Wuxiong Zhang^{1, 2}, Weidong Fang^{1, 2, *}, Qianqian Zhao^{1, 2}, Xiaohong Ji³, Guoqing Jia³

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 787-811, 2020, DOI:10.32604/cmc.2020.07620

Abstract Energy efficiency is very important for the Internet of Things (IoT), especially for front-end sensed terminal or node. It not only embodies the node’s life, but also reflects the lifetime of the network. Meanwhile, it is also a key indicator of green communications. Unfortunately, there is no article on systematic analysis and review for energy efficiency evaluation in IoT. In this paper, we systemically analyze the architecture of IoT, and point out its energy distribution, Furthermore, we summarized the energy consumption model in IoT, analyzed the pros and cons of improving energy efficiency, presented a state of the art the… More >

Xiangmao Chang^{1, 2, *}, Yuan Qiu¹, Shangting Su¹, Deliang Yang³

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 691-703, 2020, DOI:10.32604/cmc.2020.07923

Abstract Wireless sensor networks are increasingly used in sensitive event monitoring. However, various abnormal data generated by sensors greatly decrease the accuracy of the event detection. Although many methods have been proposed to deal with the abnormal data, they generally detect and/or repair all abnormal data without further differentiate. Actually, besides the abnormal data caused by events, it is well known that sensor nodes prone to generate abnormal data due to factors such as sensor hardware drawbacks and random effects of external sources. Dealing with all abnormal data without differentiate will result in false detection or missed detection of the events.… More >

Omid Mahdi Ebadati E.^{1, *}, Farshad Eshghi², Amin Zamani¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 323-349, 2020, DOI:10.32604/cmes.2020.08079

Abstract Transmission pipelines are vulnerable to various accidents and acts of vandalism. Therefore, a reliable monitoring system is needed to secure the transmission pipelines. A wireless sensor network is a wireless network consisting of distributed devices distributed at various distances, which monitors the physical and environmental conditions using sensors. Wireless sensor networks have many uses, including the built-in sensor on the outside of the pipeline or installed to support bridge structures, robotics, healthcare, environmental monitoring, etc. Wireless Sensor networks could be used to monitor the temperature, pressure, leak detection and sabotage of transmission lines. Wireless sensor networks are vulnerable to various… More >

Hui Wang¹, Songyou Li², Lei Liang^3,*, Gang Xu^4,5, Bin Tu⁶

Structural Durability & Health Monitoring, Vol.13, No.4, pp. 347-359, 2019, DOI:10.32604/sdhm.2019.05139

Abstract Pipelines are one of the most important modern energy transportation methods, used especially for the transportation of certain dangerous energy media materials such as crude oil, natural gas, and chemical raw materials. New requirements have been put forward for the health monitoring and early security warning of pipelines because of the large-scale and complicated development trend of the pipe network system. To achieve an accurate assessment of the health conditions of pipeline infrastructure, obtaining as many precise operating parameters as possible, particularly at some critical parts of the pipeline, is necessary. Therefore, a novel type of fiber grating strain sensor… More >

Sasan Saqaeeyan¹, Hamid Haj Seyyed Javadi^1,2,*, Hossein Amirkhani^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.3, pp. 815-834, 2019, DOI:10.32604/cmes.2019.07848

Abstract Anomaly detection in smart homes provides support to enhance the health and safety of people who live alone. Compared to the previous studies done on this topic, less attention has been given to hybrid methods. This paper presents a two-steps hybrid probabilistic anomaly detection model in the smart home. First, it employs various algorithms with different characteristics to detect anomalies from sensory data. Then, it aggregates their results using a Bayesian network. In this Bayesian network, abnormal events are detected through calculating the probability of abnormality given anomaly detection results of base methods. Experimental evaluation of a real dataset indicates… More >

Orrabalis C^1,2, H Gorostegui^1,2, E Calandri¹, C Guzmán¹

Phyton-International Journal of Experimental Botany, Vol.83, pp. 117-125, 2014, DOI:10.32604/phyton.2014.83.117

