bluuebunny/crossref_metadata_2025 huggingface dataset:
Mid-infrared high birefringence As2Se3-based PCF with large nonlinearity and distinctive dispersion by using asymmetric elliptical air hole cladding
Authors: Hui Zhanqiang , Yang Min , Zhang Youkun , Zhang Meizhi
Published: January 2018

A novel high birefringence As2Se3-based hexagonal lattice photonic crystal fiber (PCF) is proposed. In the structure, a central defect core and three kinds of elliptical air holes with different major axes length and ellipticity are introduced in the cladding. The finite difference time domain (FDTD) method with perfectly matched layer (PML) absorption boundary conditions are used to simulate the guided modes of the designed PCF. The properties of this PCF are investigated in detail including the birefringence, beat length, dispersion, nonlinearity and polarization mode dispersion in the 2–5 [Formula: see text] mid-infrared range. The results show that for the optimized structure parameters of [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], the high birefringence of 0.1192 and beat length of 41.93 [Formula: see text] are obtained. The maximum nonlinearity coefficient of 10,050 w[Formula: see text]km[Formula: see text] and 15,200 w[Formula: see text]km[Formula: see text] for x- and y-polarization modes are achieved. The distinctive dispersion is analyzed, which is all-normal in x-polarization direction while it has two zero dispersion points at 3.18 [Formula: see text] and 3.65 [Formula: see text] in y-polarization direction. The designed PCF with high birefringence, large nonlinearity and distinctive dispersion will be beneficial for mid-infrared fiber sensing, mid-infrared spectroscopy and nonlinear optics applications.
Efficient ultrawideband linear polarization conversion metasurface based on Φ-shaped
Authors: Fang Zhenhua , Chen Huan , Song Kun , Luo Chunrong , Zhao Xiaopeng
Published: January 2018

Polarization is a property of transverse waves that specify the geometrical orientation of the oscillations, and it is of significant importance to control the polarization of waves at the information storage and processing. In this paper, we propose a new type of polarization conversion metasurface based on the [Formula: see text]-shaped structure in reflection mode. An ultrawideband cross-polarization conversion is obtained. The simulated results show that this metasurface can rotate the polarized direction of the linearly polarized electromagnetic wave by 90[Formula: see text] and the polarization conversion efficiency reaches up to 90% in the ultrawideband from 6.9 GHz to 22.2 GHz. The relative bandwidth is 105%. In addition, the experimental results of polarization conversion efficiency are in good agreement with the simulations. With the advantages of high conversion efficiency, ultrawide operating band and the simple geometric structure, the application of this polarization conversion metasurface structure can be extended to the frequency range of terahertz or even the visible light.
THE EFFECT OF ELECTROLYTE TEMPERATURE AND SEALING SOLUTION IN ANODIZING OPERATION ON HARDNESS AND WEAR BEHAVIOR OF 7075 -T6 ALUMINUM ALLOY
Authors: NIYAZBAKHSH SAEED , AMINI KAMRAN , GHARAVI FARHAD
Published: January 2018

Anodic oxide coatings are applied on aluminum alloys in order to improve corrosion resistance and to increase hardness and wear resistance. In the current study, a hard anodic coating was applied on AA7075-T6 aluminum alloy. To survey the anodizing temperature (electrolyte temperature) effect, three temperatures, namely, [Formula: see text]C, 0∘C and 5∘C were chosen and the samples were sealed in boiling water and sodium dichromate to study the role of sealing. For measuring the oxide coatings porosity and hardness and also for comparing the samples’ wear resistance field-emission scanning electron microscopy (FESEM), microhardness test and pin-on-disk method were utilized, respectively. The results showed that by increasing the anodizing temperature, hardness and consequently wear resistance decreased so that hardness and weight loss in the samples with no sealing decreased from 460[Formula: see text]HV and 0.61[Formula: see text]mg at [Formula: see text]C to 405 and 358[Formula: see text]HV and 1.05 and 1.12[Formula: see text]mg at 0∘C and 5∘C, respectively, which is due to the porosity increment by increasing the anodizing temperature. Also, sealing in boiling water and dichromate contributed to soft phases and coating hydration, which resulted in a decrease in hardness and wear resistance. Hardness and weight loss in the coated samples at [Formula: see text]C decreased from 460[Formula: see text]HV and 0.61[Formula: see text]mg in the samples with no sealing to 435 and 417[Formula: see text]HV and 0.72 and 0.83[Formula: see text]mg in the samples sealed in boiling water and dichromate, respectively.
PIEZOELECTRIC MATERIAL AND ONE-DIMENSIONAL PHONONIC CRYSTAL
Authors: ALY ARAFA H. , NAGATY AHMED , KHALIFA Z.
Published: January 2018

