Abstract: Ad hoc networks are characterized by multihop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. We compare the performance of three routing protocols for mobile ad hoc networks: Dynamic Source Routing (DSR), Ad Hoc On-Demand Distance Vector Routing (AODV), location-aided routing (LAR1).Our evaluation is based on energy consumption in mobile ad hoc networks. The performance differentials are analyzed using varying network load, mobility, and network size. We simulate protocols with GLOMOSIM simulator. Based on the observations, we make recommendations about when the performance of either protocol can be best.
Abstract: Wheat has a bimodal starch granule population and the dependency of the rate of enzymatic hydrolysis on particle size has been investigated. Ungelatinised wheaten starch granules were separated into two populations by sedimentation and decantation. Particle size was analysed by laser diffraction and morphological characteristics were viewed using SEM. The sedimentation technique though lengthy, gave satisfactory separation of the granules. Samples (10μm and original) were digested with a-amylase using a dialysis model. Granules of 10μm (p10μm. Moreover, the digestion rate was dependent on particle size whereby smaller granules produced higher rate of release. The methodology and results reported here can be used as a basis for further evaluations designed to delay the release of glucose during the digestion of native starches.
Abstract: Semiconductor nanomaterials like TiO2 nanoparticles
(TiO2-NPs) approximately less than 100 nm in diameter have become
a new generation of advanced materials due to their novel and
interesting optical, dielectric, and photo-catalytic properties. With the
increasing use of NPs in commerce, to date few studies have
investigated the toxicological and environmental effects of NPs.
Motivated by the importance of TiO2-NPs that may contribute to the
cancer research field especially from the treatment prospective
together with the fractal analysis technique, we have investigated the
effect of TiO2-NPs on colony morphology in the dark condition
using fractal dimension as a key morphological characterization
parameter. The aim of this work is mainly to investigate the cytotoxic
effects of TiO2-NPs in the dark on the growth of human cervical
carcinoma (HeLa) cell colonies from morphological aspect. The in
vitro studies were carried out together with the image processing
technique and fractal analysis. It was found that, these colonies were
abnormal in shape and size. Moreover, the size of the control
colonies appeared to be larger than those of the treated group. The
mean Df +/- SEM of the colonies in untreated cultures was
1.085±0.019, N= 25, while that of the cultures treated with TiO2-NPs
was 1.287±0.045. It was found that the circularity of the control
group (0.401±0.071) is higher than that of the treated group
(0.103±0.042). The same tendency was found in the diameter
parameters which are 1161.30±219.56 μm and 852.28±206.50 μm
for the control and treated group respectively. Possible explanation of
the results was discussed, though more works need to be done in
terms of the for mechanism aspects. Finally, our results indicate that
fractal dimension can serve as a useful feature, by itself or in
conjunction with other shape features, in the classification of cancer
colonies.
Abstract: Quantitative researching on the degree of incidence between the logistics industry and relevant macroscopic system elements is the basis of reasonable and scientific policy on industrial development. In the light of the macro-level, the logistics industry system is consisted of multiple macroscopic agents such as macro-economic, infrastructure, social environment, market demanding, the traditional industry, industry life cycle, policy , system and so on. This paper studies the grey incidence among the macroscopic agents in the logistics industry system. It is demonstrated that the releasing of the logistics services from the logistics outsourcing enterprises determines the growth of the logistics size. Although the information and communication technology is able to promote the formation of the modern logistics industry to some extent, the development of the modern logistics industry depends more on the development of national economy and the investment in the capital assets of the logistics industry.
