Long noncoding RNA (lncRNA) plays a crucial role in many critical biological processes and participates in complex human diseases through interaction with proteins. Considering that identifying lncRNA–protein interactions through experimental methods...
Identifying cancer-causing mutations from sequenced cancer genomes hold much promise for targeted therapy and precision medicine. “Driver” mutations are primarily responsible for cancer progression, while “passengers” are functionally neutral. Althou...
For the task of time-series data classification (TSC), some methods directly classify raw time-series (TS) data. However, certain sequence features are not evident in the time domain and the human brain can extract visual features based on visualizat...
Third-generation DNA sequencers provided by Oxford Nanopore Technologies (ONT) produce a series of samples of an electrical current in the nanopore. Such a time series is used to detect the sequence of nucleotides. The task of translation of current...
We propose a method for dynamic facial expression recognition that integrates three complementary feature streams from video sequences: (1) raw texture features extracted with EfficientNet-B0, (2) deep geometric features from face mesh representation...
The global antibiotic resistance crisis, driven by overuse and misuse of antibiotics, is multifaceted. This study aimed to assess the microbiological and genetic characteristics of raw retail pork meat through various methods, including the isolation...
Parcel-based crop classification using multi-temporal satellite optical images plays a vital role in precision agriculture. However, optical image sequences may be incomplete due to the occlusion of clouds and shadows. Thus, exploring inherent time-s...
Intelligent fault diagnosis is a promising tool to deal with industrial big data due to its ability in rapidly and efficiently processing collected signals and providing accurate diagnosis results. In traditional static intelligent diagnosis methods,...
Human skeleton data obtained using a depth camera have been used for pathological gait recognition to support doctor or physician diagnosis decisions. Most studies for skeleton-based pathological gait recognition have used either raw skeleton sequenc...
In the field of rough set, feature reduction is a hot topic. Up to now, to better guide the explorations of this topic, various devices regarding feature reduction have been developed. Nevertheless, some challenges regarding these devices should not...
A necessary pre-processing data analysis step is the removal of adapter sequences from the raw reads. While most adapter trimming tools require adapter sequence as an essential input, adapter information is often incomplete or missing. This can impac...
This paper proposes a new feature learning method for the recognition of radar high resolution range profile (HRRP) sequences. HRRPs from a period of continuous changing aspect angles are jointly modeled and discriminated by a single model named the...
This study investigates whether CNN-based front-end feature extraction improves the predictive performance of deep learning models applied to 1 min intraday CSI 300 index data. Three baseline sequence models, LSTM, GRU, and TCN, are compared against...
Circular RNA (circRNA) is a distinguishable circular formed long non-coding RNA (lncRNA), which has specific roles in transcriptional regulation, multiple biological processes. The identification of circRNA from other lncRNA is necessary for relevant...
Automatic modulation recognition (AMR) is essential for spectrum sensing and non-cooperative wireless monitoring. Although multi-scale temporal representations provide complementary information from received in-phase and quadrature (I/Q) signals, the...
Fly ash microspheres, also called cenospheres, have many valuable properties that allow them to be widely used. Some of its most important properties are its mechanical and thermal strength as well as its chemical stability. These features constitute...
Background/Objectives: Cell-free DNA (cfDNA) end-motifs (EDMs) are promising fragmentomic features for noninvasive cancer detection; however, their diagnostic utility may be limited by background signals from abundant hematopoietic-derived cfDNA frag...
Nucleosome positioning is involved in diverse cellular biological processes by regulating the accessibility of DNA sequences to DNA-binding proteins and plays a vital role. Previous studies have manifested that the intrinsic preference of nucleosomes...
Recently, the radar high-resolution range profiles (HRRPs) have gained significant attention in the field of radar automatic target recognition due to their advantages of being easy to acquire, having a small data footprint, and providing rich target...
Deep learning (DL) and machine learning (ML) have advanced rapidly. This has driven significant progress in intelligent fault diagnosis (IFD) of bearings. However, methods like self-attention have limitations. They only capture features within a sing...
Background: Radiomics has become a valuable tool in medical imaging, but its clinical use is limited by data variability and a lack of reproducibility between centers. This study aims to assess the differences between two scanners and provide guidanc...
Tool wear state recognition is an important part of tool condition monitoring (TCM). Online tool wear monitoring can avoid wasteful early tool changes and degraded workpiece quality due to later tool changes. This study incorporated an attention mech...
This paper develops a novel soft fault diagnosis approach for analog circuits. The proposed method employs the backward difference strategy to process the data, and a novel variant of convolutional neural network, i.e., convolutional neural network w...
Experiments in which complex virome sequencing data is generated remain difficult to explore and unpack for scientists without a background in data science. The processing of raw sequencing data by high throughput sequencing workflows usually results...
Global navigation satellite system (GNSS) positions include various useful signals and some unmodeled errors. In order to enhance the accuracy and extract the features of the GNSS daily time sequence, an improved method of complete ensemble empirical...
