Abstract: Dispersions of casein micelles (CM) were studied at a
constant protein concentration of 5 wt % in high NaCl environment
ranging from 0% to 12% by Dynamic light scattering (DLS) and
Fourier Transform Infrared (FTIR). The rehydration profiles obtained
were interpreted in term of wetting, swelling and dispersion stages by
using a turbidity method. Two behaviours were observed depending
on the salt concentration. The first behaviour (low salt concentration)
presents a typical rehydration profile with a significant change
between 3 and 6% NaCl indicating quick wetting, swelling and long
dispersion stage. On the opposite, the dispersion stage of the second
behaviour (high salt concentration) was significantly shortened
indicating a strong modification of the protein backbone. A salt
increase result to a destabilization of the micelle and the formation of
mini-micelles more or less aggregated indicating an average micelles
size ranging from 100 to 200 nm. For the first time, the estimations
of secondary structural elements (irregular, ß-sheet, α-helix and turn)
by the Amide III assignments were correlated with results from
Amide I.
Abstract: Water leakage is a serious problem in the maintenance of a waterworks facility. Monitoring the water flow rate is one way to locate leakage. However, conventional flowmeters such as the wet-type flowmeter and the clamp-on type ultrasonic flowmeter require additional construction for their installation and are therefore quite expensive. This paper proposes a novel estimation system for the flow rate in a water pipeline, which employs a vibration sensor. This assembly can be attached to any water pipeline without the need for additional high-cost construction. The vibration sensor is designed based on a condenser microphone. This sensor detects vibration caused by water flowing through a pipeline. It is possible to estimate the water flow rate by measuring the amplitude of the output signal from the vibration sensor. We confirmed the validity of the proposed sensing system experimentally.
Abstract: In this paper, a Markovian risk model with two-type claims is considered. In such a risk model, the occurrences of the two type claims are described by two point processes {Ni(t), t ¸ 0}, i = 1, 2, where {Ni(t), t ¸ 0} is the number of jumps during the interval (0, t] for the Markov jump process {Xi(t), t ¸ 0} . The ruin probability ª(u) of a company facing such a risk model is mainly discussed. An integral equation satisfied by the ruin probability ª(u) is obtained and the bounds for the convergence rate of the ruin probability ª(u) are given by using key-renewal theorem.
Abstract: This research investigates the suitability of fuel oil in
improving gypseous soil. A detailed laboratory tests were carried-out
on two soils (soil I with 51.6% gypsum content, and soil II with
26.55%), where the two soils were obtained from Al-Therthar site
(Al-Anbar Province-Iraq).
This study examines the improvement of soil properties using the
gypsum material which is locally available with low cost to minimize
the effect of moisture on these soils by using the fuel oil. This study
was conducted on two models of the soil gypsum, from the Tharthar
area. The first model was sandy soil with Gypsum content of (51.6%)
and the second is clayey soil and the content of Gypsum is (26.55%).
The program included tests measuring the permeability and
compressibility of the soil and their collapse properties. The shear
strength of the soil and the amounts of weight loss of fuel oil due to
drying had been found. These tests have been conducted on the
treated and untreated soils to observe the effect of soil treatment on
the engineering properties when mixed with varying degrees of fuel
oil with the equivalent of the water content.
The results showed that fuel oil is a good material to modify the
basic properties of the gypseous soil of collapsibility and
permeability, which are the main problems of this soil and retained
the soil by an appropriate amount of the cohesion suitable for
carrying the loads from the structure.
Abstract: In this paper we introduce a novel kernel classifier
based on a iterative shrinkage algorithm developed for compressive
sensing. We have adopted Bregman iteration with soft and hard
shrinkage functions and generalized hinge loss for solving l1 norm
minimization problem for classification. Our experimental results
with face recognition and digit classification using SVM as the
benchmark have shown that our method has a close error rate
compared to SVM but do not perform better than SVM. We have
found that the soft shrinkage method give more accuracy and in some
situations more sparseness than hard shrinkage methods.
Abstract: Inadequate curriculum for software engineering is considered to be one of the most common software risks. A number of solutions, on improving Software Engineering Education (SEE) have been reported in literature but there is a need to collectively present these solutions at one place. We have performed a mapping study to present a broad view of literature; published on improving the current state of SEE. Our aim is to give academicians, practitioners and researchers an international view of the current state of SEE. Our study has identified 70 primary studies that met our selection criteria, which we further classified and categorized in a well-defined Software Engineering educational framework. We found that the most researched category within the SE educational framework is Innovative Teaching Methods whereas the least amount of research was found in Student Learning and Assessment category. Our future work is to conduct a Systematic Literature Review on SEE.
Abstract: In this paper, an improvement of PDLZW implementation
with a new dictionary updating technique is proposed. A
unique dictionary is partitioned into hierarchical variable word-width
dictionaries. This allows us to search through dictionaries in parallel.
