations are focused on the hopcalite catalyst (CuMn2O4) as the best copper-manganese catalyst. Now it’s known that this is true only for CO oxidation, but not for mixture of CO and VOCs. The purpose of this study is to investigate the alumina supported copper-manganese catalysts with different Cu/Mn molar ratio in terms of oxidation of CO, methanol and dimethyl ether. The catalysts were prepared by impregnation of γ-Al2O3 with copper and manganese nitrates and the catalytic activity measurements were carried out in continuous flow equipment with a four-channel isothermal stainless steel reactor. Gas mixtures on the input and output of the reactor were analyzed with a gas chromatograph, equipped with FID and TCD detectors. The texture characteristics were determined by low-temperature (- 196 oС) nitrogen adsorption in a Quantachrome Instruments NOVA 1200e (USA) specific surface area&pore analyzer. Thermal, XRD and TPR analyses were performed. It was established that the active component of the mixed Cu-Mn/γ–alumina catalysts strongly depends on the Cu/Mn molar ratio. Highly active alumina supported Cu-Mn catalysts for CO, methanol and DME oxidation were synthesized. While the hopcalite is the best catalyst for CO oxidation, the best compromise for simultaneous oxidation of all components is the catalyst with Cu/Mn molar ratio 1:5.

Keywords: supported copper-manganese catalysts, CO, VOCs oxidation, combustion of exhaust gases

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Authors: Ana Serafimovic, Karthik Devarajan

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Non-negative matrix factorization approximates a high dimensional non-negative matrix V as the product of two non-negative matrices, W and H, and allows only additive linear combinations of data, enabling it to learn parts with representations in reality. It has been successfully applied in the analysis and interpretation of high dimensional data arising in neuroscience, computational biology, and natural language processing, to name a few. The objective of this paper is to assess a hybrid algorithm for non-negative matrix factorization with multiplicative updates. The method aims to minimize the symmetric version of Kullback-Leibler divergence known as intrinsic information and assumes that the noise is signal-dependent and that it originates from an arbitrary distribution from the exponential family. It is a generalization of currently available algorithms for Gaussian, Poisson, gamma and inverse Gaussian noise. We demonstrate the potential usefulness of the new generalized algorithm by comparing its performance to the baseline methods which also aim to minimize symmetric divergence measures.

Keywords: non-negative matrix factorization, dimension reduction, clustering, intrinsic information, symmetric information divergence, signal-dependent noise, exponential family, generalized Kullback-Leibler divergence, dual divergence

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Authors: Ali Ashtiani, Cesar Carrasco

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Accurate determination of thermo-mechanical responses of jointed concrete pavement slabs is essential to implement an effective mechanistic design. Temperature-induced curling of concrete slabs can produce premature top-down cracking in rigid pavements. Curling of concrete slabs can result from daily temperature variation through the slab thickness. The slab curling can also result from temperature gradients due hot weather construction, drying shrinkage and creep that are permanently built into the slabs. The existence of permanent curling implies that concrete slabs are not flat at zero temperature gradient. In this case, slabs may not be in full contact with the underlying base layer when subjecting to traffic. Built-in curling can be a major factor producing loss of slab support. The magnitude of stresses induced in slabs is influenced by the stiffness of the underlying foundation layers and the contact condition along the slab-foundation interface. An approach for finite element modeling of the effect of loss of slab support due to built-in curling is presented in this paper. A series of parametric studies is carried out for a pavement system loaded with a combination of traffic and thermal loads, considering different built-in curling and different foundation rigidities. The results explain the effect of loss of support in the magnitude of stresses produced in concrete slabs. The results of parametric study can also be used to evaluate whether the governing equations that are used to idealize the behavior of jointed concrete pavements and the effect of loss of support have been accurately selected and implemented in the finite element model.

