OpenRaiser/Intern-Atlas huggingface dataset:
Index and Materialized View Selection in Data Warehouses
Venue: arXiv cs.DB 2017
Year: 2017

The aim of this article is to present an overview of the major families of state-of-the-art index and materialized view selection methods, and to discuss the issues and future trends in data warehouse performance optimization. We particularly focus on data mining-based heuristics we developed to reduce the selection problem complexity and target the most pertinent candidate indexes and materialized views.
An Enhanced Lumped Element Electrical Model of a Double Barrier Memristive Device
Venue: arXiv cs.ET 2017
Year: 2017

The massive parallel approach of neuromorphic circuits leads to effective methods for solving complex problems. It has turned out that resistive switching devices with a continuous resistance range are potential candidates for such applications. These devices are memristive systems - nonlinear resistors with memory. They are fabricated in nanotechnology and hence parameter spread during fabrication may aggravate reproducible analyses. This issue makes simulation models of memristive devices worthwhile. Kinetic Monte-Carlo simulations based on a distributed model of the device can be used to understand the underlying physical and chemical phenomena. However, such simulations are very time-consuming and neither convenient for investigations of whole circuits nor for real-time applications, e.g. emulation purposes. Instead, a concentrated model of the device can be used for both fast simulations and real-time applications, respectively. We introduce an enhanced electrical model of a valence change mechanism (VCM) based double barrier memristive device (DBMD) with a continuous resistance range. This device consists of an ultra-thin memristive layer sandwiched between a tunnel barrier and a Schottky-contact. The introduced model leads to very fast simulations by using usual circuit simulation tools while maintaining physically meaningful parameters. Kinetic Monte-Carlo simulations based on a distributed model and experimental data have been utilized as references to verify the concentrated model.
Model-Free Control of Thermostatically Controlled Loads Connected to a District Heating Network
Venue: arXiv cs.SY 2017
Year: 2017

Optimal control of thermostatically controlled loads connected to a district heating network is considered a sequential decision- making problem under uncertainty. The practicality of a direct model-based approach is compromised by two challenges, namely scalability due to the large dimensionality of the problem and the system identification required to identify an accurate model. To help in mitigating these problems, this paper leverages on recent developments in reinforcement learning in combination with a market-based multi-agent system to obtain a scalable solution that obtains a significant performance improvement in a practical learning time. The control approach is applied on a scenario comprising 100 thermostatically controlled loads connected to a radial district heating network supplied by a central combined heat and power plant. Both for an energy arbitrage and a peak shaving objective, the control approach requires 60 days to obtain a performance within 65% of a theoretical lower bound on the cost.
MON: Mission-optimized Overlay Networks
Venue: arXiv cs.NI 2017
Year: 2017

Large organizations often have users in multiple sites which are connected over the Internet. Since resources are limited, communication between these sites needs to be carefully orchestrated for the most benefit to the organization. We present a Mission-optimized Overlay Network (MON), a hybrid overlay network architecture for maximizing utility to the organization. We combine an offline and an online system to solve non-concave utility maximization problems. The offline tier, the Predictive Flow Optimizer (PFO), creates plans for routing traffic using a model of network conditions. The online tier, MONtra, is aware of the precise local network conditions and is able to react quickly to problems within the network. Either tier alone is insufficient. The PFO may take too long to react to network changes. MONtra only has local information and cannot optimize non-concave mission utilities. However, by combining the two systems, MON is robust and achieves near-optimal utility under a wide range of network conditions. While best-effort overlay networks are well studied, our work is the first to design overlays that are optimized for mission utility.
Faster Discovery of Faster System Configurations with Spectral Learning
Venue: arXiv cs.SE 2017
Year: 2017

Despite the huge spread and economical importance of configurable software systems, there is unsatisfactory support in utilizing the full potential of these systems with respect to finding performance-optimal configurations. Prior work on predicting the performance of software configurations suffered from either (a) requiring far too many sample configurations or (b) large variances in their predictions. Both these problems can be avoided using the WHAT spectral learner. WHAT's innovation is the use of the spectrum (eigenvalues) of the distance matrix between the configurations of a configurable software system, to perform dimensionality reduction. Within that reduced configuration space, many closely associated configurations can be studied by executing only a few sample configurations. For the subject systems studied here, a few dozen samples yield accurate and stable predictors - less than 10% prediction error, with a standard deviation of less than 2%. When compared to the state of the art, WHAT (a) requires 2 to 10 times fewer samples to achieve similar prediction accuracies, and (b) its predictions are more stable (i.e., have lower standard deviation). Furthermore, we demonstrate that predictive models generated by WHAT can be used by optimizers to discover system configurations that closely approach the optimal performance.
The Hybrid k-Deck Problem: Reconstructing Sequences from Short and Long Traces
Venue: arXiv cs.IT 2017
Year: 2017

