OpenRaiser/Intern-Atlas huggingface dataset:
An Iterative Transfer Learning Based Ensemble Technique for Automatic Short Answer Grading
Venue: arXiv cs.CL 2016
Year: 2016

Automatic short answer grading (ASAG) techniques are designed to automatically assess short answers to questions in natural language, having a length of a few words to a few sentences. Supervised ASAG techniques have been demonstrated to be effective but suffer from a couple of key practical limitations. They are greatly reliant on instructor provided model answers and need labeled training data in the form of graded student answers for every assessment task. To overcome these, in this paper, we introduce an ASAG technique with two novel features. We propose an iterative technique on an ensemble of (a) a text classifier of student answers and (b) a classifier using numeric features derived from various similarity measures with respect to model answers. Second, we employ canonical correlation analysis based transfer learning on a common feature representation to build the classifier ensemble for questions having no labelled data. The proposed technique handsomely beats all winning supervised entries on the SCIENTSBANK dataset from the Student Response Analysis task of SemEval 2013. Additionally, we demonstrate generalizability and benefits of the proposed technique through evaluation on multiple ASAG datasets from different subject topics and standards.
Authcoin: Validation and Authentication in Decentralized Networks
Venue: arXiv cs.CR 2016
Year: 2016

Authcoin is an alternative approach to the commonly used public key infrastructures such as central authorities and the PGP web of trust. It combines a challenge response-based validation and authentication process for domains, certificates, email accounts and public keys with the advantages of a block chain-based storage system. As a result, Authcoin does not suffer from the downsides of existing solutions and is much more resilient to sybil attacks.
On Covering Codes and Upper Bounds for the Dimension of Simple Games
Venue: arXiv cs.GT 2016
Year: 2016

Consider a situation with $n$ agents or players where some of the players form a coalition with a certain collective objective. Simple games are used to model systems that can decide whether coalitions are successful (winning) or not (losing). A simple game can be viewed as a monotone boolean function. The dimension of a simple game is the smallest positive integer $d$ such that the simple game can be expressed as the intersection of $d$ threshold functions where each threshold function uses a threshold and $n$ weights. Taylor and Zwicker have shown that $d$ is bounded from above by the number of maximal losing coalitions. We present two new upper bounds both containing the Taylor/Zwicker-bound as a special case. The Taylor/Zwicker-bound imply an upper bound of ${n \choose n/2}$. We improve this upper bound significantly by showing constructively that $d$ is bounded from above by the cardinality of any binary covering code with length $n$ and covering radius $1$. This result supplements a recent result where Olsen et al. showed how to construct simple games with dimension $|C|$ for any binary constant weight SECDED code $C$ with length $n$. Our result represents a major step in the attempt to close the dimensionality gap for simple games.
Barcodes for Medical Image Retrieval Using Autoencoded Radon Transform
Venue: arXiv cs.CV 2016
Year: 2016

Using content-based binary codes to tag digital images has emerged as a promising retrieval technology. Recently, Radon barcodes (RBCs) have been introduced as a new binary descriptor for image search. RBCs are generated by binarization of Radon projections and by assembling them into a vector, namely the barcode. A simple local thresholding has been suggested for binarization. In this paper, we put forward the idea of "autoencoded Radon barcodes". Using images in a training dataset, we autoencode Radon projections to perform binarization on outputs of hidden layers. We employed the mini-batch stochastic gradient descent approach for the training. Each hidden layer of the autoencoder can produce a barcode using a threshold determined based on the range of the logistic function used. The compressing capability of autoencoders apparently reduces the redundancies inherent in Radon projections leading to more accurate retrieval results. The IRMA dataset with 14,410 x-ray images is used to validate the performance of the proposed method. The experimental results, containing comparison with RBCs, SURF and BRISK, show that autoencoded Radon barcode (ARBC) has the capacity to capture important information and to learn richer representations resulting in lower retrieval errors for image retrieval measured with the accuracy of the first hit only.
Virtual Micromagnetics: A Framework for Accessible and Reproducible Micromagnetic Simulation
Venue: arXiv cs.OH 2016
Year: 2016

Computational micromagnetics requires numerical solution of partial differential equations to resolve complex interactions in magnetic nanomaterials. The Virtual Micromagnetics project described here provides virtual machine simulation environments to run open-source micromagnetic simulation packages. These environments allow easy access to simulation packages that are often difficult to compile and install, and enable simulations and their data to be shared and stored in a single virtual hard disk file, which encourages reproducible research. Virtual Micromagnetics can be extended to automate the installation of micromagnetic simulation packages on non-virtual machines, and to support closed-source and new open-source simulation packages, including packages from disciplines other than micromagnetics, encouraging reuse. Virtual Micromagnetics is stored in a public GitHub repository under a three-clause Berkeley Software Distribution (BSD) license.
No-Regret Replanning under Uncertainty
Venue: arXiv cs.RO 2016
Year: 2016

