Search results for: fast Fourier algorithms

Authors: Noor Ul Huda, Mushtaq Ahmed, Nadia Mushtaq, Naila Sher, Rahmat Ali Khan

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Purpose: The green synthesis of AgNPs has been favored over chemical synthesis due to their distinctive properties such as high dispersion, surface-to-volume ratio, low toxicity, and easy preparation. In the present work, the biosynthesis of AgNPs (KE-AgNPs) was carried out in one step by using the traditionally used plant Kickxia elatine (KE) extract and then investigated its enzyme inhibiting activity against rat’s brain acetylcholinesterase (AChE) in vitro. Methods: KE-AgNPs were synthesized from 1mM AgNO₃ using KE extract and characterized by UV–spectroscopy, SEM, EDX, XRD, and FTIR analysis. Rat’s brain acetylcholinesterase (AChE) inhibition activity was evaluated by the standard protocol. Results: UV–spectrum at 416 nm confirmed the formation of KE-AgNPs. X-ray diffraction (XRD) pattern presented 2θ values corresponding to the crystalline nature of KE-AgNPs with an average size of 42.47nm. The scanning electron microscope (SEM) analysis confirmed the presence of spherical-shaped and huge density KE-AgNPs with a size of 50nm. Fourier transform infrared spectroscopy (FT-IR) suggested that the functional groups present in KE extract and on the surface of KE-AgNPs are responsible for the stability of biosynthesized NPs. Energy dispersive X-ray (EDX) displayed an intense sharp peak at 3.2 keV, presenting that Ag was the chief element with 61.67%. Both KE extract and KE-AgNPs showed good and potent anti-AChE activity, with higher inhibition potential at a concentration of 175 µg/ml. Statistical analysis showed that both KEE and AgNPs exhibited non-competitive type inhibition against AChE, i.e., Vmax decreased (34.17-68.64% and 22.29- 62.10%) in the concentration-dependent mode for KEE and KE-AgNPs respectively and while Km values remained constant. Conclusions: KEE and KE-AgNPs can be considered an inhibitor of rats’ brain AChE, and the synthesis of KE-AgNPs-based drugs can be used as a cheaper and alternative option against diseases such as Alzheimer’s disease.

Keywords: Kickxia elatine, AgNPs, brain homogenate, acetylcholinesterase, kinetics

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Authors: Nathalia Florencia Barros Azeredo, Josué Martins Gonçalves, Pamela De Oliveira Rossini, Koiti Araki, Lucio Angnes

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This work demonstrates the electroanalysis of uric acid (UA) at very low working potential (0 V vs Ag/AgCl) directly in body fluids such as saliva and sweat using electrodes modified with mixed -Ni0.75Zn0.25(OH)2 nanoparticles exhibiting stable electrocatalytic responses from alkaline down to weakly acidic media (pH 14 to 3 range). These materials were prepared for the first time and fully characterized by TEM, XRD, and spectroscopic techniques. The electrochemical properties of the modified electrodes were evaluated in a fast and simple procedure for uric acid analyses based on cyclic voltammetry and chronoamperometry, pushing down the detection and quantification limits (respectively of 2.3*10-8 and 7.6*10-8 mol L-1) with good repeatability (RSD = 3.2% for 30 successive analyses pH 14). Finally, the possibility of real application was demonstrated upon realization of unexpectedly robust and sensitive modified FTO (fluorine doped tin oxide) glass and screen-printed sensors for measurement of uric acid directly in real saliva and sweat samples, with no significant interference of usual concentrations of ascorbic acid, acetaminophen, lactate and glucose present in those body fluids (Fig. 1).

Keywords: nickel hydroxide, mixed catalyst, uric acid sensors, biofluids

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Authors: Ali Berkan Ural

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This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

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Authors: Odunayo Christy Atewolara-Odule, Olapeju O. Aiyelaagbe

