Search results for: housing price prediction

Authors: Jaspreet Singh, Gurvinder Singh, Prabhsimran Singh, Rajinder Singh, Prithvipal Singh, Karanjeet Singh Kahlon, Ravinder Singh Sawhney

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Morphological evaluation of Indian languages is one of the burgeoning fields in the area of Natural Language Processing (NLP). The evaluation of a language is an eminent task in the era of information retrieval and text mining. The extraction and classification of knowledge from text can be exploited for sentiment analysis and morphological evaluation. This study coalesce morphological evaluation and sentiment analysis for the task of classification of farmer suicide cases reported in Punjab state of India. The pre-processing of Punjabi text involves morphological evaluation and normalization of Punjabi word tokens followed by the training of proposed model using deep learning classification on Punjabi language text extracted from online Punjabi news reports. The class-wise accuracies of sentiment prediction for four negatively oriented classes of farmer suicide cases are 93.85%, 88.53%, 83.3%, and 95.45% respectively. The overall accuracy of sentiment classification obtained using proposed framework on 275 Punjabi text documents is found to be 90.29%.

Keywords: deep neural network, farmer suicides, morphological processing, punjabi text, sentiment analysis

Procedia PDF Downloads 303

Authors: Ashkan Shafee, Ahamd Fahimifar, Sajjad V. Maghvan

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Promotion of the Fiber Reinforced Concrete (FRC) as a construction material for civil engineering projects has invoked numerous researchers to investigate their mechanical behavior. Even though there is satisfactory information about the effects of fiber type and length, concrete mixture, casting type and other variables on the strength and deformability parameters of FRC, the numerical modeling of such materials still needs research attention. The focus of this study is to investigate the feasibility of Concrete Damaged Plasticity (CDP) model in prediction of Macro-synthetic FRC structures behavior. CDP model requires the tensile behavior of concrete to be well characterized. For this purpose, a series of uniaxial direct tension and four point bending tests were conducted on the notched specimens to define bilinear tension softening (post-peak tension stress-strain) behavior. With these parameters obtained, the flexural behavior of macro-synthetic FRC beams were modeled and the results showed a good agreement with the experimental measurements.

Keywords: concrete damaged plasticity, fiber reinforced concrete, finite element modeling, macro-synthetic fibers, uniaxial tensile test

Procedia PDF Downloads 402

Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

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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 184

Authors: Phanida Phukoetphim, Asaad Y. Shamseldin

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In this study, the novel Stochastic Gradient Boosting (SGB) combination method is addressed for producing daily river flows from four different rain-runoff models of Ohinemuri catchment, New Zealand. The selected rainfall-runoff models are two empirical black-box models: linear perturbation model and linear varying gain factor model, two conceptual models: soil moisture accounting and routing model and Nedbør-Afrstrømnings model. In this study, the simple average combination method and the weighted average combination method were used as a benchmark for comparing the results of the novel SGB combination method. The models and combination results are evaluated using statistical and graphical criteria. Overall results of this study show that the use of combination technique can certainly improve the simulated river flows of four selected models for Ohinemuri catchment, New Zealand. The results also indicate that the novel SGB combination method is capable of accurate prediction when used in a combination method of the simulated river flows in New Zealand.

Keywords: multi-model combination, rainfall-runoff modeling, stochastic gradient boosting, bioinformatics

Procedia PDF Downloads 322

Authors: Xiongxiong You, Zhanwen Niu

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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 129

Authors: Sajjad Negahban, Ruihe Wang, Baojiang Sun

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Gas-lift dual gradient drilling is a solution for deepwater drilling challenges. As well, Continuous development of drilling technology leads to increase employment of mineral oil based drilling fluids and synthetic-based drilling fluids, which have adequate characteristics such as: high rate of penetration, lubricity, shale inhibition and low toxicity. The paper discusses utilization of nitrified mineral oil base drilling for deepwater drilling and for more accurate prediction of pressure in DGD at marine riser, solubility and bubble pressure were considered in steady state hydraulic model. The Standing bubble pressure and solubility correlations, and two models which were acquired from experimental determination were applied in hydraulic model. The effect of the black oil correlations, and new solubility and bubble pressure models was evaluated on the PVT parameters such as oil formation volume factor, density, viscosity, volumetric flow rate. Eventually, the consequent simulated pressure profile due to these models was presented.

