Abstract: This paper presents a system for tracking the movement of laparoscopic instruments which is based on an orthogonal system of webcams and video image processing. The movements are captured with two webcams placed orthogonally inside of the physical trainer. On the image, the instruments were detected by using color markers placed on the distal tip of each instrument. The 3D position of the tip of the instrument within the work space was obtained by linear triangulation method. Preliminary results showed linearity and repeatability in the motion tracking with a resolution of 0.616 mm in each axis; the accuracy of the system showed a 3D instrument positioning error of 1.009 ± 0.101 mm. This tool is a portable and low-cost alternative to traditional tracking devices and a trustable method for the objective evaluation of the surgeon’s surgical skills.
Abstract: Streaming Applications usually run in parallel or in
series that incrementally transform a stream of input data. It poses a
design challenge to break such an application into distinguishable
blocks and then to map them into independent hardware processing
elements. For this, there is required a generic controller that
automatically maps such a stream of data into independent processing
elements without any dependencies and manual considerations. In
this paper, Kahn Process Networks (KPN) for such streaming
applications is designed and developed that will be mapped on
MPSoC. This is designed in such a way that there is a generic Cbased
compiler that will take the mapping specifications as an input
from the user and then it will automate these design constraints and
automatically generate the synthesized RTL optimized code for
specified application.
Abstract: In this paper, all-optical signal processors that perform
both microwave mixing and bandpass filtering in a radio-over-fiber
(RoF) link are presented. The key device is a Mach-Zehnder
modulator (MZM) which performs all-optical microwave mixing. An
up-converted microwave signal is obtained and other unwanted
frequency components are suppressed at the end of the fiber span.
Abstract: Ethanol has been known for a long time, being
perhaps the oldest product obtained through traditional biotechnology
fermentation. Agriculture waste as substrate in fermentation is vastly
discussed as alternative to replace edible food and utilization of
organic material. Pineapple peel, highly potential source as substrate
is a by-product of the pineapple processing industry. Bio-ethanol
from pineapple (Ananas comosus) peel extract was carried out by
controlling fermentation without any treatment. Saccharomyces
ellipsoides was used as inoculum in this fermentation process as it is
naturally found at the pineapple skin. In this study, the capability of
Response Surface Methodology (RSM) for optimization of ethanol
production from pineapple peel extract using Saccharomyces
ellipsoideus in batch fermentation process was investigated. Effect of
five test variables in a defined range of inoculum concentration 6-
14% (v/v), pH (4.0-6.0), sugar concentration (14-22°Brix),
temperature (24-32°C) and time of incubation (30-54 hrs) on the
ethanol production were evaluated. Data obtained from experiment
were analyzed with RSM of MINITAB Software (Version 15)
whereby optimum ethanol concentration of 8.637% (v/v) was
determined. The optimum condition of 14% (v/v) inoculum
concentration, pH 6, 22°Brix, 26°C and 30hours of incubation. The
significant regression equation or model at the 5% level with
correlation value of 99.96% was also obtained.
Abstract: Using the animations video of teaching materials is an
effective learning method. However, we thought that more effective learning method is to produce the teaching video by learners
themselves. The learners who act as the producer must learn and understand well to produce and present video of teaching materials to
others. The purpose of this study is to propose the project based learning (PBL) technique by co-producing video of IT (information
technology) teaching materials. We used the T2V player to produce
the video based on TVML a TV program description language. By
proposed method, we have assigned the learners to produce the
animations video for “National Examination for Information
Processing Technicians (IPA examination)" in Japan, in order to get
them learns various knowledge and skill on IT field. Experimental
result showed that learning effect has occurred at the video production
process that useful for IT personnel resources development.
Abstract: Motion estimation is a key problem in video
processing and computer vision. Optical flow motion estimation can
achieve high estimation accuracy when motion vector is small.
Three-step search algorithm can handle large motion vector but not
very accurate. A joint algorithm was proposed in this paper to
achieve high estimation accuracy disregarding whether the motion
vector is small or large, and keep the computation cost much lower
than full search.
Abstract: The fuzzy technique is an operator introduced in order
to simulate at a mathematical level the compensatory behavior in
process of decision making or subjective evaluation. The following
paper introduces such operators on hand of computer vision
application.
In this paper a novel method based on fuzzy logic reasoning
strategy is proposed for edge detection in digital images without
determining the threshold value. The proposed approach begins by
segmenting the images into regions using floating 3x3 binary matrix.
The edge pixels are mapped to a range of values distinct from each
other. The robustness of the proposed method results for different
captured images are compared to those obtained with the linear Sobel
operator. It is gave a permanent effect in the lines smoothness and
straightness for the straight lines and good roundness for the curved
lines. In the same time the corners get sharper and can be defined
easily.
