Abstract: In this work, we present a novel active learning approach
for learning a visual object detection system. Our system
is composed of an active learning mechanism as wrapper around
a sub-algorithm which implement an online boosting-based learning
object detector. In the core is a combination of a bootstrap procedure
and a semi automatic learning process based on the online boosting
procedure. The idea is to exploit the availability of classifier during
learning to automatically label training samples and increasingly
improves the classifier. This addresses the issue of reducing labeling
effort meanwhile obtain better performance. In addition, we propose
a verification process for further improvement of the classifier.
The idea is to allow re-update on seen data during learning for
stabilizing the detector. The main contribution of this empirical study
is a demonstration that active learning based on an online boosting
approach trained in this manner can achieve results comparable or
even outperform a framework trained in conventional manner using
much more labeling effort. Empirical experiments on challenging data
set for specific object deteciton problems show the effectiveness of
our approach.
Abstract: In this study, a classification-based video
super-resolution method using artificial neural network (ANN) is
proposed to enhance low-resolution (LR) to high-resolution (HR)
frames. The proposed method consists of four main steps:
classification, motion-trace volume collection, temporal adjustment,
and ANN prediction. A classifier is designed based on the edge
properties of a pixel in the LR frame to identify the spatial information.
To exploit the spatio-temporal information, a motion-trace volume is
collected using motion estimation, which can eliminate unfathomable
object motion in the LR frames. In addition, temporal lateral process is
employed for volume adjustment to reduce unnecessary temporal
features. Finally, ANN is applied to each class to learn the complicated
spatio-temporal relationship between LR and HR frames. Simulation
results show that the proposed method successfully improves both
peak signal-to-noise ratio and perceptual quality.
Abstract: The evolution of information and communication
technology has made a very powerful support for the improvement of
online learning platforms in creation of courses. This paper presents a
study that attempts to explore new web architecture for creating an
adaptive online learning system to profiles of learners, using the Web
as a source for the automatic creation of courses for the online
training platform. This architecture will reduce the time and decrease
the effort performed by the drafters of the current e-learning
platform, and direct adaptation of the Web content will greatly enrich
the quality of online training courses.
Abstract: Glazing is a process used to reduce undesirable drying or dehydration of fish during frozen or cold storage. To evaluate the effect of the time/ temperature binomial of the cryogenic frozen tunnel in the amount of glazing watera Central Composite Rotatable Design was used, with application of the Response Surface Methodology. The results reveal that the time/ temperature obtained for pink cusk-eel in experimental conditions for glazing water are similar to the industrial process, but for red fish and merluza the industrial process needs some adjustments. Control charts were established and implementedto control the amount of glazing water on sardine and merluza. They show that the freezing process was statistically controlled but there were some tendencies that must be analyzed, since the trend of sample mean values approached either of the limits, mainly in merluza. Thus, appropriate actions must be taken, in order to improve the process.
Abstract: The aim of this study was to investigate whether
magnetite nanoparticles affect the viability of Bradyrhizobium
japanicum cells residing on the surface of soybean seeds during
desiccation. Different concentrations of nanoparticles suspended in
liquid medium, mixed with and adhering to Bradyrhizobium
japanicum, were investigated at two temperatures, using both
soybean seeds and glass beads as surrogates. Statistical design was a
complete randomized block (CRB) in a factorial 6×2×2×6
experimental arrangement with four replications. The most important
variable was the viability of Bradyrhizobium on the surface of the
seeds. The nanoparticles increased Bradyrhizobium viability and
inoculated seeds stored at low temperature had greater viability when
nanoparticles had been added. At the optimum nanoparticle
concentration, 50% bacterium viability on the seeds was retained
after 5 days at 4ºC. Possible explanations for the observed effects are
proposed.
Abstract: A fault detection and identification (FDI) technique is
presented to create a fault tolerant control system (FTC). The fault
detection is achieved by monitoring the position of the light source
using an array of light sensors. When a decision is made about the
presence of a fault an identification process is initiated to locate the
faulty component and reconfigure the controller signals. The signals
provided by the sensors are predictable; therefore the existence of a
fault is easily identified. Identification of the faulty sensor is based on
the dynamics of the frame. The technique is not restricted to a
particular type of controllers and the results show consistency.
Abstract: Wind catchers are traditional natural ventilation
systems attached to buildings in order to ventilate the indoor air. The
most common type of wind catcher is four sided one which is
capable to catch wind in all directions. CFD simulation is the perfect
way to evaluate the wind catcher performance. The accuracy of CFD
results is the issue of concern, so sensitivity analyses is crucial to
find out the effect of different settings of CFD on results. This paper
presents a series of 3D steady RANS simulations for a generic
isolated four-sided wind catcher attached to a room subjected to wind
direction ranging from 0º to 180º with an interval of 45º. The CFD
simulations are validated with detailed wind tunnel experiments. The
influence of an extensive range of computational parameters is
explored in this paper, including the resolution of the computational
grid, the size of the computational domain and the turbulence model.
