Abstract: Breast cancer is the most common malignancy in the
world among women. Many therapies have been designed to treat
this disease. Mamectomy, chemotherapy and radiotherapy are still
the main therapies of breast cancer. However, the results were
unsatisfactory and still far from the ideal treatment.
PM 701is a natural product, has anticancer activity. The bioactive
fraction PMF and subfraction PMFK had been isolated from PM701.
PM 701 and its fractions were proved to have a cytotoxic properties
against different cancer cell lines. This article is directed for the
further examination of lyophilized PM701 and its active fractions on
the growth of breast cancer cells (MCF-7). PM 701, PMF or PMFK
were adding to the cultural medium, where MCF-7 is incubated.
PM 701, PMF or PMFK were able to inhibit significantly the
proliferation of MCF-7 cells, Moreover these new agents were
proved to induce apoptosis of the breast cancer cells; through its
direct effect on the nuclei.
Abstract: Abai Kunanbayev is famous for being enlightener,
composer, interpreter, social agent, philosopher, reformer, who
wanted to enrich Kazakh literature by emergence with Russian and
European culture, and also as a founder of Kazakh written literary
language. Abai Kunanbayev was born in 1845 in East Kazakhstan
area and passed away in 1904 in his hometown. His oeuvre absorbed
and reflected all changes in the life of Kazakh society of the second
half of XIX century. Because ХІХ century, especially its second half,
was an important transition period for Kazakhstan, which radically
changed traditional way of Kazakh society and predetermined further
development in consequence of activation of Russian colonial policy
and approval of commodity-money relations in Steppe Land.Abai
Kunanbayev, besides Arabic and Persian common words and
loanwords from Quran in his words of edification, had used a lot of
words of Arabic, Persian, Latin, Russian, Nogai, Shaghatai, Polish,
Greek, Turkish, which are used in the Kazakh language.
Abstract: The multi-agent system for processing Bio-signals
will help the medical practitioners to have a standard examination
procedure stored in web server. Web Servers supporting any standard
Search Engine follow all possible combinations of the search
keywords as an input by the user to a Search Engine. As a result, a
huge number of Web-pages are shown in the Web browser. It also
helps the medical practitioner to interact with the expert in the field
his need in order to make a proper judgment in the diagnosis phase
[3].A web server uses a web server plug in to establish and
maintained the medical practitioner to make a fast analysis. If the
user uses the web server client can get a related data requesting their
search. DB agent, EEG / ECG / EMG agents- user placed with
difficult aspects for updating medical information-s in web server.
Abstract: A multi-agent system is developed here to predict
monthly details of the upcoming peak of the 24th solar magnetic
cycle. While studies typically predict the timing and magnitude of
cycle peaks using annual data, this one utilizes the unsmoothed
monthly sunspot number instead. Monthly numbers display more
pronounced fluctuations during periods of strong solar magnetic
activity than the annual sunspot numbers. Because strong magnetic
activities may cause significant economic damages, predicting
monthly variations should provide different and perhaps helpful
information for decision-making purposes. The multi-agent system
developed here operates in two stages. In the first, it produces twelve
predictions of the monthly numbers. In the second, it uses those
predictions to deliver a final forecast. Acting as expert agents, genetic
programming and neural networks produce the twelve fits and
forecasts as well as the final forecast. According to the results
obtained, the next peak is predicted to be 156 and is expected to
occur in October 2011- with an average of 136 for that year.
Abstract: This paper presents an innovative approach within the area of Group Decision Support System (GDSS) by using tools based on intelligent agents. It introduces iGDSS, a software platform for decision support and collaboration and an application of this platform - eCollaborative Decisions - for academic environment, all these developed within a framework of a research project.
Abstract: Swarm principles are increasingly being used to design controllers for the coordination of multi-robot systems or, in general, multi-agent systems. This paper proposes a two-dimensional Lagrangian swarm model that enables the planar agents, modeled as point masses, to swarm whilst effectively avoiding each other and obstacles in the environment. A novel method, based on an extended Lyapunov approach, is used to construct the model. Importantly, the Lyapunov method ensures a form of practical stability that guarantees an emergent behavior, namely, a cohesive and wellspaced swarm with a constant arrangement of individuals about the swarm centroid. Computer simulations illustrate this basic feature of collective behavior. As an application, we show how multiple planar mobile unicycle-like robots swarm to eventually form patterns in which their velocities and orientations stabilize.
