Search results for: real rolled thickness of strips

Authors: Rishi Richa, N. C. Shahi, J. P. Pandey, S. S. Kautkar

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Citrus fruits rank third in area and production after banana and mango in India. Sweet oranges are the second largest citrus fruits cultivated in the country. Andhra Pradesh, Maharashtra, Karnataka, Punjab, Haryana, Rajasthan, and Uttarakhand are the main sweet orange-growing states. Citrus fruits occupy a leading position in the fruit trade of Uttarakhand, is casing about 14.38% of the total area under fruits and contributing nearly 17.75 % to the total fruit production. Malta is grown in most of the hill districts of the Uttarakhand. Malta common is having high acceptability due to its attractive colour, distinctive flavour, and taste. The excellent quality fruits are generally available for only one or two months. However due to its less shelf-life, Malta can not be stored for longer time under ambient conditions and cannot be transported to distant places. Continuous loss of water adversely affects the quality of Malta during storage and transportation. Method of picking, packaging, and cold storage has detrimental effects on moisture loss. The climatic condition such as ambient temperature, relative humidity, wind condition (aeration) and microbial attack greatly influences the rate of moisture loss and quality. Therefore, different agro-climatic zone will have different moisture loss pattern. The rate of moisture loss can be taken as one of the quality parameters in combination of one or more parameter such as RH, and aeration. The moisture contents of the fruits and vegetables determine their freshness. Hence, it is important to maintain initial moisture status of fruits and vegetable for prolonged period after the harvest. Keeping all points in views, effort was made to store Malta at ambient condition. In this study, the response surface method and experimental design were applied for optimization of independent variables to enhance the shelf life of four months stored malta. Box-Benkhen design, with, 12 factorial points and 5 replicates at the centre point were used to build a model for predicting and optimizing storage process parameters. The independent parameters, viz., scavenger (3, 4 and 5g), polythene thickness (75, 100 and 125 gauge) and fungicide concentration (100, 150 and 200ppm) were selected and analyzed. 5g scavenger, 125 gauge and 200ppm solution of fungicide are the optimized value for storage which may enhance life up to 4months.

Keywords: Malta fruit, scavenger, packaging, shelf life

Procedia PDF Downloads 274

Authors: Juan F. Muñoz-Rosas, Rosa M. García-Fernández, Encarnación Álvarez-Verdejo, Pablo J. Moya-Fernández

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Poverty measurement is a very important topic in many studies in social sciences. One of the most important indicators when measuring poverty is the low income proportion. This indicator gives the proportion of people of a population classified as poor. This indicator is generally unknown, and for this reason, it is estimated by using survey data, which are obtained by official surveys carried out by many statistical agencies such as Eurostat. The main feature of the mentioned survey data is the fact that they contain several variables. The variable used to estimate the low income proportion is called as the variable of interest. The survey data may contain several additional variables, also named as the auxiliary variables, related to the variable of interest, and if this is the situation, they could be used to improve the estimation of the low income proportion. In this paper, we use Monte Carlo simulation studies to analyze numerically the performance of estimators based on several auxiliary variables. In this simulation study, we considered real data sets obtained from the 2011 European Union Survey on Income and Living Condition. Results derived from this study indicate that the estimators based on auxiliary variables are more accurate than the naive estimator.

Keywords: inclusion probability, poverty, poverty line, survey sampling

Procedia PDF Downloads 452

Authors: Ming Lu, Xiaojun Li, Bodi Lu, Juehui Xing

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Earthquake damage phenomenon of each large earthquake gives comprehensive and profound real test to the dynamic performance and failure mechanism of different engineering structures. Cognitive engineering structure characteristics through seismic damage phenomenon are often far superior to expensive shaking table experiments. After the earthquake, people will record a variety of different types of engineering damage photos. However, a large number of earthquake damage photographs lack sufficient information and reduce their using value. To improve the research value and the use efficiency of engineering seismic damage photographs, this paper objects to explore and show seismic damage background information, which includes the earthquake magnitude, earthquake intensity, and the damaged structure characteristics. From the research requirement in earthquake engineering field, the authors use the 2008 China Wenchuan M8.0 earthquake photographs, and provide four kinds of attribute indexes and classification, which are seismic information, structure types, earthquake damage parts and disaster causation factors. The final object is to set up an engineering structural seismic damage database based on these four attribute indicators and classification, and eventually build a website providing seismic damage photographs.

