Narrative Therapy

Narrative therapy (NT) is a strengths-based approach to psychotherapy that uses collaboration between the client or family and the therapist to help clients see themselves as empowered and capable of living the way they want. In the face of crisis or trauma, NT helps clients achieve a “This too will pass” attitude, while positioning the therapist as an appreciative ally in the process. NT is useful with individuals and is used extensively with families due to its ability to separate clients from problems and unite families against problematic patterns. NT also lends itself well to joining with families because it stresses strengths and achievements over problems

Cognitive-Behavioral Therapy

Cognitive-behavioral therapy (CBT) is the merging of behavioral and cognitive therapies that mostly focuses on working with the client in the present. Although there are many approaches to CBT, there tend to be some common features. For example, CBT is generally a directive approach to psychotherapy that helps clients to challenge their problematic thoughts and to change the behaviors associated with those thoughts. In addition, most approaches to CBT are structured and time limited and include some type of homework where the client can practice the cognitive and behavioral strategies learned in the therapeutic setting. This entry focuses mostly on CBT as defined by Aaron Beck, one of the early founders of this approach

PLANNING FOR THE END OF THE CONSTRUCTION BOOM AND TRANSITION TO A NORMAL ECONOMY IN ACEH AND NIAS

There is a very real danger that the transition from the Construction Boom in 2009 to a rapidly growing sustainable normal economy in Aceh will not happen unless both preventive and effective constructive measures are implemented during the coming two years. Instead what could easily happen is a collapse into a deep recession caused by the economy of Aceh being uncompetitive relative to the rest of Indonesia because of its high costs and because in anticipation of this high cost economy situation insufficient investments were made by the private sector in 2006 and the coming two years.

How do banks make money? a variety of business strategies

In the second of two articles, the authors show that the business strategy chosen by a commercial banking company can have a substantial impact on its risk-return profile. Their analysis suggests that a wide variety of business strategies are likely to be financially viable in the future but, echoing concerns of others, they conclude that very small banking companies will face financial challenges regardless of the business strategy they selectBanks and banking ; Bank investments ; Money

How do banks make money? the fallacies of fee income

In the first of two articles in this issue, the authors document the increasing importance of noninterest income at U.S. commercial banking companies and address two fundamental misunderstandings regarding this trend: the belief that fee-based activities provide more stable earnings than interest-based income and the belief that fee income flows chiefly from nontraditional, nonbanking activities.Income ; Money ; Payment systems

Advanced techniques and technology for efficient data storage, access, and transfer

Advanced techniques for efficiently representing most forms of data are being implemented in practical hardware and software form through the joint efforts of three NASA centers. These techniques adapt to local statistical variations to continually provide near optimum code efficiency when representing data without error. Demonstrated in several earlier space applications, these techniques are the basis of initial NASA data compression standards specifications. Since the techniques clearly apply to most NASA science data, NASA invested in the development of both hardware and software implementations for general use. This investment includes high-speed single-chip very large scale integration (VLSI) coding and decoding modules as well as machine-transferrable software routines. The hardware chips were tested in the laboratory at data rates as high as 700 Mbits/s. A coding module's definition includes a predictive preprocessing stage and a powerful adaptive coding stage. The function of the preprocessor is to optimally process incoming data into a standard form data source that the second stage can handle.The built-in preprocessor of the VLSI coder chips is ideal for high-speed sampled data applications such as imaging and high-quality audio, but additionally, the second stage adaptive coder can be used separately with any source that can be externally preprocessed into the 'standard form'. This generic functionality assures that the applicability of these techniques and their recent high-speed implementations should be equally broad outside of NASA

Noiseless coding for the magnetometer

Future unmanned space missions will continue to seek a full understanding of magnetic fields throughout the solar system. Severely constrained data rates during certain portions of these missions could limit the possible science return. This publication investigates the application of universal noiseless coding techniques to more efficiently represent magnetometer data without any loss in data integrity. Performance results indicated that compression factors of 2:1 to 6:1 can be expected. Feasibility for general deep space application was demonstrated by implementing a microprocessor breadboard coder/decoder using the Intel 8086 processor. The Comet Rendezvous Asteroid Flyby mission will incorporate these techniques in a buffer feedback, rate-controlled configuration. The characteristics of this system are discussed

Algorithms for a very high speed universal noiseless coding module

The algorithmic definitions and performance characterizations are presented for a high performance adaptive coding module. Operation of at least one of these (single chip) implementations is expected to exceed 500 Mbits/s under laboratory conditions. Operation of a companion decoding module should operate at up to half the coder's rate. The module incorporates a powerful noiseless coder for Standard Form Data Sources (i.e., sources whose symbols can be represented by uncorrelated non-negative integers where the smaller integers are more likely than the larger ones). Performance close to data entropies can be expected over a Dynamic Range of from 1.5 to 12 to 14 bits/sample (depending on the implementation)