Miracle-dz/UniFAR-FTUs huggingface dataset:
The survivability of computing systems

The distributed systems are highly fault prone environment to work with. Thus, fault tolerance is a major concern in distributed computing. The available failure resiliency techniques mitigate only the failures that are limited in some way. However, it is extremely difficult to limit the failures because the autonomous nodes may suffer autonomous failures. Nevertheless, in mission critical applications, the uncontrolled failures are unaffordable. Hence, it is highly desirable that the system survives such failures. The survivability of computer networks is a popular research topic. However, the survivability of computing systems has not been in focus. In this illustration, we have attempted to raise this issue and bring out certain requirements and features related to survivable computing systems. To the best of my knowledge, it is the first attempt in the direction.
Rotational covariance and light-front current matrix elements.

Light-front current matrix elements for elastic scattering from hadrons with spin 1 or greater must satisfy a nontrivial constraint associated with the requirement of rotational covariance for the current operator. Using a model [rho] meson as a prototype for hadronic quark models, this constraint and its implications are studied at both low and high momentum transfers. In the kinematic region appropriate for asymptotic QCD, helicity rules, together with the rotational covariance condition, yield an additional relation between the light-front current matrix elements.
A General Framework for Network Survivability Quantification

In this paper, we propose a general survivability quantification framework which is applicable to a wide range of system architectures, applications, failure/recovery behaviors, and desired metrics. We show how this framework can be used to derive survivability measures based on different definitions and extend it to other measures not covered by current definitions which can provide helpful information for better understanding of system steady state and transient behaviors under failures/attacks. An illustrative example of a telecommunications switching system is given for the ease of discussion. Markov models are developed and solved to depict various aspects of system survivability.
Expressions for the Markov Chain CLT Variance

This short paper considers certain issues surrounding the variance in the central limit theorem (CLT) for Markov chains. This subject is particularly important when using Markov chain Monte Carlo (MCMC) algorithms, see e.g. [11], [18], [7], [4], [5], [8], and [10]. Let {Xn} be a stationary, reversible Markov chain on a state space X , and let h : X → R be a mean 0 measurable function. Often, n−1/2∑ni=1 h(Xi) will converge weakly to Normal(0, σ) for some σ < ∞. The asymptotic variance σ is very important in applications, and various alternate expressions for it are available in terms of limits, autocovariances, and spectral theory. This paper considers three such expressions, denoted A, B, and C, which are known to “usually” equal σ. These expressions arise in different applications in different ways. For example, it is proved by Kipnis and Varadhan [11] that if C < ∞, then a √ n-CLT exists for h, with σ = C. In a different direction, it is proved by Roberts [13] that Metropolis algorithms satisfying a certain condition must have A = ∞. Such disparate results indicate the importance of sorting out the relationships between A, B, C, and σ.
Sales management control systems: review, synthesis, and directions for future exploration

Sales management control systems (SMCSs) are designed to align salespeople's activities and actions with organizational objectives. This article reviews and synthesizes over 50 SMCS articles published in sales, marketing, and management journals over the past 30 years. We begin by building a comprehensive framework that enables us to classify prior research into digestible categories (e.g., SMCSs as antecedents, SMCSs as consequences). Next, we present an analysis of gaps in the literature. Among other findings, our analysis reveals that there is an overwhelming focus on the use of formal (specifically behavior- and outcome-based) controls as compared to their informal control counterparts. Finally, we suggest avenues for future research: (1) mapping and understanding the full spectrum of control mechanisms, (2) developing a fuller understanding of the often-overlooked forms of control (e.g., input and cultural controls), and (3) more thoroughly analyzing how controls operate (or do not operate) as an integrated system.
T-Broker: A Trust-Aware Service Brokering Scheme for Multiple Cloud Collaborative Services

Oriented by requirement of trust management in multiple cloud environment, this paper presents T-broker, a trust-aware service brokering scheme for efficient matching cloud services (or resources) to satisfy various user requests. First, a trusted third party-based service brokering architecture is proposed for multiple cloud environment, in which the T-broker acts as a middleware for cloud trust management and service matching. Then, T-broker uses a hybrid and adaptive trust model to compute the overall trust degree of service resources, in which trust is defined as a fusion evaluation result from adaptively combining the direct monitored evidence with the social feedback of the service resources. More importantly, T-broker uses the maximizing deviation method to compute the direct experience based on multiple key trusted attributes of service resources, which can overcome the limitations of traditional trust schemes, in which the trusted attributes are weighted manually or subjectively. Finally, T-broker uses a lightweight feedback mechanism, which can effectively reduce networking risk and improve system efficiency. The experimental results show that, compared with the existing approaches, our T-broker yields very good results in many typical cases, and the proposed system is robust to deal with various numbers of dynamic service behavior from multiple cloud sites.
Robotic single-port transumbilical total hysterectomy: a pilot study

