KInNeSS: A Modular Framework for Computational Neuroscience

Making use of very detailed neurophysiological, anatomical, and behavioral data to build biological-realistic computational models of animal behavior is often a difficult task. Until recently, many software packages have tried to resolve this mismatched granularity with different approaches. This paper presents KInNeSS, the KDE Integrated NeuroSimulation Software environment, as an alternative solution to bridge the gap between data and model behavior. This open source neural simulation software package provides an expandable framework incorporating features such as ease of use, scalabiltiy, an XML based schema, and multiple levels of granularity within a modern object oriented programming design. KInNeSS is best suited to simulate networks of hundreds to thousands of branched multu-compartmental neurons with biophysical properties such as membrane potential, voltage-gated and ligand-gated channels, the presence of gap junctions of ionic diffusion, neuromodulation channel gating, the mechanism for habituative or depressive synapses, axonal delays, and synaptic plasticity. KInNeSS outputs include compartment membrane voltage, spikes, local-field potentials, and current source densities, as well as visualization of the behavior of a simulated agent. An explanation of the modeling philosophy and plug-in development is also presented. Further developement of KInNeSS is ongoing with the ultimate goal of creating a modular framework that will help researchers across different disciplines to effecitively collaborate using a modern neural simulation platform.Center for Excellence for Learning Education, Science, and Technology (SBE-0354378); Air Force Office of Scientific Research (F49620-01-1-0397); Office of Naval Research (N00014-01-1-0624

XOR-Based Compact Triangulations

Media, image processing, and geometric-based systems and applications need data structures to model and represent different geometric entities and objects. These data structures have to be time efficient and compact in term of space. Many structures in use are proposed to satisfy those constraints. This paper introduces a novel compact data structure inspired by the XOR-linked lists. The subject of this paper concerns the triangular data structures. Nevertheless, the underlying idea could be used for any other geometrical subdivision. The ability of the bitwise XOR operator to reduce the number of references is used to model triangle and vertex references. The use of the XOR combined references needs to define a context from which the triangle is accessed. The direct access to any triangle is not possible using only the XOR-linked scheme. To allow the direct access, additional information are added to the structure. This additional information permits a constant time access to any element of the triangulation using a local resolution scheme. This information represents an additional cost to the triangulation, but the gain is still maintained. This cost is reduced by including this additional information to a local sub-triangulation and not to each triangle. Sub-triangulations are calculated implicitly according to the catalog-based structure. This approach could be easily extended to other representation models, such as vertex-based structures or edge-based structures. The obtained results are very interesting since the theoretical gain is estimated to 38 % and the practical gain obtained from sample benches is about 34 %

Formal Object Interaction Language: Modeling and Verification of Sequential and Concurrent Object-Oriented Software

As software systems become larger and more complex, developers require the ability to model abstract concepts while ensuring consistency across the entire project. The internet has changed the nature of software by increasing the desire for software deployment across multiple distributed platforms. Finally, increased dependence on technology requires assurance that designed software will perform its intended function. This thesis introduces the Formal Object Interaction Language (FOIL). FOIL is a new object-oriented modeling language specifically designed to address the cumulative shortcomings of existing modeling techniques. FOIL graphically displays software structure, sequential and concurrent behavior, process, and interaction in a simple unified notation, and has an algebraic representation based on a derivative of the π-calculus. The thesis documents the technique in which FOIL software models can be mathematically verified to anticipate deadlocks, ensure consistency, and determine object state reachability. Scalability is offered through the concept of behavioral inheritance; and, FOIL’s inherent support for modeling concurrent behavior and all known workflow patterns is demonstrated. The concepts of process achievability, process complete achievability, and process determinism are introduced with an algorithm for simulating the execution of a FOIL object model using a FOIL process model. Finally, a technique for using a FOIL process model as a constraint on FOIL object system execution is offered as a method to ensure that object-oriented systems modeled in FOIL will complete their processes based activities. FOIL’s capabilities are compared and contrasted with an extensive array of current software modeling techniques. FOIL is ideally suited for data-aware, behavior based systems such as interactive or process management software

A study of novice programmer performance and programming pedagogy.

