Abstract: The dramatic increasing of sea-freight container
transportations and the developing trends for using containers in the
multimodal handling systems through the sea, rail, road and land in
nowadays market cause general managers of container terminals to
face challenges such as increasing demand, competitive situation,
new investments and expansion of new activities and need to use new
methods to fulfil effective operations both along quayside and within
the yard. Among these issues, minimizing the turnaround time of
vessels is considered to be the first aim of every container port
system. Regarding the complex structure of container ports, this
paper presents a simulation model that calculates the number of
trucks needed in the Iranian Shahid Rajaee Container Port for
handling containers between the berth and the yard. In this research,
some important criteria such as vessel turnaround time, gantry crane
utilization and truck utilization have been considered. By analyzing
the results of the model, it has been shown that increasing the number
of trucks to 66 units has a significant effect on the performance
indices of the port and can increase the capacity of loading and
unloading up to 10.8%.
Abstract: Breast motion and discomfort has been studied in
Australia, Britain and the United States, while little information was
known about the breast motion conditions of Chinese women. The aim
of this paper was to study the breast motion and discomfort of Chinese
women in no bra condition, daily bra condition and sports bra
condition. Breast motion and discomfort of 8 participants was assessed
during walking at 5km h-1 and running at 10km h-1. Statistical methods
were used to analyze the difference and relationship between breast
displacement, perceived breast motion and breast discomfort. Three
indexes were developed to evaluate the functions of bras on reducing
objective breast motion, subjective breast motion and breast
discomfort. The result showed that breast motion of Chinese women
was smaller than previous research, which may be resulted from
smaller breast size in Asian women.
Abstract: In current common research reports, salient regions
are usually defined as those regions that could present the main
meaningful or semantic contents. However, there are no uniform
saliency metrics that could describe the saliency of implicit image
regions. Most common metrics take those regions as salient regions,
which have many abrupt changes or some unpredictable
characteristics. But, this metric will fail to detect those salient useful
regions with flat textures. In fact, according to human semantic
perceptions, color and texture distinctions are the main characteristics
that could distinct different regions. Thus, we present a novel saliency
metric coupled with color and texture features, and its corresponding
salient region extraction methods. In order to evaluate the
corresponding saliency values of implicit regions in one image, three
main colors and multi-resolution Gabor features are respectively used
for color and texture features. For each region, its saliency value is
actually to evaluate the total sum of its Euclidean distances for other
regions in the color and texture spaces. A special synthesized image
and several practical images with main salient regions are used to
evaluate the performance of the proposed saliency metric and other
several common metrics, i.e., scale saliency, wavelet transform
modulus maxima point density, and important index based metrics.
Experiment results verified that the proposed saliency metric could
achieve more robust performance than those common saliency
metrics.
Abstract: Complexity, as a theoretical background has made it
easier to understand and explain the features and dynamic behavior
of various complex systems. As the common theoretical background
has confirmed, borrowing the terminology for design from the
natural sciences has helped to control and understand urban
complexity. Phenomena like self-organization, evolution and
adaptation are appropriate to describe the formerly inaccessible
characteristics of the complex environment in unpredictable bottomup
systems. Increased computing capacity has been a key element in
capturing the chaotic nature of these systems.
A paradigm shift in urban planning and architectural design has
forced us to give up the illusion of total control in urban
environment, and consequently to seek for novel methods for
steering the development. New methods using dynamic modeling
have offered a real option for more thorough understanding of
complexity and urban processes. At best new approaches may renew
the design processes so that we get a better grip on the complex
world via more flexible processes, support urban environmental
diversity and respond to our needs beyond basic welfare by liberating
ourselves from the standardized minimalism.
A complex system and its features are as such beyond human
ethics. Self-organization or evolution is either good or bad. Their
mechanisms are by nature devoid of reason. They are common in
urban dynamics in both natural processes and gas. They are features
of a complex system, and they cannot be prevented. Yet their
dynamics can be studied and supported.
The paradigm of complexity and new design approaches has been
criticized for a lack of humanity and morality, but the ethical
implications of scientific or computational design processes have not
been much discussed. It is important to distinguish the (unexciting)
ethics of the theory and tools from the ethics of computer aided
processes based on ethical decisions. Urban planning and architecture
cannot be based on the survival of the fittest; however, the natural
dynamics of the system cannot be impeded on grounds of being
“non-human".
