Jun-Ping Yao¹, Kai-Yuan Cheng^1,*, Meng-Meng Ge², Xiao-Jun Li¹, Yi-Jing Wang¹

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5509-5524, 2022, DOI:10.32604/cmc.2022.030150

Abstract Recommendation algorithms regard user-item interaction as a sequence to capture the user’s short-term preferences, but conventional algorithms cannot capture information of constantly-changing user interest in complex contexts. In these years, combining the knowledge graph with sequential recommendation has gained momentum. The advantages of knowledge graph-based recommendation systems are that more semantic associations can improve the accuracy of recommendations, rich association facts can increase the diversity of recommendations, and complex relational paths can hence the interpretability of recommendations. But the information in the knowledge graph, such as entities and relations, often fails to be fully utilized and high-order connectivity is unattainable… More >

Jingyu Dai^1,*, Hongyu Dai², Yutong Xie³, T. Indumathi⁴

Journal of Renewable Materials, Vol.10, No.11, pp. 2717-2728, 2022, DOI:10.32604/jrm.2022.019735

Abstract In order to promote the application of clean energy technology in clothing and promote the integration of industrial development and artificial intelligence wearable technology, this study elaborates the energy application characteristics of intelligent wearable products at home and abroad and its application in different fields, aiming at the current research status of wearable technology in the field of textile and clothing. The wearable distributed generation technology is classified, and a creative clothing design for detecting climate temperature is designed. Based on the monitoring of body temperature, the changes in clothing pattern color can reflect people’s health and emotional status. At… More >

V. Premanand^*, Dhananjay Kumar

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1807-1821, 2023, DOI:10.32604/csse.2023.026742

Abstract On grounds of the advent of real-time applications, like autonomous driving, visual surveillance, and sports analysis, there is an augmenting focus of attention towards Multiple-Object Tracking (MOT). The tracking-by-detection paradigm, a commonly utilized approach, connects the existing recognition hypotheses to the formerly assessed object trajectories by comparing the similarities of the appearance or the motion between them. For an efficient detection and tracking of the numerous objects in a complex environment, a Pearson Similarity-centred Kuhn-Munkres (PS-KM) algorithm was proposed in the present study. In this light, the input videos were, initially, gathered from the MOT dataset and converted into frames.… More >

Deependra Sharma^*, Zainul Abdin Jaffery

Computer Systems Science and Engineering, Vol.44, No.1, pp. 191-204, 2023, DOI:10.32604/csse.2023.023728

Abstract This paper discusses about the new approach of multiple object tracking relative to background information. The concept of multiple object tracking through background learning is based upon the theory of relativity, that involves a frame of reference in spatial domain to localize and/or track any object. The field of multiple object tracking has seen a lot of research, but researchers have considered the background as redundant. However, in object tracking, the background plays a vital role and leads to definite improvement in the overall process of tracking. In the present work an algorithm is proposed for the multiple object tracking… More >

S. Hariharan^1,*, R. Venkatesan²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 407-422, 2022, DOI:10.32604/iasc.2022.025309

Abstract Background subtraction is a fundamental and crucial task for computer vision-based automatic video analysis due to various challenging situations that occur in real-world scenarios. This paper presents a novel background subtraction method by estimating the background model using linear regression and local spectral histogram which captures combined spectral and texture features. Different linear filters are applied on the image window centered at each pixel location and the features are captured via these filter responses. Each feature has been approximated by a linear combination of two representative features, each of which corresponds to either a background or a foreground pixel. These… More >

M. Murugesan^*, S. Thilagamani

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 389-405, 2022, DOI:10.32604/iasc.2022.024641

Abstract Automatic anomaly activity detection is difficult in video surveillance applications due to variations in size, type, shape, and objects’ location. The traditional anomaly detection and classification methods may affect the overall segmentation accuracy. It requires the working groups to judge their constant attention if the captured activities are anomalous or suspicious. Therefore, this defect creates the need to automate this process with high accuracy. In addition to being extraordinary or questionable, the display does not contain the necessary recording frame and activity standard to help the quick judgment of the parts’ specialized action. Therefore, to reduce the wastage of time… More >

Radek Martinek¹, Jan Baros¹, Rene Jaros¹, Lukas Danys^1,*, Jan Nedoma²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4659-4676, 2022, DOI:10.32604/cmc.2022.019904

Abstract This pilot study focuses on employment of hybrid LMS-ICA system for in-vehicle background noise reduction. Modern vehicles are nowadays increasingly supporting voice commands, which are one of the pillars of autonomous and SMART vehicles. Robust speaker recognition for context-aware in-vehicle applications is limited to a certain extent by in-vehicle background noise. This article presents the new concept of a hybrid system, which is implemented as a virtual instrument. The highly modular concept of the virtual car used in combination with real recordings of various driving scenarios enables effective testing of the investigated methods of in-vehicle background noise reduction. The study… More >

Mesfer Al Duhayyim¹, Haya Mesfer Alshahrani², Fahd N. Al-Wesabi³, Mohammed Alamgeer⁴, Anwer Mustafa Hilal^5,*, Manar Ahmed Hamza⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5871-5887, 2022, DOI:10.32604/cmc.2022.021093

Abstract An exponential growth in advanced technologies has resulted in the exploration of Ocean spaces. It has paved the way for new opportunities that can address questions relevant to diversity, uniqueness, and difficulty of marine life. Underwater Wireless Sensor Networks (UWSNs) are widely used to leverage such opportunities while these networks include a set of vehicles and sensors to monitor the environmental conditions. In this scenario, it is fascinating to design an automated fish detection technique with the help of underwater videos and computer vision techniques so as to estimate and monitor fish biomass in water bodies. Several models have been… More >

Qi Yue, Xiang Li, Dan Li^*

Computer Systems Science and Engineering, Vol.37, No.3, pp. 423-442, 2021, DOI:10.32604/csse.2021.014448

Abstract Forestry work has long been weak in data integration; its initial state will inevitably affect the forestry project development and decision-quality. Knowledge Graph (KG) can provide better abilities to organize, manage, and understand forestry knowledge. Relation Extraction (RE) is a crucial task of KG construction and information retrieval. Previous researches on relation extraction have proved the performance of using the attention mechanism. However, these methods focused on the representation of the entire sentence and ignored the loss of information. The lack of analysis of words and syntactic features contributes to sentences, especially in Chinese relation extraction, resulting in poor performance.… More >

LIHUA CAO¹, MINGSAN MIAO^1,*, YAN ZHENG², HUIYAUN HUANG², RUI ZHANG², DANDAN LIU²

BIOCELL, Vol.44, No.4, pp. 649-653, 2020, DOI:10.32604/biocell.2020.05093

Abstract To investigate the effects of Ginkgo paste for external use on tinea corporis in a guinea pig model. The guinea pig tinea corporis model were induced by infection with Trichophyton mentagrophytes strains. And then, high and low doses of Ginkgo water-paste and alcohol-paste were administrated to the animals. The symptom, tinea corporis skin lesions and histopathological aspects of guinea pig were analyzed. High and low doses of Ginkgo alcohol-paste and Ginkgo water-paste could significantly reduced the tinea corporis symptom (P < 0.01), increased negative rate of strain culture (P < 0.01), and improved pathological changes of tinea corporis (P <… More >