Operational Skill and TNA （Training Needs Analysis） for Generation Power Plant

Training needs analysis is the preliminary step in a cyclical process which adds to the overall training and progress strategy of staff in a generation power plant or a professional group, questionnaires were distributed among WAJPCO （Wadi Al Jizzi Power Company） staff and their responses were used to conduct a training need and gap analyses with a view to identify the operational skill and the training needs of the generation power plant, the time and travel commitment the industry is willing to invest in employee training, and an understanding of what skills are considered specific to lumber manufacturing and what can be combined with the needs of other industries and taught locally.

Propagation Mechanisms of Incident Tsunami Wave in Jiangsu Coastal Area,Caused by Eastern Japan Earthquake on March 11,2011

At 13：46 on March 11, 2011（Beijing time）, an earthquake of Mw=9.0 occurred in Japan. By comparing the tsunami data from Guanhekou marine station with other tsunami wave observation gathered from southeast coastal area of China, it was evident that, only in Guanhekou, the position of the maximum wave height appeared in the middle part rather than in the front of the tsunami wave train. A numerical model of tsunami propagation based on 2-D nonlinear shallow water equations was built to study the impact range and main causes of the special tsunami waveform discovered in Jiangsu coastal area. The results showed that nearly three-quarters of the Jiangsu coastal area, mainly comprised the part north of the radial sand ridges, reached its maximum tsunami wave height in the middle part of the wave train. The main cause of the special waveform was the special underwater topography condition of the Yellow Sea and the East China Sea area, which influenced the tsunami propagation and waveform significantly. Although land boundary reflection brought an effect on the position of the maximum wave height to a certain extent, as the limits of the incident waveform and distances between the observation points and shore, it was not the dominant influence factor of the special waveform. Coriolis force＇s impact on the tsunami waves was so weak that it was not the main cause for the special phenomenon in Jiangsu coastal area. The study reminds us that the most destructive wave might not appear in the first one in tsunami wave train.

On Exploring Method and Software for Evaluating Effectiveness of Military Training Aircraft

The evaluation of training effectiveness （TE） of military training aircraft, though obviously very important, appears to have attracted much less attention than what it deserves in the open literature. This article aims to start from previous studies and explore further. First, TE of military training aircraft is discussed and our ideas for evaluating TE which are expressed mathematically are proposed. Then, using the presented mathematical models, software is developed that takes into consideration the influence of parameters of flight performance and quality on TE. The software＇s environment is Borland C＋＋ and it sets up the parameters of trainer, training standard databases and training documents; it can analyze and then give the operational cost and cost-effectiveness ratio of military trainer. Finally, the software is utilized to compare the TEs of HAWK and MB339 with that of Chinese Air Force TF-6. The results of comparison show that the TE of TF-6 is the lowest.

Past review,current progress,and challenges ahead on the cocktail party problem

The cocktail party problem,i.e.,tracing and recognizing the speech of a specific speaker when multiple speakers talk simultaneously,is one of the critical problems yet to be solved to enable the wide application of automatic speech recognition(ASR) systems.In this overview paper,we review the techniques proposed in the last two decades in attacking this problem.We focus our discussions on the speech separation problem given its central role in the cocktail party environment,and describe the conventional single-channel techniques such as computational auditory scene analysis(CASA),non-negative matrix factorization(NMF) and generative models,the conventional multi-channel techniques such as beamforming and multi-channel blind source separation,and the newly developed deep learning-based techniques,such as deep clustering(DPCL),the deep attractor network(DANet),and permutation invariant training(PIT).We also present techniques developed to improve ASR accuracy and speaker identification in the cocktail party environment.We argue effectively exploiting information in the microphone array,the acoustic training set,and the language itself using a more powerful model.Better optimization ob jective and techniques will be the approach to solving the cocktail party problem.