Search results for: modified simplex algorithm

Authors: Madhu Babu Cherukuri, Tamoghna Ghosh

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Factory supply chain management spends billions of dollars every year to procure and manage equipment spare parts. Due to technology -and processes changes some of these spares become obsolete/dead inventory. Factories have huge dead inventory worth millions of dollars accumulating over time. This is due to lack of a scientific methodology to identify them and send the inventory back to the suppliers on a timely basis. The standard approach followed across industries to deal with this is: if a part is not used for a set pre-defined period of time it is declared dead. This leads to accumulation of dead parts over time and these parts cannot be sold back to the suppliers as it is too late as per contract agreement. Our main idea is the time period for identifying a part as dead cannot be a fixed pre-defined duration across all parts. Rather, it should depend on various properties of the part like historical consumption pattern, type of part, how many machines it is being used in, whether it- is a preventive maintenance part etc. We have designed a predictive algorithm which predicts part obsolescence well in advance with reasonable accuracy and which can help save millions.

Keywords: obsolete inventory, machine learning, big data, supply chain analytics, dead inventory

Procedia PDF Downloads 323

Authors: Janusz Bedkowski, Grzegorz Kisala, Michal Wlasiuk, Piotr Pokorski

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Ground-truth data is essential for VO (Visual Odometry) and SLAM (Simultaneous Localization and Mapping) quantitative evaluation using e.g. ATE (Absolute Trajectory Error) and RPE (Relative Pose Error). Many open-access data sets provide raw and ground-truth data for benchmark purposes. The issue appears when one would like to validate Visual Odometry and/or SLAM approaches on data captured using the device for which the algorithm is targeted for example mobile phone and disseminate data for other researchers. For this reason, we propose an open source, open hardware groundtruth system that provides an accurate and precise trajectory with a 3D point cloud. It is based on LiDAR Livox Mid-360 with a non-repetitive scanning pattern, on-board Raspberry Pi 4B computer, battery and software for off-line calculations (camera to LiDAR calibration, LiDAR odometry, SLAM, georeferencing). We show how this system can be used for the evaluation of various the state of the art algorithms (Stella SLAM, ORB SLAM3, DSO) in typical indoor monocular VO/SLAM.

Keywords: SLAM, ground truth, navigation, LiDAR, visual odometry, mapping

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Authors: Mrudula Kudtarkar, Rajesh Mane

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Introduction: Cleft lip repair is one of the common surgeries performed in India and the usual method used for post-operative analgesia is perioperative opioids and NSAIDs. There has been an increase in use of regional techniques and Opioids are the common adjuvants but their efficacy and safety have not been studied extensively in children. Aim: A prospective, randomized, double-blind study was done to compare the efficacy, duration and safety of intraoral infraorbital nerve block on post-operative pain relief using bupivacaine alone or in combination with fentanyl or pethidine in paediatric cleft lip repair. Methodology: 45 children between the age group 5 – 60 months undergoing cleft lip surgery randomly allocated into 3 groups of 15 each received bilateral intraoral infraorbital nerve block with 0.75ml of solution. Group B received 0.25% bupivacaine; group P received 0.25% bupivacaine with 0.25mg/kg pethidine, group F received 0.25% bupivacaine with 0.25microgm/kg fentanyl. Sedation after recovery, post-operative pain intensity and duration of post-operative analgesia were assessed using Modified Hannallah Pain Score. Results: The mean duration of analgesia was 17.8 hrs in Group B, 23.53 hrs in Group F and 35.13 hrs in Group P. There was statistically significant difference between the means of the three groups- ANOVA (p < 0.05). Conclusion: Thus we conclude that addition of fentanyl or pethidine to bupivacaine for Bilateral Intraoral Infraorbital Nerve Block prolong the duration of analgesia with no complications and can be used safely in paediatric patients.

