Abstract: The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widely used to stop this unwanted flood as it combines good performance with simplicity of the training and classification processes. However, facing the constantly changing patterns of spam, it is necessary to assure online adaptability of the classifier. This work proposes combining such a classifier with another NBC (naïve Bayesian classifier) based on pairs of adjacent words. Only the latter will be retrained with examples of spam reported by users. Tests are performed on considerable sets of mails both from public spam archives and CERN mailboxes. They suggest that this architecture can increase spam recall without affecting the classifier precision as it happens when only the NBC based on single words is retrained.
Abstract: With high speed vessels getting ever more sophisti-cated, travelling at higher and higher speeds and operating in With high speed vessels getting ever more sophisticated,
travelling at higher and higher speeds and operating in areas of
high maritime traffic density, training becomes of the highest priority
to ensure that safety levels are maintained, and risks are adequately
mitigated. Training onboard the actual craft on the actual route still
remains the most effective way for crews to gain experience. However,
operational experience and incidents during the last 10 years
demonstrate the need for supplementary training whether in the area
of simulation or man to man, man/ machine interaction. Training and
familiarisation of the crew is the most important aspect in preventing
incidents. The use of simulator, computer and web based training
systems in conjunction with onboard training focusing on critical
situations will improve the man machine interaction and thereby
reduce the risk of accidents. Today, both ship simulator and bridge
teamwork courses are now becoming the norm in order to improve
further emergency response and crisis management skills. One of the
main causes of accidents is the human factor. An efficient way to
reduce human errors is to provide high-quality training to the personnel
and to select the navigators carefully.areas of high maritime traffic density, training becomes of the highest priority to ensure that safety levels are maintained, and risks are adequately mitigated. Training onboard the actual craft on the actual route still remains the most effective way for crews to gain experience. How-ever, operational experience and incidents during the last 10 years demonstrate the need for supplementary training whether in the area of simulation or man to man, man/ machine interaction. Training and familiarisation of the crew is the most important aspect in preventing incidents. The use of simulator, computer and web based training systems in conjunction with onboard training focusing on critical situations will improve the man machine interaction and thereby reduce the risk of accidents. Today, both ship simulator and bridge teamwork courses are now becoming the norm in order to improve further emergency response and crisis management skills. One of the main causes of accidents is the human factor. An efficient way to reduce human errors is to provide high-quality training to the person-nel and to select the navigators carefully. KeywordsCBT - WBT systems, Human factors.
Abstract: Hybrid algorithm is the hot issue in Computational
Intelligence (CI) study. From in-depth discussion on Simulation
Mechanism Based (SMB) classification method and composite patterns,
this paper presents the Mamdani model based Adaptive Neural
Fuzzy Inference System (M-ANFIS) and weight updating formula in
consideration with qualitative representation of inference consequent
parts in fuzzy neural networks. M-ANFIS model adopts Mamdani
fuzzy inference system which has advantages in consequent part.
Experiment results of applying M-ANFIS to evaluate traffic Level
of service show that M-ANFIS, as a new hybrid algorithm in computational
intelligence, has great advantages in non-linear modeling,
membership functions in consequent parts, scale of training data and
amount of adjusted parameters.
Abstract: Reconfigurable optical add/drop multiplexers
(ROADMs) can be classified into three categories based on their
underlying switching technologies. Category I consists of a single
large optical switch; category II is composed of a number of small
optical switches aligned in parallel; and category III has a single
optical switch and only one wavelength being added/dropped. In this
paper, to evaluate the wavelength-routing capability of ROADMs of
category-II in dynamic optical networks,the dynamic traffic models
are designed based on Bernoulli, Poisson distributions for smooth
and regular types of traffic. Through Analytical and Simulation
results, the routing power of cat-II of ROADM networks for two
traffic models are determined.
Abstract: Facility location problem involves locating a facility
to optimize some performance measures. Location of a public facility
to serve the community, such as a fire station, significantly affects its
service quality. Main objective in locating a fire station is to
minimize the response time, which is the time duration between
receiving a call and reaching the place of incident. In metropolitan
areas, fire vehicles need to cross highways and other traffic obstacles
through some obstacle-overcoming points which delay the response
time. In this paper, fire station location problem is analyzed.
