Abstract: One of the main research directions in CAD/CAM
machining area is the reducing of machining time.
The feedrate scheduling is one of the advanced techniques that
allows keeping constant the uncut chip area and as sequel to keep
constant the main cutting force. They are two main ways for feedrate
optimization. The first consists in the cutting force monitoring, which
presumes to use complex equipment for the force measurement and
after this, to set the feedrate regarding the cutting force variation. The
second way is to optimize the feedrate by keeping constant the
material removal rate regarding the cutting conditions.
In this paper there is proposed a new approach using an extended
database that replaces the system model.
The feedrate scheduling is determined based on the identification
of the reconfigurable machine tool, and the feed value determination
regarding the uncut chip section area, the contact length between tool
and blank and also regarding the geometrical roughness.
The first stage consists in the blank and tool monitoring for the
determination of actual profiles. The next stage is the determination
of programmed tool path that allows obtaining the piece target
profile.
The graphic representation environment models the tool and blank
regions and, after this, the tool model is positioned regarding the
blank model according to the programmed tool path. For each of
these positions the geometrical roughness value, the uncut chip area
and the contact length between tool and blank are calculated. Each of
these parameters are compared with the admissible values and
according to the result the feed value is established.
We can consider that this approach has the following advantages:
in case of complex cutting processes the prediction of cutting force is
possible; there is considered the real cutting profile which has
deviations from the theoretical profile; the blank-tool contact length
limitation is possible; it is possible to correct the programmed tool
path so that the target profile can be obtained.
Applying this method, there are obtained data sets which allow the
feedrate scheduling so that the uncut chip area is constant and, as a
result, the cutting force is constant, which allows to use more
efficiently the machine tool and to obtain the reduction of machining
time.
Abstract: This paper proposes a new technique for improving
the efficiency of software testing, which is based on a conventional
attempt to reduce test cases that have to be tested for any given
software. The approach utilizes the advantage of Regression Testing
where fewer test cases would lessen time consumption of the testing
as a whole. The technique also offers a means to perform test case
generation automatically. Compared to one of the techniques in the
literature where the tester has no option but to perform the test case
generation manually, the proposed technique provides a better
option. As for the test cases reduction, the technique uses simple
algebraic conditions to assign fixed values to variables (Maximum,
minimum and constant variables). By doing this, the variables values
would be limited within a definite range, resulting in fewer numbers
of possible test cases to process. The technique can also be used in
program loops and arrays.
Abstract: Hopfield model of associative memory is studied in this work. In particular, two main problems that it possesses: the apparition of spurious patterns in the learning phase, implying the well-known effect of storing the opposite pattern, and the problem of its reduced capacity, meaning that it is not possible to store a great amount of patterns without increasing the error probability in the retrieving phase. In this paper, a method to avoid spurious patterns is presented and studied, and an explanation of the previously mentioned effect is given. Another technique to increase the capacity of a network is proposed here, based on the idea of using several reference points when storing patterns. It is studied in depth, and an explicit formula for the capacity of the network with this technique is provided.
Abstract: Skin color is an important visual cue for computer
vision systems involving human users. In this paper we combine skin
color and optical flow for detection and tracking of skin regions. We
apply these techniques to gesture recognition with encouraging
results. We propose a novel skin similarity measure. For grouping
detected skin regions we propose a novel skin region grouping
mechanism. The proposed techniques work with any number of skin
regions making them suitable for a multiuser scenario.
Abstract: The aim of this research is to evaluate surface
roughness and develop a multiple regression model for surface roughness as a function of cutting parameters during the turning of
flame hardened medium carbon steel with TiN-Al2O3-TiCN coated inserts. An experimental plan of work and signal-to-noise ratio (S/N)
were used to relate the influence of turning parameters to the
workpiece surface finish utilizing Taguchi methodology. The effects
of turning parameters were studied by using the analysis of variance (ANOVA) method. Evaluated parameters were feed, cutting speed,
and depth of cut. It was found that the most significant interaction among the considered turning parameters was between depth of cut and feed. The average surface roughness (Ra) resulted by TiN-Al2O3-
TiCN coated inserts was about 2.44 μm and minimum value was 0.74 μm. In addition, the regression model was able to predict values for surface roughness in comparison with experimental values within
reasonable limit.
