Search results for: connected component

Authors: Oluwaseun Simon Adekanle, M'hammed Guisser, Elhassane Abdelmounim, Mohamed Aboulfatah

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In this paper, modeling and control of a grid connected 660KW Doubly-Fed Induction Generator wind turbine is presented. Stator flux orientation is used to realize active-reactive power decoupling to enable independent control of active and reactive power. The recursive Integral Backstepping technique is used to control generator speed to its optimum value and to obtain unity power factor. The controller is combined with High Gain Observer to estimate the mechanical torque of the machine. The most important advantage of this combination of High Gain Observer and the Integral Backstepping controller is the annulation of static error that may occur due to incertitude between the actual value of a parameter and its estimated value by the controller. Simulation results under Matlab/Simulink show the robustness of this control technique in presence of parameter variation.

Keywords: doubly-fed induction generator, field orientation control, high gain observer, integral backstepping control

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Authors: Michael J. Cutler

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This paper presents what musical boundary play can look like when beginning music learners work with professional musicians with an emphasis on composition. Music education can be re-imagined through the lenses of boundary objects and boundary play by engaging non-professional musicians in collaborative sound creation, improvisation and composition along with professional musicians. To the author’s best knowledge, no similar study exists on boundary objects and boundary play in music education. The literature reviewed for this paper explores the epistemological perspectives connected to music education and situates musical boundary play as an alternative approach to the more prevalent paradigms of music education in K-12 settings. A qualitative multiple-case study design was chosen to seek an in-depth understanding of the role of boundary objects and musical boundary play. The constant comparative method was utilized in analyzing and interpreting the data resulting in the development of effective, transferable theory. The study gathered relevant data using audio and video recordings of musical boundary play, artifacts, interviews, and observations. Findings from this study offer insight into the development of a more inclusive music education and yield a pedagogical framework for music education based on musical boundary play. Through the facilitation of musical boundary play, it is possible for music learners to experience musical sound creation, improvisation and composition in the same way an instrumentalist or vocalist would without the acquisition of complex component operations required to play a traditional instrument or sing in a proficient manner.

Keywords: boundary play, boundary objects, music education, music pedagogy, musical boundary play

Procedia PDF Downloads 93

Authors: Rasha S. Kamal, Nehal S. Ahmed, Amal M. Nassar, Nour E. A. Abd El-Sattar

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In the present work, some lube oil antioxidants based on ester of some aromatic thiourea derivative were prepared by two steps: the first step is the reaction of succinyl chloride with ammonium thiocyanate in addition to anthranilic acid as three component system to prepare thiourea derivative (A); the second step is esterification of compound (A) by different alcohol (decyl C₁₀, tetradecyl C₁₄, and octadecyl C₁₈) alcohol. The structures of the prepared compounds were confirmed by infra-red spectroscopy, nuclear magnetic resonance, elemental analysis and determination of the molecular weights. All the prepared compounds were soluble in lube oil. The efficiency of the prepared compounds as antioxidants lube oil additives was investigated and it was found that these prepared compounds give good result as lube oil antioxidant.

Keywords: antioxidant lube oil, three component system, aromatic thiourea derivatives, esterification

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Authors: Ashfaque Hossain Khan, Brian Thomson, Ratan Debnath, Abhishek Motayed, Mulpuri V. Rao

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Though the efforts had been made, the problem of cross-sensitivity for a single metal oxide-based sensor can’t be fully eliminated. In this work, a sensor array has been designed and fabricated comprising of platinum (Pt), copper (Cu), and silver (Ag) decorated TiO2 and ZnO functionalized GaN nanowires using industry-standard top-down fabrication approach. The metal/metal-oxide combinations within the array have been determined from prior molecular simulation study using first principle calculations based on density functional theory (DFT). The gas responses were obtained for both single and mixture of NO2, SO2, ethanol, and H2 in the presence of H2O and O2 gases under UV light at room temperature. Each gas leaves a unique response footprint across the array sensors by which precise discrimination of cross-sensitive gases has been achieved. An unsupervised principal component analysis (PCA) technique has been implemented on the array response. Results indicate that each gas forms a distinct cluster in the score plot for all the target gases and their mixtures, indicating a clear separation among them. In addition, the developed array device consumes very low power because of ultra-violet (UV) assisted sensing as compared to commercially available metal-oxide sensors. The nanowire sensor array, in combination with PCA, is a potential approach for precise real-time gas monitoring applications.

