8 research outputs found
Applied Metaheuristic Computing
For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC
Applied Methuerstic computing
For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC
Literature and the Public Sphere in the Internet Age
This thesis explores the relationship between literature and the public sphere in the internet age. The introduction identifies gaps on these three topics in current academic work, and outlines the need for clarification of the links between them. The chapters go on to explicate these links with reference to the work of four contemporary authors, namely Jonathan Franzen, Dave Eggers, Zadie Smith, and David Foster Wallace. In their writing, these authors all identify different challenges to the public sphere in the internet age and, in response, ‘model’ alternative modes of being in the public sphere. These modes of being emerge from the particular formal affordances of literature, and are described here as forms of ‘literary publicness.’ The thesis situates these authors on a spectrum of discursive agency, ranging from a view of the public sphere in which writers are seen as authoritative, to a view in which reading processes are prioritised. Each chapter also addresses how these authors have themselves been considered as figures in the public sphere. As such, the story that this thesis tells both helps to clarify the role that culture plays in the public sphere, and reveals the concept of the public sphere itself as a key locus of the relationship between contemporary literature and the internet
Visual encoding quality and scalability in information visualization
Information visualization seeks to amplify cognition through interactive visual representations of data. It comprises human processes, such as perception and cognition, and computer processes, such as visual encoding. Visual encoding consists in mapping data variables to visual variables, and its quality is critical to the effectiveness of information visualizations.
The scalability of a visual encoding is the extent to which its quality is preserved as the parameters of the data grow. Scalable encodings offer good support for basic analytical tasks at scale by carrying design decisions that consider the limits of human perception and cognition. In this thesis, I present three case studies that explore different aspects of visual encoding quality and scalability: information loss, perceptual scalability, and discriminability. In the first study, I leverage information theory to model encoding quality in terms of information content and complexity. I examine how information loss and clutter affect the scalability of hierarchical visualizations and contribute an information-theoretic algorithm for adjusting these factors in visualizations of large datasets. The second study centers on the question of whether a data property (outlierness) can be lost in the visual encoding process due to saliency interference with other visual variables. I designed a controlled experiment to measure the effectiveness of motion outlier detection in complex multivariate scatterplots. The results suggest a saliency deficit effect whereby global saliency undermines support to tasks that rely on local saliency.
Finally, I investigate how discriminability, a classic visualization criterion, can explain recent empirical results on encoding effectiveness and provide the foundation for automated evaluation of visual encodings. I propose an approach for discriminability evaluation based on a perceptually motivated image similarity measure
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Analyzing the Unanalyzable: an Application to Android Apps
In general, software is unreliable. Its behavior can deviate from users’ expectations because of bugs, vulnerabilities, or even malicious code. Manually vetting software is a challenging, tedious, and highly-costly task that does not scale. To alleviate excessive costs and analysts’ burdens, automated static analysis techniques have been proposed by both the research and practitioner communities making static analysis a central topic in software engineering. In the meantime, mobile apps have considerably grown in importance. Today, most humans carry software in their pockets, with the Android operating system leading the market. Millions of apps have been proposed to the public so far, targeting a wide range of activities such as games, health, banking, GPS, etc. Hence, Android apps collect and manipulate a considerable amount of sensitive information, which puts users’ security and privacy at risk. Consequently, it is paramount to ensure that apps distributed through public channels (e.g., the Google Play) are free from malicious code. Hence, the research and practitioner communities have put much effort into devising new automated techniques to vet Android apps against malicious activities over the last decade. Analyzing Android apps is, however, challenging. On the one hand, the Android framework proposes constructs that can be used to evade dynamic analysis by triggering the malicious code only under certain circumstances, e.g., if the device is not an emulator and is currently connected to power. Hence, dynamic analyses can -easily- be fooled by malicious developers by making some code fragments difficult to reach. On the other hand, static analyses are challenged by Android-specific constructs that limit the coverage of off-the-shell static analyzers. The research community has already addressed some of these constructs, including inter-component communication or lifecycle methods. However, other constructs, such as implicit calls (i.e., when the Android framework asynchronously triggers a method in the app code), make some app code fragments unreachable to the static analyzers, while these fragments are executed when the app is run. Altogether, many apps’ code parts are unanalyzable: they are either not reachable by dynamic analyses or not covered by static analyzers. In this manuscript, we describe our contributions to the research effort from two angles: ①statically detecting malicious code that is difficult to access to dynamic analyzers because they are triggered under specific circumstances; and ② statically analyzing code not accessible to existing static analyzers to improve the comprehensiveness of app analyses. More precisely, in Part I, we first present a replication study of a state-of-the-art static logic bomb detector to better show its limitations. We then introduce a novel hybrid approach for detecting suspicious hidden sensitive operations towards triaging logic bombs. We finally detail the construction of a dataset of Android apps automatically infected with logic bombs. In Part II, we present our work to improve the comprehensiveness of Android apps’ static analysis. More specifically, we first show how we contributed to account for atypical inter-component communication in Android apps. Then, we present a novel approach to unify both the bytecode and native in Android apps to account for the multi-language trend in app development. Finally, we present our work to resolve conditional implicit calls in Android apps to improve static and dynamic analyzers
SPATIAL TRANSFORMATION PATTERN DUE TO COMMERCIAL ACTIVITY IN KAMPONG HOUSE
ABSTRACT Kampung houses are houses in kampung area of the city. Kampung House oftenly transformed into others use as urban dynamics. One of the transfomation is related to the commercial activities addition by the house owner. It make house with full private space become into mixused house with more public spaces or completely changed into full public commercial building. This study investigate the spatial transformation pattern of the kampung houses due to their commercial activities addition. Site observations, interviews and questionnaires were performed to study the spatial transformation. This study found that in kampung houses, the spatial transformation pattern was depend on type of commercial activities and owner perceptions, and there are several steps of the spatial transformation related the commercial activity addition.
Keywords: spatial transformation pattern; commercial activity; owner perception, kampung house; adaptabilit