OpenRaiser/Intern-Atlas huggingface dataset:
The Broadcast Channel with Degraded Message Sets and Unreliable Conference
Venue: arXiv cs.IT 2017
Year: 2017

As demonstrated in many recent studies, cooperation between users can greatly improve the performance of communication systems. Most of the works in the literature present models where all the users are aware of the resources available for cooperation. However, the scenario where cooperation links are sometimes unavailable or that some users cannot be updated whether the cooperation links are present or not, is more realistic in today's dynamic ad-hoc communication systems. In such a case we need coding schemes that exploit the cooperation links if they are present, and can still operate if cooperation is not possible. In this work we study the general broadcast channel model with degraded message sets and cooperation links that may be absent, and derive it's capacity region under such uncertainty conditions.
Polar Coding for Achieving the Capacity of Marginal Channels in Nonbinary-Input Setting
Venue: arXiv cs.IT 2017
Year: 2017

Achieving information-theoretic security using explicit coding scheme in which unlimited computational power for eavesdropper is assumed, is one of the main topics is security consideration. It is shown that polar codes are capacity achieving codes and have a low complexity in encoding and decoding. It has been proven that polar codes reach to secrecy capacity in the binary-input wiretap channels in symmetric settings for which the wiretapper's channel is degraded with respect to the main channel. The first task of this paper is to propose a coding scheme to achieve secrecy capacity in asymmetric nonbinary-input channels while keeping reliability and security conditions satisfied. Our assumption is that the wiretap channel is stochastically degraded with respect to the main channel and message distribution is unspecified. The main idea is to send information set over good channels for Bob and bad channels for Eve and send random symbols for channels that are good for both. In this scheme the frozen vector is defined over all possible choices using polar codes ensemble concept. We proved that there exists a frozen vector for which the coding scheme satisfies reliability and security conditions. It is further shown that uniform distribution of the message is the necessary condition for achieving secrecy capacity.
Reliable Virtual Machine Placement and Routing in Clouds
Venue: arXiv cs.DS 2017
Year: 2017

In current cloud computing systems, when leveraging virtualization technology, the customer's requested data computing or storing service is accommodated by a set of communicated virtual machines (VM) in a scalable and elastic manner. These VMs are placed in one or more server nodes according to the node capacities or failure probabilities. The VM placement availability refers to the probability that at least one set of all customer's requested VMs operates during the requested lifetime. In this paper, we first study the problem of placing at most H groups of k requested VMs on a minimum number of nodes, such that the VM placement availability is no less than $δ$, and that the specified communication delay and connection availability for each VM pair under the same placement group are not violated. We consider this problem with and without Shared-Risk Node Group (SRNG) failures, and prove this problem is NP-hard in both cases. We subsequently propose an exact Integer Nonlinear Program (INLP) and an efficient heuristic to solve this problem. We conduct simulations to compare the proposed algorithms with two existing heuristics in terms of performance. Finally, we study the related reliable routing problem of establishing a connection over at most w link-disjoint paths from a source to a destination, such that the connection availability requirement is satisfied and each path delay is no more than a given value. We devise an exact algorithm and two heuristics to solve this NP-hard problem, and evaluate them via simulations.
INGESTBASE: A Declarative Data Ingestion System
Venue: arXiv cs.DB 2017
Year: 2017

Big data applications have fast arriving data that must be quickly ingested. At the same time, they have specific needs to preprocess and transform the data before it could be put to use. The current practice is to do these preparatory transformations once the data is already ingested, however, this is expensive to run and cumbersome to manage. As a result, there is a need to push data preprocessing down to the ingestion itself. In this paper, we present a declarative data ingestion system, called INGESTBASE, to allow application developers to plan and specify their data ingestion logic in a more systematic manner. We introduce the notion of ingestions plans, analogous to query plans, and present a declarative ingestion language to help developers easily build sophisticated ingestion plans. INGESTBASE provides an extensible ingestion optimizer to rewrite and optimize ingestion plans by applying rules such as operator reordering and pipelining. Finally, the INGESTBASE runtime engine runs the optimized ingestion plan in a distributed and fault-tolerant manner. Later, at query processing time, INGESTBASE supports ingestion-aware data access and interfaces with upstream query processors, such as Hadoop MapReduce and Spark, to post- process the ingested data. We demonstrate through a number of experiments that INGESTBASE: (i) is flexible enough to express a variety of ingestion techniques, (ii) incurs a low ingestion overhead, (iii) provides efficient access to the ingested data, and (iv) has much better performance, up to 6 times, than preparing data as an afterthought, via a query processor.
Strong isomorphism in Marinatto-Weber type quantum games
Venue: arXiv cs.GT 2017
Year: 2017

