Search results for: Uncertain Neural networks

Authors: P. S. Bhowmik, D. V. Rajan, S. P. Bose

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The load flow study in a power system constitutes a study of paramount importance. The study reveals the electrical performance and power flows (real and reactive) for specified condition when the system is operating under steady state. This paper gives an overview of different techniques used for load flow study under different specified conditions.

Keywords: Load Flow Studies, Y-matrix and Z-matrix iteration, Newton-Raphson method, Fast Decoupled method, Fuzzy logic, Artificial Neural Network.

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Authors: Jong-Moon Chung, Hyung-Weon Cho, Ki-Yong Jin, Min-Hee Cho

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In this paper, we present an analytical framework for the evaluation of the uplink performance of multihop cellular networks based on dynamic time division duplex (TDD). New wireless broadband protocols, such as WiMAX, WiBro, and 3G-LTE apply TDD, and mobile communication protocols under standardization (e.g., IEEE802.16j) are investigating mobile multihop relay (MMR) as a future technology. In this paper a novel MMR TDD scheme is presented, where the dynamic range of the frame is shared to traffic resources of asymmetric nature and multihop relaying. The mobile communication channel interference model comprises of inner and co-channel interference (CCI). The performance analysis focuses on the uplink due to the fact that the effects of dynamic resource allocation show significant performance degradation only in the uplink compared to time division multiple access (TDMA) schemes due to CCI [1-3], where the downlink results to be the same or better.The analysis was based on the signal to interference power ratio (SIR) outage probability of dynamic TDD (D-TDD) and TDMA systems,which are the most widespread mobile communication multi-user control techniques. This paper presents the uplink SIR outage probability with multihop results and shows that the dynamic TDD scheme applying MMR can provide a performance improvement compared to single hop applications if executed properly.

Keywords: Co-Channel Interference, Dynamic TDD, MobileMultihop Reply, Cellular Network, Time Division Multiple Access.

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Authors: C. Ardil

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Aircraft selection decisions can be challenging due to their multidimensional and interdisciplinary nature. They involve multiple stakeholders with conflicting objectives and numerous alternative options with uncertain outcomes. This study focuses on the analysis of aerial firefighting aircraft that can be chosen for the Air Fire Service to extinguish forest fires. To make such a selection, the characteristics of the fire zones must be considered, and the capability to manage the logistics involved in such operations, as well as the purchase and maintenance of the aircraft, must be determined. The selection of firefighting aircraft is particularly complex because they have longer fleet lives and require more demanding operation and maintenance than scheduled passenger air service. This paper aims to use the fuzzy proximity measure method to select the most appropriate aerial firefighting aircraft based on decision criteria using multiple attribute decision making analysis. Following fuzzy decision analysis, the most suitable aerial firefighting aircraft is ranked and determined for the Air Fire Service.

Keywords: Aerial firefighting aircraft selection, multiple criteria decision making, fuzzy sets, standard fuzzy sets, determinate fuzzy sets, indeterminate fuzzy sets, proximity measure method, Minkowski distance family function, Hausdorff distance function, MCDM, PMM, PMM-F

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of big data technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centres or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through VADER and RoBERTa model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and Term Frequency – Inverse Document Frequency (TFIDF) Vectorization and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide if the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: Counter vectorization, Convolutional Neural Network, Crawler, data technology, Long Short-Term Memory, LSTM, Web Scraping, sentiment analysis.

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Authors: Justinian Anatory, Ekael Stephen Manase

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In recent years, the adoption of mobile phones has been exceptionally rapid in many parts of the world, and Tanzania is not exceptional. We are witnessing a number of new mobile network operators being licensed from time to time by Tanzania Communications Regulatory Authority (TCRA). This makes competition in the telecommunications market very stiff. All mobile phone companies are struggling to earn more new customers into their networks. This trend courses a stiff competition. The various measures are being taken by different companies including, lowering tariff, and introducing free short messages within and out of their networks, and free calls during off-peak periods. This paper is aimed at investigating the influence of tariffs on students’ mobile customers in selecting their mobile network operators. About seventy seven students from high learning institutions in Dodoma Municipality, Tanzania, participated in responding to the prepared questionnaires. The sought information was aimed at determining if tariffs influenced students into selection of their current mobile operators. The results indicate that tariffs were the major driving factor in selection of mobile operators. However, female mobile customers were found to be more easily attracted into subscribing to a mobile operator due to low tariffs, a bigger number of free short messages or discounted call charges than their fellow male customers.

