Search results for: Mechanical intelligence
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1638

Search results for: Mechanical intelligence

678 Distributed System Computing Resource Scheduling Algorithm Based on Deep Reinforcement Learning

Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

Abstract:

As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling. The research proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling. The paper concludes the challenges and improvement directions for Deep Reinforcement Learning-based resource scheduling algorithms.

Keywords: Resource scheduling, deep reinforcement learning, distributed system, artificial intelligence.

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677 The Effect on Rolling Mill of Waviness in Hot Rolled Steel

Authors: Sunthorn S., Kittiphat R.

Abstract:

The edge waviness in hot rolled steel is a common defect. Variables that affect such defect include raw material and machine. These variables are necessary to consider to understand such defect. This research studied the defect of edge waviness for SS 400 of metal sheet manufacture. Defect of metal sheets were divided into two groups. The specimens were investigated on chemical composition and mechanical properties to find the difference. The results of investigation showed that the difference was not significant. Therefore the roll mill machine should be used to adjust to support another location on a roller to avoide edge waviness.

Keywords: Edge waviness, Hot rolling steel, Metal sheet defect, SS 400, Roll leveler.

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676 Methods and Algorithms of Ensuring Data Privacy in AI-Based Healthcare Systems and Technologies

Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

Abstract:

Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, these projects propose AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project present the best-in-school techniques used to preserve data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptography techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures, and identifies potential correction/mitigation measures.

Keywords: Data privacy, artificial intelligence, healthcare AI, data sharing, healthcare organizations.

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675 Mechanical and Microstructural Properties of Rotary-Swaged Wire of Commercial-Purity Titanium

Authors: Michal Duchek, Jan Palán, Tomas Kubina

Abstract:

Bars made of titanium grade 2 and grade 4 were subjected to rotary forging with up to 2.2 true strain reduction in the cross-section from 10 to 3.81 mm. During progressive deformation, grain refinement in the transverse direction took place. In the longitudinal direction, ultrafine microstructure has not developed. It has been demonstrated that titanium grade 2 strengthens more than grade 4. The ultimate tensile strength increased from 650 MPa to 1040 MPa in titanium grade 4. Hardness profiles on the cross section in both materials show an increase in the centre of the wire.

Keywords: Commercial-purity titanium, wire, rotary swaging, tensile test, hardness, modulus of elasticity, microstructure.

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674 Investigation of the Effect of Milling Time on the Mechanochemical Synthesis of Fe3Al/ Al2O3 Nanocomposite

Authors: B. Ghasemi, A. A. Najafzadeh Khoee

Abstract:

In this study, the effect of mechanical activation on the synthesis of Fe3Al/Al2O3 nanocomposite has been investigated by using mechanochemical method. For this purpose, Aluminum powder and hematite as precursors, with stoichiometric ratio, have been utilized and other effective parameters in milling process were kept constant. Phase formation analysis, crystallite size measurement and lattice strain were studied by X-ray diffraction (XRD) by using Williamson-Hall method as well as microstructure and morphology were explored by Scanning electron microscopy (SEM). Also, Energy-dispersive X-ray spectroscopy (EDX) analysis was used in order to probe the particle distribution. The results showed that after 30-hour milling, the reaction was started, combustibly done and completed.

Keywords: hematite, mechanochemical, milling, nanocomposite

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673 Mechanical Properties and Microstructural Properties of CrSiN Coating

Authors: Dhiflaoui Hafedh, Khlifi Kaouthar, Ben Cheikh Larbi Ahmed

Abstract:

The present study deals with the characterization of CrSiN coatings obtained by PVD magnetron sputtering systems. CrSiN films were deposited with different Si contents, in order to check the effect of at.% variation on the different properties of the Cr–N system. Coatings were characterized by scanning electron microscopy (SEM) for thickness measurements, X-ray diffraction. Surface morphology and the roughness characteristics were explored using AFM, Mechanicals properties, elastic and plastic deformation resistance of thin films were investigated using nanoindentation test. We observed that the Si addition improved the hardness and the Young’s modulus of the Cr–N system. Indeed, the hardness value is 18,56 GPa for CrSiN coatings. Besides, the Young’s modulus value is 224,22 GPa for CrSiN coatings for Si content of 1.2 at.%.

Keywords: Thin film, mechanicals properties, PVD.

