Robust Control Mechanism Research Articles

Open Science at the Montreal Neurological Institute - LORIS & CBRAIN

Event Abstract Back to Event Open Science at the Montreal Neurological Institute - LORIS & CBRAIN Samir Das1*, Tristan Glatard1, Leigh MacIntyre1 and Alan Evans1 1 Montreal Neurological Institute, McGill Centre for Integrative Neuroscience, Canada Data sharing is becoming more of a requirement as technologies mature, and global research and communication diversifies. As a result, researchers are looking for practical solutions, not only to enhance scientific collaborations, but also to acquire larger amounts of data, and to access particular datasets. In many cases, acquisition realities present a significant burden, therefore gaining access to public datasets allows for more robust analyses and greater exploratory data mining. To answer this demand, the Montreal Neurological Institute has announced the mission of Open Science, harnessing the power of making both clinical and research data available to the world (Owens, 2016). As such, the LORIS and CBRAIN (Das et al., 2015) platforms have been tasked with the technical challenges specific to the institutional-level implementation of public data sharing, including: 1) Comprehensive linking of multimodal data (clinical, genomics, imaging, phenotypic, demographic, etc.) 2) Secure database encryption, specifically designed for institutional and multi-project data sharing, ensuring patient and subject confidentiality (using multi-tiered identifiers). 3) Querying capabilities with multiple levels of single study and institutional permissions, allowing public data sharing for all consented subject data. 4) Configurable pipelines and flags to facilitate acquisition and analysis, as well as access to High Performance Computing clusters for immediate processing. 5) Robust Quality Control mechanisms usable as covariates in analysis. 6) Long term storage (and web access) of data, resulting in little attrition (i.e. lost data). 7) Enhanced web-based visualization of imaging, genomics, and phenotypic data, allowing for real-time viewing and manipulation of data from anywhere in the world. 8) Mobile data access capabilities with responsive viewing. 9) Numerous modules for data filtering, summary statistics, and personalized and configurable dashboards. The goal of Open Science at the Montreal Neurological Institute will be a concerted undertaking that seeks to facilitate data sharing on a global scale. Our goal is to utilize the years of experience in multi-site collaborative research to implement the technical requirements to achieve this level of public data sharing in a practical, yet robust manner. Acknowledgements This work has been made possible with the support of NIH (http://nih.gov), CANARIE (http://www.canarie.ca), Compute Canada (http://www.computecanada.ca), the Irving Ludmer Family Foundation and the Ludmer Centre for Neuroinformatics and Mental Health (https://www.mcgill.ca/statisticalgenetics/ludmer-centre), the Montreal Neurological Institute (http://mnni.mcgill.ca), and the LORIS (http://loris.ca) and CBRAIN (http://mcin-cnim.ca/neuroimagingtechnologies/cbrain/) References Brian Owens, Montreal institute going ‘open’ to accelerate science, Science Magazine, January 21, 2016, DOI: 10.1126/science.aae0265 Samir Das, Tristan Glatard, Leigh C. MacIntyre, Cecile Madjar, Christine Rogers, Marc-Etienne Rousseau, Pierre Rioux, Dave MacFarlane, Zia Mohades, Rathi Gnanasekaran, Carolina Makowski, Penelope Kostopoulos, Reza Adalat, Najmeh Khalili-Mahani, Guiomar Niso, Jeremy T. Moreau, Alan C. Evans, The MNI data-sharing and processing ecosystem, NeuroImage, Volume 124, Part B, 1 January 2016, Pages 1188-1195, ISSN 1053-8119, http://dx.doi.org/10.1016/j.neuroimage.2015.08.076. (http://www.sciencedirect.com/science/article/pii/S1053811915008009) Keywords: Open Science, data sharing, infrastructure, Databases as Topic, High performance computing Conference: Neuroinformatics 2016, Reading, United Kingdom, 3 Sep - 4 Sep, 2016. Presentation Type: Poster Topic: General neuroinformatics Citation: Das S, Glatard T, MacIntyre L and Evans A (2016). Open Science at the Montreal Neurological Institute - LORIS & CBRAIN. Front. Neuroinform. Conference Abstract: Neuroinformatics 2016. doi: 10.3389/conf.fninf.2016.20.00056 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 01 May 2016; Published Online: 18 Jul 2016. * Correspondence: Mr. Samir Das, Montreal Neurological Institute, McGill Centre for Integrative Neuroscience, Montreal, QC, h3A 2t4, Canada, samir@bic.mni.mcgill.ca Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Samir Das Tristan Glatard Leigh MacIntyre Alan Evans Google Samir Das Tristan Glatard Leigh MacIntyre Alan Evans Google Scholar Samir Das Tristan Glatard Leigh MacIntyre Alan Evans PubMed Samir Das Tristan Glatard Leigh MacIntyre Alan Evans Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Variable Stiffness Treadmill (VST): System Development, Characterization, and Preliminary Experiments