Moreover, the barrel shifter is adopted for loading a new input string
into the shift register in order to achieve a faster speed. However,
the original PDLZW uses a simple FIFO update strategy, which is
not efficient. Therefore, a new window based updating technique
is implemented to better classify the difference in how often each
particular address in the window is referred. The freezing policy
is applied to the address most often referred, which would not be
updated until all the other addresses in the window have the same
priority. This guarantees that the more often referred addresses would
not be updated until their time comes. This updating policy leads
to an improvement on the compression efficiency of the proposed
algorithm while still keep the architecture low complexity and easy
to implement.
Abstract: This paper reports the influence of sucrose on the
preservation of CO2 hydrate crystal samples. The particle diameter of
hydrate samples were 1.0 and 5.6-8.0 mm. Mass fraction of sucrose in
the sample was 0.16. The samples were stored at the aerated condition
under atmospheric pressure and at the temperature of 253 or 258 K.
The results indicated that the mass fractions of CO2 hydrate in the
samples with sucrose were 0.10 ± 0.03 at the end of 3-week
preservation, regardless of temperature and particle diameter. Mass
fraction of CO2 hydrate in the samples with sucrose was higher than
that of pure CO2 hydrate for 1.0 mm particle diameter, while was
lower than that of pure CO2 hydrate for 5.6-8.0 mm particle diameter.
Discussion is made on the influence of sucrose on the dissociation of
CO2 hydrate and the resulting formation of ice.
Abstract: The paper contains a review of the literature in terms of the critical analysis of methodologies of university ranking systems. Furthermore, the initiatives supported by the European Commission (U-Map, U-Multirank) and CHE Ranking are described. Special attention is paid to the tendencies in the development of ranking systems. According to the author, the ranking organizations should abandon the classic form of ranking, namely a hierarchical ordering of universities from “the best" to “the worse". In the empirical part of this paper, using one of the method of cluster analysis called k-means clustering, the author presents university classifications of the top universities from the Shanghai Jiao Tong University-s (SJTU) Academic Ranking of World Universities (ARWU).
Abstract: In this paper a class of numerical methods to solve linear and nonlinear PDEs and also systems of PDEs is developed. The Differential Transform method associated with the Method of Lines (MoL) is used. The theory for linear problems is extended to the nonlinear case, and a recurrence relation is established. This method can achieve an arbitrary high-order accuracy in time. A variable stepsize algorithm and some numerical results are also presented.
Abstract: We develop new nonlinear methods of
immunofluorescence analysis for a sensitive technology of
respiratory burst reaction of DNA fluorescence due to oxidative
activity in the peripheral blood neutrophils. Histograms in flow
cytometry experiments represent a fluorescence flashes frequency as
functions of fluorescence intensity. We used the Shannon-Weaver
index for definition of neutrophils- biodiversity and Hurst index for
definition of fractal-s correlations in immunofluorescence for
different donors, as the basic quantitative criteria for medical
diagnostics of health status. We analyze frequencies of flashes,
information, Shannon entropies and their fractals in
immunofluorescence networks due to reduction of histogram range.
We found the number of simplest universal correlations for
biodiversity, information and Hurst index in diagnostics and
classification of pathologies for wide spectra of diseases. In addition
is determined the clear criterion of a common immunity and human
health status in a form of yes/no answers type. These answers based
on peculiarities of information in immunofluorescence networks and
biodiversity of neutrophils. Experimental data analysis has shown the
existence of homeostasis for information entropy in oxidative activity
of DNA in neutrophil nuclei for all donors.
Abstract: The inherent complexity in nowadays- business
environments is forcing organizations to be attentive to the dynamics
in several fronts. Therefore, the management of technological
innovation is continually faced with uncertainty about the future.
These issues lead to a need for a systemic perspective, able to analyze
the consequences of interactions between different factors. The field
of technology foresight has proposed methods and tools to deal with
this broader perspective. In an attempt to provide a method to analyze
the complex interactions between events in several areas, departing
from the identification of the most strategic competencies, this paper
presents a methodology based on the Delphi method and Quality
Function Deployment. This methodology is applied in a sheet metal
processing equipment manufacturer, as a case study.
Abstract: This study proposes a novel recommender system to
provide the advertisements of context-aware services. Our proposed
model is designed to apply a modified collaborative filtering (CF)
algorithm with regard to the several dimensions for the personalization
of mobile devices – location, time and the user-s needs type. In
particular, we employ a classification rule to understand user-s needs
type using a decision tree algorithm. In addition, we collect primary
data from the mobile phone users and apply them to the proposed
model to validate its effectiveness. Experimental results show that the
proposed system makes more accurate and satisfactory advertisements
than comparative systems.
Abstract: Olomouc is a unique and complex landmark with
widespread forestation and land use. This research work was
conducted to assess important and complex land use change
trajectories in Olomouc region. Multi-temporal satellite data from
1991, 2001 and 2013 were used to extract land use/cover types by
object oriented classification method. To achieve the objectives, three
different aspects were used: (1) Calculate the quantity of each
transition; (2) Allocate location based landscape pattern (3) Compare
land use/cover evaluation procedure. Land cover change trajectories
shows that 16.69% agriculture, 54.33% forest and 21.98% other areas
(settlement, pasture and water-body) were stable in all three decade.