Keywords: solubility, bubble pressure, gas-lift dual gradient drilling, steady state hydraulic model

Procedia PDF Downloads 259

Authors: Gajaanuja Megalathan, Banuka Athuraliya

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Crime is one of our society's most intimidating and threatening challenges. With the majority of the population residing in cities, many experts and data provided by local authorities suggest a rapid increase in the number of crimes committed in these cities in recent years. There has been an increasing graph in the crime rates. People living in Sri Lanka have the right to know the exact crime rates and the crime rates in the future of the place they are living in. Due to the current economic crisis, crime rates have spiked. There have been so many thefts and murders recorded within the last 6-10 months. Although there are many sources to find out, there is no solid way of searching and finding out the safety of the place. Due to all these reasons, there is a need for the public to feel safe when they are introduced to new places. Through this research, the author aims to develop a mobile application that will be a solution to this problem. It is mainly targeted at tourists, and people who recently relocated will gain advantage of this application. Moreover, the Arima Model combined with ANN is to be used to predict crime rates. From the past researchers' works, it is evidently clear that they haven’t used the Arima model combined with Artificial Neural Networks to forecast crimes.

Keywords: arima model, ANN, crime prediction, data analysis

Procedia PDF Downloads 108

Authors: Yegetaneh T. Dejenu, Delesa Kejela, Abdulak Alemu

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From the earliest time of humankind, the trenches were used for water to flow along and for soldiers to hide in during enemy attacks. Now a day due to civilization, the needs of the human being become endless, and the living condition becomes sophisticated. The unbalance between the needs and resource obligates them to find the way to manage this condition. The attempt to use the scares resource in very efficient and effective way makes the trench an endeavor practice in the world in all countries. A trencher is a construction equipment used to dig trenches, especially for laying pipes or cables, installing drainage, irrigation, installing fencing, and in preparation for trench warfare. It is a machine used to make a ditch by cutting the soil ground and effectively used in agricultural irrigation. The most common types of trencher are wheel trencher, chain trencher, micro trencher, portable trencher. In Ethiopia people have been trenching the ditch for many purposes and the tools they are using are Pickaxe, Shovel and some are using Micro Excavators. The adverse effect of using traditional equipment is, time and energy consuming, less productive, difficult and more man power is required. Hence it is necessary to design and produce low price, and simple machine to narrow this gap. Our objective is to design and model a light duty trencher that is used for trenching the ground or soil for making ditch and used for agricultural, ground cabling, ground piping, and drainage system. The designed machine trenches, maximum of 1-meter depth, 30 cm width, and the required length. The working mechanism is fully hydraulic, and the engine with 12.7 hp will provide suitable power for the pump that delivers 23 l/min at 1500 rpm to drive hydraulic motors and actuators.

Keywords: hydraulics, modelling, trenching, ditch

Procedia PDF Downloads 202

Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

Procedia PDF Downloads 485

Authors: Gyo Woo Lee, Man Young Kim

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A mathematical heat transfer model for the prediction of transient heating of the slab in a direct-fired walking beam type reheating furnace has been developed by considering the nongray thermal radiation with given furnace environments. The furnace is modeled as radiating nongray medium with carbon dioxide and water with five-zoned gas temperature and the furnace wall is considered as a constant temperature lower than furnace gas one. The slabs are moving with constant velocity depending on the residence time through the non-firing, charging, preheating, heating, and final soaking zones. Radiative heat flux obtained by considering the radiative heat exchange inside the furnace as well as convective one from the surrounding hot gases are introduced as boundary condition of the transient heat conduction within the slab. After validating thermal radiation model adopted in this work, thermal fields in both model and real reheating furnace are investigated in terms of radiative heat flux in the furnace and temperature inside the slab. The results show that the slab in the furnace can be more heated with higher slab emissivity and residence time.

