Optimal Rapid Restart of Heuristic Methods of NP Hard Problems

Many heuristic search methods exhibit a remarkable variability in the time required to solve some particular problem instances. Their cost distributions are often heavy-tailed. It has been demonstrated that, in most cases, rapid restart (RR) method can prominently suppress the heavy-tailed nature of the instances and improve computation efficiency. However, it is usually time-consuming to check whether an algorithm on a specific instance is heavy-tailed or not. Moreover, if the heavy-tailed distribution is confirmed and the RR method is relevant, an optimal RR threshold should be chosen to facilitate the RR mechanism. In this paper, an approximate approach is proposed to quickly check whether an algorithm on a specific instance is heavy-tailed or not. The method is realized by means of calculating the maximal Lyapunov exponent of its generic running trace. Then a statistical formula to estimate the optimal RR threshold is educed. The method is based on common nonparametric estimation, e.g., Kernel estimation. Two heuristic methods are selected to verify our method. The experimental results are consistent with the theoretical consideration perfectly.

Concrete Physics Method for Solving NP hard Problem

With a NP hard problem given, we may find a equivalent physical world. The rule of the changing of the physical states is simply the algorithm for solving the original NP hard problem .It is the most natural algorithm for solving NP hard problems. In this paper we deal with a famous example , the well known NP hard problem——Circles Packing. It shows that our algorithm is dramatically very efficient. We are inspired that, the concrete physics algorithm will always be very efficient for NP hard problem.

The Alleged Hard Problem： A Pseudo Problem

One of the most intriguing problems of philosophy is the question whether the human mind and human consciousness can be completely reduced to matter, namely to the brain. A special problem in this context is what has been called the ＂hard problem.＂ The hard problem denies that it is possible to reduce phenomenal experiences to brain states. The hard problem claims that it is impossible for materialists to explain what it is like to feel something. Here, we will prove that the hard problem is a pseudo problem that is based on errors in logic and language. One of the key arguments for the hard problem, the conceivability of zombies, is logically wrong within naturalism, which most philosophers acknowledge. Nevertheless, generally all questions of the type ＂What is it like to feel something？＂ are either trivial or linguistically impermissible. The core of the ＂hard problem＂ is the mix-up between non-reducibility and non-describability.

The Hard Problem of Consciousness from a Bio-Psychological Perspective

Chalmers introduced the hard problem of consciousness as a profound gap between experience and physical concepts. Philosophical theories were based on different interpretations concerning the qualia/concept gap, such as interactive dualism （Descartes）, as well as mono aspect or dual aspect monism. From a bio-psychological perspective, the gap can be explained by the different activity of two mental functions realizing a mental representation of extra-mental reality. The function of elementary sensation requires active sense organs, which create an uninterrupted physical chain from extra-mental reality to the brain and reflect the present. The function of categorizing reflection no longer needs sense organs, so that the physical chain to extra-mental reality is interrupted and now reflects the past. Whereas elementary sensation is an open system, categorizing reflection remains a closed system, separated from extra-mental reality. This creates the potentiality/reality gap, since prediction from the closed to the open system remains always uncertain. Elementary sensation is associated to specific qualia for each sense organ. Chalmers also attributed qualia to thoughts, with more neutral thought qualia. Thus at the qualia level, there is also an important gap, but now between specific sense qualia and neutral thought qualia. Since all physical concepts are simultaneously linked to neutral thought qualia, the hard problem might be explained by a qualia/qualia gap instead of a qualia/concept gap. The mental function of categorizing reflection induces the change from sense qualia to thought qualia by a categorization process. The specific sense qualia mosaic of an apple is reduced to physical concepts with neutral qualia by progressive categorization first to fruit, then to food, to chemicals and finally to calories. This might explain the gap felt in the hard problem, since specific sense qualia are completely different from neutral thought qualia, so that the hard problem could already be encountered at the qualia level. Since the gap of the hard problem is due to the interaction of different mental functions, it is compatible with a philosophical monism.

Sea Turtle Foraging Optimization-Based Controller Placement with Blockchain-Assisted Intrusion Detection in Software-Defined Networks

