Search results for: random forest algorithm

Authors: Azim Khodadadi, Sahar Sadaat Vakili, Ebrahim Babaei

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This study presents a numerical method to optimize the failure rate and repair time of a typical radial distribution system. Failure rate and repair time are effective parameters in customer and energy based indices of reliability. Decrease of these parameters improves reliability indices. Thus, system stability will be boost. The penalty functions indirectly reflect the cost of investment which spent to improve these indices. Constraints on customer and energy based indices, i.e. SAIFI, SAIDI, CAIDI and AENS have been considered by using a new method which reduces optimization algorithm controlling parameters. Imperialist Competitive Algorithm (ICA) used as main optimization technique and particle swarm optimization (PSO), simulated annealing (SA) and differential evolution (DE) has been applied for further investigation. These algorithms have been implemented on a test system by MATLAB. Obtained results have been compared with each other. The optimized values of repair time and failure rate are much lower than current values which this achievement reduced investment cost and also ICA gives better answer than the other used algorithms.

Keywords: imperialist competitive algorithm, failure rate, repair time, radial distribution network

Procedia PDF Downloads 652

Authors: M. Baghdasaryan, A. Sukiasyan

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An algorithm for estimating the stable operation conditions of the synchronous motor of the ore mill electric drive is proposed. The stable operation conditions of the synchronous motor are revealed, taking into account the estimation of the q angle change and the technological factors. The stability condition obtained allows to ensure the stable operation of the motor in the synchronous mode, taking into account the nonlinear character of the mill loading. The developed algorithm gives an opportunity to present the undesirable phenomena, arising in the electric drive system. The obtained stability condition can be successfully applied for the optimal control of the electromechanical system of the mill.

Keywords: electric drive, synchronous motor, ore mill, stability, technological factors

Procedia PDF Downloads 412

Authors: Rachel Danielson, Brendan Bohannan, S.M. Tsai, Kyle Meyer, Jorge L.M. Rodrigues

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The Amazon Rainforest is a global diversity hotspot and crucial carbon sink, but approximately 20% of its total extent has been deforested- primarily for the establishment of cattle pasture. Understanding the impact of this large-scale disturbance on soil microbial community composition and activity is crucial in understanding potentially consequential shifts in nutrient or greenhouse gas cycling, as well as adding to the body of knowledge concerning how these complex communities respond to human disturbance. In this study, surface soils (0-10cm) were collected from three forests and three 45-year-old pastures in Rondonia, Brazil (the Amazon state with the greatest rate of forest destruction) in order to determine the impact of forest conversion on microbial communities involved in nitrogen fixation. Soil chemical and physical parameters were paired with measurements of microbial activity and genetic profiles to determine how community composition and process rates relate to environmental conditions. Measuring both the natural abundance of 15N in total soil N, as well as incorporation of enriched 15N2 under incubation has revealed that conversion of primary forest to cattle pasture results in a significant increase in the rate of nitrogen fixation by free-living diazotrophs. Quantification of nifH gene copy numbers (an essential subunit encoding the nitrogenase enzyme) correspondingly reveals a significant increase of genes in pasture compared to forest soils. Additionally, genetic sequencing of both nifH genes and transcripts shows a significant increase in the diversity of the present and metabolically active diazotrophs within the soil community. Levels of both organic and inorganic nitrogen tend to be lower in pastures compared to forests, with ammonium rather than nitrate as the dominant inorganic form. However, no significant or consistent differences in total, extractable, permanganate-oxidizable, or loss-on-ignition carbon are present between the two land-use types. Forest conversion is associated with a 0.5- 1.0 unit pH increase, but concentrations of many biologically relevant nutrients such as phosphorus do not increase consistently. Increases in free-living diazotrophic community abundance and activity appear to be related to shifts in carbon to nitrogen pool ratios. Furthermore, there may be an important impact of transient, low molecular weight plant-root-derived organic carbon on free-living diazotroph communities not captured in this study. Preliminary analysis of nitrogenase gene variant composition using NovoSeq metagenomic sequencing indicates that conversion of forest to pasture may significantly enrich vanadium-based nitrogenases. This indication is complemented by a significant decrease in available soil molybdenum. Very little is known about the ecology of diazotrophs utilizing vanadium-based nitrogenases, so further analysis may reveal important environmental conditions favoring their abundance and diversity in soil systems. Taken together, the results of this study indicate a significant change in nitrogen cycling and diazotroph community composition with the conversion of the Amazon Rainforest. This may have important implications for the sustainability of cattle pastures once established since nitrogen is a crucial nutrient for forage grass productivity.

