A Traditional Scientific Perspective on the Integrated Information Theory of Consciousness

This paper assesses two different theories for explaining consciousness, a phenomenon that is widely considered amenable to scientific investigation despite its puzzling subjective aspects. I focus on Integrated Information Theory (IIT), which says that consciousness is integrated information (as ϕ^Max) and says even simple systems with interacting parts possess some consciousness. First, I evaluate IIT on its own merits. Second, I compare it to a more traditionally derived theory called Neurobiological Naturalism (NN), which says consciousness is an evolved, emergent feature of complex brains. Comparing these theories is informative because it reveals strengths and weaknesses of each, thereby suggesting better ways to study consciousness in the future. IIT’s strengths are the reasonable axioms at its core; its strong logic and mathematical formalism; its creative “experience-first” approach to studying consciousness; the way it avoids the mind-body (“hard”) problem; its consistency with evolutionary theory; and its many scientifically testable predictions. The potential weakness of IIT is that it contains stretches of logic-based reasoning that were not checked against hard evidence when the theory was being constructed, whereas scientific arguments require such supporting evidence to keep the reasoning on course. This is less of a concern for the other theory, NN, because it incorporated evidence much earlier in its construction process. NN is a less mature theory than IIT, less formalized and quantitative, and less well tested. However, it has identified its own neural correlates of consciousness (NCC) and offers a roadmap through which these NNCs may answer the questions of consciousness using the hypothesize-test-hypothesize-test steps of the scientific method.     

An ESR Framework for the Study of Consciousness

I will argue that, in an interdisciplinary study of consciousness, epistemic structural realism (ESR) can offer a feasible philosophical background for the study of consciousness and its associated neurophysiological phenomena in neuroscience and cognitive science while also taking into account the mathematical structures involved in this type of research. Applying the ESR principles also to the study of the neurophysiological phenomena associated with free will (or rather conscious free choice) and with various alterations of consciousness (AOCs) generated by various pathologies such as epilepsy would add explanatory value to the matter. This interdisciplinary approach would be in tune with Quine’s well known idea that philosophy is not simple conceptual analysis but is continuous with science and actually represents an abstract branch of the empirical research. The ESR could thus resonate with scientific models of consciousness such as the global neuronal workspace model (inspired by the global workspace theory—GWT) and the integrated information theory (IIT) model. While structural realism has already been employed in physics or biology, its application as a meta-theory contextualising and relating various scientific findings on consciousness is new indeed. Out of the two variants: ontic structural realism (OSR) and epistemic structural realism (ESR), the latter can be considered more suitable for the study of consciousness and its associated neurophysiological phenomena because it removes the pressure of the still unanswered ‘What is consciousness?’ ontological question and allows us to concentrate instead on the ‘What can we know about consciousness?’ epistemological question.     

Model Unity and the Unity of Consciousness: Developments in Expected Float Entropy Minimisation

The unity of consciousness, or, more precisely, phenomenal unity, is an important property of consciousness and an important area of research in mathematical consciousness science and the scientific study of consciousness. Due to the numerous aspects and complexity of consciousness, the property tends to engender loose or inadequate characterizations. In this article, we introduce the concept and mathematical formulation of model unity. A system has model unity if a single relational model, stretched across the whole system, is optimal. Alternatively, model unity may only be present for subsystems, although there may still be unity at some higher level. As a development in the theory of expected float entropy minimisation, such relational models provide an interpretation of system states and the theory may help to provide insights into questions such as why experience of the visual field is unified and why different people do not have a unified consciousness, for example. This article constitutes a relatively small initial study of model unity. Four investigations were undertaken and are given as examples. A postulate is also given, distilling the foundations of EFE minimisation into a clear statement allowing others to consider whether or not the postulate identifies a self-evident fundamental property of consciousness.     

Implications of Noise on Neural Correlates of Consciousness: A Computational Analysis of Stochastic Systems of Mutually Connected Processes

Random fluctuations in neuronal processes may contribute to variability in perception and increase the information capacity of neuronal networks. Various sources of random processes have been characterized in the nervous system on different levels. However, in the context of neural correlates of consciousness, the robustness of mechanisms of conscious perception against inherent noise in neural dynamical systems is poorly understood. In this paper, a stochastic model is developed to study the implications of noise on dynamical systems that mimic neural correlates of consciousness. We computed power spectral densities and spectral entropy values for dynamical systems that contain a number of mutually connected processes. Interestingly, we found that spectral entropy decreases linearly as the number of processes within the system doubles. Further, power spectral density frequencies shift to higher values as system size increases, revealing an increasing impact of negative feedback loops and regulations on the dynamics of larger systems. Overall, our stochastic modeling and analysis results reveal that large dynamical systems of mutually connected and negatively regulated processes are more robust against inherent noise than small systems.     