Keywords: cross-sensitivity, gas sensor, principle component analysis (PCA), sensor array

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Authors: Morar (Bumbu) Nicoleta Ileana

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Located in the northeastern part of Romania in a cross-border area, Bucovina region, due to historical events that took place here, is characterized by the cohabitation in the same area of a significant number of ethnic communities, represented in 54% by rural population. In addition to providing the natural, economic history and decision makers, the demographic component is responsible for the region's development trajectory to which it belongs. The influence that people exert on rural development is shown by the values of the different demographic indicator. This study will analyze the demographic indicators obtained against a strong database, emphasizing the indicators that favor the rural development of the region and those that prevent it. The study is useful in defining the rightful directions that rural economic development can focus on, also representing an important tool in developing strategies for the development of rural settlements of Bucovina region.

Keywords: Bucovina, development directions, demographic indicators, rural development

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Authors: Damian Gordon, Paul Doyle, Anna Becevel, Tina Baloh

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The goal of this research is to explore the evolution of the concept of “blended learning” over a twenty-year period, to see whether or not the conceptualization has remained consistent or if it has become either more specific or more general. To achieve this goal, the term “blended learning” (and variations) was searched for in various bibliographical repositories for each year 2003-2022 to locate a highly cited paper that is not behind a paywall, to locate unique definitions that would be freely available to all academics each year. Each of the twenty unique definitions is explored to identify how they categorize both the Classroom Component and the Computer Component of blended learning, as well as identify which discipline each definition originates from and which country it comes from to see if there are any significant geographical variations. Based on this analysis, trends that appear in the definitions are noted, as well as an overall interpretation of the notion of “Blended Learning.”

Keywords: blended learning, definitions of blended learning, e-learning, thematic searches

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Authors: Mehrshad Khosraviani, Faramarz Abbaspour Leyl Abadi

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The fundamental component of the computer network of modern information society will be considered. These networks are connected to the network of the internet generally. Due to the fact that the primary purpose of the Internet is not designed for, in recent decades, none of these networks in many of the attacks has been very important. Today, for the provision of security, different security tools and systems, including intrusion detection systems are used in the network. A common diagnosis system based on artificial immunity, the designer, the Adhasaz Foundation has been evaluated. The idea of using artificial safety methods in the diagnosis of abnormalities in computer networks it has been stimulated in the direction of their specificity, there are safety systems are similar to the common needs of m, that is non-diagnostic. For example, such methods can be used to detect any abnormalities, a variety of attacks, being memory, learning ability, and Khodtnzimi method of artificial immune algorithm pointed out. Diagnosis of the common system of education offered in this paper using only the normal samples is required for network and any additional data about the type of attacks is not. In the proposed system of positive selection and negative selection processes, selection of samples to create a distinction between the colony of normal attack is used. Copa real data collection on the evaluation of ij indicates the proposed system in the false alarm rate is often low compared to other ir methods and the detection rate is in the variations.

Keywords: artificial immune system, abnormality detection, intrusion detection, computer networks

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Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

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The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.

Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model

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Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

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A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

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Authors: Siavash Mirahmadizoghi, Steven Bell, David Simpson

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In this work a new independent component analysis (ICA) based method for noise reduction in evoked potentials is evaluated on for auditory late responses (ALR) captured with a 63-channel electroencephalogram (EEG) from 10 normal-hearing subjects. The performance of the new method is compared with a single channel alternative in terms of signal to noise ratio (SNR), the number of channels with an SNR above an empirically derived statistical critical value and an estimate of the effect of attention on the major components in the ALR waveform. The results show that the multichannel signal processing method can significantly enhance the quality of the ALR signal and also detect the effect of the attention on the ALR better than the single channel alternative.

