Miracle-dz/UniFAR-FTUs huggingface dataset:
Small fatigue cracks

This book contains over 30 papers. Some of the titles are: Overview of the Small Crack Problem; Fatigue Crack Initiation along Slip Bands; Small Crack-Environment Interactions: The Hydrogen Embrittlement Perspective; High Resolution Techniques for the Study of Small Cracks; and Crack Inititiation and Growth Under Far-Field Cyclic Compression: Theory, Experiments and Applications.
Embedded Fault-Tolerant Accelerator Architecture for SAR Backprojection

This paper presents an optimized multi-core embedded architecture to speedup and improve the resilience of the execution of a Backprojection Algorithm targeting on-board SAR imaging systems for the space environment. The proposed architecture produces SAR images by computing approximations instead of the full precision of some arithmetic operations. The proposed solution was implemented on a Xilinx SoC device with a dual-core processor. The novel fault-tolerant system exhibits graceful degradation characteristics as it is able to produce images considered acceptable, i
CLASSIFICATION OF SKIN LESIONS USING DEEP LEARNING AND IMAGE AUGMENTATION

: Due to the lack of annotated pictures and the imbalance of classes in image sets, it is difficult to classify skin lesions using data-hungry deep learning models. Overfitting may occur when there aren't enough labeled data points or the classes aren't spread uniformly. As an alternative to the current problem, image augmentation may be the answer. Overfitting and the creation of generalizing network models have been combated using picture upgrades and a variety of other strategies documented in the scientific literature. Even if it's not apparent how to choose the best decision, various current deep learning-based approaches for skin lesion categorization and picture enhancement are reviewed in this study
The Boyle Lecture 2012

This paper argues that a genuine engagement of Christianity with evolution needs to include a discussion of Christol-ogy. Further, it develops a particular approach to Christology through a theo-dramatic account of incarnation. The somewhat static post-Chalcedon theological categories of divine and human natures are hard to square with contemporary evolutionary accounts of human origins. Once the divine Logos is portrayed in the active categories of Wisdom it becomes easier to envisage divine and creaturely wisdom coexisting in the person of Christ. I argue, in particular, that a focus on God’s agency through a modiﬁed version of Hans Urs von Balthasar’s account of theo-drama invites participation and afﬁrms human agency in a way that grand narratives do not. More particularly, drawing on examples from hominid evolution, contemporary discussion of paleontology and cooperative evolutionary theories, I suggest that the most convincing accounts of evolutionary biology ﬁt into this theo-dramatic account more readily than alternatives. As such, in the spirit of Robert Boyle, this paper deliberately blurs the categories of revealed and natural theology by arguing that we can make sense of the former through concentration on the latter.
MACHINE LEARNING TECHNIQUES IN HEALTHCARE: A REVIEW

In recent time frame, huge machine learning based practices are hastily utilize by the experts of diverse field that straightforwardly or indirectly aid them for improving quality of their working decisions. Recent linked literature of this field has portrayed countless rewards of an available schemes along with the evidence that not a sole standalone practice is skilled in present time frame to aid an expert of diverse field under dissimilar working style. Furthermore, each and every model perform differently, suitability of model depends on the base of function and their attributes types. This paper presents the different This paper put an effort to categorise steered research in the area of healthcare with utilization of machine learning methodologies.
Repository ISTITUZIONALE

— The conﬁguration of security functions in computer networks is still typically performed manually, which likely leads to security breaches and long re-conﬁguration times. This problem is exacerbated for modern networks based on network virtualization, because their complexity and dynamics make a correct manual conﬁguration practically unfeasible. This article focuses on packet ﬁlters, i.e., the most common ﬁrewall technology used in computer networks, and it proposes a new methodology to automatically deﬁne the allocation scheme and conﬁguration of packet ﬁlters in the logical topology of a virtual network. The proposed method is based on solving a carefully designed partial weighted Maximum Satisﬁability Modulo Theories problem by means of a state-of-the-art solver. This approach formally guarantees the correctness of the solution, i.e., that all security requirements are satisﬁed, and it minimizes the number of needed ﬁrewalls and ﬁrewall rules. This methodology is extensively evaluated using different metrics and tests on both synthetic and real use cases, and compared to the state-of-the-art solutions, showing its superiority.
Effect of altitude and aspect on vegetation structure, carbon density and soil nutrients in Shankaracharya Forest

