Abstract: Social networks have recently gained a growing
interest on the web. Traditional formalisms for representing social
networks are static and suffer from the lack of semantics. In this
paper, we will show how semantic web technologies can be used to
model social data. The SemTemp ontology aligns and extends
existing ontologies such as FOAF, SIOC, SKOS and OWL-Time to
provide a temporal and semantically rich description of social data.
We also present a modeling scenario to illustrate how our ontology
can be used to model social networks.
Abstract: In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.
Abstract: Recent progress in the next generation of automobile
technology is geared towards incorporating information technology
into cars. Collectively called smart cars are bringing intelligence to
cars that provides comfort, convenience and safety. A branch of smart
cars is connected-car system. The key concept in connected-cars is the
sharing of driving information among cars through decentralized
manner enabling collective intelligence. This paper proposes a
foundation of the information model that is necessary to define the
driving information for smart-cars. Road conditions are modeled
through a unique data structure that unambiguously represent the time
variant traffics in the streets. Additionally, the modeled data structure
is exemplified in a navigational scenario and usage using UML.
Optimal driving route searching is also discussed using the proposed
data structure in a dynamically changing road conditions.
Abstract: In order to retrieve images efficiently from a large
database, a unique method integrating color and texture features
using genetic programming has been proposed. Opponent color
histogram which gives shadow, shade, and light intensity invariant
property is employed in the proposed framework for extracting color
features. For texture feature extraction, fast discrete curvelet
transform which captures more orientation information at different
scales is incorporated to represent curved like edges. The recent
scenario in the issues of image retrieval is to reduce the semantic gap
between user’s preference and low level features. To address this
concern, genetic algorithm combined with relevance feedback is
embedded to reduce semantic gap and retrieve user’s preference
images. Extensive and comparative experiments have been conducted
to evaluate proposed framework for content based image retrieval on
two databases, i.e., COIL-100 and Corel-1000. Experimental results
clearly show that the proposed system surpassed other existing
systems in terms of precision and recall. The proposed work achieves
highest performance with average precision of 88.2% on COIL-100
and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3%
on Corel. Thus, the experimental results confirm that the proposed
content based image retrieval system architecture attains better
solution for image retrieval.
Abstract: There was a scenario present day that drying of fresh
fruits and vegetables by indirect solar drying by using mechanical
device; hence, an effort was made to develop a small scale solar
tunnel dryer (STD). Drying of spinach is carried out to analyze the
performance of the dryer and to study its drying characteristics. To
evaluate the performance of dryer the independent variables were
selected as air flow rate, loading density and shade net while collector
efficiency, drying efficiency, overall efficiency and specific energy
consumption were selected as responses during performing the
experiments. The spinach was dried from initial moisture content
88.21-94.04% (w.b.) to final moisture content 3.50-5.13% (w.b.). The
drying time considerably reduced as compared to open sun drying of
spinach as sun drying took 15 h for drying. The average collector
efficiency, drying efficiency and overall efficiency were in the range
28.73-61.15%, 11.63% to 22.13%, and 7.61-14.66%, respectively.
Abstract: The change in orbit evolution between collocated
satellites (X, Y) inside +/-0.09° E/W and +/- 0.07° N/S cluster, after
one of these satellites is placed in an inclined orbit (satellite X) and
the effect of this change in the collocation safety inside the cluster
window has been studied and evaluated. Several collocation scenarios had been studied in order to adjust
the location of both satellites inside their cluster to maximize the
separation between them and safe the mission.
Abstract: In the past years electric mobility became part of a
public discussion. The trend to fully electrified vehicles instead of
vehicles fueled with fossil energy has notably gained momentum.
Today nearly every big car manufacturer produces and sells fully
electrified vehicles, but electrified vehicles are still not as competitive
as conventional powered vehicles. As the traction battery states the
largest cost driver, lowering its price is a crucial objective. In
addition to improvements in product and production processes a nonnegligible,
but widely underestimated cost driver of production can
be found in logistics, since the production technology is not
continuous yet and neither are the logistics systems. This paper presents an approach to evaluate cost factors on
different designs of load carrier systems. Due to numerous
interdependencies, the combination of costs factors for a particular
scenario is not transparent. This is effecting actions for cost reduction
negatively, but still cost reduction is one of the major goals for
simultaneous engineering processes. Therefore a concurrent and
phase appropriate cost valuation method is necessary to serve cost
transparency. In this paper the four phases of this cost valuation
method are defined and explained, which based upon a new approach
integrating the logistics development process in to the integrated
product and process development.
Abstract: Geological and tectonic framework indicates that
Bangladesh is one of the most seismically active regions in the world.
The Bengal Basin is at the junction of three major interacting plates:
the Indian, Eurasian, and Burma Plates. Besides there are many
active faults within the region, e.g. the large Dauki fault in the north.