Keywords: free-living diazotrophs, land use change, metagenomic sequencing, nitrogen fixation

Procedia PDF Downloads 181

Authors: CarlyWill Sloan

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Racial disparities in criminal justice outcomes are well-documented. However, there is little evidence on the extent to which racial bias by prosecutors is responsible for these disparities. This paper tests for racial bias in conviction by prosecutors. To identify effects, this paper leverages as good as random variation in prosecutor race using detailed administrative data on the case assignment process and case outcomes in New York County, New York. This paper shows that the assignment of an opposite-race prosecutor leads to a 5 percentage point (~ 8 percent) increase in the likelihood of conviction for property crimes. There is no evidence of effects for other types of crimes. Additional results indicate decreased dismissals by opposite-race prosecutors likely drive my property crime estimates.

Keywords: criminal justice, discrimination, prosecutors, racial disparities

Procedia PDF Downloads 181

Authors: Florin Leon, Silvia Curteanu

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The Bacterial Foraging Optimization (BFO) algorithm is inspired by the behavior of bacteria such as Escherichia coli or Myxococcus xanthus when searching for food, more precisely the chemotaxis behavior. Bacteria perceive chemical gradients in the environment, such as nutrients, and also other individual bacteria, and move toward or in the opposite direction to those signals. The application example considered as a case study consists in establishing the dependency between the reaction yield of hydrogels based on polyacrylamide and the working conditions such as time, temperature, monomer, initiator, crosslinking agent and inclusion polymer concentrations, as well as type of the polymer added. This process is modeled with a neural network which is included in an optimization procedure based on BFO. An experimental study of BFO parameters is performed. The results show that the algorithm is quite robust and can obtain good results for diverse combinations of parameter values.

Keywords: bacterial foraging, hydrogels, modeling and optimization, neural networks

Procedia PDF Downloads 135

Authors: Salinee Thumronglaohapun

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The proper number and appropriate locations of service centers can save cost, raise revenue and gain more satisfaction from customers. Establishing service centers is high-cost and difficult to relocate. In long-term planning periods, several factors may affect the service. One of the most critical factors is uncertain demand of customers. The opened service centers need to be capable of serving customers and making a profit although the demand in each period is changed. In this work, the capacitated location-allocation problem with stochastic demand is considered. A mathematical model is formulated to determine suitable locations of service centers and their allocation to maximize total profit for multiple planning periods. Two heuristic methods, a local search and genetic algorithm, are used to solve this problem. For the local search, five different chances to choose each type of moves are applied. For the genetic algorithm, three different replacement strategies are considered. The results of applying each method to solve numerical examples are compared. Both methods reach to the same best found solution in most examples but the genetic algorithm provides better solutions in some cases.

Keywords: location-allocation problem, stochastic demand, local search, genetic algorithm

Procedia PDF Downloads 115

Authors: Aleksander Nawrat, Karol Jędrasiak, Artur Ryt, Dawid Sobel

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The goal of the article is to present a novel Multimedia Firearms Training System. The system was developed in order to compensate for major problems of existing shooting training systems. The designed and implemented solution can be characterized by five major advantages: algorithm for automatic geometric calibration, algorithm of photometric recalibration, firearms hit point detection using thermal imaging camera, IR laser spot tracking algorithm for after action review analysis, and implementation of ballistics equations. The combination of the abovementioned advantages in a single multimedia firearms training system creates a comprehensive solution for detecting and tracking of the target point usable for shooting training systems and improving intervention tactics of uniformed services. The introduced algorithms of geometric and photometric recalibration allow the use of economically viable commercially available projectors for systems that require long and intensive use without most of the negative impacts on color mapping of existing multi-projector multimedia shooting range systems. The article presents the results of the developed algorithms and their application in real training systems.

Keywords: firearms shot detection, geometric recalibration, photometric recalibration, IR tracking algorithm, thermography, ballistics

Procedia PDF Downloads 207

Authors: Shiwei Deng, Yang Bao

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In this paper, we present a model-based regression test suite reducing approach that uses EFSM model dependence analysis and probability-driven greedy algorithm to reduce software regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. The EFSM dependence analysis is performed for each elementary modification to reduce the regression test suite, and then the probability-driven greedy algorithm is adopted to select the minimum set of test cases from the reduced regression test suite that cover all interaction patterns. Our initial experience shows that the approach may significantly reduce the size of regression test suites.

