Abstract: Minimally invasive surgery (MIS) is now being widely used as a preferred choice for various types of operations. The need to detect various tactile properties, justifies the key role of tactile sensing that is currently missing in MIS. In this regard, Laparoscopy is one of the methods of minimally invasive surgery that can be used in kidney stone removal surgeries. At this moment, determination of the exact location of stone during laparoscopy is one of the limitations of this method that no scientific solution has been found for so far. Artificial tactile sensing is a new method for obtaining the characteristics of a hard object embedded in a soft tissue. Artificial palpation is an important application of artificial tactile sensing that can be used in different types of surgeries. In this study, a new method for determining the exact location of stone during laparoscopy is presented. In the present study, the effects of stone existence on the surface of kidney were investigated using conceptual 3D model of kidney containing a simulated stone. Having imitated palpation and modeled it conceptually, indications of stone existence that appear on the surface of kidney were determined. A number of different cases were created and solved by the software and using stress distribution contours and stress graphs, it is illustrated that the created stress patterns on the surface of kidney show not only the existence of stone inside, but also its exact location. So three-dimensional analysis leads to a novel method of predicting the exact location of stone and can be directly applied to the incorporation of tactile sensing in artificial palpation, helping surgeons in non-invasive procedures.
Abstract: In this paper, the full state feedback controllers
capable of regulating and tracking the speed trajectory are presented.
A fourth order nonlinear mean value model of a 448 kW turbocharged
diesel engine published earlier is used for the purpose.
For designing controllers, the nonlinear model is linearized and
represented in state-space form. Full state feedback controllers
capable of meeting varying speed demands of drivers are presented.
Main focus here is to investigate sensitivity of the controller to the
perturbations in the parameters of the original nonlinear model.
Suggested controller is shown to be highly insensitive to the
parameter variations. This indicates that the controller is likely
perform with same accuracy even after significant wear and tear of
engine due to its use for years.
Abstract: In this paper, different approaches to solve the
forward kinematics of a three DOF actuator redundant hydraulic
parallel manipulator are presented. On the contrary to series
manipulators, the forward kinematic map of parallel manipulators
involves highly coupled nonlinear equations, which are almost
impossible to solve analytically. The proposed methods are using
neural networks identification with different structures to solve the
problem. The accuracy of the results of each method is analyzed in
detail and the advantages and the disadvantages of them in
computing the forward kinematic map of the given mechanism is
discussed in detail. It is concluded that ANFIS presents the best
performance compared to MLP, RBF and PNN networks in this
particular application.
Abstract: This paper presents a system overview of Mobile to Server Face Recognition, which is a face recognition application developed specifically for mobile phones. Images taken from mobile phone cameras lack of quality due to the low resolution of the cameras. Thus, a prototype is developed to experiment the chosen method. However, this paper shows a result of system backbone without the face recognition functionality. The result demonstrated in this paper indicates that the interaction between mobile phones and server is successfully working. The result shown before the database is completely ready. The system testing is currently going on using real images and a mock-up database to test the functionality of the face recognition algorithm used in this system. An overview of the whole system including screenshots and system flow-chart are presented in this paper. This paper also presents the inspiration or motivation and the justification in developing this system.
Abstract: The study in this paper underlines the importance of
correct joint selection of the spreading codes for uplink of multicarrier
code division multiple access (MC-CDMA) at the transmitter
side and detector at the receiver side in the presence of nonlinear
distortion due to high power amplifier (HPA). The bit error rate
(BER) of system for different spreading sequences (Walsh code, Gold
code, orthogonal Gold code, Golay code and Zadoff-Chu code) and
different kinds of receivers (minimum mean-square error receiver
(MMSE-MUD) and microstatistic multi-user receiver (MSF-MUD))
is compared by means of simulations for MC-CDMA transmission
system. Finally, the results of analysis will show, that the application
of MSF-MUD in combination with Golay codes can outperform
significantly the other tested spreading codes and receivers for all
mostly used models of HPA.
Abstract: Border Gateway Protocol (BGP) is the standard routing protocol between various autonomous systems (AS) in the internet. In the event of failure, a considerable delay in the BGP convergence has been shown by empirical measurements. During the convergence time the BGP will repeatedly advertise new routes to some destination and withdraw old ones until it reach a stable state. It has been found that the KEEPALIVE message timer and the HOLD time are tow parameters affecting the convergence speed. This paper aims to find the optimum value for the KEEPALIVE timer and the HOLD time that maximally reduces the convergence time without increasing the traffic. The KEEPALIVE message timer optimal value founded by this paper is 30 second instead of 60 seconds, and the optimal value for the HOLD time is 90 seconds instead of 180 seconds.
