Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Scheduling of Event Analytics across Edge and Cloud

Internet of Things (IoT) domains generate large volumes of high-velocity event streams from sensors, which need to be analyzed with low latency to drive decisions. Complex Event Processing (CEP) is a Big Data technique to enable such analytics and is traditionally performed on Cloud Virtual Machines (VM). Leveraging captive IoT edge resources in combination with Cloud VMs can offer better performance, flexibility, and monetary costs for CEP. Here, we formulate an optimization problem for energy-aware placement of CEP queries, composed as an analytics dataflow, across a collection of edge and Cloud resources, with the goal of minimizing the end-to-end latency for the dataflow. We propose a Genetic Algorithm (GA) meta-heuristic to solve this problem and compare it against a brute-force optimal algorithm (BF). We perform detailed real-world benchmarks on the compute, network, and energy capacity of edge and Cloud resources. These results are used to define a realistic and comprehensive simulation study that validates the BF and GA solutions for 45 diverse CEP dataflows, LAN and WAN setup, and different edge resource availability. We compare the GA and BF solutions against random and Cloud-only baselines for different configurations for a total of 1,764 simulation runs. Our study shows that GA is within 97% of the optimal BF solution that takes hours, maps dataflows with 4--50 queries in 1--26s, and only fails to offer a feasible solution ≤20% of the time.
One Node at One Step Discovery Process as an Immunization Strategy

In the context of complex networks research, underlying network structure is considered to play a crucial role in spreading processes such as virus propagation in social and computer networks. There are some assumptions that are often considered while utilizing a network structure in the immunization process, mainly the lack of global topological information and access to the partial information of underlying network structure. However, without global information about the whole network the immunization process becoms much more difficult. The main contribution of this paper is twofold. First, it develops an efficient approach called ＂One Node at One Step Discovery Process＂ to identify chains of high degree connections for immunization purpose in scale-free networks, and second, it investigates the performance of previous approaches such as acquaintance immunization strategy (AIS), common acquaintance immunization strategy (CAIS) and Intentional Random Walk with respect to their parameters. We performed the experiments on both synthetic and real data sets and conducted a multi-agent-based simulation to verify our proposed algorithm. Experimental results show the effectiveness of our proposed algorithm in targeting high degree nodes. The results also show that some existing algorithms found in prior literature are more robust than others with respect to parameter configuration and improper selection of the parameter can produce significantly different results.
Novel Treatment of Chronic Bladder Pain Syndrome and Other Pelvic Pain Disorders by OnabotulinumtoxinA Injection

Chronic pelvic pain (CPP) is defined as pain in the pelvic organs and related structures of at least 6 months’ duration. The pathophysiology of CPP is uncertain, and its treatment presents challenges. Botulinum toxin A (BoNT-A), known for its antinociceptive, anti-inflammatory, and muscle relaxant activity, has been used recently to treat refractory CPP with promising results. In patients with interstitial cystitis/bladder pain syndrome, most studies suggest intravesical BoNT-A injection reduces bladder pain and increases bladder capacity. Repeated BoNT-A injection is also effective and reduces inflammation in the bladder. Intraprostatic BoNT-A injection could significantly improve prostate pain and urinary frequency in the patients with chronic prostatitis/chronic pelvic pain syndrome. Animal studies also suggest BoNT-A injection in the prostate decreases inflammation in the prostate. Patients with CPP due to pelvic muscle pain and spasm also benefit from localized BoNT-A injections. BoNT-A injection in the pelvic floor muscle improves dyspareunia and decreases pelvic floor pressure. Preliminary studies show intravesical BoNT-A injection is useful in inflammatory bladder diseases such as chemical cystitis, radiation cystitis, and ketamine related cystitis. Dysuria is the most common adverse effect after BoNT-A injection. Very few patients develop acute urinary retention after treatment.
Application of SVM-based correctness predictions to unsupervised discriminative speaker adaptation

The effectiveness of unsupervised speaker adaptation is typically limited by errors in the estimated transcription of the adaptation data. Previous work has mitigated this negative effect by using only those sections of the adaptation data which are transcribed with relatively high confidence. In this work, phoneme correctness predictions are integrated into a discriminative unsupervised speaker adaptation procedure. Significant accuracy improvements (over the equivalent likelihood-based technique) are observed when using discriminative unsupervised speaker adaptation in combination with support vector machines to predict phoneme correctness.
Extensive Evaluation of a FrameNet-WordNet mapping resource

