Knowledge of the mass of the manipulated load (i.e. payload) in off-highway machines is useful information for a variety of reasons ranging from knowledge of machine stability to ensuring compliance with transportion regulations. This knowledge is difficult to ascertain however. This dissertation concerns itself with delineating the motivations for, and difficulties in development of a dynamic payload weighing algorithm. The dissertation will describe how the new type of dynamic payload weighing algorithm was developed and progressively overcame some of these difficulties.<p> The payload mass estimate is dependent upon many different variables within the off-highway vehicle. These variables include static variability such as machining tolerances of the revolute joints in the linkage, mass of the linkage members, etc as well as dynamic variability such as whole-machine accelerations, hydraulic cylinder friction, pin joint friction, etc. Some initial effort was undertaken to understand the static variables in this problem first by studying the effects of machining tolerances on the working linkage kinematics in a four-wheel-drive loader. This effort showed that if the linkage members were machined within the tolerances prescribed by the design of the linkage components, the tolerance stack-up of the machining variability had very little impact on overall linkage kinematics.<p> Once some of the static dependent variables were understood in greater detail significant effort was undertaken to understand and compensate for the dynamic dependent variables of the estimation problem. The first algorithm took a simple approach of using the kinematic linkage model coupled with hydraulic cylinder pressure information to calculate a payload estimate directly. This algorithm did not account for many of the aforementioned dynamic variables (joint friction, machine acceleration, etc) but was computationally expedient. This work however produced payload estimates with error far greater than the 1% full scale value being targeted. Since this initial simplistic effort met with failure, a second algorithm was needed. The second algorithm was developed upon the information known about the limitations of the first algorithm. A suitable method of compensating for the non-linear dependent dynamic variables was needed. To address this dilemma, an artificial neural network approach was taken for the second algorithm. The second algorithms construction was to utilise an artificial neural network to capture the kinematic linkage characteristics and all other dynamic dependent variable behaviour and estimate the payload information based upon the linkage position and hydraulic cylinder pressures. This algorithm was trained using emperically collected data and then subjected to actual use in the field. This experiment showed that that the dynamic complexity of the estimation problem was too large for a small (and computationally feasible) artificial neural network to characterize such that the error estimate was less than the 1% full scale requirement.<p> A third algorithm was required due to the failures of the first two. The third algorithm was constructed to ii take advantage of the kinematic model developed and utilise the artificial neural networks ability to perform nonlinear mapping. As such, the third algorithm developed uses the kinematic model output as an input to the artificial neural network. This change from the second algorithm keeps the network from having to characterize the linkage kinematics and only forces the network to compensate for the dependent dynamic variables excluded by the kinematic linkage model. This algorithm showed significant improvement over the previous two but still did not meet the required 1% full scale requirement. The promise shown by this algorithm however was convincing enough that further effort was spent in trying to refine it to improve the accuracy.<p> The fourth algorithm developed proceeded with improving the third algorithm. This was accomplished by adding additional inputs to the artificial neural network that allowed the network to better compensate for the variables present in the problem. This effort produced an algorithm that, when subjected to actual field use, produced results very near the 1% full scale accuracy requirement. This algorithm could be improved upon slightly with better input data filtering and possibly adding additional network inputs.<p> The final algorithm produced results very near the desired accuracy. This algorithm was also novel in that for this estimation, the artificial neural network was not used soley as the means to characterize the problem for estimation purposes. Instead, much of the responsibility for the mathematical characterization of the problem was placed upon a kinematic linkage model that then fed its own payload estimate into the neural network where the estimate was further refined during network training with calibration data and additional inputs. This method of nonlinear state estimation (i.e. utilising a neural network to compensate for nonlinear effects in conjunction with a first principles model) has not been seen previously in the literature.

While the hippocampus may play an essential role in the expression of memories soon after training, over time these memories are thought to become increasingly dependent on coordinated activity in a broad network of cortical and subcortical brain regions. However, the distributed nature of this representation has made it challenging to define the neural elements of the memory trace, and lesion and electrophysiological approaches provide only a narrow window into what is appreciated to be a much more global network. Here global mapping approaches are used to identify networks of brain regions that are activated and co-activated following recall of recent and remote contextual fear memory in mice. Analysis of Fos expression across 84 brain regions allowed for the description of brain-wide activity and interactivity of brain regions associated with memory expression. Activity analysis revealed that remote memory engages a broad collection of cortical and subcortical regions in comparison to recent memory expression. Interactivity analyses revealed that functional connectivity associated with fear memories depends on memory age and is altered in mutant mice that exhibit premature forgetting. In-depth functional connectivity analysis of remote long-term fear memory indicates that memory recall engages a network that has a distinct thalamic-hippocampal-cortical signature. This network is concurrently integrated and segregated and therefore has small-world properties as well as a resilient core of highly inter-connected regions. Centrality measures identify a collection of regions that may play a critical role in the function of the network including expected regions such as the anterior cingulate cortex and prelimbic cortex as well as novel regions including the reuniens thalamic nucleus. Post conditioning lesions of the reuniens lead to mild deficits in contextual fear memory expression providing support for the idea that identified hub regions may play a critical role in the function of the network. These results identify and describe functional activity and interactivity of brain regions underlying recent and remote fear memory expression and provide strong evidence for reorganization and distribution of the functional organization of memories over time.

