Keberkesanan modul infusi kemahiran berfikir aras tinggi pembelajaran luar bilik darjah (iKBAT-PLBD) bagi bidang pembelajaran sukatan dan geometri

Kemahiran berfikir aras tinggi (KBAT) merupakan satu kemahiran berfikir yang sangat diperlukan dalam mendepani cabaran kehidupan masa kini terutama dalam bidang matematik. Oleh itu, kajian ini dijalankan untuk mengkaji sama ada KBAT matematik pelajar dapat ditingkatkan dengan menggunakan modul infusi Kemahiran Berfikir Aras Tinggi - Pembelajaran Luar Bilik Darjah (iKBAT–PLBD) atau tidak? Justeru itu, satu kerangka perancangan telah dibuat terhadap empat kemahiran tertinggi dalam Taksonomi Bloom semakan semula yang juga merupakan konstruk utama dalam KBAT. Konstruk KBAT tersebut ialah konstruk menganlisis, mengaplikasi menilai dan mencipta. Sampel kajian ini melibatkan 120 pelajar tingkatan 1 di empat buah sekolah yang berbeza di negeri Johor. Dalam menjalankan kajian kuasi eksperimental ini, data dikumpul melalui kajian keputusan ujian pra dan ujian pos sebelum dan selepas menggunakan modul bagi kumpulan rawatan. Manakala pendekatan PdP tradisional pula digunakan bagi kumpulan kawalan. Hasil daripada analisis data menunjukkan bahawa aktiviti pembelajaran dan pemudahcaraan (PdPc) yang bertunjangkan modul iKBAT–PLBD telah dapat meningkatkan penguasaan matematik pelajar dalam kempat-empat tahap KBAT serta bagi keseluruhan tahap. Dapatan kajian ini menunjukkan terdapat perbezaan yang signifikasi antara kumpulan kawalan dan kumpulan rawatan terhadap peningkatan KBAT pelajar dalam matematik dengan menggunakan pendekatan iKBAT–PLBD bagi tahap mengaplikasi, menganalisis, menilai, mencipta juga secara keseluruhan. Kesimpulannya, kajian ini dapat memberi manfaat kepada semua pihak termasuk pihak Kementerian Pendidikan Malaysia (KPM), pihak pentadbiran sekolah, ibubapa, guru matematik malah bagi pelajar itu dari segi pengubalan dasar yang berkaitan, pengaplikasian dan sebagai satu bukti keberkesanan dalam proses pemerkasaan KBAT matematik di Malaysia

A systematic review of data quality issues in knowledge discovery tasks

Hay un gran crecimiento en el volumen de datos porque las organizaciones capturan permanentemente la cantidad colectiva de datos para lograr un mejor proceso de toma de decisiones. El desafío mas fundamental es la exploración de los grandes volúmenes de datos y la extracción de conocimiento útil para futuras acciones por medio de tareas para el descubrimiento del conocimiento; sin embargo, muchos datos presentan mala calidad. Presentamos una revisión sistemática de los asuntos de calidad de datos en las áreas del descubrimiento de conocimiento y un estudio de caso aplicado a la enfermedad agrícola conocida como la roya del café.Large volume of data is growing because the organizations are continuously capturing the collective amount of data for better decision-making process. The most fundamental challenge is to explore the large volumes of data and extract useful knowledge for future actions through knowledge discovery tasks, nevertheless many data has poor quality. We presented a systematic review of the data quality issues in knowledge discovery tasks and a case study applied to agricultural disease named coffee rust

Early detection of plant diseases using spectral data

Early detection of crop disease is an essential step in food security. Usually, the detection becomes possible in a stage where disease symptoms are already visible on the aerial part of the plant. However, once the disease has manifested in different parts of the plant, little can be done to salvage the situation. Here, we suggest that the use of visible and near infrared spectral information facilitates disease detection in cassava crops before symptoms can be seen by the human eye. To test this hypothesis, we grow cassava plants in a screen house where they are inoculated with disease viruses. We monitor the plants over time collecting both spectra and plant tissue for wet chemistry analysis. Our results demonstrate that suitably trained classifiers are indeed able to detect cassava diseases. Specifically, we consider Generalized Matrix Relevance Learning Vector Quantization (GMLVQ) applied to original spectra and, alternatively, in combination with dimension reduction by Principal Component Analysis (PCA). We show that successful detection is possible shortly after the infection can be confirmed by wet lab chemistry, several weeks before symptoms manifest on the plants

