Abstract: In a none-super-competitive environment the concepts
of closed system, management control remains to be the dominant
guiding concept to management. The merits of closed loop have been
the sources of most of the management literature and culture for
many decades. It is a useful exercise to investigate and poke into the
dynamics of the control loop phenomenon and draws some lessons to
use for refining the practice of management. This paper examines the
multitude of lessons abstracted from the behavior of the Input /output
/feedback control loop model, which is the core of control theory.
There are numerous lessons that can be learned from the insights this
model would provide and how it parallels the management dynamics
of the organization. It is assumed that an organization is basically a
living system that interacts with the internal and external variables. A
viable control loop is the one that reacts to the variation in the
environment and provide or exert a corrective action. In managing
organizations this is reflected in organizational structure and
management control practices. This paper will report findings that
were a result of examining several abstract scenarios that are
exhibited in the design, operation, and dynamics of the control loop
and how they are projected on the functioning of the organization.
Valuable lessons are drawn in trying to find parallels and new
paradigms, and how the control theory science is reflected in the
design of the organizational structure and management practices. The
paper is structured in a logical and perceptive format. Further
research is needed to extend these findings.
Abstract: Electronics Products that achieve high levels of integrated communications, computing and entertainment, multimedia features in small, stylish and robust new form factors are winning in the market place. Due to the high costs that an industry may undergo and how a high yield is directly proportional to high profits, IC (Integrated Circuit) manufacturers struggle to maximize yield, but today-s customers demand miniaturization, low costs, high performance and excellent reliability making the yield maximization a never ending research of an enhanced assembly process. With factors such as minimum tolerances, tighter parameter variations a systematic approach is needed in order to predict the assembly process. In order to evaluate the quality of upcoming circuits, yield models are used which not only predict manufacturing costs but also provide vital information in order to ease the process of correction when the yields fall below expectations. For an IC manufacturer to obtain higher assembly yields all factors such as boards, placement, components, the material from which the components are made of and processes must be taken into consideration. Effective placement yield depends heavily on machine accuracy and the vision of the system which needs the ability to recognize the features on the board and component to place the device accurately on the pads and bumps of the PCB. There are currently two methods for accurate positioning, using the edge of the package and using solder ball locations also called footprints. The only assumption that a yield model makes is that all boards and devices are completely functional. This paper will focus on the Monte Carlo method which consists in a class of computational algorithms (information processed algorithms) which depends on repeated random samplings in order to compute the results. This method utilized in order to recreate the simulation of placement and assembly processes within a production line.
Abstract: The objective of this research is to develop an advanced driver assistance system characterized with the functions of lane departure warning (LDW), forward collision warning (FCW) and adaptive front-lighting system (AFS). The system is mainly configured a CCD/CMOS camera to acquire the images of roadway ahead in association with the analysis made by an image-processing unit concerning the lane ahead and the preceding vehicles. The input image captured by a camera is used to recognize the lane and the preceding vehicle positions by image detection and DROI (Dynamic Range of Interesting) algorithms. Therefore, the system is able to issue real-time auditory and visual outputs of warning when a driver is departing the lane or driving too close to approach the preceding vehicle unwittingly so that the danger could be prevented from occurring. During the nighttime, in addition to the foregoing warning functions, the system is able to control the bending light of headlamp to provide an immediate light illumination when making a turn at a curved lane and adjust the level automatically to reduce the lighting interference against the oncoming vehicles driving in the opposite direction by the curvature of lane and the vanishing point estimations. The experimental results show that the integrated vehicle image system is robust to most environments such as the lane detection and preceding vehicle detection average accuracy performances are both above 90 %.
Abstract: In CMOS integrated circuit design there is a trade-off between static power consumption and technology scaling. Recently, the power density has increased due to combination of higher clock speeds, greater functional integration, and smaller process geometries. As a result static power consumption is becoming more dominant. This is a challenge for the circuit designers. However, the designers do have a few methods which they can use to reduce this static power consumption. But all of these methods have some drawbacks. In order to achieve lower static power consumption, one has to sacrifice design area and circuit performance. In this paper, we propose a new method to reduce static power in the CMOS VLSI circuit using Variable Body Biasing technique without being penalized in area requirement and circuit performance.
