Search results for: artificial kidney
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2377

Search results for: artificial kidney

787 Hydro-Gravimetric Ann Model for Prediction of Groundwater Level

Authors: Jayanta Kumar Ghosh, Swastik Sunil Goriwale, Himangshu Sarkar

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Groundwater is one of the most valuable natural resources that society consumes for its domestic, industrial, and agricultural water supply. Its bulk and indiscriminate consumption affects the groundwater resource. Often, it has been found that the groundwater recharge rate is much lower than its demand. Thus, to maintain water and food security, it is necessary to monitor and management of groundwater storage. However, it is challenging to estimate groundwater storage (GWS) by making use of existing hydrological models. To overcome the difficulties, machine learning (ML) models are being introduced for the evaluation of groundwater level (GWL). Thus, the objective of this research work is to develop an ML-based model for the prediction of GWL. This objective has been realized through the development of an artificial neural network (ANN) model based on hydro-gravimetry. The model has been developed using training samples from field observations spread over 8 months. The developed model has been tested for the prediction of GWL in an observation well. The root means square error (RMSE) for the test samples has been found to be 0.390 meters. Thus, it can be concluded that the hydro-gravimetric-based ANN model can be used for the prediction of GWL. However, to improve the accuracy, more hydro-gravimetric parameter/s may be considered and tested in future.

Keywords: machine learning, hydro-gravimetry, ground water level, predictive model

Procedia PDF Downloads 109
786 Raising Test of English for International Communication (TOEIC) Scores through Purpose-Driven Vocabulary Acquisition

Authors: Edward Sarich, Jack Ryan

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In contrast to learning new vocabulary incidentally in one’s first language, foreign language vocabulary is often acquired purposefully, because a lack of natural exposure requires it to be studied in an artificial environment. It follows then that foreign language vocabulary may be more efficiently acquired if it is purpose-driven, or linked to a clear and desirable outcome. The research described in this paper relates to the early stages of what is seen as a long-term effort to measure the effectiveness of a methodology for purpose-driven foreign language vocabulary instruction, specifically by analyzing whether directed studying from high-frequency vocabulary lists leads to an improvement in Test of English for International Communication (TOEIC) scores. The research was carried out in two sections of a first-year university English composition class at a small university in Japan. The results seem to indicate that purposeful study from relevant high-frequency vocabulary lists can contribute to raising TOEIC scores and that the test preparation methodology used in this study was thought by students to be beneficial in helping them to prepare to take this high-stakes test.

Keywords: corpus vocabulary, language asssessment, second language vocabulary acquisition, TOEIC test preparation

Procedia PDF Downloads 129
785 [Keynote Talk]: Analysis of Intelligent Based Fault Tolerant Capability System for Solar Photovoltaic Energy Conversion

Authors: Albert Alexander Stonier

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Due to the fossil fuel exhaustion and environmental pollution, renewable energy sources especially solar photovoltaic system plays a predominant role in providing energy to the consumers. It has been estimated that by 2050 the renewable energy sources will satisfy 50% of the total energy requirement of the world. In this context, the faults in the conversion process require a special attention which is considered as a major problem. A fault which remains even for a few seconds will cause undesirable effects to the system. The presentation comprises of the analysis, causes, effects and mitigation methods of various faults occurring in the entire solar photovoltaic energy conversion process. In order to overcome the faults in the system, an intelligent based artificial neural networks and fuzzy logic are proposed which can significantly mitigate the faults. Hence the presentation intends to find the problem in renewable energy and provides the possible solution to overcome it with simulation and experimental results. The work performed in a 3kWp solar photovoltaic plant whose results cites the improvement in reliability, availability, power quality and fault tolerant ability.

Keywords: solar photovoltaic, power electronics, power quality, PWM

Procedia PDF Downloads 262
784 Data Clustering in Wireless Sensor Network Implemented on Self-Organization Feature Map (SOFM) Neural Network

Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

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Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

Procedia PDF Downloads 493
783 Analysis of Cyber Activities of Potential Business Customers Using Neo4j Graph Databases

Authors: Suglo Tohari Luri

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Data analysis is an important aspect of business performance. With the application of artificial intelligence within databases, selecting a suitable database engine for an application design is also very crucial for business data analysis. The application of business intelligence (BI) software into some relational databases such as Neo4j has proved highly effective in terms of customer data analysis. Yet what remains of great concern is the fact that not all business organizations have the neo4j business intelligence software applications to implement for customer data analysis. Further, those with the BI software lack personnel with the requisite expertise to use it effectively with the neo4j database. The purpose of this research is to demonstrate how the Neo4j program code alone can be applied for the analysis of e-commerce website customer visits. As the neo4j database engine is optimized for handling and managing data relationships with the capability of building high performance and scalable systems to handle connected data nodes, it will ensure that business owners who advertise their products at websites using neo4j as a database are able to determine the number of visitors so as to know which products are visited at routine intervals for the necessary decision making. It will also help in knowing the best customer segments in relation to specific goods so as to place more emphasis on their advertisement on the said websites.

