Search results for: mapping algorithm
4396 Critical Appraisal of Different Drought Indices of Drought Predection and Their Application in KBK Districts of Odisha
Authors: Bibhuti Bhusan Sahoo, Ramakar Jha
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Mapping of the extreme events (droughts) is one of the adaptation strategies to consequences of increasing climatic inconsistency and climate alterations. There is no operational practice to forecast the drought. One of the suggestions is to update mapping of drought prone areas for developmental planning. Drought indices play a significant role in drought mitigation. Many scientists have worked on different statistical analysis in drought and other climatological hazards. Many researchers have studied droughts individually for different sub-divisions or for India. Very few workers have studied district wise probabilities over large scale. In the present study, district wise drought probabilities over KBK (Kalahandi-Balangir-Koraput) districts of Odisha, India, Which are seriously prone to droughts, has been established using Hydrological drought index and Meteorological drought index along with the remote sensing drought indices to develop a multidirectional approach in the field of drought mitigation. Mapping for moderate and severe drought probabilities for KBK districts has been done and regions belonging different class intervals of probabilities of drought have been demarcated. Such type of information would be a good tool for planning purposes, for input in modelling and better promising results can be achieved.Keywords: drought indices, KBK districts, proposed drought severity index, SPI
Procedia PDF Downloads 4494395 An Algorithm of Regulation of Glucose-Insulin Concentration in the Blood
Authors: B. Selma, S. Chouraqui
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The pancreas is an elongated organ that extends across the abdomen, below the stomach. In addition, it secretes certain enzymes that aid in food digestion. The pancreas also manufactures hormones responsible for regulating blood glucose levels. In the present paper, we propose a mathematical model to study the homeostasis of glucose and insulin in healthy human, and a simulation of this model, which depicts the physiological events after a meal, will be represented in ordinary humans. The aim of this paper is to design an algorithm which regulates the level of glucose in the blood. The algorithm applied the concept of expert system for performing an algorithm control in the form of an "active" used to prescribe the rate of insulin infusion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. The results showed a performance of the control system.Keywords: modeling, algorithm, regulation, glucose-insulin, blood, control system
Procedia PDF Downloads 1774394 Using Mind Mapping and Morphological Analysis within a New Methodology for Teaching Students of Products’ Design
Authors: Kareem Saber
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Many products’ design instructors search for how to help students to develop their designs simply by reducing design stages and extrapolating simple design process forms to achieve design creativity. So, the researcher extrapolated a new design process form called “hierarchical design” which reduced design process into three stages and he had tried that methodology on about two hundred students. That trial had led to great results as students could develop their designs which characterized by creativity and innovation. That proved the success and effectiveness of the proposed methodology.Keywords: mind mapping, morphological analysis, product design, design process
Procedia PDF Downloads 1784393 Power Allocation Algorithm for Orthogonal Frequency Division Multiplexing Based Cognitive Radio Networks
Authors: Bircan Demiral
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Cognitive radio (CR) is the promising technology that addresses the spectrum scarcity problem for future wireless communications. Orthogonal Frequency Division Multiplexing (OFDM) technology provides more power band ratios for cognitive radio networks (CRNs). While CR is a solution to the spectrum scarcity, it also brings up the capacity problem. In this paper, a novel power allocation algorithm that aims at maximizing the sum capacity in the OFDM based cognitive radio networks is proposed. Proposed allocation algorithm is based on the previously developed water-filling algorithm. To reduce the computational complexity calculating in water filling algorithm, proposed algorithm allocates the total power according to each subcarrier. The power allocated to the subcarriers increases sum capacity. To see this increase, Matlab program was used, and the proposed power allocation was compared with average power allocation, water filling and general power allocation algorithms. The water filling algorithm performed worse than the proposed algorithm while it performed better than the other two algorithms. The proposed algorithm is better than other algorithms in terms of capacity increase. In addition the effect of the change in the number of subcarriers on capacity was discussed. Simulation results show that the increase in the number of subcarrier increases the capacity.Keywords: cognitive radio network, OFDM, power allocation, water filling
