Abstract: Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.
Abstract: This paper is focused on the investigation of productivity (total productivity and partial productivity). The value productivity is an indicator of level and changes in technical economic efficiency of production factors. It represents an important factor in achieving corporate objectives. This text works with the contemporary concept of value productivity that means that indicators of the productivity express the effect of economic efficiency not only of inputs consumption, but also of inputs binding efficiency. This approach is based on principles of the economic profit, respectively the economic value added (EVA). The research is done on the sample of Czech enterprises operating in the automotive industry in the regions of Liberec and the Central Bohemia. The data sample covers the time period 2006-2011 which allows the comparison of development before crisis and during crisis period. It enables to discover the companies' reaction during crises and the regional comparison allows to showing if there are significant differences between regions.
Abstract: Although many factors play a significant role in agricultural production and productivity, the importance of soil fertility cannot be underestimated. The extent to which small farmers are able to manage the fertility of their farmlands is crucial in agricultural development particularly in sub-Saharan Africa (SSA). This paper assesses the nutrient status of selected farmers’ fields in relation to how government policy addresses the allocation of and access to agricultural inputs (e.g. chemical fertilizers) in a unique social-ecological environment of the Okavango Delta in northern Botswana. It also analyses small farmers and soil scientists’ perceptions about the political economy of integrated soil fertility management (ISFM) in the area. A multi-stage sampling procedure was used to elicit quantitative and qualitative information from 228 farmers and 9 soil researchers through the use of interview schedules and questionnaires, respectively. Knowledge validation workshops and focus group discussions (FGDs) were also used to collect qualitative data from farmers. Thirty-three composite soil samples were collected from 30 farmers’ plots in three farming communities of Makalamabedi, Nokaneng and Mohembo for laboratory analysis. While meeting points exist, farmers and scientists have divergent perspectives on soil fertility management. Laboratory analysis carried out shows that most soils in the wetland and the adjoining dry-land/upland surroundings are low in essential nutrients as well as in cation exchange capacity (CEC). Although results suggest the identification and use of appropriate inorganic fertilizers, the low CEC is an indication that holistic cultural practices, which are beyond mere chemical fertilizations, are critical and more desirable for improved soil health and sustainable livelihoods in the area. Farmers’ age (t= -0.728; p≤0.10); their perceptions about the political economy (t = -0.485; p≤0.01) of ISFM; and their preference for the use of local knowledge in soil fertility management (t = -10.254; p≤0.01) had a significant relationship with how they perceived their involvement in the implementation of ISFM.
Abstract: Widespread use of response spectra in seismic design and evaluation of different types of structures makes them one of the most important seismic inputs. This importance urges the local design codes to adapt precise data based on updated information about the recent major earthquakes happened and also localized geotechnical data. In this regard, this paper derives the response spectra with a geotechnical approach for various scenarios coming from the recent major earthquakes happened in Iran for different types of hard soils, and compares the results to the corresponding spectra from the current seismic code. This comparison implies the need for adapting new design spectra for seismic design, because of major differences in the frequency domains and amplifications.
Abstract: The aim of this paper is to evaluate the performance of the faculties of Islamic Azad University of Zahedan Branch based on two-component (teaching and research) decision making units (DMUs) in data envelopment analysis (DEA). Nowadays it is obvious that most of the systems as DMUs do not act as a simple inputoutput structure. Instead, if they have been studied more delicately, they include network structure. University is such a network in which different sections i.e. teaching, research, students and office work as a parallel structure. They consume some inputs of university commonly and some others individually. Then, they produce both dependent and independent outputs. These DMUs are called two-component DMUs
with network structure. In this paper, performance of the faculties of Zahedan branch is calculated by using relative efficiency model and also, a formula to compute relative efficiencies teaching and research components based on DEA are offered.
