Miracle-dz/UniFAR-FTUs huggingface dataset:
SynchronizationCoherence:ATransparentHardwareMechanismfor CacheCoherenceandFine-GrainedSynchronization

The quest to improve performance forces designers to explore flner-grained multiprocessor machines. Ever increasing chip densities based on CMOS improvements fuel research in highly parallel chip multiprocessors with 100s of processing elements. With such increasing levels of parallelism, synchronization is set to become a major performance bottleneck and e‐cient support for synchronization an important design criterion. Previous research has shown that integrating support for flne-grained synchronization can have signiflcant performance beneflts compared to traditional coarse-grained synchronization. Not much progress has been made in supporting flne-grained synchronization transparently to processor nodes: a key reason perhaps why wide adoption has not followed. In this paper, we propose a novel approach called Synchronization Coherence that can provide transparent flnegrained synchronization and caching in a multiprocessor machine and single-chip multiprocessor. Our approach merges flne-grained synchronization mechanisms with traditional cache coherence protocols. It reduces network utilization as well as synchronization related processing overheads while adding minimal hardware complexity as compared to cache coherence mechanisms or previously reported flne-grained synchronization techniques. In addition to its beneflt of making synchronization transparent to processor nodes, for the applications studied, it provides up to 23% improvement in performance and up to 24% improvement in energy e‐ciency with no L2 caches compared to previous flne-grained synchronization techniques. The performance improvement increases up to 38% when simulating with an ideal L2 cache system.
Motion Artifact Reduction in Electrocardiogram Using Adaptive Filter

Removing motion artifacts from an electrocardiogram (ECG) is one of the important issues to be considered during real-time heart rate measurements in telemetric health care. However, motion artifacts are part of the transient baseline change caused by the electrode motions that are the results of a subject's movement. Therefore, an accelerometer was used to measure the acceleration signal of the vibrations or movement of the trunk as the reference inputs of the adaptive filter. The optimal weight of the adaptive filter could be adjusted by a least mean square algorithm. Experiments with synthetic and real data were performed to demonstrate the efficacy of this proposed method. We have found that the QRS complex of the filtered ECG was clearly appeared.
Caries Prevalence in Preschool Children in a City of Southern Brazil According to Two Diagnostic Criteria: dmf-t and ICDAS II

Objective: This cross-sectional research evaluated caries prevalence and treatment need in pre-school children using different indexes. Material and Methods: A sample of 931 children (3-5 years old) attending public schools were examined by two calibrated researchers, who recorded the caries prevalence using dmf-t and ICDAS II. The clinical records obtained directed the decision regarding the treatment needs, which were divided into non-invasive and invasive procedures according to the scores registered in the different caries indexes. Descriptive statistics were used to present the data related to each index; qui-square test was used to compare the need of invasive and non-invasive treatment in the different ages. Results: The mean dmf-t was 1.8 ± 2.9, with a 42.9% caries prevalence. Using cut-off points of ICDAS II (≥1, ≥3 and ≥4), the caries prevalence values found were 50.7%, 40.8% and 30.7%, respectively. Five-year-old children exhibited the highest caries prevalence, assessed with dmf-t or ≥3 and ≥4 cut-off points of ICDAS II (≥3: p=0.032; ≥4: p=0.015). The percentages of caries-free children were 49.1% and 57.1%, respectively for ICDAS II and dmf-t. Restorative treatment in at least one tooth was required by 30.7% and 40% of the children for ICDAS II and dmf-t. Only ICDAS II could establish the percentage of non-invasive treatments (20%). Both indices pointed out the expressive need of restorative treatment. Conclusion: The use of dmf-t in epidemiological surveys may underestimate caries prevalence whereas the ICDAS II allowed the identification of early carious lesions and the viability of the use of non-invasive procedures as caries control measures in a child population.
Combination methods for software verification

The thesis is devoted to the development of formal methods for software verification. Indeed, two are among the most widespread techniques that allow to rigorously specify the possible executions of a system and check whether it contains bugs. On the one hand, correctness of a program can be guaranteed by showing the unsatisfiability of a formula modulo a theory which usually axiomatizes the involved datatypes; on the other hand, model checking techniques are used to certify that every possible run of the system satisfies the desired properties. The contributions of the thesis are the following: First of all, we give decidability result for the constraint satisfiability problem for interesting extensions of the theory of arrays. Secondly, along the lines of Manna and Pnueli, who have shown how a mixture of first-order logic and linear time temporal logic is sufficient to state verification problems for the class of reactive systems, we draw on the recent literature about combination of decision procedures to give decidability and undecidability results for the satisfiability problem for logics that allow to plug reasoning modulo first-order theories into a temporal setting. The results obtained in the case of linear flows of time are then generalized to temporal and modal logics whose relativized satisfiability problem is decidable. The last contribution is the decidability of the model checking problem for linear flows of time under suitable hypothesis over the first-order theories involved. The proofs of the decidability results suggest that efficient Satisfiability Modulo Theories solvers might be successfully employed in the model checking of infinite-state systems.
Bayesian Minimum Description Length Techniques for Multiple Changepoint Detection

