Abstract: Nowadays there is a growing environmental concern
and the business communities have slowly started recognising
environmental protection and sustainable utilization of natural
resources into their marketing strategies. This paper discusses the
various Ecolabeling and Certification Systems developed world
over to regulate and introduce Fair Trade in Ornamental Fish
Industry. Ecolabeling and green certification are considered as part
of these strategies implemented partly out of compulsion from the
National and International Regulatory Bodies and Environmental
Movements. All the major markets of ornamental fishes like
European Union, USA and Japan have started putting restrictions on
the trade to impose ecolabeling as a non tariff barrier like the one
imposed on seafood and aqua cultured products. A review was done
on the available Ecolabeling and Green Certification Schemes
available at local, national and international levels for fisheries
including aquaculture and ornamental fish trade and to examine the
success and constraints faced by these schemes during its
implementation. The primary downside of certification is the
multiplicity of ecolabels and cost incurred by applicants for
certification, costs which may in turn be passed on to consumers.
The studies reveal serious inadequacies in a number of ecolabels
and cast doubt on their overall contribution to effective fisheries
management and sustainability. The paper also discusses the
inititive taken in India to develop guidelines for Green Certification
of Fresh water ornamental fishes.
Abstract: Vinegar or sour wine is a product of alcoholic and
subsequent acetous fermentation of sugary precursors derived from
several fruits or starchy substrates. This delicious food additive and
supplement contains not less than 4 grams of acetic acid in 100 cubic
centimeters at 20°C. Among the large number of bacteria that are
able to produce acetic acid, only few genera are used in vinegar
industry most significant of which are Acetobacter and
Gluconobacter. In this research we isolated and identified an
Acetobacter strain from Iranian apricot, a very delicious and sensitive
summer fruit to decay, we gathered from fruit's stores in Isfahan,
Iran. The main culture media we used were Carr, GYC, Frateur and
an industrial medium for vinegar production. We isolated this strain
using a novel miniature fermentor we made at Pars Yeema
Biotechnologists Co., Isfahan Science and Technology Town (ISTT),
Isfahan, Iran. The microscopic examinations of isolated strain from
Iranian apricot showed gram negative rods to cocobacilli. Their
catalase reaction was positive and oxidase reaction was negative and
could ferment ethanol to acetic acid. Also it showed an acceptable
growth in 5%, 7% and 9% ethanol concentrations at 30°C using
modified Carr media after 24, 48 and 96 hours incubation
respectively. According to its tolerance against high concentrations of
ethanol after four days incubation and its high acetic acid production,
8.53%, after 144 hours, this strain could be considered as a suitable
industrial strain for a production of a new type of vinegar, apricot
vinegar, with a new and delicious taste. In conclusion this is the first
report of isolation and identification of an Acetobacter strain from
Iranian apricot with a very good tolerance against high ethanol
concentrations as well as high acetic acid productivity in an
acceptable incubation period of time industrially. This strain could be
used in vinegar industry to convert apricot spoilage to a beneficiary
product and mentioned characteristics have made it as an amenable
strain in food and agricultural biotechnology.
Abstract: Due to the limited energy resources, energy efficient operation of sensor node is a key issue in wireless sensor networks. Clustering is an effective method to prolong the lifetime of energy constrained wireless sensor network. However, clustering in wireless sensor network faces several challenges such as selection of an optimal group of sensor nodes as cluster, optimum selection of cluster head, energy balanced optimal strategy for rotating the role of cluster head in a cluster, maintaining intra and inter cluster connectivity and optimal data routing in the network. In this paper, we propose a protocol supporting an energy efficient clustering, cluster head selection/rotation and data routing method to prolong the lifetime of sensor network. Simulation results demonstrate that the proposed protocol prolongs network lifetime due to the use of efficient clustering, cluster head selection/rotation and data routing.
Abstract: In this paper, we propose improved versions of DVHop
algorithm as QDV-Hop algorithm and UDV-Hop algorithm for
better localization without the need for additional range measurement
hardware. The proposed algorithm focuses on third step of DV-Hop,
first error terms from estimated distances between unknown node and
anchor nodes is separated and then minimized. In the QDV-Hop
algorithm, quadratic programming is used to minimize the error to
obtain better localization. However, quadratic programming requires
a special optimization tool box that increases computational
complexity. On the other hand, UDV-Hop algorithm achieves
localization accuracy similar to that of QDV-Hop by solving
unconstrained optimization problem that results in solving a system
of linear equations without much increase in computational
complexity. Simulation results show that the performance of our
proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop
and DV-Hop based algorithms in all considered scenarios.
