OpenRaiser/Intern-Atlas huggingface dataset:
A Parallel Implementation of the Ensemble Kalman Filter Based on Modified Cholesky Decomposition
Venue: arXiv cs.NA 2016
Year: 2016

This paper discusses an efficient parallel implementation of the ensemble Kalman filter based on the modified Cholesky decomposition. The proposed implementation starts with decomposing the domain into sub-domains. In each sub-domain a sparse estimation of the inverse background error covariance matrix is computed via a modified Cholesky decomposition; the estimates are computed concurrently on separate processors. The sparsity of this estimator is dictated by the conditional independence of model components for some radius of influence. Then, the assimilation step is carried out in parallel without the need of inter-processor communication. Once the local analysis states are computed, the analysis sub-domains are mapped back onto the global domain to obtain the analysis ensemble. Computational experiments are performed using the Atmospheric General Circulation Model (SPEEDY) with the T-63 resolution on the Blueridge cluster at Virginia Tech. The number of processors used in the experiments ranges from 96 to 2,048. The proposed implementation outperforms in terms of accuracy the well-known local ensemble transform Kalman filter (LETKF) for all the model variables. The computational time of the proposed implementation is similar to that of the parallel LETKF method (where no covariance estimation is performed). Finally, for the largest number of processors, the proposed parallel implementation is 400 times faster than the serial version of the proposed method.
Unifying Geometric Features and Facial Action Units for Improved Performance of Facial Expression Analysis
Venue: arXiv cs.CV 2016
Year: 2016

Previous approaches to model and analyze facial expression analysis use three different techniques: facial action units, geometric features and graph based modelling. However, previous approaches have treated these technique separately. There is an interrelationship between these techniques. The facial expression analysis is significantly improved by utilizing these mappings between major geometric features involved in facial expressions and the subset of facial action units whose presence or absence are unique to a facial expression. This paper combines dimension reduction techniques and image classification with search space pruning achieved by this unique subset of facial action units to significantly prune the search space. The performance results on the publicly facial expression database shows an improvement in performance by 70% over time while maintaining the emotion recognition correctness.
Factors Influencing mHealth Acceptance among Elderly People in Bangladesh
Venue: arXiv cs.CY 2016
Year: 2016

mHealth (mobile health) be the blessing of ICT and is probably one of the most prominent services with noticeable effect on the development of healthcare sector. Given the potential benefits mHealth can bring to older people, it is important to understand the users (elderly population) intention to use the technology. However, little research has been done to draw any systematic study of elderlys adoption and usage of mHealth. The aim of this study is to determine factors that influence the adoption and use of mHealth technology and services by the elderly in Bangladesh. This research will develop a theoretical model to determine the elderly behavioral intention to adopt mHealth application. It is intended to determine if there is any significant relationship between attitudinal constructs such as Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Condition, Hedonic Motivation, Price Value, Habit and acceptance of mHealth services in Bangladesh. The study will also investigate the moderating role of gender & experience and their influence on the adoption of mHealth technology and services.
Evaluating Electronic Customer Relationship Management Performance: Case Studies from Persian Automotive and Computer Industry
Venue: arXiv cs.CY 2016
Year: 2016

This research paper investigates the influence of industry on electronic customer relationship management (e-CRM) performance. A case study approach with two cases was applied to evaluate the influence of e-CRM on customer behavioral and attitudinal loyalty along with customer pyramid. The cases covered two industries consisting of computer and automotive industries. For investigating customer behavioral loyalty and customer pyramid companies database were computed while for examining customer attitudinal loyalty a survey was conducted. The results show that e-CRM has significantly different impacts on customer behavioral and attitudinal loyalty and customer pyramid in two industries. This research provides new approach for organizations to evaluate their e-CRM performance and compare it with other companies in order to formulate stronger policies for customer relationship management.
Individual Level Culture Effects on Multi-Perspective iTrust in B2C E-commerce
Venue: arXiv cs.CY 2016
Year: 2016

Consumer trust is one of the key obstacles to online vendors seeking to extend their consumers across cultures. This research identifies culture at the individual consumer level. Based on the Stimulus-Organism-Response (SOR) model, this study focuses on the moderating role of uncertainty avoidance culture value on privacy and security as cognition influences, joy and fear as emotional influences (Stimuli), and individualism-collectivism on social networking services as social influence and subsequently on interpersonal trust (cognitive and affect-based trust) (Organism) towards purchase intention (Response). Data were collected in Australia and the Partial least squares (PLS) approach was used to test the research model. The findings confirmed the moderating role of individual level culture on consumer's cognitive and affect-based trust in B2Ce-commerce websites with diverse degrees of uncertainty avoidance and individualism.
A Comparative Analysis of MOOC - Australia's Position in the International Education Market
Venue: arXiv cs.CY 2016
Year: 2016

