Capping computation time and storage requirements for appearance-based localization with CAT-SLAM

Appearance-based localization is increasingly used for loop closure detection in metric SLAM systems. Since it relies only upon the appearance-based similarity between images from two locations, it can perform loop closure regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale linearly not only with the size of the environment but also with the operation time of the platform. These properties impose severe restrictions on longterm autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. We present a set of improvements to the appearance-based SLAM algorithm CAT-SLAM to constrain computation scaling and memory usage with minimal degradation in performance over time. The appearance-based comparison stage is accelerated by exploiting properties of the particle observation update, and nodes in the continuous trajectory map are removed according to minimal information loss criteria. We demonstrate constant time and space loop closure detection in a large urban environment with recall performance exceeding FAB-MAP by a factor of 3 at 100% precision, and investigate the minimum computational and memory requirements for maintaining mapping performance.

Computational experiments involving population size for FPGA-based implementation of a GA for the TSP

The feasibility of using an in-hardware implementation of a genetic algorithm (GA) to solve the computationally expensive travelling salesman problem (TSP) is explored, especially in regard to hardware resource requirements for problem and population sizes. We investigate via numerical experiments whether a small population size might prove sufficient to obtain reasonable quality solutions for the TSP, thereby permitting relatively resource efficient hardware implementation on field programmable gate arrays (FPGAs). Software experiments on two TSP benchmarks involving 48 and 532 cities were used to explore the extent to which population size can be reduced without compromising solution quality, and results show that a GA allowed to run for a large number of generations with a smaller population size can yield solutions of comparable quality to those obtained using a larger population. This finding is then used to investigate feasible problem sizes on a targeted Virtex-7 vx485T-2 FPGA platform via exploration of hardware resource requirements for memory and data flow operations.

Towards persistent indoor appearance-based localization, mapping and navigation using CAT-Graph

The challenge of persistent appearance-based navigation and mapping is to develop an autonomous robotic vision system that can simultaneously localize, map and navigate over the lifetime of the robot. However, the computation time and memory requirements of current appearance-based methods typically scale not only with the size of the environment but also with the operation time of the platform; also, repeated revisits to locations will develop multiple competing representations which reduce recall performance. In this paper we present a solution to the persistent localization, mapping and global path planning problem in the context of a delivery robot in an office environment over a one-week period. Using a graphical appearance-based SLAM algorithm, CAT-Graph, we demonstrate constant time and memory loop closure detection with minimal degradation during repeated revisits to locations, along with topological path planning that improves over time without using a global metric representation. We compare the localization performance of CAT-Graph to openFABMAP, an appearance-only SLAM algorithm, and the path planning performance to occupancy-grid based metric SLAM. We discuss the limitations of the algorithm with regard to environment change over time and illustrate how the topological graph representation can be coupled with local movement behaviors for persistent autonomous robot navigation.

