Towards Fine-Grained Online Adaptive Approximation Control for Dense SLAM on Embedded GPUs

Dense SLAM is an important application on an embedded environment. However, embedded platforms usually fail to provide enough computation resources for high-accuracy real-time dense SLAM, even with high-parallelism architecture such as GPUs. To tackle this problem, one solution is to design proper approximation techniques for dense SLAM on embedded GPUs. In this work, we propose two novel approximation techniques, critical data identification and redundant branch elimination. We also analyze the error characteristics of the other two techniques—loop skipping and thread approximation. Then, we propose SLaPP, an online adaptive approximation controller, which aims to control the error to be under an acceptable threshold. The evaluation shows SLaPP can achieve 2.0× performance speedup and 30% energy saving on average compared to the case without approximation.

Cohomology of complements of toric arrangements associated with root systems

We develop an algorithm for computing the cohomology of complements of toric arrangements. In the case a finite group $$\Gamma $$ Γ is acting on the arrangement, the algorithm determines the cohomology groups as representations of $$\Gamma $$ Γ . As an important application, we determine the cohomology groups of the complements of the toric arrangements associated with root systems of exceptional type as representations of the corresponding Weyl groups.

Li–Yau inequalities for general non-local diffusion equations via reduction to the heat kernel

We establish a reduction principle to derive Li–Yau inequalities for non-local diffusion problems in a very general framework, which covers both the discrete and continuous setting. Our approach is not based on curvature-dimension inequalities but on heat kernel representations of the solutions and consists in reducing the problem to the heat kernel. As an important application we solve a long-standing open problem by obtaining a Li–Yau inequality for positive solutions u to the fractional (in space) heat equation of the form $$(-\Delta )^{\beta /2}(\log u)\le C/t$$ ( - Δ ) β / 2 ( log u ) ≤ C / t , where $$\beta \in (0,2)$$ β ∈ ( 0 , 2 ) . We also show that this Li–Yau inequality allows to derive a Harnack inequality. We further illustrate our general result with an example in the discrete setting by proving a sharp Li–Yau inequality for diffusion on a complete graph.

Plasmonic Sensor Based On Silver Nanoparticles For The Detection of Glucose

Sensors for detecting glucose concentrations are crucial to medical testing. Here, we introduce silver nanoparticles (Ag NPs) uniformly distributed in space to investigate the sensing properties for detecting glucose by using the finite-different time-domain (FDTD) and experimental methods. The results show that the transmittance of dip for the proposed structural model gradually decreases as the number of Ag NPs increases, when the concentration of glucose is constant. And the transmission spectrum shows slight red shift with the increasing of the glucose concentration. Moreover, the simulation results are in agreement with the experimental results. Especially, the maximum sensitivity S=1144.07407 nm/RIU can be realized for glucose concentration variation from 0.3 to 0.4 mol/L. The research results reveal an excellent sensing property that has important application value in medical detection.

A Study of Big Data Processing for Sentiments Analysis

Data processing has become an important field in today's big data-dominated world. The data has been generating at a tremendous pace from different sources. There has been a change in the nature of data from batch-data to streaming-data, and consequently, data processing methodologies have also changed. Traditional SQL is no longer capable of dealing with this big data. This chapter describes the nature of data and various tools, techniques, and technologies to handle this big data. The chapter also describes the need of shifting big data on to cloud and the challenges in big data processing in the cloud, the migration from data processing to data analytics, tools used in data analytics, and the issues and challenges in data processing and analytics. Then the chapter touches an important application area of streaming data, sentiment analysis, and tries to explore it through some test case demonstrations and results.

Application of the Pick Function in the Lieb Concavity Theorem for Deformed Exponentials

The Lieb concavity theorem, successfully solved in the Wigner–Yanase–Dyson conjecture, is an important application of matrix concave functions. Recently, the Thompson–Golden theorem, a corollary of the Lieb concavity theorem, was extended to deformed exponentials. Hence, it is worthwhile to study the Lieb concavity theorem for deformed exponentials. In this paper, the Pick function is used to obtain a generalization of the Lieb concavity theorem for deformed exponentials, and some corollaries associated with exterior algebra are obtained.

Maintainability of electronic instruments for meteorological applications

The concept of Maintainability (M) of electronic instruments. though of recent origin, has Important application for meteorological equipments, which have special requirements. M is defined quantitatively in terms of mean time to repair and is Influenced by the failure behaviour of an equipment. An equipment goes through teething trouble, useful and terminal phase. Much of maintainability can be incorporated during design and production phase. This reduces the effective overall cost of the equipment during its life time. Special maintenance support system is necessary for meteorological Instruments. Some recent tools for trouble shooting in digital systems have been discussed.

Understanding User Perceptions of Proactive Smart Speakers

Voice assistants, such as Amazon's Alexa and Google Home, increasingly find their way into consumer homes. Their functionality, however, is currently limited to being passive answer machines rather than proactively engaging users in conversations. Speakers' proactivity would open up a range of important application scenarios, including health services, such as checking in on patient states and triggering medication reminders. It remains unclear how passive speakers should implement proactivity. To better understand user perceptions, we ran a 3-week field study with 13 participants where we modified the off-the-shelf Google Home to become proactive. During the study, our speaker proactively triggered conversations that were essentially Experience Sampling probes allowing us to identify when to engage users. Applying machine-learning, we are able to predict user responsiveness with a 71.6% accuracy and find predictive features. We also identify self-reported factors, such as boredom and mood, that are significantly correlated with users' perceived availability. Our prototype and findings inform the design of proactive speakers that verbally engage users at opportune moments and contribute to the design of proactive application scenarios and voice-based experience sampling studies.

From LTL to unambiguous Büchi automata via disambiguation of alternating automata

Due to the high complexity of translating linear temporal logic (LTL) to deterministic automata, several forms of “restricted” nondeterminism have been considered with the aim of maintaining some of the benefits of deterministic automata, while at the same time allowing more efficient translations from LTL. One of them is the notion of unambiguity. This paper proposes a new algorithm for the generation of unambiguous Büchi automata (UBA) from LTL formulas. Unlike other approaches it is based on a known translation from very weak alternating automata (VWAA) to NBA. A notion of unambiguity for alternating automata is introduced and it is shown that the VWAA-to-NBA translation preserves unambiguity. Checking unambiguity of VWAA is determined to be PSPACE-complete, both for the explicit and symbolic encodings of alternating automata. The core of the LTL-to-UBA translation is an iterative disambiguation procedure for VWAA. Several heuristics are introduced for different stages of the procedure. We report on an implementation of our approach in the tool and compare it to an existing LTL-to-UBA implementation in the tool set. Our experiments cover model checking of Markov chains, which is an important application of UBA.

Design of Visible Broadband Metamaterial Absorber Based on Metal Nickel

In this paper,we have proposed a visible broadband metamaterial absorber based on metal Nickel. The metamaterial absorber (MA) is composed of three layers,which are Nickel-based pattern array on the top, silicon dioxide in the middle layer and Nickel film at the bottom. In the whole visible spectrum(380-780nm) of our study, the average absorption of the absorber is up to 95.60%. The absorption rates at 500nm and 637nm are 96.63% and 99.93%, respectively. Also, the proposed MA is insensitive of polarization in the whole visible regime. Later, the mechanism of the absorption and the influence of the structural parameters on the absorption spectrum are investigated. Strong electrical and magnetic resonance are related to the absorption peak at the resonant wavelength. The results show the resonant wavelength of 500nm is fixed and the resonant wavelength of 637nm can be tuned by the parameters.The proposed structure will have important application prospects in the field of solar cells.