Open Access

ARTICLE

Jamel Nebhen^1,*, Pietro M. Ferreira^2,3
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 607-631, 2022, DOI:10.32604/cmes.2022.016086
Abstract This paper presents a proposed low-noise and high-sensitivity Internet of Thing (IoT) system based on an M&NEMS microphone. The IoT device consists of an M&NEMS resistive accelerometer associated with an electronic readout circuit, which is a silicon nanowire and a Continuous-Time (CT) Δ Σ ADC. The first integrator of the Δ Σ ADC is based on a positive feedback DC-gain enhancement two-stage amplifier due to its high linearity and low-noise operations. To mitigate both the offset and 1/f noise, a suggested delay-time chopper negative-R stabilization technique is applied around the first integrator. A 65-nm CMOS process implements the CT Δ… More >

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Darshan Babu L. Arasu¹, Ahmad Sufril Azlan Mohamed^1,*, Nur Intan Raihana Ruhaiyem¹, Nagaletchimee Annamalai², Syaheerah Lebai Lutfi¹, Mustafa M. Al Qudah¹
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 633-652, 2022, DOI:10.32604/cmes.2021.016985
（This article belongs to this Special Issue: Computer-Assisted Imaging Processing and Machine Learning Applications on Diagnosis of Chest Radiograph)
Abstract Stress is a normal reaction of the human organism which triggered in situations that require a certain level of activation. This reaction has both positive and negative effects on everyone’s life. Therefore, stress management is of vital importance in maintaining the psychological balance of a person. Thermal-based imaging technique is becoming popular among researchers due to its non-contact conductive nature. Moreover, thermal-based imaging has shown promising results in detecting stress in a non-contact and non-invasive manner. Compared to other non-contact stress detection methods such as pupil dilation, keystroke behavior, social media interaction and voice modulation, thermal-based imaging provides better features… More >

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ARTICLE

Jiao Wang^1,*, Xihua Chu^2,*, Jinbao Wang³
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 653-670, 2022, DOI:10.32604/cmes.2022.018207
Abstract Common structures in engineering such as slopes, roadbeds, ballasts, etc., are closely related to granular materials. They are usually subjected to long-term cyclic loads. This study mainly focused on the mechanical behaviors of randomly arranged granular materials before they reach a stable state under different cyclic loads. The variation of the maximum axial strain and the influence of CSR (cyclic stress ratio) were analyzed. The energy consumed in each cycle under constant confining stress loading condition is significantly greater than that of the fixed wall loading condition. The internal deformation evolution of granular materials is studied in detail. The deformation… More >

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883

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ARTICLE

Fuqi Yao¹, Jinwei Sun¹, Jianhua Dong^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 671-700, 2022, DOI:10.32604/cmes.2022.018450
Abstract Accurate estimation of dew point temperature (T_dew) plays a very important role in the fields of water resource management, agricultural engineering, climatology and energy utilization. However, there are few studies on the applicability of local T_dew algorithms at regional scales. This study evaluated the performance of a new machine learning algorithm, i.e., gradient boosting on decision trees with categorical features support (CatBoost) to estimate daily T_dew using limited local and cross-station meteorological data. The random forests (RF) algorithm was also assessed for comparison. Daily meteorological data from 2016 to 2019, including maximum, minimum and average temperature (T_max, T_min and T_mean),… More >

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839

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Xiaosai Duan, Suihuai Yu^*, Jianjie Chu, Dengkai Chen and Zhaojing Su
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 701-721, 2022, DOI:10.32604/cmes.2022.016779
Abstract The rational design of airflow distribution is of great importance for comfort and energy conservation. Several numerical investigations of flow and temperature characteristics in cockpits have been performed to study the distinct airflow distribution. This study developed the coupled heat transfer model of radiation, convection, and heat conduction for the cockpit flight environment. A three-dimensional physical model was created and a shear stress transfer (SST) k-w turbulence model was well verified with a high prediction accuracy of 91% for the experimental data. The strong inhomogeneous flow and temperature distribution were captured for various initial operating conditions (inlet temperature, inlet pressure,… More >

