Abstract: The value of overall oxygen transfer Coefficient
(KLa), which is the best measure of oxygen transfer in water through
aeration, is obtained by a simple approach, which sufficiently
explains the utility of the method to eliminate the discrepancies due
to inaccurate assumption of saturation dissolved oxygen
concentration. The rate of oxygen transfer depends on number of
factors like intensity of turbulence, which in turns depends on the
speed of rotation, size, and number of blades, diameter and
immersion depth of the rotor, and size and shape of aeration tank, as
well as on physical, chemical, and biological characteristic of water.
An attempt is made in this paper to correlate the overall oxygen
transfer Coefficient (KLa), as an independent parameter with other
influencing parameters mentioned above. It has been estimated that
the simulation equation developed predicts the values of KLa and
power with an average standard error of estimation of 0.0164 and
7.66 respectively and with R2 values of 0.979 and 0.989 respectively,
when compared with experimentally determined values. The
comparison of this model is done with the model generated using
Computational fluid dynamics (CFD) and both the models were
found to be in good agreement with each other.
Abstract: Cell phone forensics to acquire and analyze data in the
cellular phone is nowadays being used in a national investigation
organization and a private company. In order to collect cellular phone
flash memory data, we have two methods. Firstly, it is a logical
method which acquires files and directories from the file system of the
cell phone flash memory. Secondly, we can get all data from bit-by-bit
copy of entire physical memory using a low level access method. In
this paper, we describe a forensic tool to acquire cell phone flash
memory data using a logical level approach. By our tool, we can get
EFS file system and peek memory data with an arbitrary region from
Korea CDMA cell phone.
Abstract: The paper describes a new approach for fingerprint
classification, based on the distribution of local features (minute
details or minutiae) of the fingerprints. The main advantage is that
fingerprint classification provides an indexing scheme to facilitate
efficient matching in a large fingerprint database. A set of rules based
on heuristic approach has been proposed. The area around the core
point is treated as the area of interest for extracting the minutiae
features as there are substantial variations around the core point as
compared to the areas away from the core point. The core point in a
fingerprint has been located at a point where there is maximum
curvature. The experimental results report an overall average
accuracy of 86.57 % in fingerprint classification.
Abstract: A new conserving approach in the context of Immersed Boundary Method (IBM) is presented to simulate one dimensional, incompressible flow in a moving boundary problem. The method employs control volume scheme to simulate the flow field. The concept of ghost node is used at the boundaries to conserve the mass and momentum equations. The Present method implements the conservation laws in all cells including boundary control volumes. Application of the method is studied in a test case with moving boundary. Comparison between the results of this new method and a sharp interface (Image Point Method) IBM algorithm shows a well distinguished improvement in both pressure and velocity fields of the present method. Fluctuations in pressure field are fully resolved in this proposed method. This approach expands the IBM capability to simulate flow field for variety of problems by implementing conservation laws in a fully Cartesian grid compared to other conserving methods.
Abstract: This paper has presented research in progress
concerning the contribution of target costing approach to
achievement competitive price in the Iraqi firm. The title of the
paper is one of the subjects that get large concerns in the finance and
business world in the present time. That is because many competitive
firms have appeared in the regional and global markets and the rapid
changes that covered all fields of life. On the other hand, this paper
concentrated on lack knowledge of the industrial firms, regarding the
significant role of target cost for achieving the competitive prices.
The paper depends on the main supposition, using the competitive
price to get the target cost in the industrial firms. In order to achieve
competitive advantage in business world the firms should rely on
modern methods to manage cost and profit. From strategic
perspective the target cost achieves a so powerful competitive
advantage represented in cost reduction. Nevertheless the target cost
does not exclude the calculation and survey of costs during the
production process. Products- estimated costs are calculated and
compared with the target costs.
Abstract: Small satellites have become increasingly popular recently as a means of providing educational institutes with the chance to design, construct, and test their spacecraft from beginning to the possible launch due to the low launching cost. This approach is remarkably cost saving because of the weight and size reduction of such satellites. Weight reduction could be realised by utilising electromagnetic coils solely, instead of different types of actuators. This paper describes the restrictions of using only “Electromagnetic" actuation for 3D stabilisation and how to make the magnetorquer based attitude control feasible using Fuzzy Logic Control (FLC). The design is developed to stabilize the spacecraft against gravity gradient disturbances with a three-axis stabilizing capability.
Abstract: A new approach for facial expressions recognition based on face context and adaptively weighted sub-pattern PCA (Aw-SpPCA) has been presented in this paper. The facial region and others part of the body have been segmented from the complex environment based on skin color model. An algorithm has been proposed to accurate detection of face region from the segmented image based on constant ratio of height and width of face (δ= 1.618). The paper also discusses on new concept to detect the eye and mouth position. The desired part of the face has been cropped to analysis the expression of a person. Unlike PCA based on a whole image pattern, Aw-SpPCA operates directly on its sub patterns partitioned from an original whole pattern and separately extracts features from them. Aw-SpPCA can adaptively compute the contributions of each part and a classification task in order to enhance the robustness to both expression and illumination variations. Experiments on single standard face with five types of facial expression database shows that the proposed method is competitive.
