AGRO-GUARD:Machine Learning-Driven Plant Real-Time Disease Detection,Clustering and Community Notifications
Agro-guard aims to revolutionize disease identification and community-based projects in the field of agriculture. Integrating Machine learning, Computer vision, clustering, and community-based technology, this project helped farmers to detect their plant disease with their solution and for early warning of plant disease which was spreading in their community which helped in crop management. The research project is divided into three parts.First,Integrating Machine learning to detect and classify plant disease with their solutions.Second,Integrating Density-Based Spatial Clustering of Applications with Noise (DBSCAN),to identify disease and analyze the pattern within agricultural regions.Third,Establishing notification system to notify real-time alerts to farmers about disease spreading in particular region.The research is crucial because it solve one of the crucial problem of our community which is untimely detection of disease.The finding of the research highlight the effectiveness of Agro-Guard framework in early disease detection and community detection.The machine learning models achieved high accuracy in identifying common plant disease and clustering results the pattern in diseases that were very important for notifying the community.The significance of these findings is that it can build powerful system which will overall grow the production of crops and plants due to timely update of the disease prevailing in the community.It contributes in sustainability production of crops and plants which ultimately ensure the good livelihood of farmer.
Automatic Solar Panel Sprinkler Irrigation System
As the global demand for sustainable agriculture practices and renewable energy sources continues to rise, the integration of solar power technology with irrigation systems has gained significant attention. This abstract presents an overview of an innovative solution known as the "Automatic Solar Panel Sprinkler Irrigation System," which combines solar panels and smart irrigation technology to efficiently manage water resources in agricultural settings. The proposed system leverages solar panels to generate electricity and simultaneously operate an automated sprinkler irrigation system. Solar panels are strategically positioned in proximity to crop fields, utilizing photovoltaic cells to convert solar energy into electrical power. This energy is then harnessed to power the irrigation system, providing a sustainable and eco-friendly method for crop hydration. In Solar Power Generation the system consists of photovoltaic panels designed to capture solar energy during daylight. This renewable energy source is converted into electrical power, which is stored in batteries for subsequent use. Automated Sprinkler Irrigation is an advanced control system manages the irrigation process, ensuring efficient water distribution based on crop requirements. Soil moisture sensors and weather data are integrated to optimize irrigation scheduling. In Remote Monitoring and Control, farmers can remotely monitor and control the irrigation system through a user friendly interface, accessible via smartphones or computers. This feature enables real-time adjustments and ensures that water resources are utilized optimally. In Water Conservation the system is designed to minimize water wastage by delivering precise and targeted irrigation, reducing over-watering and the associated environmental impact. In Cost Savings the harnessing solar power, this system reduces electricity expenses, making it an economically viable solution for farmers, particularly in regions with ample sunlight. Using a tracker with an automatic solar panel sprinkler irrigation system can be a smart and efficient way to optimize the system's performance. And the most important thing is that in my prototype it is under the panel and will track the location of the Sun and with that it will lead to the Automatic movement of the panel from east to west and when the evening starts it will go back to its position.
Sport specific assessment of inter-limb asymmetries: A way to reduce injuries
In recent years, lower inter-limb asymmetries have become a topic of increasing interest in sports research. Numerous studies have investigated the occurrence of between-limb differences in a variety of physical tests, ranging from strength, sprinting, and change of direction speed to jumping tasks. The main focus has been the association of asymmetries to either enhanced injury risk or reduced physical performance. Sport specific aspects and differences of lower limb asymmetries have not often been analysed. Additionally, most studies have been performed with male athletes. Women, however, present higher prevalence of lower limb asymmetries in strength, coordination, and postural control than men. These two aspects were therefore addressed in the present study. Female youth soccer (n=18, age: 16.7 ± 0.8 years) and floorball (n=18, age: 17.6 ± 0.9 years) players completed a test battery consisting of six unilateral jumping tasks in horizontal and lateral direction to detect sport specificity in inter-limb asymmetries. The test comprised the following hops: (1) Single Leg Hop for Distance and (2) a newly created version of it, (3) Single Leg Triple Hop, (4) Single Leg Crossover Hop, (5) Side Hop and (6) Single Leg 6-meters Timed Hop. The scores of every jump were calculated into Limb Symmetry Indexes for each participant. A linear mixed effect (LME) model (using function lmer in program R) was applied to evaluate the effects of sport and jump type on asymmetries. In terms of the whole test battery, there was a significantly higher magnitude of asymmetries in soccer compared to floorball (p=0.0067) with a mean difference of 1.9%. Three significant differences between the effects of different jump types were detected (5>2: p=0.027; 5>3: p6: p=0.014). Moreover, the results showed no significant effect on leg dominance. According to the findings of this study, soccer appears to be more asymmetric than floorball, leading to the suggestion that inter-limb asymmetries may not only be task-specific, but also sportspecific. Since no significant correlations were detected, this study suggests that inter-limb asymmetries are independent of leg dominance. Considering the possible reduction in athletic performance and increasing injury risk, strength and conditioning coaches are advised to assess athletes' inter-limb asymmetries using a broad, sport specific test battery and decrease them.