Keywords: auditory late response (ALR), attention, EEG, independent component analysis (ICA), multichannel signal processing

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Authors: Kirill Filianin, Satu-Pia Reinikainen, Tuomo Sainio

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Frequent measurements of product steam quality create a data overload that becomes more and more difficult to handle. In the current study, plant history data with multiple variables was successfully treated by principal component analysis to detect abnormal process behavior, particularly, in copper solvent extraction. The multivariate model is based on the concentration levels of main process metals recorded by the industrial on-stream x-ray fluorescence analyzer. After mean-centering and normalization of concentration data set, two-dimensional multivariate model under principal component analysis algorithm was constructed. Normal operating conditions were defined through control limits that were assigned to squared score values on x-axis and to residual values on y-axis. 80 percent of the data set were taken as the training set and the multivariate model was tested with the remaining 20 percent of data. Model testing showed successful application of control limits to detect abnormal behavior of copper solvent extraction process as early warnings. Compared to the conventional techniques of analyzing one variable at a time, the proposed model allows to detect on-line a process failure using information from all process variables simultaneously. Complex industrial equipment combined with advanced mathematical tools may be used for on-line monitoring both of process streams’ composition and final product quality. Defining normal operating conditions of the process supports reliable decision making in a process control room. Thus, industrial x-ray fluorescence analyzers equipped with integrated data processing toolbox allows more flexibility in copper plant operation. The additional multivariate process control and monitoring procedures are recommended to apply separately for the major components and for the impurities. Principal component analysis may be utilized not only in control of major elements’ content in process streams, but also for continuous monitoring of plant feed. The proposed approach has a potential in on-line instrumentation providing fast, robust and cheap application with automation abilities.

Keywords: abnormal process behavior, failure detection, principal component analysis, solvent extraction

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Authors: Attila Vámosi, Tamás Mankovits, Dávid Huri, Imre Kocsis, Tamás Szabó

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Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. Rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. The shape optimization problem of rubber parts led to the study of FEM based calculation processes. This type of problems was posed and investigated by several authors. In this paper the time demand of certain calculation methods are studied and the possibilities of time reduction is presented.

Keywords: rubber bumper, data acquisition, finite element analysis, support vector regression

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Authors: Agnieszka Sobczak-Kupiec, Dagmara Malina, Klaudia Pluta, Wioletta Florkiewicz, Bozena Tyliszczak

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Introduction: Request for compound of phosphorus grows continuously, thus, it is searched for alternative sources of this element. One of these sources could be by-products from meat industry which contain prominent quantity of phosphorus compounds. Hydroxyapatite, which is natural component of animal and human bones, is leading material applied in bone surgery and also in stomatology. This is material, which is biocompatible, bioactive and osteoinductive. Methodology: Hydroxyapatite preparation: As a raw material was applied deproteinized and defatted bone pulp called bone sludge, which was formed as waste in deproteinization process of bones, in which a protein hydrolysate was the main product. Hydroxyapatite was received in calcining process in chamber kiln with electric heating in air atmosphere in two stages. In the first stage, material was calcining in temperature 600°C within 3 hours. In the next stage unified material was calcining in three different temperatures (750°C, 850°C and 950°C) keeping material in maximum temperature within 3.0 hours. Bone sludge: Bone sludge was formed as waste in deproteinization process of bones, in which a protein hydrolysate was the main product. Pork bones coming from the partition of meat were used as a raw material for the production of the protein hydrolysate. After disintegration, a mixture of bone pulp and water with a small amount of lactic acid was boiled at temperature 130-135°C and under pressure4 bar. After 3-3.5 hours boiled-out bones were separated on a sieve, and the solution of protein-fat hydrolysate got into a decanter, where bone sludge was separated from it. Results of the study: The phase composition was analyzed by roentgenographic method. Hydroxyapatite was the only crystalline phase observed in all the calcining products. XRD investigation was shown that crystallization degree of hydroxyapatite was increased with calcining temperature. Conclusion: The researches were shown that phosphorus content is around 12%, whereas, calcium content amounts to 28% on average. The conducted researches on bone-waste calcining at the temperatures of 750-950°C confirmed that thermal utilization of deproteinized bone-waste was possible. X-ray investigations were confirmed that hydroxyapatite is the main component of calcining products, and also XRD investigation was shown that crystallization degree of hydroxyapatite was increased with calcining temperature. Contents of calcium and phosphorus were distinctly increased with calcining temperature, whereas contents of phosphorus soluble in acids were decreased. It could be connected with higher crystallization degree of material received in higher temperatures and its stable structure. Acknowledgements: “The authors would like to thank the The National Centre for Research and Development (Grant no: LIDER//037/481/L-5/13/NCBR/2014) for providing financial support to this project”.

