Search results for: current vector

Authors: Anil S. Khopkar, Kartik S. Pandya

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Overvoltage in power systems is a phenomenon that cannot be avoided. However, it can be controlled to a certain extent. Power system equipment is to be protected against overvoltage to avoid system failure. Metal Oxide Surge Arresters (MOSA) are connected to the system for the protection of the power system against overvoltages. The MOSA will behave as an insulator under normal working conditions, where it offers a conductive path under voltage conditions. MOSA consists of zinc oxide elements (ZnO Blocks), which have non-linear V-I characteristics. ZnO blocks are connected in series and fitted in ceramic or polymer housing. This degrades due to the aging effect under continuous operation. Degradation of zinc oxide elements increases the leakage current flowing from the surge arresters. This Increased leakage current results in the increased temperature of the surge arrester, which further decreases the resistance of zinc oxide elements. As a result, leakage current increases, which again increases the temperature of a MOSA. This creates thermal runaway conditions for MOSA. Once it reaches the thermal runaway condition, it cannot return to normal working conditions. This condition is a primary cause of premature failure of surge arresters, as MOSA constitutes a core protective device for electrical power systems against transients. It contributes significantly to the reliable operation of the power system network. Hence, the condition monitoring of surge arresters should be done at periodic intervals. Online and Offline condition monitoring techniques are available for surge arresters. Offline condition monitoring techniques are not very popular as they require removing surge arresters from the system, which requires system shutdown. Hence, online condition monitoring techniques are very popular. This paper presents the evaluation technique for the surge arrester condition based on the leakage current analysis. Maximum amplitude of total leakage current (IT), Maximum amplitude of fundamental resistive leakage current (IR) and maximum amplitude of third harmonic resistive leakage current (I3rd) have been analyzed as indicators for surge arrester condition monitoring.

Keywords: metal oxide surge arrester (MOSA), over voltage, total leakage current, resistive leakage current

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Authors: Ming-Yue Zhai

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Due to the multipath and pulse noise nature, power line communications(PLC) channel can be modelled as a memory one with the finite states Markov model(FSMC). As the most important parameter modelling a Markov channel,the memory order in an FSMC is not solved in PLC systems yet. In the paper, the mutual information is used as a measure of the dependence between the different symbols, treated as the received SNA or amplitude of the current channel symbol or that of previous symbols. The joint distribution probabilities of the envelopes in PLC systems are computed based on the multi-path channel model, which is commonly used in PLC. we confirm that given the information of the symbol immediately preceding the current one, any other previous symbol is independent of the current one in PLC systems, which means the PLC channels is a Markov chain with the first-order. The field test is also performed to model the received OFDM signals with the help of AR model. The results show that the first-order AR model is enough to model the fading channel in PLC systems, which means the amount of uncertainty remaining in the current symbol should be negligible, given the information corresponding to the immediately preceding one.

Keywords: power line communication, channel model, markovian, information theory, first-order

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Authors: Saeed Yazdani, Sima Mohamadi Amidabadi, Amir Mohamadi Nejsd, Farahnaz Nekoofar

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As a result of uncertainty and doubts about the quantity of agricultural products, greater significance has been attached to risk management in the agricultural sector. Normally, farmers seek to minimize risks, and crop diversity has always been a means to reduce risk. The study at hand seeks to explore the long-term impact of crop diversity on income risk reduction. The timeframe of the study is 1998 to 2018. Initially, the Herfindahl index was used to estimate crop diversity in different periods, and next, the Hodrick-Prescott filter was applied to estimate income risk both in nominal and real terms. Finally, using the vector error correction model (VECM), the long-term impact of crop diversity on two modes of risk for the farmer's income has been estimated. Given the long-term pattern’s results, it is evident that in the long run, crop diversity can reduce income fluctuations in two nominal and real terms. Moreover, results showed that in case the fluctuation shock affects the agricultural income in the short run, to balance out the shock in nominal and real terms, 4 and 3 cycles are needed, respectively. In other words, in each cycle, 25% and 33% of the shock impact can be removed, respectively. Thus, as the results of the error correction coefficient showed, policies need to be put in place to prevent income shocks. In case of a shock, they need to be balanced out in a four-year period, taking inflation into account, and in a three-year period irrespective of the inflation, and reparative policies such as insurance services should be developed.

