Enhanced knowledge graph recommendation algorithm based on multi-level contrastive learning.

Integrating the Knowledge Graphs (KGs) into recommendation systems enhances personalization and accuracy. However, the long-tail distribution of knowledge graphs often leads to data sparsity, which limits the effectiveness in practical applications. To address this challenge, this study proposes a knowledge-aware recommendation algorithm framework that incorporates multi-level contrastive learning.

Improved marine predators algorithm for engineering design optimization problems.

The Marine Predator Algorithm (MPA) has unique advantages as an important branch of population-based algorithms. However, it emerges more disadvantages gradually, such as traps to local optima, insufficient diversity, and premature convergence, when dealing with complex problems in practical industrial engineering design applications. In response to these limitations, this paper proposes a novel Improved Marine Predator Algorithm (IMPA).

An image encryption algorithm based on the double time-delay Lorenz system.

The traditional image encryption technology has the disadvantages of low encryption efficiency and low security. According to the characteristics of image information, an image encryption algorithm based on double time-delay chaos is proposed by combining the delay chaotic system with traditional encryption technology. Because of the infinite dimension and complex dynamic behavior of the delayed chaotic system, it is difficult to be simulated by AI technology.

The Control Method of Autonomous Flight Avoidance Barriers of UAVs in Confined Environments.

This paper proposes an improved 3D-Vector Field Histogram (3D-VFH) algorithm for autonomous flight and local obstacle avoidance of multi-rotor unmanned aerial vehicles (UAVs) in a confined environment. Firstly, the method employs a target point coordinate system based on polar coordinates to convert the point cloud data, considering that long-range point cloud information has no effect on local obstacle avoidance by UAVs. This enables UAVs to effectively utilize obstacle information for obstacle avoidance and improves the real-time performance of the algorithm.

A Novel Affective Analysis System Modeling Method Integrating Affective Cognitive Model and Bi-LSTM Neural Network.

The severity of mental health issues among college students has increased over the past few years, having a significant negative impact on not only their academic performance but also on their families and even society as a whole. Therefore, one of the pressing issues facing college administrators right now is finding a method that is both scientific and useful for determining the mental health of college students. In pace with the advancement of Internet technology, the Internet has become an important communication channel for contemporary college students.

A Novel Stress State Assessment Method for College Students Based on EEG.

Stress is an unavoidable problem for today's college students. Stress can arouse strong personal emotional and behavioral responses. Compared with other groups of the same age, college students have a special way of life and living environment.

A Data-Driven Adaptive Emotion Recognition Model for College Students Using an Improved Multifeature Deep Neural Network Technology.

With the increasing pressure on college students in terms of study, work, emotion, and life, the emotional changes of college students are becoming more and more obvious. For college student management workers, if they can accurately grasp the emotional state of each college student in all aspects of the whole process, it will be of great help to student management work. The traditional way to understand students' emotions at a certain stage is mostly through chats, questionnaires, and other methods.

A Novel Fatigue Driving State Recognition and Warning Method Based on EEG and EOG Signals.

Traffic accidents are easily caused by tired driving. If the fatigue state of the driver can be identified in time and a corresponding early warning can be provided, then the occurrence of traffic accidents could be avoided to a large extent. At present, the recognition of fatigue driving states is mostly based on recognition accuracy.

Multimodal MRI Brain Tumor Image Segmentation Using Sparse Subspace Clustering Algorithm.

Brain tumors are one of the most deadly diseases with a high mortality rate. The shape and size of the tumor are random during the growth process. Brain tumor segmentation is a brain tumor assisted diagnosis technology that separates different brain tumor structures such as edema and active and tumor necrosis tissues from normal brain tissue.

Outlier Detection Using Improved Support Vector Data Description in Wireless Sensor Networks.

Wireless sensor networks (WSNs) are susceptible to faults in sensor data. Outlier detection is crucial for ensuring the quality of data analysis in WSNs. This paper proposes a novel improved support vector data description method (ID-SVDD) to effectively detect outliers of sensor data.

Data Fusion Using Improved Support Degree Function in Aquaculture Wireless Sensor Networks.

For monitoring the aquaculture parameters in pond with wireless sensor networks (WSN), high accuracy of fault detection and high precision of error correction are essential. However, collecting accurate data from WSN to server or cloud is a bottleneck because of the data faults of WSN, especially in aquaculture applications, limits their further development. When the data fault occurs, data fusion mechanism can help to obtain corrected data to replace abnormal one.

Synthesis, Aggregation Induced Emission and Mechanochromic Luminescence of New β-Diketone Derivatives Bearing Tetraphenylene Moieties.

A series of β-diketone derivatives bearing tetraphenylene (TPE) moieties were synthesized and characterized. Their photophysical properties were investigated systematically via spectroscopic and theoretical methods. All compounds exhibit broad absorption bands between 300 and 450 nm, which are assigned to the π-π* transition of the conjugated system mixed intramolecular charge-transfer (ICT) transitions.

Synthesis, Luminescent Properties of aza-Boron-Diquinomethene Difluoride Complexes and Their Application for Fluorescent Security Inks.

Two aza-boron-diquinomethene (aza-BODIQU) complexes bearing phenyl and carbazyl substituents were synthesized and characterized. Their photophysical properties were investigated systematically via spectroscopic and theoretical methods. Both complexes exhibit strong (1)π-π* transition absorptions (λ(abs) = 400-540 nm) and intense fluorescent emissions (λ(em) = 440-600 nm, Φ(PL) = 0.