Search results for: parking space detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6948

Search results for: parking space detection

5568 Research on Road Openness in the Old Urban Residential District Based on Space Syntax: A Case Study on Kunming within the First Loop Road

Authors: Haoyang Liang, Dandong Ge

Abstract:

With the rapid development of Chinese cities, traffic congestion has become more and more serious. At the same time, there are many closed old residential area in Chinese cities, which seriously affect the connectivity of urban roads and reduce the density of urban road networks. After reopening the restricted old residential area, the internal roads in the original residential area were transformed into urban roads, which was of great help to alleviate traffic congestion. This paper uses the spatial syntactic theory to analyze the urban road network and compares the roads with the integration and connectivity degree to evaluate whether the opening of the roads in the residential areas can improve the urban traffic. Based on the road network system within the first loop road in Kunming, the Space Syntax evaluation model is established for status analysis. And comparative analysis method will be used to compare the change of the model before and after the road openness of the old urban residential district within the first-ring road in Kunming. Then it will pick out the areas which indicate a significant difference for the small dimensions model analysis. According to the analyzed results and traffic situation, the evaluation of road openness in the old urban residential district will be proposed to improve the urban residential districts.

Keywords: Space Syntax, Kunming, urban renovation, traffic jam

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5567 Construction and Performance of Nanocomposite-Based Electrochemical Biosensor

Authors: Jianfang Wang, Xianzhe Chen, Zhuoliang Liu, Cheng-An Tao, Yujiao Li

Abstract:

Organophosphorus (OPs) pesticide used as insecticides are widely used in agricultural pest control, household and storage deworming. The detection of pesticides needs more simple and efficient methods. One of the best ways is to make electrochemical biosensors. In this paper, an electrochemical enzyme biosensor based on acetylcholine esterase (AChE) was constructed, and its sensing properties and sensing mechanisms were studied. Reduced graphene oxide-polydopamine complexes (RGO-PDA), gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were prepared firstly and composited with AChE and chitosan (CS), then fixed on the glassy carbon electrode (GCE) surface to construct the biosensor GCE/RGO-PDA-AuNPs-AgNPs-AChE-CS by one-pot method. The results show that graphene oxide (GO) can be reduced by dopamine (DA) and dispersed well in RGO-PDA complexes. And the composites have a synergistic catalysis effect and can improve the surface resistance of GCE. The biosensor selectively can detect acetylcholine (ACh) and OPs pesticide with good linear range and high sensitivity. The performance of the biosensor is affected by the ratio and adding ways of AChE and the adding of AuNPs and AChE. And the biosensor can achieve a detection limit of 2.4 ng/L for methyl parathion and a wide linear detection range of 0.02 ng/L ~ 80 ng/L, and has excellent stability, good anti-interference ability, and excellent preservation performance, indicating that the sensor has practical value.

Keywords: acetylcholine esterase, electrochemical biosensor, nanoparticles, organophosphates, reduced graphene oxide

Procedia PDF Downloads 104
5566 Validity of Universe Structure Conception as Nested Vortexes

Authors: Khaled M. Nabil

Abstract:

This paper introduces the Nested Vortexes conception of the universe structure and interprets all the physical phenomena according this conception. The paper first reviews recent physics theories, either in microscopic scale or macroscopic scale, to collect evidence that the space is not empty. But, these theories describe the property of the space medium without determining its structure. Determining the structure of space medium is essential to understand the mechanism that leads to its properties. Without determining the space medium structure, many phenomena; such as electric and magnetic fields, gravity, or wave-particle duality remain uninterpreted. Thus, this paper introduces a conception about the structure of the universe. It assumes that the universe is a medium of ultra-tiny homogeneous particles which are still undiscovered. Like any medium with certain movements, possibly because of a great asymmetric explosion, vortexes have occurred. A vortex condenses the ultra-tiny particles in its center forming a bigger particle, the bigger particles, in turn, could be trapped in a bigger vortex and condense in its center forming a much bigger particle and so on. This conception describes galaxies, stars, protons as particles at different levels. Existing of the particle’s vortexes make the consistency of the speed of light postulate is not true. This conception shows that the vortex motion dynamic agrees with the motion of all the universe particles at any level. An experiment has been carried out to detect the orbiting effect of aggregated vortexes of aligned atoms of a permanent magnet. Based on the described particle’s structure, the gravity force of a particle and attraction between particles as well as charge, electric and magnetic fields and quantum mechanics characteristics are interpreted. All augmented physics phenomena are solved.

