Search results for: breath monitoring using pressure sensors

Authors: Mehtap Çalışkan, Nilüfer Yıldız Varan, Volkan Kaplan

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In this study, the effects of an atmospheric plasma treatment on the durability of water and oil repellent finishes of PET and PET/Spandex fabrics were tested. Fabrics were treated with a low-frequency atmospheric pressure glow discharge. After plasma treatments, the water and oil repellent finishes were applied using pad-dry-cure method. It was observed that plasma treatments improved the durability finish for all fabrics.

Keywords: atmospheric plasma, durable coating, oil repellency, PET/spandex fabrics, water repellency

Procedia PDF Downloads 412

Authors: Maria De Albuquerque Bercot, Caio Gustavo Mesquita Angelo, Daniela Maria Moreira Siqueira, Augusto Assucena De Vasconcellos, Rodrigo Studart Correa

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Mining is an important socioeconomic activity in Brazil although it negatively impacts the environment. Mineral operations cause irreversible changes in topography, removal of vegetation and topsoil, habitat destruction, displacement of fauna, loss of biodiversity, soil erosion, siltation of watercourses and have potential to enhance climate change. Due to the impacts and its pollution potential, mining activity in Brazil is legally subjected to environmental licensing. Unlicensed mining operations or operations that not abide to the terms of an obtained license are taken as environmental crimes in the country. This work reports a case analyzed in the Forensic Institute of the Brazilian Federal District Civil Police. The case consisted of detecting illegal aspects of sand exploitation from a licensed mine in Federal District, nearby Brasilia city. The fieldwork covered an area of roughly 6 ha, which was surveyed with an unmanned aerial vehicle (UAV) (PHANTOM 3 ADVANCED). The overflight with UAV took about 20 min, with maximum flight height of 100 m. 592 UAV georeferenced images were obtained and processed in a photogrammetric software (AGISOFT PHOTOSCAN 1.1.4), which generated a mosaic of geo-referenced images and a 3D model in less than six working hours. The 3D model was analyzed in a forensic software for accurate modeling and volumetric analysis. (MAPTEK I-SITE FORENSIC 2.2). To ensure the 3D model was a true representation of the mine site, coordinates of ten control points and reference measures were taken during fieldwork and compared to respective spatial data in the model. Finally, these spatial data were used for measuring mining area, excavation depth and volume of exploited sand. Results showed that mine holder had not complied with some terms and conditions stated in the granted license, such as sand exploration beyond authorized extension, depth and volume. Easiness, the accuracy and expedition of procedures used in this case highlight the employment of UAV imagery and computational photogrammetry as efficient tools for outdoor forensic exams, especially on environmental issues.

Keywords: computational photogrammetry, environmental monitoring, mining, UAV

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Authors: Arindam Roy, Madhushree Das, Apurba Manna, Samir Maity

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In this research paper, an algorithmic approach is developed to solve a novel multi-objective four-dimensional traveling salesman problem (MO4DTSP) where different paths with various numbers of conveyances are available to travel between two cities. NSGA-II and Decomposition algorithms are modified to solve MO4DTSP in an IoT-based transport system. This IoT-based transport system can be widely observed, analyzed, and controlled by an extensive distribution of traffic networks consisting of various types of sensors and actuators. Due to urbanization, most of the cities are connected using an intelligent traffic management system. Practically, for a traveler, multiple routes and vehicles are available to travel between any two cities. Thus, the classical TSP is reformulated as multi-route and multi-vehicle i.e., 4DTSP. The proposed MO4DTSP is designed with traveling cost, time, and customer satisfaction as objectives. In reality, customer satisfaction is an important parameter that depends on travel costs and time reflects in the present model.

Keywords: multi-objective four-dimensional traveling salesman problem (MO4DTSP), decomposition, NSGA-II, IoT-based transport system, customer satisfaction

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Authors: Komal Saini, B. K. Sahoo, B.S. Bajwa

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In the present study, indoor radon and thoron concentrations have been estimated using newly developed twin cup based pin hole dosimeter with single entry face in some areas of Punjab state, India. The equilibrium equivalent concentration (EEC) of radon and thoron has also been estimated directly by using progeny sensors, fabricated by BARC, India. Observed radon and thoron concentrations varied from 38.7±5.79 to 98.7±13.11 Bq/m3 and 25.38±6.56 to 126.56±14.23 Bq/m3 with an average value of 61.59±8.11 & 70.89±9.52 Bq/m3 respectively. Average equilibrium equivalent concentration of radon and thoron was 27.98±4.66 & 2.24±0.61 Bq/m3. Calculated equilibrium factor for radon and thoron was 0.467 and 0.034 in the present study. Annual inhalation dose calculated from the present observed concentrations, varied from 1.80 to 3.60 mSv/year with an average value of 2.52 mSv/year, which is well within reference level. It has been observed from the present study that thoron is a significant contributor to the inhalation dose which is about 25% of the total inhalation dose.

