bluuebunny/crossref_metadata_2025 huggingface dataset:
Chronic diseases as predictors of labour market attachment after participation in subsidised re-employment programme: a 6-year follow-up study
Authors: Nwaru Chioma A , Peutere Laura , Kivimäki Mika , Pentti Jaana , Vahtera Jussi , Virtanen Pekka J
Published: September 2017

Background

Little is known about the work patterns of re-employed people. We investigated the labour market attachment trajectories of re-employed people and assessed the influence of chronic diseases on these trajectories.

Methods

The study was based on register data of 18 944 people (aged 18–60 years) who participated in a subsidised re-employment programme in Finland. Latent class growth analysis with zero-inflated Poisson was used to model the labour market attachment trajectories over a 6-year follow-up time. Multinomial logistic regression was used to examine the associations between chronic diseases and labour market attachment trajectories, adjusting for age, gender, educational level, size of town and calendar year in subsidised re-employment programme.

Results

We identified four distinct labour market attachment trajectories, namely: strengthening (a relatively stable attachment throughout the follow-up time; 77%), delayed (initial weak attachment increasing later; 6%), leavers (attachment declined with time; 10%) and none-attached (weak attachment throughout the study period; 7%). We found that severe mental problems strongly increased the likelihood of belonging in the leavers (OR 3.61; 95% CI 2.23 to 5.37) and none-attached (OR 3.41; 95% CI 1.91 to 6.10) trajectories, while chronic hypertension was associated with none-attached (OR 1.37; 95% CI 1.06 to 1.77) trajectory. The associations between other chronic diseases (diabetes, heart disease, asthma and arthritics) and labour market attachment trajectories were less evident.

Conclusions

Re-employed people appear to follow distinct labour market attachment trajectories over time. Having chronic diseases, especially mental disorders appear to increase the risk for relatively poor labour market attachment.
Pointed finite tensor categories over abelian groups
Authors: Angiono Iván , Galindo César
Published: September 2017

We give a characterization of finite pointed tensor categories obtained as de-equivariantizations of the category of corepresentations of finite-dimensional pointed Hopf algebras with abelian group of group-like elements only in terms of the (cohomology class of the) associator of the pointed part. As an application we prove that every coradically graded pointed finite braided tensor category is a de-equivariantization of the category of corepresentations of a finite-dimensional pointed Hopf algebras with abelian group of group-like elements.
Congestion control strategy on complex network with privilege traffic
Authors: Li Shi-Bao , He Ya , Liu Jian-Hang , Zhang Zhi-Gang , Huang Jun-Wei
Published: September 2017

The congestion control of traffic is one of the most important studies in complex networks. In the previous congestion algorithms, all the network traffic is assumed to have the same priority, and the privilege of traffic is ignored. In this paper, a privilege and common traffic congestion control routing strategy (PCR) based on the different priority of traffic is proposed, which can be devised to cope with the different traffic congestion situations. We introduce the concept of privilege traffic in traffic dynamics for the first time and construct a new traffic model which taking into account requirements with different priorities. Besides, a new factor [Formula: see text] is introduced by the theoretical derivation to characterize the interaction between different traffic routing selection, furthermore, [Formula: see text] is related to the network throughput. Since the joint optimization among different kinds of traffic is accomplished by PCR, the maximum value of [Formula: see text] can be significantly reduced and the network performance can be improved observably. The simulation results indicate that the network throughput with PCR has a better performance than the other strategies. Moreover, the network capacity is improved by 25% at least. Additionally, the network throughput is also influenced by privilege traffic number and traffic priority.
Dirac oscillator in a space with spin noncommutativity of coordinates
Authors: Hamil B.
Published: September 2017

The movement of relativistic particle of spin-[Formula: see text] submitted to the field of the Dirac oscillator (DO) is studied in space where the coordinates have the properties of spin noncommutativity (SNC). The problem is considered in (1 + 1) dimensions, and it is treated algebraically. From the obtained spectrum energy, the thermodynamic properties of DO in the presence of SNC are then analyzed.
Automatic Software Categorization Using Ensemble Methods and Bytecode Analysis
Authors: Catal Cagatay , Tugul Serkan , Akpinar Basar
Published: September 2017

Software repositories consist of thousands of applications and the manual categorization of these applications into domain categories is very expensive and time-consuming. In this study, we investigate the use of an ensemble of classifiers approach to solve the automatic software categorization problem when the source code is not available. Therefore, we used three data sets (package level/class level/method level) that belong to 745 closed-source Java applications from the Sharejar repository. We applied the Vote algorithm, AdaBoost, and Bagging ensemble methods and the base classifiers were Support Vector Machines, Naive Bayes, J48, IBk, and Random Forests. The best performance was achieved when the Vote algorithm was used. The base classifiers of the Vote algorithm were AdaBoost with J48, AdaBoost with Random Forest, and Random Forest algorithms. We showed that the Vote approach with method attributes provides the best performance for automatic software categorization; these results demonstrate that the proposed approach can effectively categorize applications into domain categories in the absence of source code.
ZnO THIN FILMS: RECENT DEVELOPMENT, FUTURE PERSPECTIVES AND APPLICATIONS FOR DYE SENSITIZED SOLAR CELL
Authors: TAHIR MUHAMMAD BILAL , JAVAD HASNAIN , NADEEM KHALID , MAJID A.
Published: September 2017

