OpenRaiser/Intern-Atlas huggingface dataset:
Online Budgeted Truthful Matching
Venue: arXiv cs.DS 2016
Year: 2016

An online truthful budgeted matching problem is considered for a bipartite graph, where the right vertices are available ahead of time, and individual left vertices arrive sequentially. On arrival of a left vertex, its edge utilities (or weights) to all the right vertices and a corresponding cost (or bid) are revealed. If a left vertex is matched to any of the right vertices, then it has to be paid at least as much as its cost. The problem is to match each left vertex instantaneously and irrevocably to any one of the right vertices, if at all, to find the maximum weight matching that is truthful, under a payment budget constraint. Truthfulness condition requires that no left vertex has any incentive of misreporting its cost. Assuming that the vertices arrive in an uniformly random order (secretary model) with arbitrary utilities, a truthful algorithm is proposed that is $24β$-competitive (where $β$ is the ratio of the maximum and the minimum utility) and satisfies the payment budget constraint. Direct applications of this problem include crowdsourcing auctions, and matching wireless users to cooperative relays in device-to-device enabled cellular network.
An Extended Symbol Table Infrastructure to Manage the Composition of Output-Specific Generator Information
Venue: arXiv cs.SE 2016
Year: 2016

Code generation is regarded as an essential part of model-driven development (MDD) to systematically transform the abstract models to concrete code. One current challenges of templatebased code generation is that output-specific information, i.e., information about the generated source code, is not explicitly modeled and, thus, not accessible during code generation. Existing approaches try to either parse the generated output or store it in a data structure before writing into a file. In this paper, we propose a first approach to explicitly model parts of the generated output. These modeled parts are stored in a symbol for efficient management. During code generation this information can be accessed to ensure that the composition of the overall generated source code is valid. We achieve this goal by creating a domain model of relevant generator output information, extending the symbol table to store this information, and adapt the overall code generation process.
Spectrally-Precoded OFDM for 5G Wideband Operation in Fragmented sub-6GHz Spectrum
Venue: arXiv cs.IT 2016
Year: 2016

We consider spectrally-precoded OFDM waveforms for 5G wideband transmission in sub-6GHz band. In this densely packed spectrum, a low out-of-band (OOB) waveform is a critical 5G component to achieve the promised high spectral efficiency. By precoding data symbols before OFDM modulation, it is possible to achieve extremely low out-of-band emission with very sharp spectrum transition enabling an efficient and flexible usage of frequency resources. Spectrally-precoded OFDM shows promising results for reaching 5G targets in high-data rate enhanced mobile broadband and ultra-reliable low-latency communications use cases. Spectral precoding is particularly efficient for wideband transmission enabling short-time transmission, which will often require flexible fragmented spectrum usage.
How Fluffy is the Cloud ?: Cloud Intelligence for a Not-For-Profit
Venue: arXiv cs.CY 2016
Year: 2016

Business Intelligence (BI) is becoming more accessible and less expensive with fewer risks through various deployment options available in the Cloud. Cloud computing facilitates the acquisition of custom solutions for not-for-profit (NFP) organisations at affordable and scalable costs on a flexible pay-as-you-go basis. In this paper, we explore the key technical and organisational aspects of BI in the Cloud (Cloud Intelligence) deployment in an Australian NFP whose BI maturity is rising although still low. This organisation aspires to Cloud Intelligence for improved managerial decision making yet the issues surrounding the adoption of Cloud Intelligence are complex, especially where corporate and Cloud governance is concerned. From the findings of the case study, a conceptual framework has been developed and presented which offers a view of how governance could be deployed so that NFPs gain maximum leverage through their adoption of the Cloud.
Implications of managing health related records and relevant information systems within intergovernmental agencies
Venue: arXiv cs.CY 2016
Year: 2016

The implications of intergovernmental agencies may forever change the way in which governments provide common services within a federated Australia. As governments seek to reduce duplication and inconsistencies across state and territory borders, intergovernmental agencies, born out of intergovernmental agreements, without any link to specific state or territory legislation, are challenging managers to develop, new approaches to procurement and implement information systems within this new legal dynamic framework. This paper considers the implications to managing health related records and their IT systems, having common legislative obligations across all Australia jurisdictions, to determine whether these new forms of government allow for the disposal of information, aimed at saving costs, improving the quality of data and reduce litigious risk. The paper also investigates the more general implications for any organisation operating nationally, to data sovereignty and how legislative ownership of records may predetermine how and where intergovernmental agencies can manage information assets.
The Power of Fair Information Practices - A Control Agency Approach
Venue: arXiv cs.CY 2016
Year: 2016

