Journal articles: 'KFFM'

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Bi, Xiaobo, Jiansheng Lin, Daijie Tang, Fengrong Bi, Xin Li, Xiao Yang, Teng Ma, and Pengfei Shen. "VMD-KFCM Algorithm for the Fault Diagnosis of Diesel Engine Vibration Signals." Energies 13, no. 1 (January 2, 2020): 228. http://dx.doi.org/10.3390/en13010228.

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Accurate and timely fault diagnosis for the diesel engine is crucial to guarantee it works safely and reliably, and reduces the maintenance costs. A novel diagnosis method based on variational mode decomposition (VMD) and kernel-based fuzzy c-means clustering (KFCM) is proposed in this paper. Firstly, the VMD algorithm is optimized to select the most suitable K value adaptively. Then KFCM is employed to classify the feature parameters of intrinsic mode functions (IMFs). Through the comparison of many different parameters, the singular value is selected finally because of the good classification effect. In this paper, the diesel engine fault simulation experiment was carried out to simulate various faults including valve clearance fault, fuel supply fault and common rail pressure fault. Each kind of machine fault varies in different degrees. To prove the effectiveness of VMD-KFCM, the proposed method is compared with empirical mode decomposition (EMD)-KFCM, ensemble empirical mode decomposition (EEMD)-KFCM, VMD-back propagation neural network (BPNN), and VMD-deep belief network (DBN). Results show that VMD-KFCM has advantages in accuracy, simplicity, and efficiency. Therefore, the method proposed in this paper can be used for diesel engine fault diagnosis, and has good application prospects.

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Hossein-Abad, Hadi Mahdipour, Mohsen Shabanian, and Iman Abaspur Kazerouni. "Vectorized Kernel-Based Fuzzy C-Means: a Method to Apply KFCM on Crisp and Non-Crisp Numbers." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 28, no. 04 (August 2020): 635–59. http://dx.doi.org/10.1142/s0218488520500270.

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Kernel methods are a class of algorithms for pattern analysis to robust them to noise, overlaps, outliers and also unequal sized clusters. In this paper, kernel-based fuzzy c-means (KFCM) method is extended to apply KFCM on any crisp and non-crisp input numbers only in a single structure. The proposed vectorized KFCM (VKFM) algorithm maps the input (crisp or non-crisp) features to crisp ones and applies the KFCM (with prototypes in feature space) on them. Finally the resulted crisp prototypes in the mapped space are influenced by an inverse mapping to obtain the prototypes’ (centers’) parameters in the input features space. The performance of the proposed method has been compared with the conventional FCM and KFCM and other new methods, to show its effectiveness in clustering of gene expression data and segmentation of land-cover using satellite images. Simulation results show good accuracy of proposed method in compare to other methods.

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Dubey, Bhoomika. "Image Segmentation using KFCM." International Journal for Research in Applied Science and Engineering Technology 7, no. 6 (June 30, 2019): 2107–11. http://dx.doi.org/10.22214/ijraset.2019.6351.

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Hjermitslev, Hans Henrik. "Fra Marken til Arenaen." Forum for Idræt 33 (February 1, 2018): 82–99. http://dx.doi.org/10.7146/ffi.v33i1.109047.

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Formålet med denne artikel er at benytte Tvis KFUM som case til at beskrive dele af den generelle udvikling inden for klubhåndbolden i Danmark. Historien om Tvis KFUM er nemlig på mange måder typisk for de ændringer, der har fundet sted i mange succesrige landsby- og KFUM-klubber gennem de sidste 40 år. Klubben er således gået fra at være en lokalt og ideologisk forankret kristen forening til at blive et professionelt aktieselskab med regionalt fokus. Den har samtidig været igennem følelsesladede fusionsprocesser og økonomiske vanskeligheder i denne transformation fra forening til forretning.

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Raghavulu, Vivaram, and Ande Prasad. "Moving Object Segmentation Using Level Set Algorithm with GWO-KFCM Clustering." International Journal of Intelligent Engineering and Systems 13, no. 6 (December 31, 2020): 374–83. http://dx.doi.org/10.22266/ijies2020.1231.33.

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Video analytics is widely used to automatically analyze the videos to extract the required information and detect the various events object identification and traffic analysis. The segmentation of the image is referring to extracting the required region from an image. The major objective of the segmentation process is to cluster the images without being affected by the noises. The detection of the moving objects is a challenging task in video analysis due to the dynamic background of the video. The major drawback of the existing Kernel Fuzzy C-Means (KFCM) clustering is initialization of random centroids which increases the execution time to identify the segmented portions. In this research, the Grey Wolf Optimization (GWO) algorithm used to initialize the centroids of required clusters in KFCM and Level Set (LS) Algorithm is used to segment the objects in video sequence. The proposed KFCM-GWO-LS is implemented for moving and static object detection in the videos obtained from SBM-RGBD dataset. For object detection, determining central clusters are important which is performed by using KFCM. GWO helps in finding the best centroids clusters by matching with KFCM. The centroids clusters are segmented by using LS algorithm which undergoes over segmentation problem that is overcome by GWO. As all the three techniques are dependent on one another hybrid of all these techniques obtains better results. The proposed KFCM-GWO-LS is evaluated in terms of Recall, Specificity, Precision and F-measure and the experimental results showed that the proposed method improved the system performance from 0.3 % to 14.35 % compared to existing methods Multi-Sensor Scheduler Algorithm and Statistical Inference Theory model.

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Zhang, Hongmao, Haiyang Gao, Zheng Yang, Zhenzhen Wang, Yang Luo, and Zhibin Zhang. "Effects of interspecific competition on food hoarding and pilferage in two sympatric rodents." Behaviour 151, no. 11 (2014): 1579–96. http://dx.doi.org/10.1163/1568539x-00003201.

