Search results for: image encryption algorithms
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4603

Search results for: image encryption algorithms

1783 Modified Bat Algorithm for Economic Load Dispatch Problem

Authors: Daljinder Singh, J.S.Dhillon, Balraj Singh

Abstract:

According to no free lunch theorem, a single search technique cannot perform best in all conditions. Optimization method can be attractive choice to solve optimization problem that may have exclusive advantages like robust and reliable performance, global search capability, little information requirement, ease of implementation, parallelism, no requirement of differentiable and continuous objective function. In order to synergize between exploration and exploitation and to further enhance the performance of Bat algorithm, the paper proposed a modified bat algorithm that adds additional search procedure based on bat’s previous experience. The proposed algorithm is used for solving the economic load dispatch (ELD) problem. The practical constraint such valve-point loading along with power balance constraints and generator limit are undertaken. To take care of power demand constraint variable elimination method is exploited. The proposed algorithm is tested on various ELD problems. The results obtained show that the proposed algorithm is capable of performing better in majority of ELD problems considered and is at par with existing algorithms for some of problems.

Keywords: bat algorithm, economic load dispatch, penalty method, variable elimination method

Procedia PDF Downloads 456
1782 Using Jumping Particle Swarm Optimization for Optimal Operation of Pump in Water Distribution Networks

Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

Abstract:

Carefully scheduling the operations of pumps can be resulted to significant energy savings. Schedules can be defined either implicit, in terms of other elements of the network such as tank levels, or explicit by specifying the time during which each pump is on/off. In this study, two new explicit representations based on time-controlled triggers were analyzed, where the maximum number of pump switches was established beforehand, and the schedule may contain fewer switches than the maximum. The optimal operation of pumping stations was determined using a Jumping Particle Swarm Optimization (JPSO) algorithm to achieve the minimum energy cost. The model integrates JPSO optimizer and EPANET hydraulic network solver. The optimal pump operation schedule of VanZyl water distribution system was determined using the proposed model and compared with those from Genetic and Ant Colony algorithms. The results indicate that the proposed model utilizing the JPSP algorithm outperformed the others and is a versatile management model for the operation of real-world water distribution system.

Keywords: JPSO, operation, optimization, water distribution system

Procedia PDF Downloads 240
1781 A New Learning Automata-Based Algorithm to the Priority-Based Target Coverage Problem in Directional Sensor Networks

Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

Abstract:

Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

Procedia PDF Downloads 407
1780 Approaches to Promote Healthy Recreation Activities for Elderly Tourists at Bang Nam Phueng Floating Market, Prapradeang District, Samutprakarn Province

Authors: Sasitorn Chetanont

Abstract:

The objectives of this study are to find out the approaches to promote healthy recreation activities for elderly tourists and develop Bang Nam Phueng Floating Market to be a health tourism attraction. The research methodology was to analyze internal and external situations according to MP-MF and the MC-STEPS principles. As for the results of this study the researcher found that the healthy recreational activities for elderly tourists could be divided in 7 groups; travelling Bang Nam Phueng Floating Market activity, homestay relaxation, arts center platform activity, healthy massage activity, paying homage to a Buddha image activity, herbal joss-stick home activity, making local desserts and food activity.

Keywords: elderly tourists, recreation activities, Bang Nam Phueng Floating Market, health tourism

Procedia PDF Downloads 414
1779 Approximating Maximum Speed on Road from Curvature Information of Bezier Curve

Authors: M. Yushalify Misro, Ahmad Ramli, Jamaludin M. Ali

Abstract:

Bezier curves have useful properties for path generation problem, for instance, it can generate the reference trajectory for vehicles to satisfy the path constraints. Both algorithms join cubic Bezier curve segment smoothly to generate the path. Some of the useful properties of Bezier are curvature. In mathematics, the curvature is the amount by which a geometric object deviates from being flat, or straight in the case of a line. Another extrinsic example of curvature is a circle, where the curvature is equal to the reciprocal of its radius at any point on the circle. The smaller the radius, the higher the curvature thus the vehicle needs to bend sharply. In this study, we use Bezier curve to fit highway-like curve. We use the different approach to finding the best approximation for the curve so that it will resemble highway-like curve. We compute curvature value by analytical differentiation of the Bezier Curve. We will then compute the maximum speed for driving using the curvature information obtained. Our research works on some assumptions; first the Bezier curve estimates the real shape of the curve which can be verified visually. Even, though, the fitting process of Bezier curve does not interpolate exactly on the curve of interest, we believe that the estimation of speed is acceptable. We verified our result with the manual calculation of the curvature from the map.

Keywords: speed estimation, path constraints, reference trajectory, Bezier curve

Procedia PDF Downloads 371
1778 Reusing Assessments Tests by Generating Arborescent Test Groups Using a Genetic Algorithm

Authors: Ovidiu Domşa, Nicolae Bold

Abstract:

Using Information and Communication Technologies (ICT) notions in education and three basic processes of education (teaching, learning and assessment) can bring benefits to the pupils and the professional development of teachers. In this matter, we refer to these notions as concepts taken from the informatics area and apply them to the domain of education. These notions refer to genetic algorithms and arborescent structures, used in the specific process of assessment or evaluation. This paper uses these kinds of notions to generate subtrees from a main tree of tests related between them by their degree of difficulty. These subtrees must contain the highest number of connections between the nodes and the lowest number of missing edges (which are subtrees of the main tree) and, in the particular case of the non-existence of a subtree with no missing edges, the subtrees which have the lowest (minimal) number of missing edges between the nodes, where a node is a test and an edge is a direct connection between two tests which differs by one degree of difficulty. The subtrees are represented as sequences. The tests are the same (a number coding a test represents that test in every sequence) and they are reused for each sequence of tests.

Keywords: chromosome, genetic algorithm, subtree, test

Procedia PDF Downloads 321
1777 Quantitative Wide-Field Swept-Source Optical Coherence Tomography Angiography and Visual Outcomes in Retinal Artery Occlusion

Authors: Yifan Lu, Ying Cui, Ying Zhu, Edward S. Lu, Rebecca Zeng, Rohan Bajaj, Raviv Katz, Rongrong Le, Jay C. Wang, John B. Miller

Abstract:

Purpose: Retinal artery occlusion (RAO) is an ophthalmic emergency that can lead to poor visual outcome and is associated with an increased risk of cerebral stroke and cardiovascular events. Fluorescein angiography (FA) is the traditional diagnostic tool for RAO; however, wide-field swept-source optical coherence tomography angiography (WF SS-OCTA), as a nascent imaging technology, is able to provide quick and non-invasive angiographic information with a wide field of view. In this study, we looked for associations between OCT-A vascular metrics and visual acuity in patients with prior diagnosis of RAO. Methods: Patients with diagnoses of central retinal artery occlusion (CRAO) or branched retinal artery occlusion (BRAO) were included. A 6mm x 6mm Angio and a 15mm x 15mm AngioPlex Montage OCT-A image were obtained for both eyes in each patient using the Zeiss Plex Elite 9000 WF SS-OCTA device. Each 6mm x 6mm image was divided into nine Early Treatment Diabetic Retinopathy Study (ETDRS) subfields. The average measurement of the central foveal subfield, inner ring, and outer ring was calculated for each parameter. Non-perfusion area (NPA) was manually measured using 15mm x 15mm Montage images. A linear regression model was utilized to identify a correlation between the imaging metrics and visual acuity. A P-value less than 0.05 was considered to be statistically significant. Results: Twenty-five subjects were included in the study. For RAO eyes, there was a statistically significant negative correlation between vision and retinal thickness as well as superficial capillary plexus vessel density (SCP VD). A negative correlation was found between vision and deep capillary plexus vessel density (DCP VD) without statistical significance. There was a positive correlation between vision and choroidal thickness as well as choroidal volume without statistical significance. No statistically significant correlation was found between vision and the above metrics in contralateral eyes. For NPA measurements, no significant correlation was found between vision and NPA. Conclusions: This is the first study to our best knowledge to investigate the utility of WF SS-OCTA in RAO and to demonstrate correlations between various retinal vascular imaging metrics and visual outcomes. Further investigations should explore the associations between these imaging findings and cardiovascular risk as RAO patients are at elevated risk for symptomatic stroke. The results of this study provide a basis to understand the structural changes involved in visual outcomes in RAO. Furthermore, they may help guide management of RAO and prevention of cerebral stroke and cardiovascular accidents in patients with RAO.

