Abstract: We present a method for the selection of students
in interdisciplinary studies based on the hybrid averaging
operator. We assume that the available information given in
the problem is uncertain so it is necessary to use interval
numbers. Therefore, we suggest a new type of hybrid
aggregation called uncertain induced generalized hybrid
averaging (UIGHA) operator. It is an aggregation operator
that considers the weighted average (WA) and the ordered
weighted averaging (OWA) operator in the same formulation.
Therefore, we are able to consider the degree of optimism of
the decision maker and grades of importance in the same
approach. By using interval numbers, we are able to represent
the information considering the best and worst possible results
so the decision maker gets a more complete view of the
decision problem. We develop an illustrative example of the
proposed scheme in the selection of students in
interdisciplinary studies. We see that with the use of the
UIGHA operator we get a more complete representation of the
selection problem. Then, the decision maker is able to
consider a wide range of alternatives depending on his
interests. We also show other potential applications that could
be used by using the UIGHA operator in educational problems
about selection of different types of resources such as
students, professors, etc.
Abstract: In this paper, an adaptive polarized Multiple-Input
Multiple-Output (MIMO) Multicarrier Spread Spectrum Code Division Multiple Access (MC-SS-CDMA) system is designed for downlink mobile communications. The proposed system will be
examined in Frequency Division Duplex (FDD) mode for both macro urban and suburban environments. For the same transmission
bandwidth, a performance comparison between both nonoverlapped and orthogonal Frequency Division Multiplexing (FDM) schemes will be presented. Also, the proposed system will be compared with
both the closed loop vertical MIMO MC-SS-CDMA system and the
synchronous vertical STBC-MIMO MC-SS-CDMA system. As will
be shown, the proposed system introduces a significant performance
gain as well as reducing the spatial dimensions of the MIMO system
and simplifying the receiver implementation. The effect of the
polarization diversity characteristics on the BER performance will be
discussed. Also, the impact of excluding the cross-polarization MCSS-
CDMA blocks in the base station will be investigated. In addition,
the system performance will be evaluated under different Feedback
Information (FBI) rates for slowly-varying channels. Finally, a
performance comparison for vehicular and pedestrian environments
will be presented
Abstract: Hospital staff and managers are under pressure and
concerned for effective use and management of scarce resources. The
hospital admissions require many decisions that have complex and
uncertain consequences for hospital resource utilization and patient
flow. It is challenging to predict risk of admissions and length of stay
of a patient due to their vague nature. There is no method to capture
the vague definition of admission of a patient. Also, current methods
and tools used to predict patients at risk of admission fail to deal with
uncertainty in unplanned admission, LOS, patients- characteristics.
The main objective of this paper is to deal with uncertainty in
health system variables, and handles uncertain relationship among
variables. An introduction of machine learning techniques along with
statistical methods like Regression methods can be a proposed
solution approach to handle uncertainty in health system variables. A
model that adapts fuzzy methods to handle uncertain data and
uncertain relationships can be an efficient solution to capture the
vague definition of admission of a patient.
Abstract: The research on two-wheels balancing robot has
gained momentum due to their functionality and reliability when
completing certain tasks. This paper presents investigations into the
performance comparison of Linear Quadratic Regulator (LQR) and
PID-PID controllers for a highly nonlinear 2–wheels balancing robot.
The mathematical model of 2-wheels balancing robot that is highly
nonlinear is derived. The final model is then represented in statespace
form and the system suffers from mismatched condition. Two
system responses namely the robot position and robot angular
position are obtained. The performances of the LQR and PID-PID
controllers are examined in terms of input tracking and disturbances
rejection capability. Simulation results of the responses of the
nonlinear 2–wheels balancing robot are presented in time domain. A
comparative assessment of both control schemes to the system
performance is presented and discussed.
Abstract: In this work, we study the problem of determining
the minimum scheduling length that can satisfy end-to-end (ETE)
traffic demand in scheduling-based multihop WSNs with cooperative
multiple-input multiple-output (MIMO) transmission scheme. Specifically,
we present a cross-layer formulation for the joint routing,
scheduling and stream control problem by incorporating various
power and rate adaptation schemes, and taking into account an
antenna beam pattern model and the signal-to-interference-and-noise
(SINR) constraint at the receiver. In the context, we also propose
column generation (CG) solutions to get rid of the complexity
requiring the enumeration of all possible sets of scheduling links.