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1187

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Muhammad Zafar^1,#,*, Muhammad Saif Ullah^1,#, Tareq Manzoor², Muddassir Ali³, Kashif Nazar⁴, Shaukat Iqbal⁵, Habib Ullah Manzoor⁶, Rizwan Haider¹, Woo Young Kim^7,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 723-749, 2022, DOI:10.32604/cmes.2022.017257
Abstract In recent years, the emergence of nanotechnology experienced incredible development in the field of medical sciences. During the past decade, investigating the characteristics of nanoparticles during fluid flow has been one of the intriguing issues. Nanoparticle distribution and uniformity have emerged as substantial criteria in both medical and engineering applications. Adverse effects of chemotherapy on healthy tissues are known to be a significant concern during cancer therapy. A novel treatment method of magnetic drug targeting (MDT) has emerged as a promising topical cancer treatment along with some attractive advantages of improving efficacy, fewer side effects, and reduce drug dose. During… More >

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705

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ARTICLE

Usman Inayat^1,*, Shaukat Iqbal¹, Tareq Manzoor²
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 751-776, 2022, DOI:10.32604/cmes.2022.018665
Abstract In this contemporary study, theoritical investigation of nanofluidic model is thought-out. Two-dimensional nanomaterials based mixed flow is considered here. Convective solar radiative heat transport properties have been investigated over a nonlinearly stretched wall in the presence of magneto-hydrodynamic (MHD), by innovative application of semi analytical “optimal homotopy asymptotic method (OHAM)”. OHAM does not require any discretization, linearization and small parameter assumption. OHAM describes extremely precise order solutions without the need of computing further higher order terms, therefore, fast convergence is observed. Nanofluidic governing model is transformed into system of ordinary differential equations (ODEs) by exploitation of similarity transformation. To study… More >

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898

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ARTICLE

Bogusław Bożek¹, Lucjan Sapa^1,*, Katarzyna Tkacz-Śmiech², Marek Danielewski², Janusz Rybak²
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 777-803, 2022, DOI:10.32604/cmes.2022.017729
Abstract Low-temperature nitriding of steel or iron can produce an expanded austenite phase, which is a solid solution of a large amount of nitrogen dissolved interstitially in fcc lattice. It is characteristic that the nitogen depth profiles in expanded austenite exhibit plateau-type shapes. Such behavior cannot be considered with a standard analytic solution for diffusion in a semi-infinite solid and a new approach is necessary. We formulate a model of interdiffusion in viscoelastic solid (Maxwell model) during the nitriding process. It combines the mass conservation and Vegard’s rule with the Darken bi-velocity method. The model is formulated in any dimension, i.e.,… More >

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ARTICLE

Jiandong Huang¹, Jia Zhang¹, Yuan Gao^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 805-821, 2022, DOI:10.32604/cmes.2022.017792
（This article belongs to this Special Issue: Soft Computing Techniques in Materials Science and Engineering)
Abstract

Pervious concrete (PC) is at risk of clogging due to the continuous blockage of sand into it during its service time. This study aims to evaluate and predict such clogging behavior of PC using hybrid machine learning techniques. Based on the 84 groups of the dataset developed in the earlier study, the clogging behavior of the PC was determined by the algorithm combing the SVM (support vector machines) and particle swarm optimization (PSO) methods. The PSO algorithm was employed to adjust the hyperparameters of the SVM and verify the performance using 10-fold cross-validation. The predicting results of the developed model… More >

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ARTICLE

Nishant Behar^*, Manish Shrivastava
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 823-839, 2022, DOI:10.32604/cmes.2022.017030
（This article belongs to this Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics)
Abstract Breast cancer is considered an immense threat and one of the leading causes of mortality in females. It is curable only when detected at an early stage. A standard cancer diagnosis approach involves detection of cancer-related anomalies in tumour histopathology images. Detection depends on the accurate identification of the landmarks in the visual artefacts present in the slide images. Researchers are continuously striving to develop automatic machine-learning algorithms for processing medical images to assist in tumour detection. Nowadays, computer-based automated systems play an important role in cancer image analysis and help healthcare experts make rapid and correct inferences about the… More >

