Performance of T2-based PCA mix control chart with KDE control limit for monitoring variable and attribute characteristics.

In this work, the mixed multivariate T2 control chart's detailed performance evaluation based on PCA mix is explored. The control limit of the proposed control chart is calculated using the kernel density approach. Through simulation studies, the proposed chart's performance is assessed in terms of its capacity to identify outliers and process shifts. When 30% more outliers are included in the data, the proposed chart provides a consistent accuracy rate for identifying mixed outliers. For the balanced percentage of attribute qualities, misdetection happens because of the high false alarm rate. For unbalanced attribute qualities and excessive proportions, the masking effect is the key issue. The proposed chart shows the improved performance for the shift in identifying the shift in the process.

Support vector data description with kernel density estimation (SVDD-KDE) control chart for network intrusion monitoring.

Multivariate control charts have been applied in many sectors. One of the sectors that employ this method is network intrusion detection. However, the issue arises when the conventional control chart faces difficulty monitoring the network-traffic data that do not follow a normal distribution as required. Consequently, more false alarms will be found when inspecting network traffic data. To settle this problem, support vector data description (SVDD) is suggested. The control chart based on the SVDD distance can be applied for the non-normal distribution, even the unknown distributions. Kernel density estimation (KDE) is the nonparametric approach that can be applied in estimating the control limit of the non-parametric control charts. Based on these facts, a multivariate chart based on the integrated SVDD and KDE (SVDD-KDE) is proposed to monitor the network's anomaly. Simulation using the synthetic dataset is performed to examine the performance of the SVDD-KDE chart in detecting multivariate data shifts and outliers. Based on the simulation results, the proposed method produces better performance in detecting shifts and higher accuracy in detecting outliers. Further, the proposed method is applied in the intrusion detection system (IDS) to monitor network attacks. The NSL-KDD data is analyzed as the benchmark dataset. A comparison between the SVDD-KDE chart with the other IDS-based-control chart and the machine learning algorithms is executed. Although the it has high computational cost, the results show that the IDS based on the SVDD-KDE chart produces a high accuracy at 0.917 and AUC at 0.915 with a low false positive rate compared to several algorithms.

Time series forecasting using singular spectrum analysis, fuzzy systems and neural networks.

Hybrid methodologies have become popular in many fields of research as they allow researchers to explore various methods, understand their strengths and weaknesses and combine them into new frameworks. Thus, the combination of different methods into a hybrid methodology allows to overcome the shortcomings of each singular method. This paper presents the methodology for two hybrid methods that can be used for time series forecasting. The first combines singular spectrum analysis with linear recurrent formula (SSA-LRF) and neural networks (NN), while the second combines the SSA-LRF and weighted fuzzy time series (WFTS). Some of the highlights of these proposed methodologies are:•The two hybrid methods proposed here are applicable to load data series and other time series data.•The two hybrid methods handle the deterministic and the nonlinear stochastic pattern in the data.•The two hybrid methods show a significant improvement to the single methods used separately and to other hybrid methods.

Regularized logistic regression with adjusted adaptive elastic net for gene selection in high dimensional cancer classification.

Cancer classification and gene selection in high-dimensional data have been popular research topics in genetics and molecular biology. Recently, adaptive regularized logistic regression using the elastic net regularization, which is called the adaptive elastic net, has been successfully applied in high-dimensional cancer classification to tackle both estimating the gene coefficients and performing gene selection simultaneously. The adaptive elastic net originally used elastic net estimates as the initial weight, however, using this weight may not be preferable for certain reasons: First, the elastic net estimator is biased in selecting genes. Second, it does not perform well when the pairwise correlations between variables are not high. Adjusted adaptive regularized logistic regression (AAElastic) is proposed to address these issues and encourage grouping effects simultaneously. The real data results indicate that AAElastic is significantly consistent in selecting genes compared to the other three competitor regularization methods. Additionally, the classification performance of AAElastic is comparable to the adaptive elastic net and better than other regularization methods. Thus, we can conclude that AAElastic is a reliable adaptive regularized logistic regression method in the field of high-dimensional cancer classification.

Enhanced cumulative sum charts for monitoring process dispersion.

