Abstract: In the present work, we propose a new method for
solving the matrix equation AXB=F . The new method can
be considered as a generalized form of the well-known global full
orthogonalization method (Gl-FOM) for solving multiple linear
systems. Hence, the method will be called extended Gl-FOM (EGl-
FOM). For implementing EGl-FOM, generalized forms of block
Krylov subspace and global Arnoldi process are presented. Finally,
some numerical experiments are given to illustrate the efficiency of
our new method.
Abstract: The paper proposes and validates a new method of solving instances of the vehicle routing problem (VRP). The approach is based on a multiple agent system paradigm. The paper contains the VRP formulation, an overview of the multiple agent environment used and a description of the proposed implementation. The approach is validated experimentally. The experiment plan and the discussion of experiment results follow.
Abstract: In this paper, an alternating implicit block method for
solving two dimensional scalar wave equation is presented. The
new method consist of two stages for each time step implemented
in alternating directions which are very simple in computation. To
increase the speed of computation, a group of adjacent points is
computed simultaneously. It is shown that the presented method
increase the maximum time step size and more accurate than the
conventional finite difference time domain (FDTD) method and other
existing method of natural ordering.
Abstract: In this paper, we show that the stability can not be
achieved with current stabilizing MPC methods for some unstable
processes. Hence we present a new method for stabilizing these
processes. The main idea is to use a new time varying weighted cost
function for traditional GPC. This stabilizes the closed loop system
without adding soft or hard constraint in optimization problem. By
studying different examples it is shown that using the proposed
method, the closed-loop stability of unstable nonminimum phase
process is achieved.
Abstract: In this paper, we propose a new method to distinguish
between arousal and relaxation states by using multiple features
acquired from a photoplethysmogram (PPG) and support vector
machine (SVM). To induce arousal and relaxation states in subjects, 2
kinds of sound stimuli are used, and their corresponding biosignals are
obtained using the PPG sensor. Two features–pulse to pulse interval
(PPI) and pulse amplitude (PA)–are extracted from acquired PPG
data, and a nonlinear classification between arousal and relaxation is
performed using SVM.
This methodology has several advantages when compared with
previous similar studies. Firstly, we extracted 2 separate features from
PPG, i.e., PPI and PA. Secondly, in order to improve the classification
accuracy, SVM-based nonlinear classification was performed.
Thirdly, to solve classification problems caused by generalized
features of whole subjects, we defined each threshold according to
individual features.
Experimental results showed that the average classification
accuracy was 74.67%. Also, the proposed method showed the better
identification performance than the single feature based methods.
From this result, we confirmed that arousal and relaxation can be
classified using SVM and PPG features.
Abstract: Pyrite (FeS2) is a promising candidate for cathode
materials in batteries because of it`s high theoretical capacity, low
cost and non-toxicity. In this study, nano size iron disulfide thin film
was prepared on graphite substrate through a new method as battery
cathode. In this way, acetylene black and poly vinylidene fluoride
were used as electron conductor and binder, respectively. Fabricated
thin films were analyzed by XRD and SEM. These results and
electrochemical data confirm improvement of battery discharge
capacity in comparison with commercial type of pyrite.
Abstract: SVM ( Support Vector Machine ) is a new method in the artificial neural network ( ANN ). In the steel making, how to use computer to predict the end point of BOF accuracy is a great problem. A lot of method and theory have been claimed, but most of the results is not satisfied. Now the hot topic in the BOF end point predicting is to use optical way the predict the end point in the BOF. And we found that there exist some regular in the characteristic curve of the flame from the mouse of pudding. And we can use SVM to predict end point of the BOF, just single spectrum intensity should be required as the input parameter. Moreover, its compatibility for the input space is better than the BP network.
