Search results for: vector density

Authors: Youhang Zhou, Weimin Zeng, Qi Xie

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Abstract: In order to solve the wear recognition problem of the machine tool guide surface, a new machine tool guide surface recognition method based on the radar-graph barycentre feature is presented in this paper. Firstly, the gray mean value, skewness, projection variance, flat degrees and kurtosis features of the guide surface image data are defined as primary characteristics. Secondly, data Visualization technology based on radar graph is used. The visual barycentre graphical feature is demonstrated based on the radar plot of multi-dimensional data. Thirdly, a classifier based on the support vector machine technology is used, the radar-graph barycentre feature and wear original feature are put into the classifier separately for classification and comparative analysis of classification and experiment results. The calculation and experimental results show that the method based on the radar-graph barycentre feature can detect the guide surface effectively.

Keywords: guide surface, wear defects, feature extraction, data visualization

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Authors: Rima T. Alfaraj, Murtadha J. Al Tammar, Khaqan Khan, Khalid M. Alruwaili

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OBJECTIVE/SCOPE (25-75): Caliper logging data provides critical information about wellbore shape and deformations, such as stress-induced borehole breakouts or washouts. Multiarm mechanical caliper logs are often run using wireline, which can be time-consuming, costly, and/or challenging to run in certain formations. To minimize rig time and improve operational safety, it is valuable to develop analytical solutions that can estimate caliper logs using available Logging-While-Drilling (LWD) data without the need to run wireline caliper logs. As a first step, the objective of this paper is to perform statistical analysis using an extensive datasetto identify important physical parameters that should be considered in developing such analytical solutions. METHODS, PROCEDURES, PROCESS (75-100): Caliper logs and LWD data of eleven wells, with a total of more than 80,000 data points, were obtained and imported into a data analytics software for analysis. Several parameters were selected to test the relationship of the parameters with the measured maximum and minimum caliper logs. These parameters includegamma ray, porosity, shear, and compressional sonic velocities, bulk densities, and azimuthal density. The data of the eleven wells were first visualized and cleaned.Using the analytics software, several analyses were then preformed, including the computation of Pearson’s correlation coefficients to show the statistical relationship between the selected parameters and the caliper logs. RESULTS, OBSERVATIONS, CONCLUSIONS (100-200): The results of this statistical analysis showed that some parameters show good correlation to the caliper log data. For instance, the bulk density and azimuthal directional densities showedPearson’s correlation coefficients in the range of 0.39 and 0.57, which wererelatively high when comparedto the correlation coefficients of caliper data with other parameters. Other parameters such as porosity exhibited extremely low correlation coefficients to the caliper data. Various crossplots and visualizations of the data were also demonstrated to gain further insights from the field data. NOVEL/ADDITIVE INFORMATION (25-75): This study offers a unique and novel look into the relative importance and correlation between different LWD measurements and wireline caliper logs via an extensive dataset. The results pave the way for a more informed development of new analytical solutions for estimating the size and shape of the wellbore in real-time while drilling using LWD data.

Keywords: LWD measurements, caliper log, correlations, analysis

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Authors: Małgorzata Golonka, Jadwiga Laska

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Among self-healing materials, the most unexplored group are thermoplastic polymers. These polymers are used not only to produce packaging with a relatively short life but also to obtain coatings, insulation, casings, or parts of machines and devices. Due to its exceptional resistance to weather conditions, hydrophobicity, sufficient mechanical strength, and ease of extrusion, polyethylene is used in the production of polymer pipelines and as an insulating layer for steel pipelines. Polyethylene or PE coated steel pipelines can be used in difficult conditions such as underground or underwater installations. Both installation and use under such conditions are associated with high stresses and consequently the formation of microdamages in the structure of the material, loss of its integrity and final applicability. The ideal solution would be to include a self-healing system in the polymer material. In the presented study the behavior of resin-coated microcapsules in the extrusion process of low-density polyethylene was examined. Microcapsules are a convenient element of the repair system because they can be filled with appropriate reactive substances to ensure the repair process, but the main problem is their durability under processing conditions. Rapeseed oil, which has a relatively high boiling point of 240⁰C and low volatility, was used as the core material that simulates the reactive agents. The capsule shell, which is a key element responsible for its mechanical strength, was obtained by in situ polymerising urea-formaldehyde, melamine-urea-formaldehyde or melamine-formaldehyde resin on the surface of oil droplets dispersed in water. The strength of the capsules was compared based on the shell material, and in addition, microcapsules with single- and multilayer shells were obtained using different combinations of the chemical composition of the resins. For example, the first layer of appropriate tightness and stiffness was made of melamine-urea-formaldehyde resin, and the second layer was a melamine-formaldehyde reinforcing layer. The size, shape, distribution of capsule diameters and shell thickness were determined using digital optical microscopy and electron microscopy. The efficiency of encapsulation (i.e., the presence of rapeseed oil as the core) and the tightness of the shell were determined by FTIR spectroscopic examination. The mechanical strength and distribution of microcapsules in polyethylene were tested by extruding samples of crushed low-density polyethylene mixed with microcapsules in a ratio of 1 and 2.5% by weight. The extrusion process was carried out in a mini extruder at a temperature of 150⁰C. The capsules obtained had a diameter range of 70-200 µm. FTIR analysis confirmed the presence of rapeseed oil in both single- and multilayer shell microcapsules. Microscopic observations of cross sections of the extrudates confirmed the presence of both intact and cracked microcapsules. However, the melamine-formaldehyde resin shells showed higher processing strength compared to that of the melamine-urea-formaldehyde coating and the urea-formaldehyde coating. Capsules with a urea-formaldehyde shell work very well in resin coating systems and cement composites, i.e., in pressureless processing and moulding conditions. The addition of another layer of melamine-formaldehyde coating to both the melamine-urea-formaldehyde and melamine-formaldehyde resin layers significantly increased the number of microcapsules undamaged during the extrusion process. The properties of multilayer coatings were also determined and compared with each other using computer modelling.