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ARTICLE

Zhongxiang Chen¹, Huijuan Zha¹, Zhiquan Shu², Juyi Ye³, Jiaji Pan^1,4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 841-854, 2022, DOI:10.32604/cmes.2022.017574
（This article belongs to this Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics)
Abstract This study aims to improve control schemes for COVID-19 by a numerical model with estimation of parameters. We established a multi-level and multi-objective nonlinear SEIDR model to simulate the virus transmission. The early spread in Japan was adopted as a case study. The first 96 days since the infection were divided into five stages with parameters estimated. Then, we analyzed the trend of the parameter value, age structure ratio, and the defined PCR test index (standardization of the scale of PCR tests). It was discovered that the self-healing rate and confirmed rate were linear with the age structure ratio and… More >

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860

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ARTICLE

Shouming Hou, Ji Han^*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 855-869, 2022, DOI:10.32604/cmes.2022.016621
（This article belongs to this Special Issue: Computer-Assisted Imaging Processing and Machine Learning Applications on Diagnosis of Chest Radiograph)
Abstract Many people around the world have lost their lives due to COVID-19. The symptoms of most COVID-19 patients are fever, tiredness and dry cough, and the disease can easily spread to those around them. If the infected people can be detected early, this will help local authorities control the speed of the virus, and the infected can also be treated in time. We proposed a six-layer convolutional neural network combined with max pooling, batch normalization and Adam algorithm to improve the detection effect of COVID-19 patients. In the 10-fold cross-validation methods, our method is superior to several state-of-the-art methods. In… More >

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ARTICLE

Jung Rye Lee¹, Aftab Hussain², Asfand Fahad³, Ali Raza³, Muhammad Imran Qureshi^3,*, Abid Mahboob⁴, Choonkil Park⁵
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 871-885, 2022, DOI:10.32604/cmes.2022.016836
（This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
Abstract In quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR) studies, computation of topological indices is a vital tool to predict biochemical and physio-chemical properties of chemical structures. Numerous topological indices have been inaugurated to describe different topological features. The ev and ve-degree are recently introduced novelties, having stronger prediction ability. In this article, we derive formulae of the ev-degree and ve-degree based topological indices for chemical structure of Si₂C₃ − I[a,b]. More >

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ARTICLE

Hassen Aydi^1,2,3, Ashish Verma⁴, Jihad Younis⁵, Jung Rye Lee^6,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 887-902, 2022, DOI:10.32604/cmes.2022.016924
（This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
Abstract Several (generalized) hypergeometric functions and a variety of their extensions have been presented and investigated in the literature by many authors. In the present paper, we investigate four new hypergeometric functions in four variables and then establish several recursion formulas for these new functions. Also, some interesting particular cases and consequences of our results are discussed. More >

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ARTICLE

Nusrat Raza¹, Umme Zainab² and Serkan Araci^3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 903-921, 2022, DOI:10.32604/cmes.2022.017669
（This article belongs to this Special Issue: Trend Topics in Special Functions and Polynomials: Theory, Methods, Applications and Modeling)
Abstract In this paper, we introduce mon-symbolic method to obtain the generating functions of the hybrid class of Hermite-associated Laguerre and its associated polynomials. We obtain the series definitions of these hybrid special polynomials. Also, we derive the double lacunary generating functions of the Hermite-Laguerre polynomials and the Hermite-Laguerre-Wright polynomials. Further, we find multiplicative and derivative operators for the Hermite-Laguerre-Wright polynomials which helps to find the symbolic differential equation of the Hermite-Laguerre-Wright polynomials. Some concluding remarks are also given. More >

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ARTICLE

Ritam Sharma¹, Janki Ballabh Sharma¹, Ranjan Maheshwari¹, Praveen Agarwal^2,3,4,5,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 923-947, 2022, DOI:10.32604/cmes.2022.016065
（This article belongs to this Special Issue: Advanced Mathematical Tool-Based Internet of Things (IoT))
Abstract In this paper, a novel hybrid texture feature set and fractional derivative filter-based breast cancer detection model is introduced. This paper also introduces the application of a histogram of linear bipolar pattern features (HLBP) for breast thermogram classification. Initially, breast tissues are separated by masking operation and filtered by Grmwald–Letnikov fractional derivative-based Sobel mask to enhance the texture and rectify the noise. A novel hybrid feature set using HLBP and other statistical feature sets is derived and reduced by principal component analysis. Radial basis function kernel-based support vector machine is employed for detecting the abnormality in the thermogram. The performance… More >

