Search results for: compound processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4564

Search results for: compound processing

3664 Investigating the Form of the Generalised Equations of Motion of the N-Bob Pendulum and Computing Their Solution Using MATLAB

Authors: Divij Gupta

Abstract:

Pendular systems have a range of both mathematical and engineering applications, ranging from modelling the behaviour of a continuous mass-density rope to utilisation as Tuned Mass Dampers (TMD). Thus, it is of interest to study the differential equations governing the motion of such systems. Here we attempt to generalise these equations of motion for the plane compound pendulum with a finite number of N point masses. A Lagrangian approach is taken, and we attempt to find the generalised form for the Euler-Lagrange equations of motion for the i-th bob of the N -bob pendulum. The co-ordinates are parameterized as angular quantities to reduce the number of degrees of freedom from 2N to N to simplify the form of the equations. We analyse the form of these equations up to N = 4 to determine the general form of the equation. We also develop a MATLAB program to compute a solution to the system for a given input value of N and a given set of initial conditions.

Keywords: classical mechanics, differential equation, lagrangian analysis, pendulum

Procedia PDF Downloads 189
3663 Optimizing Telehealth Internet of Things Integration: A Sustainable Approach through Fog and Cloud Computing Platforms for Energy Efficiency

Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

Abstract:

The swift proliferation of telehealth Internet of Things (IoT) devices has sparked concerns regarding energy consumption and the need for streamlined data processing. This paper presents an energy-efficient model that integrates telehealth IoT devices into a platform based on fog and cloud computing. This integrated system provides a sustainable and robust solution to address the challenges. Our model strategically utilizes fog computing as a localized data processing layer and leverages cloud computing for resource-intensive tasks, resulting in a significant reduction in overall energy consumption. The incorporation of adaptive energy-saving strategies further enhances the efficiency of our approach. Simulation analysis validates the effectiveness of our model in improving energy efficiency for telehealth IoT systems, particularly when integrated with localized fog nodes and both private and public cloud infrastructures. Subsequent research endeavors will concentrate on refining the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability across various healthcare and industry sectors.

Keywords: energy-efficient, fog computing, IoT, telehealth

Procedia PDF Downloads 58
3662 Application Methodology for the Generation of 3D Thermal Models Using UAV Photogrammety and Dual Sensors for Mining/Industrial Facilities Inspection

Authors: Javier Sedano-Cibrián, Julio Manuel de Luis-Ruiz, Rubén Pérez-Álvarez, Raúl Pereda-García, Beatriz Malagón-Picón

Abstract:

Structural inspection activities are necessary to ensure the correct functioning of infrastructures. Unmanned Aerial Vehicle (UAV) techniques have become more popular than traditional techniques. Specifically, UAV Photogrammetry allows time and cost savings. The development of this technology has permitted the use of low-cost thermal sensors in UAVs. The representation of 3D thermal models with this type of equipment is in continuous evolution. The direct processing of thermal images usually leads to errors and inaccurate results. A methodology is proposed for the generation of 3D thermal models using dual sensors, which involves the application of visible Red-Blue-Green (RGB) and thermal images in parallel. Hence, the RGB images are used as the basis for the generation of the model geometry, and the thermal images are the source of the surface temperature information that is projected onto the model. Mining/industrial facilities representations that are obtained can be used for inspection activities.

Keywords: aerial thermography, data processing, drone, low-cost, point cloud

Procedia PDF Downloads 122
3661 Evaluation of Parameters of Subject Models and Their Mutual Effects

Authors: A. G. Kovalenko, Y. N. Amirgaliyev, A. U. Kalizhanova, L. S. Balgabayeva, A. H. Kozbakova, Z. S. Aitkulov

Abstract:

It is known that statistical information on operation of the compound multisite system is often far from the description of actual state of the system and does not allow drawing any conclusions about the correctness of its operation. For example, from the world practice of operation of systems of water supply, water disposal, it is known that total measurements at consumers and at suppliers differ between 40-60%. It is connected with mathematical measure of inaccuracy as well as ineffective running of corresponding systems. Analysis of widely-distributed systems is more difficult, in which subjects, which are self-maintained in decision-making, carry out economic interaction in production, act of purchase and sale, resale and consumption. This work analyzed mathematical models of sellers, consumers, arbitragers and the models of their interaction in the provision of dispersed single-product market of perfect competition. On the basis of these models, the methods, allowing estimation of every subject’s operating options and systems as a whole are given.

Keywords: dispersed systems, models, hydraulic network, algorithms

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3660 A Computational Approach to Screen Antagonist’s Molecule against Mycobacterium tuberculosis Lipoprotein LprG (Rv1411c)

Authors: Syed Asif Hassan, Tabrej Khan

Abstract:

Tuberculosis (TB) caused by bacillus Mycobacterium tuberculosis (Mtb) continues to take a disturbing toll on human life and healthcare facility worldwide. The global burden of TB remains enormous. The alarming rise of multi-drug resistant strains of Mycobacterium tuberculosis calls for an increase in research efforts towards the development of new target specific therapeutics against diverse strains of M. tuberculosis. Therefore, the discovery of new molecular scaffolds targeting new drug sites should be a priority for a workable plan for fighting resistance in Mycobacterium tuberculosis (Mtb). Mtb non-acylated lipoprotein LprG (Rv1411c) has a Toll-like receptor 2 (TLR2) agonist actions that depend on its association with triacylated glycolipids binding specifically with the hydrophobic pocket of Mtb LprG lipoprotein. The detection of a glycolipid carrier function has important implications for the role of LprG in Mycobacterial physiology and virulence. Therefore, considering the pivotal role of glycolipids in mycobacterial physiology and host-pathogen interactions, designing competitive antagonist (chemotherapeutics) ligands that competitively bind to glycolipid binding domain in LprG lipoprotein, will lead to inhibition of tuberculosis infection in humans. In this study, a unified approach involving ligand-based virtual screening protocol USRCAT (Ultra Shape Recognition) software and molecular docking studies using Auto Dock Vina 1.1.2 using the X-ray crystal structure of Mtb LprG protein was implemented. The docking results were further confirmed by DSX (DrugScore eXtented), a robust program to evaluate the binding energy of ligands bound to the Ligand binding domain of the Mtb LprG lipoprotein. The ligand, which has the higher hypothetical affinity, also has greater negative value. Based on the USRCAT, Lipinski’s values and molecular docking results, [(2R)-2,3-di(hexadecanoyl oxy)propyl][(2S,3S,5S,6R)-3,4,5-trihydroxy-2,6-bis[[(2R,3S,4S,5R,6S)-3,4,5-trihydroxy-6 (hydroxymethyl)tetrahydropyran-2-yl]oxy]cyclohexyl] phosphate (XPX) was confirmed as a promising drug-like lead compound (antagonist) binding specifically to the hydrophobic domain of LprG protein with affinity greater than that of PIM2 (agonist of LprG protein) with a free binding energy of -9.98e+006 Kcal/mol and binding affinity of -132 Kcal/mol, respectively. A further, in vitro assay of this compound is required to establish its potency in inhibiting molecular evasion mechanism of MTB within the infected host macrophages. These results will certainly be helpful in future anti-TB drug discovery efforts against Multidrug-Resistance Tuberculosis (MDR-TB).

Keywords: antagonist, agonist, binding affinity, chemotherapeutics, drug-like, multi drug resistance tuberculosis (MDR-TB), RV1411c protein, toll-like receptor (TLR2)

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3659 Wave Agitated Signatures in the Oolitic Limestones of Kunihar Formation, Proterozoic Simla Group, Lesser Himalaya, India

Authors: Alono Thorie, Ananya Mukhopadhyay

Abstract:

Ooid bearing horizons of the Proterozoic Kunihar Formation, Simla Group, Lesser Himalaya have been addressed in the present work. The study is concentrated around the outskirts of Arki town, Solan district, Himachal Pradesh, India. Based on the sedimentary facies associations, the processes that promote the formation of ooids have been documented. The facies associations that have been recorded are: (i) Oolitic-Intraclastic grainstone (FA1), (ii) Oolitic grainstone (FA2), (iii) Boundstone (FA3), (iv) Dolomudstone (FA4) and (v) Rudstone (FA5). Oolitic-Intraclastic grainstone (FA1) mainly consists of well sorted ooids with concentric laminae and intraclasts. Large ooids with grain sizes more than 4 mm are characteristic of oolites throughout the area. Normally graded beds consisting of ooids and intraclasts are frequently documented in storm sediments in shelf environments and carbonate platforms. The well-sorted grainstone fabric indicates deposition in a high-energy shoal with tidal currents and storm reworking. FA2 comprises spherical to elliptical grains up to 8.5cm in size with concentric cortex and micritic nuclei. Peloids in FA2 are elliptical, rounded objects <0.3 mm in size. FA1 and FA2 have been recorded alongside boundstones (FA3) comprising stromatolites having columnar, wavy and domal morphology. Boundstones (FA3) reflect microbial growth in carbonate platforms and reefs. Dolomudstones (FA4) interbedded with cross laminated sandstones and erosional surfaces reflect sedimentation in storm dominated zones below fair-weather wave base. Rudstone (FA5) is composed of oolitic grainstone (FA2), boundstone (FA3) and dolomudstone (FA4). These clasts are few mm to more than 10 cm in length. Rudstones indicate deposition along a slope with intermittent influence of wave currents and storm activities. Most ooids from the Kunihar Formation are regular ooids with abundance of broken ooids. Compound and concentric ooids indicating medium to low energy environments are present but scarce. Ooids from high energy domains are more dominant than ooids developed from low energy environments. The unusually large size of the Kunihar ooids (more than 8.5 cm) is rare in the geological record. Development of carbonate deposits such as oolitic- intraclastic Grainstones (FA1), oolitic grainstones (FA2) and rudstones (FA5), and reflect deposition in an agitated beach environment with abundant microbial activity and high energy shallow marine waters influenced by tide, wave and storm currents. Occurrences of boundstone (FA4) or stromatolitic carbonate amongst oolitic facies (FA1 and FA2) and appearance of compound and concentric ooids indicate intervals of calm in between agitated phases of storm, wave and tidal activities.

