Knowledge and integrated data management model for personalized intercropping in rubber plantation

Selection and allocation of space for intercropping in rubber plantations to maximize yield and minimum costs for individual farmers involves Multi-Criteria Decision Making (MCDM) and several conditions.  The problem is that the information is scattered in many related agencies, there are separate stores and some data is redundant. In addition, the format of the data varies depending on the purpose of the data. The knowledge of selecting plants to grow in the rubber plantation is the tacit knowledge acquired from the experience of successful farmers in rubber plantations and from agricultural experts. Therefore, this research involves an Integrated Ontology-based knowledge and Multi-Objective Optimization model for intercropping Decision Support Systems (DSS). This article presents the knowledge and integrated data management model for developing the Intercropping in Rubber Plantations Ontology by using the Triangulation in the method to verify the accuracy of the data and results.  Moreover, propose ways to create recommendation rules that are easy to rule update and maintenance.  Using an ontology for DSS helps to recommended plants according to the appropriate environment of the farmer area by rule-based inference to represent logical reasoning.  It could also be applied to another domain that requires Intelligent DSS for MCDM

Agricultural information dissemination using ICTs: a review and analysis of information dissemination models in China

Open Access funded by China Agricultural UniversityOver the last three decades, China’s agriculture sector has been transformed from the traditional to modern practice through the effective deployment of Information and Communication Technologies (ICTs). Information processing and dissemination have played a critical role in this transformation process. Many studies in relation to agriculture information services have been conducted in China, but few of them have attempted to provide a comprehensive review and analysis of different information dissemination models and their applications. This paper aims to review and identify the ICT based information dissemination models in China and to share the knowledge and experience in applying emerging ICTs in disseminating agriculture information to farmers and farm communities to improve productivity and economic, social and environmental sustainability. The paper reviews and analyzes the development stages of China’s agricultural information dissemination systems and different mechanisms for agricultural information service development and operations. Seven ICT-based information dissemination models are identified and discussed. Success cases are presented. The findings provide a useful direction for researchers and practitioners in developing future ICT based information dissemination systems. It is hoped that this paper will also help other developing countries to learn from China’s experience and best practice in their endeavor of applying emerging ICTs in agriculture information dissemination and knowledge transfer

Group facilitation skills for participatory decision-making: report of a follow-up outcome evaluation

This working paper reports on an evaluation designed to assess the usefulness of the skills gained during the training course, if the skills learned have been applied and, if so, how the new facilitation tools and techniques have changed meeting processes. The evaluation also identified obstacles to the use of new skills faced by participants, additional follow-on activities that have been conducted by participants, and other related skills that are needed to complement what was learned in the ILAC facilitation course

Smart-Insect Monitoring System Integration and Interaction via AI Cloud Deployment and GPT

The Insect Detection Server was developed to explore the deployment and integration of an Artificial Intelligence model for Computer Vision in the context of insect detection. The model was developed to accurately identify insects from images taken by camera systems installed on farms. The goal is to integrate the model into an easily accessible, cloud-based application that allows farmers to analyze automatically uploaded images containing groups of insects found on their farms. The application returns the bounding boxes and the detected classes of insects whenever an image is captured on-site, enabling farmers to take appropriate actions to address the issue of the insects\u27 presence. To extend the capabilities of the application, the server is linked to a GPT-3.5 API. This will allow users to ask questions about the bugs detected on their farms, creating an online expert -like feature. Python, C++, and Computer Vision libraries were used for the detection model, while the OpenAI API was used for GPT-3.5\u27s integration. By combining these technologies, farmers can more effectively and efficiently manage pests on their farms than current alternatives. This Generative Pre-trained Transformer (GPT) aspect of the project can be leveraged to enable the emulation of agricultural experts for users/farmers. The large language model (LLM) neural network can be fine-tuned using prompt engineering to generate natural language responses to user queries. This will enable farmers to get expert advice and guidance on pest management without having to consult with a human expert. The integration of GPT-3.5 API will also allow the application to provide personalized recommendations based on each farm\u27s specific needs and circumstances. This added feature will give the farmers a more comprehensive and tailored approach to pest management, further increasing the efficiency and effectiveness of their pest control strategies. The significance of this research lies in the development of a practical and accessible tool for farmers to manage pests on their farms. Using Computer Vision and Artificial Intelligence, farmers can quickly and accurately identify insects, leading to more efficient and effective pest management. This could help farmers reduce the use of pesticides and other forms of pest management, leading to improved crop yields and reduced environmental impacts. The potential benefits of this technology extend beyond the agricultural industry, as the techniques used in this research can be applied to a wide range of computer vision and user-facing data analytic applications. For example, the developed techniques could be applied to other fields, such as surveillance, security, and medical imaging

Legal process and economic development : a case study of Indonesia

Westeners often complain that laws are not enforced in developing countries."Good"laws are on the books, but in reality individuals and firms evade them with impunity. For example taxes are uncollected, bankruptcy laws unenforced, environmental controls ignored and trade restrictions evaded. Furthermore, corruption often flourishes in government despite repeated condemnation by public leaders. This paper tries to unravel the nature of legal processes in developing countries and explain how and why they may differ from legal processes in more advanced nations. It identifies three broad functions of a legal system and introduces the central theme of the paper - how risk and information costs affect many of the characteristics of the legal process. Next, it proposes two opposing models, the formal and informal, to illustrate different means by which legal functions can be handled. While these models are presented as contrasting alternatives for purposes of exposition, neither pure prototype exists in practice. Real life is always some mixture of the two, with the balance shifting from country to country. The paper then describes formal and informal legal processes in Indonesia, using the Indonesian tax system as a case study.National Governance,Environmental Economics&Policies,Legal Products,Health Economics&Finance,Insurance&Risk Mitigation

In defense of science—What would John do?

Recent onslaughts on the importance of pure research to our collective well-being are trending. In this essay, I discuss the issues involved and offer a rebuttal. The thoughts are inspired by my mentor, academic sibling, and idol John Leask Lumley