Objective To evaluate the feasibility of robotic single-port transumbilical total hysterectomy using a home-made surgical glove port system. Methods We retrospectively reviewed the medical records of patients who underwent robotic single-port transumbilical total hysterectomy between January 2010 and July 2010. All surgical procedures were performed through a single 3-4-cm umbilical incision, with a multi-channel system consisting of a wound retractor, a surgical glove, and two 10/12-mm and two 8 mm trocars. Results Seven patients were treated with robotic single-port transumbilical total hysterectomy. Procedures included total hysterectomy due to benign gynecological disease (n=5), extra-fascial hysterectomy due to carcinoma in situ of the cervix (n=1), and radical hysterectomy due to cervical cancer IB1 (n=1). The median total operative time was 109 minutes (range, 105 to 311 minutes), the median blood loss was 100 mL (range, 10 to 750 mL), and the median weight of the resected uteri was 200 g (range, 40 to 310 g). One benign case was converted to 3-port robotic surgery due to severe pelvic adhesions, and no post-operative complications occurred. Conclusion Robotic single-port transumbilical total hysterectomy is technically feasible in selected patients with gynecological disease. Robotics may enhance surgical skills during single-port transumbilical hysterectomy, especially in patients with gynecologic cancers.
Characterization of signal perturbation using voting based curve fitting for multispectral images

Signal degradation impacts the final quality of images acquired using remote sensing radiometer. The effectiveness of a restoration algorithm strongly depends on two main factors: an accurate model of the disturbs introduced by the acquisition device and adaptation of the filtering method to image content. In this paper we target the first factor, by providing a solution for characterizing multispectral image signal degradation. A framework for estimating signal disturbs from heterogeneous sets of multispectral images is presented jointly with a voting-based technique for determining the best coefficients of the fitting equation. Tests conducted on multispectral images confirm the effectiveness of the proposed approach.
Non-Graded Adaptive Grid Approaches to the Incompressible Navier-Stokes Equations

We describe two finite difference schemes for simulating incompressible flows on nonuniform meshes using quadtree/octree data structures. The first one uses a cell-centered Pois- son solver that yields first-order accurate solu- tions, while producing symmetric linear systems. The second uses a node-based Poisson solver that produces second-order accurate solutions and second-order accurate gradients, while producing nonsymmetric linear systems as the basis for a second-order accurate Navier-Stokes solver. The grids considered can be non-graded, i.e. the dif- ference of level between two adjacent cells can be arbitrary. In both cases semi-Lagrangian methods are used to update the intermediate fluid velocity in a standard projection framework. Numerical results are presented in two and three spatial di- mensions.
Study on Genetic Algorithm Optimization for Support Vector Machine in Network Intrusion Detection

Abstract This paper studies on methods taken in solving the existing network disorders in network intrusion detection. Traditional parameter-optimized Support Vector Machine (SVM) may easily generate improper parameter-selections, and may further lead to a low accuracy in network intrusion detection. In order to overcome such problems, so well as to ensure the network security, this paper tries to put forward with a Genetic Algorithm optimized Support Vector Machine in network intrusion detection. For this purpose, some procedures have to be taken. Firstly the network intrusion data should be normalized and simplified for inputs, and then to obtain optimal parameters through the parameteroptimization for SVM with a Genetic Algorithm; Finally to get network intrusion results through detecting the network data normalized by an optimal Support Vector Machine (SVM) model. The simulating results show that, compared with the traditional network intrusion detection methods, the optimized Support Vector Machine (SVM) model with a Genetic Algorithm has a high accuracy, and a low rate of losing or false alarms, and is proved to be effective in network intrusion detection.
Removal of Zn from Contaminated Sediment by FeCl3 in HCl Solution

Harbor sediments contaminated with ZnS concentrate were treated by ferric chloride in HCl solution to remove Zn. The sediments were evaluated using Tessier’s sequential extraction method to determine the different metal phase associations of Zn. Leaching tests were performed to investigate the effects of experimental factors, such as agitation speed, ferric ion concentration, temperature, and pulp density, on the removal of Zn. The sequential extraction procedure revealed that about 17.7% of Zn in the sediment was associated with soluble carbonate and oxide phases. The results of the leaching tests indicated that higher ferric concentration and temperature increased the leaching efficiencies significantly, while the agitation speed has a negligible effect on the removal of Zn. The removal ratio increased to more than 99% within 120 min of treatment at 1 kmol·m−3 HCl solution with 1 kmol·m−3 Fe3+, 10% pulp density, and 400 rpm at 90 °C. The dissolution kinetics of Zn were discussed by comparing the two shrinking core models. It was determined that the kinetic data followed the diffusion controlled model well compared to the surface chemical reaction model. The activation energies were calculated to be 76.9 kJ/mol, 69.6 kJ/mol, and 58.5 kJ/mol for 0.25 kmol·m−3, 0.5 kmol·m−3, and 1 kmol·m−3 Fe3+, respectively.
Bridging the design‐science gap with tools: Science learning and design behaviors in a simulated environment for engineering design

