In this paper, we propose a multilayer perceptron-based recognition method for driving cycles of commercial vehicles. Our method solves the problem of identifying the type of driving cycle for commercial vehicles, and improves the efficiency and sust...
The range-gated laser imaging instrument can capture face images in a dark environment, which provides a new idea for long-distance face recognition at night. However, the laser image has low contrast, low SNR and no color information, which affects...
Aiming at the problems inherent in the traditional fuzzy energy management strategy (F-EMS), such as poor adaptive ability and lack of self-learning, a neural network fuzzy energy management strategy (NNF-EMS) for hybrid electric vehicles (HEVs) base...
The conventional finger-vein recognition system is trained using one type of database and entails the serious problem of performance degradation when tested with different types of databases. This degradation is caused by changes in image characteris...
The efficiency and accuracy of target recognition in synthetic aperture radar (SAR) imagery have seen significant progress lately, stemming from the encouraging advancements of automatic target recognition (ATR) technology based on deep learning. How...
22 May 2023
Perception of internal and external cues is an important determinant of pacing behaviour, but little is known about the capacity to attend to such cues as exercise intensity increases. This study investigated whether changes in attentional focus and...
The driving pattern has an important influence on the parameter optimization of the energy management strategy (EMS) for hybrid electric vehicles (HEVs). A new algorithm using simulated annealing particle swarm optimization (SA-PSO) is proposed for p...
The categorization and identification of agricultural imagery constitute the fundamental requisites of contemporary farming practices. Among the various methods employed for image classification and recognition, the convolutional neural network (CNN)...
Knitted fabric sensors have been widely used as strain sensors in the sports health field and its large strain performance and structure are suitable for human body movements. When a knitted structure is worn, different human body movements are refle...
This paper discusses the problem of recognizing defective epoxy drop images for the purpose of performing vision-based die attachment inspection in integrated circuit (IC) manufacturing based on deep neural networks. Two supervised and two unsupervis...
The energy management strategy (EMS) is a critical technology for pure electric vehicles equipped with hybrid energy storage systems. This study addresses the challenges of limited adaptability to driving cycles and significant battery capacity degra...
Against the backdrop of precision livestock farming, sow behavior analysis holds significant theoretical and practical value. Traditional production methods face challenges such as low production efficiency, high labor intensity, and increased diseas...
Variable-condition fish recognition is a type of cross-scene and cross-camera fish re-identification (re-ID) technology. Due to the difference in the domain distribution of fish images collected under different culture conditions, the available train...
We can benefit from various services with context recognition using wearable sensors. In this study, we focus on the contexts acquired from sensor data in the nostrils. Nostrils can provide various contexts on breathing, nasal congestion, and higher...
The popularization of smart phones and the large-scale application of location-based services (e.g., exercises, traveling and food delivery via cycling) have resulted in the emergence of massive amounts of personalized cycling trajectory data, spurri...
The objective of this work is to develop an optimal management strategy to improve the energetic efficiency of a hybrid electric vehicle. The strategy is built based on an extensive experimental study of mobility in order to allow trips recognition a...
Context recognition using wearable devices is a mature research area, but one of the biggest issues it faces is the high energy consumption of the device that is sensing and processing the data. In this work we propose three different methods for opt...
The Norwegian business-to-business (B2B) market for bicycles consists mainly of international brands, such as Shimano, Trek, Cannondale, and Specialized. The product descriptions for these brands are usually in English and need local translation. How...
Image-based gender classification is very useful in many applications, such as intelligent surveillance, micromarketing, etc. One common approach is to adopt a machine learning algorithm to recognize the gender class of the captured subject based on...
In tomato leaf disease identification tasks, the high cost and consumption of deep learning-based recognition methods affect their deployment and application on embedded devices. In this study, an improved YOLOX-based tomato leaf disease identificati...
The present experiment aimed at determining whether the timing of the maternal recognition of pregnancy (MRP) was specific to individual mares by determining when luteostasis, a failure to return to oestrus, reliably occurred in individuals following...
We study a conditional finite-dimensional operator construction based on two imported Recognition-Science inputs: a continuous comparison cost satisfying a multiplicative coherence axiom and equilibrium calibration, and a three-coordinate, eight-tick...
This paper presents the development of a wearable accelerometry system for real-time gait cycle parameter recognition. Using a tri-axial accelerometer, the wearable motion detector is a single waist-mounted device to measure trunk accelerations durin...
Pulse signals carry comprehensive information regarding human cardiovascular physiology and pathology, providing a noninvasive and continuous method to assess cardiovascular health status in blood pressure monitoring. The blood pressure measurement m...
To address the challenges of poor model generalization and suboptimal recognition accuracy stemming from limited and imbalanced sample sizes in tomato leaf disease identification, this study proposes a novel recognition strategy. This approach synerg...