Tertiary education is one of the most important industries in Australia and a crucial source of income for its universities. Therefore, any new form of tertiary education that may have impact on Australian universities should be closely watched for implications on their business models. In the past decade, MOOC-Massive Open Online Courses have emerged with the promise to offer world class education accessible anywhere and anytime for free or at very reasonable costs. MOOC not only provide opportunities for lifelong learning, they are also designed to enrich, compliment and even (partly) substitute classic tertiary education. Hence, it is of crucial importance how and where Australia takes its stand in this rapidly evolving market. In this paper, Australia's international position as a provider of MOOC is analysed and compared, in particular to Germany and the US.
The Role of Translated Information Quality in a Global e-Retailing Context
Venue: arXiv cs.CY 2016
Year: 2016

Global e-retailing continues to gain in popularity, but little attention is being paid to the role of translation. This paper proposes a study investigating whether improving translated information quality of product descriptions increases the customers' information satisfaction, while reducing the perceived product risk, which in turn improves their intention to use an online shopping website. To manipulate translation quality, two translation methods are used: machine and crowdsourced. The chosen translation written language pair is from English to Simplified Chinese, as these are the official languages of world's two largest economies (U.S.A and China respectively) that also have large e-tailing markets. A model based on an integration of two theories, DeLone & McLean's Information Systems Success Model, and Perceived Risk Theory, has been developed for testing the impact of translated information quality. The moderating effect of translation method and e-retailer's brand influencing customers' tolerance of imperfect translation is also considered.
Developing a Methodology for Online Service Failure Prevention: Reporting on an Action Design Research Project-in-Progress
Venue: arXiv cs.CY 2016
Year: 2016

The increasing use of online channels for service delivery raises new challenges in service failure prevention. This work-in-progress paper reports on the first phase of an action-design research project to develop a service failure prevention methodology. In this paper we review the literature on online services, failure prevention and failure recovery and develop a theoretical framework for online service failure prevention. This provides the theoretical grounding for the artefact (the methodology) to be developed. We use this framework to develop an initial draft of our methodology. We then outline the remaining phases of the research, and offer some initial conclusions gained from the project to date.
An Exact Linearization Method for OLTC of Transformer in Branch Flow Model
Venue: arXiv cs.SY 2016
Year: 2016

The branch flow based optimal power flow(OPF) problem in radianlly operated distribution networks can be exactly relazed to a second order cone programming (SOCP) model without considering transformers. However, the introdution of nonlinear transformer models will make the OPF model non-convex. This paper presents an exact linearized transformer's OLTC model to keep the OPF model convex via binary expanstion scheme and big-M method. Validity of the proposed method is verified using IEEE 33-bus test system.
Delay Optimal Scheduling of Arbitrarily Bursty Traffic over Multi-State Time-Varying Channels
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, we study joint queue-aware and channel-aware scheduling of arbitrarily bursty traffic over multi-state time-varying channels, where the bursty packet arrival in the network layer, the backlogged queue in the data link layer, and the power adaptive transmission with fixed modulation in the physical layer are jointly considered from a cross-layer perspective. To achieve minimum queueing delay given a power constraint, a probabilistic cross-layer scheduling policy is proposed, and characterized by a Markov chain model. To describe the delay-power tradeoff, we formulate a non-linear optimization problem, which however is very challenging to solve. To handle with this issue, we convert the optimization problem into an equivalent Linear Programming (LP) problem, which allows us to obtain the optimal threshold-based scheduling policy with an optimal threshold imposed on the queue length in accordance with each channel state.
Selecting the Best Player Formation for Corner-Kick Situations Based on Bayes' Estimation
Venue: arXiv cs.AI 2016
Year: 2016

In the domain of the Soccer simulation 2D league of the RoboCup project, appropriate player positioning against a given opponent team is an important factor of soccer team performance. This work proposes a model which decides the strategy that should be applied regarding a particular opponent team. This task can be realized by applying preliminary a learning phase where the model determines the most effective strategies against clusters of opponent teams. The model determines the best strategies by using sequential Bayes' estimators. As a first trial of the system, the proposed model is used to determine the association of player formations against opponent teams in the particular situation of corner-kick. The implemented model shows satisfying abilities to compare player formations that are similar to each other in terms of performance and determines the right ranking even by running a decent number of simulation games.
The belief noisy-or model applied to network reliability analysis
Venue: arXiv cs.AI 2016
Year: 2016