Keywords: cleft lip, infraorbital block, NSAIDS, Opiods

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Authors: Aysegul Evren Yapicioglu

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The social roles and responsibilities expected from citizens are increasing due to changing global living conditions. Science education is expected to prepare conscious and sensitive students. Because today’s students are the adults of future. Precondition of this task is Teacher Education. In the past decade, one of the most important research field is socioscientific issues. This study deals with advantages and disadvantages of socioscientific issue based instruction in science classroom according to pre-service science teachers’ views. A case study approach that is one of the qualitative research design was used to explore their views. Fourteen pre-service science teachers participated to instruction process. Dolphinariums, Kyoto Protocol, genetically modified organisms, recyclable black bags’ benefits and damages, genetic tests, alternative energy sources and organ donation are examples of socioscientific issues, which were taught through activities in a special teaching course. Diaries and focus group interview were used as data collection tools. As a result of the study, the advantages of socioscientific issue based instruction in science classroom comprise of six sub-categories which are multi-skilling, social awareness development of thinking, meaningful learning, character and professional development, contribution of scientific literacy whereas disadvantages of this instruction process are challenges teachers and students, limitations of teaching and learning process in pre-service science teachers’ perspectives. Finally, this study contributes to science teachers and researchers to overcome disadvantages and benefit from the advantage of socioscientific issue based instruction in science classroom.

Keywords: science education, socioscientific issues, socioscientific issue based instruction, pre-service science teacher

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Authors: Sopana Wongtawee

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Purpose: Adequate bowel cleansing is essential for a high quality, effective and safe colonoscopy. The aims of this study were to compare the efficacy of bowel preparation based on a low-residue diet before 8:00 followed by a clear-liquid diet, and a low-residue diet until 16:00 one day before colonoscopy using sodium phosphate solution (Xubil ®), the side effects of the two protocols and the patient satisfaction with them. Method: This was an endoscopist-blinded, prospective, randomized, controlled trial. A total of 224 patients (112 in each group) scheduled for outpatient colonoscopy met the criteria.They were randomized to either a low-residue diet consisting of white rice porridge with either fish, chicken or eggs before 8:00 followed by a clear-liquid diet (Group 1) or a low-residue diet consisting of the same food and drink, until 16:00 the day before colonoscopy(Group 2). All of them received 45 ml of sodium phosphate solution (Xubil ®) and three glasses of water (300 ml/glass) the evening before and the morning of the procedure. The cleansing efficacy of bowel preparation was rated according to the modified Rajawithi hospital bowel preparation score scale, patient satisfaction with bowel preparation was rated using Likert scale, and side effects of the 2 protocols was assessed using a patient questionnaire. Results: The cleansing efficacy between the two groups was significantly different (p=0.02). Satisfaction with bowel preparation and side effects were not different, except for the feeling of hunger in the first group (p=0.001). Conclusion: The low-residue diet consisting of white rice porridge with fish, chicken or eggs until 16:00 one day before colonoscopy achieved a better bowel-cleansing efficacy than the protocol consisting of clear liquid all day and rice porridge only before 8:00 one day before colonoscopy.

Keywords: bowel preparation, colonoscopy, sodium phosphate solution, nursing management

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Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

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Authors: J. Prathap Kumar, G. Vaitheeswaran

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The present study investigates the role of ammonium and potassium ion in the electronic, bonding and optical properties of dinitramide salts due to their stability and non-toxic nature. A detailed analysis of bonding between NH₄ and K with dinitramide, optical transitions from the valence band to the conduction band, absorption spectra, refractive indices, reflectivity, loss function are reported. These materials are well known as oxidizers in solid rocket propellants. In the present work, we use full potential linear augmented plane wave (FP-LAPW) method which is implemented in the Wien2k package within the framework of density functional theory. The standard DFT functional local density approximation (LDA) and generalized gradient approximation (GGA) always underestimate the band gap by 30-40% due to the lack of derivative discontinuities of the exchange-correlation potential with respect to an occupation number. In order to get reliable results, one must use hybrid functional (HSE-PBE), GW calculations and Tran-Blaha modified Becke-Johnson (TB-mBJ) potential. It is very well known that hybrid functionals GW calculations are very expensive, the later methods are computationally cheap. The new developed TB-mBJ functionals use information kinetic energy density along with the charge density employed in DFT. The TB-mBJ functionals cannot be used for total energy calculations but instead yield very much improved band gap. The obtained electronic band gap at gamma point for both the ammonium dinitramide and potassium dinitramide are found to be 2.78 eV and 3.014 eV with GGA functional, respectively. After the inclusion of TB-mBJ, the band gap improved by 4.162 eV for potassium dinitramide and 4.378 eV for ammonium dinitramide. The nature of the band gap is direct in ADN and indirect in KDN. The optical constants such as dielectric constant, absorption, and refractive indices, birefringence values are presented. Overall as there are no experimental studies we present the improved band gap with TB-mBJ functional following with optical properties.