Keywords: radon, thoron, pin hole cup dosimeter, DTPS/DRPS, annual inhalation dose

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Authors: Akila Murali, Prithika Manivel

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Disasters are defined as a serious disruption of the functioning of a community or a society, which involves widespread human, material, economic or environmental impacts. The number of people suffering food crisis as a result of natural disasters has tripled in the last thirty years. The economic losses due to natural disasters have shown an increase with a factor of eight over the past four decades, caused by the increased vulnerability of the global society, and also due to an increase in the number of weather-related disasters. Efficient disaster detection and alerting systems could reduce the loss of life and properties. In the event of a disaster, another important issue is a good search and rescue system with high levels of precision, timeliness and safety for both the victims and the rescuers. Wireless Sensor Networks technology has the capability of quick capturing, processing, and transmission of critical data in real-time with high resolution. This paper studies the capacity of sensors and a Wireless Sensor Network to collect, collate and analyze valuable and worthwhile data, in an ordered manner to help with disaster management.

Keywords: alerting systems, disaster detection, Ad Hoc network, WSN technology

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Authors: Moumen Abdelhafidh, Stribu Bogdan, Laboureur Delphine, Gallant Johan, Hendrick Patrick

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This study is part of an ongoing effort to improve the understanding of phenomena occurring during the intermediate ballistic phase, such as muzzle flows. A thorough comprehension of muzzle flow fields is essential for optimizing muzzle device and projectile design. This flow characterization has heretofore been almost entirely limited to local and intrusive measurement techniques such as pressure measurements using pencil probes. Consequently, the body of quantitative experimental data is limited, so is the number of numerical codes validated in this field. The objective of the work presented here is to demonstrate the applicability of the Particle Image Velocimetry (PIV) technique in the challenging environment of the propellant flow of a .300 blackout weapon to provide accurate velocity measurements. The key points of a successful PIV measurement are the selection of the particle tracer, their seeding technique, and their tracking characteristics. We have experimentally investigated the aforementioned points by evaluating the resistance, gas dispersion, laser light reflection as well as the response to a step change across the Mach disk for five different solid tracers using two seeding methods. To this end, an experimental setup has been performed and consisted of a PIV system, the combustion chamber pressure measurement, classical high-speed schlieren visualization, and an aerosol spectrometer. The latter is used to determine the particle size distribution in the muzzle flow. The experimental results demonstrated the ability of PIV to accurately resolve the salient features of the propellant flow, such as the under the expanded jet and vortex rings, as well as the instantaneous velocity field with maximum centreline velocities of more than 1000 m/s. Besides, naturally present unburned particles in the gas and solid ZrO₂ particles with a nominal size of 100 nm, when coated on the propellant powder, are suitable as tracers. However, the TiO₂ particles intended to act as a tracer, surprisingly not only melted but also functioned as a combustion accelerator and decreased the number of particles in the propellant gas.

Keywords: intermediate ballistic, muzzle flow fields, particle image velocimetry, propellant gas, particle size distribution, under expanded jet, solid particle tracers

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Authors: Luis Castiella, Mariano Rueda, Catalina Palacio

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The world’s rapid urbanisation represents an excellent opportunity to implement initiatives that are oriented towards a country’s general development. However, this phenomenon has created considerable pressure on current urban models, pushing them nearer to a crisis. As a result, several factors usually associated with underdevelopment have been steadily rising. Moreover, actions taken by public authorities have not been able to keep up with the speed of urbanisation, which has impeded them from meeting the demands of society, responding with reactionary policies instead of with coordinated, organised efforts. In contrast, the concept of a Smart City which emerged around two decades ago, in principle, represents a city that utilises innovative technologies to remedy the everyday issues of the citizen, empowering them with the newest available technology and information. This concept has come to adopt a wider meaning, including human and social capital, as well as productivity, economic growth, quality of life, environment and participative governance. These developments have also disrupted the management of institutions such as academia, which have become key in generating scientific advancements that can solve pressing problems, and in forming a specialised class that is able to follow up on these breakthroughs. In this light, the Ministry of Modernisation of the Argentinian Nation has created a model that is rooted in the concept of a ‘Smart City’. This effort considered all the dimensions that are at play in an urban environment, with careful monitoring of each sub-dimensions in order to establish the government’s priorities and improving the effectiveness of its operations. In an attempt to ameliorate the overall efficiency of the country’s economic and social development, these focused initiatives have also encouraged citizen participation and the cooperation of the private sector: replacing short-sighted policies with some that are coherent and organised. This process was developed gradually. The first stage consisted in building the model’s structure; the second, at applying the method created on specific case studies and verifying that the mechanisms used respected the desired technical and social aspects. Finally, the third stage consists in the repetition and subsequent comparison of this experiment in order to measure the effects on the ‘treatment group’ over time. The first trial was conducted on 717 municipalities and evaluated the dimension of Governance. Results showed that levels of governmental maturity varied sharply with relation to size: cities with less than 150.000 people had a strikingly lower level of governmental maturity than cities with more than 150.000 people. With the help of this analysis, some important trends and target population were made apparent, which enabled the public administration to focus its efforts and increase its probability of being successful. It also permitted to cut costs, time, and create a dynamic framework in tune with the population’s demands, improving quality of life with sustained efforts to develop social and economic conditions within the territorial structure.