Keywords: Consumer Buying, mobile operators, tariff.

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Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

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In this contribution an innovative platform is being presented that integrates intelligent agents and evolutionary computation techniques in legacy e-learning environments. It introduces the design and development of a scalable and interoperable integration platform supporting: I) various assessment agents for e-learning environments, II) a specific resource retrieval agent for the provision of additional information from Internet sources matching the needs and profile of the specific user and III) a genetic algorithm designed to extract efficient information (classifying rules) based on the students- answering input data. The agents are implemented in order to provide intelligent assessment services based on computational intelligence techniques such as Bayesian Networks and Genetic Algorithms. The proposed Genetic Algorithm (GA) is used in order to extract efficient information (classifying rules) based on the students- answering input data. The idea of using a GA in order to fulfil this difficult task came from the fact that GAs have been widely used in applications including classification of unknown data. The utilization of new and emerging technologies like web services allows integrating the provided services to any web based legacy e-learning environment.

Keywords: Bayesian Networks, Computational Intelligencetechniques, E-learning legacy systems, Service Oriented Integration, Intelligent Agents, Genetic Algorithms.

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Authors: Angelo Lerro, Manuela Battipede, Piero Gili, Alberto Brandl

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Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility.

Keywords: Neural network, aerodynamic angles, virtual sensor, unmanned aerial vehicle, air data system, flight test.

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Authors: Sakshi Kausha, R.K Sharma

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High speed networks provide realtime variable bit rate service with diversified traffic flow characteristics and quality requirements. The variable bit rate traffic has stringent delay and packet loss requirements. The burstiness of the correlated traffic makes dynamic buffer management highly desirable to satisfy the Quality of Service (QoS) requirements. This paper presents an algorithm for optimization of adaptive buffer allocation scheme for traffic based on loss of consecutive packets in data-stream and buffer occupancy level. Buffer is designed to allow the input traffic to be partitioned into different priority classes and based on the input traffic behavior it controls the threshold dynamically. This algorithm allows input packets to enter into buffer if its occupancy level is less than the threshold value for priority of that packet. The threshold is dynamically varied in runtime based on packet loss behavior. The simulation is run for two priority classes of the input traffic – realtime and non-realtime classes. The simulation results show that Adaptive Partial Buffer Sharing (ADPBS) has better performance than Static Partial Buffer Sharing (SPBS) and First In First Out (FIFO) queue under the same traffic conditions.

Keywords: Buffer Management, Consecutive packet loss, Quality-of-Service, Priority based packet discarding, partial buffersharing.

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Authors: V. T. S. Dao, T. G. Etoh, C. Vo Le, H. D. Nguyen, K. Takehara, T. Akino, K. Nishi

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Since 2004, we have been developing an in-situ storage image sensor (ISIS) that captures more than 100 consecutive images at a frame rate of 10 Mfps with ultra-high sensitivity as well as the video camera for use with this ISIS. Currently, basic research is continuing in an attempt to increase the frame rate up to 100 Mfps and above. In order to suppress electro-magnetic noise at such high frequency, a digital-noiseless imaging transfer scheme has been developed utilizing solely sinusoidal driving voltages. This paper presents highly efficient-yet-accurate expressions to estimate attenuation as well as phase delay of driving voltages through RC networks of an ultra-high-speed image sensor. Elmore metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE data, we found a simple expression that significantly improves the accuracy of the approximation. Similarly, another simple closed-form model to estimate phase delay through fundamental RC networks is also obtained. Estimation error of both expressions is much less than previous works, only less 2% for most of the cases . The framework of this analysis can be extended to address similar issues of other VLSI structures.