Keywords: ammonium dinitramide, potassium dinitramide, DFT, propellants

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Authors: Tomas Menard

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The synthesis of output-feedback control law has been investigated by many researchers since the last century. While many results exist for the case of Linear Time Invariant systems whose measurements are continuously available, nowadays, control laws are usually implemented on micro-controller, then the measurements are discrete-time by nature. This fact has to be taken into account explicitly in order to obtain a satisfactory behavior of the closed-loop system. One considers here a general class of systems corresponding to an observability normal form and which is subject to uncertainties in the dynamics and sampling of the output. Indeed, in practice, the modeling of the system is never perfect, this results in unknown uncertainties in the dynamics of the model. We propose here an output feedback algorithm which is based on a linear state feedback and a continuous-discrete time observer. The main feature of the proposed control law is that only discrete-time measurements of the output are needed. Furthermore, it is formally proven that the state of the closed loop system exponentially converges toward the origin despite the unknown uncertainties. Finally, the performances of this control scheme are illustrated with simulations.

Keywords: dynamical systems, output feedback control law, sampling, uncertain systems

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Authors: John Pomerat, Aviv Segev

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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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Authors: Ansah Iris Baffour, Dong-Ho Kim, Sung-Gyu Park

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The ongoing COVID-19 pandemic, caused by the SARS-CoV-2 virus and is gradually shifting to an endemic phase which implies the outbreak is far from over and will be difficult to eradicate. Global cooperation has led to unified precautions that aim to suppress epidemiological spread (e.g., through travel restrictions) and reach herd immunity (through vaccinations); however, the primary strategy to restrain the spread of the virus in mass populations relies on screening protocols that enable rapid on-site diagnosis of infections. Herein, we employed surface enhanced Raman spectroscopy (SERS) for the rapid detection of SARS-CoV-2 lysate on an Au-modified Au nanodimple(AuND)electrode. Through in situone-pot Au electrodeposition on the AuND electrode, Au-lysate nanocomposites were synthesized, generating3D internal hotspots for large SERS signal enhancements within 30 s of the deposition. The capture of lysate into newly generated plasmonic nanogaps within the nanocomposite structures enhanced metal-spike protein contact in 3D spaces and served as hotspots for sensitive detection. The limit of detection of SARS-CoV-2 lysate was 5 x 10-2 PFU/mL. Interestingly, ultrasensitive detection of the lysates of influenza A/H1N1 and respiratory syncytial virus (RSV) was possible, but the method showed ultimate selectivity for SARS-CoV-2 in lysate solution mixtures. We investigated the practical application of the approach for rapid on-site diagnosis by detecting SARS-CoV-2 lysate spiked in normal human saliva at ultralow concentrations. The results presented demonstrate the reliability and sensitivity of the assay for rapid diagnosis of COVID-19.

Keywords: label-free detection, nanocomposites, SARS-CoV-2, surface-enhanced raman spectroscopy

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Authors: Shuji Fujimoto, Fumiko Kojima, Mika Shigematsu

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Biorisk management (Biosafety/Biosecurity) is required for anyone working in a clinical laboratory (including medical/clinical research laboratories) where infectious agents and potentially hazardous biological materials are examined/stored. Proper education and training based on international standards of biorisk management should be provided not only as a part of laboratory safety program in work place but also as a part of introductory training at educational institutions for continuity and to elevate overall baseline of the biorisk management. We reported results of the pilot study of biorisk management education for graduate students majored in laboratory diagnostics previously. However, postgraduate education is still late in their profession and the participants’ interview also revealed importance and demands of earlier biorisk management education for undergraduates. The aim of this study is to identify the need for biosafety/biosecurity education and training program which is designed for undergraduate students who are entering the profession in clinical microbiology. We modified the previous program to include more basic topics and explanations (risk management, principles of safe clinical lab practices, personal protective equipment, disinfection, disposal of biological substances) and provided incorporating in the routine educational system for faculty of medical sciences in Kyushu University. The results of the pre and post examinations showed that the knowledge of the students on biorisk control had developed effectively as a proof of effectiveness of the program even in the undergraduate students. Our study indicates that administrating the basic biorisk management program in the earlier stage of learning will add positive impact to the understanding of biosafety to the health professional education.