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The search for new natural anti-oxidants has grown tremendously over the years because reactive oxygen species (ROS) production and oxidative stress have been linked to a large number of human degenerative diseases, such as cancer, cardiovascular diseases, inflammation, and diabetes. Tapinanthus bangwensis, a parasitic plant commonly known as mistletoe belonging to the Loranthaceae family, is mostly employed traditionally to treat inflammation, cancer, diabetes, and hypertension to mention a few. In this study, air-dried pulverized leaves and stem of Tapinanthus bangwensis were successively extracted with n-hexane, ethyl acetate, and methanol to give the corresponding crude extracts. The extracts were purified by column chromatography and high-performance liquid chromatography to give the isolated compounds. Structural elucidation was done using mass spectrometry, Fourier transform infra-red, 1D and 2D NMR spectroscopy. The antioxidant activity of the compounds was evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ascorbic acid as standard. Three compounds; Friedelin, Eudesmic acid (3,4,5-trimethoxybenzoic) and Methyl-3,4,5-trimethoxybenzoate were isolated from the extracts of Tapinanthus bangwensis. Friedelin was isolated from the ethyl acetate extract of the stem while the two other compounds were isolated from the methanol extract of the leaves. The percentages of free radical scavenging activities of the compounds are as follows: Friedelin, 73.69%, methyl-3,4,5-trimethoxybenzoate, 79.33% and eudesmic, 87.68% anti-oxidant activity which were quite comparable to 93.96% given by ascorbic acid. We are reporting, to our best knowledge, for the first time the occurrence of friedelin and eudesmic acid in Tapinanthus bangwensis. The high anti-oxidant activity of these compounds supports the use of this plant in the management of diabetes and hypertension as they will be useful in combating complications arising from the disease.

Keywords: column chromatography, eudesmic acid, friedelin, Tapinanthus bangwensis

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Authors: Sahin Yakut, H. Kemal Ulutas, Deniz Deger

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Plasma Assisted Physical Vapor Deposition (PAPVD) method used to produce Poly(ethylene oxide) (pPEO) thin films. Depositions were progressed at various plasma discharge powers as 0, 2, 5 and 30 W for pPEO at 500nm film thicknesses. The capacitance and dielectric dissipation of the thin films were measured at 0,1-107 Hz frequency range and 173-353 K temperature range by an impedance analyzer. Then, alternative conductivity (σac) and activation energies were derived from capacitance and dielectric dissipation. σac of conventional PEO (PEO precursor) was measured to determine the effect of plasma discharge. Differences were observed between the alternative conductivity of PEO’s and pPEO’s depending on plasma discharge power. By this purpose, structural characterization techniques such as Differential Scanning Calorimetry (DSC) and Fourier Transform Infrared Spectroscopy (FT-IR) were applied on pPEO thin films. Structural analysis showed that density of crosslinking is plasma power dependent. The crosslinking density increases with increasing plasma discharge power and this increase is displayed as increasing dynamic glass transition temperatures at DSC results. Also, shifting of frequencies of some type of bond vibrations, belonging to bond vibrations produced after fragmentation because of plasma discharge, were observed at FTIR results. The dynamic glass transition temperatures obtained from alternative conductivity results for pPEO consistent with the results of DSC. Activation energies exhibit Arrhenius behavior. Activation energies decrease with increasing plasma discharge power. This behavior supports the suggestion expressing that long polymer chains and long oligomers are fragmented into smaller oligomers or radicals.

Keywords: activation energy, dielectric spectroscopy, organic thin films, plasma polymer

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Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang

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Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.

Keywords: acute hepatitis, medical resource cost, artificial neural network, support vector regression

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Authors: Mohanad Al-Behadili, Djamila Ouelhadj

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In this paper, a specific type of vehicle routing problem under stochastic demand (SVRP) is considered. This problem is of great importance because it models for many of the real world vehicle routing applications. This paper used a robust optimisation model to solve the problem along with the novel Simulation-Particle Swarm Optimisation (Sim-PSO) approach. The proposed Sim-PSO approach is based on the hybridization of the Monte Carlo simulation technique with the PSO algorithm. A comparative study between the proposed model and the Sim-PSO approach against other solution methods in the literature has been given in this paper. This comparison including the Analysis of Variance (ANOVA) to show the ability of the model and solution method in solving the complicated SVRP. The experimental results show that the proposed model and Sim-PSO approach has a significant impact on the obtained solution by providing better quality solutions comparing with well-known algorithms in the literature.

Keywords: stochastic vehicle routing problem, robust optimisation model, Monte Carlo simulation, particle swarm optimisation

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Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade

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The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.