Abstract: The importance for manipulating an incorporated
scaffold and directing cell behaviors is well appreciated for tissue
engineering. Here, we developed newly nano-topographic oxidized
silicon nanosponges capable of being various chemical modifications
to provide much insight into the fundamental biology of how cells
interact with their surrounding environment in vitro. A wet etching
technique is exerted to allow us fabricated the silicon nanosponges in a
high-throughput manner. Furthermore, various organo-silane
chemicals enabled self-assembled on the surfaces by vapor deposition.
We have found that Chinese hamster ovary (CHO) cells displayed
certain distinguishable morphogenesis, adherent responses, and
biochemical properties while cultured on these chemical modified
nano-topographic structures in compared with the planar oxidized
silicon counterparts, indicating that cell behaviors can be influenced
by certain physical characteristic derived from nano-topography in
addition to the hydrophobicity of contact surfaces crucial for cell
adhesion and spreading. Of particular, there were predominant
nano-actin punches and slender protrusions formed while cells were
cultured on the nano-topographic structures. This study shed potential
applications of these nano-topographic biomaterials for controlling
cell development in tissue engineering or basic cell biology research.
Abstract: Determination of wellbore problems during a
production/injection process might be evaluated thorough
temperature log analysis. Other applications of this kind of log
analysis may also include evaluation of fluid distribution analysis
along the wellbore and identification of anomalies encountered
during production/injection process. While the accuracy of such
prediction is paramount, the common method of determination of a
wellbore temperature log includes use of steady-state energy balance
equations, which hardly describe the real conditions as observed in
typical oil and gas flowing wells during production operation; and
thus increase level of uncertainties. In this study, a practical method
has been proposed through development of a simplified semianalytical
model to apply for predicting temperature profile along the
wellbore. The developed model includes an overall heat transfer
coefficient accounting all modes of heat transferring mechanism,
which has been focused on the prediction of a temperature profile as
a function of depth for the injection/production wells. The model has
been validated with the results obtained from numerical simulation.
Abstract: In this study, synthesis of biomemitic patterned nano
hydroxyapatite-starch biocomposites using different concentration of
starch to evaluate effect of polymer alteration on biocomposites
structural properties has been reported. Formation of hydroxyapatite
nano particles was confirmed by X-ray diffraction (XRD) and Fourier
transform infrared spectroscopy (FT-IR). Size and morphology of the
samples were characterized using scanning and transmission electron
microscopy (SEM and TEM). It seems that by increasing starch
content, the more active site of polymer (oxygen atoms) can be
provided for interaction with Ca2+ followed by phosphate and
hydroxyl group.
Abstract: In competitive electricity markets all over the world, an adoption of suitable transmission pricing model is a problem as transmission segment still operates as a monopoly. Transmission pricing is an important tool to promote investment for various transmission services in order to provide economic, secure and reliable electricity to bulk and retail customers. The nodal pricing based on SRMC (Short Run Marginal Cost) is found extremely useful by researchers for sending correct economic signals. The marginal prices must be determined as a part of solution to optimization problem i.e. to maximize the social welfare. The need to maximize the social welfare subject to number of system operational constraints is a major challenge from computation and societal point of views. The purpose of this paper is to present a nodal transmission pricing model based on SRMC by developing new mathematical expressions of real and reactive power marginal prices using GA-Fuzzy based optimal power flow framework. The impacts of selecting different social welfare functions on power marginal prices are analyzed and verified with results reported in literature. Network revenues for two different power systems are determined using expressions derived for real and reactive power marginal prices in this paper.
Abstract: This paper presents an information retrieval model on
XML documents based on tree matching. Queries and documents are
represented by extended trees. An extended tree is built starting from
the original tree, with additional weighted virtual links between each
node and its indirect descendants allowing to directly reach each
descendant. Therefore only one level separates between each node
and its indirect descendants. This allows to compare the user query
and the document with flexibility and with respect to the structural
constraints of the query. The content of each node is very important to
decide weither a document element is relevant or not, thus the content
should be taken into account in the retrieval process. We separate
between the structure-based and the content-based retrieval processes.