Keywords: risk, long-term model, Herfindahl index, time series model, vector error correction model

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Authors: Mahmoud Hassanin, Roshan Thawale, Kiran Yelamati

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Background: During current practice, intraoperative regular endotracheal cuff pressure monitoring is not routine, despite the significant number of clinicians interested in checking it after intubation to ensure a good seal and adequate ventilation. Aims and objectives: to highlight that the current practice has no guidance related to regular intra-operative monitoring of the endotracheal tube cuff pressure, which can improve patient safety and post-operative experience. Methods: local department survey was done targeting anaesthetists' current practice, measuring their knowledge and problem awareness to improve patient satisfaction and change the current approach. Results: The participants were not using the manometer, despite their interest in ensuring that the cuff pressure was high enough and there was a proper seal. More than 50% of the participant don't know the ideal range of the endotracheal tube cuff pressure range, and 32% don't know whether it is available or not in the theatre. Despite the previous finding, 100% of the participants used different methods to ensure adequate cuff pressure. The collected data revealed that at least 26% of the participant confirmed that they had seen patients having post-intubation complications. Conclusion: There is an increasing importance placed on quality assurance. Clinical practice varies widely among practitioners, with the only consistency being the omission of cuff manometers during routine intra-operative management, despite their proven benefit and efficacy. Encourage the anaesthetists and ODPs to use cuff pressure manometers. The availability of portable pressure manometers can help to maintain safe cuff pressures in patients requiring endotracheal intubation.

Keywords: endotracheal cuff pressure, intra-operative monitoring, current practice, patient satisfaction

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Authors: Maryam Mehrabpour

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The sports industry has recognized its impact on the natural environment and has taken steps to address relevant environmental issues. Two key initiatives have emerged: reducing the ecological footprint of sports activities and utilizing sports as a platform to raise environmental awareness. This article provides an overview of the scholarly research conducted on environmental sustainability in sports. It highlights various environmental programs implemented by sports organizations worldwide and examines the current state of environmental efforts in the field. The research utilized semi-structured interviews, website analysis, and published documents as data sources, and qualitative analysis methods were employed to identify themes representing the current status of environmental efforts in sports.

Keywords: environmental sustainability, sport industry, ecological footprint, environmental awareness, environmental programs

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Authors: S. Nazhan, Hassan K. Al-Musawi, Khalid A. Humood

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This paper reports on an experimental investigation into the influence of current modulation on the properties of a vertical-cavity surface-emitting laser (VCSEL) with a direct square wave modulation. The optical output power response, as a function of the pumping current, modulation frequency, and amplitude, is measured for an 850 nm VCSEL. We demonstrate that modulation frequency and amplitude play important roles in reducing the VCSEL’s power consumption for optical generation. Indeed, even when the biasing current is below the static threshold, the VCSEL emits optical power under the square wave modulation. The power consumed by the device to generate light is significantly reduced to > 50%, which is below the threshold current, in response to both the modulation frequency and amplitude. An operating VCSEL device at low power is very desirable for less thermal effects, which are essential for a high-speed modulation bandwidth.

Keywords: vertical-cavity surface-emitting lasers, VCSELs, optical power generation, power consumption, square wave modulation

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Authors: Rachel Y. Zhang, Christopher K. Anderson

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A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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Authors: Sara Kamalisiahroudi, Jun Huang, Zhe Li, Jianbo Zhang

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Two types of commercial cylindrical lithium ion batteries (Panasonic 3.4 Ah NCR-18650B and Samsung 2.9 Ah INR-18650), were investigated experimentally. The capacities of these samples were individually measured using constant current-constant voltage (CC-CV) method at different ambient temperatures (-10 ℃, 0 ℃, 25 ℃). Their internal resistance was determined by electrochemical impedance spectroscopy (EIS) and pulse discharge methods. The cells with different configurations of parallel connection NCR-NCR, INR-INR and NCR-INR were charged/discharged at the aforementioned ambient temperatures. The results showed that the difference of internal resistance between cells much more evident at low temperatures. Furthermore, the parallel connection of NCR-NCR exhibits the most uniform temperature distribution in cells at -10 ℃, this feature is quite favorable for the safety of the battery pack.