Keywords: bone by-products, bone sludge, calcination, hydroxyapatite

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Authors: Kamran Siddique, Hiroyuki Asada, Yoshifumi Ogami

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Micro gas turbine (MGT) nowadays has a wide variety of applications from drones to hybrid electric vehicles. As microfabrication technology getting better, the size of MGT is getting smaller. Overall performance of MGT is dependent on the individual components. Each component’s performance is dependent and interrelated with another component. Therefore, careful consideration needs to be given to each and every individual component of MGT. In this study, the focus is on improving the performance of the compressor in order to improve the overall performance of MGT. Computational Fluid Dynamics (CFD) is being performed using the software FLUENT to analyze the design of a micro compressor. Operating parameters like mass flow rate and RPM, and design parameters like inner blade angle (IBA), outer blade angle (OBA), blade thickness and number of blades are varied to study its effect on the performance of the compressor. Pressure ratio is used as a tool to measure the performance of the compressor. Higher the pressure ratio, better the design is. In the study, target mass flow rate is 0.2 g/s and RPM to be less than or equal to 900,000. So far, a pressure ratio of above 3 has been achieved at 0.2 g/s mass flow rate with 5 rotor blades, 0.36 mm blade thickness, 94.25 degrees OBA and 10.46 degrees IBA. The design in this study differs from a regular centrifugal compressor used in conventional gas turbines such that compressor is designed keeping in mind ease of manufacturability. So, this study proposes a compressor design which has a good pressure ratio, and at the same time, it is easy to manufacture using current microfabrication technologies.

Keywords: computational fluid dynamics, FLUENT microfabrication, RPM

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Authors: Abdelhak-Djamel Seriai, Selim Kebir, Allaoua Chaoui

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During the last decades, object oriented program- ming has been massively used to build large-scale systems. However, evolution and maintenance of such systems become a laborious task because of the lack of object oriented programming to offer a precise view of the functional building blocks of the system. This lack is caused by the fine granularity of classes and objects. In this paper, we use a post object-oriented technology namely software components, to propose an approach based on the identification of the functional building blocks of an object oriented system by analyzing its source code. These functional blocks are specified as software components and the result is a multi-layer component based software architecture.

Keywords: software comprehension, software component, object oriented, software architecture, reverse engineering

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Authors: Anjushi Verma, Tirthankar Gayen

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Although, reliability is an important attribute of quality, especially for mission critical systems, yet, there does not exist any versatile model even today for the reliability assessment of component-based software. The existing Black Box models are found to make various assumptions which may not always be realistic and may be quite contrary to the actual behaviour of software. They focus on observing the manner in which the system behaves without considering the structure of the system, the components composing the system, their interconnections, dependencies, usage frequencies, etc.As a result, the entropy (uncertainty) in assessment using these models is much high.Though, there are some models based on operation profile yet sometimes it becomes extremely difficult to obtain the exact operation profile concerned with a given operation. This paper discusses the drawbacks, deficiencies and limitations of Black Box approaches from the perspective of various authors and finally proposes a conceptual model for the reliability assessment of software.