Keywords: OCTA, swept-source OCT, retinal artery occlusion, Zeiss Plex Elite

Procedia PDF Downloads 134
1776 Path Planning for Multiple Unmanned Aerial Vehicles Based on Adaptive Probabilistic Sampling Algorithm

Authors: Long Cheng, Tong He, Iraj Mantegh, Wen-Fang Xie

Abstract:

Path planning is essential for UAVs (Unmanned Aerial Vehicle) with autonomous navigation in unknown environments. In this paper, an adaptive probabilistic sampling algorithm is proposed for the GPS-denied environment, which can be utilized for autonomous navigation system of multiple UAVs in a dynamically-changing structured environment. This method can be used for Unmanned Aircraft Systems Traffic Management (UTM) solutions and in autonomous urban aerial mobility, where a number of platforms are expected to share the airspace. A path network is initially built off line based on available environment map, and on-board sensors systems on the flying UAVs are used for continuous situational awareness and to inform the changes in the path network. Simulation results based on MATLAB and Gazebo in different scenarios and algorithms performance measurement show the high efficiency and accuracy of the proposed technique in unknown environments.

Keywords: path planning, adaptive probabilistic sampling, obstacle avoidance, multiple unmanned aerial vehicles, unknown environments

Procedia PDF Downloads 152
1775 Study for an Optimal Cable Connection within an Inner Grid of an Offshore Wind Farm

Authors: Je-Seok Shin, Wook-Won Kim, Jin-O Kim

Abstract:

The offshore wind farm needs to be designed carefully considering economics and reliability aspects. There are many decision-making problems for designing entire offshore wind farm, this paper focuses on an inner grid layout which means the connection between wind turbines as well as between wind turbines and an offshore substation. A methodology proposed in this paper determines the connections and the cable type for each connection section using K-clustering, minimum spanning tree and cable selection algorithms. And then, a cost evaluation is performed in terms of investment, power loss and reliability. Through the cost evaluation, an optimal layout of inner grid is determined so as to have the lowest total cost. In order to demonstrate the validity of the methodology, the case study is conducted on 240MW offshore wind farm, and the results show that it is helpful to design optimally offshore wind farm.

Keywords: offshore wind farm, optimal layout, k-clustering algorithm, minimum spanning algorithm, cable type selection, power loss cost, reliability cost

Procedia PDF Downloads 384
1774 Machine Learning-Driven Prediction of Cardiovascular Diseases: A Supervised Approach

Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

Abstract:

Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

Procedia PDF Downloads 32
1773 Comparative Analysis of Predictive Models for Customer Churn Prediction in the Telecommunication Industry

Authors: Deepika Christopher, Garima Anand

Abstract:

To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

Procedia PDF Downloads 53
1772 A Deep Learning-Based Pedestrian Trajectory Prediction Algorithm

Authors: Haozhe Xiang

Abstract:

With the rise of the Internet of Things era, intelligent products are gradually integrating into people's lives. Pedestrian trajectory prediction has become a key issue, which is crucial for the motion path planning of intelligent agents such as autonomous vehicles, robots, and drones. In the current technological context, deep learning technology is becoming increasingly sophisticated and gradually replacing traditional models. The pedestrian trajectory prediction algorithm combining neural networks and attention mechanisms has significantly improved prediction accuracy. Based on in-depth research on deep learning and pedestrian trajectory prediction algorithms, this article focuses on physical environment modeling and learning of historical trajectory time dependence. At the same time, social interaction between pedestrians and scene interaction between pedestrians and the environment were handled. An improved pedestrian trajectory prediction algorithm is proposed by analyzing the existing model architecture. With the help of these improvements, acceptable predicted trajectories were successfully obtained. Experiments on public datasets have demonstrated the algorithm's effectiveness and achieved acceptable results.

