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KSII Transactions on Internet and Information Systems (TIIS) update

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  • : 공학분야  >  기타(공학)
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수록정보
15권7호(2021) |수록논문 수 : 20
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15권8호(2021년 08월) 수록논문
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KCI등재 SCI SCOPUS

1Impact Force Reconstruction of Composite materials based on Improved Regularization Technology

저자 : Yajie Sun , Tao Yin , Jian Yang , Zhiyu Cai , Shaoen Wu

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 8호 발행 연도 : 2021 페이지 : pp. 2718-2731 (14 pages)

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In the structural health monitoring of composite materials, in order to solve the ill-posed problem of impact force reconstruction, regularization techniques are often used to deal with it. Due to the poor convergence of the traditional Tikhonov regularization method, in order to accurately reconstruct the time history of the impact force, this paper improves Tikhonov regularization method and constructs homotopy function with strong convergence. Since the optimal regularization parameters need to be found in the homotopy function, the Newton downhill method is used to find the optimal parameters and the homotopy function can be calculated, which can accurately reconstruct the time history of the impact force. In order to verify the universality of the method in this paper, impact hammers of different materials were used in the experiment in this paper to study and compare the reconstruction effect of impact time history of different impact hammers.

KCI등재 SCI SCOPUS

2Integrated Media Platform-based Virtual Office Hours Implementation for Online Teaching in Post-COVID-19 Pandemic Era

저자 : Mingzi Chen , Xin Wei , Liang Zhou

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 8호 발행 연도 : 2021 페이지 : pp. 2732-2748 (17 pages)

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In post-COVID-19 pandemic era, students' learning effects and experience may sharply decrease when teaching is transferred from offline to online. Several tools suitable for online teaching have been developed to guarantee and promote students' learning effects. However, they cannot fully consider teacher-student interaction in online teaching. To figure out this issue, this paper proposes integrated media platform-based virtual office hours implementation for online teaching. Specifically, an integrated media platform (IMP) is first constructed. Then, virtual office hours (VOH) is implemented based on the IMP, aiming at increasing student-teacher interactions. For evaluating the effectiveness of this scheme, 140 undergraduate students using IMP are divided into one control group and three experimental groups that respectively contain text, voice and video modes. The experiment results indicate that applying VOH in the IMP can improve students' online presence and test scores. Furthermore, students' participating modes during VOH implementation can largely affect their degree of presence, which can be well classified by using principal component analysis. The implication of this work is that IMP-based VOH is an effective and sustainable tool to be continuously implemented even when the COVID-19 pandemic period ends.

KCI등재 SCI SCOPUS

3Reflectance estimation for infrared and visible image fusion

저자 : Yan Gu , Feng Yang , Weijun Zhao , Yiliang Guo , Chaobo Min

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 8호 발행 연도 : 2021 페이지 : pp. 2749-2763 (15 pages)

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The desirable result of infrared (IR) and visible (VIS) image fusion should have textural details from VIS images and salient targets from IR images. However, detail information in the dark regions of VIS image has low contrast and blurry edges, resulting in performance degradation in image fusion. To resolve the troubles of fuzzy details in dark regions of VIS image fusion, we have proposed a method of reflectance estimation for IR and VIS image fusion. In order to maintain and enhance details in these dark regions, dark region approximation (DRA) is pro-posed to optimize the Retinex model.With the improved Retinex model based on DRA, quasi-Newton method is adopted to estimate the reflectance of a VIS image. The final fusion out-come is obtained by fusing the DRA-based reflectance of VIS image with IR image. Our method could simultaneously retain the low visibility details in VIS images and the high con-trast targets in IR images. Experiment statistic shows that compared to some advanced ap-proaches, the proposed method has superiority on detail preservation and visual quality.

