Abstract: In the past decade, artificial neural networks (ANNs)
have been regarded as an instrument for problem-solving and
decision-making; indeed, they have already done with a substantial
efficiency and effectiveness improvement in industries and businesses.
In this paper, the Back-Propagation neural Networks (BPNs) will be
modulated to demonstrate the performance of the collaborative
forecasting (CF) function of a Collaborative Planning, Forecasting and
Replenishment (CPFR®) system. CPFR functions the balance between
the sufficient product supply and the necessary customer demand in a
Supply and Demand Chain (SDC). Several classical standard BPN will
be grouped, collaborated and exploited for the easy implementation of
the proposed modular ANN framework based on the topology of a
SDC. Each individual BPN is applied as a modular tool to perform the
task of forecasting SKUs (Stock-Keeping Units) levels that are
managed and supervised at a POS (point of sale), a wholesaler, and a
manufacturer in an SDC. The proposed modular BPN-based CF
system will be exemplified and experimentally verified using lots of
datasets of the simulated SDC. The experimental results showed that a
complex CF problem can be divided into a group of simpler
sub-problems based on the single independent trading partners
distributed over SDC, and its SKU forecasting accuracy was satisfied
when the system forecasted values compared to the original simulated
SDC data. The primary task of implementing an autonomous CF
involves the study of supervised ANN learning methodology which
aims at making “knowledgeable" decision for the best SKU sales plan
and stocks management.
Abstract: Optical 3D measurement of objects is meaningful in
numerous industrial applications. In various cases shape acquisition
of weak textured objects is essential. Examples are repetition parts
made of plastic or ceramic such as housing parts or ceramic bottles as
well as agricultural products like tubers. These parts are often
conveyed in a wobbling way during the automated optical inspection.
Thus, conventional 3D shape acquisition methods like laser scanning
might fail. In this paper, a novel approach for acquiring 3D shape of
weak textured and moving objects is presented. To facilitate such
measurements an active stereo vision system with structured light is
proposed. The system consists of multiple camera pairs and auxiliary
laser pattern generators. It performs the shape acquisition within one
shot and is beneficial for rapid inspection tasks. An experimental
setup including hardware and software has been developed and
implemented.
Abstract: Nagaland, the 16th state of India in order of
statehood, is situated between 25° 6' and 27° 4' latitude north and
between 93º 20' E and 95º 15' E longitude of equator in the North
Eastern part of the India. Endowed with varied topography, soil and
agro climatic conditions it is known for its potentiality to grow all
most all kinds of horticultural crops. Pineapple being grown since
long organically by default is one of the most promising crops of the
state with emphasis being laid for commercialization by the
government of Nagaland. In light of commercialization, globalization
and scope of setting small-scale industries, a research study was
undertaken to examine the socio-economic and personal
characteristics, entrepreneurial characteristics and attitude of the
pineapple growers towards improved package of practices of
pineapple cultivation. The study was conducted in Medziphema
block of Dimapur district of the Nagaland state of India following ex
post facto research design. Ninety pineapple growers were selected
from four different villages of Medziphema block based on
proportionate random selection procedure. Findings of the study
revealed that majority of the respondents had medium level of
entrepreneurial characteristics in terms of knowledge level, risk
orientation, self confidence, management orientation, farm decision
making ability and leadership ability and most of them had
favourable attitude towards improved package of practices of
pineapple cultivation. The variables age, education, farm size, risk
orientation, management orientation and sources of information
utilized were found important to influence the attitude of the
respondents. The study revealed that favourable attitude and
entrepreneurial characteristics of the pineapple cultivators might be
harnessed for increased production of pineapple in the state thereby
bringing socio economic upliftment of the marginal and small-scale
farmers.
Abstract: This paper proposes the hypothesis that multilateralism and regionalism are complementary, and that regional income convergence is likely with a like minded and committed regionalism that often has links geographically and culturally. The association between international trade, income per capita, and regional income convergence in founder members of ASEAN and SAARC, is explored by applying the Lumsdaine, and Papell approach. The causal relationships between the above variables are also studied in respective trade blocs by using Granger causality tests. The conclusion is that global reforms have had a greater impact on increasing trade for both trade blocs and induced convergence only in ASEAN-5 countries. The experience of ASEAN countries shows a two-way causal relationship between the flow from trade to regional income convergence, and vice versa. There is no evidence in SAARC countries for income convergence and causality.
Abstract: The successful implementation of Service-Oriented Architecture (SOA) is not confined to Information Technology systems and required changes of the whole enterprise. In order to adapt IT and business, the enterprise requires adequate and measurable methods. The adoption of SOA creates new problem with regard to measuring and analysis the performance. In fact the enterprise should investigate to what extent the development of services will increase the value of business. It is required for every business to measure the extent of SOA adaptation with the goals of enterprise. Moreover, precise performance metrics and their combination with the advanced evaluation methodologies as a solution should be defined. The aim of this paper is to present a systematic methodology for designing a measurement system at the technical and business levels, so that: (1) it will determine measurement metrics precisely (2) the results will be analysed by mapping identified metrics to the measurement tools.