基于Bi PLS结合Si PLS的组合权值COD浓度预测模型

水体中过高浓度的有机物含量危害巨大,不仅会造成严重的环境污染,而且危害人类身体健康,传统化学法检测水体化学需氧量(COD)的步骤繁琐且时效性差,不利于水体中COD的快速定量检测。针对这些问题,提出了一种将紫外光谱与组合权值模型相结合的快速定量检测COD方法,该组合权值模型是基于反向区间偏最小二乘法(BiPLS)结合组合区间偏最小二乘法(SiPLS)算法对紫外光谱的特征子区间筛选组合,然后依据特征子区间的权值建立的预测模型。首先按照一定的浓度梯度配制45份COD标准液样本,通过实验获取标准液的紫外光谱数据;对获取到的COD紫外光谱数据做一阶导数和S-G滤波(Savitzky-Golay)的预处理,消除基线漂移和环境干扰噪声;应用SPXY(Sample set partitioning based on jiont X-Y)算法将实验样本数据组划分成校正集和预测集。然后基于BiPLS算法对全光谱区间进行波长筛选,在BiPLS筛选过程中,目标区间的划分数量会对建模产生较大影响,于是对子区间划分数量进行优化,把子区间分成15~25个,在不同区间数下都进行偏最小二乘(PLS)建模,通过交互验证均方根误差(RMSECV)来筛选最优子区间数,得到区间数为18时,模型效果最佳。从18个波长区间筛选出了6个特征波长子区间,入选的子区间为2,1,3,11,7和6,对应波长为234~240,262~268,269~275,290~296,297~303和304~310 nm,这6个特征波长区间涵盖了大量的光谱信息,对最终预测模型的贡献度大;接下来通过SiPLS算法对这6个初选区间进行进一步的筛选组合,采用不同的组合数构建不同特征区间上的PLS模型,在相同组合数下,筛选出一个区间组合数最优的结果,对比不同组合数下预测模型的误差与相关性,将6个区间筛选组合为3个特征波长区间,分别为234~240,262~275和290~310 nm,这三个特征区间最佳因子数分别为4,4和3。对传统SiPLS的特征区间组合方法进行改进,基于权值的大小来对这3个特征区间进行线性组合,代替过去特征区间直接组合的方法。通过权值公式计算出这3个特征区间的权重大小分别为0.509,0.318和0.173,最终建立线性组合权值COD浓度预测模型。为了验证组合权重预测模型的精度,另外建立了全波长范围内的PLS预测模型、单个特征波长区间的PLS预测模型、直接组合特征波长区间的PLS模型,并使用评价参数相关系数的平方(R2)、预测值与真实浓度值的均方根误差(RMSEP)和预测回收率(T)来对模型评价。验证结果表明,相比其他预测模型,组合权值模型相关系数的平方达到了0.999 7,明显优于直接组合特征区间建模的0.968 0,预测均方根误差为0.532,比直接组合特征区间的预测模型误差降低了29.3%,预测回收率为96.4%~103.1%,显著地提高了预测精度。该方法简单可行,不会产生二次污染,可为在线监测水体中COD浓度提供一定的技术支持。     

一种基于HLLC算法的Mie-Grüneisen多介质混合模型

建立一种修正的HLLC （Harten-Lax-Van Leer-Contact）格式下稳定的Mie-Grüneisen多介质混合计算模型.Mie-Grüneisen混合模型中的通量包括守恒和非守恒两个部分,原始的HLLC格式对守恒部分适用,但是原始的HLLC格式直接用于非守恒部分,很难控制住数值振荡的产生.在原始格式中,间断面的移动速度为间断网格的左侧或右侧速度,修正后替换为网格中的平均速度,经过修正后,对HLLC格式重新进行推导,并随之扩展到二维问题.数值实验表明,利用修改后的HLLC格式,Mie-Grüneisen混合模型可以取得较好的稳定性和准确性.     

基于守恒高阶模型的动态交通分配建模与仿真

针对路网中的动态交通分配问题,采用高阶守恒模型（CHO）进行建模与数值研究,并推广高阶守恒模型二进二出路口的Riemann问题;同时将高阶守恒模型与动态网络加载（DNL）模型相结合,通过变分不等式对动态网络加载模型进行分析.数值模拟采用一阶有限体积法求解高阶守恒模型,同时采用梯度下降方法迭代求解动态网络加载模型的变分不等式问题,最终以动态用户最优条件为目标实现分配均衡.数值结果表明CHO模型与DNL模型结合解决动态交通分配问题是可行的,对传统模型的研究有一定的指导意义.     