Abstract: In order to enhance the contrast in the regions where the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes these regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrasts in the images and the results are compared to the conventional approaches to show its superiority.
Abstract: Image compression can improve the performance of
the digital systems by reducing time and cost in image storage
and transmission without significant reduction of the image quality.
Furthermore, the discrete cosine transform has emerged as the new
state-of-the art standard for image compression. In this paper, a
hybrid image compression technique based on reversible blockade
transform coding is proposed. The technique, implemented over
regions of interest (ROIs), is based on selection of the coefficients
that belong to different transforms, depending on the coefficients is
proposed. This method allows: (1) codification of multiple kernals
at various degrees of interest, (2) arbitrary shaped spectrum,and (3)
flexible adjustment of the compression quality of the image and the
background. No standard modification for JPEG2000 decoder was
required. The method was applied over different types of images.
Results show a better performance for the selected regions, when
image coding methods were employed for the whole set of images.
We believe that this method is an excellent tool for future image
compression research, mainly on images where image coding can
be of interest, such as the medical imaging modalities and several
multimedia applications. Finally VLSI implementation of proposed
method is shown. It is also shown that the kernal of Hartley and
Cosine transform gives the better performance than any other model.
Abstract: Patients with diabetes are susceptible to chronic foot
wounds which may be difficult to manage and slow to heal.
Diagnosis and treatment currently rely on the subjective judgement of
experienced professionals. An objective method of tissue assessment
is required. In this paper, a data fusion approach was taken to wound
tissue classification. The supervised Maximum Likelihood and
unsupervised Multi-Modal Expectation Maximisation algorithms
were used to classify tissues within simulated wound models by
weighting the contributions of both colour and 3D depth information.
It was found that, at low weightings, depth information could show
significant improvements in classification accuracy when compared
to classification by colour alone, particularly when using the
maximum likelihood method. However, larger weightings were
found to have an entirely negative effect on accuracy.
Abstract: Worm propagation profiles have significantly changed
since 2003-2004: sudden world outbreaks like Blaster or Slammer
have progressively disappeared and slower but stealthier worms
appeared since, most of them for botnets dissemination. Decreased
worm virulence results in more difficult detection.
In this paper, we describe a stealth worm propagation model
which has been extensively simulated and analysed on a huge virtual
network. The main features of this model is its ability to infect any
Internet-like network in a few seconds, whatever may be its size while
greatly limiting the reinfection attempt overhead of already infected
hosts. The main simulation results shows that the combinatorial
topology of routing may have a huge impact on the worm propagation
and thus some servers play a more essential and significant role than
others. The real-time capability to identify them may be essential to
greatly hinder worm propagation.
Abstract: TiO2/Ag composite films were prepared by
incorporating Ag in the pores of mesoporous TiO2 films using a
photoreduction method. The Ag nanoparticle sizes were in a range of
3.66-38.56 nm. The TiO2/Ag composite films were characterized by
X-ray diffraction (XRD), scanning electron microscopy (SEM) and
transmission electron microscropy (TEM). The TiO2 films and
TiO2/Ag composite films were immersed in a 0.3 mM N719 dye
solution and characterized by UV-Vis spectrophotometer. The
TiO2/Ag/N719 composite film showed that an optimal size of Ag
nanoparticles was 19.12 nm and, hence, gave the maximum optical
absorption spectra. The improved absorption was due to surface
plasmon resonance induced by the Ag nanoparticles to enhance the
absorption coefficient of the dye.
Abstract: Because of the great advance in multimedia
technology, digital multimedia is vulnerable to malicious
manipulations. In this paper, a public key self-recovery block-based
video authentication technique is proposed which can not only
precisely localize the alteration detection but also recover the missing
data with high reliability. In the proposed block-based technique,
multiple description coding MDC is used to generate two codes (two
descriptions) for each block. Although one block code (one
description) is enough to rebuild the altered block, the altered block
is rebuilt with better quality by the two block descriptions. So using
MDC increases the ratability of recovering data. A block signature is
computed using a cryptographic hash function and a doubly linked
chain is utilized to embed the block signature copies and the block
descriptions into the LSBs of distant blocks and the block itself. The
doubly linked chain scheme gives the proposed technique the
capability to thwart vector quantization attacks. In our proposed
technique , anyone can check the authenticity of a given video using
the public key. The experimental results show that the proposed
technique is reliable for detecting, localizing and recovering the
alterations.