Keywords: biorisk management, biosafety, biosecurity, clinical microbiology, education for undergraduates

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Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

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Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

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Authors: Ninlawat Phuangchoke, Waraporn Viyanon, Setta Sasananan

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The most important process of the water treatment plant process is the coagulation using alum and poly aluminum chloride (PACL), and the value of usage per day is a hundred thousand baht. Therefore, determining the dosage of alum and PACL are the most important factors to be prescribed. Water production is economical and valuable. This research applies an artificial neural network (ANN), which uses the Levenberg–Marquardt algorithm to create a mathematical model (Soft Jar Test) for prediction chemical dose used to coagulation such as alum and PACL, which input data consists of turbidity, pH, alkalinity, conductivity, and, oxygen consumption (OC) of Bangkhen water treatment plant (BKWTP) Metropolitan Waterworks Authority. The data collected from 1 January 2019 to 31 December 2019 cover changing seasons of Thailand. The input data of ANN is divided into three groups training set, test set, and validation set, which the best model performance with a coefficient of determination and mean absolute error of alum are 0.73, 3.18, and PACL is 0.59, 3.21 respectively.

Keywords: soft jar test, jar test, water treatment plant process, artificial neural network

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Authors: Lule Basha, Eralda Gjika

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The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable in one country's competitiveness, trade and current account, inflation, wages, domestic economic activity, and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021, and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables on the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of the Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: exchange rate, random forest, time series, machine learning, prediction

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Omogboyega Abe

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This paper examines the relationships between socio-economic inequalities of power, race, wealth engendered by corporate structure, and domination in postcolonial Africa. The paper further considers how land as an epitome of property and power for the locals paved the way for capitalist accumulation and control in the hands of transnational corporations. European colonization of Africa was contingent on settler colonialism, where properties, including land, were re-modified as extractive resources for primitive accumulation. In developing Africa's extractive resources, transnational corporations (TNCs) usurped states' structures and domination over native land. The usurpation/corporate capture that exists to date has led to remonstrations and arguably a counter-productive approach to development projects. In some communities, the mention of extractive companies triggers resentment. The paradigm of state capture and state autonomy is simply inadequate to either describe or resolve the play of forces or actors responsible for severe corporate-induced human rights violations in emerging markets. Moreover, even if the deadly working conditions are conceived as some regulatory failure, it is tough to tell whose failure. The analysis in this paper is that the complexity and ambiguity evidenced by the multiple regimes and political and economic forces shaping production, consumption, and distribution of socio-economic variables are not exceptional in emerging markets. Instead, the varied experience in developing countries provides a window for seeing what we face in understanding and theorizing the structure and operation of the global economic and regulatory order in general.

Keywords: colonial, emerging markets, business, human rights, corporation

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Authors: Tukur Daiyabu Abdulkadir, Wan Ishak Wan Ismail, Muhammad Saufi Mohd Kassim

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Seed singulation and accuracy in seed spacing are the major challenges associated with the adoption of mechanical seeder for system of rice intensification. In this research the metering system of a pneumatic planter was modified and automated for increase precision to meet the demand of system of rice intensification SRI. The chain and sprocket mechanism of a conventional vacuum planter were now replaced with an electro mechanical system made up of a set of servo motors, limit switch, micro controller and a wheel divided into 10 equal angles. The circumference of the planter wheel was determined based on which seed spacing was computed and mapped to the angles of the metering wheel. A program was then written and uploaded to arduino micro controller and it automatically turns the seed plates for seeding upon covering the required distance. The servo motor was calibrated with the aid of labVIEW. The machine was then calibrated using a grease belt and varying the servo rpm through voltage variation between 37 rpm to 47 rpm until an optimum value of 40 rpm was obtained with a forward speed of 5 kilometers per hour. A pressure of 1.5 kpa was found to be optimum under which no skip or double was recorded. Precision in spacing (coefficient of variation), miss index, multiple index, doubles and skips were investigated. No skip or double was recorded both at laboratory and field levels. The operational parameters under consideration were both evaluated at laboratory and field. Even though there was little variation between the laboratory and field values of precision in spacing, multiple index and miss index, the different is not significant as both laboratory and field values fall within the acceptable range.

