Human Being Emotion in Cognitive Intelligent Robotic Control Pt I: Quantum / Soft Computing Approach

Intelligent Control and Cognitive Control for a global coherence and sustainable economic growth for the humankind.

This work presents the solution based on the augmenting sequence of linear programming problems (LPP) as a tool for intellectualizing home environment. The proposed solution empowers the intelligent decision making procedure which can be applied to various intelligent control applications. The augmenting self-training procedure based on LPP approach is presented as well, which allows making reasonable decisions having only limited data about the controlled environment. The method permits retraining the decision making system when new data is available. As a proof of concept, this solution is applied to intelligent light control application. The obtained simulation results show the method’s capability in making reasonable decisions according to users preferences. DOI: http://dx.doi.org/10.5755/j01.itc.44.2.10235

The service sector is an important and consistently growing sector of the world economy. It is estimated that the sector will make up two thirds of the total world Gross Domestic Product (GDP). Information Technology (IT) has been an important contributor to the fast and high grow of the sector by increasingly digitising the production, delivery and use of services. IT has enabled multiple parties, including user support service staff, employees (internal IT users) and customers (external IT users) of an organisation, to engage in the production, delivery and use of digital services. Consequently, both users and user support service staff of the organisations have an increased responsibility to both prevent IT problems from occurring, and solve them when they do occur. Problems with ITs can occur at different stages of a digital service value chain (i.e. sequential steps/stages required to produce and deliver a digital service), and may lead to a service failure in the user’s mind. Examples include problems with a self-check-out machine at a library, problems with an online registration system that occurs for university students, or a website that does not include an online payment functionality a user expects. Numerous studies in both Information Systems (IS) and service literature have focused on the role of the service staff in both preventing and solving digital service failures, but few have considered the user’s role in these. This thesis includes four original articles. The first article emphasises that prevention from digital service failures must be considered before establishing effective approaches to solving the problems. The article presents a typology of technologies and technological approaches that customers and businesses can use to support prevention from these failures. The rest of the articles consider situations where an IT-related service problem has occurred, and address the user’s behaviour of persistence in solving their own IT problem. From the user’s perspective, their persistence in solving the problem contributes to achieving a satisfactory outcome, and from the organisational perspective, such an outcome is important for maintaining their user satisfaction. User persistence is important both when trying to solve an IT problem alone, and when using support services. Studying user persistence can help organisations to design their user support services in a way that encourages user persistence, resolves the problems more efficiently and cheaply; and maintains their user satisfaction. The study of user persistence included the use of focus groups for data collection purposes. Surprisingly, qualitative methodology literature has little to say on analytical approaches to focus group data – particularly interactive participant data. Therefore, a focus group analysis framework was designed (presented in the second article) and was used in the analysis phase of the user persistence study. The third article uses the framework in its analysis phase, and (a) presents a conceptual clarification of user persistence in IT problem solving, (b) identifies the factors that contribute to user persistence, (c) develops a theory to explain that why a user decides to persist with a method of solving IT problems, and (d) develops a theory to explain that why the user decides to persist with the overall process (collective methods) of solving the problem. The fourth article presents the results of evaluating the robustness of the two theories and shows that the two theories are confirmed. The thesis concludes with the ‘contributions and conclusion’ chapter where it presents a summary of the contributions of the four articles to IS theory, methodology and practice.

Bare-bones languages serve small systems with ease: Cushmann, R HEDN Vol 25 No 16 (5 September 1980) pp 171–177

Considering different types of time-varying lag system, control strategy is determined by recognition of transient characteristics of responses and cooperation with expert system, forming the basic idea of intelligent controller design. Based on the dynamic response mode of the controlled object, multi-control mode was applied in control law, which can solve the oscillation problems appeared in common control system during pure lag link and improve the robustness of the control system. The application of intelligent temperature controller based on the pattern recognition in the same category of controlled objects requires no specific parameters and mathematical model of the controlled objects, but can bring a stable increase of manipulated variable, quick response, small overshoot, and no steady-state error, enabling it appropriate for different types of controlled objects and achieving perfect control effect.

Although many studies have reported higher rates of trauma exposure and posttraumatic stress disorder (PTSD) among persons with severe mental illness, the screening, diagnosis, and treatment of PTSD in public mental health centers remain at a suboptimal level and PTSD is often overlooked and untreated. This study used routine PTSD screening and service use data in electronic medical records to determine the association of PTSD, psychiatric symptoms, and service use in a sample of individuals with serious mental illness in a community-based treatment setting. The sample included 1,834 active clients between January 2007 and November 2010 who were screened for PTSD and who completed the 24-item Behavior and Symptom Identification Scale (BASIS-24). Service data included services provided a year before and a year after the screening date. PTSD was associated with more severe psychiatric symptoms and increased no-show rates but not with increased service use or use of high-intensity services. PTSD likelihood interacted with race in accounting for elevated scores among African Americans on the psychosis domain of the BASIS-24. PTSD screening is feasible and recommended in service environments and may contribute significantly to better understanding of racial-ethnic and other differences in service use and diagnostic practices.

