Ergodic control of partially observed Markov chains

The ergodic or long-run average cost control problem for a partially observed finite-state Markov chain is studied via the associated fully observed separated control problem for the nonlinear filter. Dynamic programming equations for the latter are derived, leading to existence and characterization of optimal stationary policies.

Model Predictive Static Programming: A Computationally Efficient Technique For Suboptimal Control Design

Combining the philosophies of nonlinear model predictive control and approximate dynamic programming, a new suboptimal control design technique is presented in this paper, named as model predictive static programming (MPSP), which is applicable for finite-horizon nonlinear problems with terminal constraints. This technique is computationally efficient, and hence, can possibly be implemented online. The effectiveness of the proposed method is demonstrated by designing an ascent phase guidance scheme for a ballistic missile propelled by solid motors. A comparison study with a conventional gradient method shows that the MPSP solution is quite close to the optimal solution.

LibVM: An architecture for shared library sandboxing

Many software applications extend their functionality by dynamically loading libraries into their allocated address space. However, shared libraries are also often of unknown provenance and quality and may contain accidental bugs or, in some cases, deliberately malicious code. Most sandboxing techniques which address these issues require recompilation of the libraries using custom tool chains, require significant modifications to the libraries, do not retain the benefits of single address-space programming, do not completely isolate guest code, or incur substantial performance overheads. In this paper we present LibVM, a sandboxing architecture for isolating libraries within a host application without requiring any modifications to the shared libraries themselves, while still retaining the benefits of a single address space and also introducing a system call inter-positioning layer that allows complete arbitration over a shared library’s functionality. We show how to utilize contemporary hardware virtualization support towards this end with reasonable performance overheads and, in the absence of such hardware support, our model can also be implemented using a software-based mechanism. We ensure that our implementation conforms as closely as possible to existing shared library manipulation functions, minimizing the amount of effort needed to apply such isolation to existing programs. Our experimental results show that it is easy to gain immediate benefits in scenarios where the goal is to guard the host application against unintentional programming errors when using shared libraries, as well as in more complex scenarios, where a shared library is suspected of being actively hostile. In both cases, no changes are required to the shared libraries themselves.

From vision to actions: Towards adaptive and autonomous humanoid robots

Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.

Programming an FPGA to Emulate the Dynamics of DC Machines

This paper presents the programming an FPGA (Field Programmable Gate Array) to emulate the dynamics of DC machines. FPGA allows high speed real time simulation with high precision. The described design includes block diagram representation of DC machine, which contain all arithmetic and logical operations. The real time simulation of the machine in FPGA is controlled by user interfaces they are Keypad interface, LCD display on-line and digital to analog converter. This approach provides emulation of electrical machine by changing the parameters. Separately Exited DC machine implemented and experimental results are presented.

Fast matrix transposition computer implementation

Eklundh's (1972) algorithm to transpose a large matrix stored on an external device such as a disc has been programmed and tested. A simple description of computer implementation is given in this note.

Improved Algorithms for Reservoir Capacity Calculation Incorporating Storage-Dependent Losses and Reliability Norm

Two algorithms that improve upon the sequent-peak procedure for reservoir capacity calculation are presented. The first incorporates storage-dependent losses (like evaporation losses) exactly as the standard linear programming formulation does. The second extends the first so as to enable designing with less than maximum reliability even when allowable shortfall in any failure year is also specified. Together, the algorithms provide a more accurate, flexible and yet fast method of calculating the storage capacity requirement in preliminary screening and optimization models.

Access path query language for relational database systems

Database management systems offer a very reliable and attractive data organization for fast and economical information storage and processing for diverse applications. It is much more important that the information should be easily accessible to users with varied backgrounds, professional as well as casual, through a suitable data sublanguage. The language adopted here (APPLE) is one such language for relational database systems and is completely nonprocedural and well suited to users with minimum or no programming background. This is supported by an access path model which permits the user to formulate completely nonprocedural queries expressed solely in terms of attribute names. The data description language (DDL) and data manipulation language (DML) features of APPLE are also discussed. The underlying relational database has been implemented with the help of the DATATRIEVE-11 utility for record and domain definition which is available on the PDP-11/35. The package is coded in Pascal and MACRO-11. Further, most of the limitations of the DATATRIEVE-11 utility have been eliminated in the interface package.

Impact of automatic region-of-interest coding on perceived quality in mobile video

At present, the most reliable method to obtain end-user perceived quality is through subjective tests. In this paper, the impact of automatic region-of-interest (ROI) coding on perceived quality of mobile video is investigated. The evidence, which is based on perceptual comparison analysis, shows that the coding strategy improves perceptual quality. This is particularly true in low bit rate situations. The ROI detection method used in this paper is based on two approaches: - (1) automatic ROI by analyzing the visual contents automatically, and; - (2) eye-tracking based ROI by aggregating eye-tracking data across many users, used to both evaluate the accuracy of automatic ROI detection and the subjective quality of automatic ROI encoded video. The perceptual comparison analysis is based on subjective assessments with 54 participants, across different content types, screen resolutions, and target bit rates while comparing the two ROI detection methods. The results from the user study demonstrate that ROI-based video encoding has higher perceived quality compared to normal video encoded at a similar bit rate, particularly in the lower bit rate range.