Keywords: built-in curling, finite element modeling, loss of slab support, rigid pavement

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Authors: Navneet Kaur, S. D. Tiwari

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Magnetic nanoparticles possess fascinating properties which make their behavior unique in comparison to corresponding bulk materials. Superparamagnetism is one such interesting phenomenon exhibited only by small particles of magnetic materials. In this state, the thermal energy of particles become more than their magnetic anisotropy energy, and so particle magnetic moment vectors fluctuate between states of minimum energy. This situation is similar to paramagnetism of non-interacting ions and termed as superparamagnetism. The magnetization of such systems has been described by Langevin function. But, the estimated fit parameters, in this case, are found to be unphysical. It is due to non-consideration of particle size distribution. In this work, analysis of magnetization data on NiO nanoparticles is presented considering the effect of particle size distribution. Nanoparticles of NiO of two different sizes are prepared by heating freshly synthesized Ni(OH)₂ at different temperatures. Room temperature X-ray diffraction patterns confirm the formation of single phase of NiO. The diffraction lines are seen to be quite broad indicating the nanocrystalline nature of the samples. The average crystallite size are estimated to be about 6 and 8 nm. The samples are also characterized by transmission electron microscope. Magnetization of both sample is measured as function of temperature and applied magnetic field. Zero field cooled and field cooled magnetization are measured as a function of temperature to determine the bifurcation temperature. The magnetization is also measured at several temperatures in superparamagnetic region. The data are fitted to an appropriate expression considering a distribution in particle size following a least square fit procedure. The computer codes are written in PYTHON. The presented analysis is found to be very useful for estimating the particle size distribution present in the samples. The estimated distributions are compared with those determined from transmission electron micrographs.

Keywords: anisotropy, magnetization, nanoparticles, superparamagnetism

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Authors: Raed Kouta

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A fuel cell is a multi-physical system. Its electrical performance depends on chemical, electrochemical, fluid, and mechanical parameters. Many studies focus on physical and chemical aspects. Our study contributes to the evaluation of the influence of mechanical aspects on the performance of a fuel cell. This study is carried out as part of a reliability approach. Reliability modeling allows to consider the uncertainties of the incoming parameters and the probabilistic modeling of the outgoing parameters. The fuel cell studied is the one often used in land, sea, or air transport. This is the Low-Temperature Proton Exchange Membrane Fuel Cell (PEMFC). This battery can provide the required power level. One of the main scientific and technical challenges in mastering the design and production of a fuel cell is to know its behavior in its actual operating environment. The study proposes to highlight the influence on the production of electrical energy: Mechanical design and manufacturing parameters and their uncertainties (Young module, GDL porosity, permeability, etc.). The influence of the geometry of the bipolar plates is also considered. An experimental design is proposed with two types of materials as well as three geometric shapes for three joining pressures. Other experimental designs are also proposed for studying the influence of uncertainties of mechanical parameters on cell performance. - Mechanical (static, dynamic) and thermal (tightening - compression, vibrations (road rolling and tests on vibration-climatic bench, etc.) loads. This study is also carried out according to an experimental scheme on a fuel cell system for vibration loads recorded on a vehicle test track with three temperatures and three expected performance levels. The work will improve the coupling between mechanical, physical, and chemical phenomena.

Keywords: fuel cell, mechanic, reliability, uncertainties

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Authors: M. S. Tajul Islam, Md. Zahangir Alam

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To enhance biogas production through anaerobic digestion, the application of various type of pre-treatment method has some limitations in terms of sustainable environmental management. Many studies on pretreatments especially chemical and physical processes are carried out to evaluate the anaerobic digestion for enhanced biogas production. Among the pretreatment methods acid and alkali pre-treatments gained the highest importance. Previous studies have showed that although acid and alkali pretreatment has significant effect on degradation of biomass, these methods have some negative impact on environment due to their hazard in nature while enzymatic pre-treatment is environmentally friendly. One of the constrains to use of enzyme in pretreatment process for biogas production is high cost which is currently focused to reduce cost through fermentation of waste-based media. As such palm oil mill effluent (POME) as an abundant resource generated during palm oil processing at mill is being used a potential fermentation media for enzyme production. This low cost of enzyme could be an alternative to biogas pretreatment process. This review is to focus direct application of enzyme as enzymatic pre-treatment on POME to enhanced production of biogas.

