12,901 research outputs found
Note: Tormenta: An open source Python-powered control software for camera based optical microscopy
Until recently, PC control and synchronization of scientific instruments was only possible through closed-source expensive frameworks like National Instruments' LabVIEW. Nowadays, efficient cost-free alternatives are available in the context of a continuously growing community of open-source software developers. Here, we report on Tormenta, a modular open-source software for the control of camera-based optical microscopes. Tormenta is built on Python, works on multiple operating systems, and includes some key features for fluorescence nanoscopy based on single molecule localization.Fil: Barabas, Federico MartĂn. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias ; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de FĂsica; ArgentinaFil: Masullo, Luciano AndrĂ©s. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias ; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de FĂsica; ArgentinaFil: Stefani, Fernando Daniel. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Parque Centenario. Centro de Investigaciones en Bionanociencias ; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de FĂsica; Argentin
Flooding attacks to internet threat monitors (ITM): Modeling and counter measures using botnet and honeypots
The Internet Threat Monitoring (ITM),is a globally scoped Internet monitoring
system whose goal is to measure, detect, characterize, and track threats such
as distribute denial of service(DDoS) attacks and worms. To block the
monitoring system in the internet the attackers are targeted the ITM system. In
this paper we address flooding attack against ITM system in which the attacker
attempt to exhaust the network and ITM's resources, such as network bandwidth,
computing power, or operating system data structures by sending the malicious
traffic. We propose an information-theoretic frame work that models the
flooding attacks using Botnet on ITM. Based on this model we generalize the
flooding attacks and propose an effective attack detection using Honeypots
Impact of use of optical surface imaging on initial patient setup for stereotactic body radiotherapy treatments
Purpose
To evaluate the effectiveness of surface image guidance (SG) for preâimaging setup of stereotactic body radiotherapy (SBRT) patients, and to investigate the impact of SG reference surface selection on this process.
Methods and materials
284 SBRT fractions (SGâSBRT = 113, nonâSGâSBRT = 171) were retrospectively evaluated. Differences between initial (preâimaging) and treatment couch positions were extracted from the recordâandâverify system and compared for the two groups. Rotational setup discrepancies were also computed. The utility of orthogonal kVs in reducing CBCT shifts in the SGâSBRT/nonâSGâSBRT groups was also calculated. Additionally, the number of CBCTs acquired for setup was recorded and the average for each cohort was compared. These data served to evaluate the effectiveness of surface imaging in preâimaging patient positioning and its potential impact on the necessity of including orthogonal kVs for setup. Since reference surface selection can affect SG setup, daily surface reproducibility was estimated by comparing cameraâacquired surface references (VRT surface) at each fraction to the external surface of the planning CT (DICOM surface) and to the VRT surface from the previous fraction.
Results
The reduction in all initialâtoâtreatment translation/rotation differences when using SGâSBRT was statistically significant (RankâSum test, α = 0.05). Orthogonal kV imaging kept CBCT shifts below reimaging thresholds in 19%/51% of fractions for SGâSBRT/nonâSGâSBRT cohorts. Differences in average number of CBCTs acquired were not statistically significant. The reference surface study found no statistically significant differences between the use of DICOM or VRT surfaces.
Conclusions
SGâSBRT improved preâimaging treatment setup compared to inâroom laser localization alone. It decreased the necessity of orthogonal kV imaging prior to CBCT but did not affect the average number of CBCTs acquired for setup. The selection of reference surface did not have a significant impact on initial patient positioning
Vector processing-aware advanced clock-gating techniques for low-power fused multiply-add
The need for power efficiency is driving a rethink of design decisions in processor architectures. While vector processors succeeded in the high-performance market in the past, they need a retailoring for the mobile market that they are entering now. Floating-point (FP) fused multiply-add (FMA), being a functional unit with high power consumption, deserves special attention. Although clock gating is a well-known method to reduce switching power in synchronous designs, there are unexplored opportunities for its application to vector processors, especially when considering active operating mode. In this research, we comprehensively identify, propose, and evaluate the most suitable clock-gating techniques for vector FMA units (VFUs). These techniques ensure power savings without jeopardizing the timing. We evaluate the proposed techniques using both synthetic and âreal-worldâ application-based benchmarking. Using vector masking and vector multilane-aware clock gating, we report power reductions of up to 52%, assuming active VFU operating at the peak performance. Among other findings, we observe that vector instruction-based clock-gating techniques achieve power savings for all vector FP instructions. Finally, when evaluating all techniques together, using âreal-worldâ benchmarking, the power reductions are up to 80%. Additionally, in accordance with processor design trends, we perform this research in a fully parameterizable and automated fashion.The research leading to these results has received funding from the RoMoL ERC Advanced Grant GA 321253 and is supported in part by the European Union (FEDER funds) under contract TTIN2015-65316-P.