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ARTICLE

Jienan Chen, Chuang Zhang, Yu Yan, Yuan Liu^*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 949-966, 2022, DOI:10.32604/cmes.2022.017516
（This article belongs to this Special Issue: Blockchain Security)
Abstract Online file management systems enable cooperatively editing and sharing. However, due to the cost of communication and storage infrastructures, traditional online file management services, e.g., Google Drive and OneDrive, usually provide limited storage space and relatively low download speed for free users. To achieve better performance, ordinary users have to purchase their expensive services. Moreover, these file management systems are based on centralized architecture and bear the privacy leakage risk, because users’ personal files are stored and controlled by their servers. To address the above problems, we propose a peer-to-peer (P2P) file management system based on IPFS and Hyperledger Fabric,… More >

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ARTICLE

Jun Yan^1,2, Qianqian Sui¹, Zhirui Fan¹, Zunyi Duan^3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 967-986, 2022, DOI:10.32604/cmes.2022.017708
（This article belongs to this Special Issue: New Trends in Structural Optimization)
Abstract This study establishes a multiscale and multi-material topology optimization model for thermoelastic lattice structures (TLSs) considering mechanical and thermal loading based on the Extended Multiscale Finite Element Method (EMsFEM). The corresponding multi-material and multiscale mathematical formulation have been established with minimizing strain energy and structural mass as the objective function and constraint, respectively. The Solid Isotropic Material with Penalization (SIMP) interpolation scheme has been adopted to realize micro-scale multi-material selection of truss microstructure. The modified volume preserving Heaviside function (VPHF) is utilized to obtain a clear 0/1 material of truss microstructure. Compared with the classic topology optimization of single-material TLSs,… More >

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Kang Xu, Tong Li, Gaofei Guan, Jianlong Qu, Zhen Zhao, Xinsheng Xu^*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 987-1002, 2022, DOI:10.32604/cmes.2022.018128
（This article belongs to this Special Issue: New Trends in Structural Optimization)
Abstract By means of the local surface nanocrystallization that enables to change the material on local positions, an innovative embedded multi-cell (EMC) thin-walled energy absorption structures with local surface nanocrystallization is proposed in this paper. The local surface nanacrystallization stripes are regarded as the moving morphable components in the domain for optimal design. Results reveal that after optimizing the local surface nanocrystallization layout, the specific energy absorption (SEA) is increased by 50.78% compared with the untreated counterpart. Besides, in contrast with the optimized 4-cell structure, the SEA of the nanocrystallized embedded 9-cell structure is further enhanced by 27.68%, in contrast with… More >

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Liwei Wang^1,2,3, Jiankun Sun^1,2,3, Xiong Luo^1,2,3,*, Xi Yang⁴
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1003-1016, 2022, DOI:10.32604/cmes.2022.018492
（This article belongs to this Special Issue: Machine Learning-Guided Intelligent Modeling with Its Industrial Applications)
Abstract With the development of information technology, malware threats to the industrial system have become an emergent issue, since various industrial infrastructures have been deeply integrated into our modern works and lives. To identify and classify new malware variants, different types of deep learning models have been widely explored recently. Generally, sufficient data is usually required to achieve a well-trained deep learning classifier with satisfactory generalization ability. However, in current practical applications, an ample supply of data is absent in most specific industrial malware detection scenarios. Transfer learning as an effective approach can be used to alleviate the influence of the… More >