Abstract: Generalized Center String (GCS) problem are
generalized from Common Approximate Substring problem
and Common substring problems. GCS are known to be
NP-hard allowing the problems lies in the explosion of
potential candidates. Finding longest center string without
concerning the sequence that may not contain any motifs is
not known in advance in any particular biological gene
process. GCS solved by frequent pattern-mining techniques
and known to be fixed parameter tractable based on the
fixed input sequence length and symbol set size. Efficient
method known as Bpriori algorithms can solve GCS with
reasonable time/space complexities. Bpriori 2 and Bpriori
3-2 algorithm are been proposed of any length and any
positions of all their instances in input sequences. In this
paper, we reduced the time/space complexity of Bpriori
algorithm by Constrained Based Frequent Pattern mining
(CBFP) technique which integrates the idea of Constraint
Based Mining and FP-tree mining. CBFP mining technique
solves the GCS problem works for all center string of any
length, but also for the positions of all their mutated copies
of input sequence. CBFP mining technique construct TRIE
like with FP tree to represent the mutated copies of center
string of any length, along with constraints to restraint
growth of the consensus tree. The complexity analysis for
Constrained Based FP mining technique and Bpriori
algorithm is done based on the worst case and average case
approach. Algorithm's correctness compared with the
Bpriori algorithm using artificial data is shown.
Abstract: A big organization may have multiple branches spread across different locations. Processing of data from these branches becomes a huge task when innumerable transactions take place. Also, branches may be reluctant to forward their data for centralized processing but are ready to pass their association rules. Local mining may also generate a large amount of rules. Further, it is not practically possible for all local data sources to be of the same size. A model is proposed for discovering valid rules from different sized data sources where the valid rules are high weighted rules. These rules can be obtained from the high frequency rules generated from each of the data sources. A data source selection procedure is considered in order to efficiently synthesize rules. Support Equalization is another method proposed which focuses on eliminating low frequency rules at the local sites itself thus reducing the rules by a significant amount.
Abstract: One of the methods for detecting the target position
error in the laser tracking systems is using Four Quadrant (4Q)
detectors. If the coordinates of the target center is yielded through the
usual relations of the detector outputs, the results will be nonlinear,
dependent on the shape, target size and its position on the detector
screen. In this paper we have designed an algorithm with using
neural network that coordinates of the target center in laser tracking
systems is calculated by using detector outputs obtained from visual
modeling. With this method, the results except from the part related
to the detector intrinsic limitation, are linear and dependent from the
shape and target size.
Abstract: This paper aims to fabricated high quality anodic
aluminum oxide (AAO) film by anodization method. AAO pore size,
pore density, and film thickness can be controlled in 10~500 nm,
108~1011 pore．cm-2, and 1~100 μm. AAO volume and surface area can
be computed based on structural parameters such as thickness, pore
size, pore density, and sample size. Base on the thetorical calculation,
AAO has 100 μm thickness with 15 nm, 60 nm, and 500 nm pore
diameters AAO surface areas are 1225.2 cm2, 3204.4 cm2, and 549.7
cm2, respectively. The large unit surface area which is useful for
adsorption application. When AAO adsorbed pH indictor of
bromphenol blue presented a sensitive pH detection of solution
change. This testing method can further be used for the precise
measurement of biotechnology, convenience measurement of
industrial engineering.
Abstract: Graph coloring is an important problem in computer
science and many algorithms are known for obtaining reasonably
good solutions in polynomial time. One method of comparing
different algorithms is to test them on a set of standard graphs where
the optimal solution is already known. This investigation analyzes a
set of 50 well known graph coloring instances according to a set of
complexity measures. These instances come from a variety of
sources some representing actual applications of graph coloring
(register allocation) and others (mycieleski and leighton graphs) that
are theoretically designed to be difficult to solve. The size of the
graphs ranged from ranged from a low of 11 variables to a high of
864 variables. The method used to solve the coloring problem was
the square of the adjacency (i.e., correlation) matrix. The results
show that the most difficult graphs to solve were the leighton and the
queen graphs. Complexity measures such as density, mobility,
deviation from uniform color class size and number of block
diagonal zeros are calculated for each graph. The results showed that
the most difficult problems have low mobility (in the range of .2-.5)
and relatively little deviation from uniform color class size.