Keywords: composite index, comprehensive model, smart cities, strategic framework

Procedia PDF Downloads 178

Authors: Masuma Novak, Daniel Novak

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Background: Sweden along with other Nordic countries has the highest incidence of type 1 diabetes mellitus (T1DM) worldwide. The trend is increasing globally. The diagnosis is often given at the emergency clinic when children arrive with cardinal symptom of T1DM. Children with T1DM are known to have an increased risk of microvascular- and macrovascular complications. A family history of cardiovascular complications may further increase their risk. Clinically evident diabetes-related vascular complications are however rarely visible in childhood and adolescence, whereby an intensive diabetes treatment and normoglycemic control is a goal for every child. This study is a risk evaluation of children with T1DM based on their family’s cardiovascular history. Method: Since 2005 the Better Diabetes Diagnosis (BDD) study is a nationwide Swedish prospective cohort study that recruits new-onset T1DM who are less than 18 years old at time of diagnosis. For each newly diagnosed child, blood samples are collected for specific HLA genotyping and islet autoantibody assays and their family’s cardiovascular history is evaluated. As part of the BDD study, during the years 2010-2013 all children diagnosed with T1DM at the Queen Silvia’s Children’s Hospital in Sweden were asked about their family’s cardiovascular history. Questions regarded maternal and paternal high blood pressure, stroke, and myocardial infarction before the age of 55 years, and hyperlipidemia were answered. A maximum risk score of eight was possible. All children are clinically observed prospectively for early functional and structural abnormalities such as protein uremia, blood pressure, and retinopathy. Results: A total of 275 children aged 0 to 18 years were diagnosed with T1DM at the Queen Silvia’s Children’s Hospital emergency clinic during this four year period. The participation rate was 99.7%. 26.4% of the children had no hereditary cardiovascular risk factors. 22.7 % had one risk factor and 18.8% had two risk factors. 14.8% had three risk factors. 9.7% had four risk factors and 7.5% had five risk factors or more. Conclusion: Among children with T1DM in Sweden there is a difference in hereditary cardiovascular risk factors. These results indicate that children with T1DM who also have increased hereditary cardiovascular risk factors should be monitored closely with early screening for functional and structural cardiovascular abnormalities. This is a very preliminary and ongoing study which will be complemented with the cardiovascular risk analysis among children without T1DM.

Keywords: children, type I diabetes, emergency clinic, CVD risk

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Authors: Kossigan Bernard Dedey, David Grenier, Tiphaine Lucas

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Bread dough is often described as a dispersion of gas cells in a continuous gluten/starch matrix. The final bread crumb structure is strongly related to gas cell walls (GCWs) rupture during baking. At the end of proofing and during baking, part of the thinnest GCWs between expanding gas cells is reduced to a gluten film of about the size of a starch granule. When such size is reached gluten and starch granules must be considered as interacting phases in order to account for heterogeneities and appropriately describe GCW rupture. Among experimental investigations carried out to assess GCW rupture, no experimental work was performed to observe the GCW rupture in the baking conditions at GCW scale. In addition, attempts to numerically understand GCW rupture are usually not performed at the GCW scale and often considered GCWs as continuous. The most relevant paper that accounted for heterogeneities dealt with the gluten/starch interactions and their impact on the mechanical behavior of dough film. However, stress concentration in GCW was not discussed. In this study, both experimental and numerical approaches were used to better understand GCW rupture in bread dough during baking. Experimentally, a macro-scope placed in front of a two-chamber device was used to observe the rupture of a real GCW of 200 micrometers in thickness. Special attention was paid in order to mimic baking conditions as far as possible (temperature, gas pressure and moisture). Various differences in pressure between both sides of GCW were applied and different modes of fracture initiation and propagation in GCWs were observed. Numerically, the impact of gluten/starch interactions (cohesion or non-cohesion) and rheological moduli ratio on the mechanical behavior of GCW under unidirectional extension was assessed in 2D/3D. A non-linear viscoelastic and hyperelastic approach was performed to match the finite strain involved in GCW during baking. Stress concentration within GCW was identified. Simulated stresses concentration was discussed at the light of GCW failure observed in the device. The gluten/starch granule interactions and rheological modulus ratio were found to have a great effect on the amount of stress possibly reached in the GCW.

Keywords: dough, experimental, numerical, rupture

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Authors: Siyamak Ziyaei, Siti Khalijah Mazlan, Petros Lappas