KCI등재 SCI SCOPUS

4A City-Level Boundary Nodes Identification Algorithm Based on Bidirectional Approaching

저자 : Zhiyuan Tao , Fenlin Liu , Yan Liu , Xiangyang Luo

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 8호 발행 연도 : 2021 페이지 : pp. 2764-2782 (19 pages)

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Existing city-level boundary nodes identification methods need to locate all IP addresses on the path to differentiate which IP is the boundary node. However, these methods are susceptible to time-delay, the accuracy of location information and other factors, and the resource consumption of locating all IPes is tremendous. To improve the recognition rate and reduce the locating cost, this paper proposes an algorithm for city-level boundary node identification based on bidirectional approaching. Different from the existing methods based on time-delay information and location results, the proposed algorithm uses topological analysis to construct a set of candidate boundary nodes and then identifies the boundary nodes. The proposed algorithm can identify the boundary of the target city network without high-precision location information and dramatically reduces resource consumption compared with the traditional algorithm. Meanwhile, it can label some errors in the existing IP address database. Based on 45,182,326 measurement results from Zhengzhou, Chengdu and Hangzhou in China and New York, Los Angeles and Dallas in the United States, the experimental results show that: The algorithm can accurately identify the city boundary nodes using only 20.33% location resources, and more than 80.29% of the boundary nodes can be mined with a precision of more than 70.73%.

KCI등재 SCI SCOPUS

5A Dynamic Adjustment Method of Service Function Chain Resource Configuration

저자 : Xiaoyang Han , Xiangru Meng , Zhenhua Yu , Dong Zhai

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 8호 발행 연도 : 2021 페이지 : pp. 2783-2804 (22 pages)

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In the network function virtualization environment, dynamic changes in network traffic will lead to the dynamic changes of service function chain resource demand, which entails timely dynamic adjustment of service function chain resource configuration. At present, most researches solve this problem through virtual network function migration and link rerouting, and there exist some problems such as long service interruption time, excessive network operation cost and high penalty. This paper proposes a dynamic adjustment method of service function chain resource configuration for the dynamic changes of network traffic. First, a dynamic adjustment request of service function chain is generated according to the prediction of network traffic. Second, a dynamic adjustment strategy of service function chain resource configuration is determined according to substrate network resources. Finally, the resource configuration of a service function chain is pre-adjusted according to the dynamic adjustment strategy. Virtual network functions combination and virtual machine reusing are fully considered in this process. The experimental results show that this method can reduce the influence of service function chain resource configuration dynamic adjustment on quality of service, reduce network operation cost and improve the revenue of service providers.

KCI등재 SCI SCOPUS

6Polymorphic Path Transferring for Secure Flow Delivery

저자 : Rongbo Zhang , Xin Li , Yan Zhan

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 8호 발행 연도 : 2021 페이지 : pp. 2805-2826 (22 pages)

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In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.

KCI등재 SCI SCOPUS

7A Lightweight and Privacy-Preserving Answer Collection Scheme for Mobile Crowdsourcing

저자 : Yingling Dai , Jian Weng , Anjia Yang , Shui Yu , Robert H. Deng

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 8호 발행 연도 : 2021 페이지 : pp. 2827-2848 (22 pages)

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Mobile Crowdsourcing (MCS) has become an emerging paradigm evolved from crowdsourcing by employing advanced features of mobile devices such as smartphones to perform more complicated, especially spatial tasks. One of the key procedures in MCS is to collect answers from mobile users (workers), which may face several security issues. First, authentication is required to ensure that answers are from authorized workers. In addition, MCS tasks are usually location-dependent, so the collected answers could disclose workers' location privacy, which may discourage workers to participate in the tasks. Finally, the overhead occurred by authentication and privacy protection should be minimized since mobile devices are resource-constrained. Considering all the above concerns, in this paper, we propose a lightweight and privacy-preserving answer collection scheme for MCS. In the proposed scheme, we achieve anonymous authentication based on traceable ring signature, which provides authentication, anonymity, as well as traceability by enabling malicious workers tracing. In order to balance user location privacy and data availability, we propose a new concept named current location privacy, which means the location of the worker cannot be disclosed to anyone until a specified time. Since the leakage of current location will seriously threaten workers' personal safety, causing such as absence or presence disclosure attacks, it is necessary to pay attention to the current location privacy of workers in MCS. We encrypt the collected answers based on timed-release encryption, ensuring the secure transmission and high availability of data, as well as preserving the current location privacy of workers. Finally, we analyze the security and performance of the proposed scheme. The experimental results show that the computation costs of a worker depend on the number of ring signature members, which indicates the flexibility for a worker to choose an appropriate size of the group under considerations of privacy and efficiency.