Procedia PDF Downloads 1374392 Topographic Mapping of Farmland by Integration of Multiple Sensors on Board Low-Altitude Unmanned Aerial System
Authors: Mengmeng Du, Noboru Noguchi, Hiroshi Okamoto, Noriko Kobayashi
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This paper introduced a topographic mapping system with time-saving and simplicity advantages based on integration of Light Detection and Ranging (LiDAR) data and Post Processing Kinematic Global Positioning System (PPK GPS) data. This topographic mapping system used a low-altitude Unmanned Aerial Vehicle (UAV) as a platform to conduct land survey in a low-cost, efficient, and totally autonomous manner. An experiment in a small-scale sugarcane farmland was conducted in Queensland, Australia. Subsequently, we synchronized LiDAR distance measurements that were corrected by using attitude information from gyroscope with PPK GPS coordinates for generation of precision topographic maps, which could be further utilized for such applications like precise land leveling and drainage management. The results indicated that LiDAR distance measurements and PPK GPS altitude reached good accuracy of less than 0.015 m.Keywords: land survey, light detection and ranging, post processing kinematic global positioning system, precision agriculture, topographic map, unmanned aerial vehicle
Procedia PDF Downloads 2364391 Multi-Objective Variable Neighborhood Search Algorithm to Solving Scheduling Problem with Transportation Times
Authors: Majid Khalili
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This paper deals with a bi-objective hybrid no-wait flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which we consider transportation times between stages. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. This paper presents a new multi-objective variable neighborhood algorithm (MOVNS). A set of experimental instances are carried out to evaluate the algorithm by advanced multi-objective performance measures. The algorithm is carefully evaluated for its performance against available algorithm by means of multi-objective performance measures and statistical tools. The related results show that a variant of our proposed MOVNS provides sound performance comparing with other algorithms. Procedia PDF Downloads 4184390 Simulation of 3-D Direction-of-Arrival Estimation Using MUSIC Algorithm
Authors: Duckyong Kim, Jong Kang Park, Jong Tae Kim
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DOA (Direction of Arrival) estimation is an important method in array signal processing and has a wide range of applications such as direction finding, beam forming, and so on. In this paper, we briefly introduce the MUSIC (Multiple Signal Classification) Algorithm, one of DOA estimation methods for analyzing several targets. Then we apply the MUSIC algorithm to the two-dimensional antenna array to analyze DOA estimation in 3D space through MATLAB simulation. We also analyze the design factors that can affect the accuracy of DOA estimation through simulation, and proceed with further consideration on how to apply the system.Keywords: DOA estimation, MUSIC algorithm, spatial spectrum, array signal processing
Procedia PDF Downloads 3794389 Assessing the Risk of Pressure Injury during Percutaneous Nephrolithotomy Using Pressure Mapping
Authors: Jake Tempo, Taylor Smithurst, Jen Leah, Skye Waddingham, Amanda Catlin, Richard Cetti
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Introduction: Percutaneous nephrolithotomy (PCNL) is the gold-standard procedure for removing large or complex renal stones. Many operating positions can be used, and the debate over the ideal position continues. PCNL can be a long procedure during which patients can sustain pressure injuries. These injuries are often underreported in the literature. Interface pressure mapping records the pressure loading between a surface and the patient. High pressures with prolonged loading result in ischaemia, muscle deformation, and reperfusion which can cause skin breakdown and muscular injury. We compared the peak pressure indexes of common PCNL positions to identify positions which may be at high risk of pressure injuries. We hope the data