Keywords: astrophysics, cosmology, particles’ structure model, particles’ forces

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5565 Taxonomy of Threats and Vulnerabilities in Smart Grid Networks

Authors: Faisal Al Yahmadi, Muhammad R. Ahmed

Abstract:

Electric power is a fundamental necessity in the 21st century. Consequently, any break in electric power is probably going to affect the general activity. To make the power supply smooth and efficient, a smart grid network is introduced which uses communication technology. In any communication network, security is essential. It has been observed from several recent incidents that adversary causes an interruption to the operation of networks. In order to resolve the issues, it is vital to understand the threats and vulnerabilities associated with the smart grid networks. In this paper, we have investigated the threats and vulnerabilities in Smart Grid Networks (SGN) and the few solutions in the literature. Proposed solutions showed developments in electricity theft countermeasures, Denial of services attacks (DoS) and malicious injection attacks detection model, as well as malicious nodes detection using watchdog like techniques and other solutions.

Keywords: smart grid network, security, threats, vulnerabilities

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5564 B Spline Finite Element Method for Drifted Space Fractional Tempered Diffusion Equation

Authors: Ayan Chakraborty, BV. Rathish Kumar

Abstract:

Off-late many models in viscoelasticity, signal processing or anomalous diffusion equations are formulated in fractional calculus. Tempered fractional calculus is the generalization of fractional calculus and in the last few years several important partial differential equations occurring in the different field of science have been reconsidered in this term like diffusion wave equations, Schr$\ddot{o}$dinger equation and so on. In the present paper, a time-dependent tempered fractional diffusion equation of order $\gamma \in (0,1)$ with forcing function is considered. Existence, uniqueness, stability, and regularity of the solution has been proved. Crank-Nicolson discretization is used in the time direction. B spline finite element approximation is implemented. Generally, B-splines basis are useful for representing the geometry of a finite element model, interfacing a finite element analysis program. By utilizing this technique a priori space-time estimate in finite element analysis has been derived and we proved that the convergent order is $\mathcal{O}(h²+T²)$ where $h$ is the space step size and $T$ is the time. A couple of numerical examples have been presented to confirm the accuracy of theoretical results. Finally, we conclude that the studied method is useful for solving tempered fractional diffusion equations.

Keywords: B-spline finite element, error estimates, Gronwall's lemma, stability, tempered fractional

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5563 Stochastic Edge Based Anomaly Detection for Supervisory Control and Data Acquisitions Systems: Considering the Zambian Power Grid

Authors: Lukumba Phiri, Simon Tembo, Kumbuso Joshua Nyoni

Abstract:

In Zambia recent initiatives by various power operators like ZESCO, CEC, and consumers like the mines to upgrade power systems into smart grids target an even tighter integration with information technologies to enable the integration of renewable energy sources, local and bulk generation, and demand response. Thus, for the reliable operation of smart grids, its information infrastructure must be secure and reliable in the face of both failures and cyberattacks. Due to the nature of the systems, ICS/SCADA cybersecurity and governance face additional challenges compared to the corporate networks, and critical systems may be left exposed. There exist control frameworks internationally such as the NIST framework, however, there are generic and do not meet the domain-specific needs of the SCADA systems. Zambia is also lagging in cybersecurity awareness and adoption, therefore there is a concern about securing ICS controlling key infrastructure critical to the Zambian economy as there are few known facts about the true posture. In this paper, we introduce a stochastic Edged-based Anomaly Detection for SCADA systems (SEADS) framework for threat modeling and risk assessment. SEADS enables the calculation of steady-steady probabilities that are further applied to establish metrics like system availability, maintainability, and reliability.

Keywords: anomaly, availability, detection, edge, maintainability, reliability, stochastic

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5562 A Novel Approach to Design of EDDR Architecture for High Speed Motion Estimation Testing Applications

Authors: T. Gangadhararao, K. Krishna Kishore

Abstract:

Motion Estimation (ME) plays a critical role in a video coder, testing such a module is of priority concern. While focusing on the testing of ME in a video coding system, this work presents an error detection and data recovery (EDDR) design, based on the residue-and-quotient (RQ) code, to embed into ME for video coding testing applications. An error in processing Elements (PEs), i.e. key components of a ME, can be detected and recovered effectively by using the proposed EDDR design. The proposed EDDR design for ME testing can detect errors and recover data with an acceptable area overhead and timing penalty.

Keywords: area overhead, data recovery, error detection, motion estimation, reliability, residue-and-quotient (RQ) code

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5561 Alcohol Detection with Engine Locking System Using Arduino and ESP8266

Authors: Sukhpreet Singh, Kishan Bhojrath, Vijay, Avinash Kumar, Mandlesh Mishra

Abstract:

The project uses an Arduino and ESP8266 to construct an alcohol detection system with an engine locking mechanism, offering a distinct way to fight drunk driving. An alcohol sensor module is used by the system to determine the amount of alcohol present in the ambient air. When the system detects alcohol levels beyond a certain threshold that is deemed hazardous for driving, it activates a relay module that is linked to the engine of the car, so rendering it inoperable. By preventing people from operating a vehicle while intoxicated, this preventive measure seeks to improve road safety. Adding an ESP8266 module also allows for remote monitoring and notifications, giving users access to real-time status updates on their system. By using an integrated strategy, the initiative provides a workable and efficient way to lessen the dangers related to driving while intoxicated.

