Wireless power transfer (WPT) has been a very popular topic of research recently. In most research the coil design is based on the classical theory and the parameters of the coils are obtained by calculations or direct measurements. However, the method has its limitation when the shape and structure of the coil is complex or the coil hasn't been constructed. The purpose of this paper is to present the whole process of designing coils and building a wireless power transfer system with the finite element analysis (FEA) and with MATLAB simulation in detail. Finally the experimental results will be presented to verify the validity and reasonability of the design method.

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Abstract:Purpose: Collusion is a common behavior of oligarch enterprises aiming to get an advantage in market competition. The purpose of the research is to explore positive or negative effects from the electricity generation manufacturers' collusion through statistical analysis approach. To be exact, these effects are discovered both in market economy at a macro-economic level and in enterprise behaviors at a micro-economic level.Design/methodology/approach: This research designs a model as an extension of Porter's model (Green & Porter, 1984). In this model FIML is applied. Taking price bidding project launched in China's power industry as an example, this paper conducts an empirical research on its relevant price data collected from subordinate power plants of China's five power generation groups in the pilots. Findings:It is found in this paper that power generation enterprises are facing collusion issues in the market. To be exact, it is such a situation in which non-cooperative competition and collusion alternate. Under the competition, market is relatively steady, thus forming a lower network price. It is helpful to the development of the whole industry. However, once Cartel is formed, the price will rise and clash with power enterprises and transmission-distribution companies concerning the interests conflicts. At the same time, a higher power price will form in the market, making consumers suffer losses. All of these are bad for industry development.-943-Journal of Industrial Engineering and Management -http://dx.doi. org/10.3926/jiem.1515 Not only the collusion of power enterprises affects power price but also the market power that caused by long-time Cartel will reduce the market entrant in electricity generation. Market resources are centralized in the hands of Cartel, causing a low effective competition in the market, which has passive effects on users. Implications:The empirical research also indicates that collusion undoubtedly benefits the power enterprises that involved. As a cooperation pattern, collusion can lead to the synergy between relevant companies. However, collusion harms the benefits of other market entities.During the process of enterprises creating common interests cooperatively, collusion may bring harm to the outside industry.Originality/value: Using empirical research method, the paper takes China's power industry as an example to show the gains and losses of collusion from two aspects, namely market economy and strategic management.

The length of a shoe has significant value in reflecting characteristics of the owner, and thereby, it can help in tracking suspects in criminal cases. However, the shoeprints left at a crime scene are often incomplete, resulting in difficulties in assessing shoe length. To find a way to estimate the shoe length from a partial shoeprint, 109 shoes with different sizes and general patterns were collected, and their prints were lifted using magnetic powder. Four feature points were defined on a shoeprint, and the longest distance between the feature points was defined as shoe length. Using linear, quadratic, and cubic regression analyses, a total of 15 equations were obtained between the shoe length and the other distances between the feature points. Out of these, the five most accurate equations were selected as the optimal equation. The verified test, including another 18 pairs of shoes, showed an average error of equations between 0.591 cm and 0.732 cm. The equations were also applied in two practical cases, resulting in good accuracy. The study demonstrates that shoe length could be determined from partial shoeprints through the proven equations.

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