Identifying and mitigating the difficulties experienced by novice programmers is an active area of research that has embraced a number of research areas. The aim of this research was to perform a holistic study into the causes of poor performance in novice programmers and to develop teaching approaches to mitigate them. A grounded action methodology was adopted to enable the primary concepts of programming cognitive psychology and their relationships to be established, in a systematic and formal manner. To further investigate novice programmer behaviour, two sub-studies were conducted into programming performance and ability. The first sub-study was a novel application of the FP-Tree algorithm to determine if novice programmers demonstrated predictable patterns of behaviour. This was the first study to data mine programming behavioural characteristics rather than the learner’s background information such as age and gender. Using the algorithm, patterns of behaviour were generated and associated with the students’ ability. No patterns of behaviour were identified and it was not possible to predict student results using this method. This suggests that novice programmers demonstrate no set patterns of programming behaviour that can be used determine their ability, although problem solving was found to be an important characteristic. Therefore, there was no evidence that performance could be improved by adopting pedagogies to promote simple changes in programming behaviour beyond the provision of specific problem solving instruction. A second sub-study was conducted using Raven’s Matrices which determined that cognitive psychology, specifically working memory, played an important role in novice programmer ability. The implication was that programming pedagogies must take into consideration the cognitive psychology of programming and the cognitive load imposed on learners. Abstracted Construct Instruction was developed based on these findings and forms a new pedagogy for teaching programming that promotes the recall of abstract patterns while reducing the cognitive demands associated with developing code. Cognitive load is determined by the student’s ability to ignore irrelevant surface features of the written problem and to cross-reference between the problem domain and their mental program model. The former is dealt with by producing tersely written exercises to eliminate distractors, while for the latter the teaching of problem solving should be delayed until the student’s program model is formed. While this does delay the development of problem solving skills, the problem solving abilities of students taught using this pedagogy were found to be comparable with students taught using a more traditional approach. Furthermore, monitoring students’ understanding of these patterns enabled micromanagement of the learning process, and hence explanations were provided for novice behaviour such as difficulties using arrays, inert knowledge and “code thrashing”. For teaching more complex problem solving, scaffolding of practice was investigated through a program framework that could be developed in stages by the students. However, personalising the level of scaffolding required was complicated and found to be difficult to achieve in practice. In both cases, these new teaching approaches evolved as part of a grounded theory study and a clear progression of teaching practice was demonstrated with appropriate evaluation at each stage in accordance with action researc

Neural networks and their application for structural self-diagnosis

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2001.Includes bibliographical references (leaves 85-87).by Tung-Ju Hsieh.S.M

Increasing the Semantic Similarity of Object-Oriented Domain Models by Performing Behavioral Analysis First

The main goal of any object-oriented analysis (OOA) method is to produce a model that aids in understanding and communicating knowledge about a modeled domain. A higher degree of similarity among independently produced domain models provides an indication of how well the domain was understood by the different analysts, i. e. , more similar models indicate a closer and a more common understanding of a domain. A common understanding is of critical importance for effective knowledge communication and sharing. The core of any OOA method is discovering and understanding concepts and their relationships in a domain. The main artifact produced by an OOA method is a domain model of the domain. A domain model often serves as the main source of design concepts during objectoriented design (OOD). This thesis evaluates two OOA methods by comparing the degree of similarity of the resulting domain models. In particular, this work compares the semantic similarity of domain models extracted from use cases by specification of sequence diagrams and then domain models, and specification of unified use case statecharts and then domain models. The thesis makes case studies out of the application of the first method to 31 instances of large Voice-over-IP (VoIP) system and its information management system (IMS) and to 3 small elevator systems, and out of the application of the second method to 46 instances of the same large VoIP system and its IMS and to 12 instances of a medium-sized elevator system. From an analysis of data from these case studies, the thesis concludes that there is an increase of 10% in the semantic similarity of domain models produced using the second method, but at the cost of less than or equal to 25% more analysis time

Real-time modeling of river basin response using radar-generated rainfall maps and a distributed hydrologic database

Thesis (Civ. E)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1992.Includes bibliographical references (p. 315-324).by Luis Garrote.Civ.