Search results for: edge detection algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7215

Search results for: edge detection algorithm

2505 Analysis of Automotive Sensor for Engine Knock System

Authors: Miroslav Gutten, Jozef Jurcik, Daniel Korenciak, Milan Sebok, Matej Kuceraa

Abstract:

This paper deals with the phenomenon of the undesirable detonation combustion in internal combustion engines. A control unit of the engine monitors these detonations using piezoelectric knock sensors. With the control of these sensors the detonations can be objectively measured just outside the car. If this component provides small amplitude of the output voltage it could happen that there would have been in the areas of the engine ignition combustion. The paper deals with the design of a simple device for the detection of this disorder. A construction of the testing device for the knock sensor suitable for diagnostics of knock combustion in internal combustion engines will be presented. The output signal of presented sensor will be described by Bessel functions. Using the first voltage extremes on the characteristics it is possible to create a reference for the evaluation of the polynomial residue. It should be taken into account that the velocity of sound in air is 330 m/s. This sound impinges on the walls of the combustion chamber and is detected by the sensor. The resonant frequency of the clicking of the motor is usually in the range from 5 kHz to 15 kHz. The sensor worked in the field to 37 kHz, which shall be taken into account on an own sensor resonance.

Keywords: diagnostics, knock sensor, measurement, testing device

Procedia PDF Downloads 447
2504 Early Detection of Kidney Failure by Using a Distinct Technique for Sweat Analysis

Authors: Saba. T. Suliman, Alaa. H. Osman, Sara. T. Ahmed, Zeinab. A. Mustafa, Akram. I. Omara, Banazier. A. Ibraheem

Abstract:

Diagnosis by sweat is one of the emerging methods whereby sweat can identify many diseases in the human body. Sweat contains many elements that help in the diagnostic process. In this research, we analyzed sweat samples by using a Colorimeter device to identify the disease of kidney failure in its various stages. This analysis is a non-invasive method where the sample is collected from outside the body, and then this sample is analyzed. Urea refers to the disease of kidney failure when its quantity is high in the blood and then in the sweat, and by experience, we found that the amount of urea for males differs from its quantity for females, where there is a noticeable increase for males in normal and pathological cases. In this research, we took many samples from a normal group that does not suffer from renal failure and another who suffers from the disease to compare the percentage of urea, and after analysis, we found that the urea percentage is high in people with kidney failure disease. with an accuracy of results of 85%.

Keywords: sweat analysis, kidney failure, urea, non-invasive, eccrine glands, mineral composition, sweat test

Procedia PDF Downloads 43
2503 Radical Web Text Classification Using a Composite-Based Approach

Authors: Kolade Olawande Owoeye, George R. S. Weir

Abstract:

The widespread of terrorism and extremism activities on the internet has become a major threat to the government and national securities due to their potential dangers which have necessitated the need for intelligence gathering via web and real-time monitoring of potential websites for extremist activities. However, the manual classification for such contents is practically difficult or time-consuming. In response to this challenge, an automated classification system called composite technique was developed. This is a computational framework that explores the combination of both semantics and syntactic features of textual contents of a web. We implemented the framework on a set of extremist webpages dataset that has been subjected to the manual classification process. Therein, we developed a classification model on the data using J48 decision algorithm, this is to generate a measure of how well each page can be classified into their appropriate classes. The classification result obtained from our method when compared with other states of arts, indicated a 96% success rate in classifying overall webpages when matched against the manual classification.

Keywords: extremist, web pages, classification, semantics, posit

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2502 Multiclass Analysis of Pharmaceuticals in Fish and Shrimp Tissues by High-Performance Liquid Chromatography-Tandem Mass Spectrometry

Authors: Reza Pashaei, Reda Dzingelevičienė

Abstract:

An efficient, reliable, and sensitive multiclass analytical method has been expanded to simultaneously determine 15 human pharmaceutical residues in fish and shrimp tissue samples by ultra-high-performance liquid chromatography-tandem mass spectrometry. The investigated compounds comprise ten classes, namely analgesic, antibacterial, anticonvulsant, cardiovascular, fluoroquinolones, macrolides, nonsteroidal anti-inflammatory, penicillins, stimulant, and sulfonamide. A simple liquid extraction procedure based on 0.1% formic acid in methanol was developed. Chromatographic conditions were optimized, and mobile phase namely 0.1 % ammonium acetate (A), and acetonitrile (B): 0 – 2 min, 15% B; 2 – 5 min, linear to 95% B; 5 – 10 min, 95% B; and 10 – 12 min was obtained. Limits of detection and quantification ranged from 0.017 to 1.371 μg/kg and 0.051 to 4.113 μg/kg, respectively. Finally, amoxicillin, azithromycin, caffeine, carbamazepine, ciprofloxacin, clarithromycin, diclofenac, erythromycin, furosemide, ibuprofen, ketoprofen, naproxen, sulfamethoxazole, tetracycline, and triclosan were quantifiable in fish and shrimp samples.

