Consciousness in the universe: A review of the ‘Orch OR’ theory

The nature of consciousness, the mechanism by which it occurs in the brain, and its ultimate place in the universe are unknown. We proposed in the mid 1990's that consciousness depends on biologically ‘orchestrated’ coherent quantum processes in collections of microtubules within brain neurons, that these quantum processes correlate with, and regulate, neuronal synaptic and membrane activity, and that the continuous Schrödinger evolution of each such process terminates in accordance with the specific Diósi–Penrose (DP) scheme of ‘objective reduction’ (‘OR’) of the quantum state. This orchestrated OR activity (‘Orch OR’) is taken to result in moments of conscious awareness and/or choice. The DP form of OR is related to the fundamentals of quantum mechanics and space–time geometry, so Orch OR suggests that there is a connection between the brain's biomolecular processes and the basic structure of the universe. Here we review Orch OR in light of criticisms and developments in quantum biology, neuroscience, physics and cosmology. We also introduce a novel suggestion of ‘beat frequencies’ of faster microtubule vibrations as a possible source of the observed electro-encephalographic (‘EEG’) correlates of consciousness. We conclude that consciousness plays an intrinsic role in the universe.     

A continuous distance model (CDM) for the single-file pedestrian movement considering step frequency and length

A good evacuation model should be good to predict actual macroscopic and microscopic characteristics of pedestrian movement. In order to explore pedestrian movement behavior, we conducted controlled experiments of the single-file pedestrian movement, extracted the motion data by using a mean-shift digital image processing algorithm and analyzed the movement characteristics of pedestrians. It is found that both the pedestrian step length and frequency decreases with the increasing global pedestrian density. Furthermore, there is linear relationship between the step frequency and the distance headway of a pedestrian. Based on the characteristics observed from our experiments, we built a continuous distance model (CDM) for the single-file pedestrian movement. Two new insights were taken into account in the movement algorithm. The first one is that, the continuous step length is adopted to avoid unreasonable results caused by the simplification of the step length in traditional discrete models. The second one is that the dependency between the transition probability and the distance headway is introduced for the reason that the transition probability is correlated with the actual step frequency. Simulation results indicated that there is a close agreement on the flow-density and velocity–density relations between the experiments and modeling. Moreover, it is found that the CDM model is capable of reproducing microscopic features for the scenario with high density.     

Time-dependent Benioff strain release diagrams

New time-dependent Benioff strain (TDBS) release diagrams were analyzed for acoustic emission during various loading tests and for electromagnetic (EM) radiation emanating during compression and, tension, which end in failure. TDBS diagrams are Benioff diagrams that are built consecutively, each time using a greater number of events (acoustic or EM emissions) using the last event as if it were associated with the ‘actual failure’. An examination of such TDBS diagrams shows that at a certain time point (this time point is denoted by the term ‘alarm’ time), a comparatively short interval prior to actual collapse, their decreasing part is broken by a positive ‘bulge’. This ‘bulge’ is quantified and an algorithm proposed for its assessment. Using the alarm time and other parameters of the failure process (fall, bulge size and escalation factors, bulge slope and slope fall time), a criterion for estimating the time of the actual collapse is developed and shown to agree well with laboratory experimental results.     

Constraints on Determinism: Bell Versus Conway–Kochen

Bell’s Theorem from Physics 36:1–28 (1964) and the (Strong) Free Will Theorem of Conway and Kochen from Notices AMS 56:226–232 (2009) both exclude deterministic hidden variable theories (or, in modern parlance, ‘ontological models’) that are compatible with some small fragment of quantum mechanics, admit ‘free’ settings of the archetypal Alice and Bob experiment, and satisfy a locality condition akin to parameter independence. We clarify the relationship between these theorems by giving reformulations of both that exactly pinpoint their resemblance and their differences. Our reformulation imposes determinism in what we see as the only consistent way, in which the ‘ontological state’ initially determines both the settings and the outcome of the experiment. The usual status of the settings as ‘free’ parameters is subsequently recovered from independence assumptions on the pertinent (random) variables. Our reformulation also clarifies the role of the settings in Bell’s later generalization of his theorem to stochastic hidden variable theories.     

