Search results for: robotic experiments
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3441

Search results for: robotic experiments

2301 Reinforcement Learning for Classification of Low-Resolution Satellite Images

Authors: Khadija Bouzaachane, El Mahdi El Guarmah

Abstract:

The classification of low-resolution satellite images has been a worthwhile and fertile field that attracts plenty of researchers due to its importance in monitoring geographical areas. It could be used for several purposes such as disaster management, military surveillance, agricultural monitoring. The main objective of this work is to classify efficiently and accurately low-resolution satellite images by using novel technics of deep learning and reinforcement learning. The images include roads, residential areas, industrial areas, rivers, sea lakes, and vegetation. To achieve that goal, we carried out experiments on the sentinel-2 images considering both high accuracy and efficiency classification. Our proposed model achieved a 91% accuracy on the testing dataset besides a good classification for land cover. Focus on the parameter precision; we have obtained 93% for the river, 92% for residential, 97% for residential, 96% for the forest, 87% for annual crop, 84% for herbaceous vegetation, 85% for pasture, 78% highway and 100% for Sea Lake.

Keywords: classification, deep learning, reinforcement learning, satellite imagery

Procedia PDF Downloads 190
2300 Faulty Sensors Detection in Planar Array Antenna Using Pelican Optimization Algorithm

Authors: Shafqat Ullah Khan, Ammar Nasir

Abstract:

Using planar antenna array (PAA) in radars, Broadcasting, satellite antennas, and sonar for the detection of targets, Helps provide instant beam pattern control. High flexibility and Adaptability are achieved by multiple beam steering by using a Planar array and are particularly needed in real-life Sanrio’s where the need arises for several high-directivity beams. Faulty sensors in planar arrays generate asymmetry, which leads to service degradation, radiation pattern distortion, and increased levels of sidelobe. The POA, a nature-inspired optimization algorithm, accurately determines faulty sensors within an array, enhancing the reliability and performance of planar array antennas through extensive simulations and experiments. The analysis was done for different types of faults in 7 x 7 and 8 x 8 planar arrays in MATLAB.

Keywords: Planar antenna array, , Pelican optimisation Algorithm, , Faculty sensor, Antenna arrays

Procedia PDF Downloads 41
2299 The Adsorption of Zinc Metal in Waste Water Using ZnCl2 Activated Pomegranate Peel

Authors: S. N. Turkmen, A. S. Kipcak, N. Tugrul, E. M. Derun, S. Piskin

Abstract:

Activated carbon is an amorphous carbon chain which has extremely extended surface area. High surface area of activated carbon is due to the porous structure. Activated carbon, using a variety of materials such as coal and cellulosic materials; can be obtained by both physical and chemical methods. The prepared activated carbon can be used for decolorize, deodorize and also can be used for removal of organic and non-organic pollution. In this study, pomegranate peel was subjected to 800W microwave power for 1 to 4 minutes. Also fresh pomegranate peel was used for the reference material. Then ZnCl2 was used for the chemical activation purpose. After the activation process, activated pomegranate peels were used for the adsorption of Zn metal (40 ppm) in the waste water. As a result of the adsorption experiments, removal of heavy metals ranged from 89% to 85%.

Keywords: activated carbon, adsorption, chemical activation, microwave, pomegranate peel

Procedia PDF Downloads 528
2298 Contextual Toxicity Detection with Data Augmentation

Authors: Julia Ive, Lucia Specia

Abstract:

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

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

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2297 Application of the Experimental Planning Design to the Notched Precracked Tensile Fracture of Composite

Authors: N. Mahmoudi, B. Guedim

Abstract:

Composite materials have important assets compared to traditional materials. They bring many functional advantages: lightness, mechanical resistance and chemical, etc. In the present study we examine the effect of a circular central notch and a precrack on the tensile fracture of two woven composite materials. The tensile tests were applied to a standardized specimen, notched and a precracked (orientation of the crack 0°, 45°, and 90°). These tensile tests were elaborated according to an experimental planning design of the type 23.31 requiring 24 experiments with three repetitions. By the analysis of regression, we obtained a mathematical model describing the maximum load according to the influential parameters (hole diameter, precrack length, angle of a precrack orientation). The specimens precracked at 90° have a better behavior than those having a precrack at 45° and still better than those having of the precracks oriented at 0°. In addition the maximum load is inversely proportional to the notch size.

