Abstract: This work focuses on the remediation of polycyclic
aromatic hydrocarbons (PAHs)-contaminated soil via Fenton
treatment coupled with novel chelating agent (CA). The feasibility of
chelated modified Fenton (MF) treatment to promote PAH oxidation
in artificially contaminated soils was investigated in laboratory scale
batch experiments at natural pH. The effects of adding inorganic and
organic CA are discussed. Experiments using different iron catalyst
to CA ratios were conducted, resulting in hydrogen peroxide: soil:
iron: CA weight ratios that varied from 0.049: 1: 0.072: 0.008 to
0.049: 1: 0.072: 0.067. The results revealed that (1) inorganic CA
could provide much higher PAH removal efficiency and (2) most of
the proposed CAs were more efficient than commonly utilised CAs
even at mild ratio. This work highlights the potential of novel
chelating agents in maintaining a suitable environment throughout
the Fenton treatment, particularly in soils with high buffer capacity.
Abstract: The feasibility of employing solar radiation for
enhanced Fenton process in degradation of combined chlorpyrifos,
cypermethrin and chlorothalonil pesticides was examined. The effect
of various operating conditions of the process on biodegradability
improvement and mineralization of the pesticides were also
evaluated. The optimum operating conditions for treatment of
aqueous solution containing 100, 50 and 250 mg L-1 chlorpyrifos
cypermethrin and chlorothalonil, respectively were observed to be
H2O2/COD molar ratio 2, H2O2/Fe2+ molar ratio 25 and pH 3. Under
the optimum operating conditions, complete degradation of the
pesticides occurred in 1 min. Biodegradability (BOD5/COD)
increased from zero to 0.36 in 60 min, and COD and TOC removal
were 74.19 and 58.32%, respectively in 60 min. Due to
mineralization of organic carbon, decrease in ammonia-nitrogen from
22 to 4.3 mg L-1 and increase in nitrate from 0.7 to 18.1 mg L-1 in
60 min were recorded. The study indicated that solar photo-Fenton
process can be used for pretreatment of chlorpyrifos, cypermethrin
and chlorothalonil pesticides in aqueous solution for further
biological treatment.
Abstract: This paper presents an algorithm which extends the rapidly-exploring random tree (RRT) framework to deal with change of the task environments. This algorithm called the Retrieval RRT Strategy (RRS) combines a support vector machine (SVM) and RRT and plans the robot motion in the presence of the change of the surrounding environment. This algorithm consists of two levels. At the first level, the SVM is built and selects a proper path from the bank of RRTs for a given environment. At the second level, a real path is planned by the RRT planners for the given environment. The suggested method is applied to the control of KUKA™,, a commercial 6 DOF robot manipulator, and its feasibility and efficiency are demonstrated via the cosimulatation of MatLab™, and RecurDyn™,.
Abstract: In this article, we are going to do a study that consist in the configuration of a link between an earth station to broadcast multimedia service and a user of this service via a geostationary satellite in Ka- band and the set up of the different components of this link and then to make the calculation of the link budget for this system. The application carried out in this work, allows us to calculate the link budget in both directions: the uplink and downlink, as well as all parameters used in the calculation and the development of a link budget. Finally, we will try to verify using the application developed the feasibility of implementation of this system.
Abstract: The ionizing radiation of livestock wastewater for the
removal of nitrogen and phosphorus was studied in the presence of a
natural zeolite. The feasibility of a combined process of zeolite ion
exchange and electron beam irradiation of livestock wastewater was
also investigated. The removal efficiencies of NH4
+-N, T-N and T-P
were significantly enhanced by electron beam irradiation after zeolite
ion exchange as a pre-treatment. The presence of silica zeolite
accelerated the decomposition rate of livestock wastewater in the
electron beam irradiation process. These results indicate that the
combined process of zeolite ion exchange and electron beam
irradiation has the potential for the treatment of livestock wastewater
Abstract: It was determined that woody biomass and livestock excreta can be utilized as hydrogen resources and hydrogen produced from such sources can be used to fill fuel cell vehicles (FCVs) at hydrogen stations. It was shown that the biomass transport costs for hydrogen production may be reduced the costs for co-generation. In the Tokyo Metropolitan Area, there are only a few sites capable of producing hydrogen from woody biomass in amounts greater than 200 m3/h-the scale required for a hydrogen station to be operationally practical. However, in the case of livestock excreta, it was shown that 15% of the municipalities in this area are capable of securing sufficient biomass to be operationally practical for hydrogen production. The differences in feasibility of practical operation depend on the type of biomass.