Keywords: batteries in parallel connection, internal resistance, low temperature, temperature difference, current distribution

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Authors: Matthew Holland, Jason Everett, Martin Cox, Iain Suthers

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High spatial-resolution distribution of planktivorous reef fish can reveal behavioural adaptations to optimise the balance between feeding success and predator avoidance. We used a multi-beam echosounder to record bathymetry and the three-dimensional distribution of fish schools associated with natural and artificial reefs. We utilised generalised linear models to assess the distribution, orientation, and aggregation of fish schools relative to the structure, vertical relief, and currents. At artificial reefs, fish schooled more closely to the structure and demonstrated a preference for the windward side, particularly when exposed to strong currents. Similarly, at natural reefs fish demonstrated a preference for windward aspects of bathymetry, particularly when associated with high vertical relief. Our findings suggest that under conditions with stronger current velocity, fish can exercise their preference to remain close to structure for predator avoidance, while still receiving an adequate supply of zooplankton delivered by the current. Similarly, when current velocity is low, fish tend to disperse for better access to zooplankton. As artificial reefs are generally deployed with the goal of creating productivity rather than simply attracting fish from elsewhere, we advise that future artificial reefs be designed as semi-linear arrays perpendicular to the prevailing current, with multiple tall towers. This will facilitate the conversion of dispersed zooplankton into energy for higher trophic levels, enhancing reef productivity and fisheries.

Keywords: artificial reef, current, forage fish, multi-beam, planktivorous fish, reef fish, schooling

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Authors: Paiboon Chuwatthanakij

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Each of the countries around the world has different ways of management and many of them depend on people to administrate their country. Thailand, for example, empowers the sovereignty of Thai people under constitution; however, our Thai voting system is not able to flow fast enough under the current Political management system. The sovereignty of Thai people is addressing this problem through representatives during current elections, in order to set a new policy for the countries ideology to change in the House and the Cabinet. This is particularly important in a democracy to be developed under our current political institution. The Organic Act on Political Parties 2007 is the establishment we have today that is causing confrontations within the establishment. There are many political parties that will soon be abolished. Many political parties have already been subsidized. This research study is to analyze the legal problems with the political party establishment under the Organic Act on Political Parties 2007. This will focus on the freedom of each political establishment compared to an effective political operation. Textbooks and academic papers will be referenced from studies home and abroad. The study revealed that Organic Act on Political Parties 2007 has strict provisions on the political structure over the number of members and the number of branches involved within political parties system. Such operations shall be completed within one year; but under the existing laws the small parties are not able to participate with the bigger parties. The cities are capable of fulfilling small political party requirements but fail to become coalesced because the current laws won't allow them to be united as one. It is important to allow all independent political parties to join our current political structure. Board members can’t help the smaller parties to become a large organization under the existing Thai laws. Creating a new establishment that functions efficiently throughout all branches would be one solution to these legal problems between all political parties. With this new operation, individual political parties can participate with the bigger parties during elections. Until current political institutions change their system to accommodate public opinion, these current Thai laws will continue to be a problem with all political parties in Thailand.

Keywords: coalesced, political party, sovereignty, elections

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Authors: Sun-Ki Hong, Ki-Seok Kim, Yong-Ho Jo

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Lots of motors have been being used in industry. Therefore many researchers have studied about the failure diagnosis of motors. In this paper, the effect of measuring environment for diagnosis of gear fault connected to a motor shaft is studied. The fault diagnosis is executed through the comparison of normal gear and abnormal gear. The measured FFT data are compared with the normal data and analyzed for q-axis current, noise and vibration. For bad and good environment, the diagnosis results are compared. From these, it is shown that the bad measuring environment may not be able to detect exactly the motor gear fault. Therefore it is emphasized that the measuring environment should be carefully prepared.