We have theoretically obtained the transmittance properties of one-dimensional phononic crystals incorporating a piezoelectric material as a defect layer. We have used the transfer matrix method in our analysis with/without defect materials. By increasing the thickness of the defect layer, we obtained a sharp peak created within the bandgap, that indicates to the significance of defect layer thickness on the band structure. The localized modes and a particular intensity estimated within the bandgap depend on the piezoelectric material properties. By applying different quantities of an external electric field, the position of the peak shifts to different frequencies. The electric field induces a relative change in the piezoelectric thickness. Our structure may be very useful in some applications such as sensors, acoustic switches, and energy applications.
Existence of Unique Equilibrium in Cournot Mixed Oligopoly
Authors: Okuguchi Koji , Yamazaki Takeshi
Published: January 2018

The properties of Cournot mixed oligopoly consisting of one public firm and one or more than one private firms have mostly been analyzed for simple cases on the basis of numerical calculations of the equilibrium values for a linear market demand function and linear or quadratic cost functions. In this paper, after proving the existence of a unique equilibrium in Cournot mixed oligopoly under general conditions on the market demand and each firm’s cost function, we derive conditions ensuring the existence of a unique Nash equilibrium for the mixed oligopoly where one public firm and at least one of the private firms are active in a general model of Cournot mixed oligopoly with one public firm and several private firms.
Face liveness detection scheme with static and dynamic features
Authors: Wu Lifang , Xu Yaowen , Jian Meng , Xu Xiao , Qi Wei
Published: January 2018

Face liveness detection is a significant research topic in face-based online authentication. The current face liveness detection approaches utilize either static or dynamic features, but not both. In fact, the dynamic and static features have different advantages in face liveness detection. In this paper, we propose a scheme combining dynamic and static features to capture merits of them for face liveness detection. First, the dynamic maps are captured from the inter-frame motion in the video, which investigates motion information of the face in the video. Then, with a Convolutional Neural Network (CNN), the dynamic and static features are extracted from the dynamic maps and the frame images, respectively. Next, in CNN, the fully connected layers containing the dynamic and static features are concatenated to form a fused feature. Finally, the fused features are used to train a binary Support Vector Machine (SVM) classifier, which classifies the frames into two categories, i.e. frame with real or fake face. Experimental results and the corresponding analysis demonstrate that the proposed scheme is capable of discovering face liveness by fusing dynamic and static features and it outperforms the current state-of-the-art face liveness detection approaches.
Robust and discriminative dictionary learning for face recognition
Authors: Lin Guojun , Yang Meng , Shen Linlin , Yang Mingzhong , Xie Mei
Published: January 2018

For face recognition, conventional dictionary learning (DL) methods have some disadvantages. First, face images of the same person vary with facial expressions and pose, illumination and disguises, so it is hard to obtain a robust dictionary for face recognition. Second, they don’t cover important components (e.g., particularity and disturbance) completely, which limit their performance. In the paper, we propose a novel robust and discriminative DL (RDDL) model. The proposed model uses sample diversities of the same face image to learn a robust dictionary, which includes class-specific dictionary atoms and disturbance dictionary atoms. These atoms can well represent the data from different classes. Discriminative regularizations on the dictionary and the representation coefficients are used to exploit discriminative information, which improves effectively the classification capability of the dictionary. The proposed RDDL is extensively evaluated on benchmark face image databases, and it shows superior performance to many state-of-the-art dictionary learning methods for face recognition.
Accurate landmarking from 3D facial scans by CNN and cascade regression
Authors: Kai Wang , An Jun , Zhao Xi , Zou Jianhua
Published: January 2018

Facial landmarking locates the key facial feature points on facial data, which provides not only information on semantic facial structures, but also prior knowledge for other types of facial analysis. However, most of the existing works still focus on the 2D facial image which is quite sensitive to the lighting condition changes. In order to address this limitation, this paper proposed a coarse-to-fine method only based on the 3D facial scan data extracted from professional equipment to automatically and accurately estimate the landmark localization. Specifically, we firstly trained a convolutional neural network (CNN) to initialize the face landmarks instead of the mean shape. Then the proposed cascade regression networks learn the mapping function between 3D facial geometry feature and landmarks location. Tested on Bosphorus database, the experimental results demonstrated effectiveness and accuracy of the proposed method for [Formula: see text] landmarks. Compared with other methods, the results in several points demonstrate state-of-the-art performance.
A semantic tree method for image classification and video action recognition
Authors: Liu Chongwen , Shang Zhaowei , Lin Bo , Tang Yuan Yan
Published: January 2018

The multi-task learning (MTL) methods consider learning a problem together with other related problems simultaneously. The major challenge of MTL is how to selectively screen the shared information. The information of each task must be related to the others, but when sharing information between two unrelated tasks it degenerates the performance of both tasks. To ensure the related problems are related to the main task is the most important point in MTL. In this paper, we will design a novel algorithm to calculate the degrees of relationship among tasks by using a semantical space of features in each task and then build semantical tree to achieve better learning performance. We propose an MTL method under this algorithm which achieves good experimental performance. Our experiments are taken on both image classification and video action recognition, compared with the state-of-the-art MTL methods. Our method proposes good performance in the four public datasets.
Non-convex clustering via proximal alternating linearized minimization method
Authors: Xie Ting , Chen Feiyu
Published: January 2018