Dye sensitized solar cells (DSSCs) provide promisingly, organic–inorganic, clean hybrid, cost effective and efficient molecular solar cell devices. Due to their distinct and multifunctional qualities, zinc oxide (ZnO) nanostructures are promising materials used to create photoanodes for DSSCs due to the availability of larger surface area than bulk sheet substance, effectual light-dispersing centers, and when mixed with titanium dioxide they produce a core–shell formation that diminishes the coalition rate and provide direct charge. Moreover, ZnO thin sheets have been broadly observed due of its potential application in various fields i.e. piezoelectric, photovoltaic, pyroelectric and optoelectronic utilization. This review studies the recent advances in the fabrication of zinc oxide-based photovoltaics; synthesis of ZnO nanostructures with variable morphologies including thin sheets, nanotubes, nanorods, nanoflowers, nanofibers and factors that control the growth and morphologies of these nanospecies and part of crystallographic planes for the fabrication of various zinc oxide nanoshapes. In the next part of this paper, numerous fabrication routes — doped and undoped ZnO thin films — are discussed and different parameters of photovoltaics are investigated, e.g. efficiency pre and post annealing temperatures, fill factors spinning speed and coating time, additives, nature of precursor which impacts on morphological and optical parameters of these sheets. In short, this review is dedicated to the ZnO photoanode, its properties, issues related to ZnO photoanode, various improvement approaches, fabrication methods successfully trialled so far followed by market potential of the DSSC technology, conclusion and recommendations
SYNERGISTIC EFFECTS OF WEAR AND CORROSION ON MASS LOSS OF GZ62K ALLOY IN SIMULATED BODY FLUID FOR ORTHOPEDIC APPLICATION
Authors: LIU SIYU , DAI JIANWEI , NI SHENGNAN , WANG ZHANGZHONG , ZHANG XIAOBO
Published: September 2017

The friction and wear behavior of the as-cast Mg–6Gd–2Zn–0.4Zr (wt.%, GZ62K) alloy has been studied under dry and simulated body fluid (SBF) conditions for orthopedic application. The results show that the friction coefficient in SBF is much lower than that under dry sliding condition. The mass loss in SBF is lower than that of dry sliding condition before the corrosion products were removed but higher after they were removed. In SBF, wear is significantly alleviated due to lubrication and corroded film, but corrosion is extremely aggravated by wear debris. It is indicated that corrosion contributes much more mass loss than wear with the increase of sliding time.
Quantum modeling of the reaction between ozone and hydrogen cyanide
Authors: Said Kahina Sidi , Achour Madjid Nait
Published: September 2017

This work consists of an investigation, using current methods of quantum chemistry and, at first, on the basis of the available experimental results, about the new mechanisms of the reaction between ozone and hydrogen cyanide (HCN) in gaseous phases. Three possible reaction pathways which we have determined as the most probable and, all three, leading exactly to the same products, are proposed here. For each of these pathways, several steps for which we performed a kinetic study were identified in the singlet potential energy surface. To confirm the proposed mechanisms, we have achieved a study including the intrinsic reaction coordinate (IRC), the topological analysis of atoms in molecule and the harmonic vibrational frequencies calculations. The obtained results reveal that the final products have considerable thermodynamic stability and this reaction is exothermic in standard conditions.
Global stability of multi-group SEIRS epidemic models with vaccination
Authors: Fan Dejun , Hao Pengmiao , Sun Dongyan , Wei Junjie
Published: September 2017

In this paper, a susceptible–exposed–infective–recovered–susceptible (SEIRS) epidemic model with vaccination has been formulated. We studied the global stability of the corresponding single-group model, multi-group model with strongly connected network and multi-group model without strongly connected network by means of analyzing their basic reproduction numbers and the application of Lyapunov functionals. Finally, we provide some numerical simulations to illustrate our analysis results.
Economic Development and Climate Protection: Coloring, Texturing and Shading of Response Measures in Sustainable Development
Authors: GOVINDASAMY Peter
Published: September 2017