Keywords: motor fault, diagnosis, FFT, vibration, noise, q-axis current, measuring environment

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Authors: Teoman Ozer, Ozlem Orhan

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This study deals with symmetry group properties and conservation laws of partial differential equations. We give a geometrical interpretation of notion of μ-prolongations of vector fields and of the related concept of μ-symmetry for partial differential equations. We show that these are in providing symmetry reduction of partial differential equations and systems and invariant solutions.

Keywords: λ-symmetry, μ-symmetry, classification, invariant solution

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Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov

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For optimal unbiased filter as mean-square and in the case of functioning anomalous noises in the observation memory channel, we have proved insensitivity of filter to inaccurate knowledge of the anomalous noise intensity matrix and its equivalence to truncated filter plotted only by non anomalous components of an observation vector.

Keywords: mathematical expectation, filtration, anomalous noise, memory

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Authors: Meltem Anafarta Şendağ, Funda Kutlu

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Attachment theory has some major postulates that direct attention of psychologists from many different domains. First, the theory suggests that attachment is a lifetime process. This means that every human being from cradle to grave needs someone stronger to depend on in times of stress. Second, the attachment is a dynamic process and as one goes through developmental stages it is being transferred from one figure to another (friends, romantic partners). Third, the quality of attachment relationships later in time directly affected by the earliest attachment relationship established between the mother and the infant. Depending on these postulates, attachment literature focuses mostly on mother – child attachment during childhood and romantic relationship during adulthood. However, although romantic partners are important attachment figures in adults’ life, parents are not dropped out from the attachment hierarchy but they keep being important attachment figures. Despite the fact that parents could still be an important figure in adults’ life, adult – parent attachment is overlooked in the literature. Accordingly, this study focuses on adult daughters’ current attachment to their old mothers in relation with early parental bonding and current attachment to husbands. Participants of the study were 383 adult women (Average age = 40, ranging between 23 and 70) whose mothers were still alive and who were married at the time of the study. Participants were completed Adult Attachment Scale, Parental Bonding Instrument, and Experiences in Close Relationship – II together with demographic questionnaire. Results revealed that daughters’ attachment to their mothers weakens as they get older, have more children, and have longer marriages. Stronger attachment to mothers was found positively correlated with current satisfaction with the relationship, perception of maternal care before the age of 12 and negatively correlated with perception of controlling behavior before the age 12. Considering the relationship between current parental attachment and romantic attachment, it was found that as the current attachment to mother strengthens attachment avoidance towards husband decreases. Results revealed that although attachment between the adult daughters and old mothers weakens, the relationship is still critical in daughters’ lives. The strength of current attachment with the mother is related both with the early relationship with the mother and current attachment with the husband. The current study is thought to contribute to attachment theory emphasizing the attachment as a lifetime construct.

Keywords: adult daughter, attachment, old mothers, parental bonding

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

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The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: artificial neural networks (ANNs), classifier algorithms, credit risk assessment, logistic regression, machine Learning, support vector machines

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Authors: A. Benyahia, M. Zergoug, M. Amir, M. Fodil

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The main objective of this work is to enhance the Pulsed Eddy Current (PEC) response from the aluminum structure using signal processing. Cracks and metal loss in different structures cause changes in PEC response measurements. In this paper, time-frequency analysis is used to represent PEC response, which generates a large quantity of data and reduce the noise due to measurement. Power Spectral Density (PSD) after Wavelet Decomposition (PSD-WD) is proposed for defect detection. The experimental results demonstrate that the cracks in the surface can be extracted satisfactorily by the proposed methods. The validity of the proposed method is discussed.

Keywords: DT, pulsed eddy current, continuous wavelet transform, Mexican hat wavelet mother, defect detection, power spectral density.