Derivation of Two-Fluid Model Based on Onsager Principle

Using the Onsager variational principle, we study the dynamic coupling between the stress and the composition in a polymer solution. In the original derivation of the two-fluid model of Doi and Onuki the polymer stress was introduced a priori; therefore, a constitutive equation is required to close the equations. Based on our previous study of viscoelastic fluids with homogeneous composition, we start with a dumbbell model for the polymer, and derive all dynamic equations using the Onsager variational principle.     

利用传感器距离和能耗约束的无线传感器网络路由优化

针对大多数现有的无线传感器网络设计方法通常仅找到给定图的最短路径而导致只能优化单个用户性能的问题,提出了一种寻找节点之间的最短路径和最低能耗的路由优化模型,该模型约束WSNs的特定资源,考虑多种约束条件：多周期、最短距离和低能耗。本文按照混合整数线性规划,使用11.0 ILOG CPLEX优化引擎的ILOG OPL开发工具5.5进行编码和求解本文的优化模型。实验结果表明,相比一般可行网络,本文模型的节点的总距离和能耗均有明显降低,此外,在三个不同周期和约束条件数下,每组实验花费的时间均少于10s,完全满足资源有限的无线网络应用要求。     

一种基于热补偿电流的大功率VCSEL模型

基于激光速率方程并加入了热补偿电流,建立了一种用于分析大功率垂直腔面发射激光器(VCSELs)输出特性(P-I)的模型。先测得已知温度下的P-I特性,根据实验数据,利用阈值电流和温度的关系和Gao等人的方法得到a参数和其它参数。把所得参数代入模型,可以获得所需温度下的P-I特性。从模拟结果可以看出,不同温度下,模拟结果与实验结果吻合的非常好,而不考虑热补偿电流时差别很大,从而证明了该激光器模型的有效性;同时,从有源区温度和电流关系曲线可以看出,有源区随着电流增加温升很快,进一步证实了我们研究温度影响的重要性。     

基于视觉注意的彩色图像检索方法

基于视觉注意模型提取的特征能够反映图像高层语义的新特征,将视觉注意机制引入到图像分析领域能有效地减小语义鸿沟,获得高效的图像检索性能.根据视觉感知的特点,对Itti视觉注意模型进行了改进.采用主分量图表示亮度图,将纹理粗糙度信息融入视觉注意模型,进而提出了一种基于视觉注意空间分布特征的图像检索算法.首先由改进视觉注意模型将图像分解得到38个视觉特征图,然后采用网格平分法提取视觉特征图的空间分布信息,组成特征矢量来多层次地对图像特征进行描述,用于图像检索.实验结果表明,该算法利用基于改进注意力模型方法来提取图像空间分布特征进行图像检索,能获得较高的检索率.     

对一个力学碰撞问题的讨论

对普通物理力学中有关碰撞的一个问题,从恢复系数e的取值角度出发,进行了详细求解和讨论,得到了更完整的结果.     

基于凸组合核函数的化合物太赫兹透射光谱分类

物质的太赫兹光谱包含着非常丰富的物理和化学信息。它对化合物晶体具有高的灵敏度、 单光子能量低等特点。但受到检测人员知识背景、 背景噪声、 识别算法精度等因素的影响,光谱样本识别准确率和效率较低。为了提高对太赫兹光谱的检测能力,提出应用基于凸组合核函数的support vector machines(SVM)对化合物的THz脉冲透射谱进行分类。在使用小波变换对数据进行滤波预处理之后,提取了传统波峰、 波谷位置特征和term frequency-inverse document frequency (TF-IDF) 最大间隔特征。TF-IDF方法使用信息论的原理确定每个采样点的权重,选择权重较大的点作为特征。针对太赫兹透射谱特征相似、 维数较低带来的分类困难问题,构建基于凸组合核函数的SVM分类模型。并利用核评价的方法,通过高维非线性规划方程求解最优凸组合参数。当最优凸组合参数被确定时,构建分类模型进行分类和预测。相比较于单一核函数,凸组合核函数将透射谱特征与分类模型融合起来。对于不同的检测样本,数据经过凸组合核函数映射到高维空间后,特征具有更显著的区分度。使用不同的太赫兹透射谱样本进行分类实验,结果表明,分类准确率得到极大提高。     

A Conceptual Model of Somali Jet Based on the Biot--Savart Law

We study the relationship between thermal conditions on the earth bottom boundary and the formation of Somali jet based on the Biot-Savart law and the data from National Centres for Environmental Prediction （NCEP）. As the radiation from the Sun gradually moves from the southern meridian, the temperature on the surface of Somali Peninsular and Arabic Peninsular gradually increases. During the same period the surface temperature of the Northern Indian Ocean increases much slower. It is shown that this increase of the temperature difference between the land and sea is inductive to the formation and development of Rayleigh-Benard convection and leads to the increasing relative vorticity strength between positive and negative vertical vortices over the land and sea. According to the Biot-Savart law, increase of vorticity strength will correspondingly induce the horizontal velocity. A pair of positive and negative vorticity fields over the two Peninsulars and the sea surface is effective in forming and maintaining this current. This mechanism is referred to as the ＇Somali suction pump＇. It draws air continually from the Southern hemisphere and releases it at the coastal area of Somali.     