Abstract: Creating shared value (CSV) is a newly introduced
concept whose essence and expressions, relationship to Corporate
social responsibility (CSR) and implications for the business and
society is now at the core of management and social responsibility
debates of the scientific world. The aim of the paper is to gain clearer
understanding of the CSR and CSV concepts, their implementation
and role in sustainable development of organizations in Latvia. In this
paper the authors discuss and compare the two conceptsand, based on
the results of Sustainability Index (SI) initiative and analysis of
publically available company information, evaluate their
implementation in Latvia and draw conclusions on the development
trends and potential of these approaches in Latvian market.
Abstract: This paper presents a novel approach for tuning unified power flow controller (UPFC) based damping controller in order to enhance the damping of power system low frequency oscillations. The design problem of damping controller is formulated as an optimization problem according to the eigenvalue-based objective function which is solved using iteration particle swarm optimization (IPSO). The effectiveness of the proposed controller is demonstrated through eigenvalue analysis and nonlinear time-domain simulation studies under a wide range of loading conditions. The simulation study shows that the designed controller by IPSO performs better than CPSO in finding the solution. Moreover, the system performance analysis under different operating conditions show that the δE based controller is superior to the mB based controller.
Abstract: In this paper, we study the instability of the zero solution to a nonlinear differential equation with variable delay. By using the Lyapunov functional approach, some sufficient conditions for instability of the zero solution are obtained.
Abstract: Fluids are used for heat transfer in many engineering
equipments. Water, ethylene glycol and propylene glycol are some
of the common heat transfer fluids. Over the years, in an attempt to
reduce the size of the equipment and/or efficiency of the process,
various techniques have been employed to improve the heat transfer
rate of these fluids. Surface modification, use of inserts and
increased fluid velocity are some examples of heat transfer
enhancement techniques. Addition of milli or micro sized particles
to the heat transfer fluid is another way of improving heat transfer
rate. Though this looks simple, this method has practical problems
such as high pressure loss, clogging and erosion of the material of
construction. These problems can be overcome by using nanofluids,
which is a dispersion of nanosized particles in a base fluid.
Nanoparticles increase the thermal conductivity of the base fluid
manifold which in turn increases the heat transfer rate. In this work,
the heat transfer enhancement using aluminium oxide nanofluid has
been studied by computational fluid dynamic modeling of the
nanofluid flow adopting the single phase approach.
Abstract: In this paper, a new K-means clustering based
approach for identification of voltage control areas is developed.
Voltage control areas are important for efficient reactive power
management in power systems operating under deregulated
environment. Although, voltage control areas are formed using
conventional hierarchical clustering based method, but the present
paper investigate the capability of K-means clustering for the
purpose of forming voltage control areas. The proposed method is
tested and compared for IEEE 14 bus and IEEE 30 bus systems. The
results show that this K-means based method is competing with
conventional hierarchical approach
Abstract: Power flow (PF) study, which is performed to
determine the power system static states (voltage magnitudes and
voltage angles) at each bus to find the steady state operating
condition of a system, is very important and is the most frequently
carried out study by power utilities for power system planning,
operation and control. In this paper, a counterpropagation neural
network (CPNN) is proposed to solve power flow problem under
different loading/contingency conditions for computing bus voltage
magnitudes and angles of the power system. The counterpropagation
network uses a different mapping strategy namely
counterpropagation and provides a practical approach for
implementing a pattern mapping task, since learning is fast in this
network. The composition of the input variables for the proposed
neural network has been selected to emulate the solution process of a
conventional power flow program. The effectiveness of the proposed
CPNN based approach for solving power flow is demonstrated by
computation of bus voltage magnitudes and voltage angles for
different loading conditions and single line-outage contingencies in
IEEE 14-bus system.
Abstract: Timetabling problems are often hard and timeconsuming
to solve. Most of the methods of solving them concern
only one problem instance or class. This paper describes a universal
method for solving large, highly constrained timetabling problems
from different domains. The solution is based on evolutionary
algorithm-s framework and operates on two levels – first-level
evolutionary algorithm tries to find a solution basing on given set of
operating parameters, second-level algorithm is used to establish
those parameters. Tabu search is employed to speed up the solution
finding process on first level. The method has been used to solve
three different timetabling problems with promising results.
Abstract: This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang-s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying the proposed model to the APP problems with three scenarios of inventory levels. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple combined response levels. There has been a trend to solve complex planning problems using various metaheuristics. Therefore, in this paper, the multi-objective APP problem is solved by hybrid metaheuristics of the hunting search (HuSIHSA) and firefly (FAIHSA) mechanisms on the improved harmony search algorithm. Results obtained from the solution of are then compared. It is observed that the FAIHSA can be used as a successful alternative solution mechanism for solving APP problems over three scenarios. Furthermore, the FAIHSA provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the desirability function approach and related model parameters until a good optimal solution is obtained with proper selection of control parameters when compared.