Clustering is a fundamental learning task in a wide range of research fields. The most popular clustering algorithm is arguably the K-means algorithm, it is well known that the performance of K-means algorithm heavily depends on initialization due to its strong non-convexity nature. To overcome the initialization issue, in this paper, we first relax the K-means model as an optimization problem with non-convex constraints, then employ the Proximal Alternating Linearized Minimization (PALM) method to solve the relaxed non-convex optimization model. The convergence analysis of PALM algorithm for the clustering problem is also provided. Experimental results on several benchmark datasets are conducted to evaluate the efficiency of our approach.
Stability of the parabolic Poincaré bundle
Authors: Basu Suratno , Biswas Indranil , Dan Krishanu
Published: January 2018

Given a compact Riemann surface [Formula: see text] and a moduli space [Formula: see text] of parabolic stable bundles on it of fixed determinant of complete parabolic flags, we prove that the Poincaré parabolic bundle on [Formula: see text] is parabolic stable with respect to a natural polarization on [Formula: see text].
Participation in the Water Body Irrigation Management in Saline Zone in West Bengal in India
Authors: Lise Wietze , Jana Sebak Kumar , Manna Siddhartha
Published: January 2018

This study analyzes farmers’ participation in irrigation management for small scale irrigation through water bodies in a saline zone in India. Principal Component Analysis shows that key decision variables of farmers are (i) strength of decision making body, (ii) water body quality and maintenance, (iii) water sharing fairness and (iv) water sufficiency. Regression analysis indicates that the farmers’ participation increases with variables like membership of water users’ association, proximity to the market, possession of agricultural assets, hired labor in the family, higher shares of aman paddy and vegetable crops, existence of fish cultivation. Four non-cooperative participation games were estimated and the results show that sharing of water body irrigation benefits among the farmers is not harmonious.
GALS-HMP
Authors: Salcic Zoran , Malik Avinash
Published: January 2018

We present a new heterogeneous multiprocessor (GALS-HMP) for the execution of Globally Asynchronous Locally Synchronous (GALS) programming languages. It specifically targets SystemJ GALS language, which extends Java with asynchronous and synchronous concurrency. A SystemJ program is partitioned by a compiler onto data-driven and control-driven parts, which are then allocated for the execution on traditional and reactive processors, which constitute GALS-HMP. The reactive processor is customized to meet the requirements of the control parts of the SystemJ programs. The prototypes developed on an FPGA show significant improvements in code size and execution speed compared to the case of using just traditional processors.
A HW/SW co-verification framework for SystemC
Authors: Herber Paula , Glesner Sabine
Published: January 2018

SystemC is widely used for modeling and simulation in hardware/software co-design. However, existing verification techniques are mostly ad-hoc and non-systematic. In this article, we present a systematic, comprehensive, and formally founded co-verification framework for digital HW/SW systems that are modeled in SystemC. The framework is based on a formal semantics of SystemC and uses a combination of model checking and testing, whereby testing includes both the automated generation of timed inputs and automated conformance evaluation. We demonstrate its performance and its error detecting capability with two case studies, namely a packet switch and an anti-slip regulation and anti-lock braking system.
QUKU
Authors: Bergmann Neil W. , Shukla Sunil K. , Becker Jürgen
Published: January 2018

A new architecture, QUKU, is proposed for implementing stream-based algorithms on FPGAs, which combines the advantages of FPGA and Coarse Grain Reconfigurable Arrays (CGRAs). QUKU consists of a dynamically reconfigurable, coarse-grain Processing Element (PE) array with an associated softcore processor providing system support. At a coarse-grain, the PE array can be reconfigured on a cycle-by-cycle basis to change the PE functionality similarly to that in a conventional CGRA. At a fine-grain, the whole FPGA can be reconfigured statically to implement a completely different PE array that serves the target application in a better way. Advantages of the fine-grain reconfiguration include individually customized PEs, adaptable numeric format support and customizable interconnect network. A prototype CAD tool framework is also developed which facilitates programming the QUKU architecture. An example application consisting of two different image detectors is implemented to demonstrate the advantages of QUKU. QUKU provides up to 140 times speedup and 40 times improvement in area-time product compared to an implementation running on an FPGA-based softcore. The area-time product for QUKU is around 16% lower than that of a custom circuit based implementation on the same FPGA. The per-PE customization provides an area-time saving of approximately 31% compared to a homogeneous 4 × 4 array of PEs for the same application. The experimental results demonstrate that a dual layered reconfigurable architecture provides significant potential benefits in terms of flexibility, area and processing efficiency over existing reconfigurable computing architectures for DSP.
Hybrid Optimal Control under Mode Switching Constraints with Applications to Pesticide Scheduling
Authors: Ali Usman , Egerstedt Magnus
Published: January 2018

