scholarly journals Minimal intervention strategies in logical signaling networks with ASP

2013 ◽  
Vol 13 (4-5) ◽  
pp. 675-690 ◽  
Author(s):  
ROLAND KAMINSKI ◽  
TORSTEN SCHAUB ◽  
ANNE SIEGEL ◽  
SANTIAGO VIDELA
Keyword(s):  
Large Scale ◽  
Quantitative Methods ◽  
Answer Set Programming ◽  
Intervention Strategies ◽  
Signaling Networks ◽  
Fine Grained ◽  
Qualitative Approaches ◽  
Large Scale Networks ◽  
Biological Signaling Networks ◽  
Biological Outcomes

AbstractProposing relevant perturbations to biological signaling networks is central to many problems in biology and medicine because it allows for enabling or disabling certain biological outcomes. In contrast to quantitative methods that permit fine-grained (kinetic) analysis, qualitative approaches allow for addressing large-scale networks. This is accomplished by more abstract representations such as logical networks. We elaborate upon such a qualitative approach aiming at the computation of minimal interventions in logical signaling networks relying on Kleene's three-valued logic and fixpoint semantics. We address this problem within answer set programming and show that it greatly outperforms previous work using dedicated algorithms.

scholarly journals MOBILE NETWORKING FOR “SMART DUST” WITH RFID SENSOR NETWORKS

2013 ◽  
pp. 272-276
Author(s):  
SHYAM D. BAWANKAR ◽  
SONAL B. BHOPLE ◽  
VISHAL D. JAISWAL
Keyword(s):  
Sensor Networks ◽  
Large Scale ◽  
Mobile Network ◽  
Base Station ◽  
Sensor Nodes ◽  
Node Localization ◽  
Fine Grained ◽  
Mobile Networking ◽  
Smart Dust ◽  
Large Scale Networks

Large-scale networks of wireless sensors are becoming an active topic of research.. We review the key elements of the emergent technology of “Smart Dust” and outline the research challenges they present to the mobile networking and systems community, which must provide coherent connectivity to large numbers of mobile network nodes co-located within a small volume. Smart Dust sensor networks – consisting of cubic millimeter scale sensor nodes capable of limited computation, sensing, and passive optical communication with a base station – are envisioned to fulfil complex large scale monitoring tasks in a wide variety of application areas. RFID technology can realize “smart-dust” applications for the sensor network community. RFID sensor networks (RSNs), which consist of RFID readers and RFID sensor nodes (WISPs), extend RFID to include sensing and bring the advantages of small, inexpensive and long-lived RFID tags to wireless sensor networks. In many potential Smart Dust applications such as object detection and tracking, fine-grained node localization plays a key role.

scholarly journals An efficient path reconstruction in dynamic and large-scale networks using extensive hashing

2017 ◽  
Vol 7 (1.1) ◽  
pp. 329
Author(s):  
David Raju Kuppala ◽  
Jayasimha Reddy Ambati ◽  
Naveen Racharla ◽  
Devi Prasanna.K
Keyword(s):  
Large Scale ◽  
Sensor Systems ◽  
Fine Grained ◽  
Remote Sensor ◽  
Game Plan ◽  
Large Scale Networks ◽  
Broad Scale

Late remote sensor systems (WSNs) are be-coming logically complex with the creating framework scale and the dynamic thought of remote correspondences. Various estimation and decisive techniques depend upon per-divide courses for correct and fine-grained examination of the psyche boggling net-work hones. In this paper, we propose iPath, a novel way inferring approach to manage reproducing the per-package directing courses in capable and broad scale frameworks. The basic idea of iPath is to abuse high path closeness to iteratively accumulate long courses from short ones. IPath starts with a hidden known game plan of ways and performs way derivation iteratively. iPath consolidates a novel layout of a lightweight Extensible hashing, hash work for affirmation of the construed ways. To furthermore improve the conclusion capacity and moreover the execution capability, iPath fuses a brisk bootstrapping computation to change the hidden game plan of ways. We also execute iPath and survey its execution using takes after from tremendous scale WSN associations and moreover expansive multiplications. Results show that iPath achieves essentially higher revamping extents under different framework settings stood out from other best in class approaches.

scholarly journals Train Scheduling with Hybrid Answer Set Programming

2020 ◽  
pp. 1-31
Author(s):  
DIRK ABELS ◽  
JULIAN JORDI ◽  
MAX OSTROWSKI ◽  
TORSTEN SCHAUB ◽  
AMBRA TOLETTI ◽  
...  
Keyword(s):  
Real World ◽  
Large Scale ◽  
Hybrid Approach ◽  
Answer Set Programming ◽  
Scheduling Problems ◽  
Planning And Scheduling ◽  
Train Scheduling ◽  
Fine Grained ◽  
Difference Constraints ◽  
Answer Set

Abstract We present a solution to real-world train scheduling problems, involving routing, scheduling, and optimization, based on Answer Set Programming (ASP). To this end, we pursue a hybrid approach that extends ASP with difference constraints to account for a fine-grained timing. More precisely, we exemplarily show how the hybrid ASP system clingo[DL] can be used to tackle demanding planning and scheduling problems. In particular, we investigate how to boost performance by combining distinct ASP solving techniques, such as approximations and heuristics, with preprocessing and encoding techniques for tackling large-scale, real-world train-scheduling instances.