Abstract: In this paper, RSA encryption algorithm and its hardware
implementation in Xilinx-s Virtex Field Programmable Gate
Arrays (FPGA) is analyzed. The issues of scalability, flexible performance,
and silicon efficiency for the hardware acceleration of
public key crypto systems are being explored in the present work.
Using techniques based on the interleaved math for exponentiation,
the proposed RSA calculation architecture is compared to existing
FPGA-based solutions for speed, FPGA utilization, and scalability.
The paper covers the RSA encryption algorithm, interleaved multiplication,
Miller Rabin algorithm for primality test, extended Euclidean
math, basic FPGA technology, and the implementation details of
the proposed RSA calculation architecture. Performance of several
alternative hardware architectures is discussed and compared. Finally,
conclusion is drawn, highlighting the advantages of a fully flexible
& parameterized design.
Abstract: Abrasive Jet Machining is an Unconventional
machining process in which the metal is removed from brittle and
hard material in the form of micro-chips. With increase in need of
materials like ceramics, composites, in manufacturing of various
Mechanical & Electronic components, AJM has become a useful
technique for micro machining. The present study highlights the
influence of different parameters like Pressure, SOD, Time, Abrasive
grain size, nozzle diameter on the Metal removal of FRP (Fiber
Reinforced Polymer) composite by Abrasive jet machining. The
results of the Experiments conducted were analyzed and optimized
with TAGUCHI method of Optimization and ANOVA for Optimal
Value.
Abstract: Image mosaicing is a technique that permits to enlarge the field of view of a camera. For instance, it is employed to achieve panoramas with common cameras or even in scientific applications, to achieve the image of a whole culture in microscopical imaging. Usually, a mosaic of cell cultures is achieved through using automated microscopes. However, this is often performed in batch, through CPU intensive minimization algorithms. In addition, live stem cells are studied in phase contrast, showing a low contrast that cannot be improved further. We present a method to study the flat field from live stem cells images even in case of 100% confluence, this permitting to build accurate mosaics on-line using high performance algorithms.
Abstract: This paper presents a ray tracing simulation technique for characterize the radiowave propagation inside building. The implementation of an algorithm capable of enumerating a large number of propagation paths in interactive time for the special case of 2.5D. The effective dielectric constants of the building structure in the simulations are indicated. The study describes an efficient 2.5D model of ray tracing algorithm were compared with 3D model. The result of the first investigations is that the environment of the indoor wave significantly changes as we change the electric parameters of material constructions. A detailed analysis of the dependence of the indoor wave on the wideband characteristics of the channel: root mean square (RMS) delay spread characteristics and Mean excess delay, is also investigated.
Abstract: In this paper a hybrid technique of Genetic Algorithm
and Simulated Annealing (HGASA) is applied for Fractal Image
Compression (FIC). With the help of this hybrid evolutionary
algorithm effort is made to reduce the search complexity of matching
between range block and domain block. The concept of Simulated
Annealing (SA) is incorporated into Genetic Algorithm (GA) in order
to avoid pre-mature convergence of the strings. One of the image
compression techniques in the spatial domain is Fractal Image
Compression but the main drawback of FIC is that it involves more
computational time due to global search. In order to improve the
computational time along with acceptable quality of the decoded
image, HGASA technique has been proposed. Experimental results
show that the proposed HGASA is a better method than GA in terms
of PSNR for Fractal image Compression.
