The influence of automation in the agriculture and construction industry plays a vital role development economic backbone any country. factors such as power, torque speed are efficiently controlled by devices using Internet things (IoT). heavy vehicles multi-faced application carrier which is been used construction, agriculture, mining other heavy-duty fields. This research focuses on developing IoT integrated sensor-based obstacle detection system for programmed autonomous will improve...

The disease severity of onion white rot has to be measured carefully and correctly ensure proper agricultural management this crop. It is one the most threatening diseases affecting onions since it caused by fungal organism called Sclerotium cepivourum. This imperative calls for research we introduce, a novel hybrid model combining ability Convolutional Neural Networks (CNN) with explained decision tree (DT). symbiotic integration tries enhance precision classifying intensity fine-tuned...

With the improvement of mobile Internet technology, it has become important to secure medical image information. Conventional techniques for watermarking images face several challenges, particularly concerning degree security provided against attacks, which compromise confidentiality and usability images. To solve these issues, this article presents a novel zero-watermarking algorithm-based approach based on medical-image security. The proposed solution uses Discrete Cosine Transform (DCT)...

This research presents a novel method that uses CNNs and LSTMs to improve nail-related diagnosis accuracy efficiency. We investigate the interface of innovative machine learning medical diagnostics in dermatology, where correct is crucial. aims test our CNN-LSTM model on various nail situations. measured model's evaluate its performance. The scores table demonstrate ability categorize conditions, revealing practical utility. for each state shown table. Staring at values shows significant...

The world's most well-known cryptocurrency, Bitcoin, is much attractive to financial market players due its recent price boom and fall. It very difficult anticipate because of the substantial volatility Bitcoin conversion scale. Forecasting behavior crucial for industry sectors. Some research works have been used machine learning techniques on past trends data predictions but they lack in accuracy. Therefore, aim this paper look into global crypto-currency movement about social media...

Automated navigation is an important feature of any mobile robot and a challenge for to plan the path in unknown environment. We can categorize planning strategy robots two methods, first Classical Methods second Heuristic Methods. In this paper, modified whale optimization algorithm proposed that ensures optimal collision-free path. (WOA) fitness will be calculated by taking consideration target location obstacles search space. Many simulations were run different spaces find at end...

Abstract Glaucoma is an ailment causing permanent vision loss but can be prevented through the early detection. Optic disc to cup ratio one of key factors for glaucoma diagnosis. But accurate segmentation and still a challenge. To mitigate this challenge, effective system optic using deep learning architecture presented in paper. Modified Groundtruth utilized train proposed model. It works as fused marking by multiple experts that helps improving performance system. Extensive computer...

Tea leaf diseases have become a significant problem in the vast field of agricultural research, calling for sophisticated diagnostic methods. This research takes cutting-edge approach, carefully classifying tea illnesses using power Federated Learning combined with Convolutional Neural Networks (CNN). project included records from six customers, each representing four levels illness severity. The eliminated requirement centralized data aggregation by decentralized architecture federated...

Test suite optimization is an ever-demanded approach for regression test cost reduction. Regression testing conducted to identify any adverse effects of maintenance activity on previously working versions the software. It consumes almost seventy percent overall software development lifecycle budget. reduction therefore vital importance. most explored reduce size re-execute. This article focuses as a case selection, which proven N-P hard combinatorial problem. The authors have proposed safe...

The abstract summarizes the important findings & results of this research study, which focuses on categorization various hair conditions with a machine-learning model. Precision, recall, and F1-Score metrics for many illness classes, like Alopecia Areata, Tinea Capitis, Telogen Effluvium, Scarring Alopecia, Trichotillomania, Folliculitis, Head Lice, or Psoriasis, are quite promising. demonstrate model's abilities to reliably categorize diseases, accuracy values fluctuating between 88.04%...

Technological advancements have led to increased confidence in the design of large-scale wireless networks that comprise small energy constraint devices. Despite boost technological advancements, dissipation and fault tolerance are amongst key deciding factors while designing deploying sensor networks. This paper proposes a Fault-tolerant Energy-efficient Hierarchical Clustering Algorithm (FEHCA) for (WSNs), which demonstrates energy-efficient clustering fault-tolerant operation cluster...

The worldwide agricultural sector is vital to feeding the growing population. Crop health and production must be protected for food security. Sustainable agriculture requires timely plant disease identification management. This study examines potato of leaf detection, an important part modern agriculture. They test machine learning deep on a Kaggle dataset leaves, including leaves. aims determine best detection tool. CNN Random Forest are main models. Pooling layers after many convolutional...

Regression testing is a way of catching bugs in new builds and releases to avoid the product risks. Corrective, progressive, retest all selective regression are strategies perform testing. Retesting existing test cases one most reliable approaches but it costly terms time effort. This limitation opened scope optimize cost by selecting only subset that can detect faults optimal paper proposes Pareto based Multi-Objective Harmony Search approach for case selection from an suite achieve some...

The objective of this research is to examine whether a model for classifying things works by giving detailed look at various phases rice leaf impairment. It's vital accurately analyze health if you want maximize harvests and pursue ethical farming. Its efficacy assessed using precision, recall, F1-score metrics stages deficits, from healthy states severe deficits. With total precision 89.20%, the findings show excellent precision. Precision values between 86.12% 91.31% that can categorize...