Abstract: A novel idea presented in this paper is to combine
multihop routing with single-frequency networks (SFNs) for a
broadcasting scenario. An SFN is a set of multiple nodes that transmit
the same data simultaneously, resulting in transmitter macrodiversity.
Two of the most important performance factors of multihop
networks, node reachability and routing robustness, are analyzed.
Simulation results show that our proposed SFN-D routing algorithm
improves the node reachability by 37 percentage points as compared
to non-SFN multihop routing. It shows a diversity gain of 3.7 dB,
meaning that 3.7 dB lower transmission powers are required for the
same reachability. Even better results are possible for larger
networks. If an important node becomes inactive, this algorithm can
find new routes that a non-SFN scheme would not be able to find.
Thus, two of the major problems in multihopping are addressed;
achieving robust routing as well as improving node reachability or
reducing transmission power.
Abstract: The public sector holds large amounts of data of
various areas such as social affairs, economy, or tourism. Various
initiatives such as Open Government Data or the EU Directive on
public sector information aim to make these data available for public
and private service providers. Requirements for the provision of
public sector data are defined by legal and organizational
frameworks. Surprisingly, the defined requirements hardly cover
security aspects such as integrity or authenticity.
In this paper we discuss the importance of these missing
requirements and present a concept to assure the integrity and
authenticity of provided data based on electronic signatures. We
show that our concept is perfectly suitable for the provisioning of
unaltered data. We also show that our concept can also be extended
to data that needs to be anonymized before provisioning by
incorporating redactable signatures. Our proposed concept enhances
trust and reliability of provided public sector data.
Abstract: In this paper sensitivity analysis is performed for
reliability evaluation of power systems. When examining the
reliability of a system, it is useful to recognize how results
change as component parameters are varied. This knowledge
helps engineers to understand the impact of poor data, and
gives insight on how reliability can be improved. For these
reasons, a sensitivity analysis can be performed. Finally, a real
network was used for testing the presented method.
Abstract: The paper discusses optimising work on a method of processing ceramic / metal composite coatings for various applications and is based on preliminary work on processing anodes for solid oxide fuel cells (SOFCs). The composite coating is manufactured by the electroless co-deposition of nickel and yttria stabilised zirconia (YSZ) simultaneously on to a ceramic substrate. The effect on coating characteristics of substrate surface treatments and electroless nickel bath parameters such as pH and agitation methods are also investigated. Characterisation of the resulting deposit by scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDXA) is also discussed.
Abstract: This paper introduces a novel design for boring bar with enhanced damping capability. The principle followed in the design phase was to enhance the damping capability minimizing the loss in static stiffness through implementation of composite material interfaces. The newly designed tool has been compared to a conventional tool. The evaluation criteria were the dynamic characteristics, frequency and damping ratio, of the machining system, as well as the surface roughness of the machined workpieces. The use of composite material in the design of damped tool has been demonstrated effective. Furthermore, the autoregressive moving average (ARMA) models presented in this paper take into consideration the interaction between the elastic structure of the machine tool and the cutting process and can therefore be used to characterize the machining system in operational conditions.
Abstract: In the Equivalent Transformation (ET) computation
model, a program is constructed by the successive accumulation of
ET rules. A method by meta-computation by which a correct ET
rule is generated has been proposed. Although the method covers a
broad range in the generation of ET rules, all important ET rules
are not necessarily generated. Generation of more ET rules can be
achieved by supplementing generation methods which are specialized
for important ET rules. A Specialization-by-Equation (Speq) rule is
one of those important rules. A Speq rule describes a procedure in
which two variables included in an atom conjunction are equalized
due to predicate constraints. In this paper, we propose an algorithm
that systematically and recursively generate Speq rules and discuss
its effectiveness in the synthesis of ET programs. A Speq rule is
generated based on proof of a logical formula consisting of given
atom set and dis-equality. The proof is carried out by utilizing some
ET rules and the ultimately obtained rules in generating Speq rules.
Abstract: The purpose of this study is to investiagte the use of
the ecommerce website in Indonesia as a developing country. The
ecommerce website has been identified having the significant impact
on business activities in particular solving the geographical problem
for islanded countries likes Indonesia. Again, website is identified as
a crucial marketing tool. This study presents the effect of quality and
features on the use and user satisfaction employing ecommerce
websites. Survey method for 115 undergraduate students of
Management Department in Andalas University who are attending
Management Information Systems (SIM) class have been
undertaken. The data obtained is analyzed using Structural Equation
Modeling (SEM) using SmartPLS program. This result found that
quality of system and information, feature as well satisfaction
influencing the use ecommerce website in Indonesia contexts.
