Sensor Selection to Support Practical Use of Health-Monitoring Smart Environments

The data mining and pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals experiencing difficulties living independently at home. In order to monitor the functional health of smart home residents, we need to design technologies that recognize and track activities that people normally perform as part of their daily routines. One question that frequently arises, however, is how many smart home sensors are needed and where should they be placed in order to accurately recognize activities? We employ data mining techniques to look at the problem of sensor selection for activity recognition in smart homes. We analyze the results based on six data sets collected in five distinct smart home environments.     

Assessing robustness of factor ranking for supersaturated designs

Supersaturated designs can potentially be a beneficial tool for efficiently exploring a large number of factors with a moderately sized design. However, because more factors are being considered than there are runs, the stability of the identified factors depends heavily on effect sparsity and the lack of highly influential observations. A helpful tool for the analysis of supersaturated designs is least absolute shrinkage and selection operation (LASSO), which is useful when the effects of many explanatory variables are sparse in a high‐dimensional dataset. To understand the impact of individual observations on the selected factors, the LASSO influence plot was created. This paper describes an application of this plot and its variants that can be used to identify influential points, increase understanding of the impact of individual observations on model parameters, and the robustness of results in analyses with supersaturated designs. These graphical methods can serve as a complement to other regression diagnostics techniques in the LASSO regression setting.     

Diamond,Jagersfontein Mine,Free State Province,South Africa

The following short article is important for several reasons. It illustrates the fact that despite the extremely exacting nature of crystallography, it is still difficult for even the most experienced mineralogists to instantly and on-sight identify all forms and twin laws for even the most common species, no matter how large and perfect the crystals. For the observant collector, interesting and occasionally unidentified or questionably identified specimens still abound, many times at prices all of us can afford. Therein lies the challenge and, to a large degree, the charm of mineral collecting.     

Crosslinking of mixtures of diglycidylether of bisphenol‐A with 1,6‐dioxaspiro[4.4] nonan‐2,7‐dione initiated by tertiary amines: III. Effect of hydroxyl groups on network formation

BACKGROUND: Blends of epoxy resin oligomers, diglycidylether of bisphenol‐A (DGEBA), and a bislactone, 1,6‐dioxaspiro[4.4]nonan‐2,7‐dione (s(γBL)), were anionically copolymerized using two tertiary amines as anionic initiators. Their curing rheology and gelation behaviour were studied to provide a more comprehensive knowledge of the curing of these previously studied systems. RESULTS: The activation energy for gelation was found to be similar to that previously measured using differential scanning calorimetry and appeared to increase in the presence of the bislactone. The reaction rate during copolymerization of DGEBA with s(γBL) was slower than DGEBA homopolymerization alone because the alkoxide attack on the epoxide is faster than the reaction of the carboxylate ion and the epoxy group. The effect of the initiator type on the gel conversion was small and was presumably due to differences in the kinetic chain length caused by amine regeneration from the quaternary amine. For the same initiator and at a constant ratio of DGEBA/s(γBL), an increase in the hydroxyl concentration of the DGEBA oligomer raised the gel conversion. For a DGEBA oligomer with low hydroxyl levels, an increase in the concentration of s(γBL) increased the gel conversion; however, for a DGEBA oligomer with high hydroxyl levels, increasing s(γBL) concentration decreased the gel conversion. CONCLUSION: These results are interpreted in terms of the effect of initiation rate and chain transfer rate on the kinetic chain length. The glass transition temperature of the gel was found to be controlled by the fraction of the aliphatic s(γBL) and the amount of plasticizing sol in the matrix. Copyright © 2009 Society of Chemical Industry     

Applying sensors to automatic assembly systems

The author describes the classes of sensors that are available to the automatic assembly machine designer. Examples of each class of sensor along with a discussion of their specific benefits and problems are included. Guidelines that will aid a machine designer in the selection and application of sensors for automatic assembly systems are provided. The necessity of providing methods in the automation for verifying the sensors' accuracy is discussed     

Evaluating the crash and citation rates of Utah drivers licensed with medical conditions, 1992-1996

