YAJIE LIU, LINLIN FANG, CHUNXUE YANG^*

BIOCELL, Vol.46, No.11, pp. 2475-2488, 2022, DOI:10.32604/biocell.2022.021477

Abstract Arbuscular mycorrhizal (AM) fungi are widely distributed in various habitats, and the community composition varies in response to the changing environmental conditions. To explore the response of community composition to the succession of saline-alkali land, soil samples were collected from three succession stages of Songnen saline-alkali grassland. Subsequently, the soil characteristics were determined and the AM fungi in soil samples were analyzed by high-throughput sequencing. Then, the response relationship between community composition and soil characteristics was studied by Canonical correlation and Pearson analyses. The soil properties improved with the succession of saline-alkali grassland. There was no significant difference in alpha… More >

Shenglong Wang^1,*, Jing Yang^1,*, Xiaoyu Ding², Jianpei Zhang¹, Meng Zhao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 215-249, 2022, DOI:10.32604/cmes.2022.018050

Abstract In recent years, local community detection algorithms have developed rapidly because of their nearly linear computing time and the convenience of obtaining the local information of real-world networks. However, there are still some issues that need to be further studied. First, there is no local community detection algorithm dedicated to detecting a seed-oriented local community, that is, the local community with the seed as the core. The second and third issues are that the quality of local communities detected by the previous local community detection algorithms are largely dependent on the position of the seed and predefined parameters, respectively. To… More >

K. Chitra^*, A. Tamilarasi

Computer Systems Science and Engineering, Vol.44, No.1, pp. 327-337, 2023, DOI:10.32604/csse.2023.023920

Abstract The structure and dynamic nature of real-world networks can be revealed by communities that help in promotion of recommendation systems. Social Media platforms were initially developed for effective communication, but now it is being used widely for extending and to obtain profit among business community. The numerous data generated through these platforms are utilized by many companies that make a huge profit out of it. A giant network of people in social media is grouped together based on their similar properties to form a community. Community detection is recent topic among the research community due to the increase usage of… More >

Jiaming Wang², Xiaolan Xie^1,2,*, Xiaochun Cheng³, Yuhan Wang²

Computer Systems Science and Engineering, Vol.43, No.3, pp. 997-1008, 2022, DOI:10.32604/csse.2022.027005

Abstract

There is a large amount of information in the network data that we can exploit. It is difficult for classical community detection algorithms to handle network data with sparse topology. Representation learning of network data is usually paired with clustering algorithms to solve the community detection problem. Meanwhile, there is always an unpredictable distribution of class clusters output by graph representation learning. Therefore, we propose an improved density peak clustering algorithm (ILDPC) for the community detection problem, which improves the local density mechanism in the original algorithm and can better accommodate class clusters of different shapes. And we study the… More >

Haibin Cao¹, Houqi Dong¹, Yongjie Ren¹, Yuqing Wang^2,*, Na Li³, Ming Zeng¹

Energy Engineering, Vol.119, No.3, pp. 965-984, 2022, DOI:10.32604/ee.2022.020051

Abstract As the proportion of renewable energy power generation continues to increase, the number of grid-connected microgrids is gradually increasing, and geographically adjacent microgrids can be interconnected to form a Micro-Grid Community (MGC). In order to reduce the operation and maintenance costs of a single micro grid and reduce the adverse effects caused by unnecessary energy interaction between the micro grid and the main grid while improving the overall economic benefits of the micro grid community, this paper proposes a bi-level energy management model with the optimization goal of maximizing the social welfare of the micro grid community and minimizing the… More >

Xin Zhang^*, Jinpeng Jiang, Haoran Zheng, Jihong Zhang

Energy Engineering, Vol.119, No.3, pp. 1117-1140, 2022, DOI:10.32604/ee.2022.017288

Abstract China consumes significant amount of natural gas in winter. The integrated community energy utilization system (ICEUS) cannot stabilize the output of electricity and heat if there is a shortage of natural gas. The operation cost of the system still needs improvement. An energy supply structure using garbage power as the core of ICEUS was established in the study. The optimal dispatching model of ICEUS was established using the regulating characteristic of the community load. The sine-cosine algorithm (SCA) based on nonlinear factors and segmented weight was presented to solve the optimal dispatching model of ICEUS. From the simulation results, compared… More >

Muhammad Sanaullah^1,*, Muhammad Kashif², Babar Ahmad², Tauqeer Safdar², Mehdi Hassan³, Mohd Hilmi Hasan⁴, Amir Haider⁵

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2501-2519, 2022, DOI:10.32604/cmc.2022.021990

Abstract Communication is a basic need of every human being to exchange thoughts and interact with the society. Acute peoples usually confab through different spoken languages, whereas deaf people cannot do so. Therefore, the Sign Language (SL) is the communication medium of such people for their conversation and interaction with the society. The SL is expressed in terms of specific gesture for every word and a gesture is consisted in a sequence of performed signs. The acute people normally observe these signs to understand the difference between single and multiple gestures for singular and plural words respectively. The signs for singular… More >

Yue Jiang, Xinyu Zhang, Wohuan Jia, Li Xu^*

Journal on Artificial Intelligence, Vol.3, No.4, pp. 163-169, 2021, DOI:10.32604/jai.2021.027590

Abstract As a new type of knowledge sharing platform, the community question answer website realizes the acquisition and sharing of knowledge, and is loved and sought after by the majority of users. But for multi-answer questions, answer quality assessment becomes a challenge. The answer selection in CQA (Community Question Answer) was proposed as a challenge task in the SemEval competition, which gave a data set and proposed two subtasks. Task-A is to give a question (including short title and extended description) and its answers, and divide each answer into absolutely relevant (good), potentially relevant (potential) and bad or irrelevant (bad, dialog,… More >

Yun-Jung Choi¹, Mi-Ra Won², Dong-Hee Cho^1,*

International Journal of Mental Health Promotion, Vol.24, No.1, pp. 85-94, 2022, DOI:10.32604/ijmhp.2022.018017

Abstract As industries develop, fire disasters and their associated damage are increasing. Investigating the mental health of victims is imperative because this is an essential issue for community recovery after a disaster. This study was conducted to determine the efficacy of a program implemented by a community mental health center based on the investigation of the victims’ depression and post-traumatic stress disorder (PTSD) levels immediately after the disaster and at one-year follow-up. As a result, victims’ depression and PTSD recovered over time, and more changes were confirmed. In particular, the high-risk group for PTSD showed a high program participation rate, and… More >

G. Naga Chandrika¹, Khalid Alnowibet², K. Sandeep Kautish³, E. Sreenivasa Reddy⁴, Adel F. Alrasheedi², Ali Wagdy Mohamed^5,6,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5707-5720, 2022, DOI:10.32604/cmc.2022.021186

Abstract Graphs are used in various disciplines such as telecommunication, biological networks, as well as social networks. In large-scale networks, it is challenging to detect the communities by learning the distinct properties of the graph. As deep learning has made contributions in a variety of domains, we try to use deep learning techniques to mine the knowledge from large-scale graph networks. In this paper, we aim to provide a strategy for detecting communities using deep autoencoders and obtain generic neural attention to graphs. The advantages of neural attention are widely seen in the field of NLP and computer vision, which has… More >