Keywords: fish, liquid chromatography, mass spectrometry, pharmaceuticals, shrimp, solid-phase extraction

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2501 An Activatable Prodrug for the Treatment of Metastatic Tumors

Authors: Eun-Joong Kim, Sankarprasad Bhuniya, Hyunseung Lee, Hyun Min Kim, Chaejoon Cheong, Su-khendu Maiti, Kwan Soo Hong, Jong Seung Kim

Abstract:

Metastatic cancers have historically been difficult to treat. However, metastatic tumors have been found to have high levels of reactive oxygen species such as hydrogen peroxide (H2O2), supporting the hypothesis that a prodrug could be activated by intracellular H2O2 and lead to a potential anti-metastatic therapy. In this study, prodrug 7 was designed to be activated by H2O2-mediated boronate oxidation, resulting in activation of the fluorophore for detection and release of the therapeutic agent, SN-38. Drug release from prodrug 7 was investigated by monitoring fluorescence after addition of H2O2 to the cancer cells. Prodrug 7 activated by H2O2 selectively inhibited tumor cell growth. Furthermore, intratracheally administered prodrug 7 showed effective anti-tumor activity in a mouse model of metastatic lung disease. Thus, this H2O2-responsive prodrug has therapeutic potential as a novel treatment for metastatic cancer via cellular imaging with fluorescence as well as selective release of the anti-cancer drug, SN-38.

Keywords: hydrogen peroxide, prodrug, metastatic tumors, fluorescence

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2500 Intelligent Production Machine

Authors: A. Şahinoğlu, R. Gürbüz, A. Güllü, M. Karhan

Abstract:

This study in production machines, it is aimed that machine will automatically perceive cutting data and alter cutting parameters. The two most important parameters have to be checked in machine control unit are progress feed rate and speeds. These parameters are aimed to be controlled by sounds of machine. Optimum sound’s features introduced to computer. During process, real time data is received and converted by Matlab software. Data is converted into numerical values. According to them progress and speeds decreases/increases at a certain rate and thus optimum sound is acquired. Cutting process is made in respect of optimum cutting parameters. During chip remove progress, features of cutting tools, kind of cut material, cutting parameters and used machine; affects on various parameters. Instead of required parameters need to be measured such as temperature, vibration, and tool wear that emerged during cutting process; detailed analysis of the sound emerged during cutting process will provide detection of various data that included in the cutting process by the much more easy and economic way. The relation between cutting parameters and sound is being identified.

Keywords: cutting process, sound processing, intelligent late, sound analysis

Procedia PDF Downloads 334
2499 Mesoporous Carbon Ceramic SiO2/C Prepared by Sol-Gel Method and Modified with Cobalt Phthalocyanine and Used as an Electrochemical Sensor for Nitrite

Authors: Abdur Rahim, Lauro Tatsuo Kubota, Yoshitaka Gushikem

Abstract:

Carbon ceramic mesoporous SiO2/50wt%C (SBET= 170 m2g-1), where C is graphite, was prepared by the sol gel method. Scanning electron microscopy images and the respective element mapping showed that, within the magnification used, no phase segregation was detectable. It presented the electric conductivities of 0.49 S cm-1. This material was used to support cobalt phthalocyanine, prepared in situ, to assure a homogeneous dispersion of the electro active complex in the pores of the matrix. The surface density of cobalt phthalocyanine, on the matrix surfaces was 0.015 mol cm-2. Pressed disk, made with SiO2/50wt%C/CoPc, was used to fabricate an electrode and tested as sensors for nitrite determination by electro chemical technique. A linear response range between 0.039 and 0.42 mmol l−1,and correlation coefficient r=0.9996 was obtained. The electrode was chemically very stable and presented very high sensitivity for this analyte, with a limit of detection, LOD = 1.087 x 10-6 mol L-1.