The country has experienced a number of destructive earthquakes due
to the movement of these active faults. Current seismic provisions of
Bangladesh are mostly based on earthquake data prior to the 1990.
Given the record of earthquakes post 1990, there is a need to revisit
the design provisions of the code. This paper compares the base shear
demand of three major cities in Bangladesh: Dhaka (the capital city),
Sylhet, and Chittagong for earthquake scenarios of magnitudes
7.0MW, 7.5MW, 8.0MW, and 8.5MW using a stochastic model. In
particular, the stochastic model allows the flexibility to input region
specific parameters such as shear wave velocity profile (that were
developed from Global Crustal Model CRUST2.0) and include the
effects of attenuation as individual components. Effects of soil
amplification were analysed using the Extended Component
Attenuation Model (ECAM). Results show that the estimated base
shear demand is higher in comparison with code provisions leading to
the suggestion of additional seismic design consideration in the study
regions.
Abstract: With the increasing dependence of countries on the
critical infrastructure, it increases their vulnerability. Big threat is
primarily in the human factor (personnel of the critical infrastructure)
and in terrorist attacks. It emphasizes the development of
methodology for searching of weak points and their subsequent
elimination. This article discusses methods for the analysis of safety
in the objects of critical infrastructure. It also contains proposal for
methodology for training employees of security services in the
objects of the critical infrastructure and developing scenarios of
attacks on selected objects of the critical infrastructure.
Abstract: Non-linear dynamic time history analysis is
considered as the most advanced and comprehensive analytical
method for evaluating the seismic response and performance of
multi-degree-of-freedom building structures under the influence of
earthquake ground motions. However, effective and accurate
application of the method requires the implementation of advanced
hysteretic constitutive models of the various structural components
including masonry infill panels. Sophisticated computational research
tools that incorporate realistic hysteresis models for non-linear
dynamic time-history analysis are not popular among the professional
engineers as they are not only difficult to access but also complex and
time-consuming to use. In addition, commercial computer programs
for structural analysis and design that are acceptable to practicing
engineers do not generally integrate advanced hysteretic models
which can accurately simulate the hysteresis behavior of structural
elements with a realistic representation of strength degradation,
stiffness deterioration, energy dissipation and ‘pinching’ under cyclic
load reversals in the inelastic range of behavior. In this scenario,
push-over or non-linear static analysis methods have gained
significant popularity, as they can be employed to assess the seismic
performance of building structures while avoiding the complexities
and difficulties associated with non-linear dynamic time-history
analysis. “Push-over” or non-linear static analysis offers a practical
and efficient alternative to non-linear dynamic time-history analysis
for rationally evaluating the seismic demands. The present paper is
based on the analytical investigation of the effect of distribution of
masonry infill panels over the elevation of planar masonry infilled
reinforced concrete [R/C] frames on the seismic demands using the
capacity spectrum procedures implementing nonlinear static analysis
[pushover analysis] in conjunction with the response spectrum
concept. An important objective of the present study is to numerically
evaluate the adequacy of the capacity spectrum method using
pushover analysis for performance based design of masonry infilled
R/C frames for near-field earthquake ground motions.
Abstract: Recent investigations have demonstrated the global
sea level rise due to climate change impacts. In this study, climate
changes study the effects of increasing water level in the strait of
Hormuz. The probable changes of sea level rise should be
investigated to employ the adaption strategies. The climatic output
data of a GCM (General Circulation Model) named CGCM3 under
climate change scenario of A1b and A2 were used. Among different
variables simulated by this model, those of maximum correlation
with sea level changes in the study region and least redundancy
among themselves were selected for sea level rise prediction by using
stepwise regression. One of models (Discrete Wavelet artificial
Neural Network) was developed to explore the relationship between
climatic variables and sea level changes. In these models, wavelet
was used to disaggregate the time series of input and output data into
different components and then ANN was used to relate the
disaggregated components of predictors and input parameters to each
other. The results showed in the Shahid Rajae Station for scenario
A1B sea level rise is among 64 to 75 cm and for the A2 Scenario sea
level rise is among 90 t0 105 cm. Furthermore, the result showed a
significant increase of sea level at the study region under climate
change impacts, which should be incorporated in coastal areas
management.
Abstract: This paper presents the design and implementation
details of a complete unmanned aerial system (UAS) based
on commercial-off-the-shelf (COTS) components, focusing on
safety, security, search and rescue scenarios in GPS-denied
environments. In particular, The aerial platform is capable
of semi-autonomously navigating through extremely low-light,
GPS-denied indoor environments based on onboard sensors only,
including a downward-facing optical flow camera. Besides, an
additional low-cost payload camera system is developed to stream
both infra-red video and visible light video to a ground station in
real-time, for the purpose of detecting sign of life and hidden humans.
