S-phase fractions of breast carcinomas. Relationships to morphology, estrogen and progesterone receptors, and early recurrence

Analysis of the S-phase fractions (SPF) measured by in vitro thymidine labeling, morphological appearances, and estrogen receptor (ER) assays of primary invasive breast carcinomas demonstrated several interrelationships. Lobular, mucinous, tubular, and adenocystic carcinomas consistently had low SPF and were usually positive for ER. The same was true for the carcinomas of no special histologic type [the not otherwise specified (NOS) group of E. R. Fisher including "infiltrating ductal" and undifferentiated carcinomas] with minimal anaplasia. Medullary, atypical medullary, and morphologically unclassifiable carcinomas with marked nuclear anaplasia nearly always had high SPF and were usually negative for ER. High SPF was associated with advanced stages of carcinoma initially or with early recurrence following mastectomy.     

Interactive augmented reality system for enhancing library instruction in elementary schools

Due to limited budgets and manpower, most elementary schools in Taiwan do not plan or provide library instruction for students. Although students can use libraries, they typically lack the knowledge needed to use library resources effectively. Consequently, students have difficulty finding the books they need and can easily become overwhelmed by the massive amount of information in libraries. Computer-assisted instruction for teaching basic library skills to large numbers of students is an appealing method. Particularly, developing augmented reality (AR) technologies for learning have garnered considerable attention in education research. Many researchers and scholars believe that integrating teaching and AR enhances student learning performance and motivation. This work develops an educational AR system based on situated learning theory, and applies innovative augmented reality interactive technology to a library’s learning environment. Student library knowledge can be enhanced via the proposed augmented reality library instruction system (ARLIS). Experimental results demonstrate that student learning performance is improved significantly by using the proposed ARLIS. Moreover, this work demonstrates that using the proposed ARLIS for library instruction results in the same learning performance as conventional librarian instruction and there is no gender difference on learning performance between the proposed ARLIS and conventional librarian instruction. Moreover, the proposed library instruction system overcomes shortcomings of personal teaching skills of librarians that may adversely affect student learning performance by conveying the same learning content to all students. Additionally, the proposed system results in better learning performance for learners with the field-dependent cognitive style than learners with the field-independent cognitive style. Further, the proposed system provides more benefits in terms of library skills of application and comprehension than conventional librarian instruction. Moreover, the learning performance of students is not affected by their gaming skills. Therefore, student gaming skills do not need to be considered when adopting the proposed system in library instruction programs.     

Preliminary cost estimates for thin-film transistor liquid–crystal display inspection and repair equipment: A hybrid hierarchical approach

The thin-film transistor liquid–crystal display (TFT-LCD) industry has developed rapidly in recent years. Because TFT-LCD manufacturing is highly complex and requires different tools for different products, accurately estimating the cost of manufacturing TFT-LCD equipment is essential. Conventional cost estimation models include linear regression (LR), artificial neural networks (ANNs), and support vector regression (SVR). Nevertheless, in accordance with recent evidence that a hierarchical structure outperforms a flat structure, this study proposes a hierarchical classification and regression (HCR) approach for improving the accuracy of cost predictions for TFT-LCD inspection and repair equipment. Specifically, first-level analyses by HCR classify new unknown cases into specific classes. The cases are then inputted into the corresponding prediction models for the final output. In this study, experimental results based on a real world dataset containing data for TFT-LCD equipment development projects performed by a leading Taiwan provider show that three prediction models based on HCR approach are generally comparable or better than three conventional flat models (LR, ANN, and SVR) in terms of prediction accuracy. In particular, the 4-class and 5-class support vector machines in the first-level HCR combined with individual SVR obtain the lowest root mean square error (RMSE) and mean average percentage error (MAPE) rates, respectively.     

Optimal expansion of competence sets with multilevel skills

The purpose of competence set expansion is to find an optimal expansion process at the minimal cost and then obtain the required competence set from the acquired competence set to solve a problem. Several models have been proposed to address the competence set expansion problem of only a single decision maker or multiple decision makers without considering multilevel skills. However, a practical competence set expansion model should involve multiple decision makers and multilevel skills. This study discusses an optimal expansion model of incorporating competence sets of group decision makers with multilevel skills. The proposed method not only obtains the optimal competence set expansion of all decision makers with the maximal total benefit but finds all optimal alternatives of the competence set expansion model. A cooperative alliance problem is solved to illustrate the usefulness of the proposed method.     

The effect of moderator’s facilitative strategies on online synchronous discussions

Moderators play an important role within a computer supported collaborative learning environment, and thus facilitative strategies and communication technology are nowadays used to enhance students’ learning. This study proposed facilitative strategies as a guide for students’ learning, and explored the influence of these strategies on the students’ online synchronous discussion. A total of 331 senior high school students from eight computer classes in northern Taiwan were recruited to participate in this study. They were randomly assigned into an experimental condition, with the moderators’ facilitation to complete online learning tasks, and the control condition without moderators’ support. To fulfill the goal of the research, four strategies—helping students focus on the main topic, facilitating students’ making argumentation, giving students positive feedback, and helping students sustain threaded discussion—were adopted to facilitate the online synchronous discussion in the experimental condition. According to the results of the content analysis, four group discussion patterns were revealed, including collaboration, centralization, partial contribution, and non-interaction. The findings suggest that the moderator helped enhance the collaboration pattern and increase the online participation rate. In addition, it was found that the strategies of helping students focus on the main topic and giving students positive feedback were frequently employed.     

