• Title/Summary/Keyword: combined systems

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A review of Chinese named entity recognition

  • Cheng, Jieren;Liu, Jingxin;Xu, Xinbin;Xia, Dongwan;Liu, Le;Sheng, Victor S.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.6
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    • pp.2012-2030
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    • 2021
  • Named Entity Recognition (NER) is used to identify entity nouns in the corpus such as Location, Person and Organization, etc. NER is also an important basic of research in various natural language fields. The processing of Chinese NER has some unique difficulties, for example, there is no obvious segmentation boundary between each Chinese character in a Chinese sentence. The Chinese NER task is often combined with Chinese word segmentation, and so on. In response to these problems, we summarize the recognition methods of Chinese NER. In this review, we first introduce the sequence labeling system and evaluation metrics of NER. Then, we divide Chinese NER methods into rule-based methods, statistics-based machine learning methods and deep learning-based methods. Subsequently, we analyze in detail the model framework based on deep learning and the typical Chinese NER methods. Finally, we put forward the current challenges and future research directions of Chinese NER technology.

Prediction of compressive strength of concrete modified with fly ash: Applications of neuro-swarm and neuro-imperialism models

  • Mohammed, Ahmed;Kurda, Rawaz;Armaghani, Danial Jahed;Hasanipanah, Mahdi
    • Computers and Concrete
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    • v.27 no.5
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    • pp.489-512
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    • 2021
  • In this study, two powerful techniques, namely particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) were selected and combined with a pre-developed ANN model aiming at improving its performance prediction of the compressive strength of concrete modified with fly ash. To achieve this study's aims, a comprehensive database with 379 data samples was collected from the available literature. The output of the database is the compressive strength (CS) of concrete samples, which are influenced by 9 parameters as model inputs, namely those related to mix composition. The modeling steps related to ICA-ANN (or neuro-imperialism) and PSO-ANN (or neuro-swarm) were conducted through the use of several parametric studies to design the most influential parameters on these hybrid models. A comparison of the CS values predicted by hybrid intelligence techniques with the experimental CS values confirmed that the neuro-swarm model could provide a higher degree of accuracy than another proposed hybrid model (i.e., neuro-imperialism). The train and test correlation coefficient values of (0.9042 and 0.9137) and (0.8383 and 0.8777) for neuro-swarm and neuro-imperialism models, respectively revealed that although both techniques are capable enough in prediction tasks, the developed neuro-swarm model can be considered as a better alternative technique in mapping the concrete strength behavior.

A Study on trend Analysis and Future Prospects of Cloud Game Industry - Focus on Device, Platform, Contents - (클라우드 게임산업 동향분석 및 전망에 관한 연구 - 디바이스, 플랫폼, 콘텐츠를 중심으로 -)

  • Doo, Ill Chul;Baek, Jae Yong;Shin, Hyun Wook
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.10 no.4
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    • pp.181-195
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    • 2014
  • The game Industry has been a major leader in business world with its size and volume in terms of profit and culture contents, and ever increasing at the moment. Cloud Game has appeared as a new, combined game format, playable on smart TV and smart phone with its upgraded storage size and fast spreading N-screen. This research studies the present reality of the cloud industry by focusing on three categories which are device type, Platform, and game contents consequently in order to determine the future prospect of cloud games. First, the cloud game business will thrive as devices such as smart TV and smart phone are used widely. Second, the cloud game industry will have a new era when OS systems of Platform are united effectively. Third, the previous platform holders will have to face new challenges brought up by cloud games' service providers. Forth, the gamer, developer, and service provider need each other in order to widen the spectrum of business in cloud game industry.