The present investigation entitled “ Effect of altitude and aspect on vegetation structure, carbon density and soil nutri ents in Shankaracharya forest ” was carried out, during the year 2011 and 2012. Locally also known as Sulaiman Teng, the study site is situated between an altitud e of 1575 to 1967 m amsl and a latitude of 34°04′35.56′′ N and 74°51′08.63′′ E longitude. The hillock over looks famous Dal lake and presents a beautiful look of Sr inagar city on the eastern side. The Phyto-sociological status of the entire reserve forest grove, growth and biomass production of conifers, carbon sequestratio n by conifers and soil nutrient analysis was worked out at three different aspects along the altitudinal range. The vegetation sampling was done by quadrat method, and the sample quadrats were located by systematic random sampling procedure. Al together ninety nine quadrats were laid and sampled. Various community attributes (viz. importance value index, species frequency, density, abundance to frequency ratio were analyzed as per standard procedures. The taxonomic compendium of plant community on Sh ankaracharya reserve forest included a total of 84 plant spe cies (18 trees, 12 shrubs and 54 grasses and herbs) belonging to 72 genera and 4 0 families. The species composition and structure further revealed that Sha nkaracharya reserve grove is a deodar dominated forest. The critical examination of the study area envisages that the three altitudinal gradients varied in species a s ociation with: Cupressus torulosa, Cytisus scoparius and Iris nepalensis forming a dominant community on lower altitude (1575-1705 m), Cedrus deodara , Rubus fructicosus and Salvia moorcraftiana was the principal community on middle altitude (17 05-1835 m) and
A Review of the Applications of Deep Learning-Based Emergent Communication

Emergent communication, or emergent language, is the field of research which studies how human language-like communication systems emerge de novo in deep multi-agent reinforcement learning environments. The possibilities of replicating the emergence of a complex behavior like language have strong intuitive appeal, yet it is necessary to complement this with clear notions of how such research can be applicable to other fields of science, technology, and engineering. This paper comprehensively reviews the applications of emergent communication research across machine learning, natural language processing, linguistics, and cognitive science. Each application is illustrated with a description of its scope, an explication of emergent communication’s unique role in addressing it, a summary of the extant literature working towards the application, and brief recommendations for near-term research directions.
A Comparison of Permanent Magnet and Wound Rotor Synchronous Machines for Portable Power Generation

Permanent magnet and wound rotor synchronous machines (PMSMs and WRSMs) are often used in diesel enginebased portable power generation systems. In these applications, there is a growing desire to improve machine efficiency in order to reduce fossil fuel requirements. In addition, there is a desire to reduce mass to improve mobility. To attempt to address these competing performance objectives, a system analyst is confronted with numerous choices, including machine type (PM or WR), converter architecture (active/passive), and control. Herein, to assist the analyst, design tools capable of performing automated multi-objective optimization of PMSMs and WRSMs connected to both active and passive rectifiers are described. The tools are then used to derive tradeoffs between mass and efficiency for a 3 kW application.
A 3-level Atomicity Model for Decentralized Work ow Management Systems Israel

A work ow management systems (WFMS) employs a work ow manager (WM) to execute and automate the various activities within a work ow. To protect the consistency of data, the WM encapsulates each activity with a transaction; a transaction manager (TM) then guarantees the atomicity of activities. Since work ows often group several activities together, the TM is responsible for guaranteeing the atomicity of these units. There are scalability issues, however, with centralized WFMSs. Decentralized WFMSs provide an architecture for multiple autonomous WFMSs to interoperate, thus accommodating multiple work ows and geographically-dispersed teams. When atomic units are composed of activities spread across multiple WFMSs, however, there is a con ict between global atomicity and local autonomy of each WFMS. This paper describes a decentralized atomicity model that enables work ow administrators to specify the scope of multi-site atomicity based upon the desired semantics of multi-site tasks in the decentralized WFMS. We describe an architecture that realizes our model and execution paradigm.
Proceedings of the 18th USENIX Symposium on Networked Systems Design and Implementation.