Abstract: This study is concerned with the investigation of the
suitability of several empirical and semi-empirical drying models
available in the literature to define drying behavior of viscose yarn
bobbins. For this purpose, firstly, experimental drying behaviour of
viscose bobbins was determined on an experimental dryer setup
which was designed and manufactured based on hot-air bobbin
dryers used in textile industry. Afterwards, drying models considered
were fitted to the experimentally obtained moisture ratios. Drying
parameters were drying temperature and bobbin diameter. The fit
was performed by selecting the values for constants in the models in
such a way that these values make the sum of the squared differences
between the experimental and the model results for moisture ratio
minimum. Suitability of fitting was specified as comparing the
correlation coefficient, standard error and mean square deviation.
The results show that the most appropriate model in describing the
drying curves of viscose bobbins is the Page model.
Abstract: A new, rapidly convergent, numerical procedure for
internal loading distribution computation in statically loaded, singlerow,
angular-contact ball bearings, subjected to a known combined
radial and thrust load, which must be applied so that to avoid tilting
between inner and outer rings, is used to find the load distribution
differences between a loaded unfitted bearing at room temperature,
and the same loaded bearing with interference fits that might
experience radial temperature gradients between inner and outer
rings. For each step of the procedure it is required the iterative
solution of Z + 2 simultaneous nonlinear equations – where Z is the
number of the balls – to yield exact solution for axial and radial
deflections, and contact angles.
Abstract: The ability of the brain to organize information and generate the functional structures we use to act, think and communicate, is a common and easily observable natural phenomenon. In object-oriented analysis, these structures are represented by objects. Objects have been extensively studied and documented, but the process that creates them is not understood. In this work, a new class of discrete, deterministic, dissipative, host-guest dynamical systems is introduced. The new systems have extraordinary self-organizing properties. They can host information representing other physical systems and generate the same functional structures as the brain does. A simple mathematical model is proposed. The new systems are easy to simulate by computer, and measurements needed to confirm the assumptions are abundant and readily available. Experimental results presented here confirm the findings. Applications are many, but among the most immediate are object-oriented engineering, image and voice recognition, search engines, and Neuroscience.
Abstract: Support vector regression (SVR) has been regarded
as a state-of-the-art method for approximation and regression. The
importance of kernel function, which is so-called admissible support
vector kernel (SV kernel) in SVR, has motivated many studies
on its composition. The Gaussian kernel (RBF) is regarded as a
“best" choice of SV kernel used by non-expert in SVR, whereas
there is no evidence, except for its superior performance on some
practical applications, to prove the statement. Its well-known that
reproducing kernel (R.K) is also a SV kernel which possesses many
important properties, e.g. positive definiteness, reproducing property
and composing complex R.K by simpler ones. However, there are a
limited number of R.Ks with explicit forms and consequently few
quantitative comparison studies in practice. In this paper, two R.Ks,
i.e. SV kernels, composed by the sum and product of a translation
invariant kernel in a Sobolev space are proposed. An exploratory
study on the performance of SVR based general R.K is presented
through a systematic comparison to that of RBF using multiple
criteria and synthetic problems. The results show that the R.K is
an equivalent or even better SV kernel than RBF for the problems
with more input variables (more than 5, especially more than 10) and
higher nonlinearity.
Abstract: Applied a mouse-s roller with a gripper to increase the
efficiency for a gripper can learn to a material handling without
slipping. To apply a gripper, we use the optimize principle to develop
material handling by use a signal for checking a roller mouse that
rotate or not. In case of the roller rotates means that the material slips.
A gripper will slide to material handling until the roller will not
rotate. As this experiment has test material handling for comparing a
grip force that uses to material handling of the 10-human with the
applied gripper. We can summarize that human exert the material
handling more than the applied gripper. Because of the gripper can
exert more befit to material handling than human and may be a
minimum force to lift a material without slipping.
Abstract: This paper focuses on developing an integrated
reliable and sophisticated model for ultra large wind turbines And to
study the performance and analysis of vector control on large wind
turbines. With the advance of power electronics technology, direct
driven multi-pole radial flux PMSG (Permanent Magnet Synchronous
Generator) has proven to be a good choice for wind turbines
manufacturers. To study the wind energy conversion systems, it is
important to develop a wind turbine simulator that is able to produce
realistic and validated conditions that occur in real ultra MW wind
turbines. Three different packages are used to simulate this model,
namely, Turbsim, FAST and Simulink. Turbsim is a Full field wind
simulator developed by National Renewable Energy Laboratory
(NREL). The wind turbine mechanical parts are modeled by FAST
(Fatigue, Aerodynamics, Structures and Turbulence) code which is
also developed by NREL. Simulink is used to model the PMSG, full
scale back to back IGBT converters, and the grid.
Abstract: WebGL is typically used with web browsers. In this
paper, we represent a standalone WebGL execution environment,
where the original WebGL source codes show the same result to those
of WebGL-capable web browsers. This standalone environment
enables us to run WebGL programs without web browsers and/or
internet connections. Our implementation shows the same rendering
results with typical web browser outputs. This standalone environment
is suitable for low-tier devices and/or debugging purposes.