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Compressed Natural Gas (CNG) mainly consists of Methane CH₄ and has a low carbon to hydrogen ratio relative to other hydrocarbons. As a result, it has the potential to reduce CO₂ emissions by more than 20% relative to conventional fuels like diesel or gasoline Although Natural Gas (NG) has environmental advantages compared to other hydrocarbon fuels whether they are gaseous or liquid, its main component, CH₄, burns at a slower rate than conventional fuels A higher pressure and a leaner cylinder environment will overemphasize slow burn characteristic of CH₄. Lean combustion and high compression ratios are well-known methods for increasing the efficiency of internal combustion engines. In order to achieve successful CNG lean combustion in Spark Ignition (SI) engines, a strong ignition system is essential to avoid engine misfires, especially in ultra-lean conditions. Turbulent Jet Ignition (TJI) is an ignition system that employs a pre-combustion chamber to ignite the lean fuel mixture in the main combustion chamber using a fraction of the total fuel per cycle. TJI enables ultra-lean combustion by providing distributed ignition sites through orifices. The fast burn rate provided by TJI enables the ordinary SI engine to be comparable to other combustion systems such as Homogeneous Charge Compression Ignition (HCCI) or Controlled Auto-Ignition (CAI) in terms of thermal efficiency, through the increased levels of dilution without the need of sophisticated control systems. Due to the physical geometry of TJIs, which contain small orifices that connect the prechamber to the main chamber, scavenging is one of the main factors that reduce TJI performance. Specifically, providing the right mixture of fuel and air has been identified as a key challenge. The reason for this is the insufficient amount of air that is pushed into the pre-chamber during each compression stroke. There is also the problem that combustion residual gases such as CO₂, CO and NOx from the previous combustion cycle dilute the pre- chamber fuel-air mixture preventing rapid combustion in the pre-chamber. An air-controlled active TJI is presented in this paper in order to address these issues. By applying air to the pre-chamber at a sufficient pressure, residual gases are exhausted, and the air-fuel ratio is controlled within the pre-chamber, thereby improving the quality of combustion. This paper investigates the 3D-simulated combustion characteristics of a Direct Injected (DI-CNG) fuelled SI en- gine with a pre-chamber equipped with an air channel by using AVL FIRE software. Experiments and simulations were performed at the Worldwide Mapping Point (WWMP) at 1500 Revolutions Per Minute (RPM), 3.3 bar Indicated Mean Effective Pressure (IMEP), using only conventional spark plugs as the baseline. After validating simulation data, baseline engine conditions were set for all simulation scenarios at λ=1. Following that, the pre-chambers with and without an auxiliary fuel supply were simulated. In the simulated (DI-CNG) SI engine, active TJI was observed to perform better than passive TJI and spark plug. In conclusion, the active pre-chamber with an air channel demon-strated an improved thermal efficiency (ηth) over other counterparts and conventional spark ignition systems.

Keywords: turbulent jet ignition, active air control turbulent jet ignition, pre-chamber ignition system, active and passive pre-chamber, thermal efficiency, methane combustion, internal combustion engine combustion emissions

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Authors: Hassan Sharafuddin, Chekra Allani

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Academicians at the Arab Open University have always voiced their concern about the efficacy of the blended learning process. Based on 75% independent study and 25% face-to-face tutorial, it poses the challenge of the predisposition to adjustment. Being used to the psychology of traditional educational systems, AOU students cannot be easily weaned from being spoon-fed. Hence they lack the motivation to plunge into self-study. For better involvement of AOU students into the learning practices, it is imperative to diagnose the factors that impede or increase their motivation. This is conducted through an empirical study grounded upon observations and tested hypothesis and aimed at monitoring and optimizing the students’ learning outcome. Recommendations of the research will follow the findings.

Keywords: academic performance, blended learning, educational psychology, independent study, pedagogy

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Authors: M. Blokh

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Method of combined teaching laws of classical mechanics and hydrostatics in non-inertial reference frames for undergraduate students is proposed. Pressure distribution in a liquid (or gas) moving with acceleration is considered. Combined effect of hydrostatic force and force of inertia on a body immersed in a liquid can lead to paradoxical results, in a motion of pendulum in particular. The body motion under Stokes force influence and forces in rotating reference frames are investigated as well. Problems and difficulties in student perceptions are analyzed.

Keywords: hydrodynamics, mechanics, non-inertial reference frames, teaching

Procedia PDF Downloads 377

Authors: Ching-Ting Hsu, Wei-Hua Ho, Yi-Chun Chang

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Video object tracking is one of the popular research topics in computer graphics area. The trajectory can be applied in security, traffic control, even the sports training. The trajectory for sports training can be utilized to analyze the athlete’s performance without traditional sensors. There are many relevant works which utilize mean shift algorithm with background subtraction. This kind of the schemes should select a kernel function which may affect the accuracy and performance. In this paper, we consider the motion information in the pre-coded bitstream. The proposed algorithm extracts the trajectory by composing the motion vectors from the pre-coded bitstream. We gather the motion vectors from the overlap area of the object and calculate mean of the overlapped motion vectors. We implement and simulate our proposed algorithm in H.264 video codec. The performance is better than relevant works and keeps the accuracy of the object trajectory. The experimental results show that the proposed trajectory extraction can extract trajectory form the pre-coded bitstream in high accuracy and achieve higher performance other relevant works.

Keywords: H.264, video bitstream, video object tracking, sports training

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Authors: Sui Yan Wong, Keat Ping Yeoh, Chi Wai Hui

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In this study, supercritical steam is introduced to Combined Cycle Power Plant (CCPP) in an attempt to further optimize energy recovery. Subcritical steam is commonly used in the CCPP, operating at maximum pressures around 150-160 bar. Supercritical steam is an alternative to increase heat recovery during vaporization period of water. The idea of improvement using supercritical steam is further examined with the use of exergy, pinch analysis and Aspen Plus simulation.

