Search results for: cost performance

Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

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Authors: Galo D. Soria, Jenny S. Casame, Eddy F. Pazmino

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In Ecuador, mining operations have significantly impacted water sources. Artisanal mining extensively relies in mercury amalgamation. Mercury is a neurotoxic substance even at low concentrations. The objective of this investigation is to exploit Hg-removal capacity of sulfur-limonene polysulfide (SLP), which is a low-cost polymer, in order to prepare granular media (sand) coated with SLP to be used in laboratory scale column-filtration systems. Preliminary results achieved 85% removal of Hg⁺⁺ from synthetic effluents using 20-cm length and 5-cm diameter columns at 119m/day average pore water velocity. During elution of the column, the SLP-coated sand indicated that Hg⁺⁺ is permanently fixed to the collector surface, in contrast, uncoated sand showed reversible retention in Hg⁺⁺ in the solid phase. Injection of 50 pore volumes decreased Hg⁺⁺ removal to 46%. Ongoing work has been focused in optimizing the synthesis of SLP and the polymer content in the porous media coating process to improve Hg⁺⁺ removal and extend the lifetime of the column-filter.

Keywords: column-filter, mercury, mining, polysulfide, water treatment

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Authors: K. Bourouni, M. Chacha, T. Jaber, A. Tchantchane

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In Multi-Effect Distillation (MED) desalination evaporators, the scale deposit outside the tubes presents a barrier to heat transfers reducing the global heat transfer coefficient and causing a decrease in water production; hence a loss of efficiency and an increase in operating and maintenance costs. Scale removal (by acid cleaning) is the main maintenance operation and constitutes the major reason for periodic plant shutdowns. A better understanding of scale deposition mechanisms will lead to an accurate determination of the variation of scale thickness around the tubes and an improved accuracy of the overall heat transfer coefficient calculation. In this paper, a coupled heat transfer-calcium carbonate scale deposition model on a horizontal tube bundle is presented. The developed tool is used to determine precisely the heat transfer area leading to a significant cost reduction for a given water production capacity. Simulations are carried to investigate the influence of different parameters such as water salinity, temperature, etc. on the heat transfer.

Keywords: multi-effect-evaporator, scale deposition, water desalination, heat transfer coefficient

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Authors: Joyraj Chakraborty, Geoffrey Ottoy, Jean-Pierre Goemaere, Lieven De Strycker

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Sensor swarms can be a cost-effectieve and more user-friendly alternative for location based service systems in different application like health-care. To increase the lifetime of such swarm networks, the energy consumption should be scaled to the required localization accuracy. In this paper we have investigated some parameter for energy model that couples localization accuracy to energy-related sensor parameters such as signal length,Bandwidth and sample frequency. The goal is to use the model for the localization of undetermined environmental sounds, by means of wireless acoustic sensors. we first give an overview of TDOA-based localization together with the primary sources of TDOA error (including reverberation effects, Noise). Then we show that in localization, the signal sample rate can be under the Nyquist frequency, provided that enough frequency components remain present in the undersampled signal. The resulting localization error is comparable with that of similar localization systems.

Keywords: sensor swarms, localization, wireless sensor swarms, scalable energy

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Authors: Monalisha Ghosh, Asit Mohanty

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The lack of sanitation increases living costs, decreases spend on education and nutrition, lowers income earning potential, and threatens safety and welfare. This is especially true for rural India. Only 32% of rural households have their own toilets and that less than half of Indian households have a toilet at home. Of the estimated billion people in the world who defecate in the open, more than half reside in rural India. It is empirically established that poor sanitation leads to high infant mortality rate and low income generation in rural India. In India, 1,600 children die every day before reaching their fifth birthday and 24% of girls drop out of school as the lack of basic sanitation. Above all, lack of sanitation is not a symptom of poverty but a major contributing factor. According to census 2011, 67.3% of the rural households in the country still did not have access to sanitation facilities. India’s sanitation deficit leads to losses worth roughly 6% of its gross domestic product (GDP) according to World Bank estimates by raising the disease burden in the country. The dropout rate for girl child is thirty percent in schools in rural areas because of lack of sanitation facilities for girl students. The productivity loss per skilled labors during a year is calculated at Rs.44, 160 in Odisha. The performance of the state of Odisha has not been satisfactory in improving sanitation facilities. The biggest challenge is triggering behavior change in vast section of rural population regarding need to use toilets. Another major challenge is funding and implementation for improvement of sanitation facility. In an environment of constrained economic resources, Public Private Partnership in form of performance based management or maintenance contract will be all the more relevant to improve the sanitation status in rural sector.

