OpenRaiser/Intern-Atlas huggingface dataset:
Caching Meets Millimeter Wave Communications for Enhanced Mobility Management in 5G Networks
Venue: arXiv cs.GT 2017
Year: 2017

One of the most promising approaches to overcome the uncertainty and dynamic channel variations of millimeter wave (mmW) communications is to deploy dual-mode base stations that integrate both mmW and microwave ($μ$W) frequencies. If properly designed, such dual-mode base stations can enhance mobility and handover in highly mobile wireless environments. In this paper, a novel approach for analyzing and managing mobility in joint $μ$W-mmW networks is proposed. The proposed approach leverages device-level caching along with the capabilities of dual-mode base stations to minimize handover failures, reduce inter-frequency measurement energy consumption, and provide seamless mobility in emerging dense heterogeneous networks. First, fundamental results on the caching capabilities, including caching probability and cache duration are derived for the proposed dual-mode network scenario. Second, the average achievable rate of caching is derived for mobile users. Third, the proposed cache-enabled mobility management problem is formulated as a dynamic matching game between mobile user equipments (MUEs) and small base stations (SBSs). The goal of this game is to find a distributed handover mechanism that subject to the network constraints on HOFs and limited cache sizes, allows each MUE to choose between executing an HO to a target SBS, being connected to the macrocell base station (MBS), or perform a transparent HO by using the cached content. The formulated matching game allows capturing the dynamics of the mobility management problem caused by HOFs. To solve this dynamic matching problem, a novel algorithm is proposed and its convergence to a two-sided dynamically stable HO policy is proved. Numerical results corroborate the analytical derivations and show that the proposed solution will provides significant reductions in both the HOF and energy consumption by MUEs.
Comparison of the Efficiency of Different Algorithms on Recommendation System Design: a Case Study
Venue: arXiv cs.IR 2017
Year: 2017

By the growing trend of online shopping and e-commerce websites, recommendation systems have gained more importance in recent years in order to increase the sales ratios of companies. Different algorithms on recommendation systems are used and every one produce different results. Every algorithm on this area have positive and negative attributes. The purpose of the research is to test the different algorithms for choosing the best one according as structure of dataset and aims of developers. For this purpose, threshold and k-means based collaborative filtering and content-based filtering algorithms are utilized on the dataset contains 100*73421 matrix length. What are the differences and effects of these different algorithms on the same dataset? What are the challenges of the algorithms? What criteria are more important in order to evaluate a recommendation systems? In the study, we answer these crucial problems with the case study.
Temporal Overdrive Recurrent Neural Network
Venue: arXiv cs.NE 2017
Year: 2017

In this work we present a novel recurrent neural network architecture designed to model systems characterized by multiple characteristic timescales in their dynamics. The proposed network is composed by several recurrent groups of neurons that are trained to separately adapt to each timescale, in order to improve the system identification process. We test our framework on time series prediction tasks and we show some promising, preliminary results achieved on synthetic data. To evaluate the capabilities of our network, we compare the performance with several state-of-the-art recurrent architectures.
Minimization of Visibly Pushdown Automata Using Partial Max-SAT
Venue: arXiv cs.FL 2017
Year: 2017

We consider the problem of state-space reduction for nondeterministic weakly-hierarchical visibly pushdown automata (VPA). VPA recognize a robust and algorithmically tractable fragment of context-free languages that is natural for modeling programs. We define an equivalence relation that is sufficient for language-preserving quotienting of VPA. Our definition allows to merge states that have different behavior, as long as they show the same behavior for reachable equivalent stacks. We encode the existence of such a relation as a Boolean partial maximum satisfiability (PMax-SAT) problem and present an algorithm that quickly finds satisfying assignments. These assignments are sub-optimal solutions to the PMax-SAT problem but can still lead to a significant reduction of states. We integrated our method in the automata-based software verifier Ultimate Automizer and show performance improvements on benchmarks from the software verification competition SV-COMP.
Uplink Interference Reduction in Large Scale Antenna Systems
Venue: arXiv cs.IT 2017
Year: 2017

A massive MIMO system entails a large number (tens or hundreds) of base station antennas serving a much smaller number of terminals. These systems demonstrate large gains in spectral and energy efficiency compared with conventional MIMO technology. As the number of antennas grows, the performance of a massive MIMO system gets limited by the interference caused by pilot contamination. Earlier A. Ashikhmin and T. Marzetta proposed (under the name of Pilot Contamination Precoding) Large Scale Fading Precoding (LSFP) and Decoding (LSFD) based on limited cooperation between base stations. They showed that Zero-Forcing LSFP and LSFD eliminate pilot contamination entirely and lead to an infinite throughput as the number of antennas grows. In this paper, we focus on the uplink and show that even in the case of a finite number of base station antennas, LSFD yields a very large performance gain. In particular, one of our algorithms gives a more than 140 fold increase in the 5% outage data transmission rate! We show that the performance can be improved further by optimizing the transmission powers of the users. Finally, we present decentralized LSFD that requires limited cooperation only between neighboring cells.
Risk-aware dynamic reserve prices of programmatic guarantee in display advertising
Venue: arXiv cs.GT 2017
Year: 2017

