Accumulating evidence supports the role of PDZ-binding kinase (PBK)/T-lymphokine-activated killer-cell-originated protein kinase (TOPK) in mitosis and cell-cycle progression of mitotically active cells, especially proliferative malignant cells. PBK/T...
Oral cancer is a common cancer with poor prognosis. We evaluated the expression of PBK/TOPK (PDZ-binding kinase/T-LAK cell-originated protein kinase) and its prognostic significance in oral cancer. PBK/TOPK expression was measured by immunohistochemi...
T-lymphokine-activated killer cell-originated protein kinase (TOPK, also known as PDZ-binding kinase or PBK) plays a crucial role in cell cycle regulation and mitotic progression. Abnormal overexpression or activation of TOPK has been observed in man...
Anomaly-based intrusion detection systems use profiles to characterize expected behavior of network users. Most of these systems characterize the entire network traffic within a single profile. This work proposes a user-level anomaly-based intrusion...
Immune checkpoint inhibitor therapy has proven efficacy in a subset of colon cancer patients featuring a deficient DNA mismatch repair system or a high microsatellite instability profile. However, there is high demand for more effective biomarkers to...
Sparse autoencoders (SAEs) decompose transformer activations into sparse feature dictionaries, but one-shot support selection can leave many features unused and become difficult to optimize at very small active budgets. We study an SAE-like dictionar...
T-LAK-cell-originated protein kinase (TOPK) is a PDZ-binding kinase (PBK) that was recently identified as a novel member of the mitogen-activated protein kinase (MAPK) family. It has been shown to play an important role in many cellular functions. Ho...
Background/Objectives: Non-melanoma skin cancer (NMSC) is among the most common cancers in the United States, with solar ultraviolet (UV) radiation being a primary etiological factor. T-LAK cell-originated protein kinase (TOPK), a serine/threonine ki...
Background: Glioblastoma (GBM) remains the most lethal primary brain tumor in adults, largely due to recurrence after surgery. Cancer vaccines, which can activate a patient’s adaptive immune system against specific tumor antigens, are a promisi...
Glycycoumarin (GCM) is a representative of bioactive coumarin compounds isolated from licorice, an edible and medicinal plant widely used for treating various diseases including liver diseases. The purpose of the present study is to examine the possi...
Nonmelanoma skin cancers (NMSC) are the most common skin cancers, and about 5.4 million people are diagnosed each year in the United States. A newly developed T-lymphokine-activated killer cell-originated protein kinase (TOPK) inhibitor, HI-TOPK-032,...
SimRank is a widely used metric for evaluating vertex similarity based on graph topology, with diverse applications such as large-scale graph mining and natural language processing. The objective of the single-source and top-k SimRank query problem i...
Graph search techniques are increasingly vital for applications involving labeled or textual content on network vertices. A key task is the top-k nearest keyword (kNK) search on undirected graphs where a query vertex and keywords identify k closest v...
A labeled graph is a special structure with node identification capability, which is often used in information networks, biological networks, and other fields. The subgraph query is widely used as an important means of graph data analysis. As the siz...
With advancements in computing technology and the rapid progress of data science, machine learning has been widely applied in various fields, showing great potential, especially in digital healthcare. In recent years, conversational diagnostic system...
After the failure of the power system, a large amount of alarm information will flood into the dispatching terminal instantly. At the same time, there are inevitable problems, such as the abnormal operation of the protection and the circuit breaker,...
Background/Objectives In this study we approach the problem of medical image segmentation by introducing a new loss function envelope that is derived from the Top-k loss strategy. We exploit the fact that, for semantic segmentation, the training loss...
This paper presents a novel approach for accelerating the top-k heavy hitters query in data streams using Field Programmable Gate Arrays (FPGAs). Current hardware acceleration approaches rely on the direct and strict mapping of software algorithms in...
Top-k graph similarity search on probabilistic graphs is widely used in various scenarios, such as symptom–disease diagnostics, community discovery, visual pattern recognition, and communication networks. The state-of-the-art method uses the ch...
High-utility itemset mining (HUIM) utilizes the threshold value to extract HUI from the transactional database. However, it is difficult to define an optimal threshold value, since it depends on the domain knowledge of the application. Therefore, top...
The rapid growth of the Internet of Things (IoT) has created vast networks of interconnected devices that are increasingly exposed to cyberattacks. Ensuring the security of such distributed systems requires efficient and adaptive intrusion detection...
A novel network paradigm of mobile edge computing, namely TMWSNs (two-tiered mobile wireless sensor networks), has just been proposed by researchers in recent years for its high scalability and robustness. However, only a few works have considered th...
Top-k spatial preference queries rank objects based on the score of feature objects in their spatial neighborhood. Top-k preference queries are crucial for a wide range of location based services such as hotel browsing and apartment searching. In rec...
In order to cope with the massive scale of traffic and reduce the memory overhead of traffic statistics, the traffic statistics method based on the Sketch algorithm has become a research hotspot for traffic statistics. This paper studies the problem...