Software-defined networking(SDN)algorithms are gaining increas-ing interest and are making networks flexible and agile.The basic idea of SDN is to move the control planes to more than one server’s named controllers and limit the data planes to numerous sending network components,enabling flexible and dynamic network management.A distinctive characteristic of SDN is that it can logically centralize the control plane by utilizing many physical controllers.The deployment of the controller—that is,the controller placement problem(CPP)—becomes a vital model challenge.Through the advancements of blockchain technology,data integrity between nodes can be enhanced with no requirement for a trusted third party.Using the lat-est developments in blockchain technology,this article designs a novel sea turtle foraging optimization algorithm for the controller placement problem(STFOA-CPP)with blockchain-based intrusion detection in an SDN environ-ment.The major intention of the STFOA-CPP technique is the maximization of lifetime,network connectivity,and load balancing with the minimization of latency.In addition,the STFOA-CPP technique is based on the sea turtles’food-searching characteristics of tracking the odour path of dimethyl sulphide(DMS)released from food sources.Moreover,the presented STFOA-CPP technique can adapt with the controller’s count mandated and the shift to controller mapping to variable network traffic.Finally,the blockchain can inspect the data integrity,determine significantly malicious input,and improve the robust nature of developing a trust relationship between sev-eral nodes in the SDN.To demonstrate the improved performance of the STFOA-CPP algorithm,a wide-ranging experimental analysis was carried out.The extensive comparison study highlighted the improved outcomes of the STFOA-CPP technique over other recent approaches.

Quantum Theory of Consciousness

Both consciousness and quantum phenomenon are subjective and indeterministic. In this paper, we propose consciousness is a quantum phenomenon. A quantum theory of consciousness (QTOC) is presented based on a new interpretation of quantum physics. We show that this QTOC can address the mind and body problem, the hard problem of consciousness. It also provides a physics foundation and mathematical formulation to study consciousness and neural network. We demonstrate how to apply it to develop and extend various models of consciousness. We show the predictions from this theory about the existence of a universal quantum vibrational field and the large-scale, nearly instantaneous synchrony of brainwaves among different parts of brain, body, people, and objects. The correlation between Schumann Resonances and some brainwaves is explained. Recent progress in quantum information theory, especially regarding quantum entanglement and quantum error correction code, is applied to study memory and shed new light in neuroscience.

Hybridizing grey wolf optimization with differential evolution for global optimization and test scheduling for 3D stacked SoC

A new meta-heuristic method is proposed to enhance current meta-heuristic methods for global optimization and test scheduling for three-dimensional （3D） stacked system-on-chip （SoC） by hybridizing grey wolf optimization with differential evo- lution （HGWO）. Because basic grey wolf optimization （GWO） is easy to fall into stagnation when it carries out the operation of at- tacking prey, and differential evolution （DE） is integrated into GWO to update the previous best position of grey wolf Alpha, Beta and Delta, in order to force GWO to jump out of the stagnation with DE＇s strong searching ability. The proposed algorithm can accele- rate the convergence speed of GWO and improve its performance. Twenty-three well-known benchmark functions and an NP hard problem of test scheduling for 3D SoC are employed to verify the performance of the proposed algorithm. Experimental results show the superior performance of the proposed algorithm for exploiting the optimum and it has advantages in terms of exploration.

A Conceptual Framework for Consciousness Based on a Deep Understanding of Matter

One of the main challenges in consciousness research is widely known as the hard problem of consciousness. In order to tackle this problem, I utilize an approach from theoretical physics, called stochastic electrodynamics （SED） which goes one step beyond quantum theory and sheds new light on the reality behind matter. According to this approach, matter is a resonant oscillator that is orchestrated by an all-pervasive stochastic radiation field, called zero-point field （ZPF）. The properties of matter are not intrinsic but acquired by dynamic interaction with the ZPF, which in turn picks up information about the material system as soon as an ordered state, i.e., a stable attractor, is reached. I point out that these principles apply also to macroscopic biological systems. From this perspective, long-range correlations in the brain, such as neural gamma synchrony, can be interpreted in terms of order phenomena induced and stabilized by the ZPF, suggesting that every attractor in the brain goes along with an information state in the ZPF. In order to build the bridge to consciousness, I employ additional input from Eastern philosophy. From a comparison between SED and Eastern philosophy I draw the conclusion that the ZPF is an appropriate candidate for the substrate of consciousness, implying that information states in the ZPF are associated with conscious states. On this basis I develop a conceptual framework for consciousness that is fully consistent with physics, neurophysiology, and Eastern philosophy. I argue that this conceptual framework has many interesting features and opens a door to a theory of consciousness. Particularly, it solves the problem of how matter and consciousness communicate in a causally closed functional chain, it gives a physical grounding to existing approaches regarding the connection between consciousness and information, and it gives clear direction to future models and experiments.

Key Exchange Protocol Based on Tensor Decomposition Problem

The hardness of tensor decomposition problem has many achievements, but limited applications in cryptography, and the tensor decomposition problem has been considered to have the potential to resist quantum computing. In this paper, we firstly proposed a new variant of tensor decomposition problem, then two one-way functions are proposed based on the hard problem. Secondly we propose a key exchange protocol based on the one-way functions, then the security analysis, efficiency, recommended parameters and etc. are also given. The analyses show that our scheme has the following characteristics: easy to implement in software and hardware, security can be reduced to hard problems, and it has the potential to resist quantum computing.Besides the new key exchange can be as an alternative comparing with other classical key protocols.