Keywords: automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection

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Authors: Sandesh Achar

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Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

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Authors: Qi Lu, Jian Deng, Daishun Huang, Chao Guo

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The lead cooled fast reactor is considered as one of the most potential Generation IV nuclear systems due to the low working pressure, the appreciable neutron economy, and the considerable passive characteristics. Meanwhile, the lead bismuth eutectic (LBE) has the related advantages of lead with the weaker corrosiveness, which has been paid much attention by recent decades. Moreover, the sub-channel code is a necessary analysis tool for the reactor thermal-hydraulic design and safety analysis, which has been developed combined with the accumulation of LBE experimental data and the understanding of physical phenomena. In this study, a sub-channel code available for LBE was developed, and the corresponding geometric characterization method of typical sub-channels was described in detail, especially for for the fuel assembly with wire spacer. As for this sub-channel code, the transversal thermal conduction through gap was taken into account. In addition, the physical properties, the heat transfer model, the flow resistance model and the turbulent mixing model were analyzed. Finally, the thermal-hydraulic experiments of LBE conducted on THEADES (THErmal-hydraulics and Ads DESign) were selected as the evaluation data of this sub-channel code, including 19 rods with wire spacer, and the calculated results were in good agreement with the experimental results.

Keywords: lead bismuth eutectic, sub-channel code, wire spacer, transversal thermal conduction

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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: Ling Ai Wong, Hussain Shareef, Azah Mohamed, Ahmad Asrul Ibrahim

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The installation of photovoltaic based distributed generation (PVDG) in active distribution system can lead to voltage fluctuation due to the intermittent and unpredictable PVDG output power. This paper presented a method in mitigating the voltage rise by optimally locating and sizing the battery energy storage system (BESS) in PVDG integrated distribution network. The improved firefly algorithm is used to perform optimal placement and sizing. Three objective functions are presented considering the voltage deviation and BESS off-time with state of charge as the constraint. The performance of the proposed method is compared with another optimization method such as the original firefly algorithm and gravitational search algorithm. Simulation results show that the proposed optimum BESS location and size improve the voltage stability.

Keywords: BESS, firefly algorithm, PVDG, voltage fluctuation

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Authors: Yinheng Li

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The remarkable advancements in large language models (LLMs) have brought about significant improvements in natural language processing tasks. This paper presents a comprehensive review of in-context learning techniques, focusing on different types of prompts, including discrete, continuous, few-shot, and zero-shot, and their impact on LLM performance. We explore various approaches to prompt design, such as manual design, optimization algorithms, and evaluation methods, to optimize LLM performance across diverse tasks. Our review covers key research studies in prompt engineering, discussing their methodologies and contributions to the field. We also delve into the challenges faced in evaluating prompt performance, given the absence of a single ”best” prompt and the importance of considering multiple metrics. In conclusion, the paper highlights the critical role of prompt design in harnessing the full potential of LLMs and provides insights into the combination of manual design, optimization techniques, and rigorous evaluation for more effective and efficient use of LLMs in various Natural Language Processing (NLP) tasks.

Keywords: in-context learning, prompt engineering, zero-shot learning, large language models

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Authors: Mohamed Abd Elfattah Ibraheem Elghrbawy

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Biodeterioration of cultural heritage is a complex process which is caused by the interaction of many physical, chemical and biological agents; the growth of microorganisms can cause staining, cracking, powdering, disfigurement and displacement of monuments material, which leads to the permanent loss of monuments material. Organisms causing biodeterioration on monuments have usually been controlled by chemical products (biocides). In order to overcome the impact of biocides on the environment, human health and monument substrates, alternative tools such as antimicrobial agents from natural products can be used for monuments conservation and protection. The problem is how to formulate antibacterial agents with high efficiency and low toxicity. Various types of biodegradable metal nanoparticles (MNPs) have many applications in plant extract delivery. So, Nano-encapsulation of metal and natural antimicrobial agents using polymers such as chitosan increases their efficacy, specificity and targeting ability. Green synthesis and characterization of metal nanoparticles such as silver with natural products extracted from some plants having antimicrobial properties, using the ecofriendly method one pot synthesis. Encapsulation of the new synthesized mixture using some biopolymers such as chitosan nanoparticles. The dispersions and homogeneity of the antimicrobial heterogeneous metal nanoparticles encapsulated by biopolymers will be characterized and confirmed by Fourier Transform Infrared Spectroscopy (FTIR), Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM) and Zeta seizer. The effect of the antimicrobial biopolymer metal nano-formulations on normal human cell lines will be investigated to evaluate the environmental safety of these formulations. The antimicrobial toxic activity of the biopolymeric antimicrobial metal nanoparticles formulations will be will be investigated to evaluate their efficiency towards different pathogenic bacteria and fungi.