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Bhimraj Basumatary^1,*, Nijwm Wary¹, Jeevan Krishna Khaklary², Usha Rani Basumatary¹
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1017-1031, 2022, DOI:10.32604/cmes.2022.018066
（This article belongs to this Special Issue: Advances in Neutrosophic and Plithogenic Sets for Engineering and Sciences: Theory, Models, and Applications (ANPSESTMA))
Abstract The neutrality’s origin, character, and extent are studied in the Neutrosophic set. The neutrosophic set is an essential issue to research since it opens the door to a wide range of scientific and technological applications. The neutrosophic set can find its spot to research because the universe is filled with indeterminacy. Neutrosophic set is currently being developed to express uncertain, imprecise, partial, and inconsistent data. Truth membership function, indeterminacy membership function, and falsity membership function are used to express a neutrosophic set in order to address uncertainty. The neutrosophic set produces more rational conclusions in a variety of practical problems.… More >

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D. Ajay¹, J. Aldring¹, G. Rajchakit², P. Hammachukiattikul³, N. Boonsatit^4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1033-1076, 2022, DOI:10.32604/cmes.2022.018267
（This article belongs to this Special Issue: Advances in Neutrosophic and Plithogenic Sets for Engineering and Sciences: Theory, Models, and Applications (ANPSESTMA))
Abstract In this paper, sine trigonometry operational laws (ST-OLs) have been extended to neutrosophic sets (NSs) and the operations and functionality of these laws are studied. Then, extending these ST-OLs to complex neutrosophic sets (CNSs) forms the core of this work. Some of the mathematical properties are proved based on ST-OLs. Fundamental operations and the distance measures between complex neutrosophic numbers (CNNs) based on the ST-OLs are discussed with numerical illustrations. Further the arithmetic and geometric aggregation operators are established and their properties are verified with numerical data. The general properties of the developed sine trigonometry weighted averaging/geometric aggregation operators for… More >

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Yonghua Li^1,*, Xiaoning Bai², Shanshan Shi¹, Shenxuan Wang¹
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1077-1092, 2022, DOI:10.32604/cmes.2022.018181
（This article belongs to this Special Issue: Computer-Aided Structural Integrity and Safety Assessment)
Abstract Multiple failure modes and strength degradation are usually inherent in the gear transmission system, which brings new challenges for conducting fatigue reliability analysis and design. This paper proposes a novel dynamic fatigue reliability analysis method for failure dependence and strength degradation based on the combination of the Copula function and Gamma process. Firstly, the dynamic simulation model of the gear transmission system is established to obtain the dynamic stress-time history. The Gamma process is then used to describe the strength degradation to establish the dynamic stress-strength interference model. The marginal distribution functions of tooth contact fatigue and dedendum bending fatigue… More >

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985

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ARTICLE

Xiaolan Liu^1,*, Yixiang Chen², Yan Zhou¹, Kai Zhang³
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1093-1112, 2022, DOI:10.32604/cmes.2022.018072
（This article belongs to this Special Issue: Computer Modelling in Disaster Prevention and Mitigation for Engineering Structures)
Abstract Pavement construction in permafrost regions is complicated by the fact that the permafrost properties are influenced by the temperature and are extremely unstable. The numerical model for runway structures in permafrost regions is applied to analyze the time–space characteristics of the temperature field and the depth of the frozen layer. The influence of the installation layer is studied to enable structural optimization of the runway. Numerical results show that the temperature stabilization depth, low- and high-temperature interlayer response ranges, and maximum depth of the frozen layer are greater in runway engineering than in highway and railway engineering. The time history… More >

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812

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Borui Yang¹, Jun Luo², Bo Wan^1,*, Yutai Su^1,3, Guicui Fu¹, Xu Long^3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1113-1134, 2022, DOI:10.32604/cmes.2022.018037
（This article belongs to this Special Issue: Mechanical Reliability of Advanced Materials and Structures for Harsh Applications)
Abstract A thermal fatigue lifetime prediction model of ceramic ball grid array (CBGA) packages is proposed based on the Darveaux model. A finite element model of the CBGA packages is established, and the Anand model is used to describe the viscoplasticity of the CBGA solder. The average viscoplastic strain energy density increment ΔWave of the CBGA packages is obtained using a finite element simulation, and the influence of different structural parameters on the ΔWave is analyzed. A simplified analytical model of the ΔWave is established using the simulation data. The thermal fatigue lifetime of CBGA packages is obtained from a thermal… More >

