关于设计思想研究的几点思考

设计思想是人类对设计活动的认识、概括、论证和思考的结晶,是社会和设计发展到一定阶段的产物,是人类社会进入文明时代、设计上升到自觉状态的标志。通过对设计思想研究方向的自觉认识,可以更好地服务于当前的设计活动,提高效率,并指出发展趋势。     

A Neurocomputational Approach to Abduction

Recent developments in the cognitive sciences and artificial intelligence suggest ways of answering the most serious challenge to Peirce's notion of abduction. Either there is no such logical process as abduction or, if abduction is a form of inference, it is essentially unconscious and therefore beyond rational control so that it lacks any normative significance. Peirce himself anticipates and attempts to answer this challenge. Peirce argues that abduction is both a source of creative insight and a form of logical inference subject to a degree of conscious control. In this paper I shall sketch a developing account of abduction that is suggested by the work of Paul Churchland, Paul Thagard, Chris Eliasmith, William Wimsatt, Owen Flanagan, and others. I shall argue that a credible account of abduction will require that we approach the phenomenon from both higher and lower levels as represented by these approaches.     

HT树：缓存敏感的内存数据库索引

在内存数据库系统中,针对处理器缓存对提高内存数据库的性能有重要影响的情况,在B＋树的基础上提出一种新的缓存敏感的索引——HT索引。将Hash方法和树结构相结合,构造一种适用于内存数据库的索引。结果证明,该索引结构能提高处理器缓存的利用率,其整体操作性能优于传统的缓存敏感索引。     

Intentionality,qualia, and mind/brain identity

The paper examines the status of conscious presentation with regard to mental content and intentional states. I argue that conscious presentation of mental content should be viewed on the model of a secondary quality, as a subjectiveeffect of the microstructure of an underlying brain state. The brain state is in turn viewed as the instantiation of an abstract computational state, with the result that introspectively accessible content is interpreted as a presentation of the associated computational state realized by the brain. However, if the relation between consciousness and representational content is construed in this manner, then conscious presentation does not provide an adequate foundation for the claim that human mental states areintrinsically intentional. On this model, I argue that functionalism is able to account for (non-intrinsic) intentionality, but not for consciousness, which has implications for the computational paradigm, as well as for Searle's Chinese room thought experiment.     

Organizational Data Breach: Building Conscious Care Behavior in Incident Response

Organizational and end user data breaches are highly implicated by the role of information security conscious care behavior in respective incident responses. This research study draws upon the literature in the areas of information security, incident response, theory of planned behaviour, and protection motivation theory to expand and empirically validate a modified framework of information security conscious care behaviour formation. The applicability of the theoretical framework is shown through a case study labelled as a cyber-attack of unprecedented scale and sophistication in Singapore’s history to-date, the 2018 SingHealth data breach. The single in-depth case study observed information security awareness, policy, experience, attitude, subjective norms, perceived behavioral control, threat appraisal and self-efficacy as emerging prominently in the framework’s applicability in incident handling. The data analysis did not support threat severity relationship with conscious care behaviour. The findings from the above-mentioned observations are presented as possible key drivers in the shaping information security conscious care behaviour in real-world cyber incident management.     

基于AFSA—BP神经网络的基坑变形预测模型研究

为改善BP神经网络收敛速度慢、初始权阈值对计算结果影响较大且易陷入局部最优等缺陷,为提高模型的预测精度和稳定性,使用具有全局优化能力的鱼群算法优化BP神经网络的初始权阈值,依托工程实例,将BP模型及改进的模型用于基坑变形预测中,通过预测值与实测值进行对比,结果表明：AFSA-BP模型的预测精度要高于BP模型,且预测结果稳定、预测速度较快、预测误差可以满足工程的要求,对于下一步施工具有良好的指导作用,所以AFSA-BP模型是一种有效的基坑变形预测模型。     

The GuideCane-applying mobile robot technologies to assist thevisually impaired

The GuideCane is a device designed to help blind or visually impaired users navigate safely and quickly among obstacles and other hazards. During operation, the user pushes the lightweight GuideCane forward. When the GuideCane's ultrasonic sensors detect an obstacle, the embedded computer determines a suitable direction of motion that steers the GuideCane and the user around it. The steering action results in a very noticeable force felt in the handle, which easily guides the user without any conscious effort on his/her part     