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Authors: Ly. Benbahouche

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Currently, several soft switching topologies have been studied to achieve high power switching efficiency, reduced cost, improved reliability and reduced parasites. It is well known that improvement in power electronics systems always depend on advanced in power devices. The IGBT has been successfully used in a variety of switching applications such as motor drives and appliance control because of its superior characteristics. The aim of this paper is focuses on simulation and explication of the internal dynamics of IGBTs behaviour under the most popular soft switching schemas that is Zero Current Switching (ZCS) environments. The main purpose of this paper is to point out some mechanisms relating to current tail during the turn-off and examination of the response at turn-off with variation of temperature, inductance L, snubber capacitors Cs, and bus voltage in order to achieve an improved understanding of internal carrier dynamics. It is shown that the snubber capacitor, the inductance and even the temperature controls the magnitude and extent of the tail current, hence the turn-off time (switching speed of the device). Moreover, it has also been demonstrated that the ZCS switching can be utilized efficiently to improve and reduce the power losses as well as the turn-off time. Furthermore, the turn-off loss in ZCS was found to depend on the time of switching of the device.

Keywords: PT-IGBT, ZCS, turn-off losses, dV/dt

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Authors: Mojtaba Abolfazli, Mohammad Gahderi, Alireza Ashoorizadeh, Rahim Zeinali

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Interconnection between countries provides noticeable economic, technical and environmental benefits. Iran grid has an excellent condition for connection to neighbouring countries. There are two main options including High Voltage Direct Current (HVDC) and High Voltage Alternative Current (HVAC) for interconnection between the grids. At present, all of Iran cross border interconnections are HVAC while HVDC brings more benefits in comparison which should be considered by system planners. This paper presents a comprehensive review of technical considerations of HVDC for interconnection of Iran grid to neighbouring countries. Converter technology, converter transformers, converter valves, filters, and transmission link are studied for a good cognition to HVDC. In addition, a comparison between HVDC and HVAC for transmitting of power is discussed. Finally, a conclusion on HVDC technology and components is drawn out to provide a comprehensive knowledge for system planners.

Keywords: interconnection, HVDC, HVAC, voltage sourced converter, current sourced converter

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Authors: Rohit Gupta, Ravinder Agarwal

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Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: classifiers, feature selection, locomotion, sEMG

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining

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Authors: Isabelle Snyder

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Microgrid protection presents challenges to conventional protection techniques due to the low induced fault current. Protection relays present in microgrid applications require a combination of settings groups to adjust based on the architecture of the microgrid in islanded and grid-connected mode. In a radial system where the microgrid is at the other end of the feeder, directional elements can be used to identify the direction of the fault current and switch settings groups accordingly (grid connected or microgrid connected). However, with multiple microgrid connections, this concept becomes more challenging, and the direction of the current alone is not sufficient to identify the source of the fault current contribution. ORNL has previously developed adaptive relaying schemes through other DOE-funded research projects that will be evaluated and used as a baseline for this research. The four protection techniques in this study are the following: (1) Adaptive Current only Protection System (ACPS), Intentional (2) Unbalanced Control for Protection Control (IUCPC), (3) Adaptive Protection System with Communication Controller (APSCC) (4) Adaptive Model-Driven Protective Relay (AMDPR). The first two methods focus on identifying the islanded mode without communication by monitoring the current sequence component generated by the system (ACPS) or induced with inverter control during islanded mode (IUCPC) to identify the islanding condition without communication at the relay to adjust the settings. These two methods are used as a backup to the APSCC, which relies on a communication network to communicate the islanded configuration to the system components. The fourth method relies on a short circuit model inside the relay that is used in conjunction with communication to adjust the system configuration and computes the fault current and adjusts the settings accordingly.

Keywords: adaptive relaying, microgrid protection, sequence components, islanding detection, communication controlled protection, integrated short circuit model

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Authors: Tareg Omar Mansour, Khaled Omar Elhaji

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Model solutions of pentanol in the salt water of various concentrations were subjected to electrochemical oxidation using a dimensionally stable anode (DSA) and a platinised titanium cathode. The removal of pentanol was analysed over time using gas chromatography (GC) and by monitoring the total organic carbon (TOC) concentration of the reaction mixture. It was found that the removal of pentanol occurred more efficiently at higher salinities and higher applied electrical current values. When using a salt concentration of 20,000 ppm and an applied current of 100 mA there was a decrease in concentration of pentanol of 15 %. When the salt concentration and applied current were increased to 58,000 ppm and 500 mA respectively, the decrease in concentration was improved to 64 %.