Most companies' new business practices are based on customer data. These practices have raised privacy concerns because of the associated risks. Privacy laws require companies to gain customer consent before using their information, which stands as the biggest roadblock to monetise this asset. Privacy literature suggests that reducing privacy concerns and building trust may increase individuals' intention to authorise the use of personal information. Fair information practices (FIPs) are potential means to achieve this goal. However, there is lack of empirical evidence on the mechanisms through which the FIPs affect privacy concerns and trust. This research argues that FIPs load individuals with control, which has been found to influence privacy concerns and trust level. We will use an experimental design methodology to conduct the study. The results are expected to have both theoretical and managerial implications.
Comparison of 14 different families of classification algorithms on 115 binary datasets
Venue: arXiv cs.LG 2016
Year: 2016

We tested 14 very different classification algorithms (random forest, gradient boosting machines, SVM - linear, polynomial, and RBF - 1-hidden-layer neural nets, extreme learning machines, k-nearest neighbors and a bagging of knn, naive Bayes, learning vector quantization, elastic net logistic regression, sparse linear discriminant analysis, and a boosting of linear classifiers) on 115 real life binary datasets. We followed the Demsar analysis and found that the three best classifiers (random forest, gbm and RBF SVM) are not significantly different from each other. We also discuss that a change of less then 0.0112 in the error rate should be considered as an irrelevant change, and used a Bayesian ANOVA analysis to conclude that with high probability the differences between these three classifiers is not of practical consequence. We also verified the execution time of "standard implementations" of these algorithms and concluded that RBF SVM is the fastest (significantly so) both in training time and in training plus testing time.
MUREN: delivering edge services in joint SDN-SDR multi-radio nodes
Venue: arXiv cs.NI 2016
Year: 2016

To meet the growing local and distributed computing needs, the cloud is now descending to the network edge and sometimes to user equipments. This approach aims at distributing computing, data processing, and networking services closer to the end users. Instead of concentrating data and computation in a small number of large clouds, many edge systems are envisioned to be deployed close to the end users or where computing and intelligent networking can best meet user needs. In this paper, we go further converging such massively distributed computing systems with multiple radio accesses. We propose an architecture called MUREN (Multi-Radio Edge Node) for managing traffic in future mobile edge networks. Our solution is based on the Mobile Edge Cloud (MEC) architecture and its close interaction with Software Defined Networking (SDN), the whole jointly interacting with Software-Defined Radios (SDR). We have implemented our architecture in a proof of concept and tested it with two edge scenarios. Our experiments show that centralizing the intelligence in the MEC allows to guarantee the requirements of the edge services either by adapting the waveform parameters, or through changing the radio interface or even by reconfiguring the applications. More generally, the best decision can be seen as the optimal reaction to the wireless links variations
An EV Charging Scheduling Mechanism to Maximize User Convenience and Cost Efficiency
Venue: arXiv cs.SY 2016
Year: 2016

This paper studies charging scheduling problem of electric vehicles (EVs) in the scale of a microgrid (e.g., a university or town) where a set of charging stations are controlled by a central aggregator. A bi-objective optimization problem is formulated to jointly optimize total charging cost and user convenience. Then, a close-to-optimal online scheduling algorithm is proposed as solution. The algorithm achieves optimal charging cost and is near optimal in terms of user convenience. Moreover, the proposed method applies an efficient load forecasting technique to obtain future load information. The algorithm is assessed through simulation and compared to the previous studies. The results reveal that our method not only improves previous alternative methods in terms of Pareto-optimal solution of the bi-objective optimization problem, but also provides a close approximation for the load forecasting.
Automated Road Traffic Congestion Detection and Alarm Systems: Incorporating V2I communications into ATCSs
Venue: arXiv cs.CR 2016
Year: 2016

In this position paper, we address the problems of automated road congestion detection and alerting systems and their security properties. We review different theoretical adaptive road traffic control approaches, and three widely deployed adaptive traffic control systems (ATCSs), namely, SCATS, SCOOT and InSync. We then discuss some related research questions, and the corresponding possible approaches, as well as the adversary model and potential attack scenarios. Two theoretical concepts of automated road congestion alarm systems (including system architecture, communication protocol, and algorithms) are proposed on top of ATCSs, such as SCATS, SCOOT and InSync, by incorporating secure wireless vehicle-to-infrastructure (V2I) communications. Finally, the security properties of the proposed system have been discussed and analysed using the ProVerif protocol verification tool.
From Mechatronic Components to Industrial Automation Things - An IoT model for cyber-physical manufacturing systems
Venue: arXiv cs.SE 2016
Year: 2016