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672 Piezoelectric Bimorph Harvester Based on Different Lead Zirconate Titanate Materials to Enhance Energy Collection

Authors: Irene Perez-Alfaro, Nieves Murillo, Carlos Bernal, Daniel Gil-Hernandez

Abstract:

Nowadays, the increasing applicability of internet of things (IoT) systems has changed the way that the world around is perceived. The massive interconnection of systems by means of sensing, processing and communication, allows multitude of data to be at our fingertips. In this way, countless advances have been made in different fields such as personal care, predictive maintenance in industry, quality control in production processes, security, and in everything imaginable. However, all these electronic systems have in common the need to be electrically powered. In this context, batteries and wires are the most commonly used solutions, but they are not a definitive solution in some applications, because of the attainability, the serviceability, or the performance requirements. Therefore, the need arises to look for other types of solutions based on energy harvesting and long-life electronics. Energy Harvesting can be defined as the action of capturing energy from the environment and store it for an instantaneous use or later use. Among the materials capable of harvesting energy from the environment, such as thermoelectrics, electromagnetics, photovoltaics or triboelectrics, the most suitable is the piezoelectric material. The phenomenon of piezoelectricity is one of the most powerful sources for energy harvesting, ranging from a few micro wats to hundreds of wats, depending on certain factors such as material type, geometry, excitation frequency, mechanical and electrical configurations, among others. In this research work, an exhaustive study is carried out on how different types of piezoelectric materials and electrical configurations influence the maximum power that a bimorph harvester is able to extract from mechanical vibrations. A series of experiments has been carried out in which the manufactured bimorph specimens are excited under fixed inertial vibrational conditions. In addition, in order to evaluate the dependence of the maximum transferred power, different load resistors are tested. In this way, the pure active power that achieves the maximum power transfer can be approximated. In this paper, we present the design of low-cost energy harvesting solutions based on piezoelectric smart materials with tunable frequency. The results obtained show the differences in energy extraction between the PZT materials studied and their electrical configurations. The aim of this work is to gain a better understanding of the behavior of piezoelectric materials, and the design process of bimorph PZT harvesters to optimize environmental energy extraction.

Keywords: Bimorph harvesters, electrical impedance, energy harvesting, piezoelectric, smart material.

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671 Toward Understanding and Testing Deep Learning Information Flow in Deep Learning-Based Android Apps

Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

Abstract:

The widespread popularity of mobile devices and the development of artificial intelligence (AI) have led to the widespread adoption of deep learning (DL) in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace, a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Additionally, we propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. Using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We conduct an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace outperformed FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: Mobile computing, deep learning apps, sensitive information, static analysis.

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670 Ribbon Beam Antenna for RFID Technology

Authors: T. Zalabsky, P. Bezousek, T. Shejbal

Abstract:

The paper describes new concept of the ribbon beam antenna for RFID technology. Antenna is located near to railway lines to monitor tags situated on trains. Antenna works at 2.45 GHz and it is fabricated by microstrip technology. Antenna contains two same mirrored parts having the same radiation patterns. Each part consists of three dielectric layers. The first layer has on one side radiation elements. The second layer is only for mechanical construction and it sets optimal electromagnetic field for each radiating elements. The third layer has on its top side a ground plane and on the bottom side a microstrip circuit used for individual radiation elements feeding.

Keywords: RFID, cosecant radiation pattern, ribbon beam, patch antenna, microstrip.

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669 Characterization of an Almond Shell Composite Based on PHBH

Authors: J. Ivorra-Martinez, L. Quiles-Carrillo, J. Gomez-Caturla, T. Boronat, R. Balart

Abstract:

The utilization of almond crop by-products to obtain Poly(3-hydroxybutyrat-co-3-hydroxyhexanoat) (PHBH)-based composites was carried out by using an extrusion process followed by an injection to obtain test samples. To improve the properties of the resulting composite, the incorporation of Oligomer Lactic Acid (OLA 8) as a coupling agent and plasticizer was additionally considered. A characterization process was carried out by the measurement of mechanical properties, thermal properties, surface morphology, and water absorption ability. The use of the almond residue allows obtaining composites based on PHBH with a higher environmental interest and lower cost.

Keywords: Almond shell, PHBH, composite, polymer.

