Development of a simple sprinkler system designing and pump selection expert system (SSSDPS expert)

In Sri Lanka most of the micro-irrigation systems such as sprinkler irrigation systems are installed with the help of manual based decision making or in many cases without proper designing procedures. These systems do not perform to the expectations. The problems encountered are low water use efficiency due to losses and improper distributions. An expert system with all the design criteria could help non-technical and inexperienced irrigation system installers and farmers. Therefore, this study was done with the objective to develop an expert system for simple sprinkler irrigation system designing and pump selection for efficient water resource use in Sri Lanka. Needed data for the designing, such as crop data, soil data, pump data, pipe data and climatic information were collected from many published reports. Then crop water requirements and irrigation intervals were calculated using standard procedures. Irrigation block selection, lateral pipe selection and main line selection were done through a set of rules and conditional statements. The wxCLIPS was used to represent the knowledge, rules and conditional statements and to develop the Graphical User Interface of the expert system. The developed expert system (Simple Sprinkler System Designing Expert Systems- SSSDPS Expert) can be used easily by interacting with it. The interaction is by just selecting the inputs according to the user’s locality and providing simple information through text windows according to the land area. This system generates very accurate outputs and it is shown in the text window. The user can compare many alternate systems through simple interactions with the expert system as it is not taking much time to generate different designs

Evaluating novice and expert users on handheld video retrieval systems

Content-based video retrieval systems have been widely associated with desktop environments that are largely complex in nature, targeting expert users and often require complex queries. Due to this complexity, interaction with these systems can be a challenge for regular ”novice” users. In recent years, a shift can be observed from this traditional desktop environment to that of handheld devices, which requires a different approach to interacting with the user. In this paper, we evaluate the performance of a handheld content-based video retrieval system on both expert and novice users. We show that with this type of device, a simple and intuitive interface, which incorporates the principles of content-based systems, though hidden from the user, attains the same accuracy for both novice and desktop users when faced with complex information retrieval tasks. We describe an experiment which utilises the Apple iPad as our handheld medium in which both a group of experts and novice users run the interactive experiments from the 2010 TRECVid Known-Item Search task. The results indicate that a carefully defined interface can equalise the performance of both novice and expert users

Natural Language for Expert Systems: Comparisons with Database Systems

Do natural language database systems still provide a valuable environment for further work on natural language processing? Are there other systems which provide the same hard environment for testing, but allow us to explore more interesting natural language questions? In order to answer no to the first question and yes to the second (the position taken by our panel's chair), there must be an interesting language problem which is more naturally studied in some other system than in the database system. We are currently working on natural language for expert systems at Columbia and thus, expert systems provide a natural alternative environment to compare against the database system. The relatively recent success of expert systems in commercial environments (e.g., Stolfo and Vesonder 83, McDermott 81) indicates that they meet the criteria of a hard test environment. In our work, we are particularly interested in developing the ability to generate explanations that are tailored to the user of the system based on the previous discourse in order to do this in an interesting way. We assume that explanation will be part of natural language dialog with the system, allowing the user maximum flexibility in interacting with the system and allowing the system maximum opportunity to provide different explanations

INTELLIGENT INTERFACE AGENT FOR AGRICULTURAL EXPERT SYSTEMS

The acceptance of an expert system by the end user has been regarded as one of the major criteria of expert systems success. Expert systems are characterized by its requirement for heavy and complex interaction with the end user. This paper introduces an approach for interacting with multiple expert system applications through a unified domain-specific intelligent interface agent. The proposed intelligent interface agent communicates with different expert system applications transparently from the end user, and makes the necessary actions when needed. This approach increases the usability of expert system applications and introduces a new methodology for expert systems development using multi-agent systems (MAS). The proposed approach has been applied by the Central Laboratory for Agricultural Expert Systems (CLAES) where two expert system applications – diagnosis and irrigation – have been interfaced by an intelligent interface agent. According to our proposed approach a number of advantages have been accomplished at both practical and theoretical levels

An Experimental Comparison of Speech and DTMF for VoiceXML-Based Expert Systems

Comparisons of DTMF and speech modalities for interacting with diverse dialogue systems for different tasks, among different user populations have led to different design recommendations for different user populations. This paper reports the results of the experimental comparison of these input modalities in a new context of VoiceXML-based diseases diagnosis expert system among a new user population - Nigerians. The results show that DTMF was more satisfying than speech for system satisfaction. Modality wise, speech was more satisfying than DTMF. Speech was also more natural than DTMF. DTMF was preferred by the majority and was more effective and efficient than speech. For diseases diagnosis expert health dialogue systems in Nigeria, DTMF is recommended for effectiveness and efficiency. It is also recommended for satisfaction. Speech is recommended for modality satisfaction while both modalities are recommended for entertainment purpose. Speech is advocated for modality naturalness. However, a platform that incorporates the two modalities will provide the benefits of the two, and allow the users varieties of choices that best suit their need