Performance evaluation of a distributed concurrency control algorithm

Concurrency control (CC) algorithms are important in distributed database systems to ensure consistency of the database. A number of such algorithms are available in the literature. The issue of performance evaluation of these algorithms has been recognized to be important. However, only a few studies have been carried out towards this. This paper deals with the performance evaluation of a CC algorithm proposed by Rosenkrantz et al. through a detailed simulation study. In doing so, the algorithm has been modified so that it can, within itself, take care of the redundancy in the database. The influences of various system parameters and the transaction profile on the response time and on the degree of conflict are considered. The entire study has been carried out using the programming language SIMULA on a DEC-1090 system.

Studies of working memory in interrupted human-computer interaction

Distraction in the workplace is increasingly more common in the information age. Several tasks and sources of information compete for a worker's limited cognitive capacities in human-computer interaction (HCI). In some situations even very brief interruptions can have detrimental effects on memory. Nevertheless, in other situations where persons are continuously interrupted, virtually no interruption costs emerge. This dissertation attempts to reveal the mental conditions and causalities differentiating the two outcomes. The explanation, building on the theory of long-term working memory (LTWM; Ericsson and Kintsch, 1995), focuses on the active, skillful aspects of human cognition that enable the storage of task information beyond the temporary and unstable storage provided by short-term working memory (STWM). Its key postulate is called a retrieval structure an abstract, hierarchical knowledge representation built into long-term memory that can be utilized to encode, update, and retrieve products of cognitive processes carried out during skilled task performance. If certain criteria of practice and task processing are met, LTWM allows for the storage of large representations for long time periods, yet these representations can be accessed with the accuracy, reliability, and speed typical of STWM. The main thesis of the dissertation is that the ability to endure interruptions depends on the efficiency in which LTWM can be recruited for maintaing information. An observational study and a field experiment provide ecological evidence for this thesis. Mobile users were found to be able to carry out heavy interleaving and sequencing of tasks while interacting, and they exhibited several intricate time-sharing strategies to orchestrate interruptions in a way sensitive to both external and internal demands. Interruptions are inevitable, because they arise as natural consequences of the top-down and bottom-up control of multitasking. In this process the function of LTWM is to keep some representations ready for reactivation and others in a more passive state to prevent interference. The psychological reality of the main thesis received confirmatory evidence in a series of laboratory experiments. They indicate that after encoding into LTWM, task representations are safeguarded from interruptions, regardless of their intensity, complexity, or pacing. However, when LTWM cannot be deployed, the problems posed by interference in long-term memory and the limited capacity of the STWM surface. A major contribution of the dissertation is the analysis of when users must resort to poorer maintenance strategies, like temporal cues and STWM-based rehearsal. First, one experiment showed that task orientations can be associated with radically different patterns of retrieval cue encodings. Thus the nature of the processing of the interface determines which features will be available as retrieval cues and which must be maintained by other means. In another study it was demonstrated that if the speed of encoding into LTWM, a skill-dependent parameter, is slower than the processing speed allowed for by the task, interruption costs emerge. Contrary to the predictions of competing theories, these costs turned out to involve intrusions in addition to omissions. Finally, it was learned that in rapid visually oriented interaction, perceptual-procedural expectations guide task resumption, and neither STWM nor LTWM are utilized due to the fact that access is too slow. These findings imply a change in thinking about the design of interfaces. Several novel principles of design are presented, basing on the idea of supporting the deployment of LTWM in the main task.

Personality and social psychological studies on computer-mediated communication in school settings

The present study examined how personality and social psychological factors affect third and fourth graders' computer-mediated communication. Personality was analysed in terms of the following strategies: optimism, pessimism and defensive pessimism. Students worked either individually or in dyads which were paired homogeneously or heterogeneously according to the strategies. Moreover, the present study compared horizontal and vertical interaction. The study also examined the role that popularity plays, and students were divided into groups based on their popularity level. The results show that an optimistic strategy is useful. Optimism was found to be related to the active production and processing of ideas. Although previous research has identified drawbacks to pessimism in achievement settings, this study shows that the pessimistic strategy is not as debilitating a strategy as is usually assumed. Pessimistic students were able to process their ideas. However, defensive pessimists were somewhat cautious in introducing or changing ideas. Heterogeneous dyads were not beneficial configurations with respect to producing, introducing, or changing ideas. Moreover, many differences were found to exist between the horizontal and vertical interaction; specifically, the students expressed more opinions and feelings when teachers took no part in the discussions. Strong emotions were observed especially in the horizontal interaction. Further, group working skills were found to be more important for boys than for girls, while rejected students were not at a disadvantage compared to popular ones. Schools can encourage emotional and social learning. The present study shows that students can use computers to express their feelings. In addition, students who are unpopular in non-computer contexts or students who use pessimism can benefit from computers. Participation in computer discussions can give unpopular children a chance to develop confidence when relating to peers.

Mathematics, programming, and STEM

Learning mathematics is a complex and dynamic process. In this paper, the authors adopt a semiotic framework (Yeh & Nason, 2004) and highlight programming as one of the main aspects of the semiosis or meaning-making for the learning of mathematics. During a 10-week teaching experiment, mathematical meaning-making was enriched when primary students wrote Logo programs to create 3D virtual worlds. The analysis of results found deep learning in mathematics, as well as in technology and engineering areas. This prompted a rethinking about the nature of learning mathematics and a need to employ and examine a more holistic learning approach for the learning in science, technology, engineering, and mathematics (STEM) areas.