This paper concerns optimal mode-scheduling in autonomous switched-mode hybrid dynamical systems, where the objective is to minimize a cost-performance functional defined on the state trajectory as a function of the schedule of modes. The controlled variable, namely the modes’ schedule, consists of the sequence of modes and the switchover times between them. We propose a gradient-descent algorithm that adjusts a given mode-schedule by changing multiple modes over time-sets of positive Lebesgue measures, thereby avoiding the inefficiencies inherent in existing techniques that change the modes one at a time. The algorithm is based on steepest descent with Armijo step sizes along Gâteaux differentials of the performance functional with respect to schedule-variations, which yields effective descent at each iteration. Since the space of mode-schedules is infinite dimensional and incomplete, the algorithm’s convergence is proved in the sense of Polak’s framework of optimality functions and minimizing sequences. Simulation results are presented, and possible extensions to problems with dwell-time lower-bound constraints are discussed.
SMT-Based Observer Design for Cyber-Physical Systems under Sensor Attacks
Authors: Shoukry Yasser , Chong Michelle , Wakaiki Masashi , Nuzzo Pierluigi , Sangiovanni-Vincentelli Alberto , Seshia Sanjit A. , Hespanha JOÃo P. , Tabuada Paulo
Published: January 2018

We introduce a scalable observer architecture, which can efficiently estimate the states of a discrete-time linear-time-invariant system whose sensors are manipulated by an attacker, and is robust to measurement noise. Given an upper bound on the number of attacked sensors, we build on previous results on necessary and sufficient conditions for state estimation, and propose a novel Multi-Modal Luenberger (MML) observer based on efficient Satisfiability Modulo Theory (SMT) solving. We present two techniques to reduce the complexity of the estimation problem. As a first strategy, instead of a bank of distinct observers, we use a family of filters sharing a single dynamical equation for the states, but different output equations, to generate estimates corresponding to different subsets of sensors. Such an architecture can reduce the memory usage of the observer from an exponential to a linear function of the number of sensors. We then develop an efficient SMT-based decision procedure that is able to reason about the estimates of the MML observer to detect at runtime which sets of sensors are attack-free, and use them to obtain a correct state estimate. Finally, we discuss two optimization-based algorithms that can efficiently select the observer parameters with the goal of minimizing the sensitivity of the estimates with respect to sensor noise. We provide proofs of convergence for our estimation algorithm and report simulation results to compare its runtime performance with alternative techniques. We show that our algorithm scales well for large systems (including up to 5,000 sensors) for which many previously proposed algorithms are not implementable due to excessive memory and time requirements. Finally, we illustrate the effectiveness of our approach, both in terms of resiliency to attacks and robustness to noise, on the design of large-scale power distribution networks.
Selecting the Transition Speeds of Engine Control Tasks to Optimize the Performance
Authors: Biondi Alessandro , Natale Marco Di , Buttazzo Giorgio C. , Pazzaglia Paolo
Published: January 2018

Engine control applications include functions that need to be executed at specific rotation angles of the crankshaft. The tasks performing these functions are activated at variable rates and are programmed to be adaptive with respect to the rotation speed of the engine to avoid overloading the CPU. Simplified control implementations are used at high speeds; for example, reducing the number of fuel injections or the complexity of the computations. Such different control implementations define execution modes with different execution times for different ranges of the rotation speed. The selection of the switching speeds for the operating modes of such tasks is an optimization problem, consisting in determining the optimal transition speeds that maximize the engine performance while guaranteeing schedulability.

This article presents three methods for tackling such an optimization problem under a set of assumptions about the performance metrics: two heuristics and a branch and bound method that guarantees finding the optimal solution within a given speed granularity. In addition, a simple method to compute a performance upper bound is presented. The approach and the hypothesis are validated using a Simulink model of the engine and the computational tasks, considering the engine efficiency and the production of pollutants (NO
2
) as metrics of interest. Simulation experiments show that the performance of proposed heuristics is quite close to that of the upper bound and the optimum within a finite granularity.
Metamorphic Testing
Authors: Chen Tsong Yueh , Kuo Fei-Ching , Liu Huai , Poon Pak-Lok , Towey Dave , Tse T. H. , Zhou Zhi Quan
Published: January 2018

Metamorphic testing is an approach to both test case generation and test result verification. A central element is a set of metamorphic relations, which are necessary properties of the target function or algorithm in relation to multiple inputs and their expected outputs. Since its first publication, we have witnessed a rapidly increasing body of work examining metamorphic testing from various perspectives, including metamorphic relation identification, test case generation, integration with other software engineering techniques, and the validation and evaluation of software systems. In this article, we review the current research of metamorphic testing and discuss the challenges yet to be addressed. We also present visions for further improvement of metamorphic testing and highlight opportunities for new research.
Exiting the Risk Assessment Maze
Authors: Gritzalis Dimitris , Iseppi Giulia , Mylonas Alexios , Stavrou Vasilis
Published: January 2018