Keywords: rural sanitation, infant mortality rate, income, granger causality, pooled OLS method test public private partnership

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Authors: S. M. Arciniegas, D. Vargas, L. Gutierrez

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The aim of this study was to develop oral drug presentation of doxycycline hyclate that maintains longer therapeutic levels than conventional forms. A polymethacrylate and acrylic acid based matrix were used in different proportions to obtain controlled-release formulations; DOX1 (1:0.25:0.0035), DOX2 (1:2:0.0225) and DOX-C (without excipients). All were tested in vivo in healthy dogs and their serum concentrations vs. time profile was investigated after its oral administration in this species. DOX1 and DOX2 show therapeutic concentrations for 60 hours, while DOX-C only for 24 hours. The pharmacokinetics values tested were K½el, Cmax, Tmax, AUC, AUC∞, AUCt, AUMC, RT, Kel, Vdss, Clb and Frel. DOX1 does not differ significantly from DOX-C, but shows significant differences in all variables with DOX2 (p<0.05). In conclusion, DOX1 presents best pharmacokinetics for time-dependent drug and longer release time of 60 hours, thereby reducing the frequency of administration, the patient's stress, the occurrence of adverse effects and the cost of treatment.

Keywords: tetracyclines, long-acting, sustained-release, carbopol, eudragit, canine

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Authors: Ali Gharib, Leila Vojdanifard, Nader Noroozi Pesyan

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Different Pyrazoline derivatives were synthesized by cyclization of substituted chalcone derivatives in presence of hydrazine hydrate. A series of novel 1,3,5-triaryl pyrazoline derivatives has been synthesized by the reaction of chalcone and phenylhydrazine in the presence of the Fe3O4 NPs, in high yields. The structures of compounds obtained were determined by IR and 1H NMR spectra. Fe3O4 NPs was recycled and no appreciable change in activity was noticed after three cycles.

Keywords: pyrazoline, chalcone, nanoparticles, Fe3O4, catalyst, synthesis

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Authors: Matthew Yeager, Christopher Willy, John Bischoff

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The conceptualization and design phases of a system lifecycle consume a significant amount of the lifecycle budget in the form of direct tasking and capital, as well as the implicit costs associated with unforeseeable design errors that are only realized during downstream phases. Ad hoc or iterative approaches to generating system requirements oftentimes fail to consider the full array of feasible systems or product designs for a variety of reasons, including, but not limited to: initial conceptualization that oftentimes incorporates a priori or legacy features; the inability to capture, communicate and accommodate stakeholder preferences; inadequate technical designs and/or feasibility studies; and locally-, but not globally-, optimized subsystems and components. These design pitfalls can beget unanticipated developmental or system alterations with added costs, risks and support activities, heightening the risk for suboptimal system performance, premature obsolescence or forgone development. Supported by rapid advances in learning algorithms and hardware technology, sensors and sensor systems have become commonplace in both commercial and industrial products. The evolving array of hardware components (i.e. sensors, CPUs, modular / auxiliary access, etc…) as well as recognition, data fusion and communication protocols have all become increasingly complex and critical for design engineers during both concpetualization and implementation. This work seeks to develop and utilize a non-deterministic approach for sensor system design within the multi-attribute tradespace exploration (MATE) paradigm, a technique that incorporates decision theory into model-based techniques in order to explore complex design environments and discover better system designs. Developed to address the inherent design constraints in complex aerospace systems, MATE techniques enable project engineers to examine all viable system designs, assess attribute utility and system performance, and better align with stakeholder requirements. Whereas such previous work has been focused on aerospace systems and conducted in a deterministic fashion, this study addresses a wider array of system design elements by incorporating both traditional tradespace elements (e.g. hardware components) as well as popular multi-sensor data fusion models and techniques. Furthermore, statistical performance features to this model-based MATE approach will enable non-deterministic techniques for various commercial systems that range in application, complexity and system behavior, demonstrating a significant utility within the realm of formal systems decision-making.