This dissertation develops a minimum description length (MDL) multiple changepoint detection procedure that allows for prior distributions. MDL methods, which are penalized likelihood techniques with penalties based on data descriptionlength information principles, have been successfully applied to many recent multiple changepoint problems. This work shows how to modify the MDL penalty to account for various prior knowledge. Our motivation lies in climatology. Here, a metadata record, which is a file listing times when a recording station physically moved, instrumentation was changed, etc., sometimes exists. While metadata records are notoriously incomplete, they permit the construct a prior distribution that helps detect changepoints. This allows both documented and undocumented changepoints to be analyzed in tandem. The method developed here takes into account 1) metadata, 2) reference series, 3) seasonal means, and 4) autocorrelations. Asymptotically, our estimated multiple changepoint configuration of monthly data is shown to be consistent. The methods are illustrated in the analysis of 114 years of monthly temperatures from Tuscaloosa, Alabama. The multivariate aspect of the methods allow maximum and minimum temperatures to be jointly studied. A method for homogenizing daily temperature series is also developed. While daily temperatures have a complex structure, statistical techniques have been accu-
Performability of Integrated Networked Control Systems

APA Citation Moustafa, E. (2014). Performability of Integrated Networked Control Systems [Master's Thesis, the American University in Cairo]. AUC Knowledge Fountain. https://fount.aucegypt. edu/etds/1249 MLA Citation Moustafa, Eslam. Performability of Integrated Networked Control Systems. 2014. American University in Cairo, Master's Thesis. AUC Knowledge Fountain. https://fount.aucegypt. edu/etds/1249
Using Eye Movements to Understand how Security Screeners Search for Threats in X-Ray Baggage

There has been an increasing drive to understand failures in searches for weapons and explosives in X-ray baggage screening. Tracking eye movements during the search has produced new insights into the guidance of attention during the search, and the identification of targets once they are fixated. Here, we review the eye-movement literature that has emerged on this front over the last fifteen years, including a discussion of the problems that real-world searchers face when trying to detect targets that could do serious harm to people and infrastructure.
Exploring the Role of Community Self-Organisation in the Creation and Creative Dissolution of a Community Food Initiative

Community food initiatives are gaining momentum. Across various geographical contexts, community food initiatives are self-organising, providing communities with inspiration, knowledge and the opportunity to work towards responsible and socially acceptable transformations in food systems. In this article, we explore how self-organisation manifests itself in the daily activities and developments of community food initiatives. Through the conceptual lens of community self-organisation, we aim to provide a more detailed understanding of how community food initiatives contribute to broader and transformational shifts in food systems. Drawing on a multi-method approach, including community-based participatory research, interviews and observations, this article follows the creation and creative dissolution of the Free Café—a surplus food sharing initiative in Groningen, the Netherlands, which in the eye of the public remains unified, but from the volunteers’ perspectives split up into three different initiatives. The results suggest that community self-organisation accommodates differing motivations and experiences embedded in the everyday collective performances of community rationalities and aspirations. This article also points to the changing individual and collective perspectives, vulnerabilities and everyday politics within community food initiatives. This paper contributes to emerging debates on community self-organising within food systems and the potential of community initiatives to promote broader social realignments.
Harmful internet use - Part I: Internet addiction and problematic use

This report reviews the existing scientific evidence regarding internet-use-related addiction problems at an individual level in Europe. In the last two decades, there has been an exponential growth in research in this field. Since 2013, internet gaming disorder has been included in the appendix of the American Psychiatric Association's fifth Diagnostic and Statistical Manual of Mental Disorders, and gaming disorder has been included in the eleventh International Classification of Diseases published by the World Health Organization. The study includes a detailed critical literature review on generalised internet addiction, online gaming, and gambling addiction in Europe. Based on scientific databases, 19 empirical studies with both community and clinical samples have been selected from Denmark, France, Germany, Greece, Italy, the Netherlands, and Spain. The majority of individuals with internet-use-related addictions were found to be educated adolescents and young males. Comorbidities with other psychiatric conditions were present as a rule, and they were more severe in the case of gaming. Cognitive behavioural therapy was the usual treatment with positive prognosis. This report provides the conceptualisation of these three internet-use-related addiction problems, together with a set of policy options, preventive actions, and evidence to support future policies in the European Union context.
Restricting the Power of Cophonologies: A Representational Solution to Stem Allomorphy in Uspanteko