Abstract: The growing interest on national heritage
preservation has led to intensive efforts on digital documentation of
cultural heritage knowledge. Encapsulated within this effort is the
focus on ontology development that will help facilitate the
organization and retrieval of the knowledge. Ontologies surrounding
cultural heritage domain are related to archives, museum and library
information such as archaeology, artifacts, paintings, etc. The growth
in number and size of ontologies indicates the well acceptance of its
semantic enrichment in many emerging applications. Nowadays,
there are many heritage information systems available for access.
Among others is community-based e-museum designed to support the
digital cultural heritage preservation. This work extends previous
effort of developing the Traditional Malay Textile (TMT) Knowledge
Model where the model is designed with the intention of auxiliary
mapping with CIDOC CRM. Due to its internal constraints, the
model needs to be transformed in advance. This paper addresses the
issue by reviewing the previous harmonization works with CIDOC
CRM as exemplars in refining the facets in the model particularly
involving TMT-Artifact class. The result is an extensible model
which could lead to a common view for automated mapping with
CIDOC CRM. Hence, it promotes integration and exchange of
textile information especially batik-related between communities in
e-museum applications.
Abstract: This paper has two main ideas. Firstly, it describes Evans and Wurster-s concepts “the trade-off between reach and richness", and relates them to the impact of technology on the virtual markets. Authors Evans and Wurster see the transfer of information as a 'trade'off between richness and reach-. Reach refers to the number of people who share particular information, with Richness ['Rich'] being a more complex concept combining: bandwidth, customization, interactivity, reliability, security and currency. Traditional shopping limits the number of shops the shopper is able to visit due to time and other cost constraints; the time spent traveling consequently leaves the shopper with less time to evaluate the product. The paper concludes that although the Web provides Reach, offering Richness and the sense of community required for creating and sustaining relationships with potential clients could be difficult.
Abstract: Over the past several years, there has been a
considerable amount of research within the field of Quality of
Service (QoS) support for distributed multimedia systems. One of the
key issues in providing end-to-end QoS guarantees in packet
networks is determining a feasible path that satisfies a number of
QoS constraints. The problem of finding a feasible path is NPComplete
if number of constraints is more than two and cannot be
exactly solved in polynomial time. We proposed Feasible Path
Selection Algorithm (FPSA) that addresses issues with pertain to
finding a feasible path subject to delay and cost constraints and it
offers higher success rate in finding feasible paths.
Abstract: Avionics software is safe-critical embedded software
and its architecture is evolving from traditional federated architectures
to Integrated Modular Avionics (IMA) to improve resource usability.
ARINC 653 (Avionics Application Standard Software Interface) is a
software specification for space and time partitioning in Safety-critical
avionics Real-time operating systems. Arinc653 uses two-level
scheduling strategies, but current modeling tools only apply to simple
problems of Arinc653 two-level scheduling, which only contain time
property. In avionics industry, we are always manually allocating
tasks and calculating the timing table of a real-time system to ensure
it-s running as we design. In this paper we represent an automatically
generating strategy which applies to the two scheduling problems with
dependent constraints in Arinc653 partition run-time environment. It
provides the functionality of automatic generation from the task and partition models to scheduling policy through allocating the tasks to the partitions while following the constraints, and then we design a simulating mechanism to check whether our policy is schedulable or
not
Abstract: Performance of vehicle depends on driving patterns
and vehicle drive train configuration. Driving patterns depends on
traffic condition, road condition and driver behavior. HEV design is
carried out under certain constrain like vehicle operating range,
acceleration, decelerations, maximum speed and road grades which
are directly related to the driving patterns. Therefore the detailed
study on HEV performance over a different drive cycle is required
for selection and sizing of HEV components. A simple hardware is
design to measured velocity v/s time profile of the vehicle by
operating vehicle on Indian roads under real traffic conditions. To
size the HEV components, a detailed dynamic model of the vehicle is
developed considering the effect of inertia of rotating components
like wheels, drive chain, engine and electric motor. Using vehicle
model and different Indian drive cycles data, total tractive power
demanded by vehicle and power supplied by individual components
has been calculated.Using above information selection and estimation
of component sizing for HEV is carried out so that HEV performs
efficiently under hostile driving condition. Complete analysis is
carried out in LABVIEW.