WiFi backscattering can enable direct connectivity of IoT devices with commodity WiFi hardware at low power. However, most existing work in this area has overlooked the importance of synchronization and, as a result, accepted either limited range between the transmitter and the IoT device, reduced throughput via bit repetition, or both. In this paper, we present SyncScatter, which achieves accurate synchronization with incident signals at the IoT device level while realizing maximum possible sensitivity afforded by a backscatter link budget. SyncScatter creates a novel modeling framework and derives the maximal optimal range and synchronization error that the receiver can tolerate without signiﬁcant performance compromises. Next, SyncScatter builds a novel hierarchical wake-up protocol, which, together with a custom ASIC, achieves a range of 30+ meters and the peak throughput of 500Kbps, with an average power consumption of 30 µ W.
The Choreography of the Creative process: Drawing in Time and Space

abstract:This article provides a new perspective on the contribution of computers to visual art, exploring how the visual product's aesthetic qualities and the making process itself can render a hybrid artistic outcome. A medium that unifies the physical product with the spirit of the making process has innovative potential for computational artistic practice. The article demonstrates various techniques to visualize artists' motor performance in activities such as drawing and carving. The authors digitally track artists' movements and computer graphic tools to expose expressive performance, highlight working styles and bring their strokes' hidden paths to the artwork's forefront. The authors discuss contextual application of this form of visualization to new domains of visual art.
TRACE: Tennessee Research and Creative TRACE: Tennessee Research and Creative Exchange Exchange

This work evaluates Tor users’ risk of de-anonymization in the presence of a network-level adversary. We evaluate the likelihood that a Tor user, who is consuming modern web content, will be susceptible to a traﬃc analysis or watermarking attack. This work shows that the previously studied point-to-point model for Tor connections is not realistic and does not fully capture the risk of de-anonymization for Tor users. We show these results by measuring network paths along key parts of a Tor circuit. First, we measure the paths between the Tor exit relays and web resources requested when accessing the Alexa Top 1000 websites. Then, we use available and trusted traceroute data to approximate paths between Tor users and likely guard nodes. Then, the intersection of these paths at an autonomous system level is examined to determine if they share any elements. If the intersection of the paths is non-empty, then a Tor user making a request with those paths is susceptible to de-anonymization. Results from weighted selection of Tor exit and guard relays indicate that a Tor user visiting a random Alexa Top 1000 website is susceptible to de-anonymization with 20% probability for almost half of the Alexa Top 1000. Multiple resources account for signiﬁcant additional de-anonymization risk over the point-to-point model, and shorter network paths to content distribution nodes do not eﬀectively compensate.
Dynamic performance analysis of an integrated wind-photovoltaic microgrid with storage

This paper presents a power and energy management strategy for a wind-photovoltaic (PV) microgrid with an energy storage system (ESS) and PV array current injection on the DC-link. The ESS consists of a battery and a supercapacitor interfaced to the DC-link through bi-directional DC-DC converters. Cascade PI control is used to regulate the current supplied by the ESS to the DC-link. A fuzzy logic controller is proposed for efficient power sharing between the battery and the supercapacitor. A discrete-time simulation model is used to study the microgrid operation. The PV array model is implemented as an s-function. Using the proposed system, the power supplied to the grid is maintained at the desired reference value during changes in wind speed, solar radiation, and grid power demand. Results also show that the ESS improves the DC-link voltage stability during three-Keywords
Topic-specific Knowledge Bases: Selecting Relevant Entities through Text, Co-Occurrences and Relations

