Search results for: large array

Authors: M. Habibi

Abstract:

The time-resolved studies of soft and hard X-ray were carried out over a wide range of argon pressures by employing an array of eight filtered photo PIN diodes and a scintillation detector, simultaneously. In 50% of the discharges, the soft X-ray is seen to be emitted in short multiple pulses corresponding to different compression, whereas it is a single pulse for hard X-rays corresponding to only the first strong compression. It should be stated that multiple compressions dominantly occur at low pressures and high pressures are mostly in the single compression regime. In 43% of the discharges, at all pressures except for optimum pressure, the first period is characterized by two or more sharp peaks.The X–ray signal intensity during the second and subsequent compressions is much smaller than the first compression.

Keywords: plasma focus device, SXR, HXR, Pin-diode, argon plasma

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Authors: M. Bakhtaoui, L. Merahi

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The reliability of the filtered HVBK model is now investigated via some large eddy simulations of freely decaying isotropic superfluid turbulence. For homogeneous turbulence at very high Reynolds numbers, comparison of the terms in the spectral kinetic energy budget equation indicates, in the energy-containing range, that the production and energy transfer effects become significant except for dissipation. In the inertial range, where the two fluids are perfectly locked, the mutual friction maybe neglected with respect to other terms. Also the LES results for the other terms of the energy balance are presented.

Keywords: superfluid turbulence, HVBK, energy budget, Large Eddy Simulation

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Authors: Abbas Raza Ali

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Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

Procedia PDF Downloads 175

Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Anupama Singh, Papia Raj

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Though Municipal Solid Waste (MSW) is a worldwide problem, yet its implications are enormous in developing countries, as they are unable to provide proper Municipal Solid Waste Management (MSWM) for the large volume of MSW. As a result, the collected wastes are dumped in open dumping at landfilling sites while the uncollected wastes remain strewn on the roadside, many-a-time clogging drainage. Such unsafe and inadequate management of MSW causes various public health hazards. For example, MSW directly on contact or by leachate contaminate the soil, surface water, and ground water; open burning causes air pollution; anaerobic digestion between the piles of MSW enhance the greenhouse gases i.e., carbon dioxide and methane (CO2 and CH4) into the atmosphere. Moreover, open dumping can cause spread of vector borne disease like cholera, typhoid, dysentery, and so on. Patna, the capital city of Bihar, one of the most underdeveloped provinces in India, is a unique representation of this situation. Patna has been identified as the ‘garbage city’. Over the last decade there has been an exponential increase in the quantity of MSW generation in Patna. Though a large proportion of such MSW is recyclable in nature, only a negligible portion is recycled. Plastic constitutes the major chunk of the recyclable waste. The chemical composition of plastic is versatile consisting of toxic compounds, such as, plasticizers, like adipates and phthalates. Pigmented plastic is highly toxic and it contains harmful metals such as copper, lead, chromium, cobalt, selenium, and cadmium. Human population becomes vulnerable to an array of health problems as they are exposed to these toxic chemicals multiple times a day through air, water, dust, and food. Based on analysis of health data it can be emphasized that in Patna there has been an increase in the incidence of specific diseases, such as, diarrhoea, dysentry, acute respiratory infection (ARI), asthma, and other chronic respiratory diseases (CRD). This trend can be attributed to improper MSWM. The results were reiterated through a survey (N=127) conducted during 2014-15 in selected areas of Patna. Random sampling method of data collection was used to better understand the relationship between different variables affecting public health due to exposure to MSW and lack of MSWM. The results derived through bivariate and logistic regression analysis of the survey data indicate that segregation of wastes at source, segregation behavior, collection bins in the area, distance of collection bins from residential area, and transportation of MSW are the major determinants of public health issues. Sustainable recycling is a robust method for MSWM with its pioneer concerns being environment, society, and economy. It thus ensures minimal threat to environment and ecology consequently improving public health conditions. Hence, this paper concludes that sustainable recycling would be the most viable approach to manage MSW in Patna and would eventually reduce public health hazards.