Keywords: reheating furnace, steel slab, radiative heat transfer, WSGGM, emissivity, residence time

Procedia PDF Downloads 268

Authors: Samia Rabet, Rachida Chemini, Gerhard Schäfer, Farid Aiouache

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The textile industry generates large quantities of wastewater, which poses significant environmental problems due to its complex composition and high levels of pollutants loaded principally with heavy metals, large amounts of COD, and dye. Separation treatment methods are often known for their effectiveness in removing contaminants whereas membrane separation techniques are a promising process for the treatment of textile effluent due to their versatility, efficiency, and low energy requirements. This study focuses on the modeling and simulation of membrane separation technologies with a cross-flow filtration process for textile effluent treatment. It aims to explore the application of mathematical models and computational simulations using ASPEN Plus Software in the prediction of a complex and real effluent separation. The results demonstrate the effectiveness of modeling and simulation techniques in predicting pollutant removal efficiencies with a global deviation percentage of 1.83% between experimental and simulated results; membrane fouling behavior, and overall process performance (hydraulic resistance, membrane porosity) were also estimated and indicating that the membrane losses 10% of its efficiency after 40 min of working.

Keywords: membrane separation, ultrafiltration, textile effluent, modeling, simulation

Procedia PDF Downloads 42

Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

Procedia PDF Downloads 124

Authors: Tienfuan Kerh, Hsienchang Lu, Rob Saunders

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Shoreline erosion problems caused by global warming and sea level rising may result in losing of land areas, so it should be examined regularly to reduce possible negative impacts. Initially in this study, three sets of survey images obtained from the years of 1990, 2001, and 2010, respectively, are digitalized by using graphical software to establish the spatial coordinates of six major beaches around the island of Taiwan. Then, by overlaying the known multi-period images, the change of shoreline can be observed from their distribution of coordinates. In addition, the neural network approximation is used to develop a model for predicting shoreline variation in the years of 2015 and 2020. The comparison results show that there is no significant change of total sandy area for all beaches in the three different periods. However, the prediction results show that two beaches may exhibit an increasing of total sandy areas under a statistical 95% confidence interval. The proposed method adopted in this study may be applicable to other shorelines of interest around the world.

Keywords: digitalized shoreline coordinates, survey image overlaying, neural network approximation, total beach sandy areas

Procedia PDF Downloads 257

Authors: Khaled M.Naguib, Ahmed M.Noureldin

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This paper aims to achieve many goals such as knowing (quantities produced- main properties- characteristics) of sludge produced from Bahr EL-Baqar drains treatment plant. This prediction or projection was made by laboratory analysis and modelling of Model samples from sludge depending on many studies that have previously done, second check the feasibility and do a risk analysis to know the best alternatives for reuse in producing secondary products that add value to sludge. Also, to know alternatives that have no value to add. All recovery methods are relatively very expensive and challenging to be done in this mega plant, so the recommendation from this study is to use the sludge as a coagulant to reduce some compounds or in secondary products. The study utilized sludge-cement replacement percentages of 10%, 20%, 30%, 40% and 50%. Produced tiles were tested for water absorption and breaking (bending) strength. The study showed that all produced tiles exhibited a water absorption ratio of around 10%. The study concluded that produced tiles, except for 50% sludge-cement replacement, comply with the breaking strength requirements of 2.8 MPa for tiles for external use.

Keywords: cement, tiles, water treatment sludge, breaking strength, absorption, heavy metals, risk analysis

