Use and performances of Web-based portfolio assessment

This research explored the influence of a Web-based portfolio assessment system on students' performances. The methodological procedure adopted was to have the experimental group use the system, with the control group using conventional assessment. The study subjects were junior high school students of two computer classes. The experimental results revealed that the use of the system has significant positive influence on students' performances. According to estimated effect size, the most significant indicators were reflection, self-assessment, continuous improvement, goal setting, problem solving, data gathering, work and peer interaction. However, peer-assessment performance was not enhanced significantly. Therefore, one recommendation was to reduce peer-assessment and instead offer specific illustrations to the students as well as the opportunity to drill.     

五加科分族新纲要

The present paper deals with the following three aspects:      1. It attempts to discuss the problems on primitive forms of the family Araliaceae. The genus Tupidanthus Hook. f. & Thoms. was considered by H. Harms (1894) and H. L. Li (1942) as primitive, whilst another genus Plerandra A. Gray was regarded as primitive by R. H. Eyde & C. C. Tseng in 1971. Having made a detailed comparison of the taxonomical characters of these two genera, the present authors believe that both genera are not the most primitive in the Araliaceae. Their affinit yis not close enough and they possibly evolved in parallel lines from a common ancestor which is so far un- known yet.      2. By studying the systems of the past, the present authors believe that none of them is entirely satisfactory. Bentham (1867) recognized five ‘series’ (in fact, equival- ent to ‘tribe’ with the ending-eae of names) based on the petaline arrangement in the bud, the numbers of stamen and the types of endospem. This is a plausible funda- mental treatment for the Araliaceae, but choosing the endosperm as a criteria in dividing tribe is artifical. As we know today, both ruminate and uniform endosperm are usually presente in the same genus.  Seemann’s system (1868) divided the Hederaceae (excl. Trib. Aralieae) into five tribes, in addition to the locules of ovary.  The criteria are essentially the same as Bentham’s. The system of Hams (1894) divided the family into three tribes. Two tribes, Aralieae and Mackinlayeae, of  Bentham are  retained,  but other groups were combined in the Trib. Schefflereae.  However, Harms did not retain one of those three oldest legitimate names which had named by Bentham, that is con- trary to the law of priority in the International Code of Botanical Nomenelature. Hut- chinson (1967) adopted seven tribes for the family. The criteria essentially follow those of Bentham, but the inflorescence is overstressed. The inflorescence is an artifical taxono- mical character in dividing tribes, because of some dioecious plants, such as Meryta sin- clairii (Hook. f.) Seem., have two types of inflorescence in male and female plants. Ac- cording to Hutchinson’s arrangement, the male and female plants would be put in se- parate tribes.     3.   The present authors are of the opinion that in the study of a natural classi- fication of plant groups emphasis should be laid not only on the characters of the repro- ductive organs, but on those of vegetative organs as well.  The present revised system is based principally upon the characters of both flowers and leaves of the five tribes as follows:       Trib. 1. Plerandreae Benth. emend. Hoo & Tseng      Trib. 2. Tetraplasandreae Hoo & Tseng       Trib. 3. Mackinlayeae Benth.      Trib. 4. Aralieae Benth.       Trib. 5. Panaceae Benth. emend. Hoo & Tseng     

Effects of compression garments on surface EMG and physiological responses during and after distance running

BackgroundThe few previous studies that focused on the effects of compression garments (CG) on distance running performance have simultaneously measured electromyogram, physiological, and perceptual parameters. Therefore, this study investigated the effects of CG on muscle activation and median frequency during and after distance running, as well as blood-lactate concentration and rating of perceived exertion (RPE) during distance running.MethodsEight healthy male recreational runners were recruited to randomly perform two 40 min treadmill running trials, one with CG, and the other with control garment made of normal cloth. The RPE and the surface electromyography (EMG) of 5 lower extremity muscles including gluteus maximus (GM), rectus femoris (RF), semitendinosus (ST), tibialis anterior (TA), and gastrocnemius (GAS) were measured during the running trial. The blood-lactate levels before and after the running trial were measured.ResultsWearing CG led to significant lower muscle activation (p < 0.05) in the GM (decreased 7.40%–14.31%), RF (decreased 4.39%–4.76%), and ST (decreased 3.42%–7.20%) muscles; moreover, significant higher median frequency (p < 0.05) in the GM (increased 5.57%) and ST (increased 10.58%) muscles. Wearing CG did not alter the RPE values or the blood-lactate levels (p > 0.05).ConclusionWearing CG was associated with significantly lower muscle activation and higher median frequency in the running-related key muscles during distance running. This finding suggested that wearing CG may improve muscle function, which might enhance running performance and prevent muscle fatigue.     

Mining fuzzy frequent itemsets for hierarchical document clustering

As text documents are explosively increasing in the Internet, the process of hierarchical document clustering has been proven to be useful for grouping similar documents for versatile applications. However, most document clustering methods still suffer from challenges in dealing with the problems of high dimensionality, scalability, accuracy, and meaningful cluster labels. In this paper, we will present an effective Fuzzy Frequent Itemset-Based Hierarchical Clustering (F²IHC) approach, which uses fuzzy association rule mining algorithm to improve the clustering accuracy of Frequent Itemset-Based Hierarchical Clustering (FIHC) method. In our approach, the key terms will be extracted from the document set, and each document is pre-processed into the designated representation for the following mining process. Then, a fuzzy association rule mining algorithm for text is employed to discover a set of highly-related fuzzy frequent itemsets, which contain key terms to be regarded as the labels of the candidate clusters. Finally, these documents will be clustered into a hierarchical cluster tree by referring to these candidate clusters. We have conducted experiments to evaluate the performance based on Classic4, Hitech, Re0, Reuters, and Wap datasets. The experimental results show that our approach not only absolutely retains the merits of FIHC, but also improves the accuracy quality of FIHC.