基于OTSU分割和HOG特征的行人检测与跟踪方法

传统的HOG算法针对整幅图像进行行人特征提取,大量的非人窗口计算必然降低检测的准确率和效率。为此,提出一种基于OTSU分割和HOG特征的行人检测与跟踪方法。利用OTSU算法以最佳阈值分割图像,在分割区域的基础上进行Canny边缘检测,通过边缘的对称性计算确定行人候选区,继而采用经PCA方法降维后的HOG特征和隐马尔可夫模型对行人候选区进行检测验证。最后,以确定的行人区域为跟踪窗口,利用CamShift算法跟踪行人。多组实验结果证明,本文方法的行人检测效率和精度均有所提高,跟踪性能稳定、可靠。     

New scheme of anticipating synchronization for arbitrary anticipation time and its application to long-term prediction of chaotic states

How to predict the dynamics of nonlinear chaotic systems is still a challenging subject with important real-life applications. The present paper deals with this important yet difficult problem via a new scheme of anticipating synchronization. A global, robust, analytical and delay-independent sufficient condition is obtained to guarantee the existence of anticipating synchronization manifold theoretically in the framework of the Krasovskii-Lyapunov theory. Different from ＇traditional techniques （or regimes）＇ proposed in the previous literature, the present scheme guarantees that the receiver system can synchronize with the future state of a transmitter system for an arbitrarily long anticipation time, which allows one to predict the dynamics of chaotic transmitter at any point of time if necessary. Also it is simple to implement in practice. A classical chaotic system is employed to demonstrate the application of the proposed scheme to the long-term prediction of chaotic states.[第一段]     

Calibrating cellular automaton models for pedestrians walking through corners

Cellular Automata (CA) based pedestrian simulation models have gained remarkable popularity as they are simpler and easier to implement compared to other microscopic modeling approaches. However, incorporating traditional floor field representations in CA models to simulate pedestrian corner navigation behavior could result in unrealistic behaviors. Even though several previous studies have attempted to enhance CA models to realistically simulate pedestrian maneuvers around bends, such modifications have not been calibrated or validated against empirical data. In this study, two static floor field (SFF) representations, namely ‘discrete representation’ and ‘continuous representation’, are calibrated for CA-models to represent pedestrians' walking behavior around 90° bends. Trajectory data collected through a controlled experiment are used to calibrate these model representations. Calibration results indicate that although both floor field representations can represent pedestrians' corner navigation behavior, the ‘continuous’ representation fits the data better. Output of this study could be beneficial for enhancing the reliability of existing CA-based models by representing pedestrians' corner navigation behaviors more realistically.     

Multiscale top-hat selection transform based infrared and visual image fusion with emphasis on extracting regions of interest

To effectively combine regions of interest in original infrared and visual images, an adaptively weighted infrared and visual image fusion algorithm is developed based on the multiscale top-hat selection transform. First, the multiscale top-hat selection transform using multiscale structuring elements with increasing sizes is discussed. Second, the image regions of the original infrared and visual images at each scale are extracted by using the multiscale top-hat selection transform. Third, the final fusion regions are constructed from the extracted multiscale image regions. Finally, the final fusion regions are combined into a base image calculated from the original images to form the final fusion result. The combination of the final fusion regions uses the adaptive weight strategy, and the weights are adaptively obtained based on the importance of the extracted features. In the paper, we compare seven image fusion methods: wavelet pyramid algorithm (WP), shift invariant discrete wavelet transform algorithm (SIDWT), Laplacian pyramid algorithm (LP), morphological pyramid algorithm (MP), multiscale morphology based algorithm (MSM), center-surround top-hat transform based algorithm (CSTHT), and the proposed multiscale top-hat selection transform based algorithm. These seven methods are compared over five different publicly available image sets using three metrics of spatial frequency, mean gradient, and Q. The results show that the proposed algorithm is effective and may be useful for the applications related to the infrared and visual image fusion.     

Robust pedestrian detection in thermal infrared imagery using the wavelet transform

A novel and robust pedestrian detection method in thermal infrared images based on the double-density dual-tree complex wavelet transform (DD-DT CWT) and wavelet entropy is presented in this paper. The regions of interest (ROIs) are located first making use of high brightness property of the pedestrian pixels caused by the self-emission of the pedestrians related to the Planck’s law. The candidate ROIs are then decomposed by DD-DT CWT and the wavelet entropy features are extracted from the high frequency subbands. The true pedestrian regions are finally classified and recognized using the support vector machine (SVM) classifier. Comparisons between our approach and traditional approaches are presented and experimental results using several thermal infrared image databases show the proposed scheme to be very promising.     

