A Dynamic Hybrid Option Pricing Model by Genetic Algorithm and Black- Scholes Model

Unlike this study focused extensively on trading behavior of option market, those researches were just taken their attention to model-driven option pricing. For example, Black-Scholes (B-S) model is one of the most famous option pricing models. However, the arguments of B-S model are previously mentioned by some pricing models reviewing. This paper following suggests the importance of the dynamic character for option pricing, which is also the reason why using the genetic algorithm (GA). Because of its natural selection and species evolution, this study proposed a hybrid model, the Genetic-BS model which combining GA and B-S to estimate the price more accurate. As for the final experiments, the result shows that the output estimated price with lower MAE value than the calculated price by either B-S model or its enhanced one, Gram-Charlier garch (G-C garch) model. Finally, this work would conclude that the Genetic-BS pricing model is exactly practical.

On the Verification of Power Nap Associated with Stage 2 Sleep and Its Application

One of the most important causes of accidents is driver fatigue. To reduce the accidental rate, the driver needs a quick nap when feeling sleepy. Hence, searching for the minimum time period of nap is a very challenging problem. The purpose of this paper is twofold, i.e. to investigate the possible fastest time period for nap and its relationship with stage 2 sleep, and to develop an automatic stage 2 sleep detection and alarm device. The experiment for this investigation is designed with 21 subjects. It yields the result that waking up the subjects after getting into stage 2 sleep for 3-5 minutes can efficiently reduce the sleepiness. Furthermore, the automatic stage 2 sleep detection and alarm device yields the real-time detection accuracy of approximately 85% which is comparable with the commercial sleep lab system.

Selective Minterms Based Tabular Method for BDD Manipulations

The goal of this work is to describe a new algorithm for finding the optimal variable order, number of nodes for any order and other ROBDD parameters, based on a tabular method. The tabular method makes use of a pre-built backend database table that stores the ROBDD size for selected combinations of min-terms. The user uses the backend table and the proposed algorithm to find the necessary ROBDD parameters, such as best variable order, number of nodes etc. Experimental results on benchmarks are given for this technique.

Optimal Control Strategy for High Performance EV Interior Permanent Magnet Synchronous Motor

The controllable electrical loss which consists of the copper loss and iron loss can be minimized by the optimal control of the armature current vector. The control algorithm of current vector minimizing the electrical loss is proposed and the optimal current vector can be decided according to the operating speed and the load conditions. The proposed control algorithm is applied to the experimental PM motor drive system and this paper presents a modern approach of speed control for permanent magnet synchronous motor (PMSM) applied for Electric Vehicle using a nonlinear control. The regulation algorithms are based on the feedback linearization technique. The direct component of the current is controlled to be zero which insures the maximum torque operation. The near unity power factor operation is also achieved. More over, among EV-s motor electric propulsion features, the energy efficiency is a basic characteristic that is influenced by vehicle dynamics and system architecture. For this reason, the EV dynamics are taken into account.

Torsion Behavior of Steel Fibered High Strength Self Compacting Concrete Beams Reinforced by GFRB Bars

This paper investigates experimentally and analytically the torsion behavior of steel fibered high strength self compacting concrete beams reinforced by GFRP bars. Steel fibered high strength self compacting concrete (SFHSSCC) and GFRP bars became in the recent decades a very important materials in the structural engineering field. The use of GFRP bars to replace steel bars has emerged as one of the many techniques put forward to enhance the corrosion resistance of reinforced concrete structures. High strength concrete and GFRP bars attract designers and architects as it allows improving the durability as well as the esthetics of a construction. One of the trends in SFHSSCC structures is to provide their ductile behavior and additional goal is to limit development and propagation of macro-cracks in the body of SFHSSCC elements. SFHSSCC and GFRP bars are tough, improve the workability, enhance the corrosion resistance of reinforced concrete structures, and demonstrate high residual strengths after appearance of the first crack. Experimental studies were carried out to select effective fiber contents. Three types of volume fraction from hooked shape steel fibers are used in this study, the hooked steel fibers were evaluated in volume fractions ranging between 0.0%, 0.75% and 1.5%. The beams shape is chosen to create the required forces (i.e. torsion and bending moments simultaneously) on the test zone. A total of seven beams were tested, classified into three groups. All beams, have 200cm length, cross section of 10×20cm, longitudinal bottom reinforcement of 3

