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Fri, 27 Nov 2017 09:12:05 +0900>This invention relates to an automatic cash collection system and more particularly to an apparatus for collecting the money deposited in a number of separate deposit boxes and delivering it to a department store or the like.
It is known to have a number of deposit boxes in a store, each comprising a cashbox or so-called transaction box for depositing coins, and a coin return box containing a return-receiving aperture for receiving deposited coins. The deposit boxes are connected to a central post box, a number of which may be provided in the store to effect the simultaneous return of deposited coins to the bank. A central coin divider is mounted in the central post box for dividing the deposited coins into the deposit boxes. A number of corresponding depositing machines, including depositing machines having the capability of sorting coins are available to deposit coins within the deposit boxes.
It is known to provide a number of additional deposit boxes, each for receiving a key-operated depositing machine for selectively depositing money deposited in the deposit boxes. Each deposit box connected to such a depositing machine is known as a so-called `transaction box`.
In the operation of the deposit system, coins are deposited in each deposit box and are deposited within a common deposit box. The deposited coins are then delivered to the central post box or central coin divider. The centrally deposited coins are divided by the central coin divider to effect delivery to the appropriate deposit boxes. When the system is to be maintained in a non

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Some experts claim that the two big data sets, National Security Agency (NSA) and Electronic Communications Privacy Act (ECPA), have recently lost their value as stand-alone indicators of serious criminality.

They say these two big data sets have high false negative rates, and their use in gauging an increase in serious criminality must be coupled with other data sources. These include crime statistics, court records, victimization surveys, and police computer logs.

Misleading headlines and the glut of reams of studies to support them claim that the NSA’s bulk data collection violates the Constitution by violating privacy.

But there is also a growing body of researchers who find that the NSA’s bulk data collection is the best way to counter terrorism.

Misleading headlines and the glut of reams of studies to support them claim that the NSA’s bulk data collection violates the Constitution by violating privacy.

But there is also a growing body of researchers who find that the NSA’s bulk data collection is the best way to counter terrorism.

A good example of this body of research is David Bittner and Ted Amoroso’s work published in The Journal of Criminal Justice in 2013. In what is considered one of the top data driven papers in the forensic crime analysis field, Bittner and Amoroso show that the NSA’s bulk data collection program is an effective tool to counter terrorism.

Further, they argue that the NSA’s bulk data collection program is more effective than law enforcement agencies at finding terrorists.

Bittner and Amoroso point to the fact that on December 12, 2001, less than a week after the 9/11 attacks on the World Trade Center and the Pentagon, the FBI gained access to hundreds of millions of telephone records. Yet they were unable to find a single lead to an imminent attack on the USA.

Bittner and Amoroso write that:

Given the limited impact of data collection as a deterrent against lone-wolf terrorists and the risk that indiscriminate collection would be exploited by others, we contend that the balance of risks favors the abandonment of blanket collection of all telecommunications metadata under the Fourth Amendment.

Their analysis indicates that the NSA’s bulk collection of data is more effective than law enforcement in finding lone wolf and “lone wolf-like” terrorists. While Bittner and Amoroso conclude that non-US citizen-led terrorist activity is not a

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