Decision support for optimised irrigation scheduling

The system, developed under the FLOW-AID (an FP6 project), is a farm level water management system of special value in situations where the water availability and quality is limited. This market-ready precision irrigation management system features new models, hardware and software. The hardware platform delivers a maintenance-free low cost dielectric tensiometer and several low-end irrigation or fertigation controllers for serving different situations. The software includes a complete, web based, Decision Support System (DSS) that consists of an expert planner for farm zoning (MOPECO) and a universal irrigation scheduler, based on crop-water stress models (UNIPI) and water and nutrient uptake calculations. The system, designed also to service greenhouse fertigation and hydroponics, is scalable from one to many zones. It consists of 1) a data gathering tool which uploads agronomic data, from monitored crops around the world, to a central web Data Base (DB), and 2) a web based Decision Support System (DSS). The DSS processes intelligently the data of the crop using Crop Response Models, Nutrient Uptake Models and Water Uptake Models. The central system returns over Internet to the low-end controller a command file containing water scheduling and nutrient supply guideline

Baymax- Your Mental Health Care Companion - An Artificial Intelligence based Chat bot for Mental Health Care

Artificial intelligence (AI) technologies and techniques have useful purposes in every domain of mental health care including clinical decision-making, treatments, assessment, self-care, mental health care management and more. Recent technological innovations are highlighted to demonstrate capabilities and opportunities. This application involves an AI based Expert System which can significantly contribute to improving mental health of an individual to lead a better life without any stress or melancholy. The expert system provides expert advice and therapy to overcome negative thoughts. This app can also help to reduce the number of suicides caused due to extreme depression. It is about virtual human conversation with the system to support user’s interaction within a mental health care context. It provides private online healthcare guidance and support where the app can serve the role of a clinician or a psychotherapist.It uses Smartphone technology particularly relevant for applications in Mental health. Recent advances in artificial intelligence are providing an unprecedented ability of online mental health care research and clinical organizations to collect and analyse data that is broader in scope. This application provides a system capable of calculating the depression level using Fuzzy Logic Controller. It sends an alert message to user’s acquaintance thereby preventing the user from causing harm to himself. It tries to imbibe happy thoughts and optimism into the user. Thus, this system can have a meaningful impact on people’s lives by improving their mental health

Interventions to Reduce Perceived Stress Among Graduate Students: A Systematic Review With Implications for Evidence‐Based Practice

Background: Stress is a part of daily life for graduate students, including graduate nursing students. Contemporary graduate nursing students are facing unprecedented challenges to meet rigorous academic standards as they prepare for their advanced professional role to meet the demands of the nation’s complex and ever-changing healthcare system. Empowering graduate nursing students to ease their perceived stress and minimize undesirable health effects may benefit their capacity to adapt and successfully manage perceived stress in their future healthcare role. Aims: To conduct a systematic review to evaluate the existing evidence with the aim of identifying evidence-based self-care interventions for coping with perceived stress. Methods: We conducted a systematic review, searching CINAHL Plus with Full Text, PsycINFO, and MEDLINE. Inclusion criteria included self-care, graduate students, perceived stress as measured by Perceived Stress Scale, quantitative analysis, conducted within the United States, English language, and peer reviewed. Two authors completed an asynchronous review of the articles, and one expert evidence-based practice mentor and one wellness expert conducted rigorous appraisal of the eight identified studies. Evidence was evaluated and synthesized, and recommendations for practice were determined. Results: Eight studies meeting the criteria for this systematic review were critically appraised. The interventions varied from a stress management course to mind-body-stress-reduction (MBSR) techniques, such as yoga, breath work, meditation, and mindfulness. All studies measured the outcome of stress with the Perceived Stress Scale. Each study demonstrated a reduction in perceived stress post intervention. Linking Evidence to Action: Most effective self-care MBSR interventions include (a) a didactic component, (b) a guided MBSR practice session, and (c) homework. Consideration should be given to a trained or certified MBSR instructor to teach the intervention

Multi-level architecture and human mental activity : connections and feedback during expert system building

We want to point out in this paper how expert knowledge acquisition may induce the choice and the refinement of a software architecture for an expert system and how, in return, this architecture may provide a guide for knowledge acquisition. This idea will be discussed along two axes, through the example of the Rosy multi-ES, designed in the domain of urban road management. First, we show that the first meetings between the expert and the knowledge engineers led us to choose a multi-expert, then a "multi-level multi-expert" architecture for the system, and that this choice improved the phase of knowledge acquisition. Secondly, we stress the close cooperation between knowledge acquisition and modeling, on one side, and the system structure organization, on the other side, until the final state of the system. We have come to the design of a methodology including the concept of constructors for building expert systems and we think that this approach may be generalized to other systems concerned with a similar kind of expertise

Development of an expert system for irrigation and fertilization management in the Pacific Northwest

