Abstract: Spent petroleum catalyst from Korean petrochemical
industry contains trace amount of metals such as Ni, V and Mo.
Therefore an attempt was made to recover those trace metal using
bioleaching process. Different leaching parameters such as Fe(II)
concentration, pulp density, pH, temperature and particle size of
spent catalyst particle were studied to evaluate their effects on the
leaching efficiency. All the three metal ions like Ni, V and Mo
followed dual kinetics, i.e., initial faster followed by slower rate. The
percentage of leaching efficiency of Ni and V were higher than Mo.
The leaching process followed a diffusion controlled model and the
product layer was observed to be impervious due to formation of
ammonium jarosite (NH4)Fe3(SO4)2(OH)6. In addition, the lower
leaching efficiency of Mo was observed due to a hydrophobic coating
of elemental sulfur over Mo matrix in the spent catalyst.
Abstract: Terminal localization for indoor Wireless Local Area
Networks (WLANs) is critical for the deployment of location-aware
computing inside of buildings. A major challenge is obtaining high
localization accuracy in presence of fluctuations of the received signal
strength (RSS) measurements caused by multipath fading. This paper
focuses on reducing the effect of the distance-varying noise by spatial
filtering of the measured RSS. Two different survey point geometries
are tested with the noise reduction technique: survey points arranged
in sets of clusters and survey points uniformly distributed over the
network area. The results show that the location accuracy improves
by 16% when the filter is used and by 18% when the filter is applied
to a clustered survey set as opposed to a straight-line survey set.
The estimated locations are within 2 m of the true location, which
indicates that clustering the survey points provides better localization
accuracy due to superior noise removal.
Abstract: In this paper, the problem of reducing switching
activity in on-chip buses at the stage of high-level synthesis is
considered, and a high-level low power bus binding based on dynamic
bit reordering is proposed. Whereas conventional methods use a fixed
bit ordering between variables within a bus, the proposed method
switches a bit ordering dynamically to obtain a switching activity
reduction. As a result, the proposed method finds a binding solution
with a smaller value of total switching activity (TSA). Experimental
result shows that the proposed method obtains a binding solution
having 12.0-34.9% smaller TSA compared with the conventional
methods.
Abstract: The concentrations of aliphatic and polycyclic aromatic hydrocarbons (PAH) were determined in atmospheric aerosol samples collected at a rural site in Hungary (K-puszta, summer 2008), a boreal forest (Hyytiälä,
April 2007) and a polluted rural area in Italy (San Pietro Capofiume, Po Valley, April 2008). A clear distinction between “clean" and “polluted" periods was observed. Concentrations obtained for Hyytiälä are significantly lower than those for the other two sites. Source reconciliation was performed using diagnostic parameters, such as the carbon preference index and ratios between PAH. The presence of an unresolved complex mixture of hydrocarbons, especially for the Finnish and Italian samples, is indicative of petrogenic inputs. In K-puszta, the aliphatic hydrocarbons are dominated by leaf wax n-alkanes. The long range transport of anthropogenic pollution contributed to the Finnish aerosol. Industrial activities and vehicular emissions represent major sources in San Pietro Capofiume. PAH in K-puszta consist of both pyrogenic and petrogenic compounds.
Abstract: In this paper, we develop a Spatio-Temporal graph as
of a key component of our knowledge representation Scheme. We
design an integrated representation Scheme to depict not only present
and past but future in parallel with the spaces in an effective and
intuitive manner. The resulting multi-dimensional comprehensive
knowledge structure accommodates multi-layered virtual world
developing in the time to maximize the diversity of situations in the
historical context. This knowledge representation Scheme is to be used
as the basis for simulation of situations composing the virtual world
and for implementation of virtual agents' knowledge used to judge and
evaluate the situations in the virtual world. To provide natural contexts
for situated learning or simulation games, the virtual stage set by this
Spatio-Temporal graph is to be populated by agents and other objects
interrelated and changing which are abstracted in the ontology.
Abstract: This paper presents a low cost automatic system for
sampling the electric field in a limited area. The scanning area is a
flat surface parallel to the ground at a selected height. We discuss
in detail the hardware, software and all the arrangements involved
in the system operation. In order to show the system performance
we include a campaign of narrow band measurements with 6017
sample points in the surroundings of a cellular base station. A
commercial isotropic antenna with three orthogonal axes was used
as sampling device. The results are analyzed in terms of its space
average, standard deviation and statistical distribution.
Abstract: This paper describes the optimization of a complex
dairy farm simulation model using two quite different methods of
optimization, the Genetic algorithm (GA) and the Lipschitz
Branch-and-Bound (LBB) algorithm. These techniques have been
used to improve an agricultural system model developed by Dexcel
Limited, New Zealand, which describes a detailed representation of
pastoral dairying scenarios and contains an 8-dimensional parameter
space. The model incorporates the sub-models of pasture growth and
animal metabolism, which are themselves complex in many cases.