KCI등재 SCI SCOPUS

8UEPF:A blockchain based Uniform Encoding and Parsing Framework in multi-cloud environments

저자 : Dehao Tao , Zhen Yang , Xuanmei Qin , Qi Li , Yongfeng Huang , Yubo Luo

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 8호 발행 연도 : 2021 페이지 : pp. 2849-2864 (16 pages)

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The emerging of cloud data sharing can create great values, especially in multi-cloud environments. However, “data island” between different cloud service providers (CSPs) has drawn trust problem in data sharing, causing contradictions with the increasing sharing need of cloud data users. And how to ensure the data value for both data owner and data user before sharing, is another challenge limiting massive data sharing in the multi-cloud environments. To solve the problems above, we propose a Uniform Encoding and Parsing Framework (UEPF) with blockchain to support trustworthy and valuable data sharing. We design namespace-based unique identifier pair to support data description corresponding with data in multi-cloud, and build a blockchain-based data encoding protocol to manage the metadata with identifier pair in the blockchain ledger. To share data in multi-cloud, we build a data parsing protocol with smart contract to query and get the sharing cloud data efficiently. We also build identifier updating protocol to satisfy the dynamicity of data, and data check protocol to ensure the validity of data. Theoretical analysis and experiment results show that UEPF is pretty efficient.

KCI등재 SCI SCOPUS

9Recoverable Private Key Scheme for Consortium Blockchain Based on Verifiable Secret Sharing

저자 : Guojia Li , Lin You , Gengran Hu , Liqin Hu

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 8호 발행 연도 : 2021 페이지 : pp. 2865-2878 (14 pages)

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As a current popular technology, the blockchain has a serious issue: the private key cannot be retrieved due to force majeure. Since the outcome of the blockchain-based Bitcoin, there have been many occurrences of the users who lost or forgot their private keys and could not retrieve their token wallets, and it may cause the permanent loss of their corresponding blockchain accounts, resulting in irreparable losses for the users. We propose a recoverable private key scheme for consortium blockchain based on the verifiable secret sharing which can enable the user's private key in the consortium blockchain to be securely recovered through a verifiable secret sharing method. In our secret sharing scheme, users use the biometric keys to encrypt shares, and the preset committer peers in the consortium blockchain act as the participants to store the users' private key shares. Due to the particularity of the biometric key, only the user can complete the correct secret recovery. Our comparisons with the existing mnemonic systems or the multi-signature schemes have shown that our scheme can allow users to recover their private keys without storing the passwords accurately. Hence, our scheme can improve the account security and recoverability of the data-sharing systems across physical and virtual platforms that use blockchain technology.

KCI등재 SCI SCOPUS

10Cyclic Shift Based Tone Reservation PAPR Reduction Scheme with Embedding Side Information for FBMC-OQAM Systems

저자 : Yongpeng Shi , Yujie Xia , Ya Gao , Jianhua Cui

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 8호 발행 연도 : 2021 페이지 : pp. 2879-2899 (21 pages)