Keywords: deep learning, graph convolutional network, attention mechanism, LSTM

Procedia PDF Downloads 61
1771 N400 Investigation of Semantic Priming Effect to Symbolic Pictures in Text

Authors: Thomas Ousterhout

Abstract:

The purpose of this study was to investigate if incorporating meaningful pictures of gestures and facial expressions in short sentences of text could supplement the text with enough semantic information to produce and N400 effect when probe words incongruent to the picture were subsequently presented. Event-related potentials (ERPs) were recorded from a 14-channel commercial grade EEG headset while subjects performed congruent/incongruent reaction time discrimination tasks. Since pictures of meaningful gestures have been shown to be semantically processed in the brain in a similar manner as words are, it is believed that pictures will add supplementary information to text just as the inclusion of their equivalent synonymous word would. The hypothesis is that when subjects read the text/picture mixed sentences, they will process the images and words just like in face-to-face communication and therefore probe words incongruent to the image will produce an N400.

Keywords: EEG, ERP, N400, semantics, congruency, facilitation, Emotiv

Procedia PDF Downloads 252
1770 Travel Planning in Public Transport Networks Applying the Algorithm A* for Metropolitan District of Quito

Authors: M. Fernanda Salgado, Alfonso Tierra, Wilbert Aguilar

Abstract:

The present project consists in applying the informed search algorithm A star (A*) to solve traveler problems, applying it by urban public transportation routes. The digitization of the information allowed to identify 26% of the total of routes that are registered within the Metropolitan District of Quito. For the validation of this information, data were taken in field on the travel times and the difference with respect to the times estimated by the program, resulting in that the difference between them was not greater than 2:20 minutes. We validate A* algorithm with the Dijkstra algorithm, comparing nodes vectors based on the public transport stops, the validation was established through the student t-test hypothesis. Then we verified that the times estimated by the program using the A* algorithm are similar to those registered on field. Furthermore, we review the performance of the algorithm generating iterations in both algorithms. Finally, with these iterations, a hypothesis test was carried out again with student t-test where it was concluded that the iterations of the base algorithm Dijsktra are greater than those generated by the algorithm A*.

Keywords: algorithm A*, graph, mobility, public transport, travel planning, routes

Procedia PDF Downloads 230
1769 Modeling and Dynamics Analysis for Intelligent Skid-Steering Vehicle Based on Trucksim-Simulink

Authors: Yansong Zhang, Xueyuan Li, Junjie Zhou, Xufeng Yin, Shihua Yuan, Shuxian Liu

Abstract:

Aiming at the verification of control algorithms for skid-steering vehicles, a vehicle simulation model of 6×6 electric skid-steering unmanned vehicle was established based on Trucksim and Simulink. The original transmission and steering mechanism of Trucksim are removed, and the electric skid-steering model and a closed-loop controller for the vehicle speed and yaw rate are built in Simulink. The simulation results are compared with the ones got by theoretical formulas. The results show that the predicted tire mechanics and vehicle kinematics of Trucksim-Simulink simulation model are closed to the theoretical results. Therefore, it can be used as an effective approach to study the dynamic performance and control algorithm of skid-steering vehicle. In this paper, a method of motion control based on feed forward control is also designed. The simulation results show that the feed forward control strategy can make the vehicle follow the target yaw rate more quickly and accurately, which makes the vehicle have more maneuverability.