Using Swarm Intelligence for Improving Accuracy of Fuzzy Classifiers

This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle swarm optimization (PSO). Two different fuzzy classifiers are considered and optimized. The first classifier is based on Mamdani fuzzy inference system (M_PSO fuzzy classifier). The second classifier is based on Takagi- Sugeno fuzzy inference system (TS_PSO fuzzy classifier). The parameters of the proposed fuzzy classifiers including premise (antecedent) parameters, consequent parameters and structure of fuzzy rules are optimized using PSO. Experimental results show that higher classification accuracy can be obtained with a lower number of fuzzy rules by using the proposed PSO fuzzy classifiers. The performances of M_PSO and TS_PSO fuzzy classifiers are compared to other fuzzy based classifiers

VoIP and Database Traffic Co-existence over IEEE 802.11b WLAN with Redundancy

This paper presents the findings of two experiments that were performed on the Redundancy in Wireless Connection Model (RiWC) using the 802.11b standard. The experiments were simulated using OPNET 11.5 Modeler software. The first was aimed at finding the maximum number of simultaneous Voice over Internet Protocol (VoIP) users the model would support under the G.711 and G.729 codec standards when the packetization interval was 10 milliseconds (ms). The second experiment examined the model?s VoIP user capacity using the G.729 codec standard along with background traffic using the same packetization interval as in the first experiment. To determine the capacity of the model under various experiments, we checked three metrics: jitter, delay and data loss. When background traffic was added, we checked the response time in addition to the previous three metrics. The findings of the first experiment indicated that the maximum number of simultaneous VoIP users the model was able to support was 5, which is consistent with recent research findings. When using the G.729 codec, the model was able to support up to 16 VoIP users; similar experiments in current literature have indicated a maximum of 7 users. The finding of the second experiment demonstrated that the maximum number of VoIP users the model was able to support was 12, with the existence of background traffic.

A Robust Audio Fingerprinting Algorithm in MP3 Compressed Domain

In this paper, a new robust audio fingerprinting algorithm in MP3 compressed domain is proposed with high robustness to time scale modification (TSM). Instead of simply employing short-term information of the MP3 stream, the new algorithm extracts the long-term features in MP3 compressed domain by using the modulation frequency analysis. Our experiment has demonstrated that the proposed method can achieve a hit rate of above 95% in audio retrieval and resist the attack of 20% TSM. It has lower bit error rate (BER) performance compared to the other algorithms. The proposed algorithm can also be used in other compressed domains, such as AAC.

One Dimensional Object Segmentation and Statistical Features of an Image for Texture Image Recognition System

Traditional object segmentation methods are time consuming and computationally difficult. In this paper, onedimensional object detection along the secant lines is applied. Statistical features of texture images are computed for the recognition process. Example matrices of these features and formulae for calculation of similarities between two feature patterns are expressed. And experiments are also carried out using these features.

Robot Control by ERPs of Brain Waves

This paper presented the technique of robot control by event-related potentials (ERPs) of brain waves. Based on the proposed technique, severe physical disabilities can free browse outside world. A specific component of ERPs, N2P3, was found and used to control the movement of robot and the view of camera on the designed brain-computer interface (BCI). Users only required watching the stimuli of attended button on the BCI, the evoked potentials of brain waves of the target button, N2P3, had the greatest amplitude among all control buttons. An experimental scene had been constructed that the robot required walking to a specific position and move the view of camera to see the instruction of the mission, and then completed the task. Twelve volunteers participated in this experiment, and experimental results showed that the correct rate of BCI control achieved 80% and the average of execution time was 353 seconds for completing the mission. Four main contributions included in this research: (1) find an efficient component of ERPs, N2P3, for BCI control, (2) embed robot's viewpoint image into user interface for robot control, (3) design an experimental scene and conduct the experiment, and (4) evaluate the performance of the proposed system for assessing the practicability.

