Search results for: computing network control systems

Authors: Bliss Singhal

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Epilepsy is a prevalent neurological disorder affecting approximately 50 million individuals worldwide and 1.2 million Americans. There exist millions of pediatric patients with intractable epilepsy, a condition in which seizures fail to come under control. The occurrence of seizures can result in physical injury, disorientation, unconsciousness, and additional symptoms that could impede children's ability to participate in everyday tasks. Predicting seizures can help parents and healthcare providers take precautions, prevent risky situations, and mentally prepare children to minimize anxiety and nervousness associated with the uncertainty of a seizure. This research proposes a comprehensive framework to predict seizures in pediatric patients by evaluating machine learning algorithms on unimodal neuroimaging data consisting of electroencephalogram signals. The bandpass filtering and independent component analysis proved to be effective in reducing the noise and artifacts from the dataset. Various machine learning algorithms’ performance is evaluated on important metrics such as accuracy, precision, specificity, sensitivity, F1 score and MCC. The results show that the deep learning algorithms are more successful in predicting seizures than logistic Regression, and k nearest neighbors. The recurrent neural network (RNN) gave the highest precision and F1 Score, long short-term memory (LSTM) outperformed RNN in accuracy and convolutional neural network (CNN) resulted in the highest Specificity. This research has significant implications for healthcare providers in proactively managing seizure occurrence in pediatric patients, potentially transforming clinical practices, and improving pediatric care.

Keywords: intractable epilepsy, seizure, deep learning, prediction, electroencephalogram channels

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Authors: Carlo Gozzelino

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Since the early 2000s, the phenomenon of the two-sided markets has been of growing interest in academic literature as such kind of markets differs by having cross-side network effects and same-side network effects characterizing the transactions, which make the analysis different when compared to traditional seller-buyer concept. Due to such externalities, pricing strategies can be based on subsidizing the participation of one side (i.e. considered key for the platform to attract the other side) while recovering the loss on the other side. In recent years, several players of the Italian financial intermediation industry moved from an integrated landscape (i.e. selling their own products) to an open one (i.e. intermediating third party products). According to academic literature such behavior can be interpreted as a merchant move towards a platform, operating in a two-sided market environment. While several application of two-sided market framework are available in academic literature, purpose of this paper is to use a two-sided market concept to suggest a new framework applied to financial intermediation. To this extent, a model is developed to show how competitors behave when vertically integrated and how the peculiarities of a two-sided market act as an incentive to disintegrate. Additionally, we show that when all players act as a platform, the dynamics of a two-sided markets can allow at least a Nash equilibrium to exist, in which platform of different sizes enjoy positive profit. Finally, empirical evidences from Italian market are given to sustain – and to challenge – this interpretation.

Keywords: financial intermediation, network externalities, two-sided markets, vertical differentiation

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Authors: Tiago Sampaio, André Vasconcelos, Bruno Fragoso

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The Normalized Systems Theory, which is designed to be applied to software architectures, provides a set of theorems, elements and rules, with the purpose of enabling evolution in Information Systems, as well as ensuring that they are ready for change. In order to make that possible, this work’s solution is to apply the Normalized Systems Theory to the domain of enterprise architectures, using Archimate. This application is achieved through the adaptation of the elements of this theory, making them artifacts of the modeling language. The theorems are applied through the identification of the viewpoints to be used in the architectures, as well as the transformation of the theory’s encapsulation rules into architectural rules. This way, it is possible to create normalized enterprise architectures, thus fulfilling the needs and requirements of the business. This solution was demonstrated using the Portuguese Public Procurement System. The Portuguese government aims to make this system as fair as possible, allowing every organization to have the same business opportunities. The aim is for every economic operator to have access to all public tenders, which are published in any of the 6 existing platforms, independently of where they are registered. In order to make this possible, we applied our solution to the construction of two different architectures, which are able of fulfilling the requirements of the Portuguese government. One of those architectures, TO-BE A, has a Message Broker that performs the communication between the platforms. The other, TO-BE B, represents the scenario in which the platforms communicate with each other directly. Apart from these 2 architectures, we also represent the AS-IS architecture that demonstrates the current behavior of the Public Procurement Systems. Our evaluation is based on a comparison between the AS-IS and the TO-BE architectures, regarding the fulfillment of the rules and theorems of the Normalized Systems Theory and some quality metrics.

