Abstract: The myoelectric signal (MES) is one of the Biosignals
utilized in helping humans to control equipments. Recent approaches
in MES classification to control prosthetic devices employing pattern
recognition techniques revealed two problems, first, the classification
performance of the system starts degrading when the number of
motion classes to be classified increases, second, in order to solve the
first problem, additional complicated methods were utilized which
increase the computational cost of a multifunction myoelectric
control system. In an effort to solve these problems and to achieve a
feasible design for real time implementation with high overall
accuracy, this paper presents a new method for feature extraction in
MES recognition systems. The method works by extracting features
using Wavelet Packet Transform (WPT) applied on the MES from
multiple channels, and then employs Fuzzy c-means (FCM)
algorithm to generate a measure that judges on features suitability for
classification. Finally, Principle Component Analysis (PCA) is
utilized to reduce the size of the data before computing the
classification accuracy with a multilayer perceptron neural network.
The proposed system produces powerful classification results (99%
accuracy) by using only a small portion of the original feature set.
Abstract: The authors of this work indicate by means of a concrete example that it is possible to apply efficaciously the method of multiple criteria programming in dealing with the problem of determining the optimal production plan for a certain period of time. The work presents: (1) the selection of optimization criteria, (2) the setting of the problem of determining an optimal production plan, (3) the setting of the model of multiple criteria programming in finding a solution to a given problem, (4) the revised surrogate trade-off method, (5) generalized multicriteria model for solving production planning problem and problem of choosing technological variants in the metal manufacturing industry. In the final part of this work the authors reflect on the application of the method of multiple criteria programming while determining the optimal production plan in manufacturing enterprises.
Abstract: In this paper, a data mining model to SMEs for detecting financial and operational risk indicators by data mining is presenting. The identification of the risk factors by clarifying the relationship between the variables defines the discovery of knowledge from the financial and operational variables. Automatic and estimation oriented information discovery process coincides the definition of data mining. During the formation of model; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the data and the identification of effect level of every factor. In addition, this paper is based on a project which was funded by The Scientific and Technological Research Council of Turkey (TUBITAK).
Abstract: In order to avoid the potentially devastating
consequences of global warming and climate change, the carbon
dioxide “CO2" emissions caused due to anthropogenic activities must
be reduced considerably. This paper presents the first study
examining the feasibility of carbon sequestration in construction and
demolition “C&D" waste. Experiments were carried out in a self
fabricated Batch Reactor at 40ºC, relative humidity of 50-70%, and
flow rate of CO2 at 10L/min for 1 hour for water-to-solids ratio of 0.2
to 1.2. The effect of surface area was found by comparing the
theoretical extent of carbonation of two different sieve sizes (0.3mm
and 2.36mm) of C&D waste. A 38.44% of the theoretical extent of
carbonation equating to 4% CO2 sequestration extent was obtained
for C&D waste sample for 0.3mm sieve size. Qualitative,
quantitative and morphological analyses were done to validate
carbonate formation using X-ray diffraction “X.R.D.," thermal
gravimetric analysis “T.G.A., “X-Ray Fluorescence Spectroscopy
“X.R.F.," and scanning electron microscopy “S.E.M".
Abstract: To calculate the temperature distribution of the slab in
a hot rolled reheating furnace a mathematical model has been
developed by considering the thermal radiation in the furnace and
transient conduction in the slab. The furnace is modeled as radiating
medium with spatially varying temperature. Radiative heat flux within
the furnace including the effect of furnace walls, combustion gases,
skid beams and buttons is calculated using the FVM and is applied as
the boundary condition of the transient conduction equation of the
slab. After determining the slab emissivity by comparison between
simulation and experimental work, variation of heating characteristics
in the slab is investigated in the case of changing furnace temperature
with various time and the slab residence time is optimized with this
evaluation.
Abstract: We propose a low-cost uniform analysis framework
allowing comparison of the strengths and weaknesses of the
bicycling experience within and between cities. A primary
component is an expedient, one-page mobility survey from which
mode share is calculated. The bicycle mode share of many cities
remains unknown, creating a serious barrier for both scientists and
policy makers aiming to understand and increase rates of bicycling.
Because of its low cost and expedience, this framework could be
replicated widely, uniformly filling the data gap. The framework has
been applied to 13 Central European cities with success. Data is
collected on multiple modes with specific questions regarding both
behavior and quality of travel experience. Individual preferences are
also collected, examining the conditions under which respondents
would change behavior to adopt more sustainable modes (bicycling
or public transportation). A broad analysis opportunity results,
intended to inform policy choices.