Procedia PDF Downloads 92

Authors: Yunmi Park, Mahn-Jo Kim

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The purpose of this research is to find out the effect of raising poultry in environment-friendly producing area to fruit quality and crop within chestnut tree yield. This study was conducted on chestnut tree cultivation sites raising poultry at intervals of five to ten days for three years in the mountainous area which was located in the middle corner of Chungcheongbuk-do province, Korea. The quality of chestnut fruit and the control effects of harmful insects have been investigated between the sites raising poultry and control sites for three years. As a result, the harvest yielded were two to five kilograms higher in the chestnut tree cultivation sites raising poultry compared with the control site without poultry. Also, for the purposes of determining the price when selling, the ratio of the biggest fruit is higher by 3% to 14% in the chestnut tree cultivation sites raising poultry. In order to investigate the effects of pest control through raising poultry, the ratio of harmful insect species to treatment sites was relatively low compared to control site. The appreciable result is that the control effect of larvae of the chestnut leaf-cut weevil was higher in the position where raising the poultry of 4 to 5 weeks compared to the position where raising the poultry of 12 weeks. This study found that the spread of poultry in the cultivation of chestnut trees increased the fruit quality by improving the size of fruits and lowering the dosage of harmful insect, chestnut leaf-cut weevil. Also, the eco-friendly chicken produced by these mountainous regions is expected to contribute to enhancing the incomes of the farmers by differentiating themselves from existing products.

Keywords: chestnut tree, environment-friendly, fruit quality, raising poultry

Procedia PDF Downloads 278

Authors: Yudhajit Datta

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Will is a phenomenon that has puzzled humanity for a long time. It is a belief that Will Power of an individual affects the success achieved by an individual in life. It is thought that a person endowed with great will power can overcome even the most crippling setbacks of life while a person with a weak will cannot make the most of life even the greatest assets. Behavioral aspects of the human experience such as will are rarely subjected to quantitative study owing to the numerous uncontrollable parameters involved. This work is an attempt to subject the phenomena of will to the test of an artificial neural network. The claim being tested is that will power of an individual largely determines success achieved in life. In the study, an attempt is made to incorporate the behavioral phenomenon of will into a computational model using data pertaining to the success of individuals obtained from an experiment. A neural network is to be trained using data based upon part of the model, and subsequently used to make predictions regarding will corresponding to data points of success. If the prediction is in agreement with the model values, the model is to be retained as a candidate. Ultimately, the best-fit model from among the many different candidates is to be selected, and used for studying the correlation between success and will.

Keywords: will power, will, success, apathy factor, random factor, characteristic function, life story

Procedia PDF Downloads 369

Authors: Sanoj Sahu, Ramakar Jha

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Odisha (India) is in need of reliable, cost-effective power generation. A prolonged electricity crisis and increasing power demand have left over thousands of citizens without access to electricity, and much of the population suffers from sporadic outages. The purpose of this project is to build a methodology to evaluate small hydropower potential, which can be used to alleviate the Odisha’s energy problem among rural communities. This project has three major tasks: the design of a simple SHEP for a single location along a river in the Odisha; the development of water flow prediction equations through a linear regression analysis; and the design of an ArcGIS toolset to estimate the flow duration curves (FDCs) at locations where data do not exist. An explanation of the inputs to the tool, as well has how it produces a suitable output for SHEP evaluation will be presented. The paper also gives an explanation of hydroelectric power generation in the Odisha, SHEPs, and the technical and practical aspects of hydroelectric power. Till now, based on topographical and rainfall analysis we have located hundreds of sites. Further work on more number of site location and accuracy of location is to be done.