Keywords: archimate, architecture, broker, enterprise, evolvable systems, interoperability, normalized architectures, normalized systems, normalized systems theory, platforms

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Authors: H. El-Kamchouchi, Heba Gaber, Fatma Ahmed, Dalia H. El-Kamchouchi

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Due to the rapid growth in modern communication systems, fault tolerance and data security are two important issues in a secure transaction. During the transmission of data between the sender and receiver, errors may occur frequently. Therefore, the sender must re-transmit the data to the receiver in order to correct these errors, which makes the system very feeble. To improve the scalability of the scheme, we present a secure proxy signature scheme with fault tolerance over an efficient and secure authenticated key agreement protocol based on RSA system. Authenticated key agreement protocols have an important role in building a secure communications network between the two parties.

Keywords: proxy signature, fault tolerance, rsa, key agreement protocol

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Authors: Mehdi Basirat, Mohammad Rouhani, Shahla Borzouei, Majid Zarangi, Asma Abolghasemi, Mohammad Fazel Soltani, Mohammad Gorji, Mohammad Amin Samih

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The common pistachio psylla, Agonoscena pistaciae Burckhardt and Lauterer (Hemiptera: Aphalaridae), as one of the most detrimental pests in all pistachio producing regions, causes great economic damages to pistachio trees. Nowadays, various pesticides are used to control the common pistachio psylla and robust pesticide exposure has occurred in orchards. In this study, field experiments were conducted during 2018–2021 to assess the effects of sulfur on A. pistaciae. This study compared sulfur with asafoetida extract and pesticide (acetamiprid) on A. pistaciae based on complete randomized blocks with three replications. The analysis results of variance showed that the effect of treatments on egg (F2,24 = 17.61, P = 0.00) and nymphs (F2,24 = 18.29, P = 0.00) had a significant difference at a 1% level. The results demonstrated that sulfur had the highest measure of control on eggs and nymphs significantly compared to the plant extract and pesticide (negative control). These results provide support to the potential use of sulfur as an alternative pest management tool against A. pistaciae. The results clearly indicated that sulfur could control the common pistachio psylla population for six weeks at least.

Keywords: Agonoscena pistaciae, pesticide exposure, pistachio, sulfur

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Authors: Jeelka Ray

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Survey of the papers revealed that there is no practical design available for packaging machine based on Embedded system, so the need arose for the development of the prototype model. In this paper, author has worked on the development of an ARM7 based Embedded Controller for controlling the sequence of packaging machine. The unit is made user friendly with TFT and Touch Screen implementing human machine interface (HMI). The different system components are briefly discussed, followed by a description of the overall design. The major functions which involve bag forming, sealing temperature control, fault detection, alarm, animated view on the home screen when the machine is working as per different parameters set makes the machine performance more successful. LPC2478 ARM 7 Embedded Microcontroller controls the coordination of individual control function modules. In back gone days, these machines were manufactured with mechanical fittings. Later on, the electronic system replaced them. With the help of ongoing technologies, these mechanical systems were controlled electronically using Microprocessors. These became the backbone of the system which became a cause for the updating technologies in which the control was handed over to the Microcontrollers with Servo drives for accurate positioning of the material. This helped to maintain the quality of the products. Including all, RS 485 MODBUS Communication technology is used for synchronizing AC Drive & Servo Drive. These all concepts are operated either manually or through a Graphical User Interface. Automatic tuning of heaters, sealers and their temperature is controlled using Proportional, Integral and Derivation loops. In the upcoming latest technological world, the practical implementation of the above mentioned concepts is really important to be in the user friendly environment. Real time model is implemented and tested on the actual machine and received fruitful results.

Keywords: packaging machine, embedded system, ARM 7, micro controller, HMI, TFT, touch screen, PID

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Authors: Mahmoud Samkan

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Dispersed Generation (DG) is a promising solution to many power system problems such as voltage regulation and power loss. This paper proposes a heuristic two-step method to optimize the location and size of DG for reducing active power losses and, therefore, improve the voltage profile in radial distribution networks. In addition to a DG placed at the system load gravity center, this method consists in assigning a DG to each lateral of the network. After having determined the central DG placement, the location and size of each lateral DG are predetermined in the first step. The results are then refined in the second step. This method is tested for 33-bus system for 100% DG penetration. The results obtained are compared with those of other methods found in the literature.