Keywords: black box, faults, failure, software reliability

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Authors: Krasimir Ivanov, Elitsa Kolentsova, Dimitar Dimitrov

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The development of active and stable catalysts without noble metals for low temperature oxidation of exhaust gases remains a significant challenge. The purpose of this study is to determine the influence of the preparation method on the catalytic activity of the supported copper-manganese mixed oxides in terms of VOCs oxidation. The catalysts were prepared by impregnation of γ-Al2O3 with copper and manganese nitrates and acetates and the possibilities for CO, CH3OH and dimethyl ether (DME) oxidation were evaluated using continuous flow equipment with a four-channel isothermal stainless steel reactor. Effect of the support, Cu/Mn mole ratio, heat treatment of the precursor and active component loading were investigated. Highly active alumina supported Cu-Mn catalysts for CO and VOCs oxidation were synthesized. The effect of preparation conditions on the activity behavior of the catalysts was discussed. The synergetic interaction between copper and manganese species increases the activity for complete oxidation over mixed catalysts. Type of support, calcination temperature and active component loading along with catalyst composition are important factors, determining catalytic activity. Cu/Mn molar ratio of 1:5, heat treatment at 450oC and 20 % active component loading are the best compromise for production of active catalyst for simultaneous combustion of CO, CH3OH and DME.

Keywords: copper-manganese catalysts, CO, VOCs oxidation, exhaust gases

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Authors: Vaishakh Medikeri

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Lightning, the marvelous, spectacular and the awesome truth of nature is one of the greatest energy sources left unharnessed since ages. A single lightning bolt of lightning contains energy of about 15 billion joules. This huge amount of energy cannot be harnessed completely but partially. This paper proposes to harness the energy from lightning strikes. Throughout the globe the frequency of lightning is 40-50 flashes per second, totally 1.4 billion flashes per year; all of these flashes carrying an average energy of about 15 billion joules each. When a lightning bolt strikes the ground, tremendous amounts of energy is transferred to earth which propagates in the form of concentric circular energy waves. These waves have a frequency of about 7.83Hz. Harvesting the lightning bolt directly seems impossible, but harvesting the energy waves produced by the lightning is pretty easier. This can be done using a tricoil energy harnesser which is a new device which I have invented. We know that lightning bolt seeks the path which has minimum resistance down to the earth. For this we can make a lightning rod about 100 meters high. Now the lightning rod is attached to the tricoil energy harnesser. The tricoil energy harnesser contains three coils whose centers are collinear and all the coils are parallel to the ground. The first coil has one of its ends connected to the lightning rod and the other end grounded. There is a secondary coil wound on the first coil with one of its end grounded and the other end pointing to the ground and left unconnected and placed a little bit above the ground so that this end of the coil produces more intense currents, hence producing intense energy waves. The first coil produces very high magnetic fields and induces them in the second and third coils. Along with the magnetic fields induced by the first coil, the energy waves which are currents also flow through the second and the third coils. The second and the third coils are connected to a generator which in turn is connected to a capacitor which stores the electrical energy. The first coil is placed in the middle of the second and the third coil. The stored energy can be used for transmission of electricity. This new technique of harnessing the lightning strikes would be most efficient in places with more probability of the lightning strikes. Since we are using a lightning rod sufficiently long, the probability of cloud to ground strikes is increased. If the proposed apparatus is implemented, it would be a great source of pure and clean energy.

Keywords: generator, lightning rod, tricoil energy harnesser, harvesting energy

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Authors: Safia Bashir, Zulfiqar Memon

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During the last decade, renewable energy sources in particular solar photovoltaic (PV) has gained increased attention. Therefore, various PV converters topologies have emerged. Among this topology, the modular multilevel converter (MMC) is considered as one of the most promising topologies for the grid-connected PV system due to its modularity and transformerless features. When it comes to the safe operation of MMC, the balancing of the Submodules Voltages (SMs) plays a critical role. This paper proposes a balancing approach based on space vector PWM (SVPWM). Unlike the existing techniques, this method generates the switching vectors for the MMC by using only one SVPWM for the upper arm. The lower arm switching vectors are obtained by finding the complement of the upper arm switching vectors. The use of one SVPWM not only simplifies the calculation but also helped in reducing the circulating current in the MMC. The proposed method is varied through simulation using Matlab/Simulink and compared with other available modulation methods. The results validate the ability of the suggested method in balancing the SMs capacitors voltages and reducing the circulating current which will help in reducing the power loss of the PV system.