Topic-specific knowledge graphs can help to support the work of subject matter experts. Through the topical context, many ambiguities can be easily resolved and spurious relationships can be removed. A crucial step in the construction of topic-specific knowledge graphs is to identify topically relevant entities from a larger background knowledge graph and a text corpus. To achieve high-recall coverage, it is not sufficient to only select entities whose name or abstract matches the topic. Our approach demonstrates the efficacy of using relevant passages to identify relevant entities and relations, outperforming relational information from knowledge graph links and bibliographic coupling. Evaluating different approaches on a benchmark of open-domain topics, we find that the co-occurrence of entities in relevant text is one of the strongest indicators (0.2534 MAP), and hence should be included when building topic-specific knowledge bases.
Bone substitutes based on biomineralization

Abstract: The establishment of new and effective approaches to regenerative medicine requires a high interdisciplinary character between materials science, biology and surgery; this new paradigm is today fostering large advances in materials science and a more clear definition of the key aspects related to bone tissue regeneration. In this respect new bio-inspired approaches for the synthesis of biomaterials, such as in vitro biomineralization, enables the production of a new generation of smart, multifunctional and stimuli-responsive biomimetic materials for hard tissue regeneration. Among these advances, the implementation of new functionalities triggered by external magnetic signals may open the way to new therapeutic approaches to increase the regenerative potential of the scaffold, also reducing invasiveness during the implantation surgery.
Classifying Named Entities in an Alpine Heritage Corpus

In the project “Text+Berg" we digitize and archive the heritage of alpine literature from various European countries. In a first step our group digitizes all yearbooks of the Swiss Alpine Club from 1864 until today. The books comprise articles in German, French and Italian, a total of around 100.000 pages. This paper describes the corpus and the project phases towards its digitalization. We then focus on the classification of named entities, in particular person names and geographic entities.
Zircon Mineralogy and Trace Elements Composition of the Metallogenic Granites in the Nanshankeng Mine,Eastern Nanling

Nanshankeng tungsten-tin polymetallic mine, which is located in the eastern Nanling metallogenic belt, is newly discovered by geological investigation and evaluation with prospecting potential ( Xiao et al.,2008,2010,2013; Fan et al.,2013 ) . Our field investigations have identified various stages of granites associated with mineralization, some of which are A-type granites(Yao et al.,2011). In this paper, zircon mineralogy, CL image, BSE image and trace elements composition of biotite monzonitic granite closely related to skarn-type tungsten-tin mineralization are studied.
E(cid:14)cient and E(cid:11)ective Metasearch for Text Databases Incorporating Linkages among Documents (cid:3)

time the information is employed in a metasearch engine. Our experimental results show that the techniques we provide can yield retrieval e(cid:11)ectiveness close to the situation as if all documents were located in one database. The strengths of our techniques are their simplicity (the necessary and su(cid:14)cient conditions for optimal ranking of databases, the co-ordination algorithm which guarantees optimal retrieval if the databases are optimally ranked) and (cid:13)exibility (the estimation algorithms to rank databases, while taking into
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We introduce Jaspis, an open framework for adaptive speech applications. Jaspis is designed to support distributed, highly context-sensitive applications that adapt to a user and an environment. Jaspis is especially designed for multilingual applications. In this paper we introduce the fundamental principles of the Jaspis framework, including shared information management, evaluator-based agent frameworks (for dialogue management and speech outputs) and input agent based communication management. A multilingual speech e-mail client, Postimies (Mailman), is described as an example application. Jaspis is written in Java and will soon be freely available for researchers and application developers.
Proceedings of the Linux Symposium

