Abstract: This paper presents a method of reducing the feedback
delay time of DWA(Data Weighted Averaging) used in sigma-delta
modulators. The delay time reduction results from the elimination of
the latch at the quantizer output and also from the falling edge
operation. The designed sigma-delta modulator improves the timing
margin about 16%. The sub-circuits of sigma-delta modulator such as
SC(Switched Capacitor) integrator, 9-level quantizer, comparator, and
DWA are designed with the non-ideal characteristics taken into
account. The sigma-delta modulator has a maximum SNR (Signal to
Noise Ratio) of 84 dB or 13 bit resolution.
Abstract: To create a solution for a specific problem in machine
learning, the solution is constructed from the data or by use a search
method. Genetic algorithms are a model of machine learning that can
be used to find nearest optimal solution. While the great advantage of
genetic algorithms is the fact that they find a solution through
evolution, this is also the biggest disadvantage. Evolution is inductive,
in nature life does not evolve towards a good solution but it evolves
away from bad circumstances. This can cause a species to evolve into
an evolutionary dead end. In order to reduce the effect of this
disadvantage we propose a new a learning tool (criteria) which can be
included into the genetic algorithms generations to compare the
previous population and the current population and then decide
whether is effective to continue with the previous population or the
current population, the proposed learning tool is called as Keeping
Efficient Population (KEP). We applied a GA based on KEP to the
production line layout problem, as a result KEP keep the evaluation
direction increases and stops any deviation in the evaluation.
Abstract: This paper deals with an adaptive multiuser detector for direct sequence code division multiple-access (DS-CDMA) systems. A modified receiver, precombinig LMMSE is considered under time varying channel environment. Detector updating is performed with two criterions, mean square estimation (MSE) and MOE optimization technique. The adaptive implementation issues of these two schemes are quite different. MSE criterion updates the filter weights by minimizing error between data vector and adaptive vector. MOE criterion together with canonical representation of the detector results in a constrained optimization problem. Even though the canonical representation is very complicated under time varying channels, it is analyzed with assumption of average power profile of multipath replicas of user of interest. The performance of both schemes is studied for practical SNR conditions. Results show that for poor SNR, MSE precombining LMMSE is better than the blind precombining LMMSE but for greater SNR, MOE scheme outperforms with better result.
Abstract: This article deals with the numerical simulation of the
floor heating convector in 3D. Presented convector can operate in
two modes – cooling mode and heating mode. This initial numerical
simulation is focused on cooling mode of the convector. Models with
different temperature of the fins are compared and three various
shapes of the fins are examined as well. The objective of the work is
to predict air flow and heat transfer inside convector for further
optimalization of these devices. For the numerical simulation was
used commercial software Ansys Fluent.
Abstract: In this paper the effects of top management commitment on knowledge management activities has been analyzed. This research has been conducted as a case study in an academic environment. The data collection was carried out in the form of semi-structured interview with an interview guide. This study shows the effects of knowledge management strategic plan developing in academia strategic plan on knowledge management success. This paper shows the importance top management commitment factors including strategic plan, communication, and training on knowledge management success in academia. In particular the most important role of Strategic planning in knowledge management success is clarified. This study explores one of the necessary organizational infrastructures of successful implementation of knowledge management. The idea of this research could be applied in the other context especially in the industrial organizations.
Abstract: This paper is aimed to give an illustration on the
application of Data Envelopment Analysis (DEA) as a tool to assess
Quality Management (QM) efficiency. A variant of DEA, slack based
measure (SBM) is used for this purpose. From this study, it is found
that DEA is suitable to measure QM efficiency and give
improvement suggestions to the inefficient QM.
Abstract: We depend upon explanation in order to “make sense"
out of our world. And, making sense is all the more important when
dealing with change. But, what happens if our explanations are
wrong? This question is examined with respect to two types of
explanatory model. Models based on labels and categories we shall
refer to as “representations." More complex models involving
stories, multiple algorithms, rules of thumb, questions, ambiguity we
shall refer to as “compressions." Both compressions and
representations are reductions. But representations are far more
reductive than compressions. Representations can be treated as a set
of defined meanings – coherence with regard to a representation is
the degree of fidelity between the item in question and the definition
of the representation, of the label. By contrast, compressions contain
enough degrees of freedom and ambiguity to allow us to make
internal predictions so that we may determine our potential actions in
the possibility space. Compressions are explanatory via mechanism.
Representations are explanatory via category. Managers are often
confusing their evocation of a representation (category inclusion) as
the creation of a context of compression (description of mechanism).
When this type of explanatory error occurs, more errors follow. In
the drive for efficiency such substitutions are all too often proclaimed
– at the manager-s peril..
