Mesoporous silicas have enjoyed great interest among scientists practically from the moment of their discovery thanks to their unique attractive properties. Many types of mesoporous silicas have been described in literature, the most thoroughly MCM-4...
The cutterhead torque and thrust, reflecting the obstruction degree of the geological environment and the behavior of excavation, are the key operating parameters for the tunneling of tunnel boring machines (TBMs). In this paper, a hybrid hidden Mark...
When developing a fully automatic system for evaluating motor activities performed by a person, it is necessary to segment and recognize the different activities in order to focus the analysis. This process must be carried out by a Human Activity Rec...
Advances in artificial intelligence-based autonomous applications have led to the advent of domestic robots for smart elderly care; the preliminary critical step for such robots involves increasing the comprehension of robotic visualizing of human ac...
As one of the most important and computationally-intensive parts in bioinformatics analysis, the Pair Hidden Markov Model (Pair-HMM) forward algorithm is widely recognized and has great potential. Therefore, it is important to accelerate the process...
KPIs (Key Performance Indicators) in distributed systems may involve a variety of anomalies, which will lead to system failure and huge losses. Detecting KPI anomalies in the system is very important. This paper presents a time series anomaly detecti...
The development of convolution neural networks (CNNs) has become a significant means to solve the problem of remote sensing scene image classification. However, well-performing CNNs generally have high complexity and are prone to overfitting. To hand...
In the field of network intrusion, malware usually evades anomaly detection by disguising malicious behavior as legitimate access. Therefore, detecting these attacks from network traffic has become a challenge in this an adversarial setting. In this...
Hyperbolic metamaterials (HMMs), supporting surface plasmon polaritons (SPPs), and highly confined bulk plasmon polaritons (BPPs) possess promising potential for application as surface-enhanced Raman scattering (SERS) substrates. In the present study...
Bearing performance degradation assessment (PDA), as an important part of prognostics and health management (PHM), is significant to prevent major accidents and economic losses in industry. For the data-driven PDA, the extraction and selection of fea...
Stereoscopic displays can induce visual discomfort despite their wide application. Electroencephalography (EEG) technology has been applied to assess 3D visual discomfort, because it can capture brain activities with high temporal resolution. Previou...
A data center network is vulnerable to suffer from concealed low-rate distributed denial of service (L-DDoS) attacks because its data flow has the characteristics of data flow delay, diversity, and synchronization. Several studies have proposed addre...
Based on the combination of improved Local Mean Decomposition (LMD), Multi-scale Permutation Entropy (MPE) and Hidden Markov Model (HMM), the fault types of bearings are diagnosed. Improved LMD is proposed based on the self-similarity of roller beari...
Spatiotemporal data from urban road traffic are pivotal for intelligent transportation systems and urban planning. Nonetheless, missing data in traffic datasets is a common challenge due to equipment failures, communication issues, and monitoring lim...
This study proposes an enhanced ship-type classification model that employs a sequential processing methodology integrating hidden Markov model (HMM), deep neural network (DNN), and convolutional neural network (CNN) techniques. Four different ship t...
Practitioners have used hidden Markov models (HMMs) in different problems for about sixty years. Moreover, conditional random fields (CRFs) are an alternative to HMMs and appear in the literature as different and somewhat concurrent models. We propos...
Spider venoms are rich cocktails of bioactive peptides, proteins, and enzymes that are being intensively investigated over the years. In order to provide a better comprehension of that richness, we propose a three-level family classification system f...
This paper presents an enhanced PDR-BLE compensation mechanism for improving indoor localization, which is considerably resilient against variant uncertainties. The proposed method of ePDR-BLE compensation mechanism (EPBCM) takes advantage of the non...
The remote control ship is considered to be the most likely implementation of maritime autonomous surface ships (MASS) in the near-term future. With collaborative control from onboard controllers and operators ashore, ships may operate in three navig...
Human–computer interaction (HCI) plays a crucial role across various fields, with eye-tracking technology emerging as a key enabler for intuitive and dynamic control in assistive systems like Assistive Robotic Arms (ARAs). By precisely tracking...
3 July 2024
Background: Biomedical data are usually collections of longitudinal data assessed at certain points in time. Clinical observations assess the presences and severity of symptoms, which are the basis for the description and modeling of disease progress...
Single-crystal diamond tools occupy an important position in the field of optical processing as the basis and key to advanced optical manufacturing technology, such as grating manufacturing and optical mirror-turning processing. Single-crystal diamon...
Profile hidden Markov models (HMMs) are a powerful way of modeling biological sequence diversity and constitute a very sensitive approach to detecting divergent sequences. Here, we report the development of protocols for the rational design of profil...
In a health management system, prognostics, which is an engineering discipline that predicts a system’s future health, is an important aspect yet there is currently limited research in this field. In this paper, a hybrid approach for prognostics is p...
