We present a taint analysis that can automatically detect when string operations result in a string that is free of taints, where all the tainted patterns have been removed. This is an improvement on the conservative behavior of previous taint analyzers, where a string operation on a tainted string always leads to a tainted string unless the operation is manually marked as a sanitizer. The taint analysis is built on top of a string analysis that uses finite state automata to approximate the sets of values that string variables can take during the execution of a program. The proposed approach has been implemented as an extension of FlowDroid and experimental results show that the resulting taint analyzer is much more precise than the original FlowDroid. Keywords—Android, static analysis, string analysis, taint analysis.
This paper presents a preliminary overview of a model which can be used as a part of a decision support system when fusing data from multiple sensing environment. Combining information from various sensing modalities has been a subject of research for the past many years. A number of methodologies have been designed and developed for handling and integrating uncertainties when deciding on how to combine the sensed information from various sources. In general, determining a suitable framework remains an open problem. For example, a method based on Dempster-Shafer evidence theory has been used as an approach for information fusion in a given decision making environment. Data fusion from a sensor network plays an increasingly significant role during people tracking and activity recognition. This paper explores a quantum model as a part of a decision-making process in the context of multi-sensor information fusion. The paper shows how the framework of a quantum model can be used to handle uncertainties from a sensor as a part of the network having common source can be mapped and viewed with respect to other sensors. The paper presents basic definitions and relationships associating with the decision-making process and quantum model formulation in the presence of uncertainties.
Abstract — This paper draws a comparison between two microstrip patch antennas having different ground structures. The designs utilize 45 mm x 40 mm x 1.6 mm FR4 epoxy substrate (relative permittivity of 4.4 and dielectric loss tangent of 0.02) and CPW feeding technique. The design 1 uses conducting partial ground plates along the two sides of the radiating X’mas tree shaped patch. The design 2 utilizes an X’mas tree shaped slotted ground structure that features a circular radiating patch. A comparative analysis of results of both designs has been carried. The two designs are intended to serve the fixed satellite applications in X and Ku band respectively.
A triple band circularly polarized antenna covering 1.17, 1.22, and 1.57 GHz is presented. To extend to the triple-band operation, we need to add one more ring while maintaining the mechanism to independently control each ring. The inset-part in the feeding scheme is used to excite the band at 1.22 GHz, while the proximate-part of the feeding scheme is used to excite not only the band at 1.57 GHz but also the band at 1.17 GHz. This is achieved by up-vertically coupled with one ring to radiate at 1.57 GHz and down-vertically coupled another ring to radiate at 1.17 GHz. It is also noted that the inset-part in our feeding scheme is by horizontal coupling. Furthermore, to increase the gain at all three bands, three air-layers are added to make the total height of the antenna be 7.8 mm. The total thickness of the three air-layers is 3 mm. The gains of the three bands are all greater than 5 dBiC after adding the air-layers. Keywords—Circular polarization, global position system, triband antenna, high gain.
In this paper, we propose a blind and robust audio watermarking scheme based on spread spectrum in Discrete Wavelet Transform (DWT) domain. Watermarks are embedded in the lowfrequency coefficients, which is less audible. The key idea is dividing the audio signal into small frames, and magnitude of the 6th level of DWT approximation coefficients is modifying based upon the Direct Sequence Spread Spectrum (DSSS) technique. Also, the psychoacoustic model for enhancing in imperceptibility, as well as Savitsky-Golay filter for increasing accuracy in extraction, is used. The experimental results illustrate high robustness against most common attacks, i.e. Gaussian noise addition, Low pass filter, Resampling, Requantizing, MP3 compression, without significant perceptual distortion (ODG is higher than -1). The proposed scheme has about 83 bps data payload. Keywords—Audio watermarking, spread spectrum, discrete wavelet transform, psychoacoustic, Savitsky-Golay filter.
The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection. Keywords—Tripadvisor, Opinion detection, SentiWordNet, trust score.
Accounting Information System (AIS) is important to any organisations especially medium and large organisations this is essential to doing businesses now and in the future. In order to AIS successfully, it is important to consider the factors influences MS adoption, which seriously impacts, the effectiveness of MS adoption practice and the optimisation of MS adoption decisions. This study aims to explore critical factors influence AIS adoption quality and to investigate the relationships between critical factors influences MS adoption and MS adoption quality. This research was done on 46 respondents at ten organisations within organisations in Thailand. Among the 46 respondents, 13% were private national manufactures enterprises, 11% were higher educational institutions (public large); others included government in maintenance of highway assets and management and operation of a transport system and related infrastructure (public large), private national agricultural enterprise (private large), private banking organisation (private large), higher educational institution (public SMEs), and government organisation in the maintenance of assets (Public SMEs), 9% were private company of rice mill (private SMEs), and 6% were private organization of the conventional paper industry and government funded research institution. The results indicate that the factors influences MS adoption defines 25 factors from the case studies were categorised into four groups: organisation factors, stakeholder's factors, technology factors, and external organisation factors. As a result, the empirical evidence suggests that organisation should understanding of the importance of influences factors for chooses and use of software and hardware to support operations, strategic management, and decision making in accounting information systems adoption. This information should be considered in adopting AIS in order to improve its effectiveness.