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Food hoarding and pilferage in rodents may be regulated by intense competition between sympatric species that have similar habitats, diets and activity, but studies exploring this remain rare. Here, we used semi-natural enclosures to investigate food-hoarding and cache pilferage interactions between sympatric Korean field mice (KFM) (Apodemus peninsulae) and Chinese white-bellied rats (CWR) (Niviventer confucianus). KFM and CWR have similar diets, habitat and nocturnal activity, but the smaller KFM larder and scatter hoards and larger CWR larder hoard only. We found that KFM harvest, larder-hoard and eat seeds at a greater intensity when CWR are present as an audience (present but cannot pilfer). KFM ate 11.5%, re-larder-hoarded 17.9% and re-scatter-hoarded 1.3% of their scatter-hoarded seeds, and ate 29.3% of their larder-hoarded seeds when CWR were present as pilferers. A total of 12.8% of the seeds scatter-hoarded and 50% of seeds directly put on the ground by KFM were pilfered by CWR. CWR did not alter hoarding intensity in the presence of KFM and their stores cannot be pilfered by KFM. These results indicate that large-sized rodent species (more dominant) significantly increase the hoarding intensity of small-sized species and show a unidirectional pilferage of seeds cached by small-sized species. The behavioural differences between these two species may reduce competition for resources and promote coexistence between sympatric rodents.

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Chen, Wei Tong, Hew Cameron Merrett, Shih Tong Lu, and Leonard Mortis. "Analysis of Key Failure Factors in Construction Partnering—A Case Study of Taiwan." Sustainability 11, no. 14 (July 23, 2019): 3994. http://dx.doi.org/10.3390/su11143994.

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Construction partnering is commonly touted as a win-win arrangement for project owners and contractors alike. The failure or success of construction partnering arrangements is contingent upon a multitude of influences, many of which can be controlled through careful planning and active project management. This study examines the key failure factors (KFFs) of construction partnering projects based on data collected from a survey of industry professionals in Taiwan. Methods: Factor analysis is performed using data gathered from a survey of industry practitioners operating in Taiwan to identify KFFs and better understand the level of significance of each factor. A total of 15 failure variables (FV) were included in the survey. This study applied Principle Components Analysis to classify groups of crucial FV relevant to construction partnering based on their relative perceived contribution to project failure. Study results confirm that there are four KFFs to partnering failure in construction projects; they are absence of agility, collaboration barriers, partnering barriers, and organizational management barriers. The biggest influencer on partnership failure in construction projects is the association between absence of agility and organizational management barriers, while the next most significant is the relationship between collaboration barriers and partnering barriers. Avoiding failure of construction partnering requires careful planning and management considerations of the four KFFs found.

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Liu, Bowen, Ting Zhang, Yujian Li, Zhaoying Liu, and Zhilin Zhang. "Kernel Probabilistic K-Means Clustering." Sensors 21, no. 5 (March 8, 2021): 1892. http://dx.doi.org/10.3390/s21051892.

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Kernel fuzzy c-means (KFCM) is a significantly improved version of fuzzy c-means (FCM) for processing linearly inseparable datasets. However, for fuzzification parameter m=1, the problem of KFCM (kernel fuzzy c-means) cannot be solved by Lagrangian optimization. To solve this problem, an equivalent model, called kernel probabilistic k-means (KPKM), is proposed here. The novel model relates KFCM to kernel k-means (KKM) in a unified mathematic framework. Moreover, the proposed KPKM can be addressed by the active gradient projection (AGP) method, which is a nonlinear programming technique with constraints of linear equalities and linear inequalities. To accelerate the AGP method, a fast AGP (FAGP) algorithm was designed. The proposed FAGP uses a maximum-step strategy to estimate the step length, and uses an iterative method to update the projection matrix. Experiments demonstrated the effectiveness of the proposed method through a performance comparison of KPKM with KFCM, KKM, FCM and k-means. Experiments showed that the proposed KPKM is able to find nonlinearly separable structures in synthetic datasets. Ten real UCI datasets were used in this study, and KPKM had better clustering performance on at least six datsets. The proposed fast AGP requires less running time than the original AGP, and it reduced running time by 76–95% on real datasets.

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Mogstad, T., S. J. Cyvin, B. N. Cyvin, J. Brunvoll, and G. Díaz Fleming. "Molecular Vibrations of Aluminum Trichloride Monomer with Application of the Keating Bendings." Zeitschrift für Naturforschung A 40, no. 4 (April 1, 1985): 373–78. http://dx.doi.org/10.1515/zna-1985-0410.

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The vibrational spectra and previous normal coordinate analyses of AICI3 are reviewed. The valence force field (VFF), central force field (CFF) and Keating force field (KFF) are tested. KFF is found to be the best one of these approximations with regard to the agreement with an observed isotopic frequency. A final force field is taken from a very recent work. It confirms that KFF is superior to both CFF and KFF. The data of a Coriolis constant, mean amplitudes of vibration and the Bastiansen-Morino shrinkage effect are calculated and discussed.

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10

Schnee, Ian. "THERE IS NO KNOWLEDGE FROM FALSEHOOD." Episteme 12, no. 1 (October 7, 2014): 53–74. http://dx.doi.org/10.1017/epi.2014.26.

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AbstractA growing number of authors defend putative examples of knowledge from falsehood (KFF), inferential knowledge based in a critical or essential way on false premises, and they argue that KFF has important implications for many areas of epistemology (whether evidence can be false, the Gettier debate, defeasibility theories of knowledge, etc.). I argue, however, that there is no KFF, because in any supposed example either the falsehood does not contribute to the knowledge or the subject lacks knowledge. In particular, I show that if the subject actually has knowledge in putative KFF cases, then there is always a veridical evidential path meeting the basing conditions that accounts for her knowledge; if there is no such path, then the subject is in a type of Gettier case. All the recent arguments that rely on KFF are therefore based on a mistake.

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Hu, Guang, and Zhenbin Du. "Adaptive Kernel-Based Fuzzy C-Means Clustering with Spatial Constraints for Image Segmentation." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 01 (October 11, 2018): 1954003. http://dx.doi.org/10.1142/s021800141954003x.

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In order to resolve the disadvantages of fuzzy C-means (FCM) clustering algorithm for image segmentation, an improved Kernel-based fuzzy C-means (KFCM) clustering algorithm is proposed. First, the reason why the kernel function is introduced is researched on the basis of the classical KFCM clustering. Then, using spatial neighborhood constraint property of image pixels, an adaptive weighted coefficient is introduced into KFCM to control the influence of the neighborhood pixels to the central pixel automatically. At last, a judging rule for partition fuzzy clustering numbers is proposed that can decide the best clustering partition numbers and provide an optimization foundation for clustering algorithm. An adaptive kernel-based fuzzy C-means clustering with spatial constraints (AKFCMS) model for image segmentation approach is proposed in order to improve the efficiency of image segmentation. Various experiment results show that the proposed approach can get the spatial information features of an image accurately and is robust to realize image segmentation.