Abstract: Performance of a cobalt doped sol-gel derived silica (Co/SiO2) catalyst for Fischer–Tropsch synthesis (FTS) in slurryphase reactor was studied using paraffin wax as initial liquid media. The reactive mixed gas, hydrogen (H2) and carbon monoxide (CO) in a molar ratio of 2:1, was flowed at 50 ml/min. Braunauer-Emmett- Teller (BET) surface area and X-ray diffraction (XRD) techniques were employed to characterize both the specific surface area and crystallinity of the catalyst, respectively. The reduction behavior of Co/SiO2 catalyst was investigated using the Temperature Programmmed Reduction (TPR) method. Operating temperatures were varied from 493 to 533K to find the optimum conditions to maximize liquid fuels production, gasoline and diesel.
Abstract: This paper describes an algorithm to estimate realtime vehicle velocity using image processing technique from the known camera calibration parameters. The presented algorithm involves several main steps. First, the moving object is extracted by utilizing frame differencing technique. Second, the object tracking method is applied and the speed is estimated based on the displacement of the object-s centroid. Several assumptions are listed to simplify the transformation of 2D images from 3D real-world images. The results obtained from the experiment have been compared to the estimated ground truth. From this experiment, it exhibits that the proposed algorithm has achieved the velocity accuracy estimation of about ± 1.7 km/h.
Abstract: Hexavalent chromium is highly toxic to most living organisms and a known human carcinogen by the inhalation route of exposure. Therefore, treatment of Cr(VI) contaminated wastewater is essential before their discharge to the natural water bodies. Cr(VI) reduction to Cr(III) can be beneficial because a more mobile and more toxic chromium species is converted to a less mobile and less toxic form. Zero-valence-state metals, such as scrap iron, can serve as electron donors for reducing Cr(VI) to Cr(III). The influence of pH on scrap iron capacity to reduce Cr(VI) was investigated in this study. Maximum reduction capacity of scrap iron was observed at the beginning of the column experiments; the lower the pH, the greater the experiment duration with maximum scrap iron reduction capacity. The experimental results showed that highest maximum reduction capacity of scrap iron was 12.5 mg Cr(VI)/g scrap iron, at pH 2.0, and decreased with increasing pH up to 1.9 mg Cr(VI)/g scrap iron at pH = 7.3.
Abstract: Avalanche velocity (from start to track zone) has been estimated in the present model for an avalanche which is triggered artificially by an explosive devise. The initial development of the model has been from the concept of micro-continuum theories [1], underwater explosions [2] and from fracture mechanics [3] with appropriate changes to the present model. The model has been computed for different slab depth R, slope angle θ, snow density ¤ü, viscosity μ, eddy viscosity η*and couple stress parameter η. The applicability of the present model in the avalanche forecasting has been highlighted.
Abstract: In this paper, first, a characterization of spherical
Pseudo null curves in Semi-Euclidean space is given. Then, to
investigate position vector of a pseudo null curve, a system of
differential equation whose solution gives the components of the
position vector of a pseudo null curve on the Frenet axis is
established by means of Frenet equations. Additionally, in view of
some special solutions of mentioned system, characterizations of
some special pseudo null curves are presented.
Abstract: This work consists of three parts. First, the alias-free
condition for the conventional two-channel quadrature mirror filter
bank is analyzed using complex arithmetic. Second, the approach
developed in the first part is applied to the complex quadrature mirror
filter bank. Accordingly, the structure is simplified and the theory is
easier to follow. Finally, a new class of complex quadrature mirror
filter banks is proposed. Interesting properties of this new structure
are also discussed.
Abstract: The ability of UML to handle the modeling process of complex industrial software applications has increased its popularity to the extent of becoming the de-facto language in serving the design purpose. Although, its rich graphical notation naturally oriented towards the object-oriented concept, facilitates the understandability, it hardly successes to report all domainspecific aspects in a satisfactory way. OCL, as the standard language for expressing additional constraints on UML models, has great potential to help improve expressiveness. Unfortunately, it suffers from a weak formalism due to its poor semantic resulting in many obstacles towards the build of tools support and thus its application in the industry field. For this reason, many researches were established to formalize OCL expressions using a more rigorous approach. Our contribution join this work in a complementary way since it focuses specifically on OCL predefined properties which constitute an important part in the construction of OCL expressions. Using formal methods, we mainly succeed in expressing rigorously OCL predefined functions.
Abstract: This paper is motivated by the aspect of uncertainty in
financial decision making, and how artificial intelligence and soft
computing, with its uncertainty reducing aspects can be used for
algorithmic trading applications that trade in high frequency.
