Web GIS to support irrigation management: a prototype for SAGRA network, Alentejo Portugal

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesAn efficient water management, not only allows significant savings in costs of irrigation, but also an effective control on the quality of products, which can have obvious consequences on income operation and reducing the environmental impact of irrigation. As the Internet is becoming the easiest way of information distribution, irrigation management system can also be benefitted with it. Integrating GIS functionality with internet capacity will redefine the way of decision making, sharing and processing of information. In irrigation systems weather plays an imperative role in decision making, implementing and forecasting. Temperature, humidity, precipitation, and solar radiation are the most important parameters to calculate evapotranspiration by which crop water requirement can be determined. SAGRA (Sistema Agrometeorológico para a Gestão da Rega no Alentejo) network is providing information to the farmers through web but still lacks the use of GIS in their information to decision support system. Irrigation management support system can be benefitted with the use of Web GIS. In this thesis, web based GIS is designed using popular open source tools and software. Using data from automatic weather station maps are produced using Geo-statistical interpolation techniques and published in web map. These maps can be viewed with popular online maps like Google maps, Microsoft Bing and Openstreet maps. Animated weather maps are also created which are useful for visualizing changing pattern of weather parameters and water requirement over time

Integrated spatial decision support system for precision agriculture

Excessive application of plant nutrients and pesticides on agricultural land has resulted in both environmental degradation and economic loss to the farming community. Agricultural non-point source pollution was cited as the primary source of the water quality problems in many areas of the United States. Environmental concerns resulting from agricultural non-point source pollution has placed demands on farmers and ranchers to implement the best management practices (BMPs) to reduce the delivery of pollutants to streams and aquifers. Precision agriculture, a relatively recent crop production and agricultural management strategy holds great promise to minimize environmental pollution while to maximize economic productivity and profitability. It has benefited from rapidly evolving geospatial information technologies, such as global positing systems (GPS), geographic information systems (GIS), remote sensing (RS), and electronic sensors and intelligent controllers. However, the complexity of making routine, coherent, and cost-effective farm management decisions presents a formidable challenge to farmers. What is lacking in precision agriculture is an analytical tool that integrates these component technologies with biophysical and economic models for tactical, strategic, and policy-level decision make. In this dissertation, a decision support system called IDSSPA is developed to include modules for evaluating crop yield and chemical losses in response to site-specific management of agricultural inputs. Using this system, not only can users store, visualize, manipulate, and analyze spatial/non-spatial field experiment data, but they also can do various simulations through the easy-operated biophysical models, which take field spatial variability into account. In the system, the functionalities of the traditional models and analysis methods have been enhanced by coupling them with each other and with ArcView GIS. Uniquely designed GIS-based interfaces enable the lumped biophysical models to incorporate and represent field spatial variability. Statistical and data mining tools are also included in the system to improve analysis of field measured data and to further enhance interpretation of model simulation results. Other components incorporated into the system are as follows: The CERES-Maize plant growth model seamlessly integrated with RZWQM to provide an alternative phonologically based model for predicting growth and yield of maize (corn), and several tools for evaluating economic and ecologic risks of precision agriculture implementation. The application examples indicated that IDSSPA is a useful research and decision make tool for precision agriculture at field and watershed scales

Systematic approach to providing intelligent decision support whilst digital transformation of management processes in agro-industrial complex

Modern economic conditions, characterized by digitalization processes and the influence of geopolitical factors contributing to the development of domestic information technologies have made the issue of providing support for management decision-making by specialized systems important. In this regard, the purpose of the study is to analyze the logistics of information flows and identify problems associated with the digital transformation of management processes in the agro-industrial complex (AIC). A systematic approach was chosen as the main method. The logical analysis and synthesis were used as well. Based on the identified movements and interrelations of information flows, and limiting factors for its effective use, an automated information and analytical decision support system (AIASDSS) is proposed in the context of a unified digital platform. Its components are described and principles of operation are formulated. In the focus is the creation of an information platform module oriented mainly on agricultural producers who occupy a central place in the agro-industrial complex. It is noted that work is underway to ensure the intellectualization of decision-making processes in agricultural organizations through the use of mathematical, statistical and information tools. Particular solutions are given. The research materials are addressed to authorities and can be used in managing agricultural production