The total cost of the complete system is estimated to be $1150,
and the effectiveness of the system has been tested and validated
in practical scenarios.
Abstract: Adequate and reliable estimates of aquifer parameters
are of utmost importance for proper management of vital
groundwater resources. At present scenario, the ground water is
polluted because of industrial waste disposed over the land and the
contaminants are transported in the aquifer from one area to another
area, which is depending on the characteristics of the aquifer and
contaminants. To know the contaminant transport, the accurate
estimation of aquifer properties is highly needed. Conventionally,
these properties are estimated through pumping tests carried out on
water wells. The occurrence and movement of ground water in the
aquifer are characteristically defined by the aquifer parameters. The
pumping (aquifer) test is the standard technique for estimating
various hydraulic properties of aquifer systems, viz., transmissivity
(T), hydraulic conductivity (K), storage coefficient (S) etc., for which
the graphical method is widely used. The study area for conducting
pumping test is Pydibheemavaram Industrial area near the coastal
belt of Srikulam, AP, India. The main objective of the present work is
to estimate the aquifer properties for developing contaminant
transport model for the study area.
Abstract: The UK is leading in online retail and mobile
adoption. However, there is a dearth of information relating to mobile
apparel retail, and developing an understanding about consumer
browsing and purchase behaviour in m-retail channel would provide
apparel marketers, mobile website and app developers with the
necessary understanding of consumers’ needs. Despite the rapid
growth of mobile retail businesses, no published study has examined
shopping behaviour on fashion mobile apps and websites. A mixed method approach helped to understand why fashion
consumers prefer websites on smartphones, when diverse mobile
apps are also available. The following research methods were
employed: survey, eye-tracking experiments, observation, and
interview with retrospective think aloud. The mobile gaze tracking
device by SensoMotoric Instruments was used to understand
frustrations in navigation and other issues facing consumers in
mobile channel. This method helped to validate and compliment
other traditional user-testing approaches in order to optimize user
experience and enhance the development of mobile retail channel.
The study involved eight participants - females aged 18 to 35 years
old, who are existing mobile shoppers. The participants used the
Topshop mobile app and website on a smart phone to complete a task
according to a specified scenario leading to a purchase. The
comparative study was based on: duration and time spent at different
stages of the shopping journey, number of steps involved and product
pages visited, search approaches used, layout and visual clues, as
well as consumer perceptions and expectations. The results from the data analysis show significant differences in
consumer behaviour when using a mobile app or website on a smart
phone. Moreover, two types of problems were identified, namely
technical issues and human errors. Having a mobile app does not
guarantee success in satisfying mobile fashion consumers. The
differences in the layout and visual clues seem to influence the
overall shopping experience on a smart phone. The layout of search
results on the website was different from the mobile app. Therefore,
participants, in most cases, behaved differently on different
platforms. The number of product pages visited on the mobile app
was triple the number visited on the website due to a limited visibility
of products in the search results. Although, the data on traffic trends
held by retailers to date, including retail sector breakdowns for visits
and views, data on device splits and duration, might seem a valuable
source of information, it cannot explain why consumers visit many
product pages, stay longer on the website or mobile app, or abandon
the basket. A comprehensive list of pros and cons was developed by
highlighting issues for website and mobile app, and recommendations
provided. The findings suggest that fashion retailers need to be aware of
actual consumers’ behaviour on the mobile channel and their expectations in order to offer a seamless shopping experience. Added
to which is the challenge of retaining existing and acquiring new
customers. There seem to be differences in the way fashion
consumers search and shop on mobile, which need to be explored in
further studies.
Abstract: This study aims at improving the urban hydrological
cycle of the Orléans agglomeration (France) and understanding the
relationship between physical and chemical parameters of urban
surface runoff and the hydrological conditions. In particular water
quality parameters such as pH, conductivity, total dissolved solids,
major dissolved cations and anions, and chemical and biological
oxygen demands were monitored for three types of urban water
discharges (wastewater treatment plant output (WWTP), storm
overflow and stormwater outfall) under two hydrologic scenarios (dry
and wet weather). The first results were obtained over a period of five
months. Each investigated (Ormes, l’Egoutier and La Corne) outfall
represents an urban runoff source that receives water from runoff
roads, gutters, the irrigation of gardens and other sources of flow over
the Earth’s surface that drains in its catchments and carries it to the
Loire River. In wet weather conditions there is rain water runoff and
an additional input from the roof gutters that have entered the
stormwater system during rainfall. For the comparison the results La
Chilesse is a storm overflow that was selected in our study as a
potential source of waste water which is located before the (WWTP). The comparison of the physical-chemical parameters (total
dissolved solids, turbidity, pH, conductivity, dissolved organic
carbon (DOC), concentration of major cations and anions) together
with the chemical oxygen demand (COD) and biological oxygen
demand (BOD) helped to characterize sources of runoff waters in the
different watersheds. It also helped to highlight the infiltration of
wastewater in some stormwater systems that reject directly in the
Loire River. The values of the conductivity measured in the outflow
of Ormes were always higher than those measured in the other two
outlets. The results showed a temporal variation for the Ormes outfall
of conductivity from 1465 μS cm-1 in the dry weather flow to 650 μS
cm-1 in the wet weather flow and also a spatial variation in the wet
weather flow from 650 μS cm-1 in the Ormes outfall to 281 μS cm-1
in L’Egouttier outfall. The ultimate BOD (BOD28) showed a
significant decrease in La Corne outfall from 181 mg L-1 in the wet
weather flow to 95 mg L-1 in the dry weather flow because of the
nutrient load that was transported by the runoff.
