Design Of Human Computer Interaction Systems Research Articles

Design of Human-Computer Interaction System of Electro-hydraulic Hitch for Hillside Tractors

In view of the complex terrain, low level of mechanization and intelligence in hilly region, a human-computer interaction system was designed for electro-hydraulic hitch control system of tractors in hilly region. According to the actual functional requirements of electro-hydraulic hitch control system of tractors in hilly areas, human-computer interaction interface was designed in flash environment, and CAN communication module in Human-computer interaction system was designed in Flash Develop environment. Finally, a hardware test platform of the human-computer interaction system was built in the room for laboratory tests. The results showed that the human-computer interaction system can meet the working requirements of the electro-hydraulic hitch control system of tractors in hilly areas.

An overview on human-computer interaction

Human-Computer Interaction (HCI) is a multidisciplinary area of research that focuses on computer technology design and, in particular, the interaction between people (users) and computers. The use of computers had always raised the issue of interfacing. The methods by which humans interact with computers have progressed significantly. HCI began with computers and has now grown to include virtually all aspects of information technology design. This paper's goal is to provide a broad overview of the field of Human-Computer Interaction. The fundamental concepts and terminology are covered, as well as a review of current technologies and recent developments in the area, typical architectures used in the design of HCI systems, including unimodal and multimodal configurations, and HCI applications. In addition, this paper provides a complete list of references for each HCI idea, technique, and application.

The influence of context on information processing.

The main research question of this study is how the processing of information relates to different contextual characteristics. More specifically, how the context is associated with efficiency of information processing (success and speed), size of chunks, speed of chunk processing and the recall of a chunk. The research domain was the game of chess. The efficiency of information processing and the chunk characteristics were defined with the reconstruction of sequences of chess moves. Context variables were defined using a slightly adapted chess program. Variables on information dispersion, deviation, complexity and positivity were extracted in each chess position. Overall, the results showed that higher dispersion and complexity and lower positivity of information in a context lead to less efficient information processing. The results support the assumptions of the cognitive load theory about the negative effects of external factors burden on information processing and working memory. Our results also support the ACT-R theory, which suggests that more frequent information has a higher activation level and can therefore be retrieved more easily and quickly. The results are also congruent with the positivity effect, which proposes that it is easier to remember positive information than negative information. The findings of our study can be beneficial for the development of intelligent tutoring systems and the design of human-computer interaction systems.

Large-Screen Interactive Imaging System with Switching Federated Filter Method Based on 3D Sensor

Large-screen human-computer interaction technology is reflected in all aspects of daily life. The dynamic gesture tracking algorithm commonly used in recent large-screen interactive technologies demonstrates compelling results but suffers from accuracy and real-time problems. This paper systematically addresses these issues by a switching federated filter method that combines particle filtering and Mean Shifting algorithms based on a 3D sensor. Compared with several algorithms, the results show that the one-hand and two-hand large-screen gesture tracking based on the switched federated filtering algorithm work well, and there is no tracking failure and loss of target. Therefore, the switching federated tracking positioning algorithm can be well applied to the design of human-computer interaction system and provide new ideas for future human-computer interaction.

Promoting college student’s learning motivation and creativity through a STEM interdisciplinary PBL human-computer interaction system design and development course