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The tone reservation (TR) scheme is an attractive method to reduce peak-to-average power ratio (PAPR) in the filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) systems. However, the high PAPR of FBMC signal will severely degrades system performance. To address this issue, a cyclic shift based TR (CS-TR) scheme with embedding side information (SI) is proposed to reduce the PAPR of FBMC signals. At the transmitter, four candidate signals are first generated based on cyclic shift of the output of inverse discrete Fourier transform (IDFT), and the SI of the selected signal with minimum peak power among the four candidate signals is embedded in sparse symbols with quadrature phase-shift keying constellation. Then, the TR weighted by optimal scaling factor is employed to further reduce PAPR of the selected signal. At the receiver, a reliable SI detector is presented by determining the phase rotation of SI embedding symbols, and the transmitted data blocks can be correctly demodulated according to the detected SI. Simulation results show that the proposed scheme significantly outperforms the existing TR schemes in both PAPR reduction and bit error rate (BER) performances. In addition, the proposed scheme with detected SI can achieve the same BER performance compared to the one with perfect SI.

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KCI등재SCISCOUPUS

1CAB: Classifying Arrhythmias based on Imbalanced Sensor Data

저자 : Yilin Wang , Le Sun , Sudha Subramani

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 7호 발행 연도 : 2021 페이지 : pp. 2304-2320 (17 pages)

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Intelligently detecting anomalies in health sensor data streams (e.g., Electrocardiogram, ECG) can improve the development of E-health industry. The physiological signals of patients are collected through sensors. Timely diagnosis and treatment save medical resources, promote physical health, and reduce complications. However, it is difficult to automatically classify the ECG data, as the features of ECGs are difficult to extract. And the volume of labeled ECG data is limited, which affects the classification performance. In this paper, we propose a Generative Adversarial Network (GAN)-based deep learning framework (called CAB) for heart arrhythmia classification. CAB focuses on improving the detection accuracy based on a small number of labeled samples. It is trained based on the class-imbalance ECG data. Augmenting ECG data by a GAN model eliminates the impact of data scarcity. After data augmentation, CAB classifies the ECG data by using a Bidirectional Long Short Term Memory Recurrent Neural Network (Bi-LSTM). Experiment results show a better performance of CAB compared with state-of-the-art methods. The overall classification accuracy of CAB is 99.71%. The F1-scores of classifying Normal beats (N), Supraventricular ectopic beats (S), Ventricular ectopic beats (V), Fusion beats (F) and Unclassifiable beats (Q) heartbeats are 99.86%, 97.66%, 99.05%, 98.57% and 99.88%, respectively.
Unclassifiable beats (Q) heartbeats are 99.86%, 97.66%, 99.05%, 98.57% and 99.88%, respectively.

KCI등재SCISCOUPUS

2DeepPTP: A Deep Pedestrian Trajectory Prediction Model for Traffic Intersection

저자 : Zhiqiang Lv , Jianbo Li , Chuanhao Dong , Yue Wang , Haoran Li , Zhihao Xu

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 7호 발행 연도 : 2021 페이지 : pp. 2321-2338 (18 pages)

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Compared with vehicle trajectories, pedestrian trajectories have stronger degrees of freedom and complexity, which poses a higher challenge to trajectory prediction tasks. This paper designs a mode to divide the trajectory of pedestrians at a traffic intersection, which converts the trajectory regression problem into a trajectory classification problem. This paper builds a deep model for pedestrian trajectory prediction at intersections for the task of pedestrian short-term trajectory prediction. The model calculates the spatial correlation and temporal dependence of the trajectory. More importantly, it captures the interactive features among pedestrians through the Attention mechanism. In order to improve the training speed, the model is composed of pure convolutional networks. This design overcomes the single-step calculation mode of the traditional recurrent neural network. The experiment uses Vulnerable Road Users trajectory dataset for related modeling and evaluation work. Compared with the existing models of pedestrian trajectory prediction, the model proposed in this paper has advantages in terms of evaluation indicators, training speed and the number of model parameters.