Abstract: Text data mining is a process of exploratory data
analysis. Classification maps data into predefined groups or classes.
It is often referred to as supervised learning because the classes are
determined before examining the data. This paper describes proposed
radial basis function Classifier that performs comparative crossvalidation
for existing radial basis function Classifier. The feasibility
and the benefits of the proposed approach are demonstrated by means
of data mining problem: direct Marketing. Direct marketing has
become an important application field of data mining. Comparative
Cross-validation involves estimation of accuracy by either stratified
k-fold cross-validation or equivalent repeated random subsampling.
While the proposed method may have high bias; its performance
(accuracy estimation in our case) may be poor due to high variance.
Thus the accuracy with proposed radial basis function Classifier was
less than with the existing radial basis function Classifier. However
there is smaller the improvement in runtime and larger improvement
in precision and recall. In the proposed method Classification
accuracy and prediction accuracy are determined where the
prediction accuracy is comparatively high.
Abstract: This paper describes a feasibility study that is
included with the research, development and testing of a micro
communications sonobuoy deployable by Maritime Fixed wing
Unmanned Aerial Vehicles (M-UAV) and rotor wing Quad Copters
which are both currently being developed by the University of
Adelaide. The micro communications sonobuoy is developed to act
as a seamless communication relay between an Autonomous
Underwater Vehicle (AUV) and an above water human operator
some distance away. Development of such a device would eliminate
the requirement of physical communication tethers attached to
submersible vehicles for control and data retrieval.
Abstract: In this paper we present a photo mosaic smartphone
application in client-server based large-scale image databases. Photo
mosaic is not a new concept, but there are very few smartphone
applications especially for a huge number of images in the
client-server environment. To support large-scale image databases,
we first propose an overall framework working as a client-server
model. We then present a concept of image-PAA features to efficiently
handle a huge number of images and discuss its lower bounding
property. We also present a best-match algorithm that exploits the
lower bounding property of image-PAA. We finally implement an
efficient Android-based application and demonstrate its feasibility.
Abstract: The paper investigates the feasibility of constructing a software multi-agent based monitoring and classification system and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. The agents function autonomously to provide continuous and periodic monitoring of excels spreadsheet workbooks. Resulting in, the development of the MultiAgent classification System (MACS) that is in compliance with the specifications of the Foundation for Intelligent Physical Agents (FIPA). However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies that are Windows Communication Foundation (WCF) services, Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). The Microsoft's .NET widows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW that is in order to satisfy the monitoring and classification of the multiple developer aspect. ODM was used to automate the classification phase of MACS.
Abstract: The practice of burying the solid waste under the ground is one of the waste disposal methods and dumping is known as an ultimate method in the fastest-growing cities like Rasht city in Iran. Some municipalities select the solid waste landfills without feasibility studies, programming, design and management plans. Therefore, several social and environmental impacts are created by these sites. In this study, the suitability of solid waste landfill in Rasht city, capital of Gilan Province is reviewed using Regional Screening Method (RSM), Geographic Information System (GIS) and Analytical Hierarchy Process (AHP). The results indicated that according to the suitability maps, the value of study site is midsuitable to suitable based on RSM and mid-suitable based on AHP.