Keywords: skid-steering, Trucksim-Simulink, feedforward control, dynamics

Procedia PDF Downloads 320
1768 XRD and Image Analysis of Low Carbon Type Recycled Cement Using Waste Cementitious Powder

Authors: Hyeonuk Shin, Hun Song, Yongsik Chu, Jongkyu Lee, Dongcheon Park

Abstract:

Although much current research has been devoted to reusing concrete in the form of recycled aggregate, insufficient attention has been given to researching the utilization of waste concrete powder, which constitutes 20 % or more of waste concrete and therefore the majority of waste cementitious powder is currently being discarded or buried in landfills. This study consists of foundational research for the purpose of reusing waste cementitious powder in the form of recycled cement that can answer the need for low carbon green growth. Progressing beyond the conventional practice of using the waste cementitious powder as inert filler material, this study contributes to the aim of manufacturing high value added materials that exploits the chemical properties of the waste cementitious powder, by presenting a pre-treatment method for the material and an optimal method of proportioning the mix of materials to develop a low carbon type of recycled cement.

Keywords: Low carbon type cement, Waste cementitious powder, Waste recycling

Procedia PDF Downloads 459
1767 A Supervised Face Parts Labeling Framework

Authors: Khalil Khan, Ikram Syed, Muhammad Ehsan Mazhar, Iran Uddin, Nasir Ahmad

Abstract:

Face parts labeling is the process of assigning class labels to each face part. A face parts labeling method (FPL) which divides a given image into its constitutes parts is proposed in this paper. A database FaceD consisting of 564 images is labeled with hand and make publically available. A supervised learning model is built through extraction of features from the training data. The testing phase is performed with two semantic segmentation methods, i.e., pixel and super-pixel based segmentation. In pixel-based segmentation class label is provided to each pixel individually. In super-pixel based method class label is assigned to super-pixel only – as a result, the same class label is given to all pixels inside a super-pixel. Pixel labeling accuracy reported with pixel and super-pixel based methods is 97.68 % and 93.45% respectively.

Keywords: face labeling, semantic segmentation, classification, face segmentation

Procedia PDF Downloads 251
1766 Order Optimization of a Telecommunication Distribution Center through Service Lead Time

Authors: Tamás Hartványi, Ferenc Tóth

Abstract:

European telecommunication distribution center performance is measured by service lead time and quality. Operation model is CTO (customized to order) namely, a high mix customization of telecommunication network equipment and parts. CTO operation contains material receiving, warehousing, network and server assembly to order and configure based on customer specifications. Variety of the product and orders does not support mass production structure. One of the success factors to satisfy customer is to have a proper aggregated planning method for the operation in order to have optimized human resources and highly efficient asset utilization. Research will investigate several methods and find proper way to have an order book simulation where practical optimization problem may contain thousands of variables and the simulation running times of developed algorithms were taken into account with high importance. There are two operation research models that were developed, customer demand is given in orders, no change over time, customer demands are given for product types, and changeover time is constant.

Keywords: CTO, aggregated planning, demand simulation, changeover time

Procedia PDF Downloads 261
1765 Laser Irradiated GeSn Photodetector for Improved Infrared Photodetection

Authors: Patrik Scajev, Pavels Onufrijevs, Algirdas Mekys, Tadas Malinauskas, Dominykas Augulis, Liudvikas Subacius, Kuo-Chih Lee, Jevgenijs Kaupuzs, Arturs Medvids, Hung Hsiang Cheng

Abstract:

In this study, we focused on the optoelectronic properties of the photodiodes prepared by using 200 nm thick Ge₀.₉₅Sn₀.₀₅ epitaxial layers on Ge/n-Si substrate with aluminum contacts. Photodiodes were formed on non-irradiated and Nd: YAG laser irradiated Ge₀.₉₅Sn₀.₀₅ layers. The samples were irradiated by pulsed Nd: YAG laser with 136.7-462.6 MW/cm² intensity. The photodiodes were characterized by using short laser pulses with the wavelength in the 2.0-2.6 μm range. The laser-irradiated diode was found more sensitive in the long-wavelength range due to laser-induced Sn atoms redistribution providing formation of graded bandgap structure. Sub-millisecond photocurrent relaxation in the diodes revealed their suitability for image sensors. Our findings open the perspective for improving the photo-sensitivity of GeSn alloys in the mid-infrared by pulsed laser processing.