Sign language is designed as a natural communication method for the deaf community to convey messages and connect with society. In American sign language, twenty-six special sign gestures from the alphabet are used for the fingerspelling of proper wo...
Image restoration lies between camera acquisition and geometric estimation, but pixel improvements may not transfer to motion estimates. We evaluated directional-kernel Richardson–Lucy (RL) deblurring under kernel-length and direction controls....
Traditional fault diagnosis methods often require extracting features from raw vibration signals based on prior knowledge, which are then input into intelligent classifiers for pattern recognition. This process is prone to information loss and can be...
The huge genetic diversity of circulating viruses is a challenge for diagnostic assays for emerging or rare viral diseases. High-throughput technology offers a new opportunity to explore the global virome of patients without preconception about the c...
In order to improve the accuracy of leakage detection in water pipelines, this paper proposes a novel method based on Transformer and transfer learning. A laboratory test platform was established to obtain datasets with rich leakage characteristics....
The axle-box bearing is a critical load-bearing component in high-speed trains and is prone to failure under long-term heavy-duty operation, affecting both operational efficiency and safety. Current deep-learning-based fault diagnosis methods face tw...
Anticancer peptides (ACPs) have been proven to possess potent anticancer activities. Although computational methods have emerged for rapid ACPs identification, their accuracy still needs improvement. In this study, we propose a model called ACP-BC, a...
We have compared the performance of different machine learning techniques for human activity recognition. Experiments were made using a benchmark dataset where each subject wore a device in the pocket and another on the wrist. The dataset comprises t...
High-impedance fault detection poses significant challenges for distribution network maintenance and operation. We propose a dual-path neural network for high-impedance fault detection. To enhance feature extraction, we use a Gramian Angular Field al...
Goat cheese is an important element of the Mediterranean diet, appreciated for its health-promoting features and unique taste. A pivotal role in the development of these characteristics is attributed to the microbiota and its continuous remodeling ov...
Solar photovoltaic (PV) power forecasting has become an important issue with regard to the power grid in terms of the effective integration of large-scale PV plants. As the main influence factor of PV power generation, solar irradiance and its accura...
Similar time series search is one of the most important time series mining tasks in our daily life. As recent advances in sensor technologies accumulate abundant multi-dimensional time series data associated with multivariate quantities, it becomes a...
Data-driven approaches have emerged as powerful tools for analyzing process data. This study focuses on two data-driven methods: n-gram chi-square feature selection for extracting key action segments and K-medoids clustering combined with Dynamic Tim...
Circular RNAs (circRNAs) are extensively expressed in cells and tissues, and play crucial roles in human diseases and biological processes. Recent studies have reported that circRNAs could function as RNA binding protein (RBP) sponges, meanwhile RBPs...
Accurate estimation of the state of health (SOH) of lithium-ion batteries is crucial for the safe operation of electric vehicles and energy storage systems. However, most existing methods rely on complete charging curves or manual feature engineering...
Bone drilling is a widely encountered process in orthopedic surgeries and keyhole neuro surgeries. We are developing a sensor-integrated smart end-effector for drilling for robotic surgical applications. In manual surgeries, surgeons assess tool wear...
Ship wake detection plays a crucial role in compensating for target detection failures caused by defocusing or displacement in SAR images due to vessel motion. This study addresses the challenge of enhancing wake features in high-resolution spaceborn...
The cognitive state of a person can be categorized using the Circumplex model of emotional states, a continuous model of two dimensions: arousal and valence. We exploit the Remote Collaborative and Affective Interactions (RECOLA) database, which incl...
In this paper, an approach for radar clutter, especially sea and land clutter classification, is considered under the following conditions: the average amplitude levels of the clutter are close to each other, and the distributions of the clutter are...
Clinical mobility assessment is traditionally performed in laboratories using complex and expensive equipment. The low accessibility to such equipment, combined with the emerging trend to assess mobility in a free-living environment, creates a need f...
Sign language is a complex and dynamic visual language that requires the coordinated movement of various body parts, such as the hands, arms, and limbs—making it an ideal application domain for sensor networks to capture and interpret human ges...
The genus Varicosavirus is one of six genera of plant-infecting rhabdoviruses. Varicosaviruses have non-enveloped, flexuous, rod-shaped virions and a negative-sense, single-stranded RNA genome. A distinguishing feature of varicosaviruses, which is sh...
The spontaneous combustion of coal gangue dumps after reclamation causes severe harm to the ecological environment surrounding mining areas. Using remote sensing technology to determine vegetation heat stress levels is an important way to evaluate th...
Cross-condition bearing diagnosis is challenged by simultaneous changes in transient impacts, spectral-energy patterns, and source–target feature distributions as speed and load vary. Handcrafted indicators and single-representation networks of...
In the stock market, predicting the trend of price series is one of the most widely investigated and challenging problems for investors and researchers. There are multiple time scale features in financial time series due to different durations of imp...
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