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Gaspers installed in commercial airliner cabins are used to improve passengers' thermal comfort. To understand the impact of gasper airflow on the air quality in a cabin, this investigation measured the distributions of air velocity, air temperature, and gaseous contaminant concentration in five rows of the economy-class section of an MD-82 commercial aircraft. The gaseous contaminant was simulated using SF6 as a tracer gas with the source located at the mouth of a seated manikin close to the aisle. Two-fifths of the gaspers next to the aisle were turned on in the cabin, and each of them supplied air at a flow rate of 0.66 l/s. The airflow rate in the economy-class cabin was controlled at 10 l/s per passenger. Data obtained in a previous study of the cabin with all gaspers turned off were used for comparison. The results show that the jets from the gaspers had a substantial impact on the air velocity and contaminant transport in the cabin. The air velocity in the cabin was higher, and the air temperature slightly more uniform, when the gaspers were on than when they were off, but turning on the gaspers may not have improved the air quality.

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Intel Software Guard eXtension (SGX), a hardware supported trusted execution environment (TEE), is designed to protect security critical applications. However, it does not terminate traditional memory corruption vulnerabilities for the software running inside enclave, since enclave software is still developed with type unsafe languages such as C/C++. This paper presents Rust-SGX, an efficient and layered approach to exterminating memory corruption for software running inside SGX enclaves. The key idea is to enable the development of enclave programs with an efficient memory safe system language Rust with a Rust-SGX SDK by solving the key challenges of how to (1) make the SGX software memory safe and (2) meanwhile run as efficiently as with the SDK provided by Intel. We therefore propose to build Rust-SGX atop Intel SGX SDK, and tame unsafe components with formally proven memory safety. We have implemented Rust-SGX and tested with a series of benchmark programs. Our evaluation results show that Rust-SGX imposes little extra overhead (less than 5% with respect to the SGX specific features and services compared to software developed by Intel SGX SDK), and meanwhile have stronger memory safety. CCS CONCEPTS• Security and privacy → Formal methods and theory of security; Systems security;

Abstract-Recent development of sophisticated smartphones has made them indispensable part of our everyday life. However, advances in battery technology cannot keep up with the demand for longer battery life. Subsequently, energy efficiency has become one of the most important factors in designing smartphones. Multitasking and better multimedia features in the mobile applications continuously push memory requirements further, making energy optimizations for memory critical. Mobile RAM is already optimized for energy efficiency at the hardware level. It also provides power state switching interfaces to the operating system which enables the OS level energy optimizations. Many RAM optimizations have been explored for computer systems and in this paper we explore their applicability to smartphone hardware. In addition, we apply those optimizations to the newly emerging Phase Change Memory and study their energy efficiency and performance. Finally, we propose a hybrid approach to take the advantage of both Mobile RAM and Phase Change Memory. Results show that our hybrid mechanism can save more than 98% of memory energy as compared to the standard smartphone system with negligible impact on user experience.

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This investigation evaluated the impact of three mesh types (hexahedral, tetrahedral, and hybrid cells) and five grid numbers (3, 6, 12, 24, and >38 million cells) on the accuracy and computing costs of air distribution simulations in a first-class cabin. This study performed numerical error analysis and compared the computed distributions of airflow and temperature. The study found that hexahedral meshes were the most accurate, but the computing costs were also the highest. Twelve-million-cell hexahedral meshes would produce acceptable numerical results for the first-class cabin. Different mesh types would require different grid numbers in order to generate accurate results.