BACKGROUND: Medical problems may affect the ability to drive motor vehicles, and programs that control the issuing of driver licenses to individuals with medical conditions exist in most states. The main activity of these programs is the imposition of restrictions upon the driving privileges of individuals with medical conditions that are deemed to pose some risk to public safety. However, little is known about the effectiveness of these licensing programs. OBJECTIVE: The objective of this study was to compare the rates of adverse driving events (crash, at-fault crash and citations) experienced by drivers licensed with medical conditions to those of age-, sex- and location-matched controls. Separate comparisons were made for drivers reporting medical conditions licensed with full driving privileges, and those with restricted driving privileges (e.g. speed, area and time of day). DESIGN: Retrospective case-control. METHODS: The study population was all drivers licensed in the state of Utah who reported a medical condition on their driver license application, over the 5-year period 1992-1996. Drivers enter the program by self-reporting their medical problems. Control drivers were chosen from the entire population of drivers licensed in Utah for the same period. Information on driver license status, participation in the medical conditions program, citations, involvement in crashes, and death certificate data was obtained from the relevant state agencies. Probabilistic linkage methodology was used to link the records in these disparate databases for eventual analysis. Rates of citation, crashes and at-fault crashes, expressed as events per 10000 license days, were calculated separately for program drivers and their corresponding control groups for each medical condition category and restriction status. These data were used to determine an estimate of relative risk (RR) and 95% confidence intervals. Results: As a group, medical conditions drivers had modestly elevated rates of adverse driving events compared with control drivers (RR 1.09-1.74). Rates in the largest medical category, 'cardiovascular conditions', were not higher than controls. Rates were higher than control for some conditions, such as 'alcohol' and 'learning and memory', for some adverse events (RR 2.2 -5.75). Drivers with more than one medical condition appeared comparable to the general group of medical conditions program drivers. CONCLUSIONS: Drivers in Utah medical conditions program had modestly elevated rates of adverse driving events compared to matched controls. Possible underreporting of medical conditions and accurate assessment of exposure rates are potential weaknesses in the program.     

Segmented flow injection,UV digestion,and amperometric detection for the determination of total cyanide in wastewater treatment plant effluents

The currently approved method for the analysis of total cyanide (TCN) in wastewaters has remained virtually unchanged in the 25 years since its initial use; this despite its subjection to a number of interferences, many of which provide a positive bias in cyanide measurements, including the formation of TCN during sample processing and some of which remain undocumented to this day. In particular, many municipal wastewater treatment plant chlorinated effluents throughout North America have often been cited for permit violations on the levels of total cyanide in their effluents measured using this methodology. A recently developed procedure for the analysis of TCN in various matrixes that utilizes segmented flow injection for sample transport and reaction, on-line acidic UV digestion for conversion of complexed cyanide to HCN, and amperometric detection achieved within 4 min of sample injection is demonstrated on chlorinated effluents discharged from municipal wastewater treatment plants. Through a systematic evaluation of the chemistry of the processes involved in this method and an understanding of the complexity of the wastewater matrix, an application was developed that showed consistent reproducibility in measuring TCN in a variety of effluents. The method was employed initially on synthetic solutions containing controlled levels of constituents identified in the literature as interfering with the measurement of TCN through the traditional distillation/colorimetric approach. In its application to the analysis of TCN in chlorinated wastewaters, an approach was evolved that ensured that dechlorination carried out during sample processing did not bias the results of analysis.     

Automotive Powertrain Control — A Survey

This paper surveys recent and historical publications on automotive powertrain control. Control‐oriented models of gasoline and diesel engines and their aftertreatment systems are reviewed, and challenging control problems for conventional engines, hybrid vehicles and fuel cell powertrains are discussed. Fundamentals are revisited and advancements are highlighted. A comprehensive list of references is provided.     

Movie Making at Pixar: A Collaboration of Art and Technology

This talk takes you behind the scenes at Pixar Animation Studios for an in‐depth look at how its 3d computer graphics films are made. Making a computer animated film involves people with artistic talent and people with technical skills working together in close collaboration. The process starts with the development of the story and continues with modeling the geometry, adding articulation controls, using those controls to animate the characters, simulating things like water and cloth and hair, defining the look of the surfaces, putting lights in the scene, adding special effects, rendering, and post‐production. Special emphasis is given to the roles of technology and computer graphics research in supporting the filmmaker.