One difficulty faced in knowledge engineering for Bayesian Network (BN) is the quan-tification step where the Conditional Probability Tables (CPTs) are determined. The number of parameters included in CPTs increases exponentially with the number of parent variables. The most common solution is the application of the so-called canonical gates. The Noisy-OR (NOR) gate, which takes advantage of the independence of causal interactions, provides a logarithmic reduction of the number of parameters required to specify a CPT. In this paper, an extension of NOR model based on the theory of belief functions, named Belief Noisy-OR (BNOR), is proposed. BNOR is capable of dealing with both aleatory and epistemic uncertainty of the network. Compared with NOR, more rich information which is of great value for making decisions can be got when the available knowledge is uncertain. Specially, when there is no epistemic uncertainty, BNOR degrades into NOR. Additionally, different structures of BNOR are presented in this paper in order to meet various needs of engineers. The application of BNOR model on the reliability evaluation problem of networked systems demonstrates its effectiveness.
Investigating the Impacts of Recommendation Agents on Impulsive Purchase Behaviour
Venue: arXiv cs.CY 2016
Year: 2016

The usage of recommendation agents (RAs) in the online marketplace can help consumers to locate their desired products. RAs can help consumers effectively obtain comprehensive product information and compare their candidate target products. As a result, RAs have affected consumers shopping behaviour. In this study, we investigate the usage and the influence of RAs in the online marketplace. Based on the Stimulus-Organism-Response (SOR) model, we propose that the stimulus of using RAs (informativeness, product search effectiveness and the lack of sociality stress) can affect consumers attitude (perceived control and satisfaction), which further affects their behavioural outcomes like impulsive purchase. We validate this research model with survey data from 157 users of RAs. The data largely support the proposed model and indicate that the RAs can significantly contribute to impulsive purchase behaviour in online marketplaces. Theoretical and practical contributions are discussed.
Towards an Understanding of Valence in E-Government Services
Venue: arXiv cs.CY 2016
Year: 2016

The Australian government, to remind job seekers of appointments with employment services providers in order to cut costs and free up human resources, is using technologies such as Short Messaging Services (SMS). However, the technologies in-use are but one side of this equation the specifics of how these technologies are used is the other side, and these specifics are highly under-theorized, particularly in regard to the views of the people to which these technologies are directed. The purpose of this paper is to provide a theoretical framing for this phenomenon as well as to introduce an emerging methodological direction that may allow for a better understanding of demographic-specific values and thereby better valence framing. The paper also theorizes reactions to information that could be applicable elsewhere, not just in e-government or with SMS, thereby contributing to discussions surrounding the Big Data debate.
The Lived User Experience of Virtual Environments: Initial Steps of a Phenomenological Analysis in a Safety Training Setting
Venue: arXiv cs.CY 2016
Year: 2016

Virtual environments (VEs) are making their way into various sectors of life to enhance and support human activity, including learning. VEs have been used in various contexts for training, and in many cases they are designed to model or simulate - as accurately and authentically as possible - a specific work context. In striving for authenticity, visual and representative realism tends to receive most of the development input, despite of several studies that challenge its importance. New training avenues have raised the importance of rigorous phenomenological descriptions for a deeper understanding of user experience in the actual context of use. This paper reports the preliminary steps in a phenomenological analysis of how employees working in actual hazardous settings experience virtual safety training environments. Such open-ended research project can reveal new aspects of user experience that can advice the development and evaluation of human-computer interaction in digital technology-enhanced training contexts.
Investigation of Audience Interaction Tools from the Perspective of Activity Theory
Venue: arXiv cs.CY 2016
Year: 2016

Maintaining engagement of large audiences is not easy. Traditionally, lectures and presentations rely on one-way communication from the presenter to the listening audience. Without receiving ongoing feedback, speakers cannot be sure that their delivery is at an appropriate pace, or that their message is being received and understood by their audience. This study suggests using a real-time audience engagement solution (Xorro-Q) to facilitate synchronous interaction between lecturers and their student audiences. Using activity theory as a theoretical framework we conducted a study to investigate student participation and engagement with an audience interaction tool in two undergraduate computing courses. In one classroom setting, discussion questions are raised during the class and instant feedback provided to students. In the second setting, subject related questions were asked near the end of the lecture to gauge students knowledge of concepts just taught in the class. In this study quantitative data such as attendance, response rates, and assessment outcomes were collected to explore how participant engagement varies across different lecturing techniques. Findings from the study show that continuous use of audience interaction tools through activity theory based settings is preferred than merely using tools for assessment purpose in traditional classroom settings. Although these findings are at a very initial stage, they give some indication on how real-time audience engagement tools can be developed within classroom settings for assisting in teaching and learning practices.
Effective Multi-Robot Spatial Task Allocation using Model Approximations
Venue: arXiv cs.AI 2016
Year: 2016