Keywords: polymer matrix, glasses, fracture, precracks

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2296 The Use of Microorganisms in the Bioleaching of Soils Polluted with Heavy Metals

Authors: I. M. Sur, A. M. Chirila-Babau, T. Gabor, V. Micle

Abstract:

This paper shows researches in order to extract Cr, Cu and Ni from the polluted soils. Research is based on preliminary studies regarding the usage of Thiobacillus ferrooxidans bacterium (9K medium) for bioleaching of soil polluted with heavy metal (Cu, Cr and Ni). The microorganisms (Thiobacillus ferooxidans) selected directly from polluted soil samples were used in this experimental work. Soil samples used in the experimental research were taken from an area polluted with heavy metals from Romania. The soil samples are subjected to the cleaning process using the 9K medium solution (20 mL and 40 mL, respectively), stirred 200 rpm for 20 hours at a controlled temperature (30 ˚C). During the experiment (0, 2, 4, 8 and 20 h), liquid samples have been extracted and analyzed using the Atomic Absorption Spectrophotometer AA-6800 (AAS) in order to determine the Cr, Cu and Ni concentration. Experiments led to the conclusion that these soils can be depolluted by bioleaching, being a biological treatment method involving the use of microorganisms to favor the extraction of Cr, Cu and Ni from polluted soils.

Keywords: bioleaching, extraction, microorganisms, soil, polluted, Thiobacillus ferooxidans

Procedia PDF Downloads 144
2295 Swimming Pool Water Chlorination Detection System Utilizing TDSTestr

Authors: Fahad Alamoudi, Yaser Miaji, Fawzy Jalalah

Abstract:

The growing popularity of swimming pools and other activities in the water for sport, fitness, therapy or just enjoyable relaxation have led to the increased use of swimming pools and the establishment of a variety of specific-use pools such as spa pools, Waterslides and more recently, hydrotherapy and wave pools. In this research a few simple equipments are used for test, Detect and alert for detection of water cleanness and pollution. YSI Photometer Systems, TDSTestr High model, rio 12HF, and Electrode A1. The researchers used electrolysis as a method of separating bonded elements and compounds by passing an electric current through them. The results which use 41 experiments show the higher the salt concentration, the more efficient the electrode and the smaller the gap between the plates and The lower the electrode voltage. Furthermore, it is proved that the larger the surface area, the lower the cell voltage and the higher current used the more chlorine produced.

Keywords: photometer, electrode, electrolysis, swimming pool chlorination

Procedia PDF Downloads 333
2294 Using Self Organizing Feature Maps for Classification in RGB Images

Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

Abstract:

Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

Procedia PDF Downloads 459
2293 Industrial Wastewater Treatment Improvements Using Limestone

Authors: Mamdouh Y. Saleh, Gaber El Enany, Medhat H. Elzahar, Moustafa H. Omran

Abstract:

The discharge limits of industrial wastewater effluents are subjected to regulations which are getting more restricted with time. A former research occurred in Port Said city studied the efficiency of treating industrial wastewater using the first stage (A-stage) of the multiple-stage plant (AB-system).From the results of this former research, the effluent treated wastewater has high rates of total dissolved solids (TDS) and chemical oxygen demand (COD). The purpose of this paper is to improve the treatment process in removing TDS and COD. So a pilot plant was constructed at wastewater pump station in the industrial area in the south of Port Said. Experimental work was divided into several groups adding powdered limestone with different dosages to wastewater, and for each group wastewater was filtered after being mixed with activated carbon. pH and TSS as variables were also studied. Significant removals of TDS and COD were observed in these experiments showing that using effective adsorbents can aid such removals to a large extent.

Keywords: adsorption, filtration, synthetic wastewater, TDS removal, COD removal

Procedia PDF Downloads 433
2292 Extrudate Swell under the Effect of Radial Flow and Intrinsic Factors to the Polymer Upstream of the Die

Authors: Hela Krir, Abdelhak Ayadi, Chedly Bradaii

Abstract:

The influence of both intrinsic factors, elastic energy and memory effect, and radial flow on the appearance and the evolution of the extrudate swelling are investigated in the present work. The experiments have been performed with linear polydimethylsiloxane (PDMS) via a capillary rheometer in which a convergent radial flow was created upstream the contraction. The correspondence between the effects of radial flow, entry elastic stored energy and memory effect is discussed. In particular, as the influence of the considered radial flow, extrudate photographs showed that when the gap ratio is reduced, the extrudate swell is lessened than what it is when radial flow geometry is not installed. Moreover, with a narrower gap, the polymer stores less energy during its passage through the die which implies a lower extrudate swelling at the outlet of the die. Results previously mentioned may be related both to shear and elongational components of radial flow.