The work of I. Ratkovic was supported by a FPU research grant from the Spanish MECD.Peer ReviewedPostprint (author's final draft
Incremental Consistency Guarantees for Replicated Objects
Programming with replicated objects is difficult. Developers must face the
fundamental trade-off between consistency and performance head on, while
struggling with the complexity of distributed storage stacks. We introduce
Correctables, a novel abstraction that hides most of this complexity, allowing
developers to focus on the task of balancing consistency and performance. To
aid developers with this task, Correctables provide incremental consistency
guarantees, which capture successive refinements on the result of an ongoing
operation on a replicated object. In short, applications receive both a
preliminary---fast, possibly inconsistent---result, as well as a
final---consistent---result that arrives later.
We show how to leverage incremental consistency guarantees by speculating on
preliminary values, trading throughput and bandwidth for improved latency. We
experiment with two popular storage systems (Cassandra and ZooKeeper) and three
applications: a Twissandra-based microblogging service, an ad serving system,
and a ticket selling system. Our evaluation on the Amazon EC2 platform with
YCSB workloads A, B, and C shows that we can reduce the latency of strongly
consistent operations by up to 40% (from 100ms to 60ms) at little cost (10%
bandwidth increase, 6% throughput drop) in the ad system. Even if the
preliminary result is frequently inconsistent (25% of accesses), incremental
consistency incurs a bandwidth overhead of only 27%.Comment: 16 total pages, 12 figures. OSDI'16 (to appear
A stateless opportunistic routing protocol for underwater sensor networks
Routing packets in Underwater Sensor Networks (UWSNs) face different challenges, the most notable of which is perhaps how to deal with void communication areas. While this issue is not addressed in some underwater routing protocols, there exist some partially state-full protocols which can guarantee the delivery of packets using excessive communication overhead. However, there is no fully stateless underwater routing protocol, to the best of our knowledge, which can detect and bypass trapped nodes. A trapped node is a node which only leads packets to arrive finally at a void node. In this paper, we propose a Stateless Opportunistic Routing Protocol (SORP), in which the void and trapped nodes are locally detected in the different area of network topology to be excluded during the routing phase using a passive participation approach. SORP also uses a novel scheme to employ an adaptive forwarding area which can be resized and replaced according to the local density and placement of the candidate forwarding nodes to enhance the energy efficiency and reliability. We also make a theoretical analysis on the routing performance in case of considering the shadow zone and variable propagation delays. The results of our extensive simulation study indicate that SORP outperforms other protocols regarding the routing performance metrics
Fooling Vision and Language Models Despite Localization and Attention Mechanism
Adversarial attacks are known to succeed on classifiers, but it has been an
open question whether more complex vision systems are vulnerable. In this
paper, we study adversarial examples for vision and language models, which
incorporate natural language understanding and complex structures such as
attention, localization, and modular architectures. In particular, we
investigate attacks on a dense captioning model and on two visual question
answering (VQA) models. Our evaluation shows that we can generate adversarial
examples with a high success rate (i.e., > 90%) for these models. Our work
sheds new light on understanding adversarial attacks on vision systems which
have a language component and shows that attention, bounding box localization,
and compositional internal structures are vulnerable to adversarial attacks.
These observations will inform future work towards building effective defenses.Comment: CVPR 201
A novel cooperative opportunistic routing scheme for underwater sensor networks
Increasing attention has recently been devoted to underwater sensor networks (UWSNs) because of their capabilities in the ocean monitoring and resource discovery. UWSNs are faced with different challenges, the most notable of which is perhaps how to efficiently deliver packets taking into account all of the constraints of the available acoustic communication channel. The opportunistic routing provides a reliable solution with the aid of intermediate nodesâ collaboration to relay a packet toward the destination. In this paper, we propose a new routing protocol, called opportunistic void avoidance routing (OVAR), to address the void problem and also the energy-reliability trade-off in the forwarding set selection. OVAR takes advantage of distributed beaconing, constructs the adjacency graph at each hop and selects a forwarding set that holds the best trade-off between reliability and energy efficiency. The unique features of OVAR in selecting the candidate nodes in the vicinity of each other leads to the resolution of the hidden node problem. OVAR is also able to select the forwarding set in any direction from the sender, which increases its flexibility to bypass any kind of void area with the minimum deviation from the optimal path. The results of our extensive simulation study show that OVAR outperforms other protocols in terms of the packet delivery ratio, energy consumption, end-to-end delay, hop count and traversed distance
Fooling Vision and Language Models Despite Localization and Attention Mechanism
Adversarial attacks are known to succeed on classifiers, but it has been an
open question whether more complex vision systems are vulnerable. In this
paper, we study adversarial examples for vision and language models, which
incorporate natural language understanding and complex structures such as
attention, localization, and modular architectures. In particular, we
investigate attacks on a dense captioning model and on two visual question
answering (VQA) models. Our evaluation shows that we can generate adversarial
examples with a high success rate (i.e., > 90%) for these models. Our work
sheds new light on understanding adversarial attacks on vision systems which
have a language component and shows that attention, bounding box localization,
and compositional internal structures are vulnerable to adversarial attacks.
These observations will inform future work towards building effective defenses.Comment: CVPR 201
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