In Uspanteko, a Mayan language spoken in Guatemala, certain possessive prefixes lead to variation in stress and pitch accent and can sometimes trigger vowel length alternations or consonant deletion in roots. We argue that this complex pattern of stem allomorphy can be successfully analyzed within a morpheme-based model of morphology given two assumptions: i. underlying representations can contain metrical templates (e.g. Saba Kirchner 2013, Iosad 2016, Köhnlein 2016, 2019 for recent proposals); ii. pitch-accent contrasts in Uspanteko are a surface exponent of a difference between trochaic (falling tone) and iambic feet (level tone), as proposed in Köhnlein (2019). We claim that our analysis is more restrictive than an earlier account by Bennett & Henderson (2013; henceforth B&H), who divide relevant items into several nominal cophonologies. In analyzing non-concatenative exponence as an epiphenomenon of metrical affixation, our approach is in line with principles of Generalized Non-Linear Affixation (e.g. Bermúdez-Otero 2012, Trommer & Zimmermann 2014).
ACTIVE LISTENING: SPEECH INTELLIGIBILITY IN NOISY ENVIRONMENTS

INTRODUCTION Here we briefly review some experiments that have contributed to our understanding about listening in noisy environments: The so-called “cocktail party problem” (CPP). Concurrent talkers at a cocktail party will mask each other not only in terms of their energetic overlap but in the way in which a listener can extract meaning from the ensemble of sounds. Central to this process is how the bottom-up mechanisms of grouping segregate the acoustic elements associated with each sound and then how streaming these groups over time contribute to the formation of the auditory objects of our perception. Over the last decade, research has increasingly pointed to the important role of attention in overcoming informational masking. We will consider some of the evidence that attention not only acts on auditory objects but can modulate some of the “primitive” processes of grouping and stream formation. These advances have significantly shifted the focus from “hearing in noise” to listening as an active cognitive process and complement the development of ideas more generally in speech recognition and semantic processing [1].
Graph-Based Semi-Supervised Relation Extraction: Graph-Based Semi-Supervised Relation Extraction

This paper investigates a graph-based semi-supervised learning algorithm, that is, label propagation algorithm for relation extraction. Labeled and unlabeled examples are represented as the nodes, and their distances as the weights of edges in the graph. The relation extraction tries to obtain a labeling function on this graph to satisfy the global consistency assumption. Experimental results on the ACE (automatic content extraction) corpus showed that this method achieves a better performance than SVM (support vector machine) when only very few labeled examples are available, and it also performs better than bootstrapping for the relation extraction task.
Decentralized Model Predictive Control for smart grid applications

This thesis focuses on a model predictive control scheme which allows organizing the power production of power plants in a decentralized fashion. That way a less computationally demanding control scheme can be applied to control the frequency at each power plant without a governing, high level controller for the whole power grid. The main contribution was to develop a communication scheme between power plants that can be applied in a competitive environment like the energy market. Most established schemes for decentralized power production require giving away a mathematical representation of a plant to all its neighbors. However, the developed control scheme only requires informing the neighboring power plants the expected future evolution of the power networks voltage angle. This is information which is more efficiently communicated by power plant operators. Additionally, this simplification does not only yield a notable reduction in communicated data but also reduces the computational complexity of the control problem for a single power plant. The aforementioned control scheme was applied to a network consisting of several different plants for each of which a model was developed. The modeled plants range from conventionally generated plants like hydro-, gas- or wind power plants to more modern converter coupled plants like photovoltaic installations. The plants were modeled such that energy buffers - in the form of aggregated Electric Vehicle Batteries - can be taken into account. For the power plants and the energy transfer between them, linear time-invariant models were augmented with linear matrix inequalities. These represent physical bounds which the model has to regard in order to have a realistic system evolution ie, maximal power line capacities or limiting power plant production capabilities. Proofs are given which indicate necessary properties of the developed algorithm to ensure nominal or robust stability. Simulations were carried out which verified the conditions obtained from the proofs. Also by simulation, the obtained control scheme was compared with a centralized approach, amongst others. Considering the developments towards a Smart Grid one can say that a power production which is organized in a decentralized way reduces the computational effort greatly with a tolerable loss of performance. This statement is backed up with results from the simulations. The findings also indicate that the addition of buffers is very beneficial regarding disturbance rejection in the power grid.
Incremental advancements in public health adaptation to climate change in Florida