Keywords: optimal location, optimal size, dispersed generation (DG), radial distribution networks, reducing losses

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Authors: Kuanrong Qiu, Sebnem Madrali, Evgueniy Entchev

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To achieve the satisfactory objectives in deploying integrated renewable energy systems, it is crucial to consider all the related parameters affecting the design and decision-making. The multi-criteria evaluation method is a reliable and efficient tool for achieving the most appropriate solution. The approach considers the influential factors and their relative importance in prioritizing the alternatives. In this paper, a multi-criteria decision framework, based on the criteria including technical, economic, environmental and reliability, is developed to evaluate and prioritize renewable energy technologies and configurations of their integrated systems for community applications, identify their viability, and thus support the adoption of the clean energy technologies and the decision-making regarding energy transitions and transition patterns. Case studies for communities in Canada show that resource availability and the configurations of the integrated systems significantly impact the economic performance and environmental performance.

Keywords: multi-criteria, renewables, integrated energy systems, decision-making, model

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Authors: Zaia Derrar Kaddour

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The study of a beam throughout an optical path is generally achieved by means of diffraction integral. Unfortunately, in some problems, this tool turns out to be not very friendly and hard to implement. Instead, the beam expansion method for computing field profiles appears to be an interesting alternative. The beam expansion method consists of expanding the field pattern as a series expansion in a set of orthogonal functions. Propagating each individual component through a circuit and adding up the derived elements leads easily to the result. The problem is then reduced to finding how the expansion coefficients change in a circuit. The beam expansion method requires a systematic study of each type of optical element that can be met in the considered optical path. In this work, we analyze the following fundamental elements: first order optical systems, hard apertures and waveguides. We show that the former element type is completely defined thanks to the Gouy phase shift expression we provide and the latters require a suitable mode conversion. For endorsing the usefulness and relevance of the beam expansion approach, we show here some of its applications such as the treatment of the thermal lens effect and the study of unstable resonators.

Keywords: gouy phase shift, modes, optical resonators, unstable resonators

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Authors: Jair Servín-Aguilar, Yu Tang

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We address the problem of robust attitude tracking for agile satellites under unknown bounded torque disturbances using a double-gimbal variable-speed control-moment gyro (DGVSCMG) driven by a cluster of three permanent magnet synchronous motors (PMSMs). Uniform practical asymptotic stability is achieved at the torque control level first. The desired speed of gimbals and the acceleration of the spin wheel to produce the required torque are then calculated by a velocity-based steering law and tracked at the PMSM speed-control level by designing a speed-tracking controller with compensation for the vibration caused by eccentricity and imbalance due to mechanical imperfection in the DGVSCMG. Uniform practical asymptotic stability of the overall system is ensured by loan relying on the analysis of the resulting cascaded system. Numerical simulations are included to show the performance improvement of the proposed controller.

Keywords: agile satellites, vibration compensation, internal model, stability

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Authors: Isaac Laryea

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Underwater remote-operated vehicles (ROVs) are highly useful in aquatic research and underwater operations. Unfortunately, unsteady and unpredictable conditions underwater make it difficult for underwater vehicles to maintain a steady attitude during motion. Existing underwater vehicles make use of multiple thrusters positioned at specific positions on their frame to maintain a certain pose. This study proposes an alternate way of maintaining a steady attitude during horizontal motion at low speeds by making use of a thrust vector-controlled propulsion system. The study began by carrying out some preliminary calculations to get an idea of a suitable shape and form factor. Flow simulations were carried out to ensure that enough thrust could be generated to move the system. Using the Lagrangian approach, a mathematical system was developed for the ROV, and this model was used to design a control system. A PID controller was selected for the control system. However, after tuning, it was realized that a PD controller satisfied the design specifications. The designed control system produced an overshoot of 6.72%, with a settling time of 0.192s. To achieve the effect of thrust vectoring, an inverse kinematics synthesis was carried out to determine what angle the actuators need to move to. After building the system, intermittent angular displacements of 10°, 15°, and 20° were given during bench testing, and the response of the control system as well as the servo motor angle was plotted. The final design was able to move in water but was not able to handle large angular displacements as a result of the small angle approximation used in the mathematical model.

