Abstract: In this paper, we aim to investigate a new stability analysis for discrete-time switched linear systems based on the comparison, the overvaluing principle, the application of Borne-Gentina criterion and the Kotelyanski conditions. This stability conditions issued from vector norms correspond to a vector Lyapunov function. In fact, the switched system to be controlled will be represented in the Companion form. A comparison system relative to a regular vector norm is used in order to get the simple arrow form of the state matrix that yields to a suitable use of Borne-Gentina criterion for the establishment of sufficient conditions for global asymptotic stability. This proposed approach could be a constructive solution to the state and static output feedback stabilization problems.
Abstract: Malate dehydrogenase-glutamate oxaloacetate
aminotransferase (MDh-GOAT) enzyme complex (the EC) was
isolated and purified from wheat and rise, their some main physicchemical
properties were studied. Michael-s constants of the EC
MDh-GOAT to malate, glutamate and NAD were investigated. This
kinetic results show a high relationship to glutamate. Taking into
account important role of the the EC in catabolism of glutamate – the
central amino acid of a nitric exchange, there is a sharp necessity of
deeper studying of this enzyme complex. Therefore the basic purpose
of the work is studying the basic physical and chemical properties of
this enzyme complex discovered by us, which would be very
important for understanding the mechanisms of reaction catalyzed by
the EC.
Abstract: The UK Government has emphasized the role of Local Authorities as a key player in its flagship residential energy efficiency strategies, by identifying and targeting areas for energy efficiency improvements. Residential energy consumption in England is characterized by significant geographical variation in energy demand, which makes centralized targeting of areas for energy efficiency intervention difficult. This paper draws on research which aims to understand how demographic, social, economic, urban form and climatic factors influence the geographical variations in English residential gas consumption. The paper reports the findings of a multiple regression model that shows how 64% of the geographical variation in residential gas consumption is accounted for by variations in these factors. Results from this study, after further refinement and validation, can be used by Local Authorities to identify areas within their boundaries that have higher than expected gas consumption, these may be prime targets for energy efficiency initiatives.
Abstract: In this paper we compare the response of linear and
nonlinear neural network-based prediction schemes in prediction of
received Signal-to-Interference Power Ratio (SIR) in Direct
Sequence Code Division Multiple Access (DS/CDMA) systems. The
nonlinear predictor is Multilayer Perceptron MLP and the linear
predictor is an Adaptive Linear (Adaline) predictor. We solve the
problem of complexity by using the Minimum Mean Squared Error
(MMSE) principle to select the optimal predictors. The optimized
Adaline predictor is compared to optimized MLP by employing
noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an
urban environment. The results show that the Adaline predictor can
estimates SIR with the same error as MLP when the user has the
velocity of 5 km/h and 60 km/h but by increasing the velocity up-to
120 km/h the mean squared error of MLP is two times more than
Adaline predictor. This makes the Adaline predictor (with lower
complexity) more suitable than MLP for closed-loop power control
where efficient and accurate identification of the time-varying
inverse dynamics of the multi path fading channel is required.
Abstract: In this paper we designed and implemented a new
ensemble of classifiers based on a sequence of classifiers which were
specialized in regions of the training dataset where errors of its
trained homologous are concentrated. In order to separate this
regions, and to determine the aptitude of each classifier to properly
respond to a new case, it was used another set of classifiers built
hierarchically. We explored a selection based variant to combine the
base classifiers. We validated this model with different base
classifiers using 37 training datasets. It was carried out a statistical
comparison of these models with the well known Bagging and
Boosting, obtaining significantly superior results with the
hierarchical ensemble using Multilayer Perceptron as base classifier.
Therefore, we demonstrated the efficacy of the proposed ensemble,
as well as its applicability to general problems.
Abstract: Abstract–Indoor air (VOCs) samples were collected
simultaneously from variety of indoors (e.g. living rooms, baby-s
rooms) and outdoor environments which were voluntarily selected
from the houses in which pregnant residents live throughout Ankara.