KCI등재SCISCOUPUS

3An IoT based Green Home Architecture for Green Score Calculation towards Smart Sustainable Cities

저자 : K. Manikanda Kumaran , M. Chinnadurai , S. Manikandan , S. Palani Murugan , E. Elakiya

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 7호 발행 연도 : 2021 페이지 : pp. 2337-2358 (22 pages)

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In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

KCI등재SCISCOUPUS

4A Novel Algorithm of Joint Probability Data Association Based on Loss Function

저자 : Hao Jiao , Yunxue Liu , Hui Yu , Ke Li , Feiyuan Long , Yingjie Cui

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 7호 발행 연도 : 2021 페이지 : pp. 2339-2355 (17 pages)

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In this paper, a joint probabilistic data association algorithm based on loss function (LJPDA) is proposed so that the computation load and accuracy of the multi-target tracking algorithm can be guaranteed simultaneously. Firstly, data association is divided in to three cases based on the relationship among validation gates and the number of measurements in the overlapping area for validation gates. Also the contribution coefficient is employed for evaluating the contribution of a measurement to a target, and the loss function, which reflects the cost of the new proposed data association algorithm, is defined. Moreover, the equation set of optimal contribution coefficient is given by minimizing the loss function, and the optimal contribution coefficient can be attained by using the Newton-Raphson method. In this way, the weighted value of each target can be achieved, and the data association among measurements and tracks can be realized. Finally, we compare performances of LJPDA proposed and joint probabilistic data association (JPDA) algorithm via numerical simulations, and much attention is paid on real-time performance and estimation error. Theoretical analysis and experimental results reveal that the LJPDA algorithm proposed exhibits small estimation error and low computation complexity.

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5Evolutionary Neural Network based on Quantum Elephant Herding Algorithm for Modulation Recognition in Impulse Noise

저자 : Hongyuan Gao , Shihao Wang , Yumeng Su , Helin Sun , Zhiwei Zhang

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 7호 발행 연도 : 2021 페이지 : pp. 2356-2376 (21 pages)

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In this paper, we proposed a novel modulation recognition method based on quantum elephant herding algorithm (QEHA) evolving neural network under impulse noise environment. We use the adaptive weight myriad filter to preprocess the received digital modulation signals which passing through the impulsive noise channel, and then the instantaneous characteristics and high order cumulant features of digital modulation signals are extracted as classification feature set, finally, the BP neural network (BPNN) model as a classifier for automatic digital modulation recognition. Besides, based on the elephant herding optimization (EHO) algorithm and quantum computing mechanism, we design a quantum elephant herding algorithm (QEHA) to optimize the initial thresholds and weights of the BPNN, which solves the problem that traditional BPNN is easy into local minimum values and poor robustness. The experimental results prove that the adaptive weight myriad filter we used can remove the impulsive noise effectively, and the proposed QEHA-BPNN classifier has better recognition performance than other conventional pattern recognition classifiers. Compared with other global optimization algorithms, the QEHA designed in this paper has a faster convergence speed and higher convergence accuracy. Furthermore, the effect of symbol shape has been considered, which can satisfy the need for engineering.

KCI등재SCISCOUPUS

6A Hybrid Recommendation System based on Fuzzy C-Means Clustering and Supervised Learning

저자 : Li Duan , Weiping Wang , Baijing Han

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 7호 발행 연도 : 2021 페이지 : pp. 2399-2413 (15 pages)

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A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users. However, the cold-start problem of users and items is still a major research hotspot on service recommendations. To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models. The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering. The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity. The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.

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7Automation Monitoring With Sensors For Detecting Covid Using Backpropagation Algorithm

저자 : Pravin R. Kshirsagar , Hariprasath Manoharan , Vineet Tirth , Mohd Naved , Ahmad Tasnim Siddiqui , Arvind K. Sharma

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 7호 발행 연도 : 2021 페이지 : pp. 2414-2433 (20 pages)

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This article focuses on providing remedial solutions for COVID disease through the data collection process. Recently, In India, sudden human losses are happening due to the spread of infectious viruses. All people are not able to differentiate the number of affected people and their locations. Therefore, the proposed method integrates robotic technology for monitoring the health condition of different people. If any individual is affected by infectious disease, then data will be collected and within a short span of time, it will be reported to the control center. Once, the information is collected, then all individuals can access the same using an application platform. The application platform will be developed based on certain parametric values, where the location of each individual will be retained. For precise application development, the parametric values related to the identification process such as sub-interval points and intensity of detection should be established. Therefore, to check the effectiveness of the proposed robotic technology, an online monitoring system is employed where the output is realized using MATLAB. From simulated values, it is observed that the proposed method outperforms the existing method in terms of data quality with an observed percentage of 82.