can be used to adapt high-risk positions so that the PPI can be lessened by either adapting the positions or by using adjuncts to lower PPI. Materials and Methods: We placed a 23-year-old male subject in fourteen different PCNL positions while performing interface pressure mapping. The subject was 179 cm with a weight of 63.3 kg, BMI 19.8kg/m². Results: Supine positions had a higher mean PPI (119mmHg (41-137)) compared to prone positions (64mmHg (32-89)) (p=0.046 two tailed t-test). The supine flexed position with a bolster under the flank produced the highest PPI (194mmHg), and this was at the sacrum. Peak pressure indexes >100mmHg were recorded in eight PCNL positions. Conclusion: Supine PCNL positions produce higher PPI than prone PCNL positions. Our study shows where ‘at risk’ bony prominences are for each PCNL position. Surgeons must ensure these areas are protected during prolonged operations.Keywords: PCNL, pressure ulcer, interface pressure mapping, surgery
Procedia PDF Downloads 834388 Weak Convergence of Mann Iteration for a Hybrid Pair of Mappings in a Banach Space
Authors: Alemayehu Geremew Geremew
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We prove the weak convergence of Mann iteration for a hybrid pair of maps to a common fixed point of a selfmap f and a multivalued f nonexpansive mapping T in Banach space E.Keywords: common fixed point, Mann iteration, multivalued mapping, weak convergence
Procedia PDF Downloads 3354387 Part of Speech Tagging Using Statistical Approach for Nepali Text
Authors: Archit Yajnik
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Part of Speech Tagging has always been a challenging task in the era of Natural Language Processing. This article presents POS tagging for Nepali text using Hidden Markov Model and Viterbi algorithm. From the Nepali text, annotated corpus training and testing data set are randomly separated. Both methods are employed on the data sets. Viterbi algorithm is found to be computationally faster and accurate as compared to HMM. The accuracy of 95.43% is achieved using Viterbi algorithm. Error analysis where the mismatches took place is elaborately discussed.Keywords: hidden markov model, natural language processing, POS tagging, viterbi algorithm
Procedia PDF Downloads 3274386 Implementation of Iterative Algorithm for Earthquake Location
Authors: Hussain K. Chaiel
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The development in the field of the digital signal processing (DSP) and the microelectronics technology reduces the complexity of the iterative algorithms that need large number of arithmetic operations. Virtex-Field Programmable Gate Arrays (FPGAs) are programmable silicon foundations which offer an important solution for addressing the needs of high performance DSP designer. In this work, Virtex-7 FPGA technology is used to implement an iterative algorithm to estimate the earthquake location. Simulation results show that an implementation based on block RAMB36E1 and DSP48E1 slices of Virtex-7 type reduces the number of cycles of the clock frequency. This enables the algorithm to be used for earthquake prediction.Keywords: DSP, earthquake, FPGA, iterative algorithm
Procedia PDF Downloads 3894385 Alternative Key Exchange Algorithm Based on Elliptic Curve Digital Signature Algorithm Certificate and Usage in Applications
Authors: A. Andreasyan, C. Connors
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The Elliptic Curve Digital Signature algorithm-based X509v3 certificates are becoming more popular due to their short public and private key sizes. Moreover, these certificates can be stored in Internet of Things (IoT) devices, with limited resources, using less memory and transmitted in network security protocols, such as Internet Key Exchange (IKE), Transport Layer Security (TLS) and Secure Shell (SSH) with less bandwidth. The proposed method gives another advantage, in that it increases the performance of the above-mentioned protocols in terms of key exchange by saving one scalar multiplication operation.Keywords: cryptography, elliptic curve digital signature algorithm, key exchange, network security protocol
Procedia PDF Downloads 1464384 Hybrid Gravity Gradient Inversion-Ant Colony Optimization Algorithm for Motion Planning of Mobile Robots
Authors: Meng Wu