Um levantamento sobre o processo de representação do conhecimento dos pequenso produtores de banana (Musa spp.) em Mangaratiba, RJ

The banana, the world's most widely produced and commercialized fruit, is grown in all tropical regions of the world, being strongly present in local businesses and subsistence crops serving as an important source of nutrients for the poorest populations. In the state of Rio de Janeiro it is commonly found in hillside and difficult access areas, where most other crops would not be able to settle and, because of this, is grown with inadequate management or insufficient, resulting in low productivity in the areas of Rio de Janeiro. The objective of the present work is to carry out a survey of smallholder information from the Vale do Rio Sahy Association in Mangaratiba, RJ, to enable the representation of knowledge in this domain. From the data collected in this research, it was realized that producers have been engaged in this activity for a long time. However, it was found that the knowledge used to production is extremely tacit, without systematization. The variety of banana species (Musa spp.) grown in the production area of the association's small farmers. The knowledge transfer process knowledge to the knowledge base of an expert system is called knowledge acquisition, where it involves extract all the knowledge from the source of the specialists to systematically represent in a coded form the domain information in an appropriate medium. It was observed, even if preliminarily, that this knowledge are not represented in a database for consultation. Thus, there is a need to define human expertise or producers capable of representing in a technological way data that can be conveniently accessed for Problem solving. In view of the evidence presented in the research, the use of representation of human knowledge (small local producers) to feed and train the system according to the domain presented. Thus, enabling the prototype to help understand climate and soil variables and collaborate in decision making.A banana (Musa spp.), fruta mais produzida e comercializada no mundo, é cultivada em todas as regiões tropicais do mundo, estando fortemente presente no comércio local e nas culturas de subsistência, servindo como importante fonte de nutrientes para as populações mais pobres. No estado do Rio de Janeiro é comumente encontrado em áreas de encostas e de difícil acesso, onde a maioria das outras lavouras não conseguiria se estabelecer e, por isso, é cultivado com manejo inadequado ou insuficiente, resultando em baixa produtividade nas áreas de. Rio de Janeiro. O objetivo do presente trabalho é realizar um levantamento de informações dos produtores rurais da Associação Vale do Rio Sahy em Mangaratiba, RJ, para possibilitar a representação do conhecimento neste domínio. A partir dos dados coletados nesta pesquisa, percebeu-se que os produtores estão engajados nesta atividade há muito tempo. Porém, constatou-se que o conhecimento utilizado para a produção é extremamente tácito, sem sistematização. A variedade de espécies de bananeiras (Musa spp.) Cultivadas na área de produção dos pequenos agricultores da associação. O processo de transferência de conhecimento para a base de conhecimento de um sistema especialista é denominado aquisição de conhecimento, onde envolve extrair todo o conhecimento da fonte dos especialistas para representar sistematicamente de forma codificada as informações do domínio em um meio apropriado. Observou-se, ainda que preliminarmente, que esses conhecimentos não estão representados em um banco de dados para consulta. Assim, existe a necessidade de definir expertise humana ou produtores capazes de representar de forma tecnológica dados que possam ser convenientemente acessados para resolução de problemas. Tendo em vista as evidências apresentadas na pesquisa, o uso da representação do conhecimento humano (pequenos produtores locais) para alimentar e treinar o sistema de acordo com o domínio apresentado. Desta forma, possibilita que o protótipo ajude a entender as variáveis do clima e do solo e colabore na tomada de decisões

Technologie en innovatie in Vlaanderen: Prioriteiten.

Vlaanderen;

Proposal of architecture for IoT solution for monitoring and management of plantations

The world population growth is increasing the demand for food production. Furthermore, the reduction of the workforce in rural areas and the increase in production costs are challenges for food production nowadays. Smart farming is a farm management concept that may use Internet of Things (IoT) to overcome the current challenges of food production This work presents a systematic review of the existing literature on smart farming with IoT. The systematic review reveals an evolution in the way data are processed by IoT solutions in recent years. Traditional approaches mostly used data in a reactive manner. In contrast, recent approaches allowed the use of data to prevent crop problems and to improve the accuracy of crop diagnosis. Based on the finds of the systematic review, this work proposes an architecture of an IoT solution that enables monitoring and management of crops in real time. The proposed architecture allows the usage of big data and machine learning to process the collected data. A prototype is implemented to validate the operation of the proposed architecture and a security risk assessment of the implemented prototype is carried out. The implemented prototype successfully validates the proposed architecture. The architecture presented in this work allows the implementation of IoT solutions in different scenarios of farming, such as indoor and outdoor

