Estimating and reducing the memory requirements of signal processing codes for embedded systems

Most embedded systems have limited amount of memory. In contrast, the memory requirements of the digital signal processing (DSP) and video processing codes (in nested loops, in particular) running on embedded systems is significant. This paper addresses the problem of estimating and reducing the amount of memory needed for transfers of data in embedded systems. First, the problem of estimating the region associated with a statement or the set of elements referenced by a statement during the execution of nested loops is analyzed. For a fixed execution ordering, a quantitative analysis of the number of elements referenced is presented; exact expressions for uniformly generated references and a close upper and lower bound for nonuniformly generated references are derived. Second, in addition to presenting an algorithm that computes the total memory required, this paper also discusses the effect of transformations (that change the execution ordering) on the lifetimes of array variables, i.e., the time between the first and last accesses to a given array location. The term maximum window size is introduced, and quantitative expressions are derived to compute the maximum window size. A detailed analysis of the effect of unimodular transformations on data locality, including the calculation of the maximum window size, is presented.     

Reliability models for computer systems: An overview including dataflow graphs

The reliability of a system is the probability that the system will perform its intended mission under given conditions. This paper provides an overview of the approaches to reliability modelling and identifies their strengths and weaknesses. The models discussed include structure models, simple stochastic models and decomposable stochastic models. Ignoring time-dependence, structure models give reliability as a function of the topological structure of the system. Simple stochastic models make direct use of the properties of underlying stochastic processes, while decomposable models consider more complex systems and analyse them through subsystems. Petri nets and dataflow graphs facilitate the analysis of complex systems by providing a convenient framework for reliability analysis.     

Protecting against key-exposure: strongly key-insulated encryption with optimal threshold

Key-insulated encryption schemes use a combination of key splitting and key evolution to protect against key exposure. Existing schemes, however scale poorly, having cost proportional to the number t of time periods that may be compromised by the adversary, and thus are practical only for small values of t. Yet in practice t might be large. This paper presents a strongly key-insulated encryption scheme with optimal threshold. In our scheme, t need not be known in advance and can be as large as one less than the total number of periods, yet the cost of the scheme is not impacted. This brings key-insulated encryption closer to practice. Our scheme is based on the Boneh-Franklin identity-based encryption (IBE) scheme [9], and exploits algebraic properties of the latter. Another contribution of this paper is to show that (not strongly) key-insulated encryption with optimal threshold and allowing random-access key updates (which our scheme and all others known allow) is equivalent to a restricted form of IBE. This means that the connection between key-insulated encryption and IBE is not accidental. Supported in part by NSF grants CCR-0098123, ANR-0129617 and CCR-0208842, and by an IBM Faculty Partnership Development Award. Supported in part by an NSF graduate fellowship.     

Adenosine A1 receptor stimulation antagonizes the negative inotropic effects of the PKC activator dioctanoylglycerol

It has been suggested that adenosine cardioprotection occurs via adenosine A1 receptor-mediated activation of protein kinase C (PKC). However, adenosine has well-known vasodilatory effects in the myocardium, whereas PKC is a vasoconstrictor. This study examined whether adenosine A1 receptor activation alters the effects of the PKC activator. 1,2-dioctanoyl-s,n-glycerol (DOG) in isolated perfused rat hearts (left-ventricular developed pressure) and rat ventricular myocytes ([Ca2+]i and cell shortening). Exposure to DOG decreased left-ventricular developed pressure by 30%, an effect that was completely reversible. Pretreatment of isolated hearts with either the PKC inhibitor chelerythrine or the adenosine A1 agonist 2-chloro-N6-cyclo-cyclo-isolated pentlyadenosine (CCPA) attenuated the negative inotropic effects of DOG. In the isolated myocytes, DOG decreased [Ca2+]i and cell shortening by 25 and 28%, respectively, effects that were attenuated by both chelerythrine and CCPA. The CCPA attenuation of the DOG-induced decrease in [Ca2+]i and cell shortening was blocked by pretreating the myocytes with the adenosine A1 antagonist, 8-cyclopentyl-1,3-dipropylxanthine (DPCPX). These results indicate that in rat ventricular myocardium, adenosine A1 receptor activation attenuates the apparent PKC-dependent negative inotropic effects of DOG via preservation of [Ca2+]i levels.     