The Paris Agreement recognizes that countries may be affected not only by climate change, but also by impacts of measures taken in response to it.  The Agreement also requires parties to address the adverse implications arising from the use of response measures, particularly on developing countries. Parties' tool-kit of response measures to meet their pre-2020 actions and post-2020 intended nationally determined contributions (INDCs) could include trade measures such as carbon taxes, cap-and-trade schemes and related offsets, carbon border tax adjustments, carbon standards and labelling, and subsidies for low carbon goods. Aside from parties, international organizations are also developing response measures such as the ISO's carbon footprint standards (CFPs). These measures could have economic and trade implications and may possibly modify the conditions of competition in various sectors. Depending on how these measures are designed and applied, they can also be incompatible with WTO law. The inter-linkages between trade and climate response measures will become more pronounced as parties implement their pre-2020 climate actions and post-2020 INDCs. Trade disputes are more likely in a world of uncoordinated and conflicting national responses to climate challenge. What should be done to foster coherence between the WTO and UNFCCC regimes, and prevent legal inconsistencies from arising? This calls for the governance of response measures — the need for pre-emptive cooperation at the national and international levels supplemented by ex-ante and ex-post transparency and guided by parameters to foster coherence between the trade and climate regimes. While this paper discusses response measures and their implications from the trade-climate lens, the approach adopted in the paper would also be applicable in the interaction of response measures with other policy areas such as economic diversification, just transition in the workforce and development issues.  In sum, as the paper highlights, from the perspective of the Paris Agreement's mandate that climate protection should be enhanced in the context of sustainable development, and response measures must also colored, textured and shaded in sustainable development.
Dynamic mean variance asset allocation: Tests for robustness
Authors: Forsyth Peter A. , Vetzal Kenneth R.
Published: September 2017

We consider a portfolio consisting of a risk-free bond and an equity index which follows a jump diffusion process. Parameters for the inflation-adjusted return of the stock index and the risk-free bond are determined by examining 89 years of data. The optimal dynamic asset allocation strategy for a long-term pre-commitment mean variance (MV) investor is determined by numerically solving a Hamilton–Jacobi–Bellman partial integro-differential equation. The MV strategy is mathematically equivalent to minimizing the quadratic shortfall of the target terminal wealth. We incorporate realistic constraints on the strategy: discrete rebalancing (yearly), maximum leverage, and no trading if insolvent. Extensive synthetic market tests and resampled backtests of historical data indicate that the multi-period MV strategy achieves approximately the same expected terminal wealth as a constant weight strategy, but with much smaller variance and probability of shortfall.
Analytical pricing formulas for discretely sampled generalized variance swaps under stochastic time change
Authors: Tong Zhigang , Liu Allen
Published: September 2017

We propose a new class of models for pricing generalized variance swaps. We assume that, in the most general form, the process for the asset price is a function of a general time-homogeneous diffusion process belonging to a symmetric pricing semigroup, time changed by a composition of a Lévy subordinator and an absolutely continuous process. We derive the analytical pricing formulas for various types of generalized variance swaps based on eigenfunction expansion method. We also numerically implement the model and test its sensitivity to some of the key parameters of the model.
Negative interest rates effects on option pricing: Back to basics?
Authors: Burro Giacomo , Giribone Pier Giuseppe , Ligato Simone , Mulas Martina , Querci Francesca
Published: September 2017

We provide the first formal investigation of the consequences of negative interest rates in the Eurozone on the pricing of interest rate options. Since the money market rates settled in negative territory and other market segments experienced negative yields, the broader financial community has had to face an unknown environment. The well-known Black–Scholes (BS) framework has become unfeasible for interest rate option valuation. First of all, no-arbitrage properties are breached, allowing arbitrage opportunities. More, the BS framework’s assumption of a log-normal distribution of the underlying rates does not stand with negative interest rates. We argue that the most notable approach which allows interest rate option pricing is [Bachelier, L (1900). Théorie de la speculation, 3rd Annales scientifiques de l’École Normale Supēérieure 17, 21–86.], which assumes a normal distribution of the underlying rates. We demonstrate that the Bachelier model represents an answer to the critical issues that are raised in our study. Still, we highlight that it is far from being an accurate pricing model. Our research aims to light up an intense debate about alternative solutions among academics, financial professionals and institutions, and policy makers.
Efficient, Long-Term Logging of Rich Data Sensors Using Transient Sensor Nodes
Authors: Gomez Andres , Sigrist Lukas , Schalch Thomas , Benini Luca , Thiele Lothar
Published: September 2017

While energy harvesting is generally seen to be the key to power cyber-physical systems in a low-cost, long-term, efficient manner, it has generally required large energy storage devices to mitigate the effects of the source’s variability. The emerging class of transiently powered systems embrace this variability by performing computation in proportion to the energy harvested, thereby minimizing the obtrusive and expensive storage element. By using an efficient Energy Management Unit (EMU), small bursts of energy can be buffered in an optimally sized capacitor and used to supply generic loads, even when the average harvested power is only a fraction of that required for sustained system operation. Dynamic Energy Burst Scaling (DEBS) can be used by the load to dynamically configure the EMU to supply small bursts of energy at its optimal power point, independent from the harvester’s operating point. Parameters like the maximum burst size, the solar panel’s area, as well as the use of energy-efficient Non-Volatile Memory Hierarchy (NVMH) can have a significant impact on the transient system’s characteristics such as the wake-up time and the amount of work that can be done per unit of energy. Experimental data from a solar-powered, long-term autonomous image acquisition application show that, regardless of its configuration, the EMU can supply energy bursts to a 43.4mW load with efficiencies of up to 79.7% and can work with input power levels as low as 140μW. When the EMU is configured to use DEBS and NVMH, the total energy cost of acquiring, processing and storing an image can be reduced by 77.8%, at the price of increasing the energy buffer size by 65%.
Predictive Retransmissions for Intermittently Connected Sensor Networks with Transmission Diversity
Authors: Rajib MD. Majharul Islam , Nasipuri Asis
Published: September 2017