In this paper the ethical challenges of using the dynamic models
are contemplated in light of a few examples of new architecture and
dynamic urban models and literature. It is suggested that ethical
challenges in computational design processes could be reframed
under the concepts of responsibility and transparency.
Abstract: Applicability of tuning the controller gains for Stewart manipulator using genetic algorithm as an efficient search technique is investigated. Kinematics and dynamics models were introduced in detail for simulation purpose. A PD task space control scheme was used. For demonstrating technique feasibility, a Stewart manipulator numerical-model was built. A genetic algorithm was then employed to search for optimal controller gains. The controller was tested onsite a generic circular mission. The simulation results show that the technique is highly convergent with superior performance operating for different payloads.
Abstract: Multi-agent system approach has proven to be an effective and appropriate abstraction level to construct whole models of a diversity of biological problems, integrating aspects which can be found both in "micro" and "macro" approaches when modeling this type of phenomena. Taking into account these considerations, this paper presents the important computational characteristics to be gathered into a novel bioinformatics framework built upon a multiagent architecture. The version of the tool presented herein allows studying and exploring complex problems belonging principally to structural biology, such as protein folding. The bioinformatics framework is used as a virtual laboratory to explore a minimalist model of protein folding as a test case. In order to show the laboratory concept of the platform as well as its flexibility and adaptability, we studied the folding of two particular sequences, one of 45-mer and another of 64-mer, both described by an HP model (only hydrophobic and polar residues) and coarse grained 2D-square lattice. According to the discussion section of this piece of work, these two sequences were chosen as breaking points towards the platform, in order to determine the tools to be created or improved in such a way to overcome the needs of a particular computation and analysis of a given tough sequence. The backwards philosophy herein is that the continuous studying of sequences provides itself important points to be added into the platform, to any time improve its efficiency, as is demonstrated herein.
Abstract: This paper explains a project based learning method where autonomous mini-robots are developed for research, education and entertainment purposes. In case of remote systems wireless sensors are developed in critical areas, which would collect data at specific time intervals, send the data to the central wireless node based on certain preferred information would make decisions to turn on or off a switch or control unit. Such information transfers hardly sums up to a few bytes and hence low data rates would suffice for such implementations. As a robot is a multidisciplinary platform, the interfacing issues involved are discussed in this paper. The paper is mainly focused on power supply, grounding and decoupling issues.
Abstract: Perspective of food security in 21 century showed
shortage of food that production is faced to vital problem. Food
security strategy is applied longtime method to assess required food.
Meanwhile, nanotechnology revolution changes the world face.
Nanotechnology is adequate method utilize of its characteristics to
decrease environmental problems and possible further access to food
for small farmers. This article will show impact of production and
adoption of nanocrops on food security. Population is researchers of
agricultural research center of Esfahan province. The results of study
show that there was a relationship between uses, conversion,
distribution, and production of nanocrops, operative human
resources, operative circumstance, and constrains of usage of
nanocrops and food security. Multivariate regression analysis by
enter model shows that operative circumstance, use, production and
constrains of usage of nanocrops had positive impact on food security
and they determine in four steps 20 percent of it.
Abstract: Mathematical, graphical and intuitive models are often
constructed in the development process of computational systems.
The Unified Modeling Language (UML) is one of the most popular
modeling languages used by practicing software engineers. This
paper critically examines UML models and suggests an augmented
use case view with the addition of new constructs for modeling
software. It also shows how a use case diagram can be enhanced. The
improved modeling constructs are presented with examples for
clarifying important design and implementation issues.
Abstract: The main aim of this research is to investigate a novel technique for implementing a more natural and intelligent conversation system. Conversation systems are designed to converse like a human as much as their intelligent allows. Sometimes, we can think that they are the embodiment of Turing-s vision. It usually to return a predetermined answer in a predetermined order, but conversations abound with uncertainties of various kinds. This research will focus on an integrated natural language processing approach. This approach includes an integrated knowledge-base construction module, a conversation understanding and generator module, and a state manager module. We discuss effectiveness of this approach based on an experiment.