Keywords: dimensionally stable anode (DSA), total organic hydrocarbon (TOC), gas chromatography mass spectrometry (GCMS), electrochemical oxidation

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Authors: N. Ravikumar, S. Krishnan, B. Yokeshkumar

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In present days, the power quality issues are increases due to non-linear loads like fridge, AC, washing machines, induction motor, etc. This power quality issues will affects the output voltages, output current, and output power of the total performance of the generator. This paper explains how to test the generator using the Fluke 435 II series power quality analyser. This Fluke 435 II series power quality analyser is used to measure the voltage, current, power, energy, total harmonic distortion (THD), current harmonics, voltage harmonics, power factor, and frequency. The Fluke 435 II series power quality analyser have several advantages. They are i) it will records output in analog and digital format. ii) the fluke analyzer will records at every 0.25 sec. iii) it will also measure all the electrical parameter at a time.

Keywords: THD, harmonics, power quality, TNEB, Fluke 435

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Authors: Gulnara Galeeva

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The Analytic Hierarchy Process is widely used in the economic and financial studies, including the formation of investment portfolios. In this study, a generalized method of obtaining a vector of priorities for the case with separate pairwise comparisons of the expert opinion being presented as a set of several equal evaluations on a ratio scale is examined. The author claims that this method allows solving an important and up-to-date problem of excluding vagueness and ambiguity of the expert opinion in the decision making theory. The study describes the authentic wide pairwise comparison matrix. Its application in the formation of the efficient investment portfolio of intangible assets of a small business enterprise with limited funding is considered. The proposed method has been successfully approbated on the practical example of a functioning dental clinic. The result of the study confirms that the wide pairwise comparison matrix can be used as a simple and reliable method for forming the enterprise investment policy. Moreover, a comparison between the method based on the wide pairwise comparison matrix and the classical analytic hierarchy process was conducted. The results of the comparative analysis confirm the correctness of the method based on the wide matrix. The application of a wide pairwise comparison matrix also allows to widely use the statistical methods of experimental data processing for obtaining the vector of priorities. A new method is available for simple users. Its application gives about the same accuracy result as that of the classical hierarchy process. Financial directors of small and medium business enterprises get an opportunity to solve the problem of companies’ investments without resorting to services of analytical agencies specializing in such studies.

Keywords: analytic hierarchy process, decision processes, investment portfolio, intangible assets

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Authors: Wajeehah Aayeshah, Joy Higgs

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The term “transcending pedagogies” has been created to refer to teaching and learning strategies that transcend the mode of student enrolment, the needs of different students, and different learning spaces. The value of such pedagogies in the current arena when learning spaces, technologies and preferences are more volatile than ever before, is a key focus of this paper. The paper will examine current and emerging pedagogies that transcend the learning spaces and enrollment modes of on campus, distance, virtual and workplace learning contexts. A further point of interest is how academics in professional and higher education settings interpret and implement pedagogies in the current global conversation space and re-creation of higher education. This study questioned how the notion and practice of transcending pedagogies enables us to re-imagine and reshape university curricula. It explored the nature of teaching and learning spaces and those professional and higher education (current and emerging) pedagogies that can be implemented across these spaces. We set out to identify how transcending pedagogies can assist students in learning to deal with complexity, uncertainty and change in the practice worlds and better appeal to students who are making decisions on where to enrol. The data for this study was collected through in-depth interviews and focus groups with academics and policy makers within academia.