Keywords: automation, calibration, pneumatic seed planter, system of rice intensification

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Authors: Sheam-Chyun Lin, Wei-Kai Chen, Hung-Cheng Yen, Yung-Jen Cheng, Yu-Cheng Chen

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Result from the constant dwindle in natural resources, the alternative way to reduce the costs in our daily life would be urgent to be found in the near future. As the ancient technique based on the theory of solar chimney since roman times, the double-skin façade are simply composed of two large glass panels in purpose of daylighting and also natural ventilation in the daytime. Double-skin façade is generally installed on the exterior side of buildings as function as the window, so there’s always a huge amount of passive solar energy the façade would receive to induce the airflow every sunny day. Therefore this article imposes a domestic double-skin window for residential usage and attempts to improve the volume flow rate inside the cavity between the panels by the frame geometry design, the installation of outlet guide plate and the solar energy collection system. Note that the numerical analyses are applied to investigate the characteristics of flow field, and the boundary conditions in the simulation are totally based on the practical experiment of the original prototype. Then we redesign the prototype from the knowledge of the numerical results and fluid dynamic theory, and later the experiments of modified prototype will be conducted to verify the simulation results. The velocities at the inlet of each case are increase by 5%, 45% and 15% from the experimental data, and also the numerical simulation results reported 20% improvement in volume flow rate both for the frame geometry design and installation of outlet guide plate.

Keywords: solar energy, double-skin façades, thermal buoyancy, fluid machinery

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Authors: Rashmi Yadawad, Disha Narayanan, Ravi Gautam

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Through Wall Radar Imaging is gaining increasing importance now a days in the field of Defense and one of the most important criteria that forms the basis for the image quality obtained is the Cross-Range resolution of the image. In this research paper, the Bilateral Back projection algorithm has been implemented for Through Wall Radar Imaging. The sole purpose is to enhance the resolution in the cross range direction of the obtained Back projection image. Synthetic Data is generated for two targets which are placed at various locations in a room of dimensions 8 m by 6m. Two algorithms namely, simple back projection and Bilateral Back projection have been implemented, images are obtained and the obtained images are compared. Numerical simulations have been coded in MATLAB and experimental results of the two algorithms have been shown. Based on the comparison between the two images, it can be clearly seen that the ringing effect and chess board effect have been heavily reduced in the bilaterally back projected image and hence promising results are obtained giving a relatively sharper image with relatively well defined edges.

Keywords: through wall radar imaging, bilateral back projection, cross range resolution, synthetic data

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Authors: Xiongxiong You, Zhanwen Niu

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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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Authors: Adeline Meriaux, Claire Gaiani, Jennifer Burgain, Frantz Fournier, Lionel Muniglia, Jérémy Petit