Keywords: self-healing polymers, polyethylene, microcapsules, extrusion

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Authors: Mohammed Qasim, Kyoung-Dae Kim

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In this paper, we present the design of the super-ellipsoidal potential function (SEPF), that can be used for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3-dimensional space. In the design of SEPF, we have the full control over the shape and size of the potential function. In particular, we can adjust the length, width, height, and the amount of flattening at the tips of the potential function so that the collision avoidance motion vector generated from the potential function can be adjusted accordingly. Based on the idea of the SEPF, we also propose an approach for the local autonomy of a UAV for its collision avoidance when the UAV is teleoperated by a human operator. In our proposed approach, a teleoperated UAV can not only avoid collision autonomously with other surrounding objects but also track the operator’s control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high-level guidance and navigation task without worrying too much about the UAVs collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human-in-the-loop simulation of quadrotor UAV teleoperation using virtual robot experimentation platform (v-rep) and Matlab programs.

Keywords: artificial potential function, autonomous collision avoidance, teleoperation, quadrotor

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Authors: Apidet Booranawong, Wiklom Teerapabkajorndet

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An enhanced ad-hoc on-demand distance vector routing (E-AODV) protocol for control system applications in wireless sensor and actuator networks (WSANs) is proposed. Our routing algorithm is designed by considering both wireless network communication and the control system aspects. Control system error and network delay are the main selection criteria in our routing protocol. The control and communication performance is evaluated on multi-hop IEEE 802.15.4 networks for building-temperature control systems. The Gilbert-Elliott error model is employed to simulate packet loss in wireless networks. The simulation results demonstrate that the E-AODV routing approach can significantly improve the communication performance better than an original AODV routing under various packet loss rates. However, the control performance result by our approach is not much improved compared with the AODV routing solution.

Keywords: WSANs, building temperature control, AODV routing protocol, control system error, settling time, delay, delivery ratio

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Authors: Badr M. Alshammari, A. Rabeh, A. K. Mohamed

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This paper presents the modeling and the control of a grid-connected photovoltaic system (PVS). Firstly, the MPPT control of the PVS and its associated DC/DC converter has been analyzed in order to extract the maximum of available power. Secondly, the control system of the grid side converter (GSC) which is a three-phase voltage source inverter (VSI) has been presented. A special attention has been paid to the control algorithms of the GSC converter during grid voltages imbalances. Especially, three different control objectives are to achieve; the mitigation of the grid imbalance adverse effects, at the point of common coupling (PCC), on the injected currents, the elimination of double frequency oscillations in active power flow, and the elimination of double frequency oscillations in reactive power flow. Simulation results of two control strategies have been performed via MATLAB software in order to demonstrate the particularities of each control strategy according to power quality standards.

Keywords: renewable energies, photovoltaic systems, dc link, voltage source inverter, space vector SVPWM, unbalanced voltage dips, symmetrical components

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Authors: Abdullah Eqal Al Mazrooei

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In this paper, a nonlinear dynamical system is presented. This system is a bilinear class. The bilinear systems are very important kind of nonlinear systems because they have many applications in real life. They are used in biology, chemistry, manufacturing, engineering, and economics where linear models are ineffective or inadequate. They have also been recently used to analyze and forecast weather conditions. Bilinear systems have three advantages: First, they define many problems which have a great applied importance. Second, they give us approximations to nonlinear systems. Thirdly, they have a rich geometric and algebraic structures, which promises to be a fruitful field of research for scientists and applications. The type of nonlinearity that is treated and analyzed consists of bilinear interaction between the states vectors and the system input. By using some properties of the tensor product, these systems can be transformed to linear systems. But, here we discuss the nonlinearity when the state vector is multiplied by itself. So, this model will be able to handle evolutions according to the Lotka-Volterra models or the Lorenz weather models, thus enabling a wider and more flexible application of such models. Here we apply by using an estimator to estimate temperatures. The results prove the efficiency of the proposed system.

Keywords: Lorenz models, nonlinear systems, nonlinear estimator, state-space model

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Authors: G. Massaad, E. Roziere, A. Loukili, L. Izoret

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Based on the monitoring of mass, hydrostatic weighing, and the amount of leached OH- we deduced the nature of leached and precipitated minerals, the amount of lost aggregates and the evolution of porosity and cracking during the sulphate attack. Using these information, we are able to draw the volume / mass changes brought by mineralogical variations and cracking of the cement matrix. Then we defined a new performance indicator, the averaged density, capable to resume along the test of sulphate attack the occurred physicochemical variation occurred in the cementitious matrix and then highlight.

Keywords: monitoring strategy, performance indicator, sulphate attack, mechanism of degradation

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Authors: A. Giniatoulline

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A nonlinear model of the mathematical fluid dynamics which describes the motion of an incompressible viscous rotating fluid in a homogeneous gravitational field is considered. The model is a generalization of the known Navier-Stokes system with the addition of the Coriolis parameter and the equations for changeable density. An explicit algorithm for the solution is constructed, and the proof of the existence and uniqueness theorems for the strong solution of the nonlinear problem is given. For the linear case, the localization and the structure of the spectrum of inner waves are also investigated.