The operational environments of engineering systems are becoming increasingly complex and require automatic control systems to be more intelligent. Cognitive control extends the domain of intelligent control, whereby cognitive science theories are applied to guide the design of automatic control systems to make them conform to the human cognition paradigm and behave like a real person, hence improving physical systems performance. Cognitive control has been investigated in several fields, but a comprehensive review covering all these fields has yet to be provided in any paper. This paper first presents a review of cognitive control development and related works. Then, the relationship between cognitive control and cognitive science is analyzed, based on which the definition and framework of cognitive control are summarized from the perspective of automation and control. Cognitive control is then compared with similar concepts, such as cognitive radio and cognitive radar, and similar control methods, such as intelligent control, robust control, and adaptive control. Finally, the main issues, research directions, and development prospects are discussed. We expect that this paper will contribute to the development of cognitive control.

After more than 30 years of development, the precise treatment technology of orthopedic surgical robot has changed the traditional orthopedic treatment methods and attracted worldwide attention. Orthopedic robotic navigation surgery is the result of multidisciplinary combination integrating computer, industrial automation, intelligent control, electronic information, ergonomics and medical technologies, so as to provide intelligent, minimally invasive and precise navigation technology for clinic surgery and high-quality service for patients. Throughout the development of orthopedic surgical robot at home and abroad, thanks to the progress of software design and automation technology as well as the improvement of accuracy and flexibility of manipulators, robots can perform more complex operations than existing surgical navigation technologies. This paper briefly reviews the history, navigation principles, types, clinical application and shortcomings, and the future development trend, hoping to provide reference for the research of robotic navigation surgery. Key words: Robotics; Surgical procedures, operative; Artificial intelligence; Navigation

The application of conventional and intelligent control paradigms to the dispensing of adhesive in the manufacture of mixed technology printed circuit boards, a real process with real time constraints and error conditions, is outlined in this paper. A description of the process and its various operation and error states is followed by a brief discussion of the application of conventional (system identification and incremental proportional control) and intelligent (knowledge-based, fuzzy logic and neural network) controllers to the system. Comments on the control and timing performance of each paradigm are given.

In view of the characteristics of the electrohydraulic servo system, a man-simulated intelligent controller is designed so as to improve the system static precision and dynamic characteristic by application of intelligent control theory in this paper. The results of the emulation and experiment indicate that this controller has good control.

Intelligent control techniques are suited for problems that are either difficult to tackle mathematically or where the use of these techniques provides improved performance, easier implementation, or faster time to market. The authors present some industrial applications of fuzzy logic and neural networks at Rockwell, comprising motor control, autopilot level change control, aircraft autothrottle control, aircraft gain schedule generation, sensor diagnostics, and control of color printing. The authors discuss the driving factors for using fuzzy and neural approaches in these applications and the benefits derived. The authors also comment on how to select the right application of intelligent control techniques to derive maximum commercial payoff.

Expert System Approach of Industrial Process Adaptive Control

In intelligent control applications, neural models and controllers are usually designed by performing an off-line training, and then adapting it online when placed in the operating environment. It is therefore of crucial importance to obtain a good off-line model by means of a good off-line training algorithm. In the paper a method is presented that fully exploits the linear-nonlinear structure found in radial basis function networks, being additionally applicable to other feedforward supervised neural networks. The new algorithm is compared with two known hybrid methods.

This paper presents a type of solar thermal power plant and also studies the efficiency of the common type of this distributed generation resource. In order to improve the efficiency of the power station, several techniques are studied such as the combined cycle plant, the thermoelectric generator and the intelligent control application. The thermodynamic analysis of the power plant and the performance of the equipment with an intelligent control system are validated by the developed experimental prototype.

A convolutional neural network (CNN) was designed and built on an embedded building lighting control system to determine whether the application of CNN could increase the accuracy of image recognition and reduce energy consumption. Currently, lighting control systems rely mainly on information technology, with sensors to detect people’s existence or absence in an environment. However, due to the deviation of this perception, the accuracy of image detection is not high. In order to validate the effectiveness of the new system based on CNN, an experiment was designed and operated. The importance of the research lies in the fact that high image detection would bring in less energy consumption. The result of the experiment indicated that, when comparing the actual position with the positioning position, the difference was between 0.01 to 0.20 m, indicating that the image recognition accuracy of the CNN-based embedded control system was very high. Moreover, comparing the luminous flux of the designed system with natural light and the designed system without natural light with the system without intelligent control, the energy savings is about 40%.