This study found that CFD simulation is a reliable method for wind
catcher study, but it is less accurate in prediction of models with non
perpendicular wind directions.
Abstract: Seasonal variability of nutrients concentration in the Baltic Sea using the 3D ecosystem numerical model 3D-CEMBS has been investigated. Additionally this study shows horizontal and vertical distribution of nutrients in the Baltic Sea. Model domain is an extended Baltic Sea area divided into 600x640 horizontal grid cells. Aside from standard hydrodynamic parameters 3D-CEMBS produces modeled ecological variables such as: three types of phytoplankton, two detrital classes, dissolved oxygen and the nutrients (nitrate, ammonium, phosphate and silicate). The presented model allows prediction of parameters that describe distribution of nutrients concentration and phytoplankton biomass. 3D-CEMBS can be used to study the effect of different hydrodynamic and biogeochemical processes on distributions of these variables in a larger scale.
Abstract: This study uses natural water and the surface properties of powdered activated carbon to acclimatize organics, forming biofilms on the surface of powdered activated carbon. To investigate the influence of different hydraulic retention times on the removal efficacy of trace organics in raw water, and to determine the optimal hydraulic retention time of a biological powdered activated carbon system, this study selects ozone-treated water processed by Feng-shan Advanced Water Purification Plant in southern Taiwan for the experiment. The evaluation indicators include assimilable organic carbon, dissolved organic carbon, and total organic carbon. The results of this study can improve the quality of drinking water treated using advanced water purification procedures.
Abstract: A code has been developed in Mathematica using
Direct Simulation Monte Carlo (DSMC) technique. The code was
tested for 2-D air flow around a circular cylinder. Same geometry
and flow properties were used in FLUENT 6.2 for comparison. The
results obtained from Mathematica simulation indicated significant
agreement with FLUENT calculations, hence providing insight into
particle nature of fluid flows.
Abstract: Some theoretical and experimental aspects related to
the conceptual analyses concerning the direct correspondence
identification between the shape, area and orientation of plantar
pressure and obtaining adequate corrective insoles by rapid
prototyping are presented in this paper. In the first part of the paper
there is the theoretical-correlative concept, which is the fundament of
correspondence deduction between plantar surface characteristics and
respectively corrective insoles. In the second part of the paper the
experimental equipment used to analyze and perform the
correspondence stages and then the integral ones between the
analyzed foot shapes and the ones with corrective insoles is
presented. In the final parte the results used to adapt the insoles
obtained by rapid prototyping but also some specific aspects and
conclusions of the conceptual analysis of direct and rapid
correspondence are shown.
Abstract: There are extensive applications of lithium
bromide-water absorption chillers in industry, but the heat exchangers
corrosion and refrigerating capacity loss are very difficult to be solved.
In this paper, an experiment was conducted by using plastic heat
transfer tubes instead of copper tubes. As an example, for a lithium
bromide-water absorption chiller of refrigerating capacity of 35kW,
the correlative performance of the lithium bromide-water absorption
chiller using plastic heat transfer tubes was compared with the
traditional lithium bromide-water absorption chiller. And then the
following three aspects, i.e., heat transfer area, pipe resistance, and
safety strength, are analyzed. The results show that plastic heat
transfer tubes can be used on lithium bromide-water absorption
chillers, and its prospect is very optimistic.
Abstract: Membrane distillation (MD) is a rising technology for
seawater or brine desalination process. In this work, an air gap
membrane distillation (AGMD) performance was investigated for
aqueous NaCl solution along with natural ground water and seawater.
In order to enhance the performance of the AGMD process in
desalination, that is, to get more flux, it is necessary to study the
effect of operating parameters on the yield of distillate water. The
influence of operational parameters such as feed flow rate, feed
temperature, feed salt concentration, coolant temperature and air gap
thickness on the membrane distillation (MD) permeation flux have
been investigated for low and high salt solution. the natural
application of ground water and seawater over 90 h continuous
operation, scale deposits observed on the membrane surface and
reduction in flux represents 23% for ground water and 60% for
seawater, in 90 h. This reduction was eliminated (less than 14 %) by
acidification of feed water. Hence, promote the research attention in
apply of AGMD for the ground water as well as seawater
desalination over today-s conventional RO operation.