Abstract: In this paper three different approaches for person
verification and identification, i.e. by means of fingerprints, face and
voice recognition, are studied. Face recognition uses parts-based
representation methods and a manifold learning approach. The
assessment criterion is recognition accuracy. The techniques under
investigation are: a) Local Non-negative Matrix Factorization
(LNMF); b) Independent Components Analysis (ICA); c) NMF with
sparse constraints (NMFsc); d) Locality Preserving Projections
(Laplacianfaces). Fingerprint detection was approached by classical
minutiae (small graphical patterns) matching through image
segmentation by using a structural approach and a neural network as
decision block. As to voice / speaker recognition, melodic cepstral
and delta delta mel cepstral analysis were used as main methods, in
order to construct a supervised speaker-dependent voice recognition
system. The final decision (e.g. “accept-reject" for a verification
task) is taken by using a majority voting technique applied to the
three biometrics. The preliminary results, obtained for medium
databases of fingerprints, faces and voice recordings, indicate the
feasibility of our study and an overall recognition precision (about
92%) permitting the utilization of our system for a future complex
biometric card.
Abstract: Nowadays, desalination of salt water is considered an important industrial process. In many parts of the world, particularly in the gulf countries, the multi-stage flash (MSF) water desalination has an essential contribution in the production of fresh water. In this study, a simple mathematical model is defined to design a MSF desalination system and the feasibility of using the MSF desalination process in proximity of a 42 MW power plant is investigated. This power plant can just provide 10 ton/h superheated steam from low pressure (LP) section of heat recovery steam generator (HRSG) for thermal desalting system. The designed MSF system with gained output ratio (GOR) of 10.3 has 24 flashing stages and can produce 2480 ton/d of fresh water. The expected performance characteristics of the designed MSF desalination plant are determined. In addition, the effect of motive water pressure on the amount of non-condensable gases removed by water jet vacuum pumps is investigated.
Abstract: In this paper, we propose a robust disease detection
method, called adaptive orientation code matching (Adaptive OCM),
which is developed from a robust image registration algorithm:
orientation code matching (OCM), to achieve continuous and
site-specific detection of changes in plant disease. We use two-stage
framework for realizing our research purpose; in the first stage,
adaptive OCM was employed which could not only realize the
continuous and site-specific observation of disease development, but
also shows its excellent robustness for non-rigid plant object searching
in scene illumination, translation, small rotation and occlusion changes
and then in the second stage, a machine learning method of support
vector machine (SVM) based on a feature of two dimensional (2D)
xy-color histogram is further utilized for pixel-wise disease
classification and quantification. The indoor experiment results
demonstrate the feasibility and potential of our proposed algorithm,
which could be implemented in real field situation for better
observation of plant disease development.
Abstract: In recent methodological articles related to structural equation modeling (SEM), the question of how to measure endogenous formative variables has been raised as an urgent, unresolved issue. This research presents an empirical application from the CRM system development context to test a recently developed technique, which makes it possible to measure endogenous formative constructs in structural models. PLS path modeling is used to demonstrate the feasibility of measuring antecedent relationships at the formative indicator level, not the formative construct level. Empirical results show that this technique is a promising approach to measure antecedent relationships of formative constructs in SEM.
Abstract: Using Dynamic Bayesian Networks (DBN) to model genetic regulatory networks from gene expression data is one of the major paradigms for inferring the interactions among genes. Averaging a collection of models for predicting network is desired, rather than relying on a single high scoring model. In this paper, two kinds of model searching approaches are compared, which are Greedy hill-climbing Search with Restarts (GSR) and Markov Chain Monte Carlo (MCMC) methods. The GSR is preferred in many papers, but there is no such comparison study about which one is better for DBN models. Different types of experiments have been carried out to try to give a benchmark test to these approaches. Our experimental results demonstrated that on average the MCMC methods outperform the GSR in accuracy of predicted network, and having the comparable performance in time efficiency. By proposing the different variations of MCMC and employing simulated annealing strategy, the MCMC methods become more efficient and stable. Apart from comparisons between these approaches, another objective of this study is to investigate the feasibility of using DBN modeling approaches for inferring gene networks from few snapshots of high dimensional gene profiles. Through synthetic data experiments as well as systematic data experiments, the experimental results revealed how the performances of these approaches can be influenced as the target gene network varies in the network size, data size, as well as system complexity.