Keywords: dependence analysis, EFSM model, greedy algorithm, regression test

Procedia PDF Downloads 415

Authors: C. Iraklis, G. Evmiridis, A. Iraklis

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Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: congestion, distribution networks, loss reduction, particle swarm optimization, smart grid

Procedia PDF Downloads 434

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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Accurate Liver, spleen and kidneys segmentation in abdominal CT images is one of the most important steps for computer aided abdominal organs pathology diagnosis. In this paper, we have proposed a new semi-automatic algorithm for Liver, spleen and kidneys area extraction in abdominal CT images. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. The algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, multi-abdominal organ segmentation, mosaic image, the watershed algorithm

Procedia PDF Downloads 482

Authors: Iftikhar A. Tayubi, Aabdulrahman Alsubhi, Abdullah Althrwi

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The deoxyribonucleic acid text provides a single source of high-quality Cryptography about Deoxyribonucleic acid sequence for structural biologists. We will provide an intuitive, well-organized and user-friendly web interface that allows users to encrypt and decrypt Deoxy Ribonucleic Acid sequence text. It includes complex, securing by using Algorithm to encrypt and decrypt Deoxy Ribonucleic Acid sequence. The utility of this Deoxy Ribonucleic Acid Sequence Text is that, it can provide a user-friendly interface for users to Encrypt and Decrypt store the information about Deoxy Ribonucleic Acid sequence. These interfaces created in this project will satisfy the demands of the scientific community by providing fully encrypt of Deoxy Ribonucleic Acid sequence during this website. We have adopted a methodology by using C# and Active Server Page.NET for programming which is smart and secure. Deoxy Ribonucleic Acid sequence text is a wonderful piece of equipment for encrypting large quantities of data, efficiently. The users can thus navigate from one encoding and store orange text, depending on the field for user’s interest. Algorithm classification allows a user to Protect the deoxy ribonucleic acid sequence from change, whether an alteration or error occurred during the Deoxy Ribonucleic Acid sequence data transfer. It will check the integrity of the Deoxy Ribonucleic Acid sequence data during the access.

Keywords: algorithm, ASP.NET, DNA, encrypt, decrypt

Procedia PDF Downloads 219

Authors: Po-Wen Chen, Jin-Yu Wu, Md. Manirul Ali, Yang Peng, Chen-Te Chang, Der-Jun Jan

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Dynamics of cathode spot has become a major part of vacuum arc discharge with its high academic interest and wide application potential. In this article, using a three-dimensional statistical model, we simulate the distribution of the ignition probability of a new cathode spot occurring in different magnetic pressure on old cathode spot surface and at different arcing time. This model for the ignition probability of a new cathode spot was proposed in two typical situations, one by the pure isotropic random walk in the absence of an external magnetic field, other by the retrograde motion in external magnetic field, in parallel with the cathode surface. We mainly focus on developed relationship between the ignition probability density distribution of a new cathode spot and the external magnetic field.

Keywords: cathode spot, vacuum arc discharge, transverse magnetic field, random walk

Procedia PDF Downloads 422

Authors: Gagandeep Kaur

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Cloud computing uses various computing resources such as CPU, memory, processor etc. which is used to deliver service over the network and is one of the emerging fields for large scale distributed computing. In cloud computing, execution of large number of tasks with available resources to achieve high performance, minimal total time for completion, minimum response time, effective utilization of resources etc. are the major research areas. In the proposed research, an algorithm has been proposed to achieve high performance in load balancing and resource utilization. The proposed algorithm is used to reduce the makespan, increase the resource utilization and performance cost for independent tasks. Further scheduling metrics based on algorithm in cloud computing has been proposed.

Keywords: resource utilization, response time, load balancing, performance cost

Procedia PDF Downloads 170

Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

Procedia PDF Downloads 211

Authors: Sophia Fry, Mahir Irtiza, Alexa Hoffman, Yousef Sardahi

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This study presents an intelligent control algorithm for a flexible robotic arm. Fuzzy control is used to control the motion of the arm to maintain the arm tip at the desired position while reducing vibration and increasing the system speed of response. The Fuzzy controller (FC) is based on adding the tip angular position to the arm deflection angle and using their sum as a feedback signal to the control algorithm. This reduces the complexity of the FC in terms of the input variables, number of membership functions, fuzzy rules, and control structure. Also, the design of the fuzzy controller is model-free and uses only our knowledge about the system. To show the efficacy of the FC, the control algorithm is implemented on the flexible joint manipulator (FJM) developed by Quanser. The results show that the proposed control method is effective in terms of response time, overshoot, and vibration amplitude.

