these problems can lead to the development of procedures to reduce their likelihood, including the management of resources. The challenges of police and other investigations may also be reduced by the development of decision support tools that reduce the complexity of the information that needs to be understood, and assists in the derivation of appropriate inferences from the material that is available to the police. The decision support tools that are emerging for use by police investigators each draw on particular perspectives on the nature of the problem.
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queries, i.e. the records in SNDVs, are stored after being joined with a time label. For example, a demon can generate queries at speci c time intervals or at the occurrence of a speci c event, and insert the records of SNDVs resulting from these queries into the ESNDT. To distinguish the equal amplitudes sensed by the same node about a speci c task during different periods, the task, location and time elds make up the key elds in an ESNDT. In DADMA, a statement that has the structure given in Figure 4.15 starts a query. This structure is largely a part of the SQL standard [10] except for the last eld starting with based on which will be explained later in this section. Using an SQL style statements for a generic query interface has some advantages as described in [70]. Programmers and system administrators can use this practical and standard interface for all kinds of WSN applications. Hardware design for WSNs can also be optimized to run this language. In the select keyword of the SQL statement, common aggregation functions such as avg, min, max can be used to indicate how to aggregate the amplitude eld. The elds to be projected from an ESNDT are also listed after this keyword. The from keyword indicates the nodes to be involved in the query. Any means that even a single node may be enough to resolve the query, and any node in the sensor network can do it. When the every keyword is used, all of the nodes in the sensor network are supposed to be involved in the query. When a task or a set of tasks is given in the query, only the sensors in the speci ed types carry out the measurement. Aggregate
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time-independent, a steady limiting current is obtained. However, if the electrode reaction occurs at a stationary electrode that is kept at a constant potential, the thickness of the diffusion layer increases with time by the relation d *(pDt)1/2, where t is the time after the
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Murder is committed for a wide variety of reasons passion, hatred, money, flight, psychosis, pride, or simply to cover the commission of another crime by leaving no witnesses. Fraud is committed for only one reason greed. I am mindful here of Cressey s finding that some frauds are committed to try to save a dying business, perhaps implying some sort of altruistic behavior, but I do not believe these are so common that they befoul the causal definition. If greed is the common motivator behind most frauds, we have a much cleaner analytical landscape on which to think about research directed toward deterrent strategies. Murders are committed in a wide variety of locations, from cornfields to highrise apartment buildings. Frauds are committed in the workplaces we call home. We have much tighter control over what is by definition a much more limited arena of activity. Murderers flee. Only the insane or the emotionally immobile remain at the scene of the crime. Those committing occupational fraud return to the scene of their crime time and time again, often for many years. Fraud tends to be accumulative. When one commits a murder, there is usually no driving imperative to commit two the next time and four the next. Fraud, on the other hand, usually tends to get bigger with time. Murderers are usually anonymous. We have the whole world to look at for suspects. Occupational fraud perpetrators are within the confines of our organizations: they wear the same employee badges we do and eat in the same cafeterias. They also have the same human resources files, full of potentially useful information about who they are, where they came from, how well educated they are, how many kids they have, and where they live. While there are occasionally witnesses to a murder, the victim can provide no information as to who committed the crime or why. While the exceptionally rare fraud may result in murder, we almost always have a victim available, usually with detailed knowledge about the perpetrator(s), the technique(s) utilized, and, perhaps, the motive(s). Since the penalties are less for fraud, the possibilities for cooperation are increased. Plea bargains in murder cases are the stuff of noisy headlines and stern editorials, but they still occur. The implicated fraud perpetrator is not facing death by lethal injection and we, the investigator/victim organization, may decide that in exchange for valuable information about the incident(s) we are willing to bargain. We probably think we know more about the efficacy of deterrence than we do. Perhaps giving the white-collar criminal 30 years instead of 30 months will have a deterrent effect on others, but I would hazard that this proposition is built more on intuition and emotional investment than it is on empirical research. We
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FIGURE 11.7 Input and output of the testing procedure.
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