Display advertising is an important online advertising type where banner advertisements (shortly ad) on websites are usually measured by how many times they are viewed by online users. There are two major channels to sell ad views. They can be auctioned off in real time or be directly sold through guaranteed contracts in advance. The former is also known as real-time bidding (RTB), in which media buyers come to a common marketplace to compete for a single ad view and this inventory will be allocated to a buyer in milliseconds by an auction model. Unlike RTB, buying and selling guaranteed contracts are not usually programmatic but through private negotiations as advertisers would like to customise their requests and purchase ad views in bulk. In this paper, we propose a simple model that facilitates the automation of direct sales. In our model, a media seller puts future ad views on sale and receives buy requests sequentially over time until the future delivery period. The seller maintains a hidden yet dynamically changing reserve price in order to decide whether to accept a buy request or not. The future supply and demand are assumed to be well estimated and static, and the model's revenue management is using inventory control theory where each computed reverse price is based on the updated supply and demand, and the unsold future ad views will be auctioned off in RTB to the meet the unfulfilled demand. The model has several desirable properties. First, it is not limited to the demand arrival assumption. Second, it will not affect the current equilibrium between RTB and direct sales as there are no posted guaranteed prices. Third, the model uses the expected revenue from RTB as a lower bound for inventory control and we show that a publisher can receive expected total revenue greater than or equal to those from only RTB if she uses the computed dynamic reserves prices for direct sales.
CERES in Propositional Proof Schemata
Venue: arXiv cs.LO 2017
Year: 2017

Cut-elimination is one of the most famous problems in proof theory, and it was defined and solved for first-order sequent calculus by Gentzen in his celebrated Hauptsatz. Ceres is a different cut-elimination algorithm for first- and higher-order classical logic. Ceres was extended to proof schemata, which are templates for usual first-order proofs, with parameters for natural numbers. However, while Ceres is known to be a complete cut-elimination algorithm for first-order logic, it is not clear whether this holds for first-order schemata too: given in input a proof schema with cuts, does Ceres always produce a schema for a cut-free proof? The difficult step is finding and representing an appropriate refutation schema for the characteristic term schema of a proof schema. In this thesis, we progress in solving this problem by restricting Ceres to propositional schemata, which are templates for propositional proofs. By limiting adequately the expressivity of propositional schemata and proof schemata, we aim at providing a version of schematic Ceres which is a complete cut-elimination algorithm for propositional schemata. We focus on one particular step of Ceres: resolution refutation schemata. First, we prove that by naively adapting Ceres for first-order schemata to our case, we end up with an incomplete algorithm. Then, we modify slightly the concept of resolution refutation schema: to refute a clause set, first we bring it to a generic form, and then we use a fixed refutation of that generic clause set. Our variation of schematic Ceres is the first step towards completeness with respect to propositional schemata.
Decoupled Access-Execute on ARM big.LITTLE
Venue: arXiv cs.DC 2017
Year: 2017

Energy-efficiency plays a significant role given the battery lifetime constraints in embedded systems and hand-held devices. In this work we target the ARM big.LITTLE, a heterogeneous platform that is dominant in the mobile and embedded market, which allows code to run transparently on different microarchitectures with individual energy and performance characteristics. It allows to se more energy efficient cores to conserve power during simple tasks and idle times and switch over to faster, more power hungry cores when performance is needed. This proposal explores the power-savings and the performance gains that can be achieved by utilizing the ARM big.LITTLE core in combination with Decoupled Access-Execute (DAE). DAE is a compiler technique that splits code regions into two distinct phases: a memory-bound Access phase and a compute-bound Execute phase. By scheduling the memory-bound phase on the LITTLE core, and the compute-bound phase on the big core, we conserve energy while caching data from main memory and perform computations at maximum performance. Our preliminary findings show that applying DAE on ARM big.LITTLE has potential. By prefetching data in Access we can achieve an IPC improvement of up to 37% in the Execute phase, and manage to shift more than half of the program runtime to the LITTLE core. We also provide insight into advantages and disadvantages of our approach, present preliminary results and discuss potential solutions to overcome locking overhead.
Where do we stand in requirements engineering improvement today? First results from a mapping study
Venue: arXiv cs.SE 2017
Year: 2017