Abstract: One of the United Nations Millennium Development targets is to 'achieve significant improvement in lives of at least 100 million slum dwellers, by 2020'. To monitor progress on this target a first step is to develop an operational definition to identify slum settlements. The indicators selected are: access to water and sanitation, sufficient living area, a house with durable material on a non-hazardous location and with tenure security. This paper describes the techniques of identifying slums and applied the techniques in identifying slum in Lafia town. The methodology used was selection of one district in Lafia town for this study and the district was zoned into four units. The total of 10% sample size out of 2,482 households of 250 questionnaires was administered using systematic sampling method based on proportion of houses at each zones as 90, 70, 40 and 50 respectively. The result shows that the area is a second order degeneration that needs a major improvement. Recommendations were made in this regard for urgent intervention in improving or upgrading of housing and infrastructural facilities
Abstract: This paper describes an automated implementable
system for impulsive signals detection and recognition. The system
uses a Digital Signal Processing device for the detection and
identification process. Here the system analyses the signals in real
time in order to produce a particular response if needed. The system
analyses the signals in real time in order to produce a specific output
if needed. Detection is achieved through normalizing the inputs and
comparing the read signals to a dynamic threshold and thus avoiding
detections linked to loud or fluctuating environing noise.
Identification is done through neuronal network algorithms. As a
setup our system can receive signals to “learn” certain patterns.
Through “learning” the system can recognize signals faster, inducing
flexibility to new patterns similar to those known. Sound is captured
through a simple jack input, and could be changed for an enhanced
recording surface such as a wide-area recorder. Furthermore a
communication module can be added to the apparatus to send alerts
to another interface if needed.
Abstract: The banking sector poses a lot of problems in Nigeria in general and the non-oil export sector in particular. The banks' lack effectiveness in handling small, medium or long-term credit risk (lack of training of loan officers, lack of information on borrowers and absence of a reliable credit registry) results in non-oil exporters being burdened with high requirements, such as up to three years of financial statements, enough collateral to cover both the loan principal and interest (including a cash deposit that may be up to 30% of the loans' net present value), and to provide every detail of the international trade transaction in question. The stated problems triggered this research. Consequently, information on bank financing of non-oil exports was collected from 100 respondents from the 20 Deposit Money Banks (DMBs) in Nigeria. The data was analysed by the use of descriptive statistics correlation and regression. It is found that, Nigerian banks are participants in the financing of non-oil exports. Despite their participation, the rate of interest for credit extended to non-oil export is usually high, ranging between 15-20%. Small and medium sized non-oil export businesses lack the credit history for banks to judge them as reputable. Banks also consider the non-oil export sector very risky for investment. The banks actually do grant less credit than the exporters may require and therefore are not properly funded by banks. Banks grant very low volume of foreign currency loan in addition to, unfavorable exchange rate at which Naira is exchanged to the Dollar and other currencies in the country. This makes importation of inputs costly and negatively impacted on the non-oil export performance in Nigeria.
Abstract: In this paper, a low-power digital controller for DC-DC power conversion was presented. The controller generates the pulse-width modulated (PWM) signal from digital inputs provided by analog-to-digital converter (ADC). An efficient and simple design scheme to develop the control unit was discussed. This method allows minimization of the consumed resources of the chip and it is based on direct digital design approach. In this application, with the proposed scheme, nearly half area and two-third of the power consumption was saved compared to the conventional schemes. This work illustrates the possibility of implementing low-power and area-efficient power management circuit using direct digital design based approach.
Abstract: Learning the gradient of neuron's activity function
like the weight of links causes a new specification which is
flexibility. In flexible neural networks because of supervising and
controlling the operation of neurons, all the burden of the learning is
not dedicated to the weight of links, therefore in each period of
learning of each neuron, in fact the gradient of their activity function,
cooperate in order to achieve the goal of learning thus the number of
learning will be decreased considerably.
Furthermore, learning neurons parameters immunes them against
changing in their inputs and factors which cause such changing.