An Improved Steganography Method Based on Least-Significant-Bit Substitution and Pixel-Value Differencing

  • Liu, Hsing-Han;Su, Pin-Chang;Hsu, Meng-Hua
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.11
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    • pp.4537-4556
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    • 2020
  • This research was based on the study conducted by Khodaei et al. (2012), namely, the least-significant-bit (LSB) substitution combined with the pixel-value differencing (PVD) steganography, and presented an improved irreversible image steganography method. Such a method was developed through integrating the improved LSB substitution with the modulus function-based PVD steganography to increase steganographic capacity of the original technique while maintaining the quality of images. It partitions the cover image into non-overlapped blocks, each of which consists of 3 consecutive pixels. The 2nd pixel represents the base, in which secret data are embedded by using the 3-bit LSB substitution. Each of the other 2 pixels is paired with the base respectively for embedding secret data by using an improved modulus PVD method. The experiment results showed that the method can greatly increase steganographic capacity in comparison with other PVD-based techniques (by a maximum amount of 135%), on the premise that the quality of images is maintained. Last but not least, 2 security analyses, the pixel difference histogram (PDH) and the content-selective residual (CSR) steganalysis were performed. The results indicated that the method is capable of preventing the detection of the 2 common techniques.

Bayesian in-situ parameter estimation of metallic plates using piezoelectric transducers

  • Asadi, Sina;Shamshirsaz, Mahnaz;Vaghasloo, Younes A.
    • Smart Structures and Systems
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    • v.26 no.6
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    • pp.735-751
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    • 2020
  • Identification of structure parameters is crucial in Structural Health Monitoring (SHM) context for activities such as model validation, damage assessment and signal processing of structure response. In this paper, guided waves generated by piezoelectric transducers are used for in-situ and non-destructive structural parameter estimation based on Bayesian approach. As Bayesian approach needs iterative process, which is computationally expensive, this paper proposes a method in which an analytical model is selected and developed in order to decrease computational time and complexity of modeling. An experimental set-up is implemented to estimate three target elastic and geometrical parameters: Young's modulus, Poisson ratio and thickness of aluminum and steel plates. Experimental and simulated data are combined in a Bayesian framework for parameter identification. A significant accuracy is achieved regarding estimation of target parameters with maximum error of 8, 11 and 17 percent respectively. Moreover, the limitation of analytical model concerning boundary reflections is addressed and managed experimentally. Pulse excitation is selected as it can excite the structure in a wide frequency range contrary to conventional tone burst excitation. The results show that the proposed non-destructive method can be used in service for estimation of material and geometrical properties of structure in industrial applications.

A Simulation Study of Urban Public Transport Transfer Station Based on Anylogic

  • Liu, Weiwei;Wang, Fu;Zhang, Chennan;Zhang, Jingyu;Wang, Lei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.4
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    • pp.1216-1231
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    • 2021
  • With the increase in the population of our cities and the rapid increase in the number of private cars, urban traffic has become more and more congested. At this stage, urban public transportation has become one of the main ways to improve urban traffic congestion. Aiming at the problem of how to improve the basic capacity of buses in multi-line transfer stations, this paper conducts simulation research based on anylogic software. Through micro-simulation analysis of vehicles entering, stopping, and exiting the station, combined with the delay model theory, the vehicle is given Stop organization optimization and station layout improvement methods, so that vehicles can run in the station more stably, smoothly and safely. Case analysis shows that applying this method to the roadside parking problem, the main and auxiliary bus stations have a significant improvement in operating capacity compared with the conventional tandem double bus stations, and the service level of the main and auxiliary bus stations has been significantly improved.

Visual Object Tracking using Surface Fitting for Scale and Rotation Estimation

  • Wang, Yuhao;Ma, Jun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.5
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    • pp.1744-1760
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    • 2021
  • Since correlation filter appeared in the field of object tracking, it plays an increasingly vital role due to its excellent performance. Although many sophisticated trackers have been successfully applied to track the object accurately, very few of them attaches importance to the scale and rotation estimation. In order to address the above limitation, we propose a novel method combined with Fourier-Mellin transform and confidence evaluation strategy for robust object tracking. In the first place, we construct a correlation filter to locate the target object precisely. Then, a log-polar technique is used in the Fourier-Mellin transform to cope with the rotation and scale changes. In order to achieve subpixel accuracy, we come up with an efficient surface fitting mechanism to obtain the optimal calculation result. In addition, we introduce a confidence evaluation strategy modeled on the output response, which can decrease the impact of image noise and perform as a criterion to evaluate the target model stability. Experimental experiments on OTB100 demonstrate that the proposed algorithm achieves superior capability in success plots and precision plots of OPE, which is 10.8% points and 8.6% points than those of KCF. Besides, our method performs favorably against the others in terms of SRE and TRE validation schemes, which shows the superiority of our proposed algorithm in scale and rotation evaluation.

