Abstract: This paper presents an optimal broadcast algorithm
for the hypercube networks. The main focus of the paper is the
effectiveness of the algorithm in the presence of many node faults.
For the optimal solution, our algorithm builds with spanning tree
connecting the all nodes of the networks, through which messages
are propagated from source node to remaining nodes. At any given
time, maximum n − 1 nodes may fail due to crashing. We show
that the hypercube networks are strongly fault-tolerant. Simulation
results analyze to accomplish algorithm characteristics under many
node faults. We have compared our simulation results between our
proposed method and the Fu’s method. Fu’s approach cannot tolerate
n − 1 faulty nodes in the worst case, but our approach can tolerate
n − 1 faulty nodes.
Abstract: Theory of Mind (ToM) refers to the ability to infer
another’s mental state. With appropriate ToM, one can behave well in
social interactions. A growing body of evidence has demonstrated that
patients with temporal lobe epilepsy (TLE) may damage ToM by
affecting on regions of the underlying neural network of ToM.
However, the question of whether there is cerebral laterality for ToM
functions remains open. This study aimed to examine whether there is
cerebral lateralization for ToM abilities in TLE patients. Sixty-seven
adult TLE patients and 30 matched healthy controls (HC) were
recruited. Patients were classified into right (RTLE), left (LTLE), and
bilateral (BTLE) TLE groups on the basis of a consensus panel review
of their seizure semiology, EEG findings, and brain imaging results.
All participants completed an intellectual test and four tasks measuring
basic and advanced ToM. The results showed that, on all ToM tasks,
(1) each patient group performed worse than HC; (2) there were no
significant differences between LTLE and RTLE groups; and (3) the
BTLE group performed the worst. It appears that the neural network
responsible for ToM is distributed evenly between the cerebral
hemispheres.
Abstract: The Scheduling and mapping of tasks on a set of
processors is considered as a critical problem in parallel and
distributed computing system. This paper deals with the problem of
dynamic scheduling on a special type of multiprocessor architecture
known as Linear Crossed Cube (LCQ) network. This proposed
multiprocessor is a hybrid network which combines the features of
both linear types of architectures as well as cube based architectures.
Two standard dynamic scheduling schemes namely Minimum
Distance Scheduling (MDS) and Two Round Scheduling (TRS)
schemes are implemented on the LCQ network. Parallel tasks are
mapped and the imbalance of load is evaluated on different set of
processors in LCQ network. The simulations results are evaluated
and effort is made by means of through analysis of the results to
obtain the best solution for the given network in term of load
imbalance left and execution time. The other performance matrices
like speedup and efficiency are also evaluated with the given
dynamic algorithms.
Abstract: The following article presents Technology Centre of
Ostrava (TCO) in the Czech Republic describing the structure and
main research areas realized by the project ENET - Energy Units for
Utilization of non Traditional Energy Sources. More details are
presented from the research program dealing with transformation,
accumulation and distribution of electric energy. Technology Centre
has its own energy mix consisting of alternative sources of fuel
sources that use of process gases from the storage part and also the
energy from distribution network. The article will be focus on the
properties and application possibilities SiC semiconductor devices for
power semiconductor converter for photovoltaic systems.
Abstract: The advent of social networking technologies has been
met with mixed reactions in academic and corporate circles around
the world. This study explored the influence of social network in
current era, the relation being maintained between the Social
networking site and its user by the extent of use, benefits and latest
technologies. The study followed a descriptive research design
wherein a questionnaire was used as the main research tool. The data
collected was analyzed using SPSS 16. Data was gathered from 1205
users and analyzed in accordance with the objectives of the study.
The analysis of the results seem to suggest that the majority of users
were mainly using Facebook, despite of concerns raised about the
disclosure of personal information on social network sites, users
continue to disclose huge quantity of personal information, they find
that reading privacy policy is time consuming and changes made can
result into improper settings.