Qualitative Approaches in Internet-Mediated Research: Opportunities, Issues, Possibilities

2020 ◽  
pp. 632-673
Author(s):  
Claire Hewson
Keyword(s):  
Qualitative Research ◽  
21St Century ◽  
Quantitative Methods ◽  
Viable Alternative ◽  
Design Practice ◽  
Good Design ◽  
Practical Advice ◽  
Research Opportunities ◽  
Qualitative Approaches ◽  
Research Domains

Internet-mediated research (IMR) has grown expansively since the start of the 21st Century in scope, range of methodological possibilities, and breadth of penetration across disciplines and research domains. However, the use of IMR approaches to support qualitative research has lagged behind its application in supporting quantitative methods. This chapter discusses the possibilities of using IMR methods in qualitative research and considers the issues and debates that have led some qualitative researchers to be reluctant to consider IMR as a viable alternative to traditional offline methods. The chapter adopts an optimistic stance on the potential for qualitative IMR and outlines a range of possible methods and strategies, as well as examples of successful (and less successful) studies. Practical advice on tools, procedures, and guidelines for good design practice is offered. A comment on likely future scope, methods, emerging techniques, and developments in qualitative IMR is presented.

scholarly journals Strategic resources and smallholder performance at the bottom of the pyramid

2019 ◽  
Vol 22 (3) ◽  
pp. 365-380 ◽  
Author(s):  
Matthias Olthaar ◽  
Wilfred Dolfsma ◽  
Clemens Lutz ◽  
Florian Noseleit
Keyword(s):  
Large Scale ◽  
Business Environment ◽  
Agricultural Economics ◽  
Local Market ◽  
Bottom Of The Pyramid ◽  
Fine Grained ◽  
Strategic Resources ◽  
Relative Contribution ◽  
The Relationship ◽  
Resource Based Theory

In a competitive business environment at the Bottom of the Pyramid smallholders supplying global value chains may be thought to be at the whims of downstream large-scale players and local market forces, leaving no room for strategic entrepreneurial behavior. In such a context we test the relationship between the use of strategic resources and firm performance. We adopt the Resource Based Theory and show that seemingly homogenous smallholders deploy resources differently and, consequently, some do outperform others. We argue that the ‘resource-based theory’ results in a more fine-grained understanding of smallholder performance than approaches generally applied in agricultural economics. We develop a mixed-method approach that allows one to pinpoint relevant, industry-specific resources, and allows for empirical identification of the relative contribution of each resource to competitive advantage. The results show that proper use of quality labor, storage facilities, time of selling, and availability of animals are key capabilities.

scholarly journals Contribution of Ionotropic Glutamatergic Receptors to Excitability and Attentional Signals in Macaque Frontal Eye Field

2021 ◽  
Author(s):  
Miguel Dasilva ◽  
Christian Brandt ◽  
Marc Alwin Gieselmann ◽  
Claudia Distler ◽  
Alexander Thiele
Keyword(s):  
Attentional Control ◽  
Large Scale ◽  
Neuronal Excitability ◽  
Cell Types ◽  
Receptor Activation ◽  
Frontal Eye Field ◽  
Control Signals ◽  
Cognitive Operations ◽  
Eye Field ◽  
Large Scale Networks

Abstract Top-down attention, controlled by frontal cortical areas, is a key component of cognitive operations. How different neurotransmitters and neuromodulators flexibly change the cellular and network interactions with attention demands remains poorly understood. While acetylcholine and dopamine are critically involved, glutamatergic receptors have been proposed to play important roles. To understand their contribution to attentional signals, we investigated how ionotropic glutamatergic receptors in the frontal eye field (FEF) of male macaques contribute to neuronal excitability and attentional control signals in different cell types. Broad-spiking and narrow-spiking cells both required N-methyl-D-aspartic acid and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor activation for normal excitability, thereby affecting ongoing or stimulus-driven activity. However, attentional control signals were not dependent on either glutamatergic receptor type in broad- or narrow-spiking cells. A further subdivision of cell types into different functional types using cluster-analysis based on spike waveforms and spiking characteristics did not change the conclusions. This can be explained by a model where local blockade of specific ionotropic receptors is compensated by cell embedding in large-scale networks. It sets the glutamatergic system apart from the cholinergic system in FEF and demonstrates that a reduction in excitability is not sufficient to induce a reduction in attentional control signals.

scholarly journals Inverse Infiltration Modeling of Dike Covers Made of Dredged Material Using PEST and AMALGAM

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 41
Author(s):  
Tim Jurisch ◽  
Stefan Cantré ◽  
Fokke Saathoff
Keyword(s):  
Large Scale ◽  
Measurement Data ◽  
Fine Grained ◽  
Dredged Materials ◽  
Measurement Results ◽  
Large Scale Field ◽  
Eigenvalue Ratio ◽  
Ill Posed ◽  
Materials Used ◽  
Installation Technology

A variety of studies recently proved the applicability of different dried, fine-grained dredged materials as replacement material for erosion-resistant sea dike covers. In Rostock, Germany, a large-scale field experiment was conducted, in which different dredged materials were tested with regard to installation technology, stability, turf development, infiltration, and erosion resistance. The infiltration experiments to study the development of a seepage line in the dike body showed unexpected measurement results. Due to the high complexity of the problem, standard geo-hydraulic models proved to be unable to analyze these results. Therefore, different methods of inverse infiltration modeling were applied, such as the parameter estimation tool (PEST) and the AMALGAM algorithm. In the paper, the two approaches are compared and discussed. A sensitivity analysis proved the presumption of a non-linear model behavior for the infiltration problem and the Eigenvalue ratio indicates that the dike infiltration is an ill-posed problem. Although this complicates the inverse modeling (e.g., termination in local minima), parameter sets close to an optimum were found with both the PEST and the AMALGAM algorithms. Together with the field measurement data, this information supports the rating of the effective material properties of the applied dredged materials used as dike cover material.

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