Abstract: The special constraints of sensor networks impose a
number of technical challenges for employing them. In this review,
we study the issues and existing protocols in three areas: coverage
and routing. We present two types of coverage problems: to
determine the minimum number of sensor nodes that need to perform
active sensing in order to monitor a certain area; and to decide the
quality of service that can be provided by a given sensor network.
While most routing protocols in sensor networks are data-centric,
there are other types of routing protocols as well, such as
hierarchical, location-based, and QoS-aware. We describe and
compare several protocols in each group. We present several multipath
routing protocols and single-path with local repair routing
protocols, which are proposed for recovering from sensor node
crashes. We also discuss some transport layer schemes for reliable
data transmission in lossy wireless channels.
Abstract: At any point of time, a power system operating
condition should be stable, meeting various operational criteria and it
should also be secure in the event of any credible contingency. Present
day power systems are being operated closer to their stability limits
due to economic and environmental constraints. Maintaining a stable
and secure operation of a power system is therefore a very important
and challenging issue. Voltage instability has been given much
attention by power system researchers and planners in recent years,
and is being regarded as one of the major sources of power system
insecurity. Voltage instability phenomena are the ones in which the
receiving end voltage decreases well below its normal value and does
not come back even after setting restoring mechanisms such as VAR
compensators, or continues to oscillate for lack of damping against the
disturbances. Reactive power limit of power system is one of the major
causes of voltage instability. This paper investigates the effects of
coordinated series capacitors (SC) with static VAR compensators
(SVC) on steady-state voltage stability of a power system. Also, the
influence of the presence of series capacitor on static VAR
compensator controller parameters and ratings required to stabilize
load voltages at certain values are highlighted.
Abstract: Anaerobic Digestion has become a promising
technology for biological transformation of organic fraction of the
municipal solid wastes (MSW). In order to represent the kinetic
behavior of such biological process and thereby to design a reactor
system, development of a mathematical model is essential.
Addressing this issue, a simplistic mathematical model has been
developed for anaerobic digestion of MSW in a continuous flow
reactor unit under homogeneous steady state condition. Upon
simulated hydrolysis, the kinetics of biomass growth and substrate
utilization rate are assumed to follow first order reaction kinetics.
Simulation of this model has been conducted by studying sensitivity
of various process variables. The model was simulated using typical
kinetic data of anaerobic digestion MSW and typical MSW
characteristics of Kolkata. The hydraulic retention time (HRT) and
solid retention time (SRT) time were mainly estimated by varying
different model parameters like efficiency of reactor, influent
substrate concentration and biomass concentration. Consequently,
design table and charts have also been prepared for ready use in the
actual plant operation.
Abstract: The Connection Admission Control (CAC) problem is formulated in this paper as a discrete time optimal control problem. The control variables account for the acceptance/ rejection of new connections and forced dropping of in-progress connections. These variables are constrained to meet suitable conditions which account for the QoS requirements (Link Availability, Blocking Probability, Dropping Probability). The performance index evaluates the total throughput. At each discrete time, the problem is solved as an integer-valued linear programming one. The proposed procedure was successfully tested against suitably simulated data.
Abstract: This paper presents parametric probability density
models for call holding times (CHTs) into emergency call center
based on the actual data collected for over a week in the public
Emergency Information Network (EIN) in Mongolia. When the set of
chosen candidates of Gamma distribution family is fitted to the call
holding time data, it is observed that the whole area in the CHT
empirical histogram is underestimated due to spikes of higher
probability and long tails of lower probability in the histogram.
Therefore, we provide the Gaussian parametric model of a mixture of
lognormal distributions with explicit analytical expressions for the
modeling of CHTs of PSNs. Finally, we show that the CHTs for
PSNs are fitted reasonably by a mixture of lognormal distributions
via the simulation of expectation maximization algorithm. This result
is significant as it expresses a useful mathematical tool in an explicit
manner of a mixture of lognormal distributions.
Abstract: In this paper a combined feature selection method is
proposed which takes advantages of sample domain filtering,
resampling and feature subset evaluation methods to reduce
dimensions of huge datasets and select reliable features. This method
utilizes both feature space and sample domain to improve the process
of feature selection and uses a combination of Chi squared with
Consistency attribute evaluation methods to seek reliable features.
This method consists of two phases. The first phase filters and
resamples the sample domain and the second phase adopts a hybrid
procedure to find the optimal feature space by applying Chi squared,
Consistency subset evaluation methods and genetic search.
Experiments on various sized datasets from UCI Repository of
Machine Learning databases show that the performance of five
classifiers (Naïve Bayes, Logistic, Multilayer Perceptron, Best First
Decision Tree and JRIP) improves simultaneously and the
classification error for these classifiers decreases considerably. The
experiments also show that this method outperforms other feature
selection methods.