IoT is considered as one of the key enabling technologies for the fourth industrial revolution, that is known as Industry 4.0. In this paper, we consider the mechatronic component as the lowest level in the system composition hierarchy that tightly integrates mechanics with the electronics and software required to convert the mechanics to intelligent (smart) object offering well defined services to its environment. For this mechatronic component to be integrated in the IoT-based industrial automation environment, a software layer is required on top of it to convert its conventional interface to an IoT compliant one. This layer, that we call IoTwrapper, transforms the conventional mechatronic component to an Industrial Automation Thing (IAT). The IAT is the key element of an IoT model specifically developed in the context of this work for the manufacturing domain. The model is compared to existing IoT models and its main differences are discussed. A model-to-model transformer is presented to automatically transform the legacy mechatronic component to an IAT ready to be integrated in the IoT-based industrial automation environment. The UML4IoT profile is used in the form of a Domain Specific Modeling Language to automate this transformation. A prototype implementation of an Industrial Automation Thing using C and the Contiki operating system demonstrates the effectiveness of the proposed approach.
The complexity of reverse engineering problems for conjunctive queries
Venue: arXiv cs.DB 2016
Year: 2016

Reverse engineering problems for conjunctive queries (CQs), such as query by example (QBE) or definability, take a set of user examples and convert them into an explanatory CQ. Despite their importance, the complexity of these problems is prohibitively high (coNEXPTIME-complete). We isolate their two main sources of complexity and propose relaxations of them that reduce the complexity while having meaningful theoretical interpretations. The first relaxation is based on the idea of using existential pebble games for approximating homomorphism tests. We show that this characterizes QBE/definability for CQs up to treewidth $k$, while reducing the complexity to EXPTIME. As a side result, we obtain that the complexity of the QBE/definability problems for CQs of treewidth $k$ is EXPTIME-complete for each $k \geq 1$. The second relaxation is based on the idea of "desynchronizing" direct products, which characterizes QBE/definability for unions of CQs and reduces the complexity to coNP. The combination of these two relaxations yields tractability for QBE and characterizes it in terms of unions of CQs of treewidth at most $k$. We also study the complexity of these problems for conjunctive regular path queries over graph databases, showing them to be no more difficult than for CQs.
Prefix frequency of lost positions
Venue: arXiv cs.FL 2016
Year: 2016

The concept of "lost positions" is a recently introduced tool for counting the number of runs in words. We investigate the frequency of lost positions in prefixes of words. This leads to an algorithm that allows to show, using an extensive computer search, that the asymptotic density of runs in binary words is less than $183/193\approx 0.9482$.
Enhancing the LexVec Distributed Word Representation Model Using Positional Contexts and External Memory
Venue: arXiv cs.CL 2016
Year: 2016

In this paper we take a state-of-the-art model for distributed word representation that explicitly factorizes the positive pointwise mutual information (PPMI) matrix using window sampling and negative sampling and address two of its shortcomings. We improve syntactic performance by using positional contexts, and solve the need to store the PPMI matrix in memory by working on aggregate data in external memory. The effectiveness of both modifications is shown using word similarity and analogy tasks.
Conforming restricted Delaunay mesh generation for piecewise smooth complexes
Venue: arXiv cs.CG 2016
Year: 2016

A Frontal-Delaunay refinement algorithm for mesh generation in piecewise smooth domains is described. Built using a restricted Delaunay framework, this new algorithm combines a number of novel features, including: (i) an unweighted, conforming restricted Delaunay representation for domains specified as a (non-manifold) collection of piecewise smooth surface patches and curve segments, (ii) a protection strategy for domains containing curve segments that subtend sharply acute angles, and (iii) a new class of off-centre refinement rules designed to achieve high-quality point-placement along embedded curve features. Experimental comparisons show that the new Frontal-Delaunay algorithm outperforms a classical (statically weighted) restricted Delaunay-refinement technique for a number of three-dimensional benchmark problems.
Finding Multiple New Optimal Locations in a Road Network
Venue: arXiv cs.DB 2016
Year: 2016

We study the problem of optimal location querying for location based services in road networks, which aims to find locations for new servers or facilities. The existing optimal solutions on this problem consider only the cases with one new server. When two or more new servers are to be set up, the problem with minmax cost criteria, MinMax, becomes NP-hard. In this work we identify some useful properties about the potential locations for the new servers, from which we derive a novel algorithm for MinMax, and show that it is efficient when the number of new servers is small. When the number of new servers is large, we propose an efficient 3-approximate algorithm. We verify with experiments on real road networks that our solutions are effective and attains significantly better result quality compared to the existing greedy algorithms.
A Conceptual Framework to Assess the Effectiveness of Rubric Tool
Venue: arXiv cs.CY 2016
Year: 2016