Abstract: An integrated modeling approach was used in this study for energy planning and climate change mitigation assessment. The main objective of this study was to develop various green-house gas (GHG) mitigations scenarios in the energy demand and supply sectors for the state of Florida. The Long range energy alternative planning (LEAP) model was used in this study to examine the energy alternative and GHG emissions reduction scenarios for short and long term (2010-2050). One of the energy analysis and GHG mitigation scenarios was developed by taking into account the available renewable energy resources potential for power generation in the state of Florida. This will help to compare and analyze the GHG reduction measure against “Business As Usual” and ‘State of Florida Policy” scenarios. Two master scenarios: “Electrification” and “Energy efficiency and Lifestyle” were developed through combination of various mitigation scenarios: technological changes and energy efficiency and conservation. The results show a net reduction of the energy demand and GHG emissions by adopting these two energy scenarios compared to the business as usual.
Abstract: Recently, numerous documents including large
volumes of unstructured data and text have been created because of the
rapid increase in the use of social media and the Internet. Usually,
these documents are categorized for the convenience of users. Because
the accuracy of manual categorization is not guaranteed, and such
categorization requires a large amount of time and incurs huge costs.
Many studies on automatic categorization have been conducted to help
mitigate the limitations of manual categorization. Unfortunately, most
of these methods cannot be applied to categorize complex documents
with multiple topics because they work on the assumption that
individual documents can be categorized into single categories only.
Therefore, to overcome this limitation, some studies have attempted to
categorize each document into multiple categories. However, the
learning process employed in these studies involves training using a
multi-categorized document set. These methods therefore cannot be
applied to the multi-categorization of most documents unless
multi-categorized training sets using traditional multi-categorization
algorithms are provided. To overcome this limitation, in this study, we
review our novel methodology for extending the category of a
single-categorized document to multiple categorizes, and then
introduce a survey-based verification scenario for estimating the
accuracy of our automatic categorization methodology.
Abstract: This paper addresses the issue of resource allocation
in the emerging cognitive technology. Focusing the Quality of
Service (QoS) of Primary Users (PU), a novel method is proposed for
the resource allocation of Secondary Users (SU). In this paper, we
propose the unique Utility Function in the game theoretic model of
Cognitive Radio which can be maximized to increase the capacity of
the Cognitive Radio Network (CRN) and to minimize the
interference scenario. Utility function is formulated to cater the need
of PUs by observing Signal to Noise ratio. Existence of Nash
Equilibrium for the postulated game is established.
Abstract: Home Energy Management System (HEMS), which makes the residential consumers, contribute to the demand response is attracting attention in recent years. An aim of HEMS is to minimize their electricity cost by controlling the use of their appliances according to electricity price. The use of appliances in HEMS may be affected by some conditions such as external temperature and electricity price. Therefore, the user’s usage pattern of appliances should be modeled according to the external conditions, and the resultant usage pattern is related to the user’s comfortability on use of each appliances. This paper proposes a methodology to model the usage pattern based on the historical data with the copula function. Through copula function, the usage range of each appliance can be obtained and is able to satisfy the appropriate user’s comfort according to the external conditions for next day. Within the usage range, an optimal scheduling for appliances would be conducted so as to minimize an electricity cost with considering user’s comfort. Among the home appliance, electric heater (EH) is a representative appliance, which is affected by the external temperature. In this paper, an optimal scheduling algorithm for an electric heater (EH) is addressed based on the method of branch and bound. As a result, scenarios for the EH usage are obtained according to user’s comfort levels and then the residential consumer would select the best scenario. The case study shows the effects of the proposed algorithm compared with the traditional operation of the EH, and it represents impacts of the comfort level on the scheduling result.
Abstract: This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for the jobs and the advance/tardiness for the maintenance activities. To solve the problem, a genetic algorithm was developed and successfully tested and validated on many problem instances. The computational results showed that the new genetic algorithm outperforms another earlier proposed algorithm.