Keywords: POME, enzymatic pre-treatment, biogas, lignocellulosic biomass, anaerobic digestion

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Authors: María Reveles-Miranda, Daniella Pacheco-Catalán

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Sierra Papacal commissary is located north of Merida, Yucatan, México, where the indigenous Maya population predominates. Due to its location, the region has an elevation of fewer than 4.5 meters above sea level, with a high risk of flooding associated with storms and hurricanes and a high vulnerability of infrastructure and housing in the presence of strong gusts of wind. In environmental contingencies, the challenge is providing an autonomous electrical supply using renewable energy sources that cover vulnerable populations' health, food, and water pumping needs. To address this challenge, a hybrid energy storage module is proposed for the emergency photovoltaic (PV) system of the community shelter in Sierra Papacal, Yucatán, which combines high-energy-density batteries and high-power-density supercapacitors (SC) in a single module, providing a quick response to energy demand, reducing the thermal stress on batteries and extending their useful life. Incorporating SC in energy storage modules can provide fast response times to power variations and balanced energy extraction, ensuring a more extended period of electrical supply to vulnerable populations during contingencies. The implemented control strategy increases the module's overall performance by ensuring the optimal use of devices and balanced energy exploitation. The operation of the module with the control algorithm is validated with MATLAB/Simulink® and experimental tests.

Keywords: batteries, community shelter, environmental contingencies, hybrid energy storage, isolated photovoltaic system, supercapacitors

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Authors: I. Kurashvili, G. Darsavelidze, T. Kimeridze, G. Chubinidze, I. Tabatadze

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At present, a number of modern semiconductor devices based on SiGe alloys have been created in which the latest achievements of high technologies are used. These devices might cause significant changes to networking, computing, and space technology. In the nearest future new materials based on SiGe will be able to restrict the A³B⁵ and Si technologies and firmly establish themselves in medium frequency electronics. Effective realization of these prospects requires the solution of prediction and controlling of structural state and dynamical physical –mechanical properties of new SiGe materials. Based on these circumstances, a complex investigation of structural defects and structural-sensitive dynamic mechanical characteristics of SiGe alloys under different external impacts (deformation, radiation, thermal cycling) acquires great importance. Internal friction (IF) and shear modulus temperature and amplitude dependences of the monocrystalline boron-doped Si_1-xGe_x(x≤0.05) alloys grown by Czochralski technique is studied in initial and ⁶⁰Co gamma-irradiated states. In the initial samples, a set of dislocation origin relaxation processes and accompanying modulus defects are revealed in a temperature interval of 400-800 ⁰C. It is shown that after gamma-irradiation intensity of relaxation internal friction in the vicinity of 280 ⁰C increases and simultaneously activation parameters of high temperature relaxation processes reveal clear rising. It is proposed that these changes of dynamical mechanical characteristics might be caused by a decrease of the dislocation mobility in the Cottrell atmosphere enriched by the radiation defects.

Keywords: internal friction, shear modulus, gamma-irradiation, SiGe alloys

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Authors: Bung-Orn Hemung, Nachayut Chanshotigul, Koo Bok Chin