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668 Simulation of the Visco-Elasto-Plastic Deformation Behaviour of Short Glass Fibre Reinforced Polyphthalamides

Authors: V. Keim, J. Spachtholz, J. Hammer

Abstract:

The importance of fibre reinforced plastics continually increases due to the excellent mechanical properties, low material and manufacturing costs combined with significant weight reduction. Today, components are usually designed and calculated numerically by using finite element methods (FEM) to avoid expensive laboratory tests. These programs are based on material models including material specific deformation characteristics. In this research project, material models for short glass fibre reinforced plastics are presented to simulate the visco-elasto-plastic deformation behaviour. Prior to modelling specimens of the material EMS Grivory HTV-5H1, consisting of a Polyphthalamide matrix reinforced by 50wt.-% of short glass fibres, are characterized experimentally in terms of the highly time dependent deformation behaviour of the matrix material. To minimize the experimental effort, the cyclic deformation behaviour under tensile and compressive loading (R = −1) is characterized by isothermal complex low cycle fatigue (CLCF) tests. Combining cycles under two strain amplitudes and strain rates within three orders of magnitude and relaxation intervals into one experiment the visco-elastic deformation is characterized. To identify visco-plastic deformation monotonous tensile tests either displacement controlled or strain controlled (CERT) are compared. All relevant modelling parameters for this complex superposition of simultaneously varying mechanical loadings are quantified by these experiments. Subsequently, two different material models are compared with respect to their accuracy describing the visco-elasto-plastic deformation behaviour. First, based on Chaboche an extended 12 parameter model (EVP-KV2) is used to model cyclic visco-elasto-plasticity at two time scales. The parameters of the model including a total separation of elastic and plastic deformation are obtained by computational optimization using an evolutionary algorithm based on a fitness function called genetic algorithm. Second, the 12 parameter visco-elasto-plastic material model by Launay is used. In detail, the model contains a different type of a flow function based on the definition of the visco-plastic deformation as a part of the overall deformation. The accuracy of the models is verified by corresponding experimental LCF testing.

Keywords: Complex low cycle fatigue, material modelling, short glass fibre reinforced polyphthalamides, visco-elasto-plastic deformation.

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667 Briquetting of Metal Chips by Controlled Impact: Experimental Study

Authors: Todor Penchev, Dimitar Karastojanov, Ivan Altaparmakov

Abstract:

For briquetting of metal chips are used hydraulic and mechanical presses. The density of the briquettes in this case is about 60% - 70 % on the density of solid metal. In this work are presented the results of experimental studies for briquetting of metal chips, by using a new technology for impact briquetting. The used chips are by Armco iron, steel, cast iron, copper, aluminum and brass. It has been found that: (i) in a controlled impact the density of the briquettes can be increases up to 30%; (ii) at the same specific impact energy Es (J/sm3) the density of the briquettes increases with increasing of the impact velocity; (iii), realization of the repeated impact leads to decrease of chips density, which can be explained by distribution of elastic waves in the briquette.

Keywords: Briquetting, chips briquetting, impact briquetting.

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666 The Effect of Air Entraining Agents on Compressive Strength

Authors: Demet Yavuz

Abstract:

Freeze-thaw cycles are one of the greatest threats to concrete durability. Lately, protection against this threat excites scientists’ attention. Air-entraining admixtures have been widely used to produce freeze-thaw resistant at concretes. The use of air-entraining agents (AEAs) enhances not only freeze-thaw endurance but also the properties of fresh concrete such as segregation, bleeding and flow ability. This paper examines the effects of air-entraining on compressive strength of concrete. Air-entraining is used between 0.05% and 0.4% by weight of cement. One control and four fiber reinforced concrete mixes are prepared and three specimens are tested for each mix. It is concluded from the test results that when air entraining is increased the compressive strength of concrete reduces for all mixes with AEAs.

Keywords: Concrete, air-entraining, compressive strength, mechanical properties.

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665 Design Optimization of the Primary Containment Building of a Pressurized Water Reactor

Authors: M. Hossain, A. H. Khan, M. A. R. Sarkar

Abstract:

Primary containment structure is one of the five safety layers of a nuclear facility which is needed to be designed in such a manner that it can withstand the pressure and excessive radioactivity during accidental situations. It is also necessary to ensure minimization of cost with maximum possible safety in order to make the design economically feasible and attractive. This paper attempts to identify the optimum design conditions for primary containment structure considering both mechanical and radiation safety keeping the economic aspects in mind. This work takes advantage of commercial simulation software to identify the suitable conditions without the requirement of costly experiments. Generated data may be helpful for further studies.