Abstract: One of the disadvantages of using OFDM is the larger
peak to averaged power ratio (PAPR) in its time domain signal. The
larger PAPR signal would course the fatal degradation of bit error
rate performance (BER) due to the inter-modulation noise in the nonlinear
channel. This paper proposes an improved DSI (Dummy
Sequence Insertion) method, which can achieve the better PAPR and
BER performances. The feature of proposed method is to optimize
the phase of each dummy sub-carrier so as to reduce the PAPR
performance by changing all predetermined phase coefficients in the
time domain signal, which is calculated for data sub-carriers and
dummy sub-carriers separately. To achieve the better PAPR
performance, this paper also proposes to employ the time-frequency
domain swapping algorithm for fine adjustment of phase coefficient
of the dummy subcarriers, which can achieve the less complexity of
processing and achieves the better PAPR and BER performances
than those for the conventional DSI method. This paper presents
various computer simulation results to verify the effectiveness of
proposed method as comparing with the conventional methods in the
non-linear channel.
Abstract: This article presents the results using a parametric approach and a Wavelet Transform in analysing signals emitting from the sperm whale. The extraction of intrinsic characteristics of these unique signals emitted by marine mammals is still at present a difficult exercise for various reasons: firstly, it concerns non-stationary signals, and secondly, these signals are obstructed by interfering background noise. In this article, we compare the advantages and disadvantages of both methods: Auto Regressive models and Wavelet Transform. These approaches serve as an alternative to the commonly used estimators which are based on the Fourier Transform for which the hypotheses necessary for its application are in certain cases, not sufficiently proven. These modern approaches provide effective results particularly for the periodic tracking of the signal's characteristics and notably when the signal-to-noise ratio negatively effects signal tracking. Our objectives are twofold. Our first goal is to identify the animal through its acoustic signature. This includes recognition of the marine mammal species and ultimately of the individual animal (within the species). The second is much more ambitious and directly involves the intervention of cetologists to study the sounds emitted by marine mammals in an effort to characterize their behaviour. We are working on an approach based on the recordings of marine mammal signals and the findings from this data result from the Wavelet Transform. This article will explore the reasons for using this approach. In addition, thanks to the use of new processors, these algorithms once heavy in calculation time can be integrated in a real-time system.
Abstract: Video sensor networks operate on stringent requirements
of latency. Packets have a deadline within which they have
to be delivered. Violation of the deadline causes a packet to be
treated as lost and the loss of packets ultimately affects the quality
of the application. Network latency is typically a function of many
interacting components. In this paper, we propose ways of reducing
the forwarding latency of a packet at intermediate nodes. The
forwarding latency is caused by a combination of processing delay
and queueing delay. The former is incurred in order to determine the
next hop in dynamic routing. We show that unless link failures in a
very specific and unlikely pattern, a vast majority of these lookups
are redundant. To counter this we propose source routing as the
routing strategy. However, source routing suffers from issues related
to scalability and being impervious to network dynamics. We propose
solutions to counter these and show that source routing is definitely
a viable option in practical sized video networks. We also propose a
fast and fair packet scheduling algorithm that reduces queueing delay
at the nodes. We support our claims through extensive simulation on
realistic topologies with practical traffic loads and failure patterns.
Abstract: Morphological operators transform the original image
into another image through the interaction with the other image of
certain shape and size which is known as the structure element.
Mathematical morphology provides a systematic approach to analyze
the geometric characteristics of signals or images, and has been
applied widely too many applications such as edge detection,
objection segmentation, noise suppression and so on. Fuzzy
Mathematical Morphology aims to extend the binary morphological
operators to grey-level images. In order to define the basic
morphological operations such as fuzzy erosion, dilation, opening
and closing, a general method based upon fuzzy implication and
inclusion grade operators is introduced. The fuzzy morphological
operations extend the ordinary morphological operations by using
fuzzy sets where for fuzzy sets, the union operation is replaced by a
maximum operation, and the intersection operation is replaced by a
minimum operation.
In this work, it consists of two articles. In the first one, fuzzy set
theory, fuzzy Mathematical morphology which is based on fuzzy
logic and fuzzy set theory; fuzzy Mathematical operations and their
properties will be studied in details. As a second part, the application
of fuzziness in Mathematical morphology in practical work such as
image processing will be discussed with the illustration problems.
Abstract: 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.
Abstract: In this paper, we propose a method of alter duration in
frequency domain that control prosody in real time after pitch
alteration. If there has a method to alteration duration freely among
prosody information, that may used in several fields such as speech
impediment person's pronunciation proof reading or language study.
The pitch alteration method used control prosody altered by PSOLA
synthesis method which is in time domain processing method.
However, the duration of pitch alteration speech is changed by the
frequency domain. In this paper, we altered the duration with the
method of duration alteration by Fast Fourier Transformation in
frequency domain. Consequently, the intelligibility of the pitch and
duration are controlled has a slight decrease than the case when only
pitch is changed, but the proposed algorithm obtained the higher MOS
score about naturalness.