Lexical resources are basic components of many text processing system devoted to information extraction, question answering or dialogue. In paste years many resources have been developed such as FrameNet and WordNet. FrameNet describes prototypical situations (i.e. Frames) while WordNet defines lexical meaning (senses) for the majority of English nouns, verbs, adjectives and adverbs. A major difference between FrameNet and WordNet refers to their coverage. Due of this lack of coverage, in recent years some approaches have been studied to make a bridge between this two resources, so a resource is used to extend the coverage of the other one. The nature of these approaches leave from supervised to supervised methods. The major problem is that there is not a standard in evaluation of the mapping. Each different work have tested own approach with a custom gold standard. This work give an extensive evaluation of the model proposed in (De Cao et al., 2008) using gold standard proposed in other works. Moreover this work give an empirical comparison between other available resources. As outcome of this work we also release the full mapping resource made according to the model proposed in (De Cao et al., 2008).
Politik Konjonktür Dalgalanmalarının Ekonomi Üzerindeki Etkisi ve Türkiye Uygulaması (1980 – 2006)

Bu calismada, politikacilarin ekonomiyi istedikleri yonde idare etmeleri (manipulasyon) icin kullandiklari yontemler ve araclar firsatci politik konjonktur dalgalanmalari acisindan ele alinmis ve Turkiye'nin 1980—2006 donemine ait aylik verileri EKK yontemi kullanilarak test edilmistir. Calismada kullanilan aylik verilerle elde edilen sonucta, bankalararasi faiz oranin secimlere daha hizli tepki verdigi ve secimlerin enflasyon orani uzerinde politik konjonktur dalgalanmasi olusturdugu belirlenmistir. Diger bir ifadeyle secimlerin sadece bankalararasi Faiz oraiii ve enllasyon orani gibi parasal sektor gostergeleri uzerinde etkili oldugu reel sektor gostergelerini ise dogrudan etkilemedigini soyleyebiliriz
NBTI-aware dual threshold voltage assignment for leakage power reduction

Dual threshold voltage (dual-Vth) assignment is recognized as a useful technique to reduce the leakage power. However, as the process technology shrinks to the deep sub-micron regime, the negative bias temperature instability (NBTI) effect becomes a serious concern. The NBTI effect may cause the degradation of threshold voltage over a period of months or years. Since previous dual-Vth assignment techniques do not consider the NBTI effect, they often decrease the circuit lifetime. In this paper, we propose an NBTI-aware dual-Vth assignment algorithm. Our objective is not only to reduce the leakage power but also to maintain the lifetime of the circuit. By assigning independent candidate gates to high threshold voltage (HTV) simultaneously, in each benchmark circuit, our approach can achieve a better result with a smaller CPU time. Experimental data consistently show that our approach works well in practice.
Joint Sparse Factor Analysis and Topic Modeling for Learning Analytics ( Poster )

Introduction Personalized education based on machine learning has the potential to revolutionize education and to improve learning for students of diverse backgrounds, abilities, and interests, at a large, global scale. We have previously developed a statistical framework for discovering and representing domain knowledge based on sparse latent factor analysis (SPARFA, for short) [1]. The framework assumes that N students answer a subset of P questions involving K P,N underlying (latent) concepts. Let the column vector cj ∈ R , j ∈ {1, . , N}, represent the latent concept understanding of the jth student, let wi ∈ R , i ∈ {1, . , P}, represent the concept associations of question i, and let the scalar μi ∈ R model the intrinsic difficulty of question i. Then, we model the student–response relationships as [1]:
$\mu $ -Stability of Nonlinear Positive Systems With Unbounded Time-Varying Delays

The stability of the zero solution plays an important role in the investigation of positive systems. In this brief, we discuss the <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>-stability of positive nonlinear systems with unbounded time-varying delays. The system is modeled by the continuous-time ordinary differential equation. Under some assumptions on the nonlinear functions, such as homogeneous, cooperative, and nondecreasing, we propose a novel transform, by which the nonlinear system reduces to a new system. Thus, we analyze its dynamics, which can simplify the nonlinear homogenous functions with respect to the arbitrary dilation map to those with respect to the standard dilation map. We finally get some new criteria for the global <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>-stability taking the degree into consideration. A numerical example is given to demonstrate the validity of obtained results.
Evaluation of control system reliability using combined dynamic fault trees and Markov models