Keywords: municipal solid waste, Patna, public health, sustainable recycling

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Authors: Othman Saleh Al-Razgan

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Obesity establishes an epidemic along with an array of comorbidities and this call for careful clinical assessment, to identify causal factors and comprehensive management. In Kuwait, this epidemic reflects the progressive, socio-economic and age-related issues, along with the shift of nutrition from traditional to modern-style. The current research attempts to narrate the obesity and related health issues in Kuwait, with a special emphasis on the magnitude of the issue in Kuwait, nutrition transition over the past three decades, change in life-style, and possible solution for this issue.

Keywords: clinical assessment, comorbidities, obesity, socio-economic

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Authors: Ilkay Turk Cakir, Murat Altinli, Zekeriya Uysal, Abdulkadir Senol, Olcay Bolukbasi Yalcinkaya, Ali Yilmaz

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The Higgs boson was discovered by the ATLAS and CMS experimental groups in 2012 at the Large Hadron Collider (LHC). Production and decay properties of the Higgs boson, Standard Model (SM) couplings, and limits on effective scale of the Higgs boson’s couplings with other bosons are investigated at particle colliders. Deviations from SM estimates are parametrized by effective Lagrangian terms to investigate Higgs couplings. This is a model-independent method for describing the new physics. In this study, sensitivity to neutral gauge boson anomalous couplings with the Higgs boson is investigated using the parameters of the Large Hadron electron Collider (LHeC) and the Future Circular electron-hadron Collider (FCC-eh) with a model-independent approach. By using MadGraph5_aMC@NLO multi-purpose event generator with the parameters of LHeC and FCC-eh, the bounds on the anomalous Hγγ, HγZ and HZZ couplings in e− p → e− q H process are obtained. Detector simulations are also taken into account in the calculations.

Keywords: anomalos couplings, FCC-eh, Higgs, Z boson

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Authors: Sumana Kumar, Abha Misra

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Micro-supercapacitors hold great attention as one of the promising energy storage devices satisfying the increasing quest for miniaturized and portable devices. Despite having impressive power density, superior cyclic lifetime, and high charge-discharge rates, micro-supercapacitors still suffer from low energy density, which limits their practical application. The energy density (E=1/2CV²) can be increased either by increasing specific capacitance (C) or voltage range (V). Asymmetric micro-supercapacitors have attracted great attention by using two different electrode materials to expand the voltage window and thus increase the energy density. Currently, versatile fabrication technologies such as inkjet printing, lithography, laser scribing, etc., are used to directly or indirectly pattern the electrode material; these techniques still suffer from scalable production and cost inefficiency. Here, we demonstrate the scalable production of a three-dimensional (3D) carbon foam (CF) based asymmetric micro-supercapacitor by spray printing technique on an array of interdigital electrodes. The solid-state asymmetric micro-supercapacitor comprised of CF-MnO positive electrode and CF-Fe₂O₃ negative electrode achieves a high areal capacitance of 18.4 mF/cm² (2326.8 mF/cm³) at 5 mV/s and a wider potential window of 1.4 V. Consequently, a superior energy density of 5 µWh/cm² is obtained, and high cyclic stability is confirmed with retention of the initial capacitance by 86.1% after 10000 electrochemical cycles. The optimized decoration of pseudocapacitive metal oxides in the 3D carbon network helps in high electrochemical utilization of materials where the 3D interconnected network of carbon provides overall electrical conductivity and structural integrity. The research provides a simple and scalable spray printing method to fabricate an asymmetric micro-supercapacitor using a custom-made mask that can be integrated on a large scale.

Keywords: asymmetric micro-supercapacitors, high energy-density, hybrid materials, three-dimensional carbon-foam

