Abstract: Data gathering is an essential operation in wireless
sensor network applications. So it requires energy efficiency
techniques to increase the lifetime of the network. Similarly,
clustering is also an effective technique to improve the energy
efficiency and network lifetime of wireless sensor networks. In this
paper, an energy efficient cluster formation protocol is proposed with
the objective of achieving low energy dissipation and latency without
sacrificing application specific quality. The objective is achieved by
applying randomized, adaptive, self-configuring cluster formation
and localized control for data transfers. It involves application -
specific data processing, such as data aggregation or compression.
The cluster formation algorithm allows each node to make
independent decisions, so as to generate good clusters as the end.
Simulation results show that the proposed protocol utilizes minimum
energy and latency for cluster formation, there by reducing the
overhead of the protocol.
Abstract: The rapid development of the BlackBerry games industry and its development goals were not just for entertainment, but also used for educational of students interactively. Unfortunately the development of adaptive educational games on BlackBerry in Indonesian language that interesting and entertaining for learning process is very limited. This paper shows the research of development of novel adaptive educational games for students who can adjust the difficulty level of games based on the ability of the user, so that it can motivate students to continue to play these games. We propose a method where these games can adjust the level of difficulty, based on the assessment of the results of previous problems using neural networks with three inputs in the form of percentage correct, the speed of answer and interest mode of games (animation / lessons) and 1 output. The experimental results are presented and show the adaptive games are running well on mobile devices based on BlackBerry platform
Abstract: With increasing data in medical databases, medical
data retrieval is growing in popularity. Some of this analysis
including inducing propositional rules from databases using many
soft techniques, and then using these rules in an expert system.
Diagnostic rules and information on features are extracted from
clinical databases on diseases of congenital anomaly. This paper
explain the latest soft computing techniques and some of the
adaptive techniques encompasses an extensive group of methods
that have been applied in the medical domain and that are used for
the discovery of data dependencies, importance of features,
patterns in sample data, and feature space dimensionality
reduction. These approaches pave the way for new and interesting
avenues of research in medical imaging and represent an important
challenge for researchers.
Abstract: Emotions are related with learning processes and
physiological signals can be used to detect them for the
personalization of learning resources and to control the pace of
instruction. A model of relevant emotions has been developed, where
specific combinations of emotions and cognition processes are
connected and integrated with the concept of 'flow', in order to
improve learning. The cardiac pulse is a reliable signal that carries
useful information about the subject-s emotional condition; it is
detected using a classroom chair adapted with non invasive EMFi
sensor and an acquisition system that generates a ballistocardiogram
(BCG), the signal is processed by an algorithm to obtain
characteristics that match a specific emotional condition. The
complete chair system is presented in this work, along with a
framework for the personalization of learning resources.
Abstract: In this paper, zigbee communication based wireless energy surveillance system is presented. The proposed system consists of multiple energy surveillance devices and an energy surveillance monitor. Each different standby power-off value of electric device is set automatically by using learning function of energy surveillance device. Thus adaptive standby power-off function provides user convenience and it maximizes the energy savings. Also, power consumption monitoring function is helpful to reduce inefficient energy consumption in home. The zigbee throughput simulator is designed to evaluate minimum transmission power and maximum allowable information quantity in the proposed system. The test result of prototype has been satisfied all the requirements. The proposed system has confirmed that can be used as an intelligent energy surveillance system for energy savings in home or office.
Abstract: In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.
Abstract: Active vibration isolation systems are less commonly
used than passive systems due to their associated cost and power
requirements. In principle, semi-active isolation systems can deliver
the versatility, adaptability and higher performance of fully active
systems for a fraction of the power consumption. Various semi-active
control algorithms have been suggested in the past. This paper
studies the 4DOF model of semi-active suspension performance
controlled by on–off and continuous skyhook damping control
strategy. The frequency and transient responses of model are
evaluated in terms of body acceleration, roll angle and tire deflection
and are compared with that of a passive damper. The results show
that the semi-active system controlled by skyhook strategy always
provides better isolation than a conventional passively damped
system except at tire natural frequencies.
