Macsyma: A personal history

The Macsyma system arose out of research on mathematical software in the AI group at MIT in the 1960s. Algorithm development in symbolic integration and simplification arose out of the interest of people, such as the author, who were also mathematics students. The later development of algorithms for the GCD of sparse polynomials, for example, arose out of the needs of our user community. During various times in the 1970s the computer on which Macsyma ran was one of the most popular nodes on the ARPANET. We discuss the attempts in the late 70s and the 80s to develop Macsyma systems that ran on popular computer architectures. Finally, we discuss the impact of the fundamental ideas in Macsyma on the author’s current research on large scale engineering and socio-technical systems.     

Nondestructive NMR determination of oil composition in transformed canola seeds

Magic-angle spinning (MAS) ¹³C nuclear magnetic resonance (NMR) spectroscopy is a convenient method for nondestructive, quantitative characterization of seed oil composition. We describe results for intact hybrid and transformed canola seeds. The MAS ¹³C NMR technique complements and agrees with gas chromatography results. The spectral resolution approaches that of neat, liquid oils. MAS ¹³C NMR data allow quantitative analysis of major oil components, including saturates and oleic, linoleic, and linolenic acyl chains. ¹³C NMR directly and quantitatively elucidates, triglyceride regiochemistry and acyl chain cis-trans isomers that cannot be quickly detected by other methods. MAS ¹³C NMR can serve as the primary method for development of near-infrared seed oil calibrations. These NMR methods are nondestructive and attractive for plant-breeding programs or other studies (e.g., functional genomics) where loss of seed viability is inconvenient.     

Characteristics of Metal Droplets in Slag Tapped from the Blast Furnace

Slag samples, hot‐metal samples and hot‐metal temperatures were obtained during tapping of two blast furnaces. Sampling was carried out at different time points during tapping of three separate heats. The size distribution and composition of metal droplets found in the slag were determined using scanning electron microscopy. Only metal droplets above 0.75 μm could be counted and analysed. All droplets were below 8 μm in diameter and the great majority of these droplets were found to be between 0.75 and 2 μm. The size distribution did not differ significantly for different slag samples. Iron was the main droplet component. Electron probe microanalysis showed that the droplets contained small amounts of carbon. The percentage of the area in a studied cross‐section that was covered with metal droplets varied between 0.01 and 0.07%. Calculations based on Stoke's law showed that the distance droplets travel in the slag is in the micron range. Slag samples taken in the beginning of slag tapping contained more droplets than those taken in the middle of slag tapping, an indication that most droplets can be found in the area near the furnace wall. Some droplets were determined to have magnesium enrichment at the external surface.     

Optimal decoder for block-transform based video coders

In this paper, we introduce a new decoding algorithm for DCT-based video encoders, such as Motion JPEG (M-JPEG), H26x, or MPEG. This algorithm considers not only the compression artifacts but also the ones due to transmission, acquisition or storage of the video. The novelty of our approach is to jointly tackle these two problems, using a variational approach. The resulting decoder is object-based, allowing independent and adaptive processing of objects and backgrounds, and considers available information provided by the bitstream, such as quantization steps, and motion vectors. Several experiments demonstrate the efficiency of the proposed method. Objective and subjective quality assessment methods are used to evaluate the improvement upon standard algorithms, such as the deblocking and deringing filters included in MPEG-4 postprocessing.     

Distributed Job Scheduling in Rings

We give a distributed approximation algorithm for job scheduling in a ring architecture. In contrast to many other parallel scheduling models, the model we consider captures the influence of the underlying communications network by specifying that task migration from one processor to another takes time proportional to the distance between those two processors in the network. As a result, our algorithm must balance computational load and communication time. The algorithm is simple, requires no global control, and yields schedules of length at most 4.22 times optimal. We also give a lower bound on the performance of any distributed algorithm and the results of simulation experiments which suggest better performance than does our worst-case analysis.     

Evaluating the Endophenotype Model of ADHD Neuropsychological Deficit: Results for Parents and Siblings of Children With ADHD Combined and Inattentive Subtypes.

Neurogenetic models predict neuropsychological weaknesses in the relatives of children with attention-deficit/ hyperactivity disorder (ADHD). The authors examined executive and regulatory measures in 386 relatives (307 parents, 79 siblings) of children with ADHD combined type, ADHD inattentive type, and controls. Predicted deficits were seen on trailmaking (relatives of ADHD combined type only), stop-signal reaction times (relatives of girls only), and response variability (mothers only) but not on naming or output speed. Effects generally held, even with relatives' ADHD status controlled. A neuropsychologically impaired subgroup of children with ADHD had relatives with clear neuropsychological weaknesses. The authors conclude that a neurogenetic model of ADHD etiology is supportable only for a subset of executive functions and that neuropsychological heterogeneity warrants more examination in ADHD. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Role of Melodic and Temporal Cues in Perceiving Musical Meter.

