The previous two chapters showed how the concept of last-in-first-out data processing is surprisingly powerful. We’ll now consider the stack’s counterpart, the queue. Like a waiting line, a queue stores a set of items and returns them in first-in-first-out (FIFO) order. Pushing to the queue adds a new item to the back of the line and pulling retrieves the oldest item from the front. Queues have a lower profile than stacks, and are rarely the centerpiece of an algorithm. Instead, queues tend to serve as utility data structures in a larger system.

A hash, in culinary terms, is a dish made of mixed foods – often including corned beef and onions – chopped into tiny pieces. In the early twentieth century, it became a shorthand for something of dubious origin, probably unwise to consume. In computer science, a hash function is an operation that rearranges, mixes, and combines data to produce a single fixed-size output. Unlike their culinary namesake, hash functions are wonderfully useful. A hash value is like a “fingerprint” of the input used to calculate it. Hash functions have applications to security, distributed systems, and – as we’ll explore – data structures.

In some situations, it is convenient to apply modifications to the conventional digital PAM scheme, in order to achieve desired properties of the transmit signal and/or in order to modify the demodulation process. First, we have a look at the crest factor or peak-to-average power ratio of the transmit signal, which should be as low as possible. In this context, offset QAM, minimum-shift keying, and Gaussian minimum-shift keying are studied. Moreover, the replacement of the coherent I/Q demodulator by different principles is addressed. First, “carrierless” amplitude and phase modulation is treated as an alternative approach to PAM. Here, no explicit mixing of the pulse-shaped continuous-time baseband signal to the RF domain is required. Second, in some cases (e.g., fiber-optical transmission), coherent reception is possible in principle but very costly. Here it is desired that even when demodulating without phase information (i.e., by conducting energy detection), a performance close to a coherent receiver is enabled. We study in detail an advanced scheme, called the Kramers–Kronig coherent receiver, which meets this aim by performing more complex operations at the digital part.

[I] Q. Mucius augur multa narrare de C. Laelio socero suo memoriter et iucunde solebat, nec dubitare illum in omni sermone appellare sapientem. ego autem a patre ita eram deductus ad Scaeuolam sumpta uirili toga ut quoad possem et liceret a senis latere numquam discederem. itaque multa ab eo prudenter disputata, multa etiam breuiter et commode dicta memoriae mandabam fierique studebam eius prudentia doctior.

Whatever their private religious convictions, nearly all contemporary psychologists of religion – when they act in professional roles – agree to operate in accordance with scientific rules. Recognition of the imperfections of individual methodologies has led to an emphasis on testing theories and verifying “facts” in multiple studies. Most of this chapter explores the pros and cons associated with various research methods, including experimentation, observation, and survey research. Although the logic of experimentation is undeniable and psychologists in various subfields frequently deem it the method of choice, many questions that we most want to answer in the psychology of religion cannot be addressed through experiments that are feasible, ethical, and convincing. Thus, the psychology of religion has always relied heavily on quantitative and qualitative survey research studies. Good surveys must strive to avoid biases rooted in question wording, question order, mode of data collection, social desirability, attitude-behavior discrepancies, and the tendency to overreport religious behavior. Fortunately, many existing measures of religious attitudes and behaviors have good psychometric qualities.