Keywords: PID control, thrust vectoring, parallel manipulators, ROV, underwater, attitude control

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Authors: Despoina Mouratidis, Katia Lida Kermanidis

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Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

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Authors: Ayad Al-Mahturi, Herman Wahid

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This paper presents an optimal state feedback controller based on Linear Quadratic Regulator (LQR) for a two-rotor aero-dynamical system (TRAS). TRAS is a highly nonlinear multi-input multi-output (MIMO) system with two degrees of freedom and cross coupling. There are two parameters that define the behavior of LQR controller: state weighting matrix and control weighting matrix. The two parameters influence the performance of LQR. Particle Swarm Optimization (PSO) is proposed to optimally tune weighting matrices of LQR. The major concern of using LQR controller is to stabilize the TRAS by making the beam move quickly and accurately for tracking a trajectory or to reach a desired altitude. The simulation results were carried out in MATLAB/Simulink. The system is decoupled into two single-input single-output (SISO) systems. Comparing the performance of the optimized proportional, integral and derivative (PID) controller provided by INTECO, results depict that LQR controller gives a better performance in terms of both transient and steady state responses when PSO is performed.

Keywords: LQR controller, optimal control, particle swarm optimization (PSO), two rotor aero-dynamical system (TRAS)

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Authors: T. Tulwin, M. Gęca, R. Sochaczewski

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Recent improvements in electric propulsion systems and energy storage systems allow for the electrification of many sectors where it was previously not feasible. This analysis proves the feasibility of electric propulsion in aviation applications reviewing recent energy storage developments. It can be more quiet, energy efficient and more environmentally friendly. Numerical simulations were done to prove that energy efficiency can be improved for rotorcrafts especially in hover conditions. New types of aircraft configurations are reviewed and future trends are presented.

Keywords: aircraft, propulsion , efficiency, storage

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Authors: Lutful Karim, Mohammed S. Al-kahtani

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Sensors are being used in various applications such as agriculture, health monitoring, air and water pollution monitoring, traffic monitoring and control and hence, play the vital role in the growth of big data. However, sensors collect redundant data. Thus, aggregating and filtering sensors data are significantly important to design an efficient big data framework. Current researches do not focus on aggregating and filtering data at multiple layers of sensor-based big data framework. Thus, this paper introduces (i) three layers data aggregation and framework for big data and (ii) a priority-based, dynamic data aggregation scheme (PDDA) for the lowest layer at sensors. Simulation results show that the PDDA outperforms existing tree and cluster-based data aggregation scheme in terms of overall network energy consumptions and end-to-end data transmission delay.

Keywords: big data, clustering, tree topology, data aggregation, sensor networks

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Authors: Jane A. Luke

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Persistent pressure passed on to manufacturers from escalating consumer expectations and the ever growing global competitiveness have produced a rapidly increasing interest in the development of various manufacturing strategy models. Academic and industrial circles are taking keen interest in the field of manufacturing strategy. Many manufacturing strategies are currently centered on the traditional concepts of focused manufacturing capabilities such as quality, cost, dependability and innovation. Process capability indices was conducted assuming that the process under study is in statistical control and independent observations are generated over time. However, in practice, it is very common to come across processes which, due to their inherent natures, generate autocorrelated observations. The degree of autocorrelation affects the behavior of patterns on control charts. Even, small levels of autocorrelation between successive observations can have considerable effects on the statistical properties of conventional control charts. When observations are autocorrelated the classical control charts exhibit nonrandom patterns and lack of control. Many authors have considered the effect of autocorrelation on the performance of statistical process control charts. In this paper, the effect of autocorrelation on confidence intervals for different PCIs was included. Stationary Gaussian processes is explained. Effect of autocorrelation on PCIs is described in detail. Confidence intervals for Cp and Cpk are constructed for PCIs when data are both independent and autocorrelated. Confidence intervals for Cp and Cpk are computed. Approximate lower confidence limits for various Cpk are computed assuming AR(1) model for the data. Simulation studies and industrial examples are considered to demonstrate the results.

