Samsung

About: Samsung is a company organization based out in Seoul, South Korea. It is known for research contribution in the topics: Layer (electronics) & Signal. The organization has 134067 authors who have published 163691 publications receiving 2057505 citations. The organization is also known as: Samsung Group & Samsung chaebol.

Jalangi: a selective record-replay and dynamic analysis framework for JavaScript

Abstract: JavaScript is widely used for writing client-side web applications and is getting increasingly popular for writing mobile applications. However, unlike C, C++, and Java, there are not that many tools available for analysis and testing of JavaScript applications. In this paper, we present a simple yet powerful framework, called Jalangi, for writing heavy-weight dynamic analyses. Our framework incorporates two key techniques: 1) selective record-replay, a technique which enables to record and to faithfully replay a user-selected part of the program, and 2) shadow values and shadow execution, which enables easy implementation of heavy-weight dynamic analyses. Our implementation makes no special assumption about JavaScript, which makes it applicable to real-world JavaScript programs running on multiple platforms. We have implemented concolic testing, an analysis to track origins of nulls and undefined, a simple form of taint analysis, an analysis to detect likely type inconsistencies, and an object allocation profiler in Jalangi. Our evaluation of Jalangi on the SunSpider benchmark suite and on five web applications shows that Jalangi has an average slowdown of 26X during recording and 30X slowdown during replay and analysis. The slowdowns are comparable with slowdowns reported for similar tools, such as PIN and Valgrind for x86 binaries. We believe that the techniques proposed in this paper are applicable to other dynamic languages.

A Survey of Artificial Intelligence for Cognitive Radios

Abstract: Cognitive radio (CR) is an enabling technology for numerous new capabilities such as dynamic spectrum access, spectrum markets, and self-organizing networks. To realize this diverse set of applications, CR researchers leverage a variety of artificial intelligence (AI) techniques. To help researchers better understand the practical implications of AI to their CR designs, this paper reviews several CR implementations that used the following AI techniques: artificial neural networks (ANNs), metaheuristic algorithms, hidden Markov models (HMMs), rule-based systems, ontology-based systems (OBSs), and case-based systems (CBSs). Factors that influence the choice of AI techniques, such as responsiveness, complexity, security, robustness, and stability, are discussed. To provide readers with a more concrete understanding, these factors are illustrated in an extended discussion of two CR designs.

First-Principles Studies on Cation Dopants and Electrolyte|Cathode Interphases for Lithium Garnets

Abstract: Lithium garnet with the formula Li7La3Zr2O12 (LLZO) has many properties of an ideal electrolyte in all-solid state lithium batteries. However, internal resistance in batteries utilizing these electrolytes remains high. For widespread adoption, the LLZO’s internal resistance must be lowered by increasing its bulk conductivity, reducing grain boundary resistance, and/or pairing it with an appropriate cathode to minimize interfacial resistance. Cation doping has been shown to be crucial in LLZO to stabilize the higher conductivity cubic structure, yet there is still little understanding about which cations have high solubility in LLZO. In this work, we apply density functional theory (DFT) to calculate the defect energies and site preference of all possible dopants in these materials. Our findings suggest several novel dopants such as Zn2+ and Mg2+ predicted to be stable on the Li- and Zr-sites, respectively. To understand the source of interfacial resistance between the electrolyte and the cathode, we inves...