Batteryless wireless sensor networks that rely on energy harvested from the environment often exhibit random power outages due to limitations of energy resources, which give rise to intermittent connectivity and long transmission delays. To improve the delay performance in such networks, we consider a design strategy that uses predictive retransmissions to maximize the probability of success for each transmission. This is applied to two different transmission diversity schemes: cooperative relaying over unicast routes and opportunistic routing. Performance evaluations from theoretical models and simulations are presented that show that significant gains can be achieved using the proposed approach in such networks.
A Data Structure for Nearest Common Ancestors with Linking
Authors: Gabow Harold N.
Published: September 2017

Consider a forest that evolves via
link
operations that make the root of one tree the child of a node in another tree. Intermixed with
link
operations are
nca
operations, which return the nearest common ancestor of two given nodes when such exists. This article shows that a sequence of
m
such
nca
and
link
operations on a forest of
n
nodes can be processed online in time
O
(
m
α (
m
,
n
)+
n
). This was previously known only for a restricted type of
link
operation.

The special case where a
link
only extends a tree by adding a new leaf occurs in Edmonds’ algorithm for finding a maximum weight matching on a general graph. Incorporating our algorithm into the implementation of Edmonds’ algorithm in [9] achieves time
O
(
n
(
m
+
n
log
n
)) for weighted matching, an arguably optimum asymptotic bound (
n
and
m
are the number of vertices and edges, respectively). Our data structure also provides a simple alternative implementation of the incremental-tree set merging algorithm of Gabow and Tarjan [11].
Modeling and Analysis of Power Consumption in Live Video Streaming Systems
Authors: Sharrab Yousef O. , Sarhan Nabil J.
Published: September 2017

This article develops an aggregate power consumption model for live video streaming systems, including many-to-many systems. In many-to-one streaming systems, multiple video sources (i.e., cameras and/or sensors) stream videos to a monitoring station. We model the power consumed by the video sources in the capturing, encoding, and transmission phases and then provide an overall model in terms of the main capturing and encoding parameters, including resolution, frame rate, number of reference frames, motion estimation range, and quantization. We also analyze the power consumed by the monitoring station due to receiving, decoding, and upscaling the received video streams. In addition to modeling the power consumption, we model the achieved bitrate of video encoding. We validate the developed models through extensive experiments using two types of systems and different video contents. Furthermore, we analyze many-to-one systems in terms of bitrate, video quality, and the power consumed by the sources, as well as that by the monitoring station, considering the impacts of multiple parameters simultaneously.
Evolved Control of Natural Plants
Authors: Hofstadler Daniel Nicolas , Wahby Mostafa , Heinrich Mary Katherine , Hamann Heiko , Zahadat Payam , Ayres Phil , Schmickl Thomas
Published: September 2017

Mixing societies of natural and artificial systems can provide interesting and potentially fruitful research targets. Here we mix robotic setups and natural plants in order to steer the motion behavior of plants while growing. The robotic setup uses a camera to observe the plant and uses a pair of light sources to trigger phototropic response, steering the plant to user-defined targets. An evolutionary robotic approach is used to design a controller for the setup. Initially, preliminary experiments are performed with a simple predetermined controller and a growing bean plant. The plant behavior in response to the simple controller is captured by image processing, and a model of the plant tip dynamics is developed. The model is used in simulation to evolve a robot controller that steers the plant tip such that it follows a number of randomly generated target points. Finally, we test the simulation-evolved controller in the real setup controlling a natural bean plant. The results demonstrate a successful crossing of the reality gap in the setup. The success of the approach allows for future extensions to more complex tasks including control of the shape of plants and pattern formation in multiple plant setups.
SASO 2016
Authors: Cabri Giacomo , Picard Gauthier , Suri Niranjan
Published: September 2017

The IEEE International Conference on Self-Adapting and Self-Organizing Systems (SASO) is the main forum for studying and discussing the foundations of a principled approach to engineering systems, networks, and services based on self-adaptation and self-organization. Over the past decade, it has consolidated as the primary scientific conference for sharing ideas on algorithms, technologies, tools, and applications across a wide range of scientific fields. In 2016, the conference was hosted by the University of Augsburg, in Augsburg, Germany; its scientific program comprised full papers, short papers, poster and demo presentations, workshops, doctoral symposium and tutorials. This special issue of
ACM TAAS
champions some of the most solid research results of SASO 2016, presenting selected, revised, and extended best articles.
An Efficient Motion Detection and Tracking Scheme for Encrypted Surveillance Videos
Authors: Guo Jianting , Zheng Peijia , Huang Jiwu
Published: September 2017