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Zong, Yongsheng, and Guoyan Huang. "Application of artificial fish swarm optimization semi-supervised kernel fuzzy clustering algorithm in network intrusion." Journal of Intelligent & Fuzzy Systems 39, no. 2 (August 31, 2020): 1619–26. http://dx.doi.org/10.3233/jifs-179935.

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For the unsupervised learning based clustering algorithm, the intrusion detection rate is low, and the training sample based on supervised learning clustering algorithm is insufficient. A semi-supervised kernel fuzzy C-means clustering algorithm based on artificial fish swarm optimization (AFSA-KFCM) is proposed. Firstly, the kernel function is used to change the distance function in the traditional semi-supervised fuzzy C-means clustering algorithm to define a new objective function, thus improving the probabilistic constraints of the fuzzy C-means algorithm. Then, the artificial fish swarm algorithm with strong global optimization ability is used to improve the KFCM sensitivity to the initial cluster center and easy to fall into the local extremum, thus improving the convergence speed and improving the classification effect. The test results in the Wine and IRIS public datasets show that the AFSA-KFCM clustering algorithm is superior to the traditional algorithm in clustering accuracy and time efficiency. At the same time, the experimental results in KDDCUP99 experimental data show that the algorithm can obtain the ideal detection rate and false detection rate in intrusion detection.

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Wagner, Tino, Hannes Beyer, Patrick Reissner, Philipp Mensch, Heike Riel, Bernd Gotsmann, and Andreas Stemmer. "Kelvin probe force microscopy for local characterisation of active nanoelectronic devices." Beilstein Journal of Nanotechnology 6 (November 23, 2015): 2193–206. http://dx.doi.org/10.3762/bjnano.6.225.

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Frequency modulated Kelvin probe force microscopy (FM-KFM) is the method of choice for high resolution measurements of local surface potentials, yet on coarse topographic structures most researchers revert to amplitude modulated lift-mode techniques for better stability. This approach inevitably translates into lower lateral resolution and pronounced capacitive averaging of the locally measured contact potential difference. Furthermore, local changes in the strength of the electrostatic interaction between tip and surface easily lead to topography crosstalk seen in the surface potential. To take full advantage of the superior resolution of FM-KFM while maintaining robust topography feedback and minimal crosstalk, we introduce a novel FM-KFM controller based on a Kalman filter and direct demodulation of sidebands. We discuss the origin of sidebands in FM-KFM irrespective of the cantilever quality factor and how direct sideband demodulation enables robust amplitude modulated topography feedback. Finally, we demonstrate our single-scan FM-KFM technique on an active nanoelectronic device consisting of a 70 nm diameter InAs nanowire contacted by a pair of 120 nm thick electrodes.

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Wu, Zhiwei, Hai Lin, Yun Li, and Youmin Tang. "Seasonal Prediction of Killing-Frost Frequency in South-Central Canada during the Cool/Overwintering-Crop Growing Season." Journal of Applied Meteorology and Climatology 52, no. 1 (January 2013): 102–13. http://dx.doi.org/10.1175/jamc-d-12-059.1.

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AbstractSeasonal killing-frost frequency (KFF) during the cool/overwintering-crop growing season is important for the Canadian agricultural sector to prepare and respond to such extreme agrometeorological events. On the basis of observed daily surface air temperature across Canada for 1957–2007, this study found that more than 86% of the total killing-frost events occur in April–May and exhibit consistent variability over south-central Canada, the country’s major agricultural region. To quantify the KFF year-to-year variations, a simple index is defined as the mean KFF of the 187 temperature stations in south-central Canada. The KFF variability is basically dominated by two components: the decadal component with a peak periodicity around 11 yr and the interannual component of 2.5–3.8 yr. A statistical method called partial least squares (PLS) regression is utilized to uncover principal sea surface temperature (SST) modes in the winter preceding the KFF anomalies. It is found that most of the leading SST modes resemble patterns of El Niño–Southern Oscillation (ENSO) and/or the Pacific decadal oscillation (PDO). This indicates that ENSO and the PDO might be two dominant factors for the KFF variability. From a 41-yr training period (1957–97), a PLS seasonal prediction model is established, and 1-month-lead real-time forecasts are performed for the validation period of 1998–2007. A promising skill level is obtained. For the KFF variability, the prediction skill of the PLS model is comparable to or even better than the newly developed Canadian Seasonal to Interannual Prediction System (CanSIPS), which is a state-of-the-art global coupled dynamical system.

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Ligowski, Maciej, Michiharu Tabe, and Ryszard Jabłoński. "Kelvin Probe Force Microscope Measurement Uncertainty." Advanced Materials Research 222 (April 2011): 114–17. http://dx.doi.org/10.4028/www.scientific.net/amr.222.114.

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Kelvin Probe Force Microscopy is an attractive technique for characterizing the surface potential of various samples. The main advantage of this technique is its high spatial resolution together with high sensitivity. However as in any nanoscale measurements also in case of KFM it is extremly difficult to describe the uncertainty of the measurement. Moreover, a wide variety of measuring conditions, together with the complicated operation principle cause situation, where no standard calibration methods are available. In the paper we propose the model of the KFM microscope and analyze the uncertainty of the KFM measurement.

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Geller, B. L., J. D. Deere, D. A. Stein, A. D. Kroeker, H. M. Moulton, and P. L. Iversen. "Inhibition of Gene Expression in Escherichia coli by Antisense Phosphorodiamidate Morpholino Oligomers." Antimicrobial Agents and Chemotherapy 47, no. 10 (October 2003): 3233–39. http://dx.doi.org/10.1128/aac.47.10.3233-3239.2003.

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ABSTRACT Antisense phosphorodiamidate morpholino oligomers (PMOs) were tested for the ability to inhibit gene expression in Escherichia coli. PMOs targeted to either a myc-luciferase reporter gene product or 16S rRNA did not inhibit luciferase expression or growth. However, in a strain with defective lipopolysaccharide (lpxA mutant), which has a leaky outer membrane, PMOs targeted to the myc-luciferase or acyl carrier protein (acpP) mRNA significantly inhibited their targets in a dose-dependent response. A significant improvement was made by covalently joining the peptide (KFF)3KC to the end of PMOs. In strains with an intact outer membrane, (KFF)3KC-myc PMO inhibited luciferase expression by 63%. A second (KFF)3KC-PMO conjugate targeted to lacI mRNA induced β-galactosidase in a dose-dependent response. The end of the PMO to which (KFF)3KC is attached affected the efficiency of target inhibition but in various ways depending on the PMO. Another peptide-lacI PMO conjugate was synthesized with the cationic peptide CRRRQRRKKR and was found not to induce β-galactosidase. We conclude that the outer membrane of E. coli inhibits entry of PMOs and that (KFF)3KC-PMO conjugates are transported across both membranes and specifically inhibit expression of their genetic targets.