A Hidden Markov Model-Based Isolated and Meaningful Hand Gesture Recognition

Gesture recognition is a challenging task for extracting meaningful gesture from continuous hand motion. In this paper, we propose an automatic system that recognizes isolated gesture, in addition meaningful gesture from continuous hand motion for Arabic numbers from 0 to 9 in real-time based on Hidden Markov Models (HMM). In order to handle isolated gesture, HMM using Ergodic, Left-Right (LR) and Left-Right Banded (LRB) topologies is applied over the discrete vector feature that is extracted from stereo color image sequences. These topologies are considered to different number of states ranging from 3 to 10. A new system is developed to recognize the meaningful gesture based on zero-codeword detection with static velocity motion for continuous gesture. Therefore, the LRB topology in conjunction with Baum-Welch (BW) algorithm for training and forward algorithm with Viterbi path for testing presents the best performance. Experimental results show that the proposed system can successfully recognize isolated and meaningful gesture and achieve average rate recognition 98.6% and 94.29% respectively.

Failure Analysis of Methanol Evaporator

Thermal water hammer is a special type of water hammer which rarely occurs in heat exchangers. In biphasic fluids, if steam bubbles are surrounded by condensate, regarding lower condensate temperature than steam, they will suddenly collapse. As a result, the vacuum caused by an extreme change in volume lead to movement of the condensates in all directions and their collision the force produced by this collision leads to a severe stress in the pipe wall. This phenomenon is a special type of water hammer. According to fluid mechanics, this phenomenon is a particular type of transient flows during which abrupt change of fluid leads to sudden pressure change inside the tube. In this paper, the mechanism of abrupt failure of 80 tubes of 481 tubes of a methanol heat exchanger is discussed. Initially, due to excessive temperature differences between heat transfer fluids and simultaneous failure of 80 tubes, thermal shock was presupposed as the reason of failure. Deeper investigation on cross-section of failed tubes showed that failure was, ductile type of failure, so the first hypothesis was rejected. Further analysis and more accurate experiments revealed that failure of tubes caused by thermal water hammer. Finally, the causes of thermal water hammer and various solutions to avoid such mechanism are discussed.

Intervention of Sambucus Nigra Polyphenolic Extract in Experimental Arterial Hypertension

The research focuses on the effects of polyphenols extracted from Sambucus nigra fruit, using an experimental arterial hypertension pattern, as well as their influence on the oxidative stress. The results reveal the normalization of the reduced glutathion concentration, as well as a considerable reduction in the malondialdehide serum concentration by the polyphenolic protection. The rat blood pressure values were recorded using a CODATM system, which uses a non-invasive blood pressure measuring method. All the measured blood pressure components revealed a biostatistically significant (p

Adaptive Weighted Averaging Filter Using the Appropriate Number of Consecutive Frames

In this paper, we propose a novel adaptive spatiotemporal filter that utilizes image sequences in order to remove noise. The consecutive frames include: current, previous and next noisy frames. The filter proposed in this paper is based upon the weighted averaging pixels intensity and noise variance in image sequences. It utilizes the Appropriate Number of Consecutive Frames (ANCF) based on the noisy pixels intensity among the frames. The number of consecutive frames is adaptively calculated for each region in image and its value may change from one region to another region depending on the pixels intensity within the region. The weights are determined by a well-defined mathematical criterion, which is adaptive to the feature of spatiotemporal pixels of the consecutive frames. It is experimentally shown that the proposed filter can preserve image structures and edges under motion while suppressing noise, and thus can be effectively used in image sequences filtering. In addition, the AWA filter using ANCF is particularly well suited for filtering sequences that contain segments with abruptly changing scene content due to, for example, rapid zooming and changes in the view of the camera.