Keywords: data, engine, intelligence, customer, neo4j, database

Procedia PDF Downloads 181
782 A Neural Network Model to Simulate Urban Air Temperatures in Toulouse, France

Authors: Hiba Hamdi, Thomas Corpetti, Laure Roupioz, Xavier Briottet

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Air temperatures are generally higher in cities than in their rural surroundings. The overheating of cities is a direct consequence of increasing urbanization, characterized by the artificial filling of soils, the release of anthropogenic heat, and the complexity of urban geometry. This phenomenon, referred to as urban heat island (UHI), is more prevalent during heat waves, which have increased in frequency and intensity in recent years. In the context of global warming and urban population growth, helping urban planners implement UHI mitigation and adaptation strategies is critical. In practice, the study of UHI requires air temperature information at the street canyon level, which is difficult to obtain. Many urban air temperature simulation models have been proposed (mostly based on physics or statistics), all of which require a variety of input parameters related to urban morphology, land use, material properties, or meteorological conditions. In this paper, we build and evaluate a neural network model based on Urban Weather Generator (UWG) model simulations and data from meteorological stations that simulate air temperature over Toulouse, France, on days favourable to UHI.

Keywords: air temperature, neural network model, urban heat island, urban weather generator

Procedia PDF Downloads 63
781 Ochratoxin-A in Traditional Meat Products from Croatian Households

Authors: Jelka Pleadin, Nina Kudumija, Ana Vulic, Manuela Zadravec, Tina Lesic, Mario Skrivanko, Irena Perkovic, Nada Vahcic

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Products of animal origin, such as meat and meat products, can contribute to human mycotoxins’ intake coming as a result of either indirect transfer from farm animals exposed to naturally contaminated grains and feed (carry-over effects) or direct contamination with moulds or naturally contaminated spice mixtures used in meat production. Ochratoxin A (OTA) is mycotoxin considered to be of the outermost importance from the public health standpoint in connection with meat products. The aim of this study was to investigate the occurrence of OTA in different traditional meat products circulating on Croatian markets during 2018, produced by a large number of households situated in eastern and north Croatian regions using a variety of technologies. Concentrations of OTA were determined in traditional meat products (n = 70), including dry fermented sausages (Slavonian kulen, Slavonian sausage, Istrian sausage and domestic sausage; n = 28), dry-cured meat products (pancetta, pork rack and ham; n = 22) and cooked sausages (liver sausages, black pudding sausages and pate; n = 20). OTA was analyzed by use of quantitative screening immunoassay method (ELISA) and confirmed for positive samples (higher than the limit of detection) by liquid chromatography tandem mass spectrometry (LC-MS/MS) method. Whereas the bacon samples contaminated with OTA were not found, its level in dry fermented sausages ranged from 0.22 to 2.17 µg/kg and in dry-cured meat products from 0.47 to 5.35 µg/kg, with in total 9% of positive samples. Besides possible primary contamination of these products arising due to improper manufacturing or/and storage conditions, observed OTA contamination could also be the consequence of secondary contamination that comes as a result of contaminated feed the animals were fed on. OTA levels obtained in cooked sausages ranged from 0.32 to 4.12 µg/kg (5% of positives) and could probably be linked to the contaminated raw materials (liver, kidney and spices) used in the sausages production. The results showed an occasional OTA contamination of traditional meat products, pointing that to avoid such contamination on households these products should be produced and processed under standardized and well-controlled conditions. Further investigations should be performed in order to identify mycotoxin-producing moulds on the surface of the products and to define preventative measures that can reduce the contamination of traditional meat products during their production on households and period of storage.

Keywords: Croatian households, ochratoxin-A, traditional cooked sausages, traditional dry-cured meat products

Procedia PDF Downloads 171
780 Active Space Debris Removal by Extreme Ultraviolet Radiation

Authors: A. Anandha Selvan, B. Malarvizhi

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In recent year the problem of space debris have become very serious. The mass of the artificial objects in orbit increased quite steadily at the rate of about 145 metric tons annually, leading to a total tally of approximately 7000 metric tons. Now most of space debris object orbiting in LEO region about 97%. The catastrophic collision can be mostly occurred in LEO region, where this collision generate the new debris. Thus, we propose a concept for cleaning the space debris in the region of thermosphere by passing the Extreme Ultraviolet (EUV) radiation to in front of space debris object from the re-orbiter. So in our concept the Extreme Ultraviolet (EUV) radiation will create the thermosphere expansion by reacting with atmospheric gas particles. So the drag is produced in front of the space debris object by thermosphere expansion. This drag force is high enough to slow down the space debris object’s relative velocity. Therefore the space debris object gradually reducing the altitude and finally enter into the earth’s atmosphere. After the first target is removed, the re-orbiter can be goes into next target. This method remove the space debris object without catching debris object. Thus it can be applied to a wide range of debris object without regard to their shapes or rotation. This paper discusses the operation of re-orbiter for removing the space debris in thermosphere region.

Keywords: active space debris removal, space debris, LEO, extreme ultraviolet, re-orbiter, thermosphere

Procedia PDF Downloads 443
779 Chemical Pollution of Water: Waste Water, Sewage Water, and Pollutant Water