Abstract We evaluated the possibility of making jam (product A) and simile sweet potato jam (product B) from the edible pulp of the fruits of Geoffroea decorticans. The first step was the chemical characterization of the flour (pulp) highlighting their carbohydrate (85.6%), protein (9.4%) and mineral (4.2%) concentrations. Sucrose (29.5%), glucose (3.80%) and fructose (5.30%) levels were quantified using gas chromatography. Contents of protein (5.7%), minerals (3.4%), dietary fiber (0.97%), sucrose (46.8%), glucose (1.9%) and fructose (2.4%) were very good in jam. The simile sweet potato jam had low calories (140 Kcal/100g) and provided protein (4.6%). During the 12-month-storage period, the… More >

Xia Wang¹, Hongming Shen¹, Huawei Tao², Ruiyu Liang³, Xing Deng^4,5, Haijian Shao⁵, Li Zhao^6,*, Cairong Zou⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.2, pp. 551-567, 2019, DOI:10.32604/cmes.2019.06314

Abstract To make full use of the residual audible frequency band of hearing-loss patients and improve the intelligibility of speech, an adaptive nonlinear frequency compression (NFC) algorithm is proposed, which amplifies signals below the cutoff frequency while compresses signals above the cutoff frequency. Firstly, high-frequency signals are decomposed to critical band signals according to the BARK scale. Secondly, the global compression ratio is determined according to the patient's cutoff frequency and maximum audible frequency. Thirdly, the sub-band compression ratio is adaptively determined based on the global compression ratio and normalized average energy of subband signals. Finally, the high frequency signals are… More >

Bing Hu¹, Feng Xiang², Fan Wu³, Jian Liu⁴, Zhe Sun¹, Zhixin Sun^1,*

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1323-1344, 2019, DOI:10.32604/cmc.2019.06414

Abstract To cope with the arbitrariness of the network delays, a novel method, referred to as the composite particle filter approach based on variational Bayesian (VB-CPF), is proposed herein to estimate the clock skew and clock offset in wireless sensor networks. VB-CPF is an improvement of the Gaussian mixture kalman particle filter (GMKPF) algorithm. In GMKPF, Expectation-Maximization (EM) algorithm needs to determine the number of mixture components in advance, and it is easy to generate overfitting and underfitting. Variational Bayesian EM (VB-EM) algorithm is introduced in this paper to determine the number of mixture components adaptively according to the observations. Moreover,… More >

Donghui Li¹, Cong Shen^2,*, Xiaopeng Dai¹, Xinghui Zhu¹, Jian Luo¹, Xueting Li¹, Haiwen Chen³, Zhiyao Liang⁴

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1217-1231, 2019, DOI:10.32604/cmc.2019.06354

Abstract Data fusion can effectively process multi-sensor information to obtain more accurate and reliable results than a single sensor. The data of water quality in the environment comes from different sensors, thus the data must be fused. In our research, self-adaptive weighted data fusion method is used to respectively integrate the data from the PH value, temperature, oxygen dissolved and NH3 concentration of water quality environment. Based on the fusion, the Grubbs method is used to detect the abnormal data so as to provide data support for estimation, prediction and early warning of the water quality. More >

Clyde K Coelho, Cristobal Hiche, Aditi Chattopadhyay

Structural Durability & Health Monitoring, Vol.7, No.1&2, pp. 65-82, 2011, DOI:10.3970/sdhm.2011.007.065

Abstract Low velocity impacts on composite plates often create subsurface damage that is difficult to diagnose. Fiber Bragg grating (FBG) sensors can be used to detect subsurface damage in composite laminates due to low velocity impact. This paper focuses on the prediction of impact loading in composite structures as a function of time using a support vector regression approach. A time delay embedding feature extraction scheme is used since it can characterize the dynamics of the impact using the sensor signals. The novelty of this approach is that it can be applied on complex geometries and does not require a dense… More >