6,118 research outputs found
Is there a universality of the helix-coil transition in protein models?
The similarity in the thermodynamic properties of two completely different
theoretical models for the helix-coil transition is examined critically. The
first model is an all-atomic representation for a poly-alanine chain, while the
second model is a minimal helix-forming model that contains no system
specifics. Key characteristics of the helix-coil transition, in particular, the
effective critical exponents of these two models agree with each other, within
a finite-size scaling analysis.Comment: Latex, to appear in Eur. Phys. J.
Long coherence times for edge spins
We show that in certain one-dimensional spin chains with open boundary
conditions, the edge spins retain memory of their initial state for very long
times. The long coherence times do not require disorder, only an ordered phase.
In the integrable Ising and XYZ chains, the presence of a strong zero mode
means the coherence time is infinite, even at infinite temperature. When Ising
is perturbed by interactions breaking the integrability, the coherence time
remains exponentially long in the perturbing couplings. We show that this is a
consequence of an edge "almost" strong zero mode that almost commutes with the
Hamiltonian. We compute this operator explicitly, allowing us to estimate
accurately the plateau value of edge spin autocorrelator.Comment: 13 pages, 13 figures; references adde
Knowledge management in a research & development environment - The Integration of company culture and technology
This thesis will show that understanding company structure and company culture are significantly more important than the actual technological tools an organization uses to implement successful knowledge management. An examination of company structure and cultural enablers will be followed by a review of some of the most widespread knowledge management tools to illustrate how knowledge management can be successfully put into practice
Broadcasting Convolutional Network for Visual Relational Reasoning
In this paper, we propose the Broadcasting Convolutional Network (BCN) that
extracts key object features from the global field of an entire input image and
recognizes their relationship with local features. BCN is a simple network
module that collects effective spatial features, embeds location information
and broadcasts them to the entire feature maps. We further introduce the
Multi-Relational Network (multiRN) that improves the existing Relation Network
(RN) by utilizing the BCN module. In pixel-based relation reasoning problems,
with the help of BCN, multiRN extends the concept of `pairwise relations' in
conventional RNs to `multiwise relations' by relating each object with multiple
objects at once. This yields in O(n) complexity for n objects, which is a vast
computational gain from RNs that take O(n^2). Through experiments, multiRN has
achieved a state-of-the-art performance on CLEVR dataset, which proves the
usability of BCN on relation reasoning problems.Comment: Accepted paper at ECCV 2018. 24 page
Ratchet-like dynamics of fluxons in annular Josephson junctions driven by bi-harmonic microwave fields
Experimental observation of the unidirectional motion of a topological
soliton driven by a bi-harmonic ac force of zero mean is reported. The
observation is made by measuring the current-voltage characteristics for a
fluxon trapped in an annular Josephson junction that was placed into a
microwave field. The measured dependence of the fluxon mean velocity (rectified
voltage) at zero dc bias versus the phase shift between the first and second
harmonic of the driving force is in qualitative agreement with theoretical
expectations.Comment: 6 figure
Impact of mobility on the IoT MAC infrastructure: IEEE 802.15.4e TSCH and LLDN platform
Realizing the target of high reliability and availability is a crucial concept in the IoT context. Different types of IoT applications introduce several requirements and obstacles. One of the important aspects degrading network performance is the node mobility inside the network. Without a solid and adaptive mechanism, node mobility can disrupt the network performance due to dissociations from the network. Hence, reliable techniques must be incorporated to tackle the overhead of node movement. In this paper, the overhead of mobility on both IEEE 802.15.4e timeslotted channel hopping (TSCH) and low latency deterministic (LLDN) modes is investigated. These two modes can be considered as the MAC layer of the IoT paradigm because of their importance and resilience to different network obstacles. In addition, the set of metrics and limitations that influence the network survivability will be identified to ensure efficient mobile node handling process. Both TSCH and LLDN have been implemented via the Contiki OS to determine their functionality. TSCH has been demonstrated to have better node connectivity due to the impact of frame collision in LLDN. In addition, by neglecting the overhead of collision, the LLDN has been shown to have better connectivity and low radio duty cycle (RDC)
Dynamic cluster head election protocol for mobile wireless sensor networks
A dynamic cluster head election protocol (DCHEP) is proposed in this work to improve network availability and energy efficiency for mobile wireless sensor networks (WSNs) under the beacon-enabled IEEE 802.15.4 standard. The proposed protocol (DCHEP) is developed and simulated using CASTALIA/OMNET++ with a realistic radio model and node behaviour. DCHEP improves the network availability and lifetime and maintains clusters hierarchy in a proactive manner even in a mobile WSN where all the nodes including cluster heads (CHs) are mobile, this is done by dynamically switching CHs allowing nodes to act as multiple backup cluster heads (BCHs) with different priorities based on their residual energy and connectivity to other clusters. DCHEP is a flexible and scalable solution targeted for dense WSNs with random mobility. The proposed protocol achieves an average of 33% and 26% improvement to the availability and energy efficiency respectively compared with the original standard
Mesh-under cluster-based routing protocol for IEEE 802.15.4 sensornetwork
The radio duty cycle (RDC) of wireless sensor nodes can be considered as a crucial factor that determines the wireless sensor network (WSN) lifetime and its service availability. Clustering would be a preferable solution to minimize node radio duty cycle by electing multiple cluster heads (CHs) around the network to schedule node transmissions and collect readings. This paper presents a mesh-under cluster-based routing (MUCBR) protocol that will divide the sensor network into multiple clusters and perform the routing function within the IEEE 802.15.4 platform. MUCBR is implemented via the Contiki operating system (OS). It reschedules the structure of the 802.15.4 standard in order to reduce the RDC of the sensor nodes and minimize the number of collisions. The election of the CHs is density-aware and determined by the routing direction inside the network which in turn reduces the number of hops and minimizes the number of collisions caused by the existence of multiple CHs in a single area. The proposed MUCBR manages to achieve a RDC of 0.08% for non-CH nodes and 1.3% for CH nodes while reducing the impact of collision by 40% as compared to the 802.15.4 standard
- …