Keywords: antimicrobial, biodeterioration, chitosan, cultural heritage, silver

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Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

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Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

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Authors: Francis Alterado, Jennifer Enriquez

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Semantic Based Analysis in Complaint Management System with Analytics is an enhanced tool of providing complaints by the clients as well as a mechanism for Palawan Polytechnic College to gather, process, and monitor status of these complaints. The study has a mobile application that serves as a remote facility of communication between the students and the school management on the issues encountered by the student and the solution of every complaint received. In processing the complaints, text mining and clustering algorithms were utilized. Every module of the systems was tested and based on the results; these are 100% free from error before integration was done. A system testing was also done by checking the expected functionality of the system which was 100% functional. The system was tested by 10 students by forwarding complaints to 10 departments. Based on results, the students were able to submit complaints, the system was able to process accordingly by identifying to which department the complaints are intended, and the concerned department was able to give feedback on the complaint received to the student. With this, the system gained 4.7 rating which means Excellent.

Keywords: technology adoption, emerging technology, issues challenges, algorithm, text mining, mobile technology

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Authors: Mohammad Amjad, Muhammad Iqbal Zafar, Ashfaq Ahmed Maan, Muhammad Tayyab Kashif

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Obesity is an abnormal physical condition where an increased and undesirable fat accumulates in the human body. Obesity is an international phenomenon. In the present study, 12 schools were randomly selected from each district considering the areas i.e. Elite Private Schools in the private sector, Government schools in urban areas and Government schools in rural areas. Interviews were conducted with male students studying in grade 5 to grade 9 in each school. The sample size was 600 students; 300 from Faisalabad district and 300 from Rawalpindi district in Pakistan. A well-structured and pre-tested questionnaire was used for data collection. The calibrated scales were used to attain the heights and weights of the respondents. Obesity of school-going children depends on family types, family size, family history, junk food consumption, mother’s education, weekly time spent in walking, and sports facility at school levels. Academic performance, physical health and psychological health of school going children are affected with obesity. Concrete steps and policies could minimize the incidence of obesity in children in Pakistan.

Keywords: body mass index, cardiovascular disease, fast food, morbidity, overweight

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Authors: Mert Kıranç, Ekrem Duman, Murat Özbilen

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In order to achieve new product development (NPD) activities on time and within budgetary constraints, the NPD managers need a well-designed methodology. This study intends to create an integrated project management methodology for the ones who focus on new product development projects. In the scope of the study, four different management systems are combined. These systems are called as 'Schedule-oriented Stage-Gate Method, Risk Management, Change Management and Earned Value Management'. New product development term is quite common in many different industries such as defense industry, construction, health care/dental, higher education, fast moving consumer goods, white goods, electronic devices, marketing and advertising and software development. All product manufacturers run against each other’s for introducing a new product to the market. In order to achieve to produce a more competitive product in the market, an optimum project management methodology is chosen, and this methodology is adapted to company culture. The right methodology helps the company to present perfect product to the customers at the right time. The benefits of proposed methodology are discussed as an application by a company. As a result, how the integrated methodology improves the efficiency and how it achieves the success of the project are unfolded.

Keywords: project, project management, management methodology, new product development, risk management, change management, earned value, stage-gate

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Authors: Ahmed Tarek, Ahmed Alveed

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Vehicle routing problem is a well-known re-search avenue in computing. Modern vehicle routing is more focused with the GPS-based coordinate system, as the state-of-the-art vehicle, and trucking systems are equipped with digital navigation. In this paper, a new two dimensional coordinate-based algorithm for addressing the vehicle routing problem for a supply chain network is proposed and explored, and the algorithm is compared with other available, and recently devised heuristics. For the algorithms discussed, which includes the pro-posed coordinate-based search heuristic as well, the advantages and the disadvantages associated with the heuristics are explored. The proposed algorithm is studied from the stand point of a small supermarket chain delivery network that supplies to its stores in four different states around the East Coast area, and is trying to optimize its trucking delivery cost. Minimizing the delivery cost for the supply network of a supermarket chain is important to ensure its business success.