Abstract: In the last years numerous applications of Human-
Computer Interaction have exploited the capabilities of Time-of-
Flight cameras for achieving more and more comfortable and precise
interactions. In particular, gesture recognition is one of the most active
fields. This work presents a new method for interacting with a virtual
object in a 3D space. Our approach is based on the fusion of depth
data, supplied by a ToF camera, with color information, supplied
by a HD webcam. The hand detection procedure does not require
any learning phase and is able to concurrently manage gestures of
two hands. The system is robust to the presence in the scene of
other objects or people, thanks to the use of the Kalman filter for
maintaining the tracking of the hands.
Abstract: Electromagnetic flowmeters with DC excitation are used for a wide range of fluid measurement tasks, but are rarely found in dosing applications with short measurement cycles due to the achievable accuracy. This paper will identify a number of factors that influence the accuracy of this sensor type when used for short-term measurements. Based on these results a new signal-processing algorithm will be described that overcomes the identified problems to some extend. This new method allows principally a higher accuracy of electromagnetic flowmeters with DC excitation than traditional methods.
Abstract: Resource discovery is one of the chief services of a grid. A new approach to discover the provenances in grid through learning automata has been propounded in this article. The objective of the aforementioned resource-discovery service is to select the resource based upon the user-s applications and the mercantile yardsticks that is to say opting for an originator which can accomplish the user-s tasks in the most economic manner. This novel service is submitted in two phases. We proffered an applicationbased categorization by means of an intelligent nerve-prone plexus. The user in question sets his or her application as the input vector of the nerve-prone nexus. The output vector of the aforesaid network limns the appropriateness of any one of the resource for the presented executive procedure. The most scrimping option out of those put forward in the previous stage which can be coped with to fulfill the task in question is picked out. Te resource choice is carried out by means of the presented algorithm based upon the learning automata.
Abstract: The one of best robust search technique on large scale
search area is heuristic and meta heuristic approaches. Especially in
issue that the exploitation of combinatorial status in the large scale
search area prevents the solution of the problem via classical
calculating methods, so such problems is NP-complete. in this
research, the problem of winner determination in combinatorial
auctions have been formulated and by assessing older heuristic
functions, we solve the problem by using of genetic algorithm and
would show that this new method would result in better performance
in comparison to other heuristic function such as simulated annealing
greedy approach.
Abstract: Limited infrastructure development on peats and
organic soils is a serious geotechnical issues common to many
countries of the world especially Malaysia which distributed 1.5 mill
ha of those problematic soil. These soils have high water content and
organic content which exhibit different mechanical properties and
may also change chemically and biologically with time. Constructing
structures on peaty ground involves the risk of ground failure and
extreme settlement. Nowdays, much efforts need to be done in
making peatlands usable for construction due to increased landuse.
Deep mixing method employing cement as binders, is generally used
as measure again peaty/ organic ground failure problem. Where the
technique is widely adopted because it can improved ground
considerably in a short period of time. An understanding of
geotechnical properties as shear strength, stiffness and compressibility
behavior of these soils was requires before continues construction on
it. Therefore, 1- 1.5 meter peat soil sample from states of Johor and
an organic soil from Melaka, Malaysia were investigated. Cement
were added to the soil in the pre-mixing stage with water cement ratio
at range 3.5,7,14,140 for peats and 5,10,30 for organic soils,
essentially to modify the original soil textures and properties. The
mixtures which in slurry form will pour to polyvinyl chloride (pvc)
tube and cured at room temperature 250C for 7,14 and 28 days.
Laboratory experiments were conducted including unconfined
compressive strength and bender element , to monitor the improved
strength and stiffness of the 'stabilised mixed soils'. In between,
scanning electron miscroscopic (SEM) were observations to
investigate changes in microstructures of stabilised soils and to
evaluated hardening effect of a peat and organic soils stabilised
cement. This preliminary effort indicated that pre-mixing peat and
organic soils contributes in gaining soil strength while help the
engineers to establish a new method for those problematic ground
improvement in further practical and long term applications.