Abstract: The increasing demand for sufficient and clean
energy forces industrial and service companies to align their strategies towards efficient consumption. This trend refers also to the
residential building sector. There, large amounts of energy consumption are caused by house and facility heating. Many of the
operated hot water heating systems lack hydraulic balanced working
conditions for heat distribution and –transmission and lead to
inefficient heating. Through hydraulic balancing of heating systems,
significant energy savings for primary and secondary energy can be
achieved. This paper addresses the use of KNX-technology (Smart
Buildings) in residential buildings to ensure a dynamic adaption of
hydraulic system's performance, in order to increase the heating
system's efficiency. In this paper, the procedure of heating system
segmentation into hydraulically independent units (meshes) is
presented. Within these meshes, the heating valve are addressed and
controlled by a central facility server. Feasibility criteria towards
such drivers will be named. The dynamic hydraulic balance is
achieved by positioning these valves according to heating loads, that
are generated from the temperature settings in the corresponding
rooms. The energetic advantages of single room heating control
procedures, based on the application FacilityManager, is presented.
Abstract: In recent years demolished concrete waste handling and management is the new primary challenging issue faced by the countries all over the world. It is very challenging and hectic problem that has to be tackled in an indigenous manner, it is desirable to completely recycle demolished concrete waste in order to protect natural resources and reduce environmental pollution. In this research paper an experimental study is carried out to investigate the feasibility and recycling of demolished waste concrete for new construction. The present investigation to be focused on recycling demolished waste materials in order to reduce construction cost and resolving housing problems faced by the low income communities of the world. The crushed demolished concrete wastes is segregated by sieving to obtain required sizes of aggregate, several tests were conducted to determine the aggregate properties before recycling it into new concrete. This research shows that the recycled aggregate that are obtained from site make good quality concrete. The compressive strength test results of partial replacement and full recycled aggregate concrete and are found to be higher than the compressive strength of normal concrete with new aggregate.
Abstract: Current OCR technology does not allow to
accurately recognizing small text images, such as those found
in web images. Our goal is to investigate new approaches to
recognize very low resolution text images containing antialiased
character shapes.
This paper presents a preliminary study on the variability of
such characters and the feasibility to discriminate them by
using geometrical features. In a first stage we analyze the
distribution of these features. In a second stage we present a
study on the discriminative power for recognizing isolated
characters, using various rendering methods and font
properties. Finally we present interesting results of our
evaluation tests leading to our conclusion and future focus.
Abstract: Fecal coliform bacteria are widely used as indicators of
sewage contamination in surface water. However, there are some
disadvantages in these microbial techniques including time consuming
(18-48h) and inability in discriminating between human and animal
fecal material sources. Therefore, it is necessary to seek a more
specific indicator of human sanitary waste. In this study, the feasibility
was investigated to apply caffeine and human pharmaceutical
compounds to identify the human-source contamination. The
correlation between caffeine and fecal coliform was also explored.
Surface water samples were collected from upstream, middle-stream
and downstream points respectively, along Rochor Canal, as well as 8
locations of Marina Bay. Results indicate that caffeine is a suitable
chemical tracer in Singapore because of its easy detection (in the range
of 0.30-2.0 ng/mL), compared with other chemicals monitored.
Relative low concentrations of human pharmaceutical compounds (<
0.07 ng/mL) in Rochor Canal and Marina Bay water samples make
them hard to be detected and difficult to be chemical tracer. However,
their existence can help to validate sewage contamination. In addition,
it was discovered the high correlation exists between caffeine
concentration and fecal coliform density in the Rochor Canal water
samples, demonstrating that caffeine is highly related to the
human-source contamination.