Abstract: The one-class support vector machine “support vector
data description” (SVDD) is an ideal approach for anomaly or outlier
detection. However, for the applicability of SVDD in real-world
applications, the ease of use is crucial. The results of SVDD are
massively determined by the choice of the regularisation parameter C
and the kernel parameter of the widely used RBF kernel. While for
two-class SVMs the parameters can be tuned using cross-validation
based on the confusion matrix, for a one-class SVM this is not
possible, because only true positives and false negatives can occur
during training. This paper proposes an approach to find the optimal
set of parameters for SVDD solely based on a training set from
one class and without any user parameterisation. Results on artificial
and real data sets are presented, underpinning the usefulness of the
approach.
Abstract: Recently, X. Ge and J. Qian investigated some relations between higher mathematics scores and calculus scores (resp. linear algebra scores, probability statistics scores) for Chinese university students. Based on rough-set theory, they established an information system S = (U,CuD,V, f). In this information system, higher mathematics score was taken as a decision attribute and calculus score, linear algebra score, probability statistics score were taken as condition attributes. They investigated importance of each condition attribute with respective to decision attribute and strength of each condition attribute supporting decision attribute. In this paper, we give further investigations for this issue. Based on the above information system S = (U, CU D, V, f), we analyze the decision rules between condition and decision granules. For each x E U, we obtain support (resp. strength, certainty factor, coverage factor) of the decision rule C —>x D, where C —>x D is the decision rule induced by x in S = (U, CU D, V, f). Results of this paper gives new analysis of on higher mathematics scores for Chinese university students, which can further lead Chinese university students to raise higher mathematics scores in Chinese graduate student entrance examination.
Abstract: Due to today-s fierce competition, companies have to
be proactive creators of the future by effectively developing
innovations. Especially radical innovations allow high profit margins
– but they also entail high risks. One possibility to realize radical
innovations and reduce the risk of failure is cross-industry innovation
(CII). CII brings together problems and solution ideas from different
industries. However, there is a lack of systematic ways towards CII.
Bridging this gap, the present paper provides a systematic approach
towards planned CII. Starting with the analysis of potentials, the
definition of promising search strategies is crucial. Subsequently,
identified solution ideas need to be assessed. For the most promising
ones, the adaption process has to be systematically planned –
regarding the risk affinity of a company. The introduced method is
explained on a project from the furniture industry.
Abstract: Small cracks or chips of a product appear very
frequently in the course of continuous production of an automatic
press process system. These phenomena become the cause of not only
defective product but also damage of a press mold. In order to solve
this problem AE system was introduced. AE system was expected to
be very effective to real time detection of the defective product and to
prevention of the damage of the press molds.
In this study, for pick and analysis of AE signals generated from the
press process, AE sensors/pre-amplifier/analysis and processing board
were used as frequently found in the other similar cases. For analysis
and processing the AE signals picked in real time from the good or bad
products, specialized software called cdm8 was used. As a result of
this work it was conformed that intensity and shape of the various AE
signals differ depending on the weight and thickness of metal sheet
and process type.
Abstract: Much research into handwritten Thai character
recognition have been proposed, such as comparing heads of
characters, Fuzzy logic and structure trees, etc. This paper presents a
system of handwritten Thai character recognition, which is based on
the Ant-minor algorithm (data mining based on Ant colony
optimization). Zoning is initially used to determine each character.
Then three distinct features (also called attributes) of each character
in each zone are extracted. The attributes are Head zone, End point,
and Feature code. All attributes are used for construct the
classification rules by an Ant-miner algorithm in order to classify
112 Thai characters. For this experiment, the Ant-miner algorithm is
adapted, with a small change to increase the recognition rate. The
result of this experiment is a 97% recognition rate of the training set
(11200 characters) and 82.7% recognition rate of unseen data test
(22400 characters).