Keywords: Transcending Pedagogies, teaching and learning strategies, learning spaces, pedagogies

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

Procedia PDF Downloads 102

Authors: Nathaniel C. Villanueva, Ian K. H. Chun, Alyssa S. Fujiwara, Emily R. Leibovitch, Brennan E. Yamamoto, Loren G. Yamamoto

Abstract:

Introduction: In previous studies of high school sports, over 15% of concussions were attributed to contact with the playing surface. While artificial turf fields are increasing in popularity due to lower maintenance costs, artificial turf has been associated with more ankle and knee injuries, with inconclusive data on concussions. In this study, natural grass and artificial football fields were compared in terms of deceleration on fall impact. Methods: Accelerometers were placed on the forehead, apex of the head, and right ear of a Century Body Opponent Bag (BOB) manikin. A Riddell HITS football helmet was secured onto the head of the manikin over the accelerometers. This manikin was dropped onto natural grass (n = 10) and artificial turf (n = 9) high school football fields. The manikin was dropped from a stationary position at a height of 60 cm onto its front, back, and left side. Each of these drops was conducted 10 times at the 40-yard line, 20-yard line, and endzone. The net deceleration on impact was calculated as a net vector from each of the three accelerometers’ x, y, and z vectors from the three different locations on the manikin’s head (9 vector measurements per drop). Results: Mean values for the multiple drops were calculated for each accelerometer and drop type for each field. All accelerometers in forward and backward falls and one accelerometer in side falls showed significantly greater impact force on synthetic turf compared to the natural grass surfaces. Conclusion: Impact force was higher on synthetic fields for all drop types for at least one of the accelerometer locations. These findings suggest that concussion risk might be higher for athletes playing on artificial turf fields.

Keywords: concussion, football, biomechanics, sports

Procedia PDF Downloads 154

Authors: Peng Lu, Branimir Radisavljevic, Martin Seeger, Daniel Over, Torsten Votteler, Bernardo Galletti

Abstract:

CO₂-based gas mixtures exhibit huge potential as the interruption medium for replacing SF₆ in high voltage switchgears. In this paper, the recovery characteristics of dielectric strength of CO₂-O₂ mixture in the post arc phase after the current zero are presented. As representative examples, the dielectric recovery curves under conditions of different gas filling pressures and short-circuit current amplitudes are presented. A series of dielectric recovery measurements suggests that the dielectric recovery rate is proportional to the mass flux of the blowing gas, and the dielectric strength recovers faster in the case of lower short circuit currents.

Keywords: CO₂ mixture, high voltage circuit breakers, dielectric recovery rate, short-circuit current, mass flux

Procedia PDF Downloads 189

Authors: Evren Isen

Abstract:

In grid-connected renewable energy systems, input power is controlled by AC/DC converter or/and DC/DC converter depending on output voltage of input source. The power is injected to DC-link, and DC-link voltage is regulated by inverter controlling the grid current. Inverter performance is considerable in grid-connected renewable energy systems to meet the utility standards. In this paper, modelling and simulation of hysteresis current controlled single-phase grid-connected inverter that is utilized in renewable energy systems, such as wind and solar systems, are presented. 2 kW single-phase grid-connected inverter is simulated in Simulink and modeled in Matlab-m-file. The grid current synchronization is obtained by phase locked loop (PLL) technique in dq synchronous rotating frame. Although dq-PLL can be easily implemented in three-phase systems, there is difficulty to generate β component of grid voltage in single-phase system because single-phase grid voltage exists. Inverse-Park PLL with low-pass filter is used to generate β component for grid angle determination. As grid current is controlled by constant bandwidth hysteresis current control (HCC) technique, average switching frequency and variation of switching frequency in a fundamental period are considered. 3.56% total harmonic distortion value of grid current is achieved with 0.5 A bandwidth. Average value of switching frequency and total harmonic distortion curves for different hysteresis bandwidth are obtained from model in m-file. Average switching frequency is 25.6 kHz while switching frequency varies between 14 kHz-38 kHz in a fundamental period. The average and maximum frequency difference should be considered for selection of solid state switching device, and designing driver circuit. Steady-state and dynamic response performances of the inverter depending on the input power are presented with waveforms. The control algorithm regulates the DC-link voltage by adjusting the output power.

Keywords: grid-connected inverter, hysteresis current control, inverter modelling, single-phase inverter

Procedia PDF Downloads 475