Unconscious emotions: quantifying and logging something we are not aware of

Lifelogging tools aim to precisely capture daily experiences of people from the first-person perspective. Although there have been numerous lifelogging tools developed for users to record the external environment around them, the internal part of experience characterized by emotions seems to be neglected in the lifelogging field. However, the internal experiences of people are important and, therefore, lifelogging tools should be able to capture not only the environmental data, but also emotional experiences, thereby providing a more complete archive of past events. Moreover, there are implicit emotions that cannot be consciously experienced, but still influence human behaviors and memories. It has been proven that conscious emotions can be recognized from physiological signals of the human body. This fact may be used to enhance life-logs with information about unconscious emotions, which otherwise would remain hidden. On the other hand, it is not clear if unconscious emotions can be recognized from physiological signals and differentiated from conscious emotions. Therefore, an experiment was designed to elicit emotions (both conscious and unconscious) with visual and auditory stimuli and to record cardiovascular responses of 34 participants. The experimental results showed that heart rate responses to the presentation of the stimuli are unique for every category of the emotional stimuli and allow differentiation between various emotional experiences of the participants.     

Understanding the Role of Conscious and Automatic Mechanisms in Social Networking Services: A Longitudinal Study

Given the proliferation of social networking sites (SNSs), it has become important to understand users’ continued attraction and usage of them. Previous works on information systems (IS) and marketing have paid little attention to the role of automatic mechanisms in frequently used IS such as mobile applications and SNSs. We develop an integrated framework to examine the effects of conscious and automatic mechanisms on SNS users’ postadoption behaviors. Considering the unique characteristics of SNSs, we posit user satisfaction, trust in an SNS provider, and prior SNS use as key drivers accelerating the development of SNS habitual use. Longitudinal data collected from 250 Facebook users were tested against the research model using partial least squares. The findings showed that SNS continuance usage is shaped by automatic factor as well as by reasoned conscious factor. In particular, SNS continuance usage is largely explained by SNS habit. User satisfaction, trust in an SNS provider, and prior SNS use were found to be the key enablers of developing SNS habit. Moreover, the analysis results clarify the exact role of relationship management, self-presentation, perceived enjoyment, and trust in an SNS provider in users’ decision-making processes. Implications for research and practice are described.     

On an Argument for Functional Invariance

The principle of functional invariance states that it is a natural law that conscious beings with the same functional organization have the same quality of conscious experience. A group of arguments in support of this principle are rejected, on the grounds that they establish at most only the weaker intra-subjective principle that any two stages in the life of a single conscious being that duplicate one another in terms of functional organization also duplicate one another in terms of quality of phenomenal experience.

A virtual “Room” with a cue: Detecting personality through spatial customization in a city simulation game

Online simulation games provide an opportunity for people to express their personality through the design of their in-game virtual environment in a manner visible to third-party observers. We found that zero-acquaintance observers of these games can identify personality traits by simply looking at screenshots of the created virtual environment, and that the observed personality is closer to the self-reported “real” personality than “ideal” personality of the creator. These results contradict studies on avatar customization and personality, suggesting that spatial customization is more reflective of unintentional behavioral residue than conscious selective self-presentation.     

An innovative approach of risk planning for space programs.

According to the current rule-based risk management approach at the National Aeronautics and Space Administration (NASA), the effort is directed to contain all identified risks of a program. The identification of hazards and mitigation effort proceeds along with the development of the system hardware, till all the tradable resources for a program is exhausted. In this process, no conscious effort is made to evaluate risks and associated cost, and the final design is likely to have undesirable residual risks. This approach also results in allocating a significant amount of resources to gain only marginal mitigation of hazard and leave some undesirable hazards in the system due to the budget limitation. The approach in the proposed knowledge-based risk planning system makes a conscious attempt to trade risk with other resources, e.g., schedule, cost, reliability, performance, and others in a judicious and cost-effective way. A knowledge of the feasible option sets requiring high incremental cost for a marginal gain in hazard reduction helps the management to make decision for residual risk that falls within an acceptable range for an option set.     

