Abstract: Protection and proper management of archaeological heritage are an essential process of studying and interpreting the generations present and future. Protecting the archaeological heritage is based upon multidiscipline professional collaboration. This study aims to gather data by different sources (Photogrammetry and Geographic Information System (GIS)) integrated for the purpose of documenting one the of significant archeological sites (Ahl-Alkahf, Jordan). 3D modeling deals with the actual image of the features, shapes and texture to represent reality as realistically as possible by using texture. The 3D coordinates that result of the photogrammetric adjustment procedures are used to create 3D-models of the study area. Adding Textures to the 3D-models surfaces gives a 'real world' appearance to the displayed models. GIS system combined all data, including boundary maps, indicating the location of archeological sites, transportation layer, digital elevation model and orthoimages. For realistic representation of the study area, 3D - GIS model prepared, where efficient generation, management and visualization of such special data can be achieved.
Abstract: This paper proposes a Particle Swarm Optimization
(PSO) based technique for the optimal allocation of Distributed
Generation (DG) units in the power systems. In this paper our aim is
to decide optimal number, type, size and location of DG units for
voltage profile improvement and power loss reduction in distribution
network. Two types of DGs are considered and the distribution load
flow is used to calculate exact loss. Load flow algorithm is combined
appropriately with PSO till access to acceptable results of this
operation. The suggested method is programmed under MATLAB
software. Test results indicate that PSO method can obtain better
results than the simple heuristic search method on the 30-bus and 33-
bus radial distribution systems. It can obtain maximum loss reduction
for each of two types of optimally placed multi-DGs. Moreover,
voltage profile improvement is achieved.
Abstract: This paper presents a conceptual model of agreement
options for negotiation support in multi-person decision on
optimizing high-rise building columns. The decision is complicated
since many parties involved in choosing a single alternative from a
set of solutions. There are different concern caused by differing
preferences, experiences, and background. Such building columns as
alternatives are referred to as agreement options which are
determined by identifying the possible decision maker group,
followed by determining the optimal solution for each group. The
group in this paper is based on three-decision makers preferences that
are designer, programmer, and construction manager. Decision
techniques applied to determine the relative value of the alternative
solutions for performing the function. Analytical Hierarchy Process
(AHP) was applied for decision process and game theory based agent
system for coalition formation. An n-person cooperative game is
represented by the set of all players. The proposed coalition
formation model enables each agent to select individually its allies or
coalition. It further emphasizes the importance of performance
evaluation in the design process and value-based decision.
Abstract: This study has investigated the antidiabetic and
antioxidant potential of Pseudovaria macrophylla bark extract on
streptozotocin–nicotinamide induced type 2 diabetic rats. LCMSQTOF
and NMR experiments were done to determine the chemical
composition in the methanolic bark extract. For in vivo experiments,
the STZ (60 mg/kg/b.w, 15 min after 120 mg/kg/1 nicotinamide, i.p.)
induced diabetic rats were treated with methanolic extract of
Pseuduvaria macrophylla (200 and 400 mg/kg·bw) and
glibenclamide (2.5 mg/kg) as positive control respectively.
Biochemical parameters were assayed in the blood samples of all
groups of rats. The pro-inflammatory cytokines, antioxidant status
and plasma transforming growth factor βeta-1 (TGF-β1) were
evaluated. The histological study of the pancreas was examined and
its expression level of insulin was observed by
immunohistochemistry. In addition, the expression of glucose
transporters (GLUT 1, 2 and 4) were assessed in pancreas tissue by
western blot analysis. The outcomes of the study displayed that the
bark methanol extract of Pseuduvaria macrophylla has potentially
normalized the elevated blood glucose levels and improved serum
insulin and C-peptide levels with significant increase in the
antioxidant enzyme, reduced glutathione (GSH) and decrease in the
level of lipid peroxidation (LPO). Additionally, the extract has
markedly decreased the levels of serum pro-inflammatory cytokines
and transforming growth factor beta-1 (TGF-β1). Histopathology
analysis demonstrated that Pseuduvaria macrophylla has the
potential to protect the pancreas of diabetic rats against peroxidation
damage by downregulating oxidative stress and elevated
hyperglycaemia. Furthermore, the expression of insulin protein,
GLUT-1, GLUT-2 and GLUT-4 in pancreatic cells was enhanced.
The findings of this study support the anti-diabetic claims of
Pseudovaria macrophylla bark.