Abstract: The authors report a case of swine urolithiasis caused
by improper administration of sulfamonomethoxine and which was
diagnosed by examination of urinary sediments and analyzing the
composition of the uroliths. The chemical composition of urinary
calculi obtained from affected pigs with urolithiasis was further
confimed as sulfamonomethoxine by fourier transform infrared
(FTIR). It is suggested that appearance of typical fanlike or wheat
bunchy crystals in urinary sediments under observation of lightmicroscope
and determination by FTIR for the crystals are helpful in
diagnosing sulfa calculi causced swine urolithiasis.
Abstract: In networks, mainly small and medium-sized businesses benefit from the knowledge, experiences and solutions offered by experts from industry and science or from the exchange with practitioners. Associations which focus, among other things, on networking, information and knowledge transfer and which are interested in supporting such cooperations are especially well suited to provide such networks and the appropriate web platforms. Using METORA as an example – a project developed and run by the Federal Association for Information Economy, Telecommunications and New Media e.V. (BITKOM) for the Federal Ministry of Economics and Technology (BMWi) – This paper will discuss how associations and other network organizations can achieve this task and what conditions they have to consider.
Abstract: Bovine viral diarrhea virus (BVDV) can cause lifelong
persistent infection. One reason for the phenomena is attributed to
BVDV infection to placenta tissue. However the mechanisms that
BVDV invades into placenta tissue remain unclear. To clarify the
molecular mechanisms, we investigated the possible means that
BVDV entered into bovine trophoblast cells (TPC). Yeast two-hybrid
system was used to identify proteins extracted from TPC, which
interact with BVDV envelope glycoprotein E2. A PGbkt7-E2 yeast
expression vector and TPC cDNA library were constructed. Through
two rounds of screening, three positive clones were identified.
Sequencing analysis indicated that all the three positive clones
encoded the same protein clathrin. Physical interaction between
clathrin and BVDV E2 protein was further confirmed by
coimmunoprecipitation experiments. This result suggested that the
clathrin might play a critical role in the process of BVDV entry into
placenta tissue and might be a novel antiviral target for preventing
BVDV infection.
Abstract: The new framework the Higher Education is
immersed in involves a complete change in the way lecturers must
teach and students must learn. Whereas the lecturer was the main
character in traditional education, the essential goal now is to
increase the students' participation in the process. Thus, one of the
main tasks of lecturers in this new context is to design activities of
different nature in order to encourage such participation. Seminars
are one of the activities included in this environment. They are active
sessions that enable going in depth into specific topics as support of
other activities. They are characterized by some features such as
favoring interaction between students and lecturers or improving
their communication skills. Hence, planning and organizing strategic
seminars is indeed a great challenge for lecturers with the aim of
acquiring knowledge and abilities. This paper proposes a method
using Artificial Intelligence techniques to obtain student profiles
from their marks and preferences. The goal of building such profiles
is twofold. First, it facilitates the task of splitting the students into
different groups, each group with similar preferences and learning
difficulties. Second, it makes it easy to select adequate topics to be a
candidate for the seminars. The results obtained can be either a
guarantee of what the lecturers could observe during the development
of the course or a clue to reconsider new methodological strategies in
certain topics.
Abstract: The objective of this paper was to designing a
ventilation system to enhance the performance of roof solar collector
(RSC) for reducing heat accumulation inside the house. The RSC has
1.8 m2 surface area made of CPAC monier roof tiles on the upper part
and gypsum board on the lower part. The space between CPAC
monier and gypsum board was fixed at 14 cm.
Ventilation system of modified roof solar collector (modified
RSC) consists of 9 tubes of 0.15m diameter and installed in the
lower part of RSC. Experimental result showed that the temperature
of the room, and attic temperature. The average temperature
reduction of room of house used modified RSC is about 2oC. and the
percentage of room temperature reduction varied between 0 to 10%.
Therefore, modified RSC is an interesting option in the sense that it
promotes solar energy and conserve energy.