Rubrics are being used in a wide variety of disciplines in higher education to evaluate assessments and provide feedback to students. Rubrics are traditionally implemented as paper-based table format to grade assessments and provide feedback. The advancement of technology has integrated Rubric Tool into Learning Management Systems (LMS) like Blackboard to facilitate online marking. In this study, we aim to evaluate the effectiveness of Rubric Tool. We propose an integrated conceptual framework using various theories from extant literature to assess the effectiveness of Rubric Tool. Further, this framework has been applied in an undergraduate course at the Asian campus of an Australian International University. This is a research in progress paper which adds to the literature on integrating information systems theory, learning theory, political philosophy and communication theory to examine the effectiveness of Rubric Tool in student learning.
ICE Buckets: Improved Counter Estimation for Network Measurement
Venue: arXiv cs.NI 2016
Year: 2016

Measurement capabilities are essential for a variety of network applications, such as load balancing, routing, fairness and intrusion detection. These capabilities require large counter arrays in order to monitor the traffic of all network flows. While commodity SRAM memories are capable of operating at line speed, they are too small to accommodate large counter arrays. Previous works suggested estimators, which trade precision for reduced space. However, in order to accurately estimate the largest counter, these methods compromise the accuracy of the smaller counters. In this work, we present a closed form representation of the optimal estimation function. We then introduce Independent Counter Estimation Buckets (ICE-Buckets), a novel algorithm that improves estimation accuracy for all counters. This is achieved by separating the flows to buckets and configuring the optimal estimation function according to each bucket's counter scale. We prove a tighter upper bound on the relative error and demonstrate an accuracy improvement of up to 57 times on real Internet packet traces.
One-dimensional Cutting Stock Problem with Divisible Items
Venue: arXiv cs.OH 2016
Year: 2016

This paper considers the one-dimensional cutting stock problem with divisible items, which is a new problem in the cutting stock literature. The problem exists in steel industries. In the new problem, each item can be divided into smaller pieces, then they can be recombined again by welding. The objective is to minimize both the trim loss and the number of the welds. We present a mathematical model and a dynamic programming based heuristic for the problem. Furthermore, a software, which is based on the proposed heuristic algorithm, is developed to use in MKA company, and its performance is analyzed by solving real-life problems in the steel industry. The computational experiments show the efficiency of the proposed algorithm.
Using Multimedia Presentations to Improve Digital Forensic Understanding: A Pilot Study
Venue: arXiv cs.CY 2016
Year: 2016

Improving employees' understanding of digital forensic technical terms and concepts within an organisation is likely to increase the potential of successful collaboration during a cyber security incident (e.g. data breach) investigation within that organisation. In this paper, we seek to determine whether multimedia presentations, in this case videos, are an effective tool in improving a learner's technical understanding of digital forensic terms and concepts. Using the cognitive theory of multimedia learning as the underlying theoretical lens, we surveyed nine participants from the financial sector who have cyber security-related responsibilities. With the exception of one participant, the study found that the use of multimedia presentations can improve participants' understanding of technical digital forensic terms and concepts. Potential future research questions are also identified.
Antecedents for Successful Collaboration in Requirements Engineering
Venue: arXiv cs.CY 2016
Year: 2016

The main focus of the requirements engineering (RE) literature has been on the technical aspects related to the RE projects. Furthermore, research has mainly focused on the specific methods for collecting the requirements for an information system. To fill this gap, this paper studies the contribution of social factors, such as social ties, knowledge sharing and flexibility, to successful collaboration in RE teams. Data were collected from a successful RE and development project in a public sector company in Finland. The results suggest that human-related issues, such as flexibility and transactive memory, were important for collaborative work in the RE team studied. The paper concludes by discussing the implications for theory and suggesting practical guidelines to enhance collaborative work in RE teams.
Short range networks of wearables for safer mobility in smart cities
Venue: arXiv cs.CY 2016
Year: 2016

Ensuring safe and efficient mobility is a critical issue for smart city operators. Increasing safety not only reduces the likelihood of road injuries and fatalities, but also reduces traffic congestion and disruptions caused by accidents, increasing efficiency. While new vehicles are increasingly equipped with semi-automation, the added costs will initially limit the penetration rate of these systems. An inexpensive way to replace or augment these systems is to create networks of wearables (smart glasses, watches) that exchange positional and path data at a very fast rate between all users, identify collision risks and feedback collision resolution information to all users in an intuitive way through their smart glasses.
Coordination in Categorical Compositional Distributional Semantics
Venue: arXiv cs.CL 2016
Year: 2016

An open problem with categorical compositional distributional semantics is the representation of words that are considered semantically vacuous from a distributional perspective, such as determiners, prepositions, relative pronouns or coordinators. This paper deals with the topic of coordination between identical syntactic types, which accounts for the majority of coordination cases in language. By exploiting the compact closed structure of the underlying category and Frobenius operators canonically induced over the fixed basis of finite-dimensional vector spaces, we provide a morphism as representation of a coordinator tensor, and we show how it lifts from atomic types to compound types. Linguistic intuitions are provided, and the importance of the Frobenius operators as an addition to the compact closed setting with regard to language is discussed.