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Communications of the ACM

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CHiMiT '09: Proceedings of the Symposium on Computer Human Interaction for the Management of Information Technology

Information Technology (IT) is central to modern life. From our homes to our largest enterprises, we are surrounded by software and hardware components that support our work and personal lives: wireless access points, network routers, firewalls, virus scanners, databases, web servers, storage and backup systems, etc. These components exist to permit us to do other things, e.g., manage inventory, communicate with friends or customers, sell products through websites, yet all too often managing the underlying IT infrastructure takes time and resources away from the real work at hand. IT systems have grown increasingly complex over the years, and the cost for keeping the infrastructure running is now a significant burden. We are at a turning point where further advances in technology and business efficiency and growth require fundamentally new approaches to IT system design, management, and services.

Started in 2007, ACM CHIMIT Symposium is the leading forum for discussing topics on IT management with a focus on people, business, and technology. At CHIMIT, researchers and practitioners share issues, solutions, and research drawing upon fields such as human-computer interaction, human factors, computer systems, and management and service sciences to address cognitive, social, and technical issues in managing the increasing complexity of modern Information Technology (IT) systems.

Navigation with a tiny brain: Getting home without knowing where you are

The use of visual information for navigation is a universal strategy for sighted animals, amongst whom social insects are particular experts. The general interest in studies of insect navigation is in part due to their small brains; biomimetic engineers can take inspiration from elegant and parsimonious control solutions, while biologists look for a description of the minimal cognitive requirements for complex spatial behaviours. We take an interdisciplinary approach to studying visual guided navigation by combining behavioural experiments with modelling and robotics to understand how complex behaviour can emerge from the combination of a simple sensory system and brain, interacting with innate behaviours all tuned to the natural habitat. In so doing, we show that an agent can robustly navigate without ever knowing where it is, without specifying when or what it should learn, nor requiring it to recognise specific objects, places routes or maps. This leads to an algorithm in which navigation is driven by familiarity detection rather than explicit recall, with sensory data specifying actions not locations. Route navigation is thus recast as a search for familiar views, allowing an agent to encode routes through visually complex worlds in a single layer neural network after a single training run. We suggest that this work is a specific example of a more general idea which has implications for engineers seeking nature-inspired solutions: By considering how animals directly acquire and use task-specific information through specialised sensors, brains and behaviours, we can solve complex problems without complex processing.

New techniques for best-match retrieval

A scheme to answer best-match queries from a file containing a collection of objects is described. A best-match query is to find the objects in the file that are closest (according to some (dis)similarity measure) to a given target. Previous work [5, 331] suggests that one can reduce the number of comparisons required to achieve the desired results using the triangle inequality, starting with a data structure for the file that reflects some precomputed intrafile distances. We generalize the technique to allow the optimum use of any given set of precomputed intrafile distances. Some empirical results are presented which illustrate the effectiveness of our scheme, and its performance relative to previous algorithms.

Space-time tradeoff for answering range queries (Extended Abstract)

In this paper, we raise and investigate the question of (storage) space- (retrieval) time tradeoff for a static database, in the general framework of Fredman's. As will be seen, such tradeoff results also lead to lower bounds on the complexity of processing a sequence of m INSERT and QUERY instructions. The latter results are incomparable to Fredman's, since the presence of DELETE instructions was crucial for his proof technique. We will present our results in detail in the next few sections. Here we will only mention three main conclusions. Firstly, circular query is shown to be intrinsically hard in the sense that, for some static database with n records, there is a space-time tradeoff TS > n1 + ε where ε>0; in contrast, orthogonal query can always be implemented with space S=0(n(log n)k) and time T=0((log n)k) for fixed k. Furthermore, any algorithm for processing 0(n) INSERT and QUERY instructions must use time Ω(n1+ε) in the worst case. Secondly, for the “interval” query, we have determined the space-time tradeoff quite precisely to be T @@@@ α(S,n), where α is the inverse to an Ackermann's function first defined by Tarjan [9]. This is a rare case where the function α arises outside the context of path compression, and is obtained through a totally independent derivation. Thirdly, we prove that, for the interval query, any algorithm to process a sequence of 0(n) INSERT and QUERY must take time Ω((n log n)/(log log n)) in the worst case. This means that one cannot hope to maintain the most efficient static data structure (with retrieval time α(S,n)) in the dynamic case.