This paper explores the problem of path planning under uncertainty. Specifically, we consider online receding horizon based planners that need to operate in a latent environment where the latent information can be modeled via Gaussian Processes. Online path planning in latent environments is challenging since the robot needs to explore the environment to get a more accurate model of latent information for better planning later and also achieves the task as quick as possible. We propose UCB style algorithms that are popular in the bandit settings and show how those analyses can be adapted to the online robotic path planning problems. The proposed algorithm trades-off exploration and exploitation in near-optimal manner and has appealing no-regret properties. We demonstrate the efficacy of the framework on the application of aircraft flight path planning when the winds are partially observed.
Simulating device-to-device communications in OMNeT++ with SimuLTE: scenarios and configurations
Venue: arXiv cs.NI 2016
Year: 2016

SimuLTE is a tool that enables system-level simulations of LTE/LTE-Advanced networks within OMNeT++. It is designed such that it can be plugged within network elements as an additional Network Interface Card (NIC) to those already provided by the INET framework (e.g. Wi-Fi). Recently, device-to-device (D2D) technology has been widely studied by the research community, as a mechanism to allow direct communications between devices of a LTE cellular network. In this work, we present how SimuLTE can be employed to simulate both one-to-one and one-to-many D2D communications, so that the latter can be exploited as a new communication opportunity in several research fields, like vehicular networks, IoT and machine-to-machine (M2M) applications.
Privacy Preserving Distance Computation using Somewhat-trusted Third Parties
Venue: arXiv cs.CR 2016
Year: 2016

A critically important component of most signal processing procedures is that of computing the distance between signals. In multi-party processing applications where these signals belong to different parties, this introduces privacy challenges. The signals may themselves be private, and the parties to the computation may not be willing to expose them. Solutions proposed to the problem in the literature generally invoke homomorphic encryption schemes, secure multi-party computation, or other cryptographic methods which introduce significant computational complexity into the proceedings, often to the point of making more complex computations requiring repeated computations unfeasible. Other solutions invoke third parties, making unrealistic assumptions about their trustworthiness. In this paper we propose an alternate approach, also based on third party computation, but without assuming as much trust in the third party. Individual participants to the computation "secure" their data through a proposed secure hashing scheme with shared keys, prior to sharing it with the third party. The hashing ensures that the third party cannot recover any information about the individual signals or their statistics, either from analysis of individual computations or their long-term aggregate patterns. We provide theoretical proof of these properties and empirical demonstration of the feasibility of the computation.
Extending OMNeT++ Towards a Platform for the Design of Future In-Vehicle Network Architectures
Venue: arXiv cs.NI 2016
Year: 2016

In-vehicle communication technologies are evolving. While today's cars are equipped with fieldbusses to interconnect the various electronic control units, next generation vehicles have timing and bandwidth requirements that exceed the capacities. In particular Advanced Driver Assistance Systems (ADAS) and automated driving using high bandwidth sensors such as cameras, LIDAR or radar will challenge the in-car network. Automotive Ethernet is the most promising candidate to solve the upcoming challenges. But to design and evaluate new protocols, concepts, and architectures suitable analysis tools are required. Especially in the interim period with architectures using automotive Ethernet and legacy fieldbusses together, careful planning and design is of vital importance. Simulation can provide a good understanding of the expectable network metrics in an early development phase. This paper contributes a workflow as well as the required toolchain to evaluate new real-time Ethernet communication architectures using event based simulation in OMNeT++. We introduce a domain specific language (DSL) - the Abstract Network Description Language (ANDL) - to describe and configure the simulation and present the required simulation models for real-time Ethernet and fieldbus technologies such as CAN and FlexRay. We further introduce new analysis tools for special in-vehicle network use-cases and the interaction of the simulation with third-party applications established in the automotive domain.
Geometric Nontermination Arguments
Venue: arXiv cs.LO 2016
Year: 2016

We present a new kind of nontermination argument, called geometric nontermination argument. The geometric nontermination argument is a finite representation of an infinite execution that has the form of a sum of several geometric series. For so-called linear lasso programs we can decide the existence of a geometric nontermination argument using a nonlinear algebraic $\exists$-constraint. We show that a deterministic conjunctive loop program with nonnegative eigenvalues is nonterminating if an only if there exists a geometric nontermination argument. Furthermore, we present an evaluation that demonstrates that our method is feasible in practice.
Babel Routing Protocol for OMNeT++ - More than just a new simulation module for INET framework
Venue: arXiv cs.NI 2016
Year: 2016