This is the first comprehensive study done in Turkey starting from
prenatal period and continued till the babies had one year old. VOCs
levels were measured over 76 homes. Air samples were collected in
Tenax TA sorbent filled tubes with active sampling method and
analyzed with Thermal Desorber and Gas Chromatography/Mass
spectrometry (TD-GC/MS). At the first sampling period in the baby-s
rooms maximum concentration of toluene was measured about
240.77μg.m-3 and in the living rooms maximum concentration of
naphthalene was 180.24μg.m-3. At the second sampling period in the
baby-s rooms maximum concentration of toluene was measured
about 144.97μg.m-3 and in the living rooms maximum concentration
of naphthalene was 247.89μg.m-3. Concentration of TVOCs in the
first period was generally higher than the second period.
Abstract: This paper presents the simulation results of electric field and potential distributions along surface of silicone rubber polymer insulators under clean and various contamination conditions with/without water droplets. Straight sheds insulator having leakage distance 290 mm was used in this study. Two type of contaminants, playwood dust and cement dust, have been studied the effect of contamination on the insulator surface. The objective of this work is to comparison the effect of contamination on potential and electric field distributions along the insulator surface when water droplets exist on the insulator surface. Finite element method (FEM) is adopted for this work. The simulation results show that contaminations have no effect on potential distribution along the insulator surface while electric field distributions are obviously depended on contamination conditions.
Abstract: Recycling of aluminum alloys often decrease fluidity,
consequently influence the castability of the alloy. In this study, the
fluidity of Al-Zn alloys, such as the standard A713 alloy with and
without scrap addition has been investigated. The scrap added was
comprised of contaminated alloy turning chips. Fluidity
measurements were performed with double spiral fluidity test
consisting of gravity casting of double spirals in green sand moulds
with good reproducibility. The influence of recycled alloy on fluidity
has been compared with that of the virgin alloy and the results
showed that the fluidity decreased with the increase in recycled alloy
at minimum pouring temperatures. Interestingly, an appreciable
improvement in the fluidity was observed at maximum pouring
temperature, especially for coated spirals.
Abstract: The objective of this study is to design an adaptive
neuro-fuzzy inference system (ANFIS) for estimation of surface
roughness in grinding process. The Used data have been generated
from experimental observations when the wheel has been dressed
using a rotary diamond disc dresser. The input parameters of model
are dressing speed ratio, dressing depth and dresser cross-feed rate
and output parameter is surface roughness. In the experimental
procedure the grinding conditions are constant and only the dressing
conditions are varied. The comparison of the predicted values and the
experimental data indicates that the ANFIS model has a better
performance with respect to back-propagation neural network
(BPNN) model which has been presented by the authors in previous
work for estimation of the surface roughness.
Abstract: Land degradation is of concern in many countries. People more and more must address the problems associated with the degradation of soil properties due to man. Increasingly, organic soil amendments, such as compost are being examined for their potential use in soil restoration and for preventing soil erosion. In the Czech Republic, compost is the most used to improve soil structure and increase the content of soil organic matter. Land reclamation / restoration is one of the ways to evaluate industrially produced compost because Czech farmers are not willing to use compost as organic fertilizer. The most common use of reclamation substrates in the Czech Republic is for the rehabilitation of landfills and contaminated sites.
This paper deals with the influence of reclamation substrates (RS) with different proportions of compost and sand on selected soil properties–chemical characteristics, nitrogen bioavailability, leaching of mineral nitrogen, respiration activity and plant biomass production. Chemical properties vary proportionally with addition of compost and sand to the control variant (topsoil). The highest differences between the variants were recorded in leaching of mineral nitrogen (varies from 1.36mg dm-3 in C to 9.09mg dm-3). Addition of compost to soil improves conditions for plant growth in comparison with soil alone. However, too high addition of compost may have adverse effects on plant growth. In addition, high proportion of compost increases leaching of mineral N. Therefore, mixture of 70% of soil with 10% of compost and 20% of sand may be recommended as optimal composition of RS.