Keywords: multi-attribute tradespace exploration, data fusion, sensors, systems engineering, system design

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Authors: Kishor T. Zingre, Seshadhri Srinivasan

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Energy consumption by the building sector is increasing at an alarming rate throughout the world and leading to more building-related CO₂ emissions into the environment. In buildings, the main contributors to energy consumption are heating, ventilation, and air-conditioning (HVAC) systems, lighting, and electrical appliances. It is hypothesised that the energy efficiency in buildings can be achieved by implementing sustainable technologies such as i) enhancing the thermal resistance of fabric materials for reducing heat gain (in hotter climates) and heat loss (in colder climates), ii) enhancing daylight and lighting system, iii) HVAC system and iv) occupant localization. Energy performance of various sustainable technologies is highly dependent on climatic conditions. This paper investigated the use of machine learning techniques for accurate prediction of air-conditioning energy in seasonal climates. The data required to train the machine learning techniques is obtained using the computational simulations performed on a 3-story commercial building using EnergyPlus program plugged-in with OpenStudio and Google SketchUp. The EnergyPlus model was calibrated against experimental measurements of surface temperatures and heat flux prior to employing for the simulations. It has been observed from the simulations that the performance of sustainable fabric materials (for walls, roof, and windows) such as phase change materials, insulation, cool roof, etc. vary with the climate conditions. Various renewable technologies were also used for the building flat roofs in various climates to investigate the potential for electricity generation. It has been observed that the proposed technique overcomes the shortcomings of existing approaches, such as local linearization or over-simplifying assumptions. In addition, the proposed method can be used for real-time estimation of building air-conditioning energy.

Keywords: building energy efficiency, energyplus, machine learning techniques, seasonal climates

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Authors: Azyuni Aziz, Syed A. Malik, Shahrul Kadri Ayop, Fatin Hana Naning

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Currently, organic-inorganic hybrid thin films have attracted researchers to explore them, where these thin films can give a lot of benefits. Hybrid thin films are thin films that consist of inorganic and organic materials. Inorganic and organic materials give high efficiency and low manufacturing cost in some applications such as solar cells application, furthermore, organic materials are environment-friendly. In this study, poly (3-hexylthiophene) was choosing as organic material which combined with inorganic nanoparticles, Cadmium Sulfide (CdS) quantum dots. Samples were prepared using new technique, Angle Lifting Deposition (ALD) at different weight percentage. All prepared samples were then characterized by Field Emission Scanning Electron Microscopy (FESEM) with Energy-dispersive X-ray spectroscopy (EDX) and Atomic Force Microscopy (AFM) to study surface of samples and determine their surface roughness. Results show that these inorganic nanoparticles have affected the surface of samples and surface roughness of samples increased due to increasing of weight percentage of CdS in the thin films samples.

