by Lewis C. Fort and Elisha V. Long in the preparation of the case against Lay for the murder of
Edward Farr. Leahy and Fort were two of the ablest and most energetic prosecutors in the Territory. Moreover, they and Chief Justice Mills were of one mind: the mysterious prisoner was an outlaw, a pre-convicted train robber, and a salutary example was going to be made of him.1
No chances were to be taken. When rumor reached official ears that friends of the prisoner in El Paso were collecting money to bail him out, recourse was had to another section of the Post Office act of 1872. So, on September 15, Chief Deputy
Marshal J.J. Sheridan presented additional charges of unlawfully detaining and attempting to rob the United States mail. Section 287 of the act might have been designed with a mind to flexibility.2
The purpose of this maneuver was wholly preemptive. Each charge would keep the defendant in custody pending an appearance before the U.S. commissioner, and after each hearing a further bond of $1,000 would be set. These were well-worn procedures, intended to ensure that the prisoner could not legally regain his liberty during the preparation of the substantive charges—in this instance, territorial charges of train robbery and murder.
Fundamental concept:Solving business problems with data science starts with analytical engineering: designing an analytical solution, based on the data, tools, and techniques available.
Exemplary technique:Expected value as a framework for data science solution design.
Ultimately, data science is about extracting information or knowledge from
data, based on principled techniques. However, as we’ve discussed throughout
the book, seldom does the world provide us with important business problems
perfectly aligned with these techniques, or with data represented such that
the techniques can be applied directly. Ironically, this fact often is better accepted by the business users (for whom it is often obvious) than by entry-level data scientists—because academic programs in statistics, machine learning, and data mining often present students with problems ready for the application of the tools that the programs teach.
Reality is much messier. Business problems rarely are classification problems or regression problems or clustering problems. They’re just business problems. Recall the mini-cycle in the first stages of the data mining process, where we focus on business understanding and data understanding. In these stages we must design or engineer a solution to the business problem. As with engineering more broadly, the data science team considers the needs of the business as well as the tools that might be brought to bear to solve the problem.
Ten dodatek opisuje kroki niezbdne do rozpoczcia programowania aplikacji platformy Java EE 6 za pomoc rodowiska IDE NetBeans i serwera GlassFish.
NetBeans jest oferowanym na zasadzie open source, atwym w uyciu, rozbudowanym rodowiskiem wytwarzania (IDE) aplikacji platformy Java EE 6. GlassFish jest serwerem aplikacji zgodnym z platform Java EE 6. Take ten serwer jest dostpny na zasadzie open source, a przy tym jest lekki i ma moduow budow. Poczenie rodowiska NetBeans i serwera GlassFish umoliwia sprawne wytwarzanie, wdraanie i uruchamianie aplikacji platformy Java EE 6.
rodowisko NetBeans mona pobra ze strony internetowej http://netbeans.org. Serwer GlassFish Open Source Edition mona pobra ze strony http://glassfish.org. Warto pamita, e rodowisko NetBeans jest udostpniane w formie rnych pakietw oferujcych odmienne zakresy funkcji. Na przykad pakiety nazwane All i Java EE obejmuj serwer GlassFish.
Warto odwiedzi stron http://netbeans.org/kb/trails/java-ee.html, na ktrej mona znale rozbudowan list artykuw, blogw i zapisw wideo przygotowanych m.in. z myl o programistach, ktrzy dopiero rozpoczynaj swoj przygod z platform Java EE i NetBeans. Poniej wymieniono artykuy, ktre mog bardzo pomc w opanowaniu wytwarzania i wdraania aplikacji platformy Java EE 6:
Abstract—Online gaming has frequently been analyzed as a potential medium for covert communications. However, massivelymultiplayer online role-playing games offer considerable advantages over other multiplayer game systems, allowing them to be manipulated for the purpose of leaking information with greater security and efﬁciency. This paper discusses the use of EVE Online for the construction of a covert channel combining aspects of both behavior channels and storage channels to hide the transmission of encoded data to another user.
I. I NTRODUCTION
Since the original deﬁnition of covert channels by Lampson
, emergent networking technologies have been analyzed for their potential for the transmission of covert information. To a similar extent, new protocols using existing technologies are analyzed. However, while the protocols used by Internet games are old, the exponentially increasing complexity in many online games provides new opportunities to apply Lampson’s methods of information leakage; opportunities which have not been extensively researched in recent years. That said, not all games are equal. While many online games provide the capacity to convey information, it is massively-multiplayer online role-playing games (MMORPGs) in particular that offer the best mix of traits for use in this role. As Johnson, Lutz, and Yuan  note, the communicants in an MMORPG can be extremely difﬁcult to identify due to the use of a single central server and the large number (thousands or more) of users. Although the speciﬁc methods described here are not necessarily innovative, and are similarly limited as those described by