Energy-efficient beamforming optimization for MISO communication based on reconfigurable intelligent surface

Reconfigurable intelligent surface (RIS), a planar metasurface consisting of a large number of low-cost reflecting elements, has received much attention due to its ability to improve both the spectrum and energy efficiency (EE) by reconfiguring the wireless propagation environment. In this paper, we propose a base station (BS) beamforming and RIS phase shift optimization technique that maximizes the EE of a RIS-aided multiple-input–single-output system. In particular, considering the system circuits’ energy consumption, an EE maximization problem is formulated by jointly optimizing the active beamforming at the BS and the passive beamforming at the RIS, under the constraints of each user’ rate requirement, the BS’s maximal transmit power budget and unit-modulus constraint of the RIS phase shifts. Due to the coupling of optimization variables, this problem is a complex non-convex optimization problem, and it is challenging to solve it directly. To overcome this obstacle, we divide the problem into active and passive beamforming optimization subproblems. For the first subproblem, the active beamforming is given by the maximum ratio transmission optimal strategy. For the second subproblem, the optimal phase shift matrix at the RIS is obtained by exploiting sine cosine algorithm (SCA). Moreover, for this case where each reflection element’s working state is controlled by a circuit switch, each reflection element’s switch value is optimized with the aid of particle swarm optimization algorithm. Finally, numerical results verify the effectiveness of our proposed algorithm compared to other algorithms.     

Quantum Image Location

Quantum image processing has been a hot topic as a consequence of the development of quantum computation. Many quantum image processing algorithms have been proposed, whose efficiency are theoretically higher than their corresponding classical algorithms. However, most of the quantum schemes do not consider the problem of measurement. If users want to get the results, they must measure the final state many times to get all the pixels’ values. Moreover, executing the algorithm one time, users can only measure the final state one time. In order to measure it many times, users must execute the algorithms many times. If the measurement process is taken into account, whether or not the algorithms are really efficient needs to be reconsidered. In this paper, we try to solve the problem of measurement and give a quantum image location algorithm. This scheme modifies the probability of pixels to make the target pixel to be measured with higher probability. Furthermore, it only has linear complexity.     

An optimization-based overtaking model for unidirectional pedestrian flow

We propose an optimization-based model for simulating the overtaking behaviour in the unidirectional pedestrian flow. A ‘visual area’ is introduced so that agents could receive the information regarding their surroundings and react by choosing one of three options: to move straight on, to dodge to the left, or to dodge to the right. And a side preference of each pedestrian for evading and overtaking is implemented based on traffic ‘social norms’. The model was validated by reproducing the experimentally obtained pedestrian flow patterns. The effects of the initial pedestrian formation on overtaking behaviour and the evacuation time have been analysed in different geometries. The results show that pedestrian flow patterns after overtaking are obviously influenced by both the initial positions and density of the slow pedestrians in the front. Phase changes of pedestrian formation are observed in both experiment and simulations. On the other hand, for sparse pedestrian crowds, the egress time of the fast individuals is mainly impacted by the horizontal distance between the initial positions of the slow pedestrians in the front, especially in the geometry with a bottleneck.     

Temporal inequalities for sequential multi-time actions in quantum information processing

A new kind of temporal inequalities are discussed, which apply to algorithmic processes, involving a finite memory processing unit. They are an alternative to the Leggett-Grag ones, as well as to the modified ones by Brukner et al. If one considers comparison of quantum anti classical processes involving systems of finite memory （of the same capacity in both cases）, the inequalities give a clear message why we can expect quantum speed-up. In a classical process one always has clearly defined values of possible measurements, or in terms of the information processing language, if we have a sequential computations of some function depending on data arriving at each step on an algorithm, the function always has a clearly defined value. In the quantum case only the final value, after the end of the algorithm, is defined. All intermediate values, in agreement with Bohr＇s complementarity, cannot be ascribed a definite value.     

A synapse memristor model with forgetting effect

In this Letter we improved the ion diffusion term proposed in literature [13] and redesigned the previous model as a dynamical model with two more internal state variables ‘forgetting rate’ and ‘retention’ besides the original variable ‘conductance’. The new model can not only describe the basic memory ability of memristor but also be able to capture the new finding forgetting behavior in memristor. And different from the previous model, the transition from short term memory to long term memory is also defined by the new model. Besides, the new model is better matched with the physical memristor (Pd/WOx/W) than the previous one.     

Gauss sum factorization with cold atoms

We report the first implementation of a Gauss sum factorization algorithm by an internal state Ramsey interferometer using cold atoms. A sequence of appropriately designed light pulses interacts with an ensemble of cold rubidium atoms. The final population in the involved atomic levels determines a Gauss sum. With this technique we factor the number N=263193.     