Final report on the farmer's aid in plant disease diagnoses

This report is the final report on the FAD project. The FAD project was initiated in september 1985 to test the expert system shell Babylon by developing a prototype crop disease diagnosis system in it. A short overview of the history of the project and the main problems encountered is given in chapter 1. Chapter 2 describes the result of an attempt to integrate JSD with modelling techniques like generalisation and aggregation and chapter 3 concentrates on the method we used to elicit phytopathological knowledge from specialists. Chapter 4 gives the result of knowledge acquisition for the 10 wheat diseases most commonly occurring in the Netherlands. The user interface is described briefly in chapter 5 and chapter 6 gives an overview of the additions to the implementation we made to the version of FAD reported in our second report. Chapter 7, finally, summarises the conclusions of the project and gives recommendations for follow-up projects

Kebolehcapaian nasihat bagi pengurusan penyakit tanaman oleh pekebun kecil lada hitam, Sarawak: Tinjauan awal

Lada hitam (Piper nigrum L.) merupakan salah satu tanaman industri yang mempunyai nilai eksport yang tinggi dan menyumbang kepada pertumbuhan ekonomi di Malaysia khususnya di Sarawak. Kebelakangan ini insiden serangan penyakit terhadap tanaman lada hitam telah merencat pengeluaran produktiviti tanaman ini. Situasi semasa yang dihadapi oleh pekebun kecil yang mampu memberi impak terhadap kualiti dan kuantiti hasil tanaman mereka jarang dilaporkan. Kaedah penasihatan yang kurang efisien, ketidakcukupan pengetahuan dan tempoh masa yang panjang bagi capaian sesuatu nasihat dipercayai boleh memberi kesan kepada aspek ekonomi dan pengurusan penyakit. Oleh itu, satu tinjauan awal telah dilaksanakan untuk mengenalpasti situasi semasa yang merangkumi aspek penasihatan dan penyakit tanaman khususnya bagi tanaman lada hitam daripada perspektif pekebun kecil di kawasan luar bandar. Kaedah penyelidikan ini menggunakan borang senarai semak dan telah diedar kepada pekebun kecil yang mengusaha tanaman lada hitam di kawasan Penempatan Semula Asap Koyan, Belaga yang terletak di Bahagian Kapit, Sarawak. Hasil tinjauan awal ini mendapati pekebun kecil yang mengusaha tanaman lada hitam sering menghadapi masalah tanaman berpenyakit dan turut menghadapi isu kaedah penasihatan yang kurang efisien. Kaedah sistem penasihatan baru yang strategik seperti penggunaan teknologi maklumat perlu diperkenalkan supaya pekebun kecil di kawasan luar bandar boleh memperolehi maklumat dengan pantas bagi menyelesaikan masalah apabila menghadapi insiden serangan penyakit tanaman dan membantu mengurangkan risiko kerugian akibat kemusnahan tanaman

Machine learning based anomaly detection for industry 4.0 systems.

223 p.This thesis studies anomaly detection in industrial systems using technologies from the Fourth Industrial Revolution (4IR), such as the Internet of Things, Artificial Intelligence, 3D Printing, and Augmented Reality. The goal is to provide tools that can be used in real-world scenarios to detect system anomalies, intending to improve production and maintenance processes. The thesis investigates the applicability and implementation of 4IR technology architectures, AI-driven machine learning systems, and advanced visualization tools to support decision-making based on the detection of anomalies. The work covers a range of topics, including the conception of a 4IR system based on a generic architecture, the design of a data acquisition system for analysis and modelling, the creation of ensemble supervised and semi-supervised models for anomaly detection, the detection of anomalies through frequency analysis, and the visualization of associated data using Visual Analytics. The results show that the proposed methodology for integrating anomaly detection systems in new or existing industries is valid and that combining 4IR architectures, ensemble machine learning models, and Visual Analytics tools significantly enhances theanomaly detection processes for industrial systems. Furthermore, the thesis presents a guiding framework for data engineers and end-users