Applying dynamic Bayesian networks to perturbed gene expression data

in BMC Bioinformatics (2006), 7

An approach to information retrieval and question answering in the legal domain

Scientific Conference (2016, November 15)

We describe in this paper, a report of our participation at COLIEE 2016 Information Retrieval (IR) and Legal Question Answering (LQA) tasks. Our solution for the IR part employs the use of a simple but ... [more ▼]

We describe in this paper, a report of our participation at COLIEE 2016 Information Retrieval (IR) and Legal Question Answering (LQA) tasks. Our solution for the IR part employs the use of a simple but effective Machine Learning (ML) procedure. Our Question Answering solution answers "YES or 'NO' to a question, i.e., 'YES' if the question is entailed by a text and 'NO' otherwise. With recent exploit of Multi-layered Neural Network systems at language modeling tasks, we presented a Deep Learning approach which uses an adaptive variant of the Long-Short Term Memory (LSTM), i.e. the Child Sum Tree LSTM (CST-LSTM) algorithm that we modified to suit our purpose. Additionally, we benchmarked this approach by handcrafting features for two popular ML algorithms, i.e., the Support Vector Machine (SVM) and the Random Forest (RF) algorithms. Even though we used some features that have performed well from similar works, we also introduced some semantic features for performance improvement. We used the results from these two algorithms as the baseline for our CST-LSTM algorithm. All evaluation was done on the COLIEE 2015 training and test sets. The overall result conforms the competitiveness of our approach. [less ▲]

The Arabidopsis circadian clock incorporates a cADPR-based feedback loop

in SCIENCE (2007), 318(5857), 1789-1792

Transcriptional feedback loops are a feature of circadian clocks in both animals and plants. We show that the plant circadian clock also incorporates the cytosolic signaling molecule cyclic adenosine ... [more ▼]

Transcriptional feedback loops are a feature of circadian clocks in both animals and plants. We show that the plant circadian clock also incorporates the cytosolic signaling molecule cyclic adenosine diphosphate ribose (cADPR). cADPR modulates the circadian oscillator’s transcriptional feedback loops and drives circadian oscillations of Ca2+ release. The effects of antagonists of cADPR signaling, manipulation of cADPR synthesis, and mathematical simulation of the interaction of cADPR with the circadian clock indicate that cADPR forms a feedback loop within the plant circadian clock. [less ▲]

ARL – Akademie für RaumePostwachstum und Raumentwicklung – Denkanstöße für Wissenschaft und Praxis.

Report (2021)

This position paper, drawn up by members of the ARL’s Working Group on Post-Growth Economies (2016 – 2020), situates the international post-growth debate and discusses its relevance for spatial ... [more ▼]

This position paper, drawn up by members of the ARL’s Working Group on Post-Growth Economies (2016 – 2020), situates the international post-growth debate and discusses its relevance for spatial development and spatial science research. In addition to sectoral approaches and findings, the authors make concrete proposals for post-growth focuses in planning, research and teaching, distinguishing between changes that can be achieved in the short term and measures designed for the medium to long term. [less ▲]

Assessing Equity in Carsharing Systems: the case of Munich, Germany

in Transportation Research Procedia (2021)

Assessing partial observability in network sensor location problems

in Transportation Research. Part B : Methodological (2014), 70

The quality of information on a network is crucial for different transportation planning and management applications. Problems focusing on where to strategically extract this information can be broadly ... [more ▼]