Locomotion is one of the human's most important functions that serve survival, progress, and interaction. Gait requires kinematic and dynamic coordination of the limbs and muscles, multisensory fusion, and robust control mechanisms. The force stimulus generated by the interaction of the foot with the walking surface is a vital part of human gait. Although there have been many studies trying to decipher the load feedback mechanisms of gait, there is a need for the development of a versatile system that can advance research and provide new functionality. In this paper, we present the design and characterization of a novel system, called variable stiffness treadmill (VST). The device is capable of controlling load feedback stimulus by regulating the walking surface stiffness in real time. The high range of available stiffness, the resolution and accuracy of the device, as well as the ability to regulate stiffness within the stance phase of walking, are some of the unique characteristics of the VST. We present experiments with healthy subjects in order to prove the concept of our device and show preliminary findings on the effect of altered stiffness on gait kinematics. The developed system constitutes a uniquely useful research tool, which can improve our understanding of gait and create new avenues of research on gait analysis and rehabilitation.

Automatic generation control of power system using a novel quasi-oppositional harmony search algorithm

Abstract The present work approaches a novel quasi-oppositional harmony search (QOHS) algorithm, as an optimization technique, for its optimum performance in the subject area of automatic generation control (AGC) of power system. The proposed QOHS algorithm is applied with an aim to converge rapidly towards the optimal solution(s) that houses both the characters of two guesses, i.e. opposite-point and quasi-opposite point. The area of concern of this study is to discuss the multi-objective problems of an interconnected power system for the benefits of AGC. The proposed QOHS algorithm is, individually, applied to single-area, precede to two-area considering the non-linearity effects of governor dead band and generation rate constraint and, finally, extended to four-area power system showing the consequences of multiple load disturbances. A case of robustness and stability analysis are also investigated for the studied two-area power system model. The control strategy, for the dynamic power system model, is based on area control error. The simplicity of the structure and acceptability responses of the well-known proportional–integral–derivative controller enforces to implement as a controller in this work. The comparative evaluation of the proposed QOHS algorithm is carried out by the way of comparing the dynamic performances of the studied power system model with those offered by other algorithms reported in the recent state-of-the-art literature. The simulation works, presented in the paper, reveal that the proposed QOHS algorithm may be effectively utilized for the purpose of AGC study of power system having varying degrees of complexities and non-linearities. Moreover, the proposed QOHS based control strategy adopted in this work provides a robust and stable speed control mechanism.

Intelligent Control Mechanism for Underwater Wet Welding

It is important to achieve high quality weld in underwater welding as it is vital to the integrity of the structures used in the offshore environment. Due to the difficulty in ensuring sound welds as it relates to the weld bead geometry, it is important to have a robust control mechanism that can meet this need. This work is aimed at designing a control mechanism for underwater wet welding which can control the welding process to ensure the desired weld bead geometry is achieved. Obtaining optimal bead width, penetration and reinforcement are essential parameters for the desired bead geometry. The method used in this study is the use of a control system that utilizes a combination of fuzzy and PID controller in controlling flux cored arc welding process. The outcome will ensure that optimal weld bead geometry is achieved as welding is being carried out at different water depth in the offshore environment. The result for the hybrid fuzzy-PID gives a satisfactory outcome of overshoot, rise time and steady error. This will lead to a robust welding system for oil and gas companies and other companies that carry out repair welding or construction welding in the offshore.