Keywords: PWR, concrete containment, finite element approach, neutron attenuation, Von Mises Stress.

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664 Modeling of Plasticity of Clays Submitted to Compression Test

Authors: Otávio J.U. Flores, Fernando A. Andrade, Dachamir Hotza, Hazim A. Al-Qureshi

Abstract:

In the forming of ceramic materials the plasticity concept is commonly used. This term is related to a particular mechanical behavior when clay is mixed with water. A plastic ceramic material shows a permanent strain without rupture when a compressive load produces a shear stress that exceeds the material-s yield strength. For a plastic ceramic body it observes a measurable elastic behavior before the yield strength and when the applied load is removed. In this work, a mathematical model was developed from applied concepts of the plasticity theory by using the stress/strain diagram under compression.

Keywords: Plasticity, clay, modeling, coefficient of friction.

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663 Physical and Chemical Investigation of Polycaprolactone, Nanohydroxyapatite and Poly (Vinyl Alcohol) Nanocomposite Scaffolds

Authors: A.Doustgani, E.Vasheghani- Farahani, M. Soleimani, S. Hashemi-Najafabadi

Abstract:

Aligned and random nanofibrous scaffolds of PVA/PCL/nHA were fabricated by electrospinning method. The composite nanofibrous scaffolds were subjected to detailed analysis. Morphological investigations revealed that the prepared nanofibers have uniform morphology and the average fiber diameters of aligned and random scaffolds were 135.5 and 290 nm, respectively. The obtained scaffolds have a porous structure with porosity of 88 and 76% for random and aligned nanofibers, respectively. Furthermore, FTIR analysis demonstrated that there were strong intramolecular interactions between the molecules of PVA/PCL/nHA. On the other hand, mechanical characterizations show that aligning the nanofibers, could significantly improve the rigidity of the resultant biocomposite nanofibrous scaffolds.

Keywords: Electrospinnig, nanofibrous scaffold, poly (vinyl alcohol), polycaprolactone.

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662 Springback Property and Texture Distribution of Grained Pure Copper

Authors: Takashi Sakai, Hitoshi Omata, Jun-Ichi Koyama

Abstract:

To improve the material characteristics of single- and poly-crystals of pure copper, the respective relationships between crystallographic orientations and microstructures, and the bending and mechanical properties were examined. And texture distribution is also analyzed. A grain refinement procedure was performed to obtain a grained structure. Furthermore, some analytical results related to crystal direction maps, inverse pole figures, and textures were obtained from SEM-EBSD analyses. Results showed that these grained metallic materials have peculiar springback characteristics with various bending angles.

Keywords: Pure Copper, Grain Refinement, Environmental Materials, SEM-EBSD Analysis, Texture, Microstructure

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661 Graphical Approach for Targeting Work Exchange Networks

Authors: Hui Chen, Xiao Feng

Abstract:

Depressurization and pressurization streams in industrial systems constitute a work exchange network (WEN). In this paper, a novel graphical approach for targeting energy conservation potential of a WEN is proposed. Through constructing the composite work curves in the pressure-work diagram and assuming all of the mechanical energy of the depressurization streams is recovered by expanders, the maximum work target of a WEN can be determined via the proposed targeting steps. A WEN in an ammonia production process is used as a case study to illustrate the applicability of the proposed graphical approach.

Keywords: Expanders, Graphical approach, Pressure-work diagram, Work exchange network, Work target

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660 Decision-Making Strategies on Smart Dairy Farms: A Review

Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

Abstract:

Farm management and operations will drastically change due to access to real-time data, real-time forecasting and tracking of physical items in combination with Internet of Things (IoT) developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm decision-making process does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyze on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue and environmental impact. Evolutionary Computing (EC) can be very effective in finding the optimal combination of sets of some objects and finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and EC in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management and its uptake has become a continuing trend.