Organizations are exposed to threats that increase the risk factor of their ICT systems. The assurance of their protection is crucial, as their reliance on information technology is a continuing challenge for both security experts and chief executives. As risk assessment could be a necessary process in an organization, one of its deliverables could be utilized in addressing threats and thus facilitate the development of a security strategy. Given the large number of heterogeneous methods and risk assessment tools that exist, comparison criteria can provide better understanding of their options and characteristics and facilitate the selection of a method that best fits an organization's needs. This article aims to address the problem of selecting an appropriate risk assessment method to assess and manage information security risks, by proposing a set of comparison criteria, grouped into four categories. Based upon them, it provides a comparison of the 10 popular risk assessment methods that could be utilized by organizations to determine the method that is more suitable for their needs. Finally, a case study is presented to demonstrate the selection of a method based on the proposed criteria.
Cache-Oblivious Buffer Heap and Cache-Efficient Computation of Shortest Paths in Graphs
Authors: Chowdhury Rezaul A. , Ramachandran Vijaya
Published: January 2018

We present the
buffer heap
, a cache-oblivious priority queue that supports
Delete-Min
,
Delete
, and a hybrid
Insert
/
Decrease-Key
operation in
O
(1/
B
log
2
N
/
M
) amortized block transfers from main memory, where
M
and
B
are the (unknown) cache size and block size, respectively, and
N
is the number of elements in the queue. We introduce the notion of a
slim data structure
that captures the situation when only a limited portion of the cache, which we call a
slim cache
, is available to the data structure to retain data between data structural operations. We show that a buffer heap automatically adapts to such an environment and supports all operations in
O
(1/λ + 1/
B
log
2
N
/λ) amortized block transfers each when the size of the slim cache is λ. Our results provide substantial improvements over known trivial cache performance bounds for cache-oblivious priority queues with
Decrease-Keys
.

Using the buffer heap, we present cache-oblivious implementations of Dijkstra’s algorithm for undirected and directed single-source shortest path (SSSP) problems for graphs with non-negative real edge-weights. On a graph with
n
vertices and
m
edges, our algorithm for the undirected case performs
O
(
n
+
m
/
B
log
2
n
/
M
) block transfers and for the directed case performs
O
((
n
+
m
/
B
) ċ log
2
n
/
B
) block transfers. These results give the first non-trivial cache-oblivious bounds for the SSSP problem on general graphs. For the all-pairs shortest path (APSP) problem on weighted undirected graphs, we incorporate slim buffer heaps into multi-buffer-buffer-heaps and use these to improve the cache-aware cache complexity. We also present a simple cache-oblivious APSP algorithm for unweighted undirected graphs that performs
O
(
mn
/
B
log

M
/
B

n
/
B
) block transfers. This matches the cache-aware bound and is a substantial improvement over the previous cache-oblivious bound for the problem.
Quality Control in Crowdsourcing
Authors: Daniel Florian , Kucherbaev Pavel , Cappiello Cinzia , Benatallah Boualem , Allahbakhsh Mohammad
Published: January 2018

Crowdsourcing enables one to leverage on the intelligence and wisdom of potentially large groups of individuals toward solving problems. Common problems approached with crowdsourcing are labeling images, translating or transcribing text, providing opinions or ideas, and similar—all tasks that computers are not good at or where they may even fail altogether. The introduction of humans into computations and/or everyday work, however, also poses critical, novel challenges in terms of quality control, as the crowd is typically composed of people with unknown and very diverse abilities, skills, interests, personal objectives, and technological resources. This survey studies quality in the context of crowdsourcing along several dimensions, so as to define and characterize it and to understand the current state of the art. Specifically, this survey derives a quality model for crowdsourcing tasks, identifies the methods and techniques that can be used to assess the attributes of the model, and the actions and strategies that help prevent and mitigate quality problems. An analysis of how these features are supported by the state of the art further identifies open issues and informs an outlook on hot future research directions.
Deep Bidirectional Cross-Triplet Embedding for Online Clothing Shopping
Authors: Jiang Shuhui , Wu Yue , Fu Yun
Published: January 2018

In this article, we address the cross-domain (i.e., street and shop) clothing retrieval problem and investigate its real-world applications for online clothing shopping. It is a challenging problem due to the large discrepancy between street and shop domain images. We focus on learning an effective feature-embedding model to generate robust and discriminative feature representation across domains. Existing triplet embedding models achieve promising results by finding an embedding metric in which the distance between negative pairs is larger than the distance between positive pairs plus a margin. However, existing methods do not address the challenges in the cross-domain clothing retrieval scenario sufficiently. First, the intradomain and cross-domain data relationships need to be considered simultaneously. Second, the number of matched and nonmatched cross-domain pairs are unbalanced. To address these challenges, we propose a deep cross-triplet embedding algorithm together with a cross-triplet sampling strategy. The extensive experimental evaluations demonstrate the effectiveness of the proposed algorithms well. Furthermore, we investigate two novel online shopping applications, clothing trying on and accessories recommendation, based on a unified cross-domain clothing retrieval framework.
Augmentation Techniques for Mobile Cloud Computing
Authors: Zhou Bowen , Buyya Rajkumar
Published: January 2018