Keywords: Galerkin method, Navier-Stokes equations, nonlinear partial differential equations, Sobolev spaces, stratified fluid

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Authors: Hristina Šalipur, Jasmina Dostanić, Davor Lončarević, Matej Huš

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Photocatalytic water splitting/alcohol photoreforming has been used for the conversion of sunlight energy in the process of hydrogen production due to its sustainability, environmental safety, effectiveness and simplicity. Titanate nanotubes are frequently studied materials since they combine the properties of photo-active semiconductors with the properties of layered titanates, such as the ion-exchange ability. Platinum (Pt) doping into titanate structure has been considered an effective strategy in better separation efficiency of electron-hole pairs and lowering the overpotential for hydrogen production, which results in higher photocatalytic activity. In our work, Pt doped titanate catalysts were synthesized via simple alkaline hydrothermal treatment, incipient wetness impregnation method and temperature-programmed reduction. The structural, morphological and optical properties of the prepared catalysts were investigated using various characterization techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), N2 physisorption, and diffuse reflectance spectroscopy (DRS). The activities of the prepared Pt-doped titanate photocatalysts were tested for hydrogen production via photocatalytic water splitting/alcohol photoreforming process under simulated solar light irradiation. Characterization of synthesized Pt doped titanate catalysts showed crystalline anatase phase, preserved nanotubular structure and high specific surface area. The result showed enhancement of activity in photocatalytic water splitting/alcohol photoreforming in the following order 2-butanol>1-butanol>tert-butanol, with obtained maximal hydrogen production rate of 7.5, 5.3 and 2 mmol g-1 h-1, respectively. Different possible factors influencing the hole scavenging ability, such as hole scavenger redox potential and diffusivity, adsorption and desorption rate of the hole scavenger on the surface and stability of the alcohol radical species generated via hole scavenging, were investigated. The theoretical evaluation using density functional theory (DFT) further elucidated the reaction kinetics and detailed mechanism of photocatalytic water splitting/alcohol photoreforming.

Keywords: hydrogen production, platinum, semiconductor, water splitting, density functional theory

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Authors: Fayssal Amrane, Azeddine Chaiba

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In this paper, type-2 fuzzy logic control (T2FLC) and neuro-fuzzy control (NFC) for a doubly fed induction generator (DFIG) based on direct power control (DPC) with a fixed switching frequency is proposed for wind generation application. First, a mathematical model of the doubly-fed induction generator implemented in d-q reference frame is achieved. Then, a DPC algorithm approach for controlling active and reactive power of DFIG via fixed switching frequency is incorporated using PID. The performance of T2FLC and NFC, which is based on the DPC algorithm, are investigated and compared to those obtained from the PID controller. Finally, simulation results demonstrate that the NFC is more robust, superior dynamic performance for wind power generation system applications.

Keywords: doubly fed induction generator (DFIG), direct power control (DPC), neuro-fuzzy control (NFC), maximum power point tracking (MPPT), space vector modulation (SVM), type 2 fuzzy logic control (T2FLC)

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Authors: Ayca Bilginoglu, Belma Turan

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Metabolic syndrome, is associated impaired blood glucose level, insulin resistance, dyslipidemia caused by abdominal obesity. Also, it is related with cardiovascular risk accumulation and cardiomyopathy. The hypothesis of this study was to examine the effect of thiazolidinediones such as pioglitazone which is widely used insulin-sensitizing agents that improve glycemic control, on intracellular Na+ homeostasis in metabolic syndrome-induced cardiomyopathy in male rats. Male Wistar-Albino rats were randomly divided into three groups, namely control (Con, n=7), metabolic syndrome (MetS, n=7) and pioglitazone treated metabolic syndrome group (MetS+PGZ, n=7). Metabolic syndrome was induced by providing drinking water that was 32% sucrose, for 18 weeks. All of the animals were exposed to a 12 h light – 12 h dark cycle. Abdominal obesity and glucose intolerance had measured as a marker of metabolic syndrome. Intracellular Na+ ([Na+]i) is an important modulator of excitation–contraction coupling in heart. [Na+]i at rest and [Na+]i during pacing with electrical field stimulation in 0.2 Hz, 0.8 Hz, 2.0 Hz stimulation frequency were recorded in cardiomyocytes. Also, Na+ channel current (INa) density and I-V curve were measured to understand [Na+]i homeostasis. In results, high sucrose intake, as well as the normal daily diet, significantly increased body mass and blood glucose level of the rats in the metabolic syndrome group as compared with the non-treated control group. In MetS+PZG group, the blood glucose level and body inclined to decrease to the Con group. There was a decrease in INa density and there was a shift both activation and inactivation curve of INa. Pioglitazone reversed the shift to the control side. Basal [Na+]i either MetS and Con group were not significantly different, but there was a significantly increase in [Na+]i in stimulated cardiomyocytes in MetS group. Furthermore, pioglitazone had not effect on basal [Na+]i but it reversed the increase in [Na+]i in stimulated cardiomyocytes to the that of Con group. Results of the present study suggest that pioglitazone has a significant effect on the Na+ homeostasis in the metabolic syndrome induced cardiomyopathy in rats. All animal procedures and experiments were approved by the Animal Ethics Committee of Ankara University Faculty of Medicine (2015-2-37).

