The agricultural sector is one of India's most important and major endeavors, and it is also critical to the country's economic development. Agriculture is one of the most important things that contributes to ...
详细信息
In this paper, we analyze the impact of vaccination on the dynamics of measles transmission using the SEIR mathematical model. We demonstrate that high vaccination coverage significantly reduces disease transmission a...
详细信息
Age-related Macular Degeneration (AMD) is the most common eye disease that causes visual impairment in elder people. Prevalently, AMD is detected by Spectral Domain Optical Coherence Tomography (SD-OCT) for diagnosis ...
详细信息
Detecting plagiarism in documents is a well-established task in natural language processing (NLP). Broadly, plagiarism detection is categorized into two types (1) intrinsic: to check the whole document or all the pass...
详细信息
Detecting plagiarism in documents is a well-established task in natural language processing (NLP). Broadly, plagiarism detection is categorized into two types (1) intrinsic: to check the whole document or all the passages have been written by a single author;(2) extrinsic: where a suspicious document is compared with a given set of source documents to figure out sentences or phrases which appear in both documents. In the pursuit of advancing intrinsic plagiarism detection, this study addresses the critical challenge of intrinsic plagiarism detection in Urdu texts, a language with limited resources for comprehensive language models. Acknowledging the absence of sophisticated large language models (LLMs) tailored for Urdu language, this study explores the application of various machine learning, deep learning, and language models in a novel framework. A set of 43 stylometry features at six granularity levels was meticulously curated, capturing linguistic patterns indicative of plagiarism. The selected models include traditional machine learning approaches such as logistic regression, decision trees, SVM, KNN, Naive Bayes, gradient boosting and voting classifier, deep learning approaches: GRU, BiLSTM, CNN, LSTM, MLP, and large language models: BERT and GPT-2. This research systematically categorizes these features and evaluates their effectiveness, addressing the inherent challenges posed by the limited availability of Urdu-specific language models. Two distinct experiments were conducted to evaluate the impact of the proposed features on classification accuracy. In experiment one, the entire dataset was utilized for classification into intrinsic plagiarized and non-plagiarized documents. Experiment two categorized the dataset into three types based on topics: moral lessons, national celebrities, and national events. Both experiments are thoroughly evaluated through, a fivefold cross-validation analysis. The results show that the random forest classifier achieved an ex
Adam has become one of the most favored optimizers in deep learning problems. Despite its success in practice, numerous mysteries persist regarding its theoretical understanding. In this paper, we study the implicit b...
Due to an increase in agricultural mislabeling and careless handling of non-perishable foods in recent years,consumers have been calling for the food sector to be more *** to information dispersion between divisions a...
详细信息
Due to an increase in agricultural mislabeling and careless handling of non-perishable foods in recent years,consumers have been calling for the food sector to be more *** to information dispersion between divisions and the propensity to record inaccurate data,current traceability solutions typically fail to provide reliable farm-to-fork histories of *** threemost enticing characteristics of blockchain technology are openness,integrity,and traceability,which make it a potentially crucial tool for guaranteeing the integrity and correctness of *** this paper,we suggest a permissioned blockchain system run by organizations,such as regulatory bodies,to promote the origin-tracking of shelf-stable agricultural *** propose a four-tiered architecture,parallel side chains,Zero-Knowledge Proofs(ZKPs),and Interplanetary File Systems(IPFS).These ensure that information about where an item came from is shared,those commercial competitors cannot get to it,those big storage problems are handled,and the system can be scaled to handle many transactions at *** solution maintains the confidentiality of all transaction flows when provenance data is queried utilizing smart contracts and a consumer-grade reliance *** simulation testing using Ethereum Rinkeby and Polygon demonstrates reduced execution time,latency,and throughput overheads.
This research proposes an Intelligent Decision Support System for Ground-Based Air Defense (GBAD) environments, which consist of Defended Assets (DA) on the ground that require protection from enemy aerial threats. A ...
详细信息
This research bridges traditional Kazakh heritage with modern science by developing a machine learning model to classify Kazakh clans using Y-chromosome data. This paper introduces an innovative approach for assigning...
详细信息
This paper presents a comprehensive dataset of pelargonium species that can be used to train classification and recognition models. The provided dataset consists of 1600 images divided by 4 Pelargonium species. The co...
详细信息
Vaccination strategy is crucial in fighting the COVID-19 pandemic. Since the supply is still limited in many countries, contact network-based interventions can be most powerful to set an efficient strategy by identify...
详细信息
暂无评论