Abstract: Text categorization is the problem of classifying text
documents into a set of predefined classes. After a preprocessing
step, the documents are typically represented as large sparse vectors.
When training classifiers on large collections of documents, both the
time and memory restrictions can be quite prohibitive. This justifies
the application of feature selection methods to reduce the
dimensionality of the document-representation vector. In this paper,
three feature selection methods are evaluated: Random Selection,
Information Gain (IG) and Support Vector Machine feature selection
(called SVM_FS). We show that the best results were obtained with
SVM_FS method for a relatively small dimension of the feature
vector. Also we present a novel method to better correlate SVM
kernel-s parameters (Polynomial or Gaussian kernel).
Abstract: The present study aimed to investigate whether
chlorophyll meter readings (SPAD) can be used as criterion of singleplant
selection in maize breeding. Experimentation was performed at
the ultra-low density of 0.74 plants/m2 in order the potential yield per
plant to be fully expressed. R-31 honeycomb experiments were
conducted in three different areas in Greece (Thessaloniki, Giannitsa
and Florina) using 30 inbred lines at well-watered and water-stressed
conditions during the 2012 growing season. The chlorophyll meter
readings had higher rates at dry conditions, except location of
Giannitsa where differences were not significant. Genotypes of
highest chlorophyll meter readings were consistent across areas,
emphasizing on the character’s stability. A positive correlation
between the chlorophyll meter readings and grain yield was
strengthening over time and culminated at the physiological maturity
stage. There was a clear sign that the chlorophyll meter readings has
the potential to be used for the selection of stress-adaptive genotypes
and may permit modern maize to be grown at wider range of
environments addressing the climate change scenarios.
Abstract: Surface roughness (Ra) is one of the most important requirements in machining process. In order to obtain better surface roughness, the proper setting of cutting parameters is crucial before the process take place. This research presents the development of mathematical model for surface roughness prediction before milling process in order to evaluate the fitness of machining parameters; spindle speed, feed rate and depth of cut. 84 samples were run in this study by using FANUC CNC Milling α-Τ14ιE. Those samples were randomly divided into two data sets- the training sets (m=60) and testing sets(m=24). ANOVA analysis showed that at least one of the population regression coefficients was not zero. Multiple Regression Method was used to determine the correlation between a criterion variable and a combination of predictor variables. It was established that the surface roughness is most influenced by the feed rate. By using Multiple Regression Method equation, the average percentage deviation of the testing set was 9.8% and 9.7% for training data set. This showed that the statistical model could predict the surface roughness with about 90.2% accuracy of the testing data set and 90.3% accuracy of the training data set.
Abstract: On a such wide-area environment as a Grid, data
placement is an important aspect of distributed database systems. In
this paper, we address the problem of initial placement of database
no-replicated fragments in Grid architecture. We propose a graph
based approach that considers resource restrictions. The goal is to
optimize the use of computing, storage and communication
resources. The proposed approach is developed in two phases: in the
first phase, we perform fragment grouping using knowledge about
fragments dependency and, in the second phase, we determine an
efficient placement of the fragment groups on the Grid. We also
show, via experimental analysis that our approach gives solutions
that are close to being optimal for different databases and Grid
configurations.
Abstract: Mechanical buckling analysis of rectangular plates
with central circular cutout is performed in this paper. The finiteelement
method is used to study the effects of plate-support
conditions, aspect ratio, and hole size on the mechanical buckling
strength of the perforated plates subjected to linearly varying loading.
Results show that increasing the hole size does not necessarily reduce
the mechanical buckling strength of the perforated plates. It is also
concluded that the clamped boundary condition increases the
mechanical buckling strength of the perforated plates more than the
simply-supported boundary condition and the free boundary
conditions enhance the mechanical buckling strength of the
perforated plates more effectively than the fixed boundary conditions.
Furthermore, for the bending cases, the critical buckling load of
perforated plates with free edges is less than perforated plates with
fixed edges.
Abstract: Key management represents a major and the most
sensitive part of cryptographic systems. It includes key generation,
key distribution, key storage, and key deletion. It is also considered
the hardest part of cryptography. Designing secure cryptographic
algorithms is hard, and keeping the keys secret is much harder.
Cryptanalysts usually attack both symmetric and public key
cryptosystems through their key management. We introduce a
protocol to exchange cipher keys over insecure communication
channel. This protocol is based on public key cryptosystem,
especially elliptic curve cryptosystem. Meanwhile, it tests the cipher
keys and selects only the good keys and rejects the weak one.