Analysis of stream cipher based authenticated encryption schemes

Authenticated Encryption (AE) is the cryptographic process of providing simultaneous confidentiality and integrity protection to messages. This approach is more efficient than applying a two-step process of providing confidentiality for a message by encrypting the message, and in a separate pass providing integrity protection by generating a Message Authentication Code (MAC). AE using symmetric ciphers can be provided by either stream ciphers with built in authentication mechanisms or block ciphers using appropriate modes of operation. However, stream ciphers have the potential for higher performance and smaller footprint in hardware and/or software than block ciphers. This property makes stream ciphers suitable for resource constrained environments, where storage and computational power are limited. There have been several recent stream cipher proposals that claim to provide AE. These ciphers can be analysed using existing techniques that consider confidentiality or integrity separately; however currently there is no existing framework for the analysis of AE stream ciphers that analyses these two properties simultaneously. This thesis introduces a novel framework for the analysis of AE using stream cipher algorithms. This thesis analyzes the mechanisms for providing confidentiality and for providing integrity in AE algorithms using stream ciphers. There is a greater emphasis on the analysis of the integrity mechanisms, as there is little in the public literature on this, in the context of authenticated encryption. The thesis has four main contributions as follows. The first contribution is the design of a framework that can be used to classify AE stream ciphers based on three characteristics. The first classification applies Bellare and Namprempre's work on the the order in which encryption and authentication processes take place. The second classification is based on the method used for accumulating the input message (either directly or indirectly) into the into the internal states of the cipher to generate a MAC. The third classification is based on whether the sequence that is used to provide encryption and authentication is generated using a single key and initial vector, or two keys and two initial vectors. The second contribution is the application of an existing algebraic method to analyse the confidentiality algorithms of two AE stream ciphers; namely SSS and ZUC. The algebraic method is based on considering the nonlinear filter (NLF) of these ciphers as a combiner with memory. This method enables us to construct equations for the NLF that relate the (inputs, outputs and memory of the combiner) to the output keystream. We show that both of these ciphers are secure from this type of algebraic attack. We conclude that using a keydependent SBox in the NLF twice, and using two different SBoxes in the NLF of ZUC, prevents this type of algebraic attack. The third contribution is a new general matrix based model for MAC generation where the input message is injected directly into the internal state. This model describes the accumulation process when the input message is injected directly into the internal state of a nonlinear filter generator. We show that three recently proposed AE stream ciphers can be considered as instances of this model; namely SSS, NLSv2 and SOBER-128. Our model is more general than a previous investigations into direct injection. Possible forgery attacks against this model are investigated. It is shown that using a nonlinear filter in the accumulation process of the input message when either the input message or the initial states of the register is unknown prevents forgery attacks based on collisions. The last contribution is a new general matrix based model for MAC generation where the input message is injected indirectly into the internal state. This model uses the input message as a controller to accumulate a keystream sequence into an accumulation register. We show that three current AE stream ciphers can be considered as instances of this model; namely ZUC, Grain-128a and Sfinks. We establish the conditions under which the model is susceptible to forgery and side-channel attacks.