Keywords: GeSn, laser processing, photodetector, infrared

Procedia PDF Downloads 141
1764 Understanding the Polygon with the Eyes of Blinds

Authors: Tuğba Horzum, Ahmet Arikan

Abstract:

This paper was part of a broader study that investigated what blind students (BSs) understood and how they used concept definitions (CDs) and concept images (CIs) for some mathematical concepts. This paper focused on the polygon concept. For this purpose, four open-ended questions were asked to five blind middle school students. During the interviews, BSs were presented with raised-line materials and were given opportunities to construct geometric shapes with magnetic sticks and micro-balls. Qualitative research techniques applied in grounded theory were used for analyzing documents pictures which were taken from magnetic geometric shapes that BSs constructed, raised-line materials and researcher’s observation notes and interviews. At the end of the analysis, it was observed that BSs used mostly their CIs and never took into account the CDs. Besides, BSs encountered with the difficulties associated with the combination of polygon edges’ endpoints consecutively. Additionally, they focused on the interior of the polygon and the angles which have smaller a size. Lastly, BSs were often conflicted about triangle, rectangle, square and circle whether or not a polygon.

Keywords: blind students, concept definition, concept image, polygon

Procedia PDF Downloads 292
1763 Dynamic Foot Pressure Measurement System Using Optical Sensors

Authors: Tanapon Keatsamarn, Chuchart Pintavirooj

Abstract:

Foot pressure measurement provides necessary information for diagnosis diseases, foot insole design, disorder prevention and other application. In this paper, dynamic foot pressure measurement is presented for pressure measuring with high resolution and accuracy. The dynamic foot pressure measurement system consists of hardware and software system. The hardware system uses a transparent acrylic plate and uses steel as the base. The glossy white paper is placed on the top of the transparent acrylic plate and covering with a black acrylic on the system to block external light. Lighting from LED strip entering around the transparent acrylic plate. The optical sensors, the digital cameras, are underneath the acrylic plate facing upwards. They have connected with software system to process and record foot pressure video in avi file. Visual Studio 2017 is used for software system using OpenCV library.

Keywords: foot, foot pressure, image processing, optical sensors

Procedia PDF Downloads 242
1762 Application and Assessment of Artificial Neural Networks for Biodiesel Iodine Value Prediction

Authors: Raquel M. De sousa, Sofiane Labidi, Allan Kardec D. Barros, Alex O. Barradas Filho, Aldalea L. B. Marques

Abstract:

Several parameters are established in order to measure biodiesel quality. One of them is the iodine value, which is an important parameter that measures the total unsaturation within a mixture of fatty acids. Limitation of unsaturated fatty acids is necessary since warming of a higher quantity of these ones ends in either formation of deposits inside the motor or damage of lubricant. Determination of iodine value by official procedure tends to be very laborious, with high costs and toxicity of the reagents, this study uses an artificial neural network (ANN) in order to predict the iodine value property as an alternative to these problems. The methodology of development of networks used 13 esters of fatty acids in the input with convergence algorithms of backpropagation type were optimized in order to get an architecture of prediction of iodine value. This study allowed us to demonstrate the neural networks’ ability to learn the correlation between biodiesel quality properties, in this case iodine value, and the molecular structures that make it up. The model developed in the study reached a correlation coefficient (R) of 0.99 for both network validation and network simulation, with Levenberg-Maquardt algorithm.

Keywords: artificial neural networks, biodiesel, iodine value, prediction

Procedia PDF Downloads 602
1761 English Learning Speech Assistant Speak Application in Artificial Intelligence

Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri

Abstract:

Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.

Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation

Procedia PDF Downloads 101
1760 Prediction Fluid Properties of Iranian Oil Field with Using of Radial Based Neural Network

Authors: Abdolreza Memari

Abstract:

In this article in order to estimate the viscosity of crude oil,a numerical method has been used. We use this method to measure the crude oil's viscosity for 3 states: Saturated oil's viscosity, viscosity above the bubble point and viscosity under the saturation pressure. Then the crude oil's viscosity is estimated by using KHAN model and roller ball method. After that using these data that include efficient conditions in measuring viscosity, the estimated viscosity by the presented method, a radial based neural method, is taught. This network is a kind of two layered artificial neural network that its stimulation function of hidden layer is Gaussian function and teaching algorithms are used to teach them. After teaching radial based neural network, results of experimental method and artificial intelligence are compared all together. Teaching this network, we are able to estimate crude oil's viscosity without using KHAN model and experimental conditions and under any other condition with acceptable accuracy. Results show that radial neural network has high capability of estimating crude oil saving in time and cost is another advantage of this investigation.

Keywords: viscosity, Iranian crude oil, radial based, neural network, roller ball method, KHAN model

Procedia PDF Downloads 494
1759 Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP) for Recovering Signal

Authors: Israa Sh. Tawfic, Sema Koc Kayhan

Abstract:

Given a large sparse signal, great wishes are to reconstruct the signal precisely and accurately from lease number of measurements as possible as it could. Although this seems possible by theory, the difficulty is in built an algorithm to perform the accuracy and efficiency of reconstructing. This paper proposes a new proved method to reconstruct sparse signal depend on using new method called Least Support Matching Pursuit (LS-OMP) merge it with the theory of Partial Knowing Support (PSK) given new method called Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP). The new methods depend on the greedy algorithm to compute the support which depends on the number of iterations. So to make it faster, the PKLS-OMP adds the idea of partial knowing support of its algorithm. It shows the efficiency, simplicity, and accuracy to get back the original signal if the sampling matrix satisfies the Restricted Isometry Property (RIP). Simulation results also show that it outperforms many algorithms especially for compressible signals.

Keywords: compressed sensing, lest support orthogonal matching pursuit, partial knowing support, restricted isometry property, signal reconstruction

Procedia PDF Downloads 234
1758 Strategic Orientation of Islamic Banks: A Review of Strategy Language

Authors: Imam Uddin, Imtiaz Ahmed Memon

Abstract:

This paper analyzes the ideological contextuality of market oriented strategy language used by Industry leaders to envision the future of Islamic financial Institutions (IFIs) in the light of Wittgenstein language-games and Foucault’s power-discourse framework. The analysis infers that the explicit market orientation of strategy language and modern knowledge of finance now defines various concepts related of Islamic finance, let alone Islamic finance theory itself. Theorizing and practicing Islamic finance therefore under the dominant influence of modern strategy discourse and modern knowledge of finance has significant implications for developing an ethical and spiritual orientation of Islamic banks. The concerned academia and scholarship therefore need to review such trends and work around the possible degradation to the public image of IFIs and resulting disappointments of religiously inspired customers.

Keywords: Islamic finance discourse, strategy discourse, language games, strategic intent, productive misunderstanding

Procedia PDF Downloads 391
1757 Evaluation of Three Digital Graphical Methods of Baseflow Separation Techniques in the Tekeze Water Basin in Ethiopia

Authors: Alebachew Halefom, Navsal Kumar, Arunava Poddar

Abstract:

The purpose of this work is to specify the parameter values, the base flow index (BFI), and to rank the methods that should be used for base flow separation. Three different digital graphical approaches are chosen and used in this study for the purpose of comparison. The daily time series discharge data were collected from the site for a period of 30 years (1986 up to 2015) and were used to evaluate the algorithms. In order to separate the base flow and the surface runoff, daily recorded streamflow (m³/s) data were used to calibrate procedures and get parameter values for the basin. Additionally, the performance of the model was assessed by the use of the standard error (SE), the coefficient of determination (R²), and the flow duration curve (FDC) and baseflow indexes. The findings indicate that, in general, each strategy can be used worldwide to differentiate base flow; however, the Sliding Interval Method (SIM) performs significantly better than the other two techniques in this basin. The average base flow index was calculated to be 0.72 using the local minimum method, 0.76 using the fixed interval method, and 0.78 using the sliding interval method, respectively.