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Spray-drying process is widely used for the production of dairy powders for food and pharmaceuticals industries. It involves the atomization of a liquid feed into fine droplets, which are subsequently dried through contact with a hot air flow. The resulting powders permit transportation cost reduction and shelf life increase but can also exhibit various interesting functionalities (flowability, solubility, protein modification or acid gelation), depending on operating conditions and milk composition. Indeed, particles porosity, surface composition, lactose crystallization, protein denaturation, protein association or crust formation may change. Links between spray-drying conditions and physicochemical and functional properties of powders were investigated by a design of experiment methodology and analyzed by principal component analysis. Quadratic models were developed, and multicriteria optimization was carried out by the use of genetic algorithm. At the time of abstract submission, verification spray-drying trials are ongoing. To perform experiments, milk from dairy farm was collected, skimmed, froze and spray-dried at different air pressure (between 1 and 3 bars) and outlet temperature (between 75 and 95 °C). Dry matter, minerals content and proteins content were determined by standard method. Solubility index, absorption index and hygroscopicity were determined by method found in literature. Particle size distribution were obtained by laser diffraction granulometry. Location of the powder color in the Cielab color space and water activity were characterized by a colorimeter and an aw-value meter, respectively. Flow properties were characterized with FT4 powder rheometer; in particular compressibility and shearing test were performed. Air pressure and outlet temperature are key factors that directly impact the drying kinetics and powder characteristics during spray-drying process. It was shown that the air pressure affects the particle size distribution by impacting the size of droplet exiting the nozzle. Moreover, small particles lead to more cohesive powder and less saturated color of powders. Higher outlet temperature results in lower moisture level particles which are less sticky and can explain a spray-drying yield increase and the higher cohesiveness; it also leads to particle with low water activity because of the intense evaporation rate. However, it induces a high hygroscopicity, thus, powders tend to get wet rapidly if they are not well stored. On the other hand, high temperature provokes a decrease of native serum proteins which is positively correlated to gelation properties (gel point and firmness). Partial denaturation of serum proteins can improve functional properties of powder. The control of air pressure and outlet temperature during the spray-drying process significantly affects the physicochemical and functional properties of powder. This study permitted to better understand the links between physicochemical and functional properties of powder, to identify correlations between air pressure and outlet temperature. Therefore, mathematical models have been developed and the use of genetic algorithm will allow the optimization of powder functionalities.

Keywords: dairy powders, spray-drying, powders functionalities, design of experiment

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Authors: Antonia Stergiou

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Background: Due to the developmental trajectory of executive function in preschool age, the majority of existing studies investigating the association between acute physical activity and cognitive control have focused on adolescents and adult population. Aim- The aim of this study was to investigate the possible effects of physical activity on the inhibitory control of pre-school children. Methods: This is a prospectively designed study that was conducted in a primary school in Bristol in June 2015. The total number of subjects was n=61 and 20 trials of a modified Eriksen Flanker Task were completed before and after a 30-minutes session of moderate exercise (including both 5 minutes of warm up and cool down). For each test a pre- and post-test assessment took place that included both congruent and incongruent trials. The congruent trials were considered as the control condition and the incongruent trials as those that measure inhibitory control (experimental condition). At the end of the assessment, the participants were instructed to choose the face that described their current feelings between three options (happy, neutral, sad). Results: There was a trend for increased accuracy following moderate exercise, but there was statistical significance (p > .05). However, there was statistically significant improvement in the reaction time following the same type of exercise (p = .005). Face board assessment revealed positive emotions after 30 minutes of moderate exercise. Conclusions: The current study supports findings from previous studies related to the benefits of physical activity on the children’s inhibitory control and provides evidence of those benefits in even younger ages. Further research should take place considering each child individually. Implementation of those findings could result in an improved curriculum in schools with additional time spent on physical education courses.

Keywords: cognitive control, inhibition, physical activity, pre-school children

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Authors: Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio Velastin

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We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from color video sequences. Our approach proceeds along two stages. In the first, we run a real-time 2D pose detector to determine the precise pixel location of important key points of the body. A two-stream neural network is then designed and trained to map detected 2D keypoints into 3D poses. In the second, we deploy the Efficient Neural Architecture Search (ENAS) algorithm to find an optimal network architecture that is used for modeling the Spatio-temporal evolution of the estimated 3D poses via an image-based intermediate representation and performing action recognition. Experiments on Human3.6M, Microsoft Research Redmond (MSR) Action3D, and Stony Brook University (SBU) Kinect Interaction datasets verify the effectiveness of the proposed method on the targeted tasks. Moreover, we show that our method requires a low computational budget for training and inference.

Keywords: human action recognition, pose estimation, D-CNN, deep learning

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Authors: Ekramul Hoque, Zinat Ara Eakut Zarin, Ershad Ali