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Tomato pomace (TP) is the waste from tomato processing plants and its utilization as food ingredient may provide sustainable industry by reducing waste. TP was extracted by ethanol using microwave-assisted method at 180W for 90s. The ethanol was evaporated out, and an extract was encapsulated with maltodextrin (1:10) by spray drying to obtain an encapsulated TP extract (ETPE). The redness (a value) of ETPE powder was 6.5±0.05, and it was used as natural ingredient in the low-nitrite chicken sausage. Chicken emulsion sausage was prepared at 25 mg/kg of nitrite for being control. Effect of ETPE (1.0%) was evaluated along with the reference (150 mg/kg of nitrite without ETPE). The redness (a value) of sausage with ETPE was found at 6.8±0.03, which was higher than those of reference and control, which were at 4.8±.022 and 5.1±0.15, respectively. However, hardness, expressible moisture content and cooking yield values were reduced slightly. During storage at 10 °C in the air packed condition for 1 week, changes in color, pH, redness, and thiobarbituric acid reactive substances value were not significantly different. However, total microbial count of sausage samples with ETPE was lower than control for a 1 log cycle, suggesting microbial stability. Therefore, the addition of ETPE could be an alternative strategy to utilize TP as a natural colorant and antimicrobial agent to extend the shelf life of low-nitrite chicken sausage.

Keywords: antimicrobial ingredient, chicken sausage, ethanolic extract, low-nitrite sausage, tomato pomace

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Authors: Dhivya Arumugam, Kaliyappan Thananjeyan

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The monomer of (3-((4-(methacryloyloxy)phenylimino)methyl)-2-hydroxybenzoic acid) schiff base polymer was prepared by reacting methacryloyl chloride with imine compound derived from 3-formylsalisylic acid and 4- aminophenol. The monomer was polymerized in DMF at 70oC using benzoyl peroxide as free radical initiator. Polymer metal complex was obtained in DMF solution of polymer with aqueous solution of metal ions. The polymer and the polymer metal complex were characterized by elemental analysis and spectral studies. The elemental analysis data suggest that the metal to ligand ratio is 1:1 and hence, it acts as a binucleating compartmental ligand. The IR spectral data of these complexes suggest that the metals are coordinated through nitrogen of the imine group, the oxygen of carboxylate ion and the oxygen of the phenolic –OH group which also acts as the bridging ligand. The electronic spectra and magnetic moments of the polychelates shows that octahedral and square planar structure for Ni(II) and Cu(II) complexes respectively. X-ray diffraction studies revealed that polychelates are highly crystalline. The thermal and electrical properties, catalytic activity, structure property relationships are discussed. Further the synthesized polymer was used for metal uptake studies from waste water, which is one of the effective waste water treatment strategies. And also, the polymers and polychelates were investigated for antimicrobial activity with various microorganisms by using agar well diffusion method and the results have been discussed.

Keywords: acyclic compartmental ligands, binucleating ligand, 3-formylsalicylic acid, free radical polymerization, polluting ions, polychelate

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Authors: Khue Nguyen Dinh, Loi Nguyen Van, Thanh Nguyen Nhu

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In this paper, we propose an adaptive method to resolve ambiguities and a ghost target removal process to extract targets detected by a ground-based pulse-Doppler radar using medium pulse repetition frequency (PRF) waveforms. The ambiguity resolution method is an adaptive implementation of the coincidence algorithm, which is implemented on a two-dimensional (2D) range-velocity matrix to resolve range and velocity ambiguities simultaneously, with a proposed clustering filter to enhance the anti-error ability of the system. Here we consider the scenario of multiple target environments. The ghost target removal process, which is based on the power after Doppler processing, is proposed to mitigate ghosting detections to enhance the performance of ground-based radars using a short PRF schedule in multiple target environments. Simulation results on a ground-based pulsed Doppler radar model will be presented to show the effectiveness of the proposed approach.

Keywords: ambiguity resolution, coincidence algorithm, medium PRF, ghosting removal

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Authors: Shrey Sharma, Gunjan Kumar Verma

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High density electrical prospecting has been widely used in groundwater investigation, civil engineering and environmental survey. For efficient inversion, the forward modeling routine, sensitivity calculation, and inversion algorithm must be efficient. This paper attempts to provide a brief summary of the past and ongoing developments of the method. It includes reviews of the procedures used for data acquisition, processing and inversion of electrical resistivity data based on compilation of academic literature. In recent times there had been a significant evolution in field survey designs and data inversion techniques for the resistivity method. In general 2-D inversion for resistivity data is carried out using the linearized least-square method with the local optimization technique .Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Continued developments in computation technology, as well as fast data inversion techniques and software, have made it possible to use optimization techniques to obtain model parameters to a higher accuracy. A brief discussion on the limitations of the electrical resistivity method has also been presented.