Imagining neighbourhood-based community : an autoethnography

This research is an autoethnographic investigation of consumption experiences, public and quasi-public spaces, and their relationship to community within an inner city neighbourhood. The research specifically focuses on the gentrifying inner city, where class-based processes of change can have implications for people’s abilities to remain within, or feel connected to place. However, the thesis draws on broader theories of the throwntogetherness of the contemporary city (e.g., Amin and Thrift, 2002; Massey 2005) to argue that the city is a space where place-based meanings cannot be seen to be fixed, and are instead better understood as events of place – based on ever shifting interrelations between the trajectories of people and things. This perspective argues the experience of belonging to community is not just born of a social encounter, but also draws on the physical and symbolic elements of the context in which it is situated. The thesis particularly explores the ways people construct identifications within this shifting urban environment. As such, consumption practices and spaces offer one important lens through which to explore the interplay of the physical, social and symbolic. Consumer research tells us that consumption practices can facilitate experiences in which identity-defining meaning can be generated and shared. Consumption spaces can also support different kinds of collective identification – as anchoring realms for specific cultural groups or exposure realms that enable individuals to share in the identification practices of others with limited risk (Aubert-Gamet & Cova, 1999). Furthermore, the consumption-based lifestyles that gentrifying inner city neighbourhoods both support and encourage can also mean that consumption practices may be a key reason that people are moving through public space. That is, consumption practices and spaces may provide a purpose for which – and spatial frame against which – our everyday interactions and connections with people and objects are undertaken within such neighbourhoods. The purpose of this investigation then was to delve into the subjectivities at the heart of identifying with places, using the lens of our consumption-based experiences within them. The enquiry describes individual and collective identifications and emotional connections, and explores how these arise within and through our experiences within public and quasi-public spaces. It then theorises these ‘imaginings’ as representative of an experience of community. To do so, it draws on theories of imagination and its relation to community. Theories of imagined community remind us that both the values and identities of community are held together by projections that create relational links out of objects and shared practices (e.g., Benedict Anderson, 2006; Urry, 2000). Drawing on broader theories of the processes of the imagination, this thesis suggests that an interplay between reflexivity and fantasy – which are products of the critical and the fascinated consciousness – plays a role in this imagining of community (e.g., Brann, 1991; Ricoeur, 1994). This thesis therefore seeks to explore how these processes of imagining are implicated within the construction of an experience of belonging to neighbourhood-based community through consumption practices and the public and quasi-public spaces that frame them. The key question of this thesis is how do an individual’s consumption practices work to construct an imagined presence of neighbourhood-based community? Given the focus on public and quasi-public spaces and our experiences within them, the research also asked how do experiences in the public and quasi-public spaces that frame these practices contribute to the construction of this imagined presence? This investigation of imagining community through consumption practices is based on my own experiences of moving to, and attempting to construct community connections within, an inner city neighbourhood in Melbourne, Australia. To do so, I adopted autoethnographic methodology. This is because autoethnography provides the methodological tools through which one can explore and make visible the subjectivities inherent within the lived experiences of interest to the thesis (Ellis, 2004). I describe imagining community through consumption as an extension of a placebased self. This self is manifest through personal identification in consumption spaces that operate as anchoring realms for specific cultural groups, as well as through a broader imagining of spaces, people, and practices as connected through experiences within realms of exposure. However, this is a process that oscillates through cycles of identification; these anchor one within place personally, but also disrupt those attachments. This instability can force one to question the orientation and motives of these imaginings, and reframe them according to different spaces and reference groups in ways that can also work to construct a more anonymous and, conversely, more achievable collective identification. All the while, the ‘I’ at the heart of this identification is in an ongoing process of negotiation, and similarly, the imagined community is never complete. That is, imagining community is a negotiation, with people and spaces – but mostly with the different identifications of the self. This thesis has been undertaken by publication, and thus the process of imagining community is explored and described through four papers. Of these, the first two focus on specific types of consumption spaces – a bar and a shopping centre – and consider the ways that anchoring and exposure within these spaces support the process of imagining community. The third paper examines the ways that the public and quasi-public spaces that make up the broader neighbourhood context are themselves throwntogether as a realm of exposure, and considers the ways this shapes my imaginings of this neighbourhood as community. The final paper develops a theory of imagined community, as a process of comparison and contrast with imagined others, to provide a summative conceptualisation of the first three papers. The first paper, chapter five, explores this process of comparison and contrast in relation to authenticity, which in itself is a subjective assessment of identity. This chapter was written as a direct response to the recent work of Zukin (2010), and draws on theories of authenticity as applied to personal and collective identification practices by consumer researchers Arnould and Price (2000). In this chapter, I describe how my assessments of the authenticity of my anchoring experiences within one specific consumption space, a neighbourhood bar, are evaluated in comparison to my observations of and affective reactions to the social practices of another group of residents in a different consumption space, the local shopping centre. Chapter five also provides an overview of the key sites and experiences that are considered in more detail in the following two chapters. In chapter six, I again draw on my experiences within the bar introduced in chapter five, this time to explore the process of developing a regular identity within a specific consumption space. Addressing the popular theory of the cafe or bar as third place (Oldenburg, 1999), this paper considers the purpose of developing anchored relationships with people within specific consumption spaces, and explores the different ways this may be achieved in an urban context where the mobilities and lifestyle practices of residents complicate the idea of a consumption space as an anchoring or third place. In doing so, this chapter also considers the manner in which this type of regular identification may be seen to be the beginning of the process of imagining community. In chapter seven, I consider the ways the broader public spaces of the neighbourhood work cumulatively to expose different aspects of its identity by following my everyday movements through the neighbourhood’s shopping centre and main street. Drawing on the theories of Urry (2000), Massey (2005), and Amin (2007, 2008), this chapter describes how these spaces operate as exposure realms, enabling the expression of different senses of the neighbourhood’s spaces, times, cultures, and identities through their physical, social, and symbolic elements. Yet they also enable them to be united: through habitual pathways, group practices of appropriation of space, and memory traces that construct connections between objects and experiences. This chapter describes this as a process of exposure to these different elements. Our imagination begins to expand the scope of the frames onto which it projects an imagined presence; it searches for patterns within the physical, social, and symbolic environment and draws connections between people and practices across spaces. As the final paper, chapter eight, deduces, it is in making these connections that one constructs the objects and shared practices of imagined community. This chapter describes this as an imagining of neighbourhood as a place-based extension of the self, and then explores the ways in which I drew on physical, social, and symbolic elements in an attempt to construct a fit between the neighbourhood’s offerings and my desires for place-based identity definition. This was as a cumulative but fragmented process, in which positive and negative experiences of interaction and identification with people and things were searched for their potential to operate as the objects and shared practices of imagined community. This chapter describes these connections as constructed through interplay between reflexivity and fantasy, as the imagination seeks balance between desires for experiences of belonging, and the complexities of constructing them within the throwntogether context of the contemporary city. The conclusion of the thesis describes the process of imagining community as a reflexive fantasy, that is, as a product of both the critical and fascinated consciousness (Ricoeur, 1994). It suggests that the fascinated consciousness imbues experiences with hope and desire, which the reflexive imagining can turn to disappointment and shame as it critically reflects on the reality of those fascinated projections. At the same time, the reflexive imagination also searches the practices of others for affirmation of those projections, effectively seeking to prove the reality of the fantasy of the imagined community.