Keywords: Dimensional Analysis, ISIS, Digital-noiseless, RC network, Attenuation, Phase Delay, Elmore model

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Authors: O. S. Ebrahim, K. O. Shawky, M. A. Badr, P. K. Jain

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This paper proposes an intelligent, supervisory, hysteresis liquid-level control with three-state energy saving mode (ESM) for induction motor (IM) in fluid transportation system (FTS) including storage tank. The IM pump drive comprises a modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to the computer’s ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. Considering the motor’s thermal capacity used (TCU) and grid-compatible tariff structure, a logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction. Fuzzy-logic (FL) based availability assessment is designed and deployed on cloud, in order to provide mobilized service for the star/delta switch and highly reliable contactors. Moreover, an artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and computer simulations are performed to demonstrate the validity and effectiveness of the proposed control system in terms of reliability, power quality and operational cost reduction with a motivation of power factor correction.

Keywords: Artificial Neural Network, ANN, Contactor Health Assessment, Energy Saving Mode, Induction Machine, IM, Supervisory Control, Fluid Transportation, Fuzzy Logic, FL, cloud computing, pumped storage.

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Authors: Pradeep Kumar, Shibashish Chakraborty, Sasadhar Bera

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In the anticipation of demand fluctuations, services cannot be inventoried and hence it creates a difficult problem in marketing of services. The inability to meet customers (patients) requirements in healthcare context has more serious consequences than other service sectors. In order to meet patient requirements in the current uncertain environment, healthcare organizations are seeking ways for improved service delivery. Flexibility provides a mechanism for reducing variability in service encounters and improved performance. Flexibility is defined as the ability of the organization to cope with changing circumstances or instability caused by the environment. Patient satisfaction is an important performance outcome of healthcare organizations. However, the paucity of information exists in healthcare delivery context to examine the impact of flexibility on patient satisfaction and behavioral intention. The present study is an attempt to develop a conceptual foundation for investigating overall impact of flexibility on patient satisfaction and behavioral intention. Several dimensions of flexibility in healthcare context are examined and proposed to have a significant impact on patient satisfaction and intention. Furthermore, the study involves a critical examination of determinants of patient satisfaction and development of a comprehensive view the relationship between flexibility, patient satisfaction and behavioral intention. Finally, theoretical contributions and implications for healthcare professionals are suggested from flexibility perspective.

Keywords: Healthcare, flexibility, patient satisfaction, behavioral intention.

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Authors: Kejun Zhuang, Zhaohui Wen

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In this paper, a tri–neuron network model with time delay is investigated. By using the Bendixson-s criterion for high– dimensional ordinary differential equations and global Hopf bifurcation theory for functional differential equations, sufficient conditions for existence of periodic solutions when the time delay is sufficiently large are established.

Keywords: Delay, global Hopf bifurcation, neural network, periodicsolutions.

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Authors: Satyasen Panda, Urmila Bhanja

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In this paper, we have presented and analyzed three-dimensional (3-D) matrices of wavelength/time/space code for optical code division multiple access (OCDMA) networks with NAND subtraction detection technique. The 3-D codes are constructed by integrating a two-dimensional modified quadratic congruence (MQC) code with one-dimensional modified prime (MP) code. The respective encoders and decoders were designed using fiber Bragg gratings and optical delay lines to minimize the bit error rate (BER). The performance analysis of the 3D-OCDMA system is based on measurement of signal to noise ratio (SNR), BER and eye diagram for a different number of simultaneous users. Also, in the analysis, various types of noises and multiple access interference (MAI) effects were considered. The results obtained with NAND detection technique were compared with those obtained with OR and AND subtraction techniques. The comparison results proved that the NAND detection technique with 3-D MQC\MP code can accommodate more number of simultaneous users for longer distances of fiber with minimum BER as compared to OR and AND subtraction techniques. The received optical power is also measured at various levels of BER to analyze the effect of attenuation.

Keywords: Cross correlation, three-dimensional optical code division multiple access, spectral amplitude coding optical code division multiple access, multiple access interference, phase induced intensity noise, three-dimensional modified quadratic congruence/modified prime code.