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Yousheng Deng, Chengpu Peng^*, Jialin Su, Lingtao Li, Liqing Meng, Long Li
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1135-1148, 2022, DOI:10.32604/cmes.2022.018349
（This article belongs to this Special Issue: Mechanical Reliability of Advanced Materials and Structures for Harsh Applications)
Abstract Moso bamboo has the advantages of high short-term strength and reproducibility, appropriating for temporary supporting structure of shallow foundation pit. According to the displacement of the pile top from an indoor model test, the reliability of the supporting effect of the moso bamboo pile was analyzed. First, the calculation formula of reliability index was deduced based on the mean-value first-order second-moment (MVFOSM)method and probability theory under ultimate limit state and serviceability limit state. Then, the dimensionless bias factor (the ratio of the measured value to the calculated value) was introduced to normalize the displacement. The mathematical characteristics of the displacement… More >

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Yiping Sun^1,2, Qiang Bai¹, Xuefeng Zhao¹, Meng Tao^1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1149-1170, 2022, DOI:10.32604/cmes.2022.017760
（This article belongs to this Special Issue: Data-Driven Model and Deep Learning for Advanced Smart Materials and Structures)
Abstract A cavity viscoelastic structure has a good sound absorption performance and is often used as a reflective baffle or sound absorption cover in underwater acoustic structures. The acoustic performance field has become a key research direction worldwide. Because of the time-consuming shortcomings of the traditional numerical analysis method and the high cost of the experimental method for measuring the reflection coefficient to evaluate the acoustic performance of coatings, this innovative study predicted the reflection coefficient of a viscoelastic coating containing a cylindrical cavity based on an artificial neural network (ANN). First, the mapping relationship between the input characteristics and reflection… More >

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Wanni Xu^1,*, Huasen Xu², Xingyu Guo³
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1171-1192, 2022, DOI:10.32604/cmes.2022.017824
（This article belongs to this Special Issue: Application of Deep Learning in Medical Image Analysis (DL-MIA))
Abstract Color language has important meaning for children’s picture books. Understanding children’s preferences in terms of color language will be helpful when designers model computerized picture books in order to adapt to children’s visual senses and effectively stimulate children’s interest in reading. In this study, we aimed to further explore the general characteristics of children’s preference for colors, color depth and color matching forms in picture books. For the study, 256 children between the ages of three and six were selected and divided into four groups. According to the implementation needs of the children’s color preference test, these children were asked… More >

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Haibao Jiang¹, Dezhi Han^1,*, Han Liu¹, Jiuzhang Han¹ and Wenjing Nie²
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1193-1219, 2022, DOI:10.32604/cmes.2022.017663
（This article belongs to this Special Issue: New Trends in Statistical Computing and Data Science)
Abstract Nowadays, distance is usually used to evaluate the error of trajectory compression. These methods can effectively indicate the level of geometric similarity between the compressed and the raw trajectory, but it ignores the velocity error in the compression. To fill the gap of these methods, assuming the velocity changes linearly, a mathematical model called SVE (Time Synchronized Velocity Error) for evaluating compression error is designed, which can evaluate the velocity error effectively, conveniently and accurately. Based on this model, an innovative algorithm called SW-MSVE (Minimum Time Synchronized Velocity Error Based on Sliding Window) is proposed, which can minimize the velocity… More >

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Yanli Gao¹, Wanfeng Ma², Jing Cao², Jianling Qu¹ and Yuan Xu^2,3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1221-1237, 2022, DOI:10.32604/cmes.2022.017533
（This article belongs to this Special Issue: Advances on Modeling and State Estimation for Industrial Processes)
Abstract For improving the localization accuracy, a multi-interval extended finite impulse response (EFIR)-based RauchTung-Striebel (R-T-S) smoother is proposed for the range-only ultra wide band (UWB) simultaneous localization and mapping (SLAM) for robot localization. In this mode, the EFIR R-T-S (ERTS) smoother employs EFIR filter as the forward filter and the R-T-S smoothing method to smooth the EFIR filter’s output. When the east or the north position is considered as stance, the ERTS is used to smooth the position directly. Moreover, the estimation of the UWB Reference Nodes’ (RNs’) position is smoothed by the R-T-S smooth method in parallel. The test illustrates… More >

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