From immediate agreement to eventual agreement: early stopping agreement protocol for dynamic networks with malicious faulty processors

With the rapid advancement of wireless networking technology, networks have evolved from static to dynamic. Reliability of dynamic networks has virtually become an important issue. Fortunately, a solution to the above issue can be derived from solutions to the Byzantine Agreement (BA) problem. BA problem can be solved by protocols that make processors reach an agreement through message exchange. Protocols used to solve the problem can be divided into Immediate Byzantine Agreement (IBA) protocols and Eventual Byzantine Agreement (EBA) protocols. In IBA protocols, the number of rounds of message exchange is determined by the total number of processors in the network. Even if no faulty processor is present in the network, IBA protocols still require a fixed number of rounds of message exchange, causing a waste of time. In contrast, EBA protocols dynamically adjust the number of rounds of message exchange according to the interference of faulty processors. In terms of efficiency, EBA protocols certainly outperform IBA protocols. Due to the fact that the existing EBA protocols have been designed for static networks, they cannot work on dynamic networks. In this paper, we revisit the EBA problem in dynamic networks to increase the reliability of dynamic networks. Simulations will be conducted to validate that the proposed protocol requires the minimum rounds of message exchange and can tolerate the maximum number of malicious faulty processors compared to other existing protocols.     

A fast regularity measure for surface defect detection

In this paper, we propose a fast regularity measure for defect detection in non-textured and homogeneously textured surfaces, with specific emphasis on ill-defined subtle defects. A small neighborhood window of proper size is first chosen and they slide over the entire inspection image in a pixel-by-pixel basis. The regularity measure for each image patch enclosed in the window is then derived from the eigenvalues of the covariance matrix formed by the variance–covariance of the x- and y-coordinates with the pixel gray levels as the weights for all pixel points in the window. The two eigenvalues of the weighted covariance matrix will be approximately the same when the image patch contains only a homogeneous region, whereas the two eigenvalues will be relatively different if the image patch in the window contains a defect. The smaller eigenvalue of the covariance matrix is then used as the regularity measure. The integral image technique is introduced to the computation of the regularity measure so that it is invariant to the neighborhood window size. The proposed method uses only one single discrimination feature for defect detection. It avoids the use of complicated classifiers in a high-dimensional feature space, and requires no learning process from a set of defective and defect-free training samples. Experimental results on a variety of material surfaces found in industry, including textured images of plastic surfaces and leather and non-textured images of backside solar wafers and LCD backlight panels, have shown the effectiveness of the proposed regularity measure for surface defect detection. It is computationally very fast, and takes only 0.032 s for a 400 × 400 image on a Pentium 3.00?GHz personal computer. In a test set of 73 backside solar wafer images involving 53 defect-free and 20 defective samples, the proposed regularity measure can correctly identify all the test images.     

A three-axis SOI accelerometer sensing with both in-plane and vertical comb electrodes

A three-axis capacitive accelerometer based on silicon-on-insulator is designed and fabricated. In the accelerometer, totally eight groups of capacitors are compactly arranged around an octagonal proof mass. The four groups of capacitors along orthogonal direction with in-plane comb electrodes detect XY acceleration, while the other four groups of capacitors along diagonal direction with vertical comb electrodes detect Z acceleration. Measurements of in-plane and vertical motion by the respective in-plane and vertical comb electrodes enable direct detection for all the three axes with differential capacitive sensing scheme. For the fabricated accelerometer in the size of 4 × 4 mm², the capacitance sensitivities of in-plane and out-of-plane accelerometers are 145.3 and 9.1 fF/g, respectively.     

A new hybrid and dynamic fusion of multiple experts for intelligent porch system

Intelligent porch research is an important issue in smart home development; however, such a field was rarely investigated in the literature. This investigation proposes a new hybrid and dynamic fusion of multiple experts for the intelligent porch system. First, a new hybrid priority tree with decision fusion (HPTD-fusion) is proposed to eliminate the problems of tag-based authentication outdoors. The HPTD-fusion first verifies the vocal entrance code (VEC), and subsequently the remaining experts are performed in the cases of AND, OR or majority voting for decision fusion. Second, the post-mapping dynamic weighted fusion (PMDW-fusion) scheme is presented to adapt the indoor porch audio-visual environment. The PMDW-fusion dynamically assigns the higher weight to experts with higher performance, and then sums all participating experts for score fusion. The experimental results demonstrate that FRR and FAR can reach up to 0.18 and 0.19, respectively, when the system is tested in the outdoor environment. Furthermore, the indoor recognition accuracy can be increased to 86.1% using the proposed fusion scheme. The experiments have verified the effectiveness and feasibility of the proposed system. Restated, the contribution of this work is to develop a novel intelligent porch system incorporating a natural and unobtrusive method for identity recognition. The proposed system has been installed and tested in a real-world environment in the Technologies for Ubiquitous Computing and Humanity (TOUCH) Center at National Cheng Kung University.