Keywords: attribute index, classification method, earthquake damage picture, engineering structure

Procedia PDF Downloads 759

Authors: Fariba Azizi, Firoozeh Haghighi, Viliam Makis

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In this paper, we propose a method to model the relationship between failure time and degradation for a simple step stress test where underlying degradation path is linear and different causes of failure are possible. It is assumed that the intensity function depends only on the degradation value. No assumptions are made about the distribution of the failure times. A simple step-stress test is used to shorten failure time of products and a tampered failure rate (TFR) model is proposed to describe the effect of the changing stress on the intensities. We assume that some of the products that fail during the test have a cause of failure that is only known to belong to a certain subset of all possible failures. This case is known as masking. In the presence of masking, the maximum likelihood estimates (MLEs) of the model parameters are obtained through an expectation-maximization (EM) algorithm by treating the causes of failure as missing values. The effect of incomplete information on the estimation of parameters is studied through a Monte-Carlo simulation. Finally, a real example is analyzed to illustrate the application of the proposed methods.

Keywords: cause of failure, linear degradation path, reliability function, expectation-maximization algorithm, intensity, masked data

Procedia PDF Downloads 327

Authors: Sajid Hussain

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The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

Procedia PDF Downloads 100

Authors: Vaidehi Iyer, Konstantin Borozdin

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Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

Procedia PDF Downloads 224

Authors: John Segars

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Built out of a real-world need to have better, more detailed, asset and infrastructure documentation, this project will lay out the case for using the database functionality of ArcGIS as a tool to track and maintain infrastructure location, status, maintenance and serviceability. Workflows and processes will be presented and detailed which may be applied to an organizations’ infrastructure needs that might allow them to make use of the robust tools which surround the ArcGIS platform. The end result is a value-added information system framework with a geographic component e.g., the spatial location of various I.T. assets, a detailed set of records which not only documents location but also captures the maintenance history for assets along with photographs and documentation of these various assets as attachments to the numerous feature class items. In addition to the asset location and documentation benefits, the staff will be able to log into the devices and pull SNMP (Simple Network Management Protocol) based query information from within the user interface. The entire collection of information may be displayed in ArcGIS, via a JavaScript based web application or via queries to the back-end database. The project is applicable to all organizations which maintain an IT infrastructure but specifically targets post-secondary educational institutions where access to ESRI resources is generally already available in house.

Keywords: ESRI, GIS, infrastructure, network documentation, PostgreSQL

Procedia PDF Downloads 177

Authors: J. A. Batsis, G. G. Boateng, L. M. Seo, C. L. Petersen, K. L. Fortuna, E. V. Wechsler, R. J. Peterson, S. B. Cook, D. Pidgeon, R. S. Dokko, R. J. Halter, D. F. Kotz

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Resistance exercise bands are a core component of any physical activity strengthening program. Strength training can mitigate the development of sarcopenia, the loss of muscle mass or strength and function with aging. Yet, the adherence of such behavioral exercise strategies in a home-based setting are fraught with issues of monitoring and compliance. Our group developed a Bluetooth-enabled resistance exercise band capable of transmitting data to an open-source platform. In this work, we developed an application to capture this information in real-time, and conducted three usability studies in two mixed-aged groups of participants (n=6 each) and a group of older adults with obesity participating in a weight-loss intervention (n=20). The system was favorable, acceptable and provided iterative information that could assist in future deployment on ubiquitous platforms. Our formative work provides the foundation to deliver home-based monitoring interventions in a high-risk, older adult population.

Keywords: application, mHealth, older adult, resistance exercise band, sarcopenia

Procedia PDF Downloads 170

Authors: Soo Min Kim, Soo-Won Chae, Soung-Yon Kim, Haea Lee, Ju Yong Kang, Juneyong Lee, Seung-Ho Han