Human factors are the most important factor in road traffic crashes. Human-caused traffic crashes can be reduced through the active safety system of vehicles. Road hypnosis is an unconscious driving state caused by the combination of external environ...
Sequence–structure alignment for protein sequences is an important task for the template-based modeling of 3D structures of proteins. Building a reliable sequence–structure alignment is a challenging problem, especially for remote homolog...
Tumors are often polyclonal due to copy number alteration (CNA) events. Through the CNA profile, we can understand the tumor heterogeneity and consistency. CNA information is usually obtained through DNA sequencing. However, many existing studies hav...
Statistical complexity is a measure of complexity of discrete-time stationary stochastic processes, which has many applications. We investigate its more abstract properties as a non-linear function of the space of processes and show its close relatio...
Human activity recognition (HAR) has become an interesting topic in healthcare. This application is important in various domains, such as health monitoring, supporting elders, and disease diagnosis. Considering the increasing improvements in smart de...
Attention capability is an essential component of human–robot interaction. Several robot attention models have been proposed which aim to enable a robot to identify the attentiveness of the humans with which it communicates and gives them its a...
This paper proposes a new Hidden Markov Model (HMM) framework integrated with the Skew Exponential Power (SEP) distribution, named SEP-HMM. The primary advantage of this method is its ability to capture and represent asymmetric and non-mesokurtic emi...
Automatic key gesture detection and recognition are difficult tasks in Human–Computer Interaction due to the need to spot the start and the end points of the gesture of interest. By integrating Hidden Markov Models (HMMs) and Deep Neural Networ...
23 September 2022
Addressing the problems facing the elderly, whether living independently or in managed care facilities, is considered one of the most important applications for action recognition research. However, existing systems are not ready for automation, or f...
In order to solve the problem of low recognition accuracy of traditional pig sound recognition methods, deep neural network (DNN) and Hidden Markov Model (HMM) theory were used as the basis of pig sound signal recognition in this study. In this study...
Marine passive acoustic monitoring can be used to study biological, geophysical, and anthropogenic phenomena in the ocean. The wide range of characteristics from geophysical, biological, and anthropogenic sounds sources makes the simultaneous automat...
Autonomy represents one of the most promising directions in the future development of surgical robotics, and Learning from Demonstration (LfD) is a key methodology for advancing technologies in this field. The proposed approach extends the classical...
Wearable gait analysis systems using inertial sensors offer the potential for easy-to-use gait assessment in lab and free-living environments. This can enable objective long-term monitoring and decision making for individuals with gait disabilities....
Over the past decades, there has been significant research effort dedicated to the development of intelligent vehicles and V2X systems. This paper proposes a road traffic risk assessment method for road traffic accident prevention of intelligent vehi...
Packet loss is a major problem for wireless networks and has significant effects on the perceived quality of many internet services. Packet loss models are used to understand the behavior of packet losses caused by several reasons, e.g., interference...
Nanopore-based DNA sequencing has emerged as a transformative biosensing technology, enabling real-time molecular diagnostics in compact and mobile form factors. However, the computational complexity of the basecalling process—the step that tra...
Radars, as active detection sensors, are known to play an important role in various intelligent devices. Target recognition based on high-resolution range profile (HRRP) is an important approach for radars to monitor interesting targets. Traditional...
Estimating the remaining useful life (RUL) of engineering systems is crucial for maintenance planning and the reliability of complex mechanical units. Accurate RUL predictions support timely interventions and help to prevent unexpected failures. This...
There has been a growing demand for portfolio management using artificial intelligence (AI). To sustain a competitive advantage for portfolio management, stock market investors require a strategic investment decision that can realize better returns....
Using Hidden Markov Models (HMMs) as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorpor...
Low-affinity PBP4, historically linked to penicillin resistance in Enterococcus faecalis, may still have affinity for novel cephalosporins. Ceftobiprole (BPR) is a common therapeutic choice, even with PBP4-related overexpression and amino acid substi...
Over the years, WiFi received signal strength indicator (RSSI) measurements have been widely implemented for determining the location of a user’s position in an indoor environment, where the GPS signal might not be received. This method utilizes a hu...
Background/Objectives: Granulicatella adiacens infective endocarditis is conventionally managed with penicillin, ampicillin, or ceftriaxone in combination with gentamicin, although double beta-lactam regiments have been proposed a safer alternative t...
Automatic speech recognition, especially large vocabulary continuous speech recognition, is an important issue in the field of machine learning. For a long time, the hidden Markov model (HMM)-Gaussian mixed model (GMM) has been the mainstream speech...
In recent years, time series land cover products have been developed rapidly. However, the traditional classification strategy rarely considers time continuity and spatial consistency, which leads to the existence of unreasonable changes among the mu...
The majority of handwritten word recognition strategies are constructed on learning-based generative frameworks from letter or word training samples. Theoretically, constructing recognition models through discriminative learning should be the more ef...
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