Keywords: SiO2/C/CoPc, sol-gel method, electrochemical sensor, nitrite oxidation, carbon ceramic material, cobalt phthalocyanine

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2498 Optical Characterization of Transition Metal Ion Doped ZnO Microspheres Synthesized via Laser Ablation in Air

Authors: Parvathy Anitha, Nilesh J. Vasa, M. S. Ramachandra Rao

Abstract:

ZnO is a semiconducting material with a direct wide band gap of 3.37 eV and a large exciton binding energy of 60 meV at room temperature. Microspheres with high sphericity and symmetry exhibit unique functionalities which makes them excellent omnidirectional optical resonators. Hence there is an advent interest in fabrication of single crystalline semiconductor microspheres especially magnetic ZnO microspheres, as ZnO is a promising material for semiconductor device applications. Also, ZnO is non-toxic and biocompatible, implying it is a potential material for biomedical applications. Room temperature Photoluminescence (PL) spectra of the fabricated ZnO microspheres were measured, at an excitation wavelength of 325 nm. The ultraviolet (UV) luminescence observed is attributed to the room-temperature free exciton related near-band-edge (NBE) emission in ZnO. Besides the NBE luminescence, weak and broad visible luminescence (~560nm) was also observed. This broad emission band in the visible range is associated with oxygen vacancies related to structural defects. In transition metal (TM) ion-doped ZnO, 3d levels emissions of TM ions will modify the inherent characteristic emissions of ZnO. A micron-sized ZnO crystal has generally a wurtzite structure with a natural hexagonal cross section, which will serve as a WGM (whispering gallery mode) lasing micro cavity due to its high refractive index (~2.2). But hexagonal cavities suffers more optical loss at their corners in comparison to spherical structures; hence spheres may be a better candidate to achieve effective light confinement. In our study, highly smooth spherical shaped micro particles with different diameters ranging from ~4 to 6 μm were grown on different substrates. SEM (Scanning Electron Microscopy) and AFM (Atomic Force Microscopy) images show the presence of uniform smooth surfaced spheres. Raman scattering measurements from the fabricated samples at 488 nm light excitation provide convincing supports for the wurtzite structure of the prepared ZnO microspheres. WGM lasing studies from TM-doped ZnO microparticles are in progress.

Keywords: laser ablation, microcavity, photoluminescence, ZnO microsphere

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2497 A Vision-Based Early Warning System to Prevent Elephant-Train Collisions

Authors: Shanaka Gunasekara, Maleen Jayasuriya, Nalin Harischandra, Lilantha Samaranayake, Gamini Dissanayake

Abstract:

One serious facet of the worsening Human-Elephant conflict (HEC) in nations such as Sri Lanka involves elephant-train collisions. Endangered Asian elephants are maimed or killed during such accidents, which also often result in orphaned or disabled elephants, contributing to the phenomenon of lone elephants. These lone elephants are found to be more likely to attack villages and showcase aggressive behaviour, which further exacerbates the overall HEC. Furthermore, Railway Services incur significant financial losses and disruptions to services annually due to such accidents. Most elephant-train collisions occur due to a lack of adequate reaction time. This is due to the significant stopping distance requirements of trains, as the full braking force needs to be avoided to minimise the risk of derailment. Thus, poor driver visibility at sharp turns, nighttime operation, and poor weather conditions are often contributing factors to this problem. Initial investigations also indicate that most collisions occur in localised “hotspots” where elephant pathways/corridors intersect with railway tracks that border grazing land and watering holes. Taking these factors into consideration, this work proposes the leveraging of recent developments in Convolutional Neural Network (CNN) technology to detect elephants using an RGB/infrared capable camera around known hotspots along the railway track. The CNN was trained using a curated dataset of elephants collected on field visits to elephant sanctuaries and wildlife parks in Sri Lanka. With this vision-based detection system at its core, a prototype unit of an early warning system was designed and tested. This weatherised and waterproofed unit consists of a Reolink security camera which provides a wide field of view and range, an Nvidia Jetson Xavier computing unit, a rechargeable battery, and a solar panel for self-sufficient functioning. The prototype unit was designed to be a low-cost, low-power and small footprint device that can be mounted on infrastructures such as poles or trees. If an elephant is detected, an early warning message is communicated to the train driver using the GSM network. A mobile app for this purpose was also designed to ensure that the warning is clearly communicated. A centralized control station manages and communicates all information through the train station network to ensure coordination among important stakeholders. Initial results indicate that detection accuracy is sufficient under varying lighting situations, provided comprehensive training datasets that represent a wide range of challenging conditions are available. The overall hardware prototype was shown to be robust and reliable. We envision a network of such units may help contribute to reducing the problem of elephant-train collisions and has the potential to act as an important surveillance mechanism in dealing with the broader issue of human-elephant conflicts.

