A study of learning time patterns in asynchronous learning environments

Abstract This research makes use of learning time intensity, burst evaluating equations, and state denotation approaches to evaluate the learning time characteristics of students. Through comparing learning time intensity, six burst styles and three diligence styles are categorized. From the statistical results and interaction content analysis, some pedagogical phenomena were found. The first finding is that the more diligent learners were, the higher the quality and quantity of their interaction. The second is that learners whose learning time intensity was mainly located in the early period of the course and whose interaction content included many complaints were suspected to be possible dropouts. The third finding is that learners whose learning time intensity was mainly located in the later period had achievements that were significantly different from those of the regular periodical reading learners whose learning time intensity was distributed in all periods of the course. The above findings raise some issues and suggestions for those concerned with proposing asynchronous courses. As students can pace their own learning in an asynchronous learning environment, it is hard to avoid getting used to intermittent intensive reading. Instructors should consider seriously how to guide students to learn in a proper sequence through a well‐scheduled instructional programme. It is necessary to encourage students to exercise self‐discipline in regular on‐line reading for better learning outcomes.     

Runx1 Messenger RNA Delivered by Polyplex Nanomicelles Alleviate Spinal Disc Hydration Loss in a Rat Disc Degeneration Model

Vertebral disc degenerative disease (DDD) affects millions of people worldwide and is a critical factor leading to low back and neck pain and consequent disability. Currently, no strategy has addressed curing DDD from fundamental aspects, because the pathological mechanism leading to DDD is still controversial. One possible mechanism points to the homeostatic status of extracellular matrix (ECM) anabolism, and catabolism in the disc may play a vital role in the disease’s progression. If the damaged disc receives an abundant amount of cartilage, anabolic factors may stimulate the residual cells in the damaged disc to secrete the ECM and mitigate the degeneration process. To examine this hypothesis, a cartilage anabolic factor, Runx1, was expressed by mRNA through a sophisticated polyamine-based PEG-polyplex nanomicelle delivery system in the damaged disc in a rat model. The mRNA medicine and polyamine carrier have favorable safety characteristics and biocompatibility for regenerative medicine. The endocytosis of mRNA-loaded polyplex nanomicelles in vitro, mRNA delivery efficacy, hydration content, disc shrinkage, and ECM in the disc in vivo were also examined. The data revealed that the mRNA-loaded polyplex nanomicelle was promptly engulfed by cellular late endosome, then spread into the cytosol homogeneously at a rate of less than 20 min post-administration of the mRNA medicine. The mRNA expression persisted for at least 6-days post-injection in vivo. Furthermore, the Runx1 mRNA delivered by polyplex nanomicelles increased hydration content by ≈43% in the punctured disc at 4-weeks post-injection (wpi) compared with naked Runx1 mRNA administration. Meanwhile, the disc space and ECM production were also significantly ameliorated in the polyplex nanomicelle group. This study demonstrated that anabolic factor administration by polyplex nanomicelle-protected mRNA medicine, such as Runx1, plays a key role in alleviating the progress of DDD, which is an imbalance scenario of disc metabolism. This platform could be further developed as a promising strategy applied to regenerative medicine.     

Integration of a-Si:H solar cell with novel twist nematic liquid crystal cell for adjustable brightness and enhanced power characteristics

This study improves the output power and brightness characteristics of a translucent hydrogenated amorphous silicon (a-Si:H) solar cell by integrating the solar cell with a novel twist nematic (TN) liquid crystal (LC) cell incorporating a sub-wavelength metal grating polarization beam splitter (PBS). Although conventional TN-LC cells are widely used to adjust the brightness in many display applications, the sheet polarizers used in such cells decay when exposed to ultraviolet (UV) rays and have a low light efficiency. Accordingly, in this study, a sub-wavelength metal grating PBS is used to replace not only the sheet polarizers in the conventional TN-LC cell but also the upper and lower alignment layers and transparent electrodes. Therefore, a translucent a-Si:H solar cell integrating with the novel TN-LC cell with the sub-wavelength metal grating PBS could improve power efficiency and durability in UV ray environment. The experimental results show that the transmittance gap between the “on” and “off” states of the enhanced translucent a-Si:H solar cell/novel TN-LC cell is of the order of 26.6% (i.e. 4.3-30.9%) for incident light with a wavelength of 800 nm, 6.3% (i.e. 10.8-17.1%) for an incident wavelength of 400 nm and 2.7% (i.e. 0-2.7%) for an incident wavelength of 510 nm. Moreover, it is shown that the novel TN-LC cell increases the maximum electrical power developed by the translucent a-Si:H solar cell and improves its power conversion efficiency by 0.209% in the “off” state and 0.417% in the “on” state. As a result, the proposed device represents an ideal solution for building-integrated photovoltaic (BIPV) systems, automobile industry applications and many other adjustable brightness photovoltaic applications.     

