An investigation of trends and issues of technology education

The purpose of this study was to investigate the nature of the current technology education movement and its impacts, problems, directions, as well as prospects for future development of technology education;A survey questionnaire consisting of three parts was used for collecting the data pertaining to program characteristics, objectives, problems, solutions, and prospects of technology education. Factor analysis was performed to verify the underlying structure of the instrument. Four orthogonal factors were extracted from the analysis for philosophical objectives of technology education. These four factors were: (1) technological literacy, (2) conventional IA objective, (3) intellectual development, and (4) use of tools and machines;Six problem factors derived from factor analysis were labeled as: (1) teaching content, (2) perception of program, (3) teacher education program, (4) student recruitment, (5) facility, and (6) teacher shortage;Six solution factors for solving TE problems were also extracted from factor analysis. They included: (1) curriculum development, (2) public relations, (3) teacher education, (4) perspective teacher recruitment, (5) female student recruitment, and (6) facility planning and innovation;Three prospect factors were extracted from factor analysis and were identified as: (1) program quality and image, (2) facility and curriculum, and (3) graduate and enrollment. These derived factors were used for further hypothesis testing;Eight hypotheses were formulated and tested in this study;Results of the study indicated that the responses of the three subject groups were very uniform. Their perceptions on most of the objective, problem, solution, and prospect factors of technology education were not significantly different from one another;A technology education curriculum development framework was presented along with the teaching scope and sequence for K-12

Protection of the Extracts of Lentinus edodes Mycelia against Carbon-Tetrachloride-Induced Hepatic Injury in Rats

Lentinus edodes is the medicinal macrofungus showing potential for therapeutic applications in infectious disorders including hepatitis. In an attempt to develop the agent for handling hepatic injury, we used the extracts of Lentinus edodes mycelia (LEM) to screen the effect on hepatic injury in rats induced by carbon tetrachloride (CCl4). Intraperitoneal administration of CCl4 not only increased plasma glutamic oxaloacetic transaminase (GOT) and glutamic pyruvic transaminase (GPT) but also decreased hepatic superoxide dismutase (SOD) and glutathione peroxidase (GPx) levels in rats. Similar to the positive control silymarin, oral administration (three times daily) of this product (LEM) for 8 weeks significantly reduced plasma GOT and GPT. Also, the activities of antioxidant enzymes of SOD and GPx were elevated by LEM. in liver from CCl4-treated rats, indicating that mycelium can increase antioxidant-like activity. Moreover, the hepatic mRNA and protein levels of SOD and GPx were both markedly raised by LEM. The obtained results suggest that oral administration of the extracts of Lentinus edodes mycelia (LEM) has the protective effect against CCl4-induced hepatic injury in rats, mainly due to an increase in antioxidant-like action

Pure spin current generation in a Rashba-Dresselhaus quantum channel

We demonstrate a spin pump to generate pure spin current of tunable intensity and polarization in the absence of charge current. The pumping functionality is achieved by means of an ac gate voltage that modulates the Rashba constant dynamically in a local region of a quantum channel with both static Rashba and Dresselhaus spin-orbit interactions. Spin-resolved Floquet scattering matrix is calculated to analyze the whole scattering process. Pumped spin current can be divided into spin-preserved transmission and spin-flip reflection parts. These two terms have opposite polarization of spin current and are competing with each other. Our proposed spin-based device can be utilized for non-magnetic control of spin flow by tuning the ac gate voltage and the driving frequency.Comment: 6 pages, 3 figure

A Neural Network Decision Method for Software Maintenance Life Cycle Identification

The software maintenance life cycle concept is a powerful model in helping software maintenance planning. The operationalization of the life cycle concept requires a heuristic decision method. Although the heuristic decision method works most of the time, the method requires integration of different tools and sometimes leads to errors. In this paper, we propose a neural network decision method, which combines data smoothing and maintenance stage identification into one unit

Identifying the attack sources of botnets for a renewable energy management system by using a revised locust swarm optimisation scheme

Distributed denial of service (DDoS) attacks often use botnets to generate a high volume of packets and adopt controlled zombies for flooding a victim’s network over the Internet. Analysing the multiple sources of DDoS attacks typically involves reconstructing attack paths between the victim and attackers by using Internet protocol traceback (IPTBK) schemes. In general, traditional route-searching algorithms, such as particle swarm optimisation (PSO), have a high convergence speed for IPTBK, but easily fall into the local optima. This paper proposes an IPTBK analysis scheme for multimodal optimisation problems by applying a revised locust swarm optimisation (LSO) algorithm to the reconstructed attack path in order to identify the most probable attack paths. For evaluating the effectiveness of the DDoS control centres, networks with a topology size of 32 and 64 nodes were simulated using the ns-3 tool. The average accuracy of the LS-PSO algorithm reached 97.06 for the effects of dynamic traffic in two experimental networks (number of nodes = 32 and 64). Compared with traditional PSO algorithms, the revised LSO algorithm exhibited a superior searching performance in multimodal optimisation problems and increased the accuracy in traceability analysis for IPTBK problems

Adversarially Robust Submodular Maximization under Knapsack Constraints

We propose the first adversarially robust algorithm for monotone submodular maximization under single and multiple knapsack constraints with scalable implementations in distributed and streaming settings. For a single knapsack constraint, our algorithm outputs a robust summary of almost optimal (up to polylogarithmic factors) size, from which a constant-factor approximation to the optimal solution can be constructed. For multiple knapsack constraints, our approximation is within a constant-factor of the best known non-robust solution. We evaluate the performance of our algorithms by comparison to natural robustifications of existing non-robust algorithms under two objectives: 1) dominating set for large social network graphs from Facebook and Twitter collected by the Stanford Network Analysis Project (SNAP), 2) movie recommendations on a dataset from MovieLens. Experimental results show that our algorithms give the best objective for a majority of the inputs and show strong performance even compared to offline algorithms that are given the set of removals in advance.Comment: To appear in KDD 201