Influence of Jerusalem Artichoke Powder on the Nutritional Value of Pastry Products

From year to year, the incidence of different diseases is increasing in humans, and the cause is inadequate intake of dietary fibre, vitamins, and minerals. One of the possibilities to take care of your health preventively is including in the diet products with increased dietary fibre, vitamin, and mineral content.Jerusalem artichoke powder (JAP) made from Jerusalem artichoke (Helianthus tuberosus L) roots is a valuable product. By adding it to pastry goods, we can obtain a fibre-rich food that could be healthier and an excellent alternative to the classical pastry products of this kind.Experiments were carried out at the Faculty of Food Technology of Latvia University of Agriculture (LLU). Results of experiments showed that addition of Jerusalem artichoke powder has significant impact on all the studied pastry products nutritional value (p

A Learning-Community Recommendation Approach for Web-Based Cooperative Learning

Cooperative learning has been defined as learners working together as a team to solve a problem to complete a task or to accomplish a common goal, which emphasizes the importance of interactions among members to promote the whole learning performance. With the popularity of society networks, cooperative learning is no longer limited to traditional classroom teaching activities. Since society networks facilitate to organize online learners, to establish common shared visions, and to advance learning interaction, the online community and online learning community have triggered the establishment of web-based societies. Numerous research literatures have indicated that the collaborative learning community is a critical issue to enhance learning performance. Hence, this paper proposes a learning community recommendation approach to facilitate that a learner joins the appropriate learning communities, which is based on k-nearest neighbor (kNN) classification. To demonstrate the viability of the proposed approach, the proposed approach is implemented for 117 students to recommend learning communities. The experimental results indicate that the proposed approach can effectively recommend appropriate learning communities for learners.

Mechanical Modeling Issues in Optimization of Dynamic Behavior of RF MEMS Switches

This paper details few mechanical modeling and design issues of RF MEMS switches. We concentrate on an electrostatically actuated broad side series switch; surface micromachined with a crab leg membrane. The same results are extended to any complex structure. With available experimental data and fabrication results, we present the variation in dynamic performance and compliance of the switch with reference to few design issues, which we find are critical in deciding the dynamic behavior of the switch, without compromise on the RF characteristics. The optimization of pull in voltage, transient time and resonant frequency with regard to these critical design parameters are also presented.

Utilization of EAF Reducing Slag from Stainless Steelmaking Process as a Sorbent for CO2

In this study, an experimental investigation was carried out to fix CO2 into the electronic arc furnace (EAF) reducing slag from stainless steelmaking process under wet grinding. The slag was ground by the vibrating ball mill with the CO2 and pure water. The reaction behavior was monitored with constant pressure method, and the change of CO2 volume in the experimental system with grinding time was measured. It was found that the CO2 absorption occurred as soon as the grinding started. The CO2 absorption under wet grinding was significantly larger than that under dry grinding. Generally, the amount of CO2 absorption increased as the amount of water, the amount of slag, the diameter of alumina ball and the initial pressure of CO2 increased. However, the initial absorption rate was scarcely influenced by the experimental conditions except for the initial CO2 pressure. According to this research, the CO2 reacted with the CaO inside the slag to form CaCO3.

A WIP Control Based On an Intelligent Controller

In this study, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive output recurrent cerebellar model articulation control (AORCMAC) and H∞ control technique is proposed for wheeled inverted pendulums (WIPs) real-time control with exact system dynamics unknown. Moreover, a robust H∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. The experimental results indicate that the WIPs can stand upright stably when using the proposed RIBTC.

Globally Convergent Edge-preserving Reconstruction with Contour-line Smoothing

The standard approach to image reconstruction is to stabilize the problem by including an edge-preserving roughness penalty in addition to faithfulness to the data. However, this methodology produces noisy object boundaries and creates a staircase effect. The existing attempts to favor the formation of smooth contour lines take the edge field explicitly into account; they either are computationally expensive or produce disappointing results. In this paper, we propose to incorporate the smoothness of the edge field in an implicit way by means of an additional penalty term defined in the wavelet domain. We also derive an efficient half-quadratic algorithm to solve the resulting optimization problem, including the case when the data fidelity term is non-quadratic and the cost function is nonconvex. Numerical experiments show that our technique preserves edge sharpness while smoothing contour lines; it produces visually pleasing reconstructions which are quantitatively better than those obtained without wavelet-domain constraints.