Federated Learning (FL) is increasingly vulnerable to model poisoning attacks, where malicious clients degrade the global model's accuracy with manipulated updates. Unfortunately, most existing defenses struggle to handle the scenarios when multiple ...

Computing the distance between two non-normalized vectors x and y, represented by Δ (x, y) and comparing it to a predefined public threshold τ is an essential functionality used in privacy-sensitive applications such as biometric authentication, ...

In response to the lack of relevant high-quality Q&A (question and answer) datasets in some specific domain Q&A systems, this paper proposes a large language model Q&A Method based on specific domain regulation documents. The paper adopts natural ...

Cosine-similarity is the cosine of the angle between two vectors, or equivalently the dot product between their normalizations. A popular application is to quantify semantic similarity between high-dimensional objects by applying cosine-similarity to a ...

As undergraduate enrollment in computer science rises, instructors continue to investigate methods to improve the student experience at scale. One aspect commonly used in courses at scale is queue-driven office hours, in which students join an online ...

Aiming to improve the accuracy, recall, and F1 value of data classification, this paper proposes an applied university innovation and entrepreneurship data classification method based on the nearest neighbour criterion. Firstly, the decision tree ...

In order to overcome the problems of poor recommendation accuracy, low recommendation recall and long recommendation time in traditional teaching resource recommendation methods, a knowledge map based Chinese online teaching resource recommendation ...

Hepatitis B Virus (HBV) reactivation is the most common complication for patients with primary liver cancer (PLC) after radiotherapy. How to reduce the reactivation of HBV has been a hot topic in the study of postoperative radiotherapy for ...

Currently, we are studying a meeting note generation system to automatically make a note from voice records. Previously, we implemented the first function of the system to convert voice records to texts using the Whisper model. However, the current ...

Plagiarism is a pressing issue in academia and industry, where individuals often modify existing content without providing due credit to the original creator and unethically claiming the work to be their own. Existing plagiarism detection tools ...

To solve the problem of inaccurate user phase identification, the paper proposes a new algorithm based on improved cloud model and adaptive segmented voltage algorithm. Firstly, the new algorithm uses improved cloud model to calculate the digital features ...

Large deployment of wireless sensor networks in various fields bring great benefits. With the increasing volume of sensor data, traditional data collection and processing schemes gradually become unable to meet the requirements in actual ...

In order to solve the problems of high retrieval error rate and long retrieval time existing in traditional online social network image retrieval methods, this paper proposes an online social network image retrieval method based on deep belief network. ...

In order to solve the problem of low evaluation accuracy of English teaching quality evaluation methods, this paper designs a diversified evaluation method of MOOC online English teaching quality based on social network. Firstly, the characteristics of ...

Much work has been done in the computer vision domain for the problem of facial mask detection to curb the spread of the Coronavirus disease (COVID-19). Preventive measures developed using deep learning-based models have got enormous attention. ...

It is a significant and challenging task to detect the informative features to carry out explainable analysis for high dimensional data, especially for those with very small number of samples. Feature selection especially the unsupervised ones are ...

An important question that arises in the study of high-dimensional vector representations learned from data are, given a set D of vectors and a query q, estimate the number of points within a specified distance threshold of q. We develop two estimators, ...

Phishing has represented a more noteworthy danger to clients. In the current work, the authors attempted to build up a powerful anti-phishing technique based on hybrid similarity approach combining Cosine and Soft Cosine similarity that measures the ...

Self-supervised learning algorithms have become one of the best tools for unsupervised representation learning. Although self- supervised algorithms have achieved state-of-the-art performance for classification tasks in the case of natural image data, ...

Techniques of data compression involve de-duplication of data that plays an important role in eliminating duplicate copies of information and has been widely employed in cloud storage to scale back the storage capacity and save information measure. A ...