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The growth and development of explants is governed by the effect of nutrient medium. Ammonium nitrate (NH4NO3) as a major salt of stock solution-1 for the preparation of tissue culture medium. But, it has several demerits on human civilization. It is use for the preparation of bomb and other destructive activities. Hence, it is totally ban in our country. A new chemical was identified as a substitute of ammonium nitrate. The concentrations of the other ingredients of major and minor salt were modified from the MS medium. The formulation of new medium is totally different from the MS nutrient composition. The most widely use MS medium composition was used as first check treatment and MS powder (Duchefa Biocheme, The Netherland) was used as second check treatment. The experiments were carried out at the Department of Biotechnology, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh. Two potato varieties viz. Diamant and Asterix were used as experimental materials. The regeneration potentiality of potato onto new medium was best as compare with the two check treatments. The traits -node number, leaf number, shoot length, root lengths were highest in new medium. The plantlets were healthy, robust and strong as compare to plantlets regenerated from check treatments. Three subsequent sub-cultures were made in the new medium to observe the growth pattern of plantlet. It was also showed the best performance in all the parameter under studied. The regenerated plantlet produced good quality minituber under field condition. Hence, it is concluded that, a new plant tissue culture medium as discovered from the Department of Biotechnology, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh under the leadership of Professor Dr. Md. Ekramul Hoque.

Keywords: new medium, potato, regeneration, ammonium nitrate

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Authors: Muhammad Zaheer Babar, Amer Kashif, Muhammad Rizwan Javed

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Nowadays distributed generation integration is best way to overcome the increasing load demand. Optimal allocation of distributed generation plays a vital role in reducing system losses and improves voltage profile. In this paper, a Meta heuristic technique is proposed for allocation of DG in order to reduce power losses and improve voltage profile. The proposed technique is based on Multi Objective Particle Swarm optimization. Fewer control parameters are needed in this algorithm. Modification is made in search space of PSO. The effectiveness of proposed technique is tested on IEEE 33 bus test system. Single DG as well as multiple DG scenario is adopted for proposed method. Proposed method is more effective as compared to other Meta heuristic techniques and gives better results regarding system losses and voltage profile.

Keywords: Distributed generation (DG), Multi Objective Particle Swarm Optimization (MOPSO), particle swarm optimization (PSO), IEEE standard Test System

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Authors: Jafar Akbari

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Quinolines are very important compounds partially because of their pharmacological properties which include wide applications in medicinal chemistry. notable among them are antimalarial drugs, anti-inflammatory agents, antiasthamatic, antibacterial, antihypertensive, and tyrosine kinase inhibiting agents. Despite quinoline usage in pharmaceutical and other industries, comparatively few methods for their preparation have been reported.The Friedlander annulation is one of the simplest and most straightforward methods for the synthesis of poly substituted quinolines. Although, modified methods employing lewis or br¢nsted acids have been reported for the synthesis of quinolines, the development of water stable acidic catalyst for quinoline synthesis is quite desirable. One of the most remarkable features of ionic liquids is that the yields can be optimized by changing the anions or the cations. Recently, sulfonic acid functionalized ionic liquids were used as solvent-catalyst for several organic reactions. We herein report the one pot domino approach for the synthesis of quinoline derivatives in Friedlander manner using TSIL as a catalyst. These ILs are miscible in water, and their homogeneous system is readily separated from the reaction product, combining advantages of both homogeneous and heterogeneous catalysis. In this reaction, the catalyst plays a dual role; it ensures an effective condensation and cyclization of 2-aminoaryl ketone with second carbonyl group and it also promotes the aromatization to the final product. Various types of quinolines from 2-aminoaryl ketones and β-ketoesters/ketones were prepared in 85-98% yields using the catalytic system of SO3-H functionalized ionic liquid/H2O. More importantly, the catalyst could be easily recycled for five times without loss of much activity.

Keywords: antimalarial drugs, green chemistry, ionic liquid, quinolines

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Authors: Alireza Ansariyar, Mansoureh Jeihani

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Light Detection and Ranging (LiDAR) sensors are capable of recording traffic data including the number of passing vehicles and bicyclists, the speed of vehicles and bicyclists, and the number of conflicts among both road users. In order to collect real-time traffic data and investigate the safety of different road users, a LiDAR sensor was installed at Cold Spring Ln – Hillen Rd intersection in Baltimore City. The frequency and severity of collected real-time conflicts were analyzed and the results highlighted that 122 conflicts were recorded over a 10-month time interval from May 2022 to February 2023. By using an innovative image-processing algorithm, a new safety Measure of Effectiveness (MOE) was proposed to recognize the critical zones for bicyclists entering each zone. Considering the trajectory of conflicts, the results of the analysis demonstrated that conflicts in the northern approach (zone N) are more frequent and severe. Additionally, sunny weather is more likely to cause severe vehicle-bike conflicts.