Keywords: insulin resistance, intracellular sodium, metabolic syndrome, sodium current

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Authors: Sri Satya Antarlina, Elok Zubaidah, Teti Istiana, Harijono

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Sorghum bicolor (Sorghum bicolor L. Moench) has the potential as a flour for gluten-free food products. Sorghum flour production needs grain soaking treatment. Soaking can reduce the tannin content which is an anti-nutrient, so it can increase the protein digestibility. Fine particle size decreases the yield of flour, so it is necessary to study various particle sizes to increase the yield. This study aims to determine the characteristics of sorghum flour in the treatment of soaking peeled grain and particle size. The material of white sorghum varieties KD-4 from farmers in East Java, Indonesia. Factorial randomized factorial design (two factors), repeated three times, factor I were the time of grain soaking (five levels) that were 0, 12, 24, 36, and 48 hours, factor II was the size of the starch particles sifted with a fineness level of 40, 60, 80, and 100 mesh. The method of making sorghum flour is grain peeling, soaking peeled grain, drying using the oven at 60ᵒC, milling, and sieving. Physico-chemical analysis of sorghum flour. The results show that there is an interaction between soaking time of grain with the size of sorghum flour particles. Interaction in yield of flour, L* color (brightness level), whiteness index, paste properties, amylose content, protein content, bulk density, and protein digestibility. The method of making sorghum flour through the soaking of peeled grain and the difference in particle size has an important role in producing the physicochemical properties of the specific flour. Based on the characteristics of sorghum flour produced, it is determined the method of making sorghum flour through sorghum grain soaking for 24 hours, the particle size of flour 80 mesh. The sorghum flour with characteristic were 24.88% yield of flour, 88.60 color L* (brightness level), 69.95 whiteness index, 3615 Cp viscosity, 584.10 g/l of bulk density, 24.27% db protein digestibility, 90.02% db starch content, 23.4% db amylose content, 67.45% db amylopectin content, 0.22% db crude fiber content, 0.037% db tannin content, 5.30% db protein content, ash content 0.18% db, carbohydrate content 92.88 % db, and 1.94% db fat content. The sorghum flour is recommended for cookies products.

Keywords: characteristic, sorghum (Sorghum bicolor L. Moench) flour, grain soaking, particle size, physicochemical properties

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Authors: Sara Saboonian, Pierre Filion

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The dispersed-suburban model has been the dominant one across North America for the past seventy years, characterized by automobile reliance, low density, and land-use specialization. Two planning models have emerged as possible alternatives to address the ills inflicted by this development pattern. First, there is intensification, which promotes efficient infrastructure by connecting high-density, multi-functional, and walkable nodes with public transit services within the suburban landscape. Second is green infrastructure, which provides environmental health and human well-being by preserving and restoring ecosystem services. This research studies incompatibilities and the possibility of amalgamating the two alternatives in an attempt to develop a comprehensive alternative to suburban model that advocates density, multi-functionality and transit- and pedestrian-conduciveness, with measures capable of mitigating the adverse environmental impacts of compactness. The research investigates three Canadian urban growth centers, where intensification is the current planning practice, and the awareness of green infrastructure benefits is on the rise. However, these three centers are contrasted by their development stage, the presence or absence of protected natural land, their environmental approach, and their adverse environmental consequences according to the planning cannons of different periods. The methods include reviewing the literature on green infrastructure planning, criticizing the Ontario provincial plans for intensification, surveying residents’ preferences for alternative models, and interviewing officials who deal with the local planning for the centers. Moreover, the research draws on recalling debates between New Urbanism and Landscape/Ecological Urbanism. The case studies expose the difficulties in creating urban growth centres that accommodate green infrastructure while adhering to intensification principles. First, the dominant status of intensification and the obstacles confronting intensification have monopolized the planners’ concerns. Second, the tension between green infrastructure and intensification explains the absence of the green infrastructure typologies that correspond to intensification-compatible forms and dynamics. Finally, the lack of highlighted social-economic benefits of green infrastructure reduces residents’ participation. Moreover, the results from the research provide insight into predominating urbanization theories, New Urbanism and Landscape/Ecological Urbanism. In order to understand political, planning, and ecological dynamics of such blending, dexterous context-specific planning is required. Findings suggest the influence of the following factors on amalgamating intensification and green infrastructure. Initially, producing ecosystem services-based justifications for green infrastructure development in the intensification context provides an expert-driven backbone for the implementation programs. This knowledge-base should be translated to effectively imbue different urban stakeholders. Moreover, due to the limited greenfields in intensified areas, spatial distribution and development of multi-level corridors such as pedestrian-hospitable settings and transportation networks along green infrastructure measures are required. Finally, to ensure the long-term integrity of implemented green infrastructure measures, significant investment in public engagement and education, as well as clarification of management responsibilities is essential.