复杂环境中的车牌字母和数字识别研究

当前车牌识别的研究大都是针对正常环境进行的,对于复杂环境下的车牌难以达到识别要求。本文提出一种用BP神经网络构造并行神经网络的车牌字母和数字识别方法,利用PVM网络在虚拟并行平台上实现了并行神经网络,最后对复杂现场环境下获取的车牌进行了实验。实验结果证明,该算法具有良好的性能,能在28ms内实时准确的识别车牌字母和数字。     

一种基于神经网络集成的规则学习算法

将神经网络集成与规则学习相结合，提出了一种基于神经网络集成的规则学习算法．该算法以神经网络集成作为规则学习的前端，利用其产生出规则学习所用的数据集，在此基础上进行规则学习．在UCl机器学习数据库上的实验结果表明，该算法可以产生泛化能力非常强的规则．     

神经网络结构动态优化设计的分析与展望

阐述了神经网络结构设计对神经网络性能的影响. 介绍了动态结构神经网络, 尤其是增长型和修剪型神经网络研究的发展过程, 分析了动态设计方法研究在计算能力、学习理论和网络的稳定性等方面取得的成果. 最后对神经网络动态设计的研究进行总结, 给出了神经网络结构动态设计研究的发展趋势.     

The interplay of conscious and automatic mechanisms in the context of routine use: An integrative and comparative study of contrasting mechanisms

Researchers have been closely studying how information technology services became a routine part of our lives. Studies have found that users who routinely use online services either consciously develop loyalty or automatically develop a habit. But many studies now mix the elements of conscious and automatic use despite the great differences in these phenomena. This study proposes a new theoretical framework of how the conscious and automatic mechanisms simultaneously, but differentially, regulate postadoption phenomena in the context of online information services. An empirical test confirms that these two mechanisms have highly discernible patterns that researchers and managers alike must heed.     

Neurocomputing hardware: present and future

This paper discusses the current state of the art of industrial neurocomputing, and then speculates on its future.Three examples of commercial neuro-silicon are presented: the Adaptive Solutions CNAPS system, the Intel ETANN chip, and the Synaptics OCR chip.We then speculate on where commercial neurocomputing hardware is going. In particular we propose that commercial systems will evolve in the direction of capturing more contextual, knowledge level information. Some results of an industrial handwritten character recognition system created at Apple Computers will be presented which demonstrate the power of adding contextual knowledge to neural network based recognition. Also discussed will be some of the possible directions required for neural network algorithms needed to capture such knowledge and utilize it effectively, as well as results from experiments on capturing contextual knowledge using several different neural network algorithms.Finally, the issues involved in designing VLSI architectures for the efficient emulation of sparsely activated, sparsely connected contextual networks will be discussed. There are fundamental cost/performance limits when emulating such sparse structures in both the digital and analog domain.     

基于暂态混沌神经网络的组播路由算法

讨论了高速包交换计算机网络中具有端到端时延的组播路由问题。首先给出了这类问题的网络模型及其数学描述，然后提出了基于暂态混沌神经网络的组播路由算法。实验结果表明，该算法能够快速有效地实现组播路由优化，并且计算性能及解的质量优于基于Hopfield神经网络的路由算法。     

An Artificial Neural Network-Based Model for Effective Software Development Effort Estimation

In project management, effective cost estimation is one of the most crucial activities to efficiently manage resources by predicting the required cost to fulfill a given task. However, finding the best estimation results in software development is challenging. Thus, accurate estimation of software development efforts is always a concern for many companies. In this paper, we proposed a novel software development effort estimation model based both on constructive cost model II (COCOMO II) and the artificial neural network (ANN). An artificial neural network enhances the COCOMO model, and the value of the baseline effort constant A is calibrated to use it in the proposed model equation. Three state-of-the-art publicly available datasets are used for experiments. The backpropagation feedforward procedure used a training set by iteratively processing and training a neural network. The proposed model is tested on the test set. The estimated effort is compared with the actual effort value. Experimental results show that the effort estimated by the proposed model is very close to the real effort, thus enhanced the reliability and improving the software effort estimation accuracy.