Keywords: baseflow index, digital graphical methods, streamflow, Emba Madre Watershed

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1756 Multi-Objective Four-Dimensional Traveling Salesman Problem in an IoT-Based Transport System

Authors: Arindam Roy, Madhushree Das, Apurba Manna, Samir Maity

Abstract:

In this research paper, an algorithmic approach is developed to solve a novel multi-objective four-dimensional traveling salesman problem (MO4DTSP) where different paths with various numbers of conveyances are available to travel between two cities. NSGA-II and Decomposition algorithms are modified to solve MO4DTSP in an IoT-based transport system. This IoT-based transport system can be widely observed, analyzed, and controlled by an extensive distribution of traffic networks consisting of various types of sensors and actuators. Due to urbanization, most of the cities are connected using an intelligent traffic management system. Practically, for a traveler, multiple routes and vehicles are available to travel between any two cities. Thus, the classical TSP is reformulated as multi-route and multi-vehicle i.e., 4DTSP. The proposed MO4DTSP is designed with traveling cost, time, and customer satisfaction as objectives. In reality, customer satisfaction is an important parameter that depends on travel costs and time reflects in the present model.

Keywords: multi-objective four-dimensional traveling salesman problem (MO4DTSP), decomposition, NSGA-II, IoT-based transport system, customer satisfaction

Procedia PDF Downloads 103
1755 Applications of Visual Ethnography in Public Anthropology

Authors: Subramaniam Panneerselvam, Gunanithi Perumal, KP Subin

Abstract:

The Visual Ethnography is used to document the culture of a community through a visual means. It could be either photography or audio-visual documentation. The visual ethnographic techniques are widely used in visual anthropology. The visual anthropologists use the camera to capture the cultural image of the studied community. There is a scope for subjectivity while the culture is documented by an external person. But the upcoming of the public anthropology provides an opportunity for the participants to document their own culture. There is a need to equip the participants with the skill of doing visual ethnography. The mobile phone technology provides visual documentation facility to everyone to capture the moments instantly. The visual ethnography facilitates the multiple-interpretation for the audiences. This study explores the effectiveness of visual ethnography among the tribal youth through public anthropology perspective. The case study was conducted to equip the tribal youth of Nilgiris in visual ethnography and the outcome of the experiment shared in this paper.

Keywords: visual ethnography, visual anthropology, public anthropology, multiple-interpretation, case study

Procedia PDF Downloads 175
1754 Tumor Detection of Cerebral MRI by Multifractal Analysis

Authors: S. Oudjemia, F. Alim, S. Seddiki

Abstract:

This paper shows the application of multifractal analysis for additional help in cancer diagnosis. The medical image processing is a very important discipline in which many existing methods are in search of solutions to real problems of medicine. In this work, we present results of multifractal analysis of brain MRI images. The purpose of this analysis was to separate between healthy and cancerous tissue of the brain. A nonlinear method based on multifractal detrending moving average (MFDMA) which is a generalization of the detrending fluctuations analysis (DFA) is used for the detection of abnormalities in these images. The proposed method could make separation of the two types of brain tissue with success. It is very important to note that the choice of this non-linear method is due to the complexity and irregularity of tumor tissue that linear and classical nonlinear methods seem difficult to characterize completely. In order to show the performance of this method, we compared its results with those of the conventional method box-counting.

Keywords: irregularity, nonlinearity, MRI brain images, multifractal analysis, brain tumor

Procedia PDF Downloads 438