Abstract: Road transportation system is the most important
method of transporting the goods. Considering the most suitable
geographical situation of Iran to transport the goods between Europe
and Asia and placement of this country in direction of international
corridors (east- west) , (north-south) and Asian land transport to
infrastructure development “A.L.T.I.D" and Transport corridor
Europe - Caucasus - Asia “T.R.A.C.E.C.A", noticing the security of
road transportation system in this country is so important. In this
paper the main factors of accidents on the roads of Iran are
categorized regarding the rate of accidents occurred. Then apart from
studying the main reasons of accidents of every category, the main
factors of these events are studied and its strategies in Iran are
introduced.
Abstract: Every day human life experiences new equipments
more automatic and with more abilities. So the need for faster
processors doesn-t seem to finish. Despite new architectures and
higher frequencies, a single processor is not adequate for many
applications. Parallel processing and networks are previous solutions
for this problem. The new solution to put a network of resources on a
chip is called NOC (network on a chip). The more usual topology for
NOC is mesh topology. There are several routing algorithms suitable
for this topology such as XY, fully adaptive, etc. In this paper we
have suggested a new algorithm named Intermittent X, Y (IX/Y). We
have developed the new algorithm in simulation environment to
compare delay and power consumption with elders' algorithms.
Abstract: Long term rainfall analysis and prediction is a
challenging task especially in the modern world where the impact of
global warming is creating complications in environmental issues.
These factors which are data intensive require high performance
computational modeling for accurate prediction. This research paper
describes a prototype which is designed and developed on grid
environment using a number of coupled software infrastructural
building blocks. This grid enabled system provides the demanding
computational power, efficiency, resources, user-friendly interface,
secured job submission and high throughput. The results obtained
using sequential execution and grid enabled execution shows that
computational performance has enhanced among 36% to 75%, for
decade of climate parameters. Large variation in performance can be
attributed to varying degree of computational resources available for
job execution.
Grid Computing enables the dynamic runtime selection, sharing
and aggregation of distributed and autonomous resources which plays
an important role not only in business, but also in scientific
implications and social surroundings. This research paper attempts to
explore the grid enabled computing capabilities on weather indices
from HOAPS data for climate impact modeling and change
detection.
Abstract: this paper presents a novel neural network controller
with composite adaptation low to improve the trajectory tracking
problems of biped robots comparing with classical controller. The
biped model has 5_link and 6 degrees of freedom and actuated by
Plated Pneumatic Artificial Muscle, which have a very high power to
weight ratio and it has large stoke compared to similar actuators. The
proposed controller employ a stable neural network in to approximate
unknown nonlinear functions in the robot dynamics, thereby
overcoming some limitation of conventional controllers such as PD
or adaptive controllers and guarantee good performance. This NN
controller significantly improve the accuracy requirements by
retraining the basic PD/PID loop, but adding an inner adaptive loop
that allows the controller to learn unknown parameters such as
friction coefficient, therefore improving tracking accuracy.
Simulation results plus graphical simulation in virtual reality show
that NN controller tracking performance is considerably better than
PD controller tracking performance.
Abstract: An end-member selection method for spectral unmixing that is based on Particle Swarm Optimization (PSO) is developed in this paper. The algorithm uses the K-means clustering algorithm and a method of dynamic selection of end-members subsets to find the appropriate set of end-members for a given set of multispectral images. The proposed algorithm has been successfully applied to test image sets from various platforms such as LANDSAT 5 MSS and NOAA's AVHRR. The experimental results of the proposed algorithm are encouraging. The influence of different values of the algorithm control parameters on performance is studied. Furthermore, the performance of different versions of PSO is also investigated.
Abstract: Enzymatic saccharification of biomass for reducing
sugar production is one of the crucial processes in biofuel production
through biochemical conversion. In this study, enzymatic
saccharification of dilute potassium hydroxide (KOH) pre-treated
Tetraselmis suecica biomass was carried out by using cellulase
enzyme obtained from Trichoderma longibrachiatum. Initially, the
pre-treatment conditions were optimised by changing alkali reagent
concentration, retention time for reaction, and temperature. The T.