Authors: Nabiyeva Jamala

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We divide water into drinking, mineral, industrial, technical and thermal-energetic types according to its use and purpose. Drinking water must comply with sanitary requirements and norms according to organoleptic devices and physical and chemical properties. Mineral water - must comply with the norms due to some components having therapeutic properties. Industrial water must fulfill its normative requirements by being used in the industrial field. Technical water should be suitable for use in the field of agriculture, household, and irrigation, and the normative requirements should be met. Heat-energy water is used in the national economy, and it consists of thermal and energy water. Water is a filter-accumulator of all types of pollutants entering the environment. This is explained by the fact that it has the property of dissolving compounds of mineral and gaseous water and regular water circulation. Environmentally clean, pure, non-toxic water is vital for the normal life activity of humans, animals and other living beings. Chemical pollutants enter water basins mainly with wastewater from non-ferrous and ferrous metallurgy, oil, gas, chemical, stone, coal, pulp and paper and forest materials processing industries and make them unusable. Wastewater from the chemical, electric power, woodworking and machine-building industries plays a huge role in the pollution of water sources. Chlorine compounds, phenols, and chloride-containing substances have a strong lethal-toxic effect on organisms when mixed with water. Heavy metals - lead, cadmium, mercury, nickel, copper, selenium, chromium, tin, etc. water mixed with ingredients cause poisoning in humans, animals and other living beings. Thus, the mixing of selenium with water causes liver diseases in people, the mixing of mercury with the nervous system, and the mixing of cadmium with kidney diseases. Pollution of the World's ocean waters and other water basins with oil and oil products is one of the most dangerous environmental problems facing humanity today. So, mixing even the smallest amount of oil and its products in drinking water gives it a bad, unpleasant smell. Mixing one ton of oil with water creates a special layer that covers the water surface in an area of 2.6 km2. As a result, the flood of light, photosynthesis and oxygen supply of water is getting weak and there is a great danger to the lives of living beings.

Keywords: chemical pollutants, wastewater, SSAM, polyacrylamide

Procedia PDF Downloads 56
778 Hydroxyapatite from Biowaste for the Reinforcement of Polymer

Authors: John O. Akindoyo, M. D. H. Beg, Suriati Binti Ghazali, Nitthiyah Jeyaratnam

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Regeneration of bone due to the many health challenges arising from traumatic effects of bone loss, bone tumours and other bone infections is fast becoming indispensable. Over the period of time, some approaches have been undertaken to mitigate this challenge. This includes but not limited to xenografts, allografts, autografts as well as artificial substitutions like bioceramics, synthetic cements and metals. However, most of these techniques often come along with peculiar limitation and problems such as morbidity, availability, disease transmission, collateral site damage or absolute rejection by the body as the case may be. Hydroxyapatite (HA) is very compatible and suitable for this application. However, most of the common methods for HA synthesis are expensive and environmentally unfriendly. Extraction of HA from bio-wastes have been perceived not only to be cost effective, but also environment-friendly. In this research, HA was produced from bio-waste: namely bovine bones through a combination of hydrothermal chemical processes and ordinary calcination techniques. Structure and property of the HA was carried out through different characterization techniques (such as TGA, FTIR, DSC, XRD and BET). The synthesized HA was found to possess similar properties to stoichiometric HA with highly desirable thermal, degradation, structural and porous properties. This material is unique for its potential minimal cost, environmental friendliness and property controllability. It is also perceived to be suitable for tissue and bone engineering applications.

Keywords: biomaterial, biopolymer, bone, hydroxyapatite

Procedia PDF Downloads 306
777 Investigating Best Strategies Towards Creating Alternative Assessment in Literature

Authors: Sandhya Rao Mehta

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As ChatGpt and other Artificial Intelligence (AI) forms are becoming part of our regular academic world, the consequences are being gradually discussed. The extent to which an essay written by a student is itself of any value if it has been downloaded by some form of AI is perhaps central to this discourse. A larger question is whether writing should be taught as an academic skill at all. In literature classrooms, this has major consequences as writing a traditional paper is still the single most preferred form of assessment. This study suggests that it is imperative to investigate alternative forms of assessment in literature, not only because the existing forms can be written by AI, but in a larger sense, students are increasingly skeptical of the purpose of such work. The extent to which an essay actually helps the students professionally is a question that academia has not yet answered. This paper suggests that using real-world tasks like creating podcasts, video tutorials, and websites is a far better way to evaluate students' critical thinking and application of ideas, as well as to develop digital skills which are important to their future careers. Using the example of a course in literature, this study will examine the possibilities and challenges of creating digital projects as a way of confronting the complexities of student evaluation in the future. The study is based on a specific university English as a Foreign Language (EFL) context.

Keywords: assessment, literature, digital humanities, chatgpt

Procedia PDF Downloads 68
776 Integration of Artificial Neural Network with Geoinformatics Technology to Predict Land Surface Temperature within Sun City Jodhpur, Rajasthan, India

Authors: Avinash Kumar Ranjan, Akash Anand

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The Land Surface Temperature (LST) is an essential factor accompanying to rise urban heat and climate warming within a city in micro level. It is also playing crucial role in global change study as well as radiation budgets measuring in heat balance studies. The information of LST is very substantial to recognize the urban climatology, ecological changes, anthropological and environmental interactions etc. The Chief motivation of present study focus on time series of ANN model that taken a sequence of LST values of 2000, 2008 and 2016, realize the pattern of variation within the data set and predict the LST values for 2024 and 2032. The novelty of this study centers on evaluation of LST using series of multi-temporal MODIS (MOD 11A2) satellite data by Maximum Value Composite (MVC) techniques. The results derived from this study endorse the proficiency of Geoinformatics Technology with integration of ANN to gain knowledge, understanding and building of precise forecast from the complex physical world database. This study will also focus on influence of Land Use/ Land Cover (LU/LC) variation on Land Surface Temperature.