The effects of stress on memory and the hippocampus throughout the life cycle: implications for childhood development and aging

Studies in animals showing hippocampal atrophy and associated memory deficits in stress and aging have implications for stress and aging in humans. Clinical studies in traumatized human populations with posttraumatic stress disorder (PTSD) have replicated studies in animals, showing reduction in volume of the hippocampus measured with magnetic resonance imaging and associated memory deficits. Trauma at different stages of development (early childhood abuse versus trauma in later life due to combat) may influence the nature of memory deficits and hippocampal atrophy. Studies in aging human subjects are consistent with animal studies, although future research is needed in this area. The similarities between biological findings related to cortisol and the hippocampus in stress and aging in both animal and human studies raises the question of whether PTSD can be seen as a form of accelerated aging. Evidence that stress affects the hippocampus and the capacity for learning has broad implications for public health policy, underlying the need for additional resources in this important area and a reexamination of our understanding of factors influencing academic achievement.     

Realization of a temperature sensor using both two- and three-dimensional photonic structures through a machine learning technique

A temperature sensor based on photonic crystal structures with two- and three-dimensional geometries is proposed, and its measurement performance is estimated using a machine learning technique. The temperature characteristics of the photonic crystal structures are studied by mathematical modeling. The physics of the structure is investigated based on the effective electrical permittivity of the substrate (silicon) and column (air) materials for a signal at 1200 nm, whereas the mathematical principle of its operation is studied using the plane-wave expansion method. Moreover, the intrinsic characteristics are investigated based on the absorption and reflection losses as frequently considered for such photonic structures. The output signal (transmitted energy) passing through the structures determines the magnitude of the corresponding temperature variation. Furthermore, the numerical interpretation indicates that the output signal varies nonlinearly with temperature for both the two- and three-dimensional photonic structures. The relation between the transmitted energy and the temperature is found through polynomial-regression-based machine learning techniques. Moreover, rigorous mathematical computations indicate that a second-order polynomial regression could be an appropriate candidate to establish this relation. Polynomial regression is implemented using the Numpy and Scikit-learn library on the Google Colab platform.

     

Membrane degumming of crude rice bran oil: Pilot plant study

The procedure for the classical chemical refining of vegetable oils consists of degumming, alkali neutralization, bleaching, and deodorization. Conventional refining of rice bran oil using alkali gives oil of acceptable quality, but the refining losses are very high. A critical work has been carried out to study the application of membrane technology in the pretreatment of crude rice bran oil. Oils intended for physical refining should have a low phosphorus content, and this is not readily achievable by the conventional acid/water degumming process. The application of membrane technology for the pretreatment of rice bran oil has been investigated. The process has already been successfully applied to other vegetable oils. Ceramic membranes, which are important from the commercial point of view, were examined for this purpose. The results showed that the membrane‐filtered oils met the requirements of physical refining, with a substantial reduction in color. It was observed that most of the waxy material was also rejected. Experiments were carried out to establish the relationship between permeate flux and rejection with membrane pore size, trans‐membrane pressure and micellar solute concentration.     

Alkylation of Benzene with Isopropyl Alcohol over SAPO-5 Catalyst in an Integral Pressure Reactor

The alkylation of benzene with isopropyl alcohol was studied in an integral pressure reactor over silicon substituted aluminophosphate molecular sieves, SAPO-5. The influence of various process parameters such as temperature, pressure, time on stream, weight hourly space velocity, and mole ratio of reactants on cumene yield and selectivity were investigated. The activity of SAPO-5 was compared with that of Hbeta for this reaction under similar conditions and in the same reactor. At pressures higher than atmospheric, almost the theoretical maximum yields of cumene were achieved on this SAPO-5. Among the diisopropyl benzenes formed by the alkylation of cumene, the meta-isomer was found to form in a significant amount followed by the para-isomer. The ortho-isomer with relatively high strain energy of 4.26 kcal/mol was almost negligible. The cumene yield goes through a maximum in the temperature range 498-543 K studied. Cumene selectivity was found to decrease at higher temperatures, higher pressures and lower benzene to isopropanol mole ratios.