Routing and switching capabilities of computer networks seem as the closed environment containing a limited set of deployed protocols, which nobody dares to change. The majority of wired network designs are stuck with OSPF (guaranteeing dynamic routing exchange on network layer) and RSTP (securing loop-free data-link layer topology). Recently, more use-case specific routing protocols, such as Babel, have appeared. These technologies claim to have better characteristic than current industry standards. Babel is a fresh contribution to the family of distance-vector routing protocols, which is gaining its momentum for small double-stack (IPv6 and IPv4) networks. This paper briefly describes Babel behavior and provides details on its implementation in OMNeT++ discrete event simulator.
Lossy Asymptotic Equipartition property for Networked Data Structures
Venue: arXiv cs.IT 2016
Year: 2016

In this article we prove a Generalized Asypmtotic Equipartition Property for Networked Data Structures modelled as coloured random graphs. The main techniques in this article remains large deviation principles for suitably defined empirical measures on coloured random graphs. We apply our main result to a concrete example from the field of Biology.
Distributed Processing of Generalized Graph-Pattern Queries in SPARQL 1.1
Venue: arXiv cs.DB 2016
Year: 2016

We propose an efficient and scalable architecture for processing generalized graph-pattern queries as they are specified by the current W3C recommendation of the SPARQL 1.1 "Query Language" component. Specifically, the class of queries we consider consists of sets of SPARQL triple patterns with labeled property paths. From a relational perspective, this class resolves to conjunctive queries of relational joins with additional graph-reachability predicates. For the scalable, i.e., distributed, processing of this kind of queries over very large RDF collections, we develop a suitable partitioning and indexing scheme, which allows us to shard the RDF triples over an entire cluster of compute nodes and to process an incoming SPARQL query over all of the relevant graph partitions (and thus compute nodes) in parallel. Unlike most prior works in this field, we specifically aim at the unified optimization and distributed processing of queries consisting of both relational joins and graph-reachability predicates. All communication among the compute nodes is established via a proprietary, asynchronous communication protocol based on the Message Passing Interface.
Online Group-exercises for Older Adults of Different Physical Abilities
Venue: arXiv cs.HC 2016
Year: 2016

In this paper we describe the design and validation of a virtual fitness environment aiming at keeping older adults physically and socially active. We target particularly older adults who are socially more isolated, physically less active, and with less chances of training in a gym. The virtual fitness environment, namely Gymcentral, was designed to enable and motivate older adults to follow personalised exercises from home, with a (heterogeneous) group of remote friends and under the remote supervision of a Coach. We take the training activity as an opportunity to create social interactions, by complementing training features with social instruments. Finally, we report on the feasibility and effectiveness of the virtual environment, as well as its effects on the usage and social interactions, from an intervention study in Trento, Italy
Solving the Wastewater Treatment Plant Problem with SMT
Venue: arXiv cs.AI 2016
Year: 2016

In this paper we introduce the Wastewater Treatment Plant Problem, a real-world scheduling problem, and compare the performance of several tools on it. We show that, for a naive modeling, state-of-the-art SMT solvers outperform other tools ranging from mathematical programming to constraint programming. We use both real and randomly generated benchmarks. From this and similar results, we claim for the convenience of developing compiler front-ends being able to translate from constraint programming languages to the SMT-LIB standard language.
Applications of Data Mining (DM) in Science and Engineering: State of the art and perspectives
Venue: arXiv cs.AI 2016
Year: 2016

The continuous increase in the availability of data of any kind, coupled with the development of networks of high-speed communications, the popularization of cloud computing and the growth of data centers and the emergence of high-performance computing does essential the task to develop techniques that allow more efficient data processing and analyzing of large volumes datasets and extraction of valuable information. In the following pages we will discuss about development of this field in recent decades, and its potential and applicability present in the various branches of scientific research. Also, we try to review briefly the different families of algorithms that are included in data mining research area, its scalability with increasing dimensionality of the input data and how they can be addressed and what behavior different methods in a scenario in which the information is distributed or decentralized processed so as to increment performance optimization in heterogeneous environments.
Stereotypes in Search Engine Results: Understanding The Role of Local and Global Factors
Venue: arXiv cs.CY 2016
Year: 2016

The internet has been blurring the lines between local and global cultures, affecting in different ways the perception of people about themselves and others. In the global context of the internet, search engine platforms are a key mediator between individuals and information. In this paper, we examine the local and global impact of the internet on the formation of female physical attractiveness stereotypes in search engine results. By investigating datasets of images collected from two major search engines in 42 countries, we identify a significant fraction of replicated images. We find that common images are clustered around countries with the same language. We also show that existence of common images among countries is practically eliminated when the queries are limited to local sites. In summary, we show evidence that results from search engines are biased towards the language used to query the system, which leads to certain attractiveness stereotypes that are often quite different from the majority of the female population of the country.
Color: A Crucial Factor for Aesthetic Quality Assessment in a Subjective Dataset of Paintings
Venue: arXiv cs.CV 2016
Year: 2016