Keywords: proterozoic, Simla Group, ooids, stromatolites

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3658 Proposition Model of Micromechanical Damage to Predict Reduction in Stiffness of a Fatigued A-SMC Composite

Authors: Houssem Ayari

Abstract:

Sheet molding compounds (SMC) are high strength thermoset moulding materials reinforced with glass treated with thermocompression. SMC composites combine fibreglass resins and polyester/phenolic/vinyl and unsaturated acrylic to produce a high strength moulding compound. These materials are usually formulated to meet the performance requirements of the moulding part. In addition, the vinyl ester resins used in the new advanced SMC systems (A-SMC) have many desirable features, including mechanical properties comparable to epoxy, excellent chemical resistance and tensile resistance, and cost competitiveness. In this paper, a proposed model is used to take into account the Young modulus evolutions of advanced SMC systems (A-SMC) composite under fatigue tests. The proposed model and the used approach are in good agreement with the experimental results.

Keywords: composites SFRC, damage, fatigue, Mori-Tanaka

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3657 The Role of Executive Attention and Literacy on Consumer Memory

Authors: Fereshteh Nazeri Bahadori

Abstract:

In today's competitive environment, any company that aims to operate in a market, whether industrial or consumer markets, must know that it cannot address all the tastes and demands of customers at once and serve them all. The study of consumer memory is considered an important subject in marketing research, and many companies have conducted studies on this subject and the factors affecting it due to its importance. Therefore, the current study tries to investigate the relationship between consumers' attention, literacy, and memory. Memory has a very close relationship with learning. Memory is the collection of all the information that we have understood and stored. One of the important subjects in consumer behavior is information processing by the consumer. One of the important factors in information processing is the mental involvement of the consumer, which has attracted a lot of attention in the past two decades. Since consumers are the turning point of all marketing activities, successful marketing begins with understanding why and how consumers behave. Therefore, in the current study, the role of executive attention and literacy on consumers' memory has been investigated. The results showed that executive attention and literacy would play a significant role in the long-term and short-term memory of consumers.

Keywords: literacy, consumer memory, executive attention, psychology of consumer behavior

Procedia PDF Downloads 73
3656 Performance Evaluation of Refinement Method for Wideband Two-Beams Formation

Authors: C. Bunsanit

Abstract:

This paper presents the refinement method for two beams formation of wideband smart antenna. The refinement method for weighting coefficients is based on Fully Spatial Signal Processing by taking Inverse Discrete Fourier Transform (IDFT), and its simulation results are presented using MATLAB. The radiation pattern is created by multiplying the incoming signal with real weights and then summing them together. These real weighting coefficients are computed by IDFT method; however, the range of weight values is relatively wide. Therefore, for reducing this range, the refinement method is used. The radiation pattern concerns with five input parameters to control. These parameters are maximum weighting coefficient, wideband signal, direction of mainbeam, beamwidth, and maximum of minor lobe level. Comparison of the obtained simulation results between using refinement method and taking only IDFT shows that the refinement method works well for wideband two beams formation.

Keywords: fully spatial signal processing, beam forming, refinement method, smart antenna, weighting coefficient, wideband

Procedia PDF Downloads 216
3655 Modified Graphene Oxide in Ceramic Composite

Authors: Natia Jalagonia, Jimsher Maisuradze, Karlo Barbakadze, Tinatin Kuchukhidze

Abstract:

At present intensive scientific researches of ceramics, cermets and metal alloys have been conducted for improving materials physical-mechanical characteristics. In purpose of increasing impact strength of ceramics based on alumina, simple method of graphene homogenization was developed. Homogeneous distribution of graphene (homogenization) in pressing composite became possible through the connection of functional groups of graphene oxide (-OH, -COOH, -O-O- and others) and alumina superficial OH groups with aluminum organic compounds. These two components connect with each other with -O-Al–O- bonds, and by their thermal treatment (300–500°C), graphene and alumina phase are transformed. Thus, choosing of aluminum organic compounds for modification is stipulated by the following opinion: aluminum organic compounds fragments fixed on graphene and alumina finally are transformed into an integral part of the matrix. By using of other elements as modifier on the matrix surface (Al2O3) other phases are transformed, which change sharply physical-mechanical properties of ceramic composites, for this reason, effect caused by the inclusion of graphene will be unknown. Fixing graphene fragments on alumina surface by alumoorganic compounds result in new type graphene-alumina complex, in which these two components are connected by C-O-Al bonds. Part of carbon atoms in graphene oxide are in sp3 hybrid state, so functional groups (-OH, -COOH) are located on both sides of graphene oxide layer. Aluminum organic compound reacts with graphene oxide at the room temperature, and modified graphene oxide is obtained: R2Al-O-[graphene]–COOAlR2. Remaining Al–C bonds also reacts rapidly with surface OH groups of alumina. In a result of these process, pressing powdery composite [Al2O3]-O-Al-O-[graphene]–COO–Al–O–[Al2O3] is obtained. For the purpose, graphene oxide suspension in dry toluene have added alumoorganic compound Al(iC4H9)3 in toluene with equimolecular ratio. Obtained suspension has put in the flask and removed solution in a rotary evaporate presence nitrogen atmosphere. Obtained powdery have been researched and used to consolidation of ceramic materials based on alumina. Ceramic composites are obtained in high temperature vacuum furnace with different temperature and pressure conditions. Received ceramics do not have open pores and their density reaches 99.5 % of TD. During the work, the following devices have been used: High temperature vacuum furnace OXY-GON Industries Inc (USA), device of spark-plasma synthesis, induction furnace, Electronic Scanning Microscopes Nikon Eclipse LV 150, Optical Microscope NMM-800TRF, Planetary mill Pulverisette 7 premium line, Shimadzu Dynamic Ultra Micro Hardness Tester DUH-211S, Analysette 12 Dynasizer and others.

