Search results for: ensemble Kalman filter
521 Application of Random Forest Model in The Prediction of River Water Quality
Authors: Turuganti Venkateswarlu, Jagadeesh Anmala
Abstract:
Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.Keywords: water quality, land use factors, random forest, fecal coliform
Procedia PDF Downloads 197520 An Adaptive Hybrid Surrogate-Assisted Particle Swarm Optimization Algorithm for Expensive Structural Optimization
Authors: Xiongxiong You, Zhanwen Niu
Abstract:
Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms
Procedia PDF Downloads 141519 The Concentration of Selected Cosmogenic and Anthropogenic Radionuclides in the Ground Layer of the Atmosphere (Polar and Mid-Latitudes Regions)
Authors: A. Burakowska, M. Piotrowski, M. Kubicki, H. Trzaskowska, R. Sosnowiec, B. Myslek-Laurikainen
Abstract:
The most important source of atmospheric radioactivity are radionuclides generated as a result of the impact of primary and secondary cosmic radiation, with the nuclei of nitrogen oxygen and carbon in the upper troposphere and lower stratosphere. This creates about thirty radioisotopes of more than twenty elements. For organisms, the four of them are most important: ³H, ⁷Be, ²²Na, ¹⁴C. The natural radionuclides, which are present in Earth crust, also settle on dust and particles of water vapor. By this means, the derivatives of uranium and thorium, and long-life 40K get into the air. ¹³⁷Cs is the most widespread isotope, that is implemented by humans into the environment. To determine the concentration of radionuclides in the atmosphere, high volume air samplers were used, where the aerosol collection took place on a special filter fabric (Petrianov filter tissue FPP-15-1.5). In 2002 the high volume air sampler AZA-1000 was installed at the Polish Polar Observatory of the Polish Academy of Science in Hornsund, Spitsbergen (77°00’N, 15°33’E), designed to operate in all weather conditions of the cold polar region. Since 1991 (with short breaks) the ASS-500 air sampler has been working, which is located in Swider at the Kalinowski Geophysical Observatory of Geophysics Institute of the Polish Academy of Science (52°07’N, 21°15’E). The following results of radionuclides concentrations were obtained from both stations using gamma spectroscopy analysis: ⁷Be, ¹³⁷Cs, ¹³⁴Cs, ²¹⁰Pb, ⁴⁰K. For gamma spectroscopy analysis HPGe (High Purity Germanium) detector were used. These data were compared with each other. The preliminary results gave evidence that radioactivity measured in aerosols is not proportional to the amount of dust for both studied regions. Furthermore, the results indicate annual variability (seasonal fluctuations) as well as a decrease in the average activity of ⁷Be with increasing latitude. The content of ⁷Be in surface air also indicates the relationship with solar activity cycles.Keywords: aerosols, air filters, atmospheric beryllium, environmental radionuclides, gamma spectroscopy, mid-latitude regions radionuclides, polar regions radionuclides, solar cycles
Procedia PDF Downloads 140518 Will My Home Remain My Castle? Tenants’ Interview Topics regarding an Eco-Friendly Refurbishment Strategy in a Neighborhood in Germany
Authors: Karin Schakib-Ekbatan, Annette Roser
Abstract:
According to the Federal Government’s plans, the German building stock should be virtually climate neutral by 2050. Thus, the “EnEff.Gebäude.2050” funding initiative was launched, complementing the projects of the Energy Transition Construction research initiative. Beyond the construction and renovation of individual buildings, solutions must be found at the neighborhood level. The subject of the presented pilot project is a building ensemble from the Wilhelminian period in Munich, which is planned to be refurbished based on a socially compatible, energy-saving, innovative-technical modernization concept. The building ensemble, with about 200 apartments, is part of the building cooperative. To create an optimized network and possible synergies between researchers and projects of the funding initiative, a Scientific Accompanying Research was established for cross-project analyses of findings and results in order to identify further research needs and trends. Thus, the project is characterized by an interdisciplinary approach that combines constructional, technical, and socio-scientific expertise based on a participatory understanding of research by involving the tenants at an early stage. The research focus is on getting insights into the tenants’ comfort requirements, attitudes, and energy-related behaviour. Both