Many pedagogical innovations aim to integrate engineering design and science learning. However, students frequently show little attempt or have difficulties in connecting their design projects with the underlying science. Drawing upon the Cultural-Historical Activity Theory, we argue that the design tools available in a learning environment implicitly shape knowledge development as they mediate students’ design actions. To explore the roles of tools in design-science integrated learning environments, this study investigated how secondary students’ tool-mediated design actions were linked with their science learning in a tool-rich design environment with minimal explicit guidance. Eighty-three ninth-grade students completed an energy-efficient home design challenge in a simulated environment for engineering design supported by rich design tools. Results showed that students substantially improved their knowledge as a result of designing with the tools. Further, their learning gains were positively associated with three types of design actions—representation, analysis, and reflection—measured by the cumulative counts of relevant computer logs. In addition, these design actions were linked with learning gains in ways that were consistent with their theoretical impacts on knowledge development. These findings suggest that, instead of being passive components in a learning environment, tools considerably shape design processes, and learning paths. As such, tools offer possibilities to help bridge the design-science gap. © 2017 The Authors. Journal of Research in Science Teaching Published by Wiley Periodicals, Inc. J Res Sci Teach 9999:1049–1096, 2017
Survey on Natural Interaction Techniques for an Unmanned Aerial Vehicle System

The paper provides an overview of existing interaction techniques for controlling Unmanned Aerial Vehicle (UAV) systems. This work focuses on user interfaces with non-traditional input modalities such as gestures, speech, and gaze direction. Although we analyze interaction with UAV systems, most of the findings can be applied to Human-Robot Interaction in general. We report on interaction techniques employed to control single as well as multiple UAV systems, define intuitiveness of input vocabularies in the considered context, and introduce a new classification scheme based on the mental models underlying the interaction vocabulary
Social media video popularity evolution analyzing based on information spreading model

Understanding the videos' popularity evolution in social media is important to service providers, video uploaders and viewers. Such understanding can not only drive the improvement of load balancing in the network, but also can be helpful in advertising and discovering new business opportunities. While concentrating on the evolution of video's cumulative number of views after uploading, by modifying and extending an information spreading model, we characterize the popularity evolution process of videos from a new angle. In this paper, we propose a two-phase algorithm for video popularity evolution analysis: (1) For each video, we use the modified information spreading model to divide its popularity evolution process into several stages, and extract the corresponding features by fitting the parameters of model; (2) For the key feature of each stage, the increasing rate of cumulative number of views, we optimize it by using the idea of the least-squares method and improve the performance of the model. The result shows that we are able to accurately reproduce the popularity evolution process, and we also obtain some new understandings about this process.
Personalized Coupon Campaigns : Understanding and Directing Customers 1

Firms use two types of targeted coupons: Personalized rewards and targeted promotions. Personalized rewards show appreciation to loyal customers by surprising and delighting them with a discount for a broad set of frequently purchased products. Targeted promotions, on the other hand, recommend and o↵er discounts for a specific set of products relevant to a targeted customer group. I find that while the redemption rates are higher for personalized rewards, the spillover e↵ects of targeted promotions imply higher overall sales for targeted promotions. Targeted promotions have increasing returns to successive campaigns by increasing probability of coming to the store and spending once in the store while personalized rewards have decreasing returns. Further, I identify department sales of the promoted products as the primary spillover channel through which targeted promotions increase sales once customers are in the store. JEL Classifications: L21, M31, M37
Urban Warming Drives Insect Pest Abundance on Street Trees