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Meng, Wang, Dui Hongyan, Zhou Shiyuan, Dong Zhankui, and Wu Zige. "The Kernel Rough K-Means Algorithm." Recent Advances in Computer Science and Communications 13, no. 2 (June 3, 2020): 234–39. http://dx.doi.org/10.2174/2213275912666190716121431.

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Background: Clustering is one of the most important data mining methods. The k-means (c-means ) and its derivative methods are the hotspot in the field of clustering research in recent years. The clustering method can be divided into two categories according to the uncertainty, which are hard clustering and soft clustering. The Hard C-Means clustering (HCM) belongs to hard clustering while the Fuzzy C-Means clustering (FCM) belongs to soft clustering in the field of k-means clustering research respectively. The linearly separable problem is a big challenge to clustering and classification algorithm and further improvement is required in big data era. Objective: RKM algorithm based on fuzzy roughness is also a hot topic in current research. The rough set theory and the fuzzy theory are powerful tools for depicting uncertainty, which are the same in essence. Therefore, RKM can be kernelized by the mean of KFCM. In this paper, we put forward a Kernel Rough K-Means algorithm (KRKM) for RKM to solve nonlinear problem for RKM. KRKM expanded the ability of processing complex data of RKM and solve the problem of the soft clustering uncertainty. Methods: This paper proposed the process of the Kernel Rough K-Means algorithm (KRKM). Then the clustering accuracy was contrasted by utilizing the data sets from UCI repository. The experiment results shown the KRKM with improved clustering accuracy, comparing with the RKM algorithm. Results: The classification precision of KFCM and KRKM were improved. For the classification precision, KRKM was slightly higher than KFCM, indicating that KRKM was also an attractive alternative clustering algorithm and had good clustering effect when dealing with nonlinear clustering. Conclusion: Through the comparison with the precision of KFCM algorithm, it was found that KRKM had slight advantages in clustering accuracy. KRKM was one of the effective clustering algorithms that can be selected in nonlinear clustering.

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Zhu, Li, Yi Quan Wu, and Jun Yin. "Segmentation of Marine Spill Oil SAR Image Based on Gabor, Krawtchouk Moments and KFCM." Advanced Materials Research 760-762 (September 2013): 1462–66. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.1462.

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To further improve the accuracy of SAR image segmentation in the marine spill oil detection, a segmentation method of marine spill oil images based on Gabor, Krawtchouk moments and KFCM is proposed in this paper. Firstly, the marine spill oil image is decomposed by Gabor transform to obtain the texture features of image. Then, the Krawtchouk moments are applied to extract the shape features of image. Finally, the image segmentation is achieved based on KFCM. A large number of experimental results show that, compared with the related segmentation methods such as Tsallis entropy threshold method,CV model method and the method based on Gabor, Krawtchouk moments and FCM, the proposed method can achieve better result.

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Rodrigues, Tiegue Vieira. "Revisiting knowledge from Falsehood." Veritas (Porto Alegre) 62, no. 3 (December 28, 2017): 705. http://dx.doi.org/10.15448/1984-6746.2017.3.28610.

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***Revisitando o Conhecimento a partir de Falsidade***Os defensores da teoria do Conhecimento a partir de Falsidade (KFF) nos apresentam exemplos putativos de conhecimento inferencial nos quais um sujeito S, supostamente, adquire conhecimento através de uma inferência competente realizada a partir de uma falsidade. Se eles estiverem certos, teremos que enfrentar alguns problemas importantes para a epistemologia do raciocínio. No entanto, neste artigo, argumentarei que não há conhecimento a partir de falsidades (KFF), os casos apresentados pelos defensores de KFF não constituem casos de conhecimento inferencial genuíno e a reação intuitiva de atribuir conhecimento ao sujeito em tais casos não tem nenhuma relação com a falsidade. Eu irei direcionar a minha oposição à KFF através de duas objeções que ofereço à explicação apresentada por Peter Klein em seu artigo "Useful False Beliefs" (2008). Em particular, mostro que a explicação de Klein falha porque ela (i) é incapaz de demonstrar como uma falsidade pode fornecer um status epistêmico positivo à crença inferida para torná-la conhecimento; e (ii) ela é incompatível com uma noção tácita e amplamente aceita de inferência.

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Alves, Eduardo. "Restaurando a Explicação do Anulabilismo Falibilista sobre o Conhecimento a partir de Crença Falsa." Intuitio 14, no. 1 (September 2, 2021): e40517. http://dx.doi.org/10.15448/1983-4012.2021.1.40517.

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O objetivo deste artigo é responder a duas objeções que podem ser feitas à explicação do anulabilismo falibilista referente à possibilidade de conhecimento inferencial originado em falsidade (KFF). A primeira objeção é que a ausência de restauradores indica a incompletude da explicação anulabilista falibilista de KFF, enquanto a segunda é que o experimento mental de KFF viola o Princípio Resistência à Verdade* (RV*) — a principal tese do anulabilismo falibilista. Na primeira seção, explicarei no que consiste o debate acerca da possibilidade de conhecimento inferencial a partir de falsidade; na segunda seção, explicarei o anulabilismo falibilista, desenvolvida por de Almeida (2017); na última seção, desenvolverei os argumentos que podem ser feitos contra o anulabilismo falibilista e explicarei por que não funcionam.

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Xuejun Li, Yuxiang Cao, Lingli Jiang, and Ping Li. "Fault diagnostic method based on KPCA and KFCM." International Journal of Digital Content Technology and its Applications 7, no. 6 (March 31, 2013): 1284–91. http://dx.doi.org/10.4156/jdcta.vol7.issue6.147.

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Wei, Guanghong, Normand Mousseau, and Philippe Derreumaux. "Sampling the Self-Assembly Pathways of KFFE Hexamers." Biophysical Journal 87, no. 6 (December 2004): 3648–56. http://dx.doi.org/10.1529/biophysj.104.047688.