Despite the rapid growth of hardware capacity and popularity in mobile devices, limited resources in battery and processing capacity still lack the ability to meet increasing mobile users’ demands. Both conventional techniques and emerging approaches are brought together to fill this gap between user demand and mobile devices’ limited capabilities. Recent research has focused on enhancing the performance of mobile devices via augmentation techniques. Augmentation techniques for mobile cloud computing refer to the computing paradigms and solutions to outsource mobile device computation and storage to more powerful computing resources in order to enhance a mobile device’s computing capability and energy efficiency (e.g., code offloading). Adopting augmentation techniques in the heterogeneous and intermittent mobile cloud computing environment creates new challenges for computation management, energy efficiency, and system reliability. In this article, we aim to provide a comprehensive taxonomy and survey of the existing techniques and frameworks for mobile cloud augmentation regarding both computation and storage. Different from the existing taxonomies in this field, we focus on the techniques aspect, following the idea of realizing a complete mobile cloud computing system. The objective of this survey is to provide a guide on what available augmentation techniques can be adopted in mobile cloud computing systems as well as supporting mechanisms such as decision-making and fault tolerance policies for realizing reliable mobile cloud services. We also present a discussion on the open challenges and future research directions in this field.
Access to Data and Number of Iterations
Authors: Ahn Kook Jin , Guha Sudipto
Published: January 2018

In this article, we consider graph algorithms in models of computation where the space usage (random accessible storage, in addition to the read-only input) is sublinear in the number of edges
m
and the access to input is constrained. These questions arise in many natural settings, and in particular in the analysis of streaming algorithms, MapReduce or similar algorithms, or message passing distributed computing that model constrained parallelism with sublinear central processing.

We focus on weighted nonbipartite maximum matching in this article. For any constant
p
> 1, we provide an iterative sampling-based algorithm for computing a (1 − ε)-approximation of the weighted nonbipartite maximum matching that uses
O
(
p
/ε) rounds of sampling, and
O
(
n

1+1/
p

) space. The results extend to
b
-Matching with small changes. This article combines adaptive sketching literature and fast primal-dual algorithms based on relaxed Dantzig-Wolfe decision procedures. Each round of sampling is implemented through linear sketches and can be executed in a single round of streaming or two rounds of MapReduce. The article also proves that nonstandard linear relaxations of a problem, in particular penalty-based formulations, are helpful in reducing the adaptive dependence of the iterations.
Design of a High-Performance GEMM-like Tensor–Tensor Multiplication
Authors: Springer Paul , Bientinesi Paolo
Published: January 2018

We present “GEMM-like Tensor–Tensor multiplication” (GETT), a novel approach for dense tensor contractions that mirrors the design of a high-performance general matrix–matrix multiplication (GEMM). The critical insight behind GETT is the identification of three index sets, involved in the tensor contraction, which enable us to systematically reduce an arbitrary tensor contraction to loops around a highly tuned “macro-kernel.” This macro-kernel operates on suitably prepared (“packed”) sub-tensors that reside in a specified level of the cache hierarchy. In contrast to previous approaches to tensor contractions, GETT exhibits desirable features such as unit-stride memory accesses, cache-awareness, as well as full vectorization, without requiring auxiliary memory. We integrate GETT alongside the so-called Transpose–Transpose-GEMM-Transpose and Loops-over-GEMM approaches into an open source “Tensor Contraction Code Generator.” The performance results for a wide range of tensor contractions suggest that GETT has the potential of becoming the method of choice: While GETT exhibits excellent performance across the board, its effectiveness for bandwidth-bound tensor contractions is especially impressive, outperforming existing approaches by up to 12.4×. More precisely, GETT achieves speedups of up to 1.41× over an equivalent-sized GEMM for bandwidth-bound tensor contractions while attaining up to 91.3% of peak floating-point performance for compute-bound tensor contractions.
Implementing 64-bit Maximally Equidistributed F
2
-Linear Generators with Mersenne Prime Period
Authors: Harase Shin , Kimoto Takamitsu
Published: January 2018

CPUs and operating systems are moving from 32 to 64 bits, and hence it is important to have good pseudorandom number generators designed to fully exploit these word lengths. However, existing 64-bit very long period generators based on linear recurrences modulo 2 are not completely optimized in terms of the equidistribution properties. Here, we develop 64-bit maximally equidistributed pseudorandom number generators that are optimal in this respect and have speeds equivalent to 64-bit Mersenne Twisters. We provide a table of specific parameters with period lengths from 2
607
-1 to 2
44497
-1.
CUMODP
Authors: Haque S. Anisul , Li X. , Mansouri F. , Maza M. Moreno , Mohajerani D. , Pan W.
Published: January 2018