Keywords: small hydropower, ArcGIS, rainfall analysis, Odisha’s energy problem

Procedia PDF Downloads 435

Authors: Mehrnoosh Abouzari, Shahrokh Sahraei

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Arrival of artificial intelligence or smart robots in the modern world put them in charge on pericise and at risk. So acting human activities with robots makes criminal or civil responsibilities for their acts or behavior. The practical usage of smart robots has entered them in to a unique situation when naturalization happens and smart robots are identifies as members of society. There would be some legal situation by adopting these new smart citizens. The first situation is about legal responsibility of robots. Recognizing the naturalization of robot involves some basic right , so humans have the rights of employment, property, housing, using energy and other human rights may be employed for robots. So how would be the practice of these rights in the society and if some problems happens with these rights, how would the civil responsibility and punishment? May we consider them as population and count on the social programs? The second episode is about the criminal responsibility of robots in important activity instead of human that is the aim of inventing robots with handling works in AI technology , but the problem arises when some accidents are happened by robots who are in charge of important activities like army, surgery, transporting, judgement and so on. Moreover, recognizing independent identification for robots in the legal world by register ID cards, naturalization and civilian rights makes and prepare the same rights and obligations of human. So, the civil responsibility is not avoidable and if the robot commit a crime it would have criminal responsibility and have to be punished. The basic component of criminal responsibility may changes in so situation. For example, if designation for criminal responsibility bounds to human by sane, maturity, voluntariness, it would be for robots by being intelligent, good programming, not being hacked and so on. So it is irrational to punish robots by prisoning , execution and other human punishments for body. We may determine to make digital punishments like changing or repairing programs, exchanging some parts of its body or wreck it down completely. Finally the responsibility of the smart robot creators, programmers, the boss in chief, the organization who employed robot, the government which permitted to use robot in important bases and activities , will be analyzing and investigating in their article.

Keywords: robot, artificial intelligence, personality, responsibility

Procedia PDF Downloads 130

Authors: Tharsinithevy Kirupananthan

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This study analyzed the decision on growing three different crops which suit dry zone of Sri Lanka using the opportunity cost concept in economics. The variable cost of production of sugar cane, sweet orange, and soybean was 112,418.76, 13,463 and 10,928.08 Sri Lankan Rs. (LKR) per acre in the dry zone of Sri Lanka. The yield of the sugar cane, sweet orange, and soybean were 49.33 tons, 25,595 fruits, and 1032 kg per acre. The market price of the sugar cane, sweet orange, and soybean were 4200 LKR/ton, LKR 14.66 per fruit and LKR 89.69 per kg. The market value or the total income of the sugar cane, sweet orange, and soybean were LKR 207194.4, 283090.74, and 92560.08. The accounting profit of the sugar cane, sweet orange, and soybean was 94,775.64, 269,627.74, and 81,632 LKR per acre. Therefore, the opportunity cost of sugarcane per acre in terms of accounting profit was LKR. 269,627.74 from sweet orange and LKR 81,632 from soybean. The highest opportunity cost per acre in terms of accounting profit was found when soybean is produced instead of sweet orange. The opportunity cost which compared among the crops in terms of market value for sugar cane per acre was LKR 283090.74 of sweet orange and LKR 92560.08 of soybean. The highest opportunity cost both in terms of accounting profit and market value was found when growing soybean instead of sweet orange by using the resource per acre of land. The economic profit of sugar cane production in place of sweet orange was LKR -188315.1 per acre. The highest economic profit LKR 177067.66 was found when sweet orange is produced in place of soybean. A positive value of economic profit was found in all combination of sweet orange production without considering the first harvest duration of the crop.

Keywords: agricultural economics, crop, opportunity cost, Sri Lanka

Procedia PDF Downloads 330

Authors: Jiin-Yuh Jang, Yu-Feng Gan

Abstract:

In order to improve the comprehensive mechanical properties of the steel, the cooling rate, and the temperature distribution must be controlled in the cooling process. A three-dimensional numerical model for the prediction of the heat transfer coefficient distribution of H-beam in the controlled cooling process was performed in order to obtain the uniform temperature distribution and minimize the maximum stress and the maximum deformation after the controlled cooling. An algorithm developed with a simplified conjugated-gradient method was used as an optimizer to optimize the heat transfer coefficient distribution. The numerical results showed that, for the case of air cooling 5 seconds followed by water cooling 6 seconds with uniform the heat transfer coefficient, the cooling rate is 15.5 (℃/s), the maximum temperature difference is 85℃, the maximum the stress is 125 MPa, and the maximum deformation is 1.280 mm. After optimize the heat transfer coefficient distribution in control cooling process with the same cooling time, the cooling rate is increased to 20.5 (℃/s), the maximum temperature difference is decreased to 52℃, the maximum stress is decreased to 82MPa and the maximum deformation is decreased to 1.167mm.