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Reverse total shoulder arthroplasty (RTSA) has become an effective treatment option for cuff tear arthropathy and massive, irreparable rotator cuff tears and indications for its use are expanding. Numerous methods for optimal fixation of the glenoid component have been suggested, such as inferior overhang, inferior tilt, to maximize initial fixation and prevent glenoid component loosening. The inferior tilt fixation of a glenoid component has been suggested, which is expected to decrease scapular notching and to improve the stability of a glenoid component fixation in reverse total shoulder arthroplasty. Inferior tilt fixation of the glenoid component has been suggested, which can improve stability and, because it provides the most uniform compressive forces and imparts the least amount of tensile forces and micromotion, reduce the likelihood of mechanical failure. Another study reported that glenoid component inferior tilt improved impingement-free range of motion as well as minimized the scapular notching. Several authors have shown that inferior tilt of a glenoid component reduces scapular notching. However, controversy still exists regarding its importance in the literature. In this study the influence of inferior tilt fixation on the primary stability of a glenoid component has been investigated. Finite element models were constructed from cadaveric scapulae and glenoid components were implanted with neutral and 10° inferior tilts. Most previous biomechanical studies regarding the effect of glenoid component inferior tilt used a solid rigid polyurethane foam or sawbones block, not cadaveric scapulae, to evaluate the stability of the RTSA. Relative micromotions at the bone-glenoid component interface, and the distribution of bone stresses under the glenoid component and around the screws were analyzed and compared between neutral and 10° inferior tilt groups. Contact area between bone and screws and cut surface area of the cancellous bone exposed after reaming of the glenoid have also been investigated because of the fact that cancellous and cortical bone thickness vary depending on the resection level of the inferior glenoid bone. The greater relative micromotion of the bone-glenoid component interface occurred in the 10° inferior tilt group than in the neutral tilt group, especially at the inferior area of the bone-glenoid component interface. Bone stresses under the glenoid component and around the screws were also higher in the 10° inferior tilt group than in the neutral tilt group, especially at the inferior third of the glenoid bone surface under the glenoid component and inferior scapula. Thus inferior tilt fixation of the glenoid component may adversely affect the primary stability and longevity of the reverse total shoulder arthroplasty.

Keywords: finite element analysis, glenoid component, inferior tilt, reverse total shoulder arthroplasty

Procedia PDF Downloads 284

Authors: Mahmoud Abdelrazig Mahmoud Barakat

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Achievement tests administered at national level play a significant role in the lives of test-takers as well as the whole society. This paper aims to investigate the effect of giving students a choice between two optional questions on their overall performance in a high stake achievement test for university admission. It is hypothesized that questions targeting writing-based productive skills and language system necessitate display of abilities which are different from fact-based questions designed around story content. The two items are assumed to reflect different constructs that require different criteria of assessment. Consequently, the student’s overall score is affected by the item they choose to answer, which might not be reflective of their real language abilities. An open-ended interview was carried out with ten teachers working with grade 3 students in model secondary schools to investigate the nature of the two test items and their impact on the student’s performance. The data has proved that giving choice in an achievement test generates different performances that are assessed differently. It is recommended that in order to address the question of fairness, it is important to clearly define and balance the construct of the items that affect the student’s choice and performance.

Keywords: achievement test, assessment, choice, fairness performance

Procedia PDF Downloads 216

Authors: Muhammad Ali Syed, Arshad Saleem Bhatti, Chen-zhong Li, Habib Ali Bokhari

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Surface plasmon resonance (SPR) biosensors have emerged as a promising technique for bioanalysis as well as microbial detection and identification. Real time, sensitive, cost effective, and label free detection of biomolecules from complex samples is required for early and accurate diagnosis of infectious diseases. Like many other types of optical techniques, SPR biosensors may also be successfully utilized for microbial detection for accurate, point of care, and rapid results. In the present study, we have utilized a commercially available automated SPR biosensor of BI company to study the microbial detection form water samples spiked with different concentration of Staphylococcus aureus bacterial cells. The gold thin film sensor surface was functionalized to react with proteins such as protein G, which was used for directed immobilization of monoclonal antibodies against Staphylococcus aureus. The results of our work reveal that this immunosensor can be used to detect very small number of bacterial cells with higher sensitivity and specificity. In our case 10^3 cells/ml of water have been successfully detected. Therefore, it may be concluded that this technique has a strong potential to be used in microbial detection and identification.

