Just-in-time value specialization

JavaScript emerges today as one of the most important programming languages for the development of client-side web applications. Therefore, it is essential that browsers be able to execute JavaScript programs efficiently. However, the dynamic nature of this programming language makes it very challenging to achieve this much needed efficiency. In this paper we propose parameter-based value specialization as a way to improve the quality of the code produced by JIT engines. We have empirically observed that almost 60% of the JavaScript functions found in the world's 100 most popular websites are called only once, or are called with the same parameters. Capitalizing on this observation, we adapt a number of classic compiler optimizations to specialize code based on the runtime values of function's actual parameters. We have implemented the techniques proposed in this paper in IonMonkey, an industrial quality JavaScript JIT compiler developed at the Mozilla Foundation. Our experiments, run across three popular JavaScript benchmarks, SunSpider, V8 and Kraken, show that, in spite of its highly speculative nature, our optimization pays for itself. As an example, we have been able to speed up V8 by 4.83%, and to reduce the size of its generated native code by 18.84%.     

Sub-band temporal modulation envelopes and their normalization for automatic speech recognition in reverberant environments

Automatic speech recognition (ASR) in reverberant environments is still a challenging task. In this study, we propose a robust feature-extraction method on the basis of the normalization of the sub-band temporal modulation envelopes (TMEs). The sub-band TMEs were extracted using a series of constant bandwidth band-pass filters with Hilbert transforms followed by low-pass filtering. Based on these TMEs, the modulation spectrums in both clean and reverberation spaces are transformed to a reference space by using modulation transfer functions (MTFs), wherein the MTFs are estimated as the measure of the modulation transfer effect on the sub-band TMEs between the clean, reverberation, and reference spaces. By using the MTFs on the modulation spectrum, it is supposed that the difference on the modulation spectrum caused by the difference of the recording environments is removed. Based on the normalized modulation spectrum, inverse Fourier transform was conducted to restore the sub-band TMEs by retaining their original phase information. We tested the proposed method on speech recognition experiments in a reverberant room with differing speaker to microphone distance (SMD). For comparison, the recognition performance of using the traditional Mel frequency cepstral coefficients with mean and variance normalization was used as the baseline. The experimental results showed that by averaging the results for SMDs from 50 cm to 400 cm, we obtained a 44.96% relative improvement by only using sub-band TME processing, and obtained a further 15.68% relative improvement by performing the normalization on the modulation spectrum of the sub-band TMEs. In all, we obtained a 53.59% relative improvement, which was better than using other temporal filtering and normalization methods.     

沥青路面抗凝冰损伤防护材料研究

优选低表面能材料及高温改制沥青为成膜物质,从表面自由能的角度研究了这种疏水型防护材料的抗水、抗冻黏及抗冻融黏附能力.结果表明：疏水型防护材料具有优异的抗水、冰破坏性能,能够有效降低冰与路表结构的冻黏力;随涂膜固化时间的延长,防护材料对湿轮磨耗试件表面细集料的黏附效果优异,抗水及耐冻融黏附性能显著提高.抗凝冰损伤疏水型防护材料的应用对促进沥青路面预防性养护新技术的发展具有重要意义.     

时间相关密码协议逻辑及其形式化语义

在密码协议中,主体的认知与信仰状态是随时间推移而不断变化的.为了在协议分析中体现这种动态性,提出一种时间相关密码协议逻辑.该逻辑基于谓词模态逻辑,通过在谓词及模态词中引入时间参数以体现时间因素,使得逻辑可表达各个主体在协议不同时间点的行为、知识及信仰.给出该逻辑的形式化语义,在避免逻辑语言二义性的同时保证了逻辑的可靠性.该语义基于Kripke结构,将可能世界建立在主体局部世界与时间局部世界的基础上,使得任一可能世界能够反映协议的一个可能的全过程.该逻辑为密码协议,特别是时间相关密码协议提供了灵活的分析方法,增强了基于逻辑方法的协议分析能力.     

非恒定流清水冲刷输沙规律初步研究

通过波动水流及定常流量的清水冲刷水槽试验,对非恒定流输沙特性进行了研究。分析了洪峰过程中,涨、落水流速、比降、输沙率的变化特性及影响输沙率的主要因素;揭示了加速流和减速流的输沙滞后效应;提出了洪峰输沙量的估算方法以及与洪峰流量输沙等效的当量流量。对人造洪峰设计,河床变形分析计算以及河工模型设计等有一定参考意义。     