Keywords: LST, geoinformatics technology, ANN, MODIS satellite imagery, MVC

Procedia PDF Downloads 224
775 Regional Anesthesia in Carotid Surgery: A Single Center Experience

Authors: Daniel Thompson, Muhammad Peerbux, Sophie Cerutti, Hansraj Riteesh Bookun

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Patients with carotid stenosis, which may be asymptomatic or symptomatic in the form of transient ischaemic attack (TIA), amaurosis fugax, or stroke, often require an endarterectomy to reduce stroke risk. Risks of this procedure include stroke, death, myocardial infarction, and cranial nerve damage. Carotid endarterectomy is most commonly performed under general anaesthetic, however, it can also be undertaken with a regional anaesthetic approach. Our tertiary centre generally performs carotid endarterectomy under regional anaesthetic. Our major tertiary hospital mostly utilises regional anaesthesia for carotid endarterectomy. We completed a cross-sectional analysis of all cases of carotid endarterectomy performed under regional anaesthesia across a 10-year period between January 2010 to March 2020 at our institution. 350 patients were included in this descriptive analysis, and demographic details for patients, indications for surgery, procedural details, length of surgery, and complications were collected. Data was cross tabulated and presented in frequency tables to describe these categorical variables. 263 of the 350 patients in the analysis were male, with a mean age of 71 ± 9. 172 patients had a history of ischaemic heart disease, 104 had diabetes mellitus, 318 had hypertension, and 17 patients had chronic kidney disease greater than Stage 3. 13.1% (46 patients) were current smokers, and the majority (63%) were ex-smokers. Most commonly, carotid endarterectomy was performed conventionally with patch arterioplasty 96% of the time (337 patients). The most common indication was TIA and stroke in 64% of patients, 18.9% were classified as asymptomatic, and 13.7% had amaurosis fugax. There were few general complications, with 9 wound complications/infections, 7 postoperative haematomas requiring return to theatre, 3 myocardial infarctions, 3 arrhythmias, 1 exacerbation of congestive heart failure, 1 chest infection, and 1 urinary tract infection. Specific complications to carotid endarterectomy included 3 strokes, 1 postoperative TIA, and 1 cerebral bleed. There were no deaths in our cohort. This analysis of a large cohort of patients from a major tertiary centre who underwent carotid endarterectomy under regional anaesthesia indicates the safety of such an approach for these patients. Regional anaesthesia holds the promise of less general respiratory and cardiac events compared to general anaesthesia, and in this vulnerable patient group, calls for comparative research between local and general anaesthesia in carotid surgery.

Keywords: anaesthesia, carotid endarterectomy, stroke, carotid stenosis

Procedia PDF Downloads 99
774 A Method for False Alarm Recognition Based on Multi-Classification Support Vector Machine

Authors: Weiwei Cui, Dejian Lin, Leigang Zhang, Yao Wang, Zheng Sun, Lianfeng Li

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Built-in test (BIT) is an important technology in testability field, and it is widely used in state monitoring and fault diagnosis. With the improvement of modern equipment performance and complexity, the scope of BIT becomes larger, and it leads to the emergence of false alarm problem. The false alarm makes the health assessment unstable, and it reduces the effectiveness of BIT. The conventional false alarm suppression methods such as repeated test and majority voting cannot meet the requirement for a complicated system, and the intelligence algorithms such as artificial neural networks (ANN) are widely studied and used. However, false alarm has a very low frequency and small sample, yet a method based on ANN requires a large size of training sample. To recognize the false alarm, we propose a method based on multi-classification support vector machine (SVM) in this paper. Firstly, we divide the state of a system into three states: healthy, false-alarm, and faulty. Then we use multi-classification with '1 vs 1' policy to train and recognize the state of a system. Finally, an example of fault injection system is taken to verify the effectiveness of the proposed method by comparing ANN. The result shows that the method is reasonable and effective.

Keywords: false alarm, fault diagnosis, SVM, k-means, BIT

Procedia PDF Downloads 136
773 Effect of Be, Zr, and Heat Treatment on Mechanical Behavior of Cast Al-Mg-Zn-Cu Alloys (7075)

Authors: Mahmoud M. Tash

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The present study was undertaken to investigate the effect of aging parameters (time and temperature) on the mechanical properties of Be-and/or Zr- treated Al-Mg-Zn (7075) alloys. Ultimate tensile strength, 0.5% offset yield strength and % elongation measurements were carried out on specimens prepared from cast and heat treated 7075 alloys containing Be and/or Zr. Different aging treatment were carried out for the as solution treated (SHT) specimens. The specimens were aged at different conditions; Natural and artificial aging was carried out at room temperature, 120C, 150C, 180C and 220C for different periods of time. Duplex aging was performed for SHT conditions (pre-aged at different time and temperature followed by high temperature aging). Ultimate tensile strength, yield strength and % elongation data results as a function of different aging parameters are analysed. A statistical design of experiments (DOE) approach using fractional factorial design is applied to acquire an understanding of the effects of these variables and their interactions on the mechanical properties of Be- and/or Zr- treated 7075 alloys. Mathematical models are developed to relate the alloy mechanical properties with the different aging parameters.