Keywords: capacitor voltage balancing, circulating current, modular multilevel converter, PV system

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Authors: Venkata Venugopal Rao Gudlur

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The Proposed Policies referred to as “SOP”, on the Internet of Things (IoT) based Forensic Investigation into Process Management is the latest revolution to save time and quick solution for investigators. The forensic investigation process has been developed over many years from time to time it has been given the required information with no policies in investigation processes. This research reveals that the current IoT based forensic investigation into Process Management based is more connected to devices which is the latest revolution and policies. All future development in real-time information on gathering monitoring is evolved with smart sensor-based technologies connected directly to IoT. This paper present conceptual framework on process management. The smart devices are leading the way in terms of automated forensic models and frameworks established by different scholars. These models and frameworks were mostly focused on offering a roadmap for performing forensic operations with no policies in place. These initiatives would bring a tremendous benefit to process management and IoT forensic investigators proposing policies. The forensic investigation process may enhance more security and reduced data losses and vulnerabilities.

Keywords: Internet of Things, Process Management, Forensic Investigation, M2M Framework

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Authors: Nguyen The Hoang Anh, Tran Huy Hoang, Vu Tat Thang, T. T. Quyen Bui

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Mental state classification is an important step for realizing a control system based on electroencephalography (EEG) signals which could benefit a lot of paralyzed people including the locked-in or Amyotrophic Lateral Sclerosis. Considering that EEG signals are nonstationary and often contaminated by various types of artifacts, classifying thoughts into correct mental states is not a trivial problem. In this work, our contribution is that we present and realize a novel model which integrates different techniques: Independent component analysis (ICA), relative wavelet energy, and support vector machine (SVM) for the same task. We applied our model to classify thoughts in two types of experiment whether with two or three mental states. The experimental results show that the presented model outperforms other models using Artificial Neural Network, K-Nearest Neighbors, etc.

Keywords: EEG, ICA, SVM, wavelet

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

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Authors: Borhan Marzougui

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Road and Transport Authority (RTA) is moving ahead with the implementation of the leader’s vision in exploring all avenues that may bring better security and safety services to the community. Smart transport means using smart technologies such as IoT (Internet of Things). This technology continues to affirm its important role in the context of Information and Transportation Systems. In fact, IoT is a network of Internet-connected objects able to collect and exchange different data using embedded sensors. With the growth of IoT, Distributed Denial of Service (DDoS) attacks is also growing exponentially. DDoS attacks are the major and a real threat to various transportation services. Currently, the defense mechanisms are mainly passive in nature, and there is a need to develop a smart technique to handle them. In fact, new IoT devices are being used into a botnet for DDoS attackers to accumulate for attacker purposes. The aim of this paper is to provide a relevant understanding of dangerous types of DDoS attack related to IoT and to provide valuable guidance for the future IoT security method. Our methodology is based on development of the distributed algorithm. This algorithm manipulates dedicated intelligent and cooperative agents to prevent and to mitigate DDOS attacks. The proposed technique ensure a preventive action when a malicious packets start to be distributed through the connected node (Network of IoT devices). In addition, the devices such as camera and radio frequency identification (RFID) are connected within the secured network, and the data generated by it are analyzed in real time by intelligent and cooperative agents. The proposed security system is based on a multi-agent system. The obtained result has shown a significant reduction of a number of infected devices and enhanced the capabilities of different security dispositives.

Keywords: IoT, DDoS, attacks, botnet, security, agents

Procedia PDF Downloads 117

Authors: Alisa Rekunova

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According to the theory of word meaning structure developed by Lev Vygotsky (and later modified by Aaro Toomela), there are several levels of thought: sensory-based concepts, situation concepts, logical concepts, and structural-systemic concepts. There are differences between people who have relatively easy access to logical thought compared to those who mostly tend to think in everyday concepts. Religious beliefs are connected with unprovable concepts (Christian Jesus’s ascension or Pagan energy) that cannot be non-controversially related to scientific concepts. However, many scientists in the research are believers of some kinds. Religious views can be different: there are believers, non-believers (atheists), and undecided (we can call them agnostics). Some of the respondents say that scientific or professional and religious spheres do not overlap. Therefore, we can assume they do not see any conflict. Some of them, on the contrary, hesitate to answer and we can conclude they see the conflicts, but they do not want (or do not believe they are able to) to solve it. Finally, the third category of respondents says that religious beliefs and scientific concepts cannot coexist in the human mind. It can be expected that the third category of respondents should have higher education (or even work in the scientific field) but many scientists in the research answer that religious and scientific spheres do not overlap. Therefore, there are other things besides the level of education that is connected with resolving conflicts.