The Linux 2.6 release provides four disk I/O schedulers: deadline, anticipatory, noop, and completely fair queuing (CFQ), along with an option to select one of these four at boot time or runtime. The selection is based on a priori knowledge of the workload, ﬁle system, and I/O system hardware conﬁguration, among other factors. The anticipatory scheduler (AS) is the default. Although the AS performs well under many situations, we have identi-ﬁed cases, under certain combinations of work-loads, where the AS leads to process starvation. To mitigate this problem, we implemented an extension to the AS (called Cooperative AS or CAS) and compared its performance with the other four schedulers. This paper brieﬂy describes the AS and the related deadline scheduler, highlighting their shortcomings; in addition, it gives a detailed description of the CAS. We report performance of all ﬁve schedulers on a set of workloads, which represent a wide range of I/O behavior. The study shows that (1) the CAS has an order of magnitude improvement in performance in cases where the AS leads to process starvation and (2) in several cases the CAS has performance comparable to that of the other schedulers. But, as the literature and this study reports, no one scheduler can provide the best possible performance for all workloads; accordingly, Linux provides four I/O schedulers from which to select. Even when dealing with just four, in systems that service concurrent workloads with different I/O behaviors, a priori selection of the scheduler with the best possible performance can be an intricate task. Dynamic selection based on workload needs, system con-ﬁguration
VR System for Spatio-Temporal Visualization of Tweet Data

Social media analysis is helpful to understand the behavior of people. Human behavior in social media is related to time and location, which is often difficult to understand the characteristics appropriately and quickly. We chose to apply virtual reality technologies to visualize the spatio-temporal social media data. This makes us easier to develop interactive and intuitive user interfaces and explore the data as we want. This paper presents our visualization of tweets of microblogs with location information. Our system features a three-dimensional temporal visualization which consists of the two-dimensional map and a time axis. In particular, we aggregate the number of tweets of each coordinate and time step, calculate scores and display them as piled cubes. We highlight only specific cubes so that users can understand the overall tendency of datasets. We also developed user interfaces for operating these cubes and panels which indicate details of tweets.
Hierarchical Sliding Inference Generator foruestion-driven Abstractive Answer Summarization

ive methods Seq2Seq+attn[42] 20.31 5.53 19.75 32.44 11.03 27.32 PGN[51] 26.83 7.54 25.20 32.91 11.54 28.11 S2S-MT[16] 26.95 7.81 26.54 33.23 12.20 27.81 Query-based methods QS[20] 27.14 7.57 25.13 32.53 11.05 26.66 SD2[45] 26.65 6.92 24.77 32.26 10.53 26.02 QPGN[10] 27.32 7.98 25.46 34.21 12.83 28.70 HSCM[12] 27.84 7.75 25.85 32.34 10.07 25.98 Our method HSIG (1-fusion) 27.85 7.87 25.94 36.29 14.51 30.60 HSIG (2-fusion) 27.84 7.96 26.01 36.42 14.69 30.84 HSIG (3-fusion) 27.80 7.81 25.87 36.67 14.64 30.68 (Seq2Seq+attn, PGN) are better than that of the extractive summary methods, and the former is more related to answer summaries for reasoning. Our model has the best performance among all the generative summary modes, and it is veriied that our method can mine the context inference information from the answer sentences, which follows the logical structure of natural language semantics and assigns more weight at the word level and sentence level so that the generated summary demonstrates reasoning and interpretability. Table 4. Performance of BERT-based models on Two Datasets Method Model WikiHowQA PubMedQA
Challenges of Open Innovation: The Paradox of Firm Investment in Open-Source Software

Open innovation is a powerful framework encompassing the generation, capture, and employment of intellectual property at the firm level. We identify three fundamental challenges for firms in applying the concept of open innovation: finding creative ways to exploit internal innovation, incorporating external innovation into internal development, and motivating outsiders to supply an ongoing stream of external innovations. This latter challenge involves a paradox, why would firms spend money on R&D efforts if the results of these efforts are available to rival firms? To explore these challenges, we examine the activity of firms in open source software to support their innovation strategies. Firms involved in open source software often make investments that will be shared with real and potential rivals. We identify four strategies firms employ — pooled R&D/product development, spinouts, selling complements and attracting donated complements — and discuss how they address the three key challenges of open innovation. We conclude with suggestions for how similar strategies may apply in other industries and offer some possible avenues for future research on open innovation.