Abstract: The necessity of updating the numerical models inputs, because of geometrical and resistive variations in rivers subject to solid transport phenomena, requires detailed control and monitoring activities. The human employment and financial resources of these activities moves the research towards the development of expeditive methodologies, able to evaluate the outflows through the measurement of more easily acquirable sizes. Recent studies highlighted the dependence of the entropic parameter on the kinematical and geometrical flow conditions. They showed a meaningful variability according to the section shape, dimension and slope. Such dependences, even if not yet well defined, could reduce the difficulties during the field activities, and also the data elaboration time. On the basis of such evidences, the relationships between the entropic parameter and the geometrical and resistive sizes, obtained through a large and detailed laboratory experience on steady free surface flows in conditions of macro and intermediate homogeneous roughness, are analyzed and discussed.
Abstract: The aim of this paper is to present a methodology in
three steps to forecast supply chain demand. In first step, various data
mining techniques are applied in order to prepare data for entering
into forecasting models. In second step, the modeling step, an
artificial neural network and support vector machine is presented
after defining Mean Absolute Percentage Error index for measuring
error. The structure of artificial neural network is selected based on
previous researchers' results and in this article the accuracy of
network is increased by using sensitivity analysis. The best forecast
for classical forecasting methods (Moving Average, Exponential
Smoothing, and Exponential Smoothing with Trend) is resulted based
on prepared data and this forecast is compared with result of support
vector machine and proposed artificial neural network. The results
show that artificial neural network can forecast more precisely in
comparison with other methods. Finally, forecasting methods'
stability is analyzed by using raw data and even the effectiveness of
clustering analysis is measured.
Abstract: Due to the increasing and varying risks that economic units face with, derivative instruments gain substantial importance, and trading volumes of derivatives have reached very significant level. Parallel with these high trading volumes, researchers have developed many different models. Some are parametric, some are nonparametric. In this study, the aim is to analyse the success of artificial neural network in pricing of options with S&P 100 index options data. Generally, the previous studies cover the data of European type call options. This study includes not only European call option but also American call and put options and European put options. Three data sets are used to perform three different ANN models. One only includes data that are directly observed from the economic environment, i.e. strike price, spot price, interest rate, maturity, type of the contract. The others include an extra input that is not an observable data but a parameter, i.e. volatility. With these detail data, the performance of ANN in put/call dimension, American/European dimension, moneyness dimension is analyzed and whether the contribution of the volatility in neural network analysis make improvement in prediction performance or not is examined. The most striking results revealed by the study is that ANN shows better performance when pricing call options compared to put options; and the use of volatility parameter as an input does not improve the performance.
Abstract: Introducing survivability into embedded real-time system (ERTS) can improve the survivability power of the system. This paper mainly discusses about the survivability of ERTS. The first is the survivability origin of ERTS. The second is survivability analysis. According to the definition of survivability based on survivability specification and division of the entire survivability analysis process for ERTS, a survivability analysis profile is presented. The quantitative analysis model of this profile is emphasized and illuminated in detail, the quantifying analysis of system was showed helpful to evaluate system survivability more accurate. The third is platform design of survivability analysis. In terms of the profile, the analysis process is encapsulated and assembled into one platform, on which quantification, standardization and simplification of survivability analysis are all achieved. The fourth is survivability design. According to character of ERTS, strengthened design method is selected to realize system survivability design. Through the analysis of embedded mobile video-on-demand system, intrusion tolerant technology is introduced in whole survivability design.
Abstract: NFκB activation plays a crucial role in anti-apoptotic responses in response to the apoptotic signaling during tumor necrosis factor (TNFa) stimulation in Multiple Myeloma (MM). Although several drugs have been found effective for the treatment of MM by mainly inhibiting NFκB pathway, there are no any quantitative or qualitative results of comparison assessment on inhibition effect between different single drugs or drug combinations. Computational modeling is becoming increasingly indispensable for applied biological research mainly because it can provide strong quantitative predicting power. In this study, a novel computational pathway modeling approach is employed to comparably assess the inhibition effects of specific single drugs and drug combinations on the NFκB pathway in MM, especially the prediction of synergistic drug combinations.
Abstract: Wireless sensor networks (WSN) are currently
receiving significant attention due to their unlimited potential. These
networks are used for various applications, such as habitat
monitoring, automation, agriculture, and security. The efficient nodeenergy
utilization is one of important performance factors in wireless
sensor networks because sensor nodes operate with limited battery
power. In this paper, we proposed the MiSense hierarchical cluster
based routing algorithm (MiCRA) to extend the lifetime of sensor
networks and to maintain a balanced energy consumption of nodes.