Keywords: elastic energy, extrudate swell, memory effect, radial flow

Procedia PDF Downloads 159
2291 A Time-Varying and Non-Stationary Convolution Spectral Mixture Kernel for Gaussian Process

Authors: Kai Chen, Shuguang Cui, Feng Yin

Abstract:

Gaussian process (GP) with spectral mixture (SM) kernel demonstrates flexible non-parametric Bayesian learning ability in modeling unknown function. In this work a novel time-varying and non-stationary convolution spectral mixture (TN-CSM) kernel with a significant enhancing of interpretability by using process convolution is introduced. A way decomposing the SM component into an auto-convolution of base SM component and parameterizing it to be input dependent is outlined. Smoothly, performing a convolution between two base SM component yields a novel structure of non-stationary SM component with much better generalized expression and interpretation. The TN-CSM perfectly allows compatibility with the stationary SM kernel in terms of kernel form and spectral base ignored and confused by previous non-stationary kernels. On synthetic and real-world datatsets, experiments show the time-varying characteristics of hyper-parameters in TN-CSM and compare the learning performance of TN-CSM with popular and representative non-stationary GP.

Keywords: Gaussian process, spectral mixture, non-stationary, convolution

Procedia PDF Downloads 179
2290 Analysis of Matching Pursuit Features of EEG Signal for Mental Tasks Classification

Authors: Zin Mar Lwin

Abstract:

Brain Computer Interface (BCI) Systems have developed for people who suffer from severe motor disabilities and challenging to communicate with their environment. BCI allows them for communication by a non-muscular way. For communication between human and computer, BCI uses a type of signal called Electroencephalogram (EEG) signal which is recorded from the human„s brain by means of an electrode. The electroencephalogram (EEG) signal is an important information source for knowing brain processes for the non-invasive BCI. Translating human‟s thought, it needs to classify acquired EEG signal accurately. This paper proposed a typical EEG signal classification system which experiments the Dataset from “Purdue University.” Independent Component Analysis (ICA) method via EEGLab Tools for removing artifacts which are caused by eye blinks. For features extraction, the Time and Frequency features of non-stationary EEG signals are extracted by Matching Pursuit (MP) algorithm. The classification of one of five mental tasks is performed by Multi_Class Support Vector Machine (SVM). For SVMs, the comparisons have been carried out for both 1-against-1 and 1-against-all methods.

Keywords: BCI, EEG, ICA, SVM

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2289 Optimization of the Energy Management for a Solar System of an Agricultural Greenhouse

Authors: Nora Arbaoui, Rachid Tadili, Ilham Ihoume

Abstract:

To improve the climatic conditions and increase production in the greenhouse during the winter season under the Mediterranean climate, this thesis project proposes a design of an integrated and autonomous solar system for heating, cooling, and conservation of production in an agricultural greenhouse. To study the effectiveness of this system, experiments are conducted in two similar agricultural greenhouses oriented north-south. The first greenhouse is equipped with an active solar system integrated into the double glazing of the greenhouse’s roof, while the second greenhouse has no system, it serves as a controlled greenhouse for comparing thermal and agronomic performance The solar system allowed for an average increase in the indoor temperature of the experimental greenhouse of 6°C compared to the outdoor environment and 4°C compared to the control greenhouse. This improvement in temperature has a favorable effect on the plants' climate and subsequently positively affects their development, quality, and production.