This paper presents an optimized high frequency trading system that
has been combined with various moving averages to produce a hybrid
system that outperforms trading systems that rely solely on moving
averages. The paper optimizes an adaptive neuro-fuzzy inference
system that takes both the price and its moving average as input,
learns to predict price movements from training data consisting of
intraday data, dynamically switches between the best performing
moving averages, and performs decision making of when to buy or
sell a certain currency in high frequency.
Abstract: The decoding of Low-Density Parity-Check (LDPC) codes is operated over a redundant structure known as the bipartite graph, meaning that the full set of bit nodes is not absolutely necessary for decoder convergence. In 2008, Soyjaudah and Catherine designed a recovery algorithm for LDPC codes based on this assumption and showed that the error-correcting performance of their codes outperformed conventional LDPC Codes. In this work, the use of the recovery algorithm is further explored to test the performance of LDPC codes while the number of iterations is progressively increased. For experiments conducted with small blocklengths of up to 800 bits and number of iterations of up to 2000, the results interestingly demonstrate that contrary to conventional wisdom, the error-correcting performance keeps increasing with increasing number of iterations.
Abstract: Interpretation of aerial images is an important task in
various applications. Image segmentation can be viewed as the essential
step for extracting information from aerial images. Among many
developed segmentation methods, the technique of clustering has been
extensively investigated and used. However, determining the number
of clusters in an image is inherently a difficult problem, especially
when a priori information on the aerial image is unavailable. This
study proposes a support vector machine approach for clustering
aerial images. Three cluster validity indices, distance-based index,
Davies-Bouldin index, and Xie-Beni index, are utilized as quantitative
measures of the quality of clustering results. Comparisons on the
effectiveness of these indices and various parameters settings on the
proposed methods are conducted. Experimental results are provided
to illustrate the feasibility of the proposed approach.
Abstract: The number of features required to represent an image
can be very huge. Using all available features to recognize objects
can suffer from curse dimensionality. Feature selection and
extraction is the pre-processing step of image mining. Main issues in
analyzing images is the effective identification of features and
another one is extracting them. The mining problem that has been
focused is the grouping of features for different shapes. Experiments
have been conducted by using shape outline as the features. Shape
outline readings are put through normalization and dimensionality
reduction process using an eigenvector based method to produce a
new set of readings. After this pre-processing step data will be
grouped through their shapes. Through statistical analysis, these
readings together with peak measures a robust classification and
recognition process is achieved. Tests showed that the suggested
methods are able to automatically recognize objects through their
shapes. Finally, experiments also demonstrate the system invariance
to rotation, translation, scale, reflection and to a small degree of
distortion.
Abstract: In order to make surfing the internet faster, and to save redundant processing load with each request for the same web page, many caching techniques have been developed to reduce latency of retrieving data on World Wide Web. In this paper we will give a quick overview of existing web caching techniques used for dynamic web pages then we will introduce a design and implementation model that take advantage of “URL Rewriting" feature in some popular web servers, e.g. Apache, to provide an effective approach of caching dynamic web pages.
Abstract: There are three approaches to complete Bayesian
Network (BN) model construction: total expert-centred, total datacentred,
and semi data-centred. These three approaches constitute the
basis of the empirical investigation undertaken and reported in this
paper. The objective is to determine, amongst these three
approaches, which is the optimal approach for the construction of a
BN-based model for the performance assessment of students-
laboratory work in a virtual electronic laboratory environment. BN
models were constructed using all three approaches, with respect to
the focus domain, and compared using a set of optimality criteria. In
addition, the impact of the size and source of the training, on the
performance of total data-centred and semi data-centred models was
investigated. The results of the investigation provide additional
insight for BN model constructors and contribute to literature
providing supportive evidence for the conceptual feasibility and
efficiency of structure and parameter learning from data. In addition,
the results highlight other interesting themes.
Abstract: The purpose of this study is to examine the self and
decision making levels of students receiving education in schools of
physical training and sports. The population of the study consisted
258 students, among which 152 were male and 106 were female
( X age=19,3713 + 1,6968), that received education in the schools of
physical education and sports of Selcuk University, Inonu University,
Gazi University and Karamanoglu Mehmetbey University. In order to
achieve the purpose of the study, the Melbourne Decision Making
Questionnary developed by Mann et al. (1998) [1] and adapted to
Turkish by Deniz (2004) [2] and the Self-Esteem Scale developed by
Aricak (1999) [3] was utilized. For analyzing and interpreting data
Kolmogorov-Smirnov test, t-test and one way anova test were used,
while for determining the difference between the groups Tukey test
and Multiple Linear Regression test were employed and significance
was accepted at P