认知诊断模型的标准误与置信区间估计：并行自助法

认知诊断模型的标准误(Standard Error, SE; 或方差—协方差矩阵)与置信区间(Confidence Interval, CI)在模型参数估计不确定性的度量、项目功能差异检验、项目水平上的模型比较、Q矩阵检验以及探索属性层级关系等领域有重要的理论与实践价值。本研究提出了两种新的SE和CI计算方法：并行参数化自助法和并行非参数化自助法。模拟研究发现：模型完全正确设定时, 在高质量及中等质量项目条件下, 这两种方法在计算模型参数的SE和CI时均有好的表现; 模型参数存在冗余时, 在高质量及中等质量项目条件下, 对于大部分允许存在的模型参数而言, 其SE和CI有好的表现。通过实证数据展示了新方法的价值及计算效率提升效果。     

Wearable computing: Will it make people prosocial?

We recently reported that people who wear an eye tracker modify their natural looking behaviour in a prosocial manner. This change in looking behaviour represents a potential concern for researchers who wish to use eye trackers to understand the functioning of human attention. On the other hand, it may offer a real boon to manufacturers and consumers of wearable computing (e.g., Google Glass), for if wearable computing causes people to behave in a prosocial manner, then the public's fear that people with wearable computing will invade their privacy is unfounded. Critically, both of these divergent implications are grounded on the assumption that the prosocial behavioural effect of wearing an eye tracker is sustained for a prolonged period of time. Our study reveals that on the very first wearing of an eye tracker, and in less than 10 min, the prosocial effect of an eye tracker is abolished, but by drawing attention back to the eye tracker, the implied presence effect is easily reactivated. This suggests that eye trackers induce a transient social presence effect, which is rendered dormant when attention is shifted away from the source of implied presence. This is good news for researchers who use eye trackers to measure attention and behaviour; and could be bad news for advocates of wearable computing in everyday life.     

Blockchain Identities: Notational Technologies for Control and Management of Abstracted Entities

This paper argues that many so‐called digital technologies can be construed as notational technologies, explored through the example of Monegraph, an art and digital asset management platform built on top of the blockchain system originally developed for the cryptocurrency bitcoin. As the paper characterizes it, a notational technology is the performance of syntactic notation within a field of reference, a technologized version of what Nelson Goodman called a “notational system.” Notational technologies produce abstracted entities through positive and reliable, or constitutive, tests of socially acceptable meaning. Accordingly, this account deviates from typical narratives of blockchains (usually characterized as Turing or state machines), instead demonstrating that blockchain technologies are effective at managing digital assets because they produce abstracted identities through the performance of notation. Since notational technologies rely on configurations of socially acceptable meaning, this paper also provides a philosophical account of how blockchain technologies are socially embedded.     

Mimic automata: A novel formal model for mimic computing

In this paper, we aim to establish a mathematical model for mimic computing. To this end, we present a novel automaton called a mimic automaton. First, a one-dimensional cellular automaton is used for expressing some dynamic changes in the structure of a computing unit, a sequential automaton is employed to describe some state transitions, a hierarchical automaton is employed to express the different granularities of some computing units, and a probabilistic automaton is used to depict some random changes of a computing unit. Second, a mimic automaton is obtained by combining the various types of automata mentioned above in a certain logical relationship. Compared with the existing models of mimic computing, the new model portrays the operational semantics for a mimic computing system, and it can directly describe the behaviors of a system. Furthermore, the new model possesses a stronger generality.     

Energy management solutions in the Internet of Things applications: Technical analysis and new research directions

By advancement of Internet of Things (IoT) technology in smart life such as smart city, smart home, smart healthcare and smart transportation, interconnections between smart things are growing that complicate evaluation of efficiency factors on the intelligent systems. Energy consumption as one of the most challenging issues is increasing with the growing IoT devices and existing interconnections between cloud data centers, mobile applications and human activities. Managing energy efficiency and power consumption is one of the important issues in green IoT-enabled technologies. This paper presents an overview on the energy management solutions in the IoT based on Systematic Literature Review (SLR). The main goal of this SLR-based overview is to recognize significant research trends in the field of energy management and power consumption techniques which need additional consideration to highlight more efficient and effective methods in IoT. Also, a taxonomy is proposed to categorize the existing research studies on energy management solutions. A statistical and technical analysis of reviewed existing papers are provided, and evaluation factors and attributes are discussed. We observed that variety of published research papers in smart home have highest percentage to evaluate energy management in the IoT. Also, deep learning and clustering methods are must popular techniques that were applied to evaluate the energy management in IoT case studies. Finally, new challenges and forthcoming issues of the energy management and efficient power consumption methods are presented.     