Abstract: Artificial Neural Network (ANN)s are best suited for
prediction and optimization problems. Trained ANNs have found
wide spread acceptance in several antenna design systems. Four
parameters namely antenna radiation resistance, loss resistance, efficiency,
and inductance can be used to design an antenna layout though
there are several other parameters available. An ANN can be trained
to provide the best and worst case precisions of an antenna design
problem defined by these four parameters. This work describes the
use of an ANN to generate the four mentioned parameters for a loop
antenna for the specified frequency range. It also provides insights
to the prediction of best and worst-case design problems observed
in applications and thereby formulate a model for physical layout
design of a loop antenna.
Abstract: A novel low-cost impedance control structure is
proposed for monitoring the contact force between end-effector and
environment without installing an expensive force/torque sensor.
Theoretically, the end-effector contact force can be estimated from the
superposition of each joint control torque. There have a nonlinear
matrix mapping function between each joint motor control input and
end-effector actuating force/torques vector. This new force control
structure can be implemented based on this estimated mapping matrix.
First, the robot end-effector is manipulated to specified positions, then
the force controller is actuated based on the hall sensor current
feedback of each joint motor. The model-free fuzzy sliding mode
control (FSMC) strategy is employed to design the position and force
controllers, respectively. All the hardware circuits and software
control programs are designed on an Altera Nios II embedded
development kit to constitute an embedded system structure for a
retrofitted Mitsubishi 5 DOF robot. Experimental results show that PI
and FSMC force control algorithms can achieve reasonable contact
force monitoring objective based on this hardware control structure.
Abstract: When it comes to last, it is regarded as the critical
foundation of shoe design and development. A computer aided
methodology for various last form designs is proposed in this study.
The reverse engineering is mainly applied to the process of scanning
for the last form. Then with the minimum energy for revision of
surface continuity, the surface reconstruction of last is rebuilt by the
feature curves of the scanned last. When the surface reconstruction of
last is completed, the weighted arithmetic mean method is applied to
the computation on the shape morphing for the control mesh of last,
thus 3D last form of different sizes is generated from its original form
feature with functions remained. In the end, the result of this study is
applied to an application for 3D last reconstruction system. The
practicability of the proposed methodology is verified through later
case studies.
Abstract: Digital broadcasting has been an area of active
research, development, innovation and business models development
in recent years. This paper presents a survey on the characteristics of
the digital terrestrial television broadcasting (DTTB) standards, and
implementation status of DTTB worldwide showing the standards
adopted. It is clear that only the developed countries and some in the
developing ones shall be able to beat the ITU set analogue to digital
broadcasting migration deadline because of the challenges that these
countries faces in digitizing their terrestrial broadcasting. The
challenges to keep on track the DTTB migration plan are also
discussed in this paper. They include financial, technology gap,
policies alignment with DTTB technology, etc. The reported
performance comparisons for the different standards are also
presented. The interesting part is that the results for many
comparative studies depends to a large extent on the objective behind
such studies, hence counter claims are common.
Abstract: This paper presents a novel method for remaining
useful life prediction using the Elliptical Basis Function (EBF)
network and a Markov chain. The EBF structure is trained by a
modified Expectation-Maximization (EM) algorithm in order to take
into account the missing covariate set. No explicit extrapolation is
needed for internal covariates while a Markov chain is constructed to
represent the evolution of external covariates in the study. The
estimated external and the unknown internal covariates constitute an
incomplete covariate set which are then used and analyzed by the EBF
network to provide survival information of the asset. It is shown in the
case study that the method slightly underestimates the remaining
useful life of an asset which is a desirable result for early maintenance
decision and resource planning.
Abstract: Attempts were made to identify anuran glial cells. They were found as nervous tissue resident. Having stage dependent morphotype changes, whereby, appeared as an ovoid to oval in resting state and amoeboid mrophotypes in activated state, stained fairly with methylene blue and take up Pelikane blue 10% aqueous solution, as well as having the ability to phagocytize heat killed Staphylococcus aureus. They were delineated from the migrating peripheral monocytes by morphotypic and morphometeric differences. Such criteria were consistence with glial cells. Thus, the anuran glial cells are being identified in the frog Rana ridibunda Pallas 1771 and this animal can be of use as a simple model for the immunobiology of glial cells.
Abstract: A Negotiation Support is required on a value-based decision to enable each stakeholder to evaluate and rank the solution alternatives before engaging into negotiation with the other stakeholders. This study demonstrates a process of negotiation support model for selection of a building system from value-based design perspective. The perspective is based on comparison of function and cost of a building system. Multi criteria decision techniques were applied to determine the relative value of the alternative solutions for performing the function. A satisfying option game theory are applied to the criteria of value-based decision which are LCC (life cycle cost) and function based FAST. The results demonstrate a negotiation process to select priorities of a building system. The support model can be extended to an automated negotiation by combining value based decision method, group decision and negotiation support.