Keywords: exergy, pinch, combined cycle power plant, supercritical steam

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Authors: Marie Kudrnová, Jana Rejková

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The samples of supplied INCONEL 601, 617, 625, and HASTELLOY C-22 alloys and experimental nickel alloy MoNiCr were examined by XPS (X-ray photoelectron spectroscopy) before and after exposure. The experiment was performed in a mixture of LiCl-KCl salt (58.2-41.8 wt. %). The exposure conditions were 440°C, pressure 0.2 MPa, 500 hours in an inert argon atmosphere. The XPS analysis shows that a thin oxide layer composed of metal oxides such as NiO, Cr₂O₃, and Nb₂O₅ was formed. After sputtering the exposed surface with Ar ions, metals were also detected in the elemental state, indicating a very thin protective oxide layer with a thickness in units of up to tens of nanometers.

Keywords: XPS, MSR, nickel alloy, metal oxides

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Authors: Mohadeseh Seyednezhad, Armin Rajabi, Andanastui Muchtar, Mahendra Rao Somalu

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This work investigates the electrical properties of NiO-SDC/SDC anode sintered at about 1200 ○C for 1h through a relatively new approach, namely the microwave method. Nano powders Sm0.2Ce0.8O1.9 (SDC) and NiO were mixed by using a high-energy ball-mill and subsequent co-pressed at three different compaction pressures 200, 300 and 400 MPa. The novelty of this study consists in the effect of compaction pressure on the electrochemical performance of Ni-SDC/SDC anode, with no binder used between layers. The electrical behavior of the prepared anode has been studied by electrochemical impedance spectra (EIS) in controlled atmospheres, operating at high temperatures (600-800 °C).

Keywords: sintering, fuel cell, electrical conductivity, nanostructures, impedance spectroscopy, ceramics

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Authors: A. Perdomo, J. R. Bacca, Q. E. Jabid

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In recent years, technological and investigative progress has been achieved in the area of monitoring of equipment and installation as a result of a deeper understanding of physical phenomenon associated with the non-destructive tests (NDT). The modal analysis proposes an efficient solution to determine the dispersion curves of an arbitrary waveguide cross-sectional. Dispersion curves are essential in the discontinuity localization based on guided waves. In this work, an isotropic hollow cylinder is dynamically analyzed in ANSYS to obtain resonant frequencies and mode shapes all of them associated with the dispersion curves. The numerical results provide the relation between frequency and wavelength which is the foundation of the dispersion curves. Results of the simulation process are validated with the software GUIGW.

Keywords: ansys APDL, dispersion curves, guide waves, modal analysis

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Authors: Joaquin Navarro Perales, Ana Lidia Franzoni Velázquez, Francisco Cervantes Pérez

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The Mexican educational system faces diverse challenges related with the quality and coverage of education. The development of Intelligent Tutoring Systems (ITS) may help to solve some of them by helping teachers to customize their classes according to the performance of the students in online courses. In this work, we propose the adaptation of a functional ITS based on Bloom’s taxonomy called Sistema de Apoyo Generalizado para la Enseñanza Individualizada (SAGE), to measure student’s metacognition and their emotional response based on Marzano’s taxonomy. The students and the system will share the control over the advance in the course, so they can improve their metacognitive skills. The system will not allow students to get access to subjects not mastered yet. The interaction between the system and the student will be implemented through Natural Language Processing techniques, thus avoiding the use of sensors to evaluate student’s response. The teacher will evaluate student’s knowledge utilization, which is equivalent to the last cognitive level in Marzano’s taxonomy.

Keywords: intelligent tutoring systems, student modelling, metacognition, affective computing, natural language processing

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Authors: S. Cherif, A. Medjahed, M. Bouafia, A. Manallah

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A light wave is characterized by 4 characteristics: its amplitude, its frequency, its phase and the direction of polarization of its luminous vector (the electric field). It is in this last characteristic that we will be interested. The polarization of the light was introduced in order to describe the vectorial behavior of the light; it describes the way in which the electric field evolves in a point of space. Our work consists in studying diffusing mediums. Different types of biological fluids were selected to study the evolution of each with increasing scattering power of the medium, and in the same time to make a comparison between them. When crossing these mediums, the light undergoes modifications and/or deterioration of its initial state of polarization. This phenomenon is related to the properties of the medium, the idea is to compare the characteristics of the entering and outgoing light from the studied medium by a white light. The advantage of this model is that it is experimentally accessible workable intensity measurements with CCD sensors and allows operation in 2D. The latter information is used to discriminate some physical properties of the studied areas. We chose four types of milk to study the evolution of each with increasing scattering power of the medium.

Keywords: light polarization, Mueller matrix, Mueller images, diffusing medium, milk

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Authors: Eugene Eduful

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This paper introduces an approach that utilizes a Wireless Sensor Network (WSN) to detect vegetation encroachment between segments of distribution lines. The WSN was designed and implemented, involving the seamless integration of Arduino Uno and Mega systems. This integration demonstrates a method for addressing the challenges posed by vegetation interference. The primary aim of the study is to improve the reliability of power supply in areas characterized by forested terrain, specifically targeting overhead powerlines. The experimental results validate the effectiveness of the proposed system, revealing its ability to accurately identify and locate instances of vegetation encroachment with a remarkably high degree of precision.