Keywords: surface plasmon resonance (SPR), Staphylococcus aureus, biosensors, microbial detection

Procedia PDF Downloads 470

Authors: Romisaa Ali

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This paper presents a comparison between twin-delayed Deep Deterministic Policy Gradient (TD3) and Soft Actor-Critic (SAC) reinforcement learning algorithms in the context of training robust navigation policies for Jackal robots. By leveraging an open-source framework and custom motion control environments, the study evaluates the performance, robustness, and transferability of the trained policies across a range of scenarios. The primary focus of the experiments is to assess the training process, the adaptability of the algorithms, and the robot’s ability to navigate in previously unseen environments. Moreover, the paper examines the influence of varying environmental complexities on the learning process and the generalization capabilities of the resulting policies. The results of this study aim to inform and guide the development of more efficient and practical reinforcement learning-based navigation policies for Jackal robots in real-world scenarios.

Keywords: Jackal robot environments, reinforcement learning, TD3, SAC, robust navigation, transferability, custom environment

Procedia PDF Downloads 94

Authors: Paul Hernandez-Herrera, Fernando Montoya, Juan Manuel Rendon, Alberto Darszon, Gabriel Corkidi

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Intracellular calcium ([Ca2+]i) regulates sperm motility. The analysis of [Ca2+]i has been traditionally achieved in two dimensions while the real movement of the cell takes place in three spatial dimensions. Due to optical limitations (high speed cell movement and low light emission) important data concerning the three dimensional movement of these flagellated cells had been neglected. Visualizing [Ca2+]i in 3D is not a simple matter since it requires complex fluorescence microscopy techniques where the resulting images have very low intensity and consequently low SNR (Signal to Noise Ratio). In 4D sequences, this problem is magnified since the flagellum oscillates (for human sperm) at least at an average frequency of 15 Hz. In this paper, a novel approach to extract the flagellum’s center-line in 4D stacks is presented. For this purpose, an iterative algorithm based on the fast-marching method is proposed to extract the flagellum’s center-line. Quantitative and qualitative results are presented in a 4D stack to demonstrate the ability of the proposed algorithm to trace the flagellum’s center-line. The method reached a precision and recall of 0.96 as compared with a semi-manual method.

Keywords: flagellum, minimal path, segmentation, sperm

Procedia PDF Downloads 277

Authors: Anchana Sooksomchitra

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This study aims to explore and compare the current condition of community radio stations in Phutthamonthon district, Nakhon Pathom province, Thailand, as well as the challenges they are facing. Qualitative research tools including in-depth interviews; documentary analysis; focus group interviews; and observation, are used to examine the content, programming, and management structure of three community radio stations currently in operation within the district. Research findings indicate that the management and operational approaches adopted by the two non-profit stations included in the study, Salaya Pattana and Voice of Dhamma, are more structured and effective than that of the for-profit Tune Radio. Salaya Pattana – backed by the Faculty of Engineering, Mahidol University, and the charity-funded Voice of Dhamma, are comparatively free from political and commercial influence, and able to provide more relevant and consistent community-oriented content to meet the real demand of the audience. Tune Radio, on the other hand, has to rely solely on financial support from political factions and business groups, which heavily influence its content.

Keywords: radio broadcasting, programming, management, community radio, Thailand

Procedia PDF Downloads 396

Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

Procedia PDF Downloads 71

Authors: Gerson E. Cornejo, Luis A. Gamarra, David S. Mauricio

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The Enterprise Resource Planning Systems (ERP) allows the integration of all the business processes of the functional areas of the companies, in order to automate and standardize the processes, obtain accurate information and improve decision making in time real. In Peru, 79% of medium and small companies (SMEs) do not use any management software, this is because it is believed that ERPs are expensive, complex and difficult to implement. However, for more than 20 years there have been Open Source ERPs, which are more accessible and have the same benefit as proprietary ERPs, but there is little information on the implementation process. In this work is made a case of study, in order to show the implementation process of an Open Source ERP, Odoo, based on the ASAP methodology (Accelerated SAP) and applied to a company of corrective and preventive maintenance services of vehicles. The ERP allowed the SME to standardize its business processes, increase its productivity, reducing up to 40% certain processes. The study of this case shows that it is feasible and profitable to implement an Open Source ERP in SMEs in the Automotive Sector of Peru. In addition, it is shown that the ASAP methodology is adequate to carry out Open Source ERPs implementation projects.

Keywords: ASAP, automotive sector, ERP implementation, open source

Procedia PDF Downloads 330

Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev

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The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.