Keywords: inversion, limitations, optimization, resistivity

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Authors: Nor-Edine Abriak, Mouhamadou Amar, Mahfoud Benzerzour

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The transition to a more sustainable economy is directed by a reduction in the consumption of raw materials in equivalent production. The recovery of byproducts and especially the dredged sediment as mineral addition in cements matrix represents an alternative to reduce raw material consumption and construction sector’s carbon footprint. However, the efficient use of sediment requires adequate and optimal treatment. Several processing techniques have so far been applied in order to improve some physicochemical properties. The heat treatment by calcination was effective in removing the organic fraction and activates the pozzolanic properties. In this article, the effect of the optimized heat treatment of marine sediments in the physico-mechanical and environmental properties of mortars are shown. A finding is that the optimal substitution of a portion of cement by treated sediments by calcination at 750 °C helps to maintain or improve the mechanical properties of the cement matrix in comparison with a standard reference mortar. The use of calcined sediment enhances mortar behavior in terms of mechanical strength and durability. From an environmental point of view and life cycle, mortars formulated containing treated sediments are considered inert with respect to the inert waste storage facilities reference (ISDI-France).

Keywords: sediment, calcination, cement, reuse

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Authors: Olumide J. Adedapo

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In this work, geothermal energy resource maps of the Niger Delta Basin were constructed using borehole thermal log data from over 300 deep wells. Three major geothermal anomalies were delineated and quantitatively interpreted in both onshore and offshore parts of the Niger Delta. The geothermal maps present the distribution of geothermal energy stored in the sedimentary rock mass in two ways: the accessible resources in depth interval 0-4000 m and static geothermal energy resources stored in the complete sedimentary infill of the basin (from the ground surface to the basement). The first map shows two major onshore anomalies, one in the north (with maximum energy values, 800 GJ/m2), another in the east to northeastern part (maximum energy values of 1250–1500 GJ/m2). Another two major anomalies occur offshore, one in the south with values of 750-1000 GJ/m2, occurring at about 100 km seawards and the other, in the southwest offshore with values 750-1250 GJ/m2, still at about 100 km from the shore. A second map of the Niger Delta shows a small anomaly in the northern part with the maximum value of 1500 GJ/m2 and a major anomaly occurring in the eastern part of the basin, onshore, with values of 2000-3500 GJ/m2. Offshore in the south and southwest anomalies in the total sedimentary rock mass occur with highest values up to 4000GJ/m2, with the southwestern anomaly extending west to the shore. It is much of interest to note the seaward–westward extension of these anomalies both in size, configuration, and magnitude for the geothermal energy in the total sedimentary thickness to the underlying basement. These anomalous fields show the most favourable locations and areas for further work on geothermal energy resources.

Keywords: geothermal energy, offshore, Niger delta, basin

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Authors: Duy Nhat Tran, Van Tien Pham, Quang Trung Trinh, Tien Hai Tran, Van Cong Bui

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In recent years, artificial intelligence and the Internet of Things have experienced significant advancements. Collecting image data and real-time analysis and processing of tasks have become increasingly popular in various aspects of life. Optical scanning devices are widely used to observe and analyze different environments, whether fixed outdoors, mounted on mobile devices, or used in unmanned aerial vehicles. As a result, the interaction between the physical environment and these devices has become more critical in terms of safety. Two commonly used methods for addressing these challenges are active and passive approaches. Each method has its advantages and disadvantages, but combining both methods can lead to higher efficiency. One solution is to utilize direct-drive motors for position control and real-time feedback within the operational range to determine appropriate control parameters with high precision. If the maximum motor torque is smaller than the inertial torque and the rotor reaches the operational limit, the spring system absorbs the impact force. Numerous experiments have been conducted to demonstrate the effectiveness of device protection during operation.

