Miracle-dz/UniFAR-FTUs huggingface dataset:
Consistency Management in Cloud Storage Systems

With the emergence of cloud computing, many organizations have moved their data to the cloud in order to provide scalable, reliable and high available services. As these services mainly rely on geographically-distributed data replication to guarantee good performance and high availability, consistency comes into question. The CAP theorem discusses tradeoffs between consistency, availability, and partition tolerance, and concludes that only two of these three properties can be guaranteed simultaneously in replicated storage systems. With data growing in size and systems growing in scale, new tradeoffs have been introduced and new models are emerging for maintaining data consistency. In this chapter, we discuss the consistency issue and describe the CAP theorem as well as its limitations and impacts on big data management in large scale systems. We then briefly introduce several models of consistency in cloud storage systems. Then, we study some state-of-the-art cloud storage systems from both enterprise and academia, and discuss their contribution to maintaining data consistency. To complete our chapter, we introduce the current trend toward adaptive consistency in big data systems and introduce our dynamic adaptive consistency solution (Harmony). We conclude by discussing the open issues and challenges raised regarding consistency in the cloud.
An optimized change-driven regression testing selection strategy for binary Java applications

Selective regression testing involves re-testing of software systems with a subset of the whole test suite to verify that modifications have not caused adverse impacts to existing functions complied with the requirements specifications. With the growing of globalization and individual testing services providers, many testing and development teams belong to different organizations, and often the testing teams only get a binary release of the application without access to its source code. This makes source code analysis based regression test selection strategy not applicable. Meanwhile source code analysis based approach has scalability problem for large applications, which hinders its wide application in industry. This paper presents an optimized regression testing selection strategy based on binary java file change analysis, through which the problems around binary java applications are avoided. Besides static regression test suite reduction and test prioritization factors, continuous and real time testing execution information are incorporated as fault-proneness indicator of the selected test cases to dynamically select and prioritize the regression test suites. In addition, the whole strategy is lightweight, making the regression test selection process more automated and effective. Experiments show that this strategy can guarantee the change point coverage, reveal faults quickly, and scale to industry-size regression testing scenarios under resource and time constraints.
Edinburgh Research Explorer On the Ubiquity of Certain Total Type Structures: (Extended Abstract)

We consider a simple and well-known category of alternating games (also known as sequential data struc- tures) and several categories derived from it. In each case, we present an extension of Plotkin’s language FPC (or a suitable linearization thereof) which deﬁnes all computable strategies of appropriate types. The quest for such languages results in a novel selection of language primitives for state encapsulation, coroutining and backtracking.
A posteriori error bounds for joint matrix decomposition problems

Joint matrix triangularization is often used for estimating the joint eigenstructure of a set M of matrices, with applications in signal processing and machine learning. We consider the problem of approximate joint matrix triangularization when the matrices in M are jointly diagonalizable and real, but we only observe a set M' of noise perturbed versions of the matrices in M. Our main result is a first-order upper bound on the distance between any approximate joint triangularizer of the matrices in M' and any exact joint triangularizer of the matrices in M. The bound depends only on the observable matrices in M' and the noise level. In particular, it does not depend on optimization specific properties of the triangularizer, such as its proximity to critical points, that are typical of existing bounds in the literature. To our knowledge, this is the first a posteriori bound for joint matrix decomposition. We demonstrate the bound on synthetic data for which the ground truth is known.
Parameter-free Method for Polygonal Representation of the Noisy Curves

We propose a parameter-free method for the detection of dominant points and polygonal representation of possibly noisy curves. Based on \cite{ND07,NguyenDebled09}, this work aims at a parameter-free method through a multiscale approach. We propose a new evaluation criterion to automatically determine the most appropriate width parameter for each input curve. Thanks to a recent result \cite{FF08} on the decomposition of a curve into a sequence of maximal blurred segments, the complexity of this algorithm is $O(n\log n)$.
A New Perfect Information Game ; No Chance

Well known classical backgammon is an ancient two-player game, at least a thousand years, older than chess according to some estimates. It is a game of luck and skill, because it involves dices. In this work we construct a new backgammon which we call No Chance Backgammon since it does not involve the dice. Instead of a random element, players choose their own numbers under certain constraints in full view of the opponent. The idea for this new game is simple but profound, and transforms a game of chance into a perfect-information game. Therefore this game becomes as rich and interesting as chess. Mathematics Subject Classification: 91A05, 91A35
Book review: Michelle O’Reilly, Jessica Nina Lester and Tom Muskett (eds), A Practical Guide to Social Interaction Research in Autism Spectrum Disorders