Keywords: MQ3 sensor, ESP 8266, arduino, IoT

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5560 A Tuning Method for Microwave Filter via Complex Neural Network and Improved Space Mapping

Authors: Shengbiao Wu, Weihua Cao, Min Wu, Can Liu

Abstract:

This paper presents an intelligent tuning method of microwave filter based on complex neural network and improved space mapping. The tuning process consists of two stages: the initial tuning and the fine tuning. At the beginning of the tuning, the return loss of the filter is transferred to the passband via the error of phase. During the fine tuning, the phase shift caused by the transmission line and the higher order mode is removed by the curve fitting. Then, an Cauchy method based on the admittance parameter (Y-parameter) is used to extract the coupling matrix. The influence of the resonant cavity loss is eliminated during the parameter extraction process. By using processed data pairs (the amount of screw variation and the variation of the coupling matrix), a tuning model is established by the complex neural network. In view of the improved space mapping algorithm, the mapping relationship between the actual model and the ideal model is established, and the amplitude and direction of the tuning is constantly updated. Finally, the tuning experiment of the eight order coaxial cavity filter shows that the proposed method has a good effect in tuning time and tuning precision.

Keywords: microwave filter, scattering parameter, coupling matrix, intelligent tuning

Procedia PDF Downloads 291
5559 Hardware-In-The-Loop Relative Motion Control: Theory, Simulation and Experimentation

Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

Abstract:

This paper presents a Guidance and Control (G&C) strategy to address spacecraft maneuvering problem for future Rendezvous and Docking (RVD) missions. The proposed strategy allows safe and propellant efficient trajectories for space servicing missions including tasks such as approaching, inspecting and capturing. This work provides the validation test results of the G&C laws using a Hardware-In-the-Loop (HIL) setup with two robotic mockups representing the chaser and the target spacecraft. Through this paper, the challenges of the relative motion control in space are first summarized, and in particular, the constraints imposed by the mission, spacecraft and, onboard processing capabilities. Second, the proposed algorithm is introduced by presenting the formulation of constrained Model Predictive Control (MPC) to optimize the fuel consumption and explicitly handle the physical and geometric constraints in the system, e.g. thruster or Line-Of-Sight (LOS) constraints. Additionally, the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description and accordingly explained. The resulting convex optimization problem allows real-time implementation capability based on a detailed discussion on the computational time requirements and the obtained results with respect to the onboard computer and future trends of space processors capabilities. Finally, the performance of the algorithm is presented in the scope of a potential future mission and of the available equipment. The results also cover a comparison between the proposed algorithms with Linear–quadratic regulator (LQR) based control law to highlight the clear advantages of the MPC formulation.

Keywords: autonomous vehicles, embedded optimization, real-time experiment, rendezvous and docking, space robotics

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5558 Glaucoma Detection in Retinal Tomography Using the Vision Transformer

Authors: Sushish Baral, Pratibha Joshi, Yaman Maharjan

Abstract:

Glaucoma is a chronic eye condition that causes vision loss that is irreversible. Early detection and treatment are critical to prevent vision loss because it can be asymptomatic. For the identification of glaucoma, multiple deep learning algorithms are used. Transformer-based architectures, which use the self-attention mechanism to encode long-range dependencies and acquire extremely expressive representations, have recently become popular. Convolutional architectures, on the other hand, lack knowledge of long-range dependencies in the image due to their intrinsic inductive biases. The aforementioned statements inspire this thesis to look at transformer-based solutions and investigate the viability of adopting transformer-based network designs for glaucoma detection. Using retinal fundus images of the optic nerve head to develop a viable algorithm to assess the severity of glaucoma necessitates a large number of well-curated images. Initially, data is generated by augmenting ocular pictures. After that, the ocular images are pre-processed to make them ready for further processing. The system is trained using pre-processed images, and it classifies the input images as normal or glaucoma based on the features retrieved during training. The Vision Transformer (ViT) architecture is well suited to this situation, as it allows the self-attention mechanism to utilise structural modeling. Extensive experiments are run on the common dataset, and the results are thoroughly validated and visualized.

Keywords: glaucoma, vision transformer, convolutional architectures, retinal fundus images, self-attention, deep learning

Procedia PDF Downloads 182
5557 Federal College of Education Kano

Authors: Mahnaz Babaei Morad, Mojtaba Zargarzadeh, Behnaz Babaei Morad, Najmeh Salari Nasab

Abstract:

Green roofs and walls are one of the key elements of sustainable design in ecology design of cities. Lack of open space and urban green at different scales from one neighborhood to district is as subject that has become challenge for urban management Use change from green space to other use is familiar for Iranian citizens. The high price of land in this area, it seems only justified reason for municipalities that reduce the green space per capita. In this paper, examines the rooftops of Iranian city as a fifth facade, as well as the opportunity to offset some of the capital's urban spaces that has been removed. Today green roof isn't a matter of taste in the world. Be proportional to the quantity and quality of the architecture become the first concern of urban professionals and ecological approaches such as "sustainable" and "green architecture" is checked. In this paper we review and present examples of green roofs have been executed in Iran over the past decade. Survey some of the urban management policies in leading province in this article constitutes the second dimension. The purpose of this paper is study example of green roof performance in different parts of Iran, along with criteria for sustainable urban development and achieves the policies and components collection of implementation sustainable development , specific of Iranian green roof and monitor the develops ways to it.