suecica biomass after pre-treatment was also characterized using
Fourier Transform Infrared Spectra and Scanning Electron
Microscope. These analyses revealed that the functional group such
as acetyl and hydroxyl groups, structure and surface of T. suecica
biomass were changed through pre-treatment, which is favourable for
enzymatic saccharification process. Comparison of enzymatic
saccharification of untreated and pre-treated microalgal biomass
indicated that higher level of reducing sugar can be obtained from
pre-treated T. suecica. Enzymatic saccharification of pre-treated T.
suecica biomass was optimised by changing temperature, pH, and
enzyme concentration to solid ratio ([E]/[S]). Highest conversion of
carbohydrate into reducing sugar of 95% amounted to reducing sugar
yield of 20 (wt%) from pre-treated T. suecica was obtained from
saccharification, at temperature: 40°C, pH: 4.5 and [E]/[S] of 0.1
after 72 h of incubation. Hydrolysate obtained from enzymatic
saccharification of pretreated T. suecica biomass was further
fermented into biobutanol using Clostridium saccharoperbutyliticum
as biocatalyst. The results from this study demonstrate a positive
prospect of application of dilute alkaline pre-treatment to enhance
enzymatic saccharification and biobutanol production from
microalgal biomass.
Abstract: The Mobile Ad-hoc Network (MANET) is a collection of self-configuring and rapidly deployed mobile nodes (routers) without any central infrastructure. Routing is one of the potential issues. Many routing protocols are reported but it is difficult to decide which one is best in all scenarios. In this paper on demand routing protocols DSR and DYMO based on IEEE 802.11 DCF MAC protocol are examined and characteristic summary of these routing protocols is presented. Their performance is analyzed and compared on performance measuring metrics throughput, dropped packets due to non availability of routes, duplicate RREQ generated for route discovery and normalized routing load by varying CBR data traffic load using QualNet 5.0.2 network simulator.
Abstract: The objective of this research was to study factors,
which were affected on surface roughness in high speed milling of
hardened tool steel. Material used in the experiment was tool steel JIS
SKD 61 that hardened on 60 ±2 HRC. Full factorial experimental
design was conducted on 3 factors and 3 levels (3
3
designs) with 2
replications. Factors were consisted of cutting speed, feed rate, and
depth of cut. The results showed that influenced factor affected to
surface roughness was cutting speed, feed rate and depth of cut which
showed statistical significant. Higher cutting speed would cause on
better surface quality. On the other hand, higher feed rate would cause
on poorer surface quality. Interaction of factor was found that cutting
speed and depth of cut were significantly to surface quality. The
interaction of high cutting speed associated with low depth of cut
affected to better surface quality than low cutting speed and high depth
of cut.
Abstract: In the automotive industry test drives are being conducted
during the development of new vehicle models or as a part of
quality assurance of series-production vehicles. The communication
on the in-vehicle network, data from external sensors, or internal
data from the electronic control units is recorded by automotive
data loggers during the test drives. The recordings are used for fault
analysis. Since the resulting data volume is tremendous, manually
analysing each recording in great detail is not feasible.
This paper proposes to use machine learning to support domainexperts
by preventing them from contemplating irrelevant data and
rather pointing them to the relevant parts in the recordings. The
underlying idea is to learn the normal behaviour from available
recordings, i.e. a training set, and then to autonomously detect
unexpected deviations and report them as anomalies.
The one-class support vector machine “support vector data description”
is utilised to calculate distances of feature vectors. SVDDSUBSEQ
is proposed as a novel approach, allowing to classify subsequences
in multivariate time series data. The approach allows to
detect unexpected faults without modelling effort as is shown with
experimental results on recordings from test drives.
Abstract: The aim of this study is to point out whether personalization of mathematical word problems could affect student achievement or not. The research was applied on two-grades students at spring semester 2008-2009. Before the treatment, students personal data were taken and given to the computer. During the treatment, paper-based personalized problems and paper-based non personalized problems were prepared by computer as the same problems and then these problems were given to students. At the end of the treatment, students- opinion was taken. As a result of this research, it was found out that there were no significant differences between learners through personalized or non-personalized materials, and also there were no significant differences between gender through personalized and non-personalized problems. However, opinion of students was highly positive through the personalized problems.