Keywords: coordinate-based optimal routing, Hamiltonian Circuit, heuristic algorithm, traveling salesman problem, vehicle routing problem

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Authors: Jaypalsinh B. Parmar, Pintu Nakrani, Ashish Chaurasia

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Digital Elevation Model (DEM) is considered as an important data in GIS-based terrain analysis for many applications and assessment of processes such as environmental and climate change studies, hydrologic modelling, etc. Vertical accuracy of DEM having geographically dynamic nature depends on different parameters which affect the model simulation outcomes. Vertical accuracy assessment in Indian landscape especially in low-lying coastal urban terrain such as lower Tapi Basin is very limited. In the present study, attempt has been made to evaluate the vertical accuracy of 30m resolution open source Indian National Cartosat-1 DEM v3 for Lower Tapi Basin (LTB) from western India. The extensive field investigation is carried out using stratified random fast static DGPS survey in the entire study region, and 117 high accuracy ground control points (GCPs) have been obtained. The above open source DEM was compared with obtained GCPs, and different statistical attributes were envisaged, and vertical error histograms were also evaluated.

Keywords: CartoDEM, Digital Elevation Model, GPS, lower Tapi basin

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Authors: Badr M. Alshammari, A. Rabeh, A. K. Mohamed

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This paper presents the modeling and the control of a grid-connected photovoltaic system (PVS). Firstly, the MPPT control of the PVS and its associated DC/DC converter has been analyzed in order to extract the maximum of available power. Secondly, the control system of the grid side converter (GSC) which is a three-phase voltage source inverter (VSI) has been presented. A special attention has been paid to the control algorithms of the GSC converter during grid voltages imbalances. Especially, three different control objectives are to achieve; the mitigation of the grid imbalance adverse effects, at the point of common coupling (PCC), on the injected currents, the elimination of double frequency oscillations in active power flow, and the elimination of double frequency oscillations in reactive power flow. Simulation results of two control strategies have been performed via MATLAB software in order to demonstrate the particularities of each control strategy according to power quality standards.

Keywords: renewable energies, photovoltaic systems, dc link, voltage source inverter, space vector SVPWM, unbalanced voltage dips, symmetrical components

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Authors: Seyed Sadegh Naseralavi, Mohsen Khatibinia

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In structural optimizations through meta-heuristic algorithms, analyses of structures are performed for many times. For this reason, performing the analyses in a time saving way is precious. The importance of the point is more accentuated in time-history analyses which take much time. To this aim, peak picking methods also known as spectrum analyses are generally utilized. However, such methods do not have the required accuracy either done by square root of sum of squares (SRSS) or complete quadratic combination (CQC) rules. The paper presents an efficient technique for evaluating the dynamic responses during the optimization process with high speed and accuracy. In the method, first by using a static equivalent of the earthquake, an initial design is obtained. Then, the displacements in the modal coordinates are achieved. The displacements are herein called basic modal displacements (MBD). For each new design of the structure, the responses can be derived by well scaling each of the MBD along the time and amplitude and superposing them together using the corresponding modal matrices. To illustrate the efficiency of the method, an optimization problems is studied. The results show that the proposed approach is a suitable replacement for the conventional time history and spectrum analyses in such problems.

Keywords: basic modal displacements, earthquake, optimization, spectrum

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Authors: Ricky Saputra, Rashmi Walvekar, Mohammad Khalid