We introduce a new variant of the $k$-deck problem, which in its traditional formulation asks for determining the smallest $k$ that allows one to reconstruct any binary sequence of length $n$ from the multiset of its $k$-length subsequences. In our version of the problem, termed the hybrid k-deck problem, one is given a certain number of special subsequences of the sequence of length $n - t$, $t > 0$, and the question of interest is to determine the smallest value of $k$ such that the $k$-deck, along with the subsequences, allows for reconstructing the original sequence in an error-free manner. We first consider the case that one is given a single subsequence of the sequence of length $n - t$, obtained by deleting zeros only, and seek the value of $k$ that allows for hybrid reconstruction. We prove that in this case, $k \in [\log t+2, \min\{ t+1, O(\sqrt{n \cdot (1+\log t)}) \} ]$. We then proceed to extend the single-subsequence setup to the case where one is given $M$ subsequences of length $n - t$ obtained by deleting zeroes only. In this case, we first aggregate the asymmetric traces and then invoke the single-trace results. The analysis and problem at hand are motivated by nanopore sequencing problems for DNA-based data storage.
Effective Analysis of C Programs by Rewriting Variability
Venue: arXiv cs.PL 2017
Year: 2017

Context. Variability-intensive programs (program families) appear in many application areas and for many reasons today. Different family members, called variants, are derived by switching statically configurable options (features) on and off, while reuse of the common code is maximized. Inquiry. Verification of program families is challenging since the number of variants is exponential in the number of features. Existing single-program analysis and verification tools cannot be applied directly to program families, and designing and implementing the corresponding variability-aware versions is tedious and laborious. Approach. In this work, we propose a range of variability-related transformations for translating program families into single programs by replacing compile-time variability with run-time variability (non-determinism). The obtained transformed programs can be subsequently analyzed using the conventional off- the-shelf single-program analysis tools such as type checkers, symbolic executors, model checkers, and static analyzers. Knowledge. Our variability-related transformations are outcome-preserving, which means that the relation between the outcomes in the transformed single program and the union of outcomes of all variants derived from the original program family is equality. Grounding. We show our transformation rules and their correctness with respect to a minimal core imperative language IMP. Then, we discuss our experience of implementing and using the transformations for efficient and effective analysis and verification of real-world C program families. Importance. We report some interesting variability-related bugs that we discovered using various state-of-the-art single-program C verification tools, such as Frama-C, Clang, LLBMC.
Image-Grounded Conversations: Multimodal Context for Natural Question and Response Generation
Venue: arXiv cs.CL 2017
Year: 2017

The popularity of image sharing on social media and the engagement it creates between users reflects the important role that visual context plays in everyday conversations. We present a novel task, Image-Grounded Conversations (IGC), in which natural-sounding conversations are generated about a shared image. To benchmark progress, we introduce a new multiple-reference dataset of crowd-sourced, event-centric conversations on images. IGC falls on the continuum between chit-chat and goal-directed conversation models, where visual grounding constrains the topic of conversation to event-driven utterances. Experiments with models trained on social media data show that the combination of visual and textual context enhances the quality of generated conversational turns. In human evaluation, the gap between human performance and that of both neural and retrieval architectures suggests that multi-modal IGC presents an interesting challenge for dialogue research.
Detection of Face using Viola Jones and Recognition using Back Propagation Neural Network
Venue: arXiv cs.CV 2017
Year: 2017

Detection and recognition of the facial images of people is an intricate problem which has garnered much attention during recent years due to its ever increasing applications in numerous fields. It continues to pose a challenge in finding a robust solution to it. Its scope extends to catering the security, commercial and law enforcement applications. Research for moreover a decade on this subject has brought about remarkable development with the modus operandi like human computer interaction, biometric analysis and content based coding of images, videos and surveillance. A trivial task for brain but cumbersome to be imitated artificially. The commonalities in faces does pose a problem on various grounds but features such as skin color, gender differentiate a person from the other. In this paper the facial detection has been carried out using Viola-Jones algorithm and recognition of face has been done using Back Propagation Neural Network (BPNN).
A proof of Hilbert's theorem on ternary quartic forms with the ladder technique
Venue: arXiv cs.SC 2017
Year: 2017

This paper proposes a totally constructive approach for the proof of Hilbert's theorem on ternary quartic forms. The main contribution is the ladder technique, with which the Hilbert's theorem is proved vividly.
Pure Rough Mereology and Counting
Venue: arXiv cs.AI 2017
Year: 2017

