Cognitive engineering based knowledge representation in neural networks

A model of a human neural knowledge processing system is presented that suggests the following. First, an entity in the outside world lends to be locally encoded in neural networks so that the conceptual information structure is mirrored in its physical implementation. Second, the knowledge of problem solving is implemented in a quite implicit way in the internal structure of the neural network (a functional group of associated hidden neurons and their connections to entity neurons) not in individual neurons or connections. Third, the knowledge system is organized and implemented in a modular fashion in neural networks according to the local specialization of problem solving where a module of neural network implements an inter-related group of knowledge such as a schema, and different modules have similar processing mechanisms, but differ in their input and output patterns. A neural network module can be tuned just as a schema structure can be adapted for changing environments. Three experiments were conducted to try to validate the suggested cognitive engineering based knowledge structure in neural networks through computer simulation. The experiments, which were based on a task of modulo arithmetic, provided some insights into the plausibility of the suggested model of a neural knowledge processing system.     

Combining natural language with direct manipulation: the conceptual framework for a hybrid human-computer interface

This paper describes the development of a conceptual model of an interaction system for future human-computer interaction. It is suggested that an integrated system is the most promising solution for diverse users and tasks. A ' hybrid interaction system' is considered, which tries to efficiently direct manipulation, menu selection, and natural language. The mechanism of the natural language interface module is described in more detail. Finally, the allocation of functionalities for generalized tasks on the conceptual model is considered from the taxonomic approach.     

Micro-persistence and difficulty in a game-based learning environment for computational thinking acquisition

Persistence has been identified as a crucial quality of learning. However, it is hard to attain in online game-based environments as the drive to progress in the game may influence the ability to achieve the learning goals. This study aimed to examine the associations between micro-persistence, that is, the tendency to complete an individual task successfully, and task difficulty while acquiring computational thinking (CT). We further explored whether contextual or personal attributes better explain micro-persistence. We analysed data of 111 school students who used the CodeMonkey platform. We took a learning analytics approach for analysing the platform's log files. We found that micro-persistence is associated with task difficulty and that students who demonstrated an aptitude to learn new material are motivated to achieve the best solution. We also found that contextual variables better-explained micro-persistence than personal attributes. Encouraging micro-persistence can improve CT acquisition and the learning processes involved.     

Bit transposition for very large scientific and statistical databases

Conventional access methods cannot be effectively used in large Scientific/Statistical Database (SSDB) applications. A file structure (called bit transposed file (BTF)) is proposed which offers several attractive features that are better suited for the special characteristics that SSDBs exhibit. This file structure is an extreme version of the (attribute) transposed file. The data are stored by vertical bit partitions. The bit patterns of attributes are assigned using one of several data encoding methods. Each of these encoding methods is appropriate for different query types. The bit partitions can also be compressed using a version of the run length encoding scheme. Efficient operators on compressed bit vectors have been developed and form the basis of a query language. Because of the simplicity of the file structure and query language, optimization problems for database design, query evaluation, and common subexpression removal can be formalized and efficient exact solution or near optimal solution can be achieved. In addition to selective power with low overheads for SSDBs, the BTF is also amenable to special parallel hardware. Results from experiments with the file structure suggest that this approach may be a reasonable alternative file structure for large SSDBs.     

Older adults’ use of smart phones: an investigation of the factors influencing the acceptance of new functions

After adopting mobile phones, most older adults use them only for calling and SMS. The purpose of this study is to extend their usage of mobile phones to new functions. To understand older adults’ requirements of mobile phones, a questionnaire was constructed and 351 Chinese older adults were recruited to complete the questionnaires. Data collected through the questionnaires were analysed using explorative factor analysis. The results revealed that older adults’ requirements were composed of 10 factors: Find a Specific Function, Awareness and Attractiveness, Readability, Personal Concern, Soft Keys and Multi-tap, Hardware Capacity, Touch Screen, Concern of Learning, Connectivity, and Social Influence. Then, from the above 10 factors, the 6 most important factors were revealed using multiple linear regression analysis. The results imply that accepting new functions is different from accepting a product. Readability and Find a Specific Function, which are critical for older adults’ acceptance of feature phones, are not determinants of their acceptance of new functions in smart phones.     