Keywords: fuzzy logic control, model-free control, flexible joint manipulators, nonlinear control

Procedia PDF Downloads 88

Authors: R. Rama Kishore, Sunesh

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Nowadays, robust and secure watermarking algorithm and its optimization have been need of the hour. A watermarking algorithm is presented to achieve the copy right protection of the owner based on visual cryptography, histogram shape property and entropy. In this, both host image and watermark are preprocessed. Host image is preprocessed by using Butterworth filter, and watermark is with visual cryptography. Applying visual cryptography on water mark generates two shares. One share is used for embedding the watermark, and the other one is used for solving any dispute with the aid of trusted authority. Usage of histogram shape makes the process more robust against geometric and signal processing attacks. The combination of visual cryptography, Butterworth filter, histogram, and entropy can make the algorithm more robust, imperceptible, and copy right protection of the owner.

Keywords: digital watermarking, visual cryptography, histogram, butter worth filter

Procedia PDF Downloads 346

Authors: Balaji Ganesh Rajagopal, Subramanian Appavu alias Balamurugan, Ayyalraj Midhun Kumar, Krishnan Nallaperumal

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Intelligent Transportation System is an Emerging area to solve multiple transportation problems. Several forms of inputs are needed in order to solve ITS problems. Advanced Traveler Information System (ATIS) is a core and important ITS area of this modern era. This involves travel time forecasting, efficient road map analysis and cost based path selection, Detection of the vehicle in the dynamic conditions and Traffic congestion state forecasting. This Article designs and provides an algorithm for traffic data generation which can be used for the above said ATIS application. By inputting the real world traffic situation in the form of video sequences, the algorithm determines the Traffic density in terms of congestion, number of vehicles in a given path which can be fed for various ATIS applications. The Algorithm deduces the key frame from the video sequences and follows the Blob detection, Identification and Tracking using connected components algorithm to determine the correlation between the vehicles moving in the real road scene.

Keywords: traffic transportation, traffic density estimation, blob identification and tracking, relative velocity of vehicles, correlation between vehicles

Procedia PDF Downloads 497

Authors: Saleh Alshehri

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Human skin detection is a vital step in many applications. Some of the applications are critical especially those related to security. This leverages the importance of a high-performance detection algorithm. To validate the accuracy of the algorithm, image databases are usually used. However, the suitability of these image databases is still questionable. It is suggested that the suitability can be measured mainly by the span the database covers of the color space. This research investigates the validity of three famous image databases.

Keywords: image databases, image processing, pattern recognition, neural networks

Procedia PDF Downloads 252

Authors: AmirHossein Mohajerzadeh, Mohammad Alishahi, Saeed Aslishahi, Mohsen Zabihi

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In this paper, we consider sensor nodes with the capability of measuring the bearings (relative angle to the target). We use geometric methods to select a set of observer nodes which are responsible for collecting data from the target. Considering the characteristics of target tracking applications, it is clear that significant numbers of sensor nodes are usually inactive. Therefore, in order to minimize the total network energy consumption, a set of sensor nodes, called sentinel, is periodically selected for monitoring, controlling the environment and transmitting data through the network. The other nodes are inactive. Furthermore, the proposed algorithm provides a joint scheduling and routing algorithm to transmit data between network nodes and the fusion center (FC) in which not only provides an efficient way to estimate the target position but also provides an efficient target tracking. Performance evaluation confirms the superiority of the proposed algorithm.

Keywords: coverage, routing, scheduling, target tracking, wireless sensor networks

Procedia PDF Downloads 367

Authors: Mohamed Abdel Sabour, Mohamed Nouh, Ian Stevans, Essam Elkholy

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We study the period change of six Cepheids using 19376 accurate flux observations of the Solar Mass Ejection Imager (SMEI) onboard the Coriolis spacecraft. All observations for the six Cepheids have been derived as templates for each star, independent of the specific sites utilized to establish and update the O-C values. Sometimes, sinusoidal patterns are superimposed on the star's O-C changes, which cannot be regarded as random fluctuations in the pulsation period. Random period changes were detected and computed using Eddington's and Plakidis's approaches. A comparison of the observed and predicted period change reveals a good agreement with some published models and a very substantial divergence with others. Between the reported period change and that estimated by the current technique, a linear fit with a correlation coefficient of 90.08 percent was obtained. The temporal rate of period change in Cepheid stars might be connected to how well these stars' mass losses are known today.