Abstract: The aim of this paper is to experimentally discover the workability coefficient of the Inconel 718 material by using a slide turning machining. Two different types of cutting inserts, one made of carbide and the other one made of ceramic, are being used. The purpose is to compare measured results and recommend the appropriate materials and cutting parameters for a machining of the Inconel 718. Furthermore, the durability of inserts with the chosen wear criterion is being compared for different cutting speeds. Machinability of these materials is a crucial characteristic as it allows us to shorten the technological cycle time and increase the machining productivity. And this is of great importance from an economic point of view.
Abstract: Determining reasonable fees is the main objective of designing the cost estimation and payment systems for consultant contracts. However, project clients utilize different cost estimation and payment systems because of their varying views on the reasonableness of consultant fees. This study reviews the cost estimation and payment systems of consultant contracts for five countries, including the US (Washington State Department of Transportation), Japan (Ministry of Land, Infrastructure, Transport and Tourism), China (Engineering Design Charging Standard) and UK (Her Majesty's Treasure). Specifically, this work investigates the budgeting process, contractor selection method, contractual price negotiation process, cost review, and cost-control concept of the systems used in these countries. The main finding indicates that that project client-s view on whether the fee is high will affect the way he controls it. In the US, the fee is commonly considered to be high. As a result, stringent auditing system (low flexibility given to the consultant) is then applied. In the UK, the fee is viewed to be low by comparing it to the total life-cycle project cost. Thus, a system that has high flexibility in budgeting and cost reviewing is given to the consultant. In terms of the flexibility allowed for the consultant, the systems applied in Japan and China fall between those of the US and UK. Both the US and UK systems are helpful in determining a reasonable fee. However, in the US system, rigid auditing standards must be established and additional cost-audit manpower is required. In the UK system, sufficient historical cost data should be needed to evaluate the reasonableness of the consultant-s proposed fee
Abstract: The purpose of this research aims to discover the
knowledge for analysis student motivation behavior on e-Learning
based on Data Mining Techniques, in case of the Information
Technology for Communication and Learning Course at Suan
Sunandha Rajabhat University. The data mining techniques was
applied in this research including association rules, classification
techniques. The results showed that using data mining technique can
indicate the important variables that influence the student motivation
behavior on e-Learning.
Abstract: This paper presents performance analysis of the
Evolutionary Programming-Artificial Neural Network (EPANN)
based technique to optimize the architecture and training parameters
of a one-hidden layer feedforward ANN model for the prediction of
energy output from a grid connected photovoltaic system. The ANN
utilizes solar radiation and ambient temperature as its inputs while the
output is the total watt-hour energy produced from the grid-connected
PV system. EP is used to optimize the regression performance of the
ANN model by determining the optimum values for the number of
nodes in the hidden layer as well as the optimal momentum rate and
learning rate for the training. The EPANN model is tested using two
types of transfer function for the hidden layer, namely the tangent
sigmoid and logarithmic sigmoid. The best transfer function, neural
topology and learning parameters were selected based on the highest
regression performance obtained during the ANN training and testing
process. It is observed that the best transfer function configuration for
the prediction model is [logarithmic sigmoid, purely linear].
Abstract: Over the past several years, there has been a
considerable amount of research within the field of Quality of
Service (QoS) support for distributed multimedia systems. One of the
key issues in providing end-to-end QoS guarantees in packet
networks is determining a feasible path that satisfies a number of
QoS constraints. The problem of finding a feasible path is NPComplete
if number of constraints is more than two and cannot be
exactly solved in polynomial time. We proposed Feasible Path
Selection Algorithm (FPSA) that addresses issues with pertain to
finding a feasible path subject to delay and cost constraints and it
offers higher success rate in finding feasible paths.
Abstract: Data clustering is an important data exploration
technique with many applications in data mining. The k-means
algorithm is well known for its efficiency in clustering large data
sets. However, this algorithm is suitable for spherical shaped clusters
of similar sizes and densities. The quality of the resulting clusters
decreases when the data set contains spherical shaped with large
variance in sizes. In this paper, we introduce a competent procedure
to overcome this problem. The proposed method is based on shifting
the center of the large cluster toward the small cluster, and recomputing
the membership of small cluster points, the experimental
results reveal that the proposed algorithm produces satisfactory
results.
Abstract: Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.
Abstract: The increments of aromatic structures are widely used to monitor the degree of humification. Compost derived from mix manures mixed with agricultural wastes was studied. The compost collected at day 0, 7, 14, 21, 28, 35, 49, 77, 91, 105, and 119 was divided into 3 stages, initial stage at day 0, thermophilic stage during day 1-48, and mature stage during day 49-119. The change of highest absorptions at wavelength range between 210-235 nm during day 0- 49 implied that small molecules such as nitrates and carboxylic occurred faster than the aromatic molecules that were found at wavelength around 280 nm. The ratio of electron-transfer band at wavelength 253 nm by the benzonoid band at wavelength 230 nm (E253/E230) also gradually increased during the fermenting period indicating the presence of O-containing functional groups. This was in agreement with the shift change from aliphatic to aromatic structures as shown by the relationship with C/N and H/C ratios (r = - 0.631 and -0.717, p< 0.05) since both were decreasing. Although the amounts of humic acid (HA) were not different much during the humification process, the UV spectral deconvolution showed better qualitative characteristics to help in determining the compost quality. From this study, the compost should be used at day 49 and should not be kept longer than 3 months otherwise the quality of HA would decline regardless of the amounts of HA that might be rising. This implied that other processes, such as mineralization had an influence on the humification process changing HA-s structure and its qualities.