Keywords: LiDAR sensor, post encroachment time threshold (PET), vehicle-bike conflicts, a measure of effectiveness (MOE), weather condition

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Authors: Ahmed Samy Elnoby

Abstract:

Ailanthus altissima native to Asia which belongs to the family Simaroubaceae was subjected to phytochemical screening and biological investigations. Phytochemical screening revealed the presence of carbohydrates, tannins, sterols, flavonoids and traces of saponins. In addition, quantitative determination of phenolics and flavonoid content were performed. The antimicrobial activity of methanolic extract of the leaves was determined against gram-positive, gram-negative bacteria in addition to fungi using a modified Kirby-Bauer disc diffusion method that was compared with standard discs ampicillin which acts as an antibacterial agent and amphotericin B which acts as an antifungal agent. A high potency was observed against gram-positive bacteria mainly staphylococcus aureus, gram-negative bacteria mainly Escherichia coli and showed no potency against fungi mainly Aspergillus flavus and candida albicans. On the other hand, the antioxidant activity of the extract was determined by 1, 1-diphenyl-2- diphenyl-2-picryl-hydrazil (DPPH). A very low potency was shown by using DPPH for the antioxidant effect so IC50 = 0 ug/ml, IC90 =0 ug /ml and remark gave 47.2 % at 100 ug/ml which is very weak. Cytotoxic activity was determined by using MTT assay (3-4, 5-Dimethylthiazol-2-yl)-2, 5-Diphenyltetrazolium Bromide) against MCF7 (Human Caucasian breast adenocarcinoma) cell line. A moderate potency was shown by using MCF7 cell line for cytotoxic effect so LC50= 90.2 ug/ml, LC90=139.9 ug/ml and the remark gave 55.2% at 100 ug/ml which is of moderate activity so, Ailanthus altissima can be considered to be a promising antimicrobial agent from natural origin.

Keywords: Ailanthus altissima, TLC, HPLC, anti-microbial activity, antifungal activity, antioxidant, cytotoxic activity

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Authors: Eva Nedeliakova, Jaroslav Masek, Juraj Camaj

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This article describes the results of research focused on quality of railway freight transport services. Improvement of these services has a crucial importance in customer considering on the future use of railway transport. Processes filling the customer demands and output quality assessment were defined as a part of the research. In this, contribution is introduced the map of quality planning and the algorithm of applied methodology. It characterises a model which takes into account characters of transportation with linking a perception services quality in ordinary and extraordinary operation. Despite the fact that rail freight transport has its solid position in the transport market, lots of carriers worldwide have been experiencing a stagnation for a couple of years. Therefore, specific results of the research have a significant importance and belong to numerous initiatives aimed to develop and support railway transport not only by creating a single railway area or reducing noise but also by promoting railway services. This contribution is focused also on the application of dynamic quality models which represent an innovative method of evaluation quality services. Through this conception, time factor, expected and perceived quality in each moment of the transportation process can be taken into account.

Keywords: quality, railway, transport, service

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Authors: L. Rakesh, T. Y. Heblekar

Abstract:

This study entails the development and optimization of a mathematical model for a floating drum biogas reactor from first principles using thermal and empirical considerations. The model was derived on the basis of mass conservation, lumped mass heat transfer formulations and empirical biogas formation laws. The treatment leads to a system of coupled nonlinear ordinary differential equations whose solution mapped four-time independent controllable parameters to five output variables which adequately serve to describe the reactor performance. These equations were solved numerically using fourth order Runge-Kutta method for a range of input parameter values. Using the data so obtained an Artificial Neural Network with a single hidden layer was trained using Levenberg-Marquardt Damped Least Squares (DLS) algorithm. This network was then fine-tuned for optimal mapping by varying hidden layer size. This fast forward model was then employed as a health score generator in the Bacterial Foraging Optimization code. The optimal operating state of the simplified Biogas reactor was thus obtained.

Keywords: biogas, floating drum reactor, neural network model, optimization

Procedia PDF Downloads 147