Abstract: The link between Gröbner basis and linear algebra was
described by Lazard [4,5] where he realized the Gr¨obner basis
computation could be archived by applying Gaussian elimination over
Macaulay-s matrix .
In this paper, we indicate how same technique may be used to
SAGBI- Gröbner basis computations in invariant rings.
Abstract: Indian subcontinent has a plethora of traditional
medicine systems that provide promising solutions to lifestyle
disorders in an 'all natural way'. Spices and oilseeds hold
prominence in Indian cuisine hence the focus of the current study
was to evaluate the bioactive molecules from Linum usitatissinum
(LU), Lepidium sativum (LS), Nigella sativa (NS) and Guizotia
abyssinica (GA) seeds. The seeds were characterized for functional
lipids like omega-3 fatty acid, antioxidant capacity, phenolic
compounds, dietary fiber and anti-nutritional factors. Analysis of the
seeds revealed LU and LS to be a rich source of α-linolenic acid
(41.85 ± 0.33%, 26.71 ± 0.63%), an omega 3 fatty acid (using
GCMS). While studying antioxidant potential NS seeds demonstrated
highest antioxidant ability (61.68 ± 0.21 TEAC/ 100 gm DW) due to
the presence of phenolics and terpenes as assayed by the Mass
spectral analysis. When screened for anti-nutritional factor
cyanogenic glycoside, LS seeds showed content as high as 1674 ± 54
mg HCN / kg. GA is a probable good source of a stable vegetable oil
(SFA: PUFA 1:2.3). The seeds showed diversified bioactive profile
and hence further studies to use different bio molecules in tandem for
the development of a possible 'nutraceutical cocktail' have been
initiated..
Abstract: Microstrip lines, widely used for good reason, are
broadband in frequency and provide circuits that are compact and
light in weight. They are generally economical to produce since they
are readily adaptable to hybrid and monolithic integrated circuit (IC)
fabrication technologies at RF and microwave frequencies. Although,
the existing EM simulation models used for the synthesis and
analysis of microstrip lines are reasonably accurate, they are
computationally intensive and time consuming. Neural networks
recently gained attention as fast and flexible vehicles to microwave
modeling, simulation and optimization. After learning and
abstracting from microwave data, through a process called training,
neural network models are used during microwave design to provide
instant answers to the task learned.This paper presents simple and
accurate ANN models for the synthesis and analysis of Microstrip
lines to more accurately compute the characteristic parameters and
the physical dimensions respectively for the required design
specifications.
Abstract: Avionic software architecture has transit from a
federated avionics architecture to an integrated modular avionics
(IMA) .ARINC 653 (Avionics Application Standard Software Interface) is a software specification for space and time partitioning in
Safety-critical avionics Real-time operating systems. Methods to transform the abstract avionics application logic function to the
executable model have been brought up, however with less
consideration about the code generating input and output model specific for ARINC 653 platform and inner-task synchronous dynamic
interaction order sequence. In this paper, we proposed an
AADL-based model-driven design methodology to fulfill the purpose
to automatically generating Cµ executable model on ARINC 653 platform from the ARINC653 architecture which defined as AADL653 in order to facilitate the development of the avionics software constructed on ARINC653 OS. This paper presents the
mapping rules between the AADL653 elements and the elements in
Cµ language, and define the code generating rules , designs an automatic C µ code generator .Then, we use a case to illustrate our
approach. Finally, we give the related work and future research directions.
Abstract: Taking into account that many problems of natural
sciences and engineering are reduced to solving initial-value problem
for ordinary differential equations, beginning from Newton, the
scientists investigate approximate solution of ordinary differential
equations. There are papers of different authors devoted to the
solution of initial value problem for ODE. The Euler-s known
method that was developed under the guidance of the famous
scientists Adams, Runge and Kutta is the most popular one among
these methods.
Recently the scientists began to construct the methods preserving
some properties of Adams and Runge-Kutta methods and called them
hybrid methods. The constructions of such methods are investigated
from the middle of the XX century. Here we investigate one
generalization of multistep and hybrid methods and on their base we
construct specific methods of accuracy order p = 5 and p = 6 for
k = 1 ( k is the order of the difference method).