MAPK-induced Gab1 translocation to the plasma membrane depends on a regulated intramolecular switch

The timely orchestration of multiple signalling pathways is crucial for the integrity of an organism and therefore tightly controlled. Gab family proteins coordinate signal transduction at the plasma membrane (PM) by acting as docking platforms for signalling components involved in MAP kinase (MAPK), PI3 kinase (PI3K), phospholipase C (PLC) and Rho family GTPase signalling. The interaction with these components as well as the targeting of the docking platform to the PM underlies complex spatial and temporal regulatory mechanisms. Deregulated Gab1 activation and membrane binding have been observed in some haematopoietic malignancies and solid tumours, thereby contributing, for example, to the development of Philadelphia chromosome-negative myeloproliferative neoplasms and certain lung cancers. Previously, we could demonstrate that the presence of PIP3 in the PM, which is increased in many cancer cells, is not sufficient for constitutive Gab1 membrane recruitment. In addition, MAPK-dependent phosphorylation of Gab1 at serine 552 (Ser552) is vital for Gab1 membrane binding. Here, we confirm our hypothesis that in the absence of MAPK activity an intrinsic part of Gab1 prevents binding to PIP3 at the PM. This epitope of Gab1, which encompasses Ser552, interacts directly with the Gab1 PH domain. Two arginines located in positions +4 and +8 of Ser552 are essential for the interaction with the PH domain, as well as for the inhibition of membrane recruitment of unphosphorylated Gab1. Ser552 phosphorylation is dispensable in respective arginine to alanine mutants of Gab1. Gab1 recruitment to the PM is highly dynamic and continuous PI3K and MAPK activities are both essential for sustained Gab1 membrane localisation. Our data document the existence of a sophisticated and robust control mechanism that prevents Gab1 translocation and signalling complex assembly after the activation of either MAPK or PI3K alone.

An accurate and precise malicious node exclusion mechanism for ad hoc networks

Mobile ad hoc networks are attractive due to the wireless communication, infrastructure-less design, and the self-organized mobile nodes. These features, however, introduce vulnerabilities, since there are no centralized control elements and the communication depends on cooperation of nodes. We propose a robust and distributed access control mechanism based on a trust model to secure the network and stimulate cooperation by excluding misbehaving nodes from the network. The mechanism divides the access control responsibility into two contexts: local and global. The local context responsibility is the neighborhood watch to notify the global context about suspicious behavior. In its turn, the global context analyzes the received information and decides whether it punishes the suspicious node using a voting scheme. We model the exclusion mechanism and perform a parameter analysis. Simulation results prove that the combination of voting and trust schemes provides an accurate and precise classification and node exclusion mechanism, even though in scenarios of limited monitoring.

A dynamic multi-channel speech enhancement system for distributed microphones in a car environment

Supporting multiple active speakers in automotive hands-free or speech dialog applications is an interesting issue not least due to comfort reasons. Therefore, a multi-channel system for enhancement of speech signals captured by distributed distant microphones in a car environment is presented. Each of the potential speakers in the car has a dedicated directional microphone close to his position that captures the corresponding speech signal. The aim of the resulting overall system is twofold: On the one hand, a combination of an arbitrary pre-defined subset of speakers’ signals can be performed, e.g., to create an output signal in a hands-free telephone conference call for a far-end communication partner. On the other hand, annoying cross-talk components from interfering sound sources occurring in multiple different mixed output signals are to be eliminated, motivated by the possibility of other hands-free applications being active in parallel. The system includes several signal processing stages. A dedicated signal processing block for interfering speaker cancellation attenuates the cross-talk components of undesired speech. Further signal enhancement comprises the reduction of residual cross-talk and background noise. Subsequently, a dynamic signal combination stage merges the processed single-microphone signals to obtain appropriate mixed signals at the system output that may be passed to applications such as telephony or a speech dialog system. Based on signal power ratios between the particular microphone signals, an appropriate speaker activity detection and therewith a robust control mechanism of the whole system is presented. The proposed system may be dynamically configured and has been evaluated for a car setup with four speakers sitting in the car cabin disturbed in various noise conditions.