This paper presents a preliminary smartphone-based inertial measurement unit (IMU) system for recognizing three common motion types, namely walking, running, and cycling, under different carrying modes. The proposed system is implemented on an Androi...
The theoretical protein–RNA recognition code was used in this study to research the compatibility of the SARS-CoV-2 envelope protein (E) with mRNAs in the human transcriptome. According to a review of the literature, the spectrum of identified...
In this framework, a completed recognition is required to remain distinguishable from its reversal; we formulate this requirement with a ledger of binary state changes.For a closed run, the primitive debit and credit increments balance; reversal ther...
Due to its versatility, virtual technology is being widely employed in different domains, from industry to amusement. The possibility to adopt this technology in early product/service design is going to bring positive effects such as the reduction of...
One of the major challenges in implementing the equivalent fuel consumption minimisation strategy in hybrid electric vehicles is the adaptation of the equivalence factor to real-world driving. In this paper, a novel adaptive equivalent fuel consumpti...
The recognition of human activity is crucial as the Internet of Things (IoT) progresses toward future smart homes. Wi-Fi-based motion-recognition stands out due to its non-contact nature and widespread applicability. However, the channel state inform...
Successful cell proliferation requires efficient and precise genome duplication followed by accurate chromosome segregation. The Cdc10-dependent transcript 1 protein (Cdt1) is required for the first step in DNA replication, and in human cells Cdt1 is...
Protein disulfide reduction by thioredoxins (TRXs) controls the conformation of enzyme active sites and their multimeric complex formation. TRXs are small oxidoreductases that are broadly conserved in all living organisms. In photosynthetic eukaryote...
To fulfil the CO2 emission reduction targets of the European Union (EU), heavy-duty (HD) trucks need to operate 15% more efficiently by 2025 and 30% by 2030. Their electrification is necessary as conventional HD trucks are already optimized for the l...
Chronic respiratory diseases, the third leading cause of mortality on a global scale, can be diagnosed at an early stage through non-invasive auscultation. However, effective manual differentiation of lung sounds (LSs) requires not only sharp auditor...
The DNA replication machinery is highly conserved from bacteria to eukaryotic cells. Faithful DNA replication is vital for cells to transmit accurate genetic information to the next generation. However, both internal and external DNA damages threaten...
Energy management strategies (EMS) in the context of electric or hybrid vehicles can optimize the available energy by minimizing consumption. Most optimization-based EMS are not real-time-applicable for an accurate estimation of future consumption. T...
A recognizer with at least two independent binary tests, changing one test at a time, has
Electrocardiogram (ECG) signals are time series data that are acquired by time change. A problem with these signals is that comparison data that have the same size as the registration data must be acquired every time. A network model of an auxiliary...
Traditional craftsmanship and culture are facing a transformation in modern science and technology development, and the cultural industry is gradually stepping into the digital era, which can realize the sustainable development of intangible cultural...
Acoustic management is very important for detecting possible events in the context of a smart environment (SE). In previous works, we proposed a reflective middleware for acoustic management (ReM-AM) and its autonomic cycles of data analysis tasks, a...
Biometric identification using surveillance video has attracted the attention of many researchers as it can be applicable not only for robust identification but also personalized activity monitoring. In this paper, we present a novel multimodal recog...
14 June 2019
The objective was to investigate if high cadence cycling altered non-motor cognition and depression symptoms in individuals with Parkinson’s disease (PD) and whether exercise responses were influenced by brain-derived neurotrophic factor (BDNF)...
Gait recognition has received widespread attention due to its non-intrusive recognition mechanism. Currently, most gait recognition methods use appearance-based recognition methods, and such methods are easily affected by occlusions when facing compl...
Counting the number of work cycles per unit of time of earthmoving excavators is essential in order to calculate their productivity in earthmoving projects. The existing methods based on computer vision (CV) find it difficult to recognize the work cy...
Recently, gesture recognition technology has attracted increasing attention because it provides another means of information exchange in some special occasions, especially for auditory impaired individuals. At present, the fusion of sensor signals an...
Smart praying mats are essential to help old and forgetful Muslims perform their religious needs. Due to the binary representation of pressure sensors embedded into the mat for posture identification, existing smart praying systems either use large s...
Although biometrics systems using an electrocardiogram (ECG) have been actively researched, there is a characteristic that the morphological features of the ECG signal are measured differently depending on the measurement environment. In general, pos...
Each individual describes unique patterns during their gait cycles. This information can be extracted from the live video stream and used for subject identification. In appearance based recognition methods, this is done by tracking silhouettes of per...
This study aimed to develop a vision-based gait recognition system for person identification. Gait is the soft biometric trait recognizable from low-resolution surveillance videos, where the face and other hard biometrics are not even extractable. Th...
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