Recent advances in computer technology have made possible the development of expert systems. Expert systems are computer programs that perform at the level of a human expert. Expert systems can help integrate and apply diverse sources of information and expertise to problems of integrated crop management. A prototype Crop Management eXpert (CMX) system has been developed. The primary goal of CMX is to provide recommendations on optimal irrigation and fertilization scheduling for wheat production in the Pacific Northwest. This system can be used by farmers and/or extension agents. OUS II Shell has been used as a implementation tool. To build this rule - based expert system, a development strategy, commonly used in the construction of expert systems, consisting of 1 ) identification; 2) conceptualization; 3) formalization; 4) implementation; and 5) testing was applied. CMX is composed of modules for irrigation and fertilization management. For irrigation management, CMX is mainly involved in the irrigation scheduling which is the major part of irrigation management. Irrigation strategies have been applied in irrigation decision making. For each strategy, timing criteria which generally consist of management allowed depletion, soil water potential, leaf water potential, and water stress indices have been used. The system provides farmers with irrigation scenarios which determine when and how much water to apply. CMX represents an integration of conventional computing and expert systems technology designed to provide expert recommendations enabling farmers to obtain the best return on their water and fertilizer investment. For fertilization management, a variety of variables have been taken into considered. Crop growth stages, soil moisture, nutrient analysis, protein requirement, and application methods are important factors for the fertilizer decision making. Several constraints have been used in optimal fertilizer advice. CMX can focus only on relevant information, thus reducing the problem space to a manageable size and significantly, improving the efficiency of the system. The facility of the expert system to explain the decision-making process enables users to better understand the underlying assumptions, facts, and reasoning used to generate recommendations. The CMX prototype demonstrates the feasibility of employing expert systems technology in agricultural applications. CMX has been validated and evaluated. The survey results showed that this prototype was successful in capturing domain experts' knowledge as rules and providing advice on the irrigation and fertilization management for wheat

Web-based Implementation of Winter Maintenance Decision Support System Using GIS and Remote Sensing, May 2005

Winter maintenance, particularly snow removal and the stress of snow removal materials on public structures, is an enormous budgetary burden on municipalities and nongovernmental maintenance organizations in cold climates. Lately, geospatial technologies such as remote sensing, geographic information systems (GIS), and decision support tools are roviding a valuable tool for planning snow removal operations. A few researchers recently used geospatial technologies to develop winter maintenance tools. However, most of these winter maintenance tools, while having the potential to address some of these information needs, are not typically placed in the hands of planners and other interested stakeholders. Most tools are not constructed with a nontechnical user in mind and lack an easyto-use, easily understood interface. A major goal of this project was to implement a web-based Winter Maintenance Decision Support System (WMDSS) that enhances the capacity of stakeholders (city/county planners, resource managers, transportation personnel, citizens, and policy makers) to evaluate different procedures for managing snow removal assets optimally. This was accomplished by integrating geospatial analytical techniques (GIS and remote sensing), the existing snow removal asset management system, and webbased spatial decision support systems. The web-based system was implemented using the ESRI ArcIMS ActiveX Connector and related web technologies, such as Active Server Pages, JavaScript, HTML, and XML. The expert knowledge on snow removal procedures is gathered and integrated into the system in the form of encoded business rules using Visual Rule Studio. The system developed not only manages the resources but also provides expert advice to assist complex decision making, such as routing, optimal resource allocation, and monitoring live weather information. This system was developed in collaboration with Black Hawk County, IA, the city of Columbia, MO, and the Iowa Department of transportation. This product was also demonstrated for these agencies to improve the usability and applicability of the system

Recommender Thermometer for Measuring the Preparedness for Flood Resilience Management

A range of various thermometers and similar scales are employed in different human and resilience management activities: Distress Thermometer, Panic Thermometer, Fear Thermometer, fire danger rating, hurricane scales, earthquake scales (Richter Magnitude Scale, Mercalli Scale), Anxiety Thermometer, Help Thermometer, Problem Thermometer, Emotion Thermometer, Depression Thermometer, the Torino scale (assessing asteroid/comet impact prediction), Excessive Heat Watch, etc. Extensive financing of the preparedness for flood resilience management with overheated full-scale resilience management might be compared to someone ill running a fever of 41°C. As the financial crisis hits and resilience management financing cools down it reminds a sick person whose body temperature is too low. The degree indicated by the Recommender Thermometer for Measuring the Preparedness for Flood Resilience Management with a scale between Tmin=34,0° and Tmax=42,0° shows either cool or overheated preparedness for flood resilience management. The formalized presentation of this research shows how changes in the micro, meso and macro environment of resilience management and the extent to which the goals pursued by various interested parties are met cause corresponding changes in the “temperature” of the preparedness for resilience management. Global innovative aspects of the Recommender Thermometer developed by the authors of this paper are, primarily, its capacity to measure the “temperature” of the preparedness for flood resilience management automatically, to compile multiple alternative recommendations (preparedness for floods, including preparing your home for floods, taking precautions against a threat of floods, retrofitting for flood-prone areas, checking your house insurance; preparedness for bushfires, preparedness for cyclones, preparedness for severe storms, preparedness for heat waves, etc.) customised for a specific user, to perform multiple criteria analysis of the recommendations, and to select the ten most rational ones for that user. Across the world, no other system offers these functions yet. The Recommender Thermometer was developed and fine-tuned in the course of the Android (Academic Network for Disaster Resilience to Optimise educational Development) project

Beacons of Excellence in Stress Prevention

NoThis report describes the work of Robertson Cooper Ltd and UMIST to identify good practice in stress prevention and then identify organisations within the UK that could be called beacons of excellence in comparison to this model. Part one of this report summarises and draws conclusions from all of the substantive academic studies on stress prevention over the last decade and uses this information, as well as advice gained from a panel of international experts, to develop a comprehensive stress prevention model. Part two of the report uses this model to describe examples of stress prevention practices that Robertson Cooper Ltd has identified within a wide range of UK organisations. Case studies are presented for each aspect of the good practice model. Examples of real documentation and organisational practice are presented.Health and Safety Executive (HSE