Physically unclonable function (PUF) and true random number generator (TRNG) are the indispensable primitives for Internet-of-Things (IoT) security. In this article, a highly robust unified PUF<inline-formula> <tex-math notation="LaTeX">$/$ </tex-math></inline-formula>TRNG design is demonstrated. An entropy source (ES) chip based on 40-nm resistive access memory (RRAM) designed fabricated, pseudo-forming technique developed to ensure excellent robustness. The tested across <inline-formula>...

Background and objective Nasopharyngeal carcinoma (NPC) is a rare disease in most parts of the world, but it highly prevalent South China. Epstein-Barr virus (EBV) one major risk factors for NPC. Hence, understanding associated with reactivation EBV from latent stage crucial preventing This study aimed to investigate NPC high-prevalence areas China using Bayesian network (BN) model combined structural equation modeling tools. Methods The baseline information this was derived screening data...

Recommendation systems provide good guidance for users to find their favorite movies from an overwhelming amount of options. However, most excessively pursue the recommendation accuracy and give rise over-specialization, which triggers emergence serendipity. Hence, serendipity has received more attention in recent years, facing three key challenges: subjectivity definition, lack data, users' floating demands To address these challenges, we introduce a new model called HAES, H ybrid A pproach...

Serendipity recommendation has attracted more and attention in recent years; it is committed to providing recommendations which could not only cater users' demands but also broaden their horizons. However, existing approaches usually measure user-item relevance with a scalar instead of vector, ignoring user preference direction, increases the risk unrelated recommendations. In addition, reasonable explanations increase trust acceptance, there no work provide for serendipitous To address...

Sparse Matrix-Vector multiplication (SpMV) is an essential computational kernel in many application scenarios. Tens of sparse matrix formats and implementations have been proposed to compress the memory storage speed up SpMV performance. We develop AlphaSparse, a superset all existing works that goes beyond scope human-designed format(s) implementation(s). AlphaSparse automatically creates novel machine-designed en-tirely from knowledge input sparsity patterns hard-ware architectures. Based...

Graph convolutional network (GCN) has been extensively applied to recommender systems (RS) and achieved significant performance improvements through iteratively aggregating high-order neighbors model the relevance between users items as well their characteristics. In aggregation process, GCN models usually give same or trainable weights based on implicit features, ignoring explicit ones. this work, we take features with meanings extracted specific purpose ones (e.g., temporal features)...

The deluge of genomics data is incurring prohibitively high computational costs. As an important building block for genomic processing algorithms, FM-index search occupies most execution time in sequence alignment. Due to massive random streaming memory references relative only small amount computations, algorithm exhibits extremely low efficiency on conventional architectures. This paper proposes Niubility, accelerator Based our algorithm-architecture co-design analysis, we found that...

Image deblurring has a lot of applications which include but not limit recovery high-quality Satellite imagery from blurry one, extract more detail information low resolution monitoring images, image compression and decompression. However, always been difficult problem in the field processing. The traditional methods can effectively improve quality by denoising technology. But this kind ability clear very vague images. Instead previous methods, we focus on challenger task that...

This paper focuses on the feature-based image stitching technology. The algorithm has been studied and experimented based steps of sample acquisition, preprocessing, feature point detection, matching, transformation model, fusion, etc. In detection part, SURF with better overall performance than Harris, FAST, SIFTS, ORB algorithms were selected. matching different are analyzed best solution is Based initially formulated scheme, optimized container stitched. quality reason output analyzed,...

Diversity is increasingly recognized as a crucial factor in recommendation systems for enhancing user satisfaction. However, existing studies on diversity-enhanced primarily focus designing strategies, often overlooking the development of evaluation metrics. Widely used diversity metrics such CC, ILAD, and ILMD are typically assessed independently accuracy. This separation leads to critical limitation: measures unable distinguish between improvements from effective recommendations those...

In this paper, a new upsampling algorithm is proposed to Fusion Upsampling, and RP-FCN network presented based on ResNeXt50, Pyramid Pooling, Upsampling FCN framework. The information perception system, operation control system dispatching command of the fully automated wharf are gradually perfected, but automatic inspection module container has not been built yet. applied identification damage in port, order add luster increasingly perfect terminal system. experiment shows that effect...

Disentangled representation has been widely explored in many fields due to its maximal compactness, interpretability and versatility. Recommendation system also needs disentanglement make more explainable general for downstream tasks. However, some challenges slow broader application -- the lack of fine-grained labels complexity user-item interactions. To alleviate these problems, we propose a Semi-Disentangled Representation Learning method (SDRL) based on autoencoders. SDRL divides each...

Crowdsourcing allows workers to participate in collaborative works. The selection of proper is essential for the quality task completion. However, crowdsourcing mode, plagiarism or collusion among connecting greatly affects some specific tasks. In this paper, we propose an independent worker framework based on technology community detection and link prediction. former used guarantee that selected have no very weak connections currently, latter they will future. We also conduct intensive...

Sparse Matrix-Vector multiplication (SpMV) is an essential computational kernel in many application scenarios. Tens of sparse matrix formats and implementations have been proposed to compress the memory storage speed up SpMV performance. We develop AlphaSparse, a superset all existing works that goes beyond scope human-designed format(s) implementation(s). AlphaSparse automatically \emph{creates novel machine-designed implementations} entirely from knowledge input sparsity patterns hardware...