Our purpose is to focus attention on a new criterion for quantum schemes by bringing together the notions of quantum game and game isomorphism. A quantum game scheme is required to generate the classical game as a special case. Now, given a quantum game scheme and two isomorphic classical games, we additionally require the resulting quantum games to be isomorphic as well. We show how this isomorphism condition influences the players' strategy sets. We are concerned with the Marinatto-Weber type quantum game scheme and the strong isomorphism between games in strategic form.
Perception-based energy functions in seam-cutting
Venue: arXiv cs.CV 2017
Year: 2017

Image stitching is challenging in consumer-level photography, due to alignment difficulties in unconstrained shooting environment. Recent studies show that seam-cutting approaches can effectively relieve artifacts generated by local misalignment. Normally, seam-cutting is described in terms of energy minimization, however, few of existing methods consider human perception in their energy functions, which sometimes causes that a seam with minimum energy is not most invisible in the overlapping region. In this paper, we propose a novel perception-based energy function in the seam-cutting framework, which considers the nonlinearity and the nonuniformity of human perception in energy minimization. Our perception-based approach adopts a sigmoid metric to characterize the perception of color discrimination, and a saliency weight to simulate that human eyes incline to pay more attention to salient objects. In addition, our seam-cutting composition can be easily implemented into other stitching pipelines. Experiments show that our method outperforms the seam-cutting method of the normal energy function, and a user study demonstrates that our composed results are more consistent with human perception.
Bandwidth management VMs live migration in wireless fog computing for 5G networks
Venue: arXiv cs.NI 2017
Year: 2017

Live virtual machine migration aims at enabling the dynamic balanced use of the networking/computing physical resources of virtualized data-centers, so to lead to reduced energy consumption. Here, we analytically characterize, prototype in software and test an optimal bandwidth manager for live migration of VMs in wireless channel. In this paper we present the optimal tunable-complexity bandwidth manager (TCBM) for the QoS live migration of VMs under a wireless channel from smartphone to access point. The goal is the minimization of the migration-induced communication energy under service level agreement (SLA)-induced hard constrains on the total migration time, downtime and overall available bandwidth.
On Optimal Spectrum Access of Cognitive Relay With Finite Packet Buffer
Venue: arXiv cs.IT 2017
Year: 2017

We investigate a cognitive radio system where secondary user (SU) relays primary user (PU) packets using two-phase relaying. SU transmits its own packets with some access probability in relaying phase using time sharing. PU and SU have queues of finite capacity which results in packet loss when the queues are full. Utilizing knowledge of relay queue state, SU aims to maximize its packet throughput while keeping packet loss probability of PU below a threshold. By exploiting structure of the problem, we formulate it as a linear program and find optimal access policy of SU. We also propose low complexity sub-optimal access policies, namely constant probability transmission and step transmission. Numerical results are presented to compare performance of proposed methods and study effect of queue sizes on packet throughput.
On Advisability of Designing Short Length QC-LDPC Codes Using Perfect Difference Families
Venue: arXiv cs.IT 2017
Year: 2017

A simple and general definition of quasi cyclic low density parity check (QC LDPC) codes which are constructed based on circulant permutation matrices (CPM) is proposed. As an special case of this definition, we first represent one type of so called combinatorially designed multiple edge protograph codes. The code construction is mainly based on perfect difference families (PDF) and is called Construction 1. Secondly, using the proposed Construction 1 along with a technique named as column dispersion technique (CDT), we design several types of multiple-edge CPM QC LDPC codes (codes with Construction 2) in a wide range of rates, lengths, girths and minimum distances. Parameters of some of these codes are reported in tables. Also included in this paper are the multiplicities of short simple cycles of length up to 10 in Tanner graph of our constructed codes. Our experimental results for short to moderate length codes show that although minimum distances of codes play an important role in waterfall region, the higher the number of short simple cycles is, the better (sharper) the waterfall is. The performances of many codes such as WiMAX, PEG, array, MacKay, algebraic and combinatorial, and also, symmetrical codes have compared with our constructed codes. Based on our numerical results and regardless of how a code is constructed, those with higher number of short simple cycles and higher minimum distances, have better waterfalls.
Cubical Categories for Higher-Dimensional Parametricity
Venue: arXiv cs.LO 2017
Year: 2017