Abstract: Rhizopus oligosporus was used in the present study
for the production of protease enzyme under SSF. Sunflower meal
was used as by-product of oil industry incorporated with organic salts
was employed for the production of protease enzyme. The main
purpose of the present was to study different parameters of protease
productivity, its yields and to optimize basal fermentation conditions.
The optimal conditions found for protease production using
sunflower meal as a substrate in the present study were inoculum size
(1%), substrate (Sunflower meal), substrate concentration (20 g), pH
(3), cultivation period (72 h), incubation temperature (35oC),
substrate to diluent-s ratio (1:2) and tween 81 (1 mL). The maximum
production of protease in the presence of cheaper substrate at low
concentration and stability at acidic pH, these characteristics make
the strain and its enzymes useful in different industry.
Abstract: For evaluating the severity of Chronic Obstructive Pulmonary Disease (COPD), one is interested in inspecting the airway wall thickening due to inflammation. Although airway segmentations have being well developed to reconstruct in high order, airway wall segmentation remains a challenge task. While tackling such problem as a multi-surface segmentation, the interrelation within surfaces needs to be considered. We propose a new method for three-dimensional airway wall segmentation using spring structural active contour model. The method incorporates the gravitational field of the image and repelling force field of the inner lumen as the soft constraint and the geometric spring structure of active contour as the hard constraint to approximate a three-dimensional coupled surface readily for thickness measurements. The results show the preservation of topology constraints of coupled surfaces. In conclusion, our springy, soft-tissue-like structure ensures the globally optimal solution and waives the shortness following by the inevitable improper inner surface constraint.
Abstract: Semantic query optimization consists in restricting the
search space in order to reduce the set of objects of interest for a
query. This paper presents an indexing method based on UB-trees
and a static analysis of the constraints associated to the views of the
database and to any constraint expressed on attributes. The result of
the static analysis is a partitioning of the object space into disjoint
blocks. Through Space Filling Curve (SFC) techniques, each
fragment (block) of the partition is assigned a unique identifier,
enabling the efficient indexing of fragments by UB-trees. The search
space corresponding to a range query is restricted to a subset of the
blocks of the partition. This approach has been developed in the
context of a KB-DBMS but it can be applied to any relational
system.
Abstract: Virtualization-based server consolidation has been
proven to be an ideal technique to solve the server sprawl problem by
consolidating multiple virtualized servers onto a few physical servers
leading to improved resource utilization and return on investment. In
this paper, we solve this problem by using existing servers, which are
heterogeneous and diversely preferred by IT managers. Five practical
consolidation rules are introduced, and a decision model is proposed to
optimally allocate source services to physical target servers while
maximizing the average resource utilization and preference value. Our
model can be regarded as a multi-objective multi-dimension
bin-packing (MOMDBP) problem with constraints, which is strongly
NP-hard. An improved grouping generic algorithm (GGA) is
introduced for the problem. Extensive simulations were performed and
the results are given.
Abstract: Software-as-a-Service (SaaS) is a form of cloud
computing that relieves the user of the burden of hardware and
software installation and management. SaaS can be used at the course
level to enhance curricula and student experience. When cloud
computing and SaaS are included in educational literature, the focus
is typically on implementing administrative functions. Yet, SaaS can
make more immediate and substantial contributions to the technical
course content in educational offerings. This paper explores cloud
computing and SaaS, provides examples, reports on experiences
using SaaS to offer specialized software in courses, and analyzes the
advantages and disadvantages of using SaaS at the course level. The
paper contributes to the literature in higher education by analyzing
the major technical concepts, potential, and constraints for using
SaaS to deliver specialized software at the course level. Further it
may enable more educators and students to benefit from this
emerging technology.