Keywords: graphene oxide, alumo-organic, ceramic

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3654 Failure Mode Analysis of a Multiple Layer Explosion Bonded Cryogenic Transition Joint

Authors: Richard Colwell, Thomas Englert

Abstract:

In cryogenic liquefaction processes, brazed aluminum core heat exchangers are used to minimize surface area/volume of the exchanger. Aluminum alloy (5083-H321; UNS A95083) piping must transition to higher melting point 304L stainless steel piping outside of the heat exchanger kettle or cold box for safety reasons. Since aluminum alloys and austenitic stainless steel cannot be directly welded to together, a transition joint consisting of 5 layers of different metals explosively bonded are used. Failures of two of these joints resulted in process shut-down and loss of revenue. Failure analyses, FEA analysis, and mock-up testing were performed by multiple teams to gain a further understanding into the failure mechanisms involved.

Keywords: explosion bonding, intermetallic compound, thermal strain, titanium-nickel Interface

Procedia PDF Downloads 193
3653 Effect of Some Metal Ions on the Activity of Lipase Produced by Aspergillus Niger Cultured on Vitellaria Paradoxa Shells

Authors: Abdulhakeem Sulyman, Olukotun Zainab, Hammed Abdulquadri

Abstract:

Lipases (triacylglycerol acyl hydrolases) (EC 3.1.1.3) are class of enzymes that catalyses the hydrolysis of triglycerides to glycerol and free fatty acids. They account for up to 10% of the enzyme in the market and have a wide range of applications in biofuel production, detergent formulation, leather processing and in food and feed processing industry. This research was conducted to study the effect of some metal ions on the activity of purified lipase produced by Aspergillus niger cultured on Vitellaria paradoxa shells. Purified lipase in 12.5 mM p-NPL was incubated with different metal ions (Zn²⁺, Ca²⁺, Mn²⁺, Fe²⁺, Na⁺, K⁺ and Mg²⁺). The final concentrations of metal ions investigated were 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 and 1.0 mM. The results obtained from the study showed that Zn²⁺, Ca²⁺, Mn²⁺ and Fe²⁺ ions increased the activity of lipase up to 3.0, 3.0, 1.0, and 26.0 folds respectively. Lipase activity was partially inhibited by Na⁺ and Mg²⁺ with up to 88.5% and 83.7% loss of activity respectively. Lipase activity was also inhibited by K⁺ with up to 56.7% loss in the activity as compared to in the absence of metal ions. The study concluded that lipase produced by Aspergillus niger cultured on Vitellaria paradoxa shells can be activated by the presence of Zn²⁺, Ca²⁺, Mn²⁺ and Fe²⁺ and inhibited by Na⁺, K⁺ and Mg²⁺.

Keywords: Aspergillus niger, Vitellaria paradoxa, lipase, metal ions

Procedia PDF Downloads 133
3652 Online Monitoring Rheological Property of Polymer Melt during Injection Molding

Authors: Chung-Chih Lin, Chien-Liang Wu

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The detection of the polymer melt state during manufacture process is regarded as an efficient way to control the molded part quality in advance. Online monitoring rheological property of polymer melt during processing procedure provides an approach to understand the melt state immediately. Rheological property reflects the polymer melt state at different processing parameters and is very important in injection molding process especially. An approach that demonstrates how to calculate rheological property of polymer melt through in-process measurement, using injection molding as an example, is proposed in this study. The system consists of two sensors and a data acquisition module can process the measured data, which are used for the calculation of rheological properties of polymer melt. The rheological properties of polymer melt discussed in this study include shear rate and viscosity which are investigated with respect to injection speed and melt temperature. The results show that the effect of injection speed on the rheological properties is apparent, especially for high melt temperature and should be considered for precision molding process.

Keywords: injection molding, melt viscosity, shear rate, monitoring

Procedia PDF Downloads 367
3651 Detection of Image Blur and Its Restoration for Image Enhancement

Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

Abstract:

Image restoration in the process of communication is one of the emerging fields in the image processing. The motion analysis processing is the simplest case to detect motion in an image. Applications of motion analysis widely spread in many areas such as surveillance, remote sensing, film industry, navigation of autonomous vehicles, etc. The scene may contain multiple moving objects, by using motion analysis techniques the blur caused by the movement of the objects can be enhanced by filling-in occluded regions and reconstruction of transparent objects, and it also removes the motion blurring. This paper presents the design and comparison of various motion detection and enhancement filters. Median filter, Linear image deconvolution, Inverse filter, Pseudoinverse filter, Wiener filter, Lucy Richardson filter and Blind deconvolution filters are used to remove the blur. In this work, we have considered different types and different amount of blur for the analysis. Mean Square Error (MSE) and Peak Signal to Noise Ration (PSNR) are used to evaluate the performance of the filters. The designed system has been implemented in Matlab software and tested for synthetic and real-time images.