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Anwar, Miftahul, Daniel Moraru, Yuya Kawai, Maciej Ligowski, Takeshi Mizuno, Ryszard Jabłoński, and Michiharu Tabe. "KFM Observation of Electron Charging and Discharging in Phosphorus-Doped SOI Channel." Key Engineering Materials 470 (February 2011): 33–38. http://dx.doi.org/10.4028/www.scientific.net/kem.470.33.

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Low temperature Kelvin Probe Force Microscopy (LT-KFM) can be used to monitor the electronic potential of individual dopants under an electric field. This capability is demonstrated for silicon-on-insulator field-effect-transistors (SOI-FETs) with a phosphorus-doped channel. We show results of the detection of individual dopants in Si by LT-KFM. Furthermore, we also observe single-electron charging in individual dopants located in the Si channel region.

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Zhang, Chao, Chuang-Jin He, Shuai Li, Yu-Ling He, Xiao-Long Wang, Xiang-Yu Liu, and Lun Cheng. "A Hybrid Method to Diagnose 3D Rotor Eccentricity Faults in Synchronous Generators Based on ALIF_PE and KFCM." Mathematical Problems in Engineering 2021 (May 31, 2021): 1–14. http://dx.doi.org/10.1155/2021/5513881.

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This paper proposed a new hybrid diagnosis method for the generator’s 3D static eccentricity faults which include the axial eccentricity, the radial eccentricity, and the mixed eccentricity composed of the former two. Firstly, adaptive local iterative filtering (ALIF) method was used to decompose the vibration signals of the generator under eccentricity faults. Then, in order to figure out the intrinsic mode function (IMF) components with the upmost feature information, the correlation coefficient was calculated. Finally, the components’ permutation entropy (PE) is extracted to construct the eigenvector matrix which can be used to input the kernel fuzzy C-means (KFCM) algorithm to obtain the result of clustering. The result indicates that the classification coefficient based on ALIF and KFCM behaves closer to 1, while the average fuzzy entropy (FE) is closer to 0, showing that this method is able to detect different eccentricity faults more accurately.

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Cyvin, B. N., S. J. Cyvin, G. Diaz, T. Mogstad, and E. Rytter. "Molecular Vibrations of Gallium Trichloride Monomer with Application of the Keating Bending." Zeitschrift für Naturforschung A 40, no. 7 (July 1, 1985): 714–18. http://dx.doi.org/10.1515/zna-1985-0711.

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The vibrational spectra and previous normal coordinate analyses of GaCl3 are reviewed. The valence force field (VFF), Keating force field (KFF) and central force field (CFF) are investigated, taking into account isotopic frequency shifts and the mass influence on Coriolis constants. It seems that KFF is an appropriate force field approximation. In its definition a new type of internal coordinates, the Keating's bending, is invoked. A final force Field is tentatively determined and used to calculate the mean amplitudes of vibration.

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Hartigan, Erin H., Joseph Zeni, Stephanie Di Stasi, Michael J. Axe, and Lynn Snyder-Mackler. "Preoperative Predictors for Noncopers to Pass Return to Sports Criteria After ACL Reconstruction." Journal of Applied Biomechanics 28, no. 4 (August 2012): 366–73. http://dx.doi.org/10.1123/jab.28.4.366.

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Less than 50% of athletes pass criteria to return to sports (RTS) 6 months after ACL reconstruction (ACLR). Using data on 38 noncopers, we hypothesized that preoperative age, quadriceps strength index (QI), and knee flexion moments (KFM) during gait would predict the ability to pass/fail RTS criteria and that preoperative quadriceps strength gains would be predictive of passing RTS criteria. Gait analysis and strength data were collected before and after a preoperative intervention and 6 months after ACLR. Age, QI, and KFM each contributed to the predictability to pass or fail RTS criteria 6 months after ACLR. Collectively, the variables predict 69% who would pass and 82% who would fail RTS criteria 6 months after ACLR. Younger athletes who have symmetrical quadriceps strength and greater KFM were more likely to pass RTS criteria. Further, 63% of those who increased preoperative quadriceps strength passed RTS criteria, whereas 73% who did not failed. Increasing quadriceps strength in noncopers before ACLR seems warranted.

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Morante-Carballo, Fernando, Boris Apolo-Masache, Paúl Carrión-Mero, Bolívar Cedeño, and Javier Montalvan-Toala. "Considerations in the Methodology for the Technical-Environmental Viability of Sanitary Landfills in Rural Communities. Northern Case of the Province of Santa Elena, Ecuador." International Journal of Sustainable Development and Planning 16, no. 2 (April 23, 2021): 317–25. http://dx.doi.org/10.18280/ijsdp.160211.

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This research focuses on providing a solution to rural sectors' problems regarding solid waste management and final disposal. It considered the Sanitary Landfill (SL) technical-environmental viability for rural communities in the north of Santa Elena-Ecuador. The objective is to propose a methodology for evaluating a sanitary landfill's technical-environmental viability, considering a Key Factors Matrix (KFM) for the possibility of its application in rural communities. The proposed methodology is based on: i) identification of preliminary and field data for assessment of the sector through the KFM, and ii) determination of the technical-environmental viability of an SL according to the aspects considered. The KFM allowed the Ayangue commune to be chosen for the location of the SL under certain precautions. Given this sector's tourist influence, solid waste accumulates 40 tons per day from the ninth year on. Therefore, it is recommended to bear in mind a possible restructuring of the SL, from a semi-mechanized system to a fully mechanized one.

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Xiang, Yan, Jian Feng He, Lei Ma, San Li Yi, and Jia Ping Xu. "A Segmentation Method for Multiple Sclerosis White Matter Lesions on Conventional Magnetic Resonance Imaging Based on Kernel Fuzzy Clustering." Applied Mechanics and Materials 339 (July 2013): 361–65. http://dx.doi.org/10.4028/www.scientific.net/amm.339.361.

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Multiple sclerosis (MS) is a chronic disease that affects the central nervous system and impacts substantially on patients. MS lesions are visible in conventional magnetic resonance imaging (cMRI) and the automatic segmentation of MS lesions enables the efficient processing of images for research studies and in clinical trials. A new method for the segmentation of MS white matter lesions (WML) on cMRI is presented in this paper. Firstly the Kernel Fuzzy C-Means Clustering (KFCM) is applied to the preprocessed T1-weight (T1-w) image for extracting the white matter (WM) region. Then region growing algorithm is applied to the WM region image to make a binary mask which is then superimposed on the corresponding T2-weight (T2-w) image to yield a masked image only containing WM structures and lesions. The KFCM is then reapplied to the masked image to obtain MS lesions. The testing results show that the proposed method is able to segment WML on cMRI automatically and effectively.