The CUDA Modular Polynomial (CUMODP) Library implements arithmetic operations for dense matrices and dense polynomials, primarily with modular integer coefficients. Some operations are available for integer or floating point coefficients. Similar to other software libraries, like CuBLAS
1
targeting Graphics Processing Units (GPUs), CUMODP focuses on efficiency-critical routines and provides them in the form of device functions and CUDA kernels. Hence, these routines are primarily designed to offer GPU support to polynomial system solvers. A bivariate system solver is part of the library, as a proof-of-concept. Its implementation is presented in [10] and it is integrated in M
aple
's Triangularize command
2
, since the release 18 of M
aple
.
Introduction to the special issue
Authors: García-Valls Marisol , Ferreira Luis Lino
Published: January 2018

As program chairs, we have the pleasure to introduce this special issue dedicated to the 4
th
edition of REACTION, the International Workshop on Real-time Computing and Distributed Systems, that was held in Porto on December 29
th
, 2016 as a co-located event to RTSS. REACTION aims at presenting contributions with a clear applied vision around, but not limited to, the challenging problems in the integration of real-time computing and distributed systems. The focus of the event is at the confluence area between distributed systems and real-time applications, that includes communication middleware, operating systems, virtualization technology, modeling or timely operation in distributed systems, among others.
Analyzing end-to-end delays in automotive systems at various levels of timing information
Authors: Becker Matthias , Dasari Dakshina , Mubeen Saad , Behnam Moris , Nolte Thomas
Published: January 2018

Software design for automotive systems is highly complex due to the presence of strict data age constraints for event chains in addition to task specific requirements. These age constraints define the maximum time for the propagation of data through an event chain consisting of independently triggered tasks. Tasks in event chains can have different periods, introducing over- and under-sampling effects, which additionally aggravates their timing analysis. Furthermore, different functionality in these systems, is developed by different suppliers before the final system integration on the ECU. The software itself is developed in a hardware agnostic manner and this uncertainty and limited information at the early design phases may not allow effective analysis of end-to-end delays during that phase. In this paper, we present a method to compute end-to-end delays given the information available in the design phases, thereby enabling timing analysis throughout the development process. The presented methods are evaluated with extensive experiments where the decreasing pessimism with increasing system information is shown.
Towards architectural support for bandwidth management in mixed-critical embedded systems
Authors: Christoforakis Ioannis , Astrinaki Maria , Kornaros George
Published: January 2018

Mixed-critical platforms require an on-chip interconnect and a memory controller capable of providing sufficient timing independence for critical applications. Existing real-time memory controllers, however, either do not support mixed criticality or still fail to ensure negligible allow a certain degree of interference between applications.

On the other hand, Networks-on-Chip manage the traffic injection rate mainly by employing complex techniques; either back-pressure based flow-control mechanisms or rate-control of traffic load (i.e. traffic shaping). This work proposes such a Traffic Shaper Module that supports both monitoring and traffic control at the on-chip network interface or the memory controller.

The advantage of this Traffic Shaper Module is that at system level it provides guaranteed memory bandwidth to the critical applications by limiting traffic of non-critical tasks.

The system is developed in the Xilinx ZYNQ7000 System-on-Chip while the measurements were captured on a Zed-board development board. By enabling the Traffic Shaper in our architecture we achieved fine-grain bandwidth control with negligible overhead, while providing bandwidth of only 0.5-5 percent less than the theoretical specified bandwidth.
Overweight young female kidney donors have low renal functional reserve postdonation
Authors: van Londen Marco , Schaeffers Anouk W. M. A. , de Borst Martin H. , Joles Jaap A. , Navis Gerjan , Lely A. Titia
Published: January 2018

Maintenance of adequate renal function after living kidney donation is important for donor outcome. Overweight donors, in particular, may have an increased risk for end-stage kidney disease (ESKD), and young female donors have an increased preeclampsia risk. Both of these risks may be associated with low postdonation renal functional reserve (RFR). Because we previously found that higher body mass index (BMI) was associated with lower postdonation RFR, we now studied the relationship between BMI and RFR in young female donors. RFR, the rise in glomerular filtration rate (GFR) (125I-iothalamate clearance) during dopamine, was measured in female donors (<45 yr) before and after kidney donation. Donors who are overweight (BMI >25) and nonoverweight donors were compared by Studentʼs t-test; the association was subsequently explored with regression analysis. We included 105 female donors [age 41 (36–44) median(IQR)] with a BMI of 25 (22–27) kg/m2. Predonation GFR was 118 (17) ml/min [mean(SD)] rising to 128 (19) ml/min during dopamine; mean RFR was 10 (10) ml/min. Postdonation GFR was 76 (13) ml/min, rising to 80 (12); RFR was 4 (6) ml/min ( P < 0.001 vs. predonation). In overweight donors, RFR was fully lost after donation (1 ml/min vs. 10 ml/min predonation, P < 0.001), and BMI was inversely associated with RFR after donation, independent of confounders (standardized β 0.37, P = 0.02). Reduced RFR might associate with the risk of preeclampsia and ESKD in kidney donors. Prospective studies should explore whether RFR is related to preeclampsia and whether BMI reduction before conception is of benefit to overweight female kidney donors during and after pregnancy.
Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks
Authors: Nie Laisen , Wang Xiaojie , Wan Liangtian , Yu Shui , Song Houbing , Jiang Dingde
Published: January 2018

