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  • Open Access

    ARTICLE

    A Generative Adversarial Networks for Log Anomaly Detection

    Xiaoyu Duan1, Shi Ying1,*, Wanli Yuan1, Hailong Cheng1, Xiang Yin2

    Computer Systems Science and Engineering, Vol.37, No.1, pp. 135-148, 2021, DOI:10.32604/csse.2021.014030

    Abstract Detecting anomaly logs is a great significance step for guarding system faults. Due to the uncertainty of abnormal log types, lack of real anomaly logs and accurately labeled log datasets. Existing technologies cannot be enough for detecting complex and various log point anomalies by using human-defined rules. We propose a log anomaly detection method based on Generative Adversarial Networks (GAN). This method uses the Encoder-Decoder framework based on Long Short-Term Memory (LSTM) network as the generator, takes the log keywords as the input of the encoder, and the decoder outputs the generated log template. The discriminator uses the Convolutional Neural… More >

  • Open Access

    ARTICLE

    COVID-19 Public Sentiment Insights: A Text Mining Approach to the Gulf Countries

    Saleh Albahli1, Ahmad Algsham1, Shamsulhaq Aeraj1, Muath Alsaeed1, Muath Alrashed1, Hafiz Tayyab Rauf2,*, Muhammad Arif3, Mazin Abed Mohammed4

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1613-1627, 2021, DOI:10.32604/cmc.2021.014265

    Abstract Social media has been the primary source of information from mainstream news agencies due to the large number of users posting their feedback. The COVID-19 outbreak did not only bring a virus with it but it also brought fear and uncertainty along with inaccurate and misinformation spread on social media platforms. This phenomenon caused a state of panic among people. Different studies were conducted to stop the spread of fake news to help people cope with the situation. In this paper, a semantic analysis of three levels (negative, neutral, and positive) is used to gauge the feelings of Gulf countries… More >

  • Open Access

    ARTICLE

    Methodology for Detecting Strabismus through Video Analysis and Intelligent Mining Techniques

    Hanan Abdullah Mengash1,*, Hanan A. Hosni Mahmoud1,2

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1013-1032, 2021, DOI:10.32604/cmc.2021.014942

    Abstract Strabismus is a medical condition that is defined as the lack of coordination between the eyes. When Strabismus is detected at an early age, the chances of curing it are higher. The methods used to detect strabismus and measure its degree of deviation are complex and time-consuming, and they always require the presence of a physician. In this paper, we present a method of detecting strabismus and measuring its degree of deviation using videos of the patient’s eye region under a cover test. Our method involves extracting features from a set of training videos (training corpora) and using them to… More >

  • Open Access

    ARTICLE

    Enhancing Network Intrusion Detection Model Using Machine Learning Algorithms

    Nancy Awadallah Awad*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 979-990, 2021, DOI:10.32604/cmc.2021.014307

    Abstract After the digital revolution, large quantities of data have been generated with time through various networks. The networks have made the process of data analysis very difficult by detecting attacks using suitable techniques. While Intrusion Detection Systems (IDSs) secure resources against threats, they still face challenges in improving detection accuracy, reducing false alarm rates, and detecting the unknown ones. This paper presents a framework to integrate data mining classification algorithms and association rules to implement network intrusion detection. Several experiments have been performed and evaluated to assess various machine learning classifiers based on the KDD99 intrusion dataset. Our study focuses… More >

  • Open Access

    ARTICLE

    Motion-Based Activities Monitoring through Biometric Sensors Using Genetic Algorithm

    Mohammed Alshehri1,*, Purushottam Sharma2, Richa Sharma2, Osama Alfarraj3

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2525-2538, 2021, DOI:10.32604/cmc.2021.012469

    Abstract Sensors and physical activity evaluation are quite limited for motion-based commercial devices. Sometimes the accelerometer of the smartwatch is utilized; walking is investigated. The combination can perform better in terms of sensors and that can be determined by sensors on both the smartwatch and phones, i.e., accelerometer and gyroscope. For biometric efficiency, some of the diverse activities of daily routine have been evaluated, also with biometric authentication. The result shows that using the different computing techniques in phones and watch for biometric can provide a suitable output based on the mentioned activities. This indicates that the high feasibility and results… More >

  • Open Access

    ARTICLE

    Development of Environmentally Friendly and Energy Efficient Refrigerants for Refrigeration Systems