qualitative and quantitative methods are applied based on the Technology-Acceptance-Model (TAM). The core of the refurbishment strategy is a wall heating system intended to replace conventional radiators. A wall heating provides comfortable and consistent radiant heat instead of convection heat, which often causes drafts and dust turbulence. Besides comfort and health, the advantage of wall heating systems is an energy-saving operation. All apartments would be supplied by a uniform basic temperature control system (around perceived room temperature of 18 °C resp. 64,4 °F), which could be adapted to individual preferences via individual heating options (e. g. infrared heating). The new heating system would affect the furnishing of the walls, in terms of not allowing the wall surface to be covered too much with cupboards or pictures. Measurements and simulations of the energy consumption of an installed wall heating system are currently being carried out in a show apartment in this neighborhood to investigate energy-related, economical aspects as well as thermal comfort. In March, interviews were conducted with a total of 12 people in 10 households. The interviews were analyzed by MAXQDA. The main issue of the interview was the fear of reduced self-efficacy within their own walls (not having sufficient individual control over the room temperature or being very limited in furnishing). Other issues concerned the impact that the construction works might have on their daily life, such as noise or dirt. Despite their basically positive attitude towards a climate-friendly refurbishment concept, tenants were very concerned about the further development of the project and they expressed a great need for information events. The results of the interviews will be used for project-internal discussions on technical and psychological aspects of the refurbishment strategy in order to design accompanying workshops with the tenants as well as to prepare a written survey involving all households of the neighbourhood.Keywords: energy efficiency, interviews, participation, refurbishment, residential buildings
Procedia PDF Downloads 126517 Design and Implementation of a Counting and Differentiation System for Vehicles through Video Processing
Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor
Abstract:
This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing
Procedia PDF Downloads 322516 156vdc to 110vac Sinusoidal Inverter Simulation and Implementation
Authors: Phinyo Mueangmeesap
Abstract:
This paper describes about pure sinusoidal inverter simulation and implementation from high voltage DC (156 Vdc). This simulation is to study and improve the efficiency of the inverter. By reducing the loss of power from boost converter in current inverter. The simulation is done by using the H-bridge circuit with pulse width modulate (PWM) signal and low-pass filter circuit. To convert the DC into AC. This paper used the PSCad for simulation. The result of simulation can be used to create prototype inverter by converting 156 Vdc to 110Vac. The inverter gives the output signal similar to the output from a simulation.Keywords: inverter simulation, PWM signal, single-phase inverter, sinusoidal inverter
Procedia PDF Downloads 412515 0.13-μm CMOS Vector Modulator for Wireless Backhaul System
Authors: J. S. Kim, N. P. Hong
Abstract:
In this paper, a CMOS vector modulator designed for wireless backhaul system based on 802.11ac is presented. A poly phase filter and sign select switches yield two orthogonal signal paths. Two variable gain amplifiers with strongly reduced phase shift of only ±5 ° are used to weight these paths. It has a phase control range of 360 ° and a gain range of -10 dB to 10 dB. The current drawn from a 1.2 V supply amounts 20.4 mA. Using a 0.13 mm technology, the chip die area amounts 1.47x0.75 mm².Keywords: CMOS, phase shifter, backhaul, 802.11ac
Procedia PDF Downloads 386514 Integral Image-Based Differential Filters
Authors: Kohei Inoue, Kenji Hara, Kiichi Urahama
Abstract:
We describe a relationship between integral images and differential images. First, we derive a simple difference filter from conventional integral image. In the derivation, we show that an integral image and the corresponding differential image are related to each other by simultaneous linear equations, where the numbers of unknowns and equations are the same, and therefore, we can execute the integration and differentiation by solving the simultaneous equations. We applied the relationship to an image fusion problem, and experimentally verified the effectiveness of the proposed method.Keywords: integral images, differential images, differential filters, image fusion
