Mobility prediction based routing for minimizing control overhead in mobile ad hoc networks

Routing in ad hoc networks faces significant challenges due to node mobility and dynamic network topology. In this work we propose the use of mobility prediction to reduce the search space required for route discovery. A method of mobility prediction making use of a sectorized cluster structure is described with the proposal of the Prediction based Location Aided routing (P-LAR) protocol. Simulation study and analytical results of the of P-LAR find it to offer considerable saving in the amount of routing traffic generated during the route discovery phase.

A performance comparison of three wireless multi hop ad-hoc network routing protocols when streaming MPEG4 traffic

Mobile ad-hoc networks are characterised by constant topology changes, the absence of fixed infrastructure and lack of any centralised control. Traditional routing algorithms prove to be inefficient in such a changing environment. Ad-hoc routing protocols such as dynamic source routing (DSR), ad-hoc on-demand distance vector routing (AODV) and destination-sequence distance vector (DSDV) have been proposed to solve the multi hop routing problem in ad-hoc networks. Performance studies of these routing protocols have assumed constant bit rate (CBR) traffic. Real-time multimedia traffic generated by video-on demand and teleconferencing services are mostly variable bit rate (VBR) traffic. Most of these multimedia traffic is encoded using the MPEG standard. (ISO moving picture expert group). When video traffic is transferred over MANETs a series of performance issues arise. In this paper we present a performance comparison of three ad-hoc routing protocols - DSR, AODV and DSDV when streaming MPEG4 traffic. Simulation studies show that DSDV performs better than AODV and DSR. However all three protocols fail to provide good performance in large, highly mobile network environments. Further study is required to improve the performance of these protocols in mobile ad-hoc networks offering VBR services.

On-line tool condition monitoring and control system in forging processes

Cold bulk metal forming has made large-scale production of small complex solid parts economically feasible. Tooling used in metal forming poses many uncertainties in the preliminary cost estimation and production process and continual tool replacement and maintenance dramatically reduces productivity and raises manufacturing cost. In order to tackle this, an on-line tool condition monitoring system using artificial neural network (ANN) to integrate information from multiple sensors for forging process has been developed. Together with the force, acoustic emission signals and process conditions, information developed from theoretical models is integrated into the ANN tool monitoring system to predict tool life and provide the maintenance schedule.

A role for skeletal muscle stearoyl-CoA desaturase 1 in control of thermogenesis

An enhanced metabolic efficiency for accelerating the recovery of fat mass (or catch-up fat) is a characteristic feature of body weight regulation after weight loss or growth retardation and is the outcome of an "adipose-specific" suppression of thermogenesis, i.e., a feedback control system in which signals from the depleted adipose tissue fat stores exert a suppressive effect on thermogenesis. Using a previously described rat model of semistarvation-refeeding in which catch-up fat results from suppressed thermogenesis per se, we report here that the gene expression of stearoyl-coenzyme A desaturase 1 (SCD1) is elevated in skeletal muscle after 2 wk of semistarvation and remains elevated in parallel to the phase of suppressed thermogenesis favoring catch-up fat during refeeding. These elevations in the SCD1 transcript are skeletal muscle specific and are associated with elevations in microsomal ^9 desaturase enzyme activity, in the ^9 desaturation index, and in the relative content of SCD1-derived monounsaturates in several lipid fractions extracted from skeletal muscle. An elevated skeletal muscle SCD1, by desaturating the products of de novo lipogenesis and diverting them away from mitochondrial oxidation, would inhibit substrate cycling between de novo lipogenesis and lipid oxidation, thereby leading to a state of suppressed thermogenesis that regulates the body’s fat stores.—Mainieri, D., Summermatter, S., Seydoux, J., Montani, J. P., Rusconi, S., Russell, A. P., Boss, O., Buchala, A. J., Dulloo, A. G. A role for skeletal muscle stearoyl-CoA desaturase 1 in control of thermogenesis.

Eccentricity and hardness control in cold rolling mills with a dynamically constructed neural controller

