Search results for: unit root
2053 Estimation of Population Mean under Random Non-Response in Two-Occasion Successive Sampling
Authors: M. Khalid, G. N. Singh
Abstract:
In this paper, we have considered the problems of estimation for the population mean on current (second) occasion in two-occasion successive sampling under random non-response situations. Some modified exponential type estimators have been proposed and their properties are studied under the assumptions that the number of sampling unit follows a discrete distribution due to random non-response situations. The performances of the proposed estimators are compared with linear combinations of two estimators, (a) sample mean estimator for fresh sample and (b) ratio estimator for matched sample under the complete response situations. Results are demonstrated through empirical studies which present the effectiveness of the proposed estimators. Suitable recommendations have been made to the survey practitioners.Keywords: modified exponential estimator, successive sampling, random non-response, auxiliary variable, bias, mean square error
Procedia PDF Downloads 3492052 Generalized Extreme Value Regression with Binary Dependent Variable: An Application for Predicting Meteorological Drought Probabilities
Authors: Retius Chifurira
Abstract:
Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe.Keywords: generalized extreme value distribution, general linear model, mean annual rainfall, meteorological drought probabilities
Procedia PDF Downloads 2002051 A Study on Characteristics of Runoff Analysis Methods at the Time of Rainfall in Rural Area, Okinawa Prefecture Part 2: A Case of Kohatu River in South Central Part of Okinawa Pref
Authors: Kazuki Kohama, Hiroko Ono
Abstract:
The rainfall in Japan is gradually increasing every year according to Japan Meteorological Agency and Intergovernmental Panel on Climate Change Fifth Assessment Report. It means that the rainfall difference between rainy season and non-rainfall is increasing. In addition, the increasing trend of strong rain for a short time clearly appears. In recent years, natural disasters have caused enormous human injuries in various parts of Japan. Regarding water disaster, local heavy rain and floods of large rivers occur frequently, and it was decided on a policy to promote hard and soft sides as emergency disaster prevention measures with water disaster prevention awareness social reconstruction vision. Okinawa prefecture in subtropical region has torrential rain and water disaster several times a year such as river flood, in which is caused in specific rivers from all 97 rivers. Also, the shortage of capacity and narrow width are characteristic of river in Okinawa and easily cause river flood in heavy rain. This study focuses on Kohatu River that is one of the specific rivers. In fact, the water level greatly rises over the river levee almost once a year but non-damage of buildings around. On the other hand in some case, the water level reaches to ground floor height of house and has happed nine times until today. The purpose of this research is to figure out relationship between precipitation, surface outflow and total treatment water quantity of Kohatu River. For the purpose, we perform hydrological analysis although is complicated and needs specific details or data so that, the method is mainly using Geographic Information System software and outflow analysis system. At first, we extract watershed and then divided to 23 catchment areas to understand how much surface outflow flows to runoff point in each 10 minutes. On second, we create Unit Hydrograph indicating the area of surface outflow with flow area and time. This index shows the maximum amount of surface outflow at 2400 to 3000 seconds. Lastly, we compare an estimated value from Unit Hydrograph to a measured value. However, we found that measure value is usually lower than measured value because of evaporation and transpiration. In this study, hydrograph analysis was performed using GIS software and outflow analysis system. Based on these, we could clarify the flood time and amount of surface outflow.Keywords: disaster prevention, water disaster, river flood, GIS software
Procedia PDF Downloads 1372050 Feature Extractions of EMG Signals during a Constant Workload Pedaling Exercise
Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang
Abstract:
Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.Keywords: electromyographic feature extraction, muscle status, pedaling exercise, relaxation segment
Procedia PDF Downloads 3032049 Applying Genetic Algorithm in Exchange Rate Models Determination
Authors: Mehdi Rostamzadeh
Abstract:
Genetic Algorithms (GAs) are an adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this study, we apply GAs for fundamental and technical models of exchange rate determination in exchange rate market. In this framework, we estimated absolute and relative purchasing power parity, Mundell-Fleming, sticky and flexible prices (monetary models), equilibrium exchange rate and portfolio balance model as fundamental models and Auto Regressive (AR), Moving Average (MA), Auto-Regressive with Moving Average (ARMA) and Mean Reversion (MR) as technical models for Iranian Rial against European Union’s Euro using monthly data from January 1992 to December 2014. Then, we put these models into the genetic algorithm system for measuring their optimal weight for each model. These optimal weights have been measured according to four criteria i.e. R-Squared (R2), mean square error (MSE), mean absolute percentage error (MAPE) and root mean square error (RMSE).Based on obtained Results, it seems that for explaining of Iranian Rial against EU Euro exchange rate behavior, fundamental models are better than technical models.Keywords: exchange rate, genetic algorithm, fundamental models, technical models
Procedia PDF Downloads 2732048 Purification and Characterization of Phycoerythrin from a Mesophilic Cyanobacterium Nostoc piscinale PUPCCC 405.17
Authors: Sandeep Kaur
Abstract:
Phycoerythrin (PE) from the mesophilic filamentous cyanobacterium Nostoc piscinale PUPCCC 405.17, a good producer of phycobiliproteins, has been characterized in terms of their unit assembly and stability. The phycoerythrin was extracted by freeze-thawing the cells in water, concentrated by ammonium sulphate fractionation and purified by anion exchange chromatography. The purification process resulted in 2.90 fold increase in phycoerythrin purity reaching to 1.54. Sodium Dodecyl Sulphate- Polyacrylamide Gel Electrophoresis of purified PE demonstrated three protein bands of 14.3, 27.54 and 39.81 kDa. The native PE also showed one band of 125.87 kDa, assumed to be a dimer (αβ)2γ based on results of non-denaturing PAGE. Lyophilized powder PE was more stable compared to phycoerythrin in the solution. The half-life of dry PE is 80 days when stored at 4 °C under dark. The phycoerythrin from this organism has potential applications in food as natural colour and as a fluorescent marker.Keywords: characterization, Nostoc piscinale, phycoerythrin, purification
Procedia PDF Downloads 1402047 Robust Adaptation to Background Noise in Multichannel C-OTDR Monitoring Systems
Authors: Andrey V. Timofeev, Viktor M. Denisov
Abstract:
A robust sequential nonparametric method is proposed for adaptation to background noise parameters for real-time. The distribution of background noise was modelled like to Huber contamination mixture. The method is designed to operate as an adaptation-unit, which is included inside a detection subsystem of an integrated multichannel monitoring system. The proposed method guarantees the given size of a nonasymptotic confidence set for noise parameters. Properties of the suggested method are rigorously proved. The proposed algorithm has been successfully tested in real conditions of a functioning C-OTDR monitoring system, which was designed to monitor railways.Keywords: guaranteed estimation, multichannel monitoring systems, non-asymptotic confidence set, contamination mixture
Procedia PDF Downloads 4302046 An Effective Route to Control of the Safety of Accessing and Storing Data in the Cloud-Based Data Base
Authors: Omid Khodabakhshi, Amir Rozdel
Abstract:
The subject of cloud computing security research has allocated a number of challenges and competitions because the data center is comprised of complex private information and are always faced various risks of information disclosure by hacker attacks or internal enemies. Accordingly, the security of virtual machines in the cloud computing infrastructure layer is very important. So far, there are many software solutions to develop security in virtual machines. But using software alone is not enough to solve security problems. The purpose of this article is to examine the challenges and security requirements for accessing and storing data in an insecure cloud environment. In other words, in this article, a structure is proposed for the implementation of highly isolated security-sensitive codes using secure computing hardware in virtual environments. It also allows remote code validation with inputs and outputs. We provide these security features even in situations where the BIOS, the operating system, and even the super-supervisor are infected. To achieve these goals, we will use the hardware support provided by the new Intel and AMD processors, as well as the TPM security chip. In conclusion, the use of these technologies ultimately creates a root of dynamic trust and reduces TCB to security-sensitive codes.Keywords: code, cloud computing, security, virtual machines