Keywords: cepheids, period change, mass loss, O-C changes, period change, mass loss, O-C

Procedia PDF Downloads 21

Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su, Junjie Wang

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The Bernoulli filter is a precise Bayesian filter for single target tracking based on the random finite set theory. The standard Bernoulli filter often underestimates the number of targets. This study proposes a Gaussian particle flow (GPF) Bernoulli filter employing particle flow to migrate particles from prior to posterior positions to improve the performance of the standard Bernoulli filter. By employing the particle flow filter, the computational speed of the Bernoulli filters is significantly improved. In addition, the GPF Bernoulli filter provides a more accurate estimation compared with that of the standard Bernoulli filter. Simulation results confirm the improved tracking performance and computational speed in two- and three-dimensional scenarios compared with other algorithms.

Keywords: Bernoulli filter, particle filter, particle flow filter, random finite sets, target tracking

Procedia PDF Downloads 78

Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

Procedia PDF Downloads 38

Authors: John Wangui, Charles Gachene, Stephen Mureithi, Boniface Kiteme

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Land use changes caused by demographic, natural variability, economic, technological and policy factors affect the goods and services derived from an ecosystem. In the past few decades, Lake Ol Bolossat catchment in Nyandarua County Kenya has been facing challenges of land cover changes threatening its capacity to perform ecosystems functions and adversely affecting communities and ecosystems downstream. This study assessed land cover changes in the catchment for a period of twenty eight years (from 1986 to 2014). Analysis of three Landsat images i.e. L5 TM 1986, L5 TM 1995 and L8 OLI/TIRS 2014 was done using ERDAS 9.2 software. The results show that dense forest, cropland and area under water increased by 27%, 29% and 3% respectively. On the other hand, open forest, dense grassland, open grassland, bushland and shrubland decreased by 3%, 3%, 11%, 26% and 1% respectively during the period under assessment. The lake was noted to have increased due to siltation caused by soil erosion causing a reduction in Lake’s depth and consequently causing temporary flooding of the wetland. The study concludes that the catchment is under high demographic pressure which would lead to resource use conflicts and therefore formulation of mitigation measures is highly recommended.

Keywords: land cover, land use change, land degradation, Nyandarua, Remote sensing

Procedia PDF Downloads 356

Authors: Shiji Hu, Lei Li, Wanting Zhou, DaoHong Yang

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The data encryption, is the foundation of today’s communication. On this basis, how to improve the speed of data encryption and decryption is always a problem that scholars work for. In this paper, we proposed an elliptic curve crypto processor architecture based on SM2 prime field. In terms of hardware implementation, we optimized the algorithms in different stages of the structure. In finite field modulo operation, we proposed an optimized improvement of Karatsuba-Ofman multiplication algorithm, and shorten the critical path through pipeline structure in the algorithm implementation. Based on SM2 recommended prime field, a fast modular reduction algorithm is used to reduce 512-bit wide data obtained from the multiplication unit. The radix-4 extended Euclidean algorithm was used to realize the conversion between affine coordinate system and Jacobi projective coordinate system. In the parallel scheduling of point operations on elliptic curves, we proposed a three-level parallel structure of point addition and point double based on the Jacobian projective coordinate system. Combined with the scalar multiplication algorithm, we added mutual pre-operation to the point addition and double point operation to improve the efficiency of the scalar point multiplication. The proposed ECC hardware architecture was verified and implemented on Xilinx Virtex-7 and ZYNQ-7 platforms, and each 256-bit scalar multiplication operation took 0.275ms. The performance for handling scalar multiplication is 32 times that of CPU(dual-core ARM Cortex-A9).

Keywords: Elliptic curve cryptosystems, SM2, modular multiplication, point multiplication.