New CRT sequence sets for a collision channel without feedback

Protocol sequences are binary and periodic sequences used for deterministic multiple access in a collision channel without feedback. In this paper, we focus on user-irrepressible (UI) protocol sequences that can guarantee a positive individual throughput per sequence period with probability one for a slot-synchronous channel, regardless of the delay offsets among the users. As the sequence period has a fundamental impact on the worst-case channel access delay, a common objective of designing UI sequences is to make the sequence period as short as possible. Consider a communication channel that is shared by M active users, and assume that each protocol sequence has a constant Hamming weight w. To attain a better delay performance than previously known UI sequences, this paper presents a CRTm construction of UI sequences with \(w=M+1\), which is a variation of the previously known CRT construction. For all non-prime \(M\ge 8\), our construction produces the shortest known sequence period and the shortest known worst-case delay of UI sequences. Numerical results show that the new construction enjoys a better average delay performance than the optimal random access scheme and other constructions with the same sequence period, in a variety of traffic conditions. In addition, we derive an asymptotic lower bound on the minimum sequence period for \(w=M+1\) if the sequence structure satisfies some technical conditions, called equi-difference, and prove the tightness of this lower bound by using the CRTm construction.

     

Communication network requirements for major smart grid applications in HAN,NAN and WAN

Since the introduction of the smart grid, accelerated deployment of various smart grid technologies and applications have been experienced. This allows the traditional power grid to become more reliable, resilient, and efficient. Despite such a widespread deployment, it is still not clear which communication technology solutions are the best fit to support grid applications. This is because different smart grid applications have different network requirements – in terms of data payloads, sampling rates, latency and reliability. Based on a variety of smart grid use cases and selected standards, this paper compiles information about different communication network requirements for different smart grid applications, ranging from those used in a Home Area Network (HAN), Neighborhood Area Network (NAN) and Wide-Area Network (WAN). Communication technologies used to support implementation of selected smart grid projects are also discussed. This paper is expected to serve as a comprehensive database of technology requirements and best practices for use by communication engineers when designing a smart grid network.     

Verifiable Threshold Scheme in Multi-Secret Sharing Distributions upon Extensions of ECC

In this paper, we propose a verifiable multi-secret sharing scheme. Some secrets are protected by distributing them among many participants, whereby only an authorized group of participants can reconstruct the secrets. In our scheme, the secret will change periodically and the dealer will periodically publish some of the information to increase the robustness of system, in addition, the participants can verify the information which they have received. Each participant holds only one permanent, private secret, and some of them use it during different time periods to reconstruct the corresponding shared secrets without revealing their own private information. Because some public information is renewed in our scheme, the old information has nothing to do with the next secret. We also compare our scheme to the same technique-based studies in the fields promoting the benefits we achieve in this paper.     

Eliminating rouge femtocells based on distance bounding protocol and geographic information

Recently, femtocell solutions have been attracting increasing attention since coverage for broadband radios can effectively eliminate wireless notspots. To restrict malicious subscribers from accessing femtocells, 3G/WiMAX standards introduce an access control strategy, called Closed Subscriber Group (CSG). However, CSG only prevents malicious clients, but not rouge femtocells. In 2009, Han et al. proposed the first mutual authentication mechanism. This mechanism does not consider the case that an attacker can locate femtocells in an unregistered area even these femtocells are legitimate.In this paper, we first define two attacks, sinkhole and wormhole attacks, in femtocell-enabled mobile networks. Then, we design two approaches based on distance bounding protocols and geographic information to defend against these two attacks. In our design, a subscriber can confirm whether or not the femtocell he connected with is physically-present. Experiment results demonstrate that the distance bounding protocol can estimate an approximate distance between a subscriber’s device and the deployed femtocell. Moreover, femtocells that are deployed inside or outside can both be identified and distinguished without the bias of signal strength based on our design.     

Identifying vegetation from laser data in structured outdoor environments

The ability to reliably detect vegetation is an important requirement for outdoor navigation with mobile robots as it enables the robot to navigate more efficiently and safely. In this paper, we present an approach to detect flat vegetation, such as grass, which cannot be identified using range measurements. This type of vegetation is typically found in structured outdoor environments such as parks or campus sites. Our approach classifies the terrain in the vicinity of the robot based on laser scans and makes use of the fact that plants exhibit specific reflection properties. It uses a support vector machine to learn a classifier for distinguishing vegetation from streets based on laser reflectivity, measured distance, and the incidence angle. In addition, it employs a vibration-based classifier to acquire training data in a self-supervised way and thus reduces manual work. Our approach has been evaluated extensively in real world experiments using several mobile robots. We furthermore evaluated it with different types of sensors and in the context of mapping, autonomous navigation, and exploration experiments. In addition, we compared it to an approach based on linear discriminant analysis. In our real world experiments, our approach yields a classification accuracy close to 100%.