Keywords: ecosystem services, green infrastructure, intensification, planning

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Authors: Chang Yu Chuan

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Background and Aim: Pressure sore is not only the consequence of any gradual damage of the skin leading to tissue defects but also an important indicator of clinical care. If hospitalized patients develop pressure sores without proper care, it would result in delayed healing, wound infection, increase patient physical pain, prolonged hospital stay and even death, which would have a negative impact on the quality of care and also increase nursing manpower and medical costs. This project is aimed at decreasing the incidence of pressure sore in one ward of internal medicine. Our data showed 53 cases (0.61%) of pressure sore in 2015, which exceeded the average (0.5%) of Taiwan Clinical Performance Indicator (TCPI) for medical centers. The purpose of this project is to reduce the incidence rate of pressure sore in the ward. After data collection and analysis from January to December 2016, the reasons of developing pressure sore were found: 1. Lack of knowledge to prevent pressure among nursing staffs; 2. No relevant courses about preventing pressure ulcers and pressure wound care being held in this unit; 3. Low complete rate of pressure sore care education that family members should receive from nursing staffs; 4. Decompression equipment is not enough; 5. Lack of standard procedures for body-turning and positioning care. After team members brainstorming, several strategies were proposed, including holding in-service education, pressure sore care seed training, purchasing decompression mattress and memory pillows, designing more elements of health education tools, such as health education pamphlet, posters and multimedia films of body-turning and positioning demonstration, formulation and promotion of standard operating procedures. In this way, nursing staffs can understand the body-turning and positioning guidelines for pressure sore prevention and enhance the quality of care. After the implementation of this project, the pressure sore density significantly decreased from 0.61%(53 cases) to 0.45%(28 cases) in this ward. The project shows good results and good example for nurses working at the ward and helps to enhance quality of care.

Keywords: body-turning and positioning, incidence density, nursing, pressure sore

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Authors: Ifeoma C. Afiaenyi, Elizabeth K. Ngwu, Rufina N. B. Ayogu

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Diabetes has crept into the rural areas of Nigeria, causing devastating effects on its sufferers; most of them could not afford diabetic medications. Moringa oleifera has been used extensively in animal models to demonstrate its antilipidaemic and haematinic qualities; however, there is a scarcity of data on the effect of graded levels of Moringa oleifera leaves on the lipid profile and hematological parameters in human diabetic subjects. The study determined the effect of Moringa oleifera leaves on the lipid profile and hematological parameters of type 2 diabetic subjects in Ukehe, a rural Nigerian community. Twenty-four adult male and female diabetic subjects were purposively selected for the study. These subjects were shared into four groups of six subjects each. The diets used in the study were isocaloric. A control group (diabetics, group 1) was fed diets without Moringa oleifera leaves. Experimental groups 2, 3 and 4 received 20g, 40g and 60g of Moringa oleifera leaves daily, respectively, in addition to the diets. The subjects' lipid profile and hematological parameters were measured prior to the feeding trial and at the end of the feeding trial. The feeding trial lasted for fourteen days. The data obtained were analyzed using the computer program Statistical Product for Service Solution (SPSS) for windows version 21. A Paired-samples t-test was used to compare the means of values collected before and after the feeding trial within the groups and significance was accepted at p < 0.05. There was a non-significant (p > 0.05) decrease in the mean total cholesterol of the subjects in groups 1, 2 and 3 after the feeding trial. There was a non-significant (p > 0.05) decrease in the mean triglyceride levels of the subjects in group 1 after the feeding trial. Groups 1 and 3 subjects had a non-significant (p > 0.05) decrease in their mean low-density lipoprotein (LDL) cholesterol after the feeding trial. Groups 1, 2 and 4 had a significant (p < 0.05) increase in their mean high-density lipoprotein (HDL) cholesterol after the feeding trial. A significant (p < 0.05) decrease in the mean hemoglobin level was observed only in group 4 subjects. Similarly, there was a significant (p < 0.05) decrease in the mean packed cell volume of group 4 subjects. It was only in group 4 that a significant (p < 0.05) decrease in the mean white blood cells of the subjects was also observed. The changes observed in the parameters assessed were not dose-dependent. Therefore, a similar study of longer duration and more samples is imperative to authenticate these results.

Keywords: anemia, diabetic subjects, lipid profile, moringa oleifera

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Authors: Salah Alrabeei, Mohammad Yousuf

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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. However, most of the option pricing models have no analytical solution. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, we solve the American option under jump diffusion models by using efficient time-dependent numerical methods. several techniques are integrated to reduced the overcome the computational complexity. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). Partial fraction decomposition technique is applied to rational approximation schemes to overcome the complexity of inverting polynomial of matrices. The proposed method is easy to implement on serial or parallel versions. Numerical results are presented to prove the accuracy and efficiency of the proposed method.

Keywords: integral differential equations, jump–diffusion model, American options, rational approximation

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Authors: Zachary Huffman, Joana Rocha

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Wall-pressure fluctuations induced by the turbulent boundary layer (TBL) developed over aircraft are a significant source of aircraft cabin noise. Since the power spectral density (PSD) of these pressure fluctuations is directly correlated with the amount of sound radiated into the cabin, the development of accurate empirical models that predict the PSD has been an important ongoing research topic. The sound emitted can be represented from the pressure fluctuations term in the Reynoldsaveraged Navier-Stokes equations (RANS). Therefore, early TBL empirical models (including those from Lowson, Robertson, Chase, and Howe) were primarily derived by simplifying and solving the RANS for pressure fluctuation and adding appropriate scales. Most subsequent models (including Goody, Efimtsov, Laganelli, Smol’yakov, and Rackl and Weston models) were derived by making modifications to these early models or by physical principles. Overall, these models have had varying levels of accuracy, but, in general, they are most accurate under the specific Reynolds and Mach numbers they were developed for, while being less accurate under other flow conditions. Despite this, recent research into the possibility of using alternative methods for deriving the models has been rather limited. More recent studies have demonstrated that an artificial neural network model was more accurate than traditional models and could be applied more generally, but the accuracy of other machine learning techniques has not been explored. In the current study, an original model is derived using a stepwise regression algorithm in the statistical programming language R, and TBL wall-pressure fluctuations PSD data gathered at the Carleton University wind tunnel. The theoretical advantage of a stepwise regression approach is that it will automatically filter out redundant or uncorrelated input variables (through the process of feature selection), and it is computationally faster than machine learning. The main disadvantage is the potential risk of overfitting. The accuracy of the developed model is assessed by comparing it to independently sourced datasets.