Keywords: optical device, collision safety, collision absorption, precise mechanics

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Authors: Dalal N. Hammod, Ekhlas K. Gbashi

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Today, cryptography is used in many applications to achieve high security in data transmission and in real-time communications. AES has long gained global acceptance and is used for securing sensitive data in various industries but has suffered from slow processing and take a large time to transfer data. This paper suggests a method to enhance Advance Encryption Standard (AES) Algorithm based on time and permutation. The suggested method (MAES) is based on modifying the SubByte and ShiftRrows in the encryption part and modification the InvSubByte and InvShiftRows in the decryption part. After the implementation of the proposal and testing the results, the Modified AES achieved good results in accomplishing the communication with high performance criteria in terms of randomness, encryption time, storage space, and avalanche effects. The proposed method has good randomness to ciphertext because this method passed NIST statistical tests against attacks; also, (MAES) reduced the encryption time by (10 %) than the time of the original AES; therefore, the modified AES is faster than the original AES. Also, the proposed method showed good results in memory utilization where the value is (54.36) for the MAES, but the value for the original AES is (66.23). Also, the avalanche effects used for calculating diffusion property are (52.08%) for the modified AES and (51.82%) percentage for the original AES.

Keywords: modified AES, randomness test, encryption time, avalanche effects

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Authors: Muhammad Muzamil Khan, Asadullah Madni, Nina Filipczek, Jiayi Pan, Nayab Tahir, Hassan Shah, Vladimir Torchilin

Abstract:

Lipid-polymer hybrid nanoparticles (LPHNP) are delivery systems for controlled drug delivery at tumor sites. The superior biocompatible properties of lipid and structural advantages of polymer can be obtained via this system for controlled drug delivery. In the present study, cisplatin-loaded lipid-chitosan hybrid nanoparticles were formulated by the single step ionic gelation method based on ionic interaction of positively charged chitosan and negatively charged lipid. Formulations with various chitosan to lipid ratio were investigated to obtain the optimal particle size, encapsulation efficiency, and controlled release pattern. Transmission electron microscope and dynamic light scattering analysis demonstrated a size range of 181-245 nm and a zeta potential range of 20-30 mV. Compatibility among the components and the stability of formulation were demonstrated with FTIR analysis and thermal studies, respectively. The therapeutic efficacy and cellular interaction of cisplatin-loaded LPHNP were investigated using in vitro cell-based assays in A2780/ADR ovarian carcinoma cell line. Additionally, the cisplatin loaded LPHNP exhibited a low toxicity profile in rats. The in-vivo pharmacokinetics study also proved a controlled delivery of cisplatin with enhanced mean residual time and half-life. Our studies suggested that the cisplatin-loaded LPHNP being a promising platform for controlled delivery of cisplatin in cancer therapy.

Keywords: cisplatin, lipid-polymer hybrid nanoparticle, chitosan, in vitro cell line study

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Authors: Lucian Mocan, Cristian Matea, Flaviu A. Tabaran, Teodora Mocan, Cornel Iancu

Abstract:

Introduction: Due to antibiotic resistance, systemic infections caused by Meticilin resistant Staphyloccocous Aureus (MRSA) are the main cause of millions of deaths each year. Development of new active biomolecules that are highly effective and refractory to antibiotic resistance may open new avenues in the field of antimicrobial therapy. In this research, we have focused on the development of a novel nanobiosystem with high affinity for MRSA microorganism to mediate its selective laser thermal ablation. Materials and Methods: Gold nanoparticles (15nm in diameter) linked to a specific antibody against MRSA surface were selectively delivered (at various concentrations and incubation times) and internalized into MRSA microorganism following the treatment these multidrug-resistant bacteria were irradiated using a 2w, 808 nm LASER. Results and Discussions: The post-irradiation necrotic rate ranged from 51.2% (for 1 mg/L) to 87.3% (for 50 mg/L) at 60 seconds (p<0.001), while at 30 minute the necrotic rate increased from 64.3% (1 mg/L) to 92.1% (50 mg/L), p value<0.001. Significantly lower apoptotic rates were obtained in irradiated MRSA treated with GNPs only (control) treated for 60 seconds and 30 minutes at concentrations ranging from 1 mg/L to 50 mg/L. We show here that the optimal LASER mediated the necrotic effect of MRSA after incubation with anti-MRSA-Ab was obtained at a concentration of 50 mg/L. Conclusion: In the presented research, we obtained a very efficacious pulse laser mode treatment of individual MRSA agents with minimal effects on the surrounding medium, providing highly localized destruction only for MRSA microorganism.

Keywords: MRSA, photothermolysis, antibiotic resistance, gold nanoparticles

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Authors: Deawan Rakin Ahamed Remal, Sinthia Chowdhury, Sharun Akter Khushbu, Sheak Rashed Haider Noori

Abstract:

Native Speech to text synthesis has its own leverage for the purpose of mankind. The extensive nature of art to speaking different accents is common but the purpose of communication between two different accent types of people is quite difficult. This problem will be motivated by the extraction of the wrong perception of language meaning. Thus, many existing automatic speech recognition has been placed to detect text. Overall study of this paper mentions a review of NSTTR (Native Speech Text to Text Recognition) synthesis compared with Text to Text recognition. Review has exposed many text to text recognition systems that are at a very early stage to comply with the system by native speech recognition. Many discussions started about the progression of chatbots, linguistic theory another is rule based approach. In the Recent years Deep learning is an overwhelming chapter for text to text learning to detect language nature. To the best of our knowledge, In the sub continent a huge number of people speak in Bangla language but they have different accents in different regions therefore study has been elaborate contradictory discussion achievement of existing works and findings of future needs in Bangla language acoustic accent.

Keywords: TTR, NSTTR, text to text recognition, deep learning, natural language processing

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Authors: Antonio Gioiosa, Simone Doanti, Eric Flumerfelt, Luca Morescalchi, Elena Pedreschi, Gianantonio Pezzullo, Ryan A. Rivera, Franco Spinella

Abstract:

The Mu2e experiment at Fermilab aims to measure the charged-lepton flavour violating neutrino-less conversion of a negative muon into an electron in the field of an aluminum nucleus. With the expected experimental sensitivity, Mu2e will improve the previous limit of four orders of magnitude. The Mu2e data acquisition (DAQ) system provides hardware and software to collect digitized data from the tracker, calorimeter, cosmic ray veto, and beam monitoring systems. Mu2e’s trigger and data acquisition system (TDAQ) uses otsdaq as its solution. developed at Fermilab, otsdaq uses the artdaq DAQ framework and art analysis framework, under-the-hood, for event transfer, filtering, and processing. Otsdaq is an online DAQ software suite with a focus on flexibility and scalability while providing a multi-user, web-based interface accessible through the Chrome or Firefox web browser. The detector read out controller (ROC) from the tracker and calorimeter stream out zero-suppressed data continuously to the data transfer controller (DTC). Data is then read over the PCIe bus to a software filter algorithm that selects events which are finally combined with the data flux that comes from a cosmic ray veto system (CRV).