Procedia PDF Downloads 83

Authors: Simeon E. H. Davies

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This study investigated whether selected metabolic responses and the perception of effort varied during four different walk protocols where speed increased progressively 3, 4, 5, 6, and 7 km/hr (progressive treadmill walk (PTW); and progressive land walk (PLW); or where the participant adjusted to random changes of speed e.g. 6, 3, 7, 4, and 5 km/hr during a randomized treadmill walk (RTW); and a randomized land walk (RLW). Mean stature and mass of the seven participants was 1.75m and 70kg respectively, with a mean body fat of 15%. Metabolic measures including heart rate, relative oxygen uptake, ventilation, increased in a linear fashion up to 6 km/hr, however at 7 km/hr there was a significant increase in metabolic response notably during the PLW, and to a similar, although lesser extent in RLW, probably as a consequence of the loss of kinetic energy when turning at each cone in order to maintain the speed during each shuttle. Respiration frequency appeared to be a more sensitive indicator of physical exertion, exhibiting a rapid elevation at 5 km/hr. The perception of effort during each mode and at each speed was largely congruent during each walk protocol.

Keywords: exertion, metabolic, progressive, random, walking

Procedia PDF Downloads 450

Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

Procedia PDF Downloads 462

Authors: Seong Jun Yoon, Jasurbek Doliev, Sang Min Oh, Rodi Hartono, Kyoojae Shin

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Electric power steering (EPS), which is commonly used in electric vehicles recently, is an electric-driven steering device for vehicles. Compared to hydraulic systems, EPS offers advantages such as simple system components, easy maintenance, and improved steering performance. However, because the EPS system is a nonlinear model, difficult problems arise in controller design. To address these, various machine learning and artificial intelligence approaches, notably artificial neural networks (ANN), have been applied. ANN can effectively determine relationships between inputs and outputs in a data-driven manner. This research explores two main areas: designing an EPS identifier using an ANN-based backpropagation (BP) algorithm and enhancing the EPS system controller with an ANN-based Levenberg-Marquardt (LM) algorithm. The proposed ANN-based BP algorithm shows superior performance and accuracy compared to linear transfer function estimators, while the LM algorithm offers better input angle reference tracking and faster response times than traditional PID controllers. Overall, the proposed ANN methods demonstrate significant promise in improving EPS system performance.

Keywords: ANN backpropagation modelling, electric power steering, transfer function estimator, electrical vehicle driving system

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Authors: Sakshi Yadav, Sushila Shekhawat

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This study addresses different types of points of view as seen in nature documentary films with the help of three eco documentaries, and it would be significant in understanding the role of the narrative point of view as a tool for showing and telling in documentaries. Narrative analysis of a film forms an essential aspect of the discourse of scholarship in film studies. Narration is the chain of events occurring in time and space. The notion of narrative provides the idea of coherence and wholeness to the story. There are various components that the narration carries, one of which is the perspective or point of view. The narrator plays the role of a mediator between the film and the audience; thus, his perspective influences the way the audience interprets the film. Feature films have been analyzed through narrative points of view; however, this research intends to conduct it from the angle of a nature documentary film. The study will examine narrative viewpoints unique to nature documentary films using three ecological documentary films-The Cove (2009), Tale of a forest (2012), and Before the flood (2016). This research will apply the framework of narrative theory and will investigate the impact of the different types of narrative points of view, as each portrays the human-nature relationship from a different standpoint, and it will also study the effect that the narrative point of view has on the mode of these eco documentaries.

Keywords: ecodocumentary, narrative, human-nature relationship, point of view

Procedia PDF Downloads 76

Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

Procedia PDF Downloads 116

Authors: Hong-Ming Chen

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This work considers the resolution of the Hull and White interest rate model with the jump process. A deterministic process is adopted to model the random behavior of interest rate variation as deterministic perturbations, which is depending on the time t. The Brownian motion and jumps uncertainty are denoted as the integral functions piecewise constant function w(t) and point function θ(t). It shows that the interest rate function and the yield function of the Hull and White interest rate model with jump process can be obtained by solving a nonlinear semi-infinite programming problem. A relaxed cutting plane algorithm is then proposed for solving the resulting optimization problem. The method is calibrated for the U.S. treasury securities at 3-month data and is used to analyze several effects on interest rate prices, including interest rate variability, and the negative correlation between stock returns and interest rates. The numerical results illustrate that our approach essentially generates the yield functions with minimal fitting errors and small oscillation.

Keywords: optimization, interest rate model, jump process, deterministic

Procedia PDF Downloads 156