Neurons Activated During Fear Memory Consolidation and Reconsolidation are Mapped to a Common and New Topography in the Lateral Amygdala

A key question in neuroscience is how memory is selectively allocated to neural networks in the brain. This question remains a significant research challenge, in both rodent models and humans alike, because of the inherent difficulty in tracking and deciphering large, highly dimensional neuronal ensembles that support memory (i.e., the engram). In a previous study we showed that consolidation of a new fear memory is allocated to a common topography of amygdala neurons. When a consolidated memory is retrieved, it may enter a labile state, requiring reconsolidation for it to persist. What is not known is whether the original spatial allocation of a consolidated memory changes during reconsolidation. Knowledge about the spatial allocation of a memory, during consolidation and reconsolidation, provides fundamental insight into its core physical structure (i.e., the engram). Using design-based stereology, we operationally define reconsolidation by showing a nearly identical quantity of neurons in the dorsolateral amygdala (LAd) that expressed a plasticity-related protein, phosphorylated mitogen-activated protein kinase, following both memory acquisition and retrieval. Next, we confirm that Pavlovian fear conditioning recruits a stable, topographically organized population of activated neurons in the LAd. When the stored fear memory was briefly reactivated in the presence of the relevant conditioned stimulus, a similar topography of activated neurons was uncovered. In addition, we found evidence for activated neurons allocated to new regions of the LAd. These findings provide the first insight into the spatial allocation of a fear engram in the LAd, during its consolidation and reconsolidation phase.

Intrusion detection in distributed systems, an approach based on taint marking

This paper presents a new framework for distributed intrusion detection based on taint marking. Our system tracks information flows between applications of multiple hosts gathered in groups (i.e., sets of hosts sharing the same distributed information flow policy) by attaching taint labels to system objects such as files, sockets, Inter Process Communication (IPC) abstractions, and memory mappings. Labels are carried over the network by tainting network packets. A distributed information flow policy is defined for each group at the host level by labeling information and defining how users and applications can legally access, alter or transfer information towards other trusted or untrusted hosts. As opposed to existing approaches, where information is most often represented by two security levels (low/high, public/private, etc.), our model identifies each piece of information within a distributed system, and defines their legal interaction in a fine-grained manner. Hosts store and exchange security labels in a peer to peer fashion, and there is no central monitor. Our IDS is implemented in the Linux kernel as a Linux Security Module (LSM) and runs standard software on commodity hardware with no required modification. The only trusted code is our modified operating system kernel. We finally present a scenario of intrusion in a web service running on multiple hosts, and show how our distributed IDS is able to report security violations at each host level.