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Authors: Parvinder S. Sandhu, Manisha Prashar, Pourush Bassi, Atul Bisht

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Software effort estimation is the process of predicting the most realistic use of effort required to develop or maintain software based on incomplete, uncertain and/or noisy input. Effort estimates may be used as input to project plans, iteration plans, budgets. There are various models like Halstead, Walston-Felix, Bailey-Basili, Doty and GA Based models which have already used to estimate the software effort for projects. In this study Statistical Models, Fuzzy-GA and Neuro-Fuzzy (NF) Inference Systems are experimented to estimate the software effort for projects. The performances of the developed models were tested on NASA software project datasets and results are compared with the Halstead, Walston-Felix, Bailey-Basili, Doty and Genetic Algorithm Based models mentioned in the literature. The result shows that the NF Model has the lowest MMRE and RMSE values. The NF Model shows the best results as compared with the Fuzzy-GA based hybrid Inference System and other existing Models that are being used for the Effort Prediction with lowest MMRE and RMSE values.

Keywords: Neuro-Fuzzy Model, Halstead Model, Walston-Felix Model, Bailey-Basili Model, Doty Model, GA Based Model, Genetic Algorithm.

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Authors: V. Pizarro-Carmona, S. Castano-Solis, M. Cortés-Carmona, J. Fraile-Ardanuy, D. Jimenez-Bermejo

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The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.

Keywords: Li-ion battery packs modeling optimized, EECM, GA, electric vehicle applications.

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Authors: Ashok Kumar, Vinod Kumar

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Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.

Keywords: localization, range free, received signal strength, link quality indicator, Mamdani fuzzy logic inference, Sugeno fuzzy logic inference.

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Authors: Ling-fei Xu, Qi Zhao, Yan-ru Chen, Mu-chun Zhou, Meng Zhang, Shi-xue Xu

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SVM ( Support Vector Machine ) is a new method in the artificial neural network ( ANN ). In the steel making, how to use computer to predict the end point of BOF accuracy is a great problem. A lot of method and theory have been claimed, but most of the results is not satisfied. Now the hot topic in the BOF end point predicting is to use optical way the predict the end point in the BOF. And we found that there exist some regular in the characteristic curve of the flame from the mouse of pudding. And we can use SVM to predict end point of the BOF, just single spectrum intensity should be required as the input parameter. Moreover, its compatibility for the input space is better than the BP network.

Keywords: SVM, predict, BOF, single spectrum intensity.

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Authors: Venerando E. Amaro, Francisco Gabriel F. de Lima, Marcelo S.T. Santos

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The morphological short-term evolution of Ponta do Tubarão Island (PTI) was investigated through high accurate surveys based on post-processed kinematic (PPK) relative positioning on Global Navigation Satellite Systems (GNSS). PTI is part of a barrier island system on a high energy northeast Brazilian coastal environment and also an area of high environmental sensitivity. Surveys were carried out quarterly over a two years period from May 2010 to May 2012. This paper assesses statically the performance of digital elevation models (DEM) derived from different interpolation methods to represent morphologic features and to quantify volumetric changes and TIN models shown the best results to that purposes. The MDE allowed quantifying surfaces and volumes in detail as well as identifying the most vulnerable segments of the PTI to erosion and/or accumulation of sediments and relate the alterations to climate conditions. The coastal setting and geometry of PTI protects a significant mangrove ecosystem and some oil and gas facilities installed in the vicinities from damaging effects of strong oceanwaves and currents. Thus, the maintenance of PTI is extremely required but the prediction of its longevity is uncertain because results indicate an irregularity of sedimentary balance and a substantial decline in sediment supply to this coastal area.

Keywords: DEM, GNSS, short-term monitoring, Brazil.