Abstract: Behavioral aspects of experience such as will power
are rarely subjected to quantitative study owing to the numerous
complexities involved. Will is a phenomenon that has puzzled
humanity for a long time. It is a belief that will power of an individual
affects the success achieved by them in life. It is also thought that a
person endowed with great will power can overcome even the most
crippling setbacks in life while a person with a weak will cannot make
the most of life even the greatest assets. This study is an attempt
to subject the phenomena of will to the test of an artificial neural
network through a computational model. The claim being tested is
that will power of an individual largely determines success achieved
in life. It is proposed that data pertaining to success of individuals
be obtained from an experiment and the phenomenon of will be
incorporated into the model, through data generated recursively using
a relation between will and success characteristic to the model.
An artificial neural network trained using part of the data, could
subsequently be used to make predictions regarding data points in
the rest of the model. The procedure would be tried for different
models and the model where the networks predictions are found to
be in greatest agreement with the data would be selected; and used
for studying the relation between success and will.
Abstract: The research of juice flavor forecasting has become
more important in China. Due to the fast economic growth in China,
many different kinds of juices have been introduced to the market. If a
beverage company can understand their customers’ preference well,
the juice can be served more attractive. Thus, this study intends to
introducing the basic theory and computing process of grapes juice
flavor forecasting based on support vector regression (SVR). Applying
SVR, BPN, and LR to forecast the flavor of grapes juice in real data
shows that SVR is more suitable and effective at predicting
performance.
Abstract: Transmission system performance analysis is vital to
proper planning and operations of power systems in the presence of
deregulation. Key performance indicators (KPIs) are often used as
measure of degree of performance. This paper gives a novel method
to determine the transmission efficiency by evaluating the ratio of
real power losses incurred from a specified transfer direction.
Available Transmission Transfer Efficiency (ATTE) expresses the
percentage of real power received resulting from inter-area available
power transfer. The Tie line (Rated system path) performance is seen
to differ from system wide (Network response) performance and
ATTE values obtained are transfer direction specific. The required
sending end quantities with specified receiving end ATC and the
receiving end power circle diagram are obtained for the tie line
analysis. The amount of real power loss load relative to the available
transfer capability gives a measure of the transmission grid
efficiency.
Abstract: Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods
Abstract: In this paper static scheme of under-frequency based load shedding is considered for chemical and petrochemical industries with islanded distribution networks relying heavily on the primary commodity to ensure minimum production loss, plant downtime or critical equipment shutdown. A simplistic methodology is proposed for in-house implementation of this scheme using underfrequency relays and a step by step guide is provided including the techniques to calculate maximum percentage overloads, frequency decay rates, time based frequency response and frequency based time response of the system. Case study of FFL electrical system is utilized, presenting the actual system parameters and employed load shedding settings following the similar series of steps. The arbitrary settings are then verified for worst overload conditions (loss of a generation source in this case) and comprehensive system response is then investigated.
Abstract: The distribution of a single global clock across a chip
has become the major design bottleneck for high performance VLSI
systems owing to the power dissipation, process variability and multicycle
cross-chip signaling. A Network-on-Chip (NoC) architecture
partitioned into several synchronous blocks has become a promising
approach for attaining fine-grain power management at the system
level. In a NoC architecture the communication between the blocks is
handled asynchronously. To interface these blocks on a chip
operating at different frequencies, an asynchronous FIFO interface is
inevitable. However, these asynchronous FIFOs are not required if
adjacent blocks belong to the same clock domain. In this paper, we
have designed and analyzed a 16-bit asynchronous micropipelined
FIFO of depth four, with the awareness of place and route on an
FPGA device. We have used a commercially available Spartan 3
device and designed a high speed implementation of the
asynchronous 4-phase micropipeline. The asynchronous FIFO
implemented on the FPGA device shows 76 Mb/s throughput and a
handshake cycle of 109 ns for write and 101.3 ns for read at the
simulation under the worst case operating conditions (voltage =
0.95V) on a working chip at the room temperature.