Keywords: computer vision, deep learning, human-elephant conflict, wildlife early warning technology

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2496 Real-Time Nonintrusive Heart Rate Measurement: Comparative Case Study of LED Sensorics' Accuracy and Benefits in Heart Monitoring

Authors: Goran Begović

Abstract:

In recent years, many researchers are focusing on non-intrusive measuring methods when it comes to human biosignals. These methods provide solutions for everyday use, whether it’s health monitoring or finessing the workout routine. One of the biggest issues with these solutions is that the sensors’ accuracy is highly variable due to many factors, such as ambiental light, skin color diversity, etc. That is why we wanted to explore different outcomes under those kinds of circumstances in order to find the most optimal algorithm(s) for extracting heart rate (HR) information. The optimization of such algorithms can benefit the wider, cheaper, and safer application of home health monitoring, without having to visit medical professionals as often when it comes to observing heart irregularities. In this study, we explored the accuracy of infrared (IR), red, and green LED sensorics in a controlled environment and compared the results with a medically accurate ECG monitoring device.

Keywords: data science, ECG, heart rate, holter monitor, LED sensors

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2495 Elongation Factor 1 Alpha Molecular Phylogenetic Analysis for Anastrepha fraterculus Complex

Authors: Pratibha Srivastava, Ayyamperumal Jeyaprakash, Gary Steck

Abstract:

Exotic, invasive tephritid fruit flies (Diptera: Tephritidae) are a major concern to fruit and vegetable production in the USA. Timely detection and identification of these agricultural pests facilitate the possibility of eradication from newly invaded areas. They spread primarily as larvae in infested fruits carried in commerce or personal baggage. Identification of larval stages to species level is difficult but necessary to determine pest loads and their pathways into the USA. The main focus of this study is the New World genus, Anastrepha. Many of its constituent taxa are pests of major economic importance. This study is significant for national quarantine use, as morphological diagnostics to separate larvae of the various members remain poorly developed. Elongation factor 1 alpha sequences were amplified from Anastrepha fraterculus specimens collected from South America (Ecuador and Peru). Phylogenetic analysis was performed to characterize the Anastrepha fraterculus complex at a molecular level.

Keywords: anastrepha, diptera, elongation factor, fruit fly

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2494 The Functions of “Question” and Its Role in Education Process: Quranic Approach

Authors: Sara Tusian, Zahra Salehi Motaahed, Narges Sajjadie, Nikoo Dialame

Abstract:

One of the methods which have frequently been used in Quran is the “question”. In the Quran, in addition to the content, methods are also important. Using analysis-interpretation method, the present study has investigated Quranic questions, and extracted its functions from educational perspective. In so doing, it has first investigated all the questions in Quran and then taking the three-stage classification of education into account, it has offered question functions. The results obtained from this study suggest that question functions in Quran are presented in three categories: the preparation stage (including preparation of the audience, revising the insights, and internal Evolution); main body (including the granting the insight, and elimination of intellectual negligence and the question of innate and logical axioms, the introducting of the realm of thinking, creating emotional arousal and alleged in the claim) and the third stage as modification and revision (including invitation to move in the framework of tasks using the individual beliefs to reveal the contradictions and, Error detection and contribution to change the function) that each of which has a special role in the education process.

Keywords: education, question, Quranic questions, Quran

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2493 Exploring Valproic Acid (VPA) Analogues Interactions with HDAC8 Involved in VPA Mediated Teratogenicity: A Toxicoinformatics Analysis

Authors: Sakshi Piplani, Ajit Kumar

Abstract:

Valproic acid (VPA) is the first synthetic therapeutic agent used to treat epileptic disorders, which account for affecting nearly 1% world population. Teratogenicity caused by VPA has prompted the search for next generation drug with better efficacy and lower side effects. Recent studies have posed HDAC8 as direct target of VPA that causes the teratogenic effect in foetus. We have employed molecular dynamics (MD) and docking simulations to understand the binding mode of VPA and their analogues onto HDAC8. A total of twenty 3D-structures of human HDAC8 isoforms were selected using BLAST-P search against PDB. Multiple sequence alignment was carried out using ClustalW and PDB-3F07 having least missing and mutated regions was selected for study. The missing residues of loop region were constructed using MODELLER and energy was minimized. A set of 216 structural analogues (>90% identity) of VPA were obtained from Pubchem and ZINC database and their energy was optimized with Chemsketch software using 3-D CHARMM-type force field. Four major neurotransmitters (GABAt, SSADH, α-KGDH, GAD) involved in anticonvulsant activity were docked with VPA and its analogues. Out of 216 analogues, 75 were selected on the basis of lower binding energy and inhibition constant as compared to VPA, thus predicted to have anti-convulsant activity. Selected hHDAC8 structure was then subjected to MD Simulation using licenced version YASARA with AMBER99SB force field. The structure was solvated in rectangular box of TIP3P. The simulation was carried out with periodic boundary conditions and electrostatic interactions and treated with Particle mesh Ewald algorithm. pH of system was set to 7.4, temperature 323K and pressure 1atm respectively. Simulation snapshots were stored every 25ps. The MD simulation was carried out for 20ns and pdb file of HDAC8 structure was saved every 2ns. The structures were analysed using castP and UCSF Chimera and most stabilized structure (20ns) was used for docking study. Molecular docking of 75 selected VPA-analogues with PDB-3F07 was performed using AUTODOCK4.2.6. Lamarckian Genetic Algorithm was used to generate conformations of docked ligand and structure. The docking study revealed that VPA and its analogues have more affinity towards ‘hydrophobic active site channel’, due to its hydrophobic properties and allows VPA and their analogues to take part in van der Waal interactions with TYR24, HIS42, VAL41, TYR20, SER138, TRP137 while TRP137 and SER138 showed hydrogen bonding interaction with VPA-analogues. 14 analogues showed better binding affinity than VPA. ADMET SAR server was used to predict the ADMET properties of selected VPA analogues for predicting their druggability. On the basis of ADMET screening, 09 molecules were selected and are being used for in-vivo evaluation using Danio rerio model.