The quality of information on a network is crucial for different transportation planning and management applications. Problems focusing on where to strategically extract this information can be broadly subdivided into observability problems, which rely on the topological properties of the network, and flow-estimation problems, where (prior) information on observed flows is needed to identify optimal sensor locations. This paper contributes mainly to the first category: more specifically, it presents a new methodology and an intuitive metric able to quantify the quality of a solution in case of partial observability, i.e. when not all flow variables are observed or can be uniquely determined from the observed flows. This methodology is based on existing approaches that can efficiently find solutions for full observability (i.e., the set of sensors needed to make the system fully determined), and exploits only the algebraic relations between link, route and origin-destination flow variables to quantify the information contained in any arbitrary subset of these variables. The new metric allows, through its adoption within simple search algorithms, to efficiently select sensor locations when the number of available sensors is limited by, for example, budget constraints and is less than the number needed to guarantee full observability. The chosen positions aim at selecting those locations that contain the largest information content on the whole network. This is an important contribution in this field, since even in small sized networks the solution for full observability requires an exceedingly large amount of sensors. The assessment of partial observability solutions, based on explicit route enumeration, allows one to categorize families of full observability solutions, and shows that these contain different information potential. This way, it is possible to rank solutions requiring a lower number of sensors while containing the same information content. We tested this new methodology both on toy networks, in order to analyse the properties of the metric and illustrate its logic, and to explain and test heuristic search algorithms for optimal sensor positioning on a real-sized network. Analysis of partial observability solutions shows that the basic search algorithms succeed in finding the links that contain the largest deal of information in a network. [less ▲]

Assessing the consistency between observed and modelled route choices through GPS data

in Proceedings of the MT-ITS Conference (2015, June)

Assessing the Performance of a Two-Step Dynamic Demand Estimation Model on Large-Scale Congested Networks

Poster (2018, January)

Assessing the robustness of decentralized gathering: a multi‐agent approach on micro‐biological systems

in Swarm Intelligence (2020), 14

Adopting a multi-agent systems paradigm, we developed, tested and exploited a computational testbed that simulates gathering features of the social amoeba Dictyostelium discoideum. It features a tailored ... [more ▼]

Adopting a multi-agent systems paradigm, we developed, tested and exploited a computational testbed that simulates gathering features of the social amoeba Dictyostelium discoideum. It features a tailored design and implementation to manage discrete simulations with autonomous agents on a microscopic scale, thus focusing on their social behavior and mutual interactions. Hence, we could assess the behavioral conditions under which decentralized gathering could occur. We investigated the dependence of the model dynamics on the main physical variables, namely density and number of amoebas, gaining indications that the process strongly depends on both. This result integrates previous researches, where density is identified as the sole relevant variable. We determined a high-density and high-numerosity region where assuming a scale-free behavior is safe. We also estimated the systematic uncertainties arising from a number of amoebas off the scale-free region, when coping with limited computational resources. Finally, we probed the robustness of the simulated gathering process against both extrinsic and intrinsic noise sources. [less ▲]

Assessment of implicit and explicit algorithms in numerical simulation of granular matter

Doctoral thesis (2012)

The objectives of this dissertation are to investigate and demonstrate the potentials of implicit integration methods in predicting the dynamics of granular media and to describe the granular dynamics on ... [more ▼]

The objectives of this dissertation are to investigate and demonstrate the potentials of implicit integration methods in predicting the dynamics of granular media and to describe the granular dynamics on forward and backward acting grates by discrete element method. Traditionally, explicit integration methods are employed within the context of Discrete Element Method. Generally, explicit equations are simpler to solve than the implicit ones but they require a small time step to be utilized. In this study, an implicit Numerov integration scheme is employed to integrate the equations of motion. The implicit method is verified in different test cases starting from simple cases to more complicated cases including hundreds of particles. Comparing the results with the results of the explicit method, it is shown that the implicit method exhibits a distinguished advantage only at very large time steps. Taking into account the overhead of solving non-linear equations at each time step, it is concluded that implicit methods are computationally too expensive for their limited gains. Addressing the second objective of this study, the residence time distribution of granular particles on forward and backward acting grates are numerically predicted. Very good agreement between the predictions and the available experimental results is achieved. It can be concluded that the Discrete Element Method is highly capable of predicting the dynamics of solid fuel particles on grate systems. Future work shall include coupling of the method with computational fluid dynamics in order to account for thermal conversion of the fuel particles. [less ▲]