KCI등재SCISCOUPUS

8A Study of Resource Utilization Improvement on Cloud Testing Platform

저자 : Jong-yih Kuo , Hui-chi Lin , Chien-hung Liu

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 7호 발행 연도 : 2021 페이지 : pp. 2434-2454 (21 pages)

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This paper developed the software testing factory-cloud testing platform (STF-CTP) to address the software compatible issues in various smart devices. Software developers who only require uploading the application under test (AUT) and test script can test plenty of smart devices in STF-CTP. The challenge for the cloud test platform is how to optimize the resource and increase the performance in the limited resource. This paper proposed a new scheduling mechanism and a new process of the system operation which is based on the OpenStack platform. We decrease about 40% memory usage of OpenStack server, increase 3% to 10% Android device usage of STF-CTP, enhance about 80% test job throughput and reduces about 40% test job average waiting time.

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9Quality Driven Approach for Product Line Architecture Customization in Patient Navigation Program Software Product Line

저자 : Afifah M. Ashari , Shahliza Abd Halim , Dayang N. A. Jawawi , Ushananthiny Suvelayutnan , Mohd Adham Isa

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 7호 발행 연도 : 2021 페이지 : pp. 2455-2475 (21 pages)

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Patient Navigation Program (PNP) is considered as an important implementation of health care systems that can assist in patient's treatment. Due to the feasibility of PNP implementation, a systematic reuse is needed for a wide adoption of PNP computerized system. SPL is one of the promising systematic reuse approaches for creating a reusable architecture to enabled reuse in several similar applications of PNP systems which has its own variations with other applications. However, stakeholder decision making which result from the imprecise, uncertain, and subjective nature of architecture selection based on quality attributes (QA) further hinders the development of the product line architecture. Therefore, this study aims to propose a quality-driven approach using Multi-Criteria Decision Analysis (MCDA) techniques for Software Product Line Architecture (SPLA) to have an objective selection based on the QA of stakeholders in the domain of PNP. There are two steps proposed to this approach. First, a clear representation of quality is proposed by extending feature model (FM) with QA feature to determine the QA in the early phase of architecture selection. Second, MCDA techniques were applied for architecture selection based on objective preference for certain QA in the domain of PNP. The result of the proposed approach is the implementation of the PNP system with SPLA that had been selected using MCDA techniques. Evaluation for the approach is done by checking the approach's applicability in a case study and stakeholder validation. Evaluation on ease of use and usefulness of the approach with selected stakeholders have shown positive responses. The evaluation results proved that the proposed approach assisted in the implementation of PNP systems.

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10UML diagram-driven test scenarios generation based on the temporal graph grammar

저자 : Zhan Shi , Xiaoqin Zeng , Tingting Zhang , Lei Han , Ying Qian

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 15권 7호 발행 연도 : 2021 페이지 : pp. 2476-2495 (20 pages)

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Model-based software architecture verification and test scenarios generation are becoming more and more important in the software industry. Based on the existing temporal graph grammar, this paper proposes a new formalization method of the context-sensitive graph grammar for aiming at UML activity diagrams, which is called the UML Activity Graph Grammar, or UAGG. In the UAGG, there are new definitions and parsing algorithms. The proposed mechanisms are able to not only check the structural correctness of the UML activity diagram but also automatically generate the test scenario according to user constraints. Finally, a case study is discussed to illustrate how the UAGG and its algorithms work.

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