Simulation models are developed for the location problems which
involve obstacles. Particular case problems are analyzed and the
results are presented.
Abstract: Intrusion Detection Systems are increasingly a key
part of systems defense. Various approaches to Intrusion Detection
are currently being used, but they are relatively ineffective. Artificial
Intelligence plays a driving role in security services. This paper
proposes a dynamic model Intelligent Intrusion Detection System,
based on specific AI approach for intrusion detection. The
techniques that are being investigated includes neural networks and
fuzzy logic with network profiling, that uses simple data mining
techniques to process the network data. The proposed system is a
hybrid system that combines anomaly, misuse and host based
detection. Simple Fuzzy rules allow us to construct if-then rules that
reflect common ways of describing security attacks. For host based
intrusion detection we use neural-networks along with self
organizing maps. Suspicious intrusions can be traced back to its
original source path and any traffic from that particular source will
be redirected back to them in future. Both network traffic and system
audit data are used as inputs for both.
Abstract: Optimization plays an important role in most real
world applications that support decision makers to take the right
decision regarding the strategic directions and operations of the
system they manage. Solutions for traffic management and traffic
congestion problems are considered major problems that most
decision making authorities for cities around the world are looking
for. This review paper gives a full description of the traffic problem
as part of the transportation planning process and present a view as a
framework of urban transportation system analysis where the core of
the system is a transportation network equilibrium model that is
based on optimization techniques and that can also be used for
evaluating an alternative solution or a combination of alternative
solutions for the traffic congestion. Different transportation network
equilibrium models are reviewed from the sequential approach to the
multiclass combining trip generation, trip distribution, modal split,
trip assignment and departure time model. A GIS-Based intelligent
decision support system framework for urban transportation system
analysis is suggested for implementation where the selection of
optimized alternative solutions, single or packages, will be based on
an intelligent agent rather than human being which would lead to
reduction in time, cost and the elimination of the difficulty, by
human being, for finding the best solution to the traffic congestion
problem.
Abstract: As the air traffic increases at a hub airport, some
flights cannot land or depart at their preferred target time. This event
happens because the airport runways become occupied to near their
capacity. It results in extra costs for both passengers and airlines
because of the loss of connecting flights or more waiting, more fuel
consumption, rescheduling crew members, etc. Hence, devising an
appropriate scheduling method that determines a suitable runway and
time for each flight in order to efficiently use the hub capacity and
minimize the related costs is of great importance. In this paper, we
present a mixed-integer zero-one model for scheduling a set of mixed
landing and departing flights (despite of most previous studies
considered only landings). According to the fact that the flight cost is
strongly affected by the level of airline, we consider different airline
categories in our model. This model presents a single objective
minimizing the total sum of three terms, namely 1) the weighted
deviation from targets, 2) the scheduled time of the last flight (i.e.,
makespan), and 3) the unbalancing the workload on runways. We
solve 10 simulated instances of different sizes up to 30 flights and 4
runways. Optimal solutions are obtained in a reasonable time, which
are satisfactory in comparison with the traditional rule, namely First-
Come-First-Serve (FCFS) that is far apart from optimality in most
cases.
Abstract: Internet is without any doubt the fastest and effective mean of communication making it possible to reach a great number of people in the world. It draws its base from exchange points. Indeed exchange points are used to inter-connect various Internet suppliers and operators in order to allow them to exchange traffic and it is with these interconnections that Internet made its great strides. They thus make it possible to limit the traffic delivered via the operators of transits. This limitation allows a significant improvement of the quality of service, a reduction in the latency time just as a reduction of the cost of connection for the final subscriber. Through this article we will show how the installation of an IXP allows an improvement and a diversification of the services just as a reduction of the Internet connection costs.
Abstract: The focus of this paper is to highlight the design and
development of an educational game prototype as an evaluation
instrument for the Malaysia driving license static test. This
educational game brings gaming technology into the conventional
objective static test to make it more effective, real and interesting.
From the feeling of realistic, the future driver can learn something,
memorized and use it in the real life. The current online objective
static test only make the user memorized the answer without knowing
and understand the true purpose of the question. Therefore, in real
life, they will not behave as expected due to behavior and moral
lacking. This prototype has been developed inform of multiple-choice
questions integrated with 3D gaming environment to make it simulate
the real environment and scenarios. Based on the testing conducted,
the respondent agrees with the use of this game prototype it can
increase understanding and promote obligation towards traffic rules.