Keywords: HDAC8, docking, molecular dynamics simulation, valproic acid

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2492 Impact of Masonry Joints on Detection of Humidity Distribution in Aerated Concrete Masonry Constructions by Electric Impedance Spectrometry Measurements

Authors: Sanita Rubene, Martins Vilnitis, Juris Noviks

Abstract:

Aerated concrete is a load bearing construction material, which has high heat insulation parameters. Walls can be erected from aerated concrete masonry constructions and in perfect circumstances additional heat insulation is not required. The most common problem in aerated concrete heat insulation properties is the humidity distribution throughout the cross section of the masonry elements as well as proper and conducted drying process of the aerated concrete construction because only dry aerated concrete masonry constructions can reach high heat insulation parameters. In order to monitor drying process of the masonry and detect humidity distribution throughout the cross section of aerated concrete masonry construction application of electrical impedance spectrometry is applied. Further test results and methodology of this non-destructive testing method is described in this paper.

Keywords: aerated concrete, electrical impedance spectrometry, humidity distribution, non-destructive testing

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2491 Systematic NIR of Internal Disorder and Quality Detection of Apple Fruit

Authors: Eid Alharbi, Yaser Miaji, Saeed Alzahrani

Abstract:

The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic convener belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300 nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950 nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950 nm region the online sorting system was constructed.

Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology

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2490 Application of Fuzzy Logic in Voltage Regulation of Radial Feeder with Distributed Generators

Authors: Anubhav Shrivastava, Lakshya Bhat, Shivarudraswamy

Abstract:

Distributed Generation is the need of the hour. With current advancements in the DG technology, there are some major issues that need to be tackled in order to make this method of generation of energy more efficient and feasible. Among other problems, the control in voltage is the major issue that needs to be addressed. This paper focuses on control of voltage using reactive power control of DGs with the help of fuzzy logic. The membership functions have been defined accordingly and the control of the system is achieved. Finally, with the help of simulation results in Matlab, the control of voltage within the tolerance limit set (+/- 5%) is achieved. The voltage waveform graphs for the IEEE 14 bus system are obtained by using simple algorithm with MATLAB and then with fuzzy logic for 14 bus system. The goal of this project was to control the voltage within limits by controlling the reactive power of the DG using fuzzy logic.

Keywords: distributed generation, fuzzy logic, matlab, newton raphson, IEEE 14 bus, voltage regulation, radial network

Procedia PDF Downloads 637
2489 Utility of Routine Colonoscopy in Acute Diverticulitis

Authors: Naya Masood, Russell Hodgson, Mark Tacey

Abstract:

Purpose: Patients with acute diverticulitis (AD) have an increased risk of underlying colorectal cancer (CRC); however, those with uncomplicated AD may have the same underlying population risk. This study informs on an Australian AD population who were not routinely offered colonoscopic follow-up. Methods: A 2-year (July 2016 – June 2018) retrospective study of patients admitted with CT-confirmed acute diverticulitis was conducted. CT findings were categorised as ‘complicated’ and ‘uncomplicated’ and were correlated with the detection of cancer in subsequent colonoscopy or follow-up. Results: 67.7% (n=292) of 431 patients were seen to have had complicated AD on an abdominopelvic CT scan. Patients were complicated most commonly due to bowel wall thickening reported on CT (90.4%), perforation (20.2%), or an abscess (12%). Follow-up colonoscopic evaluation was conducted in 52.9% (n=228) of total cases of AD, out of which 156 suffered complicated AD and the rest uncomplicated. None of the uncomplicated AD patients in our cohort were found to have CRC. Of those with complicated AD, six were found to have CRC. Conclusion: The only CRC diagnoses were made in patients with complicated AD. Despite available evidence, a significant proportion of uncomplicated AD patients were still undergoing colonoscopy. There is scope to further safely decrease the number of colonoscopies performed in AD patients.