Abstract: We address the problem of joint beamforming and multipath channel parameters estimation in Wideband Code Division Multiple Access (WCDMA) communication systems that employ Multiple-Access Interference (MAI) suppression techniques in the uplink (from mobile to base station). Most of the existing schemes rely on time multiplex a training sequence with the user data. In WCDMA, the channel parameters can also be estimated from a code multiplexed common pilot channel (CPICH) that could be corrupted by strong interference resulting in a bad estimate. In this paper, we present new methods to combine interference suppression together with channel estimation when using multiple receiving antennas by using adaptive signal processing techniques. Computer simulation is used to compare between the proposed methods and the existing conventional estimation techniques.
Abstract: In this article, our objective is the analysis of the resolution of non-linear differential systems by combining Newton and Continuation (N-C) method. The iterative numerical methods converge where the initial condition is chosen close to the exact solution. The question of choosing the initial condition is answered by N-C method.
Abstract: In the present article, a new method has been developed to enhance the application of equipment monitoring, which in turn results in improving condition-based maintenance economic impact in an automobile parts manufacturing factory. This study also describes how an effective software with a simple database can be utilized to achieve cost-effective improvements in maintenance performance. The most important results of this project are indicated here: 1. 63% reduction in direct and indirect maintenance costs. 2. Creating a proper database to analyse failures. 3. Creating a method to control system performance and develop it to similar systems. 4. Designing a software to analyse database and consequently create technical knowledge to face unusual condition of the system. Moreover, the results of this study have shown that the concept and philosophy of maintenance has not been understood in most Iranian industries. Thus, more investment is strongly required to improve maintenance conditions.
Abstract: This paper shows a new method for design of fuzzy observers for Takagi-Sugeno systems. The method is based on Linear matrix inequalities (LMIs) and it allows to insert H constraint into the design procedure. The speed of estimation can tuned be specification of a decay rate of the observer closed loop system. We discuss here also the influence of parametric uncertainties at the output control system stability.
Abstract: Architecture as a form of art, whilst actively
developing, finds new methods and conceptions. Currently,
architectural animation is actively developing as a step, successive to
architectural visualization. Interesting vistas of architectural ideas
were discovered by artists of Japanese animation, in which there are
traditional spirits, kami, and imaginary spaces relating to them.
Anime art should be considered abstract painting, another kind of an
architectural workshop, where new architectural ideas are generated.
Abstract: New methodologies for XOR-XNOR circuits are
proposed to improve the speed and power as these circuits are basic
building blocks of many arithmetic circuits. This paper evaluates and
compares the performance of various XOR-XNOR circuits. The
performance of the XOR-XNOR circuits based on TSMC 0.18μm
process models at all range of the supply voltage starting from 0.6V
to 3.3V is evaluated by the comparison of the simulation results
obtained from HSPICE. Simulation results reveal that the proposed
circuit exhibit lower PDP and EDP, more power efficient and faster
when compared with best available XOR-XNOR circuits in the
literature.
Abstract: In most rule-induction algorithms, the only operator used against nominal attributes is the equality operator =. In this paper, we first propose the use of the inequality operator, ≠, in addition to the equality operator, to increase the expressiveness of induced rules. Then, we present a new method, Binary Coding, which can be used along with an arbitrary rule-induction algorithm to make use of the inequality operator without any need to change the algorithm. Experimental results suggest that the Binary Coding method is promising enough for further investigation, especially in cases where the minimum number of rules is desirable.
Abstract: This paper proposes a new methodology for the
optimal allocation and sizing of Embedded Generation (EG)
employing Real Coded Genetic Algorithm (RCGA) to minimize the
total power losses and to improve voltage profiles in the radial
distribution networks. RCGA is a method that uses continuous
floating numbers as representation which is different from
conventional binary numbers. The RCGA is used as solution tool,
which can determine the optimal location and size of EG in radial
system simultaneously. This method is developed in MATLAB. The
effect of EG units- installation and their sizing to the distribution
networks are demonstrated using 24 bus system.