Keywords: casting aging treatment, mechanical properties, Al-Mg-Zn alloys, Be- and/or Zr-treatment, experimental correlation

Procedia PDF Downloads 350
772 Inverse Heat Conduction Analysis of Cooling on Run-Out Tables

Authors: M. S. Gadala, Khaled Ahmed, Elasadig Mahdi

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In this paper, we introduced a gradient-based inverse solver to obtain the missing boundary conditions based on the readings of internal thermocouples. The results show that the method is very sensitive to measurement errors, and becomes unstable when small time steps are used. The artificial neural networks are shown to be capable of capturing the whole thermal history on the run-out table, but are not very effective in restoring the detailed behavior of the boundary conditions. Also, they behave poorly in nonlinear cases and where the boundary condition profile is different. GA and PSO are more effective in finding a detailed representation of the time-varying boundary conditions, as well as in nonlinear cases. However, their convergence takes longer. A variation of the basic PSO, called CRPSO, showed the best performance among the three versions. Also, PSO proved to be effective in handling noisy data, especially when its performance parameters were tuned. An increase in the self-confidence parameter was also found to be effective, as it increased the global search capabilities of the algorithm. RPSO was the most effective variation in dealing with noise, closely followed by CRPSO. The latter variation is recommended for inverse heat conduction problems, as it combines the efficiency and effectiveness required by these problems.

Keywords: inverse analysis, function specification, neural net works, particle swarm, run-out table

Procedia PDF Downloads 220
771 Gas Lift Optimization Using Smart Gas Lift Valve

Authors: Mohamed A. G. H. Abdalsadig, Amir Nourian, G. G. Nasr, M. Babaie

Abstract:

Gas lift is one of the most common forms of artificial lift, particularly for offshore wells because of its relative down hole simplicity, flexibility, reliability, and ability to operate over a large range of rates and occupy very little space at the well head. Presently, petroleum industry is investing in exploration and development fields in offshore locations where oil and gas wells are being drilled thousands of feet below the ocean in high pressure and temperature conditions. Therefore, gas-lifted oil wells are capable of failure through gas lift valves which are considered as the heart of the gas lift system for controlling the amount of the gas inside the tubing string. The gas injection rate through gas lift valve must be controlled to be sufficient to obtain and maintain critical flow, also, gas lift valves must be designed not only to allow gas passage through it and prevent oil passage, but also for gas injection into wells to be started and stopped when needed. In this paper, smart gas lift valve has been used to investigate the effect of the valve port size, depth of injection and vertical lift performance on well productivity; all these aspects have been investigated using PROSPER simulator program coupled with experimental data. The results show that by using smart gas lift valve, the gas injection rate can be controlled which leads to improved flow performance.

Keywords: Effect of gas lift valve port size, effect water cut, vertical flow performance

Procedia PDF Downloads 277
770 Incidence of Fungal Infections and Mycotoxicosis in Pork Meat and Pork By-Products in Egyptian Markets

Authors: Ashraf Samir Hakim, Randa Mohamed Alarousy

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The consumption of food contaminated with molds (microscopic filamentous fungi) and their toxic metabolites results in the development of food-borne mycotoxicosis. The spores of molds are ubiquitously spread in the environment and can be detected everywhere. Ochratoxin A is a potentially carcinogenic fungal toxin found in a variety of food commodities , not only is considered the most abundant and hence the most commonly detected member but also is the most toxic one.Ochratoxin A is the most abundant and hence the most commonly detected member, but is also the most toxic of the three. A very limited research works concerning foods of porcine origin in Egypt were obtained in spite of presence a considerable swine population and consumers. In this study, the quality of various ready-to-eat local and imported pork meat and meat byproducts sold in Egyptian markets as well as edible organs as liver and kidney were assessed for the presence of various molds and their toxins as a raw material. Mycological analysis was conducted on (n=110) samples which included pig livers n=10 and kidneys n=10 from the Basateen slaughter house; local n=70 and 20 imported processed pork meat byproducts.The isolates were identified using traditional mycological and biochemical tests while, Ochratoxin A levels were quantitatively analyzed using the high performance liquid. Results of conventional mycological tests for detecting the presence of fungal growth (yeasts or molds) were negative, while the results of mycotoxins concentrations were be greatly above the permiceable limits or "tolerable weekly intake" (TWI) of ochratoxin A established by EFSA in 2006 in local pork and pork byproducts while the imported samples showed a very slightly increasing.Since ochratoxin A is stable and generally resistant to heat and processing, control of ochratoxin A contamination lies in the control of the growth of the toxin-producing fungi. Effective prevention of ochratoxin A contamination therefore depends on good farming and agricultural practices. Good Agricultural Practices (GAP) including methods to reduce fungal infection and growth during harvest, storage, transport and processing provide the primary line of defense against contamination with ochratoxin A. To the best of our knowledge this is the first report of mycological assessment, especially the mycotoxins in pork byproducts in Egypt.

Keywords: Egyptian markets, mycotoxicosis, ochratoxin A, pork meat, pork by-products

Procedia PDF Downloads 450
769 Challenges Facing Farmers in the Governorate of Al-Baha, Saudi Arabia

Authors: Mohammed Alghamdi, Ghanem Al-Ghamdi

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The Governorate of Al-Baha is known for a history of farming that focused on plant products such as Date Palm, olives, figs, pomegranate and cereals as well as raising cattle, sheep, goats and to some extent camels for many decades. However, farmers have been facing with very significant natural and artificial challenges lately. The goal of this study was to determine the most significant challenges facing farmers in the Governorate of Al-Baha. Sixty farms were surveyed during the year of 2013. Farm survey focused on the farm management, farm financial status and governmental support. Our results showed that most farms were dedicated to farming with limited number of farms used parts of its premises for recreation. About 90% of farms were engaged in exclusively farming business. The financial status was good in most of the farms (80%), stable in 16% and hardly standing in less than 5%. Nearly 60% of the farms marketed 1-3 products and 23% marketed up to 6 products, 14% of the farms marketed up to 9 products and 4% marketed more than 9 products. Less than 14% had a chance to market their products over seven times per year while about 11% market their products and 32% of farms market 3-4 per year and 43% of farms market 1-2 per year. Our data showed that most farmers are in good financial status producing healthy food.