Keywords: autocorrelation, AR(1) model, Bissell’s approximation, confidence intervals, statistical process control, specification limits, stationary Gaussian processes

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Authors: Qasim Kriri, Harsh B. Desai

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Water supply and sanitation in Saudi Arabia is portrayed by difficulties and accomplishments. One of the fundamental difficulties is water shortage. With a specific end goal to beat water shortage, significant ventures have been attempted in sea water desalination, water circulation, sewerage, and wastewater treatment. The motivation behind Statistical Process Control (SPC) is to decide whether the execution of a procedure is keeping up an acceptable quality level [AQL]. SPC is an analytical decision-making method. A fundamental apparatus in the SPC is the Control Charts, which follow the inconstancy in the estimations of the item quality attributes. By utilizing the suitable outline, administration can decide whether changes should be made with a specific end goal to keep the procedure in charge. The two most important quality factors in the distilled water which were taken into consideration were pH (Potential of Hydrogen) and TDS (Total Dissolved Solids). There were three stages at which the quality checks were done. The stages were as follows: (1) Water at the source, (2) water after chemical treatment & (3) water which is sent for packing. The upper specification limit, central limit and lower specification limit are taken as per Saudi water standards. The procedure capacity to accomplish the particulars set for the quality attributes of Berain water Factory chose to be focused by the proposed SPC system.

Keywords: acceptable quality level, statistical quality control, control charts, process charts

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Authors: Kaushikk Iyer, Richard M Hall, David Keeling

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Hardware-in-the-loop (HIL) simulation is an advanced technique for developing and testing complex real-time control systems. This paper presents the benefits of HIL simulation and how it can be implemented and used effectively to develop, test, and validate advanced control algorithms used in a spinal joint Wear simulator for the Tribological testing of spinal disc prostheses. spinal wear simulator is technologically the most advanced machine currently employed For the in-vitro testing of newly developed spinal Discimplants. However, the existing control techniques, such as a simple position control Does not allow the simulator to test non-sinusoidal waveforms. Thus, there is a need for better and advanced control methods that can be developed and tested Rigorouslybut safely before deploying it into the real simulator. A benchtop HILsetupis was created for experimentation, controller verification, and validation purposes, allowing different control strategies to be tested rapidly in a safe environment. The HIL simulation aspect in this setup attempts to replicate similar spinal motion and loading conditions. The spinal joint wear simulator containsa four-Barlinkpowered by electromechanical actuators. LabVIEW software is used to design a kinematic model of the spinal wear Simulator to Validatehow each link contributes towards the final motion of the implant under test. As a result, the implant articulates with an angular motion specified in the international standards, ISO-18192-1, that define fixed, simplified, and sinusoid motion and load profiles for wear testing of cervical disc implants. Using a PID controller, a velocity-based position control algorithm was developed to interface with the benchtop setup that performs HIL simulation. In addition to PID, a fuzzy logic controller (FLC) was also developed that acts as a supervisory controller. FLC provides intelligence to the PID controller by By automatically tuning the controller for profiles that vary in amplitude, shape, and frequency. This combination of the fuzzy-PID controller is novel to the wear testing application for spinal simulators and demonstrated superior performance against PIDwhen tested for a spectrum of frequency. Kaushikk Iyer is a Ph.D. Student at the University of Leeds and an employee at Key Engineering Solutions, Leeds, United Kingdom, (e-mail: [email protected], phone: +44 740 541 5502). Richard M Hall is with the University of Leeds, the United Kingdom as a professor in the Mechanical Engineering Department (e-mail: [email protected]). David Keeling is the managing director of Key Engineering Solutions, Leeds, United Kingdom (e-mail: [email protected]). Results obtained are successfully validated against the load and motion tolerances specified by the ISO18192-1 standard and fall within limits, that is, ±0.5° at the maxima and minima of the motion and ±2 % of the complete cycle for phasing. The simulation results prove the efficacy of the test setup using HIL simulation to verify and validate the accuracy and robustness of the prospective controller before its deployment into the spinal wear simulator. This method of testing controllers enables a wide range of possibilities to test advanced control algorithms that can potentially test even profiles of patients performing various dailyliving activities.

Keywords: Fuzzy-PID controller, hardware-in-the-loop (HIL), real-time simulation, spinal wear simulator

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Authors: Danilo López, Johana Hernández, Edwin Rivas

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The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Keywords: cognitive radio, neural network, prediction, primary user

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Authors: Boon Lee

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Research publication is an essential output of universities because it not only promotes university recognition, it also receives government funding. The history of university research culture has been one of ‘publish or perish’ and universities have consistently encouraged their academics and researchers to produce research articles in reputable journals in order to maintain a level of competitiveness. In turn, the United Kingdom (UK) government funding is determined by the number and quality of research publications. This paper aims to investigate on whether more government funding leads to more quality papers. To that end, the paper employs a Network DEA model to evaluate the UK higher education performance over a period. Sources of efficiency are also determined via second stage regression analysis.