Abstract: A new approach to determine the machine layout in flexible manufacturing cell, and to find the feasible robot configuration of the robot to achieve minimum cycle time is presented in this paper. The location of the input/output location and the optimal robot configuration is obtained for all sequences of work tasks of the robot within a specified period of time. A more realistic approach has been presented to model the problem using the robot joint space. The problem is formulated as a nonlinear optimization problem and solved using Sequential Quadratic Programming algorithm.
Abstract: The world wide web coupled with the ever-increasing
sophistication of online technologies and software applications puts
greater emphasis on the need of even more sophisticated and
consistent quality requirements modeling than traditional software
applications. Web sites and Web applications (WebApps) are
becoming more information driven and content-oriented raising the
concern about their information quality (InQ). The consistent and
consolidated modeling of InQ requirements for WebApps at different
stages of the life cycle still poses a challenge. This paper proposes an
approach to specify InQ requirements for WebApps by reusing and
extending the ISO 25012:2008(E) data quality model. We also
discuss learnability aspect of information quality for the WebApps.
The proposed ISO 25012 based InQ framework is a step towards a
standardized approach to evaluate WebApps InQ.
Abstract: One of the common problems encountered in software
engineering is addressing and responding to the changing nature of
requirements. While several approaches have been devised to address
this issue, ranging from instilling resistance to changing requirements
in order to mitigate impact to project schedules, to developing an
agile mindset towards requirements, the approach discussed in this
paper is one of conceptualizing the delta in requirement and
modeling it, in order to plan a response to it. To provide some
context here, change is first formally identified and categorized as
either formal change or informal change. While agile methodology
facilitates informal change, the approach discussed in this paper
seeks to develop the idea of facilitating formal change. To collect,
document meta-requirements that represent the phenomena of change
would be a pro-active measure towards building a realistic cognition
of the requirements entity that can further be harnessed in the
software engineering process.
Abstract: Location-aware computing is a type of pervasive
computing that utilizes user-s location as a dominant factor for
providing urban services and application-related usages. One of the
important urban services is navigation instruction for wayfinders in a
city especially when the user is a tourist. The services which are
presented to the tourists should provide adapted location aware
instructions. In order to achieve this goal, the main challenge is to
find spatial relevant objects and location-dependent information. The
aim of this paper is the development of a reusable location-aware
model to handle spatial relevancy parameters in urban location-aware
systems. In this way we utilized ontology as an approach which could
manage spatial relevancy by defining a generic model. Our
contribution is the introduction of an ontological model based on the
directed interval algebra principles. Indeed, it is assumed that the
basic elements of our ontology are the spatial intervals for the user
and his/her related contexts. The relationships between them would
model the spatial relevancy parameters. The implementation language
for the model is OWLs, a web ontology language. The achieved
results show that our proposed location-aware model and the
application adaptation strategies provide appropriate services for the
user.
Abstract: Government spending is categorized into consumption spending and capital spending. Three categories of private consumption are used: food consumption, nonfood consumption, and services consumption. The estimated model indicates substitution effects of government consumption spending on budget shares of private nonfood consumption and of government capital spending on budget share of private food consumption. However, the results do not indicate whether the negative effects of changes in the budget shares of the nonfood and the food consumption equates to reduce total private consumption. The concept of aggregate demand comprising consumption, investment, government spending (consumption spending and capital spending), export, and import are used to estimate their relationship by using the Vector Error Correction Mechanism. The study found no effect of government capital spending on either the private consumption or the growth of GDP while the government consumption spending has negative effect on the growth of GDP.
Abstract: In this paper, Land Marks for Unique Addressing( LMUA) algorithm is develped to generate unique ID for each and every node which leads to the formation of overlapping/Non overlapping clusters based on unique ID. To overcome the draw back of the developed LMUA algorithm, the concept of clustering is introduced. Based on the clustering concept a Land Marks for Unique Addressing and Clustering(LMUAC) Algorithm is developed to construct strictly non-overlapping clusters and classify those nodes in to Cluster Heads, Member Nodes, Gate way nodes and generating the Hierarchical code for the cluster heads to operate in the level one hierarchy for wireless communication switching. The expansion of the existing network can be performed or not without modifying the cost of adding the clusterhead is shown. The developed algorithm shows one way of efficiently constructing the
Abstract: Through the course of this paper we define Locationbased
Intelligence (LBI) which is outgrowing from process of
amalgamation of geolocation and Business Intelligence.
Amalgamating geolocation with traditional Business Intelligence (BI)
results in a new dimension of BI named Location-based Intelligence.
LBI is defined as leveraging unified location information for business
intelligence. Collectively, enterprises can transform location data into
business intelligence applications that will benefit all aspects of the
enterprise. Expectations from this new dimension of business
intelligence are great and its future is obviously bright.