ABSTRACT Several barriers to climate change adaptation exist, including lack of financial resources, limited technical capacity and prohibitive politics. However, there is limited praxis scholarship on the ways public health departments are planning for climate risks and how they navigate these challenges. This case study provides insights into the incremental strategies employed by public health professionals to address climate risks in Florida. The paper examines pilot adaptation projects proposed by county public health departments and supported by the Building Resilience Against Climate Effects program. We qualitatively evaluated eight projects through document reviews and interviews with state program administrators and project managers at the county level. Dedicated program funding developed evidenced-based platforms which informed traditional and experimental responses that directly or indirectly addressed climate-related hazards. Increasing the funding amounts to support pilot projects would help to move beyond the preparatory groundwork stage to broader and more sustained adaptation actions. Project managers acted incrementally to implement activities that expanded existing programs and did not generate negative political attention or publicity. Project managers also benefited from experiential learning opportunities which were supported by collaborative networks in order to implement ideas that extended beyond the traditional practice domains of public health departments.
Detection and transformation of objective and constraint structures for optimization algorithms

Diverse forms of nonlinear optimization problems can be recast to special problem types, permitting a wider variety of highly effective solvers to be used and possibly leading to reductions in solution time. Popular solvers assume, however, that the necessary transformations to required canonical forms have already been identified and carried out. This dissertation describes the construction of algorithms that automatically detect and apply transformations of appropriate nonlinear problems to two canonical forms, second-order cone programs and mixed-integer linear programs. These automated transformations allow for more effective and reliable modeling. An implementation is described that converts models in the AMPL language for use with various solvers.
Housing and populism

Abstract The recent success of populist candidates in the UK and Continental Europe has sparked a major debate between those who view populism as a reaction of the economically ‘left behind’ and those who view it as a cultural ‘backlash’ by groups with declining social status, pointing to stark divisions between urban and rural areas, core and periphery. This paper bridges the economic and values-based approaches to populism by arguing that the geography of wealth inequality offers a convincing explanation for the pattern of populist vote share. Drawing on fine-grained house price data in the UK and France, it is shown that the pattern of house prices ‒ even within small districts ‒ plays a major part in shaping support for Brexit and Marine Le Pen. The findings illustrate how longstanding variation in local wealth shapes the geography of discontent and drives populist appeal. Populism, the article concludes, is primarily a politics of place, and place is a product, in part, of the housing market.
Praproses Data Alir ADS-B dari Multi-Receiver dengan Pengelompokan Agglomerasi Berbasis Konsistensi Jarak

Abstract— ADS-B is a surveillance technology for transportation. For an aircraft, ADS-B broadcasts its information simultaneously such as identity, flight number, position, altitude, velocity, etc. Due to the limited range of receiving the data, ADS-B needs multi-receiver to increase the capability of receiving data. But, the usage of multi-receiver raises new problems in the ADS-B data stream, such as redundant and outliers. These problems can reduce the quality of data received because it does not represent its actual flight conditions, in other words the nature of time-series data are blurred. This paper proposed a new method for preprocessing the data stream of the ADS-B multi-receiver to get good quality of data. The good quality of data means all unique data successfully restored and redundant data is removed, so its timeseries characteristic is regained. This method used coordinate information (latitude and longitude) in ADS-B data as a reference for preprocessing. Applying agglomeration clustering techniques and the rule of distance consistency as merging strategy of the cluster, this method is able to generate the data ADS-B that represents the status of the real aircraft, which is time-series data. This simple method can generate good quality of data from the data ADS-B multi-receiver. Intisari— ADS-B merupakan teknologi pengawasan pesawat. Secara simultan, ADS-B menyebarkan informasi pesawat (ID, nomor penerbangan, posisi, ketinggian, kecepatan, dan lain-lain) melalui gelombang elektromagnetik. Karena terbatasnya wilayah jangkauan receiver dalam menerima data ADS-B, maka diperlukan multi-receiver untuk meningkatkan jangkauan penangkapan sinyal. Penggunaan multi-receiver ini memunculkan masalah baru dalam data alir ADS-B, antara lain data redundan dan data pencilan sehingga menyebabkan data yang diterima memiliki kualitas yang rendah karena tidak merepresentasikan kondisi sebuah penerbangan yang sebenarnya, dengan kata lain sifat timeseries pada data yang diterima menjadi kabur. Dalam makalah ini, metode baru diajukan dengan tujuan untuk praproses data alir ADS-B dari multi-receiver sehingga dihasilkan data dengan kualitas yang baik, di mana semua data unik berhasil dikembalikan sifat timeseries-nya dan data redundan berhasil dihilangkan. Metode ini memanfaatkan informasi posisi (lintang dan bujur) pesawat pada data ADS-B sebagai acuan untuk praprosesnya. Dengan teknik pengelompokan aglomerasi dan dengan aturan konsistensi jarak antar data sebagai strategi penggabungan kelompok, metode ini mampu menghasilkan data ADS-B yang merepresentasikan keadaan pesawat sebenarnya, yaitu data yang bersifat timeseries. Dengan metode yang sederhana ini dapat dihasilkan data ADS-B dari multi-receiver dengan kualitas yang baik.