Procedia PDF Downloads 506513 A Novel Approach towards Test Case Prioritization Technique
Authors: Kamna Solanki, Yudhvir Singh, Sandeep Dalal
Abstract:
Software testing is a time and cost intensive process. A scrutiny of the code and rigorous testing is required to identify and rectify the putative bugs. The process of bug identification and its consequent correction is continuous in nature and often some of the bugs are removed after the software has been launched in the market. This process of code validation of the altered software during the maintenance phase is termed as Regression testing. Regression testing ubiquitously considers resource constraints; therefore, the deduction of an appropriate set of test cases, from the ensemble of the entire gamut of test cases, is a critical issue for regression test planning. This paper presents a novel method for designing a suitable prioritization process to optimize fault detection rate and performance of regression test on predefined constraints. The proposed method for test case prioritization m-ACO alters the food source selection criteria of natural ants and is basically a modified version of Ant Colony Optimization (ACO). The proposed m-ACO approach has been coded in 'Perl' language and results are validated using three examples by computation of Average Percentage of Faults Detected (APFD) metric.Keywords: regression testing, software testing, test case prioritization, test suite optimization
Procedia PDF Downloads 338512 First Order Filter Based Current-Mode Sinusoidal Oscillators Using Current Differencing Transconductance Amplifiers (CDTAs)
Authors: S. Summart, C. Saetiaw, T. Thosdeekoraphat, C. Thongsopa
Abstract:
This article presents new current-mode oscillator circuits using CDTAs which is designed from block diagram. The proposed circuits consist of two CDTAs and two grounded capacitors. The condition of oscillation and the frequency of oscillation can be adjusted by electronic method. The circuits have high output impedance and use only grounded capacitors without any external resistor which is very appropriate to future development into an integrated circuit. The results of PSPICE simulation program are corresponding to the theoretical analysis.Keywords: current-mode, quadrature oscillator, block diagram, CDTA
Procedia PDF Downloads 453511 Detect Circles in Image: Using Statistical Image Analysis
Authors: Fathi M. O. Hamed, Salma F. Elkofhaifee
Abstract:
The aim of this work is to detect geometrical shape objects in an image. In this paper, the object is considered to be as a circle shape. The identification requires find three characteristics, which are number, size, and location of the object. To achieve the goal of this work, this paper presents an algorithm that combines from some of statistical approaches and image analysis techniques. This algorithm has been implemented to arrive at the major objectives in this paper. The algorithm has been evaluated by using simulated data, and yields good results, and then it has been applied to real data.Keywords: image processing, median filter, projection, scale-space, segmentation, threshold
Procedia PDF Downloads 432510 Automatic Target Recognition in SAR Images Based on Sparse Representation Technique
Authors: Ahmet Karagoz, Irfan Karagoz
Abstract:
Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.Keywords: automatic target recognition, sparse representation, image classification, SAR images
Procedia PDF Downloads 366509 Optimizing E-commerce Retention: A Detailed Study of Machine Learning Techniques for Churn Prediction
Authors: Saurabh Kumar
Abstract:
In the fiercely competitive landscape of e-commerce, understanding and mitigating customer churn has become paramount for sustainable business growth. This paper presents a thorough investigation into the application of machine learning techniques for churn prediction in e-commerce, aiming to provide actionable insights for businesses seeking to enhance customer retention strategies. We conduct a comparative study of various machine learning algorithms, including traditional statistical methods and ensemble techniques, leveraging a rich dataset sourced from Kaggle. Through rigorous evaluation, we assess the predictive performance, interpretability, and scalability of each method, elucidating their respective strengths and limitations in capturing the intricate dynamics of customer churn. We identified the XGBoost classifier to be the best performing. Our findings not only offer practical guidelines for selecting suitable modeling approaches but also contribute to the broader understanding of customer behavior in the e-commerce domain. Ultimately, this research equips businesses with the knowledge and tools necessary to proactively identify and address churn, thereby fostering long-term customer relationships and sustaining competitive advantage.Keywords: customer churn, e-commerce, machine learning techniques, predictive performance, sustainable business growth