Performing detection on surveillance videos contributes significantly to the goals of safety and security. However, performing detection on unprotected surveillance video may reveal the privacy of innocent people in the video. Therefore, striking a proper balance between maintaining personal privacy while enhancing the feasibility of detection is an important issue. One promising solution to this problem is to encrypt the surveillance videos and perform detection on the encrypted videos. Most existing encrypted signal processing methods focus on still images or small data volumes; however, because videos are typically much larger, investigating how to process encrypted videos is a significant challenge. In this article, we propose an efficient motion detection and tracking scheme for encrypted H.264/AVC video bitstreams, which does not require the previous decryption on the encrypted video. The main idea is to first estimate motion information from the bitstream structure and codeword length and, then, propose a region update (RU) algorithm to deal with the loss and error drifting of motion caused by the video encryption. The RU algorithm is designed based on the prior knowledge that the object motion in the video is continuous in space and time. Compared to the existing scheme, which is based on video encryption that occurs at the pixel level, the proposed scheme has the advantages of requiring only a small storage of the encrypted video and has a low computational cost for both encryption and detection. Experimental results show that our scheme performs better regarding detection accuracy and execution speed. Moreover, the proposed scheme can work with more than one format-compliant video encryption method, provided that the positions of the macroblocks can be extracted from the encrypted video bitstream. Due to the coupling of video stream encryption and detection algorithms, our scheme can be directly connected to the video stream output (e.g., surveillance cameras) without requiring any camera modifications.
Queue-Proportional Sampling
Authors: Gong Long , Tune Paul , Liu Liang , Yang Sen , Xu Jun (Jim)
Published: September 2017

Most present day switching systems, in Internet routers and data-center switches, employ a single input-queued crossbar to interconnect input ports with output ports. Such switches need to compute a matching, between input and output ports, for each switching cycle (time slot). The main challenge in designing such matching algorithms is to deal with the unfortunate tradeoff between the quality of the computed matching and the computational complexity of the algorithm. In this paper, we propose a general approach that can significantly boost the performance of both SERENA and iSLIP, yet incurs only O(1) additional computational complexity at each input/output port. Our approach is a novel proposing strategy, called
Queue-Proportional Sampling (QPS)
, that generates an excellent
starter matching
. We show, through rigorous simulations, that when starting with this starter matching, iSLIP and SERENA can output much better final matching decisions, as measured by the resulting throughput and delay performance, than they otherwise can.
Portfolio-driven Resource Management for Transient Cloud Servers
Authors: Sharma Prateek , Irwin David , Shenoy Prashant
Published: September 2017

Cloud providers have begun to offer their surplus capacity in the form of low-cost transient servers, which can be revoked unilaterally at any time. While the low cost of transient servers makes them attractive for a wide range of applications, such as data processing and scientific computing, failures due to server revocation can severely degrade application performance. Since different transient server types offer different cost and availability tradeoffs, we present the notion of server portfolios that is based on financial portfolio modeling. Server portfolios enable construction of an "optimal" mix of severs to meet an application's sensitivity to cost and revocation risk. We implement model-driven portfolios in a system called ExoSphere, and show how diverse applications can use portfolios and application-specific policies to gracefully handle transient servers. We show that ExoSphere enables widely-used parallel applications such as Spark, MPI, and BOINC to be made transiency-aware with modest effort. Our experiments show that allowing the applications to use suitable transiency-aware policies, ExoSphere is able to achieve 80% cost savings when compared to on-demand servers and greatly reduces revocation risk compared to existing approaches.
A Simple Yet Effective Balanced Edge Partition Model for Parallel Computing
Authors: Li Lingda , Geda Robel , Hayes Ari B. , Chen Yanhao , Chaudhari Pranav , Zhang Eddy Z. , Szegedy Mario
Published: September 2017

Graph edge partition models have recently become an appealing alternative to graph vertex partition models for distributed computing due to both their flexibility in balancing loads and their performance in reducing communication cost.

In this paper, we propose a simple yet effective graph edge partitioning algorithm. In practice, our algorithm provides good partition quality while maintaining low partition overhead. It also outperforms similar state-of-the-art edge partition approaches, especially for power-law graphs. In theory, previous work showed that an approximation guarantee of O(d
max
√(log n log k)) apply to the graphs with m=Ω(k
2
) edges (n is the number of vertices, and k is the number of partitions). We further rigorously proved that this approximation guarantee hold for all graphs.