Climate transitions on long timescales

The climate has changed through the history of the Earth as evidenced in the geological records. Today we might be experiencing a climate change of the same magnitude as the transition into an ice age caused by very rapid burning and emission to the atmosphere of a substantial part of the fossilised carbon. Whether this leads to a gradual warming or if we will experience a transition into a different climatic state is presently unknown. The present day state-of-the-art numerical climate models are capable of producing fair representations of the current climate and are as such trusted to also predict the climate changes due to increasing atmospheric concentrations of greenhouse gases. However, the models are not presently capable of reproducing the rapid transitions from one climatic state, such as a glacial climate, into another, such as the present climate. The reason for this is unknown. The transitions are inherently ‘non-linear’ and thus not accessible through linear response theory. The term ‘non-linear’ is in this context defined as the phenomenon that the response of the system to a change in the forcing of the system is not linearly proportional to the forcing. This would happen if a threshold is reached such that the state of the system becomes unstable and the system bifurcates into a different state. There are strong indications in the geological records of this kind of behaviour for the climate. These dynamics can be understood in the context of fairly simple models of the climate.     

Linear Partial Differential Equations and Fourier Theory,by Marcus Pivato

When energetic heavy ions such as fission fragments pass through some solids, linear trails of damage (tracks) mark their trajectories. This paper reviews the large number of experimental observations of track structure in solids and shows how the track-storing ability of a solid is related to the electronic excitation of the bombarding ion and to a number of physical properties of the solid. Two models, ‘The Electron Thermal Spike’ and ‘The Ion Explosion Spike’, proposed to account for track formation are considered in the light of these results. The final section reviews a number of practical applications of the track-forming process.     

Kalman filter based initial guess estimation for digital image correlation

In applications digital image correlation based algorithms often present a basis for analysis of movement/deformation of bodies. The sequence of the obtained images is analyzed for this purpose. Especially, in cases when the body׳s movement/deformation between two successive images is significant, the initial guess can have a major influence on the execution speed of the algorithm. In the worst case it can even cause the divergence of the algorithm. This was the inspiration to develop a new and unique approach for an accurate and reliable determination of an initial guess for each image pixel. Kalman filter has been used for this purpose. It uses past measurements of observed variable(s) for calculations. Beside that it also incorporates state space model of the actual system. This is one of the most important advantages provided by Kalman filter. The determined initial guess by the proposed method is actually close to the true one and it enables fast convergence. Even more important property of this approach is the fact that it is not path-dependant because each image pixel, which is defined in ROI, is tracked through the sequence of images based on its own past measurements and general state space model. Consequently, the proposed method can be used to analyze tasks where discontinuities between image pixels are present. The applied method can be used to predict an initial guess where reference and deformed subsets are related by translational and rotational motion. The advantages mentioned above are verified with numerical and real experiments. The experimental validations are performed by NR (Newton–Raphson) approach which is the most widely used. Beside NR method the presented algorithm is applicable for other registration methods as well. It is used as an addition for calculation of initial guesses in a sequence of deformed images.     

Differential received power measurements over off-body links for obstruction-resilient pedestrian navigation

In this paper, we aim at improving pedestrian navigation experience based on standard narrow-band wireless technologies and simple radio metrics. The proposed solution takes benefits from body shadowing effects traditionally experienced at body-worn devices, for instance over off-body radio links with respect to fixed elements of infrastructure. The main idea is to infer relative angular information between the carrying body's heading and the received signal's direction of arrival. For this purpose, we consider differential received power measurements with judiciously placed on-body nodes. In comparison with related state-of-the-art contributions, a much lighter on-the-fly self-calibration procedure is made possible, based on the full-scale dynamics of the observed power measurements. We also describe a new algorithm that jointly estimates the body's absolute position and orientation, while benefiting from the body's movement continuity over time. The overall solution is validated by means of field experiments with IEEE 802.15.4-compliant devices operating at 2.4 GHz. Overall, the system is shown to be resilient, not only against self-shadowing effects generated by carrying bodies, but also against occasional obstructions caused by moving pedestrians in the vicinity (e.g., in crowded environments).     

一种基于数字图像的多目标检测方法

为使武器系统具备同时对多个目标进行精确打击的能力,在光电系统中可采用多目标视频跟踪器辅助激光照射器、伺服稳定平台实现多个潜在目标同时捕获跟踪并打击。研究了一种运行于多目标视频跟踪器的目标检测方法,针对数字图像分辨率高、数据量大及难以在嵌入式系统中实时运行的难点,基于TMS320C6455 DSP处理器,提出基于小波金字塔的全局运动光流估计算法图像配准实现运动图像的背景补偿以获取差分图像,相比传统的块匹配、灰度投影配准及基于特征点的配准算法,具有配准精度高与可嵌入式系统实时处理等优点,在差分图像中采用区域生长结合管道滤波算法提取图像中多个运动目标。经实验验证,该方法在复杂地面场景对汽车、自行车及行人目标检出率可达95%,计算时间仅为25 ms,具有良好的实时性和检测效果。