Procedia PDF Downloads 27508 Educational Data Mining: The Case of the Department of Mathematics and Computing in the Period 2009-2018
Authors: Mário Ernesto Sitoe, Orlando Zacarias
Abstract:
University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.Keywords: evasion and retention, cross-validation, bagging, stacking
Procedia PDF Downloads 82507 Study of Adaptive Filtering Algorithms and the Equalization of Radio Mobile Channel
Authors: Said Elkassimi, Said Safi, B. Manaut
Abstract:
This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm.Keywords: adaptive filtering second equalizer, LMS, RLS Bran A, Proakis (B) MMSE, ZF
Procedia PDF Downloads 313506 Affective Communities of Women in the Classic Spanish-Mexican-Argentinian Cinema. A Comparative Perspective from a South-South Gaze
Authors: Invernizzi Agostina
Abstract:
From the 1930s, it is possible to find a phenomenon that persists through to the sixties in the national filmographies of different southern latitudes (Spain, Mexico, Argentina): the proliferation of ensemble films of groups of women who serve base to elaborate broader social conflicts and to construct imaginaries of the nation and of genders. This paper will address the modes of figuration of some affective imaginaries among women where the forms of sociability and the bonds of sisterhood are determined by the spaces in which the women are grouped. In these films, there are forms of affectivity that dispute the meanings of the patriarchal order of the time. One of the hypotheses is that these films formulate communities of women that carry out a reconfiguration of affective and transnational spaces. This research presents a multidisciplinary approach that simultaneously combines film and audiovisual studies, gender studies, decolonial feminist theories, and affects theories. The study of this phenomenon will provide us with keys for articulating with current problematics, such as the genealogies of women's movements, of which the cinema offers echoes and is a privileged medium for reflection and social change, as well as the international contact flows between these three geographical points, their migratory processes and cultural exchanges, transnationalism and integration.Keywords: affects, feminisms, film studies, gender
Procedia PDF Downloads 107505 Rapid, Direct, Real-Time Method for Bacteria Detection on Surfaces
Authors: Evgenia Iakovleva, Juha Koivisto, Pasi Karppinen, J. Inkinen, Mikko Alava
Abstract:
Preventing the spread of infectious diseases throughout the worldwide is one of the most important tasks of modern health care. Infectious diseases not only account for one fifth of the deaths in the world, but also cause many pathological complications for the human health. Touch surfaces pose an important vector for the spread of infections by varying microorganisms, including antimicrobial resistant organisms. Further, antimicrobial resistance is reply of bacteria to the overused or inappropriate used of antibiotics everywhere. The biggest challenges in bacterial detection by existing methods are non-direct determination, long time of analysis, the sample preparation, use of chemicals and expensive equipment, and availability of qualified specialists. Therefore, a high-performance, rapid, real-time detection is demanded in rapid practical bacterial detection and to control the epidemiological hazard. Among the known methods for determining bacteria on the surfaces, Hyperspectral methods can be used as direct and rapid methods for microorganism detection on different kind of surfaces based on fluorescence without sampling, sample preparation and chemicals. The aim of this study was to assess the relevance of such systems to remote sensing of surfaces for microorganisms detection to prevent a global spread of infectious diseases. Bacillus subtilis and Escherichia coli with different concentrations (from 0 to 10x8 cell/100µL) were detected with hyperspectral camera using different filters as visible visualization of bacteria and background spots on the steel