    Piyanut Saengsikhiao1, Juntakan Taweekun1,2,*, Kittinan Maliwan2, Somchai Sae-ung2, Thanansak Theppaya2

    Energy Engineering, Vol.118, No.2, pp. 411-433, 2021, DOI:10.32604/EE.2021.012860

    Abstract This paper presents the improvement of eco-friendly and power consumption saving refrigerants for refrigeration systems. The novel azeotropic refrigerant mixtures of HFCs and HCs can replace refrigeration systems, and using the R134, R32, R125, and R1270 refrigerants in several compositions found using the decision tree function of the RapidMiner software (which came first in the KDnuggets annual software poll). All refrigerant results are mixed of POE, which is A1 classification refrigerant, non-flammable, and innocuous refrigerant, and using REFPROP software and CYCLE_D-HX software are under the CAN/ANSI/AHRI540 standards. The boiling point of the new refrigerant mix R-No.595 is 4.58%, lower than… More >

  • Open Access

    ARTICLE

    A Clustering Method Based on Brain Storm Optimization Algorithm

    Tianyu Wang, Yu Xue, Yan Zhao, Yuxiang Wang*, Yan Zhang, Yuxiang He

    Journal of Information Hiding and Privacy Protection, Vol.2, No.3, pp. 135-142, 2020, DOI:10.32604/jihpp.2020.010362

    Abstract In the field of data mining and machine learning, clustering is a typical issue which has been widely studied by many researchers, and lots of effective algorithms have been proposed, including K-means, fuzzy c-means (FCM) and DBSCAN. However, the traditional clustering methods are easily trapped into local optimum. Thus, many evolutionary-based clustering methods have been investigated. Considering the effectiveness of brain storm optimization (BSO) in increasing the diversity while the diversity optimization is performed, in this paper, we propose a new clustering model based on BSO to use the global ability of BSO. In our experiment, we apply the novel… More >

  • Open Access

    ARTICLE

    SI Bitmap Index and Optimization for Membership Query

    Shu Gaoa,b,*, Zhen Wanga, Liangchen Chena

    Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 683-689, 2019, DOI:10.31209/2018.100000061

    Abstract The explosive growth of data produced by internet of things has contributed to the abundance of data. Since then, efficient indexing and querying techniques for data retrieval has become a major challenge. Bitmap index and its extension techniques, which involve a bit sequence that represents a specified property and indicates the data items that satisfies this property, are well-known methods to improve processing time for complex and interactive queries on the read-mostly or append-only data. This paper proposes an improved bitmap index technique, named Sliced-Interval Bitmap Index (SI Bitmap Index), which is efficient in both space and response time for… More >

  • Open Access

    REVIEW

    Importance of Features Selection, Attributes Selection, Challenges and Future Directions for Medical Imaging Data: A Review

    Nazish Naheed1, Muhammad Shaheen1, Sajid Ali Khan1, Mohammed Alawairdhi2,*, Muhammad Attique Khan3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 315-344, 2020, DOI:10.32604/cmes.2020.011380

    Abstract In the area of pattern recognition and machine learning, features play a key role in prediction. The famous applications of features are medical imaging, image classification, and name a few more. With the exponential growth of information investments in medical data repositories and health service provision, medical institutions are collecting large volumes of data. These data repositories contain details information essential to support medical diagnostic decisions and also improve patient care quality. On the other hand, this growth also made it difficult to comprehend and utilize data for various purposes. The results of imaging data can become biased because of… More >

  • Open Access

    ARTICLE

    Extracting Campus’ Road Network from Walking GPS Trajectories

    Yizhi Liu, Rutian Qing, Jianxun Liu*, Zhuhua Liao, Yijiang Zhao, Hong Ouyang

    Journal of Cyber Security, Vol.2, No.3, pp. 131-140, 2020, DOI:10.32604/jcs.2020.010625

    Abstract Road network extraction is vital to both vehicle navigation and road planning. Existing approaches focus on mining urban trunk roads from GPS trajectories of floating cars. However, path extraction, which plays an important role in earthquake relief and village tour, is always ignored. Addressing this issue, we propose a novel approach of extracting campus’ road network from walking GPS trajectories. It consists of data preprocessing and road centerline generation. The patrolling GPS trajectories, collected at Hunan University of Science and Technology, were used as the experimental data. The experimental evaluation results show that our approach is able to effectively and… More >

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