Abstract: The model-based approach to user interface design
relies on developing separate models capturing various aspects about
users, tasks, application domain, presentation and dialog structures.
This paper presents a task modeling approach for user interface
design and aims at exploring mappings between task, domain and
presentation models. The basic idea of our approach is to identify
typical configurations in task and domain models and to investigate
how they relate each other. A special emphasis is put on applicationspecific
functions and mappings between domain objects and
operational task structures. In this respect, we will address two
layers in task decomposition: a functional (planning) layer and an
operational layer.
Abstract: The mineral having chemical compositional formula MgAl2O4 is called “spinel". The ferrites crystallize in spinel structure are known as spinel-ferrites or ferro-spinels. The spinel structure has a fcc cage of oxygen ions and the metallic cations are distributed among tetrahedral (A) and octahedral (B) interstitial voids (sites). The X-ray diffraction (XRD) intensity of each Bragg plane is sensitive to the distribution of cations in the interstitial voids of the spinel lattice. This leads to the method of determination of distribution of cations in the spinel oxides through XRD intensity analysis. The computer program for XRD intensity analysis has been developed in C language and also tested for the real experimental situation by synthesizing the spinel ferrite materials Mg0.6Zn0.4AlxFe2- xO4 and characterized them by X-ray diffractometry. The compositions of Mg0.6Zn0.4AlxFe2-xO4(x = 0.0 to 0.6) ferrites have been prepared by ceramic method and powder X-ray diffraction patterns were recorded. Thus, the authenticity of the program is checked by comparing the theoretically calculated data using computer simulation with the experimental ones. Further, the deduced cation distributions were used to fit the magnetization data using Localized canting of spins approach to explain the “recovery" of collinear spin structure due to Al3+ - substitution in Mg-Zn ferrites which is the case if A-site magnetic dilution and non-collinear spin structure. Since the distribution of cations in the spinel ferrites plays a very important role with regard to their electrical and magnetic properties, it is essential to determine the cation distribution in spinel lattice.
Abstract: How to coordinate the behaviors of the agents through
learning is a challenging problem within multi-agent domains.
Because of its complexity, recent work has focused on how
coordinated strategies can be learned. Here we are interested in using
reinforcement learning techniques to learn the coordinated actions of a
group of agents, without requiring explicit communication among
them. However, traditional reinforcement learning methods are based
on the assumption that the environment can be modeled as Markov
Decision Process, which usually cannot be satisfied when multiple
agents coexist in the same environment. Moreover, to effectively
coordinate each agent-s behavior so as to achieve the goal, it-s
necessary to augment the state of each agent with the information
about other existing agents. Whereas, as the number of agents in a
multiagent environment increases, the state space of each agent grows
exponentially, which will cause the combinational explosion problem.
Profit sharing is one of the reinforcement learning methods that allow
agents to learn effective behaviors from their experiences even within
non-Markovian environments. In this paper, to remedy the drawback
of the original profit sharing approach that needs much memory to
store each state-action pair during the learning process, we firstly
address a kind of on-line rational profit sharing algorithm. Then, we
integrate the advantages of modular learning architecture with on-line
rational profit sharing algorithm, and propose a new modular
reinforcement learning model. The effectiveness of the technique is
demonstrated using the pursuit problem.
Abstract: Wastages such as grated coconut meat, spent tea and used sugarcane had contributed negative impacts to the environment. Vermicomposting method is fully utilized to manage the wastes towards a more sustainable approach. The worms that are used in the vermicomposting are Eisenia foetida and Eudrillus euginae. This research shows that the vermicompost of wastages has voltage of electrical energy and is able to light up the Light-Emitting Diode (LED) device. Based on the experiment, the use of replicated and double compartments of the component will produce double of voltage. Hence, for conclusion, this harmless and low cost technology of vermicompost can act as a dry cell in order to reduce the usage of hazardous chemicals that can contaminate the environment.
Abstract: Term Extraction, a key data preparation step in Text
Mining, extracts the terms, i.e. relevant collocation of words,
attached to specific concepts (e.g. genetic-algorithms and decisiontrees
are terms associated to the concept “Machine Learning" ). In
this paper, the task of extracting interesting collocations is achieved
through a supervised learning algorithm, exploiting a few
collocations manually labelled as interesting/not interesting. From
these examples, the ROGER algorithm learns a numerical function,
inducing some ranking on the collocations. This ranking is optimized
using genetic algorithms, maximizing the trade-off between the false
positive and true positive rates (Area Under the ROC curve). This
approach uses a particular representation for the word collocations,
namely the vector of values corresponding to the standard statistical
interestingness measures attached to this collocation. As this
representation is general (over corpora and natural languages),
generality tests were performed by experimenting the ranking
function learned from an English corpus in Biology, onto a French
corpus of Curriculum Vitae, and vice versa, showing a good
robustness of the approaches compared to the state-of-the-art Support
Vector Machine (SVM).