Keywords: efficiency, higher education, network data envelopment analysis, universities

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Authors: Aleksandra Aleksandrovna Filimonova, Lev Sergeevich Kazarinov, Tatyana Aleksandrovna Barbasova

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A method of effective planning and control of industrial facility energy consumption is offered. The method allows to optimally arrange the management and full control of complex production facilities in accordance with the criteria of minimal technical and economic losses at the forecasting control. The method is based on the optimal construction of the power efficiency characteristics with the prescribed accuracy. The problem of optimal designing of the forecasting model is solved on the basis of three criteria: maximizing the weighted sum of the points of forecasting with the prescribed accuracy; the solving of the problem by the standard principles at the incomplete statistic data on the basis of minimization of the regularized function; minimizing the technical and economic losses due to the forecasting errors.

Keywords: energy consumption, energy efficiency, energy management system, forecasting model, power efficiency characteristics

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Authors: Marek Dlapa

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The algebraic approach is applied to the control of the HiMAT (Highly Maneuverable Aircraft Technology). The objective is to find a robust controller which guarantees robust stability and decoupled control of longitudinal model of a scaled remotely controlled vehicle version of the advanced fighter HiMAT. Control design is performed by decoupling the nominal MIMO (multi-input multi-output) system into two identical SISO (single-input single-output) plants which are approximated by a 4th order transfer function. The algebraic approach is then used for pole placement design, and the nominal closed-loop poles are tuned so that the peak of the µ-function is minimal. As an optimization tool, evolutionary algorithm Differential Migration is used in order to overcome the multimodality of the cost function yielding simple controller with decoupling for nominal plant which is compared with the D-K iteration through simulations of standard longitudinal manoeuvres documenting decoupled control obtained from algebraic approach for nominal plant as well as worst case perturbation.

Keywords: algebraic approach, evolutionary computation, genetic algorithms, HiMAT, robust control, structured singular value

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Authors: Handan Ucun Özel, Halil Barış Özel

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The toxic effects of copper and cadmium on seed germination, seedling, root, shoot length, and seedling dry biomass of oriental beech (Fagus orientalis Lipsky) was evaluated under laboratory conditions compared to control values. Copper and cadmium treatments at 50, 100, 150, and 200 mg/l affect seed germination and seedling growth of oriental beech as compared to control. Copper treatments at 50, 100, 150, and 200 mg/l concentrations produced significant (p < 0.01) effects on seed germination and seedling length of oriental beech while copper treatment at 150 mg/l significantly affected root growth and seedling dry biomass as compared to control. Similarly, cadmium treatments from 50 to 200 mg/l affected the seed germination, root, shoot length, and seedling dry biomass of oriental beech as compared to control. Cadmium treatments showed an adverse effect on seedlings of oriental beech as compared to copper, copper and cadmium treatments at 200mg/l exhibited the lowest percentage of tolerance in seedlings of oriental beech as compared to control.

Keywords: copper, cadmium, toxicity, oriental beech

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Authors: Der-Feng Guo

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Optoelectronic switches have attracted a considerable attention in the semiconductor research field due to their potential applications in optical computing systems and optoelectronic integrated circuits (OEICs). With high gains and high-speed operations, npn heterostructures can be used to produce promising optoelectronic switches. It is known that the bulk barrier and heterostructure-induced potential spike act important roles in the characteristics of the npn heterostructures. To investigate the effects of bulk barrier and potential spike heights on the optoelectronic switching of the npn heterostructures, GaAs/InGaP and AlGaAs/GaAs/InAlGaP npn heterostructural optoelectronic switches (HSOSs) have been fabricated in this work. It is seen that the illumination decreases the switching voltage Vs and increases the switching current Is, and thus the OFF state is under dark and ON state under illumination in the optical switching of the GaAs/InGaP HSOS characteristics. But in the AlGaAs/GaAs/InAlGaP HSOS characteristics, the Vs and Is present contrary trends, and the OFF state is under illumination and ON state under dark. The studied HSOSs show quite different switching variations with incident light, which are mainly attributed to the bulk barrier and potential spike heights affected by photogenerated carriers.