Abstract: The purpose of this study was to present a reliable mean for human-computer interfacing based on finger gestures made in two dimensions, which could be interpreted and adequately used in controlling a remote robot's movement. The gestures were captured and interpreted using an algorithm based on trigonometric functions, in calculating the angular displacement from one point of touch to another as the user-s finger moved within a time interval; thereby allowing for pattern spotting of the captured gesture. In this paper the design and implementation of such a gesture based user interface was presented, utilizing the aforementioned algorithm. These techniques were then used to control a remote mobile robot's movement. A resistive touch screen was selected as the gesture sensor, then utilizing a programmed microcontroller to interpret them respectively.
Abstract: In this paper, an efficient local appearance feature
extraction method based the multi-resolution Curvelet transform is
proposed in order to further enhance the performance of the well
known Linear Discriminant Analysis(LDA) method when applied
to face recognition. Each face is described by a subset of band
filtered images containing block-based Curvelet coefficients. These
coefficients characterize the face texture and a set of simple statistical
measures allows us to form compact and meaningful feature vectors.
The proposed method is compared with some related feature extraction
methods such as Principal component analysis (PCA), as well
as Linear Discriminant Analysis LDA, and independent component
Analysis (ICA). Two different muti-resolution transforms, Wavelet
(DWT) and Contourlet, were also compared against the Block Based
Curvelet-LDA algorithm. Experimental results on ORL, YALE and
FERET face databases convince us that the proposed method provides
a better representation of the class information and obtains much
higher recognition accuracies.
Abstract: We consider a network of two M/M/1 parallel queues having the same poisonnian arrival stream with rate λ. Upon his arrival to the system a customer heads to the shortest queue and stays until being served. If the two queues have the same length, an arriving customer chooses one of the two queues with the same probability. Each duration of service in the two queues is an exponential random variable with rate μ and no jockeying is permitted between the two queues. A new numerical method, based on linear programming and convex optimization, is performed for the computation of the steady state solution of the system.
Abstract: An adaptive neural network controller for
autonomous underwater vehicles (AUVs) is presented in this paper.
The AUV model is highly nonlinear because of many factors, such as
hydrodynamic drag, damping, and lift forces, Coriolis and centripetal
forces, gravity and buoyancy forces, as well as forces from thruster.
In this regards, a nonlinear neural network is used to approximate the
nonlinear uncertainties of AUV dynamics, thus overcoming some
limitations of conventional controllers and ensure good performance.
The uniform ultimate boundedness of AUV tracking errors and the
stability of the proposed control system are guaranteed based on
Lyapunov theory. Numerical simulation studies for motion control of
an AUV are performed to demonstrate the effectiveness of the
proposed controller.
Abstract: Programmable logic controllers are the main controllers in the today's industries; they are used for several applications in industrial control systems and there are lots of examples exist from the PLC applications in industries especially in big companies and plants such as refineries, power plants, petrochemical companies, steel companies, and food and production companies. In the PLCs there are some functions in the function library in software that can be used in PLC programs as basic program elements. The aim of this project are introducing and implementing a new function block of a neural network to the function library of PLC. This block can be applied for some control applications or nonlinear functions calculations after it has been trained for these applications. The implemented neural network is a Perceptron neural network with three layers, three input nodes and one output node. The block can be used in manual or automatic mode. In this paper the structure of the implemented function block, the parameters and the training method of the network are presented by considering the especial method of PLC programming and its complexities. Finally the application of the new block is compared with a classic simulated block and the results are presented.
Abstract: During recent years, attention in 'Green Computing'
has moved research into energy-saving techniques for home
computers to enterprise systems' Client and Server machines. Saving
energy or reduction of carbon footprints is one of the aspects of
Green Computing. The research in the direction of Green Computing
is more than just saving energy and reducing carbon foot prints. This
study provides a brief account of Green Computing. The emphasis of
this study is on current trends in Green Computing; challenges in the
field of Green Computing and the future trends of Green Computing.
Abstract: This paper presents the development of low cost Nano membrane fabrication system. The system is specially designed for anodic aluminum oxide membrane. This system is capable to perform the processes such as anodization and electro-polishing. The designed machine was successfully tested for 'mild anodization' (MA) for 48 hours and 'hard anodization' (HA) for 3 hours at constant 0oC. The system is digitally controlled and guided for temperature maintenance during anodization and electro-polishing. The total cost of the developed machine is 20 times less than the multi-cooling systems available in the market which are generally used for this purpose.
Abstract: This paper proposes an active soft-switching circuit for
bridge converters aiming to improve the power conversion efficiency.