A number of different cues allow listeners to perceive musical meter. Three experiments examined effects of melodic and temporal accents on perceived meter in excerpts from folk songs scored in 6/8 or 3/4 meter. Participants matched excerpts with 1 of 2 metrical drum accompaniments. Melodic accents included contour change, melodic leaps, registral extreme, melodic repetition, and harmonic rhythm. Two experiments with isochronous melodies showed that contour change and melodic repetition predicted judgments. For longer melodies in the 2nd experiment, variables predicted judgments best at the beginning of excerpts. The final experiment, with rhythmically varied melodies, showed that temporal accents, tempo, and contour change were the strongest predictors of meter. The authors' findings suggest that listeners combine multiple melodic and temporal features to perceive musical meter. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Speech Recognition and In-Vehicle Telematics Devices: Potential Reductions in Driver Distraction

Speech Recognition is frequently cited as a potential remedy to distraction resulting from drivers' operation of in-vehicle devices. This position typically assumes that the introduction of speech recognition will result in reduced cognitive workload and improved driving performance. Past research neither fully supports nor fully discounts this assumption. However, it is difficult to compare many of these studies, due to differences in device operation tasks, the pacing of those tasks, speech recognition system performance, and system interface designs. In an effort to directly address the effect of voice recognition on driver distraction, the present authors developed a capability to manipulate the performance characteristics of a speech recognition system through a Wizard of Oz speech recognition system and installed this system in a simulated driving environment. The sensitivity of the simulated driving environment and speech recognition accuracy manipulation were evaluated in an initial study comparing driver cognitive workload and driving performance during self-paced simulated operation of a personal digital assistant (PDA) during no PDA use, manual control of the PDA, and speech control of the PDA. In the Speech PDA condition, speech recognition accuracy was varied between drivers. Analysis of drivers' emergency braking response times and rated cognitive workload revealed significantly lower cognitive demand and better performance in the No PDA condition when compared to the Manual PDA condition. The Speech PDA condition resulted in response times and rated cognitive workload levels that were between the No PDA and Manual PDA conditions, but not significantly different from either of these conditions. Further analysis of emergency braking performance revealed a non-significant trend towards better performance in conjunction with higher speech recognition accuracy levels. The potential for reducing driver distraction through the careful development and evaluation of speech recognition systems is discussed.     

Data Work: How Energy Advisors and Clients Make IoT Data Accountable

We present fieldwork findings from the deployment of an interactive sensing system that supports the work of energy advisors who give face-to-face advice to low-income households in the UK. We focus on how the system and the data it produced are articulated in the interactions between professional energy advisors and their clients, and how they collaboratively anticipate, rehearse, and perform data work. In addition to documenting how the system was appropriated in advisory work, we elaborate the ‘overhead cost’ of building collaborative action into connected devices and sensing systems, and the commensurate need to support discrete workflows and accountability systems to enable the methodical incorporation of the IoT into collaborative action. We contribute an elaboration of the social, collaborative methods of data work relevant to those who seek to design and study collaborative IoT systems.     

Relative contributions of nearshore and wetland habitats to coastal food webs in the Great Lakes

Hydrologic linkages among coastal wetland and nearshore areas allow coastal fish to move among the habitats, which has led to a variety of habitat use patterns. We determined nutritional support of coastal fishes from 12 wetland-nearshore habitat pairs using stable isotope analyses, which revealed differences among species and systems in multi-habitat use. Substantial (proportions?>?0.30) nutrition often came from the habitat other than that in which fish were captured. Nearshore subsidies to coastal wetlands indicate wetlands are not exclusively exporters of energy and materials; rather, there is reciprocity in the mutual energetic support of nearshore and wetland food webs. Coastal wetland hydrogeomorphology influenced the amount of multi-habitat use by coastal fishes. Fishes from systems with relatively open interfaces between wetland and nearshore habitats exhibited less nutritional reliance on the habitat in which they were captured, and higher use of resources from the adjacent habitat. Comparisons of stable isotope analyses of nutrition with otolith analyses of occupancy indicated nutritional sources often corresponded with habitat occupancy; however, disparities among place of capture, otolith analyses, and nutritional analyses indicated differences in the types of support those analyses inform. Disparities between occupancy information and nutritional information can stem from movements for support functions other than foraging. Together, occupancy information from otolith microchemistry and nutritional information from stable isotope analyses provide complementary measures of the use of multiple habitats by mobile consumers. This work underscores the importance of protecting or restoring a diversity of coastal habitats and the hydrologic linkages among them.