Procedia PDF Downloads 1912045 Optimal Number of Reconfigurable Robots in a Transport System
Authors: Mari Chaikovskaia, Jean-Philippe Gayon, Alain Quilliot
Abstract:
We consider a fleet of elementary robots that can be connected in different ways to transport loads of different types. For instance, a single robot can transport a small load, and the association of two robots can either transport a large load or two small loads. We seek to determine the optimal number of robots to transport a set of loads in a given time interval, with or without reconfiguration. We show that the problem with reconfiguration is strongly NP-hard by a reduction to the bin-packing problem. Then, we study a special case with unit capacities and derive simple formulas for the minimum number of robots, up to 3 types of loads. For this special case, we compare the minimum number of robots with or without reconfiguration and show that the gain is limited in absolute value but may be significant for small fleets.Keywords: fleet sizing, reconfigurability, robots, transportation
Procedia PDF Downloads 862044 Experimental Observation on Air-Conditioning Using Radiant Chilled Ceiling in Hot Humid Climate
Authors: Ashmin Aryal, Pipat Chaiwiwatworakul, Surapong Chirarattananon
Abstract:
Radiant chilled ceiling (RCC) has been perceived to save more energy and provide better thermal comfort than the traditional air conditioning system. However, its application has been rather limited by some reasons e.g., the scarce information about the thermal characteristic in the radiant room and the local climate influence on the system performance, etc. To bridge such gap, an office-like experiment room with a RCC was constructed in the hot and humid climate of Thailand. This paper presents exemplarily results from the RCC experiments to give an insight into the thermal environment in a radiant room and the cooling load associated to maintain the room's comfort condition. It gave a demonstration of the RCC system operation for its application to achieve thermal comfort in offices in a hot humid climate, as well.Keywords: radiant chilled ceiling, thermal comfort, cooling load, outdoor air unit
Procedia PDF Downloads 1282043 'Spare the Rod and Spoil the Child': The Criminal Career of an Armed Robber
Authors: Mahlogonolo Stephina Thobane
Abstract:
The aim of the study upon which this article is based was “to evaluate the possibility of using criminal career research in the development and evaluation of crime control strategies, particularly for armed robberies.” The research employed a concurrent triangulation mixed-method approach where quantitative and qualitative data were collected concurrently but analysed separately through the use of SPSS and Atlas.ti respectively. Forty offenders incarcerated at six correctional centres around the Gauteng province of South Africa for robbery with aggravating circumstances were interviewed as research participants. Since the researcher had no prior information on the total number of the population, purposive sampling (i.e. snowballing) was executed to draw the sample. This research found that offenders launched their criminal career at a very young age of, 11 years, by committing petty crimes such as theft and then, as they grew older, they progressed to more serious and violent crimes such as vehicle hijacking and Cash-in-Transit (CIT) robberies. Thus, it is pivotal that those responsible for developing crime prevention policies focus on interrupting the root causes of crime in the early stages of one’s life in order to prevent continuation of delinquent behaviour from childhood to adolescence and adulthood.Keywords: criminal career, robbery with aggravating circumstances, cash-in-transit robbery, criminal career research
Procedia PDF Downloads 4442042 Breast Cancer Metastasis Detection and Localization through Transfer-Learning Convolutional Neural Network Classification Based on Convolutional Denoising Autoencoder Stack
Authors: Varun Agarwal
Abstract:
Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images
Procedia PDF Downloads 1302041 The Leaching Kinetics of Zinc from Industrial Zinc Slag Waste
Authors: Hilary Rutto
Abstract:
The investigation was aimed at determining the extent at which the zinc will be extracted from secondary sources generated from galvanising process using dilute sulphuric acid under controlled laboratory conditions of temperature, solid-liquid ratio, and agitation rate. The leaching experiment was conducted for a period of 2 hours and to total zinc extracted calculated in relation to the amount of zinc dissolved at a unit time in comparison to the initial zinc content of the zinc ash. Sulphuric acid was found to be an effective leaching agent with an overall extraction of 91.1% when concentration is at 2M, and solid/liquid ratio kept at 1g/200mL leaching solution and temperature set at 65ᵒC while slurry agitation is at 450rpm. The leaching mechanism of zinc ash with sulphuric acid was conformed well to the shrinking core model.Keywords: leaching, kinetics, shrinking core model, zinc slag