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Motion planning is a common task required to be fulfilled by robots. A strategy combining Ant Colony Optimization (ACO) and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. In this paper, in order to realize optimal motion planning strategy, the cost function in ACO is designed based on gravity gradient inversion algorithm. The obstacles around mobile robot can cause gravity gradient anomalies; the gradiometer is installed on the mobile robot to detect the gravity gradient anomalies. After obtaining the anomalies, gravity gradient inversion algorithm is employed to calculate relative distance and orientation between mobile robot and obstacles. The relative distance and orientation deduced from gravity gradient inversion algorithm is employed as cost function in ACO algorithm to realize motion planning. The proposed strategy is validated by the simulation and experiment results.Keywords: motion planning, gravity gradient inversion algorithm, ant colony optimization
Procedia PDF Downloads 1374383 Mapping Methods to Solve a Modified Korteweg de Vries Type Equation
Authors: E. V. Krishnan
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In this paper, we employ mapping methods to construct exact travelling wave solutions for a modified Korteweg-de Vries equation. We have derived periodic wave solutions in terms of Jacobi elliptic functions, kink solutions and singular wave solutions in terms of hyperbolic functions.Keywords: travelling wave solutions, Jacobi elliptic functions, solitary wave solutions, Korteweg-de Vries equation
Procedia PDF Downloads 3314382 Penguins Search Optimization Algorithm for Chaotic Synchronization System
Authors: Sofiane Bououden, Ilyes Boulkaibet
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In terms of security of the information signal, the meta-heuristic Penguins Search Optimization Algorithm (PeSOA) is applied to synchronize chaotic encryption communications in the case of sensitive dependence on initial conditions in chaotic generator oscillator. The objective of this paper is the use of the PeSOA algorithm to exploring search space with random and iterative processes for synchronization of symmetric keys in both transmission and reception. Simulation results show the effectiveness of the PeSOA algorithm in generating symmetric keys of the encryption process and synchronizing.Keywords: meta-heuristic, PeSOA, chaotic systems, encryption, synchronization optimization
Procedia PDF Downloads 1954381 Comparative Study of Accuracy of Land Cover/Land Use Mapping Using Medium Resolution Satellite Imagery: A Case Study
Authors: M. C. Paliwal, A. K. Jain, S. K. Katiyar
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Classification of satellite imagery is very important for the assessment of its accuracy. In order to determine the accuracy of the classified image, usually the assumed-true data are derived from ground truth data using Global Positioning System. The data collected from satellite imagery and ground truth data is then compared to find out the accuracy of data and error matrices are prepared. Overall and individual accuracies are calculated using different methods. The study illustrates advanced classification and accuracy assessment of land use/land cover mapping using satellite imagery. IRS-1C-LISS IV data were used for classification of satellite imagery. The satellite image was classified using the software in fourteen classes namely water bodies, agricultural fields, forest land, urban settlement, barren land and unclassified area etc. Classification of satellite imagery and calculation of accuracy was done by using ERDAS-Imagine software to find out the best method. This study is based on the data collected for Bhopal city boundaries of Madhya Pradesh State of India.Keywords: resolution, accuracy assessment, land use mapping, satellite imagery, ground truth data, error matrices
Procedia PDF Downloads 5074380 A Genetic Algorithm Based Permutation and Non-Permutation Scheduling Heuristics for Finite Capacity Material Requirement Planning Problem
Authors: Watchara Songserm, Teeradej Wuttipornpun
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This paper presents a genetic algorithm based permutation and non-permutation scheduling heuristics (GAPNP) to solve a multi-stage finite capacity material requirement planning (FCMRP) problem in automotive assembly flow shop with unrelated parallel machines. In the algorithm, the sequences of orders are iteratively improved by the GA characteristics, whereas the required operations are scheduled based on the presented permutation and non-permutation heuristics. Finally, a linear programming is applied to minimize the total cost. The presented GAPNP algorithm is evaluated by using real datasets from automotive companies. The required parameters for GAPNP are intently tuned to obtain a common parameter setting for all case studies. The results show that GAPNP significantly outperforms the benchmark algorithm about 30% on average.Keywords: capacitated MRP, genetic algorithm, linear programming, automotive industries, flow shop, application in industry
Procedia PDF Downloads 4894379 Hyperspectral Image Classification Using Tree Search Algorithm
