Towards ANN-Based Scalable Hashing Algorithm For Secure Task Processing In Computational Clouds

2019 ◽  
Author(s):  
Jacek Tchorzewski ◽  
Agnieszka Jakobik ◽  
Daniel Grzonka
Keyword(s):  
Task Processing ◽  
Hashing Algorithm

Speeded Paper-Pencil Sustained Attention and Mental Speed Tests

2008 ◽  
Vol 29 (4) ◽  
pp. 205-216 ◽  
Author(s):  
Stefan Krumm ◽  
Lothar Schmidt-Atzert ◽  
Kurt Michalczyk ◽  
Vanessa Danthiir
Keyword(s):  
Sustained Attention ◽  
Time Pressure ◽  
Factor Model ◽  
Higher Order ◽  
Future Research ◽  
Perceptual Speed ◽  
Speed Factor ◽  
Close Relationship ◽  
Task Processing ◽  
Order Factor

Mental speed (MS) and sustained attention (SA) are theoretically distinct constructs. However, tests of MS are very similar to SA tests that use time pressure as an impeding condition. The performance in such tasks largely relies on the participants’ speed of task processing (i.e., how quickly and correctly one can perform the simple cognitive tasks). The present study examined whether SA and MS are empirically the same or different constructs. To this end, 24 paper-pencil and computerized tests were administered to 199 students. SA turned out to be highly related to MS task classes: substitution and perceptual speed. Furthermore, SA showed a very close relationship with the paper-pencil MS factor. The correlation between SA and computerized speed was considerably lower but still high. In a higher-order general speed factor model, SA had the highest loading on the higher-order factor; the higher-order factor explained 88% of SA variance. It is argued that SA (as operationalized with tests using time pressure as an impeding condition) and MS cannot be differentiated, at the level of broad constructs. Implications for neuropsychological assessment and future research are discussed.

When does explicit expectancy affect task processing?

2009 ◽  
Author(s):  
Peter A. Frensch ◽  
Sabine Schwager ◽  
Robert Gaschler ◽  
Dennis Runger
Keyword(s):  
Task Processing

scholarly journals Evaluation of Static Mapping for Dynamic Space-Shared Multi-task Processing on FPGAs

2021 ◽  
Author(s):  
Umar Ibrahim Minhas ◽  
Roger Woods ◽  
Georgios Karakonstantis
Keyword(s):  
High Performance ◽  
Design Space Exploration ◽  
Design Space ◽  
System Throughput ◽  
Design Parameters ◽  
Temporal Constraints ◽  
Shared Resources ◽  
Task Processing ◽  
High Level ◽  
Performance Computing

AbstractWhilst FPGAs have been used in cloud ecosystems, it is still extremely challenging to achieve high compute density when mapping heterogeneous multi-tasks on shared resources at runtime. This work addresses this by treating the FPGA resource as a service and employing multi-task processing at the high level, design space exploration and static off-line partitioning in order to allow more efficient mapping of heterogeneous tasks onto the FPGA. In addition, a new, comprehensive runtime functional simulator is used to evaluate the effect of various spatial and temporal constraints on both the existing and new approaches when varying system design parameters. A comprehensive suite of real high performance computing tasks was implemented on a Nallatech 385 FPGA card and show that our approach can provide on average 2.9 × and 2.3 × higher system throughput for compute and mixed intensity tasks, while 0.2 × lower for memory intensive tasks due to external memory access latency and bandwidth limitations. The work has been extended by introducing a novel scheduling scheme to enhance temporal utilization of resources when using the proposed approach. Additional results for large queues of mixed intensity tasks (compute and memory) show that the proposed partitioning and scheduling approach can provide higher than 3 × system speedup over previous schemes.

Learning of across- and within-task contingencies modulates partial-repetition costs in dual-tasking

2021 ◽  
Author(s):  
Lasse Pelzer ◽  
Christoph Naefgen ◽  
Robert Gaschler ◽  
Hilde Haider
Keyword(s):  
Dual Task ◽  
Discrimination Task ◽  
Experimental Approach ◽  
Feature Binding ◽  
Dual Tasking ◽  
Single Task ◽  
Task Set ◽  
Task Processing ◽  
Tone Discrimination ◽  
Task Sets

AbstractDual-task costs might result from confusions on the task-set level as both tasks are not represented as distinct task-sets, but rather being integrated into a single task-set. This suggests that events in the two tasks are stored and retrieved together as an integrated memory episode. In a series of three experiments, we tested for such integrated task processing and whether it can be modulated by regularities between the stimuli of the two tasks (across-task contingencies) or by sequential regularities within one of the tasks (within-task contingencies). Building on the experimental approach of feature binding in action control, we tested whether the participants in a dual-tasking experiment will show partial-repetition costs: they should be slower when only the stimulus in one of the two tasks is repeated from Trial n − 1 to Trial n than when the stimuli in both tasks repeat. In all three experiments, the participants processed a visual-manual and an auditory-vocal tone-discrimination task which were always presented concurrently. In Experiment 1, we show that retrieval of Trial n − 1 episodes is stable across practice if the stimulus material is drawn randomly. Across-task contingencies (Experiment 2) and sequential regularities within a task (Experiment 3) can compete with n − 1-based retrieval leading to a reduction of partial-repetition costs with practice. Overall the results suggest that participants do not separate the processing of the two tasks, yet, within-task contingencies might reduce integrated task processing.

scholarly journals A Study on the Optimization of Blockchain Hashing Algorithm Based on PRCA

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Jinhua Fu ◽  
Sihai Qiao ◽  
Yongzhong Huang ◽  
Xueming Si ◽  
Bin Li ◽  
...  
Keyword(s):  
Supply Chain ◽  
Internet Of Things ◽  
Data Transmission ◽  
Reconfigurable Computing ◽  
Hash Function ◽  
Network Data ◽  
Supply Chain Finance ◽  
Hash Algorithm ◽  
Hashing Function ◽  
Hashing Algorithm

Blockchain is widely used in encrypted currency, Internet of Things (IoT), supply chain finance, data sharing, and other fields. However, there are security problems in blockchains to varying degrees. As an important component of blockchain, hash function has relatively low computational efficiency. Therefore, this paper proposes a new scheme to optimize the blockchain hashing algorithm based on PRCA (Proactive Reconfigurable Computing Architecture). In order to improve the calculation performance of hashing function, the paper realizes the pipeline hashing algorithm and optimizes the efficiency of communication facilities and network data transmission by combining blockchains with mimic computers. Meanwhile, to ensure the security of data information, this paper chooses lightweight hashing algorithm to do multiple hashing and transforms the hash algorithm structure as well. The experimental results show that the scheme given in the paper not only improves the security of blockchains but also improves the efficiency of data processing.

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