Abstract: The technique of inducing micro ecosystem
restoration is one of aquatic ecology engineering methods used to
retrieve the polluted water. Batch scale study, pilot plant study, and
field study were carried out to observe the eutrophication using the
Inducing Ecology Restorative Symbiosis Agent (IERSA) consisting
mainly degraded products by using lactobacillus, saccharomycete,
and phycomycete. The results obtained from the experiments of the
batch scale and pilot plant study allowed us to development the
parameters for the field study. A pond, 5 m to the outlet of a lake,
with an area of 500 m2 and depth of 0.6-1.2 m containing about 500
tons of water was selected as a model. After the treatment with 10
mg IERSA/L water twice a week for 70 days, the micro restoration
mechanisms consisted of three stages (i.e., restoration, impact
maintenance, and ecology recovery experiment after impact). The
COD, TN, TKN, and chlorophyll a were reduced significantly in the
first week. Although the unexpected heavy rain and contaminate
from sewage system might slow the ecology restoration. However,
the self-cleaning function continued and the chlorophyll a reduced
for 50% in one month. In the 4th week, amoeba, paramecium, rotifer,
and red wriggle worm reappeared, and the number of fish flies
appeared up to1000 fish fries/m3. Those results proved that inducing
restorative mechanism can be applied to improve the eutrophication
and to control the growth of algae in the lakes by gaining the selfcleaning
through inducing and competition of microbes. The
situation for growth of fishes also can reach an excellent result due to
the improvement of water quality.
Abstract: ERP systems are often supposed to be implemented
and deployed in multi-national companies. On the other hand, an
ERP developer may plan to market and sale its product in various
countries. Therefore, an EPR system should have the ability to
communicate with its users, who usually have different languages
and cultures, in a suitable way. EPR support of Multilanguage
capability is a solution to achieve this objective. In this paper, an
agent oriented architecture including several independent but
cooperative agents has been suggested that helps to implement
Multilanguage EPR systems.
Abstract: There are many approaches proposed for solving
Sudoku puzzles. One of them is by modelling the puzzles as block
world problems. There have been three model for Sudoku solvers
based on this approach. Each model expresses Sudoku solver as
a parameterized multi agent systems. In this work, we propose a
new model which is an improvement over the existing models. This
paper presents the development of a Sudoku solver that implements
all the proposed models. Some experiments have been conducted to
determine the performance of each model.
Abstract: This paper presents the design and implements the prototype of an intelligent data processing framework in ubiquitous sensor networks. Much focus is put on how to handle the sensor data stream as well as the interoperability between the low-level sensor data and application clients. Our framework first addresses systematic middleware which mitigates the interaction between the application layer and low-level sensors, for the sake of analyzing a great volume of sensor data by filtering and integrating to create value-added context information. Then, an agent-based architecture is proposed for real-time data distribution to efficiently forward a specific event to the appropriate application registered in the directory service via the open interface. The prototype implementation demonstrates that our framework can host a sophisticated application on the ubiquitous sensor network and it can autonomously evolve to new middleware, taking advantages of promising technologies such as software agents, XML, cloud computing, and the like.
Abstract: The demand of the energy management systems (EMS) set forth by modern power systems requires fast energy management systems. Contingency analysis is among the functions in EMS which is time consuming. In order to handle this limitation, this paper introduces agent based technology in the contingency analysis. The main function of agents is to speed up the performance. Negotiations process in decision making is explained and the issue set forth is the minimization of the operating costs. The IEEE 14 bus system and its line outage have been used in the research and simulation results are presented.
Abstract: Consumer electronics are pervasive. It is impossible to
imagine a household or office without DVD players, digital cameras,
printers, mobile phones, shavers, electrical toothbrushes, etc. All
these devices operate at different voltage levels ranging from 1.8 to
20 VDC, in the absence of universal standards. The voltages
available are however usually 120/230 VAC at 50/60 Hz. This
situation makes an individual electrical energy conversion system
necessary for each device. Such converters usually involve several
conversion stages and often operate with excessive losses and poor
reliability. The aim of the project presented in this paper is to design
and implement a multi-channel DC/DC converter system,
customizing the output voltage and current ratings according to the
requirements of the load. Distributed, multi-agent techniques will be
applied for the control of the DC/DC converters.
Abstract: In wireless sensor networks,the mobile agent technology is used in data fusion. According to the node residual energy and the results of partial integration,we design the node clustering algorithm. Optimization of mobile agent in the routing within the cluster strategy for wireless sensor networks to further reduce the amount of data transfer. Through the experiments, using mobile agents in the integration process within the cluster can be reduced the path loss in some extent.
Abstract: Multi-agent system is composed by several agents
capable of reaching the goal cooperatively. The system needs an agent
platform for efficient and stable interaction between intelligent agents.
In this paper we propose a flexible and scalable agent platform by
composing the containers with multiple hierarchical agent groups. It
also allows efficient implementation of multiple domain presentations
of the agents unlike JADE. The proposed platform provides both
group management and individual management of agents for
efficiency. The platform has been implemented and tested, and it can
be used as a flexible foundation of the dynamic multi-agent system
targeting seamless delivery of ubiquitous services.