Keywords: solar system, agricultural greenhouse, heating, cooling, storage, drying

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2288 Kinetic and Thermodynamics of Sorption of 5-Fluorouracil (5-Fl) on Carbon Nanotubes

Authors: Muhammad Imran Din

Abstract:

The aim of this study was to understand the interaction between multi-walled carbon nano tubes (MCNTs) and anticancer agents and evaluate the drug-loading ability of MCNTs. Batch adsorption experiments were carried out for adsorption of 5-Fluorouracil (5-FL) using MCNTs. The effect of various operating variables, viz., adsorbent dosage, pH, contact time and temperature for adsorption of 5-Fluorouracil (5-FL) has been studied. The Freundlich adsorption model was successfully employed to describe the adsorption process. It was found that the pseudo-second-order mechanism is predominant and the overall rate of the 5-Fluorouracil (5-FL) adsorption process appears to be controlled by the more than one-step. Thermodynamic parameters such as free energy change (ΔG°), enthalpy change (ΔH°) and entropy change (ΔS°) have been calculated respectively, revealed the spontaneous, endothermic and feasible nature of adsorption process. The results showed that carbon nano tubes were able to form supra molecular complexes with 5-Fluorouracil (5-FL) by π-π stacking and possessed favorable loading properties as drug carriers.

Keywords: drug, adsorption, anticancer, 5-Fluorouracil (5-FL)

Procedia PDF Downloads 345
2287 A Heuristic Approach for the General Flowshop Scheduling Problem to Minimize the Makespan

Authors: Mohsen Ziaee

Abstract:

Almost all existing researches on the flowshop scheduling problems focus on the permutation schedules and there is insufficient study dedicated to the general flowshop scheduling problems in the literature, since the modeling and solving of the general flowshop scheduling problems are more difficult than the permutation ones, especially for the large-size problem instances. This paper considers the general flowshop scheduling problem with the objective function of the makespan (F//Cmax). We first find the optimal solution of the problem by solving a mixed integer linear programming model. An efficient heuristic method is then presented to solve the problem. An ant colony optimization algorithm is also proposed for the problem. In order to evaluate the performance of the methods, computational experiments are designed and performed. Numerical results show that the heuristic algorithm can result in reasonable solutions with low computational effort and even achieve optimal solutions in some cases.

Keywords: scheduling, general flow shop scheduling problem, makespan, heuristic

Procedia PDF Downloads 194
2286 Mechanical Properties and Shrinkage and Expansion Assessment of Rice Husk Ash Concrete and Its Comparison with the Control Concrete

Authors: Hamed Ahmadi Moghadam, Omolbanin Arasteh Khoshbin

Abstract:

The possibility of using of rice husk ash (RHA) of Guilan (a province located in the north of Iran) (RHA) in concrete was studied by performing experiments. Mechanical properties and shrinkage and expansion of concrete containing different percentage of RHA and the control concrete consisting of cement type II were investigated. For studying, a number of cube and prism concrete specimens containing of 5 to 30% of RHA with constant water to binder ratio of 0.4 were casted and the compressive strength, tensile strength, shrinkage and expansion for water curing conditions up to 360 days were measured. The tests results show that the cement replacement of rice husk ash (RHA) caused both the quality and mechanical properties alterations. It is shown that the compressive strength, tensile strength increase also shrinkage and expansion of specimens were increased that should be controlled in mass concrete structures.

Keywords: rice husk ash, mechanical properties, shrinkage and expansion, Pozzolan

Procedia PDF Downloads 391
2285 Anaerobic Co-Digestion of Duckweed (Lemna gibba) and Waste Activated Sludge in Batch Mode

Authors: Rubia Gaur, Surindra Suthar

Abstract:

The present study investigates the anaerobic co-digestion of duckweed (Lemna gibba) and waste activated sludge (WAS) of different proportions with acclimatized anaerobic granular sludge (AAGS) as inoculum in mesophilic conditions. Batch experiments were performed in 500 mL capacity reagent bottles at 300C temperature. Varied combinations of pre-treated duckweed biomass with constant volume of anaerobic inoculum (AAGS - 100 mL) and waste activated sludge (WAS - 22.5 mL) were devised into five batch tests. The highest methane generation was observed with batch study, T4. The Gompertz model fits well on the experimental data of the batch study, T4. The values of correlation coefficient were achieved relatively higher (R2 ≥ 0.99). The co-digestion without pre-treatment of both duckweed and WAS shows poor generation of methane gas.