Context: Requirements engineering process improvement (REPI) approaches have gained much attention in research and practice. Goal: So far, there is no comprehensive view on the research in REPI in terms of solutions and current state of reported evidence. We aims to provide an overview on the existing solutions, their underlying principles and their research type facets, i.e. their state of empirical evidence. Method: To this end, we conducted a systematic mapping study of the REPI publication space. Results: This paper reports on the first findings regarding research type facets of the contributions as well as selected methodological principles. We found a strong focus in the existing research on solution proposals for REPI approaches that concentrate on normative assessments and benchmarks of the RE activities rather than on holistic RE improvements according to individual goals of companies. Conclusions: We conclude, so far, that there is a need to broaden the work and to investigate more problem-driven REPI which also targets the improvement of the quality of the underlying RE artefacts, which currently seem out of scope.
T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objects
Venue: arXiv cs.CV 2017
Year: 2017

We introduce T-LESS, a new public dataset for estimating the 6D pose, i.e. translation and rotation, of texture-less rigid objects. The dataset features thirty industry-relevant objects with no significant texture and no discriminative color or reflectance properties. The objects exhibit symmetries and mutual similarities in shape and/or size. Compared to other datasets, a unique property is that some of the objects are parts of others. The dataset includes training and test images that were captured with three synchronized sensors, specifically a structured-light and a time-of-flight RGB-D sensor and a high-resolution RGB camera. There are approximately 39K training and 10K test images from each sensor. Additionally, two types of 3D models are provided for each object, i.e. a manually created CAD model and a semi-automatically reconstructed one. Training images depict individual objects against a black background. Test images originate from twenty test scenes having varying complexity, which increases from simple scenes with several isolated objects to very challenging ones with multiple instances of several objects and with a high amount of clutter and occlusion. The images were captured from a systematically sampled view sphere around the object/scene, and are annotated with accurate ground truth 6D poses of all modeled objects. Initial evaluation results indicate that the state of the art in 6D object pose estimation has ample room for improvement, especially in difficult cases with significant occlusion. The T-LESS dataset is available online at cmp.felk.cvut.cz/t-less.
High Performance Novel Skin Segmentation Algorithm for Images With Complex Background
Venue: arXiv cs.CV 2017
Year: 2017

Skin Segmentation is widely used in biometric applications such as face detection, face recognition, face tracking, and hand gesture recognition. However, several challenges such as nonlinear illumination, equipment effects, personal interferences, ethnicity variations, etc., are involved in detection process that result in the inefficiency of color based methods. Even though many ideas have already been proposed, the problem has not been satisfactorily solved yet. This paper introduces a technique that addresses some limitations of the previous works. The proposed algorithm consists of three main steps including initial seed generation of skin map, Otsu segmentation in color images, and finally a two-stage diffusion. The initial seed of skin pixels is provided based on the idea of ternary image as there are certain pixels in images which are associated to human complexion with very high probability. The Otsu segmentation is performed on several color channels in order to identify homogeneous regions. The result accompanying with the edge map of the image is utilized in two consecutive diffusion steps in order to annex initially unidentified skin pixels to the seed. Both quantitative and qualitative results demonstrate the effectiveness of the proposed system in compare with the state-of-the-art works.
Efficient Feature Matching by Progressive Candidate Search
Venue: arXiv cs.CV 2017
Year: 2017

We present a novel feature matching algorithm that systematically utilizes the geometric properties of features such as position, scale, and orientation, in addition to the conventional descriptor vectors. In challenging scenes with the presence of repetitive patterns or with a large viewpoint change, it is hard to find the correct correspondences using feature descriptors only, since the descriptor distances of the correct matches may not be the least among the candidates due to appearance changes. Assuming that the layout of the nearby features does not changed much, we propose the bidirectional transfer measure to gauge the geometric consistency of a pair of feature correspondences. The feature matching problem is formulated as a Markov random field (MRF) which uses descriptor distances and relative geometric similarities together. The unmatched features are explicitly modeled in the MRF to minimize its negative impact. For speed and stability, instead of solving the MRF on the entire features at once, we start with a small set of confident feature matches, and then progressively search the candidates in nearby features and expand the MRF with them. Experimental comparisons show that the proposed algorithm finds better feature correspondences, i.e. more matches with higher inlier ratio, in many challenging scenes with much lower computational cost than the state-of-the-art algorithms.
Automatic Generation of Typographic Font from a Small Font Subset
Venue: arXiv cs.CV 2017
Year: 2017