User Satisfaction with Tablet PC Features

Previous studies of tablet personal computers have concentrated on their use in education and healthcare. The current study focused instead on personal usage, investigating how satisfied users are with their own tablets after having used them in their daily lives. The objective was to identify the major features for tablets and to investigate how form factors affect the preference of functions by performing a comparison of iPad1 and Galaxy Tab. Also, gender and ethnicity were analyzed to determine whether they influence satisfaction with the devices. For e‐mail and web browsing functions, users’ ratings showed more satisfaction with the iPad1 since it has a larger display; for the e‐book reader function, users indicated higher satisfaction with the Galaxy Tab. Male users evaluated their devices by the function itself, whereas female users were mainly concerned with aesthetic aspects. Koreans indicated that they were less satisfied with their tablets than were other ethnic groups.     

Design and evaluation of visualization support to facilitate association rules modeling

Association rules mining is a popular data mining modeling tool. It discovers interesting associations or correlation relationships among a large set of data items, showing attribute values that occur frequently together in a given dataset. Despite their great potential benefit, current association rules modeling tools are far from optimal. This article studies how visualization techniques can be applied to facilitate the association rules modeling process, particularly what visualization elements should be incorporated and how they can be displayed. Original designs for visualization of rules, integration of data and rule visualizations, and visualization of rule derivation process for supporting interactive visual association rules modeling are proposed in this research. Experimental results indicated that, compared to an automatic association rules modeling process, the proposed interactive visual association rules modeling can significantly improve the effectiveness of modeling, enhance understanding of the applied algorithm, and bring users greater satisfaction with the task. The proposed integration of data and rule visualizations can significantly facilitate understanding rules compared to their nonintegrated counterpart.     

Smart‐Home Interface Design: Layout Organization Adapted to Americans' and Koreans' Cognitive Styles

Increases in the number of household appliances and devices with RFID tags have created a need for efficient organization of smart‐home interfaces in consideration of residents. Previous studies of information‐grouping and cultural‐differences in cognitive style on performance have yielded mixed results. Gender has not typically been considered, nor have subjective preferences been measured. We tested four participant groups (American and Korean males and females) and two interface groupings (functional and spatial). Participants performed tasks that required locating controls for specific devices/functions, after which they rated the interfaces on several scales. American males preferred the functional organization, but Koreans and American females tended to prefer the spatial organization. The results are consistent with Koreans' preference for thematic‐structure and the view that men's and women's cognitive styles differ in masculine/individualistic cultures (U.S.) but not in feminine/collectivistic cultures (Korea). Potential applications include physical (e.g., power and wall‐mounted switches) and virtual interactions (e.g., remote controls, GUI/Web/Phone). © 2012 Wiley Periodicals, Inc.     

A Soft,Fast and Versatile Electrohydraulic Gripper with Capacitive Object Size Detection

Soft robotic grippers achieve increased versatility and reduced complexity through intelligence embodied in their flexible and conformal structures. The most widely used soft grippers are pneumatically driven; they are simple and effective but require bulky air compressors that limit their application space and external sensors or computationally expensive vision systems for pick verification. In this study, a multi-material architecture for self-sensing electrohydraulic bending actuators is presented that enables a new class of highly versatile and reconfigurable soft grippers that are electrically driven and feature capacitive pick verification and object size detection. These electrohydraulic grippers are fast (step input results in finger closure in 50 ms), draw low power (6.5 mW per finger to hold grasp), and can pick a wide variety of objects with simple binary electrical control. Integrated high-voltage driving electronics are presented that greatly increase the application space of the grippers and make them readily compatible with commercially available robotic arms.