By answering in the imperative form and reusing the verb from the first turn, the daughter’s reply illustrates how an assertion in a non-first sequential position can ‘[recast] deontic rights’ (p. 291) and accomplish directive action itself, effectuating the daughter’s increasing independence. That the environment for unmodulated imperatives is joint action and mutually accepted deonticity is confirmed in Part 3, in which the speakers are in unequal but fiduciary relationships (e.g. doctor–patient (Lindström, Lindholm, Norrby, Wide and Nilsson, Chapter 10), instructor–client (Rauniomaa, Chapter 11) and teacher–pupil (Stevanovic, Chapter 12)). The role difference is important as it provides opportunities for speaker negotiation of deontic or epistemic authority through imperative turns, a theme that appears in nine of the book’s chapters. Doctors produce unmodulated imperatives in the physical examination phase of consultations, and modulated imperatives in openings, closings and projections such as arrangements for the next appointment (Chapter 10). Similarly, a driving instructor’s unmodulated imperatives present the action as primarily within the driver’s (i.e. the addressee’s) control (Chapter 11), and in violin lessons, the Finnish-speaking teacher’s non-cliticised turns occur where she and the pupil are already in an ongoing collaboration and the pupil is performing (Chapter 12). In a cookery class (Raevaara, Chapter 13), the teacher’s imperatives again manage actions already in progress while declaratives initiate a new activity, the choice being a means of encouraging independence. As Auer (Chapter 14) points out in the concluding chapter, the imperative accomplishes much more than ‘commanding’ (p. 422); far from being coercive, it coordinates ongoing joint activity by prompting actions and being linked to the here-and-now. The volume has been meticulously prepared. Images are numbered and cross-referenced to the accompanying transcript, each of which is glossed twice in English, first literally and then idiomatically. Exemplar imperative turns are highlighted in grey throughout, and commentary on the transcripts serves as a linguistic and cultural explanation of the interaction. The data are mostly video-based and therefore multimodal in character, with accompanying stills or representational line drawings providing the contextual background missing from early CA studies. An appendix contains transcription conventions and glossing symbols, and separate author and subject indexes. This enjoyable book fully succeeds in its aim of explaining the emergence of grammar from the patterns and regularities within social interaction.
Recognition of pests based on compressive sensing theory

In order to improve the performance of the existing recognition methods of pests, the limitations of these methods are analyzed in this paper. Based on the analysis, the novel recognition method of pests by using compressive sensing theory is presented in this paper. In the proposed method, a large number of representative training samples of pests are used to construct the training samples matrix, then the sparse decomposition representation of the testing samples of pests is obtained by solving the L1-norm optimization problem, which contains distinct class information and could be used for the different species of pests recognition directly. The 12 species of stored-grain pests and the 110 species of common pests are separately recognized by the proposed method. The experimental results prove that the application of compressive sensing theory in the recognition of pests is practical and feasible.
Release of outer membrane vesicles by Gram-negative bacteria is a novel envelope stress response

Conditions that impair protein folding in the Gram‐negative bacterial envelope cause stress. The destabilizing effects of stress in this compartment are recognized and countered by a number of signal transduction mechanisms. Data presented here reveal another facet of the complex bacterial stress response, release of outer membrane vesicles. Native vesicles are composed of outer membrane and periplasmic material, and they are released from the bacterial surface without loss of membrane integrity. Here we demonstrate that the quantity of vesicle release correlates directly with the level of protein accumulation in the cell envelope. Accumulation of material occurs under stress, and is exacerbated upon impairment of the normal housekeeping and stress‐responsive mechanisms of the cell. Mutations that cause increased vesiculation enhance bacterial survival upon challenge with stressing agents or accumulation of toxic misfolded proteins. Preferential packaging of a misfolded protein mimic into vesicles for removal indicates that the vesiculation process can act to selectively eliminate unwanted material. Our results demonstrate that production of bacterial outer membrane vesicles is a fully independent, general envelope stress response. In addition to identifying a novel mechanism for alleviating stress, this work provides physiological relevance for vesicle production as a protective mechanism.
The ISO/MPEG Unified Speech and Audio Coding Standard—Consistent High Quality for All Content Types and at All Bit Rates

In early 2012 the ISO/IEC JTC1/SC29/WG11 (MPEG) finalized the new MPEG-D Unified Speech and Audio Coding standard. The new codec brings together the previously separated worlds of general audio coding and speech coding. It does so by integrating elements from audio coding and speech coding into a unified system. The present publication outlines all aspects of this standardization effort, starting with the history and motivation of the MPEG work item, describing all technical features of the final system, and further discussing listening test results and performance numbers which show the advantages of the new system over current state-of-the-art codecs.
Assessing loan risks: a data mining case study