The proposed circuit achieves loss-less switching for both main and
auxiliary switches without increasing the main switch current/voltage
rating. A winding coupled to the primary of power transformer
ensures ZCS for the auxiliary switches during their turn-off. A 350 W,
100 kHz phase shifted full bridge (PSFB) converter is built to validate
the analysis and design. Theoretical loss calculations for proposed
circuit is presented. The proposed circuit is compared with passive
soft switched PSFB in terms of efficiency and loss in duty cycle.
Abstract: In this paper, a new method of image edge-detection
and characterization is presented. “Parametric Filtering method" uses
a judicious defined filter, which preserves the signal correlation
structure as input in the autocorrelation of the output. This leads,
showing the evolution of the image correlation structure as well as
various distortion measures which quantify the deviation between
two zones of the signal (the two Hamming signals) for the protection
of an image edge.
Abstract: We introduce and study the class of weak almost Dunford-Pettis operators. As an application, we characterize Banach lattices with the weak Dunford-Pettis property. Also, we establish some sufficient conditions for which each weak almost Dunford-Pettis operator is weak Dunford-Pettis. Finally, we derive some interesting results.
Abstract: In this paper, an inventory model with finite and
constant replenishment rate, price dependant demand rate, time
value of money and inflation, finite time horizon, lead time and
exponential deterioration rate and with the objective of maximizing
the present worth of the total system profit is developed. Using a
dynamic programming based solution algorithm, the optimal
sequence of the cycles can be found and also different optimal
selling prices, optimal order quantities and optimal maximum
inventories can be obtained for the cycles with unequal lengths,
which have never been done before for this model. Also, a
numerical example is used to show accuracy of the solution
procedure.
Abstract: Frequent patterns are patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a dataset. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages such as C, Cµ, Java. The imperative paradigm is significantly inefficient when itemset is large and the frequent pattern is long. We suggest a high-level declarative style of programming using a functional language. Our supposition is that the problem of frequent pattern discovery can be efficiently and concisely implemented via a functional paradigm since pattern matching is a fundamental feature supported by most functional languages. Our frequent pattern mining implementation using the Haskell language confirms our hypothesis about conciseness of the program. The performance studies on speed and memory usage support our intuition on efficiency of functional language.
Abstract: A linear feedback shift register (LFSR) is proposed which targets to reduce the power consumption from within. It reduces the power consumption during testing of a Circuit Under Test (CUT) at two stages. At first stage,
Control Logic (CL) makes the clocks of the switching units
of the register inactive for a time period when output from
them is going to be same as previous one and thus reducing
unnecessary switching of the flip-flops. And at second stage,
the LFSR reorders the test vectors by interchanging the bit
with its next and closest neighbor bit. It keeps fault coverage
capacity of the vectors unchanged but reduces the Total Hamming Distance (THD) so that there is reduction in power
while shifting operation.
Abstract: In this article, a formal specification and verification of the Rabin public-key scheme in a formal proof system is presented. The idea is to use the two views of cryptographic verification: the computational approach relying on the vocabulary of probability theory and complexity theory and the formal approach based on ideas and techniques from logic and programming languages. A major objective of this article is the presentation of the first computer-proved implementation of the Rabin public-key scheme in Isabelle/HOL. Moreover, we explicate a (computer-proven) formalization of correctness as well as a computer verification of security properties using a straight-forward computation model in Isabelle/HOL. The analysis uses a given database to prove formal properties of our implemented functions with computer support. The main task in designing a practical formalization of correctness as well as efficient computer proofs of security properties is to cope with the complexity of cryptographic proving. We reduce this complexity by exploring a light-weight formalization that enables both appropriate formal definitions as well as efficient formal proofs. Consequently, we get reliable proofs with a minimal error rate augmenting the used database, what provides a formal basis for more computer proof constructions in this area.
Abstract: In the following text, we show that by introducing
universal kinetic scheme, the origin of rate retardation and inhibition
period which observed in dithiobenzoate-mediated RAFT
polymerization can be described properly. We develop our model by
utilizing the method of moments, then we apply our model to
different monomer/RAFT agent systems, both homo- and
copolymerization. The modeling results are in an excellent
agreement with experiments and imply the validity of universal
kinetic scheme, not only for dithiobenzoate-mediated systems, but
also for different types of monomer/RAFT agent ones.
Abstract: An image texture analysis and target recognition approach of using an improved image texture feature coding method (TFCM) and Support Vector Machine (SVM) for target detection is presented. With our proposed target detection framework, targets of interest can be detected accurately. Cascade-Sliding-Window technique was also developed for automated target localization. Application to mammogram showed that over 88% of normal mammograms and 80% of abnormal mammograms can be correctly identified. The approach was also successfully applied to Synthetic Aperture Radar (SAR) and Ground Penetrating Radar (GPR) images for target detection.