Keywords: farming system, Al-Baha, healthy food, Saudi Arabia

Procedia PDF Downloads 259
768 Data Augmentation for Automatic Graphical User Interface Generation Based on Generative Adversarial Network

Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

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As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

Procedia PDF Downloads 166
767 The Prevalence of Obesity among a Huge Sample of 5-20 Years Old Jordanian Children and Adolescents Based on CDC Criteria

Authors: Walid Al-Qerem, Ruba Zumot

Abstract:

Background: The rise of obesity among children and adolescents remains a primary challenge for healthcare providers globally and in the Middle East. The aim of the present study is to determine the prevalence of obesity among 5-20 years old Jordanians based on CDC criteria. Method: A total of 5722 Jordanians (37% males; 63% females) aged 5-20 years data were retrieved from the Jordanian Ministry of Health electronic database (Hakeem). As per the CDC selection criteria, the chosen data pertains exclusively to healthy Jordanian children and adolescents who are medically sound, not suffering from health conditions, and not undergoing any treatments that could hinder normal growth patterns, such as severe infection, chronic kidney disease (CKD), Down’s syndrome, attention deficit hyperactivity disorder, cancer, heart disease, lung disease, cystic fibrosis, Crohn’s disease, type 1 diabetes, hormonal disturbances, any stress-related conditions, hormonal therapy such as corticosteroids, Growth hormones (GHS) or gonadotropin-releasing hormone agonists, insulin, and amphetamines or any other stimulants. In addition, participants with missing or invalid data values for anthropometric measurements were excluded from the study. Weight for age and body mass index for age were analyzed comparatively for Jordanian children and adolescents against the international growth standards. The Z-score for each record was computed based on CDC equations. As per CDC classifications, BMI for age percentiles, values ≥85th and < 95th are classified as overweight, and value at ≥ 95th is classified as obesity. Results: The average age of the evaluated sample was 12.33 ±4.39 years (10.79 ±3.39 for males and 13.23 ± 4.66 for females). The mean weight for males and females were 33.16±14.17 Kg and 133.54±17.17 cm for males, 43.86 ±18.82 Kg, and 142.19±18.35 for females, while for BMI the mean was for boys and girls 17.81±3.88 and 20.52±5.03 respectively. The results indicated that based on CDC criteria, 8.9% of males were classified as children/adolescents with overweight, and 9.7% were classified as children/adolescents with obesity, while in females, 17.8% were classified as children/adolescents with overweight and 10.2% were classified as children/adolescents with obesity. Discussion: The high prevalence of obesity reported in the present study emphasizes the importance of applying different strategies to prevent childhood obesity, including encouraging physical activity, promoting healthier food options, and behavioral changes. Conclusion: The results presented in this study indicated the high prevalence of overweight/obesity among Jordanian adolescents and children, which must be tagged by healthcare planners and providers.

Keywords: CDC, obesity, childhood, Jordan

Procedia PDF Downloads 38
766 Adopting Flocks of Birds Approach to Predator for Anomalies Detection on Industrial Control Systems

Authors: M. Okeke, A. Blyth

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Industrial Control Systems (ICS) such as Supervisory Control And Data Acquisition (SCADA) can be seen in many different critical infrastructures, from nuclear management to utility, medical equipment, power, waste and engine management on ships and planes. The role SCADA plays in critical infrastructure has resulted in a call to secure them. Many lives depend on it for daily activities and the attack vectors are becoming more sophisticated. Hence, the security of ICS is vital as malfunction of it might result in huge risk. This paper describes how the application of Prey Predator (PP) approach in flocks of birds could enhance the detection of malicious activities on ICS. The PP approach explains how these animals in groups or flocks detect predators by following some simple rules. They are not necessarily very intelligent animals but their approach in solving complex issues such as detection through corporation, coordination and communication worth emulating. This paper will emulate flocking behavior seen in birds in detecting predators. The PP approach will adopt six nearest bird approach in detecting any predator. Their local and global bests are based on the individual detection as well as group detection. The PP algorithm was designed following MapReduce methodology that follows a Split Detection Convergence (SDC) approach.

Keywords: artificial life, industrial control system (ICS), IDS, prey predator (PP), SCADA, SDC

Procedia PDF Downloads 284
765 Effects of Cuminum cyminum L. Essential Oil Supplementation on Components of Metabolic Syndrome: A Clinical Trial

Authors: Ashti Morovati, Hushyar Azari, Bahram Pourghassem Gargari

Abstract:

Objectives and goals: The prevalence of metabolic syndrome (MetS), as a major health burden for societies, is increasing. This clinical trial was conducted to evaluate the effects of CuEO supplementation on anthropometric indices, systolic and diastolic blood pressure, blood glucose level, insulin resistance and serum lipid level in patients suffering from MetS. Methods: This was a randomized, triple‐blind, placebo‐controlled clinical trial in which 56 patients with MetS aged 18–60 years who fulfilled the eligibility criteria were randomly allocated to an intervention or a control group. Inclusion criteria for the study were comprised of diagnosis of MetS according to the new International Federation of Diabetes. The exclusion criteria were defined as: taking herbal supplements, use of drugs having evident interaction with cumin such as anti‐depressant drugs, vitamin D, omega 3, selenium, zinc, smoking, pregnancy, or breastfeeding, suffering from cancer, having any history of gastrointestinal and hepatic, cardiovascular, thyroid and kidney disorders, and menopause. 75 mg CuEO or placebo soft gels were administered three times daily to the participants for eight weeks. The soft gel consumption was checked by asking the participants to bring the medication containers in the follow‐up visits at the 4th and the 8th weeks of the study. Data pertaining to blood pressure, height, weight, waist circumference, hip circumference and BMI, as well as food consumption were collected at the beginning and end of the study. Fasting blood samples ( glucose, triglyceride, total cholesterol, HDL-cholesterol and LDL-cholesterol) were obtained and biochemical measurements were assessed at the beginning and end of the study. Results: At eight weeks, a total of 44 patients completed this study. Except for diastolic blood pressure (DBP), the other assessed variables were not significantly different between the two groups. In intra group analysis, placebo and CuEO groups both had insignificant decrements in DBP (mean difference [MD] with 95% CI: −3.31 [−7.11, 0.47] and −1.77 [−5.95, 2.40] mmHg, respectively). However, DBP was significantly lower in CuEO compared with the placebo group at the end of study (81.41 ± 5.88 vs. 84.09 ± 5.54 mmHg, MD with 95% CI: −3.98 [−7.60, −0.35] mmHg, p < .05). Conclusions: The results of this study indicated that CuEO does not have any effect on MetS components, except for DBP in patients with MetS.

Keywords: blood pressure, fasting blood glucose, lipid profile, waist circumference

Procedia PDF Downloads 136
764 Convolutional Neural Network and LSTM Applied to Abnormal Behaviour Detection from Highway Footage

Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

Abstract:

Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

Procedia PDF Downloads 143
763 Acoustic Analysis for Comparison and Identification of Normal and Disguised Speech of Individuals

Authors: Surbhi Mathur, J. M. Vyas

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Although the rapid development of forensic speaker recognition technology has been conducted, there are still many problems to be solved. The biggest problem arises when the cases involving disguised voice samples come across for the purpose of examination and identification. Such type of voice samples of anonymous callers is frequently encountered in crimes involving kidnapping, blackmailing, hoax extortion and many more, where the speaker makes a deliberate effort to manipulate their natural voice in order to conceal their identity due to the fear of being caught. Voice disguise causes serious damage to the natural vocal parameters of the speakers and thus complicates the process of identification. The sole objective of this doctoral project is to find out the possibility of rendering definite opinions in cases involving disguised speech by experimentally determining the effects of different disguise forms on personal identification and percentage rate of speaker recognition for various voice disguise techniques such as raised pitch, lower pitch, increased nasality, covering the mouth, constricting tract, obstacle in mouth etc by analyzing and comparing the amount of phonetic and acoustic variation in of artificial (disguised) and natural sample of an individual, by auditory as well as spectrographic analysis.

Keywords: forensic, speaker recognition, voice, speech, disguise, identification

Procedia PDF Downloads 349
762 Thermographic Tests of Curved GFRP Structures with Delaminations: Numerical Modelling vs. Experimental Validation

Authors: P. D. Pastuszak

Abstract:

The present work is devoted to thermographic studies of curved composite panels (unidirectional GFRP) with subsurface defects. Various artificial defects, created by inserting PTFE stripe between individual layers of a laminate during manufacturing stage are studied. The analysis is conducted both with the use finite element method and experiments. To simulate transient heat transfer in 3D model with embedded various defect sizes, the ANSYS package is used. Pulsed Thermography combined with optical excitation source provides good results for flat surfaces. Composite structures are mostly used in complex components, e.g., pipes, corners and stiffeners. Local decrease of mechanical properties in these regions can have significant influence on strength decrease of the entire structure. Application of active procedures of thermography to defect detection and evaluation in this type of elements seems to be more appropriate that other NDT techniques. Nevertheless, there are various uncertainties connected with correct interpretation of acquired data. In this paper, important factors concerning Infrared Thermography measurements of curved surfaces in the form of cylindrical panels are considered. In addition, temperature effects on the surface resulting from complex geometry and embedded and real defect are also presented.

Keywords: active thermography, composite, curved structures, defects

Procedia PDF Downloads 306
761 Optimization of Culture Conditions of Paecilomyces Tenuipes, Entomopathogenic Fungi Inoculated into the Silkworm Larva, Bombyx Mori