The content-based score of each node is commonly based on the
well-known Tf × Idf criteria. In this paper, we compare between
this criteria and another one we call Tf × Ief. The comparison
is based on some experiments into a dataset provided by INEX1 to
show the effectiveness of our approach on one hand and those of
both weighting functions on the other.
Abstract: In this paper, we consider a risk model involving two independent classes of insurance risks and random premium income. We assume that the premium income process is a Poisson Process, and the claim number processes are independent Poisson and generalized Erlang(n) processes, respectively. Both of the Gerber- Shiu functions with zero initial surplus and the probability generating functions (p.g.f.) of the Gerber-Shiu functions are obtained.
Abstract: Hyperglycaemia is a key factor that contributes to the
development of diabetes-related microvascular disease and a major
risk factor for endothelial dysfunction. In the current study, we have
explored glucose-induced abnormal intracellular calcium (Ca2+
i)
homeostasis in mouse microvessel endothelial cells (MMECs) in
high glucose (HG) (40mmol/L) versus control (low glucose, LG) (11
mmol/L). We demonstrated that the exposure of MMECs to HG for 3
days did not change basal Ca2+
i, however, there was a significant
increase of acetylcholine-induced Ca2+ entry. Western blots
illustrated that exposure to HG also increased STIM1 (Stromal
Interaction Molecule 1), but not Orai1 (the pore forming subunit),
protein expression levels. Although the link between HG-induced
changes in STIM1 expression, enhanced Ca2+ entry and endothelial
dysfunction requires further study, the current data are suggestive
that targeting these pathways may reduce the impact of HG on
endothelial function.
Abstract: IEEE 802.15.4a impulse radio-time hopping ultra wide
band (IR-TH UWB) physical layer, due to small duty cycle and very
short pulse widths is robust against multipath propagation. However,
scattering and reflections with the large number of obstacles in indoor
channel environments, give rise to dense multipath fading. It imposes
serious problem to optimum Rake receiver architectures, for which
very large number of fingers are needed. Presence of strong noise
also affects the reception of fine pulses having extremely low power
spectral density. A robust SRake receiver for IEEE 802.15.4a IRTH
UWB in dense multipath and additive white Gaussian noise
(AWGN) is proposed to efficiently recover the weak signals with
much reduced complexity. It adaptively increases the signal to noise
(SNR) by decreasing noise through a recursive least square (RLS)
algorithm. For simulation, dense multipath environment of IEEE
802.15.4a industrial non line of sight (NLOS) is employed. The power
delay profile (PDF) and the cumulative distribution function (CDF)
for the respective channel environment are found. Moreover, the error
performance of the proposed architecture is evaluated in comparison
with conventional SRake and AWGN correlation receivers. The
simulation results indicate a substantial performance improvement
with very less number of Rake fingers.
Abstract: Tandem mass spectrometry (MS/MS) is the engine
driving high-throughput protein identification. Protein mixtures possibly
representing thousands of proteins from multiple species are
treated with proteolytic enzymes, cutting the proteins into smaller
peptides that are then analyzed generating MS/MS spectra. The
task of determining the identity of the peptide from its spectrum
is currently the weak point in the process. Current approaches to de
novo sequencing are able to compute candidate peptides efficiently.
The problem lies in the limitations of current scoring functions. In this
paper we introduce the concept of proteome signature. By examining
proteins and compiling proteome signatures (amino acid usage) it is
possible to characterize likely combinations of amino acids and better
distinguish between candidate peptides. Our results strongly support
the hypothesis that a scoring function that considers amino acid usage
patterns is better able to distinguish between candidate peptides. This
in turn leads to higher accuracy in peptide prediction.
Abstract: This research presents a system for post processing of
data that takes mined flat rules as input and discovers crisp as well as
fuzzy hierarchical structures using Learning Classifier System
approach. Learning Classifier System (LCS) is basically a machine
learning technique that combines evolutionary computing,
reinforcement learning, supervised or unsupervised learning and
heuristics to produce adaptive systems. A LCS learns by interacting
with an environment from which it receives feedback in the form of
numerical reward. Learning is achieved by trying to maximize the
amount of reward received. Crisp description for a concept usually
cannot represent human knowledge completely and practically. In the
proposed Learning Classifier System initial population is constructed
as a random collection of HPR–trees (related production rules) and
crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is
suggested for the proposed system and based on Subsumption Matrix
(SM), a suitable fitness function is proposed. Suitable genetic
operators are proposed for the chosen chromosome representation
method. For implementing reinforcement a suitable reward and
punishment scheme is also proposed. Experimental results are
presented to demonstrate the performance of the proposed system.