The study of mereology (parts and wholes) in the context of formal approaches to vagueness can be approached in a number of ways. In the context of rough sets, mereological concepts with a set-theoretic or valuation based ontology acquire complex and diverse behavior. In this research a general rough set framework called granular operator spaces is extended and the nature of parthood in it is explored from a minimally intrusive point of view. This is used to develop counting strategies that help in classifying the framework. The developed methodologies would be useful for drawing involved conclusions about the nature of data (and validity of assumptions about it) from antichains derived from context. The problem addressed is also about whether counting procedures help in confirming that the approximations involved in formation of data are indeed rough approximations?
A Systematic Literature Review on Intertemporal Choice in Software Engineering - Protocol and Results
Venue: arXiv cs.SE 2017
Year: 2017

When making choices in software projects, engineers and other stakeholders engage in decision making that involves uncertain future outcomes. Research in psychology, behavioral economics and neuroscience has questioned many of the classical assumptions of how such decisions are made. This literature review aims to characterize the assumptions that underpin the study of these decisions in Software Engineering. We identify empirical research on this subject and analyze how the role of time has been characterized in the study of decision making in SE. The literature review aims to support the development of descriptive frameworks for empirical studies of intertemporal decision making in practice.
Multilevel Code Construction for Compound Fading Channels
Venue: arXiv cs.IT 2017
Year: 2017

We consider explicit constructions of multi-level lattice codes that universally approach the capacity of the compound block-fading channel. Specifically, building on algebraic partitions of lattices, we show how to construct codes with negligible probability of error for any channel realization and normalized log-density approaching the Poltyrev limit. Capacity analyses and numerical results on the achievable rates for each partition level are provided. The proposed codes have several enjoyable properties such as constructiveness and good decoding complexity, as compared to random one-level codes. Numerical results for finite-dimensional multi-level lattices based on polar codes are exhibited.
Pooling Facial Segments to Face: The Shallow and Deep Ends
Venue: arXiv cs.CV 2017
Year: 2017

Generic face detection algorithms do not perform very well in the mobile domain due to significant presence of occluded and partially visible faces. One promising technique to handle the challenge of partial faces is to design face detectors based on facial segments. In this paper two such face detectors namely, SegFace and DeepSegFace, are proposed that detect the presence of a face given arbitrary combinations of certain face segments. Both methods use proposals from facial segments as input that are found using weak boosted classifiers. SegFace is a shallow and fast algorithm using traditional features, tailored for situations where real time constraints must be satisfied. On the other hand, DeepSegFace is a more powerful algorithm based on a deep convolutional neutral network (DCNN) architecture. DeepSegFace offers certain advantages over other DCNN-based face detectors as it requires relatively little amount of data to train by utilizing a novel data augmentation scheme and is very robust to occlusion by design. Extensive experiments show the superiority of the proposed methods, specially DeepSegFace, over other state-of-the-art face detectors in terms of precision-recall and ROC curve on two mobile face datasets.
Construction of Fixed Rate Non-Binary WOM Codes based on Integer Programming
Venue: arXiv cs.IT 2017
Year: 2017

In this paper, we propose a construction of non-binary WOM (Write-Once-Memory) codes for WOM storages such as flash memories. The WOM codes discussed in this paper are fixed rate WOM codes where messages in a fixed alphabet of size $M$ can be sequentially written in the WOM storage at least $t^*$-times. In this paper, a WOM storage is modeled by a state transition graph. The proposed construction has the following two features. First, it includes a systematic method to determine the encoding regions in the state transition graph. Second, the proposed construction includes a labeling method for states by using integer programming. Several novel WOM codes for $q$ level flash memories with 2 cells are constructed by the proposed construction. They achieve the worst numbers of writes $t^*$ that meet the known upper bound in many cases. In addition, we constructed fixed rate non-binary WOM codes with the capability to reduce ICI (inter cell interference) of flash cells. One of the advantages of the proposed construction is its flexibility. It can be applied to various storage devices, to various dimensions (i.e, number of cells), and various kind of additional constraints.
A Revision of a New Chaos-Based Image Encryption System: Weaknesses and Limitations
Venue: arXiv cs.CR 2017
Year: 2017