Keywords: wireless sensor network, vegetation encroachment, line of sight, Arduino Uno, XBEE

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Authors: R. A. C. H. Seneviratne, M. Gunawardana, R. P. N. P. Rajapakse

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To address the micronutrient deficiencies in the Asian region, the World Food Program in its current mandate highlights the requirement of employing efficient fortification of micronutrients in rice, under the program 'Scaling-up Rice Fortification in Asia'. The current industrial methods of rice fortification with micronutrients are not promising due to poor permeation or retention of fortificants. This study was carried out to develop a method to improve fortification of micronutrients in rice by removing the air barriers for diffusing micronutrients through the husk. For the purpose, soaking stage of paddy was coupled with vacuum (- 0.6 bar) for different time periods. Both long and short grain varieties of paddy (BG 352 and BG 358, respectively) initially tested for water uptake during hot soaking (70 °C) under vacuum (28.5 and 26.15%, respectively) were significantly (P < 0.05) higher than that of non-vacuum conditions (25.24 and 25.45% respectively), exhibiting the effectiveness of water diffusion into the rice grains through the cleared pores under negative pressure. To fortify the selected micronutrients (iron and zinc), paddy was vacuum-soaked in Fe2+ or Zn2+ solutions (500 ppm) separately for one hour, and continued soaking for another 3.5 h without vacuum. Significantly (P<0.05) higher amounts of Fe2+ and Zn2+ were observed throughout the soaking period, in both short and long grain varieties of rice compared to rice treated without vacuum. To achieve the recommended limits of World Food Program standards for fortified iron (40-48 mg/kg) and zinc (60-72 mg/kg) in rice, soaking was done with different concentrations of Fe2+ or Zn2+ for varying time periods. For both iron and zinc fortifications, hot soaking (70 °C) in 400 ppm solutions under vacuum (- 0.6 bar) during the first hour followed by 2.5 h under atmospheric pressure exhibited the optimum fortification (Fe2+: 46.59±0.37 ppm and Zn2+: 67.24±1.36 ppm) with a greater significance (P < 0.05) compared to the controls (Fe2+: 38.84±0.62 ppm and Zn2+: 52.55±0.55 ppm). This finding was further confirmed by the XRF images, clearly showing a greater fixation of Fe2+ and Zn2+ in the rice grains under vacuum treatment. Moreover, there were no significant (P>0.05) differences among both Fe2+ and Zn2+ contents in fortified rice even after polishing and washing, confirming their greater retention. A seven point hedonic scale showed that the overall acceptability for both iron and zinc fortified rice were significantly (P < 0.05) higher than the parboiled rice without fortificants. With all the drawbacks eliminated, per kilogram cost will be less than US$ 1 for both iron and zinc fortified rice. The new method of rice fortification studied and developed in this research, can be claimed as the best method in comparison to other rice fortification methods currently deployed.

Keywords: fortification, vacuum assisted diffusion, micronutrients, parboiling

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Authors: Ibrahim Gomaa, Hoda M. O. Mokhtar

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Although most of the existing skyline queries algorithms focused basically on querying static points through static databases; with the expanding number of sensors, wireless communications and mobile applications, the demand for continuous skyline queries has increased. Unlike traditional skyline queries which only consider static attributes, continuous skyline queries include dynamic attributes, as well as the static ones. However, as skyline queries computation is based on checking the domination of skyline points over all dimensions, considering both the static and dynamic attributes without separation is required. In this paper, we present an efficient algorithm for computing continuous skyline queries without discriminating between static and dynamic attributes. Our algorithm in brief proceeds as follows: First, it excludes the points which will not be in the initial skyline result; this pruning phase reduces the required number of comparisons. Second, the association between the spatial positions of data points is examined; this phase gives an idea of where changes in the result might occur and consequently enables us to efficiently update the skyline result (continuous update) rather than computing the skyline from scratch. Finally, experimental evaluation is provided which demonstrates the accuracy, performance and efficiency of our algorithm over other existing approaches.

Keywords: continuous query processing, dynamic database, moving object, skyline queries

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Authors: Aldona Kluczek

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Energy efficient process have become a pressing research field in manufacturing. The arguments for having an effective industrial energy efficiency processes are interacted with factors: economic and environmental impact, and energy security. Improvements in energy efficiency are most often achieved by implementation of more efficient technology or manufacturing process. Current processes of electricity production represents the biggest consumption of energy and the greatest amount of emissions to the environment. The goal of this study is to improve the potential energy-savings and reduce greenhouse emissions related to improvement scenarios for the treatment of hardwood lumber produced by an industrial plant operating in the U.S. through the application of green balancing procedure, in order to find the preferable efficient technology. The green procedure for energy is based on analysis of energy efficiency data. Three alternative scenarios of the cogeneration systems plant (CHP) construction are considered: generation of fresh steam, the purchase of a new boiler with the operating pressure 300 pounds per square inch gauge (PSIG), an installation of a new boiler with a 600 PSIG pressure. In this paper, the application of a bottom-down modelling for energy flow to devise a streamlined Energy and Emission Flow Analyze method for the technology of producing electricity is illustrated. It will identify efficiency or technology of a given process to be reached, through the effective use of energy, or energy management. Results have shown that the third scenario seem to be the efficient alternative scenario considered from the environmental and economic concerns for treating hardwood lumber. The energy conservation evaluation options could save an estimated 6,215.78 MMBtu/yr in each year, which represents 9.5% of the total annual energy usage. The total annual potential cost savings from all recommendations is $143,523/yr, which represents 30.1% of the total annual energy costs. Estimation have presented that energy cost savings are possible up to 43% (US$ 143,337.85), representing 18.6% of the total annual energy costs.