Keywords: image enhancement, motion analysis, motion detection, motion estimation

Procedia PDF Downloads 272
3650 Torque Magnetometry of Low Anisotropic CaCo2As2 Single Crystals

Authors: Kashif Nadeem, W. Zhang, X. G. Qiu

Abstract:

Role of Co spins in CaCo2As2 single crystal is systematically studied by using dc magnetization and magnetic torque measurements. A spin-flop transition in the antiferromagnetism (AFM) CaCo2As2 single crystal is studied by using dc magnetization and magnetic torque. Field dependent and angle dependent torque magnetometry confirmed the existence of spin-flop transition in this compound which is in agreement with the dc magnetization studies. A comparison of dc magnetization and torque magnetometry measurements for CaCo2As2 single crystal is done in detail. In conclusion, torque magnetometry can be a useful tool to study the spin flop transition in low anisotropic compounds analogous to dc magnetization studies.

Keywords: spin flop transition, torque magnetometry, magnetization, anisotropic

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3649 Artificial Intelligence and Distributed System Computing: Application and Practice in Real Life

Authors: Lai Junzhe, Wang Lihao, Burra Venkata Durga Kumar

Abstract:

In recent years, due to today's global technological advances, big data and artificial intelligence technologies have been widely used in various industries and fields, playing an important role in reducing costs and increasing efficiency. Among them, artificial intelligence has derived another branch in its own continuous progress and the continuous development of computer personnel, namely distributed artificial intelligence computing systems. Distributed AI is a method for solving complex learning, decision-making, and planning problems, characterized by the ability to take advantage of large-scale computation and the spatial distribution of resources, and accordingly, it can handle problems with large data sets. Nowadays, distributed AI is widely used in military, medical, and human daily life and brings great convenience and efficient operation to life. In this paper, we will discuss three areas of distributed AI computing systems in vision processing, blockchain, and smart home to introduce the performance of distributed systems and the role of AI in distributed systems.

Keywords: distributed system, artificial intelligence, blockchain, IoT, visual information processing, smart home

Procedia PDF Downloads 94
3648 Deep Learning Based Road Crack Detection on an Embedded Platform

Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

Abstract:

It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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3647 Exploring the Intersection Between the General Data Protection Regulation and the Artificial Intelligence Act

Authors: Maria Jędrzejczak, Patryk Pieniążek

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The European legal reality is on the eve of significant change. In European Union law, there is talk of a “fourth industrial revolution”, which is driven by massive data resources linked to powerful algorithms and powerful computing capacity. The above is closely linked to technological developments in the area of artificial intelligence, which has prompted an analysis covering both the legal environment as well as the economic and social impact, also from an ethical perspective. The discussion on the regulation of artificial intelligence is one of the most serious yet widely held at both European Union and Member State level. The literature expects legal solutions to guarantee security for fundamental rights, including privacy, in artificial intelligence systems. There is no doubt that personal data have been increasingly processed in recent years. It would be impossible for artificial intelligence to function without processing large amounts of data (both personal and non-personal). The main driving force behind the current development of artificial intelligence is advances in computing, but also the increasing availability of data. High-quality data are crucial to the effectiveness of many artificial intelligence systems, particularly when using techniques involving model training. The use of computers and artificial intelligence technology allows for an increase in the speed and efficiency of the actions taken, but also creates security risks for the data processed of an unprecedented magnitude. The proposed regulation in the field of artificial intelligence requires analysis in terms of its impact on the regulation on personal data protection. It is necessary to determine what the mutual relationship between these regulations is and what areas are particularly important in the personal data protection regulation for processing personal data in artificial intelligence systems. The adopted axis of considerations is a preliminary assessment of two issues: 1) what principles of data protection should be applied in particular during processing personal data in artificial intelligence systems, 2) what regulation on liability for personal data breaches is in such systems. The need to change the regulations regarding the rights and obligations of data subjects and entities processing personal data cannot be excluded. It is possible that changes will be required in the provisions regarding the assignment of liability for a breach of personal data protection processed in artificial intelligence systems. The research process in this case concerns the identification of areas in the field of personal data protection that are particularly important (and may require re-regulation) due to the introduction of the proposed legal regulation regarding artificial intelligence. The main question that the authors want to answer is how the European Union regulation against data protection breaches in artificial intelligence systems is shaping up. The answer to this question will include examples to illustrate the practical implications of these legal regulations.

Keywords: data protection law, personal data, AI law, personal data breach

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3646 Leuco Dye-Based Thermochromic Systems for Application in Temperature Sensing

Authors: Magdalena Wilk-Kozubek, Magdalena Rowińska, Krzysztof Rola, Joanna Cybińska

Abstract:

Leuco dye-based thermochromic systems are classified as intelligent materials because they exhibit thermally induced color changes. Thanks to this feature, they are mainly used as temperature sensors in many industrial sectors. For example, placing a thermochromic material on a chemical reactor may warn about exceeding the maximum permitted temperature for a chemical process. Usually two components, a color former and a developer are needed to produce a system with irreversible color change. The color former is an electron donating (proton accepting) compound such as fluoran leuco dye. The developer is an electron accepting (proton donating) compound such as organic carboxylic acid. When the developer melts, the color former - developer complex is created and the termochromic system becomes colored. Typically, the melting point of the applied developer determines the temperature at which the color change occurs. When the lactone ring of the color former is closed, then the dye is in its colorless state. The ring opening, induced by the addition of a proton, causes the dye to turn into its colored state. Since the color former and the developer are often solid, they can be incorporated into polymer films to facilitate their practical use in industry. The objective of this research was to fabricate a leuco dye-based termochromic system that will irreversibly change color after reaching the temperature of 100°C. For this purpose, benzofluoran leuco dye (as color former) and phenoxyacetic acid (as developer with a melting point of 100°C) were introduced into the polymer films during the drop casting process. The film preparation process was optimized in order to obtain thin films with appropriate properties such as transparency, flexibility and homogeneity. Among the optimized factors were the concentration of benzofluoran leuco dye and phenoxyacetic acid, the type, average molecular weight and concentration of the polymer, and the type and concentration of the surfactant. The selected films, containing benzofluoran leuco dye and phenoxyacetic acid, were combined by mild heat treatment. Structural characterization of single and combined films was carried out by FTIR spectroscopy, morphological analysis was performed by optical microscopy and SEM, phase transitions were examined by DSC, color changes were investigated by digital photography and UV-Vis spectroscopy, while emission changes were studied by photoluminescence spectroscopy. The resulting thermochromic system is colorless at room temperature, but after reaching 100°C the developer melts and it turns irreversibly pink. Therefore, it could be used as an additional sensor to warn against boiling of water in power plants using water cooling. Currently used electronic temperature indicators are prone to faults and unwanted third-party actions. The sensor constructed in this work is transparent, thanks to which it can be unnoticed by an outsider and constitute a reliable reference for the person responsible for the apparatus.

Keywords: color developer, leuco dye, thin film, thermochromism

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3645 A Neural Network Based Clustering Approach for Imputing Multivariate Values in Big Data

Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

Procedia PDF Downloads 261
3644 An ERP Study of Chinese Pseudo-Object Structures

Authors: Changyin Zhou

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Verb-argument relation is a very important aspect of syntax-semantics interaction in sentence processing. Previous ERP (event related potentials) studies in this field mainly concentrated on the relation between the verb and its core arguments. The present study aims to reveal the ERP pattern of Chinese pseudo-object structures (SOSs), in which a peripheral argument is promoted to occupy the position of the patient object, as compared with the patient object structures (POSs). The ERP data were collected when participants were asked to perform acceptability judgments about Chinese phrases. Our result shows that, similar to the previous studies of number-of-argument violations, Chinese SOSs show a bilaterally distributed N400 effect. But different from all the previous studies of verb-argument relations, Chinese SOSs demonstrate a sustained anterior positivity (SAP). This SAP, which is the first report related to complexity of argument structure operation, reflects the integration difficulty of the newly promoted arguments and the progressive nature of well-formedness checking in the processing of Chinese SOSs.

Keywords: Chinese pseudo-object structures, ERP, sustained anterior positivity, verb-argument relation

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3643 Thermo-Mechanical Processing Scheme to Obtain Micro-Duplex Structure Favoring Superplasticity in an As-Cast and Homogenized Medium Alloyed Nickel Base Superalloy

Authors: K. Sahithya, I. Balasundar, Pritapant, T. Raghua

Abstract:

Ni-based superalloy with a nominal composition Ni-14% Cr-11% Co-5.8% Mo-2.4% Ti-2.4% Nb-2.8% Al-0.26 % Fe-0.032% Si-0.069% C (all in wt %) is used as turbine discs in a variety of aero engines. Like any other superalloy, the primary processing of the as-cast superalloy poses a major challenge due to its complex alloy chemistry. The challenge was circumvented by characterizing the different phases present in the material, optimizing the homogenization treatment, identifying a suitable thermomechanical processing window using dynamic materials modeling. The as-cast material was subjected to homogenization at 1200°C for a soaking period of 8 hours and quenched using different media. Water quenching (WQ) after homogenization resulted in very fine spherical γꞌ precipitates of sizes 30-50 nm, whereas furnace cooling (FC) after homogenization resulted in bimodal distribution of precipitates (primary gamma prime of size 300nm and secondary gamma prime of size 5-10 nm). MC type primary carbides that are stable till the melting point of the material were found in both WQ and FC samples. Deformation behaviour of both the materials below (1000-1100°C) and above gamma prime solvus (1100-1175°C) was evaluated by subjecting the material to series of compression tests at different constant true strain rates (0.0001/sec-1/sec). An in-detail examination of the precipitate dislocation interaction mechanisms carried out using TEM revealed precipitate shearing and Orowan looping as the mechanisms governing deformation in WQ and FC, respectively. Incoherent/semi coherent gamma prime precipitates in the case of FC material facilitates better workability of the material, whereas the coherent precipitates in WQ material contributed to higher resistance to deformation of the material. Both the materials exhibited discontinuous dynamic recrystallization (DDRX) above gamma prime solvus temperature. The recrystallization kinetics was slower in the case of WQ material. Very fine grain boundary carbides ( ≤ 300 nm) retarded the recrystallisation kinetics in WQ. Coarse carbides (1-5 µm) facilitate particle stimulated nucleation in FC material. The FC material was cogged (primary hot working) 1120˚C, 0.03/sec resulting in significant grain refinement, i.e., from 3000 μm to 100 μm. The primary processed material was subjected to intensive thermomechanical deformation subsequently by reducing the temperature by 50˚C in each processing step with intermittent heterogenization treatment at selected temperatures aimed at simultaneous coarsening of the gamma prime precipitates and refinement of the gamma matrix grains. The heterogeneous annealing treatment carried out, resulted in gamma grains of 10 μm and gamma prime precipitates of 1-2 μm. Further thermo mechanical processing of the material was carried out at 1025˚C to increase the homogeneity of the obtained micro-duplex structure.