Each evaluation of the objective function, a composite 'Farm
Performance Index (FPI)', requires simulation of at least a one-year
period of farm operation with a daily time-step, and is therefore
computationally expensive. The problem of visualization of the
objective function (response surface) in high-dimensional spaces is
also considered in the context of the farm optimization problem.
Adaptations of the sammon mapping and parallel coordinates
visualization are described which help visualize some important
properties of the model-s output topography. From this study, it is
found that GA requires fewer function evaluations in optimization
than the LBB algorithm.
Abstract: This paper proposes a low power SRAM based on
five transistor SRAM cell. Proposed SRAM uses novel word-line
decoding such that, during read/write operation, only selected cell
connected to bit-line whereas, in conventional SRAM (CV-SRAM),
all cells in selected row connected to their bit-lines, which in turn
develops differential voltages across all bit-lines, and this makes
energy consumption on unselected bit-lines. In proposed SRAM
memory array divided into two halves and this causes data-line
capacitance to reduce. Also proposed SRAM uses one bit-line and
thus has lower bit-line leakage compared to CV-SRAM.
Furthermore, the proposed SRAM incurs no area overhead, and has
comparable read/write performance versus the CV-SRAM.
Simulation results in standard 0.25μm CMOS technology shows in
worst case proposed SRAM has 80% smaller dynamic energy
consumption in each cycle compared to CV-SRAM. Besides, energy
consumption in each cycle of proposed SRAM and CV-SRAM
investigated analytically, the results of which are in good agreement
with the simulation results.
Abstract: This paper presents a wrap-around view system with 4
smart cameras module and remote motion mobile robot control equipped with smart camera module system. The two-level scheme for
remote motion control with smart-pad(IPAD) is introduced on this
paper. In the low-level, the wrap-around view system is controlled or operated to keep the reference points lying around top view image
plane. On the higher level, a robot image based motion controller is utilized to drive the mobile platform to reach the desired position or
track the desired motion planning through image feature feedback. The
design wrap-around view system equipped on presents such advantages as follows: 1) a satisfactory solution for the FOV and affine
problem; 2) free of any complex and constraint with robot pose. The performance of the wrap-around view equipped on mobile robot
remote control is proven by experimental results.
Abstract: Image-based Rendering(IBR) techniques recently
reached in broad fields which leads to a critical challenge to build up
IBR-Driven visualization platform where meets requirement of high
performance, large bounds of distributed visualization resource
aggregation and concentration, multiple operators deploying and
CSCW design employing. This paper presents an unique IBR-based
visualization dataflow model refer to specific characters of IBR
techniques and then discusses prominent feature of IBR-Driven
distributed collaborative visualization (DCV) system before finally
proposing an novel prototype. The prototype provides a well-defined
three level modules especially work as Central Visualization Server,
Local Proxy Server and Visualization Aid Environment, by which
data and control for collaboration move through them followed the
previous dataflow model. With aid of this triple hierarchy architecture
of that, IBR oriented application construction turns to be easy. The
employed augmented collaboration strategy not only achieve
convenient multiple users synchronous control and stable processing
management, but also is extendable and scalable.
Abstract: A new algorithm called Character-Comparison to Character-Access (CCCA) is developed to test the effect of both: 1) converting character-comparison and number-comparison into character-access and 2) the starting point of checking on the performance of the checking operation in string searching. An experiment is performed using both English text and DNA text with different sizes. The results are compared with five algorithms, namely, Naive, BM, Inf_Suf_Pref, Raita, and Cycle. With the CCCA algorithm, the results suggest that the evaluation criteria of the average number of total comparisons are improved up to 35%. Furthermore, the results suggest that the clock time required by the other algorithms is improved in range from 22.13% to 42.33% by the new CCCA algorithm.
Abstract: The clustering ensembles combine multiple partitions
generated by different clustering algorithms into a single clustering
solution. Clustering ensembles have emerged as a prominent method
for improving robustness, stability and accuracy of unsupervised
classification solutions. So far, many contributions have been done to
find consensus clustering. One of the major problems in clustering
ensembles is the consensus function. In this paper, firstly, we
introduce clustering ensembles, representation of multiple partitions,
its challenges and present taxonomy of combination algorithms.
Secondly, we describe consensus functions in clustering ensembles
including Hypergraph partitioning, Voting approach, Mutual
information, Co-association based functions and Finite mixture
model, and next explain their advantages, disadvantages and
computational complexity. Finally, we compare the characteristics of
clustering ensembles algorithms such as computational complexity,
robustness, simplicity and accuracy on different datasets in previous
techniques.
Abstract: Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.
Abstract: The design requirements for successful human
accommodation in urban spaces are well known; and the range of
facilities available for meeting urban water quality and quantity
requirements is also well established. Their competing requirements
must be reconciled in order for urban spaces to be successful for
both. This paper outlines the separate human and water imperatives
and their interactions in urban spaces. Stormwater management
facilities- relative potential contributions to urban spaces are
contrasted, and design choices for achieving those potentials are
described. This study uses human success of urban space as the
evaluative criterion of stormwater amenity: human values call on
stormwater facilities to contribute to successful human spaces.