Real-world multi-agent planning problems cannot be solved using decision-theoretic planning methods due to the exponential complexity. We approximate firefighting in rescue simulation as a spatially distributed task and model with multi-agent Markov decision process. We use recent approximation methods for spatial task problems to reduce the model complexity. Our approximations are single-agent, static task, shortest path pruning, dynamic planning horizon, and task clustering. We create scenarios from RoboCup Rescue Simulation maps and evaluate our methods on these graph worlds. The results show that our approach is faster and better than comparable methods and has negligible performance loss compared to the optimal policy. We also show that our method has a similar performance as DCOP methods on example RCRS scenarios.
Leveraging ERP Implementation to Create Intellectual Capital: the Role of Organizational Learning Capability
Venue: arXiv cs.OH 2016
Year: 2016

The extent to which enterprise resource planning (ERP) systems deliver value for organizations has been debated. In this study, we argue that the presence of appropriate organizational resources is essential for capturing the potential of ERP implementation. We investigate the relationship between ERP implementation and two organizational resources, specifically, Intellectual Capital (IC) and Organizational Learning Capability (OLC) to enrich the understanding of the way the value of ERP implementations can be realized. A sample of 226 manufacturing firms in Vietnam was surveyed to test the theoretical model. Structural equation modelling with partial least square method and two approaches for moderation analysis were used to analyze the data. The results indicate that ERP implementation scope has a positive impact on intellectual capital (IC). However, firms need to build a certain level of OLC to utilize ERP implementation for the enhancement of IC.
The Use of ICT to preserve Australian Indigenous Culture and Language - a Preliminary Proposal using the Activity Theory Framework
Venue: arXiv cs.CY 2016
Year: 2016

Propinquity between Australian Indigenous communities' social structures and ICT purposed for cultural preservation is a modern area of research; historically hindered by the "digital divide" thus limiting plentiful literature and existing information systems in this field in theoretical and practical applications. Henceforth, community consultation is mandatory in deriving and delivering empirically effective processes in a cultural and language preservation IS tool designed to teach future generations of Indigenous Australians about native culture and language. More than 100 out of 250 languages spoken by Indigenous have become extinct since 1788 (Harrington, 2014) which inaugurates the urgency of this preservation tool. ICT has been identified as the best provision method; by its capacity to best collect, eternize and teach cultural knowledge and language. The aim of this research is to specify requirements and considerations for the development of a socially integrated, culturally conscious, end-user driven IS to preserve Indigenous culture in Australia.
Information Technology Platforms: Definition and Research Directions
Venue: arXiv cs.CY 2016
Year: 2016

The concept of an information technology (IT) related platform is broad and covers phenomena ranging from the operating system Linux to the Internet. Such platforms are of increasing importance to innovation and value creation across many facets of industry and daily life. There is, however, a lack of common understanding in both research and industry about what is mean by the term platform when related to IT. This lack of consensus is detrimental to research and knowledge development. Thus, the aims of this study are to: (i) provide a sound definition of the IT-platform concept by identifying its distinguishing dimensions; and (ii) identify important current research directions for the IT-platform concept. To achieve these aims a systematic literature review was undertaken with 133 relevant articles taken from major information systems journals, conferences, and business publications. The study contributes by providing a sound base for future research into IT-platforms.
Fast and Provable Algorithms for Spectrally Sparse Signal Reconstruction via Low-Rank Hankel Matrix Completion
Venue: arXiv cs.IT 2016
Year: 2016

A spectrally sparse signal of order $r$ is a mixture of $r$ damped or undamped complex sinusoids. This paper investigates the problem of reconstructing spectrally sparse signals from a random subset of $n$ regular time domain samples, which can be reformulated as a low rank Hankel matrix completion problem. We introduce an iterative hard thresholding (IHT) algorithm and a fast iterative hard thresholding (FIHT) algorithm for efficient reconstruction of spectrally sparse signals via low rank Hankel matrix completion. Theoretical recovery guarantees have been established for FIHT, showing that $O(r^2\log^2(n))$ number of samples are sufficient for exact recovery with high probability. Empirical performance comparisons establish significant computational advantages for IHT and FIHT. In particular, numerical simulations on $3$D arrays demonstrate the capability of FIHT on handling large and high-dimensional real data.