An Assessment of Testing-Effort Dependent Software Reliability Growth Models

Over the last several decades, many Software Reliability Growth Models (SRGM) have been developed to greatly facilitate engineers and managers in tracking and measuring the growth of reliability as software is being improved. However, some research work indicates that the delayed S-shaped model may not fit the software failure data well when the testing-effort spent on fault detection is not a constant. Thus, in this paper, we first review the logistic testing-effort function that can be used to describe the amount of testing-effort spent on software testing. We describe how to incorporate the logistic testing-effort function into both exponential-type, and S-shaped software reliability models. The proposed models are also discussed under both ideal, and imperfect debugging conditions. Results from applying the proposed models to two real data sets are discussed, and compared with other traditional SRGM to show that the proposed models can give better predictions, and that the logistic testing-effort function is suitable for incorporating directly into both exponential-type, and S-shaped software reliability models     

Optimal release time for software systems considering cost, testing-effort, and test efficiency

In this paper, we study the impact of software testing effort & efficiency on the modeling of software reliability, including the cost for optimal release time. This paper presents two important issues in software reliability modeling & software reliability economics: testing effort, and efficiency. First, we propose a generalized logistic testing-effort function that enjoys the advantage of relating work profile more directly to the natural flow of software development, and can be used to describe the possible testing-effort patterns. Furthermore, we incorporate the generalized logistic testing-effort function into software reliability modeling, and evaluate its fault-prediction capability through several numerical experiments based on real data. Secondly, we address the effects of new testing techniques or tools for increasing the efficiency of software testing. Based on the proposed software reliability model, we present a software cost model to reflect the effectiveness of introducing new technologies. Numerical examples & related data analyzes are presented in detail. From the experimental results, we obtain a software economic policy which provides a comprehensive analysis of software based on cost & test efficiency. Moreover, the policy can also help project managers determine when to stop testing for market release at the right time.     

Software Reliability Analysis and Measurement Using Finite and Infinite Server Queueing Models

Software reliability is often defined as the probability of failure-free software operation for a specified period of time in a specified environment. During the past 30 years, many software reliability growth models (SRGM) have been proposed for estimating the reliability growth of software. In practice, effective debugging is not easy because the fault may not be immediately obvious. Software engineers need time to read, and analyze the collected failure data. The time delayed by the fault detection & correction processes should not be negligible. Experience shows that the software debugging process can be described, and modeled using queueing system. In this paper, we will use both finite, and infinite server queueing models to predict software reliability. We will also investigate the problem of imperfect debugging, where fixing one bug creates another. Numerical examples based on two sets of real failure data are presented, and discussed in detail. Experimental results show that the proposed framework incorporating both fault detection, and correction processes for SRGM has a fairly accurate prediction capability.     

Lane-mark extraction for automobiles under complex conditions

Lane-mark detection is one of the most important parts of the intelligent transportation system (ITS). Cameras mounted in front of automobiles are used to capture the road scene to detect lane-marks. This paper proposes a new lane-mark extraction algorithm that consists of six parts. We first determine the regions of interest (ROIs) of captured images and investigate their boundaries. Then, we divide the boundary image into subimages to calculate the local edge-orientation of each block and remove edges with abnormal orientations. After that, the multi-adaptive thresholding method is employed for each subimage so that the system can work efficiently for an image that has different contrasts to indicate sub-regions for lane-marks. We then verify these candidate lane-mark edges and fit the lane-marks using either straight or curved line models. A Kalman filter is also applied to track them. The proposed method is evaluated in several situations, including in bad weather conditions and in the presence of shadow effects, obstacles such as wipers, or road signs on the road. The results show that the proposed method can detect the lane-marks in real time for various complex environments.     

The visual color QR code algorithm (DWT-QR) based on wavelet transform and human vision system

Multimedia Tools and Applications - A novel visual Quick Response (QR) code algorithm based on Wavelet transform and Human Visual System (HVS) approach is presented in this study and named DWT-QR....     

Optimal testing resource allocation, and sensitivity analysis in software development

We consider two kinds of software testing-resource allocation problems. The first problem is to minimize the number of remaining faults given a fixed amount of testing-effort, and a reliability objective. The second problem is to minimize the amount of testing-effort given the number of remaining faults, and a reliability objective. We have proposed several strategies for module testing to help software project managers solve these problems, and make the best decisions. We provide several systematic solutions based on a nonhomogeneous Poisson process model, allowing systematic allocation of a specified amount of testing-resource expenditures for each software module under some constraints. We describe several numerical examples on the optimal testing-resource allocation problems to show applications & impacts of the proposed strategies during module testing. Experimental results indicate the advantages of the approaches we proposed in guiding software engineers & project managers toward best testing resource allocation in practice. Finally, an extensive sensitivity analysis is presented to investigate the effects of various principal parameters on the optimization problem of testing-resource allocation. The results can help us know which parameters have the most significant influence, and the changes of optimal testing-effort expenditures affected by the variations of fault detection rate & expected initial faults.     

Design and analysis of GUI test-case prioritization using weight-based methods

Testing the correctness of a GUI-based application is more complex than the conventional code-based application. In addition to testing the underlying codes of the GUI application, the space of possible combinations of events with a large GUI-input sequence also requires creating numerous test cases to confirm the adequacy of the GUI testing. Running all GUI test cases and then fixing all found bugs may be time-consuming and delaying the project completion. Hence, it is important to advance the test cases that uncover the most faults as fast as possible in the testing process. Test-case prioritization has been proposed and used in recent years because it can improve the rate of fault detection during the testing phase. However, few studies have discussed the problem of GUI test-case prioritization. In this paper, we propose a weighted-event flow graph for solving the non-weighted GUI test case and ranking GUI test cases based on weight scores. The weighted scores can either be ranked from high to low or be ordered by dynamic adjusted scores. Finally, three experiments are performed, and experimental results show that the adjusted-weight method can obtain a better fault-detection rate.