Abstract: Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.
Abstract: Land use change, if not based on proper scientific
investigation affects other physical, chemical, and biological
properties of soil and leading to increased destruction and erosion. It
was imperative to study the effects of changing rangelands to
farmlands on some Soil quality indexes. Undisturbed soil samples
were collected from the depths of 0-10 and 10-30 centimeter in
pasture with good vegetation cover(GP), pasture with medium
vegetation cover(MP), abandoned dry land farming(ADF) and
degraded dry land farming(DDF) land uses in Ghareh Aghaj
watershed of Isfahan province. The results revealed that organic
matter(OM), cation exchange capacity(CEC) and available
potassium(AK) decreasing in the depth of 0-10 centimeter were 66.6,
38.8 and 70 percent and in the depth of 10-30 centimeter were 58,
61.4 and 83.5 percent respectively in DDF comparison with GP.
Concerning to the results, it seems that land use change can decrease
soil quality and increase soil degradation and lead in undesirable
consequences.
Abstract: World has entered in 21st century. The technology of
computer graphics and digital cameras is prevalent. High resolution
display and printer are available. Therefore high resolution images
are needed in order to produce high quality display images and high
quality prints. However, since high resolution images are not usually
provided, there is a need to magnify the original images. One
common difficulty in the previous magnification techniques is that of
preserving details, i.e. edges and at the same time smoothing the data
for not introducing the spurious artefacts. A definitive solution to this
is still an open issue. In this paper an image magnification using
adaptive interpolation by pixel level data-dependent geometrical
shapes is proposed that tries to take into account information about
the edges (sharp luminance variations) and smoothness of the image.
It calculate threshold, classify interpolation region in the form of
geometrical shapes and then assign suitable values inside
interpolation region to the undefined pixels while preserving the
sharp luminance variations and smoothness at the same time.
The results of proposed technique has been compared qualitatively
and quantitatively with five other techniques. In which the qualitative
results show that the proposed method beats completely the Nearest
Neighbouring (NN), bilinear(BL) and bicubic(BC) interpolation. The
quantitative results are competitive and consistent with NN, BL, BC
and others.
Abstract: This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for an unmanned aerial vehicle (UAV). Autonomous vertical flight is a challenging but important task for tactical UAVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a two stage flight control procedure using two autonomous control subsystems to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for a nontrivial nonlinear trirotor mini-UAV model. This control strategy for chosen mini-UAV model has been verified by simulation of hovering maneuvers using software package Simulink and demonstrated good performance for fast SA in realtime search-and-rescue operations.
Abstract: The shortest path question is in a graph theory model
question, and it is applied in many fields. The most short-path
question may divide into two kinds: Single sources most short-path,
all apexes to most short-path. This article mainly introduces the
problem of all apexes to most short-path, and gives a new parallel
algorithm of all apexes to most short-path according to the Dijkstra
algorithm. At last this paper realizes the parallel algorithms in the
technology of C # multithreading.
Abstract: The aim of the study was to investigate phytochemical
properties, antimicrobial activity and cytotoxicity of Aloe vera. The
phytochemical screening of the extracts of leaves of A. vera revealed
the presence of bioactive compounds such as alkaloids, tannins,
flavonoids phenolic compounds, and etc. with absence of cyanogenic
glycosides. Three different solvents such as methanol, ethanol and
Di-Methyl sulfoxide were used to screen the antimicrobial activity of
A. vera leaves against four human clinical pathogens by agar well
diffusion method. The maximum antibacterial activities were
observed in methanol extract followed by ethanol and Di-Methyl
sulfoxide. It was also found that remarkable antibacterial activities
with methanolic and ethanolic extracts of A. vera compared with the
standard antibiotic, tetracycline that was not active against E. coli
and S. boydii and supported the view that A. vera is a potent
antimicrobial agent compared with the conventional antibiotic.
Moreover, the brine shrimps (Artemia salina) toxicity test exhibited
LC50 value was 569.52 ppm. The resulting data indicated that the A.
vera plant have less toxic effects on brine shrimp. Hence, it is
signified that Aloe vera plant extract is safe to be used as an
antimicrobial agent.
Abstract: Many new experimental films which were free from conventional movie forms have appeared since Nubellbak Movement in the late 1950s. Forty years after the movement started, on March 13th, 1995, on the 100th anniversary of the birth of film, the declaration called Dogme 95, was issued in Copenhagen, Denmark. It aimed to create a new style of avant-garde film, and showed a tendency toward being anti-Hollywood and anti-genre, which were against the highly popular Hollywood trend of movies based on large-scale investment. The main idea of Dogme 95 is the opposition to 'the writer's doctrine' that a film should be the artist's individual work and to 'the overuse of technology' in film. The key figures declared ten principles called 'Vow of Chastity', by which new movie forms were to be produced. Interview (2000), directed by Byunhyuk, was made in 2000, five years after Dogme 95 was declared. This movie was dedicated as the first Asian Dogme. This study will survey the relationship between Korean film and the Vow of Chastity through the Korean films released in theaters from a viewpoint of technology and content. It also will call attention to its effects on and significance to Korean film in modern society.