Reynolds' theory of relational parametricity formalizes parametric polymorphism for System F, thus capturing the idea that polymorphically typed System F programs always map related inputs to related results. This paper shows that Reynolds' theory can be seen as the instantiation at dimension 1 of a theory of relational parametricity for System F that holds at all higher dimensions, including infinite dimension. This theory is formulated in terms of the new notion of a p-dimensional cubical category, which we use to define a p-dimensional parametric model of System F for any p, where p is a natural number or infinity. We show that every p-dimensional parametric model of System F yields a split $λ$ 2-fibration in which types are interpreted as face map- and degeneracy-preserving cubical functors and terms are interpreted as face map- and degeneracy-preserving cubical natural transformations. We demonstrate that our theory is "good" by showing that the PER model of Bainbridge et al. is derivable as another 1-dimensional instance, and that all instances at all dimensions derive higher-dimensional analogues of expected results for parametric models, such as a Graph Lemma and the existence of initial algebras and final coalgebras. Finally, our technical development resolves a number of significant technical issues arising in Ghani et al.'s recent bifibrational treatment of relational parametricity, which allows us to clarify their approach and strengthen their main result. Once clarified, their bifibrational framework, too, can be seen as a 1-dimensional instance of our theory.
A Multichannel Convolutional Neural Network For Cross-language Dialog State Tracking
Venue: arXiv cs.CL 2017
Year: 2017

The fifth Dialog State Tracking Challenge (DSTC5) introduces a new cross-language dialog state tracking scenario, where the participants are asked to build their trackers based on the English training corpus, while evaluating them with the unlabeled Chinese corpus. Although the computer-generated translations for both English and Chinese corpus are provided in the dataset, these translations contain errors and careless use of them can easily hurt the performance of the built trackers. To address this problem, we propose a multichannel Convolutional Neural Networks (CNN) architecture, in which we treat English and Chinese language as different input channels of one single CNN model. In the evaluation of DSTC5, we found that such multichannel architecture can effectively improve the robustness against translation errors. Additionally, our method for DSTC5 is purely machine learning based and requires no prior knowledge about the target language. We consider this a desirable property for building a tracker in the cross-language context, as not every developer will be familiar with both languages.
A Parallel Simulator for Massive Reservoir Models Utilizing Distributed-Memory Parallel Systems
Venue: arXiv cs.CE 2017
Year: 2017

This paper presents our work on developing parallel computational methods for two-phase flow on modern parallel computers, where techniques for linear solvers and nonlinear methods are studied and the standard and inexact Newton methods are investigated. A multi-stage preconditioner for two-phase flow is applied and advanced matrix processing strategies are studied. A local reordering method is developed to speed the solution of linear systems. Numerical experiments show that these computational methods are effective and scalable, and are capable of computing large-scale reservoir simulation problems using thousands of CPU cores on parallel computers. The nonlinear techniques, preconditioner and matrix processing strategies can also be applied to three-phase black oil, compositional and thermal models.
Uniprior Index Coding
Venue: arXiv cs.IT 2017
Year: 2017

The index coding problem is a problem of efficient broadcasting with side-information. We look at the uniprior index coding problem, in which the receivers have disjoint side-information symbols and arbitrary demand sets. Previous work has addressed single uniprior index coding, in which each receiver has a single unique side-information symbol. Modeling the uniprior index coding problem as a \textit{supergraph}, we focus on a class of uniprior problems defined on \textit{generalized cycle} supergraphs. For such problems, we prove upper and lower bounds on the optimal broadcast rate. Using a connection with Eulerian directed graphs, we also show that the upper and lower bounds are equal for a subclass of uniprior problems. We show the NP-hardness of finding the lower bound for uniprior problems on generalized cycles. Finally, we look at a simple extension of the generalized cycle uniprior class for which we give bounds on the optimal rate and show an explicit scheme which achieves the upper bound.
Emotional Qualities of VR Space
Venue: arXiv cs.HC 2017
Year: 2017

The emotional response a person has to a living space is predominantly affected by light, color and texture as space-making elements. In order to verify whether this phenomenon could be replicated in a simulated environment, we conducted a user study in a six-sided projected immersive display that utilized equivalent design attributes of brightness, color and texture in order to assess to which extent the emotional response in a simulated environment is affected by the same parameters affecting real environments. Since emotional response depends upon the context, we evaluated the emotional responses of two groups of users: inactive (passive) and active (performing a typical daily activity). The results from the perceptual study generated data from which design principles for a virtual living space are articulated. Such a space, as an alternative to expensive built dwellings, could potentially support new, minimalist lifestyles of occupants, defined as the neo-nomads, aligned with their work experience in the digital domain through the generation of emotional experiences of spaces. Data from the experiments confirmed the hypothesis that perceivable emotional aspects of real-world spaces could be successfully generated through simulation of design attributes in the virtual space. The subjective response to the virtual space was consistent with corresponding responses from real-world color and brightness emotional perception. Our data could serve the virtual reality (VR) community in its attempt to conceive of further applications of virtual spaces for well-defined activities.
Neurostream: Scalable and Energy Efficient Deep Learning with Smart Memory Cubes
Venue: arXiv cs.AR 2017
Year: 2017