Abstract: This study compares family communication patterns in association with family socio-cultural status, especially marriage and family pattern, and couples- socio-economic status between Muslim and Santal communities in rural Bangladesh. A total of 288 couples, 145 couples from the Muslim and 143 couples from the Santal were randomly selected through cluster sampling procedure from Kalna village situated in Tanore Upazila of Rajshahi district of Bangladesh, where both the communities dwell as neighbors. In order to collect data from the selected samples, interview method with semistructural questionnaire schedule was applied. The responses given by the respondents were analyzed by Pearson-s chi-squire test and bivariate correlation techniques. The results of Pearson-s chi-squire test revealed that family communication patterns (X2= 25. 90, df= 2, p0.05) were significantly different between the Muslim and Santal communities. In addition, Spearman-s bivariate correlation coefficients suggested that among the exogenous factors, family type (rs=.135, p
Abstract: This paper present some preliminary work on the
preparation and physicochemical caracterization of nanocomposite
MFI-alumina structures based on alumina hollow fibres. The fibers
are manufactured by a wet spinning process. α-alumina particles were
dispersed in a solution of polysulfone in NMP. The resulting slurry is
pressed through the annular gap of a spinneret into a precipitation
bath. The resulting green fibres are sintered. The mechanical strength
of the alumina hollow fibres is determined by a three-point-bending
test while the pore size is characterized by bubble-point testing. The
bending strength is in the range of 110 MPa while the average pore
size is 450 nm for an internal diameter of 1 mm and external diameter
of 1.7 mm. To characterize the MFI membranes various techniques
were used for physicochemical characterization of MFI–ceramic
hollow fibres membranes: The nitrogen adsorption, X-ray
diffractometry, scanning electron microscopy combined with X
emission microanalysis. Scanning Electron Microscopy (SEM) and
Energy Dispersive Microanalysis by the X-ray were used to observe
the morphology of the hollow fibre membranes (thickness,
infiltration into the carrier, defects, homogeneity). No surface film,
has been obtained, as observed by SEM and EDX analysis and
confirmed by high temperature variation of N2 and CO2 gas
permeances before cation exchange. Local analysis and characterise
(SEM and EDX) and overall (by ICP elemental analysis) were
conducted on two samples exchanged to determine the quantity and
distribution of the cation of cesium on the cross section fibre of the
zeolite between the cavities.
Abstract: Achieving success is a highly critical issue for the
companies to survive in a competitive business environment. The
construction industry is also an area where there is strong
competition due to a large number of construction contractors. There
have been many factors such as qualified employees, quality
workmanship and financial management that can lead to company
success in the construction industry. The aim of this study was to
investigate the critical factors leading to construction company
success. Within this context, a survey was carried out among 40
Turkish construction companies which are located in the Northwest
region of Turkey. In this survey, top-level managers and owners of
the companies were interviewed. The interviews took place over a
five month period between January and May 2007. Finally, the
ranking of the critical success factors has been determined by using
the Simple Multi Attribute Rating Technique (SMART). Based on
the results, business management, financial conditions and
owner/manager characteristics were determined as the most
important factors to company success.
Abstract: Computer animation is a widely adopted technique used to specify the movement of various objects on screen. The key issue of this technique is the specification of motion. Motion Control Methods are such methods which are used to specify the actions of objects. This paper discusses the various types of motion control methods with special focus on behavioral animation. A behavioral model is also proposed which takes into account the emotions and perceptions of an actor which in turn generate its behavior. This model makes use of an expert system to generate tasks for the actors which specify the actions to be performed in the virtual environment.
Abstract: Repeated additions of the unfertilized bacteria led to
increase the activity of Nitrogen-fixing bacteria in the root zone with
drip irrigation system compared to traditional manual vaccination to
increase the proportion of Nitrogen from 29% to 64%, and the
efficiency of adding Nitrogen fertilizer did not exceed 9.5% while
dropped to 4%, due to the amount of fertilizer added was not exceed
20kg N/h, and the second was the existence of a large amount of
available Nitrogen in the soil by fixation, while the efficiency of
irrigation system between 2.08 to 2.26 kg/m3.