Keywords: AFM, CdS, FESEM-EDX, hybrid thin films, P3HT

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Authors: Malek Y. S. Ibrahim, Jeffrey A. Bennett, Milad Abolhasani

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Despite the potential of hydrogen (H2) storage in liquid organic carriers to achieve carbon neutrality, the energy required for H2 release and the cost of catalyst recycling has hindered its large-scale adoption. In response, a photo flow reactor packed with rhodium (Rh)/titania (TiO2) photocatalyst was reported for the continuous and selective acceptorless dehydrogenation of 1,2,3,4-tetrahydroquinoline to H2 gas and quinoline under visible light irradiation at room temperature. The tradeoff between the reactor pressure drop and its photocatalytic surface area was resolved by selective in-situ photodeposition of Rh in the photo flow reactor post-packing on the outer surface of the TiO2 microparticles available to photon flux, thereby reducing the optimal Rh loading by 10 times compared to a batch reactor, while facilitating catalyst reuse and regeneration. An example of using quinoline as a hydrogen acceptor to lower the energy of the hydrogen production step was demonstrated via the water-gas shift reaction.

Keywords: hydrogen storage, flow chemistry, photocatalysis, solar hydrogen

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Authors: Arlan Zandro Brucal, John Lynham

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With the accelerated sea-level rise (SLR) increasingly becoming a concern, demand for coastal management and protection is expected to grow. Among the coastal management and protection methods, building seawalls are among the most controversial due to the negative externalities they impose on beachgoers and neighboring properties. This paper provides estimates of the external cost associated with building seawalls on the island of Oahu in Hawaii. Using hedonic pricing approach on real properties sold between 1980-2010 and aerial photographs of seawalls in 1995, the paper finds that (1) while seawalls do increase the value of protected properties, the share of armored properties appear to be negatively correlated with property sale prices, suggesting that the positive effect of seawalls tend to decline as more and more rely on this coastal management method; and (2) the value of beachfront properties tend to decline as they get approach seawalls. Results suggest that policymakers should devise a policy that would internalize the externalities associated with private-sector adaptation to climate change.

Keywords: private sector climate change adaptation, externalities, sea-level rise, hedonic pricing

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

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Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

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Authors: Seyedmirsajad Mokhtarimousavi, Danial Talebi, Hamidreza Asgari

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Gate Assignment Problem (GAP) is one of the most substantial issues in airport operation. In principle, GAP intends to maintain the maximum capacity of the airport through the best possible allocation of the resources (gates) in order to reach the optimum outcome. The problem involves a wide range of dependent and independent resources and their limitations, which add to the complexity of GAP from both theoretical and practical perspective. In this study, GAP was mathematically formulated as a three-objective problem. The preliminary goal of multi-objective formulation was to address a higher number of objectives that can be simultaneously optimized and therefore increase the practical efficiency of the final solution. The problem is solved by applying the second version of Non-dominated Sorting Genetic Algorithm (NSGA-II). Results showed that the proposed mathematical model could address most of major criteria in the decision-making process in airport management in terms of minimizing both airport/airline cost and passenger walking distance time. Moreover, the proposed approach could properly find acceptable possible answers.

Keywords: airport management, gate assignment problem, mathematical modeling, genetic algorithm, NSGA-II

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Authors: Mikiyas Adugna

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Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.

Keywords: agile software development, effort estimation, elastic net regression, LASSO

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Authors: Mohammedi Ferhate

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This work presents details of the study of the entire flow inside the facility where the exothermic chemical reaction process in the chemical laser cavity is analyzed. In our paper we will describe the principles of chemical lasers where flow reversal is produced by chemical reactions. We explain the device for converting chemical potential energy laser energy. We see that the phenomenon thus has an explosive trend. Finally, the feasibility and effectiveness of the proposed method is demonstrated by computer simulation

Keywords: genetic, lasers, nozzle, programming

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Authors: Tovondahiniriko Fanjirindratovo, Olga Ramiarinjanahary, Paulisimone Rasoavonjy

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

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

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Authors: Dharamvir Mangal

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Supply chain management has increasingly become an inevitable challenge to most companies to continuously survive and prosper in the global chain-based competitive environment. The current challenges of the Indian automotive world, their implications on supply chain are summarized and analyzed in this paper. In this competitive era of ‘LPG’ i.e. Liberalization, Privatization and Globalization, modern marketing systems, introduction of products with short life cycles, and the discriminating expectations of customers have enforced business enterprises to invest in and focus attention on their Supply Chains (SCs) in order to meet out the level of customer’s satisfaction and to survive in the competitive market. In fact, many of trends in the auto industry are reinforcing the need to redefine supply chain strategies layouts, and operations etc. Many manufacturing operations are designed to maximize throughput and lower costs with modest considerations for the crash on inventory levels and distribution capabilities. To improve profitability and efficiency, automotive players are seeking ways to achieve operational excellence, reduce operating cost and enhance customer service through efficient supply chain management.