Query-driven iterated neighborhood graph search for large scale indexing

In this paper, we address the approximate nearest neighbor (ANN) search problem over large scale visual descriptors. We investigate a simple but very effective approach, neighborhood graph search, which constructs a neighborhood graph to index the data points and conducts a local search, expanding neighborhoods with a best-first manner, for ANN search. Our empirical analysis shows that neighborhood expansion is very efficient, with O(1) cost, for a new NN candidate location, and has high chances to locate true NNs and hence it usually performs well. However, it often gets sub-optimal solutions since local search only checks the neighborhood of the current solution, or conducts exhaustive and continuous neighborhood expansions to find better solutions, which deteriorates the query efficiency.

In this paper, we propose a query-driven iterated neighborhood graph search approach to improve the performance. We follow the iterated local search (ILS) strategy, widely-used in combinatorial optimization, to find a solution beyond a local optimum. We handle the key challenge in making neighborhood graph search adapt to ILS, Perturbation, which generates a new pivot to restart a local search. To this end, we present a criterion to check if the local search over a neighborhood graph arrives at the local solution. Moreover, we exploit the query and search history to design the perturbation scheme, resulting in a more effective search. The major benefit is avoiding unnecessary neighborhood expansions and hence more efficiently finding true NNs. Experimental results on large scale SIFT matching, similar image search, and shape retrieval with non-metric distance measures, show that our approach performs much better than previous state-of-the-art ANN search approaches.

Predictors of on-line services and e-participation: a cross-national comparison

Effective e-government creates an environment for citizens to have greater access to their government and, in theory, makes citizen-to-government contact more inclusive. Our research examines two distinct but related measures of e-government effectiveness, namely the online service index and the e-participation index, both reported in the 2010 e-government survey conducted by the United Nations. We analyze the impact of political structure, administrative culture and policy initiatives on both indices in more than 150 countries. Our multiple regression analysis shows that there is greater e-government capability in countries that have an administrative culture of sound governance and policies that advance the development and diffusion of information and communication technologies. More democratic institutions and processes, however, appear to have a negative impact on e-government. In addition, countries that practice effective governance and promote competition in the telecommunications sector demonstrate more extensive provision of e-participation. These results suggest that the path to e-government leverages different strategies depending on a nation's political structure, and that authoritarian countries may be utilizing e-government to maintain the status quo.

MobileHCI '16: Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct

MobileHCI brings together people from diverse backgrounds and areas of expertise to provide a truly multidisciplinary forum. Academics, hardware and software developers, designers and practitioners alike can discuss challenges encountered on different frontiers of mobility, as well as potential solutions that will advance the field. The conference covers both academic and industry research, ranging from fundamental interaction models and techniques to social and cultural aspects of everyday life with mobile technologies.

Intelligent Computing in Personal Informatics: Key Design Considerations

An expanding range of apps supported by wearable and mobile devices are being used by people engaged in personal informatics in order to track and explore data about themselves and their everyday activities. While the aspect of data collection is easier than ever before through these technologies, more advanced forms of support from personal informatics systems are not presently available. This lack of next generation personal informatics systems presents research with an important role to fill, and this paper presents a two-step contribution to this effect. The first step is to present a new model of human cooperation with intelligent computing, which collates key issues from the literature. The second step is to apply this model to personal informatics, identifying twelve key considerations for integrating intelligent computing in the design of future personal informatics systems. These design considerations are also applied to an example system, which illustrates their use in eliciting new design directions.