Robust Power Control with Distribution Uncertainty in Cognitive Radio Networks

In cognitive radio networks, it is often impossible to have regular information exchange between PUs and SUs. This implies that SUs are unable to obtain up-to-date channel information at the PU side, and will face technical challenges in accurately controlling their interference to PUs through power control. In this paper, we assume that SUs can estimate the channel information in the reciprocal channel, and study the channel uncertainty due to estimation errors and its impact on SUs' performance and PUs' protection. Specifically, we model the uncertain channel gain to be a random variable following a state-dependent distribution function, and propose a power control mechanism that is robust against the channel uncertainty. We study the robust power control in two cases. In the first case, all SU transmitters (e.g., secondary base stations) transmit with the same power, while in the second case each SU transmitter may choose distinct transmit power based on its own preference. In either case, we formulate the power control problem as a chance constrained robust optimization problem and design an iterative algorithm, respectively. Numerical results show that our robust power control mechanism can provide better protection for PUs than existing methods that overlook the uncertainty in channel measurement, and the second-case power control generally provides better Quality of Service (QoS) for SUs than that in the first case.

Dynamic power management for multidomain system-on-chip platforms

Reducing energy consumption in multiprocessor systems-on-chip (MPSoCs) where communication happens via the network-on-chip (NoC) approach calls for multiple voltage/frequency island (VFI)-based designs. In turn, such multi-VFI architectures need efficient, robust, and accurate runtime control mechanisms that can exploit the workload characteristics in order to save power. Despite being tractable, the linear control models for power management cannot capture some important workload characteristics (e.g., fractality, nonstationarity) observed in heterogeneous NoCs; if ignored, such characteristics lead to inefficient communication and resources allocation, as well as high power dissipation in MPSoCs. To mitigate such limitations, we propose a new paradigm shift from power optimization based on linear models to control approaches based on fractal-state equations. As such, our approach is the first to propose a controller for fractal workloads with precise constraints on state and control variables and specific time bounds. Our results show that significant power savings can be achieved at runtime while running a variety of benchmark applications.

A morphogenetic approach to flexible and robust shape formation for swarm robotic systems

Embryonic development of multi-cellular organisms is governed by gene regulatory networks (GRNs), which are a collection of genes that interact with one another and with other chemicals in the cell. Inspired by the morphogenesis of biological organisms, in this paper, we propose a morphogenetic approach using a gene regulatory network (GRN) for swarm robotic systems to form complex shapes in a distributed manner. The target pattern, represented by non-uniform rational B-spline (NURBS), is embedded into the gene regulatory model, analogous to the morphogen gradients in multi-cellular development. Since the total number of robots is unknown to each robot, a dynamic neighborhood adaptation mechanism is proposed to evenly deploy the robots on the boundary of the target pattern. A theoretical proof of the system convergence is provided. Various simulation studies demonstrate that the proposed algorithm offers an effective and robust distributed control mechanism for swarm robotic systems to construct complex shapes. Furthermore, proof-of-concept experiments were successfully undertaken using e-puck mobile robots, which demonstrate that the proposed model works well with physical constraints of real robots.

Bone Balance within a Cortical BMU: Local Controls of Bone Resorption and Formation

Maintaining bone volume during bone turnover by a BMU is known as bone balance. Balance is required to maintain structural integrity of the bone and is often dysregulated in disease. Consequently, understanding how a BMU controls bone balance is of considerable interest. This paper develops a methodology for identifying potential balance controls within a single cortical BMU. The theoretical framework developed offers the possibility of a directed search for biological processes compatible with the constraints of balance control. We first derive general control constraint equations and then introduce constitutive equations to identify potential control processes that link key variables that describe the state of the BMU. The paper describes specific local bone volume balance controls that may be associated with bone resorption and bone formation. Because bone resorption and formation both involve averaging over time, short-term fluctuations in the environment are removed, leaving the control systems to manage deviations in longer-term trends back towards their desired values. The length of time for averaging is much greater for bone formation than for bone resorption, which enables more filtering of variability in the bone formation environment. Remarkably, the duration for averaging of bone formation may also grow to control deviations in long-term trends of bone formation. Providing there is sufficient bone formation capacity by osteoblasts, this leads to an extraordinarily robust control mechanism that is independent of either osteoblast number or the cellular osteoid formation rate. A complex picture begins to emerge for the control of bone volume. Different control relationships may achieve the same objective, and the ‘integration of information’ occurring within a BMU may be interpreted as different sets of BMU control systems coming to the fore as different information is supplied to the BMU, which in turn leads to different observable BMU behaviors.