In this paper, dynamic simulation methods for reliability evaluation of common industry-based control system architectures are investigated. Control system design often employs complex reliability structures in the forms of several levels of software and hardware redundancies, hot and cold standby systems. This is required in order to achieve certain plant availability and safety functions. Control system maintenance requires expert knowledge due to the complexity of troubleshooting steps involved with a hardware or software failures of a large system. Hence, it is crucial to understand the effect of recovery time on reliability and on overall availability in a critical control system. Dynamic Fault Tree Analysis (DFTA), Markov Chains and Reliability Block Diagrams (RBD) are presented and a block library is introduced for addressing the aforementioned modelling problems. In order to be able to evaluate dynamic fault trees and Markov Chains, Monte Carlo simulation has been used. An industry-based case study is presented, where critical failures of a redundant Programmable Logic Controller (PLC) system are identified by a Failure Mode and Effect Analysis (FMEA). The bottom up process of modelling control system reliability is discussed.
A mixed finite element formulation for a non-linear, transversely isotropic material model for the cardiac tissue

In this paper we present a mixed finite element method for modeling the passive properties of the myocardium. The passive properties are described by a non-linear, transversely isotropic, hyperelastic material model, and the myocardium is assumed to be almost incompressible. Single-field, pure displacement-based formulations are known to cause numerical difficulties when applied to incompressible or slightly compressible material cases. This paper presents an alternative approach in the form of a mixed formulation, where a separately interpolated pressure field is introduced as a primary unknown in addition to the displacement field. Moreover, a constraint term is included in the formulation to enforce (almost) incompressibility. Numerical results presented in the paper demonstrate the difficulties related to employing a pure displacement-based method, applying a set of physically relevant material parameter values for the cardiac tissue. The same problems are not experienced for the proposed mixed method. We show that the mixed formulation provides reasonable numerical results for compressible as well as nearly incompressible cases, also in situations of large fiber stretches. There is good agreement between the numerical results and the underlying analytical models.
Energy-Adaptive Display System Designs for Future Mobile Environments

The utility of a mobile computer, such as a laptop, is largely constrained by battery life. The display stands out as a major consumer of battery energy, so reducing that consumption is desirable. In this paper, we motivate and study energy-adaptive display sub-systems that match display energy consumption to the functionality required by the workload/user. Through a detailed characterization of display usage patterns, we show that screen usage of a typical user is primarily associated with content that could be displayed in smaller and simpler displays with significantly lower energy use. We propose example energy-adaptive designs that use emerging OLED displays and software optimizations that we call dark windows. Modeling the power benefits from this approach shows significant, though user-specific, energy benefits. Prototype implementations also show acceptability of the new user interfaces among users.
A Review of Broadband Dual Linearly Polarized Microstrip Antenna Designs with High Isolation [Education Column]

Dual-polarized antennas are used to achieve polarization diversity in order to increase the capacity and reliability of wireless communication links. In order to cater to increased wireless communication traffic, dual-polarized antennas are required having broad bandwidths and high isolation between two orthogonal ports. Various dual-polarized antenna designs have been explored to achieve broad bandwidth and high isolation across the entire band of interest. This paper reviews various techniques proposed in recent years for the design of dual linearly polarized antennas to achieve high isolation and broad bandwidth. A detailed analysis of these techniques in terms of their advantages and limitations is presented.
Static Var Compensator and Active Power Filter with Power Injection Capability, Using 27-level Inverters and Photovoltaic Cells

An active power filter and static VAr compensator with active power generation capability, has been implemented using a 27-level inverter. Each phase of this inverter is composed of three "H" converters, all of them connected to the same dc link and their outputs connected through output transformers scaled in power of three. The filter can compensate load currents with high harmonic content and low power factor, resulting in sinusoidal currents from the source. The dc link is connected to a battery pack, which can be charged from two sources: the ac mains supply and a photovoltaic array connected to the batteries through a MPT (maximum power tracker) converter. These characteristics make it possible to produce active power and to feed the contaminating load during prolonged voltage outages. Simulation results for this application are shown and some experiments with a 3 kVA device are also displayed
Parallizable simple authenticated key agreement protocol

Recently, Yeh and Sun proposed a simple authenticated key agreement protocol resistant to password guessing attacks called SAKA that is simple and cost-effective. And they provided a formal proof of security to show its strength against both passive and active adversaries. Compared with the previous well-known protocols, SAKA has less number of steps and less computation cost. However, considering the total execution time, SAKA is not the most efficient method, since it does not provide parties with parallel computation. In this paper, we present parallelizable simple authenticated key agreement protocol for improving the efficiency of the SAKA while maintaining provable security.
Content, Metadata, and Behavioral Information: Directions for Yahoo! Research

