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This kit contains materials necessary to administer the Cognitive Assessment System (CAS), an assessment battery designed to evaluate cognitive processing in children 5 through 17 years of age. Derived from the Planning, Attention, Simultaneous, and Successive (PASS) theory, the four processing areas comprise the four scales that make up the CAS. The kit includes: (1) the administration and scoring manual that provides general information, specific instruction for administering and scoring the subtests, norms tables, interpretive tables, and achievement comparison tables; (2) an interpretive handbook that presents the information needed to use the tests, including a discussion of the PASS theory, explanations of the test's organization and development, as well as information on standardization and norming, reliability and validity, and interpretation; (3) a stimulus book that includes all the subtest stimuli used during administration of the tests, including nonverbal matrices, verbal-spatial relations, figure memory, and expressive attention subtests; (4) response books for paper-and-pencil responses during testing of matching numbers, planned codes, planned connections, number detection, receptive attention, and figure memory; and (5) scoring templates in a spiral bound booklet for scoring response book pages. (CR)

Due to its high versatility and scalability, manual grinding is an important and widely used technology in production for rework, repair, deburring, and finishing of large or unique parts. To make the process more interactive and reliable, manual grinding needs to incorporate "skill-based design," which models a person-based system and can go significantly beyond the considerations of traditional human factors and ergonomics to encompass both processing parameters (e.g., feed rate, tool path, applied forces, material removal rate (MRR)), and machined surface quality (e.g., surface roughness). This study quantitatively analyzes the characteristics of complex techniques involved in manual operations. A series of experiments have been conducted using subjects of different levels of skill, while analyzing their visual gaze, cutting force, tool path, and workpiece quality. Analysis of variance (ANOVA) and multivariate regression analysis were performed and showed that the unique behavior of the operator affects the process performance measures of specific energy consumption and MRR. In the future, these findings can be used to predict product quality and instruct new practitioners.

The evaluation of multi-scale surface roughness parameters (SRPs) is important to solve many engineering problems (e.g. contact stress, sealing, friction) and is closely related to further fundamental problems (e.g. microbial contamination). Traditionally, surface roughness has been used as a standard for indicating process performance, such as tool wear, tool vibration etc. This paper also aims to find appropriate surface roughness parameters (SRPs) that can be used as process monitoring indices. Grade 304 stainless steel surfaces, generated by extrusion and grinding processes, were used in this study. The evaluation of different SRPs and their topography properties (such as fractal dimension) is discussed for extruded and ground surfaces. One problem with existing surface metrology is the availability of a multitude of disconnected roughness parameters. A statistical approach is presented in this paper that allows the most appropriate roughness parameters to monitor whether the intended surface quality converges to be found.