Placing water-s contribution under the overall idea of successful
urban space is an evolution from previous subjective evaluations.
The information is based on photographs and notes from
approximately 1,000 stormwater facilities and urban sites collected
during the last 35 years in North America and overseas, and the
author-s experience on multi-disciplinary design teams. This
conceptual study combines the disciplinary roles of engineering,
landscape architecture, and sociology in effecting successful urban
design.
Abstract: Unlike its conventional counterpart, Islamic principles
forbid Islamic banks to take any interest-related income and thus
makes deposits from depositors as an important source of fund for its
operational and financing. Consequently, the risk of deposit
withdrawal by depositors is an important aspect that should be wellmanaged
in Islamic banking. This paper aims to investigate factors
that influence depositors- withdrawal behavior in Islamic banks,
particularly in Malaysia, using the framework of theory of reasoned
action. A total of 368 respondents from Klang valley are involved in
the analysis. The paper finds that all the constructs variable i.e.
normative beliefs, subjective norms, behavioral beliefs, and attitude
towards behavior are perceived to be distinct by the respondents. In
addition, the structural equation model is able to verify the structural
relationships between subjective norms, attitude towards behavior
and behavioral intention. Subjective norms gives more influence to
depositors- decision on deposit withdrawal compared to attitude
towards behavior.
Abstract: A multi-board run-time reconfigurable (MRTR)
system for evolvable hardware (EHW) is introduced with the aim to
implement on hardware the bidirectional incremental evolution (BIE)
method. The main features of this digital intrinsic EHW solution rely
on the multi-board approach, the variable chromosome length
management and the partial configuration of the reconfigurable
circuit. These three features provide a high scalability to the solution.
The design has been written in VHDL with the concern of not being
platform dependant in order to keep a flexibility factor as high as
possible. This solution helps tackling the problem of evolving
complex task on digital configurable support.
Abstract: Chess is one of the indoor games, which improves the
level of human confidence, concentration, planning skills and
knowledge. The main objective of this paper is to help the chess
players to improve their chess openings using data mining
techniques. Budding Chess Players usually do practices by analyzing
various existing openings. When they analyze and correlate
thousands of openings it becomes tedious and complex for them. The
work done in this paper is to analyze the best lines of Blackmar-
Diemer Gambit(BDG) which opens with White D4... using data
mining analysis. It is carried out on the collection of winning games
by applying association rules. The first step of this analysis is
assigning variables to each different sequence moves. In the second
step, the sequence association rules were generated to calculate
support and confidence factor which help us to find the best
subsequence chess moves that may lead to winning position.
Abstract: The Major Depressive Disorder has been a burden of
medical expense in Taiwan as well as the situation around the world.
Major Depressive Disorder can be defined into different categories by
previous human activities. According to machine learning, we can
classify emotion in correct textual language in advance. It can help
medical diagnosis to recognize the variance in Major Depressive
Disorder automatically. Association language incremental is the
characteristic and relationship that can discovery words in sentence.
There is an overlapping-category problem for classification. In this
paper, we would like to improve the performance in classification in
principle of no overlapping-category problems. We present an
approach that to discovery words in sentence and it can find in high
frequency in the same time and can-t overlap in each category, called
Association Language Features by its Category (ALFC).
Experimental results show that ALFC distinguish well in Major
Depressive Disorder and have better performance. We also compare
the approach with baseline and mutual information that use single
words alone or correlation measure.
Abstract: Societal security, continuity scenarios and methodological cycling approach explained in this article. Namely societal security organizational challenges ask implementation of international standards BS 25999-2 & global ISO 22300 which is a family of standards for business continuity management system. Efficient global organization system is distinguished of high entity´s complexity, connectivity & interoperability, having not only cooperative relations in a fact. Competing business have numerous participating ´enemies´, which are in apparent or hidden opponent and antagonistic roles with prosperous organization system, resulting to a crisis scene or even to a battle theatre. Organization business continuity scenarios are necessary for such ´a play´ preparedness, planning, management & overmastering in real environments.
Abstract: The effect of the rotational speed and axial torque on
the diagnostics of tapered rolling element bearing defects was
investigated. The accelerometer was mounted on the bearing housing
and connected to Sound and Vibration Analyzer (SVAN 958) and
was used to measure the accelerations from the bearing housing. The
data obtained from the bearing was processed to detect damage of the
bearing using statistical tools and the results were subsequently
analyzed to see if bearing damage had been captured. From this study
it can be seen that damage is more evident when the bearing is
loaded. Also, at the incipient stage of damage the crest factor and
kurtosis values are high but as time progresses the crest factors and
kurtosis values decrease whereas the peak and RMS values are low at
the incipient stage but increase with damage.