Keywords: distillation, machine learning, neural networks, quantization

Procedia PDF Downloads 318

Authors: Chiang-Ho Cheng, An-Shik Yang, Hon-Yi Cheng, Ming-Yu Lai

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This paper presents the design and fabrication of a novel piezoelectric actuator for a gas micropump with check valve having the advantages of miniature size, light weight and low power consumption. The micropump is designed to have eight major components, namely a stainless steel upper cover layer, a piezoelectric actuator, a stainless steel diaphragm, a PDMS chamber layer, two stainless steel channel layers with two valve seats, a PDMS check valve layer with two cantilever-type check valves and an acrylic substrate. A prototype of the gas micropump, with a size of 52 mm × 50 mm × 5.0 mm, is fabricated by precise manufacturing. This device is designed to pump gases with the capability of performing the self-priming and bubble-tolerant work mode by maximizing the stroke volume of the membrane as well as the compression ratio via minimization of the dead volume of the micropump chamber and channel. By experiment apparatus setup, we can get the real-time values of the flow rate of micropump and the displacement of the piezoelectric actuator, simultaneously. The gas micropump obtained higher output performance under the sinusoidal waveform of 250 Vpp. The micropump achieved the maximum pumping rates of 1185 ml/min and back pressure of 7.14 kPa at the corresponding frequency of 120 and 50 Hz.

Keywords: PDMS, check valve, micropump, piezoelectric

Procedia PDF Downloads 444

Authors: Martina Drdlová, Michal Frank, Radek Řídký, Jaroslav Buchar, Josef Krátký

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The main aim of the presented experiments is to improve behaviour of sandwich structures under dynamic loading, such as crash or explosion. This paper describes experimental investigation on the response of new advanced materials to low and high velocity load. Blast wave energy absorbers were designed using two types of porous lightweight raw particle materials based on expanded glass and ceramics with dimensions of 0.5-1 mm, combined with polymeric binder. The effect of binder amount on the static and dynamic properties of designed materials was observed. Prism shaped specimens were prepared and loaded to obtain physico-mechanical parameters – bulk density, compressive and flexural strength under quasistatic load, the dynamic response was determined using Split Hopkinson Pressure bar apparatus. Numerical investigation of the material behaviour in sandwich structure was performed using implicit/explicit solver LS-Dyna. As the last step, the developed material was used as the interlayer of blast resistant litter bin, and it´s functionality was verified by real field blast tests.

Keywords: blast energy absorber, SHPB, expanded glass, expanded ceramics

Procedia PDF Downloads 454

Authors: Edy Wahyu Susilo

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This research discusses a comparative analysis of various anti-corruption responses of three Indonesian City Governments (Jakarta, Surabaya, and Medan) and completes previous findings on the effectiveness of the city anti-corruption program. Some factors (transparency, accountability, leadership, law enforcement, and bureaucratic reform) have been chosen in this study to diagnose the main role in the success and the failure of anti-corruption programs in these cities. These factors diagnose the relationship between factors and their dominancy, which is then utilized to create the city’s strategic anti-corruption programs. Although this study found leadership had a dominant influence both in encouraging and discouraging the performance of city transformation drastically, however, it is not the only factor that determined the performance of the city in the fight against corruption. It needs other factors as an ideal balancing element to achieve an anti-corruption program, namely KPK’s intervention and public engagement. Based on the dominance factors found, this research then develops an appropriate strategy using a policy evaluation approach to create a real practical guide regardless of the existence of good or bad leadership in the city. This research is expected to be a useful reference for stakeholders, especially the government, as a blueprint to prevent corruption by considering several important steps and guidance in efforts to eradicate corruption in the city, especially in Indonesia.

Keywords: intervention, KPK (corruption eradication commission), law enforcements, leadership, policy evaluation

Procedia PDF Downloads 94

Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski

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Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.