Abstract: The purpose of this paper is applied Taguchi method on the optimization for PEMFC performance, and a representative Computational Fluid Dynamics (CFD) model is selectively performed for statistical analysis. The studied factors in this paper are pressure of fuel cell, operating temperature, the relative humidity of anode and cathode, porosity of gas diffusion electrode (GDE) and conductivity of GDE. The optimal combination for maximum power density is gained by using a three-level statistical method. The results confirmed that the robustness of the optimum design parameters influencing the performance of fuel cell are founded by pressure of fuel cell, 3atm; operating temperature, 353K; the relative humidity of anode, 50%; conductivity of GDE, 1000 S/m, but the relative humidity of cathode and porosity of GDE are pooled as error due to a small sum of squares. The present simulation results give designers the ideas ratify the effectiveness of the proposed robust design methodology for the performance of fuel cell.
Abstract: As a result of the high cost of housing, the increasing population is forced to live in substandard housing and unhealthy conditions giving rise to poor residential neighborhoods. The paper examines the causes and characteristics of poor residential neighborhood. The paper finds the problems that have influence poor neighborhoods to; poverty, growth of informal sector and housing shortage. The paper asserts that poor residential neighborhoods have adverse effects on the people.
The secondary data was obtained from books, journals and seminar papers while primary data relating to building and environmental quality from structured questionnaire administered on sample of 500 household heads, from sampling frame of 5000 housing units.
The study reveals that majority of the respondents are poor and employed in informal sector. The paper suggests urban renewal and slum upgrading programs as methods in dealing with the situation and an improvement in the socio-economic circumstances of the inhabitants.
Abstract: A SnO2/CdS/CdTe heterojunction was fabricated by
thermal evaporation technique. The fabricated cells were annealed at
573K for periods of 60, 120 and 180 minutes. The structural
properties of the solar cells have been studied by using X-ray
diffraction. Capacitance- voltage measurements were studied for the
as-prepared and annealed cells at a frequency of 102 Hz. The
capacitance- voltage measurements indicated that these cells are
abrupt. The capacitance decreases with increasing annealing time.
The zero bias depletion region width and the carrier concentration
increased with increasing annealing time. The carrier transport
mechanism for the CdS/CdTe heterojunction in dark is tunneling
recombination. The ideality factor is 1.56 and the reverse bias
saturation current is 9.6×10-10A. The energy band lineup for the n-
CdS/p-CdTe heterojunction was investigated using current - voltage
and capacitance - voltage characteristics.
Abstract: Australia, while being a large and eager consumer of
innovative and cutting edge Information and Communication
Technologies (ICT), continues to struggle to remain a leader in
Technological Innovation. This paper has two main contributions to
address certain aspects of this complex issue. The first being the
current findings of an ongoing research project on Information and
Innovation Management in the Australian Information and
Communication Technologies (ICT) sector. The major issues being
considered by the project include: investigation of the possible
inherent entrepreneurial nature of ICT; how to foster ICT innovation;
and examination of the inherent difficulties currently found within
the ICT industry of Australia in regards to supporting the
development of innovative and creative ideas. The second major
contribution is details of the I.-C.A.N. (Innovation by Collaborative
Anonymous Networking) software application information
management tool created and evolving in our research group. I-CAN,
besides having a positive reinforcement acronym, is aimed at
facilitating productive collaborative innovation in an Australian
workplace. Such a work environment is frequently subjected to
cultural influences such as the 'tall poppy syndrome' and 'negative'
or 'unconstructive' peer-pressure. There influences are frequently
seen as inhibitors to employee participation, entrepreneurship and
innovation.
Abstract: Image fusion aims to enhance the perception
of a scene by combining important information captured by
different sensors. Dual-Tree Complex Wavelet (DT-CWT) has been
thouroughly investigated for image fusion, since it takes advantages
of approximate shift invariance and direction selectivity. But it can
only handle limited direction information. To allow a more flexible
directional expansion for images, we propose a novel fusion scheme,
referred to as complex contourlet transform (CCT). It successfully
incorporates directional filter banks (DFB) into DT-CWT. As a result
it efficiently deal with images containing contours and textures,
whereas it retains the property of shift invariance. Experimental
results demonstrated that the method features high quality fusion
performance and can facilitate many image processing applications.
Abstract: This paper presents an efficient emission constrained
hydrothermal scheduling algorithm that deals with nonlinear
functions such as the water discharge characteristics, thermal cost,
and transmission loss. It is then incorporated into the hydrothermal
coordination program. The program has been tested on a practical
utility system having 32 thermal and 12 hydro generating units. Test
results show that a slight increase in production cost causes a
substantial reduction in emission.