Scholarly Communication 2.0: Exploring Researchers' Opinions on Web 2.0 for Scientific Knowledge Creation, Evaluation and Dissemination

This paper presents the results of a survey aimed at gauging the potential acceptance of a collaborative and Web 2.0 inspired scholarly communication sector. While this sector has seen the birth of a multitude of innovative initiatives, there is still little empirical evidence of the acceptance of such initiatives by researchers. We received 349 completed questionnaires from researchers of many different disciplines. The results of the survey show that there is a strong positive attitude towards Web 2.0 and open publishing approaches. However, the major challenge still resides in combining free dissemination of results with robust and reliable quality control mechanisms.

Scholarly Communication 2.0: Exploring Researchers' Opinions on Web 2.0 for Scientific Knowledge Creation, Evaluation and Dissemination

This paper presents the results of a survey aimed at gauging the potential acceptance of a collaborative and Web 2.0 inspired scholarly communication sector. While this sector has seen the birth of a multitude of innovative initiatives, there is still little empirical evidence of the acceptance of such initiatives by researchers. We received 349 completed questionnaires from researchers of many different disciplines. The results of the survey show that there is a strong positive attitude towards Web 2.0 and open publishing approaches. However, the major challenge still resides in combining free dissemination of results with robust and reliable quality control mechanisms.

Combining GRN modeling and demonstration-based programming for robot control

In recent years, gene regulatory networks (GRNs) have been proposed to work as reliable and robust control mechanisms for robots. Because recurrent neural networks (RNNs) have the unique characteristic of presenting system dynamics over time, we thus adopt such kind of network structure and the principles of gene regulation to develop a biologically and computationally plausible GRN model for robot control. To simulate the regulatory effects and to make our model inferable from time-series data, we also implement an enhanced network-learning algorithm to derive network parameters efficiently. In addition, we present a procedure of programming-by-demonstration to collect behavior sequence data of the robot as expression profiles, and then employ our network-modeling framework to infer controllers. To verify the proposed approach, experiments have been conducted, and the results show that our regulatory model can be inferred for robot control successfully.

A robust cell cycle control mechanism limits E2F-induced proliferation of terminally differentiated cells in vivo.

Terminally differentiated cells in Drosophila melanogaster wings and eyes are largely resistant to proliferation upon deregulation of either E2F or cyclin E (CycE), but exogenous expression of both factors together can bypass cell cycle exit. In this study, we show this is the result of cooperation of cell cycle control mechanisms that limit E2F-CycE positive feedback and prevent cycling after terminal differentiation. Aberrant CycE activity after differentiation leads to the degradation of E2F activator complexes, which increases the proportion of CycE-resistant E2F repressor complexes, resulting in stable E2F target gene repression. If E2F-dependent repression is lost after differentiation, high anaphase-promoting complex/cyclosome (APC/C) activity degrades key E2F targets to limit cell cycle reentry. Providing both CycE and E2F activities bypasses exit by simultaneously inhibiting the APC/C and inducing a group of E2F target genes essential for cell cycle reentry after differentiation. These mechanisms are essential for proper development, as evading them leads to tissue outgrowths composed of dividing but terminally differentiated cells.

Transcriptional Control of Photosynthesis Genes: The Evolutionarily Conserved Regulatory Mechanism in Plastid Genome Function

Chloroplast sensor kinase (CSK) is a bacterial-type sensor histidine kinase found in chloroplasts—photosynthetic plastids—in eukaryotic plants and algae. Using a yeast two-hybrid screen, we demonstrate recognition and interactions between: CSK, plastid transcription kinase (PTK), and a bacterial-type RNA polymerase sigma factor-1 (SIG-1). CSK interacts with itself, with SIG-1, and with PTK. PTK also interacts directly with SIG-1. PTK has previously been shown to catalyze phosphorylation of plastid-encoded RNA polymerase (PEP), suppressing plastid transcription nonspecifically. Phospho-PTK is inactive as a PEP kinase. Here, we propose that phospho-CSK acts as a PTK kinase, releasing PTK repression of chloroplast transcription, while CSK also acts as a SIG-1 kinase, blocking transcription specifically at the gene promoter of chloroplast photosystem I. Oxidation of the photosynthetic electron carrier plastoquinone triggers phosphorylation of CSK, inducing chloroplast photosystem II while suppressing photosystem I. CSK places photosystem gene transcription under the control of photosynthetic electron transport. This redox signaling pathway has its origin in cyanobacteria, photosynthetic prokaryotes from which chloroplasts evolved. The persistence of this mechanism in cytoplasmic organelles of photosynthetic eukaryotes is in precise agreement with the CoRR hypothesis for the function of organellar genomes: the plastid genome and its primary gene products are Co-located for Redox Regulation. Genes are retained in plastids primarily in order for their expression to be subject to this rapid and robust redox regulatory transcriptional control mechanism, whereas plastid genes also encode genetic system components, such as some ribosomal proteins and RNAs, that exist in order to support this primary, redox regulatory control of photosynthesis genes. Plastid genome function permits adaptation of the photosynthetic apparatus to changing environmental conditions of light quantity and quality.