Authors: Sung-Hee Nam, Kwang-Gill Lee, You-Young Jo, HaeYong Kweon

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Entomopathogenic fungi is a Cordyceps species that is isolated from dead silkworm and cicada. Fungi on cicadas were described in old Chinese medicinal books and From ancient times, vegetable wasps and plant worms were widely known to have active substance and have been studied for pharmacological use. Among many fungi belonging to the genus Cordyceps, Cordyceps sinensis have been demonstrated to yield natural products possessing various biological activities and many bioactive components. Generally, It is commonly used to replenish the kidney and soothe the lung, and for the treatment of fatigue. Due to their commercial and economic importance, the demand for Cordyceps has been rapidly increased. However, a supply of Cordyceps specimen could not meet the increasing demand because of their sole dependence on field collection and habitat destruction. Because it is difficult to obtain many insect hosts in nature and the edibility of host insect needs to be verified in a pharmacological aspect. Recently, this setback was overcome that P. tenuipes was able to be cultivated in a large scale using silkworm as host. Pharmacological effects of P. tenuipes cultured on silkworm such as strengthening immune function, anti-fatigue, anti-tumor activity and controlling liver etc have been proved. They are widely commercialized. In this study, we attempted to establish a method for stable growth inhibition of P. tenuipes on silkworm hosts and an optimal condition for synnemata formation. To determine optimum culturing conditions, temperature and light conditions were varied. The length and number of synnemata was highest at 25℃ temperature and 100~300 lux illumination. On an average, the synnemata of wild P. tenuipes measures 70 ㎜ in length and 20 in number; those of the cultured strain were relatively shorter and more in number. The number of synnemata may have increased as a result of inoculating the host with highly concentrated conidia, while the length may have decreased due to limited nutrition per individual. It is not able that changes in light illumination cause morphological variations in the synnemata. However, regulation of only light and temperature could not produce stromata like perithecia, asci, and ascospores. Yamanaka reported that although a complete fruiting body can be produced under optimal culture conditions, it should be regarded as synnemata because it does not develop into an ascoma bearing ascospores.

Keywords: paecilomyces tenuipes, entomopathogenic fungi, silkworm larva, bombyx mori

Procedia PDF Downloads 309
760 Modeling of Daily Global Solar Radiation Using Ann Techniques: A Case of Study

Authors: Said Benkaciali, Mourad Haddadi, Abdallah Khellaf, Kacem Gairaa, Mawloud Guermoui

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In this study, many experiments were carried out to assess the influence of the input parameters on the performance of multilayer perceptron which is one the configuration of the artificial neural networks. To estimate the daily global solar radiation on the horizontal surface, we have developed some models by using seven combinations of twelve meteorological and geographical input parameters collected from a radiometric station installed at Ghardaïa city (southern of Algeria). For selecting of best combination which provides a good accuracy, six statistical formulas (or statistical indicators) have been evaluated, such as the root mean square errors, mean absolute errors, correlation coefficient, and determination coefficient. We noted that multilayer perceptron techniques have the best performance, except when the sunshine duration parameter is not included in the input variables. The maximum of determination coefficient and correlation coefficient are equal to 98.20 and 99.11%. On the other hand, some empirical models were developed to compare their performances with those of multilayer perceptron neural networks. Results obtained show that the neural networks techniques give the best performance compared to the empirical models.

Keywords: empirical models, multilayer perceptron neural network, solar radiation, statistical formulas

Procedia PDF Downloads 325
759 Breeding Biology and Induced Breeding Status of Freshwater Mud Eel, Monopterus cuchia

Authors: Faruque Miah, Hafij Ali, Enaya Jannat, Tanmoy Modok Shuvra, M. Niamul Naser

Abstract:

In this study, breeding biology and induced breeding of freshwater mud eel, Monopterus cuchia was observed during the experimental period from February to June, 2013. Breeding biology of freshwater mud eel, Monopterus cuchia was considered in terms of gonadosomatic index, length-weight relationship of gonad, ova diameter and fecundity. The ova diameter was recorded from 0.3 mm to 4.30 mm and the individual fecundity was recorded from 155 to 1495 while relative fecundity was found from 2.64 to 12.45. The fecundity related to body weight and length of fish was also discussed. A peak of GSI was observed 2.14±0.2 in male and 5.1 ±1.09 in female. Induced breeding of freshwater mud eel, Monopterus cuchia was also practiced with different doses of different inducing agents like pituitary gland (PG), human chorionic gonadotropin (HCG), Gonadotropin releasing hormone (GnRH) and Ovuline-a synthetic hormone in different environmental conditions. However, it was observed that the artificial breeding of freshwater mud eel, Monopterus cuchia was not yet succeeded through inducing agents in captive conditions, rather the inducing agent showed negative impacts on fecundity and ovarian tissues. It was seen that mature eggs in the oviduct were reduced, absorbed and some eggs were found in spoiled condition.

Keywords: breeding biology, induced breeding, Monopterus cuchia, human chorionic gonadotropin

Procedia PDF Downloads 755
758 Study of the Phenomenon Nature of Order and Disorder in BaMn(Fe/V)F7 Fluoride Glass by the Hybrid Reverse Monte Carlo Method

Authors: Sidi Mohamed Mesli, Mohamed Habchi, Mohamed Kotbi, Rafik Benallal, Abdelali Derouiche

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Fluoride glasses with a nominal composition of BaMnMF7 (M = FeV assuming isomorphous replacement) have been structurally modelled through the simultaneous simulation of their neutron diffraction patterns by a reverse Monte Carlo (RMC) model and by a Rietveld for disordered materials (RDM) method. Model is consistent with an expected network of interconnected [MF6] polyhedra. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term in acceptance criteria. This method is called the Hybrid Reverse Monte Carlo (HRMC) method. The idea of this paper is to apply the (HRMC) method to the title glasses, in order to make a study of the phenomenon nature of order and disorder by displaying and discussing the partial pair distribution functions (PDFs) g(r). We suggest that this method can be used to describe average correlations between components of fluoride glass or similar system.

Keywords: fluoride glasses, RMC simulation, neutron scattering, hybrid RMC simulation, Lennard-Jones potential, partial pair distribution functions

Procedia PDF Downloads 502