Authors: Shreya Pare, Parvin Akhter
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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm
Procedia PDF Downloads 1774378 Consumer Load Profile Determination with Entropy-Based K-Means Algorithm
Authors: Ioannis P. Panapakidis, Marios N. Moschakis
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With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.Keywords: clustering, load profiling, load modeling, machine learning, energy efficiency and quality
Procedia PDF Downloads 1644377 Mobility-Aware Relay Selection in Two Hop Unmanned Aerial Vehicles Network
Authors: Tayyaba Hussain, Sobia Jangsher, Saqib Ali, Saqib Ejaz
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Unmanned Aerial vehicles (UAV’s) have gained great popularity due to their remoteness, ease of deployment and high maneuverability in different applications like real-time surveillance, image capturing, weather atmospheric studies, disaster site monitoring and mapping. These applications can involve a real-time communication with the ground station. However, altitude and mobility possess a few challenges for the communication. UAV’s at high altitude usually require more transmit power. One possible solution can be with the use of multi hops (UAV’s acting as relays) and exploiting the mobility pattern of the UAV’s. In this paper, we studied a relay (UAV’s acting as relays) selection for a reliable transmission to a destination UAV. We exploit the mobility information of the UAV’s to propose a Mobility-Aware Relay Selection (MARS) algorithm with the objective of giving improved data rates. The results are compared with Non Mobility-Aware relay selection scheme and optimal values. Numerical results show that our proposed MARS algorithm gives 6% better achievable data rates for the mobile UAV’s as compared with Non MobilityAware relay selection scheme. On average a decrease of 20.2% in data rate is achieved with MARS as compared with SDP solver in Yalmip.Keywords: mobility aware, relay selection, time division multiple acess, unmanned aerial vehicle
Procedia PDF Downloads 2384376 Forward Stable Computation of Roots of Real Polynomials with Only Real Distinct Roots
Authors: Nevena Jakovčević Stor, Ivan Slapničar
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Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy
Procedia PDF Downloads 4174375 Mapping of Siltations of AlKhod Dam, Muscat, Sultanate of Oman Using Low-Cost Multispectral Satellite Data
Authors: Sankaran Rajendran
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Remote sensing plays a vital role in mapping of resources and monitoring of environments of the earth. In the present research study, mapping and monitoring of clay siltations occurred in the Alkhod Dam of Muscat, Sultanate of Oman are carried out using low-cost multispectral Landsat and ASTER data. The dam is constructed across the Wadi Samail catchment for ground water recharge. The occurrence and spatial distribution of siltations in the dam are studied with five years of interval from the year 1987 of construction to 2014. The deposits are mainly due to the clay, sand, and silt occurrences derived from the weathering rocks of ophiolite sequences occurred in the Wadi Samail catchment. The occurrences of clays are confirmed by minerals identification using ASTER VNIR-SWIR spectral bands and Spectral Angle Mapper supervised image processing method. The presence of clays and their spatial distribution are verified in the field. The study recommends the technique and the low-cost satellite data to similar region of the world.Keywords: Alkhod Dam, ASTER siltation, Landsat, remote sensing, Oman
Procedia PDF Downloads 4374374 A Hybrid Pareto-Based Swarm Optimization Algorithm for the Multi-Objective Flexible Job Shop Scheduling Problems
Authors: Aydin Teymourifar, Gurkan Ozturk
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In this paper, a new hybrid particle swarm optimization algorithm is proposed for the multi-objective flexible job shop scheduling problem that is very important and hard combinatorial problem. The Pareto approach is used for solving the multi-objective problem. Several new local search heuristics are integrated into an algorithm based on the critical block concept to enhance the performance of the algorithm. The algorithm is compared with the recently published multi-objective algorithms based on benchmarks selected from the literature. Several metrics are used for quantifying performance and comparison of the achieved solutions. The algorithms are also compared based on the Weighting summation of objectives approach. The proposed algorithm can find the Pareto solutions more efficiently than the compared algorithms in less computational time.Keywords: swarm-based optimization, local search, Pareto optimality, flexible job shop scheduling, multi-objective optimization