MiCRA is an extension of the HEED algorithm with two levels of
cluster heads. The performance of the proposed protocol has been
examined and evaluated through a simulation study. The simulation
results clearly show that MiCRA has a better performance in terms of
lifetime than HEED. Indeed, MiCRA our proposed protocol can
effectively extend the network lifetime without other critical
overheads and performance degradation. It has been noted that there
is about 35% of energy saving for MiCRA during the clustering
process and 65% energy savings during the routing process compared
to the HEED algorithm.
Abstract: As a result of urbanization, the unpredictable growth of industry and transport, production of chemicals, military activities, etc. the concentration of anthropogenic toxicants spread in nature exceeds all the permissible standards. Most dangerous among these contaminants are organic compounds having great persistence, bioaccumulation, and toxicity along with our awareness of their prominent occurrence in the environment and food chain. Among natural ecological tools, plants still occupying above 40% of the world land, until recently, were considered as organisms having only a limited ecological potential, accumulating in plant biomass and partially volatilizing contaminants of different structure. However, analysis of experimental data of the last two decades revealed the essential role of plants in environment remediation due to ability to carry out intracellular degradation processes leading to partial or complete decomposition of carbon skeleton of different structure contaminants. Though, phytoremediation technologies still are in research and development, their various applications have been successfully used. The paper aims to analyze mechanisms of organic contaminants uptake and detoxification in plants, being the less studied issue in evaluation and exploration of plants potential for environment remediation.
Abstract: This research was conducted for the first time at the
southeastern coasts of the Caspian Sea in order to evaluate the
performance of osteichthyes cooperatives through production (catch)
function. Using one of the indirect valuation methods in this research,
contributory factors in catch were identified and were inserted into
the function as independent variables. In order to carry out this
research, the performance of 25 Osteichthyes catching cooperatives
in the utilization year of 2009 which were involved in fishing in
Miankale wildlife refuge region. The contributory factors in catch
were divided into groups of economic, ecological and biological
factors. In the mentioned function, catch rate of the cooperative were
inserted into as the dependant variable and fourteen partial variables
in terms of nine general variables as independent variables. Finally,
after function estimation, seven variables were rendered significant at
99 percent reliably level. The results of the function estimation
indicated that human resource (fisherman quantity) had the greatest
positive effect on catch rate with an influence coefficient of 1.7 while
weather conditions had the greatest negative effect on the catch rate
of cooperatives with an influence coefficient of -2.07. Moreover,
factors like member's share, experience and fisherman training and
fishing effort played the main roles in the catch rate of cooperative
with influence coefficients of 0.81, 0.5 and 0.21, respectively.
Abstract: Choosing the right metadata is a critical, as good
information (metadata) attached to an image will facilitate its
visibility from a pile of other images. The image-s value is enhanced
not only by the quality of attached metadata but also by the technique
of the search. This study proposes a technique that is simple but
efficient to predict a single human image from a website using the
basic image data and the embedded metadata of the image-s content
appearing on web pages. The result is very encouraging with the
prediction accuracy of 95%. This technique may become a great
assist to librarians, researchers and many others for automatically and
efficiently identifying a set of human images out of a greater set of
images.
Abstract: The research objective of the project and article
“European Ecological Network Natura 2000 – opportunities and
threats” Natura 2000 sites constitute a form of environmental
protection, several legal problems are likely to result. Most
controversially, certain sites will be subject to two regimes of
protection: as national parks and as Natura 2000 sites. This dualism
of the legal regulation makes it difficult to perform certain legal
obligations related to the regimes envisaged under each form of
environmental protection. Which regime and which obligations
resulting from the particular form of environmental protection have
priority and should prevail? What should be done if these obligations
are contradictory? Furthermore, an institutional problem consists in
that no public administration authority has the power to resolve legal
conflicts concerning the application of a particular regime on a given
site. There are also no criteria to decide priority and superiority of
one form of environmental protection over the other. Which
regulations are more important, those that pertain to national parks or
to Natura 2000 sites? In the light of the current regulations, it is
impossible to give a decisive answer to these questions. The internal
hierarchy of forms of environmental protection has not been
determined, and all such forms should be treated equally.