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Authors: Genziana Lay

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A wide majority of older children and adolescents who enter the juvenile court system present with an array of problematic symptoms and behaviors including anxiety, depression, aggressive acting out, detachment, and substance abuse. Attachment theory offers a framework for understanding normative and pathological functioning, which during development is influenced by emotional, social and cognitive elements. There is clear evidence that children and adolescents with the highest risk of developing adaptation problems present an insecure attachment profile. Most offending minors have experienced dysfunctional family relationships as well as social and/or economic deprivation. Their maladaptive attachment develops not only through their relationship with caregivers but with the environment at large. Activation of their faulty attachment system leads them to feel emotionally overwhelmed and engage in destructive behaviors and decision-making. A psycho-social intervention with this population conceptualized as attachment therapy is a multi-faceted, practical approach that has shown excellent results in terms of increased psychological well-being and drastically reduced rates of re-offense/ destructive behavior. Through several; components including psychotherapy, monitoring, volunteering, meditation and socialization, the program focuses on seven dimensions: self-efficacy, responsibility, empathy/reparation, autonomy/security, containment/structure, insight building, and relational health. This paper presents the program and illustrates how the framework of attachment theory practically applied to psycho-social intervention has great therapeutic and social reparation potential. Preliminary evidence drawn from the Sassari Juvenile Court is very promising; this paper will illustrate these results and propose an even more comprehensive, applicable approach to psycho-social reparative intervention that leads to greater psychological health and reduced recidivism in the child and adolescent population.

Keywords: attachment, child, adolescent, crime, juvenile, psychosocial

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Authors: Gichun Cha, Changgil Lee, Seunghee Park

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The objective of the study is to construct the shape management method contributing to the safety of the large structure. In Korea, the research of the shape management is lack because of the new attempted technology. Terrestrial Laser Scanning (TLS) is used for measurements of large structures. TLS provides an efficient way to actively acquire accurate the point clouds of object surfaces or environments. The point clouds provide a basis for rapid modeling in the industrial automation, architecture, construction or maintenance of the civil infrastructures. TLS produce a huge amount of point clouds. Registration, Extraction and Visualization of data require the processing of a massive amount of scan data. The octree can be applied to the shape management of the large structure because the scan data is reduced in the size but, the data attributes are maintained. The octree space partitioning generates the voxel of 3D space, and the voxel is recursively subdivided into eight sub-voxels. The point cloud of scan data was converted to voxel and sampled. The experimental site is located at Sungkyunkwan University. The scanned structure is the steel-frame bridge. The used TLS is Leica ScanStation C10/C5. The scan data was condensed 92%, and the octree model was constructed with 2 millimeter in resolution. This study presents octree space partitioning for handling the point clouds. The basis is created by shape management of the large structures such as double-deck tunnel, building and bridge. The research will be expected to improve the efficiency of structural health monitoring and maintenance. "This work is financially supported by 'U-City Master and Doctor Course Grant Program' and the National Research Foundation of Korea(NRF) grant funded by the Korea government (MSIP) (NRF- 2015R1D1A1A01059291)."

Keywords: 3D scan data, octree space partitioning, shape management, structural health monitoring, terrestrial laser scanning

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Authors: L. Malic, X. Zhang, D. Brassard, L. Clime, J. Daoud, C. Luebbert, V. Barrere, A. Boutin, S. Bidawid, N. Corneau, J. Farber, T. Veres

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The incidence of infections caused by foodborne pathogens such as Listeria monocytogenes (L. monocytogenes) poses a great potential threat to public health and safety. These issues are further exacerbated by legal repercussions due to “zero tolerance” food safety standards adopted in developed countries. Unfortunately, a large number of related disease outbreaks are caused by pathogens present in extremely low counts currently undetectable by available techniques. The development of highly sensitive and rapid detection of foodborne pathogens is therefore crucial, and requires robust and efficient pre-analytical sample preparation. Immunomagnetic separation is a popular approach to sample preparation. Microfluidic chips combined with external magnets have emerged as viable high throughput methods. However, external magnets alone are not suitable for the capture of nanoparticles, as very strong magnetic fields are required. Devices that incorporate externally applied magnetic field and microstructures of a soft magnetic material have thus been used for local field amplification. Unfortunately, very complex and costly fabrication processes used for integration of soft magnetic materials in the reported proof-of-concept devices would prohibit their use as disposable tools for food and water safety or diagnostic applications. We present a sample preparation magnetic microfluidic device implemented in low-cost thermoplastic polymers using fabrication techniques suitable for mass-production. The developed magnetic capture chip (M-chip) was employed for rapid capture and release of L. monocytogenes conjugated to immunomagnetic nanoparticles (IMNs) in buffer and beef filtrate. The M-chip relies on a dense array of Nickel-coated high-aspect ratio pillars for capture with controlled magnetic field distribution and a microfluidic channel network for sample delivery, waste, wash and recovery. The developed Nickel-coating process and passivation allows generation of switchable local perturbations within the uniform magnetic field generated with a pair of permanent magnets placed at the opposite edges of the chip. This leads to strong and reversible trapping force, wherein high local magnetic field gradients allow efficient capture of IMNs conjugated to L. monocytogenes flowing through the microfluidic chamber. The experimental optimization of the M-chip was performed using commercially available magnetic microparticles and fabricated silica-coated iron-oxide nanoparticles. The fabricated nanoparticles were optimized to achieve the desired magnetic moment and surface functionalization was tailored to allow efficient capture antibody immobilization. The integration, validation and further optimization of the capture and release protocol is demonstrated using both, dead and live L. monocytogenes through fluorescence microscopy and plate- culture method. The capture efficiency of the chip was found to vary as function of listeria to nanoparticle concentration ratio. The maximum capture efficiency of 30% was obtained and the 24-hour plate-culture method allowed the detection of initial sample concentration of only 16 cfu/ml. The device was also very efficient in concentrating the sample from a 10 ml initial volume. Specifically, 280% concentration efficiency was achieved in 17 minutes only, demonstrating the suitability of the system for food safety applications. In addition, flexible design and low-cost fabrication process will allow rapid sample preparation for applications beyond food and water safety, including point-of-care diagnosis.