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The modern Artificial Narrow Intelligence (ANI) models cannot: a) independently, situationally, and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, and cognize under uncertainty and changing of the environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU). This system uses a neural network as its computational memory, and activates functions of the perception, identification of real objects, fuzzy situational control, and forming images of these objects. These images and objects are used for modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision Making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, and Wisdom. In doing so are performed analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge of the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of situational control, fuzzy logic, psycholinguistics, informatics, and modern possibilities of data science were applied. The proposed self-controlled system of brain and mind is oriented on use as a plug-in in multilingual subject applications.

Keywords: Computational psycholinguistic cognitive brain and mind system, situational fuzzy control, uncertainty, AI.

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Authors: Mohsen A. Bakouri, Andrey V. Savkin, Abdul-Hakeem H. Alomari, Robert F. Salamonsen, Einly Lim, Nigel H. Lovell

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Physiological control of a left ventricle assist device (LVAD) is generally a complicated task due to diverse operating environments and patient variability. In this work, a tracking control algorithm based on sliding mode and feed forward control for a class of discrete-time single input single output (SISO) nonlinear uncertain systems is presented. The controller was developed to track the reference trajectory to a set operating point without inducing suction in the ventricle. The controller regulates the estimated mean pulsatile flow Qp and mean pulsatility index of pump rotational speed PIω that was generated from a model of the assist device. We recall the principle of the sliding mode control theory then we combine the feed-forward control design with the sliding mode control technique to follow the reference trajectory. The uncertainty is replaced by its upper and lower boundary. The controller was tested in a computer simulation covering two scenarios (preload and ventricular contractility). The simulation results prove the effectiveness and the robustness of the proposed controller

Keywords: robust control system, discrete-sliding mode, left ventricularle assist devicse, pulsatility index.

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: Artificial bee colony algorithm, economic dispatch, unit commitment, wind power.

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Authors: P. K. Singhal, R. Naresh, V. Sharma

Abstract:

This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: Artificial bee colony algorithm, economic dispatch, unit commitment, wind power.

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Authors: Rashid S. Mohammad, Shicheng Zhang, Sun Lu, Syed Jamal-Ud-Din, Xinzhe Zhao

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A compositional reservoir simulation model (CMG-GEM) was used for cyclic CO₂ injection process in unconventional tight reservoir. Cyclic CO₂ injection is an enhanced oil recovery process consisting of injection, shut-in, and production. The study of cyclic CO₂ injection and hydrocarbon recovery in ultra-low permeability reservoirs is mainly a function of rock, fluid, and operational parameters. CMG-GEM was used to study several design parameters of cyclic CO₂ injection process to distinguish the parameters with maximum effect on the oil recovery and to comprehend the behavior of cyclic CO₂ injection in tight reservoir. On the other hand, permeability reduction induced by asphaltene precipitation is one of the major issues in the oil industry due to its plugging onto the porous media which reduces the oil productivity. In addition to asphaltene deposition, solubility of CO₂ in the aquifer is one of the safest and permanent trapping techniques when considering CO₂ storage mechanisms in geological formations. However, the effects of the above uncertain parameters on the process of CO₂ enhanced oil recovery have not been understood systematically. Hence, it is absolutely necessary to study the most significant parameters which dominate the process. The main objective of this study is to improve techniques for designing cyclic CO₂ injection process while considering the effects of asphaltene deposition and solubility of CO₂ in the brine in order to prevent asphaltene precipitation, minimize CO₂ emission, optimize cyclic CO₂ injection, and maximize oil production.

Keywords: Tight reservoirs, cyclic O2 injection, asphaltene, solubility, reservoir simulation.

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Authors: P. C. Saxena, D. K. Tayal

