Si-Yi Chen¹, Gang Xu², Xiu-Bo Chen¹, Haseeb Ahmad³, Yu-Ling Chen^4,*

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 273-284, 2021, DOI:10.32604/iasc.2021.018120 - 26 July 2021

Abstract Quantum network coding can effectively improve the aggregate throughput of quantum networks and alleviate bottlenecks caused by topological constraints. Most of previous schemes are dedicated to the efficient teleportation of unknown quantum states in a quantum network. Herein a proposal for transmission of deterministic known states over quantum repeater network based on quantum measurements. We show that the new protocol offers advantages over three aspects. Firstly, the senders in our protocol obtain the knowledge of the quantum state to be transmitted, which enables the autonomy of quantum network transmission. Secondly, we study the quantum repeater More >

Azeem Shera¹, Muhammad Waseem Iqbal^2,*, Syed Khuram Shahzad³, Madeeha Gul¹, Natash Ali Mian⁴, Muhammad Raza Naqvi⁵, Babar Ayub Khan¹

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 285-301, 2021, DOI:10.32604/iasc.2021.018009 - 26 July 2021

Abstract Blind and visually impaired (BVI) users often have interface accessibility problems while using mobile applications. This study was conducted to reduce the cognitive effort required for interface navigation by identifying the accessibility issues according to the user’s mental model. The study evaluated the accessibility of smartphone screens to solve organizational, presentation, and behavioral (OPB) problems of using mobile applications. Usability evaluation of an application was conducted and validated with a specific focus on BVI user experience. A total of 56 BVI participants were included in the evaluation. Overall, four tasks to assess organization, avoidance of… More >

Mamoona Majid¹, Muhammad Faisal Hayat², Farrukh Zeeshan Khan³, Muneer Ahmad^4,*, NZ Jhanjhi⁵, Mohammad Arif Sobhan Bhuiyan⁶, Mehedi Masud⁷, Mohammed A. AlZain⁸

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 373-386, 2021, DOI:10.32604/iasc.2021.017840 - 26 July 2021

Abstract Choosing the right university program can be very challenging for students. This is especially the case in developing countries such as India and Pakistan, where university admission depends on not only the program of interest but also other factors such as the candidate’s financial standing. Since information on the Internet can be highly scattered, university candidates often need counseling from qualified people to decide their educational programs. Traditional database systems cannot effectively organize the large unstructured data related to university programs. It is challenging, then, for prospective students to acquire the information needed to make More >

Hao Wu^1,*, B. Nagaraj²

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 81-95, 2021, DOI:10.32604/iasc.2021.017654 - 26 July 2021

Abstract English teaching has always attracted much attention. However, the processes of its transmission and acquirement is often divided into two separate parts, which seriously hinders the effective implementation of its objectives. Teachers attach particular importance to the choice of the curriculum structure and teaching material. Students are busy comprehending the assignments their teachers deem important. Under such a scenario, the effective acquisition of knowledge and the development of sustainable comprehensive abilities are ignored. The random forest algorithm in machine learning applications could play important role improving on the current English teaching system. A random forest… More >

Qin Zhang¹, Xuyu Xiang^1,*, Jiaohua Qin¹, Yun Tan¹, Qiang Liu¹, Neal N. Xiong²

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 227-241, 2021, DOI:10.32604/iasc.2021.017648 - 26 July 2021

Abstract With the rapid development of network media, the short text has become the main cover of information dissemination by quickly disseminating relevant entity information. However, the lack of context in the short text can easily lead to ambiguity, which will greatly reduce the efficiency of obtaining information and seriously affect the user’s experience, especially in the financial field. This paper proposed an entity disambiguation algorithm based on multi-word vector ensemble and decision to eliminate the ambiguity of entities and purify text information in information processing. First of all, we integrate a variety of unsupervised pre-trained… More >

K. Kalaivani^*, M. Chinnadurai

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 1-15, 2021, DOI:10.32604/iasc.2021.017515 - 26 July 2021

Abstract Fog computing extends the concept of cloud computing by providing the services of computing, storage, and networking connectivity at the edge between data centers in cloud computing environments and end devices. Having the intelligence at the edge enables faster real-time decision-making and reduces the amount of data forwarded to the cloud. When enhanced by fog computing, the Internet of Things (IoT) brings low latency and improves real time and quality of service (QoS) in IoT applications of augmented reality, smart grids, smart vehicles, and healthcare. However, both cloud and fog computing environments are vulnerable to… More >

Ghassan Ahmed Ali^*

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 351-360, 2021, DOI:10.32604/iasc.2021.017453 - 26 July 2021

Abstract Many living organisms respond to pandemics using strategies such as isolation. This is true, for example, of social insects, for whom the spread of disease can pose a high risk to colony survival. In light of such behaviors, the present study investigated a different way of developing strategies to mitigate the effects of the coronavirus pandemic. Specifically, we considered the strategies ants use to handle epidemics and limit disease spread within colonies. To enhance our understanding of these strategies, we explored ants’ social systems and how they specifically respond to infectious diseases. The early warning… More >

Gaigai Jin¹, Junsheng Zhou^1,*, Weiguang Qu¹, Yunfei Long², Yanhui Gu¹

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 161-173, 2021, DOI:10.32604/iasc.2021.017440 - 26 July 2021

Abstract Event causality identification is an essential task for information extraction that has attracted growing attention. Early researchers were accustomed to combining the convolutional neural network or recurrent neural network models with external causal knowledge, but these methods ignore the importance of rich semantic representation of the event. The event is more structured, so it has more abundant semantic representation. We argue that the elements of the event, the interaction of the two events, and the context between the two events can enrich the event’s semantic representation and help identify event causality. Therefore, the effective semantic… More >

Jianming Zhao^1,2,3,4, Peng Zeng^1,2,3,4,*, Chunyu Chen^1,2,3,4, Zhiwei Dong⁵, Jongho Han⁶

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 337-350, 2021, DOI:10.32604/iasc.2021.016966 - 26 July 2021

Abstract As networked control systems continue to be widely used in large-scale industrial productions, industrial cyber-attacks have become an inevitable problem that can cause serious damage to critical infrastructures. In practice, industrial intrusion detection has been widely acknowledged to detect abnormal communication behaviors. However, unlike traditional IT systems, networked control systems have their own communication characteristics due to specific industrial communication protocols. Thus, simple cyber-attack modeling is inadequate and impractical for high-efficiency intrusion detection because the characteristics of network control systems are less considered. Based on the status information and transmission connection in industrial communication data… More >

Juan Huang¹, Bifang Zhou¹, Huajun Huang^2,*, Dingwen Qing¹, Neal N. Xiong³

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 303-318, 2021, DOI:10.32604/iasc.2021.016953 - 26 July 2021

Abstract There are various influencing factors in regional FDI (foreign direct investment) and it is difficult to identify the main influencing factors. For this reason, a main factor selection algorithm is proposed in this article for the main factors affecting regional FDI statistics by analyzing the regional economic characteristics and the possible influencing factors in the regional FDI. Then, an example is used to illustrate its effectiveness and its stability. Firstly, the characteristics of regional economy and the regional FDI data are introduced to develop the main factor selection algorithm based on the adaptive Lasso problem… More >