Intelligent Deer Hunting Optimization Based Grid Scheduling Scheme

The grid environment is a dynamic,heterogeneous,and changeable computing system that distributes various services amongst different clients.To attain the benefits of collaborative resource sharing in Grid computing,a novel and proficient grid resource management system(RMS)is essential.Therefore,detection of an appropriate resource for the presented task is a difficult task.Several scientists have presented algorithms for mapping tasks to the resource.Few of them focus on fault tolerance,user fulfillment,and load balancing.With this motivation,this study designs an intelligent grid scheduling scheme using deer hunting optimization algorithm(DHOA),called IGSS-DHOA which schedules in such a way that the makespan gets minimized in the grid platform.The IGSS-DHOA technique is mainly based on the hunting nature of humans toward deer.It also derives an objective function with candidate solution(schedule)as input and the outcome is the makespan value denoting the quality of the candidate solution.The simulation results highlighted the supremacy of the IGSS-DHOA technique over the recent state of art techniques with the minimal average processing cost of 31717.9.

From Chaos to Qualia： An Analysis of Phenomenal Character in Light of Process Philosophy and Self-Organizing Systems

The author will propose that qualia--typically understood as the purely subjective and phenomenal elements of experience--are not specifically brain processes, but are instead best thought of as world processes that can be characterized as distributed self-organizing networks of Whiteheadian actual entities. If this is correct, then we need not wrestle with the materialist＇s ＂hard problem＂ of explaining how consciousness can arise from the purely objective particles and forces of fundamental ptiysics, but we will need to explain in what sense microparticles and other physical objects are experiential and objectively real without embracing panpsychism. Since Whiteheadian actual entities have intrinsic natures grounding the subjective and phenomenal aspects of experience, and extrinsic relations grounding objective physical properties, we find that qualia, understood in light of Whiteheadian actual entities, can provide the metaphysical foundations for both the subjective and objective aspects of the world.

Disastrous Rains Downpours and flooding cause more problems for the area hie hard by last year’s earthquake

At least six people were killed on July 25 when a rockslide smashed into a bridge in Wenchuan County,ithe epicenter of last

Theories on Solving the Travelling Salesman Problem Based on Artificial Neural Network and Their Applications

NP hard problems have appeared in many areas. In this article, it is discussed how to solve this kind of problems using artificial neural network— Hopfield/Tank model, especially the Travelling Salesman Problem (TSP). At first, a stability analysis shows the conditions of the model to converge to the vertices of the hypercube and its relation with the parameters. And then, a HT model for solving TSP is formulated. Some theorems are given to analyze the influence of parameter D on the three subspaces of the connection matrix in which D is set to zero. Based on these analyses, a dynamic analysis of the model is given and a set of parameters′ rules are established. It is indicated that, if the parameters are selected according to these rules, the final solutions are optimal or near optimal. However, the initial noise would have some influences on the final solutions. According to these theories, a 'damping' optimal method is proposed which can not only guarantee the final solutions are high quality, but also weaken the influence of the initial noise. On the other hand, many kinds of modified HT models are summarized and a more simple and effective model is given. Compared with some traditional and modern methods for solving TSP, the performance of our method is very good. Linking with the practice, some applications are exploited. Our method has also been used for programming the posts route of some city in China. Finally, a theoretical analysis is given for com munication network routing problem using HT model. Liu Rong Born in October 1966. He received the Engineering Ph.D in Beijing University Posts and Telecommunications in April 1994.

Philosophy and Science Dialogue： Consciousness

This is a dialogue between scientific explanation of consciousness. a philosopher and a scientist about the What is consciousness？ Does it admit of scientific explanation？ If so, what must a scientific theory of consciousness be like in order to provide us with a satisfying explanation of its explanandum？ And what types of entities might such a theory acknowledge as being conscious？ Philosopher Owen Flanagan and scientist Giulio Tononi weigh in on these issues during an exchange about the nature and scientific explanation of consciousness.

Two-stage controlled islanding strategy based on Stoer-Wagner and improved Dinic algorithms

The controlled islanding for the power system is an effective method to deal with the emergent situations caused by large disturbances. The size of the solution space would increase exponentially as the scale of the power grid increases. The goal of our controlled islanding strategy is to divide the system into several islands quickly. Meanwhile, the generator coherency and the power-flow disruption have to be taken into consideration carefully. This paper proposed a two-stage fast islanding strategy for large power networks, which is on the basis of large power grid graph theories. In the first stage, the Stoer-Wagner algorithm is employed to obtain the grouping cluster of coherent generators in the dynamic undirected liaison graph. In the second stage, the improved Dinic max-flow method is proposed to search the optimal splitting boundary so as to acquire the minimum power flow impact. Our two-stage islanding strategy does not need to reduce the whole power network. Simulations on IEEE 118-bus and162-bus power systems showed that the proposed strategy can acquire high quality solutions effectively and efficiently.