Keywords: aquatic weed, biogas, biomass, Gompertz equation, waste activated sludge

Procedia PDF Downloads 274
2284 Corrosion Characterization of ZA-27 Metal Matrix Composites

Authors: H. V. Jayaprakash, P. V. Krupakara

Abstract:

This paper deals with the high corrosion resistance developed by the metal matrix composites when compared with that of matrix alloy by open circuit potential test. Matrix selected is ZA-27 and reinforcement selected is red mud particulates, which is a ceramic material. The composites are prepared using liquid melt metallurgy technique using vortex method. Preheated but uncoated red mud particulates are added to the melt. Metal matrix composites containing 2, 4 and 6 weight percentage of red mud are casted. Matrix was also casted in the same way for comparison. Specimen are fabricated according to ASTM standards. The corrodents used for the tests were 0.025, 0.05 and 0.1 molar sodium hydroxide solutions. They are subjected to Open Circuit Potential studies and weight loss corrosion tests. Corrosion rate was found to be decreased with increase in exposure time in both experiments. Effect of exposure time and presence of increased percentage of reinforcement red mud is discussed in detail.

Keywords: composites, vortex, particulates, red mud

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2283 Effect of Open Burning on Soil Carbon Stock in Sugarcane Plantation in Thailand

Authors: Wilaiwan Sornpoon, Sébastien Bonnet, Savitri Garivait

Abstract:

Open burning of sugarcane fields is recognized to have a negative impact on soil by degrading its properties, especially soil organic carbon (SOC) content. Better understating the effect of open burning on soil carbon dynamics is crucial for documenting the carbon sequestration capacity of agricultural soils. In this study, experiments to investigate soil carbon stocks under burned and unburned sugarcane plantation systems in Thailand were conducted. The results showed that cultivation fields without open burning during 5 consecutive years enabled to increase the SOC content at a rate of 1.37 Mg ha-1y-1. Also it was found that sugarcane fields burning led to about 15% reduction of the total carbon stock in the 0-30 cm soil layer. The overall increase in SOC under unburned practice is mainly due to the large input of organic material through the use of sugarcane residues.

Keywords: soil organic carbon, soil inorganic carbon, carbon sequestration, open burning, sugarcane

Procedia PDF Downloads 287
2282 Open Channel Flow Measurement of Water by Using Width Contraction

Authors: Arun Goel, D. V. S. Verma, Sanjeev Sangwan

Abstract:

The present study was aimed to develop a discharge measuring device for irrigation and laboratory channels. Experiments were conducted on a sharp edged constricted flow meters having four types of width constrictions namely 2:1, 1.5:1, 1:1, and 90o in the direction of flow. These devices were made of MS sheets and installed separately in a rectangular flume. All these four devices were tested under free and submerged flow conditions. Eight different discharges varying from 2 lit/sec to 30 lit/sec were passed through each device. In total around 500 observations of upstream and downstream depths were taken in the present work. For each discharge, free submerged and critical submergence under different flow conditions were noted and plotted. Once the upstream and downstream depths of flow over any of the device are known, the discharge can be easily calculated with the help of the curves developed for free and submerged flow conditions. The device having contraction 2:1 is the most efficient one as it allows maximum critical submergence.

Keywords: flowrate, flowmeter, open channels, submergence

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2281 YBa2Cu3O7-d Nanoparticles Doped by Ferromagnetic Nanoparticles of Y3Fe5O12

Authors: Samir Khene

Abstract:

Present and future industrial uses of high critical temperature superconductors require high critical temperatures TC and strong current densities JC. These two aims constitute the two motivations of the scientific research in this domain. The most significant feature of any superconductor, from the viewpoint of uses, is the maximum electrical transport current density that this superconductor is capable of withstanding without loss of energy. In this work, vortices pinning in conventional and high-TC superconductors will be studied. Our experiments on vortices pinning in single crystals and nanoparticles of YBa2Cu3O7- and La1.85 Sr0.15CuO will be presented. It will be given special attention to the study of the YBa2Cu3O7- nanoparticles doped by ferromagnetic nanoparticles of Y3Fe5O12. The ferromagnetism and superconductivity coexistence in this compound will be demonstrated, and the influence of these ferromagnetic nanoparticles on the variations of the critical current density JC in YBa2Cu3O7- nanoparticles as a function of applied field H and temperature T will be studied.