Procedia PDF Downloads 1552040 Target and Equalizer Design for Perpendicular Heat-Assisted Magnetic Recording
Authors: P. Tueku, P. Supnithi, R. Wongsathan
Abstract:
Heat-Assisted Magnetic Recording (HAMR) is one of the leading technologies identified to enable areal density beyond 1 Tb/in2 of magnetic recording systems. A key challenge to HAMR designing is accuracy of positioning, timing of the firing laser, power of the laser, thermo-magnetic head, head-disk interface and cooling system. We study the effect of HAMR parameters on transition center and transition width. The HAMR is model using Thermal Williams-Comstock (TWC) and microtrack model. The target and equalizer are designed by the minimum mean square error (MMSE). The result shows that the unit energy constraint outperforms other constraints.Keywords: heat-assisted magnetic recording, thermal Williams-Comstock equation, microtrack model, equalizer
Procedia PDF Downloads 3522039 Multilayer System of Thermosetting Polymers and Specific Confining, Application to the Walls of the Hospital Unit
Authors: M. Bouzid, A. Djadi, C. Aribi, A. Irekti, B. Bezzazi, F. Halouene
Abstract:
The nature of materials structuring our health institutions promote the development of germs. The sustainability of nosocomial infections remains significant (12% and 15%). One of the major factors is the portland cement which is brittle and porous. As part of a national plan to fight nosocomial infections, led by the University Hospital of Blida, we opted for a composite coating, application by multilayer model, composed of epoxy-polyester resin as a binder and calcium carbonate as mineral fillers. The application of composite materials reinforce the wall coating of hospital units and eliminates the hospital infectious areas. The resistance to impact, chemicals, raising temperature and to a biologically active environment gives satisfactory results.Keywords: nosocomial infection, microbial load, composite materials, portland cement
Procedia PDF Downloads 3892038 Analysis of Reinforced Granular Pile in Soft Soil
Authors: G. Nitesh
Abstract:
Stone column or granular pile is a proven technique to mitigate settlement in soft soil. Granular pile increases both rate of consolidation and stiffness of the ground. In this paper, a method to analyze further reduction in settlement of granular column reinforced with lime pile is presented treating the system as a unit cell and considering one-dimensional compression approach. The core of the granular pile is stiffened with a steel rod or lime column. Influence of a wide range of parameters such as area ratio of granular pile-soft soil, area ratio of lime pile-granular pile, modular ratio of granular pile and modular ratio of lime pile with respect to granular pile on settlement reduction factor, etc. are obtained and presented.Keywords: lime pile, granular pile, soft soil, settlement
Procedia PDF Downloads 4102037 Turbulent Boundary Layer over 3D Sinusoidal Roughness
Authors: Misarah Abdelaziz, L Djenidi, Mergen H. Ghayesh, Rey Chin
Abstract:
Measurements of a turbulent boundary layer over 3D sinusoidal roughness are performed for friction Reynolds numbers ranging from 650 < Reτ < 2700. This surface was fabricated by a Multicam CNC Router machine of an acrylic sheet to have an amplitude of k/2 = 0.8 mm and an equal wavelength of 8k in both streamwise and spanwise directions, a 0.6 mm stepover and 12 mm ball nose cutter was used. Single hotwire anemometry measurements are done at one location x=1.5 m downstream at different freestream velocities under zero-pressure gradient conditions. As expected, the roughness causes a downward shift on the wall-unit normalised streamwise mean velocity profile when compared to the smooth wall profile. The shift is increasing with increasing Reτ, 1.8 < ∆U+ < 6.2. The coefficient of friction is almost constant at all cases Cf = 0.0042 ± 0.0002. The results show a gradual reduction in the inner peak of profiles with increasing Reτ until fully destruction at Reτ of 2700.Keywords: hotwire, roughness, TBL, ZPG
Procedia PDF Downloads 2222036 Heterogeneous Artifacts Construction for Software Evolution Control
Authors: Mounir Zekkaoui, Abdelhadi Fennan
Abstract:
The software evolution control requires a deep understanding of the changes and their impact on different system heterogeneous artifacts. And an understanding of descriptive knowledge of the developed software artifacts is a prerequisite condition for the success of the evolutionary process. The implementation of an evolutionary process is to make changes more or less important to many heterogeneous software artifacts such as source code, analysis and design models, unit testing, XML deployment descriptors, user guides, and others. These changes can be a source of degradation in functional, qualitative or behavioral terms of modified software. Hence the need for a unified approach for extraction and representation of different heterogeneous artifacts in order to ensure a unified and detailed description of heterogeneous software artifacts, exploitable by several software tools and allowing to responsible for the evolution of carry out the reasoning change concerned.Keywords: heterogeneous software artifacts, software evolution control, unified approach, meta model, software architecture
Procedia PDF Downloads 4462035 Optimization of Assay Parameters of L-Glutaminase from Bacillus cereus MTCC1305 Using Artificial Neural Network
Authors: P. Singh, R. M. Banik
Abstract:
Artificial neural network (ANN) was employed to optimize assay parameters viz., time, temperature, pH of reaction mixture, enzyme volume and substrate concentration of L-glutaminase from Bacillus cereus MTCC 1305. ANN model showed high value of coefficient of determination (0.9999), low value of root mean square error (0.6697) and low value of absolute average deviation. A multilayer perceptron neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model and its topology was obtained as 5-3-1 after applying Levenberg Marquardt (LM) training algorithm. The predicted activity of L-glutaminase was obtained as 633.7349 U/l by considering optimum assay parameters, viz., pH of reaction mixture (7.5), reaction time (20 minutes), incubation temperature (35˚C), substrate concentration (40mM), and enzyme volume (0.5ml). The predicted data was verified by running experiment at simulated optimum assay condition and activity was obtained as 634.00 U/l. The application of ANN model for optimization of assay conditions improved the activity of L-glutaminase by 1.499 fold.Keywords: Bacillus cereus, L-glutaminase, assay parameters, artificial neural network
Procedia PDF Downloads 4292034 Investigation of Extreme Gradient Boosting Model Prediction of Soil Strain-Shear Modulus
Authors: Ehsan Mehryaar, Reza Bushehri
Abstract:
One of the principal parameters defining the clay soil dynamic response is the strain-shear modulus relation. Predicting the strain and, subsequently, shear modulus reduction of the soil is essential for performance analysis of structures exposed to earthquake and dynamic loadings. Many soil properties affect soil’s dynamic behavior. In order to capture those effects, in this study, a database containing 1193 data points consists of maximum shear modulus, strain, moisture content, initial void ratio, plastic limit, liquid limit, initial confining pressure resulting from dynamic laboratory testing of 21 clays is collected for predicting the shear modulus vs. strain curve of soil. A model based on an extreme gradient boosting technique is proposed. A tree-structured parzan estimator hyper-parameter tuning algorithm is utilized simultaneously to find the best hyper-parameters for the model. The performance of the model is compared to the existing empirical equations using the coefficient of correlation and root mean square error.Keywords: XGBoost, hyper-parameter tuning, soil shear modulus, dynamic response
Procedia PDF Downloads 2012033 Case Study of Ground Improvement Solution for a Power Plant
Authors: Eleonora Di Mario
Abstract:
This paper describes the application of ground improvement to replace a typical piled foundation scheme in a power plant in Singapore. Several buildings within the plant were founded on vibro-compacted sand, including a turbine unit which had extremely stringent requirements on the allowable settlement. The achieved savings in terms of cost and schedule are presented. The monitoring data collected during the operation of the turbine are compared to the design predictions to validate the design approach, and the quality of the ground improvement works. In addition, the calculated carbon footprint of the ground improvement works are compared to the piled solution, showing that the vibro-compaction has a significantly lower carbon footprint.Keywords: ground improvement, vibro-compaction, case study, sustainability, carbon footprint
Procedia PDF Downloads 1092032 Evaluation Method for Fouling Risk Using Quartz Crystal Microbalance
Authors: Natsuki Kishizawa, Keiko Nakano, Hussam Organji, Amer Shaiban, Mohammad Albeirutty
Abstract:
One of the most important tasks in operating desalination plants using a reverse osmosis (RO) method is preventing RO membrane fouling caused by foulants found in seawater. Optimal design of the pre-treatment process of RO process for plants enables the reduction of foulants. Therefore, a quantitative evaluation of the fouling risk in pre-treated water, which is fed to RO, is required for optimal design. Some measurement methods for water quality such as silt density index (SDI) and total organic carbon (TOC) have been conservatively applied for evaluations. However, these methods have not been effective in some situations for evaluating the fouling risk of RO feed water. Furthermore, stable management of plants will be possible by alerts and appropriate control of the pre-treatment process by using the method if it can be applied to the inline monitoring system for the fouling risk of RO feed water. The purpose of this study is to develop a method to evaluate the fouling risk of RO feed water. We applied a quartz crystal microbalance (QCM) to measure the amount of foulants found in seawater using a sensor whose surface is coated with polyamide thin film, which is the main material of a RO membrane. The increase of the weight of the sensor after a certain length of time in which the sample water passes indicates the fouling risk of the sample directly. We classified the values as “FP: Fouling Potential”. The characteristics of the method are to measure the very small amount of substances in seawater in a short time: < 2h, and from a small volume of the sample water: < 50mL. Using some RO cell filtration units, a higher correlation between the pressure increase given by RO fouling and the FP from the method than SDI and TOC was confirmed in the laboratory-scale test. Then, to establish the correlation in the actual bench-scale RO membrane module, and to confirm the feasibility of the monitoring system as a control tool for the pre-treatment process, we have started a long-term test at an experimental desalination site by the Red Sea in Jeddah, Kingdom of Saudi Arabia. Implementing inline equipment for the method made it possible to measure FP intermittently (4 times per day) and automatically. Moreover, for two 3-month long operations, the RO operation pressure among feed water samples of different qualities was compared. The pressure increase through a RO membrane module was observed at a high FP RO unit in which feed water was treated by a cartridge filter only. On the other hand, the pressure increase was not observed at a low FP RO unit in which feed water was treated by an ultra-filter during the operation. Therefore, the correlation in an actual scale RO membrane was established in two runs of two types of feed water. The result suggested that the FP method enables the evaluation of the fouling risk of RO feed water.Keywords: fouling, monitoring, QCM, water quality
Procedia PDF Downloads 2122031 A Molding Surface Auto-inspection System
Authors: Ssu-Han Chen, Der-Baau Perng
Abstract:
Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded, defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.Keywords: molding surface, machine vision, statistical texture, discrete Fourier transformation
Procedia PDF Downloads 4312030 Exploring the Spatial Characteristics of Mortality Map: A Statistical Area Perspective
Authors: Jung-Hong Hong, Jing-Cen Yang, Cai-Yu Ou
Abstract:
The analysis of geographic inequality heavily relies on the use of location-enabled statistical data and quantitative measures to present the spatial patterns of the selected phenomena and analyze their differences. To protect the privacy of individual instance and link to administrative units, point-based datasets are spatially aggregated to area-based statistical datasets, where only the overall status for the selected levels of spatial units is used for decision making. The partition of the spatial units thus has dominant influence on the outcomes of the analyzed results, well known as the Modifiable Areal Unit Problem (MAUP). A new spatial reference framework, the Taiwan Geographical Statistical Classification (TGSC), was recently introduced in Taiwan based on the spatial partition principles of homogeneous consideration of the number of population and households. Comparing to the outcomes of the traditional township units, TGSC provides additional levels of spatial units with finer granularity for presenting spatial phenomena and enables domain experts to select appropriate dissemination level for publishing statistical data. This paper compares the results of respectively using TGSC and township unit on the mortality data and examines the spatial characteristics of their outcomes. For the mortality data between the period of