Procedia PDF Downloads 3684373 High-Resolution Facial Electromyography in Freely Behaving Humans
Authors: Lilah Inzelberg, David Rand, Stanislav Steinberg, Moshe David Pur, Yael Hanein
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Human facial expressions carry important psychological and neurological information. Facial expressions involve the co-activation of diverse muscles. They depend strongly on personal affective interpretation and on social context and vary between spontaneous and voluntary activations. Smiling, as a special case, is among the most complex facial emotional expressions, involving no fewer than 7 different unilateral muscles. Despite their ubiquitous nature, smiles remain an elusive and debated topic. Smiles are associated with happiness and greeting on one hand and anger or disgust-masking on the other. Accordingly, while high-resolution recording of muscle activation patterns, in a non-interfering setting, offers exciting opportunities, it remains an unmet challenge, as contemporary surface facial electromyography (EMG) methodologies are cumbersome, restricted to the laboratory settings, and are limited in time and resolution. Here we present a wearable and non-invasive method for objective mapping of facial muscle activation and demonstrate its application in a natural setting. The technology is based on a recently developed dry and soft electrode array, specially designed for surface facial EMG technique. Eighteen healthy volunteers (31.58 ± 3.41 years, 13 females), participated in the study. Surface EMG arrays were adhered to participant left and right cheeks. Participants were instructed to imitate three facial expressions: closing the eyes, wrinkling the nose and smiling voluntary and to watch a funny video while their EMG signal is recorded. We focused on muscles associated with 'enjoyment', 'social' and 'masked' smiles; three categories with distinct social meanings. We developed a customized independent component analysis algorithm to construct the desired facial musculature mapping. First, identification of the Orbicularis oculi and the Levator labii superioris muscles was demonstrated from voluntary expressions. Second, recordings of voluntary and spontaneous smiles were used to locate the Zygomaticus major muscle activated in Duchenne and non-Duchenne smiles. Finally, recording with a wireless device in an unmodified natural work setting revealed expressions of neutral, positive and negative emotions in face-to-face interaction. The algorithm outlined here identifies the activation sources in a subject-specific manner, insensitive to electrode placement and anatomical diversity. Our high-resolution and cross-talk free mapping performances, along with excellent user convenience, open new opportunities for affective processing and objective evaluation of facial expressivity, objective psychological and neurological assessment as well as gaming, virtual reality, bio-feedback and brain-machine interface applications.Keywords: affective expressions, affective processing, facial EMG, high-resolution electromyography, independent component analysis, wireless electrodes
Procedia PDF Downloads 2464372 An Improved Method to Compute Sparse Graphs for Traveling Salesman Problem
Authors: Y. Wang
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The Traveling salesman problem (TSP) is NP-hard in combinatorial optimization. The research shows the algorithms for TSP on the sparse graphs have the shorter computation time than those for TSP according to the complete graphs. We present an improved iterative algorithm to compute the sparse graphs for TSP by frequency graphs computed with frequency quadrilaterals. The iterative algorithm is enhanced by adjusting two parameters of the algorithm. The computation time of the algorithm is O(CNmaxn2) where C is the iterations, Nmax is the maximum number of frequency quadrilaterals containing each edge and n is the scale of TSP. The experimental results showed the computed sparse graphs generally have less than 5n edges for most of these Euclidean instances. Moreover, the maximum degree and minimum degree of the vertices in the sparse graphs do not have much difference. Thus, the computation time of the methods to resolve the TSP on these sparse graphs will be greatly reduced.Keywords: frequency quadrilateral, iterative algorithm, sparse graph, traveling salesman problem
Procedia PDF Downloads 2334371 A Multidimensional Genetic Algorithm Applicable for Our VRP Variant Dealing with the Problems of Infrastructure Defaults SVRDP-CMTW: “Safety Vehicle Routing Diagnosis Problem with Control and Modified Time Windows”