We also demonstrate the applicability of the proposed edge partition algorithm in real parallel computing systems. We draw our example from GPU program locality enhancement and demonstrate that the graph edge partition model does not only apply to distributed computing with many computer nodes, but also to parallel computing in a single computer node with a many-core processor.
A Case Study in Power Substation Network Dynamics
Authors: Formby David , Walid Anwar , Beyah Raheem
Published: September 2017

The modern world is becoming increasingly dependent on computing and communication technology to function, but unfortunately its application and impact on areas such as critical infrastructure and industrial control system (ICS) networks remains to be thoroughly studied. Significant research has been conducted to address the myriad security concerns in these areas, but they are virtually all based on artificial testbeds or simulations designed on assumptions about their behavior either from knowledge of traditional IT networking or from basic principles of ICS operation. In this work, we provide the most detailed characterization of an example ICS to date in order to determine if these common assumptions hold true. A live power distribution substation is observed over the course of two and a half years to measure its behavior and evolution over time. Then, a horizontal study is conducted that compared this behavior with three other substations from the same company. Although most predictions were found to be correct, some unexpected behavior was observed that highlights the fundamental differences between ICS and IT networks including round trip times dominated by processing speed as opposed to network delay, several well known TCP features being largely irrelevant, and surprisingly large jitter from devices running real-time operating systems. The impact of these observations is discussed in terms of generality to other embedded networks, network security applications, and the suitability of the TCP protocol for this environment.
Exploiting Data Longevity for Enhancing the Lifetime of Flash-based Storage Class Memory
Authors: Choi Wonil , Arjomand Mohammad , Jung Myoungsoo , Kandemir Mahmut T.
Published: September 2017

This paper proposes to exploit the capability of retention time relaxation in flash memories for improving the lifetime of an SLC-based SSD. The main idea is that as a majority of I/O data in a typical workload do not need a retention time larger than a few days, we can have multiple partial program states in a cell and use every two states to store one-bit data at each time. Thus, we can store multiple bits in a cell (one bit at each time) without erasing it after each write -- that would directly translates into lifetime enhancement. The proposed scheme is called Dense-SLC (D-SLC) flash design which improves SSD lifetime by 5.1X--8.6X.
Optimal Posted Prices for Online Cloud Resource Allocation
Authors: Zhang Zijun , Li Zongpeng , Wu Chuan
Published: September 2017

We study online resource allocation in a cloud computing platform, through a posted pricing mechanism: The cloud provider publishes a unit price for each resource type, which may vary over time; upon arrival at the cloud system, a cloud user either takes the current prices, renting resources to execute its job, or refuses the prices without running its job there. We design pricing functions based on the current resource utilization ratios, in a wide array of demand-supply relationships and resource occupation durations, and prove worst-case competitive ratios of the pricing functions in terms of social welfare. In the basic case of a single-type, non-recycled resource (i.e., allocated resources are not later released for reuse), we prove that our pricing function design is optimal, in that any other pricing function can only lead to a worse competitive ratio. Insights obtained from the basic cases are then used to generalize the pricing functions to more realistic cloud systems with multiple types of resources, where a job occupies allocated resources for a number of time slots till completion, upon which time the resources are returned back to the cloud resource pool.
A Low-Complexity Approach to Distributed Cooperative Caching with Geographic Constraints
Authors: Avrachenkov Konstantin , Goseling Jasper , Serbetci Berksan
Published: September 2017

A promising means to increase efficiency of cellular networks compared to existing architectures is to proactively cache data in the base stations. The idea is to store part of the data at the wireless edge and use the backhaul only to refresh the stored data. Data replacement will depend on the users' demand distribution over time. As this distribution is varying slowly, the stored data can be refreshed at off-peak times. In this way, caches containing popular content serve as helpers to the overall system and decrease the maximum backhaul load [1-5]. Our goal in this paper is on developing low-complexity distributed and asynchronous content placement algorithms. This is of practical relevance in cellular networks in which an operator wants to optimize the stored content in caches (i.e., base stations) while keeping the communication in the network to a minimum. In that case it will help that caches exchange information only locally.
A Spot Capacity Market to Increase Power Infrastructure Utilization in Multi-Tenant Data Centers
Authors: Islam Mohammad A. , Ren Xiaoqi , Ren Shaolei , Wierman Adam
Published: September 2017

Despite the common practice of oversubscription, power capacity is largely under-utilized in data centers. A significant factor driving this under-utilization is fluctuation of the aggregate power demand, resulting in unused "spot (power) capacity". In this paper, we tap into spot capacity for improving power infrastructure utilization in multi-tenant data centers, an important but under-explored type of data center where multiple tenants house their own physical servers. We propose a novel spot capacity market, called SpotDC, to allocate spot capacity to tenants on demand. Specifically, SpotDC extracts tenants' rack-level spot capacity demand through an elastic demand function, based on which the operator sets the market price for spot capacity allocation. We evaluate SpotDC using both testbed experiments and simulations, demonstrating that SpotDC improves power infrastructure utilization and creates a "win-win" situation: the data center operator increases its profit (by nearly 10%), while tenants improve their performance (by 1.2{1.8x on average, yet at a marginal cost).
Incentivizing Reliable Demand Response with Customers' Uncertainties and Capacity Planning
Authors: Comden Joshua , Liu Zhenhua , Zhao Yue
Published: September 2017