plate. A method of internal standards was applied for monitoring the correctness of the analysis results. Distances from sample to hyperspectral camera and light source are 25 cm and 40 cm, respectively. Each sample is optically imaged from the surface by hyperspectral imaging system, utilizing a JAI CM-140GE-UV camera. Light source is BeamZ FLATPAR DMX Tri-light, 3W tri-colour LEDs (red, blue and green). Light colors are changed through DMX USB Pro interface. The developed system was calibrated following a standard procedure of setting exposure and focused for light with λ=525 nm. The filter is ThorLabs KuriousTM hyperspectral filter controller with wavelengths from 420 to 720 nm. All data collection, pro-processing and multivariate analysis was performed using LabVIEW and Python software. The studied human eye visible and invisible bacterial stains clustered apart from a reference steel material by clustering analysis using different light sources and filter wavelengths. The calculation of random and systematic errors of the analysis results proved the applicability of the method in real conditions. Validation experiments have been carried out with photometry and ATP swab-test. The lower detection limit of developed method is several orders of magnitude lower than for both validation methods. All parameters of the experiments were the same, except for the light. Hyperspectral imaging method allows to separate not only bacteria and surfaces, but also different types of bacteria, such as Gram-negative Escherichia coli and Gram-positive Bacillus subtilis. Developed method allows skipping the sample preparation and the use of chemicals, unlike all other microbiological methods. The time of analysis with novel hyperspectral system is a few seconds, which is innovative in the field of microbiological tests.Keywords: Escherichia coli, Bacillus subtilis, hyperspectral imaging, microorganisms detection
Procedia PDF Downloads 224504 Association of Non Synonymous SNP in DC-SIGN Receptor Gene with Tuberculosis (Tb)
Authors: Saima Suleman, Kalsoom Sughra, Naeem Mahmood Ashraf
Abstract:
Mycobacterium tuberculosis is a communicable chronic illness. This disease is being highly focused by researchers as it is present approximately in one third of world population either in active or latent form. The genetic makeup of a person plays an important part in producing immunity against disease. And one important factor association is single nucleotide polymorphism of relevant gene. In this study, we have studied association between single nucleotide polymorphism of CD-209 gene (encode DC-SIGN receptor) and patients of tuberculosis. Dry lab (in silico) and wet lab (RFLP) analysis have been carried out. GWAS catalogue and GEO database have been searched to find out previous association data. No association study has been found related to CD-209 nsSNPs but role of CD-209 in pulmonary tuberculosis have been addressed in GEO database.Therefore, CD-209 has been selected for this study. Different databases like ENSEMBLE and 1000 Genome Project has been used to retrieve SNP data in form of VCF file which is further submitted to different software to sort SNPs into benign and deleterious. Selected SNPs are further annotated by using 3-D modeling techniques using I-TASSER online software. Furthermore, selected nsSNPs were checked in Gujrat and Faisalabad population through RFLP analysis. In this study population two SNPs are found to be associated with tuberculosis while one nsSNP is not found to be associated with the disease.Keywords: association, CD209, DC-SIGN, tuberculosis
Procedia PDF Downloads 309503 Performance Evaluation of On-Site Sewage Treatment System (Johkasou)
Authors: Aashutosh Garg, Ankur Rajpal, A. A. Kazmi
Abstract:
The efficiency of an on-site wastewater treatment system named Johkasou was evaluated based on its pollutant removal efficiency over 10 months. This system was installed at IIT Roorkee and had a capacity of treating 7 m3/d of sewage water, sufficient for a group of 30-50 people. This system was fed with actual wastewater through an equalization tank to eliminate the fluctuations throughout the day. Methanol and ammonium chloride was added into this equalization tank to increase the Chemical Oxygen Demand (COD) and ammonia content of the influent. The outlet from Johkasou is sent to a tertiary unit consisting of a Pressure Sand Filter and an Activated Carbon Filter for further treatment. Samples were collected on alternate days from Monday to Friday and the following parameters were evaluated: Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), Total