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Resmi, V., and S. Vijayalakshmi. "Kernel Fuzzy Clustering with Output Layer Self-Connection Recurrent Neural Networks for Software Cost Estimation." Journal of Circuits, Systems and Computers 29, no. 06 (August 13, 2019): 2050091. http://dx.doi.org/10.1142/s0218126620500917.

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In the current world, the software cost estimation problem has been resolved using various newly developed methods. Significantly, the software cost estimation problems can be dealt with effectively with the recently grown recurrent neural network (RNN) than the other newly developed methods. In this paper, an improved approach is proposed to software cost estimation using Output layer self-connection recurrent neural networks (OLSRNN) with kernel fuzzy c-means clustering (KFCM). The proposed OLSRNN method follows the basics of traditional RNN models for integrating self-connections to the output layer; thereby, the output temporal dependencies are better captured. Also, the performance of neural networks is improved using the kernel fuzzy clustering algorithm to enhance software estimation results. Ultimately, five publicly available software cost estimation datasets are adapted to verify the efficacy of the proposed KFCM-OLSRNN method using the validation metrics such as MdMRE, PRED (0.25) and MMRE. The experimental results proved the efficiency of the proposed method for solving the software cost estimation problem.

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OKIGAWA, YUKI, TAKEO UMESAKA, YUTAKA OHNO, SHIGERU KISHIMOTO, and TAKASHI MIZUTANI. "POTENTIAL PROFILE MEASUREMENT OF CARBON NANOTUBE FETs BASED ON THE ELECTROSTATIC FORCE DETECTION." Nano 03, no. 01 (February 2008): 51–54. http://dx.doi.org/10.1142/s1793292008000812.

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We have measured the potential distribution on carbon nanotube (CNT) field-effect transistors (FETs) using electrostatic force microscopy (EFM) and Kelvin probe force microscopy (KFM). Clearer potential profiles were obtained by EFM than by KFM. When the CNT-FET is in the ON state, the EFM image shows uniform potential distribution along the CNT. In contrast, when the CNT-FET is in the OFF state, nonuniform potential image with dark spots are obtained. The dark spots can be attributed to the defects in the CNTs.

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Teng, Hsiang-Ling, Daniel Wu, Favian Su, Valentina Pedoia, Richard B. Souza, C. Benjamin Ma, and Xiaojuan Li. "Gait Characteristics Associated With a Greater Increase in Medial Knee Cartilage T1ρ and T2 Relaxation Times in Patients Undergoing Anterior Cruciate Ligament Reconstruction." American Journal of Sports Medicine 45, no. 14 (September 12, 2017): 3262–71. http://dx.doi.org/10.1177/0363546517723007.

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Background: Osteoarthritis of the medial tibiofemoral joint (MTFJ) is prevalent among patients undergoing anterior cruciate ligament reconstruction (ACLR). Magnetic resonance T1ρ and T2 relaxation times provide noninvasive methods to quantify early cartilage degeneration. Altered sagittal-plane gait biomechanics have been observed after ACLR, but their associations with longitudinal changes in MTFJ cartilage T1ρ and T2 remain unclear. Hypothesis/Purpose: To examine whether the peak knee flexion moment (KFM), knee flexion angle (KFA), and vertical ground-reaction force (vGRF) during gait are associated with prospective changes in medial tibiofemoral cartilage T1ρ and T2 in ACL-reconstructed knees and to compare these gait characteristics between patients undergoing ACLR and healthy control participants. We hypothesized that a higher KFM, KFA, and vGRF would be associated with greater increases in cartilage relaxation times and that patients undergoing ACLR would demonstrate altered gait characteristics compared with healthy controls. Study Design: Controlled laboratory study. Methods: Thirty-three patients undergoing ACLR underwent gait analysis before and 6 months and 1 year after ACLR and knee magnetic resonance imaging (MRI) before and 6 months, 1 year, and 2 years after ACLR. Twelve healthy controls underwent knee MRI and gait analysis at baseline and 1 year. Cartilage T1ρ and T2 were calculated for the medial tibia and medial femoral condyle. Linear regressions were used to evaluate associations between gait characteristics and changes in cartilage relaxation times from before ACLR to follow-up time points. Independent t tests were used to compare differences in gait between patients undergoing ACLR and control participants. Results: A higher KFM and KFA before ACLR were related to greater increases in medial femoral condyle T1ρ and T2 at 6 months after ACLR. Similarly, a higher KFM, KFA, and vGRF at 6 months were associated with greater increases in medial tibia and medial femoral condyle T1ρ and T2 at 1 and 2 years after ACLR. Gait characteristics at 1 year were not associated with changes in cartilage relaxation times at 2 years after ACLR. Compared with healthy controls, patients undergoing ACLR demonstrated a lower KFM at 6 months after ACLR. Conclusion/Clinical Relevance: The findings of this study revealed that a higher KFM, KFA, and vGRF during gait, especially at 6 months after ACLR, were associated with greater deterioration of MTFJ cartilage health at later time points.

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Wu, Yiquan, Wen Hou, and Shihua Wu. "Brain MRI segmentation using KFCM and Chan-Vese model." Transactions of Tianjin University 17, no. 3 (June 2011): 215–19. http://dx.doi.org/10.1007/s12209-011-1578-4.

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Zhang, Xiaoyan, and Mengjuan Wang. "Improved SVM classification algorithm based on KFCM and LDA." Journal of Physics: Conference Series 1693 (December 2020): 012107. http://dx.doi.org/10.1088/1742-6596/1693/1/012107.

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Wang, Yuxue, Zongxiang Song, and Xiaoping Ren. "Empirical Analysis of Stock Investment Based on β-KFCM." Journal of Physics: Conference Series 1624 (October 2020): 022050. http://dx.doi.org/10.1088/1742-6596/1624/2/022050.

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KATO Tomoya. "Kindergarten-Family Collaboration Model (KFCM) to Support Raising Children." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 2, no. 4 (December 31, 2010): 123–33. http://dx.doi.org/10.4156/aiss.vol2.issue4.13.

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Stulc, J., and B. Stulcova. "Effect of NaCl load administered to the fetus on the bidirectional movement of 51Cr-EDTA across rat placenta." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 270, no. 5 (May 1, 1996): R984—R989. http://dx.doi.org/10.1152/ajpregu.1996.270.5.r984.