Abstract: Recently, information security has become a key issue
in information technology as the number of computer security
breaches are exposed to an increasing number of security threats. A
variety of intrusion detection systems (IDS) have been employed for
protecting computers and networks from malicious network-based or
host-based attacks by using traditional statistical methods to new data
mining approaches in last decades. However, today's commercially
available intrusion detection systems are signature-based that are not
capable of detecting unknown attacks. In this paper, we present a
new learning algorithm for anomaly based network intrusion
detection system using decision tree algorithm that distinguishes
attacks from normal behaviors and identifies different types of
intrusions. Experimental results on the KDD99 benchmark network
intrusion detection dataset demonstrate that the proposed learning
algorithm achieved 98% detection rate (DR) in comparison with
other existing methods.
Abstract: The main aim of this work is to establish the
capabilities of new green buildings to ascertain off-grid electricity
generation based on the integration of wind turbines in the
conceptual model of a rotating tower [2] in Dubai. An in depth
performance analysis of the WinWind 3.0MW [3] wind turbine is
performed. Data based on the Dubai Meteorological Services is
collected and analyzed in conjunction with the performance analysis
of this wind turbine. The mathematical model is compared with
Computational Fluid Dynamics (CFD) results based on a conceptual
rotating tower design model. The comparison results are further
validated and verified for accuracy by conducting experiments on a
scaled prototype of the tower design. The study concluded that
integrating wind turbines inside a rotating tower can generate enough
electricity to meet the required power consumption of the building,
which equates to a wind farm containing 9 horizontal axis wind
turbines located at an approximate area of 3,237,485 m2 [14].
Abstract: A fusion classifier composed of two modules, one made by a hidden Markov model (HMM) and the other by a support vector machine (SVM), is proposed to recognize faces with pose variations in open-set recognition settings. The HMM module captures the evolution of facial features across a subject-s face using the subject-s facial images only, without referencing to the faces of others. Because of the captured evolutionary process of facial features, the HMM module retains certain robustness against pose variations, yielding low false rejection rates (FRR) for recognizing faces across poses. This is, however, on the price of poor false acceptance rates (FAR) when recognizing other faces because it is built upon withinclass samples only. The SVM module in the proposed model is developed following a special design able to substantially diminish the FAR and further lower down the FRR. The proposed fusion classifier has been evaluated in performance using the CMU PIE database, and proven effective for open-set face recognition with pose variations. Experiments have also shown that it outperforms the face classifier made by HMM or SVM alone.
Abstract: There are some existing Java benchmarks, application benchmarks as well as micro benchmarks or mixture both of them,such as: Java Grande, Spec98, CaffeMark, HBech, etc. But none of them deal with behaviors of multi tasks operating systems. As a result, the achieved outputs are not satisfied for performance evaluation engineers. Behaviors of multi tasks operating systems are based on a schedule management which is employed in these systems. Different processes can have different priority to share the same resources. The time is measured by estimating from applications started to it is finished does not reflect the real time value which the system need for running those programs. New approach to this problem should be done. Having said that, in this paper we present a new Java benchmark, named FHOJ benchmark, which directly deals with multi tasks behaviors of a system. Our study shows that in some cases, results from FHOJ benchmark are far more reliable in comparison with some existing Java benchmarks.
Abstract: In this paper, the order, size and degree of the nodes
of the isomorphic fuzzy graphs are discussed. Isomorphism between
fuzzy graphs is proved to be an equivalence relation. Some properties
of self complementary and self weak complementary fuzzy graphs
are discussed.