January 1st, 2008 and December 31st, 2010 of the Taitung County, the all-cause age-standardized death rate (ASDR) ranges from 571 to 1757 per 100,000 persons, whereas the 2nd dissemination area (TGSC) shows greater variation, ranged from 0 to 2222 per 100,000. The finer granularity of spatial units of TGSC clearly provides better outcomes for identifying and evaluating the geographic inequality and can be further analyzed with the statistical measures from other perspectives (e.g., population, area, environment.). The management and analysis of the statistical data referring to the TGSC in this research is strongly supported by the use of Geographic Information System (GIS) technology. An integrated workflow that consists of the tasks of the processing of death certificates, the geocoding of street address, the quality assurance of geocoded results, the automatic calculation of statistic measures, the standardized encoding of measures and the geo-visualization of statistical outcomes is developed. This paper also introduces a set of auxiliary measures from a geographic distribution perspective to further examine the hidden spatial characteristics of mortality data and justify the analyzed results. With the common statistical area framework like TGSC, the preliminary results demonstrate promising potential for developing a web-based statistical service that can effectively access domain statistical data and present the analyzed outcomes in meaningful ways to avoid wrong decision making.Keywords: mortality map, spatial patterns, statistical area, variation
Procedia PDF Downloads 2582029 Addressing the Issue of Out-of-School Children in Nigeria: Challenges and Policy Recommendations
Authors: Nasir Haruna Soba
Abstract:
In addition to sustaining poverty and inequality, the issue of out-of-school children impedes efforts to accomplish the sustainable development goals (SDGs), especially Goal 4, which is to guarantee inclusive, egalitarian, and high-quality education for everyone. However, a number of social, cultural, and infrastructure barriers mean that millions of children in Nigeria are denied this privilege. This paper presents the findings of a case study conducted in Nigeria. The findings of this study revealed that out of school children in Nigeria are the most common causes of poverty; inadequate school facilities, long distances to schools, and poor road networks make it difficult for children, especially in rural areas, to access education. Social Disparities: Social inequality is sustained by differences in education, especially when it comes to financing, governance, and coordination amongst stakeholders. These differences are especially pronounced along gender and socioeconomic lines. The study recommended that policymakers and stakeholders should consider addressing the root causes, enhancing existing interventions, and implementing targeted policy measures. Nigeria can make significant strides towards ensuring inclusive and quality education for all children, thereby fostering sustainable development and reducing poverty.Keywords: poverty, inequality, funding, education, development
Procedia PDF Downloads 312028 A Photovoltaic Micro-Storage System for Residential Applications
Authors: Alia Al Nuaimi, Ayesha Al Aberi, Faiza Al Marzouqi, Shaikha Salem Ali Al Yahyaee, Ala Hussein
Abstract:
In this paper, a PV micro-storage system for residential applications is proposed. The term micro refers to the size of the PV storage system, which is in the range of few kilo-watts, compared to the grid size (~GWs). Usually, in a typical load profile of a residential unit, two peak demand periods exist: one at morning and the other at evening time. The morning peak can be partly covered by the PV energy directly, while the evening peak cannot be covered by the PV alone. Therefore, an energy storage system that stores solar energy during daytime and use this stored energy when the sun is absent is a must. A complete design procedure including theoretical analysis followed by simulation verification and economic feasibility evaluation is addressed in this paper.Keywords: battery, energy storage, photovoltaic, peak shaving, smart grid
Procedia PDF Downloads 3212027 Polyacrylate Modified Copper Nanoparticles with Controlled Size
Authors: Robert Prucek, Aleš Panáček, Jan Filip, Libor Kvítek, Radek Zbořil
Abstract:
The preparation of Cu nanoparticles (NPs) through the reduction of copper ions by sodium borohydride in the presence of sodium polyacrylate with a molecular weight of 1200 is reported. Cu NPs were synthesized at a concentration of copper salt equal to 2.5, 5, and 10 mM, and at a molar ratio of copper ions and monomeric unit of polyacrylate equal to 1:2. The as-prepared Cu NPs have diameters of about 2.5–3 nm for copper concentrations of 2.5 and 5 mM, and 6 nm for copper concentration of 10 mM. Depending on the copper salt concentration and concentration of additionally added polyacrylate to Cu particle dispersion, primarily formed NPs grow through the process of aggregation and/or coalescence into clusters and/or particles with a diameter between 20–100 nm. The amount of additionally added sodium polyacrylate influences the stability of Cu particles against air oxidation. The catalytic efficiency of the prepared Cu particles for the reduction of 4-nitrophenol is discussed.Keywords: copper, nanoparticles, sodium polyacrylate, catalyst, 4-nitrophenol
Procedia PDF Downloads 2772026 Hydro-Gravimetric Ann Model for Prediction of Groundwater Level
Authors: Jayanta Kumar Ghosh, Swastik Sunil Goriwale, Himangshu Sarkar
Abstract:
Groundwater is one of the most valuable natural resources that society consumes for its domestic, industrial, and agricultural water supply. Its bulk and indiscriminate consumption affects the groundwater resource. Often, it has been found that the groundwater recharge rate is much lower than its demand. Thus, to maintain water and food security, it is necessary to monitor and management of groundwater storage. However, it is challenging to estimate groundwater storage (GWS) by making use of existing hydrological models. To overcome the difficulties, machine learning (ML) models are being introduced for the evaluation of groundwater level (GWL). Thus, the objective of this research work is to develop an ML-based model for the prediction of GWL. This objective has been realized through the development of an artificial neural network (ANN) model based on hydro-gravimetry. The model has been developed using training samples from field observations spread over 8 months. The developed model has been tested for the prediction of GWL in an observation well. The root means square error (RMSE) for the test samples has been found to be 0.390 meters. Thus, it can be concluded that the hydro-gravimetric-based ANN model can be used for the prediction of GWL. However, to improve the accuracy, more hydro-gravimetric parameter/s may be considered and tested in future.Keywords: machine learning, hydro-gravimetry, ground water level, predictive model
Procedia PDF Downloads 1272025 The Design, Development, and Optimization of a Capacitive Pressure Sensor Utilizing an Existing 9DOF Platform
Authors: Andrew Randles, Ilker Ocak, Cheam Daw Don, Navab Singh, Alex Gu
Abstract:
Nine Degrees of Freedom (9 DOF) systems are already in development in many areas. In this paper, an integrated pressure sensor is proposed that will make use of an already existing monolithic 9 DOF inertial MEMS platform. Capacitive pressure sensors can suffer from limited sensitivity for a given size of membrane. This novel pressure sensor design increases the sensitivity by over 5 times compared to a traditional array of square diaphragms while still fitting within a 2 mm x 2 mm chip and maintaining a fixed static capacitance. The improved design uses one large diaphragm supported by pillars with fixed electrodes placed above the areas of maximum deflection. The design optimization increases the sensitivity from 0.22 fF/kPa to 1.16 fF/kPa. Temperature sensitivity was also examined through simulation.Keywords: capacitive pressure sensor, 9 DOF, 10 DOF, sensor, capacitive, inertial measurement unit, IMU, inertial navigation system, INS
Procedia PDF Downloads 5472024 Pressure Angle and Profile Shift Factor Effects on the Natural Frequency of Spur Tooth Design
Authors: Ali Raad Hassan
Abstract:
In this paper, an (irregular) case relating to base circle, root circle, and pressure angle has been discussed and a computer programme has been developed to simulate and plot spur gear tooth profile, including involute and trochoid curves based on the formulation of rack cutter using different values of pressure angle and profile shift factor and it gave the values of all important geometric parameters. The results showed the flexibility of this approach and versatility of the programme to draw many different cases of spur gear teeth of any module, pressure angle, profile shift factor, number of teeth and rack cutter tip radius. The procedure developed can be extended to produce finite element models of heretofore intractable geometrical forms, to exploring fabrication of nonstandard tooth forms also. Finite elements model of these irregular cases have been built using above programme, and modal analysis has been done using ANSYS software, and natural frequencies of these selected cases have been obtained and discussed.Keywords: involute, trochoid, pressure angle, profile shift factor, natural frequency
Procedia PDF Downloads 272