Cities profoundly alter biological communities, favoring some species over others, though the mechanisms that govern these changes are largely unknown. Herbivorous arthropod pests are often more abundant in urban than in rural areas, and urban outbreaks have been attributed to reduced control by predators and parasitoids and to increased susceptibility of stressed urban plants. These hypotheses, however, leave many outbreaks unexplained and fail to predict variation in pest abundance within cities. Here we show that the abundance of a common insect pest is positively related to temperature even when controlling for other habitat characteristics. The scale insect Parthenolecanium quercifex was 13 times more abundant on willow oak trees in the hottest parts of Raleigh, NC, in the southeastern United States, than in cooler areas, though parasitism rates were similar. We further separated the effects of heat from those of natural enemies and plant quality in a greenhouse reciprocal transplant experiment. P. quercifex collected from hot urban trees became more abundant in hot greenhouses than in cool greenhouses, whereas the abundance of P. quercifex collected from cooler urban trees remained low in hot and cool greenhouses. Parthenolecanium quercifex living in urban hot spots succeed with warming, and they do so because some demes have either acclimatized or adapted to high temperatures. Our results provide the first evidence that heat can be a key driver of insect pest outbreaks on urban trees. Since urban warming is similar in magnitude to global warming predicted in the next 50 years, pest abundance on city trees may foreshadow widespread outbreaks as natural forests also grow warmer.
Femicomfort in the Treatment of Premenstrual Syndromes: A Double-Blind, Randomized and Placebo Controlled Trial

Objective Premenstrual syndromes (PMS) affecting 20–40% of women of reproductive age. The aim of this double blind and placebo controlled trial was to investigate whether femicofort a supplement contains Vitamin B6, Vitamin E and evening primrose oil could relieve symptoms of PMS. Method This was a randomized and double blind clinical trial. The trial was conducted between November 2009 and April March 2010. Women aged 20 to 45 years with regular menstrual cycles and experience of PMS symptoms (According to the current diagnostic criteria proposed by the American College of Obstetrics and Gynecology) for at least 6 months were eligible for the study. Patients were randomized to receive femicomfort or placebo in a 1: 1 ratio using a computer-generated code. The assignments were kept in sealed, opaque envelopes until the point of analysis of data. In this double-blind, patients were randomly assigned to receive capsule of femicomfort (Group A) or capsule placebo for two menstrual cycles (cycles 3 and 4). The primary outcome measure was the Daily Symptom Report, a checklist of 17 premenstrual symptoms rated from 0 to 4 according to their severity throughout the menstrual cycle. Secondary outcome measure was Hamilton Depression Rating Scale (17-item). Results Femicomfort at this dose was found to be effective in relieving symptoms of PMS. The difference between the femicomfort and placebo in the frequency of side effects was not significant. Conclusion The results of this study indicate the efficacy of femicomfort in the treatment of PMS.
The acquisition of the English plural morpheme in EFL learners: a lexical or a developmental morphophonemic feature?

This paper presents work-in-progress investigating whether the emergence of the English plural morpheme in formal Vietnamese learners of EFL is a result of the developmental morphophonemic interface in the learners’ L2. The investigation follows the research findings of (i) Dao’s (2007) cross-sectional study on the acquisition order of the morpheme conducted in a Processability Theory (PT) framework, and (ii) Hansen’s (2004) longitudinal study on the production of English codas by two Vietnamese learners of English. Dao (2007) found that contrary to what PT predicts, Vietnamese learners of EFL acquire the phrasal nominal plural marker before the lexical nominal plural marker and the inter-phrasal verbal marker . In an explanatory account of Dao’s (2007) findings, Charters, Dao & Jansen (2011), attribute the reverse emergence order of the English nominal plural morpheme in Vietnamese learners of EFL to probable differences between L1 and L2 conceptual structure and concomitant links to lexical structure and form. Hansen (2004) on the other hand suggests that the emergence sequence of English bi-morphemic plural in her Vietnamese learners is constrained by phonological developmental effects and grammatical conditioning, as well as L1 transfer effects. The paper presents results from a morpho-phonological analysis of the speech production data of 6 of Dao’s (2007) 36 adolescent, formal Vietnamese learners of EFL, using PRAAT phonetic analysis software. The aim of the analyses is to ascertain whether Hansen’s (2004) suggestions are further supported by Dao’s data. (240 words)
Trajectory planning with adaptive control primitives for autonomous surface vehicles operating in congested civilian traffic

We introduce a model-predictive trajectory planning algorithm for unmanned surface vehicles (USVs) operating in congested civilian traffic. The planner reasons about the availability of contingency maneuvers needed in case of any of the civilian vessels breaches the International Regulations for the Prevention of Collisions at Sea (COLREGs). Our exploratory study indicated that implementing the envisioned planner requires significant speed up of trajectory planning to cope with the dynamics of the scene, and evaluation of collision risk. We describe a new method for efficiently searching 5D state space for a dynamically feasible trajectory using adaptive control action primitives. The algorithm estimates the congestion of the state space regions to evaluate collision risk, and then dynamically scales action primitives used during the search while preserving their dynamical feasibility. Our simulation experiments demonstrate that this leads to a substantial increase in the search efficiency and a decrease in the number of collisions, especially in complex scenarios with a higher number of civilian vessels.