The cumulative sum (CUSUM) control chart is widely used in industry for the detection of small and moderate shifts in process location and dispersion. For efficient monitoring of process variability, we present several CUSUM control charts for monitoring changes in standard deviation of a normal process. The newly developed control charts based on well-structured sampling techniques - extreme ranked set sampling, extreme double ranked set sampling and double extreme ranked set sampling, have significantly enhanced CUSUM chart ability to detect a wide range of shifts in process variability. The relative performances of the proposed CUSUM scale charts are evaluated in terms of the average run length (ARL) and standard deviation of run length, for point shift in variability. Moreover, for overall performance, we implore the use of the average ratio ARL and average extra quadratic loss. A comparison of the proposed CUSUM control charts with the classical CUSUM R chart, the classical CUSUM S chart, the fast initial response (FIR) CUSUM R chart, the FIR CUSUM S chart, the ranked set sampling (RSS) based CUSUM R chart and the RSS based CUSUM S chart, among others, are presented. An illustrative example using real dataset is given to demonstrate the practicability of the application of the proposed schemes.

Morphological study of the newly designed cementless femoral stem.

A morphology study was essential to the development of the cementless femoral stem because accurate dimensions for both the periosteal and endosteal canal ensure primary fixation stability for the stem, bone interface, and prevent stress shielding at the calcar region. This paper focused on a three-dimensional femoral model for Asian patients that applied preoperative planning and femoral stem design. We measured various femoral parameters such as the femoral head offset, collodiaphyseal angle, bowing angle, anteversion, and medullary canal diameters from the osteotomy level to 150 mm below the osteotomy level to determine the position of the isthmus. Other indices and ratios for the endosteal canal, metaphyseal, and flares were computed and examined. The results showed that Asian femurs are smaller than Western femurs, except in the metaphyseal region. The canal flare index (CFI) was poorly correlated (r < 0.50) to the metaphyseal canal flare index (MCFI), but correlated well (r = 0.66) with the corticomedullary index (CMI). The diversity of the femoral size, particularly in the metaphyseal region, allows for proper femoral stem design for Asian patients, improves osseointegration, and prolongs the life of the implant.

Primary stability recognition of the newly designed cementless femoral stem using digital signal processing.

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing.

Multilayer stock forecasting model using fuzzy time series.

After reviewing the vast body of literature on using FTS in stock market forecasting, certain deficiencies are distinguished in the hybridization of findings. In addition, the lack of constructive systematic framework, which can be helpful to indicate direction of growth in entire FTS forecasting systems, is outstanding. In this study, we propose a multilayer model for stock market forecasting including five logical significant layers. Every single layer has its detailed concern to assist forecast development by reconciling certain problems exclusively. To verify the model, a set of huge data containing Taiwan Stock Index (TAIEX), National Association of Securities Dealers Automated Quotations (NASDAQ), Dow Jones Industrial Average (DJI), and S&P 500 have been chosen as experimental datasets. The results indicate that the proposed methodology has the potential to be accepted as a framework for model development in stock market forecasts using FTS.

Design process of cementless femoral stem using a nonlinear three dimensional finite element analysis.

BACKGROUND: Minimal available information concerning hip morphology is the motivation for several researchers to study the difference between Asian and Western populations. Current use of a universal hip stem of variable size is not the best option for all femur types. This present study proposed a new design process of the cementless femoral stem using a three dimensional model which provided more information and accurate analysis compared to conventional methods. METHODS: This complete design cycle began with morphological analysis, followed by femoral stem design, fit and fill analysis, and nonlinear finite element analysis (FEA). Various femur parameters for periosteal and endosteal canal diameters are measured from the osteotomy level to 150 mm below to determine the isthmus position. RESULTS: The results showed better total fit (53.7%) and fill (76.7%) canal, with more load distributed proximally to prevent stress shielding at calcar region. The stem demonstrated lower displacement and micromotion (less than 40 µm) promoting osseointegration between the stem-bone and providing primary fixation stability. CONCLUSION: This new design process could be used as a preclinical assessment tool and will shorten the design cycle by identifying the major steps which must be taken while designing the femoral stem.

Fabrication of low-cost, cementless femoral stem 316L stainless steel using investment casting technique.

Total hip arthroplasty is a flourishing orthopedic surgery, generating billions of dollars of revenue. The cost associated with the fabrication of implants has been increasing year by year, and this phenomenon has burdened the patient with extra charges. Consequently, this study will focus on designing an accurate implant via implementing the reverse engineering of three-dimensional morphological study based on a particular population. By using finite element analysis, this study will assist to predict the outcome and could become a useful tool for preclinical testing of newly designed implants. A prototype is then fabricated using 316L stainless steel by applying investment casting techniques that reduce manufacturing cost without jeopardizing implant quality. The finite element analysis showed that the maximum von Mises stress was 66.88 MPa proximally with a safety factor of 2.39 against endosteal fracture, and micromotion was 4.73 µm, which promotes osseointegration. This method offers a fabrication process of cementless femoral stems with lower cost, subsequently helping patients, particularly those from nondeveloped countries.