Keywords: ferromagnetism, superconductivity, coexistence, magnetic material

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2280 Investigation Acute Toxicity and Bioaccumulation Mineral Mercury in Rutilus frisii Kutum

Authors: A. Gharaei, R. Karami

Abstract:

Rutilus frisii Kutum was exposed to various concentrations of mercuric chloride in water to determine its acute toxicity and bioaccumulation. We carried out ten treatments with three replicates and one control for each of the chemicals using the static O. E. C. D. method in 55-liter-tanks each containing 14 fingerlings. During the experiments, the average pH was recorded as 7.8, total hardness was measured to be 255 mg/l, the average water temperature was 27±1 degrees centigrade and dissolved oxygen was 7.2 mg/l. Mean LC50 values of Hgcl2 for juvenile R. frisii kutum with mean weight 1±0.2 gr were 0.102 and 0.86 mgHg/l at 24h and 96h, respectively. The bioaccumulation values during 24h in tissue, kidney, and gill were 1.55, 16.1, and 22.7 mgHg/l, respectively. So, these values during 96h were 2.8, 16.8, and 26.65 mgHg/l, respectively. The bioconcentration factors in tissue, kidney, and gill during 24h were 14.75, 153.39, and 216.11 and so during 96h were 33.8, 198.1, and 313.5 times. These results show that bioaccumulation was highest in the gill and then kidney and tissue, respectively. This study suggested that between mercury concentrations of water with bioaccumulation in tissue more than kidney and gill.

Keywords: HgCl2, LC5096h, bioaccumulation, Rutilus frisii Kutum, Caspian Sea

Procedia PDF Downloads 550
2279 Analysis of Information Sharing and Capacity Constraint on Backlog Bullwhip Effect in Two Level Supply Chain

Authors: Matloub Hussaina

Abstract:

This paper investigates the impact of information sharing and capacity constraints on backlog bullwhip effect of Automatic Pipe Line Inventory and Order Based Production Control System (APIOBPCS). System dynamic simulation using iThink Software has been applied. It has been found that smooth ordering by Tier 1 can be achieved when Tier 1 has medium capacity constraints. Simulation experiments also show that information sharing helps to reduce 50% of backlog bullwhip effect in capacitated supply chains. This knowledge is of value per se, giving supply chain operations managers and designers a practical way in to controlling the backlog bullwhip effect. Future work should investigate the total cost implications of capacity constraints and safety stocks in multi-echelon supply chain.

Keywords: supply chain dynamics, information sharing, capacity constraints, simulation, APIOBPCS

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2278 Flexible Design of Triboelectric Nanogenerators for Efficient Vibration Energy Harvesting

Authors: Meriam Khelifa

Abstract:

In recent years, many studies have focused on the harvesting of the vibrations energy to produce electrical energy using contact separation (CS) triboelectric nanogenerators (TENG). The simplest design for a TENG consists of a capacitor comprising a single moving electrode. The conversion efficiency of vibration energy into electrical energy can, in principle, reach 100%. But to actually achieve this objective, it is necessary to optimize the parameters of the TENG, such as the dielectric constant and the thickness of the insulator, the load resistance, etc. In particular, the use of a switch which is actioned at optimal times within the TENG cycle is essential. Using numerical modeling and experimental design, we applied a methodology to find the TENG parameters which optimize the energy transfer efficiency (ETE) to almost 100% for any vibration frequency and amplitude. The rather simple design of a TENG is promising as an environment friendly device. It opens the doors for harvesting acoustic vibrations from the environment and to design effective protection against environmental noise.

Keywords: vibrations, CS TENG, efficiency, design of experiments

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2277 Measurement of Coal Fineness, Air Fuel Ratio, and Fuel Weight Distribution in a Vertical Spindle Mill’s Pulverized Fuel Pipes at Classifier Vane 40%

Authors: Jayasiler Kunasagaram

Abstract:

In power generation, coal fineness is crucial to maintain flame stability, ensure combustion efficiency, and lower emissions to the environment. In order for the pulverized coal to react effectively in the boiler furnace, the size of coal particles needs to be at least 70% finer than 74 μm. This paper presents the experiment results of coal fineness, air fuel ratio and fuel weight distribution in pulverized fuel pipes at classifier vane 40%. The aim of this experiment is to extract the pulverized coal is kinetically and investigate the data accordingly. Dirty air velocity, coal sample extraction, and coal sieving experiments were performed to measure coal fineness. The experiment results show that required coal fineness can be achieved at 40 % classifier vane. However, this does not surpass the desired value by a great margin.