In recent years, STEM (Science, Technology, Engineering, and Mathematics) has been extensively advocated and implemented in education, as it is suggested to be very impactful on student’s interdisciplinary learning, which can be seen as a significant driving force for a country’s advancement in scientific and technical knowledge, innovation, economy, and international competitiveness. Developing a human-computer interaction (HCI) system to solve real-world problems requires the inventors to have interdisciplinary STEM knowledge and skills. Thus a STEM Interdisciplinary Project-based Learning (IPBL) approach was applied to teach a total number of 45 college students registered in the departments of engineering and design. Inspired by Design Thinking, the 18-week STEM IPBL course was delivered through four phases, including discover, define, develop, and deliver. All the finished HCI projects applied the interdisciplinary knowledge and skills from the domains of STEM. Evidence drawn from the 6-point Likert ‘Motivated Strategies for Learning Questionnaire (MSLQ)’ indicated that the STEM IPBL course was very impactful on student’s learning, which improved the participants’ (a) overall learning motivation (Pre M = 4.4, Post M = 4.64; p = .012), (b) self-efficacy of learning (Pre M = 4.03, Post M = 4.43; p = .003), (c) enjoyableness of learning STEM (Pre M = 4.68, Post M = 4.75; p = .556), and (d) recognizing the significance of learning STEM on future career development (Pre M = 4.73, Post M = 4.94; p = .077). It is also found that compared with design majored students, the course had a better effect on the engineering majored students. Evidence collected from ‘Abbreviated Torrance Test for Adults (ATTA)’ indicated that the student’s overall creativity was significantly improved (Pre M = 63.36, Post M = 68.44; p = .000). More specifically, among the four facets of creativity, the improvements were as follows: fluency (Pre M = 14.89, Post M = 16.2; p = .001), elaboration (Pre M = 16.69, Post M = 18.62; p = .000), flexibility (Pre M = 14.82, Post M = 16.04; p = .009), and originality (Pre M = 16.96, Post M = 17.58; p = .136). It is found that the STEM IPBL course had a different impact on the student's originality, while the originality of engineering majored students significantly improved (p = .006), the originality of design majored students did not change. Some educational implications were also provided in the article.

Categorisation of visualisation methods to support the design of Human-Computer Interaction Systems

During the design of Human-Computer Interaction (HCI) systems, the creation of visual artefacts forms an important part of design. On one hand producing a visual artefact has a number of advantages: it helps designers to externalise their thought and acts as a common language between different stakeholders. On the other hand, if an inappropriate visualisation method is employed it could hinder the design process. To support the design of HCI systems, this paper reviews the categorisation of visualisation methods used in HCI. A keyword search is conducted to identify a) current HCI design methods, b) approaches of selecting these methods. The resulting design methods are filtered to create a list of just visualisation methods. These are then categorised using the approaches identified in (b). As a result 23 HCI visualisation methods are identified and categorised in 5 selection approaches (The Recipient, Primary Purpose, Visual Archetype, Interaction Type, and The Design Process).

Portable tongue-supported human computer interaction system design and implementation.

Tongue supported human-computer interaction (TSHCI) systems can help critically ill patients interact with both computers and people. These systems can be particularly useful for patients suffering injuries above C7 on their spinal vertebrae. Despite recent successes in their application, several limitations restrict performance of existing TSHCI systems and discourage their use in real life situations. This paper proposes a low-cost, less-intrusive, portable and easy to use design for implementing a TSHCI system. Two applications of the proposed system are reported. Design considerations and performance of the proposed system are also presented.

AN SVM-BASED INCREMENTAL LEARNING ALGORITHM FOR USER ADAPTATION OF SKETCH RECOGNITION

User adaptation is a critical problem in the design of human-computer interaction systems. Many pattern recognition problems, such as handwriting/sketching recognition and speech recognition, are user dependent, since different users' handwritings, drawing styles, and accents are different. Therefore, the classifiers for these problems should provide the functionality of user adaptation so as to let each particular user experience better recognition accuracy according to his input habit/style. However, the user adaptation functionality requires the classifiers to have the incremental learning ability, by which the classifiers can adapt to the user quickly without too much computation cost. In this paper, an SVM-based incremental learning algorithm is presented to solve this problem for sketch recognition. Our algorithm utilizes only the support vectors instead of all the historical samples, and selects some important samples from all newly added samples as training data. The importance of a sample is measured according to its distance to the hyper-plane of the SVM classifier. Theoretical analysis, experimentation, and evaluation of our algorithm in our online graphics recognition system SmartSketchpad, are presented to show the effectiveness of this algorithm. According to our experiments, this algorithm can reduce both the training time and the required storage space for the training dataset to a large extent with very little loss of precision.