Abstract: Learning programming is difficult for many learners. Some researches have found that the main difficulty relates to cognitive load. Cognitive overload happens in programming due to the nature of the subject which is intrinisicly over-bearing on the working memory. It happens due to the complexity of the subject itself. The problem is made worse by the poor instructional design methodology used in the teaching and learning process. Various efforts have been proposed to reduce the cognitive load, e.g. visualization softwares, part-program method etc. Use of many computer based systems have also been tried to tackle the problem. However, little success has been made to alleviate the problem. More has to be done to overcome this hurdle. This research attempts at understanding how cognitive load can be managed so as to reduce the problem of overloading. We propose a mechanism to measure the cognitive load during pre instruction, post instruction and in instructional stages of learning. This mechanism is used to help the instruction. As the load changes the instruction is made to adapt itself to ensure cognitive viability. This mechanism could be incorporated as a sub domain in the student model of various computer based instructional systems to facilitate the learning of programming.
Abstract: A synchronous network-on-chip using wormhole packet switching
and supporting guaranteed-completion best-effort with low-priority (LP)
and high-priority (HP) wormhole packet delivery service is presented in
this paper. Both our proposed LP and HP message services deliver a good
quality of service in term of lossless packet completion and in-order message
data delivery. However, the LP message service does not guarantee minimal
completion bound. The HP packets will absolutely use 100% bandwidth of
their reserved links if the HP packets are injected from the source node with
maximum injection. Hence, the service are suitable for small size messages
(less than hundred bytes). Otherwise the other HP and LP messages, which
require also the links, will experience relatively high latency depending on the
size of the HP message. The LP packets are routed using a minimal adaptive
routing, while the HP packets are routed using a non-minimal adaptive routing
algorithm. Therefore, an additional 3-bit field, identifying the packet type,
is introduced in their packet headers to classify and to determine the type
of service committed to the packet. Our NoC prototypes have been also
synthesized using a 180-nm CMOS standard-cell technology to evaluate the
cost of implementing the combination of both services.
Abstract: XML is an important standard of data exchange and
representation. As a mature database system, using relational database
to support XML data may bring some advantages. But storing XML in
relational database has obvious redundancy that wastes disk space,
bandwidth and disk I/O when querying XML data. For the efficiency
of storage and query XML, it is necessary to use compressed XML
data in relational database. In this paper, a compressed relational
database technology supporting XML data is presented. Original
relational storage structure is adaptive to XPath query process. The
compression method keeps this feature. Besides traditional relational
database techniques, additional query process technologies on
compressed relations and for special structure for XML are presented.
In this paper, technologies for XQuery process in compressed
relational database are presented..
Abstract: Because nodes are usually battery-powered, the energy
presents a very scarce resource in wireless sensor networks. For this
reason, the design of medium access control had to take energy
efficiency as one of its hottest concerns. Accordingly, in order to
improve the energy performance of MAC schemes in wireless sensor
networks, several ways can be followed. In fact, some researchers try
to limit idle listening while others focus on mitigating overhearing
(i.e. a node can hear a packet which is destined to another node)
or reducing the number of the used control packets. We, in this
paper, propose a new hybrid MAC protocol termed ELE-MAC
(i.e. Energy Latency Efficient MAC). The ELE-MAC major design
goals are energy and latency efficiencies. It adopts less control
packets than SMAC in order to preserve energy. We carried out ns-
2 simulations to evaluate the performance of the proposed protocol.
Thus, our simulation-s results prove the ELE-MAC energy efficiency.
Additionally, our solution performs statistically the same or better
latency characteristic compared to adaptive SMAC.
Abstract: In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.
Abstract: A novel adaptive fuzzy trajectory tracking algorithm of Stewart platform based motion platform is proposed to compensate path deviation and degradation of controller-s performance due to actuator torque limit. The algorithm can be divided into two parts: the real-time trajectory shaping part and the joint space adaptive fuzzy controller part. For a reference trajectory in task space whenever any of the actuators is saturated, the desired acceleration of the reference trajectory is modified on-line by using dynamic model of motion platform. Meanwhile an additional action with respect to the difference between the nominal and modified trajectories is utilized in the non-saturated region of actuators to reduce the path error. Using modified trajectory as input, the joint space controller incorporates compute torque controller, leg velocity observer and fuzzy disturbance observer with saturation compensation. It can ensure stability and tracking performance of controller in present of external disturbance and position only measurement. Simulation results verify the effectiveness of proposed control scheme.
Abstract: Unlike the best effort service provided by the internet
today, next-generation wireless networks will support real-time
applications. This paper proposes an adaptive early packet discard
(AEPD) policy to improve the performance of the real time TCP
traffic over ATM networks and avoid the fragmentation problem.