Keywords: conflicts in thinking, cultural-historical psychology, heterogeneity of thinking, religious thinking

Procedia PDF Downloads 118

Authors: Peyman Sheikholharam Mashhadi

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Difficulties in analyzing real world images in classical image processing and machine vision framework have motivated researchers towards considering the biology-based vision. It is a common belief that mammalian visual cortex has been adapted to the statistics of the real world images through the evolution process. There are two well-known successful models of mammalian visual cortical cells: Independent Component Analysis (ICA) and Independent Subspace Analysis (ISA). In this paper, we statistically analyze the dependencies which remain in the components after applying these models to the natural images. Also, we investigate the response of feature detectors to gratings with various parameters in order to find optimal parameters of the feature detectors. Finally, the selectiveness of feature detectors to phase, in both models is considered.

Keywords: statistics, independent component analysis, independent subspace analysis, phase, natural images

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Authors: Ricardo Bragança, Tom Vinaimont

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This paper discusses the introduction of processes of self-determined learning (heutagogy) into a graduate course on financial modeling, using elements of entangled pedagogy and Biggs’ constructive alignment. To encourage learners to take control of their own learning journey and develop critical thinking and problem-solving skills, each session in the course receives tailor-made media-enhanced pedagogical assets. The design of those assets specifically supports entangled pedagogy, which opposes technological or pedagogical determinism in support of the collaborative integration of pedagogy and technology. Media assets for each of the ten sessions in this course consist of three components. The first component in this three-pronged approach is a game-cut-like cinematographic representation that introduces the context of the session. The second component represents a character from an open-source-styled community that encourages self-determined learning. The third component consists of a character, which refers to the in-person instructor and also aligns learning outcomes and assessment tasks, using Biggs’ constructive alignment, to the cinematographic and open-source-styled component. In essence, the course's metamorphosis helps students apply the concepts they've studied to actual financial modeling issues. The audio-visual media assets create a storyline throughout the course based on gamified and real-world applications, thus encouraging student engagement and interaction. The structured entanglement of pedagogy and technology also guides the instructor in the design of the in-class interactions and directs the focus on outcomes and assessments. The transformation process of this graduate course in financial modeling led to an institutional teaching award in 2021. The transformation of this course may be used as a model for other courses and programs in many disciplines to help with intended learning outcomes integration, constructive alignment, and Assurance of Learning.

Keywords: innovative education, active learning, entangled pedagogy, heutagogy, constructive alignment, project based learning, financial modeling, graduate business education

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Authors: Kourosh Modarresi

Abstract:

The abundance of media channels and devices has given users a variety of options to extract, discover, and explore information in the digital world. Since, often, there is a long and complicated path that a typical user may venture before taking any (significant) action (such as purchasing goods and services), it is critical to know how each node (media channel) in the path of user has contributed to the final action. In this work, the significance of each media channel is computed using statistical analysis and machine learning techniques. More specifically, “Regularized Singular Value Decomposition”, and “Sparse Principal Component” has been used to compute the significance of each channel toward the final action. The results of this work are a considerable improvement compared to the present approaches.

Keywords: multimedia attribution, sparse principal component, regularization, singular value decomposition, feature significance, machine learning, linear systems, variable shrinkage

Procedia PDF Downloads 280

Authors: Bazilah Ismail, Muhammad Mat Naain, Ibrahim Alhamrouni, Lilik Jamilatul Awalin, Fadi Albatsh, Mohd Fairuz Abdul Hamid

Abstract:

Rapid depletion and prices of the conventional energy sources have stimulated the development of the renewable energy source (RES). Due to the unpredicted and intermittent nature of RES, the hybrid renewable energy system (HRES) is the best solution to complement the nature of the respective sources, and the combination of the wind and solar energy is rapidly gaining popularity. The significant challenges on the operation and planning of the grid system with a high HRES penetration has become an important subject since the location of HRES plant give impact towards the existing system. This paper aims to propose the location of the grid connected Wind-PV hybrid plant (WPHP) based on load flow and voltage stability indices study. Several case studies are carried out using IEEE 14 bus system, and the system is modeled and tested in DigSILENT PowerFactory.