Vortrag UNIX-Stammtisch 02/01

The demands of future computing, as well as the challenges of nanometer-era VLSI design, will require new design techniques and design styles that are simultaneously high performance, energy-efficient, and robust to noise and process variation. One of the emerging problems concerns the communication mechanisms between the increasing number of blocks, or cores, that can be integrated onto a single chip. The bus-based systems and point-to-point interconnection strategies in use today cannot be easily scaled to accommodate the large numbers of cores projected in the near future. Network-on-chip (NoC) interconnect infrastructures are one of the key technologies that will enable the emergence of many-core processors and systems-on-chip with increased computing power and energy efficiency. This dissertation is focused on testing, yield improvement and fault-tolerance of such NoC infrastructures. A fast, efficient test method is developed for NoCs, that exploits their inherent parallelism to reduce the test time by transporting test data on multiple paths and testing multiple NoC components concurrently. The improvement of test time varies, depending on the NoC architecture and test transport protocol, from 2X to 34X, compared to current NoC test methods. This test mechanism is used subsequently to perform detection of NoC link permanent faults, which are then repaired by an on-chip mechanism that replaces the faulty signal lines with fault-free ones, thereby increasing the yield, while maintaining the same wire delay characteristics. The solution described in this dissertation improves significantly the achievable yield of NoC inter-switch channels – from 4% improvement for an 8-bit wide channel, to a 71% improvement for a 128-bit wide channel. The direct benefit is an improved fault-tolerance and increased yield and long-term reliability of NoC based multicore systems.

Twitter is one of the most popular online social networking sites. It provides a unique and novel venue of publishing: it has over 500 million active users around the globe; tweets are brief, limited to 140 characters, an ideal way for people to publish spontaneously. As a result, Twitter has the short delays in reflecting what its users perceive, compared to other venues such as blogs and product reviews. We design and implement SportSense, which exploits Twitter users as human sensors of the physical world to detect major events in real-time. Using the National Football League (NFL) games as a targeted domain, we report in-depth studies of the delay and trend of tweets, and their dependence on other properties. We present event detection method based on these findings, and demonstrate that it can effectively and accurately extract major game events using open access Twitter data. SportSense has been evolving during the 2010-11 and 2011-12 NFL seasons and it has been collecting hundreds of millions tweets. We provide SportSense API for developers to use our system to create Twitter-enabled applications.

In this thesis we focused on high performance embedded real-time networks which are designed for systems like radar signalling processing systems, control systems etc. These high performance embedded networks consist of emerging standards like PCI Express, RapidIO, and standard Ethernet. All of these switched embedded networks communicate with each other through common gateway nodes. As these networks have different rate characteristics, maximum packet size (MTU), packet priorities, addressing schemes etc we have therefore defined the gateway nodes for these heterogeneous embedded networks which will allow these heterogeneous embedded networks to communicate with each other with the help of different translation functions. These gateway nodes allow end-to-end transmission across the heterogeneous embedded networks while keeping bound on end-to-end delay and guaranteed throughput. We need to have some flow control mechanism which will shape the traffic flow in the mentioned embedded networks and will avoid from buffer overflow.

The theme of this thesis is to analyse the performance of a conventional mesh topology in a multipath fading environment and compare it with a newly proposed multiple cell based mesh topology. The communication performance in general is measured by the overall through-put, packets delivery reliability, average message delivery delay and power-consumption. In this thesis, for simplicity of the calculation the network performance is indirectly measured in-terms of the number of additional routes originally required to connect an isolated or disconnected device, percentage of the devices which have reliable and unreliable route from or to the back bone routers, number of hops from back-bone routers to the nodes and redundant routes which includes the routes inside the particular cell or outside to the other cell. In this simulation 240 nodes has been used within the area of 120 x 60 m2 which is just in accordance with an average size of industry. Network simulation is broken down into five different scenarios with respect to different number of field devices or nodes and back bone routers along with the presence of obstacles in the area and then analysed respectively. Entire simulation and analytical work have been done on MATLAB. Major applications of multiple cell based mesh topology can be used within industrial process automation, such as pulp and paper, steel, oil and gas, etc.