Keywords: superalloys, dynamic material modeling, nickel alloys, dynamic recrystallization, superplasticity

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3642 Functional Neural Network for Decision Processing: A Racing Network of Programmable Neurons Where the Operating Model Is the Network Itself

Authors: Frederic Jumelle, Kelvin So, Didan Deng

Abstract:

In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

Procedia PDF Downloads 107
3641 Synthesis, Characterization and Anti-Microbial Study of Urethanized Poly Vinyl Alcohol Metal Complexes

Authors: Maha A. Younus, Dhefaf H. Badri, Maha A. Al Abayaji, Taha M. Salih

Abstract:

Polymer metal complexes of poly vinyl alcohol and Cu (II), Ni (II), Mn (II) and Co (III) were prepared from the reaction of PVA with three different percentages of urea. The compound was characterized by fourier transform infrared spectrometry (FTIR) analysis and differential scanning calorimetric (DSC) Analysis. It has been established that the polymer and its metal complexes showed good activities against nine pathogenic bacteria (Escherichia coli, Klebsiellapneumonae, Staphylococcusaureus, Staphylococcus Albus, Salmonella Typhoid, Pseudomonas Aeruginosa, Shigella Dysentery, Proteus Morgani, Brucella Militensis). The polymer metal complexes show activity higher than that of the free polymer. The increasing activities were in the order (polymer < pol-Mn< pol-Co < pol-Ni ˂ pol-Cu). The ability of these compounds to show antimicrobial properties suggests that they can be further evaluated for medicinal and/or environmental applications.

Keywords: antimicrobial activity, PVA, polymer-metal complex, urea

Procedia PDF Downloads 321
3640 An Event-Related Potential Investigation of Speech-in-Noise Recognition in Native and Nonnative Speakers of English

Authors: Zahra Fotovatnia, Jeffery A. Jones, Alexandra Gottardo

Abstract:

Speech communication often occurs in environments where noise conceals part of a message. Listeners should compensate for the lack of auditory information by picking up distinct acoustic cues and using semantic and sentential context to recreate the speaker’s intended message. This situation seems to be more challenging in a nonnative than native language. On the other hand, early bilinguals are expected to show an advantage over the late bilingual and monolingual speakers of a language due to their better executive functioning components. In this study, English monolingual speakers were compared with early and late nonnative speakers of English to understand speech in noise processing (SIN) and the underlying neurobiological features of this phenomenon. Auditory mismatch negativities (MMNs) were recorded using a double-oddball paradigm in response to a minimal pair that differed in their middle vowel (beat/bit) at Wilfrid Laurier University in Ontario, Canada. The results did not show any significant structural and electroneural differences across groups. However, vocabulary knowledge correlated positively with performance on tests that measured SIN processing in participants who learned English after age 6. Moreover, their performance on the test negatively correlated with the integral area amplitudes in the left superior temporal gyrus (STG). In addition, the STG was engaged before the inferior frontal gyrus (IFG) in noise-free and low-noise test conditions in all groups. We infer that the pre-attentive processing of words engages temporal lobes earlier than the fronto-central areas and that vocabulary knowledge helps the nonnative perception of degraded speech.

Keywords: degraded speech perception, event-related brain potentials, mismatch negativities, brain regions

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3639 Using Analytical Hierarchy Process and TOPSIS Approaches in Designing a Finite Element Analysis Automation Program

Authors: Ming Wen, Nasim Nezamoddini

Abstract:

Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.

Keywords: finite element analysis, FEA, random vibration fatigue, process automation, analytical hierarchy process, AHP, TOPSIS, multiple-criteria decision-making, MCDM

Procedia PDF Downloads 95
3638 The Effects of Various Curing Compounds on the Mechanical Characteristics of Roller Compacted Concrete Pavements (RCCP)

Authors: Azadeh Askarinejad, Parmida Hayati, Parham Hayati, Reza Parchami

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Curing is a very important factor in the ultimate strength and durability of roller compacted concrete pavements (RCCP). Curing involves keeping the concrete is saturated or close to saturation point. Since maintaining concrete moisture has a significant impact on its mechanical properties, permeability and durability, curing is important. The most common procedure for curing of roller compacted concrete is using a white pigmented curing compound. This method is effective, economical and fast. In the present study, different curing compounds were applied on concrete specimens and the results of their effects on the mechanical properties were compared with each other and usual methods of curing in order to select appropriate materials and methods of curing for RCCP construction.