Keywords: bootstrap, edgeworth approximation, IID, quantile

Procedia PDF Downloads 155

Authors: Bachir Chemani, Rachid Halfaoui

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The aim of study was to evaluate pressure distribution characteristics of the elastic textile bandages using two instrumental techniques: a prototype Instrument and a load Transference. The prototype instrument which simulates shape of real leg has pressure sensors which measure bandage pressure. Using this instrument, the results show that elastic textile bandages presents different pressure distribution characteristics and none produces a uniform distribution around lower limb. The load transference test procedure is used to determine whether a relationship exists between elastic textile bandage structure and pressure distribution characteristics. The test procedure assesses degree of load, directly transferred through a textile when loads series are applied to bandaging surface. A range of weave fabrics was produced using needle weaving machine and a sewing technique. A textile bandage was developed with optimal characteristics far superior pressure distribution than other bandages. From results, we find that theoretical pressure is not consistent exactly with practical pressure. It is important in this study to make a practical application for specialized nurses in order to verify the results and draw useful conclusions for predicting the use of this type of elastic band.

Keywords: textile, cotton, pressure, venous ulcers, elastic

Procedia PDF Downloads 355

Authors: Yi-Ping Lo, Shi-Yao Wei, Chih-Chun Ma

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Since Google launched Google Glass in 2012, numbers of commercial wearable devices were released, such as smart belt, smart band, smart shoes, smart clothes ... etc. However, most of these devices perform as sensors to show the readings of measurements and few of them provide the interactive feedback to the user. Furthermore, these devices are single task devices which are not able to communicate with each other. In this paper a new health promotion system, Ubiquitous Life People Informatics Engine (U-Life PIE), will be presented. This engine consists of People Informatics Engine (PIE) and the interactive user interface. PIE collects all the data from the compatible devices, analyzes this data comprehensively and communicates between devices via various application programming interfaces. All the data and informations are stored on the PIE unit, therefore, the user is able to view the instant and historical data on their mobile devices any time. It also provides the real-time hands-free feedback and instructions through the user interface visually, acoustically and tactilely. These feedback and instructions suggest the user to adjust their posture or habits in order to avoid the physical injuries and prevent illness.

Keywords: machine learning, wearable devices, user interface, user experience, internet of things

Procedia PDF Downloads 282

Authors: Ragini Verma, J. Ponmozhi

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The oral cavity is home to a wide variety of microorganisms that lead to various diseases and even oral cancer. Despite advancements in the diagnosis and detection at the initial phase, the situation hasn’t improved much. Saliva-on-a-chip is an innovative point-of-care platform for early diagnosis of oral cancer and other oral diseases in live and dead cells using a microfluidic device with a current perspective. Some of the major challenges, like real-time imaging of the oral cancer microbes, high throughput values, obtaining a high spatiotemporal resolution, etc. were faced by the scientific community. Integrated microfluidics and microscopy provide powerful approaches to studying the dynamics of oral pathology, microbe interaction, and the oral microenvironment. Here we have developed a saliva-on-chip (salivary microbes) device to monitor the effect on oral cancer. Adhesion of cancer-causing F. nucleatum; subsp. Nucleatum and Prevotella intermedia in the device was observed. We also observed a significant reduction in the oral cancer growth rate when mortality and morbidity were induced. These results show that this approach has the potential to transform the oral cancer and early diagnosis study.

Keywords: microfluidic device, oral cancer microbes, early diagnosis, saliva-on-chip

Procedia PDF Downloads 93

Authors: Behrooz Khalilloo, Hamid Shahriari, Emad Roghanian

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Process capability indices (PCIs) are important concepts of statistical quality control and measure the capability of processes and how much processes are meeting certain specifications. An important issue in statistical quality control is parameter estimation. Under the assumption of multivariate normality, the distribution parameters, mean vector and variance-covariance matrix must be estimated, when they are unknown. Classic estimation methods like method of moment estimation (MME) or maximum likelihood estimation (MLE) makes good estimation of the population parameters when data are not contaminated. But when outliers exist in the data, MME and MLE make weak estimators of the population parameters. So we need some estimators which have good estimation in the presence of outliers. In this work robust M-estimators for estimating these parameters are used and based on robust parameter estimators, robust process capability indices are introduced. The performances of these robust estimators in the presence of outliers and their effects on process capability indices are evaluated by real and simulated multivariate data. The results indicate that the proposed robust capability indices perform much better than the existing process capability indices.

