The effects of the number of links and navigation support on cognitive load and learning with hypertext: The mediating role of reading order

Problems in learning with hypertext systems have been claimed to be caused by high levels of disorientation and cognitive load. This was recognized by DeStefano and LeFevre [DeStefano, D., & LeFevre, J. -A., (2007). Cognitive load in hypertext reading: A review. Computers in Human Behavior, 23(3), 1616–1641.] who predicted an increase of cognitive load and impairment of learning for hypertexts with a higher number of links per page. From a practical perspective, several navigation support techniques, such as providing link suggestions, have been proposed for guiding learners and reducing cognitive overload. In an experiment, we tested DeStefano and LeFevre’s predictions as well as the usefulness of link suggestions. Participants used different versions of a hypertext, either with 3-links or 8-links per page, presenting link suggestions or not. We tested their cognitive load and learning outcomes. Results showed that there was a benefit of using link suggestions for learning, but no effect of number of links on learning was found. Moreover, the effects of our manipulations on cognitive load were mediated by the reading order that participants selected. Implications for research and the design of navigation support systems are discussed.     

The complementary exponential geometric distribution: Model, properties, and a comparison with its counterpart

In this paper, we proposed a new two-parameter lifetime distribution with increasing failure rate, the complementary exponential geometric distribution, which is complementary to the exponential geometric model proposed by Adamidis and Loukas (1998). The new distribution arises on a latent complementary risks scenario, in which the lifetime associated with a particular risk is not observable; rather, we observe only the maximum lifetime value among all risks. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulas for its reliability and failure rate functions, moments, including the mean and variance, variation coefficient, and modal value. The parameter estimation is based on the usual maximum likelihood approach. We report the results of a misspecification simulation study performed in order to assess the extent of misspecification errors when testing the exponential geometric distribution against our complementary one in the presence of different sample size and censoring percentage. The methodology is illustrated on four real datasets; we also make a comparison between both modeling approaches.     

Groundwater Model Calibration by Meta-Heuristic Algorithms

Groundwater models are computer models that simulate or predict aquifer conditions by using input data sets and hydraulic parameters. Commonly, hydraulic parameters are extracted by calibration, using observed and simulated aquifer conditions. The accuracy of calibration affects other modeling processes, especially the hydraulic head simulation. Meta-heuristic algorithms are good candidates to determine optimal/near-optimal parameters in groundwater models. In this paper, two meta-heuristic algorithms: (1) particle swarm optimization (PSO) and (2) pattern search (PS) are applied and compared in the Ghaen aquifer, by considering the sum of the squared deviation (SSD) between observed and simulated hydraulic heads and the sum of the absolute value of deviation (SAD) between observed and simulated hydraulic heads as the objective functions. Results show that obtained values of the objective function are enhanced significantly by using the PS algorithm. Accordingly, PS improves (decreases) the SSD and SAD by 0.20 and 2.36 percent, respectively, compared to results reported by using the PSO algorithm. Results also indicate that the proposed PS optimization tool is effective in the calibration of aquifer parameters.     

Discussion of “Assessments of Impacts of Climate Change and Human Activities on Runoff with SWAT for the Huifa River Basin, Northeast China” by Aijing Zhang; Chi Zhang; Guobin Fu; Bende Wang; Zhenxin Bao; and Hongxing Zheng

Zhang et al. (Water Resour Manag doi:10.1007/s11269-012-0182-2, 2012) studied the impacts of climate change and human activities on the runoff for the Huifa River basin. They employed a soil and water assessment tool (SWAT), which was calibrated for the baseline period 1956–1964, and then used to reconstruct the natural runoff for the climate change period 1965–2000. Results showed that both climate change and human activities decrease the observed runoff. Climate change impacts on annual runoff were ?37.7, ?59.5, +36.9, and ?45.2 mm/a for 1965–1975, 1976–1985, 1986–1995, and 1996–2005 respectively, compared with the baseline period 1956–1964. Human activities decreased runoff and caused a relatively larger magnitude impact than those of climate change after 1985. Human activities decreased the annual runoff by ?32.9, ?46.8, ?67.8, and ?54.9 mm/a for 1965–1975, 1976–1985, 1986–1995, and 1996–2005 respectively. Human activities further decreased runoff in wet years due to regulation and storage of water projects.     

