Drug use, violence, and victimization among White American, Mexican American, and American Indian dropouts, students with academic problems, and students in good academic standing.

Problem-prone behaviors of White American, Mexican American, and American Indian high school dropouts, students in good academic standing, and students in poor academic standing were surveyed. Generally, dropouts were most involved with drugs, perpetration of violence, and victimization by violence, students in poor standing were the next most involved, and students in good standing were least involved. Ethnicity did not interact with academic status, suggesting that differences between dropouts and students were similar across ethnic groups. Some ethnicity and gender main effects were found. Findings were related to R. Jessor's (see record 1992-23064-001) theory of problem-prone behaviors, to peer cluster theory, and to intervention design. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Gender Differences in Mouse and Cursor Movements

Computer cursor and mouse activities such as moving, pointing, selecting, and dragging are essential parts of everyday interactions. Yet it is unknown how men and women differ in the way they move computer cursors. This study examines gender differences in movements of computer cursors. In one experiment, the authors measured trajectories of computer cursors every 20 ms in a simple choice-reaching task and tested the extent to which movement features related to controlling and targeting diverge between male and female participants. Results showed significant gender differences in cursor motions. Female participants deviated from the straight path toward the target location to a larger degree than did male participants, and female participants showed more backward motions (deviating backward from the target location) than did male participants. Implications for sources of these gender differences, user interface and input device design, and musculoskeletal disorders in women are also discussed.     

A tree-covering problem arising in integrity of tree-structured data

We introduce and solve a problem motivated by integrity verification in third-party data distribution: Given an undirected tree, find a minimum-cardinality set of simple paths that cover all the tree edges and, secondarily, have smallest total path lengths. We give a linear time algorithm for this problem.     

A model-based approximate λ-policy iteration approach to online evasive path planning and the video game Ms. Pac-Man

This paper presents a model-based approximate λ-policy iteration approach using temporal differences for optimizing paths online for a pursuit-evasion problem, where an agent must visit several target positions within a region of interest while simultaneously avoiding one or more actively pursuing adversaries. This method is relevant to applications, such as robotic path planning, mobile-sensor applications, and path exposure. The methodology described utilizes cell decomposition to construct a decision tree and implements a temporal difference-based approximate λ-policy iteration to combine online learning with prior knowledge through modeling to achieve the objectives of minimizing the risk of being caught by an adversary and maximizing a reward associated with visiting target locations. Online learning and frequent decision tree updates allow the algorithm to quickly adapt to unexpected movements by the adversaries or dynamic environments. The approach is illustrated through a modified version of the video game Ms. Pac-Man, which is shown to be a benchmark example of the pursuit-evasion problem. The results show that the approach presented in this paper outperforms several other methods as well as most human players.     

Free-living inferential modeling of blood glucose level using only noninvasive inputs

The goal of this work is to present a causation modeling methodology with the ability to accurately infer blood glucose levels using a large set of highly correlated noninvasive input variables over an extended period of time. These models can provide insight to improve glucose monitoring, and glucose regulation through advanced model-based control technologies. The efficacy of this approach is demonstrated using real data from a type 2 diabetic (T2D) subject collected under free-living conditions over a period of 25 consecutive days. The model was identified and tested using eleven variables that included three food variables as well as several activity and stress variables. The model was trained using 20 days of data and validated using 5 days of data. This gave a fitted correlation coefficient of 0.70 and an average absolute error (AAE) (i.e., the average of the absolute values for the measured glucose concentration minus modeled glucose concentration) of 13.3 mg/dL for the validation data. This AAE result was significantly better than the subject’s personal glucose meter AAE of 15.3 mg/dL for replicated measurements.     

Hume box calculus: robust system development through software transformation

Hume is a contemporary programming language oriented to systems with strong resource bounds, based on autonomous concurrent “boxes” interacting across “wires”. Hume’s design reflects the explicit separation of coordination and computation aspects of multi-process systems, which greatly eases establishing resource bounds for programs. However, coordination and computation are necessarily tightly coupled in reasoning about Hume programs. Furthermore, in Hume, local changes to coordination or computation, while preserving input/output correctness, can have profound and unforeseen effects on other aspects of programs such as timing of events and scheduling of processes. Thus, traditional program calculi prove inappropriate as they tend to focus exclusively either on the coordination of interacting processes or on computation within individual processes.     

Situation awareness acquired from monitoring process plants – the Process Overview concept and measure

We introduce Process Overview, a situation awareness characterisation of the knowledge derived from monitoring process plants. Process Overview is based on observational studies of process control work in the literature. The characterisation is applied to develop a query-based measure called the Process Overview Measure. The goal of the measure is to improve coupling between situation and awareness according to process plant properties and operator cognitive work. A companion article presents the empirical evaluation of the Process Overview Measure in a realistic process control setting. The Process Overview Measure demonstrated sensitivity and validity by revealing significant effects of experimental manipulations that corroborated with other empirical results. The measure also demonstrated adequate inter-rater reliability and practicality for measuring SA based on data collected by process experts.

Practitioner Summary: The Process Overview Measure is a query-based measure for assessing operator situation awareness from monitoring process plants in representative settings.     

Buyer-supplier games: Optimization over the core

In a buyer-supplier game, a special type of assignment game, a distinguished player, called the buyer, wishes to purchase some combinatorial structure. A set of players, called suppliers, offer various components of the structure for sale. Any combinatorial minimization problem can be transformed into a buyer-supplier game. While most previous work has been concerned with characterizing the core of buyer-supplier games, in this paper we study optimization over the set of core vectors. We give a polynomial time algorithm for optimizing over the core of any buyer-supplier game for which the underlying minimization problem is solvable in polynomial time. In addition, we show that it is hard to determine whether a given vector belongs to the core if the base minimization problem is not solvable in polynomial time. Finally, we introduce and study the concept of focus point price, which answers the question: If we are constrained to play in equilibrium, how much can we lose by playing the wrong equilibrium?