The USDA's (US Department of Agriculture) Rural Housing Service administers a loan program that lends or guarantees mortgage loans to people living in rural areas. To administer these nearly 600000 loans, the department maintains extensive information about each one in its data warehouse. As with most lending programs, some USDA loans perform better than others. Basic data mining techniques helped the USDA's Rural Housing Service better understand and classify problem loans.
Measuring cognition across mood and psychotic disorders

Cognitive impairments are present in both schizophrenia and bipolar disorder and are strong predictors of functional outcomes for patients. One barrier in cognitive research of these disorders is the lack of large, well-characterised cross-disorder samples with cognitive data. The aims of this thesis were to examine cognition across the bipolar / schizophrenia diagnostic spectrum and to develop a new online cognitive battery for use in psychiatric research. Cognition was examined in participants with bipolar disorder, schizoaffective disorder and schizophrenia through a meta-analysis of existing studies and analysing data from a large well-characterised sample. The main finding was that there is a gradient of increasing cognitive impairment from bipolar disorder through schizoaffective disorder – bipolar type to schizoaffective disorder – depressive type and schizophrenia. Participants with the subtypes of schizoaffective disorder differed in their cognitive performance. Lifetime history of psychosis was associated with cognitive performance across disorders. An online cognitive battery was developed to assess the domains outlined by the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative. The battery was validated against the MATRICS Consensus Cognitive Battery and showed that the tasks provided valid measurements of the majority of the MATRICS domains. A large sample of participants with a range of psychiatric disorders was recruited online. An examination of cognition in participants with major depressive disorder, bipolar disorder and schizophrenia showed that cognitive profiles were similar across disorders but participants with schizophrenia have more severe impairments than participants with bipolar disorder. An important concluding observation was that poorer cognitive performance was associated with poorer functional outcome across disorders. The findings of this thesis add to a growing literature showing the importance of examining cognitive function across psychiatric disorders. To date, it is the first study to develop and utilise an online cognitive assessment for psychiatric research.
Relationship between uniform connectedness and proximity in perceptual grouping

Palmer and Rock proposed that uniform connectedness (UC) occurs prior to classical Gestalt factors to define the primitive units for visual perception. Han, Humphreys and Chen, however, found that grouping by proximity can take place as quickly as that based on UC in a letter discrimination task. The present study employed a letter detection task to examine the relationship between UC and proximity grouping in 3 experiments. We showed that reaction times to targets defined by proximity or UC were equally fast when one or two global objects were presented in the visual field. However, as the number of global objects was increased, responses were faster to targets defined by UC than to targets defined by proximity. In addition, the advantage of UC over proximity was not affected by the space between global objects. The results suggest that UC was more effective than proximity in forming perceptual units under multiple object conditions. Possible reasons for this finding are discussed.
Virtual simulation instructional training for students’ drop out of mathematical science digital entrepreneurs

This research aims to provide assistance and Virtual Simulation Instructional (VSI) training for drop out as a pilot for digital mathematical entrepreneurship in the industrial revolution 4.0 era so that graduates have ICT skills and are ready to face disruption. The subject of the research was the centre of learning activities of Insan Madani School and Dewi Sartika School in Baros, Serang, Banten, Indonesia. The research method used is a combination of informative methods and interactive demonstrations. The results showed that students’ abilities in terms of ICT with an increasing model of understanding in optimal model of 75.56%, non-creative model of 7.78%, theoretical model of 4.44 practical model of 4.44%, memorizing model of 10 %, and no model of 0% and were able to produce VSI with quality that was suitable for sale. The VSI recommendations are a strategic alternative in the development of small digital scale industry businesses and their use for digital mathematics entrepreneurship pilot learning.
Current and Future Techniques in Wound Healing Modulation after Glaucoma Filtering Surgeries

