In the case of ordinary identification coding, a code is devised to identify a single object among N objects. But, in this paper, we consider a coding problem to identify K objects at once among N objects in the both cases that K objects are ranked or not ranked. By combining Moulin-Koetter scheme with the ε-almost strongly universal class of hash functions used in Kurosawa-Yoshida scheme, an efficient and explicit coding scheme is proposed for K-multiple-object identification (K-MOID) coding. Furthermore, it is shown that the K-MOID capacity CK-MOID, which is the maximum achievable coding rate in the K-MOID coding, is equal to the ordinary channel capacity, and the proposed scheme can attain CK-MOID.

In the case of ordinary identification coding, a code is devised to identify one object among N objects. But, in this paper, we consider an identification coding problem to identify M objects at once among N objects in the both cases that M objects are or are not ranked. By combining Kurosawa-Yoshida scheme with Moulin-Koetter scheme, an efficient identification code is proposed, which can attain high coding rate and error exponents compared with the case that an ordinary identification code is used M times.

Now open source style R&D is not only community based R&D but also adoptable for business. But each open source projects have their own licences. We analyse open source licenses by cluster analysis and find the importance of standards. This means that standards for license like creative commons need for easy adoption of open source programs as a part of legacy business programs. On the other hand patent pool or other frameworks starts to adopt for sharing intellectual property rights among companies, organisations, and universities. Then we show the new model for open based R&D on business.