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Landfills, water contamination, and toxic gas emission are a few impacts faced by the environment due to the increasing number of αof waste rubber tires (WRT). In spite of such concerning issue, only minimal efforts are taken to reclaim or recycle these wastes as their products are generally not-profitable for companies. Unlike the typical reclamation process, devulcanization is a method to selectively cleave sulfidic bonds within vulcanizates to avoid polymeric scissions that compromise elastomer’s mechanical and tensile properties. The process also produces devulcanizates that are re-processable similar to virgin rubber. Often, a devulcanizing agent is needed. In the current study, novel and sustainable ammonium chloride-based ternary deep eutectic solvents (TDES), with a different number of α-hydrogens, were utilised to devulcanize ground rubber tire (GRT) as an effort to implement green chemistry to tackle such issue. 40-mesh GRT were soaked for 1 day with different TDESs and sonicated at 37-80 kHz for 60-120 mins and heated at 100-140oC for 30-90 mins. Devulcanizates were then filtered, dried, and evaluated based on the percentage of by means of Flory-Rehner calculation and swelling index. The result shows that an increasing number of α-Hs increases the degree of devulcanization, and the value achieved was around eighty-percent, thirty percent higher than the typical industrial-autoclave method. Resulting bondages of devulcanizates were also analysed by Fourier transform infrared spectrometer (FTIR), Horikx fitting, and thermogravimetric analyser (TGA). The earlier two confirms only sulfidic scissions were experienced by GRT through the treatment, while the latter proves the absence or negligibility of carbon-chains scission.

Keywords: ammonium, sustainable, deep eutectic solvent, α-hydrogen, waste rubber tire

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Authors: Hamid Hossein Khezri, Afsaneh Javdani-Mallak

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Fast inhibitory neurotransmission in the mammalian nervous system is largely mediated by GABAA receptors, chloride-selective members of the superfamily of pentameric Cys-loop receptors. Cannabidiol (CBD) is one of the members of cannabinoid compounds found in cannabis. CBD and Cannabinol (CBN), as the other extract of plant Cannabis were able to reduce myofascial pain in rats with immunosuppressive and anti-inflammatory activities. In this study, we accomplished protein-protein BLAST, and the sequence was found to be for Gamma-aminobutyric acid receptor subunit alpha-1 (GBRA1) chain A and its 3D structure was subsequently downloaded from Protein Data Bank. The structures of the ligands, cannabinol, and cannabidiol, were obtained from PubChem. After the necessary process of the obtained files, AutoDock Vina was used to perform molecular docking. Docking between the ligands and GBRA1 chain A revealed that cannabinol has a higher affinity to GBRA1 (binding energy = -7.5 kcal/mol) compared to cannabidiol (binding energy = -6.5 kcal/mol). Furthermore, cannabinol seems to be able to interact with 10 residues of the protein, out of which 3 are in the neurotransmitter-gated ion-channel transmembrane domain of GBRA1, whereas cannabidiol interacts with two other residues. Although the results of this project do not indicate the activating /or inhibitory capability of the studied compounds, it suggests that cannabinol can act as a relatively strong ligand for GBRA1.

Keywords: protein-ligand docking, cannabinol, cannabidiol, GBRA1

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Authors: Dimitar Karastoyanov, Todor Penchev

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The paper presents the research of a kind of autonomous mobile robots, intended for work and adaptive perception in unknown and unstructured environment. The objective are robots, dedicated for multi-sensory environment perception and exploration, like measurements and samples taking, discovering and putting a mark on the objects as well as environment interactions–transportation, carrying in and out of equipment and objects. At that ground classification of the different types mobile robots in accordance with the way of locomotion (wheel- or chain-driven, walking, etc.), used drive mechanisms, kind of sensors, end effectors, area of application, etc. is made. Modular system for the mechanical construction of the mobile robots is proposed. Special PLC on the base of AtMega128 processor for robot control is developed. Electronic modules for the wireless communication on the base of Jennic processor as well as the specific software are developed. The methods, means and algorithms for adaptive environment behaviour and tasks realization are examined. The methods of group control of mobile robots and for suspicious objects detecting and handling are discussed too.

Keywords: mobile robots, wireless communications, environment investigations, group control, suspicious objects

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Authors: Sophie Herr, Antoine Leybros, Yves Barre, Sergey Nikitenko, Rachel Pflieger

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The proportion of soil contaminated by a wide range of pollutants (heavy metals, PCBs, pesticides, etc.) of anthropogenic origin is constantly increasing, and it is becoming urgent to address this issue. Among remediation methods, soil washing is an effective, relatively fast, and widely used process. This study assesses its coupling with ultrasound: indeed, sonication induces the formation of cavitation bubbles in solution that enhance local mass transfer through agitation and particle erosion. The removal of target toxic elements Ni(II) and Zn(II) from vermiculite clay has been studied under 20 kHz ultrasound and silent conditions. Several acids were tested, and HCl was chosen as the solvent. The effects of solid/liquid ratio and particle size were investigated. Metal repartition in the clay has been followed by Tessier's sequential extraction procedure. The results showed that more metal elements bound to the challenging residual phase were desorbed with 20 kHz ultrasound than in silent conditions. This supports the promising application of ultrasound for heavy metal desorption in difficult conditions. Further experiments were performed at high-frequency US (362 kHz), and it was shown that fragmentation of the vermiculite particles is then limited, while positive effects of US in the decontamination are kept.