Keywords: array of pillars, bacteria isolation, immunomagnetic sample preparation, polymer microfluidic device

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Authors: Kyo Jin An, Bukyo Seo, Young-Chul Park

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The current trend in car market is increase of parts of automobile and weight in vehicle. It comes from improvement of vehicle performance. Outer tie rod is a part of component of steering system and it is lighter than the others. But, weight lightening is still required for improvement of car mileage. So, we have presented a model of aluminized outer tie rod, but the process of fabrication has to be checked to manufacture the product. Therefore, we have anticipated forming load, die stress and abrasion to use the program of forging interpretation in the part of hot forging process of outer tie rod in this study. Also, we have implemented the experiments design to use the table of orthogonal arrays to reduce the forming load.

Keywords: forming load, hot forging, orthogonal array, outer tie rod (OTR), multi–step forging

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Authors: Mohamed Dakki, Genevieve Robin, Marie Suet, Abdeljebbar Qninba, Mohamed A. El Agbani, Asmâa Ouassou, Rhimou El Hamoumi, Hichem Azafzaf, Sami Rebah, Claudia Feltrup-Azafzaf, Nafouel Hamouda, Wed a.L. Ibrahim, Hosni H. Asran, Amr A. Elhady, Haitham Ibrahim, Khaled Etayeb, Essam Bouras, Almokhtar Saied, Ashrof Glidan, Bakar M. Habib, Mohamed S. Sayoud, Nadjiba Bendjedda, Laura Dami, Clemence Deschamps, Elie Gaget, Jean-Yves Mondain-Monval, Pierre Defos Du Rau

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In biodiversity monitoring, large datasets are becoming more and more widely available and are increasingly used globally to estimate species trends and con- servation status. These large-scale datasets challenge existing statistical analysis methods, many of which are not adapted to their size, incompleteness and heterogeneity. The development of scalable methods to impute missing data in incomplete large-scale monitoring datasets is crucial to balance sampling in time or space and thus better inform conservation policies. We developed a new method based on penalized Poisson models to impute and analyse incomplete monitoring data in a large-scale framework. The method al- lows parameterization of (a) space and time factors, (b) the main effects of predic- tor covariates, as well as (c) space–time interactions. It also benefits from robust statistical and computational capability in large-scale settings. The method was tested extensively on both simulated and real-life waterbird data, with the findings revealing that it outperforms six existing methods in terms of missing data imputation errors. Applying the method to 16 waterbird species, we estimated their long-term trends for the first time at the entire North African scale, a region where monitoring data suffer from many gaps in space and time series. This new approach opens promising perspectives to increase the accuracy of species-abundance trend estimations. We made it freely available in the r package ‘lori’ (https://CRAN.R-project.org/package=lori) and recommend its use for large- scale count data, particularly in citizen science monitoring programmes.