Likewise initial selecting of weights, type of activity function,
selecting the initial gradient of activity function and selecting a fixed
amount which is multiplied by gradient of error to calculate the
weight changes and gradient of activity function, has a direct affect
in convergence of network for learning.
Abstract: This paper analyses the structural changes in
education sector since the introduction of liberalization policy in
India. This paper explains how the so-called non-profit trusts and
societies appropriated the liberalization policy and enhanced
themselves as new capitalist class in higher education sector. Over
the decades, the policy witnessed the role of private sector in terms
of maintaining market equilibrium. The state also witnessed the
incompatibility of the private sector in inculcating the values of
social justice. The most important consequence of the policy is to
witness the rise of new capitalist class and academic capitalism.
When the state came to realize that it no longer cope up with
market demands, it opens the entry of private sector in higher
education. Concessions and tax exemptions were provided to the
trusts and societies to establish higher education institutions. There
is a basic difference between western countries and India in
providing higher education by the trusts and societies. In western
countries the big business houses contributed their surplus
revenues to promote higher education and research as a
complementary service to society and nation. In India, several
entrepreneurs came up with business motive using education
sector. Over the period, they accumulated wealth at the cost of
students and concessions from the government. Four major results
can now be identified: production of manpower in view of market
demands; reduction of standards in higher education; bypassing the
values of social justice; and the rise of new capitalist class from the
business of education. This paper tries to substantiate these issues
with the inputs from case studies.
Abstract: Nowadays, more engineering systems are using some
kind of Artificial Intelligence (AI) for the development of their
processes. Some well-known AI techniques include artificial neural
nets, fuzzy inference systems, and neuro-fuzzy inference systems
among others. Furthermore, many decision-making applications base
their intelligent processes on Fuzzy Logic; due to the Fuzzy
Inference Systems (FIS) capability to deal with problems that are
based on user knowledge and experience. Also, knowing that users
have a wide variety of distinctiveness, and generally, provide
uncertain data, this information can be used and properly processed
by a FIS. To properly consider uncertainty and inexact system input
values, FIS normally use Membership Functions (MF) that represent
a degree of user satisfaction on certain conditions and/or constraints.
In order to define the parameters of the MFs, the knowledge from
experts in the field is very important. This knowledge defines the MF
shape to process the user inputs and through fuzzy reasoning and
inference mechanisms, the FIS can provide an “appropriate" output.
However an important issue immediately arises: How can it be
assured that the obtained output is the optimum solution? How can it
be guaranteed that each MF has an optimum shape? A viable solution
to these questions is through the MFs parameter optimization. In this
Paper a novel parameter optimization process is presented. The
process for FIS parameter optimization consists of the five simple
steps that can be easily realized off-line. Here the proposed process
of FIS parameter optimization it is demonstrated by its
implementation on an Intelligent Interface section dealing with the
on-line customization / personalization of internet portals applied to
E-commerce.
Abstract: In this paper, an automatic system of diagnosis was
developed to detect and locate in real time the defects of the wound
rotor asynchronous machine associated to electronic converter. For
this purpose, we have treated the signals of the measured parameters
(current and speed) to use them firstly, as indicating variables of the
machine defects under study and, secondly, as inputs to the Artificial
Neuron Network (ANN) for their classification in order to detect the
defect type in progress. Once a defect is detected, the interpretation
system of information will give the type of the defect and its place of
appearance.
Abstract: The purpose of suspension system in automobiles is to
improve the ride comfort and road handling. In this research the ride
and handling performance of a specific automobile with passive
suspension system is compared to a proposed fuzzy logic semi active
suspension system designed for that automobile. The bodysuspension-
wheel system is modeled as a two degree of freedom
quarter car model. MATLAB/SIMULINK [1] was used for
simulation and controller design. The fuzzy logic controller is based
on two inputs namely suspension velocity and body velocity. The
output of the fuzzy controller is the damping coefficient of the
variable damper. The result shows improvement over passive
suspension method.