Keywords: desorption, heavy metals, ultrasound, vermiculite

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Authors: Tovondahiniriko Fanjirindratovo, Olga Ramiarinjanahary, Paulisimone Rasoavonjy

Abstract:

The sunshine duration, which is the sum of all the moments when the solar beam radiation is up to a minimal value, is an important parameter for climatology, tourism, agriculture and solar energy. Its measure is usually given by a pyrheliometer installed on a two-axis solar tracker. Due to the high cost of this device and the availability of global radiation on a horizontal surface, on the other hand, several studies have been done to make a correlation between global radiation and sunshine duration. Most of these studies are fitted for the northern hemisphere using a pyrheliometric database. The aim of the present work is to list and assess all the existing methods and apply them to Reunion Island, a tropical region in the southern hemisphere. Using a database of ten years, global, diffuse and beam radiation for a horizontal surface are employed in order to evaluate the uncertainty of existing algorithms for a tropical region. The methodology is based on indirect comparison because the solar beam radiation is not measured but calculated by the beam radiation on a horizontal surface and the sun elevation angle.

Keywords: Carpentras method, data fitting, global radiation, sunshine duration, Slob and Monna algorithm, step algorithm

Procedia PDF Downloads 130

Authors: Fernando L. P. Santos, Luiz G. Lyra, Helenice O. Florentino, Daniela R. Cantane

Abstract:

Dengue is a febrile infectious disease caused by a virus of the family Flaviridae. It is transmitted by the bite of mosquitoes, usually of the genus Aedes aegypti. It occurs in tropical and subtropical areas of the world. This disease has been a major public health problem worldwide, especially in tropical countries such as Brazil, and its incidence has increased in recent years. Dengue is a subject of intense research. Efficient forms of mosquito control must be considered. In this work, the mono-objective optimal control problem was solved for analysing the dengue disease problem. Chemical and biological controls were considered in the mathematical aspect. This model describes the dynamics of mosquitoes in water and winged phases. We applied the genetic algorithms (GA) to obtain optimal strategies for the control of dengue. Numerical simulations have been performed to verify the versatility and the applicability of this algorithm. On the basis of the present results we may recommend the GA to solve optimal control problem with a large region of feasibility.

Keywords: genetic algorithm, dengue, Aedes aegypti, biological control, chemical control

Procedia PDF Downloads 353

Authors: Haythem H. Abdullah, Hesham Elkady

Abstract:

With the fast increase in radio frequency identification (RFID) applications such as medical recording, library management, etc., the limitation of active tags stems from its need to external batteries as well as passive or active chips. The chipless RFID tag reduces the cost to a large extent but at the expense of utilizing the spectrum. The reduction of the cost of chipless RFID is due to the absence of the chip itself. The identification is done by utilizing the spectrum in such a way that the frequency response of the tags consists of some resonance frequencies that represent the bits. The system capacity is decided by the number of resonators within the pre-specified band. It is important to find a solution to enhance the spectrum utilization when using chipless RFID. Target identification is a process that results in a decision that a specific target is present or not. Several target identification schemes are present, but one of the most successful techniques in radar target identification in the oscillatory region is the extinction pulse technique (E-Pulse). The E-Pulse technique is used to identify targets via its characteristics (natural) modes. By introducing an innovative solution for chipless RFID reader and tag designs, the spectrum utilization goes to the optimum case. In this paper, a novel capacity enhancement scheme based on the E-pulse technique is introduced to improve the performance of the chipless RFID system.

Keywords: chipless RFID, E-pulse, natural modes, resonators

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Authors: Adarsh Shroff

Abstract:

Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

Procedia PDF Downloads 355