Keywords: controlled cooling, H-Beam, optimization, thermal stress

Procedia PDF Downloads 352

Authors: Amylyn F. Labasano

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A significant number of empirical studies are carried out to investigate factors affecting college students’ performance in the academic examination. With a wide-array of literature-and studies-supported findings, this study is limited only on the students’ probability of passing periodical exams which is associated with students’ gender, absences in the class, use of reference book, and hours of study. Binary logistic regression was the technique used in the analysis. The research is based on the students’ record and data collected through survey. The result reveals that gender, use of reference book and hours of study are significant predictors of passing an examination while students’ absenteeism is an insignificant predictor. Females have 45% likelihood of passing the exam than their male classmates. Students who use and read their reference book are 38 times more likely pass the exam than those who do not use and read their reference book. Those who spent more than 3 hours in studying are four (4) times more likely pass the exam than those who spent only 3 hours or less in studying.

Keywords: absences, binary logistic regression, gender, hours of study prediction-causation method, periodical exams, random sampling, reference book

Procedia PDF Downloads 292

Authors: Rama Bhattacharyya, S. N. Ojha, Umesh K. Singh

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Anthropogenic control on groundwater chemistry has emerged as a critical concern now-a-days, especially in the industrial areas. In view of this, a comprehensive study on the distribution of the heavy metal in the groundwater was conducted to investigate the impact of urbanization in the aquatic media. Water samples either from well or borehole from Fourty different sites in and around, Durgapur, West Bengal were collected for this purpose. The samples were analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for Calcium (Ca), Cobalt (Co), Chromium (Cr), Copper (Cu), Iron (Fe), Potassium (K), Magnesium (Mg), Manganese (Mn), Sodium (Na), Nickel (Ni), Lead (Pb), Zinc (Zn) content and the levels were compared with WHO specified maximum contaminant level as well as permissible limits given by the Bureau of Indian Standards (BIS). The result obtained from the present study indicates a significant risk to the population of this important emerging ‘smart city’ of eastern India. Because of the toxicity of these metals and the fact that for many tube-wells, dug-wells and bore-wells are the only sources of the water supply for a major fraction of the population in this environment. In this study, an attempt has been made to develop metal contamination risk map.

Keywords: heavy metals, ground water, maximum contamination level, ICP-MS

Procedia PDF Downloads 199

Authors: Xu Rumin, Chen Jianyi, Yue Ti, Wang Yaan

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With the rapid development of subsea oil and gas exploitation, the demand for the related underwater process equipment is increasing fast. In order to reduce the energy consuming, people tend to separate the gas and oil phase directly on the seabed. Accordingly, an advanced separator is needed. In this paper, the pressure drop of a new type of separator named Gas Liquid Cylindrical Cyclone (GLCC) which is used in the subsea system is investigated by both experiments and numerical simulation. In the experiments, the single phase flow and gas-liquid two phase flow in GLCC were tested. For the simulation, the performance of GLCC under both laboratory and industrial conditions was calculated. The Eulerian model was implemented to describe the mixture flow field in the GLCC under experimental conditions and industrial oil-natural gas conditions. Furthermore, a relationship among Euler number (Eu), Reynolds number (Re), and Froude number (Fr) is generated according to similarity analysis and simulation data, which can present the GLCC separation performance of pressure drop. These results can give reference to the design and application of GLCC in deep sea.

Keywords: dimensionless analysis, gas-liquid cylindrical cyclone, numerical simulation, pressure drop

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Authors: Imene Atek, Abed M. Affoune, Hubert Girault, Pekka Peljo

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Due to the need for a rigorous mathematical model that can help to estimate kinetic properties for soluble-insoluble systems, through voltammetric experiments, a Nicholson Semi Analytical Approach was used in this work for modeling and prediction of theoretical linear sweep voltammetry responses for reversible, quasi reversible or irreversible electron transfer reactions. The redox system of interest is a one-step metal electrodeposition process. A rigorous analysis of simulated linear scan voltammetric responses following variation of dimensionless factors, the rate constant and charge transfer coefficients in a broad range was studied and presented in the form of the so called kinetic zones diagrams. These kinetic diagrams were divided into three kinetics zones. Interpreting these zones leads to empirical mathematical models which can allow the experimenter to determine electrodeposition reactions kinetics whatever the degree of reversibility. The validity of the obtained results was tested and an excellent experiment–theory agreement has been showed.