Abstract: Decision Support System (DSS) are interactive
software systems that are built to assist the management of an
organization in the decision making process when faced with nonroutine
problems in a specific application domain. Non-functional
requirements (NFRs) for a DSS deal with the desirable qualities and
restrictions that the DSS functionalities must satisfy. Unlike the
functional requirements, which are tangible functionalities provided
by the DSS, NFRs are often hidden and transparent to DSS users but
affect the quality of the provided functionalities. NFRs are often
overlooked or added later to the system in an ad hoc manner, leading
to a poor overall quality of the system. In this paper, we discuss the
development of NFRs as part of the requirements engineering phase
of the system development life cycle of DSSs. To help eliciting
NFRs, we provide a comprehensive taxonomy of NFRs for DSSs.
Abstract: The focus of this paper is to construct daily time series
exchange rate forecast models of Samoan Tala/USD and Tala/AUD
during the year 2008 to 2012 with neural network The performance
of the models was measured by using varies error functions such as
Root Square mean error (RSME), Mean absolute error (MAE), and
Mean absolute percentage error (MAPE). Our empirical findings
suggest that AR (1) model is an effective tool to forecast the
Tala/USD and Tala/AUD.
Abstract: Accurate evaluation of damping ratios involving soilstructure interaction (SSI) effects is the prerequisite for seismic design of in-situ buildings. This study proposes a combined approach to identify damping ratios of SSI systems based on ambient excitation technique. The proposed approach is illustrated with main test process, sampling principle and algorithm steps through an engineering example, as along with its feasibility and validity. The proposed approach is employed for damping ratio identification of 82 buildings in Xi-an, China. Based on the experimental data, the variation range and tendency of damping ratios of these SSI systems, along with the preliminary influence factor, are shown and discussed. In addition, a fitting curve indicates the relation between the damping ratio and fundamental natural period of SSI system.
Abstract: Cultural stories are political. They register cultural
phenomena and their relations with the world and society in term of
their existence, function, characteristics by using different context.
This paper will provide a new way of rethinking which will help us
to rethink the relationship between fiction and politics. It discusses
the theme of human rights and it shows the relevance between art and
politics by studying the civil society through a literary framework.
Reasons to establish a relationship between fiction and politics are
the relevant themes and universal issues among the two disciplines.
Both disciplines are sets of views and ideas formulated by the human
mind to explain political or cultural phenomenon. Other reasons are
the complexity and depth of the author-s vision, and the need to
explain the violations of human rights in a more active structure
which can relate to emotional and social existence.
Abstract: The cost of developing the software from scratch can
be saved by identifying and extracting the reusable components from
already developed and existing software systems or legacy systems
[6]. But the issue of how to identify reusable components from
existing systems has remained relatively unexplored. We have used
metric based approach for characterizing a software module. In this
present work, the metrics McCabe-s Cyclometric Complexity
Measure for Complexity measurement, Regularity Metric, Halstead
Software Science Indicator for Volume indication, Reuse Frequency
metric and Coupling Metric values of the software component are
used as input attributes to the different types of Neural Network
system and reusability of the software component is calculated. The
results are recorded in terms of Accuracy, Mean Absolute Error
(MAE) and Root Mean Squared Error (RMSE).
Abstract: The survey and classification of the different security
attacks in structured peer-to-peer (P2P) overlay networks can be
useful to computer system designers, programmers, administrators,
and users. In this paper, we attempt to provide a taxonomy of
structured P2P overlay networks security attacks. We have specially
focused on the way these attacks can arise at each level of the
network. Moreover, we observed that most of the existing systems
such as Content Addressable Network (CAN), Chord, Pastry,
Tapestry, Kademlia, and Viceroy suffer from threats and vulnerability
which lead to disrupt and corrupt their functioning. We hope that our
survey constitutes a good help for who-s working on this area of
research.