Keywords: trigger, daq, mu2e, Fermilab

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Authors: A. B. Chehreh, M. Grätzel, M. Klein, J. P. Bergmann, F. Walther

Abstract:

Friction stir welding (FSW) is an advantageous method in the thermal joining processes, featuring the welding of various dissimilar and similar material combinations, joining temperatures below the melting point which prevents irregularities such as pores and hot cracks as well as high strengths mechanical joints near the base material. The FSW process consists of a rotating tool which is made of a shoulder and a probe. The welding process is based on a rotating tool which plunges in the workpiece under axial pressure. As a result, the material is plasticized by frictional heat which leads to a decrease in the flow stress. During the welding procedure, the material is continuously displaced by the tool, creating a firmly bonded weld seam behind the tool. However, the mechanical properties of the weld seam are affected by the design and geometry of the tool. These include in particular microstructural and surface properties which can favor crack initiation. Following investigation compares the dynamic properties of FSW weld seams with conventional and stationary shoulder geometry based on load increase test (LIT). Compared to classical Woehler tests, it is possible to determine the fatigue strength of the specimens after a short amount of time. The investigations were carried out on a robotized welding setup on 2 mm thick EN AW 5754 aluminum alloy sheets. It was shown that an increased tensile and fatigue strength can be achieved by using the stationary shoulder concept. Furthermore, it could be demonstrated that the LIT is a valid method to describe the fatigue behavior of FSW weld seams.

Keywords: aluminum alloy, fatigue performance, fracture, friction stir welding

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Authors: Hossein Askarinejad, Manicka Dhanasekar

Abstract:

In railway tracks, two adjacent rails are either welded or connected using bolted jointbars. In recent years the number of bolted rail joints is reduced by introduction of longer rail sections and by welding the rails at location of some joints. However, significant number of bolted rail joints remains in railways around the world as they are required to allow for rail thermal expansion or to provide electrical insulation in some sections of track. Regardless of the quality and integrity of the jointbar and bolt connections, the bending stiffness of jointbars is much lower than the rail generating large deflections under the train wheels. In addition, the gap or surface discontinuity on the rail running surface leads to generation of high wheel-rail impact force at the joint gap. These fundamental weaknesses have caused high rate of failure in track components at location of rail joints resulting in significant economic and safety issues in railways. The mechanical behavior of railway track at location of joints has not been fully understood due to various structural and material complexities. Although there have been some improvements in the methods for analysis of track at jointed rails in recent years, there are still uncertainties concerning the accuracy and reliability of the current methods. In this paper the current methods in analysis of track with a rail joint are critically evaluated and the new advances and recent research outcomes in this area are discussed. This research is part of a large granted project on rail joints which was defined by Cooperative Research Centre (CRC) for Rail Innovation with supports from Australian Rail Track Corporation (ARTC) and Queensland Rail (QR).

Keywords: jointed rails, railway mechanics, track dynamics, wheel-rail interaction

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Authors: Mayowa Philips Ibitola, Abe Oluwaseun Banji, Olorunfemi Akinade-Solomon

Abstract:

A total of 20 bottom sediment samples were collected from the Lekki Lagoon during the wet and dry season. The study was carried out to determine the textural characteristics, sediment distribution pattern and energy of transportation within the lagoon system. The sediment grain sizes and depth profiling was analyzed using dry sieving method and MATLAB algorithm for processing. The granulometric reveals fine grained sand both for the wet and dry season with an average mean value of 2.03 ϕ and -2.88 ϕ, respectively. Sediments were moderately sorted with an average inclusive standard deviation of 0.77 ϕ and -0.82 ϕ. Skewness varied from strongly coarse and near symmetrical 0.34- ϕ and 0.09 ϕ. The kurtosis average value was 0.87 ϕ and -1.4 ϕ (platykurtic and leptokurtic). Entirely, the bathymetry shows an average depth of 4.0 m. The deepest and shallowest area has a depth of 11.2 m and 0.5 m, respectively. High concentration of fine sand was observed at deep areas compared to the shallow areas during wet and dry season. Statistical parameter results show that the overall sediments are sorted, and deposited under low energy condition over a long distance. However, sediment distribution and sediment transport pattern of Lekki Lagoon is controlled by a low energy current and the down slope configuration of the bathymetry enhances the sorting and the deposition rate in the Lekki Lagoon.

Keywords: Lekki Lagoon, Marine sediment, bathymetry, grain size distribution

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Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

Abstract:

Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

Procedia PDF Downloads 130