Suspended Solids (TSS), and Total Nitrogen (TN). The Average removal efficiency for Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), Total Suspended Solids (TSS), and Total Nitrogen (TN) was observed as 89.6, 97.7, 96, and 80% respectively. The cost of treating the wastewater comes out to be Rs 23/m3 which includes electricity, cleaning and maintenance, chemical, and desludging costs. Tests for the coliforms were also performed and it was observed that the removal efficiency for total and fecal coliforms was 100%. The sludge generation rate is approximately 20% of the BOD removal and it needed to be removed twice a year. It also showed a very good response against the hydraulic shock load. We performed vacation stress analysis on the system to evaluate the performance of the system when there is no influent for 8 consecutive days. From the result of stress analysis, we concluded that system needs a recovery time of about 48 hours to stabilize. After about 2 days, the system returns again to original conditions and all the parameters in the effluent become within the limits of National Green Tribunal (NGT) standards. We also performed another stress analysis to save the electricity in which we turned the main aeration blower off for 2 to 12 hrs a day and the results showed that we can turn the blower off for about 4-6 hrs a day and this will help in reducing the electricity costs by about 25%. It was concluded that the Johkasou system can remove a sufficient amount of all the physiochemical parameters tested to satisfy the prescribed limit set as per Indian Standard.Keywords: on-site treatment, domestic wastewater, Johkasou, nutrient removal, pathogens removal
Procedia PDF Downloads 114502 Zinc Contaminate on Urban Roadside in Rush Hour, Bangkok, Thailand
Authors: Sivapan Choo-In
Abstract:
This research aims to study the Zinc (Zn) concentration in fine particulate matter on Rajchawithee roadside in rush hour. 30 Samples were collected in Jun to August 2013 by 8 stage non-avaible cascade impactor. Each samples (filter paper) were digest with nitric acid and analyed by atomic absorption spectrophotometer for Zinc determination. The highest value for the mean fraction (18.00 ± 9.28 %) is the size 9.0 – 110.0 micron follow by the range 3.3 – 4.7 micron (14.77 ± 14.66 %) and 1.1 – 2.1 micron (14.01 ± 11.77 %) .The concentration of Zn in the particulate matter of range 0.43 – 0.7 μm, 0.7 – 1.1 μm, 1.1 – 2.1 μm, 2.1 – 3.3 μm, 3.3 – 4.7 μm, 4.7 – 5.8 μm, 5.8 – 9.0 μm, 9.0 – 10.0 μm, were 41.56 – 217.62 μg/m3 (175.86 ± 32.25 μg/m3), 152.60 – 217.24 μg/m3 (187.71 ± 17.42 μg/m3), 142.90 – 214.67 μg/m3 (180.95 ± 18.71 μg/m3), 155.48 – 218.19 μg/m3 (183.22 ± 19.94 μg/m3), 151.72 – 217.39 μg/m3 (181.85 ± 17.57 μg/m3), 133.86 – 220.17 μg/m3 (178.78 ± 23.45 μg/m3), 160.00 – 220.35 μg/m3 (182.58 ± 18.08 μg/m3), 153.30 – 226.70 μg/m3 (181.52 ± 20.05 μg/m3), repectively. The Zn concentration in each size of particulate matter was not statistically significant different (p > .005)Keywords: air pollution, particulate matter, size distribution, zinc
Procedia PDF Downloads 314501 Determination of Surface Deformations with Global Navigation Satellite System Time Series
Authors: Ibrahim Tiryakioglu, Mehmet Ali Ugur, Caglar Ozkaymak
Abstract:
The development of GNSS technology has led to increasingly widespread and successful applications of GNSS surveys for monitoring crustal movements. However, multi-period GPS survey solutions have not been applied in monitoring vertical surface deformation. This study uses long-term GNSS time series that are required to determine vertical deformations. In recent years, the surface deformations that are parallel and semi-parallel to Bolvadin fault have occurred in Western Anatolia. These surface deformations have continued to occur in Bolvadin settlement area that is located mostly on alluvium ground. Due to these surface deformations, a number of cracks in the buildings located in the residential areas and breaks in underground water and sewage systems have been observed. In order to determine the amount of vertical surface deformations, two continuous GNSS stations have been established in the region. The stations have been operating since 2015 and 2017, respectively. In this study, GNSS observations from the mentioned two GNSS stations were processed with GAMIT/GLOBK (GNSS Analysis Massachusetts Institute of Technology/GLOBal Kalman) program package to create a coordinate time series. With the time series analyses, the GNSS stations’ behavior models (linear, periodical, etc.), the causes of these behaviors, and mathematical models were determined. The study results from the time series analysis of these two 2 GNSS stations shows approximately 50-80 mm/yr vertical movement.Keywords: Bolvadin fault, GAMIT, GNSS time series, surface deformations