Abstract: In recent decades, the lean methodology, and the
development of its principles and concepts have widely been applied
in supply chain management. One of the most important strategies of
being lean is having efficient inventory within the chain. On the other
hand, managing inventory efficiently requires appropriate
management of safety stock in order to protect against increasing
stretch in the breaking points of the supply chain, which in turn can
result in possible reduction of inventory. This paper applies a safety
stock cost minimization model in a manufacturing company. The
model results in optimum levels and locations of safety stock within
the company-s supply chain in order to minimize total logistics costs.
Abstract: Searching similar documents and document
management subjects have important place in text mining. One of the
most important parts of similar document research studies is the
process of classifying or clustering the documents. In this study, a
similar document search approach that includes discussion of out the
case of belonging to multiple categories (multiple categories
problem) has been carried. The proposed method that based on Fuzzy
Similarity Classification (FSC) has been compared with Rocchio
algorithm and naive Bayes method which are widely used in text
mining. Empirical results show that the proposed method is quite
successful and can be applied effectively. For the second stage,
multiple categories vector method based on information of categories
regarding to frequency of being seen together has been used.
Empirical results show that achievement is increased almost two
times, when proposed method is compared with classical approach.
Abstract: Data mining, which is the exploration of
knowledge from the large set of data, generated as a result of
the various data processing activities. Frequent Pattern Mining
is a very important task in data mining. The previous
approaches applied to generate frequent set generally adopt
candidate generation and pruning techniques for the
satisfaction of the desired objective. This paper shows how
the different approaches achieve the objective of frequent
mining along with the complexities required to perform the
job. This paper will also look for hardware approach of cache
coherence to improve efficiency of the above process. The
process of data mining is helpful in generation of support
systems that can help in Management, Bioinformatics,
Biotechnology, Medical Science, Statistics, Mathematics,
Banking, Networking and other Computer related
applications. This paper proposes the use of both upward and
downward closure property for the extraction of frequent item
sets which reduces the total number of scans required for the
generation of Candidate Sets.
Abstract: Microarrays technique allows the simultaneous measurements of the expression levels of thousands of mRNAs. By mining this data one can identify the dynamics of the gene expression time series. By recourse of principal component analysis, we uncover the circadian rhythmic patterns underlying the gene expression profiles from Cyanobacterium Synechocystis. We applied PCA to reduce the dimensionality of the data set. Examination of the components also provides insight into the underlying factors measured in the experiments. Our results suggest that all rhythmic content of data can be reduced to three main components.
Abstract: In this research, we have developed a new efficient
heuristic algorithm for the dynamic facility layout problem with
budget constraint (DFLPB). This heuristic algorithm combines two
mathematical programming methods such as discrete event
simulation and linear integer programming (IP) to obtain a near
optimum solution. In the proposed algorithm, the non-linear model
of the DFLP has been changed to a pure integer programming (PIP)
model. Then, the optimal solution of the PIP model has been used in
a simulation model that has been designed in a similar manner as the
DFLP for determining the probability of assigning a facility to a
location. After a sufficient number of runs, the simulation model
obtains near optimum solutions. Finally, to verify the performance of
the algorithm, several test problems have been solved. The results
show that the proposed algorithm is more efficient in terms of speed
and accuracy than other heuristic algorithms presented in previous
works found in the literature.
Abstract: Clustering unstructured text documents is an
important issue in data mining community and has a number of
applications such as document archive filtering, document
organization and topic detection and subject tracing. In the real
world, some of the already clustered documents may not be of
importance while new documents of more significance may evolve.
Most of the work done so far in clustering unstructured text
documents overlooks this aspect of clustering. This paper, addresses
this issue by using the Fading Function. The unstructured text
documents are clustered. And for each cluster a statistics structure
called Cluster Profile (CP) is implemented. The cluster profile
incorporates the Fading Function. This Fading Function keeps an
account of the time-dependent importance of the cluster. The work
proposes a novel algorithm Clustering n-ary Merge Algorithm
(CnMA) for unstructured text documents, that uses Cluster Profile
and Fading Function. Experimental results illustrating the
effectiveness of the proposed technique are also included.