Keywords: aircraft noise, machine learning, power spectral density models, regression models, turbulent boundary layer wall-pressure fluctuations

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Authors: Raed Alnajjar, Mohd Zakree, Ahmad Nazri

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In this study, we apply Discrete Group Search Optimizer (DGSO) for solving Traveling Salesman Problem (TSP). The DGSO is a nature inspired optimization algorithm that imitates the animal behavior, especially animal searching behavior. The proposed DGSO uses a vector representation and some discrete operators, such as destruction, construction, differential evolution, swap and insert. The TSP is a well-known hard combinatorial optimization problem, which seeks to find the shortest path among numbers of cities. The performance of the proposed DGSO is evaluated and tested on benchmark instances which listed in LIBTSP dataset. The experimental results show that the performance of the proposed DGSO is comparable with the other methods in the state of the art for some instances. The results show that DGSO outperform Ant Colony System (ACS) in some instances whilst outperform other metaheuristic in most instances. In addition to that, the new results obtained a number of optimal solutions and some best known results. DGSO was able to obtain feasible and good quality solution across all dataset.

Keywords: discrete group search optimizer (DGSO); Travelling salesman problem (TSP); Variable neighborhood search(VNS)

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Authors: Firas Daghistani, Hossam Abuel Naga

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Waste tyres is a global problem that has a negative effect on the environment, where there are approximately one billion waste tyres discarded worldwide yearly. Waste tyres are discarded in stockpiles, where they provide harm to the environment in many ways. Finding applications to these materials can help in reducing this global problem. One of these applications is recycling these waste materials and using them in geotechnical engineering. Recycled waste tyre particulates can be mixed with sand to form a lightweight material with varying shear strength characteristics. Contradicting results were found in the literature on the inclusion of particulate rubber to sand, where some experiments found that the inclusion of particulate rubber can increase the shear strength of the mixture, while other experiments stated that the addition of particulate rubber decreases the shear strength of the mixture. This research further investigates the inclusion of particulate rubber to sand and whether it can increase or decrease the shear strength characteristics of the mixture. For the experiment, a series of direct shear tests were performed on a poorly graded sand with a mean particle size of 0.32 mm mixed with recycled poorly graded particulate rubber with a mean particle size of 0.51 mm. The shear tests were performedon four normal stresses 30, 55, 105, 200 kPa at a shear rate of 1 mm/minute. Different percentages ofparticulate rubber content were used in the mixture i.e., 10%, 20%, 30% and 50% of sand dry weight at three density states, namely loose, slight dense, and dense state. The size ratio of the mixture,which is the mean particle size of the particulate rubber divided by the mean particle size of the sand, was 1.59. The results identified multiple parameters that can influence the shear strength of the mixture. The parameters were: normal stress, particulate rubber content, mixture gradation, mixture size ratio, and the mixture’s density. The inclusion of particulate rubber tosand showed a decrease to the internal friction angle and an increase to the apparent cohesion. Overall, the inclusion of particulate rubber did not have a significant influenceon the shear strength of the mixture. For all the dense states at the low normal stresses 33 and 55 kPa, the inclusion of particulate rubber showed aslight increase in the shear strength where the peak was at 20% rubber content of the sand’s dry weight. On the other hand, at the high normal stresses 105, and 200 kPa, there was a slight decrease in the shear strength.

Keywords: shear strength, direct shear, sand-rubber mixture, waste material, granular material

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Authors: Elżbieta Cygan, Bączek, Piotr Wyżga

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This paper presents the results of research on the physical, mechanical, and tribological properties of materials constituting the matrix in sintered metallic-diamond tools. The ground powders based on the Fe-Mn-Cu-Sn-C system were modified with micro-sized particles of the ceramic phase: SiC, Al₂O₃ and consolidated using the SPS (spark plasma sintering) method to a relative density of over 98% at 850-950°C, at a pressure of 35 MPa and time 10 min. After sintering, an analysis of the microstructure was conducted using scanning electron microscopy. The resulting materials were tested for the apparent density determined by Archimedes’ method, Rockwell hardness (scale B), Young’s modulus, as well as for technological properties. The performance results of obtained diamond composites were compared with the base material (Fe–Mn–Cu–Sn–C) and the commercial alloy Co-20% WC. The hardness of composites has achieved the maximum at a temperature of 900°C; therefore, it should be considered that at this temperature it was obtained optimal physical and mechanical properties of the subjects' composites were. Research on tribological properties showed that the composites modified with micro-sized particles of the ceramic phase are characterized by more than twice higher wear resistance in comparison with base materials and the commercial alloy Co-20% WC. Composites containing Al₂O₃ phase particles in the matrix material were composites containing Al₂O₃ phase particles in the matrix material were characterized by the lowest abrasion wear resistance. The manufacturing technology presented in the paper is economically justified and can be successfully used in the production process of the matrix in sintered diamond-impregnated tools used for the machining of an industrial floor system. Acknowledgment: The study was performed under LIDER IX Research Project No. LIDER/22/0085/L-9/17/NCBR/2018 entitled “Innovative metal-diamond tools without the addition of critical raw materials for applications in the process of grinding industrial floor systems” funded by the National Centre for Research and Development of Poland, Warsaw.