Keywords: electrodeposition, kinetics diagrams, modeling, voltammetry

Procedia PDF Downloads 126

Authors: Christos Spandonidis, Stefanos Tsantilas, Elias Sedikos, Nektarios Galiatsatos, Fotios Giannopoulos, Panagiotis Papadopoulos, Nikolaos Demagos, Dimitrios Reppas, Christos Giordamlis

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In the present paper, a low cost, compact and modular Internet of Things (IoT) platform for air quality monitoring in urban areas is presented. This platform comprises of dedicated low cost, low power hardware and the associated embedded software that enable measurement of particles (PM2.5 and PM10), NO, CO, CO₂ and O₃ concentration in the air, along with relative temperature and humidity. This integrated platform acts as part of a greater air pollution data collecting wireless network that is able to monitor the air quality in various regions and neighborhoods of an urban area, by providing sensor measurements at a high rate that reaches up to one sample per second. It is therefore suitable for Big Data analysis applications such as air quality forecasts, weather forecasts and traffic prediction. The first real world test for the developed platform took place in Thessaloniki, Greece, where 16 devices were installed in various buildings in the city. In the near future, many more of these devices are going to be installed in the greater Thessaloniki area, giving a detailed air quality map of the city.

Keywords: distributed sensor system, environmental monitoring, Internet of Things, smart cities

Procedia PDF Downloads 129

Authors: Mirza Waseem Abbas, Syed Danish Raza

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For many countries agriculture is still the major force driving the economy and a critically important socioeconomic sector, despite exceptional industrial development across the globe. In countries like Pakistan, this sector is considered the backbone of the economy, and most of the economic decision making revolves around agricultural outputs and data. Timely and accurate facts and figures about this vital sector hold immense significance and have serious implications for the long-term development of the economy. Therefore, any significant improvements in the statistics and other forms of data regarding agriculture sector are considered important by all policymakers. This is especially true for decision making for the betterment of crops and the agriculture sector in general. Provincial and federal agricultural departments collect data for all cash and non-cash crops and the sector, in general, every year. Traditional data collection for such a large sector i.e. agriculture, being time-consuming, prone to human error and labor-intensive, is slowly but gradually being replaced by remote sensing techniques. For this study, remotely sensed data were used for change detection (machine learning, supervised & unsupervised classification) to assess the increase or decrease in area under agriculture over the last fifteen years due to urbanization. Detailed Landsat Images for the selected agricultural districts were acquired for the year 2000 and compared to images of the same area acquired for the year 2016. Observed differences validated through detailed analysis of the areas show that there was a considerable decrease in vegetation during the last fifteen years in four major agricultural districts of the Punjab province due to urbanization (housing societies).

Keywords: change detection, area estimation, machine learning, urbanization, remote sensing

Procedia PDF Downloads 235

Authors: Jadisha Cornejo, Helio Pedrini

Abstract:

Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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Authors: Stephen Orimoloye, Jose Horrillo-Caraballo, Harshinie Karunarathna, Dominic E. Reeve

Abstract:

Prediction of wave overtopping is an essential component of coastal seawall designing and management. Not only that excessive overtopping is reported for impermeable seawalls under bimodal waves, but overtopping is also showing a high sensitivity to the peakedness of the random wave propagation patterns. In the present study, we present a comprehensive analysis of the effects of peakedness of bimodal wave patterns of the overtopping of sloping seawalls. An energy-conserved bimodal spectrum with four different spectra peak periods and swell percentages was applied to estimate wave overtopping in both numerical and experimental flumes. Results of incident surface elevations and bimodal spectra were accurately captured across the flume domain using sets of well-positioned resistant-type wave gauges. Peakedness characteristics of the wave patterns were extracted to derive a relationship between the non-dimensional overtopping and the peakedness across the wave groups in the wave series. The full paper will briefly describe the development of the spectrum and present a comprehensive results analysis leading to the derivation of the relationship between dimensionless overtopping and peakedness of bimodal waves.