Keywords: biodiversity monitoring, high-dimensional statistics, incomplete count data, missing data imputation, waterbird trends in North-Africa

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Authors: Fatima Faiza Ahmed, Syed Farrukh Hussain

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The last few decades have seen a large proportion of our population bending towards e-learning technologies, starting from learning tools used in primary and elementary schools to competency based e-learning systems specifically designed for applications like finance and marketing. The huge diversity in this crowd brings about a large number of challenges for the designers of these e-learning systems, one of which is the adaptability of such systems. This paper focuses on adaptability in the learning material in an e-learning course and how artificial intelligence and the semantic web can be used as an effective tool for this purpose. The study proved that the semantic web, still a hot topic in the area of computer science can prove to be a powerful tool in designing and implementing adaptable e-learning systems.

Keywords: adaptable e-learning, HTMLParser, information extraction, semantic web

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Authors: Bhumika Gupta, Jeayaram Subramanian, Hardik Vachhrajani, Avinash Shivdas

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Indian food processing industry is one of the largest in the world in terms of production, consumption, exports and growth opportunities. SMEs play a crucial role within this. Large manufacturing firms largely dominate innovation studies in India. Innovation sources used by SMEs are often different from that of large firms. This paper focuses on exploring various sources of innovation adopted by food processing SMEs in Kerala, South India. Outcome suggests that SMEs use various sources like suppliers, competitors, employees, government/research institutions and customers to get new ideas.

Keywords: food processing, innovation, SMEs, sources of innovation

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Bib Paruhum Silalahi, Djihad Wungguli, Sugi Guritman

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Steepest descent method is a simple gradient method for optimization. This method has a slow convergence in heading to the optimal solution, which occurs because of the zigzag form of the steps. Barzilai and Borwein modified this algorithm so that it performs well for problems with large dimensions. Barzilai and Borwein method results have sparked a lot of research on the method of steepest descent, including alternate minimization gradient method and Yuan method. Inspired by previous works, we modified the step size of the steepest descent method. We then compare the modification results against the Barzilai and Borwein method, alternate minimization gradient method and Yuan method for quadratic function cases in terms of the iterations number and the running time. The average results indicate that the steepest descent method with the new step sizes provide good results for small dimensions and able to compete with the results of Barzilai and Borwein method and the alternate minimization gradient method for large dimensions. The new step sizes have faster convergence compared to the other methods, especially for cases with large dimensions.

Keywords: steepest descent, line search, iteration, running time, unconstrained optimization, convergence

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Authors: O. Abusaeeda, J. P. O. Evans, D. Downes

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We demonstrate the synthesis of intermediary views within a sequence of X-ray images that exhibit depth from motion or kinetic depth effect in a visual display. Each synthetic image replaces the requirement for a linear X-ray detector array during the image acquisition process. Scale invariant feature transform, SIFT, in combination with epipolar morphing is employed to produce synthetic imagery. Comparison between synthetic and ground truth images is reported to quantify the performance of the approach. Our work is a key aspect in the development of a 3D imaging modality for the screening of luggage at airport checkpoints. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.

Keywords: X-ray, kinetic depth, KDE, view synthesis

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Authors: Jonghyuk Yoon, Jongil Yoon, Seong-Gyo Chung

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In many kinds of industries which usually need a large amount of power, an axial piston pump has been widely used as a main power source of a hydraulic system. The axial piston pump is a type of positive displacement pump that has several pistons in a circular array within a cylinder block. As the cylinder block and pistons start to rotate, since the exposed ends of the pistons are constrained to follow the surface of the swashed plate, the pistons are driven to reciprocate axially and then a hydraulic power is produced. In the present study, a numerical simulation which has three dimensional full model of the axial piston pump was carried out using a commercial CFD code (Ansys CFX 14.5). In order to take into consideration motion of compression and extension by the reciprocating pistons, the moving boundary conditions were applied as a function of the rotation angle to that region. In addition, this pump using hydraulic oil as working fluid is intentionally designed as a small amount of oil leaks out in order to lubricate moving parts. Since leakage could directly affect the pump efficiency, evaluation of effect of oil-leakage is very important. In order to predict the effect of the oil leakage on the pump efficiency, we considered the leakage between piston-shoe and swash-plate by modeling cylindrical shaped-feature at the end of the cylinder. In order to validate the numerical method used in this study, the numerical results of the flow rate at the discharge port are compared with the experimental data, and good agreement between them was shown. Using the validated numerical method, the effect of the discharge pressure was also investigated. The result of the present study can be useful information of small axial piston pump used in many different manufacturing industries. Acknowledgement: This research was financially supported by the “Next-generation construction machinery component specialization complex development program” through the Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT).