Semi-binary based video features for activity representation

Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

CAM : a collaborative object memory system

Physical design objects such as sketches, drawings, collages, storyboards and models play an important role in supporting communication and coordination in design studios. CAM (Cooperative Artefact Memory) is a mobile-tagging based messaging system that allows designers to collaboratively store relevant information onto their design objects in the form of messages, annotations and external web links. We studied the use of CAM in a Product Design studio over three weeks, involving three different design teams. In this paper, we briefly describe CAM and show how it serves as 'object memory'.

Cryptanalysis of RC4-based hash function

RC4-Based Hash Function is a new proposed hash function based on RC4 stream cipher for ultra low power devices. In this paper, we analyse the security of the function against collision attack. It is shown that the attacker can find collision and multi-collision messages with complexity only 6 compress function operations and negligible memory with time complexity 2 13. In addition, we show the hashing algorithm can be distinguishable from a truly random sequence with probability close to one.

Joint identification of infinite-frequency added mass and fluid-memory models of marine structures

This paper addresses the problem of joint identification of infinite-frequency added mass and fluid memory models of marine structures from finite frequency data. This problem is relevant for cases where the code used to compute the hydrodynamic coefficients of the marine structure does not give the infinite-frequency added mass. This case is typical of codes based on 2D-potential theory since most 3D-potential-theory codes solve the boundary value associated with the infinite frequency. The method proposed in this paper presents a simpler alternative approach to other methods previously presented in the literature. The advantage of the proposed method is that the same identification procedure can be used to identify the fluid-memory models with or without having access to the infinite-frequency added mass coefficient. Therefore, it provides an extension that puts the two identification problems into the same framework. The method also exploits the constraints related to relative degree and low-frequency asymptotic values of the hydrodynamic coefficients derived from the physics of the problem, which are used as prior information to refine the obtained models.

The ranking based constrained document clustering method and its application to social event detection

With the growing size and variety of social media files on the web, it’s becoming critical to efficiently organize them into clusters for further processing. This paper presents a novel scalable constrained document clustering method that harnesses the power of search engines capable of dealing with large text data. Instead of calculating distance between the documents and all of the clusters’ centroids, a neighborhood of best cluster candidates is chosen using a document ranking scheme. To make the method faster and less memory dependable, the in-memory and in-database processing are combined in a semi-incremental manner. This method has been extensively tested in the social event detection application. Empirical analysis shows that the proposed method is efficient both in computation and memory usage while producing notable accuracy.

Visual and proprioceptive representations in spatial memory

It has been shown that spatial information can be acquired from both visual and nonvisual modalities. The present study explored how spatial information from vision and proprioception was represented in memory, investigating orientation dependence of spatial memories acquired through visual and proprioceptive spatial learning. Experiment 1 examined whether visual learning alone and proprioceptive learning alone yielded orientation-dependent spatial memory. Results showed that spatial memories from both types of learning were orientation dependent. Experiment 2 explored how different orientations of the same environment were represented when they were learned visually and proprioceptively. Results showed that both visually and proprioceptively learned orientations were represented in spatial memory, suggesting that participants established two different reference systems based on each type of learning experience and interpreted the environment in terms of these two reference systems. The results provide some initial clues to how different modalities make unique contributions to spatial representations.

An adaptive appearance-based map for long-term topological localization of mobile robots

"This work considers a mobile service robot which uses an appearance-based representation of its workplace as a map, where the current view and the map are used to estimate the current position in the environment. Due to the nature of real-world environments such as houses and offices, where the appearance keeps changing, the internal representation may become out of date after some time. To solve this problem the robot needs to be able to adapt its internal representation continually to the changes in the environment. This paper presents a method for creating an adaptive map for long-term appearance-based localization of a mobile robot using long-term and short-term memory concepts, with omni-directional vision as the external sensor."--publisher website

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.