Review of Nineteenth-Century Geographies: The Transformation of Space from the Victorian Age to the American Century, eds. H. Michie and R. Thomas

It is by now a banal observation that published collections of conference papers tend to add up to a whole that is considerably less than the sum of the parts. Nineteenth-Century Geographies, a book that grew out of an interdisciplinary conference held at Rice University in 1998 falls into this category. While assuring my readers that each individual contribution is independently worth a read is likewise a predictable cliché, it is in fact the case that every one of the 17 articles collected here—notwithstanding the rather convoluted Introduction—has much to offer the study, broadly speaking, of ‘cultural spaces’ of British and American imperialisms in the nineteenth century. . . . All of my complaints aside, this turns out to be a much more enjoyable book to read than to review, and I would recommend skimming and dipping at length. I cannot quite imagine when a read-through of this book might be called for, except perhaps in graduate seminars on related topics.

Magnetic Flip Flops for Space Applications

The radiation environment of space presents a significant threat to the reliability of nonvolatile memory technologies. Ionizing radiation disturbs the charge stored on floating gates, and cosmic rays can permanently damage thin oxides. A new memory technology based on the magnetic tunneling junction (MTJ) appears to offer superior resistance to radiation effects and virtually unlimited write endurance. A magnetic flip flop has a number of potential applications, such as the configuration memory in field-programmable logic devices. However, using MTJs in a flip flop requires radically different circuitry for storing and retrieving data. New techniques are needed to insure that magnetic flip flops are reliable in the radiation environment of space. We propose a new radiation-tolerant magnetic flip flop that uses the inherent resistance of the MTJ to increase its immunity to single event upset and employs a robust “Pac-man” magnetic element.

Digital signal processing and digital system design using discrete cosine transform [student course]

The discrete cosine transform (DCT) is an important functional block for image processing applications. The implementation of a DCT has been viewed as a specialized research task. We apply a micro-architecture based methodology to the hardware implementation of an efficient DCT algorithm in a digital design course. Several circuit optimization and design space exploration techniques at the register-transfer and logic levels are introduced in class for generating the final design. The students not only learn how the algorithm can be implemented, but also receive insights about how other signal processing algorithms can be translated into a hardware implementation. Since signal processing has very broad applications, the study and implementation of an extensively used signal processing algorithm in a digital design course significantly enhances the learning experience in both digital signal processing and digital design areas for the students.

'Security Here is Not Safe': Violence, Punishment, & Space in the Contemporary U.S. Penitentiary

The US penitentiary at Lewisburg, Pennsylvania, was retrofitted in 2008 to offer the country’s first federal Special Management Unit (SMU) program of its kind. This model SMU is designed for federal inmates from around the country identified as the most intractably troublesome, and features double-celling of inmates in tiny spaces, in 23-hour or 24-hour a day lockdown, requiring them to pass through a two-year program of readjustment. These spatial tactics, and the philosophy of punishment underlying them, contrast with the modern reform ideals upon which the prison was designed and built in 1932. The SMU represents the latest punitive phase in American penology, one that neither simply eliminates men as in the premodern spectacle, nor creates the docile, rehabilitated bodies of the modern panopticon; rather, it is a late-modern structure that produces only fear, terror, violence, and death. This SMU represents the latest of the late-modern prisons, similar to other supermax facilities in the US but offering its own unique system of punishment as well. While the prison exists within the system of American law and jurisprudence, it also manifests features of Agamben’s lawless, camp-like space that emerges during a state of exception, exempt from outside scrutiny with inmate treatment typically beyond the scope of the law.

"Security Here is Not Safe": Violence, Punishment, and Space in the Contemporary US Penitentiary

The US penitentiary at Lewisburg, Pennsylvania, was retrofitted in 2008 to offer the country's first federal Special Management Unit (SMU) program of its kind. This model SMU is designed for federal inmates from around the country identified as the most intractably troublesome, and features double-celling of inmates in tiny spaces, in 23-hour or 24-hour a day lockdown, requiring them to pass through a two-year program of readjustment. These spatial tactics, and the philosophy of punishment underlying them, contrast with the modern reform ideals upon which the prison was designed and built in 1932. The SMU represents the latest punitive phase in American penology, one that neither simply eliminates men as in the premodern spectacle, nor creates the docile, rehabilitated bodies of the modern panopticon; rather, it is a late-modern structure that produces only fear, terror, violence, and death. This SMU represents the latest of the late-modern prisons, similar to other supermax facilities in the US but offering its own unique system of punishment as well. While the prison exists within the system of American law and jurisprudence, it also manifests features of Agamben's lawless, camp-like space that emerges during a state of exception, exempt from outside scrutiny with inmate treatment typically beyond the scope of the law

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.