Keywords: axial piston pump, CFD, discharge pressure, hydraulic system, moving boundary condition, oil leaks

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Authors: Ngoc-Hieu Vu

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Dairy production in Vietnam is a relatively new agricultural activity and milk production increased remarkably in recent years. Smallholders are still the main drivers for this development, especially in the southern part of the country. However, information on the farming practices is very limited. Therefore, this study aimed to determine factors influencing milk yield and quality (milk fat, total solids, solids-not-fat, total number of bacteria, and somatic cell count) and revenue of dairy farms in Southern Vietnam. The collection of data was at the farm level; individual animal records were unavailable. The 539 studied farms were located in the provinces Lam Dong (N=111 farms), Binh Duong (N=69 farms), Long An (N=174 farms), and Ho Chi Minh city (N=185 farms). The dataset included 9221 monthly test-day records of the farms from January 2013 to May 2015. Seasons were defined as rainy and dry. Farms sizes were classified as small (< 10 milking cows), medium (10 to 19 milking cows) and large (≥ 20 milking cows). The model for each trait contained year-season and farm region-farm size as subclass fixed effects, and individual farm and residual as random effects. Results showed that year-season, region, and farm size were determining sources of variation affecting all studied traits. Milk yield was higher in dry than in rainy seasons (P < 0.05), while it tended to increase from years 2013 to 2015. Large farms had higher yields (445.6 kg/cow) than small (396.7 kg/cow) and medium (428.0 kg/cow) farms (P < 0.05). Small farms, in contrast, were superior to large farms in terms of milk fat, total solids, solids-not-fat, total number of bacteria, and somatic cell count than large farms (P < 0.05). Revenue per cow was higher in large compared with medium and small farms. In conclusion, large farms achieved higher milk yields and revenues per cow, while small farms were superior in milk quality. Overall, milk yields were low and better training, financial support and marketing opportunities for farmers are needed to improve dairy production and increase farm revenues in Southern Vietnam.

Keywords: farm size, milk yield and quality, season, Southern Vietnam

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Authors: Dhananjay Singh, M. Abdullah-Al-Wadud

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The Internet of Things is a concept of a large scale ecosystem of wireless actuators. The actuators are defined as things in the IoT, those which contribute or produces some data to the ecosystem. However, ubiquitous data collection, data security, privacy preserving, large volume data processing, and intelligent analytics are some of the key challenges into the IoT technologies. In order to solve the security requirements, challenges and threats in the IoT, we have discussed a message authentication mechanism for IoT applications. Finally, we have discussed data encryption mechanism for messages authentication before propagating into IoT networks.

Keywords: Internet of Things (IoT), message authentication, privacy, security

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Authors: Nelson Lujara

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The paper presents a practical three-phase PWM inverter suitable for low voltage, low rating energy efficient systems. The work in the paper is conducted with the view to establishing the significance of the loss contribution from the PWM inverter in the determination of the complete losses of a photovoltaic (PV) array-powered induction motor drive water pumping system. Losses investigated include; conduction and switching loss of the devices and gate drive losses. It is found that the PWM inverter operates at a reasonable variable efficiency that does not fall below 92% depending on the load. The results between the simulated and experimental results for the system with or without a maximum power tracker (MPT) compares very well, within an acceptable range of 2% margin.

Keywords: energy, inverter, losses, photovoltaic

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Authors: Lokendra Kumar Devangan, Ajay Mishra

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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.

Keywords: production planning, mixed integer optimization, network model, network optimization

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Authors: Rekioua T., Rekioua D., Aissou S., Ouhabi A.