Keywords: Big data, evolutionary computing, cloud, precision technologies

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659 Preparation and Physical Characterization of Nanocomposites of PLA / Layered Silicates

Authors: I. Restrepo, S. Solorzano

Abstract:

This work was focused in to study the compatibility, dispersion and exfoliation of modified nanoclays in biodegradable polymers and evaluate its effect on the physical, mechanical and thermal properties on the biodegradable matrix used. The formulations have been developed with polylactic acid (PLA) and organically modified montmorillonite-type commercial nanoclays (Cloisite 15, Cloisite 20, and Cloisite 30B) in the presence of a plasticizer agent, specifically Polyethylene Glycol of low molecular weight. Different compositions were evaluated, in order to identify the influence of each nanoclayin the polymeric matrix. The mixtures were characterized by thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), X-ray diffraction (DRX), transmission electron microscopy (TEM) and Tensile Test. These tests have allowed understanding the behavior of each of the mixtures developed.

Keywords: Biopolymers, Nanoclays, polylacticacid (PLA), polymer blends.

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658 Early Depression Detection for Young Adults with a Psychiatric and AI Interdisciplinary Multimodal Framework

Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

Abstract:

During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: Artificial intelligence, depression detection, facial emotion recognition, natural language processing, mental disorder.

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657 LQR Control for a Multi-MW Wind Turbine

Authors: Trung-Kien Pham, Yoonsu Nam, Hyungun Kim, Jaehoon Son

Abstract:

This paper addresses linear quadratic regulation (LQR) for variable speed variable pitch wind turbines. Because of the inherent nonlinearity of wind turbine, a set of operating conditions is identified and then a LQR controller is designed for each operating point. The feedback controller gains are then interpolated linearly to get control law for the entire operating region. Besides, the aerodynamic torque and effective wind speed are estimated online to get the gain-scheduling variable for implementing the controller. The potential of the method is verified through simulation with the help of MATLAB/Simulink and GH Bladed. The performance and mechanical load when using LQR are also compared with that when using PI controller.

Keywords: variable speed variable pitch wind turbine, multi-MW size wind turbine, wind energy conversion system, LQR control.

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656 Fully Automated Methods for the Detection and Segmentation of Mitochondria in Microscopy Images

Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn

Abstract:

The detection and segmentation of mitochondria from fluorescence microscopy is crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. Although there exists a number of open-source software tools and artificial intelligence (AI) methods designed for analyzing mitochondrial images, the availability of only a few combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compactibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source Python and OpenCV library, the algorithms are implemented in three stages: pre-processing; image binarization; and coarse-to-fine segmentation. The proposed model is validated using the fluorescence mitochondrial dataset. Ground truth labels generated using Labkit were also used to evaluate the performance of our detection and segmentation model using precision, recall and rand index. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks concludes the paper.

Keywords: 2D, Binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation.

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655 The Effect of the Reaction Time on the Microwave Synthesis of Magnesium Borates from MgCl2.6H2O, MgO and H3BO3

Authors: E. Moroydor Derun, P. Gurses, M. Yildirim, A. S. Kipcak, T. Ibroska, S. Piskin

Abstract:

Due to their strong mechanical and thermal properties magnesium borates have a wide usage area such as ceramic industry, detergent production, friction reducing additive and grease production. In this study, microwave synthesis of magnesium borates from MgCl2.6H2O (Magnesium chloride hexahydrate), MgO (Magnesium oxide) and H3BO3 (Boric acid) for different reaction times is researched. X-ray Diffraction (XRD) and Fourier Transform Infrared (FT-IR) Spectroscopy are used to find out how the reaction time sways on the products. The superficial properties are investigated with Scanning Electron Microscopy (SEM). According to XRD analysis, the synthesized compounds are 00-041-1407 pdf coded Shabinite (Mg5(BO3)4Cl2(OH)5.4(H2O)) and 01-073-2158 pdf coded Karlite (Mg7(BO3)3(OH,Cl)5).

Keywords: Magnesium borate, microwave synthesis, XRD, SEM.

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654 Modeling and Analysis of the Effects of Nephrolithiasis in Kidney Using a Computational Tactile Sensing Approach

Authors: Elnaz Afshari, Siamak Najarian

Abstract:

Having considered tactile sensing and palpation of a surgeon in order to detect kidney stone during open surgery; we present the 2D model of nephrolithiasis (two dimensional model of kidney containing a simulated stone). The effects of stone existence that appear on the surface of kidney (because of exerting mechanical load) are determined. Using Finite element method, it is illustrated that the created stress patterns on the surface of kidney and stress graphs not only show existence of stone inside kidney, but also show its exact location.