Keywords: sustainable development, green roofs, Iran, green architecture

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5556 Detection of Alzheimer's Protein on Nano Designed Polymer Surfaces in Water and Artificial Saliva

Authors: Sevde Altuntas, Fatih Buyukserin

Abstract:

Alzheimer’s disease is responsible for irreversible neural damage of brain parts. One of the disease markers is Amyloid-β 1-42 protein that accumulates in the brain in the form plaques. The basic problem for detection of the protein is the low amount of protein that cannot be detected properly in body liquids such as blood, saliva or urine. To solve this problem, tests like ELISA or PCR are proposed which are expensive, require specialized personnel and can contain complex protocols. Therefore, Surface-enhanced Raman Spectroscopy (SERS) a good candidate for detection of Amyloid-β 1-42 protein. Because the spectroscopic technique can potentially allow even single molecule detection from liquid and solid surfaces. Besides SERS signal can be improved by using nanopattern surface and also is specific to molecules. In this context, our study proposes to fabricate diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin - T to detect low concentrations of Amyloid-β 1-42 protein in water and artificial saliva medium by the enhancement of protein SERS signal. The nanopatterned PC surface that was used to enhance SERS signal was fabricated by using Anodic Alumina Membranes (AAM) as a template. It is possible to produce AAMs with different column structures and varying thicknesses depending on voltage and anodization time. After fabrication process, the pore diameter of AAMs can be arranged with dilute acid solution treatment. In this study, two different columns structures were prepared. After a surface modification to decrease their surface energy, AAMs were treated with PC solution. Following the solvent evaporation, nanopatterned PC films with tunable pillared structures were peeled off from the membrane surface. The PC film was then modified with Au and Thioflavin-T for the detection of Amyloid-β 1-42 protein. The protein detection studies were conducted first in water via this biosensor platform. Same measurements were conducted in artificial saliva to detect the presence of Amyloid Amyloid-β 1-42 protein. SEM, SERS and contact angle measurements were carried out for the characterization of different surfaces and further demonstration of the protein attachment. SERS enhancement factor calculations were also completed via experimental results. As a result, our research group fabricated diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin-T to detect low concentrations of Alzheimer’s Amiloid – β protein in water and artificial saliva medium. This work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) Grant No: 214Z167.

Keywords: alzheimer, anodic aluminum oxide, nanotopography, surface enhanced Raman spectroscopy

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5555 Ontology for a Voice Transcription of OpenStreetMap Data: The Case of Space Apprehension by Visually Impaired Persons

Authors: Said Boularouk, Didier Josselin, Eitan Altman

Abstract:

In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: TTS, ontology, open street map, visually impaired

Procedia PDF Downloads 287
5554 A Real-Time Snore Detector Using Neural Networks and Selected Sound Features

Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

Abstract:

Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

Procedia PDF Downloads 197
5553 Self-Tuning Robot Control Based on Subspace Identification

Authors: Mathias Marquardt, Peter Dünow, Sandra Baßler

Abstract:

The paper describes the use of subspace based identification methods for auto tuning of a state space control system. The plant is an unstable but self balancing transport robot. Because of the unstable character of the process it has to be identified from closed loop input-output data. Based on the identified model a state space controller combined with an observer is calculated. The subspace identification algorithm and the controller design procedure is combined to a auto tuning method. The capability of the approach was verified in a simulation experiments under different process conditions.

Keywords: auto tuning, balanced robot, closed loop identification, subspace identification

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5552 Review on Quaternion Gradient Operator with Marginal and Vector Approaches for Colour Edge Detection

Authors: Nadia Ben Youssef, Aicha Bouzid

Abstract:

Gradient estimation is one of the most fundamental tasks in the field of image processing in general, and more particularly for color images since that the research in color image gradient remains limited. The widely used gradient method is Di Zenzo’s gradient operator, which is based on the measure of squared local contrast of color images. The proposed gradient mechanism, presented in this paper, is based on the principle of the Di Zenzo’s approach using quaternion representation. This edge detector is compared to a marginal approach based on multiscale product of wavelet transform and another vector approach based on quaternion convolution and vector gradient approach. The experimental results indicate that the proposed color gradient operator outperforms marginal approach, however, it is less efficient then the second vector approach.