Lately, multimedia encryption has been the focus of attention in many researches. Recently, a large number of encryption algorithms has been presented to protect image contents.The main objective of modern image encryption schemes is to reduce the computation complexity in order to respond to the real time multimedia and/or limited resources requirements without degrading the high level of security. In fact, most of the recent solutions are based on the chaotic theory. However, the majority of chaotic systems suffers from different limitations and their implementation is difficult at the hardware level because of the non integer operations that are employed requiring huge resources and latency. In this paper, we analyze the new chaos-based image encryption system presented in~\cite{el2016new}. It uses a static binary diffusion layer, followed by a key dependent bit-permutation layer that only iterates for one round. Based on their results in this paper, we claim that the uniformity and avalanche effect can be reached from the first round. However, we tried to verify the results but our conclusion was that these results were wrong because it was shown that at least 6 iterations are necessary to ensure the required cryptographic performance such as the plain-sensitivity property. Therefore, the required execution time must be multiplied by 6 and consequently this will increase the latency. In addition to all aforementioned problems, we find that ensuring the avalanche effect in the whole image introduces a high error propagation. In order to solve this problem, we recommend to ensure the avalanche effect in the level of blocks instead of the whole image.
On some consequences of the permutation paradigm for data anonymization: centrality of permutation matrices, universal measures of disclosure risk and information loss, evaluation by dominance
Venue: arXiv cs.CR 2017
Year: 2017

Recently, the permutation paradigm has been proposed in data anonymization to describe any micro data masking method as permutation, paving the way for performing meaningful analytical comparisons of methods, something that is difficult currently in statistical disclosure control research. This paper explores some consequences of this paradigm by establishing some class of universal measures of disclosure risk and information loss that can be used for the evaluation and comparison of any method, under any parametrization and independently of the characteristics of the data to be anonymized. These measures lead to the introduction in data anonymization of the concepts of dominance in disclosure risk and information loss, which formalise the fact that different parties involved in micro data transaction can all have different sensitivities to privacy and information.
Interaction semantics and its implications for an interaction oriented architecture of IoT-type applications
Venue: arXiv cs.SE 2017
Year: 2017

Several synergistic trends, subsumed under the phrase "Internet of things (IoT)" massively drive the increasing importance of networking applications. In the past, the exponential growth of the Internet was mainly due to semantically agnostic transport protocols. In the future it is to be expected that, because of the increasing autonomy of technical systems, it becomes necessary to better understand the nature of the semantics of these interaction networks to create appropriate networking applications. Appropriate means that the architecture of these applications allows to minimize the effort to adapt these applications to the permanently changing interaction networks. The proposed interaction oriented architecture is based on a reference model of interaction semantics. It provides guiding principles on how to design networking applications. The reference model of interaction semantics provides: a unifying description of the things in the physical, the information and the human world; an interaction model that is of direct runtime relevance; an understanding for how hierarchical structured components can cooperate loosely coupled; a concept to determine how much semantics has to be common to enable components of different semantic domains to cooperate loosely coupled; and a data type model. The software reference architecture provides: a definition of software layers; means to express vertical interactions, that is interactions which demarcate a software layer; means to express horizontal interactions, that is, between processes in the same software layer; a definition of a component and how to distinguish it from other entities like systems or objects; and a model how to separate reusable from non-reusable parts of an application's functionality.
User Assistance Characteristics of the USE Model Checking Tool
Venue: arXiv cs.HC 2017
Year: 2017

The Unified Modeling Language (UML) is a widely used general purpose modeling language. Together with the Object Constraint Language (OCL), formal models can be described by defining the structure and behavior with UML and additional OCL constraints. In the development process for formal models, it is important to make sure that these models are (a) correct, i.e. consistent and complete, and (b) testable in the sense that the developer is able to interactively check model properties. The USE tool (UML-based Specification Environment) allows both characteristics to be studied. We demonstrate how the tool supports modelers to analyze, validate and verify UML and OCL models via the use of several graphical means that assist the modeler in interpreting and visualizing formal model descriptions. In particular, we discuss how the so-called USE model validator plugin is integrated into the USE environment in order to allow non domain experts to use it and construct object models that help to verify properties like model consistency.
CNN as Guided Multi-layer RECOS Transform
Venue: arXiv cs.CV 2017
Year: 2017

There is a resurging interest in developing a neural-network-based solution to the supervised machine learning problem. The convolutional neural network (CNN) will be studied in this note. To begin with, we introduce a RECOS transform as a basic building block of CNNs. The "RECOS" is an acronym for "REctified-COrrelations on a Sphere". It consists of two main concepts: 1) data clustering on a sphere and 2) rectification. Afterwards, we interpret a CNN as a network that implements the guided multi-layer RECOS transform with three highlights. First, we compare the traditional single-layer and modern multi-layer signal analysis approaches, point out key ingredients that enable the multi-layer approach, and provide a full explanation to the operating principle of CNNs. Second, we discuss how guidance is provided by labels through backpropagation (BP) in the training. Third, we show that a trained network can be greatly simplified in the testing stage demanding only one-bit representation for both filter weights and inputs.