Abstract: In this paper, we propose an effective relay
communication for layered video transmission as an alternative to
make the most of limited resources in a wireless communication
network where loss often occurs. Relaying brings stable multimedia
services to end clients, compared to multiple description coding
(MDC). Also, retransmission of only parity data about one or more
video layer using channel coder to the end client of the relay device is
paramount to the robustness of the loss situation. Using these
methods in resource-constrained environments, such as real-time user
created content (UCC) with layered video transmission, can provide
high-quality services even in a poor communication environment.
Minimal services are also possible. The mathematical analysis shows
that the proposed method reduced the probability of GOP loss rate
compared to MDC and raptor code without relay. The GOP loss rate
is about zero, while MDC and raptor code without relay have a GOP
loss rate of 36% and 70% in case of 10% frame loss rate.
Abstract: In this research, we have developed a new efficient
heuristic algorithm for the dynamic facility layout problem with
budget constraint (DFLPB). This heuristic algorithm combines two
mathematical programming methods such as discrete event
simulation and linear integer programming (IP) to obtain a near
optimum solution. In the proposed algorithm, the non-linear model
of the DFLP has been changed to a pure integer programming (PIP)
model. Then, the optimal solution of the PIP model has been used in
a simulation model that has been designed in a similar manner as the
DFLP for determining the probability of assigning a facility to a
location. After a sufficient number of runs, the simulation model
obtains near optimum solutions. Finally, to verify the performance of
the algorithm, several test problems have been solved. The results
show that the proposed algorithm is more efficient in terms of speed
and accuracy than other heuristic algorithms presented in previous
works found in the literature.
Abstract: Wireless sensor networks is an emerging technology
that serves as environment monitors in many applications. Yet
these miniatures suffer from constrained resources in terms of
computation capabilities and energy resources. Limited energy
resource in these nodes demands an efficient consumption of that
resource either by developing the modules itself or by providing
an efficient communication protocols. This paper presents a
comprehensive summarization and a comparative study of the
available MAC protocols proposed for Wireless Sensor Networks
showing their capabilities and efficiency in terms of energy
consumption and delay guarantee.
Abstract: This paper presents a novel method for prediction of
the mechanical behavior of proximal femur using the general
framework of the quantitative computed tomography (QCT)-based
finite element Analysis (FEA). A systematic imaging and modeling
procedure was developed for reliable correspondence between the
QCT-based FEA and the in-vitro mechanical testing. A speciallydesigned
holding frame was used to define and maintain a unique
geometrical reference system during the analysis and testing. The
QCT images were directly converted into voxel-based 3D finite
element models for linear and nonlinear analyses. The equivalent
plastic strain and the strain energy density measures were used to
identify the critical elements and predict the failure patterns. The
samples were destructively tested using a specially-designed gripping
fixture (with five degrees of freedom) mounted within a universal
mechanical testing machine. Very good agreements were found
between the experimental and the predicted failure patterns and the
associated load levels.
Abstract: In this paper, an automatic control system design
based on Integral Squared Error (ISE) parameter optimization
technique has been implemented on longitudinal flight dynamics of
an UAV. It has been aimed to minimize the error function between
the reference signal and the output of the plant. In the following
parts, objective function has been defined with respect to error
dynamics. An unconstrained optimization problem has been solved
analytically by using necessary and sufficient conditions of
optimality, optimum PID parameters have been obtained and
implemented in control system dynamics.
Abstract: The network of delivering commodities has been an important design problem in our daily lives and many transportation applications. The delivery performance is evaluated based on the system reliability of delivering commodities from a source node to a sink node in the network. The system reliability is thus maximized to find the optimal routing. However, the design problem is not simple because (1) each path segment has randomly distributed attributes; (2) there are multiple commodities that consume various path capacities; (3) the optimal routing must successfully complete the delivery process within the allowable time constraints. In this paper, we want to focus on the design optimization of the Multi-State Flow Network (MSFN) for multiple commodities. We propose an efficient approach to evaluate the system reliability in the MSFN with respect to randomly distributed path attributes and find the optimal routing subject to the allowable time constraints. The delivery rates, also known as delivery currents, of the path segments are evaluated and the minimal-current arcs are eliminated to reduce the complexity of the MSFN. Accordingly, the correct optimal routing is found and the worst-case reliability is evaluated. It has been shown that the reliability of the optimal routing is at least higher than worst-case measure. Two benchmark examples are utilized to demonstrate the proposed method. The comparisons between the original and the reduced networks show that the proposed method is very efficient.