Authors: Ben Mansour Mouin, Elloumi Abdelkarim
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We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics
Procedia PDF Downloads 1964370 Contribution of Spatial Teledetection to the Geological Mapping of the Imiter Buttonhole: Application to the Mineralized Structures of the Principal Corps B3 (CPB3) of the Imiter Mine (Anti-atlas, Morocco)
Authors: Bouayachi Ali, Alikouss Saida, Baroudi Zouhir, Zerhouni Youssef, Zouhair Mohammed, El Idrissi Assia, Essalhi Mourad
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The world-class Imiter silver deposit is located on the northern flank of the Precambrian Imiter buttonhole. This deposit is formed by epithermal veins hosted in the sandstone-pelite formations of the lower complex and in the basic conglomerates of the upper complex, these veins are controlled by a regional scale fault cluster, oriented N70°E to N90°E. The present work on the contribution of remote sensing on the geological mapping of the Imiter buttonhole and application to the mineralized structures of the Principal Corps B3. Mapping on satellite images is a very important tool in mineral prospecting. It allows the localization of the zones of interest in order to orientate the field missions by helping the localization of the major structures which facilitates the interpretation, the programming and the orientation of the mining works. The predictive map also allows for the correction of field mapping work, especially the direction and dimensions of structures such as dykes, corridors or scrapings. The use of a series of processing such as SAM, PCA, MNF and unsupervised and supervised classification on a Landsat 8 satellite image of the study area allowed us to highlight the main facies of the Imite area. To improve the exploration research, we used another processing that allows to realize a spatial distribution of the alteration mineral indices, and the application of several filters on the different bands to have lineament maps.Keywords: principal corps B3, teledetection, Landsat 8, Imiter II, silver mineralization, lineaments
Procedia PDF Downloads 954369 Track Initiation Method Based on Multi-Algorithm Fusion Learning of 1DCNN And Bi-LSTM
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Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method.Keywords: track initiation, multi-algorithm fusion, 1DCNN, Bi-LSTM
Procedia PDF Downloads 944368 Genetic Algorithm Optimization of Microcantilever Based Resonator
Authors: Manjula Sutagundar, B. G. Sheeparamatti, D. S. Jangamshetti
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Micro Electro Mechanical Systems (MEMS) resonators have shown the potential of replacing quartz crystal technology for sensing and high frequency signal processing applications because of inherent advantages like small size, high quality factor, low cost, compatibility with integrated circuit chips. This paper presents the optimization and modelling and simulation of the optimized micro cantilever resonator. The objective of the work is to optimize the dimensions of a micro cantilever resonator for a specified range of resonant frequency and specific quality factor. Optimization is carried out using genetic algorithm. The genetic algorithm is implemented using MATLAB. The micro cantilever resonator is modelled in CoventorWare using the optimized dimensions obtained from genetic algorithm. The modeled cantilever is analysed for resonance frequency.Keywords: MEMS resonator, genetic algorithm, modelling and simulation, optimization
Procedia PDF Downloads 5504367 A Variable Incremental Conductance MPPT Algorithm Applied to Photovoltaic Water Pumping System
Authors: Sarah Abdourraziq, Rachid Elbachtiri
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The use of solar energy as a source for pumping water is one of the promising areas in the photovoltaic (PV) application. The energy of photovoltaic pumping systems (PVPS) can be widely improved by employing an MPPT algorithm. This will lead consequently to maximize the electrical motor speed of the system. This paper presents a modified incremental conductance (IncCond) MPPT algorithm with direct control method applied to a standalone PV pumping system. The influence of the algorithm parameters on system behavior is investigated and compared with the traditional (INC) method. The studied system consists of a PV panel, a DC-DC boost converter, and a PMDC motor-pump. The simulation of the system by MATLAB-SIMULINK is carried out. Simulation results found are satisfactory.Keywords: photovoltaic pumping system (PVPS), incremental conductance (INC), MPPT algorithm, boost converter
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