Control and Operation of Hybrid Microsource System Using Advanced Fuzzy- Robust Controller

This paper proposes a modeling and controller design approach for a hybrid wind power generation system that considers a fixed wind-turbine and a dump load. Since operating conditions are kept changing, it is challenge to design a control for reliable operation of the overall system. To consider variable operating conditions, Takagi-Sugeno (TS) fuzzy model is taken into account to represent time-varying system by expressing the local dynamics of a nonlinear system through sub-systems, partitioned by linguistic rules. Also, each fuzzy model has uncertainty. Thus, in this paper, a modern nonlinear control design technique, the sliding mode nonlinear control design, is utilized for robust control mechanism. In the simulation study, the proposed controller is compared with a proportional-integral (PI) controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-hybrid power generation system.

Narrative review: evolving concepts in potassium homeostasis and hypokalemia.

Humans are intermittently exposed to large variations in potassium intake, which range from periods of fasting to ingestion of potassium-rich meals. These fluctuations would abruptly alter plasma potassium concentration if not for rapid mechanisms, primarily in skeletal muscle and the liver, that buffer the changes in plasma potassium concentration by means of transcellular potassium redistribution and feedback control of renal potassium excretion. However, buffers have capacity limits, and even robust feedback control mechanisms require that the perturbation occur before feedback can initiate corrective action. In contrast, feedforward control mechanisms sense the effect of disturbances on the system's homeostasis. This review highlights recent experimental insights into the participation of feedback and feedforward control mechanisms in potassium homeostasis. New data make clear that feedforward homeostatic responses activate when decreased potassium intake is sensed, even when plasma potassium concentration is still within the normal range and before frank hypokalemia ensues, in addition to the classic feedback activation of renal potassium conservation when plasma potassium concentration decreases. Given the clinical importance of dyskalemias in patients, these novel experimental paradigms invite renewed clinical inquiry into this important area.

An adaptive fuzzy-based CAC scheme for uplink and downlink congestion control in converged IP and DVB-S2 networks

This paper introduces a robust buffer occupancy-based connection admission control (CAC) mechanism to alleviate both uplink and downlink congestions in converged IP and broadcasting networks. The scheme also ensures a fair share of downlink bandwidth among competing satellite terminals (subnetworks) in the event of congestion. The proposed scheme is dubbed Weighted Fair CAC (W-FCAC). It accepts or rejects connections based on an adaptive fuzzy-based approach. The use of the fuzzy-based mechanism is for the purpose of overcoming issues related to instantaneous link capacity assessment, flow characterization and the associated high computational complexity, and use of traffic descriptors for new flows. Additionally, the adaptive fuzzy logic makes the proposed CAC approach robust to traffic dynamics. These features make the scheme highly suitable for DVB-S2 environments where the link capacity frequently fluctuates due to the adaptive coding/modulation of the physical layer during noisy periods. Simulation results elucidate that the proposed W-FCAC scheme prevents downlink congestion and fairly allocates network resources among satellite terminals. It also minimizes the frequency of congestion events while maintaining efficient utilization of network resources.

A robust decision feedback equalizer for ATSC DTV receivers

Least mean square (LMS) decision feedback equalizer (DFE) is preferred as an effective solution to coping with inter-symbol interference (ISI) for ATSC digital television (DTV) receivers. In DTV transmission environment, echo delay often covers several hundreds symbols, which leads to very large-scale equalizer. One consequence of the large-scale equalizer is the very slow convergence, which combined with error propagation, inherent drawback of DFE, seriously deteriorates the performance of the receivers, especially in severe channels. More working modes and corresponding robust control mechanism were given to help the equalizer converge to the stable state smoothly. Simulation results show that the improved equalizer can perform better, especially in the severe channels.