This paper addresses the automatic generation of a typographic font from a subset of characters. Specifically, we use a subset of a typographic font to extrapolate additional characters. Consequently, we obtain a complete font containing a number of characters sufficient for daily use. The automated generation of Japanese fonts is in high demand because a Japanese font requires over 1,000 characters. Unfortunately, professional typographers create most fonts, resulting in significant financial and time investments for font generation. The proposed method can be a great aid for font creation because designers do not need to create the majority of the characters for a new font. The proposed method uses strokes from given samples for font generation. The strokes, from which we construct characters, are extracted by exploiting a character skeleton dataset. This study makes three main contributions: a novel method of extracting strokes from characters, which is applicable to both standard fonts and their variations; a fully automated approach for constructing characters; and a selection method for sample characters. We demonstrate our proposed method by generating 2,965 characters in 47 fonts. Objective and subjective evaluations verify that the generated characters are similar to handmade characters.
Age-Optimal Information Updates in Multihop Networks
Venue: arXiv cs.IT 2017
Year: 2017

The problem of reducing the age-of-information has been extensively studied in the single-hop networks. In this paper, we minimize the age-of-information in general multihop networks. If the packet transmission times over the network links are exponentially distributed, we prove that a preemptive Last Generated First Served (LGFS) policy results in smaller age processes at all nodes of the network (in a stochastic ordering sense) than any other causal policy. In addition, for arbitrary general distributions of packet transmission times, the non-preemptive LGFS policy is shown to minimize the age processes at all nodes of the network among all non-preemptive work-conserving policies (again in a stochastic ordering sense). It is surprising that such simple policies can achieve optimality of the joint distribution of the age processes at all nodes even under arbitrary network topologies, as well as arbitrary packet generation and arrival times. These optimality results not only hold for the age processes, but also for any non-decreasing functional of the age processes.
Systematic Mapping Protocol: The impact of using software patterns during requirements engineering activities in real-world settings
Venue: arXiv cs.SE 2017
Year: 2017

This document details the planning phase of a Systematic Mapping Study (SMS). Our goal is to identify the software patterns used during the RE phase, in real-world setting (i.e., in real projects), not in academia (toy projects) and, to understand the impact of their application, in terms of different characteristics, pertaining to the development process as well as the final product. Through a review of the literature published until January 2017, we will investigate what the research community has reported on the application of patterns in the industrial context, the data supporting these claims, the specific patterns employed, the RE activities, the results (positive or negative) and the metrics used to validate these results.
Analysis of Proportional Fair Scheduling Under Bursty On-Off Traffic
Venue: arXiv cs.IT 2017
Year: 2017

Proportional fair scheduling (PFS) has been adopted as a standard solution for fair resource allocation in modern wireless cellular networks. With the emergence of heterogeneous networks with widely varying user loads, it is of great importance to characterize the performance of PFS under bursty traffic, which is the case in most wireless streaming and data transfer services. In this letter, we provide the first analytical solution to the performance of PFS under bursty on-off traffic load. We use the Gaussian approximation model to derive a closed-form expression of the achievable user data rates. In order to further improve the accuracy of our baseline analytical solution for multi-cell networks, we design a hybrid approximation by employing multi-interference analysis. The simulation results verify that our model guarantees extremely low data rate estimation error, which is further insensitive to changes in session duration, traffic load and user density.
A Planning and Control Framework for Humanoid Systems: Robust, Optimal, and Real-time Performance
Venue: arXiv cs.RO 2017
Year: 2017

Humanoid robots are increasingly demanded to operate in interactive and human-surrounded environments while achieving sophisticated locomotion and manipulation tasks. To accomplish these tasks, roboticists unremittingly seek for advanced methods that generate whole-body coordination behaviors and meanwhile fulfill various planning and control objectives. Undoubtedly, these goals pose fundamental challenges to the robotics and control community. To take an incremental step towards reducing the performance gap between theoretical foundations and real implementations, we present a planning and control framework for the humanoid, especially legged robots, for achieving high performance and generating agile motions. A particular concentration is on the robust, optimal and real-time performance. This framework constitutes three hierarchical layers: First, we present a robust optimal phase-space planning framework for dynamic legged locomotion over rough terrain. This framework is a hybrid motion planner incorporating a series of pivotal components. Second, we take a step toward formally synthesizing high-level reactive planners for whole-body locomotion in constrained environments. We formulate a two-player temporal logic game between the contact planner and its possibly-adversarial environment. Third, we propose a distributed control architecture for the latency-prone humanoid robotic systems. A central experimental phenomenon is observed that the stability of high impedance distributed controllers is highly sensitive to damping feedback delay but much less to stiffness feedback delay. We pursue a detailed analysis of the distributed controllers where damping feedback effort is executed in proximity to the control plant, and stiffness feedback effort is implemented in a latency-prone centralized control process.