In mid-2005, Yahoo! Inc. began an ambitious program to create a world-class industrial research lab focusing on how to deliver services over the web to a range of stakeholders, including advertisers, site owners, content publishers, and users. The resulting organization, Yahoo! Research, has embarked on a number of research directions. In this document, we report on these directions, with a particular focus on the data engineering problems we see as critical to our mission.
Annular wire metamaterial resonators for Magnetic Resonance Imaging

Metamaterials are composite structures designed to produce the properties which are not available in nature and control electromagnetic waves in any desirable ways. A special class of wire metamaterials consists of periodic arrays of parallel conducting wires (the so-called wire medium), and they provide many opportunities to shape the form of electromagnetic field being especially promising for Magnetic Resonance Imaging (MRI) applications. In this work, we discuss how to efficiently use an annular wire metamaterial resonator in order to enhance and redistribute electromagnetic fields in 1.5 Tesla MRI.
Literacy mediation as a form of powerful literacies in community-based organisations working with young people in a situation of precarity

This paper aims at understanding the complex relations between bureaucratic literacies, the lives of young people in a situation of precarity and the work of employees of two community-based organisations in Québec (Canada). Drawing on the perspective of the New Literacy Studies, the focus of this article is around the role of literacy mediators that can play youth workers. It also endeavours to clarify the meaning of the term precarity (précarité) by suggesting a multidimensional perspective on it. This paper reveals that literacy mediation can be a form of powerful literacies that offer opportunities to counteract dominant literacies and support new ways of learning. Finally, it suggests a reflection on the importance of the work of community-based organisations in countering the situation of precarity experienced by some young people. It underlines the fact that these organisations are also experiencing financial uncertainty and insecurity that affect their services.
Identification of Cardiac Myosin-binding Protein C as a Candidate Biomarker of Myocardial Infarction by Proteomics Analysis*

Acute myocardial infarction (AMI) is a common cause of death for which effective treatments are available provided that diagnosis is rapid. The current diagnostic gold standards are circulating cardiac troponins I and T. However, their slow release delays diagnosis, and their persistence limits their utility in the identification of reinfarction. The aim was to identify candidate biomarkers of AMI. Isolated mouse hearts were perfused with oxygenated protein-free buffer, and coronary effluent was collected after ischemia or during matched normoxic perfusion. Effluents were analyzed using proteomics approaches based on one- or two-dimensional initial separation. Of the 459 proteins identified after ischemia with one-dimensional separation, 320 were not detected in the control coronary effluent. Among these were all classic existing biomarkers of AMI. We also identified the cardiac isoform of myosin-binding protein C in its full-length form and as a 40-kDa degradation product. This protein was not detected in the other murine organs examined, increased markedly with even trivial myocardial infarction, and could be detected in the plasma after myocardial infarction in vivo, a profile compatible with a biomarker of AMI. Two-dimensional fluorescence DIGE of ischemic and control coronary effluents identified more than 200 asymmetric spots verified by swapping dyes. Once again existing biomarkers of injury were confirmed as well as posttranslational modifications of antioxidant proteins such as peroxiredoxins. Perfusing hearts with protein-free buffers provides a platform of graded ischemic injury that allows detailed analysis of protein release and identification of candidate cardiac biomarkers like myosin-binding protein C.
Nonparametric Tests of Associations with Disease Based on U‐Statistics

In case‐control studies, association analysis was designed to test whether genetic variants were associated with human diseases. To evaluate the association, analysing one genetic marker at a time suffered from weak power, because of the correction for multiple testing and possibly small genetic effects. An alternative strategy was to test simultaneous effects of multiple markers, which was believed to be more powerful. However, when the number of markers under investigation was large, they would be subjected to weak power as well, because of the greater degrees of freedom. To conquer these limitations in case‐control studies, we proposed a novel method that could test joint association of several loci (i.e. haplotype), with only a single degree of freedom. In this research, we developed a nonparametric approach, which was based on U‐statistics. We also introduced a new kernel for U‐statistic, which could combine the haplotype structure information, and was expected to enhance the power. Simulations indicated that our proposed approach offered merits in identifying the associations between diseases and haplotypes. Application of our method to a study of candidate genes for internalising disorder illustrated its virtue in utility and interpretation, and provided an excellent result in detecting the associations.