Abstract: Simulation of the flow and sedimentation process in
the reservoir dams can be made by two methods of physical and mathematical modeling. The study area was within a region which
ranged from the Jelogir hydrometric station to the Karkheh reservoir
dam aimed at investigating the effects of stream tubes on the
GSTARS-3 model behavior. The methodologies was to run the model based on 5 stream tubes in order to observe the influence of
each scenario on longitudinal profiles, cross-section, flow velocity and bed load sediment size. Results further suggest that the use of
two stream tubes or more which result in the semi-two-dimensional
model will yield relatively closer results to the observational data
than a singular stream tube modeling. Moreover, the results of
modeling with three stream tubes shown to yield a relatively close
results with the observational data. The overall conclusion of the paper is with applying various stream tubes; it would be possible to yield a significant influence on the modeling behavior Vis-a Vis the bed load sediment size.
Abstract: Radiofrequency (RF) lesioning of nerves have been commonly used to alleviate chronic pain, where RF current preventing transmission of pain signals through the nerve by heating the nerve causing the pain. There are some factors that affect the temperature distribution and the nerve lesion size, one of these factors is the inhomogeneities in the tissue medium. Our objective is to calculate the temperature distribution and the nerve lesion size in an inhomogeneous medium surrounding the RF electrode. A two 3-D finite element models are used to compare the temperature distribution in the homogeneous and inhomogeneous medium. Also the effect of temperature-dependent electric conductivity on maximum temperature and lesion size is observed. Results show that the presence of an inhomogeneous medium around the RF electrode has a valuable effect on the temperature distribution and lesion size. The dependency of electric conductivity on tissue temperature increased lesion size.
Abstract: This paper presented a novel combined cycle of air separation and natural gas liquefaction. The idea is that natural gas can be liquefied, meanwhile gaseous or liquid nitrogen and oxygen are produced in one combined cryogenic system. Cycle simulation and exergy analysis were performed to evaluate the process and thereby reveal the influence of the crucial parameter, i.e., flow rate ratio through two stages expanders β on heat transfer temperature difference, its distribution and consequent exergy loss. Composite curves for the combined hot streams (feeding natural gas and recycled nitrogen) and the cold stream showed the degree of optimization available in this process if appropriate β was designed. The results indicated that increasing β reduces temperature difference and exergy loss in heat exchange process. However, the maximum limit value of β should be confined in terms of minimum temperature difference proposed in heat exchanger design standard and heat exchanger size. The optimal βopt under different operation conditions corresponding to the required minimum temperature differences was investigated.
Abstract: How to efficiently assign system resource to route the
Client demand by Gateway servers is a tricky predicament. In this
paper, we tender an enhanced proposal for autonomous recital of
Gateway servers under highly vibrant traffic loads. We devise a
methodology to calculate Queue Length and Waiting Time utilizing
Gateway Server information to reduce response time variance in
presence of bursty traffic.
The most widespread contemplation is performance, because
Gateway Servers must offer cost-effective and high-availability
services in the elongated period, thus they have to be scaled to meet
the expected load. Performance measurements can be the base for
performance modeling and prediction. With the help of performance
models, the performance metrics (like buffer estimation, waiting
time) can be determined at the development process.
This paper describes the possible queue models those can be
applied in the estimation of queue length to estimate the final value
of the memory size. Both simulation and experimental studies using
synthesized workloads and analysis of real-world Gateway Servers
demonstrate the effectiveness of the proposed system.
Abstract: By taking advantage of both k-NN which is highly
accurate and K-means cluster which is able to reduce the time of classification, we can introduce Cluster-k-Nearest Neighbor as "variable k"-NN dealing with the centroid or mean point of all subclasses generated by clustering algorithm. In general the algorithm of K-means cluster is not stable, in term of accuracy, for that reason we develop another algorithm for clustering our space which gives a higher accuracy than K-means cluster, less
subclass number, stability and bounded time of classification with respect to the variable data size. We find between 96% and 99.7 % of accuracy in the lassification of 6 different types of Time series by using K-means cluster algorithm and we find 99.7% by using the new clustering algorithm.