Abstract: With the development of technology, the growing
trend of fast and safe passenger transport, air pollution, traffic
congestion, increase in problems such as the increasing population
and the high cost of private vehicle usage made many cities around
the world with a population of more or less, start to build rail systems
as a means of urban transport in order to ensure the economic and
environmental sustainability and more efficient use of land in the
city. The implementation phase of rail systems costs much more than
other public transport systems. However, social and economic returns
in the long term made these systems the most popular investment tool
for planned and developing cities.
In our country, the purpose, goals and policies of transportation
plans are away from integrity, and the problems are not clearly
detected. Also, not defined and incomplete assessment of
transportation systems and insufficient financial analysis are the most
important cause of failure. Rail systems and other transportation
systems to be addressed as a whole is seen as the main factor in
increasing efficiency in applications that are not integrated yet in our
country to come to this point has led to the problem.
Abstract: Road rage is an increasingly prevalent expression of
aggression in our society. Its dangers are apparent and understanding
its causes may shed light on preventative measures. This study
involved a fifteen-minute survey administered to 147 undergraduate
students at a North Eastern suburban university. The survey
consisted of a demographics section, questions regarding financial
investment in respondents- vehicles, experience driving, habits of
driving, experiences witnessing role models driving, and an
evaluation of road rage behavior using the Driving Vengeance
Questionnaire. The study found no significant differences in driving
aggression between respondents who were financially invested in
their vehicle compared to those who were not, or between
respondents who drove in heavy traffic hours compared to those who
did not, suggesting internal factors correlate with aggressive driving
habits. The study also found significant differences in driving
aggression between males versus females, those with more points on
their license versus fewer points, and those who witnessed parents
driving aggressively very often versus rarely or never. Additional
studies can investigate how witnessing parents driving aggressively
is related to future driving behaviors.
Abstract: This paper introduces a technique for simulating a
single-server exponential queuing system. The technique called the
Q-Simulator is a computer program which can simulate the effect of
traffic intensity on all system average quantities given the arrival
and/or service rates. The Q-Simulator has three phases namely: the
formula based method, the uncontrolled simulation, and the
controlled simulation. The Q-Simulator generates graphs (crystal
solutions) for all results of the simulation or calculation and can be
used to estimate desirable average quantities such as waiting times,
queue lengths, etc.
Abstract: One of the most importance of intelligence in-car and
roadside systems is the cooperative vehicle-infrastructure system. In
Thailand, ITS technologies are rapidly growing and real-time vehicle
information is considerably needed for ITS applications; for example,
vehicle fleet tracking and control and road traffic monitoring
systems. This paper defines the communication protocols and
software design for middleware components of B-VIS (Burapha
Vehicle-Infrastructure System). The proposed B-VIS middleware architecture serves the needs of a distributed RFID sensor network and simplifies some intricate details of several communication standards.
Abstract: The Chiu-s method which generates a Takagi-Sugeno Fuzzy Inference System (FIS) is a method of fuzzy rules extraction. The rules output is a linear function of inputs. In addition, these rules are not explicit for the expert. In this paper, we develop a method which generates Mamdani FIS, where the rules output is fuzzy. The method proceeds in two steps: first, it uses the subtractive clustering principle to estimate both the number of clusters and the initial locations of a cluster centers. Each obtained cluster corresponds to a Mamdani fuzzy rule. Then, it optimizes the fuzzy model parameters by applying a genetic algorithm. This method is illustrated on a traffic network management application. We suggest also a Mamdani fuzzy rules generation method, where the expert wants to classify the output variables in some fuzzy predefined classes.
Abstract: With the drastically growth in optical communication
technology, a lossless, low-crosstalk and multifunction optical switch
is most desirable for large-scale photonic network. To realize such a
switch, we have introduced the new architecture of optical switch
that embedded many functions on single device. The asymmetrical
architecture of OXADM consists of 3 parts; selective port, add/drop
operation, and path routing. Selective port permits only the interest
wavelength pass through and acts as a filter. While add and drop
function can be implemented in second part of OXADM architecture.