Abstract: This paper is concerned with knowledge representation
and extraction of fuzzy if-then rules using Interval Type-2
Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of
fuzzy granulation. This proposed clustering algorithm is based on
information granulation in the form of IT2 based Fuzzy C-Means
(IT2-FCM) clustering and estimates the cluster centers by preserving
the homogeneity between the clustered patterns from the IT2 contexts
produced in the output space. Furthermore, we can obtain the
automatic knowledge representation in the design of Radial Basis
Function Networks (RBFN), Linguistic Model (LM), and Adaptive
Neuro-Fuzzy Networks (ANFN) from the numerical input-output data
pairs. We shall focus on a design of ANFN in this paper. The
experimental results on an estimation problem of energy performance
reveal that the proposed method showed a good knowledge
representation and performance in comparison with the previous
works.
Abstract: Typically, virtual communities exhibit the well-known
phenomenon of participation inequality, which means that only a
small percentage of users is responsible of the majority of
contributions. However, the sustainability of the community requires
that the group of active users must be continuously nurtured with new
users that gain expertise through a participation process. This paper
analyzes the time evolution of Open Source Software (OSS)
communities, considering users that join/abandon the community
over time and several topological properties of the network when
modeled as a social network. More specifically, the paper analyzes
the role of those users rejoining the community and their influence in
the global characteristics of the network.
Abstract: Taiwan is a hyper endemic area for the Hepatitis B
virus (HBV). The estimated total number of HBsAg carriers in the
general population who are more than 20 years old is more than 3
million. Therefore, a case record review is conducted from January
2003 to June 2007 for all patients with a diagnosis of acute hepatitis
who were admitted to the Emergency Department (ED) of a
well-known teaching hospital. The cost for the use of medical
resources is defined as the total medical fee. In this study, principal
component analysis (PCA) is firstly employed to reduce the number of
dimensions. Support vector regression (SVR) and artificial neural
network (ANN) are then used to develop the forecasting model. A total
of 117 patients meet the inclusion criteria. 61% patients involved in
this study are hepatitis B related. The computational result shows that
the proposed PCA-SVR model has superior performance than other
compared algorithms. In conclusion, the Child-Pugh score and
echogram can both be used to predict the cost of medical resources for
patients with acute hepatitis in the ED.
Abstract: This paper presents a novel integrated hybrid
approach for fault diagnosis (FD) of nonlinear systems. Unlike most
FD techniques, the proposed solution simultaneously accomplishes
fault detection, isolation, and identification (FDII) within a unified
diagnostic module. At the core of this solution is a bank of adaptive
neural parameter estimators (NPE) associated with a set of singleparameter
fault models. The NPEs continuously estimate unknown
fault parameters (FP) that are indicators of faults in the system. Two
NPE structures including series-parallel and parallel are developed
with their exclusive set of desirable attributes. The parallel scheme is
extremely robust to measurement noise and possesses a simpler, yet
more solid, fault isolation logic. On the contrary, the series-parallel
scheme displays short FD delays and is robust to closed-loop system
transients due to changes in control commands. Finally, a fault
tolerant observer (FTO) is designed to extend the capability of the
NPEs to systems with partial-state measurement.
Abstract: Our globalizing world has become almost a small
village and everyone can access any information at any time.
Everyone lets each other know who does whatever in which place.
We can learn which social events occur in which place in the world.
From the perspective of education, the course notes that a lecturer use
in lessons in a university in any state of America can be examined by
a student studying in a city of Africa or the Far East. This dizzying
communication we have mentioned happened thanks to fast
developments in computer and internet technologies. While these
developments occur in the world, Turkey that has a very large young
population and whose electronic infrastructure rapidly improves has
also been affected by these developments. Nowadays, mobile devices
have become common and thus, it causes to increase data traffic in
social networks. This study was carried out on students in the
different age groups in Selcuk University Vocational School of
Technical Sciences, the Department of Computer Technology.