Abstract: This paper introduces an automatic voice classification
system for the diagnosis of individual constitution based on Sasang
Constitutional Medicine (SCM) in Traditional Korean Medicine
(TKM). For the developing of this algorithm, we used the voices of
309 female speakers and extracted a total of 134 speech features from
the voice data consisting of 5 sustained vowels and one sentence. The
classification system, based on a rule-based algorithm that is derived
from a non parametric statistical method, presents 3 types of decisions:
reserved, positive and negative decisions. In conclusion, 71.5% of the
voice data were diagnosed by this system, of which 47.7% were
correct positive decisions and 69.7% were correct negative decisions.
Abstract: Many firms implemented various initiatives such as outsourced manufacturing which could make a supply chain (SC) more vulnerable to various types of disruptions. So managing risk has become a critical component of SC management. Different types of SC vulnerability management methodologies have been proposed for managing SC risk, most offer only point-based solutions that deal with a limited set of risks. This research aims to reinforce SC risk management by proposing an integrated approach. SC risks are identified and a risk index classification structure is created. Then we develop a SC risk assessment approach based on the analytic network process (ANP) and the VIKOR methods under the fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by triangular fuzzy numbers. By using FANP, risks weights are calculated and then inserted to the FVIKOR to rank the SC members and find the most risky partner.
Abstract: Two algorithms are proposed to reduce the storage requirements for mammogram images. The input image goes through a shrinking process that converts the 16-bit images to 8-bits by using pixel-depth conversion algorithm followed by enhancement process. The performance of the algorithms is evaluated objectively and subjectively. A 50% reduction in size is obtained with no loss of significant data at the breast region.
Abstract: In this paper, the Tabu search algorithm is used to
solve a transportation problem which consists of determining the
shortest routes with the appropriate vehicle capacity to facilitate the
travel of the students attending the University of Mauritius. The aim
of this work is to minimize the total cost of the distance travelled by
the vehicles in serving all the customers. An initial solution is
obtained by the TOUR algorithm which basically constructs a giant
tour containing all the customers and partitions it in an optimal way
so as to produce a set of feasible routes. The Tabu search algorithm
then makes use of a search procedure, a swapping procedure and the
intensification and diversification mechanism to find the best set of
feasible routes.
Abstract: The essence of the 21st century is knowledge economy. Knowledge has become the key resource of economic growth and social development. Construction industry is no exception. Because of the characteristic of complexity, project manager can't depend only on information management. The only way to improve the level of construction project management is to set up a kind of effective knowledge accumulation mechanism. This paper first introduced the IFC standard and the concept of ontology. Then put forward the construction method of the architectural engineering domain ontology based on IFC. And finally build up the concepts, properties and the relationship between the concepts of the ontology. The deficiency of this paper is also pointed out.
Abstract: Recommender systems are usually regarded as an
important marketing tool in the e-commerce. They use important
information about users to facilitate accurate recommendation. The
information includes user context such as location, time and interest
for personalization of mobile users. We can easily collect information
about location and time because mobile devices communicate with the
base station of the service provider. However, information about user
interest can-t be easily collected because user interest can not be
captured automatically without user-s approval process. User interest
usually represented as a need. In this study, we classify needs into two
types according to prior research. This study investigates the
usefulness of data mining techniques for classifying user need type for
recommendation systems. We employ several data mining techniques
including artificial neural networks, decision trees, case-based
reasoning, and multivariate discriminant analysis. Experimental
results show that CHAID algorithm outperforms other models for
classifying user need type. This study performs McNemar test to
examine the statistical significance of the differences of classification
results. The results of McNemar test also show that CHAID performs
better than the other models with statistical significance.
Abstract: We have developed an energy based approach for identifying the binding sites and important residues for binding in protein-protein complexes. We found that the residues and residuepairs with charged and aromatic side chains are important for binding. These residues influence to form cation-¤Ç, electrostatic and aromatic interactions. Our observation has been verified with the experimental binding specificity of protein-protein complexes and found good agreement with experiments. The analysis on surrounding hydrophobicity reveals that the binding residues are less hydrophobic than non-binding sites, which suggests that the hydrophobic core are important for folding and stability whereas the surface seeking residues play a critical role in binding. Further, the propensity of residues in the binding sites of receptors and ligands, number of medium and long-range contacts, and influence of neighboring residues will be discussed.