Optimized AI controller for reinforced concrete frame structures under earthquake excitation

  • Chen, Tim;Crosbie, Robert C.;Anandkumarb, Azita;Melville, Charles;Chan, Jcy
    • Advances in concrete construction
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    • v.11 no.1
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    • pp.1-9
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    • 2021
  • This article discusses the issue of optimizing controller design issues, in which the artificial intelligence (AI) evolutionary bat (EB) optimization algorithm is combined with the fuzzy controller in the practical application of the building. The controller of the system design includes different sub-parts such as system initial condition parameters, EB optimal algorithm, fuzzy controller, stability analysis and sensor actuator. The advantage of the design is that for continuous systems with polytypic uncertainties, the integrated H2/H∞ robust output strategy with modified criterion is derived by asymptotically adjusting design parameters. Numerical verification of the time domain and the frequency domain shows that the novel system design provides precise prediction and control of the structural displacement response, which is necessary for the active control structure in the fuzzy model. Due to genetic algorithm (GA), we use a hierarchical conditions of the Hurwitz matrix test technique and the limits of average performance, Hierarchical Fitness Function Structure (HFFS). The dynamic fuzzy controller proposed in this paper is used to find the optimal control force required for active nonlinear control of building structures. This method has achieved successful results in closed system design from the example.

Supply Chain Trust Evaluation Model Based on Improved Chain Iteration Method

  • Jiao, Hongqiang;Ding, Wanning;Wang, Xinxin
    • Journal of Information Processing Systems
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    • v.17 no.1
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    • pp.136-150
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    • 2021
  • The modern market is highly competitive. It has progressed from traditional competition between enterprises to competition between supply chains. To ensure that enterprise can form the best strategy consistently, it is necessary to evaluate the trust of other enterprises in the supply chain. First, this paper analyzes the background and significance of supply chain trust research, analyzes and expounds on the qualitative and quantitative methods of supply chain trust evaluation, and summarizes the research in this field. Analytic hierarchy process (AHP) is the most frequently used method in the literature to evaluate and rank criteria through data analysis. However, the input data for AHP analysis is based on human judgment, and hence there is every possibility that the data may be vague to some extent. Therefore, in view of the above problems, this study improves the global trust method based on chain iteration. The improved global trust evaluation method based on chain iteration is more flexible and practical, hence, it can more accurately evaluate supply chain trust. Finally, combined with an actual case of Zhaoxian Chengji Food Co. Ltd., the paper qualitatively analyzes the current situation of supply chain trust management and effectively strengthens the supervision of enterprises to cooperative enterprises. Thus, the company can identify problems on time and strategic adjustments can be implemented accordingly. The effectiveness of the evaluation method proposed in this paper is demonstrated through a quantitative evaluation of its trust in downstream enterprise A. Results suggest that the subjective preferences of and historical transactions together affect the final evaluation of trust.

Application of steel-concrete composite pile foundation system as energy storage medium

  • Agibayeva, Aidana;Lee, Deuckhang;Ju, Hyunjin;Zhang, Dichuan;Kim, Jong R.
    • Structural Engineering and Mechanics
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    • v.77 no.6
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    • pp.753-763
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    • 2021
  • Feasibility studies of a reinforced concrete (RC) deep pile foundation system with the compressed air energy storage (CAES) technology were conducted in previous studies. However, those studies showed some technical limitations in its serviceability and durability performances. To overcome such drawbacks of the conventional RC energy pile system, various steel-concrete composite pile foundations are addressed in this study to be utilized as a dual functional system for an energy storage medium and load-resistant foundation. This study conducts finite element analyses to examine the applicability of various composite energy pile foundation systems considering the combined effects of structural loading, soil boundary forces, and internal air pressures induced by the thermos-dynamic cycle of compressed air. On this basis, it was clearly confirmed that the role of inner and outer tubes is essential in terms of reliable storage tank and better constructability of pile, respectively, and the steel tubes in the composite pile foundation can also ensure improved serviceability and durability performances compared to the conventional RC pile system.