Abstract: Various mechanisms providing mutual exclusion and
thread synchronization can be used to support parallel processing
within a single computer. Instead of using locks, semaphores, barriers
or other traditional approaches in this paper we focus on alternative
ways for making better use of modern multithreaded architectures
and preparing hash tables for concurrent accesses. Hash structures
will be used to demonstrate and compare two entirely different
approaches (rule based cooperation and hardware synchronization
support) to an efficient parallel implementation using traditional
locks. Comparison includes implementation details, performance
ranking and scalability issues. We aim at understanding the effects
the parallelization schemes have on the execution environment with
special focus on the memory system and memory access
characteristics.
Abstract: A power measurement algorithm of the input mix components of the noise signal and narrowband interference is considered using functional transformations of the input mix in the postdetection processing channel. The algorithm efficiency analysis has been carried out for different interference-to-signal ratio. Algorithm performance features have been explored by numerical experiment results.
Abstract: Helical milling operations are used to generate or
enlarge boreholes by means of a milling tool. The bore diameter can be
adjusted through the diameter of the helical path. The kinematics of
helical milling on a three axis machine tool is analysed firstly. The
relationships between processing parameters, cutting tool geometry
characters with machined hole feature are formulated. The feed motion
of the cutting tool has been decomposed to plane circular feed and
axial linear motion. In this paper, the time varying cutting forces acted
on the side cutting edges and end cutting edges of the flat end cylinder
miller is analysed using a discrete method separately. These two
components then are combined to produce the cutting force model
considering the complicated interaction between the cutters and
workpiece. The time varying cutting force model describes the
instantaneous cutting force during processing. This model could be
used to predict cutting force, calculate statics deflection of cutter and
workpiece, and also could be the foundation of dynamics model and
predicting chatter limitation of the helical milling operations.
Abstract: In this paper, 3X3 routing nodes are proposed to
provide speedup and parallel processing capability in Data Vortex
network architectures. The new design not only significantly
improves network throughput and latency, but also eliminates the
need for distributive traffic control mechanism originally embedded
among nodes and the need for nodal buffering. The cost effectiveness
is studied by a comparison study with the previously proposed 2-
input buffered networks, and considerable performance enhancement
can be achieved with similar or lower cost of hardware. Unlike
previous implementation, the network leaves small probability of
contention, therefore, the packet drop rate must be kept low for such
implementation to be feasible and attractive, and it can be achieved
with proper choice of operation conditions.
Abstract: The innovative intelligent fuzzy weighted input
estimation method (FWIEM) can be applied to the inverse heat
transfer conduction problem (IHCP) to estimate the unknown
time-varying heat flux of the multilayer materials as presented in this
paper. The feasibility of this method can be verified by adopting the
temperature measurement experiment. The experiment modular may
be designed by using the copper sample which is stacked up 4
aluminum samples with different thicknesses. Furthermore, the
bottoms of copper samples are heated by applying the standard heat
source, and the temperatures on the tops of aluminum are measured by
using the thermocouples. The temperature measurements are then
regarded as the inputs into the presented method to estimate the heat
flux in the bottoms of copper samples. The influence on the estimation
caused by the temperature measurement of the sample with different
thickness, the processing noise covariance Q, the weighting factor γ ,
the sampling time interval Δt , and the space discrete interval Δx ,
will be investigated by utilizing the experiment verification. The
results show that this method is efficient and robust to estimate the
unknown time-varying heat input of the multilayer materials.
Abstract: On-line handwritten scripts are usually dealt with pen tip traces from pen-down to pen-up positions. Time evaluation of the pen coordinates is also considered along with trajectory information. However, the data obtained needs a lot of preprocessing including filtering, smoothing, slant removing and size normalization before recognition process. Instead of doing such lengthy preprocessing, this paper presents a simple approach to extract the useful character information. This work evaluates the use of the counter- propagation neural network (CPN) and presents feature extraction mechanism in full detail to work with on-line handwriting recognition. The obtained recognition rates were 60% to 94% using the CPN for different sets of character samples. This paper also describes a performance study in which a recognition mechanism with multiple thresholds is evaluated for counter-propagation architecture. The results indicate that the application of multiple thresholds has significant effect on recognition mechanism. The method is applicable for off-line character recognition as well. The technique is tested for upper-case English alphabets for a number of different styles from different peoples.
Abstract: The modified Claus process is commonly used in oil
refining and gas processing to recover sulfur and destroy
contaminants formed in upstream processing. A Claus furnace feed
containing a relatively low concentration of H2S may be incapable of
producing a stable flame. Also, incomplete combustion of
hydrocarbons in the feed can lead to deterioration of the catalyst in
the reactors due to soot or carbon deposition. Therefore, special
consideration is necessary to achieve the appropriate overall sulfur
recovery. In this paper, some configurations available to treat lean
acid gas streams are described and the most appropriate ones are
studied to overcome low H2S concentration problems. As a result,
overall sulfur recovery is investigated for feed preheating and hot gas
configurations.