Abstract: Space Vector Modulation (SVM) is an optimum Pulse Width Modulation (PWM) technique for an inverter used in a variable frequency drive applications. It is computationally rigorous and hence limits the inverter switching frequency. Increase in switching frequency can be achieved using Neural Network (NN) based SVM, implemented on application specific chips. This paper proposes a neural network based SVM technique for a Voltage Source Inverter (VSI). The network proposed is independent of switching frequency. Different architectures are investigated keeping the total number of neurons constant. The performance of the inverter is compared for various switching frequencies for different architectures of NN based SVM. From the results obtained, the network with minimum resource and appropriate word length is identified. The bit precision required for this application is identified. The network with 8-bit precision is implemented in the IC XCV 400 and the results are presented. The performance of NN based general purpose SVM with higher bit precision is discussed.
Abstract: In this paper, many techniques for blind identification of moving average (MA) process are presented. These methods utilize third- and fourth-order cumulants of the noisy observations of the system output. The system is driven by an independent and identically distributed (i.i.d) non-Gaussian sequence that is not observed. Two nonlinear optimization algorithms, namely the Gradient Descent and the Gauss-Newton algorithms are exposed. An algorithm based on the joint-diagonalization of the fourth-order cumulant matrices (FOSI) is also considered, as well as an improved version of the classical C(q, 0, k) algorithm based on the choice of the Best 1-D Slice of fourth-order cumulants. To illustrate the effectiveness of our methods, various simulation examples are presented.
Abstract: This study assessed the effects of climate change on
Thai soybeans under simulation situations. Our study is focused on
temperature variability and effects on growth, yield, and genetic
changes in 2 generations of Chiang Mai 60 cultivars. In the
experiment, soybeans were exposed to 3 levels of air temperature for
8 h day-1 in an open top chamber for 2 cropping periods. Air
temperature levels in each treatment were controlled at 30-33°C (±
2.3) for LT-treatment, 33-36°C ( ± 2.4) for AT-treatment, and 36-40
°C ( ± 3.2) for HT-treatment, respectively. Positive effects of high
temperature became obvious at the maturing stage when yield
significantly increased in both cropping periods. Results in growth
indicated that shoot length at the pre-maturing stage
(V3-R3) was more positively affected by high temperature than at the
maturing stage. However, the positive effect on growth under high
temperature was not found in the 2nd cropping period. Finally, genetic
changes were examined in phenotype characteristics by the AFLPs
technique. The results showed that the high temperature factor clearly
caused genetic change in the soybeans and showed more alteration in
the 2nd cropping period.
Abstract: The running logs of a process hold valuable
information about its executed activity behavior and generated activity
logic structure. Theses informative logs can be extracted, analyzed and
utilized to improve the efficiencies of the process's execution and
conduction. One of the techniques used to accomplish the process
improvement is called as process mining. To mine similar processes is
such an improvement mission in process mining. Rather than directly
mining similar processes using a single comparing coefficient or a
complicate fitness function, this paper presents a simplified heuristic
process mining algorithm with two similarity comparisons that are
able to relatively conform the activity logic sequences (traces) of
mining processes with those of a normalized (regularized) one. The
relative process conformance is to find which of the mining processes
match the required activity sequences and relationships, further for
necessary and sufficient applications of the mined processes to process
improvements. One similarity presented is defined by the relationships
in terms of the number of similar activity sequences existing in
different processes; another similarity expresses the degree of the
similar (identical) activity sequences among the conforming processes.
Since these two similarities are with respect to certain typical behavior
(activity sequences) occurred in an entire process, the common
problems, such as the inappropriateness of an absolute comparison and
the incapability of an intrinsic information elicitation, which are often
appeared in other process conforming techniques, can be solved by the
relative process comparison presented in this paper. To demonstrate
the potentiality of the proposed algorithm, a numerical example is
illustrated.
Abstract: In this paper, a neural network technique is applied to
real-time classifying media while a projectile is penetrating through
them. A laboratory-scaled penetrating setup was built for the
experiment. Features used as the network inputs were extracted from
the acceleration of penetrator. 6000 set of features from a single
penetration with known media and status were used to train the neural
network. The trained system was tested on 30 different penetration
experiments. The system produced an accuracy of 100% on the
training data set. And, their precision could be 99% for the test data
from 30 tests.