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Power provided by the photovoltaic array varies with solar radiation and temperature, since these parameters influence the electrical characteristic (Ipv-Vpv) of solar cells. In Scientific research, there are different methods to obtain these characteristics. In this paper, we present three methods. A simulation one using Matlab/Simulink. The second one is the standard experimental voltage method and the third one is by using LabVIEW software. This latter is based on an electronic circuit to test PV modules. All details of this electronic schemes are presented and obtained results of the three methods with a comparison and under different meteorological conditions are presented. The proposed method is simple and very efficiency for testing and measurements of electrical characteristic curves of photovoltaic panels.

Keywords: photovoltaic cells, measurement standards, temperature sensors, data acquisition

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Authors: Nurdiani Zamhari, Abang Annuar Ehsan

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The 3 dB directional coupler is designed by using silicon-on-insulator (SOI) large cross-section and simulate by Beam Propagation Method at the communication wavelength of 1.55 µm and 1.48 µm. The geometry is shaped with rib height (H) of 6 µm and varied in step factor (r) which is 0.5, 0.6, 0.7 and 0.8. The wave guide spacing is also fixed to 5 µm and the slab width is symmetrical. In general, the 3 dB coupling lengths for four different cross-sections are several millimetre long. The 1.48 of wavelength give the longer coupling length if compare to 1.55 at the same step factor (r). Besides, the low loss propagation is achieved with less than 2 % of propagation loss.

Keywords: 3 dB directional couplers, silicon-on-insulator, symmetrical rib waveguide, OptiBPM 9

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Authors: Amanbek Jainakov, Abdikerim Kurbanaliev

Abstract:

The work presents the results of mathematical modeling of large-scale flows in areas with a complex topographic relief. The Reynolds-averaged Navier—Stokes equations constitute the basis of the three-dimensional unsteady modeling. The well-known Volume of Fluid method implemented in the solver interFoam of the open package OpenFOAM 2.3 is used to track the free-boundary location. The mathematical model adequacy is checked by comparing with experimental data. The efficiency of the applied technology is illustrated by the example of modeling the breakthrough of the dams of the Andijan (Uzbekistan) and Papan (near the Osh town, Kyrgyzstan) reservoir.

Keywords: three-dimensional modeling, free boundary, the volume-of-fluid method, dam break, flood, OpenFOAM

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Authors: Mingjun Xu, Man Pun Wan

Abstract:

This study proposed an effective smoke control strategy for the large flat space with a low ceiling to achieve the requirement of perpetual tenability. For the large flat space with a low ceiling, the depth of the smoke reservoir is very shallow, and it is difficult to perpetually constrain the smoke within a limited space. A series of numerical tests were conducted to determine the smoke strategy. A zonal design i.e., the fire zone and two adjacent zones was proposed and validated to be effective in controlling smoke. Once a fire happens in a compartment space, the Engineered Smoke Control (ESC) system will be activated in three zones i.e., the fire zone, in which the fire happened, and two adjacent zones. The smoke can be perpetually constrained within the three smoke zones. To further improve the extraction efficiency, sequential activation of the ESC system within the 3 zones turned out to be more efficient than simultaneous activation. Additionally, the proposed zonal and sequential extraction design can reduce the mechanical extraction flow rate by up to 40.7 % as compared to the conventional method, which is much more economical than that of the conventional method.

Keywords: performance-based design, perpetual tenability, smoke control, fire plume

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Authors: Jin Y. Park, Jeong Wan Lee

Abstract:

An experimental and analytical research on shear buckling of a comparably large polymer composite I-section is presented. It is known that shear buckling load of a large span composite beam is difficult to determine experimentally. In order to sensitively detect shear buckling of the tested I-section, twenty strain rosettes and eight displacement sensors were applied and attached on the web and flange surfaces. The tested specimen was a pultruded composite beam made of vinylester resin, E-glass, carbon fibers and micro-fillers. Various coupon tests were performed before the shear buckling test to obtain fundamental material properties of the I-section. An asymmetric four-point bending loading scheme was utilized for the shear test. The loading scheme resulted a high shear and almost zeros moment condition at the center of the web panel. The shear buckling load was successfully determined after analyzing the obtained test data from strain rosettes and displacement sensors. An analytical approach was also performed to verify the experimental results and to support the discussed experimental program.