Abstract: Demand over web services is in growing with increases number of Web users. Web service is applied by Web application. Web application size is affected by its user-s requirements and interests. Differential in requirements and interests lead to growing of Web application size. The efficient way to save store spaces for more data and information is achieved by implementing algorithms to compress the contents of Web application documents. This paper introduces an algorithm to reduce Web application size based on reduction of the contents of HTML files. It removes unimportant contents regardless of the HTML file size. The removing is not ignored any character that is predicted in the HTML building process.
Abstract: This paper presents the results of an experimental
investigation carried out to evaluate the shrinkage of High Strength
Concrete. High Strength Concrete is made by partially replacement of
cement by flyash and silica fume. The shrinkage of High Strength
Concrete has been studied using the different types of coarse and fine
aggregates i.e. Sandstone and Granite of 12.5 mm size and Yamuna
and Badarpur Sand. The Mix proportion of concrete is 1:0.8:2.2 with
water cement ratio as 0.30. Superplasticizer dose @ of 2% by weight
of cement is added to achieve the required degree of workability in
terms of compaction factor.
From the test results of the above investigation it can be concluded
that the shrinkage strain of High Strength Concrete increases with
age. The shrinkage strain of concrete with replacement of cement by
10% of Flyash and Silica fume respectively at various ages are more
(6 to 10%) than the shrinkage strain of concrete without Flyash and
Silica fume. The shrinkage strain of concrete with Badarpur sand as
Fine aggregate at 90 days is slightly less (10%) than that of concrete
with Yamuna Sand. Further, the shrinkage strain of concrete with
Granite as Coarse aggregate at 90 days is slightly less (6 to 7%) than
that of concrete with Sand stone as aggregate of same size. The
shrinkage strain of High Strength Concrete is also compared with that
of normal strength concrete. Test results show that the shrinkage
strain of high strength concrete is less than that of normal strength
concrete.
Abstract: Bacterial magnetic nanoparticles have great useful potential in biotechnological and biomedical applications. In this study, a liquid growth medium was modified for cultivation a fastidious magnetotactic bacterium that has been isolated from Anzali
lagoon, Iran in our previous research. These modifications include
change in vitamin, mineral, carbon sources and etcetera. In our
experience, the serum bottles and designed air-tight laboratory bottles
were used to create microaerobic conditions in order to development
of a method for scale-up experiment. This information may serve as a
guide to green chemistry based biological protocols for the synthesis
of magnetic nanoparticles with control over the chemical
composition, morphology and size.
Abstract: Case-Based Reasoning (CBR) is one of machine
learning algorithms for problem solving and learning that caught a lot
of attention over the last few years. In general, CBR is composed of
four main phases: retrieve the most similar case or cases, reuse the
case to solve the problem, revise or adapt the proposed solution, and
retain the learned cases before returning them to the case base for
learning purpose. Unfortunately, in many cases, this retain process
causes the uncontrolled case base growth. The problem affects
competence and performance of CBR systems. This paper proposes
competence-based maintenance method based on deletion policy
strategy for CBR. There are three main steps in this method. Step 1,
formulate problems. Step 2, determine coverage and reachability set
based on coverage value. Step 3, reduce case base size. The results
obtained show that this proposed method performs better than the
existing methods currently discussed in literature.
Abstract: Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets1. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected.
Abstract: Ad hoc networks are characterized by multihop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. We compare the performance of three routing protocols for mobile ad hoc networks: Dynamic Source Routing (DSR) , Ad Hoc On-Demand Distance Vector Routing (AODV), location-aided routing(LAR1).The performance differentials are analyzed using varying network load, mobility, and network size. We simulate protocols with GLOMOSIM simulator. Based on the observations, we make recommendations about when the performance of either protocol can be best.