The signals can then be re-routed to any output port or/and perform
an accumulation function which multiplex all signals onto single path
and then exit to any interest output port. This will be done by path
routing operation. The unique features offered by OXADM has
extended its application to Fiber to-the Home Technology (FTTH),
here the OXADM is used as a wavelength management element in
Optical Line Terminal (OLT). Each port is assigned specifically with
the operating wavelengths and with the dynamic routing management
to ensure no traffic combustion occurs in OLT.
Abstract: The Bangalore City is facing the acute problem of
pollution in the atmosphere due to the heavy increase in the traffic
and developmental activities in recent years. The present study is an
attempt in the direction to assess trend of the ambient air quality
status of three stations, viz., AMCO Batteries Factory, Mysore Road,
GRAPHITE INDIA FACTORY, KHB Industrial Area, Whitefield
and Ananda Rao Circle, Gandhinagar with respect to some of the
major criteria pollutants such as Total Suspended particular matter
(SPM), Oxides of nitrogen (NOx), and Oxides of sulphur (SO2). The
sites are representative of various kinds of growths viz., commercial,
residential and industrial, prevailing in Bangalore, which are
contributing to air pollution. The concentration of Sulphur Dioxide
(SO2) at all locations showed a falling trend due to use of refined
petrol and diesel in the recent years. The concentration of Oxides of
nitrogen (NOx) showed an increasing trend but was within the
permissible limits. The concentration of the Suspended particular
matter (SPM) showed the mixed trend. The correlation between
model and observed values is found to vary from 0.4 to 0.7 for SO2,
0.45 to 0.65 for NOx and 0.4 to 0.6 for SPM. About 80% of data is
observed to fall within the error band of ±50%. Forecast test for the
best fit models showed the same trend as actual values in most of the
cases. However, the deviation observed in few cases could be
attributed to change in quality of petro products, increase in the
volume of traffic, introduction of LPG as fuel in many types of
automobiles, poor condition of roads, prevailing meteorological
conditions, etc.
Abstract: Traffic Management and Information Systems, which rely on a system of sensors, aim to describe in real-time traffic in urban areas using a set of parameters and estimating them. Though the state of the art focuses on data analysis, little is done in the sense of prediction. In this paper, we describe a machine learning system for traffic flow management and control for a prediction of traffic flow problem. This new algorithm is obtained by combining Random Forests algorithm into Adaboost algorithm as a weak learner. We show that our algorithm performs relatively well on real data, and enables, according to the Traffic Flow Evaluation model, to estimate and predict whether there is congestion or not at a given time on road intersections.
Abstract: The dynamics of User Datagram Protocol (UDP) traffic
over Ethernet between two computers are analyzed using nonlinear
dynamics which shows that there are two clear regimes in the data
flow: free flow and saturated. The two most important variables
affecting this are the packet size and packet flow rate. However,
this transition is due to a transcritical bifurcation rather than phase
transition in models such as in vehicle traffic or theorized large-scale
computer network congestion. It is hoped this model will help lay
the groundwork for further research on the dynamics of networks,
especially computer networks.
Abstract: High speed networks provide realtime variable bit rate
service with diversified traffic flow characteristics and quality
requirements. The variable bit rate traffic has stringent delay and
packet loss requirements. The burstiness of the correlated traffic
makes dynamic buffer management highly desirable to satisfy the
Quality of Service (QoS) requirements. This paper presents an
algorithm for optimization of adaptive buffer allocation scheme for
traffic based on loss of consecutive packets in data-stream and buffer
occupancy level. Buffer is designed to allow the input traffic to be
partitioned into different priority classes and based on the input
traffic behavior it controls the threshold dynamically. This algorithm
allows input packets to enter into buffer if its occupancy level is less
than the threshold value for priority of that packet. The threshold is
dynamically varied in runtime based on packet loss behavior. The
simulation is run for two priority classes of the input traffic –
realtime and non-realtime classes. The simulation results show that
Adaptive Partial Buffer Sharing (ADPBS) has better performance
than Static Partial Buffer Sharing (SPBS) and First In First Out
(FIFO) queue under the same traffic conditions.