Keywords: automotive industry, supply chain, challenges, market potential

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Md. Anayet U. Patwari, Mohammad Ahsan Habib, Md. Tanzib Ehsan, Md Golam Ahnaf, Md. S. I. Chowdhury

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Surface roughness is one of the key quality parameters of the finished product. During any machining operation, high temperatures are generated at the tool-chip interface impairing surface quality and dimensional accuracy of products. Cutting fluids are generally applied during machining to reduce temperature at the tool-chip interface. However, usages of cutting fluids give rise to problems such as waste disposal, pollution, high cost, and human health hazard. Researchers, now-a-days, are opting towards dry machining and other cooling techniques to minimize use of coolants during machining while keeping surface roughness of products within desirable limits. In this paper, a concept of using peltier cooling effects during aluminium milling operation has been presented and adopted with an aim to improve surface roughness of the machined surface. Experimental evidence shows that peltier cooling effect provides better surface roughness of the machined surface compared to dry machining.

Keywords: aluminium, milling operation, peltier cooling effect, surface roughness

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Authors: Wang Guangda, Ma Jun, Zhao Caiqi, Pan Rui

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Wind load is the main control load of large statue structures. Due to the irregular plane and elevation and uneven outer contour, statues’ shape coefficient can not pick up from the current code. Currently a common practice is based on wind tunnel test. But this method is time-consuming and high cost. In this paper, based on the fundamental theory of CFD, using fluid dynamics software of Fluent 15.0, a few large statue structure of 40 to 70m high, which are located in china , including large fairy statues and large Buddha statues, are analyzed by numerical wind tunnel. The results are contrasted with the recommended values in load code and the wind tunnel test results respectively. Results show that the shape coefficient has a good reliability by the numerical wind tunnel method of this kind of building. This will has a certain reference value of wind load values for large statues’ structure.

Keywords: large statue structure, shape coefficient, irregular structure, wind tunnel test, numerical wind tunnel simulation

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Authors: Chris Phan, Yong Seok Park

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The Toyota Camry is one of the best-selling cars in America. It is economical, reliable, and most importantly, safe. These attributes allowed the Camry to be the trustworthy choice when choosing dependable vehicle. However, a new finding brought question to the Camry’s safety. Since 1997, the Camry received a “good” rating on its moderate overlap front crash test through the Insurance Institute of Highway Safety. In 2012, the Insurance Institute of Highway Safety introduced a frontal small overlap crash test into the overall evaluation of vehicle occupant safety test. The 2012 Camry received a “poor” rating on this new test, while the 2015 Camry redeemed itself with a “good” rating once again. This study aims to find a possible solution that Toyota implemented to reduce the severity of a frontal small overlap crash in the Camry during a mid-cycle update. The purpose of this study is to analyze and evaluate the performance of various A-pillar shapes as energy absorbing structures in improving passenger safety in a frontal crash. First, A-pillar structures of the 2012 and 2015 Camry were modeled using CAD software, namely SolidWorks. Then, a crash test simulation using ANSYS software, was applied to the A-pillars to analyze the behavior of the structures in similar conditions. Finally, the results were compared to safety values of cabin intrusion to determine the crashworthy behaviors of both A-pillar structures by measuring total deformation. This study highlights that it is possible that Toyota improved the shape of the A-pillar in the 2015 Camry in order to receive a “good” rating from the IIHS safety evaluation once again. These findings can possibly be used to increase safety performance in future vehicles to decrease passenger injury or fatality.