Filtering surgeries are frequently used for controlling intraocular pressure in glaucoma patients. The long-term success of operation is intimately influenced by the process of wound healing at the site of surgery. Indeed, if has not been anticipated and managed accordingly, filtering surgery in high-risk patients could end up in bleb failure. Several strategies have been developed so far to overcome excessive scarring after filtering surgery. The principal step involves meticulous tissue handling and modification of surgical technique, which can minimize the severity of wound healing response at the first place. However, this is usually insufficient, especially in those with high-risk criteria. Thus, several adjuvants have been tried to stifle the exuberant scarring after filtration surgery. Conventionally, corticosteroids and anti-fibrotic agents (including 5-fluorouracil and Mitomycin-C) have been used for over three decades with semi-acceptable outcomes. Blebs and bleb associated complications are catastrophic side effects of anti-fibrotic agents, which occasionally are encountered in a subset of patients. Therefore, research continues to find a safer, yet effective adjuvant for filtering surgery. Recent efforts have primarily focused on selective inhibition of growth factors that promote scarring during wound healing process. Currently, only anti-VEGF agents have gained widespread acceptance to be translated into routine clinical practice. Robust evidence for other agents is still lacking and future confirmative studies are warranted. In this review, we explain the importance of wound healing process during filtering surgery, and describe the conventional as well as potential future adjuvants for filtration surgeries.
A Fast Simulator to Model Complex Tendon-Bone Interactions: Application to the Tendinous Networks Controlling the Fingers

Forces generated by the muscles actuating the fingers are transmitted through a complex network of tendons. Current models of the hand either ignore or simplify the structure of these networks [1]. It has been shown that the deformable nature of these tendinous networks results in a nonlinear transformation of muscle forces [2]. Our long-term objective is to understand how the topology of this network affects the control of finger force and motion. To achieve this, we will use a machine learning approach to evolve models of this network that can best replicate experimental results [3]. Here we present an anatomically realistic solver developed to model mechanical force transmission by a network of tendons in the human fingers. While most existing solvers neglect mechanics of tendon networks, there has been recent work on dynamic simulators accounting for tendon-bone interactions [4]. The solver we present here advances work in this field by being able to simulate mechanics of complex networks wrapped on arbitrarily shaped objects (like bones), and can be effectively used to model isometric force production in complex biomechanical systems. Its speed makes it an ideal simulation engine for the evolutionary algorithms we use to infer complex anatomical structures from sparse experimentation [3]. Copyright © 2009 by ASME
Deadlock-freedom-by-design: multiparty asynchronous global programming

Over the last decade, global descriptions have been successfully employed for the verification and implementation of communicating systems, respectively as protocol specifications and choreographies. In this work, we bring these two practices together by proposing a purely-global programming model. We show a novel interpretation of asynchrony and parallelism in a global setting and develop a typing discipline that verifies choreographies against protocol specifications, based on multiparty sessions. Exploiting the nature of global descriptions, our type system defines a new class of deadlock-free concurrent systems (deadlock-freedom-by-design), provides type inference, and supports session mobility. We give a notion of Endpoint Projection (EPP) which generates correct entity code (as pi-calculus terms) from a choreography. Finally, we evaluate our approach by providing a prototype implementation for a concrete programming language and by applying it to some examples from multicore and service-oriented programming.
An adaptive action model for legged navigation planning

Navigation planning for legged robots via foot placement planning has enabled several humanoids to traverse interesting environments autonomously. In this paper we explore methods of adapting foot placement actions to the terrain during the search process, allowing for fuller use of the robot's capabilities, and better resulting paths. We show the results of these adaptive action models for both the humanoid HRP-2 and the quadruped LittleDog.
Automatic Classification of Anuran Sounds Using Convolutional Neural Networks

Anurans (frogs or toads) are closely related to the ecosystem and they are commonly used by biologists as early indicators of ecological stress. Automatic classification of anurans, by processing their calls, helps biologists analyze the activity of anurans on larger scale. Wireless Sensor Networks (WSNs) can be used for gathering data automatically over a large area. WSNs usually set restrictions on computing and transmission power for extending the network's lifetime. Deep Learning algorithms have gathered a lot of popularity in recent years, especially in the field of image recognition. Being an eager learner, a trained Deep Learning model does not need a lot of computing power and could be used in hardware with limited resources. This paper investigates the possibility of using Convolutional Neural Networks with Mel-Frequency Cepstral Coefficients (MFCCs) as input for the task of classifying anuran sounds.
A Device for Robot-Assisted Brachytherapy

A device for robot-assisted brachytherapy has been designed to be used with a robotic minimally invasive surgical robot such as the ZEUSTM. It allows loading of a standard brachytherapy needle so that the robot can position and orient it as required. The device accurately retracts a hollow needle loaded with radioactive seeds while a stationary plunger pushes the seeds out within the cancerous tissue. The position error when retracting the needle is less than 0.05 mm. The incorporation of this device into robotic systems that are already approved for clinical use can potentially allow it to be commercialized much sooner than competitive technology.