Keywords: multivariate process capability indices, robust M-estimator, outlier, multivariate quality control, statistical quality control

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Authors: D. Subedi, S. Pradhan

Abstract:

Current transformers are an integral part of power system because it provides a proportional safe amount of current for protection and measurement applications. However when the power system experiences an abnormal situation leading to huge current flow, then this huge current is proportionally injected to the protection and metering circuit. Since the protection and metering equipment’s are designed to withstand only certain amount of current with respect to time, these high currents pose a risk to man and equipment. Therefore during such instances, the CT saturation characteristics have a huge influence on the safety of both man and equipment and also on the reliability of the protection and metering system. This paper shows the effect of burden on the Accuracy Limiting factor/ Instrument security factor of current transformers and also the change in saturation characteristics of the CT’s. The response of the CT to varying levels of overcurrent at different connected burden will be captured using the data acquisition software LabVIEW. Analysis is done on the real time data gathered using LabVIEW. Variation of current transformer saturation characteristics with changes in burden will be discussed.

Keywords: accuracy limiting factor, burden, current transformer, instrument security factor, saturation characteristics

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Authors: Mohammed Hasan Salahat, Stave Wade

Abstract:

This paper presents an application of a “Systematic Soft Domain Driven Design Framework” as a soft systems approach to domain-driven design of information systems development. The framework combining techniques from Soft Systems Methodology (SSM), the Unified Modeling Language (UML), and an implementation pattern knows as ‘Naked Objects’. This framework have been used in action research projects that have involved the investigation and modeling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, and a real case study ‘Information Retrieval System for Academic Research’ is used, in this paper, to show further practice and evaluation of the framework in different business domain. We argue that there are advantages from combining and using techniques from different methodologies in this way for business domain modeling. The framework is overviewed and justified as multi-methodology using Mingers Multi-Methodology ideas.

Keywords: SSM, UML, domain-driven design, soft domain-driven design, naked objects, soft language, information retrieval, multimethodology

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Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: deep-learning, image classification, image identification, industrial engineering.

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Authors: Wenxiao Liu, Kun Zhang, Yongqing Li

Abstract:

Bovine herpesvirus 1, a member of the genus Variellovirus of the subfamily Alphaherpesvirinae, has caused severe economic cost to the bovine industry. In this study, BoHV-1 glycerol protein gD was expressed in insect cells, and the purified gD was immunized in the Balb/C mice to generate monoclonal antibodies. Based on hybridoma cell fusion techniques, 20 monoclonal antibodies against Bovine herpesvirus 1 have been obtained. Further, mAb 3F8 with neutralizing activity and gD were applied to develop a blocking enzyme-linked immunosorbent assay (Elisa) for detecting neutralizing antibodies against BoHV-1, which shows a significant correlation between the blocking Elisa and VNT. The sensitivity and specificity of the test were estimated to be 94.59% and 93.42%, respectively. Furthermore, antibody pairing tests revealed that mAb 1B6 conjugated to fluorescence microspheres was used as the capture antibody, and mAb 3F9 was used as the detectable antibody to establish the immunochromatographic assay (ICS). The ICS was conducted to detect BoHV-1 in bovine samples with high sensitivity, specificity, and good stability. Clinical sample testing revealed that the results of ICS and real-time PCR have a coincidence rate of 95.42%. Our research confirmed that the ICS is a rapid and reliable method for the diagnosis of BoHV-1. In conclusion, our results lay a solid foundation for the prevention and control of BoHV-1 infection.

Keywords: bovine disease, BoHV-1, ELISA, ICS assay

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Authors: Jahedul Islam Chowdhury, Bao Kha Nguyen, David Thornhill, Roy Douglas, Stephen Glover

Abstract:

Organic Rankine Cycle (ORC) is the most commonly used method for recovering energy from small sources of heat. The investigation of the ORC in supercritical condition is a new research area as it has a potential to generate high power and thermal efficiency in a waste heat recovery system. This paper presents a steady state ORC model in supercritical condition and its simulations with a real engine’s exhaust data. The key component of ORC, evaporator, is modelled using finite volume method, modelling of all other components of the waste heat recovery system such as pump, expander and condenser are also presented. The aim of this paper is to investigate the effects of mass flow rate and evaporator outlet temperature on the efficiency of the waste heat recovery process. Additionally, the necessity of maintaining an optimum evaporator outlet temperature is also investigated. Simulation results show that modification of mass flow rate is the key to changing the operating temperature at the evaporator outlet.

Keywords: Organic Rankine cycle, supercritical condition, steady state model, waste heat recovery

Procedia PDF Downloads 401