Abstract: Time-Cost Optimization "TCO" is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Since there is a hidden trade-off relationship between project and cost, it might be difficult to predict whether the total cost would increase or decrease as a result of the schedule compression. Recently third dimension in trade-off analysis is taken into consideration that is quality of the projects. Few of the existing algorithms are applied in a case of construction project with threedimensional trade-off analysis, Time-Cost-Quality relationships. The objective of this paper is to presents the development of a practical software system; that named Automatic Multi-objective Typical Construction Resource Optimization System "AMTCROS". This system incorporates the basic concepts of Line Of Balance "LOB" and Critical Path Method "CPM" in a multi-objective Genetic Algorithms "GAs" model. The main objective of this system is to provide a practical support for typical construction planners who need to optimize resource utilization in order to minimize project cost and duration while maximizing its quality simultaneously. The application of these research developments in planning the typical construction projects holds a strong promise to: 1) Increase the efficiency of resource use in typical construction projects; 2) Reduce construction duration period; 3) Minimize construction cost (direct cost plus indirect cost); and 4) Improve the quality of newly construction projects. A general description of the proposed software for the Time-Cost-Quality Trade-Off "TCQTO" is presented. The main inputs and outputs of the proposed software are outlined. The main subroutines and the inference engine of this software are detailed. The complexity analysis of the software is discussed. In addition, the verification, and complexity of the proposed software are proved and tested using a real case study.
Abstract: The optimal control is one of the possible controllers
for a dynamic system, having a linear quadratic regulator and using
the Pontryagin-s principle or the dynamic programming method .
Stochastic disturbances may affect the coefficients (multiplicative
disturbances) or the equations (additive disturbances), provided that
the shocks are not too great . Nevertheless, this approach encounters
difficulties when uncertainties are very important or when the probability
calculus is of no help with very imprecise data. The fuzzy
logic contributes to a pragmatic solution of such a problem since it
operates on fuzzy numbers. A fuzzy controller acts as an artificial
decision maker that operates in a closed-loop system in real time.
This contribution seeks to explore the tracking problem and control
of dynamic macroeconomic models using a fuzzy learning algorithm.
A two inputs - single output (TISO) fuzzy model is applied to the
linear fluctuation model of Phillips and to the nonlinear growth model
of Goodwin.
Abstract: Realistic systems generally are systems with various
inputs and outputs also known as Multiple Input Multiple Output
(MIMO). Such systems usually prove to be complex and difficult to
model and control purposes. Therefore, decomposition was used to
separate individual inputs and outputs. A PID is assigned to each
individual pair to regulate desired settling time. Suitable parameters
of PIDs obtained from Genetic Algorithm (GA), using Mean of
Squared Error (MSE) objective function.
Abstract: Urban problems are problems of organized complexity. Thus, many models and scientific methods to resolve urban problems are failed. This study is concerned with proposing of a fuzzy system driven approach for classification and solving urban problems. The proposed study investigated mainly the selection of the inputs and outputs of urban systems for classification of urban problems. In this research, five categories of urban problems, respect to fuzzy system approach had been recognized: control, polytely, optimizing, open and decision making problems. Grounded Theory techniques were then applied to analyze the data and develop new solving method for each category. The findings indicate that the fuzzy system methods are powerful processes and analytic tools for helping planners to resolve urban complex problems. These tools can be successful where as others have failed because both incorporate or address uncertainty and risk; complexity and systems interacting with other systems.
Abstract: this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.
Abstract: In this paper we present a Adaptive Neuro-Fuzzy
System (ANFIS) with inputs the lagged dependent variable for the
prediction of Gross domestic Product growth rate in six countries.
We compare the results with those of Autoregressive (AR) model.
We conclude that the forecasting performance of neuro-fuzzy-system
in the out-of-sample period is much more superior and can be a very
useful alternative tool used by the national statistical services and the
banking and finance industry.