Students’ opinions about the use of internet and social media were
obtained. The features such as using the Internet and social media
skills, purposes, operating frequency, accessing facilities and tools,
social life and effects on vocational education and so forth were
explored. The positive effects and negative effects of both internet
and social media use on the students in this department and findings
are evaluated from different perspectives and results are obtained. In
addition, relations and differences were found out statistically.
Abstract: The aim of this paper is to present the optimization
methodology developed in the frame of a Coastal Transport
Information System. The system will be used for the effective design
of coastal transportation lines and incorporates subsystems that
implement models, tools and techniques that may support the design
of improved networks. The role of the optimization and decision
subsystem is to provide the user with better and optimal scenarios
that will best fulfill any constrains, goals or requirements posed. The
complexity of the problem and the large number of parameters and
objectives involved led to the adoption of an evolutionary method
(Genetic Algorithms). The problem model and the subsystem
structure are presented in detail, and, its support for simulation is also
discussed.
Abstract: The paper presents an innovative networked radar
system for detection of obstacles in a railway level crossing scenario.
This Monitoring System (MS) is able to detect moving or still
obstacles within the railway level crossing area automatically,
avoiding the need of human presence for surveillance. The MS is also
connected to the National Railway Information and Signaling System
to communicate in real-time the level crossing status. The
architecture is compliant with the highest Safety Integrity Level
(SIL4) of the CENELEC standard. The number of radar sensors used
is configurable at set-up time and depends on how large the level
crossing area can be. At least two sensors are expected and up four
can be used for larger areas. The whole processing chain that
elaborates the output sensor signals, as well as the communication
interface, is fully-digital, was designed in VHDL code and
implemented onto a Xilinx Virtex 6.
Abstract: In this paper, we introduced a gradient-based inverse
solver to obtain the missing boundary conditions based on the
readings of internal thermocouples. The results show that the method
is very sensitive to measurement errors, and becomes unstable when
small time steps are used. The artificial neural networks are shown to
be capable of capturing the whole thermal history on the run-out
table, but are not very effective in restoring the detailed behavior of
the boundary conditions. Also, they behave poorly in nonlinear cases
and where the boundary condition profile is different.
GA and PSO are more effective in finding a detailed
representation of the time-varying boundary conditions, as well as in
nonlinear cases. However, their convergence takes longer. A
variation of the basic PSO, called CRPSO, showed the best
performance among the three versions. Also, PSO proved to be
effective in handling noisy data, especially when its performance
parameters were tuned. An increase in the self-confidence parameter
was also found to be effective, as it increased the global search
capabilities of the algorithm. RPSO was the most effective variation
in dealing with noise, closely followed by CRPSO. The latter
variation is recommended for inverse heat conduction problems, as it
combines the efficiency and effectiveness required by these
problems.
Abstract: A model was constructed to predict the amount of
solar radiation that will make contact with the surface of the earth in
a given location an hour into the future. This project was supported
by the Southern Company to determine at what specific times during
a given day of the year solar panels could be relied upon to produce
energy in sufficient quantities. Due to their ability as universal
function approximators, an artificial neural network was used to
estimate the nonlinear pattern of solar radiation, which utilized
measurements of weather conditions collected at the Griffin, Georgia
weather station as inputs. A number of network configurations and
training strategies were utilized, though a multilayer perceptron with
a variety of hidden nodes trained with the resilient propagation
algorithm consistently yielded the most accurate predictions. In
addition, a modeled direct normal irradiance field and adjacent
weather station data were used to bolster prediction accuracy. In later
trials, the solar radiation field was preprocessed with a discrete
wavelet transform with the aim of removing noise from the
measurements. The current model provides predictions of solar
radiation with a mean square error of 0.0042, though ongoing efforts
are being made to further improve the model’s accuracy.