hard problem
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2021 ◽  
Vol 2 ◽  
Author(s):  
Michael Pauen

One of the reasons why the Neural Correlates of Consciousness Program could appear attractive in the 1990s was that it seemed to disentangle theoretical and empirical problems. Theoretical disagreements could thus be sidestepped in order to focus on empirical research regarding the neural substrate of consciousness. One of the further consequences of this dissociation of empirical and theoretical questions was that fundamental questions regarding the Mind Body Problem or the “Hard Problem of Consciousness” could remain unresolved even if the search for the neural correlates had been successful.Drawing on historical examples, a widely held consensus in the philosophy of science, and actual NCC research we argue that there is no such independence. Moreover, as the dependence between the theoretical and the empirical level is mutual, empirical progress will go hand in hand with theoretical development. Thus, contrary to what the original NCC program suggested, we conclude that NCC research may significantly take advantage from and contribute to theoretical progress in our explanation and understanding of consciousness. Eventually, this might even contribute to a solution of the Hard Problem of Consciousness.


2021 ◽  
Vol 118 (52) ◽  
pp. e2107019118
Author(s):  
Chen Yu ◽  
Yayun Zhang ◽  
Lauren K. Slone ◽  
Linda B. Smith

The learning of first object names is deemed a hard problem due to the uncertainty inherent in mapping a heard name to the intended referent in a cluttered and variable world. However, human infants readily solve this problem. Despite considerable theoretical discussion, relatively little is known about the uncertainty infants face in the real world. We used head-mounted eye tracking during parent–infant toy play and quantified the uncertainty by measuring the distribution of infant attention to the potential referents when a parent named both familiar and unfamiliar toy objects. The results show that infant gaze upon hearing an object name is often directed to a single referent which is equally likely to be a wrong competitor or the intended target. This bimodal gaze distribution clarifies and redefines the uncertainty problem and constrains possible solutions.


2021 ◽  
Vol 11 (6) ◽  
pp. 7944-7949
Author(s):  
A. Darem

Phishing attacks are increasingly exploited by cybercriminals, they become more sophisticated and evade detection even by advanced technical countermeasures. With cybercriminals resorting to more sophisticated phishing techniques, strategies, and different channels such as social networks, phishing is becoming a hard problem to solve. Therefore, the main objective for any anti-phishing solution is to minimize phishing success and its consequences through complementary means to advanced technical countermeasures. Specifically, phishing threats cannot be controlled by technical controls alone, thus it is imperative to complement cybersecurity programs with cybersecurity awareness programs to successfully fight against phishing attacks. This paper provides a review of the delivery methods of cybersecurity training programs used to enhance personnel security awareness and behavior in terms of phishing threats. Although there are a wide variety of educational intervention methods against phishing, the differences between the cybersecurity awareness delivery methods are not always clear. To this end, we present a review of the most common methods of workforce cybersecurity training methods in order for them to be able to protect themselves from phishing threats.


2021 ◽  
Author(s):  
Simon Hengeveld ◽  
Nara Rubiano da Silva ◽  
Douglas S. Gonçalves ◽  
Paulo Henrique Souto Ribeiro ◽  
Antonio Mucherino

Abstract We present the architecture of a new optical processor specialized in matrix-by-vector multiplication via the manipulation of the light wavefront. This processor can reach up to 1.2 Giga MAC (multiply-accumulate) operations per second using commercially available devices. Moreover, this architecture is compatible with hardware upgrade with potential to achieve processing speed above Tera MAC per second. We initially present the optical processor, and then discuss the use of such a processor for tackling a special class of the one-dimensional Distance Geometry Problem (DGP), which is a well-known NP-hard problem.


2021 ◽  
Vol 9 ◽  
Author(s):  
Siddharth Jain

The traveling salesman problem is a well-known NP-hard problem in combinatorial optimization. This paper shows how to solve it on an Ising Hamiltonian based quantum annealer by casting it as a quadratic unconstrained binary optimization (QUBO) problem. Results of practical experiments are also presented using D-Wave’s 5,000 qubit Advantage 1.1 quantum annealer and the performance is compared to a classical solver. It is found the quantum annealer can only handle a problem size of 8 or less nodes and its performance is subpar compared to the classical solver both in terms of time and accuracy.


Author(s):  
Xinyun Wu ◽  
Zhipeng Lü ◽  
Fred Glover

The minimum connected dominating set (MCDS) problem consists of selecting a minimum set of vertices from an undirected graph, such that each vertex not in this set is adjacent to at least one of the vertices in it, and the subgraph induced by this vertex set is connected. This paper presents a fast vertex weighting (FVW) algorithm for solving the MCDS problem, which integrates several distinguishing features, such as a vertex weighting-based local search with tabu and perturbation strategies to help the search to jump out of the local optima, as well as a search space reduction strategy to improve the search efficiency. Computational experiments on four sets of 112 commonly used public benchmark instances, as well as 15 newly introduced sparse instances, show that FVW is highly competitive compared with the state-of-the-art algorithms in the literature despite its simplicity. FVW improves the previous best-known results for 20 large public benchmark instances while matching the best-known results for all but 2 of the remaining ones. Several ingredients of FVW are investigated to demonstrate the importance of the proposed ideas and techniques. Summary of Contribution: As a challenging classical NP-hard problem, the minimum connected dominating set (MCDS) problem has been studied for decades in the areas of both operations research and computer science, although there does not exist an exact polynomial algorithm for solving it. Thus, the new breakthrough on this classical NP-hard problem in terms of the computational results on classical benchmark instances is significant. This paper presents a new fast vertex weighting local search for solving the MCDS problem. Computational experiments on four sets of 112 commonly used public benchmark instances show that fast vertex weighting (FVW) is able to improve the previous best-known results for 20 large instances while matching the best-known results for all but 2 of the remaining instances. Several ingredients of FVW are also investigated to demonstrate the importance of the proposed ideas and techniques.


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