One of the major issues with the integration of renewable energy sources into the power grid is the increased uncertainty and variability that they bring. If this uncertainty is not sufficiently addressed, it will limit the further penetration of renewables into the grid and even result in blackouts. Compared to energy storage, Demand Response (DR) has advantages to provide reserves to the load serving entities (LSEs) in a cost-effective and environmentally friendly way. DR programs work by changing customers' loads when the power grid experiences a contingency such as a mismatch between supply and demand. Uncertainties from both the customer-side and LSE-side make designing algorithms for DR a major challenge. This paper makes the following main contributions: (i) We propose DR control policies based on the optimal structures of the offline solution. (ii) A distributed algorithm is developed for implementing the control policies without efficiency loss. (iii) We further offer an enhanced policy design by allowing flexibilities into the commitment level. (iv) We perform real world trace based numerical simulations which demonstrate that the proposed algorithms can achieve near optimal social cost. Details can be found in our extended version.
Characterizing 3D Floating Gate NAND Flash
Authors: Xiong Qin , Wu Fei , Lu Zhonghai , Zhu Yue , Zhou You , Chu Yibing , Xie Changsheng , Huang Ping
Published: September 2017

In this paper, we characterize a state-of-the-art 3D floating gate NAND flash memory through comprehensive experiments on an FPGA platform. Then, we present distinct observations on performance and reliability, such as operation latencies and various error patterns. We believe that through our work, novel 3D NAND flash-oriented designs can be developed to achieve better performance and reliability.
Adaptive TTL-Based Caching for Content Delivery
Authors: Basu Soumya , Sundarrajan Aditya , Ghaderi Javad , Shakkottai Sanjay , Sitaraman Ramesh
Published: September 2017

Content Delivery Networks (CDNs) cache and serve a majority of the user-requested content on the Internet, including web pages, videos, and software downloads. We propose two TTL-based caching algorithms that automatically adapt to the heterogeneity, burstiness, and non-stationary nature of real-world content requests. The first algorithm called d-TTL dynamically adapts a TTL parameter using a stochastic approximation approach and achieves a given feasible target hit rate. The second algorithm called f-TTL uses two caches, each with its own TTL. The lower-level cache adaptively filters out non-stationary content, while the higher-level cache stores frequently-accessed stationary content. We implement d-TTL and f-TTL and evaluate both algorithms using an extensive nine-day trace consisting of more than 500 million requests from a production CDN server. We show that both d-TTL and f-TTL converge to their hit rate targets with an error of about 1.3%. We also show that f-TTL requires a significantly smaller cache size than d-TTL to achieve the same hit rate, since it effectively filters out rarely-accessed content.
Using Burstable Instances in the Public Cloud
Authors: Wang Cheng , Urgaonkar Bhuvan , Nasiriani Neda , Kesidis George
Published: September 2017

To attract more customers, public cloud providers offer virtual machine (instance) types that trade off lower prices for poorer capacities. As one salient approach, the providers employ aggressive statistical multiplexing of multiple cheaper instances on a single physical server, resulting in tenants experiencing higher dynamism in the resource capacity of these instances. Examples of this are EC2's "type" instances and GCE's "shared-core" instances.We collectively refer to these as burstable instances for their ability to dynamically "burst" (increase the capacity of) their resources. Burstable instances are significantly cheaper than the "regular" instances, and offer time-varying CPU capacity comprising a minimum guaranteed base capacity/rate, which is much smaller than a short-lived peak capacity that becomes available upon operating at lower than base rate for a sufficient duration. Table 1 summarizes our classification of resource capacity dynamism for GCE and EC2 instances along with the nature of disclosure made by the provider. To exploit burstable instances cost-effectively, a tenant would need to carefully understand the significant additional complexity of such instances beyond that disclosed by the providers.
Delay Scalings and Mean-Field Limits in Networked Systems
Authors: Borst Sem
Published: September 2017

Load balancing mechanisms and scheduling algorithms play a critical role in achieving efficient server utilization and providing robust delay performance in a wide range of networked systems. We will review some celebrated schemes and optimality results which typically assume that detailed state information, e.g. exact knowledge of queue lengths, is available in assigning jobs to queues or allocating a shared resource among competing users. In practice, however, obtaining such state information is non-trivial, and usually involves a significant communication overhead or delay, which is particularly a concern in large-scale networked systems with massive numbers of queues. These scalability issues have prompted increasing attention for the implementation complexity of load balancing and scheduling algorithms as a crucial design criterion, besides the traditional performance metrics. In this talk we examine the delay performance in such networks for various load balancing and scheduling algorithms, in conjunction with the associated implementation overhead. In the first part of the talk we focus on a scenario with a single dispatcher where jobs arrive that need to be assigned to one of several parallel queues. In the second part of the talk we turn to a system with a single resource, e.g. a shared wireless transmission medium, which is to be allocated among several nodes. We will specifically explore the delay scaling properties in a mean-field framework where the total load and service capacity grow large in proportion. The mean-field regime not only offers analytical tractability, but is also highly relevant given the immense numbers of servers in data centers and cloud networks, and dense populations of wireless devices and sensors in Internet-of-Things (IoT) applications. Time permitting, we will also discuss the impact of the underlying network structure and a few open research challenges.
Sacral neuromodulation blocks pudendal inhibition of reflex bladder activity in cats: insight into the efficacy of sacral neuromodulation in Fowler’s syndrome
Authors: Li Xing , Uy Jamie , Yu Michelle , Li Shun , Theisen Katherine , Browning Jeffery , Shen Bing , Wang Jicheng , Roppolo James R. , de Groat William C. , Tai Changfeng
Published: September 2017