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: In this paper, we propose a dynamic TDMA slot
reservation (DTSR) protocol for cognitive radio ad hoc networks.
Quality of Service (QoS) guarantee plays a critically important role
in such networks. We consider the problem of providing QoS
guarantee to users as well as to maintain the most efficient use of
scarce bandwidth resources. According to one hop neighboring
information and the bandwidth requirement, our proposed protocol
dynamically changes the frame length and the transmission schedule.
A dynamic frame length expansion and shrinking scheme that
controls the excessive increase of unassigned slots has been
proposed. This method efficiently utilizes the channel bandwidth by
assigning unused slots to new neighboring nodes and increasing the
frame length when the number of slots in the frame is insufficient to
support the neighboring nodes. It also shrinks the frame length when
half of the slots in the frame of a node are empty. An efficient slot
reservation protocol not only guarantees successful data
transmissions without collisions but also enhance channel spatial
reuse to maximize the system throughput. Our proposed scheme,
which provides both QoS guarantee and efficient resource utilization,
be employed to optimize the channel spatial reuse and maximize the
system throughput. Extensive simulation results show that the
proposed mechanism achieves desirable performance in multichannel
multi-rate cognitive radio ad hoc networks.
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: 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: 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: This work proposes an approach to address automatic
text summarization. This approach is a trainable summarizer, which
takes into account several features, including sentence position,
positive keyword, negative keyword, sentence centrality, sentence
resemblance to the title, sentence inclusion of name entity, sentence
inclusion of numerical data, sentence relative length, Bushy path of
the sentence and aggregated similarity for each sentence to generate
summaries. First we investigate the effect of each sentence feature on
the summarization task. Then we use all features score function to
train genetic algorithm (GA) and mathematical regression (MR)
models to obtain a suitable combination of feature weights. The
proposed approach performance is measured at several compression
rates on a data corpus composed of 100 English religious articles.
The results of the proposed approach are promising.
Abstract: All-to-all personalized communication, also known as complete exchange, is one of the most dense communication patterns in parallel computing. In this paper, we propose new indirect algorithms for complete exchange on all-port ring and torus. The new algorithms fully utilize all communication links and transmit messages along shortest paths to completely achieve the theoretical lower bounds on message transmission, which have not be achieved among other existing indirect algorithms. For 2D r × c ( r % c ) all-port torus, the algorithm has time complexities of optimal transmission cost and O(c) message startup cost. In addition, the proposed algorithms accommodate non-power-of-two tori where the number of nodes in each dimension needs not be power-of-two or square. Finally, the algorithms are conceptually simple and symmetrical for every message and every node so that they can be easily implemented and achieve the optimum in practice.
Abstract: Postgraduate education is generally aimed at providing in-depth knowledge and understanding that include general philosophy in the world sciences, management, technologies, applications and other elements closely related to specific areas. In most universities, besides core and non-core subjects, a thesis is one of the requirements for the postgraduate student to accomplish before graduating. This paper reports on the empirical investigation into attributes that are associated with the obstacles to thesis accomplishment among postgraduate students. Using the quantitative approach the experiences of postgraduate students were tapped. Findings clearly revealed that information seeking, writing skills and other factors which refer to supervisor and time management, in particular, are recognized as contributory factors which positively or negatively influence postgraduates’ thesis accomplishment. Among these, writing skills dimensions were found to be the most difficult process in thesis accomplishment compared to information seeking and other factors. This pessimistic indication has provided some implications not only for the students but supervisors and institutions as a whole.
Abstract: In this work we present an efficient approach for face
recognition in the infrared spectrum. In the proposed approach
physiological features are extracted from thermal images in order to
build a unique thermal faceprint. Then, a distance transform is used
to get an invariant representation for face recognition. The obtained
physiological features are related to the distribution of blood vessels
under the face skin. This blood network is unique to each individual
and can be used in infrared face recognition. The obtained results are
promising and show the effectiveness of the proposed scheme.