Keywords: Nephrolithiasis, Minimally Invasive Surgery, Artificial Tactile Sensing, Finite Element Method.

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653 Possibilities of Utilization Zeolite in Concrete

Authors: M. Sedlmajer, J. Zach, J. Hroudová, P. Rovnaníková

Abstract:

There are several possibilities of reducing the required amount of cement in concrete production. Natural zeolite is one of the raw materials which can partly substitute Portland cement. The effort to reduce the amount of Portland cement used in concrete production is brings both economical as well as ecological benefits. The paper presents the properties of concrete containing natural zeolite as an active admixture in the concrete which partly substitutes Portland cement. The properties discussed here bring information about the basic mechanical properties and frost resistance of concrete containing zeolite. The properties of concretes with the admixture of zeolite are compared with a reference concrete with no content of zeolite. The properties of the individual concretes are observed for 360 days.

Keywords: Concrete, zeolite, compressive strength, modulus of elasticity, durability.

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652 Research and Development of Lightweight Repair Mortars with Focus on Their Resistance to High Temperatures

Authors: Tomáš Melichar, Jiří Bydžovský, Vít Černý

Abstract:

In this article our research focused on study of basic physical and mechanical parameters of polymer-cement repair materials is presented. Namely the influence of applied aggregates in combination with active admixture is specially considered. New formulas which were exposed in ambient with temperature even to 1000°C were suggested. Subsequently densities and strength characteristics including their changes were evaluated. Selected samples were analyzed using electron microscope. The positive influence of porous aggregates based on sintered ash was definitely demonstrated. Further it was found than in terms of thermal resistance the effective micro silica amount represents 5% to 7.5% of cement weight.

Keywords: Aggregate, ash, high, lightweight, microsilica, mortar, polymer-cement, repair, temperature.

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651 Study of Mechanical Properties for the Aluminum Bronze Matrix Composites of Hot Pressing

Authors: Shenq Yih Luo, Chung Hsien Lu

Abstract:

The aluminum bronze matrix alumina composites using hot press and resin infiltration were investigated to study their porosities, hardness, bending strengths, and microstructures. The experiment results show that the hardness of the sintered composites with the decrease of porosity increases. The composites without and with resin infiltration have about HRF 42-61 of about 34-40% of porosity and about HRF 62-83 of about 30-36% of porosity, respectively. Besides, the alumina composites contain a more amount of iron and nickel powders would cause a lower bending strength due to forming some weaker bonding among the iron, nickel, copper, aluminum under this hot pressing of shorter time.

Keywords: Aluminum bronze matrix composite, bending strength, hot pressing, porosity.

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650 Numerical Analysis for the Performance of a Thermoelectric Generator According to Engine Exhaust Gas Thermal Conditions

Authors: Jinkyu Park, Yungjin Kim, Byungdeok In, Sangki Park, Kihyung Lee

Abstract:

Internal combustion engines rejects 30-40% of the energy supplied by fuel to the environment through exhaust gas. thus, there is a possibility for further significant improvement of efficiency with the utilization of exhaust gas energy and its conversion to mechanical energy or electrical energy. The Thermo-Electric Generator (TEG) will be located in the exhaust system and will make use of an energy flow between the warmer exhaust gas and the external environment. Predict to th optimum position of temperature distribution and the performance of TEG through numerical analysis. The experimental results obtained show that the power output significantly increases with the temperature difference between cold and hot sides of a thermoelectric generator.

Keywords: Thermoelectric generator, Numerical analysis, Seebeck coefficient, Figure of merit

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649 Geotechnical Characteristics of Miocenemarl in the Region of Medea North-South Highway, Algeria

Authors: Y. Yongli, M. H. Aissa

Abstract:

The purpose of this paper aims for a geotechnical analysis based on experimental physical and mechanical characteristics of Miocene marl situated at Medea region in Algeria. More than 150 soil samples were taken in the investigation part of the North-South Highway which extends over than 53 km from Chiffa in the North to Berrouaghia in the South of Algeria. The analysis of data in terms of Atterberg limits, plasticity index, and clay content reflects an acceptable correlation justified by a high coefficient of regression which was compared with the previous works in the region. Finally, approximated equations that serve as a guideline for geotechnical design locally have been suggested.

Keywords: Correlation, geotechnical properties, Miocene marl, north-south highway.

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