Keywords: gradient, edge detection, color image, quaternion

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5551 An Aptasensor Based on Magnetic Relaxation Switch and Controlled Magnetic Separation for the Sensitive Detection of Pseudomonas aeruginosa

Authors: Fei Jia, Xingjian Bai, Xiaowei Zhang, Wenjie Yan, Ruitong Dai, Xingmin Li, Jozef Kokini

Abstract:

Pseudomonas aeruginosa is a Gram-negative, aerobic, opportunistic human pathogen that is present in the soil, water, and food. This microbe has been recognized as a representative food-borne spoilage bacterium that can lead to many types of infections. Considering the casualties and property loss caused by P. aeruginosa, the development of a rapid and reliable technique for the detection of P. aeruginosa is crucial. The whole-cell aptasensor, an emerging biosensor using aptamer as a capture probe to bind to the whole cell, for food-borne pathogens detection has attracted much attention due to its convenience and high sensitivity. Here, a low-field magnetic resonance imaging (LF-MRI) aptasensor for the rapid detection of P. aeruginosa was developed. The basic detection principle of the magnetic relaxation switch (MRSw) nanosensor lies on the ‘T₂-shortening’ effect of magnetic nanoparticles in NMR measurements. Briefly speaking, the transverse relaxation time (T₂) of neighboring water protons get shortened when magnetic nanoparticles are clustered due to the cross-linking upon the recognition and binding of biological targets, or simply when the concentration of the magnetic nanoparticles increased. Such shortening is related to both the state change (aggregation or dissociation) and the concentration change of magnetic nanoparticles and can be detected using NMR relaxometry or MRI scanners. In this work, two different sizes of magnetic nanoparticles, which are 10 nm (MN₁₀) and 400 nm (MN₄₀₀) in diameter, were first immobilized with anti- P. aeruginosa aptamer through 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) chemistry separately, to capture and enrich the P. aeruginosa cells. When incubating with the target, a ‘sandwich’ (MN₁₀-bacteria-MN₄₀₀) complex are formed driven by the bonding of MN400 with P. aeruginosa through aptamer recognition, as well as the conjugate aggregation of MN₁₀ on the surface of P. aeruginosa. Due to the different magnetic performance of the MN₁₀ and MN₄₀₀ in the magnetic field caused by their different saturation magnetization, the MN₁₀-bacteria-MN₄₀₀ complex, as well as the unreacted MN₄₀₀ in the solution, can be quickly removed by magnetic separation, and as a result, only unreacted MN₁₀ remain in the solution. The remaining MN₁₀, which are superparamagnetic and stable in low field magnetic field, work as a signal readout for T₂ measurement. Under the optimum condition, the LF-MRI platform provides both image analysis and quantitative detection of P. aeruginosa, with the detection limit as low as 100 cfu/mL. The feasibility and specificity of the aptasensor are demonstrated in detecting real food samples and validated by using plate counting methods. Only two steps and less than 2 hours needed for the detection procedure, this robust aptasensor can detect P. aeruginosa with a wide linear range from 3.1 ×10² cfu/mL to 3.1 ×10⁷ cfu/mL, which is superior to conventional plate counting method and other molecular biology testing assay. Moreover, the aptasensor has a potential to detect other bacteria or toxins by changing suitable aptamers. Considering the excellent accuracy, feasibility, and practicality, the whole-cell aptasensor provides a promising platform for a quick, direct and accurate determination of food-borne pathogens at cell-level.

Keywords: magnetic resonance imaging, meat spoilage, P. aeruginosa, transverse relaxation time

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5550 Collision Avoidance Based on Model Predictive Control for Nonlinear Octocopter Model

Authors: Doğan Yıldız, Aydan Müşerref Erkmen

Abstract:

The controller of the octocopter is mostly based on the PID controller. For complex maneuvers, PID controllers have limited performance capability like in collision avoidance. When an octocopter needs avoidance from an obstacle, it must instantly show an agile maneuver. Also, this kind of maneuver is affected severely by the nonlinear characteristic of octocopter. When these kinds of limitations are considered, the situation is highly challenging for the PID controller. In the proposed study, these challenges are tried to minimize by using the model predictive controller (MPC) for collision avoidance with a nonlinear octocopter model. The aim is to show that MPC-based collision avoidance has the capability to deal with fast varying conditions in case of obstacle detection and diminish the nonlinear effects of octocopter with varying disturbances.

Keywords: model predictive control, nonlinear octocopter model, collision avoidance, obstacle detection

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5549 Anti-Gravity to Neo-Concretism: The Epodic Spaces of Non-Objective Art

Authors: Alexandra Kennedy

Abstract:

Making use of the notion of ‘epodic spaces’ this paper presents a reconsideration of non-objective art practices, proposing alternatives to established materialist, formalist, process-based conceptualist approaches to such work. In his Neo-Concrete Manifesto (1959) Ferreira Gullar (1930-2016) sought to create a distinction between various forms of non-objective art. He distinguished the ‘geometric’ arts of neoplasticism, constructivism, and suprematism – which he described as ‘dangerously acute rationalism’ – from other non-objective practices. These alternatives, he proposed, have an expressive potential lacking in the former and this formed the basis for their categorisation as neo-concrete. Gullar prioritized the phenomenological over the rational, with an emphasis on the role of the spectator (a key concept of minimalism). Gullar highlighted the central role of sensual experience, colour and the poetic in such work. In the early twentieth century, Russian Cosmism – an esoteric philosophical movement – was highly influential on Russian avant-garde artists and can account for suprematist artists’ interest in, and approach to, planar geometry and four-dimensional space as demonstrated in the abstract paintings of Kasimir Malevich (1879-1935). Nikolai Fyodorov (1823-1903) promoted the idea of anti-gravity and cosmic space as the field for artistic activity. The artist and writer Kuzma Petrov-Vodkin (1878-1939) wrote on the concept of Euclidean space, the overcoming of such rational conceptions of space and the breaking free from the gravitational field and the earth’s sphere. These imaginary spaces, which also invoke a bodily experience, present a poetic dimension to the work of the suprematists. It is a dimension that arguably aligns more with Gullar’s formulation of his neo-concrete rather than that of his alignment of Suprematism with rationalism. While found in experiments with planar geometry, the interest in forms suggestive of an experience of breaking free–both physically from the earth and conceptually from rational, mathematical space (in a pre-occupation with non-Euclidean space and anti-geometry) and in their engagement with the spatial properties of colour, Suprematism presents itself as imaginatively epodic. The paper discusses both historical and contemporary non-objective practices in this context, drawing attention to the manner in which the category of the non-objective is used to categorise art works which are, arguably, qualitatively different.

Keywords: anti-gravity, neo-concrete, non-Euclidian geometry, non-objective painting

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5548 Proton Irradiation Testing on Commercial Enhancement Mode GaN Power Transistor

Authors: L. Boyaci

Abstract:

Two basic equipment of electrical power subsystem of space satellites are Power Conditioning Unit (PCU) and Power Distribution Unit (PDU). Today, the main switching element used in power equipment in satellites is silicon (Si) based radiation-hardened MOSFET. GaNFETs have superior performances over MOSFETs in terms of their conduction and switching characteristics. GaNFET has started to take MOSFET’s place in many applications in industry especially by virtue of its switching performances. If GaNFET can also be used in equipment for space applications, this would be great revolution for future space power subsystem designs. In this study, the effect of proton irradiation on Gallium Nitride based power transistors was investigated. Four commercial enhancement mode GaN power transistors from Efficient Power Conversion Corporation (EPC) are irradiated with 30MeV protons while devices are switching. Flux of 8.2x10⁹ protons/cm²/s is applied for 12.5 seconds to reach ultimate fluence of 10¹¹ protons/cm². Vgs-Ids characteristics are measured and recorded for each device before, during and after irradiation. It was observed that if there would be destructive events. Proton induced permanent damage on devices is not observed. All the devices remained healthy and continued to operate. For two of these devices, further irradiation is applied with same flux for 30 minutes up to a total fluence level of 1.476x10¹³ protons/cm². We observed that GaNFETs are fully functional under this high level of radiation and no destructive events and irreversible failures took place for transistors. Results reveal that irradiated GaNFET in this experiment has radiation tolerance under proton testing and very important candidate for being one of the future power switching element in space.

Keywords: enhancement mode GaN power transistors, proton irradiation effects, radiation tolerance

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5547 Single-Molecule Analysis of Structure and Dynamics in Polymer Materials by Super-Resolution Technique

Authors: Hiroyuki Aoki

Abstract:

The physical properties of polymer materials are dependent on the conformation and molecular motion of a polymer chain. Therefore, the structure and dynamic behavior of the single polymer chain have been the most important concerns in the field of polymer physics. However, it has been impossible to directly observe the conformation of the single polymer chain in a bulk medium. In the current work, the novel techniques to study the conformation and dynamics of a single polymer chain are proposed. Since a fluorescence method is extremely sensitive, the fluorescence microscopy enables the direct detection of a single molecule. However, the structure of the polymer chain as large as 100 nm cannot be resolved by conventional fluorescence methods because of the diffraction limit of light. In order to observe the single chains, we developed the labeling method of polymer materials with a photo-switchable dye and the super-resolution microscopy. The real-space conformational analysis of single polymer chains with the spatial resolution of 15-20 nm was achieved. The super-resolution microscopy enables us to obtain the three-dimensional coordinates; therefore, we succeeded the conformational analysis in three dimensions. The direct observation by the nanometric optical microscopy would reveal the detailed information on the molecular processes in the various polymer systems.