This paper presents a novel approach for anomaly detection in industrial processes. The system solely relies on unlabeled data and employs a 1D-convolutional neural network-based deep autoencoder architecture. As a core novelty, we split the autoenco...
This paper proposed a multi-keyword ciphertext search, based on an improved-quality hierarchical clustering (MCS-IQHC) method. MCS-IQHC is a novel technique, which is tailored to work with encrypted data. It has improved search accuracy and can self-...
To overcome the severe side effects of cancer chemotherapy, it is vital to develop targeting chemotherapeutic delivery systems with the potent inhibition of tumour growth, angiogenesis, invasion and migration at low drug dosages. For this purpose, we...
Graph embedding transforms high-dimensional graphs into a lower-dimensional vector space while preserving their structural information and properties. Context-sensitive graph embedding, in particular, performs well in tasks such as link prediction an...
Federated learning (FL) has emerged as a promising framework for training shared models across diverse participants, ensuring data remains securely stored on local devices. Despite its potential, FL still faces some critical challenges, including dat...
Data mining techniques are useful in discovering hidden knowledge from large databases. One of its common techniques is sequential rule mining. A sequential rule (SR) helps in finding all sequential rules that achieved support and confidence threshol...
Federated learning (FL) is a privacy-preserving technique for training a vast amount of decentralized data and making inferences on mobile devices. As a typical language modeling problem, mobile keyboard prediction aims at suggesting a probable next...
When a camera lens is directly faced with a strong light source, image flare commonly occurs, significantly reducing the clarity and texture of the photo and interfering with image processing tasks that rely on visual sensors, such as image segmentat...
Online apparel size recommendation remains difficult because consumers cannot physically assess garment fit before purchase. It is a multi-dimensional fit evaluation problem, particularly for complex garments such as jackets, where multiple body area...
Diversified top-k weight clique (DTKWC) search problem is an important generalization of the diversified top-k clique (DTKC) search problem with practical applications. The diversified top-k weight clique search problem aims to search k maximal cliqu...
In this paper, we introduce two novel top-k spatial dataset search schemes, KSDS and KSDS+. The core innovation of these schemes lies in partitioning the spatial datasets into grids and assessing similarity based on the distribution of points within...
Aerial scenes exhibit a mismatch between where computation is spent and where information resides: targets occupy a small, unevenly distributed fraction of the frame, yet detectors process every region at identical resolution. Tiling and clustering p...
Recently, studies on secure database outsourcing have been highlighted for the cloud computing environment. A few secure Top-k query processing algorithms have been proposed in the encrypted database. However, the previous algorithms can support eith...
Ordered List Averaging (OLA) was previously introduced as a methodology for evaluating machine learning algorithms according to their ability to prioritize medically relevant feature subsets. The original methodology demonstrated, through Friedman&nd...
Accurate short-term wildfire forecasting is essential for effective early warning, operational planning, and resource allocation. This study proposes the Dynamic Spatio-Temporal Fire Pressure Model (DST-FPM), a leakage-controlled forecasting framewor...
Relation extraction tasks aim to predict the type of relationship between two entities from a given text. However, many existing methods fail to fully utilize the semantic information and the probability distribution of the output of pre-trained lang...
As a basic method of spatial data operation, spatial keyword query can provide meaningful information to meet user demands by searching spatial textual datasets. How to accurately understand users’ intentions and efficiently retrieve results fr...
Encrypted traffic accounts for 95% of the total traffic in the backbone network environment with Tbps bandwidth. As network traffic becomes more and more encrypted and link rates increase in modern networks, the measurement of encrypted traffic relie...
Camouflaged object detection (COD) encounters substantial difficulties owing to the visual resemblance between targets and their environments, together with discrepancies in multiscale representation of features. Current methodologies confront obstac...
Internet of Things (IoT)-backed smart shopping carts are generating an extensive amount of data in shopping markets around the world. This data can be cleaned and utilized for setting business goals and strategies. Artificial intelligence (AI) method...
Membership inference attacks (MIAs) determine whether a sample was used to train a target model. Existing attacks often require abundant auxiliary data or many reference models, which may be unavailable in restricted services. We propose a meta-learn...
The harmonic closeness centrality measure associates, to each node of a graph, the average of the inverse of its distances from all the other nodes (by assuming that unreachable nodes are at infinite distance). This notion has been adapted to tempora...
The rapid growth of GPS-enabled mobile devices has popularized many location-based applications. Spatial keyword search which finds objects of interest by considering both spatial locations and textual descriptions has become very useful in these app...
Optical remote sensing images play a pivotal role in numerous applications, notably feature recognition and scene semantic segmentation. Nevertheless, their efficacy is frequently compromised by various noise types, which detrimentally impact practic...
High-utility sequential pattern mining (HUSPM) helps researchers find all subsequences that have high utility in a quantitative sequential database. The HUSPM approach appears to be well suited for resource transformation in DIKWP graphs. However, al...
With the proliferation of the Internet of Things (IoT), gesture recognition has attracted attention as a core technology in human–computer interaction (HCI). In particular, mmWave frequency-modulated continuous-wave (FMCW) radar has emerged as...
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