Three-dimensional morphometric study of the trapezium shape of the trochlea tali.

The trapezium shape of the talar dome limits the use of 2-dimensional plain radiography for morphometric assessment because only 2 of the 4 required parameters can be measured. We used computed tomography data to measure the 4 morphologic parameters of the trochlea tali: anterior width, posterior width, trochlea tali length, and angle of trapezium shape. A total of 99 subjects underwent computed tomography scanning, and the left and right talus bones were both virtually modeled in 3 dimensions. The 4 morphologic parameters were measured 3 times each to obtain the intraclass correlation, and analysis of variance was used to check for any significant differences between the repeated measurements. The average intraclass correlation coefficient for the measurements for 2 to 3 trials was 0.94 ± 0.04. Statistical analyses were performed on the data from all 198 talus bones using SAS software, comparing male and female and left and right bones. All 4 morphometric values were greater in the male group. No significant differences were found between the left and right talus bones. A strong positive correlation was observed between the trochlea tali length and the anterior width. The angle of trapezium shape showed no correlation with the other 3 parameters. The measurements were compared with the dimensions of the current talar components of 4 total ankle arthroplasty implants. However, most of them did not perfectly match the trapezium shape of the talus from our population. We successfully analyzed the trapezium shape of the trochlea tali using reliable virtual 3-dimensional measurements. Compared with other published reports, our study showed a relatively smaller dimension of the trochlea tali than the European counterparts.

Morphology study of the proximal femur in Malay population / Estudio de la morfología del fémur proximal en la población malaya

Clinical practice in our country showed a lack of suitable implants that perfectly match the anthropometry of the local population. However, there have been no reports or comprehensive studies conducted to substantiate this argument. We therefore prospectively studied 120 hips from sixty subjects with an average age of 25+/-5.18 years old. The average weight and height were 61.48+/-13.84 kg and 1.65+/-9.63 m respectively. The exclusion criteria were pregnant woman, those who had injury to the hip joint, and those with implant or prosthesis. Four parameters were measured ­ the femoral head diameter (FHD), femoral neck length (FNL), femoral neck width (FNW) and collo-diaphyseal angle (CDA). Statistical analysis showed no significant differences between left and right femora but significant differences were found between male and female subjects. The results for the male and female femurs are as follows ­ FHD: 43.6+/-3.1 mm and 38.9+/-2.2 mm; FNL: 91.1+/-5.7 mm and 81.8+/-4.3 mm; FNW: 28.9+/-3.4 mm and 26.0+/-4.3 mm; CDA: 132.3°+/-3.4° and 129.9°+/-4.0°. This data could be used as a guideline to design a more suitable implant for the Malay population which covers most of the South East Asian countries.

Problemas con respecto al tamaño de los implantes en relación a cada población se han convertido en una cuestión esencial para la sociedad ortopédica. Varios factores han sido identificados en la literatura, los que pueden afectar la estabilidad del implante, especialmente en el fémur proximal. Se estudió prospectivamente 120 caderas mediante imágenes de tomografía computarizada. Sesenta sujetos fueron reclutados, edad media 25+/-5,18 años, peso de 61,48+/-13,84 kg y altura de 1,65+/-9,63m. Los criterios de exclusión para este estudio incluyeron a mujeres embarazadas, quienes hubiesen experimentado lesiones cadera, uso de implantes o prótesis. Nuestros datos se compararon usando las pruebas de Anderson-Darling y t-test. Los parámetros medidos fueron diámetro de la cabeza femoral (FHD), longitud del cuello femoral (FNL), ancho del cuello femoral (FNW) y el ángulo cuello-diafisial (CDA). Los resultados de los fémures masculinos y femeninos fueron los siguientes: FHD 43,6 +/- 3,1 mm y 38,9 +/- 2,2 mm, FNL 91,1 +/- 5,7 mm y 81,8 +/- 4,3 mm, FNW 28,9 +/- 3,4 mm y 26,0 +/- 4,3 mm; CDA 132.3 +/- 3.4 y 129.9 +/- 4,. Este estudio prospectivo y transversal centrado en la población malaya, proporcionó información esencial sobre el valor normal de la porción proximal del fémur, datos que mejorarán el conocimiento de los aspectos anatómicos y, finalmente, ayuden al diseño del vástago femoral en la artroplastía total de cadera (ATC). Los resultados proporcionarán una nueva comprensión por parte del cirujano ortopédico.