Abstract: Pattern recognition is the research area of Artificial
Intelligence that studies the operation and design of systems that
recognize patterns in the data. Important application areas are image
analysis, character recognition, fingerprint classification, speech
analysis, DNA sequence identification, man and machine
diagnostics, person identification and industrial inspection. The
interest in improving the classification systems of data analysis is
independent from the context of applications. In fact, in many
studies it is often the case to have to recognize and to distinguish
groups of various objects, which requires the need for valid
instruments capable to perform this task. The objective of this article
is to show several methodologies of Artificial Intelligence for data
classification applied to biomedical patterns. In particular, this work
deals with the realization of a Computer-Aided Detection system
(CADe) that is able to assist the radiologist in identifying types of
mammary tumor lesions. As an additional biomedical application of
the classification systems, we present a study conducted on blood
samples which shows how these methods may help to distinguish
between carriers of Thalassemia (or Mediterranean Anaemia) and
healthy subjects.
Abstract: This paper describes the application of a model predictive controller to the problem of batch reactor temperature control. Although a great deal of work has been done to improve reactor throughput using batch sequence control, the control of the actual reactor temperature remains a difficult problem for many operators of these processes. Temperature control is important as many chemical reactions are sensitive to temperature for formation of desired products. This controller consist of two part (1) a nonlinear control method GLC (Global Linearizing Control) to create a linear model of system and (2) a Model predictive controller used to obtain optimal input control sequence. The temperature of reactor is tuned to track a predetermined temperature trajectory that applied to the batch reactor. To do so two input signals, electrical powers and the flow of coolant in the coil are used. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.
Abstract: Based on statistics released by Islamic Republic of
Iran Police (IRIP), from among the total 9555 motorcycle accidents
that happened in 2007, 857 riders died and 11219 one got injured. If
we also consider the death toll and injuries of other vehicles'
accidents resulted from traffic violation by motorcycle riders, then
paying attention to the motorcycle accidents seems to be very
necessary. Therefore, in this study we tried to investigate the traits
and issues related to production, application, and training, along with
causes of motorcycle accidents from 4 perspectives of road, human,
environment and vehicle and also based on statistical and
geographical analysis of accident-sheets prepared by Iran Road
Patrol Department (IRPD). Unfamiliarity of riders with regulations
and techniques of motorcycling, disuse of safety equipments,
inefficiency of roads and design of junctions for safe trafficking of
motorcycles and finally the lack of sufficient control of responsible
organizations are among the major causes which lead to these
accidents.
Abstract: In this paper, a new adaptive Fourier decomposition
(AFD) based time-frequency speech analysis approach is proposed.
Given the fact that the fundamental frequency of speech signals often
undergo fluctuation, the classical short-time Fourier transform (STFT)
based spectrogram analysis suffers from the difficulty of window size
selection. AFD is a newly developed signal decomposition theory. It is
designed to deal with time-varying non-stationary signals. Its
outstanding characteristic is to provide instantaneous frequency for
each decomposed component, so the time-frequency analysis becomes
easier. Experiments are conducted based on the sample sentence in
TIMIT Acoustic-Phonetic Continuous Speech Corpus. The results
show that the AFD based time-frequency distribution outperforms the
STFT based one.
Abstract: Disposal of health-care waste (HCW) is considered as
an important environmental problem especially in large cities.
Multiple criteria decision making (MCDM) techniques are apt to deal
with quantitative and qualitative considerations of the health-care
waste management (HCWM) problems. This research proposes a
fuzzy multi-criteria group decision making approach with a multilevel
hierarchical structure including qualitative as well as
quantitative performance attributes for evaluating HCW disposal
alternatives for Istanbul. Using the entropy weighting method,
objective weights as well as subjective weights are taken into account
to determine the importance weighting of quantitative performance
attributes. The results obtained using the proposed methodology are
thoroughly analyzed.
Abstract: This paper deals about four items assembly process of
linear drive. This assembly will be realized in flexible assembly cell
on Institute of Manufacturing Systems and Applied Mechanics. There
is defined manufacturing cell, individual actuators created our
flexible cell. Next chapter is about control type, detailed describe a
sequence control type, which will be used in mentioned flexible
assembly cell. All cell control is divided in individual steps
instructions. There instructions illustrate table number III.
Abstract: The problem of controlling a two link robotic manipulator, consisting of a rotating and a prismatic links, is addressed. The actuations of both links are assumed to have unknown dead zone nonlinearities and friction torques modeled by LuGre friction model. Because of the existence of the unknown dead zone and friction torque at the actuations, unknown parameters and unmeasured states would appear to be part of the overall system dynamics that need for estimation. Unmeasured states observer, unknown parameters estimators, and robust adaptive control laws have been derived such that closed loop global stability is achieved. Simulation results have been performed to show the efficacy of the suggested approach.