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A hypothesis that, in the rat, fluid circulates across the placenta, with circulation being maintained by active transport of Na+ from mother to fetus, has been tested. Transfer of 51Cr-EDTA from mother to fetus and from fetus to mother has been measured and the respective unidirectional transfer constants, Kmf and Kfm, have been calculated. Immediately before the transfer measurement, the fetuses were injected intravenously with 10 microliters of isotonic glucose (controls); with 30 or 300 microliters of isotonic saline; or with 10, 30, or 60 microliters of 9% NaCl. In controls, Kmf of 51Cr-EDTA was 2.0 +/- 0.6 microliters/min, and Kfm was 4.3 +/- 1.0 microliters/min. Injecting the fetus with NaCl had no effect on Kmf, whereas the Kfm was increased significantly in a dose-dependent way. In other experiments, 51Cr-EDTA was injected into nephrectomized maternal animals, and the radioactivity of maternal and fetal plasma was followed for 30 h. The time course of fetal plasma radioactivity supported the thesis that the transfer of 51Cr-EDTA across the rat placenta is highly asymmetrical.

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Yazhini, K. K., and D. Loganathan. "DIABETIC RETINOPATHY DIAGNOSIS USING KERNEL FUZZY C MEANS WITH CONVOLUTIONAL NEURAL NETWORK BASED RESIDUAL MODEL." Advances in Mathematics: Scientific Journal 10, no. 1 (January 21, 2021): 413–22. http://dx.doi.org/10.37418/amsj.10.1.41.

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Presently, Internet of Things (IoT) becomes popular owing to diverse its application scenarios like transports, building, healthcare, etc. This study introduces an efficient IoT based diabetic retinopathy (DR) diagnosis model using Kernel Fuzzy C Means Segmentation and Residual Network. The proposed model involves a sequence of processes namely image acquisition, pre-processing, segmentation, feature extraction and classification. At the initial stage, retinal fundus image acquisition takes place which captures the retina image of the patient using head mounted camera. Next, kernel fuzzy c-means (KFCM) based segmentation process is applied to identify the diseased area. Then, the features are extracted using convolutional neural network (CNN) based residual network (ResNet) model. Finally, softmax function is employed to carry out the classification task. The validation of the presented model takes place using Kaggle DR dataset and the experimental results verified the superior performance of the presented model. The obtained results indicated that the KFCM-CNNR model has resulted to a maximum accuracy of 96.89%, sensitivity of 93.12% and specificity of 98.16%.

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Suzuki, Masatsugu, Mayumi Yokoyama, Manabu Onuma, Hiroshi Takahashi, Masami Yamanaka, Hideaki Okada, Yasuhiro Ichimura, and Noriyuki Ohtaishi. "Significant relationships between the serum leptin concentration and the conventional fat reserve indices in a wildlife species, Hokkaido sika deer (Cervus nippon yesoensis)." Wildlife Research 31, no. 1 (2004): 97. http://dx.doi.org/10.1071/wr02016.

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We assayed the serum leptin concentration and determined its correlation with the kidney fat mass (KFM), kidney fat index (KFI), and femur marrow fat (FMF) indices in 12 Hokkaido sika deer (Cervus nippon yesoensis Heude, 1884) collected in April, June, and October 2000. The KFM and KFI in April and June were both significantly lower than those in October. The leptin concentrations in April and June and in October were 1.222–1.521 ng mL–1 HE (Human Equivalent) units and 1.676–2.63 ng mL–1 HE, respectively, without overlapping. The relationships between the leptin concentration and the KFM, KFI, and FMF were all significant. Therefore, we conclude that the serum leptin concentration can be used as a new index for fat reserves in Hokkaido sika deer. However, reliable results could not be obtained from four samples collected in April and June when the deer were in a lower nutritional status. This may be due to the limited sensitivity of the antisera in the commercial multi-species leptin RIA kit used. For practical use in wildlife biology, species-specific leptin assays should be developed to eliminate this problem.

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Wang, Sizhong, Peter P. K. Chan, Ben M. F. Lam, Zoe Y. S. Chan, Janet H. W. Zhang, Chao Wang, Wing Kai Lam, Kevin Ki Wai Ho, Rosa H. M. Chan, and Roy T. H. Cheung. "Sensor-Based Gait Retraining Lowers Knee Adduction Moment and Improves Symptoms in Patients with Knee Osteoarthritis: A Randomized Controlled Trial." Sensors 21, no. 16 (August 19, 2021): 5596. http://dx.doi.org/10.3390/s21165596.

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The present study compared the effect between walking exercise and a newly developed sensor-based gait retraining on the peaks of knee adduction moment (KAM), knee adduction angular impulse (KAAI), knee flexion moment (KFM) and symptoms and functions in patients with early medial knee osteoarthritis (OA). Eligible participants (n = 71) with early medial knee OA (Kellgren-Lawrence grade I or II) were randomized to either walking exercise or gait retraining group. Knee loading-related parameters including KAM, KAAI and KFM were measured before and after 6-week gait retraining. We also examined clinical outcomes including visual analog pain scale (VASP) and Knee Injury and Osteoarthritis Outcome Score (KOOS) at each time point. After gait retraining, KAM1 and VASP were significantly reduced (both Ps < 0.001) and KOOS significantly improved (p = 0.004) in the gait retraining group, while these parameters remained similar in the walking exercise group (Ps ≥ 0.448). However, KAM2, KAAI and KFM did not change in both groups across time (Ps ≥ 0.120). A six-week sensor-based gait retraining, compared with walking exercise, was an effective intervention to lower medial knee loading, relieve knee pain and improve symptoms for patients with early medial knee OA.

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Li Jin, Liu Hao, and Wang Yuxiu. "Performance Evaluation of Cotton Yarns based on KFCM and KFDA." International Journal of Advancements in Computing Technology 4, no. 11 (June 30, 2012): 414–22. http://dx.doi.org/10.4156/ijact.vol4.issue11.45.

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Magonov, Sergei, and John Alexander. "Single-pass Kelvin force microscopy and dC/dZ measurements in the intermittent contact: applications to polymer materials." Beilstein Journal of Nanotechnology 2 (January 6, 2011): 15–27. http://dx.doi.org/10.3762/bjnano.2.2.