Algorithm for Increasing the Speed of Evolutionary Optimization and its Accuracy in Multi-objective Problems

Optimization algorithms are important tools for the solution of combinatorial management problems. Nowadays, many of those problems are addressed by using evolutionary algorithms (EAs) that move toward a near-optimal solution by repetitive simulations. Sometimes, such extensive simulations are not possible or are costly and time-consuming. Thus, in this study a method based on artificial neural networks (ANN) is proposed to reduce the number of simulations required in EAs. Specifically, an ANN simulator is used to reduce the number of simulations by the main simulator. The ANN is trained and updated only for required areas in the decision space. Performance of the proposed method is examined by integrating it with the non-dominated sorting genetic algorithm (NSGAII) in multi-objective problems. In terms of density and optimality of the Pareto front, the hybrid NSGAII-ANN is able to extract the Pareto front with much less simulation time compared to the sole use of the NSGAII algorithm. The proposed NSGAII-ANN methodology was examined using three standard test problems (FON, KUR, and ZDT1) and one real-world problem. The latter addresses the operation of a reservoir with two objectives (meeting demand and flood control). Thus, based on this study, use of the NSGAII-ANN integrative algorithm in problems with time-consuming simulators reduces the required time for optimization up to 50 times. Results of the real-world problem, despite lower computational-time requirements, show a performance similar to that achieved in the aforementioned test problems.     

Self-Organising Maps: A new way to screen the level of satisfaction of dialysis patients

Evaluation of patient satisfaction has become an important indicator for assessing health care quality. Fresenius Medical Care (FME) as a global provider of dialysis services through its NephroCare network has a strong interest in monitoring patient satisfaction.The aim of the paper is to test and validate a methodology for detecting a residual area of low satisfaction in dialysis patients.The FME Patient Satisfaction Programme questionnaire was distributed to haemodialysis (HD) patients treated in 335 centers of its network. It contained 79 questions covering various satisfaction aspects regarding Dialysis Unit, Dialysis Arrangement, Nurses, Doctors, etc.To analyse the data provided by the questionnaire, the Self-Organising Map (SOM) method was used. SOM is a neural network model for clustering and projecting high-dimensional data into a low-dimensional space, preserving topological relationships of original high-dimensional data spaces.10,632 HD patients completed the questionnaire. Mean age was 63.05 ± 14.93 years with 56.69% males. Response rate was 66%. Overall level of satisfaction was 1.99 (range from ?3 to +3). On average patients were very satisfied with all issues. Nevertheless, a group of patients, around 60 years old, balanced gender ratio, whose level of satisfaction was lower than 1, were highlighted.In the NephroCare clinics patient satisfaction with service is rather high. While traditional analysis usually stops here, the SOM method allows identification of areas of potential improvement for specific patient groups.     

Cognitive Trauma Therapy for Battered Women With PTSD (CTT-BW).

This article describes a second treatment-outcome study of cognitive trauma therapy for battered women with posttraumatic stress disorder (PTSD; CTT-BW). CTT-BW includes trauma history exploration: PTSD education; stress management; exposure to abuse and abuser reminders; self-monitoring of negative self-talk; cognitive therapy for guilt; and modules on self-advocacy, assertiveness, and how to identify perpetrators. One hundred twenty-five ethnically diverse women were randomly assigned to immediate or delayed CTT-BW. PTSD remitted in 87% of women who completed CTT-BW, with large reductions in depression and guilt and substantial increases in self-esteem. White and ethnic minority women benefited equally from CTT-BW. Similar treatment outcomes were obtained by male and female therapists and by therapists with different levels of education and training. Gains were maintained at 3- and 6-month follow-ups. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Complex chain of momentum transfer of body segments in the baseball pitching motion

Abstract

Baseball pitching requires contributions from and interaction among all limb segments. Most previous investigators have concentrated on the throwing arm itself, but the center of mass (COM) and contribution of all segments in the pitching motion have not been studied. The purpose of this study was to investigate the momentum transfer of all body segments in the pitching motion. The kinematics pitching motion data were captured from three experienced pitchers (one is professional, two are amateurs). A ten‐segment body system was modeled in this study. The results showed that the lowest position of the COM during the pitching cycle occurred around the ball release time and the fastest velocity (2.81±0.18 m/sec) of the COM was in the late cocking phase. The trunk and thigh on the throwing side showed the largest linear momentum among all segments in the late cocking phase. The upper throwing arm and forearm had peak linear momentum in the acceleration phase. The trunk also had the largest angular momentum during the pitching cycle and reached the maximum rotational momentum (4.17±1.22 Kg‐m²/sec) in the late cocking phase and medial bending momentum (9.03±5.78 Kg‐m²/sec) at the end of the late cocking phase. From the time sequence of linear momentum changes, especially in the leading direction, the force transfer from the foot to the trunk then through the upper extremity during the pitching motion was identified. The largest change rate of angular momentum found in the trunk meant that the trunk contributed the largest torque in the pitching motion. Better coordination of the body segments in the pitching motion not only enhances performance but also avoids injury. The coordination of motion by athletes in the pitching motion provides a guideline for better coaching and training.