Abstract: Describes the current situation of educational Robotics
"the State of the art" its concept, its evolution their niches of
opportunity, academic and business and the importance of education
and academic outreach. It shows that the development of high-tech
automated educational materials influence the teaching-learning
process and that communication between machines and humans is a
reality.
Abstract: As in today's semiconductor industries test costs can make up to 50 percent of the total production costs, an efficient test error detection becomes more and more important. In this paper, we present a new machine learning approach to test error detection that should provide a faster recognition of test system faults as well as an improved test error recall. The key idea is to learn a classifier ensemble, detecting typical test error patterns in wafer test results immediately after finishing these tests. Since test error detection has not yet been discussed in the machine learning community, we define central problem-relevant terms and provide an analysis of important domain properties. Finally, we present comparative studies reflecting the failure detection performance of three individual classifiers and three ensemble methods based upon them. As base classifiers we chose a decision tree learner, a support vector machine and a Bayesian network, while the compared ensemble methods were simple and weighted majority vote as well as stacking. For the evaluation, we used cross validation and a specially designed practical simulation. By implementing our approach in a semiconductor test department for the observation of two products, we proofed its practical applicability.
Abstract: The impact of noise upon live quality has become an
important aspect to make both urban and environmental policythroughout
Europe and in Turkey. Concern over the quality of urban
environments, including noise levels and declining quality of green
space, is over the past decade with increasing emphasis on designing
livable and sustainable communities. According to the World Health
Organization, noise pollution is the third most hazardous
environmental type of pollution which proceeded by only air (gas
emission) and water pollution. The research carried out in two
phases, the first stage of the research noise and plant types providing
the suction of noise was evaluated through literature study and at the
second stage, definite types (Juniperus horizontalis L., Spirea
vanhouetti Briot., Cotoneaster dammerii C.K., Berberis thunbergii
D.C., Pyracantha coccinea M. etc.) were selected for the city of
Konya. Trials were conducted on the highway of Konya. The biggest
value of noise reduction was 6.3 dB(A), 4.9 dB(A), 6.2 dB(A) value
with compared to the control which includes the group that formed
by the bushes at the distance of 7m, 11m, 20m from the source and
5m, 9m, 20m of plant width, respectively. In this paper, definitions
regarding to noise and its sources were made and the precautions
were taken against to noise that mentioned earlier with the adverse
effects of noise. Plantation design approaches and suggestions
concerning to the diversity to be used, which are peculiar to roadside,
were developed to discuss the role and the function of plant material
to reduce the noise of the traffic.
Abstract: In the literature of information theory, there is
necessity for comparing the different measures of fuzzy entropy and
this consequently, gives rise to the need for normalizing measures of
fuzzy entropy. In this paper, we have discussed this need and hence
developed some normalized measures of fuzzy entropy. It is also
desirable to maximize entropy and to minimize directed divergence
or distance. Keeping in mind this idea, we have explained the method
of optimizing different measures of fuzzy entropy.
Abstract: In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.
Abstract: In the paper it is questioned whether effective state
social policy provides happiness and social progress. For this purpose
selected correlations between Human Development Index (HDI),
share of public social expenditures in GDP, the Happy Planet Index
(HPI), GDP per capita, and Government Effectiveness are examined
and the results are graphically presented. It is shown how a
government can affect well-being and happiness in different countries
of modern world. Also, it is tested the hypothesis about existence of a
certain optimum of well-being and public social expenditures, which
affect direction of social progress. It is concluded that efficient social
policy and wealth are not the only factors determining human
happiness.
Abstract: This paper deals with stakeholders’ decisions within energy neutral urban redevelopment processes. The decisions of these stakeholders during the process will make or break energy neutral ambitions. An extensive form of game theory model gave insight in the behavioral differences of stakeholders regarding energy neutral ambitions and the effects of the changing legislation. The results show that new legislation regarding spatial planning slightly influences the behavior of stakeholders. An active behavior of the municipality will still result in the best outcome. Nevertheless, the municipality becomes more powerful when acting passively and can make the use of planning tools to provide governance towards energy neutral urban redevelopment. Moreover, organizational support, recognizing the necessity for energy neutrality, keeping focused and collaboration among stakeholders are crucial elements to achieve the objective of an energy neutral urban (re)development.
Abstract: This study presents a mathematical modeling approach to the planning of HIV therapies on an individual basis. The model replicates clinical data from typical-progressors to AIDS for all stages of the disease with good agreement. Clinical data from rapid-progressors and long-term non-progressors is also matched by estimation of immune system parameters only. The ability of the model to reproduce these phenomena validates the formulation, a fact which is exploited in the investigation of effective therapies. The therapy investigation suggests that, unlike continuous therapy, structured treatment interruptions (STIs) are able to control the increase in both the drug-sensitive and drug-resistant virus population and, hence, prevent the ultimate progression from HIV to AIDS. The optimization results further suggest that even patients characterised by the same progression type can respond very differently to the same treatment and that the latter should be designed on a case-by-case basis. Such a methodology is presented here.