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The join dependency provides the basis for obtaining lossless join decomposition in a classical relational schema. The existence of Join dependency shows that that the tables always represent the correct data after being joined. Since the classical relational databases cannot handle imprecise data, they were extended to fuzzy relational databases so that uncertain, ambiguous, imprecise and partially known information can also be stored in databases in a formal way. However like classical databases, the fuzzy relational databases also undergoes decomposition during normalization, the issue of joining the decomposed fuzzy relations remains intact. Our effort in the present paper is to emphasize on this issue. In this paper we define fuzzy join dependency in the framework of type-1 fuzzy relational databases & type-2 fuzzy relational databases using the concept of fuzzy equality which is defined using fuzzy functions. We use the fuzzy equi-join operator for computing the fuzzy equality of two attribute values. We also discuss the dependency preservation property on execution of this fuzzy equi- join and derive the necessary condition for the fuzzy functional dependencies to be preserved on joining the decomposed fuzzy relations. We also derive the conditions for fuzzy join dependency to exist in context of both type-1 and type-2 fuzzy relational databases. We find that unlike the classical relational databases even the existence of a trivial join dependency does not ensure lossless join decomposition in type-2 fuzzy relational databases. Finally we derive the conditions for the fuzzy equality to be non zero and the qualification of an attribute for fuzzy key.

Keywords: Fuzzy - equi join, fuzzy functions, fuzzy join dependency, type-1 fuzzy relational database, type-2 fuzzy relational database.

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Authors: Shaun Cox, Michael Oakes, Stefan Wermter, Maurice Hawthorne

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We report on the results of a pilot study in which a data-mining tool was developed for mining audiology records. The records were heterogeneous in that they contained numeric, category and textual data. The tools developed are designed to observe associations between any field in the records and any other field. The techniques employed were the statistical chi-squared test, and the use of self-organizing maps, an unsupervised neural learning approach.

Keywords: Audiology, data mining, chi-squared, self-organizing maps

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Authors: Miloš Šeda, Tomáš Březina

Abstract:

In this paper, we focus on the use of knowledge bases in two different application areas – control of systems with unknown or strongly nonlinear models (i.e. hardly controllable by the classical methods), and robot motion planning in eight directions. The first one deals with fuzzy logic and the paper presents approaches for setting and aggregating the rules of a knowledge base. Te second one is concentrated on a case-based reasoning strategy for finding the path in a planar scene with obstacles.

Keywords: fuzzy controller, fuzzification, rule base, inference, defuzzification, genetic algorithm, neural network, case-based reasoning

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Authors: Anil Ranjitbhai Patel, Clement John Shaji, Peter Liggesmeyer

Abstract:

Safety and security of Autonomous Vehicles (AVs) is a growing concern, first, due to the increased number of safety-critical functions taken over by automotive embedded systems; second, due to the increased exposure of the software-intensive systems to potential attackers; third, due to dynamic interaction in an uncertain and unknown environment at runtime which results in changed functional and non-functional properties of the system. Frequently occurring environmental uncertainties, random component failures, and compromise security of the AVs might result in hazardous events, sometimes even in an accident, if left undetected. Beyond these technical issues, we argue that the safety and security of AVs against accidental and deliberate faults are poorly understood and rarely implemented. One possible way to overcome this is through a well-known diversity approach. As an effective approach to increase safety and security, diversity has been widely used in the aviation, railway, and aerospace industries. Thus, paper proposes fault-tolerance by diversity model taking into consideration the mitigation of accidental and deliberate faults by application of structure and variant redundancy. The model can be used to design the AVs with various types of diversity in hardware and software-based multi-version system. The paper evaluates the presented approach by employing an example from adaptive cruise control, followed by discussing the case study with initial findings.

Keywords: Autonomous vehicles, diversity, fault-tolerance, adaptive cruise control, safety, security.

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Authors: Sahar S. Tabrizi, Dogan Ibrahim

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Cloud Computing is a convenient model for on-demand networks that uses shared pools of virtual configurable computing resources, such as servers, networks, storage devices, applications, etc. The cloud serves as an environment for companies and organizations to use infrastructure resources without making any purchases and they can access such resources wherever and whenever they need. Cloud computing is useful to overcome a number of problems in various Information Technology (IT) domains such as Geographical Information Systems (GIS), Scientific Research, e-Governance Systems, Decision Support Systems, ERP, Web Application Development, Mobile Technology, etc. Companies can use Cloud Computing services to store large amounts of data that can be accessed from anywhere on Earth and also at any time. Such services are rented by the client companies where the actual rent depends upon the amount of data stored on the cloud and also the amount of processing power used in a given time period. The resources offered by the cloud service companies are flexible in the sense that the user companies can increase or decrease their storage requirements or the processing power requirements at any time, thus minimizing the overall rental cost of the service they receive. In addition, the Cloud Computing service providers offer fast processors and applications software that can be shared by their clients. This is especially important for small companies with limited budgets which cannot afford to purchase their own expensive hardware and software. This paper is an overview of the Cloud Computing, giving its types, principles, advantages, and disadvantages. In addition, the paper gives some example engineering applications of Cloud Computing and makes suggestions for possible future applications in the field of engineering.