Procedia PDF Downloads 165500 Towards Human-Interpretable, Automated Learning of Feedback Control for the Mixing Layer
Authors: Hao Li, Guy Y. Cornejo Maceda, Yiqing Li, Jianguo Tan, Marek Morzynski, Bernd R. Noack
Abstract:
We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich database of machine learning control (MLC) optimizing a feedback law for a cost function in the plant. The proposed methodology provides (1) insights into the control landscape, which maps control laws to performance, including extrema and ridge-lines, (2) a catalogue of representative flow states and their contribution to cost function for investigated control laws and (3) visualization of the dynamics. Key enablers are classification and feature extraction methods of machine learning. The analysis is successfully applied to the stabilization of a mixing layer with sensor-based feedback driving an upstream actuator. The fluctuation energy is reduced by 26%. The control replaces unforced Kelvin-Helmholtz vortices with subsequent vortex pairing by higher-frequency Kelvin-Helmholtz structures of lower energy. These efforts target a human interpretable, fully automated analysis of MLC identifying qualitatively different actuation regimes, distilling corresponding coherent structures, and developing a digital twin of the plant.Keywords: machine learning control, mixing layer, feedback control, model-free control
Procedia PDF Downloads 223499 The Effect of Measurement Distribution on System Identification and Detection of Behavior of Nonlinearities of Data
Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri
Abstract:
In this paper, we considered and applied parametric modeling for some experimental data of dynamical system. In this study, we investigated the different distribution of output measurement from some dynamical systems. Also, with variance processing in experimental data we obtained the region of nonlinearity in experimental data and then identification of output section is applied in different situation and data distribution. Finally, the effect of the spanning the measurement such as variance to identification and limitation of this approach is explained.Keywords: Gaussian process, nonlinearity distribution, particle filter, system identification
Procedia PDF Downloads 516498 Greywater Water Reuse in South Africa
Authors: Onyeka Nkwonta, Christopher Iheukwumere
Abstract:
It is a waste to irrigate with great quantities of drinking water when plants thrive on used water containing small bits of compost. Unlike a lot of ecological stopgap measures, greywater reuse is a part of the fundamental solution to many ecological problems and will probably remain essentially unchanged in the distant future. Water is abused and wasted by both the wealthy and the poor. Education about water conservation is also needed. This study gives an outline of the sources of grey water in our home and provides a process of creating awareness on the importance of re-using grey water in our home, in order to achieve the 7th aim of the millennium development goals by 2015, which is ensuring environmental sustainability.Keywords: tickling filter, education, grey water, environmental sustainability
Procedia PDF Downloads 371497 Electrocardiogram Signal Denoising Using a Hybrid Technique
Authors: R. Latif, W. Jenkal, A. Toumanari, A. Hatim
Abstract:
This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.Keywords: hybrid technique, ADTF, DWT, thresholding, ECG signal
Procedia PDF Downloads 322496 Mental Health Diagnosis through Machine Learning Approaches
Authors: Md Rafiqul Islam, Ashir Ahmed, Anwaar Ulhaq, Abu Raihan M. Kamal, Yuan Miao, Hua Wang
Abstract:
Mental health of people is equally important as of their physical health. Mental health and well-being are influenced not only by individual attributes but also by the social circumstances in which people find themselves and the environment in which they live. Like physical health, there is a number of internal and external factors such as biological, social and occupational factors that could influence the mental health of people. People living in poverty, suffering from chronic health conditions, minority groups, and those who exposed to/or displaced by war or conflict are generally more likely to develop mental health conditions. However, to authors’ best knowledge, there is dearth of knowledge on the impact of workplace (especially the highly stressed IT/Tech workplace) on the mental health of its workers. This study attempts to examine the factors influencing the mental health of tech workers. A publicly available dataset containing more than 65,000 cells and 100 attributes is examined for this purpose. Number of machine learning techniques such as ‘Decision Tree’, ‘K nearest neighbor’ ‘Support Vector Machine’ and ‘Ensemble’, are then applied to the selected dataset to draw the findings. It is anticipated that the analysis reported in this study would contribute in presenting useful insights on the attributes contributing in the mental health of tech workers using relevant machine learning techniques.Keywords: mental disorder, diagnosis, occupational stress, IT workplace
Procedia PDF Downloads 288495 Transportation Mode Classification Using GPS Coordinates and Recurrent Neural Networks
Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem
Abstract:
The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.Keywords: classification, gated recurrent unit, recurrent neural network, transportation
Procedia PDF Downloads 137494 Conceptualising an Open Living Museum beyond Musealization in the Context of a Historic City: Study of Bhaktapur World Heritage Site, Nepal
Authors: Shyam Sunder Kawan
Abstract:
Museums are enclosed buildings encompassing and displaying creative artworks, artefacts, and discoveries for people’s knowledge and observation. In the context of Nepal, museums and exhibition areas are either adaptive to small gallery spaces in residences or ‘neo-classical palatial complexes’ that evolved during the 19th century. This study accepts the sparse occurrence of a diverse range of artworks and expressions in the country's complex cultural manifestations within vivid ethnic groups. This study explores the immense potential of one such prevalence beyond the delimitation of physical boundaries. Taking Bhaktapur World Heritage Site as a case, the study perpetuates its investigation into real-time life activities that this city and its cultural landscapes ensemble. Seeking the ‘musealization’ as an urban process to induce museums into the city precinct, this study anticipates art space into urban spaces to offer a limitless experience for this contemporary world. Unveiling art as an experiential component, this study aims to conceptualize a living heritage as an infinite resource for museum interpretation beyond just educational institute purposes.Keywords: living museum, site museum, museulization, contemporary arts, cultural heritage, historic cities
Procedia PDF Downloads 103493 Efficient Filtering of Graph Based Data Using Graph Partitioning
Authors: Nileshkumar Vaishnav, Aditya Tatu
Abstract:
An algebraic framework for processing graph signals axiomatically designates the graph adjacency matrix as the shift operator. In this setup, we often encounter a problem wherein we know the filtered output and the filter coefficients, and need to find out the input graph signal. Solution to this problem using direct approach requires O(N3) operations, where N is the number of vertices in graph. In this paper, we adapt the spectral graph partitioning method for partitioning of graphs and use it to reduce the computational cost of the filtering problem. We use the example of denoising of the temperature data to illustrate the efficacy of the approach.Keywords: graph signal processing, graph partitioning, inverse filtering on graphs, algebraic signal processing
Procedia PDF Downloads 311492 Valuation on MEMS Pressure Sensors and Device Applications
Authors: Nurul Amziah Md Yunus, Izhal Abdul Halin, Nasri Sulaiman, Noor Faezah Ismail, Ong Kai Sheng
Abstract:
The MEMS pressure sensor has been introduced and presented in this paper. The types of pressure sensor and its theory of operation are also included. The latest MEMS technology, the fabrication processes of pressure sensor are explored and discussed. Besides, various device applications of pressure sensor such as tire pressure monitoring system, diesel particulate filter and others are explained. Due to further miniaturization of the device nowadays, the pressure sensor with nanotechnology (NEMS) is also reviewed. The NEMS pressure sensor is expected to have better performance as well as lower in its cost. It has gained an excellent popularity in many applications.Keywords: pressure sensor, diaphragm, MEMS, automotive application, biomedical application, NEMS
Procedia PDF Downloads 671