Keywords: polymer materials, single molecule, super-resolution techniques, conformation

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5546 Prediction of Sepsis Illness from Patients Vital Signs Using Long Short-Term Memory Network and Dynamic Analysis

Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

Abstract:

The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

Procedia PDF Downloads 114
5545 The Complementary Effect of Internal Control System and Whistleblowing Policy on Prevention and Detection of Fraud in Nigerian Deposit Money Banks

Authors: Dada Durojaye Joshua

Abstract:

The study examined the combined effect of internal control system and whistle blowing policy while it pursues the following specific objectives, which are to: examine the relationship between monitoring activities and fraud’s detection and prevention; investigate the effect of control activities on fraud’s detection and prevention in Nigerian Deposit Money Banks (DMBs). The population of the study comprises the 89,275 members of staff in the 20 DMBs in Nigeria as at June 2019. Purposive and convenient sampling techniques were used in the selection of the 80 members of staff at the supervisory level of the Internal Audit Departments of the head offices of the sampled banks, that is, selecting 4 respondents (Audit Executive/Head, Internal Control; Manager, Operation Risk Management; Head, Financial Crime Control; the Chief Compliance Officer) from each of the 20 DMBs in Nigeria. A standard questionnaire was adapted from 2017/2018 Internal Control Questionnaire and Assessment, Bureau of Financial Monitoring and Accountability Florida Department of Economic Opportunity. It was modified to serve the purpose for which it was meant to serve. It was self-administered to gather data from the 80 respondents at the respective headquarters of the sampled banks at their respective locations across Nigeria. Two likert-scales was used in achieving the stated objectives. A logit regression was used in analysing the stated hypotheses. It was found that effect of monitoring activities using the construct of conduct of ongoing or separate evaluation (COSE), evaluation and communication of deficiencies (ECD) revealed that monitoring activities is significant and positively related to fraud’s detection and prevention in Nigerian DMBS. So also, it was found that control activities using selection and development of control activities (SDCA), selection and development of general controls over technology to prevent financial fraud (SDGCTF), development of control activities that gives room for transparency through procedures that put policies into actions (DCATPPA) contributed to influence fraud detection and prevention in the Nigerian DMBs. In addition, it was found that transparency, accountability, reliability, independence and value relevance have significant effect on fraud detection and prevention ibn Nigerian DMBs. The study concluded that the board of directors demonstrated independence from management and exercises oversight of the development and performance of internal control. Part of the conclusion was that there was accountability on the part of the owners and preparers of the financial reports and that the system gives room for the members of staff to account for their responsibilities. Among the recommendations was that the management of Nigerian DMBs should create and establish a standard Internal Control System strong enough to deter fraud in order to encourage continuity of operations by ensuring liquidity, solvency and going concern of the banks. It was also recommended that the banks create a structure that encourages whistleblowing to complement the internal control system.

Keywords: internal control, whistleblowing, deposit money banks, fraud prevention, fraud detection

Procedia PDF Downloads 68
5544 Imp_hist-Si: Improved Hybrid Image Segmentation Technique for Satellite Imagery to Decrease the Segmentation Error Rate

Authors: Neetu Manocha

Abstract:

Image segmentation is a technique where a picture is parted into distinct parts having similar features which have a place with similar items. Various segmentation strategies have been proposed as of late by prominent analysts. But, after ultimate thorough research, the novelists have analyzed that generally, the old methods do not decrease the segmentation error rate. Then author finds the technique HIST-SI to decrease the segmentation error rates. In this technique, cluster-based and threshold-based segmentation techniques are merged together. After then, to improve the result of HIST-SI, the authors added the method of filtering and linking in this technique named Imp_HIST-SI to decrease the segmentation error rates. The goal of this research is to find a new technique to decrease the segmentation error rates and produce much better results than the HIST-SI technique. For testing the proposed technique, a dataset of Bhuvan – a National Geoportal developed and hosted by ISRO (Indian Space Research Organisation) is used. Experiments are conducted using Scikit-image & OpenCV tools of Python, and performance is evaluated and compared over various existing image segmentation techniques for several matrices, i.e., Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR).

Keywords: satellite image, image segmentation, edge detection, error rate, MSE, PSNR, HIST-SI, linking, filtering, imp_HIST-SI

Procedia PDF Downloads 129
5543 Complementary Effect of Wistleblowing Policy and Internal Control System on Prevention and Detection of Fraud in Nigerian Deposit Money Banks

Authors: Dada Durojaye Joshua

Abstract:

The study examined the combined effect of internal control system and whistle blowing policy while it pursues the following specific objectives, which are to: examine the relationship between monitoring activities and fraud’s detection and prevention; investigate the effect of control activities on fraud’s detection and prevention in Nigerian Deposit Money Banks (DMBs). The population of the study comprises the 89,275 members of staff in the 20 DMBs in Nigeria as at June 2019. Purposive and convenient sampling techniques were used in the selection of the 80 members of staff at the supervisory level of the Internal Audit Departments of the head offices of the sampled banks, that is, selecting 4 respondents (Audit Executive/Head, Internal Control; Manager, Operation Risk Management; Head, Financial Crime Control; the Chief Compliance Officer) from each of the 20 DMBs in Nigeria. A standard questionnaire was adapted from 2017/2018 Internal Control Questionnaire and Assessment, Bureau of Financial Monitoring and Accountability Florida Department of Economic Opportunity. It was modified to serve the purpose for which it was meant to serve. It was self-administered to gather data from the 80 respondents at the respective headquarters of the sampled banks at their respective locations across Nigeria. Two likert-scales was used in achieving the stated objectives. A logit regression was used in analysing the stated hypotheses. It was found that effect of monitoring activities using the construct of conduct of ongoing or separate evaluation (COSE), evaluation and communication of deficiencies (ECD) revealed that monitoring activities is significant and positively related to fraud’s detection and prevention in Nigerian DMBS. So also, it was found that control activities using selection and development of control activities (SDCA), selection and development of general controls over technology to prevent financial fraud (SDGCTF), development of control activities that gives room for transparency through procedures that put policies into actions (DCATPPA) contributed to influence fraud detection and prevention in the Nigerian DMBs. In addition, it was found that transparency, accountability, reliability, independence and value relevance have significant effect on fraud detection and prevention ibn Nigerian DMBs. The study concluded that the board of directors demonstrated independence from management and exercises oversight of the development and performance of internal control. Part of the conclusion was that there was accountability on the part of the owners and preparers of the financial reports and that the system gives room for the members of staff to account for their responsibilities. Among the recommendations was that the management of Nigerian DMBs should create and establish a standard Internal Control System strong enough to deter fraud in order to encourage continuity of operations by ensuring liquidity, solvency and going concern of the banks. It was also recommended that the banks create a structure that encourages whistleblowing to complement the internal control system.

Keywords: internal control, whistleblowing, deposit money banks, fraud prevention, fraud detection

Procedia PDF Downloads 64
5542 High Thermal Selective Detection of NOₓ Using High Electron Mobility Transistor Based on Gallium Nitride

Authors: Hassane Ouazzani Chahdi, Omar Helli, Bourzgui Nour Eddine, Hassan Maher, Ali Soltani

Abstract:

The real-time knowledge of the NO, NO₂ concentration at high temperature, would allow manufacturers of automobiles to meet the upcoming stringent EURO7 anti-pollution measures for diesel engines. Knowledge of the concentration of each of these species will also enable engines to run leaner (i.e., more fuel efficient) while still meeting the anti-pollution requirements. Our proposed technology is promising in the field of automotive sensors. It consists of nanostructured semiconductors based on gallium nitride and zirconia dioxide. The development of new technologies for selective detection of NO and NO₂ gas species would be a critical enabler of superior depollution. The current response was well correlated to the NO concentration in the range of 0–2000 ppm, 0-2500 ppm NO₂, and 0-300 ppm NH₃ at a temperature of 600.

Keywords: NOₓ sensors, HEMT transistor, anti-pollution, gallium nitride, gas sensor

Procedia PDF Downloads 235
5541 Financial Service of Financial Institution for SME in Thailand

Authors: Charawee Butbumrung

Abstract:

This research aim to study the financial service of the Thailand financial Institution, second is to identify "best practices" offered by four financial institutions, namely, Kasikornthai Bank, Bangkok Bank, Siam Commercial Bank, and Thanachart Bank. In-depth interviews with managers of financial institution and borrowers reveal best practices from each financial institution. Close monitoring of and a close relationship with borrowers appear to be important for early detection of any problem. Another aspect that may be important is building up loyalty and developing reliability among members. A close and informal relationship with borrowers may also help in monitoring and early detection of problems that may arise in non-repayment of loans. Other factors that may be considered important to the success of a financial service scheme are cooperation and coordination among various agencies that provide additional support to borrowers. Indirectly, these support systems contribute to the success of a SME in Thailand.

Keywords: best practices, financial service, financial institution, SME in Thailand

Procedia PDF Downloads 281
5540 Quality Control of Automotive Gearbox Based On Vibration Signal Analysis

Authors: Nilson Barbieri, Bruno Matos Martins, Gabriel de Sant'Anna Vitor Barbieri

Abstract:

In more complex systems, such as automotive gearbox, a rigorous treatment of the data is necessary because there are several moving parts (gears, bearings, shafts, etc.), and in this way, there are several possible sources of errors and also noise. The basic objective of this work is the detection of damage in automotive gearbox. The detection methods used are the wavelet method, the bispectrum; advanced filtering techniques (selective filtering) of vibrational signals and mathematical morphology. Gearbox vibration tests were performed (gearboxes in good condition and with defects) of a production line of a large vehicle assembler. The vibration signals are obtained using five accelerometers in different positions of the sample. The results obtained using the kurtosis, bispectrum, wavelet and mathematical morphology showed that it is possible to identify the existence of defects in automotive gearboxes.

Keywords: automotive gearbox, mathematical morphology, wavelet, bispectrum

Procedia PDF Downloads 463
5539 Improving Subjective Bias Detection Using Bidirectional Encoder Representations from Transformers and Bidirectional Long Short-Term Memory

Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

Abstract:

Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

Procedia PDF Downloads 119