Abstract: The aim of this study was to screen for
microorganism that able to utilize 3-N-trimethylamino-1-propanol
(homocholine) as a sole source of carbon and nitrogen. The aerobic
degradation of homocholine has been found by a gram-positive
Rhodococcus sp. bacterium isolated from soil. The isolate was
identified as Rhodococcus sp. strain A4 based on the phenotypic
features, physiologic and biochemical characteristics, and
phylogenetic analysis. The cells of the isolated strain grown on both
basal-TMAP and nutrient agar medium displayed elementary
branching mycelia fragmented into irregular rod and coccoid
elements. Comparative 16S rDNA sequencing studies indicated that
the strain A4 falls into the Rhodococcus erythropolis subclade and
forms a monophyletic group with the type-strains of R. opacus, and
R. wratislaviensis. Metabolites analysis by capillary electrophoresis,
fast atom bombardment-mass spectrometry, and gas
chromatography- mass spectrometry, showed trimethylamine (TMA)
as the major metabolite beside β-alanine betaine and
trimethylaminopropionaldehyde. Therefore, the possible degradation
pathway of trimethylamino propanol in the isolated strain is through
consequence oxidation of alcohol group (-OH) to aldehyde (-CHO)
and acid (-COOH), and thereafter the cleavage of β-alanine betaine
C-N bonds yielded trimethylamine and alkyl chain.
Abstract: While OCD is one of the most commonly occurring
psychiatric conditions experienced by older adults, there is a paucity
of research conducted into the treatment of older adults with OCD.
This case study represents the first published investigation of a
cognitive treatment for geriatric OCD. It describes the successful
treatment of an 86-year old man with a 63-year history of OCD using
Danger Ideation Reduction Therapy (DIRT). The client received 14
individual, 50-minute treatment sessions of DIRT over 13 weeks.
Clinician-based Y-BOCS scores reduced 84% from 25 (severe) at
pre-treatment, to 4 (subclinical) at 6-month post-treatment follow-up
interview, demonstrating the efficacy of DIRT for this client. DIRT
may have particular advantages over ERP and pharmacological
approaches, however further research is required in older adults with
OCD.
Abstract: Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.
Abstract: In this paper, acoustic techniques are used to detect hidden insect infestations of date palm tress (Phoenix dactylifera L.). In particular, we use an acoustic instrument for early discovery of the presence of a destructive insect pest commonly known as the Red Date Palm Weevil (RDPW) and scientifically as Rhynchophorus ferrugineus (Olivier). This type of insect attacks date palm tress and causes irreversible damages at late stages. As a result, the infected trees must be destroyed. Therefore, early presence detection is a major part in controlling the spread and economic damage caused by this type of infestation. Furthermore monitoring and early detection of the disease can asses in taking appropriate measures such as isolating or treating the infected trees. The acoustic system is evaluated in terms of its ability for early discovery of hidden bests inside the tested tree. When signal acquisitions is completed for a number of date palms, a signal processing technique known as time-frequency analysis is evaluated in terms of providing an estimate that can be visually used to recognize the acoustic signature of the RDPW. The testing instrument was tested in the laboratory first then; it was used on suspected or infested tress in the field. The final results indicate that the acoustic monitoring approach along with signal processing techniques are very promising for the early detection of presence of the larva as well as the adult pest in the date palms.
Abstract: Modeling transfer phenomena in several chemical
engineering operations leads to the resolution of partial differential
equations systems. According to the complexity of the operations
mechanisms, the equations present a nonlinear form and analytical
solution became difficult, we have then to use numerical methods
which are based on approximations in order to transform a
differential system to an algebraic one.Finite element method is one
of numerical methods which can be used to obtain an accurate
solution in many complex cases of chemical engineering.The packed
columns find a large application like contactor for liquid-liquid
systems such solvent extraction. In the literature, the modeling of this
type of equipment received less attention in comparison with the
plate columns.A mathematical bidimensionnal model with radial and
axial dispersion, simulating packed tower extraction behavior was
developed and a partial differential equation was solved using the
finite element method by adopting the Galerkine model. We
developed a Mathcad program, which can be used for a similar
equations and concentration profiles are obtained along the column.
The influence of radial dispersion was prooved and it can-t be
neglected, the results were compared with experimental concentration
at the top of the column in the extraction system:
acetone/toluene/water.