Keywords: coal power, emissions, isokinetic sampling, power generation

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2276 Lipschitz Classifiers Ensembles: Usage for Classification of Target Events in C-OTDR Monitoring Systems

Authors: Andrey V. Timofeev

Abstract:

This paper introduces an original method for guaranteed estimation of the accuracy of an ensemble of Lipschitz classifiers. The solution was obtained as a finite closed set of alternative hypotheses, which contains an object of classification with a probability of not less than the specified value. Thus, the classification is represented by a set of hypothetical classes. In this case, the smaller the cardinality of the discrete set of hypothetical classes is, the higher is the classification accuracy. Experiments have shown that if the cardinality of the classifiers ensemble is increased then the cardinality of this set of hypothetical classes is reduced. The problem of the guaranteed estimation of the accuracy of an ensemble of Lipschitz classifiers is relevant in the multichannel classification of target events in C-OTDR monitoring systems. Results of suggested approach practical usage to accuracy control in C-OTDR monitoring systems are present.

Keywords: Lipschitz classifiers, confidence set, C-OTDR monitoring, classifiers accuracy, classifiers ensemble

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2275 Event Extraction, Analysis, and Event Linking

Authors: Anam Alam, Rahim Jamaluddin Kanji

Abstract:

With the rapid growth of event in everywhere, event extraction has now become an important matter to retrieve the information from the unstructured data. One of the challenging problems is to extract the event from it. An event is an observable occurrence of interaction among entities. The paper investigates the effectiveness of event extraction capabilities of three software tools that are Wandora, Nitro and SPSS. We performed standard text mining techniques of these tools on the data sets of (i) Afghan War Diaries (AWD collection), (ii) MUC4 and (iii) WebKB. Information retrieval measures such as precision and recall which are computed under extensive set of experiments for Event Extraction. The experimental study analyzes the difference between events extracted by the software and human. This approach helps to construct an algorithm that will be applied for different machine learning methods.

Keywords: event extraction, Wandora, nitro, SPSS, event analysis, extraction method, AFG, Afghan War Diaries, MUC4, 4 universities, dataset, algorithm, precision, recall, evaluation

Procedia PDF Downloads 574
2274 Adaptive Few-Shot Deep Metric Learning

Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

Abstract:

Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

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2273 Numerical Simulation of the Flow around Wing-In-Ground Effect (WIG) Craft

Authors: A. Elbatran, Y. Ahmed, A. Radwan, M. Ishak

Abstract:

The use of WIG craft is representing an ambitious technology that will support in reducing time, effort, and money of the conventional marine transportation in the future. This paper investigates the aerodynamic characteristic of compound wing-in-ground effect (WIG) craft model. Drag coefficient, lift coefficient and Lift and drag ratio were studied numerically with respect to the ground clearance and the wing angle of attack. The modifications of the wing has been done in order to investigate the most suitable wing configuration that can increase the wing lift-to-drag ratio at low ground clearance. A numerical investigation was carried out in this research work using finite volume Reynolds-Averaged Navier-Stokes Equations (RANSE) code ANSYS CFX, Validation was carried out by using experiments. The experimental and the numerical results concluded that the lift to drag ratio decreased with the increasing of the ground clearance.

Keywords: drag Coefficient, ground clearance, navier-stokes, WIG

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2272 Collision Theory Based Sentiment Detection Using Discourse Analysis in Hadoop

Authors: Anuta Mukherjee, Saswati Mukherjee

Abstract:

Data is growing everyday. Social networking sites such as Twitter are becoming an integral part of our daily lives, contributing a large increase in the growth of data. It is a rich source especially for sentiment detection or mining since people often express honest opinion through tweets. However, although sentiment analysis is a well-researched topic in text, this analysis using Twitter data poses additional challenges since these are unstructured data with abbreviations and without a strict grammatical correctness. We have employed collision theory to achieve sentiment analysis in Twitter data. We have also incorporated discourse analysis in the collision theory based model to detect accurate sentiment from tweets. We have also used the retweet field to assign weights to certain tweets and obtained the overall weightage of a topic provided in the form of a query. Hadoop has been exploited for speed. Our experiments show effective results.

Keywords: sentiment analysis, twitter, collision theory, discourse analysis

Procedia PDF Downloads 514