Abstract: How to coordinate the behaviors of the agents through
learning is a challenging problem within multi-agent domains.
Because of its complexity, recent work has focused on how
coordinated strategies can be learned. Here we are interested in using
reinforcement learning techniques to learn the coordinated actions of a
group of agents, without requiring explicit communication among
them. However, traditional reinforcement learning methods are based
on the assumption that the environment can be modeled as Markov
Decision Process, which usually cannot be satisfied when multiple
agents coexist in the same environment. Moreover, to effectively
coordinate each agent-s behavior so as to achieve the goal, it-s
necessary to augment the state of each agent with the information
about other existing agents. Whereas, as the number of agents in a
multiagent environment increases, the state space of each agent grows
exponentially, which will cause the combinational explosion problem.
Profit sharing is one of the reinforcement learning methods that allow
agents to learn effective behaviors from their experiences even within
non-Markovian environments. In this paper, to remedy the drawback
of the original profit sharing approach that needs much memory to
store each state-action pair during the learning process, we firstly
address a kind of on-line rational profit sharing algorithm. Then, we
integrate the advantages of modular learning architecture with on-line
rational profit sharing algorithm, and propose a new modular
reinforcement learning model. The effectiveness of the technique is
demonstrated using the pursuit problem.
Abstract: There are many kinds of metal borates found not only
in nature but also synthesized in the laboratory such as magnesium
borates. Due to its excellent properties, as remarkable ceramic
materials, they have also application areas in anti-wear and friction
reducing additives as well as electro-conductive treating agents. The
synthesis of magnesium borate powders can be fulfilled simply with
two different methods, hydrothermal and thermal synthesis.
Microwave assisted method, also another way of producing
magnesium borate, can be classified into thermal synthesis because of
using the principles of solid state synthesis. It also contributes
producing particles with small size and high purity in nano-size
material synthesize. In this study the production of magnesium
borates, are aimed using MgCl2.6H2O and H3BO3. The identification
of both starting materials and products were made by the equipments
of, X-Ray Diffraction (XRD) and Fourier Transform Infrared
Spectroscopy (FT-IR). After several synthesis steps magnesium
borates were synthesized and characterized by XRD and FT-IR, as
well.
Abstract: In this paper, we present C@sa, a multiagent system aiming at modeling, controlling and simulating the behavior of an intelligent house. The developed system aims at providing to architects, designers and psychologists a simulation and control tool for understanding which is the impact of embedded and pervasive technology on people daily life. In this vision, the house is seen as an environment made up of independent and distributed devices, controlled by agents, interacting to support user's goals and tasks.
Abstract: This paper introduces a framework based on the collaboration of multi agent and hyper-heuristics to find a solution of the real single machine production problem. There are many techniques used to solve this problem. Each of it has its own advantages and disadvantages. By the collaboration of multi agent system and hyper-heuristics, we can get more optimal solution. The hyper-heuristics approach operates on a search space of heuristics rather than directly on a search space of solutions. The proposed framework consists of some agents, i.e. problem agent, trainer agent, algorithm agent (GPHH, GAHH, and SAHH), optimizer agent, and solver agent. Some low level heuristics used in this paper are MRT, SPT, LPT, EDD, LDD, and MON
Abstract: In this paper I have developed a system for evaluating
the degree of fear emotion that the intelligent agent-based system
may feel when it encounters to a persecuting event. In this paper I
want to describe behaviors of emotional agents using human
behavior in terms of the way their emotional states evolve over time.
I have implemented a fuzzy inference system using Java
environment. As the inputs of this system, I have considered three
parameters related on human fear emotion. The system outputs can
be used in agent decision making process or choosing a person for
team working systems by combination the intensity of fear to other
emotion intensities.
Abstract: In this paper, we present user pattern learning
algorithm based MDSS (Medical Decision support system) under
ubiquitous. Most of researches are focus on hardware system, hospital
management and whole concept of ubiquitous environment even
though it is hard to implement. Our objective of this paper is to design
a MDSS framework. It helps to patient for medical treatment and
prevention of the high risk patient (COPD, heart disease, Diabetes).
This framework consist database, CAD (Computer Aided diagnosis
support system) and CAP (computer aided user vital sign prediction
system). It can be applied to develop user pattern learning algorithm
based MDSS for homecare and silver town service. Especially this
CAD has wise decision making competency. It compares current vital
sign with user-s normal condition pattern data. In addition, the CAP
computes user vital sign prediction using past data of the patient. The
novel approach is using neural network method, wireless vital sign
acquisition devices and personal computer DB system. An intelligent
agent based MDSS will help elder people and high risk patients to
prevent sudden death and disease, the physician to get the online
access to patients- data, the plan of medication service priority (e.g.
emergency case).