Wireless mesh network is prevalent for providing a decentralized access for users and other intelligent devices. Meanwhile, it can be employed as the infrastructure of the last few miles connectivity for various network applications, for example, Internet of Things (IoT) and mobile networks. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep learning architecture and the Spatiotemporal Compressive Sensing method. The proposed method first adopts discrete wavelet transform to extract the low‐pass component of network traffic that describes the long‐range dependence of itself. Then, a prediction model is built by learning a deep architecture based on the deep belief network from the extracted low‐pass component. Otherwise, for the remaining high‐pass component that expresses the gusty and irregular fluctuations of network traffic, the Spatiotemporal Compressive Sensing method is adopted to predict it. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.
Choice Behavior of the Elderly Regarding Street-Crossing Facility
Authors: Wei Chong , Yan Xuedong , Shao Chunfu , Sun Jiang , Ma Lu
Published: January 2018

This study aims to understand the street-crossing-facility choice behavior of the elderly. The footbridges were classified into three types with different levels of convenience. On the other hand, the safety of the crosswalk was assumed to be highly related to the remaining time of pedestrian green light. An adaptive SP survey was designed to collect choice data from individuals aged 60 years or above, and a multilevel logistic model was developed to analyze the behavior data. The results indicated that convenience and safety exert significant influence on the facility choice behavior. The choice behavior of the elderly toward making trade-off decision between convenience and safety was further discussed through the multilevel logistic regression analyses.
The Assessment of Static Balance in Patients after Total Hip Replacement in the Period of 2-3 Years after Surgery
Authors: Pop Teresa , Szymczyk Daniel , Majewska Joanna , Bejer Agnieszka , Baran Joanna , Bielecki Arkadiusz , Rusek Wojciech
Published: January 2018

Introduction. The aim of this study was to assess static balance of patients after Total Hip Replacement (THR) compared with the age-matched, asymptomatic control group, considering the subject’s gender and the time since the surgery. Materials and Methods. The Total Hip Replacement (THR) group consisted of 55 subjects (mean age: 56.3±8.7 years) and the control group consisted of 48 subjects (mean age: 58±6.2 years). For the assessment of static balance, a stabilometric force platform was used. All subjects performed two 30-second trials in the double-leg stance position with eyes opened and closed. In the study group, the stabilometric assessment was performed once within the period of 24 to 36 months after the surgery. Results. Subjects from the study group had significantly increased mediolateral COP velocity in the test with eyes opened, as well as the values of most of the COP parameters (excluding COP path area) in the test with eyes closed, compared to the control group. Higher values of the selected COP parameters were observed in the male subjects from the study group. Conclusion. In contrast to a number of papers, our study revealed some deficits in static balance in patients after THR up to 2-3 years after surgery.
Regularization of the Boundary-Saddle-Node Bifurcation
Authors: Liu Xia
Published: January 2018

In this paper we treat a particular class of planar Filippov systems which consist of two smooth systems that are separated by a discontinuity boundary. In such systems one vector field undergoes a saddle-node bifurcation while the other vector field is transversal to the boundary. The boundary-saddle-node (BSN) bifurcation occurs at a critical value when the saddle-node point is located on the discontinuity boundary. We derive a local topological normal form for the BSN bifurcation and study its local dynamics by applying the classical Filippov’s convex method and a novel regularization approach. In fact, by the regularization approach a given Filippov system is approximated by a piecewise-smooth continuous system. Moreover, the regularization process produces a singular perturbation problem where the original discontinuous set becomes a center manifold. Thus, the regularization enables us to make use of the established theories for continuous systems and slow-fast systems to study the local behavior around the BSN bifurcation.
Reversible Thrombocytopenia after Gabapentin in an HIV-Positive Patient
Authors: Basith Mohammed , Francis Andrew , Bellon Alfredo
Published: January 2018

Gabapentin has become increasingly used in psychiatric practice specifically for anxiety disorders. Even though gabapentin is not approved by the US Food and Drug Administration to treat anxiety, physicians sometimes use it as an alternative to benzodiazepines in patients with a history of substance abuse. Gabapentin is also prescribed when individuals are at risk of thrombocytopenia which is not considered a side effect. Among patients at risk of thrombocytopenia are those positive for human immunodeficiency virus (HIV). Here we present a case of an HIV-positive man who presented for inpatient psychiatric care with severe anxiety and a history of alcohol and benzodiazepine abuse. In this patient, gabapentin worsened thrombocytopenia after repeated exposure to this medication. We suggest caution when considering gabapentin for patients with preexisting low platelet counts, as there seems to be a risk for worsening thrombocytopenia with this antiepileptic in the presence of HIV infection.