Keywords: alternative scenario improvements, cogeneration system, energy and emission flow analyze, energy balancing, green procedure, hardwood lumber manufacturing process

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

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Authors: Sanjay Kumar, Lillie Dewan

Abstract:

The study of complex dynamic systems has advanced through various scientific approaches with the help of computer modeling. The common design trends in aerospace system design can be applied to quadcopter design. A quadcopter is a nonlinear, under-actuated system with complex aerodynamics parameters and creates challenges that demand new, robust, and effective control approaches. The flight control stability can be improved by planning and tracking the trajectory and reducing the effect of sensors and the operational environment. This paper presents a modern design Simmechanics visual modeling approach for a mechanical model of a quadcopter with three degrees of freedom. The Simmechanics model, considering inertia, mass, and geometric properties of a dynamic system, produces multiple translation and rotation maneuvers. The proportional, integral, and derivative (PID) controller is integrated with the Simmechanics model to follow a predefined quadcopter rotational trajectory for a fixed time interval. The results presented are satisfying. The simulation of the quadcopter control performed operations successfully.

Keywords: nonlinear system, quadcopter model, simscape modelling, proportional-integral-derivative controller

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Authors: Muhammad Bilal, Adil Ahmed

Abstract:

This study proposes an approach for electrical induction motor predictive maintenance utilizing machine learning algorithms. On the basis of a study of temperature data obtained from sensors put on the motor, the goal is to predict motor failures. The proposed models are trained to identify whether a motor is defective or not by utilizing machine learning algorithms like Support Vector Machines (SVM) and K-Nearest Neighbors (KNN). According to a thorough study of the literature, earlier research has used motor current signature analysis (MCSA) and vibration data to forecast motor failures. The temperature signal methodology, which has clear advantages over the conventional MCSA and vibration analysis methods in terms of cost-effectiveness, is the main subject of this research. The acquired results emphasize the applicability and effectiveness of the temperature-based predictive maintenance strategy by demonstrating the successful categorization of defective motors using the suggested machine learning models.

Keywords: predictive maintenance, electrical induction motors, machine learning, temperature signal methodology, motor failures

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Authors: Joon Hock Yeo, Munirah Ismail

Abstract:

Chronic venous insufficiency is a condition where the venous wall or venous valves fail to operate properly. As such, it is difficult for the blood to return from the lower extremities back to the heart. Chronic venous insufficiency affects many people worldwide. In last decade, there have been many new and innovative designs of prosthetic venous valves to replace the malfunction native venous valves. However, thus far, to the authors’ knowledge, there is no successful prosthetic venous valve. In this project, we have developed a venous valve which could operate under low pressure. While further testing is warranted, this unique valve could potentially alleviate problems associated with chronic venous insufficiency.

Keywords: prosthetic venous valve, bi-leaflet valve, chronic venous insufficiency, valve hemodynamics

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Authors: Ousmane Sarr

Abstract:

The Senegalese coasts have high productivity of fishery resources due to the frequency of intense up-welling system that occurs along its coast, caused by the maritime trade winds making its waters nutrients rich. Fishing plays a primordial role in Senegal's socioeconomic plans and food security. However, a global diagnosis of the Senegalese maritime fishing sector has highlighted the challenges this sector encounters. Among these concerns, some significant stocks, a priority target for artisanal fishing, need further assessment. If no efforts are made in this direction, most stock will be overexploited or even in decline. It is in this context that this research was initiated. This investigation aimed to apply a multi-modal approach (LBB, Catch-only-based CMSY model and its most recent version (CMSY++); JABBA, and JABBA-Select) to assess the stock of Atlantic bonito, Sarda sarda (Bloch, 1793) in the Senegalese Exclusive Economic Zone (SEEZ). Available catch, effort, and size data from Atlantic bonito over 15 years (2004-2018) were used to calculate the nominal and standardized CPUE, size-frequency distribution, and length at retentions (50 % and 95 % selectivity) of the species. These relevant results were employed as input parameters for stock assessment models mentioned above to define the stock status of this species in this region of the Atlantic Ocean. The LBB model indicated an Atlantic bonito healthy stock status with B/BMSY values ranging from 1.3 to 1.6 and B/B0 values varying from 0.47 to 0.61 of the main scenarios performed (BON_AFG_CL, BON_GN_Length, and BON_PS_Length). The results estimated by LBB are consistent with those obtained by CMSY. The CMSY model results demonstrate that the SEEZ Atlantic bonito stock is in a sound condition in the final year of the main scenarios analyzed (BON, BON-bt, BON-GN-bt, and BON-PS-bt) with sustainable relative stock biomass (B2018/BMSY = 1.13 to 1.3) and fishing pressure levels (F2018/FMSY= 0.52 to 1.43). The B/BMSY and F/FMSY results for the JABBA model ranged between 2.01 to 2.14 and 0.47 to 0.33, respectively. In contrast, The estimated B/BMSY and F/FMSY for JABBA-Select ranged from 1.91 to 1.92 and 0.52 to 0.54. The Kobe plots results of the base case scenarios ranged from 75% to 89% probability in the green area, indicating sustainable fishing pressure and an Atlantic bonito healthy stock size capable of producing high yields close to the MSY. Based on the stock assessment results, this study highlighted scientific advice for temporary management measures. This study suggests an improvement of the selectivity parameters of longlines and purse seines and a temporary prohibition of the use of sleeping nets in the fishery for the Atlantic bonito stock in the SEEZ based on the results of the length-base models. Although these actions are temporary, they can be essential to reduce or avoid intense pressure on the Atlantic bonito stock in the SEEZ. However, it is necessary to establish harvest control rules to provide coherent and solid scientific information that leads to appropriate decision-making for rational and sustainable exploitation of Atlantic bonito in the SEEZ and the Eastern Atlantic Ocean.