Peer-to-Peer (P2P) systems are emerging as a new form of distributed computing with a strong emphasis on self-organization, decentralization, and autonomy of the participating nodes. The characteristics of self-organization, autonomy, and decentralization allow for highly adaptive, robust, and scalable networks, making P2P an increasingly interesting way to design distributed systems. <p>Since the deployment of P2P systems involves significant resources, e.g., hundreds of hosts and users, it is often not possible to run realistic tests prior to the rollout of the system. Consequently, simulation is the only realistic approach for testing or predicting the behavior of large P2P networks. However, the majority of the existing simulators tend to provide limited flexibility in simulating the details of the users, application, protocol, and physical network. <p>In this research, the impact of user behavior, protocol, and physical network characteristic on the overall P2P system are being observed. The aim is to investigate the importance of simulating P2P systems in such detail.

Computers are networked together in order to share the information they store and process. The internet connects many of these networks together, offering a multitude of options for communication, productivity and entertainment. It also offers the opportunity for unscrupulous individuals to contact these networked computers and attempt to appropriate or destroy the data on them, the computing resources they provide, and the identity or reputation of the computer user. Measures to secure networks need to be implemented by network administrators and users to protect their computing assets. <p>Firewalls filter information as it flows through a network. This filter can be implemented in hardware or software and can be used to protect computers from unwanted access. While software firewalls are considered easier to set up and use, hardware firewalls are often considered faster and more secure. Absent from the marketplace is an embedded hardware solution applicable to desktop systems. <p>Traditional software firewalls use the processor of the computer to filter packets; this is disadvantageous because the computer can become unusable during a network attack when the processor is swamped by the firewall process. Traditional hardware firewalls are usually implemented in a single location, between a private network and the internet. Depending on the size of the private network, a hardware firewall may be responsible for filtering the network traffic of hundreds of clients. This not only makes the required hardware firewall quite expensive, but dedicates those financial resources to a single point that may fail. <p>The dynamic silicon firewall project implements a hardware firewall using a soft-core processor with a custom peripheral designed using a hardware description language. Embedding this hardware firewall on each network interface card in a network would offer many benefits. It would avoid the aforementioned denial of service problem that software firewalls are susceptible to since the custom peripheral handles the filtering of packets. It could also reduce the complexity required to secure a large private network, and eliminate the problem of a single point of failure. Also, the dynamic silicon firewall requires little to no administration since the filtering rules change with the users network activity. The design of the dynamic silicon firewall incorporates the best features from traditional hardware and software firewalls, while minimizing or avoiding the negative aspects of each.

The Internet is divided into multiple layers to reduce and manage complexity. The International Organization for Standardization (ISO) developed a 7 layer network model and had been revised to a 5 layer TCP/IP based Internet Model. The layers of the Internet can also be divided into top layer TCP/IP protocol suite layers and the underlying transport network layers. SONET/SDH, a dominant transport network, was designed initially for circuit based telephony services. Advancement in the internet world with voice and video services had pushed SONET/SDH to operate with reduced efficiencies and increased costs. Hence, redesign and redeployment of the transport network has been and continues to be a subject of research and development. Several projects are underway to explore new transport network ideas such as G.709 and GMPLS.<p> This dissertation presents the Geographical Cell Transport (GCT) protocol as a candidate for a next generation transport network. The GCT transport protocol and its cell format are described. The benefits provided by the proposed GCT transport protocol as compared to the existing transport networks are investigated. Existing switch architectures are explored and a best architecture to be implemented in VLSI for the proposed transport network input queued virtual output queuing is obtained. The objectives of this switch are high performance, guaranteed fairness among all inputs and outputs, robust behavior under different traffic patterns, and support for Quality of Service (QoS) provisioning. An implementation of this switch architecture is carried out using HDL.<p> A novel pseudo random number generation unit is designed to nullify the bias present in an arbitration unit. The validity of the designed is checked by developing a traffic load model. The speedup factor required in the switch to maintain desired throughput is explored and is presented in detail. Various simulation results are shown to study the behavior of the designed switch under uniform and hotspot traffic. The simulation results show that QoS behavior and the crossing traffic through the switch has not been affected by hotspots.