Three main aspects are incorporated in the proposed policy. First,
providing quality-of-service (QoS) guaranteed for real-time
applications by implementing a priority scheduling. Second,
resolving the partially corrupted packets problem by differentiating
the buffered cells of one packet from another. Third, adapting a
threshold dynamically using Fuzzy logic based on the traffic
behavior to maintain a high throughput under a variety of load
conditions. The simulation is run for two priority classes of the input
traffic: real time and non-real time classes. Simulation results show
that the proposed AEPD policy improves throughput and fairness
over that using static threshold under the same traffic conditions.
Abstract: In this article, an adaptive least-squares mixed finite element method is studied for pseudo-parabolic integro-differential equations. The solutions of least-squares mixed weak formulation and mixed finite element are proved. A posteriori error estimator is constructed based on the least-squares functional and the posteriori errors are obtained.
Abstract: A Cable-Driven Locomotion Interface provides a low
inertia haptic interface and is used as a way of enabling the user
to walk and interact with virtual surfaces. These surfaces generate
Cartesian wrenches which must be optimized for each motorized
reel in order to reproduce a haptic sensation in both feet. However,
the use of wrench control requires a measure of the cable tensions
applied to the moving platform. The latter measure may be inaccurate
if it is based on sensors located near the reel. Moreover, friction
hysteresis from the reel moving parts needs to be compensated
for with an evaluation of low angular velocity of the motor shaft.
Also, the pose of the platform is not known precisely due to cable
sagging and mechanical deformation. This paper presents a non-ideal
motorized reel design with its corresponding control strategy that
aims at overcoming the aforementioned issues. A transfert function
of the reel based on frequency responses in function of cable tension
and cable length is presented with an optimal adaptative PIDF
controller. Finally, an hybrid position/tension control is discussed with
an analysis of the stability for achieving a complete functionnality of
the haptic platform.
Abstract: In this paper we propose a robust adaptive fuzzy
controller for a class of nonlinear system with unknown dynamic.
The method is based on type-2 fuzzy logic system to approximate
unknown non-linear function. The design of the on-line adaptive
scheme of the proposed controller is based on Lyapunov technique.
Simulation results are given to illustrate the effectiveness of the
proposed approach.
Abstract: Two group of kids (“Safflower cake" and “Control") were fed ad libitum with pelleted total mixed rations. After a 7-days adaptation period, the diet of the “Safflower cake" group were supplemented with 20% of safflower cake. The kids were slaughtered at 96 days of age. Dietary safflower cake did not affect the growth traits of kids. In addition, kids fed experimental diet showed a lower feed intake and consequently a better feed conversion ratio in comparison to the “Control" group. The use of safflower decreased the level of SFA and increased the level of MUFA in kid meat. The level of PUFA was higher in lipid extracted from animals feeding “Control“ diet even if the UFA level was lower. Furthermore, lipid extracted from animals feeding control diet contained more ω6 fatty acids in comparison to kids feeding experimental diet while the opposite trend was observed for the level of ω3 fatty acids. The ω6 to ω3 ratio was significantly affected by diet and in particular this ratio decreased in meat of kids fed experimental diet. Our results indicate that intramuscular fatty acid composition of kid meat can be improved from a human health perspective by inclusion of safflower cake in the diet.
Abstract: EEG signal is one of the oldest measures of brain
activity that has been used vastly for clinical diagnoses and
biomedical researches. However, EEG signals are highly
contaminated with various artifacts, both from the subject and from
equipment interferences. Among these various kinds of artifacts,
ocular noise is the most important one. Since many applications such
as BCI require online and real-time processing of EEG signal, it is
ideal if the removal of artifacts is performed in an online fashion.
Recently, some methods for online ocular artifact removing have
been proposed. One of these methods is ARMAX modeling of EEG
signal. This method assumes that the recorded EEG signal is a
combination of EOG artifacts and the background EEG. Then the
background EEG is estimated via estimation of ARMAX parameters.
The other recently proposed method is based on adaptive filtering.
This method uses EOG signal as the reference input and subtracts
EOG artifacts from recorded EEG signals. In this paper we
investigate the efficiency of each method for removing of EOG
artifacts. A comparison is made between these two methods. Our
undertaken conclusion from this comparison is that adaptive filtering
method has better results compared with the results achieved by
ARMAX modeling.
Abstract: We have applied new accelerated algorithm for linear
discriminate analysis (LDA) in face recognition with support vector
machine. The new algorithm has the advantage of optimal selection
of the step size. The gradient descent method and new algorithm has
been implemented in software and evaluated on the Yale face
database B. The eigenfaces of these approaches have been used to
training a KNN. Recognition rate with new algorithm is compared
with gradient.