The main objective of a steel strip rolling process is to produce high quality steel at a desired thickness.  Thickness reduction is the result of the speed difference between the incoming and the outgoing steel strip and the application of the large normal forces via the backup and the work rolls.  Gauge control of a cold rolled steel strip is achieved using the gaugemeter principle that works adequately for the input gauge changes and the strip hardness changes.  However, the compensation of some factors is problematic, for example, eccentricity of the backup rolls.  This cyclic eccentricity effect causes a gauge deviation, but more importantly, a signal is passed to the gap position control so to increase the eccentricity deviation.  Consequently, the required high product tolerances are severely limited by the presence of the roll eccentricity effects.
In this paper a direct model reference adaptive control (MRAC) scheme with dynamically constructed neural controller was used.  The aim here is to find the simplest controller structure capable of achieving an optimal performance.  The stability of the adaptive neural control scheme (i.e. the requirement of persistency of excitation and bounded learning rates) is addressed by using as the inputs to the reference model the plant's state variables.  In such a case, excitation is due to actual plant signals (states) affected by plant disturbances and noise.  In addition, a reference model in the form of a filter with a desired transfer function using Modulus Optimum design was used to ensure variance in the desired dynamic characteristics of the system.  The gradually decreasing learning rate employed by the neural controller in this paper is aimed at eliminating controller instability resulting from over-aggressive control.  The moving target problem (i.e. the difficulty of global neural networks to perfrom several separate computational tasks in closed -loop control) is addressed by the localized architecture of the controller.  The above control scheme and learning algorithm offers a method for automatic discovery of an efficient controller.
The resulting neural controller produces an excellent disturbance rejection in both cases of eccentricity and hardness disturbances, reducing the gauge deviation due to eccentricity disturbance from 33.36% to 4.57% on average, and the gauge deviation due to hardness disturbance from 12.59% to 2.08%.

Applying fair intelligent congestion control in a hybrid QoS architecture for wireless environment

This simple and scalable Differentiated Services (DiffServ) QoS control model is acceptable for the core of the network. However, more explicit and stringent admission and reservation based QoS mechanisms are required in the wireless access segment of the network, where available resources are severely limited and the degree of traffic aggregation is not significant, thus rendering the DiffServ principles less effective. In this paper we present a suitable hybrid QoS architecture framework to address the problem. At the wireless access end, the local QoS mechanism is designed in the context of IEEE 802.11 WLAN with 802.11e QoS extensions. At the edge and over the DiffServ domain, the Fair Intelligent Congestion Control (FICC) algorithm is applied to provide fairness among traffic aggregates and control congestion at the bottleneck interface between the wireless link and the network core.

A study on look-ahead control and energy management strategies in hybrid electric vehicles

Fuel efficiency in a hybrid electric vehicle requires a fine balance between usage of combustion engine and battery power. Information about the geometry of the road and traffic ahead can have a great impact on optimized control and the power split between the main parts of a hybrid electric vehicle. This paper provides a survey on the existing methods of control and energy management emphasizing on those that consider the look-ahead road situation and trajectory information. Then it presents the future trends in the control and energy management of hybrid electric vehicles.

Simulation-based learning for control of complex conveyor networks

This research investigated the problem of path planning in complex conveyor networks. A reinforcement learning approach was applied to derive a control strategy for routing traffic. The derived strategy was verified in real world systems and was found to improve network performance by prioritising traffic flows and balancing network load.

Multimedia stream rate control over MANET based on router feedback

Streaming applications over Mobile Ad-hoc Networks (MANET) require a smooth transmission rate. The Internet is unable to provide this service during traffic congestion in the network. Designing congestion control for these applications is challenging, because the standard TCP congestion control mechanism is not able to handle the special properties of a shared wireless multi hop channel well. In particular, the frequent changes to the network topology and the shared nature of the wireless channel pose major challenges. In this paper, we propose a novel approach, which allows a quick increase of throughput by using explicit feedback from routers.

A preliminary investigation of adult defence style and physiological reactivity to infant distress signals

Species whose offspring require extended care-giving ought to be predisposed to being biologically responsive to their infant's signalling. This paper examined the interplay between biological and psychological aspects of adult response to an infant's distress. HR (heart rate) and GSR (galvanic skin response) were recorded continuously, while 50 adults listened to white noise and an infant cry audio recording. Participants completed the defence style questionnaire and the state trait anxiety inventory. HR acceleration occurred in response to the control sound, while HR decelerated in response to the infant cry. GSR responsiveness was positively correlated with immature and neurotic defence styles. When controlling for other variables, immature defence was a unique and independent predictor of GSR change in response to infant distress. Defence demonstrated a stronger relationship than self-reported anxiety, than that with physiological responsiveness. Employing defence mechanisms appears to reduce an individual's perceived anxiety, though it has little effect on physiological arousal levels.

Resisting web proxy-based HTTP attacks by temporal and spatial locality behavior

A novel server-side defense scheme is proposed to resist the Web proxy-based distributed denial of service attack. The approach utilizes the temporal and spatial locality to extract the behavior features of the proxy-to-server traffic, which makes the scheme independent of the traffic intensity and frequently varying Web contents. A nonlinear mapping function is introduced to protect weak signals from the interference of infrequent large values. Then, a new hidden semi-Markov model parameterized by Gaussian-mixture and Gamma distributions is proposed to describe the time-varying traffic behavior of Web proxies. The new method reduces the number of parameters to be estimated, and can characterize the dynamic evolution of the proxy-to-server traffic rather than the static statistics. Two diagnosis approaches at different scales are introduced to meet the requirement of both fine-grained and coarse-grained detection. Soft control is a novel attack response method proposed in this work. It converts a suspicious traffic into a relatively normal one by behavior reshaping rather than rudely discarding. This measure can protect the quality of services of legitimate users. The experiments confirm the effectiveness of the proposed scheme.