一种基于特征点间线段倾角的姿态测量方法

基于目标特征点间线段倾角信息,提出了一种适合于目标远距离成像和相机内参未知条件下解算目标姿态的目标3维姿态测量方法.采用仿真图像对该方法的正确性进行了验证.实验结果:姿态测量误差绝对值均值小于0.6°,且目标成像尺寸为350pixel时,姿态测量误差绝对值小于0.5°.实验表明该算法具有较高解算准确度和较强的收敛性.     

基于改进水平集方法的翼型拓扑优化

将改进的水平集方法与灵敏度分析方法相结合,发展了一种研究Navier-Stokes方程拓扑优化的新方法。在拓扑优化过程中,引入无需样条参数化的网格重新划分方法,实现水平集函数演化和流场求解的结合。最后,通过对低雷诺数条件下Navier-Stokes翼型优化问题的研究,表明该方法具有良好的全局性,并能有效节约优化问题的计算工作量。     

基于双光栅成像的RGB模型色彩还原效果的研究

基于双光栅衍射成像的实验方案,利用双光栅的色散和汇合光谱效应特性,用电脑摄像头拍摄作为物体的RGB模型,得到了RGB颜色模型的像。利用Photo shop软件将RGB颜色模型和得到的像进行颜色通道分离,再进行数据化分析处理,探究双光栅的RGB色彩模型色彩还原情况以及不同光栅组合对RGB颜色模型的色彩还原效果的影响。     

基于泡沫微观渗流特征的泡沫驱数学模型

通过泡沫微观渗流实验可以看出泡沫在多孔介质内呈现两种渗流状态:流动泡沫和捕集泡沫.泡沫封堵实验可以看出泡沫封堵能力具有叠加性,当泡沫驱达到稳态后,岩心入口端泡沫封堵压力梯度小于岩心后段封堵压力梯度.基于泡沫总量平衡思想和泡沫性质表征模型,建立泡沫驱多组分数学模型.对该模型进行数值求解,模型采用全隐式方法求解.通过与泡沫封堵实验拟合,验证了模型的有效性,在此基础上研究了泡沫驱过程中不同位置处泡沫数目、压力、含水饱和度等泡沫驱渗流特征参数变化规律.     

A Novel Model of Interaural Time Difference Based on Spatial Fourier Analysis

Based on the spatial Fourier analysis, a statistical model of the individualized interaural time difference （ITD） is derived from the head-related transfer function database for a Chinese subject. The model reflects the spatial left-right symmetry and front-back asymmetry of lTD. Moreover, by using three anatomical parameters of head and pinna, the model is able to predict individualized ITD in the horizontal plane. Performance of the four subjects outside the database demonstrates that the mean of the total error is less than 20 μs, while the lateral performance is inferior to that at other directions.     

基于CASI高光谱数据的作物叶面积指数估算

叶面积指数(LAI)的快速估算对于及时了解作物长势、病虫害监测以及产量评估具有重要意义。利用2012年7月7日在黑河流域张掖市获取的CASI高光谱数据,精确提取出了不同作物的光谱反射率,同时结合地面实测数据,对比分析了宽波段和“红边”植被指数在估算作物LAI方面的潜力,在此基础上,基于波段组合算法,筛选出作物LAI估算的敏感波段,并构建了两个新型光谱指数NDSI和RSI,最后对研究区域作物LAI的空间分布进行了分析。结果表明,在植被覆盖度较低的情况下,宽波段植被指数NDVI对LAI具有较好的估算效果,模型的精度R2与RMSE分别为0.52,0.45(p<0.01);对于“红边”植被指数,由于CI_{red edge}充分考虑了不同的作物类型,其对LAI的估算精度与NDVI一致;利用波段组合算法构建的光谱指数NDSI_{(569.00, 654.80)}和RSI_{(597.6, 654.80)}对LAI估算的效果要优于NDVI与CI_{red edge},其中,NDSI_{(569.00, 654.80)}主要利用了植被光谱“绿峰”和“红谷”附近的波段,模型估算的精度R2可达0.77(p<0.000 1);根据LAI与NDSI_{(569.00, 654.80)}之间的函数关系,绘制作物LAI的空间分布图,经分析,研究区域的西北部LAI值偏低,需增施肥料。研究结果,可为农业管理部门及时掌握作物长势信息、制定施肥策略提供技术支持。