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: 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: 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: In this paper, the details of an experimental method to measure the clamping force value at bolted connections due to application of wrenching torque to tighten the nut have been presented. A simplified bolted joint including a holed plate with a single bolt was considered to carry out the experiments. This method was designed based on Hooke-s law by measuring compressive axial strain of a steel bush placed between the nut and the plate. In the experimental procedure, the values of clamping force were calculated for seven different levels of applied torque, and this process was repeated three times for each level of the torque. Moreover, the effect of lubrication of threads on the clamping value was studied using the same method. In both conditions (dry and lubricated threads), relation between the torque and the clamping force have been displayed in graphs.
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 performance of adaptive beamforming degrades
substantially in the presence of steering vector mismatches. This
degradation is especially severe in the near-field, for the
3-dimensional source location is more difficult to estimate than the
2-dimensional direction of arrival in far-field cases. As a solution, a
novel approach of near-field robust adaptive beamforming (RABF) is
proposed in this paper. It is a natural extension of the traditional
far-field RABF and belongs to the class of diagonal loading
approaches, with the loading level determined based on worst-case
performance optimization. However, different from the methods
solving the optimal loading by iteration, it suggests here a simple
closed-form solution after some approximations, and consequently,
the optimal weight vector can be expressed in a closed form. Besides
simplicity and low computational cost, the proposed approach reveals
how different factors affect the optimal loading as well as the weight
vector. Its excellent performance in the near-field is confirmed via a
number of numerical examples.
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: Concept maps can be generated manually or
automatically. It is important to recognize differences of the two
types of concept maps. The automatically generated concept maps
are dynamic, interactive, and full of associations between the terms
on the maps and the underlying documents. Through a specific
concept mapping system, Visual Concept Explorer (VCE), this paper
discusses how automatically generated concept maps are different
from manually generated concept maps and how different
applications and learning opportunities might be created with the
automatically generated concept maps. The paper presents several
examples of learning strategies that take advantages of the
automatically generated concept maps for concept learning and
exploration.
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: 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 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.
Abstract: Every organization is continually subject to new damages and threats which can be resulted from their operations or their goal accomplishment. Methods of providing the security of space and applied tools have been widely changed with increasing application and development of information technology (IT). From this viewpoint, information security management systems were evolved to construct and prevent reiterating the experienced methods. In general, the correct response in information security management systems requires correct decision making, which in turn requires the comprehensive effort of managers and everyone involved in each plan or decision making. Obviously, all aspects of work or decision are not defined in all decision making conditions; therefore, the possible or certain risks should be considered when making decisions. This is the subject of risk management and it can influence the decisions. Investigation of different approaches in the field of risk management demonstrates their progress from quantitative to qualitative methods with a process approach.
Abstract: This paper is to investigate the impplementation of security
mechanism in object oriented database system. Formal methods
plays an essential role in computer security due to its powerful expressiveness
and concise syntax and semantics. In this paper, both issues
of specification and implementation in database security environment
will be considered; and the database security is achieved through
the development of an efficient implementation of the specification
without compromising its originality and expressiveness.
Abstract: Knowledge sharing in general and the contextual
access to knowledge in particular, still represent a key challenge in
the knowledge management framework. Researchers on semantic
web and human machine interface study techniques to enhance this
access. For instance, in semantic web, the information retrieval is
based on domain ontology. In human machine interface, keeping
track of user's activity provides some elements of the context that can
guide the access to information. We suggest an approach based on
these two key guidelines, whilst avoiding some of their weaknesses.
The approach permits a representation of both the context and the
design rationale of a project for an efficient access to knowledge. In
fact, the method consists of an information retrieval environment
that, in the one hand, can infer knowledge, modeled as a semantic
network, and on the other hand, is based on the context and the
objectives of a specific activity (the design). The environment we
defined can also be used to gather similar project elements in order to
build classifications of tasks, problems, arguments, etc. produced in a
company. These classifications can show the evolution of design
strategies in the company.
Abstract: This purpose of this paper is to develop and validate a
model to accurately predict the cell temperature of a PV module that
adapts to various mounting configurations, mounting locations, and
climates while only requiring readily available data from the module
manufacturer. Results from this model are also compared to results
from published cell temperature models. The models were used to
predict real-time performance from a PV water pumping systems in
the desert of Medenine, south of Tunisia using 60-min intervals of
measured performance data during one complete year. Statistical
analysis of the predicted results and measured data highlight possible
sources of errors and the limitations and/or adequacy of existing
models, to describe the temperature and efficiency of PV-cells and
consequently, the accuracy of performance of PV water pumping
systems prediction models.
Abstract: This Classifying Bird Sounds (chip notes) project-s
purpose is to reduce the unwanted noise from recorded bird sound
chip notes, design a scheme to detect differences and similarities
between recorded chip notes, and classify bird sound chip notes. The
technologies of determining the similarities of sound waves have
been used in communication, sound engineering and wireless sound
applications for many years. Our research is focused on the similarity
of chip notes, which are the sounds from different birds. The program
we use is generated by Microsoft Cµ.