A bare bones bacterial foraging optimization algorithm

Bacterial foraging optimization (BFO), based on the social foraging behaviors of bacteria, is a new intelligent optimizer. It has been widely accepted as an optimization algorithm of current interest for a variety of fields. However, compared with other optimizers, the BFO possesses a poor convergence performance over complex optimization problems. To improve the optimization capability of the BFO, in this paper a bare bones bacterial foraging optimization (BBBFO) algorithm is developed. First, a chemotactic strategy based on Gaussian distribution is incorporated into this method through making use of both the historical information of individual and the share information of group. Then the swarm diversity is introduced in the reproduction strategy to promote the exploration ability of the algorithm. The performance of BBBFO is verified on various benchmark functions, the comparative results reveal that the proposed approach is more superior to its counterparts.     

Beyond design: cybernetics,biological computers and hylozoism

The history of British cybernetics offers us a different form of science and engineering, one that does not seek to dominate nature through knowledge. I want to say that one can distinguish two different paradigms in the history of science and technology: the one that Heidegger despised, which we could call the Modern paradigm, and another, cybernetic, nonModern, paradigm that he might have approved of. This essay focusses on work in the 1950s and early 1960s by two of Britain’s leading cyberneticians, Stafford Beer and Gordon Pask, in the field of what one can call biological computing. My object is to get as clear as I can on what Beer and Pask were up to. At the end, I will discuss Beer’s hylozoist ontology of matter, mind and spirit. This material is not easy to get the hang of—but that is what one should expect from an unfamiliar paradigm. Presented at an international conference on the philosophy of technology, Copenhagen, 13–15 Oct 2005. Revised for submission to Synthese.     

Empirical and modeling study of emotional state dynamics in social videogame paradigms

The objective of this work was to study the dynamics of human emotional states in the process of social interaction in a virtual environment. The previously developed for this purpose prototypes of the virtual actor (NPC) and its virtual environment simulator “Teleport” underwent significant re-design and modification. The experimental platform was re-implemented and used in experiments with college student participants, combining electromyography, emotion recognition in facial recordings and model-based game log analysis in a social videogame paradigm. Participants interacted with two virtual actors implemented based on the eBICA cognitive architecture (Samsonovich, 2013, 2018). Positive correlations were found between eBICA model predictions and participant affects extracted from their facial expressions and facial muscle activity. Affective dynamics of social phenomena, such as the establishment of partnership or an act of betrayal, were characterized and found consistent with the model predictions. Other findings include a gradually developing emotional reaction, possibly due to the integration of appraisals of game events. Overall, obtained results confirm the eBICA model, suggesting its further extension and refinement.     

Ethical Calibration for an Intelligent Analysis Society

With the widespread application of data-driven intelligent technologies, data is increasingly used to record and influence the behavior of the world and people. Although the value rationality of dataism behind the dataization of the world has yet to be thoroughly analyzed, the new data analysis society which is characterized by an intelligent social form has quietly arrived. From a phenomenological point of view, the foundation of the operation and governance of a data analysis society is to analyze human behavior by using data and intelligent algorithms, but this kind of intelligent surveillance is speculative cognition, which may misread and improperly interfere with the agency of observed. There is an urgent need to set boundaries for possible technological abuse. At the same time, in view of the fact that data-driven social computing attempts to influence human behavior through the calculation of human behavior, the value of human behavior itself should be questioned as a problem to be solved. Further, in the face of the potential challenges of machine cognition and engineering thinking to human nature in the construction of an intelligent society, it is urgent to construct an ethical reflection arc that can restrict and correct its abuse.