Abstract: We consider the methods of construction simple
polygons for a set S of n points and applying them for searching the
minimal area polygon. In this paper we propose the approximate
algorithm, which generates the simple polygonalizations of a fixed
set of points and finds the minimal area polygon, in O (n3) time and
using O(n2) memory.
Abstract: This study shows the effect of carbon towards
molybdenum carbide alloy when exposed to Microwave. This
technique is also known as Microwave Induced Alloying (MIA) for
the preparation of molybdenum carbide. In this study ammonium
heptamolybdate solution and carbon black powder were
heterogeneously mixed and exposed to microwave irradiation for 2
minutes. The effect on amount of carbon towards the produced alloy
on morphological and oxidation states changes during microwave is
presented. In this experiment, it is expected carbon act as a reducing
agent with the ratio 2:7 molybdenum to carbon as the optimum for
the production of molybdenum carbide alloy. All the morphological
transformations and changes in this experiment were followed and
characterized using X-Ray Diffraction and FESEM.
Abstract: Because of the low maintenance and robustness induction motors have many applications in the industries. The speed control of induction motor is more important to achieve maximum torque and efficiency. Various speed control techniques like, Direct Torque Control, Sensorless Vector Control and Field Oriented Control are discussed in this paper. Soft computing technique – Fuzzy logic is applied in this paper for the speed control of induction motor to achieve maximum torque with minimum loss. The fuzzy logic controller is implemented using the Field Oriented Control technique as it provides better control of motor torque with high dynamic performance. The motor model is designed and membership functions are chosen according to the parameters of the motor model. The simulated design is tested using various tool boxes in MATLAB. The result concludes that the efficiency and reliability of the proposed speed controller is good.
Abstract: Copolymerization of ethylene with 1-hexene was
carried out using two ansa-fluorenyl titanium derivative complexes.
The substituent effect on the catalytic activity, monomer reactivity
ratio and polymer property was investigated. It was found that the
presence of t-Bu groups on fluorenyl ring exhibited remarkable
catalytic activity and produced polymer with high molecular weight.
However, these catalysts produce polymer with narrow molecular
weight distribution, indicating the characteristic of single-site
metallocene catalyst. Based on 13C NMR, we can observe that
monomer reactivity ratio was affected by catalyst structure. The rH
values of complex 2 were lower than that of complex 1 which might
be result from the higher steric hindrance leading to a reduction of 1-
hexene insertion step.
Abstract: Within the new world order, the term “crisis" is nowadays familiar to companies. Organizations are experiencing conditions which are surprising, uncertain, often adverse and usually unstable. The companies, who grasp the importance of transformation within the information age, have felt the need to develop modern methods to achieve the ability to thrive despite severe shocks. Through strategically managing human resource and developing appropriate elements of human resource system, companies can be assured for resolving the crisis. In this paper the role of HR system on resolving crisis has been evaluated. To help accomplish this, an insight on previous strategic HRM literature and an introduction to the elements and relationship within HR systems has been presented. It also reviews different attitude around resilience in literature. It continues by reviewing three elements central to developing an organization-s capacity for crisis resolving and it will demonstrate how designing proper elements of HR system can lead the organizations to possess the ability for passing through crisis. Finally it will evaluate an Iranian Insurance organization in case of one of the three central elements (specific cognitive ability) and observe how successful they were on developing an effective HR system to be ready for facing crisis.
Abstract: Bleeding in the digestive duct is an important diagnostic parameter for patients. Blood in the endoscopic image can be determined by investigating the color tone of blood due to the degree of oxygenation, under- or over- illumination, food debris and secretions, etc. However, we found that how to pre-process raw images obtained from the capsule detectors was very important. We applied various image process methods suitable for the capsule endoscopic image in order to remove noises and unbalanced sensitivities for the image pixels. The results showed that much improvement was achieved by additional pre-processing techniques on the algorithm of determining bleeding areas.
Abstract: Time series forecasting is an important and widely
popular topic in the research of system modeling. This paper
describes how to use the hybrid PSO-RLSE neuro-fuzzy learning
approach to the problem of time series forecasting. The PSO
algorithm is used to update the premise parameters of the
proposed prediction system, and the RLSE is used to update the
consequence parameters. Thanks to the hybrid learning (HL)
approach for the neuro-fuzzy system, the prediction performance
is excellent and the speed of learning convergence is much faster
than other compared approaches. In the experiments, we use the
well-known Mackey-Glass chaos time series. According to the
experimental results, the prediction performance and accuracy in
time series forecasting by the proposed approach is much better
than other compared approaches, as shown in Table IV. Excellent
prediction performance by the proposed approach has been
observed.