Keywords: abrasive wear resistance, metal matrix composites, sintered diamond tools, Spark Plasma Sintering

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Authors: Victor Bloch, Eerikki Kaila, Reetta Palva

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Field robots are an important tool for enhancing efficiency and decreasing the climatic impact of food production. There exists a number of commercial field robots; however, since this technology is still new, the robot advantages and limitations, as well as methods for optimal using of robots, are still unclear. In this study, the performance of a commercial field robot for seeding and weeding was assessed. A research 2-ha sugar beet field with 0.5m row width was used for testing, which included robotic sowing of sugar beet and weeding five times during the first two months of the growing. About three and five percent of the field were used as untreated and chemically weeded control areas, respectively. The plant detection was based on the exact plant location without image processing. The robot was equipped with six seeding and weeding tools, including passive between-rows harrow hoes and active hoes cutting inside rows between the plants, and it moved with a maximal speed of 0.9 km/h. The robot's performance was assessed by image processing. The field images were collected by an action camera with a height of 2 m and a resolution 27M pixels installed on the robot and by a drone with a 16M pixel camera flying at 4 m height. To detect plants and weeds, the YOLO model was trained with transfer learning from two available datasets. A preliminary analysis of the entire field showed that in the areas treated by the robot, the weed average density varied across the field from 6.8 to 9.1 weeds/m² (compared with 0.8 in the chemically treated area and 24.3 in the untreated area), the weed average density inside rows was 2.0-2.9 weeds / m (compared with 0 on the chemically treated area), and the emergence rate was 90-95%. The information about the robot's performance has high importance for the application of robotics for field tasks. With the help of the developed method, the performance can be assessed several times during the growth according to the robotic weeding frequency. When it’s used by farmers, they can know the field condition and efficiency of the robotic treatment all over the field. Farmers and researchers could develop optimal strategies for using the robot, such as seeding and weeding timing, robot settings, and plant and field parameters and geometry. The robot producers can have quantitative information from an actual working environment and improve the robots accordingly.

Keywords: agricultural robot, field robot, plant detection, robot performance

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Authors: Fatma Abdedayem

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We propose an extension to the famous method called Bag of words (BOW) which proved a successful role in the field of image categorization. Practically, this method based on representing image with visual words. In this work, firstly, we extract features from images using Spatial Pyramid Representation (SPR) and two dissimilar color descriptors which are opponent-SIFT and transformed-color-SIFT. Secondly, we fuse color local features by joining the two histograms coming from these descriptors. Thirdly, after collecting of all features, we generate multi-dictionaries coming from n random feature subsets that obtained by dividing all features into n random groups. Then, by using these dictionaries separately each image can be represented by n histograms which are lately concatenated horizontally and form the final histogram, that allows to combine Multiple Dictionaries (MDBoW). In the final step, in order to classify image we have applied Support Vector Machine (SVM) on the generated histograms. Experimentally, we have used two dissimilar image datasets in order to test our proposition: Caltech 256 and PASCAL VOC 2007.

Keywords: bag of words (BOW), color descriptors, multi-dictionaries, MDBoW

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Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes

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The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.

Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models

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Authors: Waddah S. Abdullah, Khaled F. Al-Omari

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Electrokinetic remediation is one of the most influential and effective methods to decontaminate contaminated soils. Electroosmosis and electromigration are the processes of electrochemical extraction of contaminants from soils. The driving force that causes removing contaminants from soils (electroosmosis process or electromigration process) is voltage gradient. Therefore, the electric field distribution throughout the soil domain is extremely important to investigate and to determine the factors that help to establish a uniform electric field distribution in order to make the clean-up process work properly and efficiently. In this study, small-sized passive electrodes (made of graphite) were placed at predetermined locations within the soil specimen, and the voltage drop between these passive electrodes was measured in order to observe the electrical distribution throughout the tested soil specimens. The electrokinetic test was conducted on two types of soils; a sandy soil and a clayey soil. The electrical distribution throughout the soil domain was conducted with different tests properties; and the electrical field distribution was observed in three-dimensional pattern in order to establish the electrical distribution within the soil domain. The effects of density, applied voltages, and degree of saturation on the electrical distribution within the remediated soil were investigated. The distribution of the moisture content, concentration of the sodium ions, and the concentration of the calcium ions were determined and established in three-dimensional scheme. The study has shown that the electrical conductivity within soil domain depends on the moisture content and concentration of electrolytes present in the pore fluid. The distribution of the electrical field in the saturated soil was found not be affected by its density. The study has also shown that high voltage gradient leads to non-uniform electric field distribution within the electroremediated soil. Very importantly, it was found that even when the electric field distribution is uniform globally (i.e. between the passive electrodes), local non-uniformity could be established within the remediated soil mass. Cracks or air gaps formed due to temperature rise (because of electric flow in low conductivity regions) promotes electrical tortuosity. Thus, fracturing or cracking formed in the remediated soil mass causes disconnection of electric current and hence, no removal of contaminant occur within these areas.