This study tested the hypothesis that sacral neuromodulation, i.e., electrical stimulation of afferent axons in sacral spinal root, can block pudendal afferent inhibition of the micturition reflex. In α-chloralose-anesthetized cats, pudendal nerve stimulation (PNS) at 3–5 Hz was used to inhibit bladder reflex activity while the sacral S1 or S2 dorsal root was stimulated at 15–30 Hz to mimic sacral neuromodulation and to block the bladder inhibition induced by PNS. The intensity threshold (T) for PNS or S1/S2 dorsal root stimulation (DRS) to induce muscle twitch of anal sphincter or toe was determined. PNS at 1.5–2T intensity inhibited the micturition reflex by significantly ( P < 0.01) increasing bladder capacity to 150–170% of control capacity. S1 DRS alone at 1–1.5T intensity did not inhibit bladder activity but completely blocked PNS inhibition and restored bladder capacity to control level. At higher intensity (1.5–2T), S1 DRS alone inhibited the micturition reflex and significantly increased bladder capacity to 135.8 ± 6.6% of control capacity. However, the same higher intensity S1 DRS applied simultaneously with PNS, suppressed PNS inhibition and significantly ( P < 0.01) reduced bladder capacity to 126.8 ± 9.7% of control capacity. S2 DRS at both low (1T) and high (1.5–2T) intensity failed to significantly reduce PNS inhibition. PNS and S1 DRS did not change the amplitude and duration of micturition reflex contractions, but S2 DRS at 1.5–2T intensity doubled the duration of the contractions and increased bladder capacity. These results are important for understanding the mechanisms underlying sacral neuromodulation of nonobstructive urinary retention in Fowler’s syndrome.
Phase-dependent deficits during reach-to-grasp after human spinal cord injury
Authors: Lei Yuming , Perez Monica A.
Published: September 2017

Most cervical spinal cord injuries result in asymmetrical functional impairments in hand and arm function. However, the extent to which reach-to-grasp movements are affected in humans with incomplete cervical spinal cord injury (SCI) remains poorly understood. Using kinematics and electromyographic (EMG) recordings in hand and arm muscles we studied the different phases of unilateral self-paced reach-to-grasp movements (arm acceleration, hand opening and closing) to a small cylinder in the more and less affected arms of individuals with cervical SCI and in age-matched controls. We found that SCI subjects showed prolonged movement duration in both arms during arm acceleration, and hand opening and closing compared with controls. Notably, the more affected arm showed an additional increase in movement duration at the time to close the hand compared with the less affected arm. Also, the time at which the index finger and thumb contacted the object and the variability of finger movement trajectory were increased in the more compared with the less affected arm of SCI participants. Participants with prolonged movement duration during hand closing were those with more pronounced deficits in sensory function. The muscle activation ratio between the first dorsal interosseous and abductor pollicis brevis muscles decreased during hand closing in the more compared with the less affected arm of SCI participants. Our results suggest that deficits in movement kinematics during reach-to-grasp movements are more pronounced at the time to close the hand in the more affected arm of SCI participants, likely related to deficits in EMG muscle activation and sensory function.

NEW & NOTEWORTHY Humans with cervical spinal cord injury usually present asymmetrical functional impairments in hand and arm function. Here, we demonstrate for the first time that deficits in movement kinematics during reaching and grasping movements are more pronounced at the time to close the hand in the more affected arm of spinal cord injury. We suggest that this is in part related to deficits in muscle activation ratios between hand muscles and a decrease in sensory function.
New Objective Refraction Metric Based on Sphere Fitting to the Wavefront
Authors: Jaskulski Mateusz , Martínez-Finkelshtein Andreí , López-Gil Norberto
Published: September 2017

Purpose. To develop an objective refraction formula based on the ocular wavefront error (WFE) expressed in terms of Zernike coefficients and pupil radius, which would be an accurate predictor of subjective spherical equivalent (SE) for different pupil sizes.Methods. A sphere is fitted to the ocular wavefront at the center and at a variable distance,t. The optimal fitting distance,topt, is obtained empirically from a dataset of 308 eyes as a function of objective refraction pupil radius,r0, and used to define the formula of a new wavefront refraction metric (MTR). The metric is tested in another, independent dataset of 200 eyes.Results. For pupil radiir0≤2 mm, the new metric predicts the equivalent sphere with similar accuracy (<0.1D), however, forr0>2 mm, the mean error of traditional metrics can increase beyond 0.25D, and the MTR remains accurate. The proposed metric allows clinicians to obtain an accurate clinical spherical equivalent value without rescaling/refitting of the wavefront coefficients. It has the potential to be developed into a metric which will be able to predict full spherocylindrical refraction for the desired illumination conditions and corresponding pupil size.