Keywords: A-pillar, Crashworthiness, Design Synthesis, Finite Element Analysis

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Authors: G. B. Manjunatha

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Natural fibers have been considerable demand in recent years due to their ecofriendly and renewable nature. The advantages of low density, acceptable specific properties, better thermal and insulate properties with low cost.In the present study, hybrid composite associating Sheep wool fiber and glass fiber reinforced with epoxy were developed and investigated the effect of stacking sequence on physical and chemical properties. The hybrid composite was designed for engineering applications as an alternative material to glass fiber composites. The hybrid composite laminates were fabricated by using hand lay-up technique at total fiber volume fraction of 60% (Sheep wool fiber 30% and Glass fiber 30%) and 40% reinforcement. The specimen preparation and testing were conducted as per American Society for Testing and Materials (ASTM) standards. Three different stacking are used. The result shows that tensile and bending tests of sequence of glass fiber between sheep wool fiber have high strength and maximum bending compared to other sequence of composites. At the same time better moisture and chemical absorption were observed.

Keywords: hybrid composites, mechanical properties, polymer composites, stacking sequence

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Authors: Zhan Jie How

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With the heightened awareness of workplace learning and its impact on improving organizational performance and developing employee competence, governments and corporations around the world are forced to intensify their cooperation to establish national workplace development programmes to guide these corporations in fostering engaging and collaborative workplace learning cultures. This conceptual paper aims to conduct a comparative study of existing workplace development programmes for small and medium-sized enterprises (SMEs) in Europe and Singapore, focusing primarily on the Swedish Production Leap, Finnish TEKES Liideri Programme, and Singapore SkillsFuture SME Mentors Programme. The study carries out a systematic review of the three workplace development programmes to examine the roles of external mentors or coaches in influencing the design and implementation of workplace learning strategies and practices in SMEs. Organizational, personal and external factors that promote or inhibit effective workplace mentorship are also scrutinized, culminating in a critical comparison and evaluation of the strengths and weaknesses of the aforementioned programmes. Based on the findings from the review and analyses, a heuristic conceptual framework is developed to illustrate the complex interrelationships among external workplace development programmes, internal learning and development initiatives instituted by the organization’s higher management, and employees' continuous learning activities at the workplace. The framework also includes a set of guiding principles that can be used as the basis for internal mediation between the competing perspectives of mentors and mentees (employers and employees of the organization) regarding workplace learning conditions, practices and their intended impact on the organization. The conceptual study provides a theoretical blueprint for future empirical research on organizational workplace learning and the impact of government-initiated workplace development programmes.

Keywords: employee competence, mentorship, organizational performance, workplace development programme, workplace learning culture

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Authors: Koko Wangjam, Naresh Kumar Sharma

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The concern for most public health policies and decision- makers is the equitable distribution of health care resource of the nation. Also, in public health care system, the primary aim is assuaging the burden of the disease. Objective: This paper captures and evaluates some important theories in equity in health with its relevance with the ART program in India. Methodology: The paper is exploratory and descriptive study based on secondary data. The sources of secondary data are published official reports from NACO (National AIDS Control Organisation), United Nations AIDS Program (UNAIDS), World Health Organisation (WHO) etc. Observation: The roll-out of the ART program in 2004 by the Govt. of India made a paradigm shift in HIV/AIDS scenario in the country. Conclusion: There are many theoretical injunctions in most of the principles and approaches in existing theories of health equity. The enervation of HIV infection by taking ART drugs had helped in curbing the prevalence and the fact that it is provided at free of cost has proven this program to be an epitome in distributive justice in public health.