Keywords: bulk barrier, heterostructure, optoelectronic switch, potential spike

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Authors: Foad Alzoughool

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Conflicting studies on the association between the rs5219 polymorphism and type 2 diabetes, some studies have confirmed a strong relationship between this variant and type2 diabetes, on the other hand, many studies denied the existence of this association. This study aimed to provide evidence about whether the rs5219 polymorphism has or hasn't a role as a risk factor for diabetes and meta-analysis to investigate the role of the control age group in the association. Genotyping of the rs5219 polymorphism was performed in a cohort of 266 healthy elderly subjects with a mean age (60.2 ± 5.1) with no history of diabetes (HbA1c < 6%) using standard Sanger sequencing methods. Lys/Lys alleles were detected in 20 persons (7.5%), Lys/Glu alleles in 96 persons (36.1%), and Glu/Glu in 150 persons (56.4%). The genotype distribution was consistent with Hardy–Weinberg equilibrium (P =0.7). Meta-analysis notably indicates no association between rs5219 polymorphism and type 2 diabetes in all studies used the younger age of the control group compared to the patient's age. In conclusion, our study sheds light on the importance of age factor among the control group recruited in case-control studies.

Keywords: Type 2 diabetes, rs5219 polymorphism, E23K, KCNJ11 gene

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Authors: Amir Jalalian-Khakshour, T. N. Croft

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Vertical Axis Wind Turbine (VAWT) systems are becoming increasingly popular as they have a number of advantages over traditional wind turbines. The advantages are reliability, ease of transportation and manufacturing. These attributes could make these technologies useful in developing economies. The performance characteristics of a VAWT are different from a horizontal axis wind turbine, which can be attributed to the low tip speed ratio operation. To unlock the potential of these VAWT systems, the operational behaviour in a number of system topologies and environmental conditions needs to be understood. In this study, a non-linear dynamic simulation method was developed in Matlab and validated against in field data of a large scale, 8-meter rotor diameter prototype. This simulation method has been utilised to determine the performance characteristics of a number of control methods and system topologies. The motivation for this research was to develop a simulation method which accurately captures the operating behaviour and is computationally inexpensive. The model was used to evaluate the performance through parametric studies and optimisation techniques. The study gave useful insights into the applications and energy generation potential of this technology.

Keywords: power generation, renewable energy, rotordynamics, wind energy

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Authors: Tori Reddy Dodla, Laura Ann Jones

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The objective of this study was to propose strategies to improve the efficiency of Knowledge Management Systems (KMS). This study highlights best practices from various industries to create an overall summary of Knowledge Management (KM) and efficiency in organizational performance. Results indicated eleven best practices for maximizing the efficiency of organizational KMS that can be divided into four categories: Designing the KMS, Identifying Case Studies, Implementing the KMS, and Promoting adoption and usage. Our findings can be used as a foundation for scholars to conduct further research on KMS efficiency.

Keywords: artificial intelligence, knowledge management efficiency, knowledge management systems, organizational performance

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Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

Abstract:

The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

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Authors: Aby Nesan Raj, Sumil K. Raj, Sumesh Jayan

Abstract:

The objective of the study is to formulate a self-regulation model that shall enhance the usage of Intelligent Transportation Systems by understanding the theory of self-efficacy. The core logic of the self-regulation model shall monitor driver's behavior based on the situations related to the various sources of Self Efficacy like enactive mastery, vicarious experience, verbal persuasion and physiological arousal in addition to the vehicle data. For this study, four different vehicle data, speed, drowsiness, diagnostic data and surround camera views are considered. This data shall be given to the self-regulation model for evaluation. The oddness, which is the output of self-regulation model, shall feed to Intelligent Transportation Systems where appropriate actions are being taken. These actions include warning to the user as well as the input to the related transportation systems. It is also observed that the usage of vehicle as a sensor reduces the wastage of resource utilization or duplication. Altogether, this approach enhances the intelligence of the transportation systems especially in safety, productivity and environmental performance.

Keywords: emergency management, intelligent transportation system, self-efficacy, traffic management

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Authors: Keyi Wang

Abstract:

Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

Procedia PDF Downloads 139