Keywords: wave overtopping, peakedness, bimodal waves, swell percentages

Procedia PDF Downloads 171

Authors: Shaoyi Lu

Abstract:

Background: Traditional Chinese medicine has been used to treat stroke, which is a major cause of morbidity and mortality. There is, however, no clear agreement about the optimal timing, population, efficacy, and predictive prognosis factors of traditional Chinese medicine supplemental therapy. Method: In this study, we used a retrospective analysis with data collection from stroke patients in Stroke Registry In Chang Gung Healthcare System (SRICHS). Stroke patients who received traditional Chinese medicine consultation in neurology ward of Keelung Chang Gung Memorial Hospital from Jan 2010 to Dec 2014 were enrolled. Clinical profiles including the neurologic deficit, activities of daily living and other basic characteristics were analyzed. Through propensity score matching, we compared the NIHSS and Barthel index before and after the hospitalization, and applied with subgroup analysis, and adjusted by multivariate regression method. Results: Totally 115 stroke patients were enrolled with experiment group in 23 and control group in 92. The most important factor for prognosis prediction were the scores of National Institutes of Health Stroke Scale and Barthel index right before the hospitalization. Traditional Chinese medicine intervention had no statistically significant influence on the neurological deficit of acute stroke patients, and mild negative influence on daily activity performance of acute hemorrhagic stroke patient. Conclusion: Efficacy of traditional Chinese medicine as a supplemental therapy for acute stroke patients was controversial. The reason for this phenomenon might be complex and require more research to comprehend. Key words: traditional Chinese medicine, acupuncture, Stroke, NIH stroke scale, Barthel index, predictive factor. Method: In this study, we used a retrospective analysis with data collection from stroke patients in Stroke Registry In Chang Gung Healthcare System (SRICHS). Stroke patients who received traditional Chinese medicine consultation in neurology ward of Keelung Chang Gung Memorial Hospital from Jan 2010 to Dec 2014 were enrolled. Clinical profiles including the neurologic deficit, activities of daily living and other basic characteristics were analyzed. Through propensity score matching, we compared the NIHSS and Barthel index before and after the hospitalization, and applied with subgroup analysis, and adjusted by multivariate regression method. Results: Totally 115 stroke patients were enrolled with experiment group in 23 and control group in 92. The most important factor for prognosis prediction were the scores of National Institutes of Health Stroke Scale and Barthel index right before the hospitalization. Traditional Chinese medicine intervention had no statistically significant influence on the neurological deficit of acute stroke patients, and mild negative influence on daily activity performance of acute hemorrhagic stroke patient. Conclusion: Efficacy of traditional Chinese medicine as a supplemental therapy for acute stroke patients was controversial. The reason for this phenomenon might be complex and require more research to comprehend.

Keywords: traditional Chinese medicine, complementary and alternative medicine, stroke, acupuncture

Procedia PDF Downloads 350

Authors: Nidhin Dani Abraham, T. K. Sri Shilpa

Abstract:

Asset liability management is an important aspect in banking business. Moreover, the today’s banking is based on BASEL III which strictly regulates on the counterparty default. This paper focuses on prediction and analysis of counter party default risk, which is a type of risk occurs when the customers fail to repay the amount back to the lender (bank or any financial institutions). This paper proposes an approach to reduce the counterparty risk occurring in the financial institutions using an appropriate data mining technique and thus predicts the occurrence of NPA. It also helps in asset building and restructuring quality. Liability management is very important to carry out banking business. To know and analyze the depth of liability of bank, a suitable technique is required. For that a data mining technique is being used to predict the dormant behaviour of various deposit bank customers. Various models are implemented and the results are analyzed of saving bank deposit customers. All these data are cleaned using data cleansing approach from the bank data warehouse.

Keywords: data mining, asset liability management, BASEL III, banking

Procedia PDF Downloads 535