Drivers display anger-congruent attention to potential traffic hazards

Previous research has suggested that angry drivers may respond differently to potential hazards. This study replicates and extends these findings. Under simulated driving conditions, two groups of drivers experienced conditions that would either increase angry mood (N=12; men =6) or not (control group, N =12; men=6). All drivers then performed a neutral drive, during which they encountered a number of traffic events not experienced in the initial drive. These included vehicles emerging from driveways into their path and jaywalking pedestrians. Subjective anger, eye-movement behaviour and driving behaviours (speed and reaction times) were measured as drivers drove. Subjective moods (Profile of Mood States) were assessed before and after each drive. Anger-provoked drivers reported reliably higher increases in angry mood when compared with the control group after the initial drive, and these increases remained stable across the subsequent neutral drive. During the neutral drive, anger provoked drivers demonstrated evidence of more heuristic style processing of potential hazards, with shorter initial gazes at less apparent hazards and longer latencies to look back at jaywalking pedestrians obscured by parked vehicles. Anger-provoked drivers also took longer to make corrective actions to avoid potential collisions. It is concluded that anger-provoked drivers may initially make more superficial assessments of certain driving situations and consequently underestimate the inherent risk.

Space vector modulation based fast speed response field-orientation control of induction motor drive with adaptive neural integrator

This paper presents a novel fast speed response control strategy for the poly-phase induction motor drive system based on flux angle. The control scheme is derived in rotor field coordinates and employs the estimation of the rotor flux and its position. An adaptive notch filter is proposed to eliminate the dc component of the integration of signals used for the rotor flux estimation. To improve the performance of the rotor flux estimator, derivative term of the back emf is incorporated in the system. The voltage components in the synchronous reference frame are generated in the controllers which are transformed to stationary reference frame for driving the motor. Space vector modulation technique is used here. Simulation of the drive system was carried out and the results were compared with those obtained for a system that produces the above mentioned voltage components using the conventional PI controller. It is observed that the proposed control methodology provides faster response than the conventional PI controller incorporated system.

Intelligent cuckoo search optimized traffic signal controllers for multi-intersection network

Traffic congestion in urban roads is one of the biggest challenges of 21 century. Despite a myriad of research work in the last two decades, optimization of traffic signals in network level is still an open research problem. This paper for the first time employs advanced cuckoo search optimization algorithm for optimally tuning parameters of intelligent controllers. Neural Network (NN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are two intelligent controllers implemented in this study. For the sake of comparison, we also implement Q-learning and fixed-time controllers as benchmarks. Comprehensive simulation scenarios are designed and executed for a traffic network composed of nine four-way intersections. Obtained results for a few scenarios demonstrate the optimality of trained intelligent controllers using the cuckoo search method. The average performance of NN, ANFIS, and Q-learning controllers against the fixed-time controller are 44%, 39%, and 35%, respectively.

Resistive vibration exercise during bed-rest reduces motor control changes in the lumbo-pelvic musculature

To understand the effects of a resistive vibration exercise (RVE) countermeasure on changes in lumbo-pelvic muscle motor control during prolonged bed-rest, 20 male subjects took part in the Berlin Bed-Rest Study (in 2003-2005) and were randomised to a RVE group or an inactive control group. Surface electromyographic signals recorded from five superficial lumbo-pelvic muscles during a repetitive knee movement task. The task, which required stabilisation of the lumbo-pelvic region, was performed at multiple movement speeds and at multiple time points during and after bed-rest. After excluding effects that could be attributed to increases in subcutaneous fat changes and improvements in movement skill, we found that the RVE intervention ameliorated the generalised increases in activity ratios between movement speeds (p⩽0.012), reductions in lumbo-pelvic extensor and flexor co-contraction (p=0.058) and increases in root-mean-square electromyographic amplitude (p=0.001) of the lumbar erector spinae muscles. Effects of RVE on preventing increases in amplitude-modulation (p=0.23) of the lumbar erector spinae muscles were not significant. Few significant changes in activation-timing were seen. The RVE intervention during bed-rest, with indirect loading of the spine during exercise, was capable of reducing some, but not all, motor control changes in the lumbo-pelvic musculature during and after bed-rest.