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We demonstrate that single-pass Kelvin force microscopy (KFM) and capacitance gradient (dC/dZ) measurements with force gradient detection of tip–sample electrostatic interactions can be performed in the intermittent contact regime in different environments. Such combination provides sensitive detection of the surface potential and capacitance gradient with nanometer-scale spatial resolution as it was verified on self-assemblies of fluoroalkanes and a metal alloy. The KFM and dC/dZ applications to several heterogeneous polymer materials demonstrate the compositional mapping of these samples in dry and humid air as well as in organic vapors. In situ imaging in different environments facilitates recognition of the constituents of multi-component polymer systems due to selective swelling of components.

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Grigor’eva, Alina, Alevtina Bardasheva, Anastasiya Tupitsyna, Nariman Amirkhanov, Nina Tikunova, Dmitrii Pyshnyi, Maksim Kleshev, and Elena Ryabchikova. "Changes in the Ultrastructure of Candida albicans Treated with Cationic Peptides." Microorganisms 8, no. 4 (April 17, 2020): 582. http://dx.doi.org/10.3390/microorganisms8040582.

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Candida albicans is becoming increasingly harmful for humans, which determines the need for new effective antifungal preparations. Currently, when testing antifungals, various morphological methods are used, among which transmission electron microscopy (TEM) is not the leading one. In this work, we used TEM to study the submicroscopic changes in C. albicans cells induced by cationic peptides R9F2 and (KFF)3K. Studies were performed on C. albicans-34 strain from the Collection of EMTC of ICBFM SB RAS in logarithmic phase. R9F2 and (KFF)3K showed an antifungal effect (MIC 10 and 20 μM) and suppressed fungal hyphal growth. Semithin and ultrathin sections of fungal suspensions incubated with 10 μM of peptides were studied at regular intervals from 15 min to 24 h. The first target of both peptides was plasmalemma, and its “alignment” was the only common morphological manifestation of their effect. Other changes in the plasmalemma and alteration of the vacuole and cell wall ultrastructure distinctly differed in cells treated with R9F2 and (KFF)3K peptides. In general, our work has shown pronounced differences of the temporal and morphologic characteristics of the effect of peptides, evidently related to their physicochemical properties. The benefit of TEM studies of ultrathin sections for understanding the mechanisms of action of antifungal drugs is shown.

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MARTENS, KOEN, STEPHEN S. SCHWARTZ, LEON BLAUSTEIN, and LEON BLAUSTEIN. "NON-MARINE OSTRACODA (CRUSTACEA) OF MOUNT CARMEL (ISRAEL), WITH TAXONOMIC NOTES ON EUCYPRIDINAE AND CIRCUM-MEDITERRANEAN HETEROCYPRIS." Israel Journal of Zoology 48, no. 1 (January 1, 2002): 53–70. http://dx.doi.org/10.1560/bmtf-kffg-076v-3m0j.

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Beechem, Michael. "Beechem Risk Inventory for Late-Onset Alcoholism." Journal of Drug Education 27, no. 4 (December 1997): 397–410. http://dx.doi.org/10.2190/v49d-5le1-ch0w-kf5m.

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This group study features an at-risk inventory administered to ninety-six respondents. The principle purposes of this study were: 1) to design a “user-friendly” assessment tool to identify elderly persons who may be at risk for drinking problems and/or late-life alcoholism; and 2) to identify unresolved loss-grief issues that will need to be addressed in the treatment phase. For each of the loss items, the respondent indicates whether the loss occurred at “(A) Age Fifty-Four and Younger” or “(B) Age Fifty-Five and Older.” The respondent also subjectively indicates the extent to which he/she feels the intensity of the loss at the moment (i.e., in the “here and now”). An additional feature of the inventory illustrates a simplified procedure to compute the respondent's unresolved loss-grief level through use of a 5-point Likert scale.

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Sass, Robert. "The Dark Side of Taiwan's Globalization Success Story." International Journal of Health Services 30, no. 4 (October 2000): 699–716. http://dx.doi.org/10.2190/kffc-wnr1-fpub-7p86.

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AUFRECHT, STEVEN E. "TOWARD A MODEL FOR DETERMINING APPROPRIATE CORRECTIVE ACTION IN PUBLIC EMPLOYEE DISCIPLINE." Journal of Collective Negotiations in the Public Sector 25, no. 3 (September 1, 1996): 1. http://dx.doi.org/10.2190/3r9e-6xq2-kfmf-lagq.

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DING, DAWEN, and WEN-HSIANG CHEN. "Damping of Moisture-Absorbed Composite Rackets." Journal of Reinforced Plastics and Composites 19, no. 11 (January 1, 2000): 848–62. http://dx.doi.org/10.1106/kfam-0xxj-areu-h1uh.

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Song, Hong, Xiangfei Cui, and Feifei Sun. "Breast Tissue 3D Segmentation and Visualization on MRI." International Journal of Biomedical Imaging 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/859746.

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Tissue segmentation and visualization are useful for breast lesion detection and quantitative analysis. In this paper, a 3D segmentation algorithm based on Kernel-based Fuzzy C-Means (KFCM) is proposed to separate the breast MR images into different tissues. Then, an improved volume rendering algorithm based on a new transfer function model is applied to implement 3D breast visualization. Experimental results have been shown visually and have achieved reasonable consistency.

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Magonov, Sergei, and John Alexander. "Multifrequency Atomic Force Microscopy: Compositional Imaging with Electrostatic Force Measurements." Microscopy and Microanalysis 17, no. 4 (July 19, 2011): 587–97. http://dx.doi.org/10.1017/s1431927611000122.

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AbstractWe demonstrate that single-pass Kelvin force microscopy (KFM) and dC/dz measurements in different environments expand the compositional imaging with atomic force microscopy. The KFM and dC/dz studies were performed in the intermittent contact mode with force gradient detection of tip-sample electrostatic interactions. Both factors contribute to sensitive measurements of the surface potential and capacitance gradient with nanometer-scale spatial resolution as it was verified on a broad range of materials: metal alloys, polymers, organic layers, and liquid-like objects. For many samples the surface potential and dC/dz variations complement each other in identification of individual components of heterogeneous materials. In situ imaging in different humidity or vapors of various organic solvents further facilitate recognition of the constituents of multicomponent polymer samples due to selective swelling of components.

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ZHANG, Na, and Yong-ping ZHANG. "Support vector machine ensemble model based on KFCM and its application." Journal of Computer Applications 30, no. 1 (March 11, 2010): 175–77. http://dx.doi.org/10.3724/sp.j.1087.2010.00175.

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Journal articles on the topic 'KFFM'

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