Keywords: curing compounds, roller compacted concrete pavements, mechanical properties, durability

Procedia PDF Downloads 592
3637 Neural Correlates of Diminished Humor Comprehension in Schizophrenia: A Functional Magnetic Resonance Imaging Study

Authors: Przemysław Adamczyk, Mirosław Wyczesany, Aleksandra Domagalik, Artur Daren, Kamil Cepuch, Piotr Błądziński, Tadeusz Marek, Andrzej Cechnicki

Abstract:

The present study aimed at evaluation of neural correlates of humor comprehension impairments observed in schizophrenia. To investigate the nature of this deficit in schizophrenia and to localize cortical areas involved in humor processing we used functional magnetic resonance imaging (fMRI). The study included chronic schizophrenia outpatients (SCH; n=20), and sex, age and education level matched healthy controls (n=20). The task consisted of 60 stories (setup) of which 20 had funny, 20 nonsensical and 20 neutral (not funny) punchlines. After the punchlines were presented, the participants were asked to indicate whether the story was comprehensible (yes/no) and how funny it was (1-9 Likert-type scale). fMRI was performed on a 3T scanner (Magnetom Skyra, Siemens) using 32-channel head coil. Three contrasts in accordance with the three stages of humor processing were analyzed in both groups: abstract vs neutral stories - incongruity detection; funny vs abstract - incongruity resolution; funny vs neutral - elaboration. Additionally, parametric modulation analysis was performed using both subjective ratings separately in order to further differentiate the areas involved in incongruity resolution processing. Statistical analysis for behavioral data used U Mann-Whitney test and Bonferroni’s correction, fMRI data analysis utilized whole-brain voxel-wise t-tests with 10-voxel extent threshold and with Family Wise Error (FWE) correction at alpha = 0.05, or uncorrected at alpha = 0.001. Between group comparisons revealed that the SCH subjects had attenuated activation in: the right superior temporal gyrus in case of irresolvable incongruity processing of nonsensical puns (nonsensical > neutral); the left medial frontal gyrus in case of incongruity resolution processing of funny puns (funny > nonsensical) and the interhemispheric ACC in case of elaboration of funny puns (funny > neutral). Additionally, the SCH group revealed weaker activation during funniness ratings in the left ventro-medial prefrontal cortex, the medial frontal gyrus, the angular and the supramarginal gyrus, and the right temporal pole. In comprehension ratings the SCH group showed suppressed activity in the left superior and medial frontal gyri. Interestingly, these differences were accompanied by protraction of time in both types of rating responses in the SCH group, a lower level of comprehension for funny punchlines and a higher funniness for absurd punchlines. Presented results indicate that, in comparison to healthy controls, schizophrenia is characterized by difficulties in humor processing revealed by longer reaction times, impairments of understanding jokes and finding nonsensical punchlines more funny. This is accompanied by attenuated brain activations, especially in the left fronto-parietal and the right temporal cortices. Disturbances of the humor processing seem to be impaired at the all three stages of the humor comprehension process, from incongruity detection, through its resolution to elaboration. The neural correlates revealed diminished neural activity of the schizophrenia brain, as compared with the control group. The study was supported by the National Science Centre, Poland (grant no 2014/13/B/HS6/03091).

Keywords: communication skills, functional magnetic resonance imaging, humor, schizophrenia

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3636 Design of a Graphical User Interface for Data Preprocessing and Image Segmentation Process in 2D MRI Images

Authors: Enver Kucukkulahli, Pakize Erdogmus, Kemal Polat

Abstract:

The 2D image segmentation is a significant process in finding a suitable region in medical images such as MRI, PET, CT etc. In this study, we have focused on 2D MRI images for image segmentation process. We have designed a GUI (graphical user interface) written in MATLABTM for 2D MRI images. In this program, there are two different interfaces including data pre-processing and image clustering or segmentation. In the data pre-processing section, there are median filter, average filter, unsharp mask filter, Wiener filter, and custom filter (a filter that is designed by user in MATLAB). As for the image clustering, there are seven different image segmentations for 2D MR images. These image segmentation algorithms are as follows: PSO (particle swarm optimization), GA (genetic algorithm), Lloyds algorithm, k-means, the combination of Lloyds and k-means, mean shift clustering, and finally BBO (Biogeography Based Optimization). To find the suitable cluster number in 2D MRI, we have designed the histogram based cluster estimation method and then applied to these numbers to image segmentation algorithms to cluster an image automatically. Also, we have selected the best hybrid method for each 2D MR images thanks to this GUI software.

Keywords: image segmentation, clustering, GUI, 2D MRI

Procedia PDF Downloads 355
3635 On a Single Server Queue with Arrivals in Batches of Variable Size, Generalized Coxian-2 Service and Compulsory Server Vacations

Authors: Kailash C. Madan

Abstract:

We study the steady state behaviour of a batch arrival single server queue in which the first service with general service times is compulsory and the second service with general service times is optional. We term such a two phase service as generalized Coxian-2 service. Just after completion of a service the server must take a vacation of random length of time with general vacation times. We obtain steady state probability generating functions for the queue size as well as the steady state mean queue size at a random epoch of time in explicit and closed forms. Some particular cases of interest including some known results have been derived.

Keywords: batch arrivals, compound Poisson process, generalized Coxian-2 service, steady state

Procedia PDF Downloads 438