Keywords: art program, burden of the disease, health equity, hiv/aids

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Authors: Mengesha Mamo Wogari

Abstract:

In this paper, low voltage multiphase brushless DC motor with square wave air-gap flux distribution for electric vehicle application is proposed. Ten-phase, 5 kW motor, has been designed and simulated by finite element methods demonstrating the desired high torque capability at low speed and flux weakening operation for high-speed operations. The motor torque is proportional to number of phases for a constant phase current and air-gap flux. The concept of vector control and simple space vector modulation technique is used on MATLAB to control the motor demonstrating simple switching pattern for selected number of phases. The low voltage DC and inverter output AC are desired characteristics to avoid any electric shock in the vehicle, accidentally and during abnormal conditions. The switching devices for inverter are of low-voltage rating and cost effective though their number is equal to twice the number of phases.

Keywords: brushless DC motors, electric Vehicle, finite element methods, Low-voltage inverter, multiphase

Procedia PDF Downloads 151

Authors: Mongezi Nene, Emma Ayesu-Koranteng, Christopher Amoah, Ayo Adeniran

Abstract:

Although its use has been criticized over the years as being unencouraging, the green building concept is quickly overtaking other concepts, particularly in the construction of commercial properties. The goal of the study is to identify the variables influencing the use of green building practices when developing residential structures. A qualitative methodology, using interviews with semi-structured open-ended questions to 35 property practitioners operating residential apartments in Bloemfontein, South Africa, was used to collect primary data which was analysed using thematic content analysis. The findings show that while respondents have a good understanding of green building principles, they are not being used in the construction of residential buildings in South Africa due to issues with green building approval procedures, the potential for tenant rent increases, the cost of materials, technical issues, contractual issues, and a lack of awareness, among others. This paper recommends among others an urgent need to implement measures by stakeholders towards enhancing the adoption of green building concepts in the construction of residential buildings as well as incentivising its construction through lowered property rates.

Keywords: green building, residential apartments, construction, South Africa

Procedia PDF Downloads 100

Authors: Payal Patel

Abstract:

Textile machinery is one of the fastest evolving areas which has an application of mechanical engineering. The modular approach towards the processing right from the stage of cotton to the fabric, allows us to observe the result of each process on its input. Cost and space being the major constraints. The flyer is a component of roving machine, which is used as a part of spinning process. In the present work using the application of Hyper Works, the flyer arm has been modified which saves the material used for manufacturing the flyer. The size optimization of the flyer is carried out with the objective of reduction in weight under the constraints of standard operating conditions. The new design of the flyer is proposed and validated using the module of HyperWorks which is equally strong, but light weighted compared to the existing design. Dynamic balancing of the optimized model is carried out to align a principal inertia axis with the geometric axis of rotation. For the balanced geometry of flyer, air resistance is obtained theoretically and with Gambit and Fluent. Static analysis of the balanced geometry has been done to verify the constraint of operating condition. Comparison of weight, deflection, and factor of safety has been made for different aluminum alloys.

Keywords: flyer, size optimization, textile, weight

Procedia PDF Downloads 210

Authors: Jawad Ul Haq, Evan Mazur, Ahmed Qureshi, Mohamed Al-Hussein

Abstract:

The uses of wood in furniture, building, bridges and aluminum in transportation and construction, make aluminum and forest economy a prominent matter in North America. Machines available to date to cut the aforementioned materials are mostly industry oriented with complex structure and operations which require special training and skill. Furthermore, requirements such as pneumatics, 3-phase supply are associated with cost, maintenance, and safety hazards. Power saws are very useful tools used to cut and shape materials; however, they can cause serious hand injuries. Operator’s hands in table saw are vulnerable as they are used to guide pieces into the saw. Apart from hands, saw operator is also prone to material being kicked back out of the saw or sustain eye or respiratory injuries due to rapidly flying sawdust and other debris. In this paper, design of an automatic saw cutting machine has been proposed to ensure safety, portability, usage at domestic level and capability to cut both aluminum and wood. This paper demonstrates detailed Mechanical design in SOLIDWORKS and Control Systems using Programmable Logic Controller (PLC), based on the aforementioned design objectives.

Keywords: programmable logic controller, saw cutting, control, automation

Procedia PDF Downloads 270