Implementation of TeamSTEPPS

This scholarly project focused on implementing Team Strategies and Tools to Enhance Performance and Patient Safety (TeamSTEPPS) in an emergency room (ER). The aim of TeamSTEPPS is to improve patient outcomes by educating healthcare professionals on communication and teamwork skills. TeamSTEPPS teaches healthcare professionals leadership skills, shared mental models, mutual trust, and closed loop communication. The purpose of the scholarly project was to improve teamwork and communication. The study method was descriptive analysis of 51 pre and posttest questionnaires, specifically looking for increased knowledge of TeamSTEPPS tools. The participants included: ER physicians, ER nurses, ER certified nursing assistants/health unit coordinators, a pharmacy technician, public safety officers, and patient revenue management organization (PRMO). Further research is needed to evaluate how to significantly increase staff knowledge on TeamSTEPPS tools in a class setting

Meja kopi modular untuk rumah minimalis moden

Peningkatan populasi di seluruh dunia adalah sangat tinggi. Di Malaysia, kadar pertumbuhan populasi rakyat Malaysia meningkat kepada 1.1% iaitu sebanyak 32.4 bilion (2018) berbanding 31.1 bilion (2015) (Mahidin, 2019). Peningkatan populasi ini meningkatkan permintaan dan bekalan terhadap keperluan asasi seperti makanan, pakaian, peluang pekerjaan dan juga ruang kediaman. Ini turut mempengaruhi reka bentuk dan saiz kediaman bagi menempatkan kesemua rakyat Malaysia dan juga pekerja asing yang berkerja di negara ini. Menurut Harian Metro Online, tanah yang semakin berkurangan menyebabkan unit kediaman sekarang banyak dibina dengan keluasan yang terhad antara 650 hingga 800 kaki persegi (Satibi, 2018). Justeru, pemilihan perabot memainkan peranan penting dalam usaha untuk menampakkan kediaman lebih luas dan selesa (Ismail, 2020)

Electronic fraud detection in the U.S. Medicaid Healthcare Program: lessons learned from other industries

It is estimated that between $600 and$850 billion annually is lost to fraud, waste, and abuse in the US healthcare system,with $125 to$175 billion of this due to fraudulent activity (Kelley 2009). Medicaid, a state-run, federally-matchedgovernment program which accounts for roughly one-quarter of all healthcare expenses in the US, has been particularlysusceptible targets for fraud in recent years. With escalating overall healthcare costs, payers, especially government-runprograms, must seek savings throughout the system to maintain reasonable quality of care standards. As such, the need foreffective fraud detection and prevention is critical. Electronic fraud detection systems are widely used in the insurance,telecommunications, and financial sectors. What lessons can be learned from these efforts and applied to improve frauddetection in the Medicaid health care program? In this paper, we conduct a systematic literature study to analyze theapplicability of existing electronic fraud detection techniques in similar industries to the US Medicaid program

How can SMEs benefit from big data? Challenges and a path forward

Big data is big news, and large companies in all sectors are making significant advances in their customer relations, product selection and development and consequent profitability through using this valuable commodity. Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. In Europe, SMEs are a vital part of the economy, and the challenges they encounter need to be addressed as a matter of urgency. This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities. The paper proposes a big data maturity model for SMEs as a first step towards an SME roadmap to data analytics. It considers the ‘state-of-the-art’ of IT with respect to usability and usefulness for SMEs and discusses how SMEs can overcome the barriers preventing them from adopting existing solutions. The paper then considers management perspectives and the role of maturity models in enhancing and structuring the adoption of data analytics in an organisation. The history of total quality management is reviewed to inform the core aspects of implanting a new paradigm. The paper concludes with recommendations to help SMEs develop their big data capability and enable them to continue as the engines of European industrial and business success. Copyright © 2016 John Wiley & Sons, Ltd.Peer ReviewedPostprint (author's final draft