Keywords: contaminant removal, electrical tortuousity, electromigration, electroosmosis, voltage distribution

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Authors: Nalla Somaiah, Praveen Kumar

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Scaling of transistors and, hence, interconnects is very important for the enhanced performance of microelectronic devices. Scaling of devices creates significant complexity, especially in the multilevel interconnect architectures, wherein current crowding occurs at the corners of interconnects. Such a current crowding creates hot-spots at the respective corners, resulting in non-uniform temperature distribution in the interconnect as well. This non-uniform temperature distribution, which is exuberated with continued scaling of devices, creates a temperature gradient in the interconnect. In particular, the increased current density at corners and the associated temperature rise due to Joule heating accelerate the electromigration induced failures in interconnects, especially at corners. This has been the classic reliability issue associated with metallic interconnects. Herein, it is generally understood that electromigration induced damages can be avoided if the length of interconnect is smaller than a critical length, often termed as Blech length. Interestingly, the effect of non-negligible temperature gradients generated at these corners in terms of thermomigration and electromigration-thermomigration coupling has not attracted enough attention. Accordingly, in this work, the interplay between the electromigration and temperature gradient induced mass transport was studied using standard Blech structure. In this particular sample structure, the majority of the current is forcefully directed into the low resistivity metallic film from a high resistivity underlayer film, resulting in current crowding at the edges of the metallic film. In this study, 150 nm thick Cu metallic film was deposited on 30 nm thick W underlayer film in the configuration of Blech structure. Series of Cu thin strips, with lengths of 10, 20, 50, 100, 150 and 200 μm, were fabricated. Current density of ≈ 4 × 1010 A/m² was passed through Cu and W films at a temperature of 250ºC. Herein, along with expected forward migration of Cu atoms from the cathode to the anode at the cathode end of the Cu film, backward migration from the anode towards the center of Cu film was also observed. Interestingly, smaller length samples consistently showed enhanced migration at the cathode end, thus indicating the existence of inverse Blech length effect in presence of temperature gradient. A finite element based model showing the interplay between electromigration and thermomigration driving forces has been developed to explain this observation.

Keywords: Blech structure, electromigration, temperature gradient, thin films

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Authors: Loyd R. Hook, Maryam Moharek

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With the envisioned future growth of low altitude urban aircraft operations for airborne delivery service and advanced air mobility, strategies to coordinate and deconflict aircraft flight paths must be prioritized. Autonomous coordination and planning of flight trajectories is the preferred approach to the future vision in order to increase safety, density, and efficiency over manual methods employed today. Difficulties arise because any conflict resolution must be constrained by all other aircraft, all airspace restrictions, and all ground-based obstacles in the vicinity. These considerations make pair-wise tactical deconfliction difficult at best and unlikely to find a suitable solution for the entire system of vehicles. In addition, more traditional methods which rely on long time scales and large protected zones will artificially limit vehicle density and drastically decrease efficiency. Instead, strategic planning, which is able to respond to highly dynamic conditions and still account for high density operations, will be required to coordinate multiple vehicles in the highly constrained low altitude urban environment. This paper develops and evaluates such a planning algorithm which can be implemented autonomously across multiple aircraft and situations. Data from this evaluation provide promising results with simulations showing up to 10 aircraft deconflicted through a relatively narrow low-altitude urban canyon without any vehicle to vehicle or obstacle conflict. The algorithm achieves this level of coordination beginning with the assumption that each vehicle is controlled to follow an independently constructed flight path, which is itself free of obstacle conflict and restricted airspace. Then, by preferencing speed change deconfliction maneuvers constrained by the vehicles flight envelope, vehicles can remain as close to the original planned path and prevent cascading vehicle to vehicle conflicts. Performing the search for a set of commands which can simultaneously ensure separation for each pair-wise aircraft interaction and optimize the total velocities of all the aircraft is further complicated by the fact that each aircraft's flight plan could contain multiple segments. This means that relative velocities will change when any aircraft achieves a waypoint and changes course. Additionally, the timing of when that aircraft will achieve a waypoint (or, more directly, the order upon which all of the aircraft will achieve their respective waypoints) will change with the commanded speed. Put all together, the continuous relative velocity of each vehicle pair and the discretized change in relative velocity at waypoints resembles a hybrid reachability problem - a form of control reachability. This paper proposes two methods for finding solutions to these multi-body problems. First, an analytical formulation of the continuous problem is developed with an exhaustive search of the combined state space. However, because of computational complexity, this technique is only computable for pairwise interactions. For more complicated scenarios, including the proposed 10 vehicle example, a discretized search space is used, and a depth-first search with early stopping is employed to find the first solution that solves the constraints.

Keywords: strategic planning, autonomous, aircraft, deconfliction

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Authors: Andres Frederic

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We present the MindFlow system supporting the detection and the diagnosis of stresses. The heart of the system is a knowledge synthesis engine allowing occupational health stakeholders (psychologists, occupational therapists and human resource managers) to formulate queries related to stress and responding to users requests by recommending a pattern of stress if one exists. The stress pattern diagnosis is based on expert knowledge stored in the MindFlow stress ontology including stress feature vector. The query processing may involve direct access to the MindFlow system by occupational health stakeholders, online communication between the MindFlow system and the MindFlow domain experts, or direct dialog between a occupational health stakeholder and a MindFlow domain expert. The MindFlow knowledge model is generic in the sense that it supports the needs of psychologists, occupational therapists and human resource managers. The system presented in this paper is currently under development as part of a Dutch-Japanese project and aims to assist organisation in the quick diagnosis of stress patterns.

Keywords: occupational stress, stress management, physiological measurement, accident prevention

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Authors: Rajamani Doraiswami, Lahouari Cheded

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Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system.

Keywords: identification, linear parameter-varying systems, least-squares estimation, fault diagnosis, Kalman filter, emulators

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

Procedia PDF Downloads 162