Keywords: acute diverticulitis, colonoscopy, colorectal cancer, advanced adenoma, complicated diverticulitis

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2488 Room Level Indoor Localization Using Relevant Channel Impulse Response Parameters

Authors: Raida Zouari, Iness Ahriz, Rafik Zayani, Ali Dziri, Ridha Bouallegue

Abstract:

This paper proposes a room level indoor localization algorithm based on the use Multi-Layer Neural Network (MLNN) classifiers and one versus one strategy. Seven parameters of the Channel Impulse Response (CIR) were used and Gram-Shmidt Orthogonalization was performed to study the relevance of the extracted parameters. Simulation results show that when relevant CIR parameters are used as position fingerprint and when optimal MLNN architecture is selected good room level localization score can be achieved. The current study showed also that some of the CIR parameters are not correlated to the location and can decrease the localization performance of the system.

Keywords: mobile indoor localization, multi-layer neural network (MLNN), channel impulse response (CIR), Gram-Shmidt orthogonalization

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2487 3D High-Precision Tunnel Gravity Exploration Method for Concealed High-Density Ore-Bodies: A Case Study on the Zhaotong Maoping Carbonate-Hosted Zn-Pb-(Ag-Ge) Deposit in Northeastern Yunnan, China

Authors: Han Run-Sheng, Li Wen-Yao, Wang Feng, Liu Fei, Qiu Wen-Long, Lei Li

Abstract:

Accurately positioning detection of concealed deposits or ore-bodies is one of the difficult problems in mineral exploration field. Theory calculation and exploration practices for tunnel gravity indicate that 3D high-precision Tunnel Gravity Exploration Method (TGEM) can find concealed high-density three-dimensional ore-bodies in the depth. The ore-finding breakthroughs at the depth of the Zhaotong Maoping carbonate-hosted Zn–Pb–(Ag–Ge) deposit in Northeastern Yunnan have proved that the exploration method in combination with MEAHFZ method is effective to detect concealed high-density ore-bodies. TGEM may overcome anomalous ambiguity of other geophysical methods for 3D positioning of concealed ore-bodies.

Keywords: 3D tunnel gravity exploration method, concealed high-density Ore-bodies, Zn–Pb–(Ag–Ge) deposit, Zaotong mapping, Northeastern Yunnan

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2486 Control of Doubly Star Induction Motor Using Direct Torque DTC Based To on RST Regulator

Authors: Nadia Akkari

Abstract:

This paper presents the analysis and simulation of the control of double star induction motor, using direct torque control (DTC) based on RST regulator. The DTC is an excellent solution for general- purpose induction drives in very wide range the short sampling time required by the TC schemes makes them suited to a very fast torque and flux controlled drives as well the simplicity of the control algorithm. DTC is inherently a motion sensorless control method. The RST regulator can improve the double star induction motor performance in terms of overshoot, rapidity, cancellation of disturbance, and capacity to maintain a high level of performance. Simulation results indicate that the proposed regulator has better performance responses. The implementation of the DTC applied to a double star induction motor based on RST regulator is validated with simulated results.

Keywords: Direct Torque Control (DTC), Double Star Induction Motor (DSIM), RST Regulator

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2485 Discussing Embedded versus Central Machine Learning in Wireless Sensor Networks

Authors: Anne-Lena Kampen, Øivind Kure

Abstract:

Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

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2484 Mathematical Modeling for Diabetes Prediction: A Neuro-Fuzzy Approach

Authors: Vijay Kr. Yadav, Nilam Rathi

Abstract:

Accurate prediction of glucose level for diabetes mellitus is required to avoid affecting the functioning of major organs of human body. This study describes the fundamental assumptions and two different methodologies of the Blood glucose prediction. First is based on the back-propagation algorithm of Artificial Neural Network (ANN), and second is based on the Neuro-Fuzzy technique, called Fuzzy Inference System (FIS). Errors between proposed methods further discussed through various statistical methods such as mean square error (MSE), normalised mean absolute error (NMAE). The main objective of present study is to develop mathematical model for blood glucose prediction before 12 hours advanced using data set of three patients for 60 days. The comparative studies of the accuracy with other existing models are also made with same data set.