Computational aesthetics is an emerging field of research which has attracted different research groups in the last few years. In this field, one of the main approaches to evaluate the aesthetic quality of paintings and photographs is a feature-based approach. Among the different features proposed to reach this goal, color plays an import role. In this paper, we introduce a novel dataset that consists of paintings of Western provenance from 36 well-known painters from the 15th to the 20th century. As a first step and to assess this dataset, using a classifier, we investigate the correlation between the subjective scores and two widely used features that are related to color perception and in different aesthetic quality assessment approaches. Results show a classification rate of up to 73% between the color features and the subjective scores.
From Data to Visualisations and Back: Selecting Visualisations Based on Data and System Design Considerations
Venue: arXiv cs.HC 2016
Year: 2016

Graphical interfaces and interactive visualisations are typical mediators between human users and data analytics systems. HCI researchers and developers have to be able to understand both human needs and back-end data analytics. Participants of our tutorial will learn how visualisation and interface design can be combined with data analytics to provide better visualisations. In the first of three parts, the participants will learn about visualisations and how to appropriately select them. In the second part, restrictions and opportunities associated with different data analytics systems will be discussed. In the final part, the participants will have the opportunity to develop visualisations and interface designs under given scenarios of data and system settings.
Minimizing Total Busy Time with Application to Energy-efficient Scheduling of Virtual Machines in IaaS clouds
Venue: arXiv cs.DC 2016
Year: 2016

Infrastructure-as-a-Service (IaaS) clouds have become more popular enabling users to run applications under virtual machines. Energy efficiency for IaaS clouds is still challenge. This paper investigates the energy-efficient scheduling problems of virtual machines (VMs) onto physical machines (PMs) in IaaS clouds along characteristics: multiple resources, fixed intervals and non-preemption of virtual machines. The scheduling problems are NP-hard. Most of existing works on VM placement reduce the total energy consumption by using the minimum number of active physical machines. There, however, are cases using the minimum number of physical machines results in longer the total busy time of the physical machines. For the scheduling problems, minimizing the total energy consumption of all physical machines is equivalent to minimizing total busy time of all physical machines. In this paper, we propose an scheduling algorithm, denoted as EMinTRE-LFT, for minimizing the total energy consumption of physical machines in the scheduling problems. Our extensive simulations using parallel workload models in Parallel Workload Archive show that the proposed algorithm has the least total energy consumption compared to the state-of-the art algorithms.
Toward a Science of Autonomy for Physical Systems: Defense
Venue: arXiv cs.CY 2016
Year: 2016

Militaries around the world have long been cognizant of the potential benefits associated with autonomous systems both in the conduct of warfare and in its prevention. This has lead to the declaration by some that this technology will lead to a fundamental change in the ways in which war is conducted, i.e., a revolution in military affairs (RMA) not unlike gunpowder, the long bow, the rifled bullet, the aircraft carrier, etc. Indeed the United States has created roadmaps for robotics with ever-increasing autonomous capability that span almost 40 years. These systems span air, sea, sea surface, littoral, ground and subterranean environments. There are serious societal and ethical concerns associated with the deployment of this technology that remain unaddressed. How can sufficient protection be afforded noncombatants? What about civilian blowback, where this technology may end up being used in policing operations against domestic groups? How can we protect the fundamental human rights of all involved? Considerable discussion is being conducted at an international level, including at the United Nations Convention on Certain Conventional Weapons (CCW) over the past two years, debating if and how such systems, particularly lethal platforms should be banned or regulated.
Generalized Fano and non-Fano networks
Venue: arXiv cs.IT 2016
Year: 2016

It is known that the Fano network has a vector linear solution if and only if the characteristic of the finite field is $2$; and the non-Fano network has a vector linear solution if and only if the characteristic of the finite field is not $2$. Using these properties of Fano and non-Fano networks it has been shown that linear network coding is insufficient. In this paper we generalize the properties of Fano and non-Fano networks. Specifically, by adding more nodes and edges to the Fano network, we construct a network which has a vector linear solution for any vector dimension if and only if the characteristic of the finite field belongs to an arbitrary given set of primes $\{p_1,p_2,\ldots,p_l\}$. Similarly, by adding more nodes and edges to the non-Fano network, we construct a network which has a vector linear solution for any vector dimension if and only if the characteristic of the finite field does not belong to an arbitrary given set of primes $\{p_1,p_2,\ldots,p_l\}$.