Non-invasive study of the electrical activity of the brain of various chordate animals
In clinical practice, EEG is used to diagnose a number of neurological diseases and to diagnose epilepsy. But at present, the question of the nature of EEG has not been completely resolved and is of great scientific interest. There have been no studies at all on the non-invasive study of the electrical activity of the brain of the shark superorder, which belongs to the class of cartilaginous fish. By studying the electrical activity of the brain of various gnathostomes, it is possible to obtain an answer to the question of the emergence of rhythms from the point of view of phylogenesis and evolution, and by comparing their EEG with the human EEG, one can identify similar patterns that help in the study of reactions to various influences. During the work, for the first time, EEG indicators of spotted cat sharks, ECG, heart rate and respiratory rate of cat sharks and toads were obtained. In the future, it is planned to assemble a smaller neuroheadset for non-invasive studies of the electrical activity of the brain of small animals (sharks, toads, monitor lizards). This data can be used for evolutionary and medical research. *No animals were harmed during or after the experiments.
AI時光機-利用照片轉換技術重溫在地歷史
目前網路上流傳許多使用人工智慧修復照片的網站或應用軟體。然而,由於這些訓練資料多數來自國外,導致修復中式建築照片的效果欠佳。此外,許多老舊照片因氧化、潮濕而泛黃,使得修復程序比起修復純黑白相片更加困難。因此,本研究旨在建🖂一個專門修復中式建築物的機器學習模型,主要分為以下三個部分:首先,使用機器學習模型對老舊照片進行修復,包括著色、去模糊化和降噪;其次,分析使用不同比例之有色調照片(模擬泛黃照片)訓練模型的效果;最後,研究不同的修復順序(著色、去模糊化、降噪)和模型執行次數對照片修復效果的影響,發現「著色、去噪、去模糊化」的順序修復效果最佳。此外，許多老舊照片因為受損等原因，只剩下極少的特徵，因此本研究採用機器學習模型，以延伸重建原始照片。透過這種方法，我們能夠重新建構當時建築物周圍可能的場景和情境。
Breaking a Caesar Cipher / Vigenère Cipher Encryption for Secure Data Communication
This project had one purpose: creating almost unbreakable encryption by breaking a Caesar – and Vigenère Cipher and getting familiar with how they work. Created a program to encrypt and decrypt messages with a Caesar Cipher and Vigenère Cipher encryption. Breaking these encryptions in these programs will help to identify the factors that contribute to strong and weak encryption systems. A program was created to encrypt messages using Caesar Cipher with a key from 1 to 25 and decrypt messages without knowing the original key by doing different types of “attacks” on the system: a brute force and frequency analysis attack. Created another program to encrypt messages using Vigenère Cipher with a keyword or keyphrase and decrypted messages whilst knowing that original keyword. Tested and compared the two different cyphers when being attacked. This helped identify factors that influenced the strength of encryption and identified the advantages and disadvantages of each Cipher as well as the weaknesses in each attack. Through testing and breaking a Caesar and Vigenère Cipher successfully, multiple factors were identified that influenced the strength of the encryption system. These were used to ensure the new encryption created will be as strong as can be. Comparing the success rate of the different attacks on each Cipher, the similarities, weaknesses and strengths in the Brute Force and Frequency Analysis attacks were found.