Keywords: multi-model approach, stock assessment, atlantic bonito, SEEZ

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Authors: Abdulsallam A. Bakdash, Aiyshah M. Alshehri, Hind M. Alenzi

Abstract:

Benzatropine (benztropine) is used to treat symptoms of Parkinson's disease or involuntary movements due to the side effects of certain psychiatric drugs. We report in this study, results of a procedure for the determination of benzatropine in hair using LLE, once with methanol and second with phosphate buffer (pH 6.0), followed by filtration and then re-extraction with dichloromethane. A GC/MS method was developed and validated for this determination using selected ion monitoring (SIM) detection without derivatization. Linearity established over the concentration range 0.1-20.0 ng/mg hair, and the correlation coefficients were greater than 0.99. Recoveries were 52.2% and 21.1% using methanol and phosphate buffer extraction, respectively. Detection limits of benzatropine in hair were between 0.65 and 3.0 ng/mg hair, while the accuracy were 10.4% and 18.5% (RSD), respectively. We also applied this method to the analysis of soaked hair samples and demonstrated that the LLE using methanol meets the requirement for the analysis of benzatropine in hair.

Keywords: hair analysis, benzatropine, liquid-liquid extraction, GC/MS

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Authors: Qiaosi Li, Frankie Kwan Kit Wong, Tung Fung

Abstract:

Lightweight unmanned aerial vehicle (UAV) loading with novel sensors offers a low cost approach for data acquisition in complex environment. This study established a framework for applying UAV system in complex environment quick mapping and assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area Mai Po Inner Deep Bay Ramsar Site, Hong Kong. The study area was part of shallow bay with flat terrain and the major species including reedbed and four mangroves: Kandelia obovata, Aegiceras corniculatum, Acrostichum auerum and Acanthus ilicifolius. Other species involved in various graminaceous plants, tarbor, shrub and invasive species Mikania micrantha. In particular, invasive species climbed up to the mangrove canopy caused damage and morphology change which might increase species distinguishing difficulty. Hyperspectral images were acquired by Headwall Nano sensor with spectral range from 400nm to 1000nm and 0.06m spatial resolution image. A sequence of multi-view RGB images was captured with 0.02m spatial resolution and 75% overlap. Hyperspectral image was corrected for radiative and geometric distortion while high resolution RGB images were matched to generate maximum dense point clouds. Furtherly, a 5 cm grid digital surface model (DSM) was derived from dense point clouds. Multiple feature reduction methods were compared to identify the efficient method and to explore the significant spectral bands in distinguishing different species. Examined methods including stepwise discriminant analysis (DA), support vector machine (SVM) and minimum noise fraction (MNF) transformation. Subsequently, spectral subsets composed of the first 20 most importance bands extracted by SVM, DA and MNF, and multi-source subsets adding extra DSM to 20 spectrum bands were served as input in maximum likelihood classifier (MLC) and SVM classifier to compare the classification result. Classification results showed that feature reduction methods from best to worst are MNF transformation, DA and SVM. MNF transformation accuracy was even higher than all bands input result. Selected bands frequently laid along the green peak, red edge and near infrared. Additionally, DA found that chlorophyll absorption red band and yellow band were also important for species classification. In terms of 3D data, DSM enhanced the discriminant capacity among low plants, arbor and mangrove. Meanwhile, DSM largely reduced misclassification due to the shadow effect and morphological variation of inter-species. In respect to classifier, nonparametric SVM outperformed than MLC for high dimension and multi-source data in this study. SVM classifier tended to produce higher overall accuracy and reduce scattered patches although it costs more time than MLC. The best result was obtained by combining MNF components and DSM in SVM classifier. This study offered a precision species distribution survey solution for inaccessible wetland area with low cost of time and labour. In addition, findings relevant to the positive effect of DSM as well as spectral feature identification indicated that the utility of UAV-borne hyperspectral and photogrammetry deriving 3D data is promising in further research on wetland species such as bio-parameters modelling and biological invasion monitoring.

Keywords: digital surface model (DSM), feature reduction, hyperspectral, photogrammetric point cloud, species mapping, unmanned aerial vehicle (UAV)

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