Keywords: back-propagation, diabetes mellitus, fuzzy inference system, neuro-fuzzy

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2483 Timing and Noise Data Mining Algorithm and Software Tool in Very Large Scale Integration (VLSI) Design

Authors: Qing K. Zhu

Abstract:

Very Large Scale Integration (VLSI) design becomes very complex due to the continuous integration of millions of gates in one chip based on Moore’s law. Designers have encountered numerous report files during design iterations using timing and noise analysis tools. This paper presented our work using data mining techniques combined with HTML tables to extract and represent critical timing/noise data. When we apply this data-mining tool in real applications, the running speed is important. The software employs table look-up techniques in the programming for the reasonable running speed based on performance testing results. We added several advanced features for the application in one industry chip design.

Keywords: VLSI design, data mining, big data, HTML forms, web, VLSI, EDA, timing, noise

Procedia PDF Downloads 254
2482 ANA Negative but FANA Positive Patients with Clinical Symptoms of Rheumatic Disease: The Suggestion for Clinicians

Authors: Abdolreza Esmaeilzadeh, Mehri Mirzaei

Abstract:

Objective: Rheumatic disease is a chronic disease that causes pain, stiffness, swelling and limited motion and function of many joints. RA is the most common form of autoimmune arthritis, affecting more than 1.3 million Americans. Of these, about 75% are women. Materials and Methods: This study was formed due to the misconception about ANA test, which is frequently performed with methods based upon solid phase as ELISA. This experiment was conducted on 430 patients, with clinical symptoms that are likely affected with rheumatic diseases, simultaneously by means of ANA and FANA. Results: 36 cases (8.37%) of patients, despite positive ANA, have demonstrated negative results via Indirect Immunofluorescence Assay (IIFA), (false positive). 116 cases (27%) have demonstrated negative ANA results, by means of the ELISA technique, although they had positive IIFA results. Conclusion: Other advantages of IIFA are antibody titration and specific pattern detection that have the capability of distinguishing positive dsDNA results. According to the restrictions and false negative cases, in patients, IIFA test is highly recommended for these disease's diagnosis.

Keywords: autoimmune disease, IIFA, EIA, rheumatic disease

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2481 Technology Maps in Energy Applications Based on Patent Trends: A Case Study

Authors: Juan David Sepulveda

Abstract:

This article reflects the current stage of progress in the project “Determining technological trends in energy generation”. At first it was oriented towards finding out those trends by employing such tools as the scientometrics community had proved and accepted as effective for getting reliable results. Because a documented methodological guide for this purpose could not be found, the decision was made to reorient the scope and aim of this project, changing the degree of interest in pursuing the objectives. Therefore it was decided to propose and implement a novel guide from the elements and techniques found in the available literature. This article begins by explaining the elements and considerations taken into account when implementing and applying this methodology, and the tools that led to the implementation of a software application for patent revision. Univariate analysis helped recognize the technological leaders in the field of energy, and steered the way for a multivariate analysis of this sample, which allowed for a graphical description of the techniques of mature technologies, as well as the detection of emerging technologies. This article ends with a validation of the methodology as applied to the case of fuel cells.

Keywords: energy, technology mapping, patents, univariate analysis

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2480 Soft Exoskeleton Elastomer Pre-Tension Drive Control System

Authors: Andrey Yatsun, Andrei Malchikov

Abstract:

Exoskeletons are used to support and compensate for the load on the human musculoskeletal system. Elastomers are an important component of exoskeletons, providing additional support and compensating for the load. The algorithm of the active elastomer tension system provides the required auxiliary force depending on the angle of rotation and the tilt speed of the operator's torso. Feedback for the drive is provided by a force sensor integrated into the attachment of the exoskeleton vest. The use of direct force measurement ensures the required accuracy in all settings of the man-machine system. Non-adjustable elastic elements make it difficult to move without load, tilt forward and walk. A strategy for the organization of the auxiliary forces management system is proposed based on the allocation of 4 operating modes of the human-machine system.

Keywords: soft exoskeleton, mathematical modeling, pre-tension elastomer, human-machine interaction

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2479 Dynamic Simulation of IC Engine Bearings for Fault Detection and Wear Prediction

Authors: M. D. Haneef, R. B. Randall, Z. Peng

Abstract:

Journal bearings used in IC engines are prone to premature failures and are likely to fail earlier than the rated life due to highly impulsive and unstable operating conditions and frequent starts/stops. Vibration signature extraction and wear debris analysis techniques are prevalent in the industry for condition monitoring of rotary machinery. However, both techniques involve a great deal of technical expertise, time and cost. Limited literature is available on the application of these techniques for fault detection in reciprocating machinery, due to the complex nature of impact forces that confounds the extraction of fault signals for vibration based analysis and wear prediction. This work is an extension of a previous study, in which an engine simulation model was developed using a MATLAB/SIMULINK program, whereby the engine parameters used in the simulation were obtained experimentally from a Toyota 3SFE 2.0 litre petrol engines. Simulated hydrodynamic bearing forces were used to estimate vibrations signals and envelope analysis was carried out to analyze the effect of speed, load and clearance on the vibration response. Three different loads 50/80/110 N-m, three different speeds 1500/2000/3000 rpm, and three different clearances, i.e., normal, 2 times and 4 times the normal clearance were simulated to examine the effect of wear on bearing forces. The magnitude of the squared envelope of the generated vibration signals though not affected by load, but was observed to rise significantly with increasing speed and clearance indicating the likelihood of augmented wear. In the present study, the simulation model was extended further to investigate the bearing wear behavior, resulting as a consequence of different operating conditions, to complement the vibration analysis. In the current simulation, the dynamics of the engine was established first, based on which the hydrodynamic journal bearing forces were evaluated by numerical solution of the Reynold’s equation. Also, the essential outputs of interest in this study, critical to determine wear rates are the tangential velocity and oil film thickness between the journal and bearing sleeve, which if not maintained appropriately, have a detrimental effect on the bearing performance. Archard’s wear prediction model was used in the simulation to calculate the wear rate of bearings with specific location information as all determinative parameters were obtained with reference to crank rotation. Oil film thickness obtained from the model was used as a criterion to determine if the lubrication is sufficient to prevent contact between the journal and bearing thus causing accelerated wear. A limiting value of 1 µm was used as the minimum oil film thickness needed to prevent contact. The increased wear rate with growing severity of operating conditions is analogous and comparable to the rise in amplitude of the squared envelope of the referenced vibration signals. Thus on one hand, the developed model demonstrated its capability to explain wear behavior and on the other hand it also helps to establish a correlation between wear based and vibration based analysis. Therefore, the model provides a cost-effective and quick approach to predict the impending wear in IC engine bearings under various operating conditions.

Keywords: condition monitoring, IC engine, journal bearings, vibration analysis, wear prediction

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2478 Modeling of Digital and Settlement Consolidation of Soil under Oedomete

Authors: Yu-Lin Shen, Ming-Kuen Chang

Abstract:

In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

Procedia PDF Downloads 333
2477 Phytoseiid Mite Species (Acari: Mesostigmata) on Blackberry Plants in Florida and Georgia, USA

Authors: Rana Akyazi, Cal Welbourn, Oscar E. Liburd

Abstract:

The family Phytoseiidae are the most common plant inhabiting group of predatory mites. They are generally considered to be important biological control agents of pest mites on many crops world-wide. Several species of these mites are commercially available in many countries. This study was carried out to determine phytoseiid mite species on nine different blackberry varieties (Arapaho, Choctaw, Kiowa, Nachez, Navaho, Osage, Ouachita, Von, Watchita). The survey was conducted from June to October 2016. Leaf samples were collected monthly from selected organic and conventional commercial blackberry (Rubus spp.) farms in Florida and Georgia, USA. Nine phytoseiid mite (Acari: Mesostigmata) species were determined during the study. The results also showed that the incidence of Phytoseiidae was greater in organic than in conventional blackberries. Future survey studies can provide detection of new species, which may hold potential for biological control of economically important pests in key fruit crops.

Keywords: biological control, mite, Phytoseiidae, predator, Rubus spp.

Procedia PDF Downloads 403
2476 Non-Signaling Chemokine Receptor CCRL1 and Its Active Counterpart CCR7 in Prostate Cancer

Authors: Yiding Qu, Svetlana V. Komarova

Abstract:

Chemokines acting through their cognate chemokine receptors guide the directional migration of the cell along the chemokine gradient. Several chemokine receptors were recently identified as non-signaling (decoy), based on their ability to bind the chemokine but produce no measurable signal in the cell. The function of these decoy receptors is not well understood. We examined the expression of a decoy receptor CCRL1 and a signaling receptor that binds to the same ligands, CCR7, in prostate cancer using publically available microarray data (www.oncomine.org). The expression of both CCRL1 and CCR7 increased in an approximately half of prostate carcinoma samples and the majority of metastatic cancer samples compared to normal prostate. Moreover, the expression of CCRL1 positively correlated with the expression of CCR7. These data suggest that CCR7 and CCRL1 can be used as clinical markers for the early detection of transformation from carcinoma to metastatic cancer. In addition, these data support our hypothesis that the non-signaling chemokine receptors actively stimulate cell migration.

Keywords: bioinformatics, cell migration, decoy receptor, meta-analysis, prostate cancer

Procedia PDF Downloads 472