High-performance computing systems are moving towards 2.5D and 3D memory hierarchies, based on High Bandwidth Memory (HBM) and Hybrid Memory Cube (HMC) to mitigate the main memory bottlenecks. This trend is also creating new opportunities to revisit near-memory computation. In this paper, we propose a flexible processor-in-memory (PIM) solution for scalable and energy-efficient execution of deep convolutional networks (ConvNets), one of the fastest-growing workloads for servers and high-end embedded systems. Our codesign approach consists of a network of Smart Memory Cubes (modular extensions to the standard HMC) each augmented with a many-core PIM platform called NeuroCluster. NeuroClusters have a modular design based on NeuroStream coprocessors (for Convolution-intensive computations) and general-purpose RISCV cores. In addition, a DRAM-friendly tiling mechanism and a scalable computation paradigm are presented to efficiently harness this computational capability with a very low programming effort. NeuroCluster occupies only 8% of the total logic-base (LoB) die area in a standard HMC and achieves an average performance of 240 GFLOPS for complete execution of full-featured state-of-the-art (SoA) ConvNets within a power budget of 2.5W. Overall 11 W is consumed in a single SMC device, with 22.5 GFLOPS/W energy-efficiency which is 3.5X better than the best GPU implementations in similar technologies. The minor increase in system-level power and the negligible area increase make our PIM system a cost-effective and energy efficient solution, easily scalable to 955 GFLOPS with a small network of just four SMCs.
Feasibility Study of Social Media for Public Health Behaviour Changes
Venue: arXiv cs.CY 2017
Year: 2017

Social networking sites such as Twitter and Facebook have been shown to function as effective social sensors that can "feel the pulse" of a community. The aim of the current study is to test the feasibility of designing, implementing and evaluating a bespoke social media-enabled intervention that can be effective for sharing and changing knowledge, attitudes and behaviours in meaningful ways to promote public health, specifically with regards to prevention of skin cancer. We present the design and implementation details of the campaign followed by summary findings and analysis.
Low-Complexity Puncturing and Shortening of Polar Codes
Venue: arXiv cs.IT 2017
Year: 2017

In this work, we address the low-complexity construction of shortened and punctured polar codes from a unified view. While several independent puncturing and shortening designs were attempted in the literature, our goal is a unique, low-complexity construction encompassing both techniques in order to achieve any code length and rate. We observe that our solution significantly reduces the construction complexity as compared to state-of-the-art solutions while providing a block error rate performance comparable to constructions that are highly optimized for specific lengths and rates. This makes the constructed polar codes highly suitable for practical application in future communication systems requiring a large set of polar codes with different lengths and rates.
Surgical Data Science: Enabling Next-Generation Surgery
Venue: arXiv cs.CY 2017
Year: 2017

This paper introduces Surgical Data Science as an emerging scientific discipline. Key perspectives are based on discussions during an intensive two-day international interactive workshop that brought together leading researchers working in the related field of computer and robot assisted interventions. Our consensus opinion is that increasing access to large amounts of complex data, at scale, throughout the patient care process, complemented by advances in data science and machine learning techniques, has set the stage for a new generation of analytics that will support decision-making and quality improvement in interventional medicine. In this article, we provide a consensus definition for Surgical Data Science, identify associated challenges and opportunities and provide a roadmap for advancing the field.
Certificate Linking and Caching for Logical Trust
Venue: arXiv cs.CR 2017
Year: 2017

SAFE is a data-centric platform for building multi-domain networked systems, i.e., systems whose participants are controlled by different principals. Participants make trust decisions by issuing local queries over logic content exchanged in certificates. The contribution of SAFE is to address a key barrier to practical use of logical trust: the problem of identifying, gathering, and assembling the certificates that are relevant to each trust decision. SAFE uses a simple linking abstraction to organize and share certificates according to scripted primitives that implement the application's trust kernel and isolate it from logic concerns. We show that trust scripting with logical data exchange yields compact trust cores for example applications: federated naming, nested groups and roles, secure IP prefix delegation and routing, attestation-based access control, and a federated infrastructure-as-a-service system. Linking allows granular control over dynamic logic content based on dependency relationships, enabling a logic server to make secure inferences at high throughput.