Approximately 30% of the study area maintained as a same land cove
type from 1991 to 2013. Here broad scale of political and socioeconomic
factors was also affect the rate and direction of landscape
changes. Distance from the settlements was the most important
predictor of land cover change trajectories. This showed that most of
landscape trajectories were caused by socio-economic activities and
mainly led to virtuous change on the ecological environment.
Abstract: This paper explains how mobile learning assures sustainable e-education for multicultural group of students. This paper reports the impact of mobile learning on distance education in multicultural environment. The emergence of learning technologies through CD, internet, and mobile is increasingly adopted by distance institutes for quick delivery and cost-effective purposes. Their sustainability is conditioned by the structure of learners as well as the teaching community. The experimental study was conducted among the distant learners of Vinayaka Missions University located at Salem in India. Students were drawn from multicultural environment based on different languages, religions, class and communities. During the mobile learning sessions, the students, who are divided on language, religion, class and community, were dominated by play impulse rather than study anxiety or cultural inhibitions. This study confirmed that mobile learning improved the performance of the students despite their division based on region, language or culture. In other words, technology was able to transcend the relative deprivation in the multicultural groups. It also confirms sustainable e-education through mobile learning and cost-effective system of instruction. Mobile learning appropriates the self-motivation and play impulse of the young learners in providing sustainable e-education to multicultural social groups of students.
Abstract: A sequential decision problem, based on the task ofidentifying the species of trees given acoustic echo data collectedfrom them, is considered with well-known stochastic classifiers,including single and mixture Gaussian models. Echoes are processedwith a preprocessing stage based on a model of mammalian cochlearfiltering, using a new discrete low-pass filter characteristic. Stoppingtime performance of the sequential decision process is evaluated andcompared. It is observed that the new low pass filter processingresults in faster sequential decisions.
Abstract: In this paper, a fiber based Fabry-Perot interferometer
is proposed and demonstrated for a non-contact displacement
measurement. A piece of micro-prism which attached to the
mechanical vibrator is served as the target reflector. Interference
signal is generated from the superposition between the sensing beam
and the reference beam within the sensing arm of the fiber sensor.
This signal is then converted to the displacement value by using a
developed program written in visual Cµ programming with a
resolution of λ/8. A classical function generator is operated for
controlling the vibrator. By fixing an excitation frequency of 100 Hz
and varying the excitation amplitude range of 0.1 – 3 Volts, the
output displacements measured by the fiber sensor are obtained from
1.55 μm to 30.225 μm. A reference displacement sensor with a
sensitivity of ~0.4 μm is also employed for comparing the
displacement errors between both sensors. We found that over the
entire displacement range, a maximum and average measurement
error are obtained of 0.977% and 0.44% respectively.
Abstract: This work presents an approach for the construction of a hybrid color-texture space by using mutual information. Feature extraction is done by the Laws filter with SVM (Support Vectors Machine) as a classifier. The classification is applied on the VisTex database and a SPOT HRV (XS) image representing two forest areas in the region of Rabat in Morocco. The result of classification obtained in the hybrid space is compared with the one obtained in the RGB color space.
Abstract: In this work, I present a review on Sparse Distributed
Memory for Small Cues (SDMSCue), a variant of Sparse Distributed
Memory (SDM) that is capable of handling small cues. I then conduct
and show some cognitive experiments on SDMSCue to test its
cognitive soundness compared to SDM. Small cues refer to input
cues that are presented to memory for reading associations; but have
many missing parts or fields from them. The original SDM failed to
handle such a problem. SDMSCue handles and overcomes this
pitfall. The main idea in SDMSCue; is the repeated projection of the
semantic space on smaller subspaces; that are selected based on the
input cue length and pattern. This process allows for Read/Write
operations using an input cue that is missing a large portion.
SDMSCue is augmented with the use of genetic algorithms for
memory allocation and initialization. I claim that SDM functionality
is a subset of SDMSCue functionality.
Abstract: Electronics Products that achieve high levels of integrated communications, computing and entertainment, multimedia features in small, stylish and robust new form factors are winning in the market place. Due to the high costs that an industry may undergo and how a high yield is directly proportional to high profits, IC (Integrated Circuit) manufacturers struggle to maximize yield, but today-s customers demand miniaturization, low costs, high performance and excellent reliability making the yield maximization a never ending research of an enhanced assembly process. With factors such as minimum tolerances, tighter parameter variations a systematic approach is needed in order to predict the assembly process. In order to evaluate the quality of upcoming circuits, yield models are used which not only predict manufacturing costs but also provide vital information in order to ease the process of correction when the yields fall below expectations. For an IC manufacturer to obtain higher assembly yields all factors such as boards, placement, components, the material from which the components are made of and processes must be taken into consideration. Effective placement yield depends heavily on machine accuracy and the vision of the system which needs the ability to recognize the features on the board and component to place the device accurately on the pads and bumps of the PCB. There are currently two methods for accurate positioning, using the edge of the package and using solder ball locations also called footprints. The only assumption that a yield model makes is that all boards and devices are completely functional. This paper will focus on the Monte Carlo method which consists in a class of computational algorithms (information processed algorithms) which depends on repeated random samplings in order to compute the results. This method utilized in order to recreate the simulation of placement and assembly processes within a production line.