Keywords: strain sensor, displacement sensor, shear buckling, polymer composite I-section, asymmetric loading

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Authors: Ravi Ande, Mousumi Hazari

Abstract:

One of the common geophysical techniques for mapping subsurface geo-electrical structures, extensive hydro-geological research, and engineering and environmental geophysics applications is the use of time domain electromagnetic (TDEM)/transient electromagnetic (TEM) soundings. A large transmitter loop for energising the ground and a small receiver loop or magnetometer for recording the transient voltage or magnetic field in the air or on the surface of the earth, with the receiver at the center of the loop or at any random point inside or outside the source loop, make up a large loop TEM system. In general, one can acquire data using one of the configurations with a large loop source, namely, with the receiver at the center point of the loop (central loop method), at an arbitrary in-loop point (in-loop method), coincident with the transmitter loop (coincidence-loop method), and at an arbitrary offset loop point (offset-loop method), respectively. Because of the mathematical simplicity associated with the expressions of EM fields, as compared to the in-loop and offset-loop systems, the central loop system (for ground surveys) and coincident loop system (for ground as well as airborne surveys) have been developed and used extensively for the exploration of mineral and geothermal resources, for mapping contaminated groundwater caused by hazardous waste and thickness of permafrost layer. Because a proper analytical expression for the TEM response over the layered earth model for the large loop TEM system does not exist, the forward problem used in this inversion scheme is first formulated in the frequency domain and then it is transformed in the time domain using Fourier cosine or sine transforms. Using the EMLCLLER algorithm, the forward computation is initially carried out in the frequency domain. As a result, the EMLCLLER modified the forward calculation scheme in NLSTCI to compute frequency domain answers before converting them to the time domain using Fourier Cosine and/or Sine transforms.

Keywords: time domain electromagnetic (TDEM), TEM system, geoelectrical sounding structure, Fourier cosine

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Authors: Oluseun A. Akinsorotan, Louise K. Gentle, Md. Mofakkarul Islam, Richard W. Yarnell

Abstract:

High levels of anthropogenic activity such as habitat destruction, poaching and encroachment into natural habitat have resulted in significant global wildlife declines. In order to protect wildlife, many protected areas such as national parks have been created. However, it is argued that many protected areas are only protected in name and are often exposed to continued, and often illegal, anthropogenic pressure. In West African protected areas, declines of large mammals have been documented between 1962 and 2008. This study aimed to produce occupancy estimates of the remaining large mammal fauna in the third largest National Park in Nigeria, Old Oyo, and to compare the estimates with historic estimates while also attempting to quantify levels of illegal anthropogenic activity using a multi-disciplinary approach. Large mammal populations and levels of illegal anthropogenic activity were assessed using empirical field data (camera trapping and transect surveys) in combination with data from questionnaires completed by local villagers and park rangers. Four of the historically recorded species in the park, lion (Panthera leo), hunting dog (Lycaon pictus), elephant (Loxodonta africana) and buffalo (Syncerus caffer) were not detected during field studies nor were they reported by respondents. In addition, occupancy estimates of hunters and illegal grazers were higher than the majority of large mammal species inside the park. This finding was reinforced by responses from the villagers and rangers who’s perception was that large mammal densities in the park were declining, and that a large proportion of the local people were entering the park to hunt wild animals and graze their domestic livestock. Our findings also suggest that widespread poverty and a lack of alternative livelihood opportunities, culture of consuming bushmeat, lack of education and awareness of the value of protected areas, and weak law enforcement are some of the reasons for the illegal activity. Law enforcement authorities were often constrained by insufficient on-site personnel and a lack of modern equipment and infrastructure to deter illegal activities. We conclude that there is a need to address the issue of illegal hunting and livestock grazing, via provision of alternative livelihoods, in combination with community outreach programmes that aim to improve conservation education and awareness and develop the capacity of the conservation authorities in order to achieve conservation goals. Our findings have implications for the conservation management of all protected areas that are available for exploitation by local communities.

Keywords: camera trapping, conservation, extirpation, illegal grazing, large mammals, national park, occupancy estimates, poaching

Procedia PDF Downloads 295