Keywords: Cloud computing, cloud services, IaaS, PaaS, SaaS, IoT.

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Authors: Melvin Chan, Chew Lee Teo

Abstract:

There has been a growing emphasis in elevating the teachers’ proficiency and competencies through continuing professional development (CPD) opportunities. In this era of a Volatile, Uncertain, Complex, Ambiguous (VUCA) world, teachers are expected to be collaborative designers, critical thinkers and creative builders. However, many of the CPD structures are still revolving in the model of transmission, which stands in contradiction to the cultivation of future-ready teachers for the innovative world of emerging technologies. This article puts forward the framing of CPD through a Principle-Based, Technological-Driven Knowledge Building Approach grounded in the essence of andragogy and progressive learning theories where growth is best exemplified through an authentic immersion in a social/community experience-based setting. Putting this Knowledge Building Professional Development Model (KBPDM) in operation via a Professional Learning Team (PLT) situated in a Secondary School in Singapore, research findings reveal that the intervention has led to a fundamental change in the learning paradigm of the teachers, henceforth equipping and empowering them successfully in their pedagogical design and practices for a 21^st century classroom experience. This article concludes with the possibility in leveraging the Learning Analytics to deepen the CPD experiences for educators.

Keywords: Continual professional development, knowledge building, learning paradigm, andragogy.

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Authors: R. Barbour

Abstract:

Peace-building organisations act as a network of information for communities. Through fieldwork, it was highlighted that grassroots organisations and activists may cooperate with each other in their actions of peace-building; however, they would not collaborate. Within two divided societies; Nicosia in Cyprus and Jerusalem in Israel, there is a distinction made by organisations and activists with regards to activities being more ‘co-operative’ than ‘collaborative’. This theme became apparent when having informal conversations and semi-structured interviews with various members of the activist communities. This idea needs further exploration as these distinctions could impact upon the efficiency of peacebuilding activities within divided societies. Civil societies within divided landscapes, both physically and socially, play an important role in conflict resolution. How organisations and activists interact with each other has the possibility to be very influential with regards to peacebuilding activities. Working together sets a positive example for divided communities. Cooperation may be considered a primary level of interaction between CSOs. Therefore, at the beginning of a working relationship, organisations cooperate over basic agendas, parallel power structures and focus, which led to the same objective. Over time, in some instances, due to varying factors such as funding, more trust and understanding within the relationship, it could be seen that processes progressed to more collaborative ways. It is evident to see that NGOs and activist groups are highly independent and focus on their own agendas before coming together over shared issues. At this time, there appears to be more collaboration in Nicosia among CSOs and activists than Jerusalem. The aims and objectives of agendas also influence how organisations work together. In recent years, Nicosia, and Cyprus in general, have perhaps changed their focus from peace-building initiatives to more environmental issues which have become new-age reconciliation topics. Civil society does not automatically indicate like-minded organisations however solidarity within social groups can create ties that bring people and resources together. In unequal societies, such as those in Nicosia and Jerusalem, it is these ties that cut across groups and are essential for social cohesion. Societies are a collection of social groups; individuals who have come together over common beliefs. These groups in turn shape the identities and determine the values and structures within societies. At many different levels and stages, social groups work together through cooperation and collaboration. These structures in turn have the capabilities to open up networks to less powerful or excluded groups, with the aim to produce social cohesion which may contribute social stability and economic welfare over any extended period.

Keywords: Collaboration, cooperation, grassroots activism, networks of communication.

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