Keywords: hybrid renewable energy system, wind farm, photovoltaic system, voltage stability and load flow

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Authors: Goran Sporiš, Dinko Vuleta, Stefan Lovro

Abstract:

The purpose of the present study was to determine the associations between health-related quality of life (HRQOL) and physical activity (PA) in different domains. In this cross-sectional study, participants were 169 Croatian police officers (mean age 35.14±8.95 yrs, mean height 180.93±7.53 cm, mean weight 88.39±14.05 kg, mean body-mass index 26.90±3.39 kg/m2). The dependent variables were two general domains extracted from the HRQOL questionnaire: (1) physical component scale (PCS) and (2) mental component scale (MCS). The independent variables were job-related, transport, domestic and leisure-time PA, along with other factors: age, body-mass index, smoking status, psychological distress, socioeconomic status and time spent in sedentary behaviour. The associations between dependent and independent variables were analyzed by using multiple regression analysis. Significance was set up at p < 0.05. PCS was positively associated with leisure-time PA (β 0.28, p < 0.001) and socioeconomic status (SES) (β 0.16, p=0.005), but inversely associated with job-related PA (β -0.15, p=0.012), domestic-time PA (β -0.14, p=0.014), age (β -0.12, p=0.050), psychological distress (β -0.43, p<0.001) and sedentary behaviour (β -0.15, p=0.009). MCS was positively associated with leisure-time PA (β 0.19, p=0.013) and SES (β 0.20, p=0.002), while inversely associated with age (β -0.23, p=0.001), psychological distress (β -0.27, p<0.001) and sedentary behaviour (β -0.22, p=0.001). Our results added new information about the associations between domain-specific PA and both physical and mental component scale in police officers. Future studies should deal with the same associations in other stressful occupations.

Keywords: health, fitness, police force, relations

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Authors: Saad Roustom, Hajo Ribberink

Abstract:

In most cities in the world, traffic has increased strongly over the last decades, causing high levels of congestion and deteriorating inner-city air quality. This study analyzes the impact of connected and automated vehicles (CAVs) on traffic performance and greenhouse gas (GHG) emissions under different CAV penetration rates in mixed fleet environments of CAVs and driver-operated vehicles (DOVs) and under three different traffic demand levels. Utilizing meso-scale traffic simulations of the City of Ottawa, Canada, the research evaluates the traffic performance of three distinct CAV driving behaviors—Cautious, Normal, and Aggressive—at penetration rates of 25%, 50%, 75%, and 100%, across three different traffic demand levels. The study employs advanced correlation models to estimate GHG emissions. The results reveal that Aggressive and Normal CAVs generally reduce traffic congestion and GHG emissions, with their benefits being more pronounced at higher penetration rates (50% to 100%) and elevated traffic demand levels. On the other hand, Cautious CAVs exhibit an increase in both traffic congestion and GHG emissions. However, results also show deteriorated traffic flow conditions when introducing 25% penetration rates of any type of CAVs. Aggressive CAVs outperform all other driving at improving traffic flow conditions and reducing GHG emissions. The findings of this study highlight the crucial role CAVs can play in enhancing urban traffic performance and mitigating the adverse impact of transportation on the environment. This research advocates for the adoption of effective CAV-related policies by regulatory bodies to optimize traffic flow and reduce GHG emissions. By providing insights into the impact of CAVs, this study aims to inform strategic decision-making and stimulate the development of sustainable urban mobility solutions.

Keywords: connected and automated vehicles, congestion, GHG emissions, mixed fleet environment, traffic performance, traffic simulations

Procedia PDF Downloads 46