Abstract: This study on “The relationship between human
resource practices and Firm Performance is a speculative
investigation research. The purpose of this research are (1) to provide
and to understand of HRM history and current HR practices in the
Philippines (2) to examine the extent of HRM practice among its
Philippine firms effectively; (3) to investigate the relationship
between HRM practice and firm performance in the Philippines. The
survey was done to 233 companies in the Philippines. The
questionnaire is divided into three parts a) to gathers information on
the profile of respondent, b) to measures the extent to which human
resource practices are being practiced in their organization c) to
measure the organizations performance as perceived by human
resource managers and top executives as compared with their
competitors in the same industry. As a result an interesting finding
was that almost 50 percent of firm performance is affected by the
extent of implementation of HR practices in the firm. These results
show that HR practices that are in line with the organization’s
strategic goals are important for future performance.
Abstract: Several studies have been carried out, using various techniques, including neural networks, to discriminate vigilance states in humans from electroencephalographic (EEG) signals, but we are still far from results satisfactorily useable results. The work presented in this paper aims at improving this status with regards to 2 aspects. Firstly, we introduce an original procedure made of the association of two neural networks, a self organizing map (SOM) and a learning vector quantization (LVQ), that allows to automatically detect artefacted states and to separate the different levels of vigilance which is a major breakthrough in the field of vigilance. Lastly and more importantly, our study has been oriented toward real-worked situation and the resulting model can be easily implemented as a wearable device. It benefits from restricted computational and memory requirements and data access is very limited in time. Furthermore, some ongoing works demonstrate that this work should shortly results in the design and conception of a non invasive electronic wearable device.
Abstract: Many research works are carried out on the analysis of
traces in a digital learning environment. These studies produce large
volumes of usage tracks from the various actions performed by a
user. However, to exploit these data, compare and improve
performance, several issues are raised. To remedy this, several works
deal with this problem seen recently. This research studied a series of
questions about format and description of the data to be shared. Our
goal is to share thoughts on these issues by presenting our experience
in the analysis of trace-based log files, comparing several approaches
used in automatic classification applied to e-learning platforms.
Finally, the obtained results are discussed.
Abstract: This paper presents a implementation of an object tracking system in a video sequence. This object tracking is an important task in many vision applications. The main steps in video analysis are two: detection of interesting moving objects and tracking of such objects from frame to frame. In a similar vein, most tracking algorithms use pre-specified methods for preprocessing. In our work, we have implemented several object tracking algorithms (Meanshift, Camshift, Kalman filter) with different preprocessing methods. Then, we have evaluated the performance of these algorithms for different video sequences. The obtained results have shown good performances according to the degree of applicability and evaluation criteria.
Abstract: In this paper, application of artificial neural networks
in typical disease diagnosis has been investigated. The real procedure
of medical diagnosis which usually is employed by physicians was
analyzed and converted to a machine implementable format. Then
after selecting some symptoms of eight different diseases, a data set
contains the information of a few hundreds cases was configured and
applied to a MLP neural network. The results of the experiments and
also the advantages of using a fuzzy approach were discussed as
well. Outcomes suggest the role of effective symptoms selection and
the advantages of data fuzzificaton on a neural networks-based
automatic medical diagnosis system.
Abstract: The focus in this work is to assess which method
allows a better forecasting of malaria cases in Bujumbura ( Burundi)
when taking into account association between climatic factors and
the disease. For the period 1996-2007, real monthly data on both
malaria epidemiology and climate in Bujumbura are described and
analyzed. We propose a hierarchical approach to achieve our
objective. We first fit a Generalized Additive Model to malaria cases
to obtain an accurate predictor, which is then used to predict future
observations. Various well-known forecasting methods are compared
leading to different results. Based on in-sample mean average
percentage error (MAPE), the multiplicative exponential smoothing
state space model with multiplicative error and seasonality performed
better.
Abstract: Data mining has been used very frequently to extract
hidden information from large databases. This paper suggests the use
of decision trees for continuously extracting the clinical reasoning in
the form of medical expert-s actions that is inherent in large number
of EMRs (Electronic Medical records). In this way the extracted data
could be used to teach students of oral medicine a number of orderly
processes for dealing with patients who represent with different
problems within the practice context over time.
Abstract: One of the essential sectors of Myanmar economy is
agriculture which is sensitive to climate variation. The most
important climatic element which impacts on agriculture sector is
rainfall. Thus rainfall prediction becomes an important issue in
agriculture country. Multi variables polynomial regression (MPR)
provides an effective way to describe complex nonlinear input output
relationships so that an outcome variable can be predicted from the
other or others. In this paper, the modeling of monthly rainfall
prediction over Myanmar is described in detail by applying the
polynomial regression equation. The proposed model results are
compared to the results produced by multiple linear regression model
(MLR). Experiments indicate that the prediction model based on
MPR has higher accuracy than using MLR.