Miracle-dz/UniFAR-FTUs huggingface dataset:
Surface Defect Detection and Recognition Method for Multi‐Scale Commutator Based on Deep Transfer Learning

In view of the fact that traditional strip surface defect detection and recognition methods cannot adapt to the changing actual detection environment, and deep learning-based detection and recognition methods have high requirements for data volume, a new strip surface defect detection and recognition based on deep transfer learning is proposed. Method: First, the ResNet network trained based on the ImageNet dataset is transferred to the Faster R-CNN classic target detection algorithm. In order to deal with the problem of large differences in defect scales, the regional recommendation network in Faster R-CNN is improved and designed. A multi-scale regional recommendation network (MS-RPN) is proposed. The strip surface defect data set is used for experimental verification. The experimental results show that compared with Faster R-CNN, the proposed method has higher accuracy and is more suitable for strip surface defect detection applications. The proposed method has an accuracy of 84.14%, 88.81%, 88.35%, 92.86%, 92.86% and 92.53 for detecting scratches, bruises, cracks, oil stains and black spots, respectively.
Intrusion Representation and Classification using Learning Algorithm

At present, machine learning (ML) algorithms are essential components in designing the sophisticated intrusion detection system (IDS). They are building-blocks to enhance cyber threat detection and help in classification at host-level and network-level in a short period. The increasing global connectivity and advancements of network technologies have added unprecedented challenges and opportunities to network security. Malicious attacks impose a huge security threat and warrant scalable solutions to thwart large-scale attacks. These activities encourage researchers to address these imminent threats by analyzing a large volume of the dataset to tackle all possible ranges of attack. In this proposed method, we calculated the fitness value of each feature from the population by using a genetic algorithm (GA) and selected them according to the fitness value. The fitness values are presented in hierarchical order to show the effectiveness of problem decomposition. We implemented Support Vector Machine (SVM) to verify the consistency of the system outcome. The well-known NSL-knowledge discovery in databases (KDD) was used to measure the performance of the system. From the experiments, we achieved a notable classification accuracies using a SVM of the current state of the art intrusion detection.
Referring Expressions in Discourse about Haptic Line Graphs

Statistical line graphs are widely used in multimodal communication settings and they are crucial elements of learning environments. For visually impaired people, haptic-audio interfaces that provide perceptual access to graphical representations seem as an effective tool to fulfill these needs. In an experimental study, we investigated referring expressions used in a collaborative joint activity between haptic ex-plorers of graphs and verbal assistants who helped haptic explorers conceptualize local and non-local second-order concepts (such as extreme values, trends, or changes of trends). The results show that haptic exploration movements evoke deictically referential links that are essential for establishing common ground between explorers and assistants.
Network Centric Warfare: Background and Oversight Issues for Congress

Abstract : Network Centric Warfare (NCW) is a key component of DOD planning for transformation of the military. NCW relies on computer processing power and networked communications technology to provide a shared awareness of the battle space for U.S. forces. Proponents say that a shared awareness increases synergy for command and control, resulting in superior decision-making, and the ability to coordinate complex military operations over long distances for an overwhelming war-fighting advantage. NCW technology saw limited deployment in Afghanistan and, more recently, increased deployment in Operation Iraqi Freedom (OIF). Several DOD key programs are now underway for deployment throughout all services.
BearWorks BearWorks

Presented in this paper is a novel system for face recognition that works well in the wild and that is based on ensembles of descriptors that utilize different preprocessing techniques. The power of our proposed approach is demonstrated on two datasets: the FERET dataset and the Labeled Faces in the Wild (LFW) dataset. In the FERET datasets, where the aim is identiﬁcation, we use the angle distance. In the LFW dataset, where the aim is to verify a given match, we use the Support Vector Machine and Similarity Metric Learning. Our proposed system performs well on both datasets, obtaining, to the best of our knowledge, one of the highest performance rates published in the literature on the FERET datasets. Particularly noteworthy is the fact that these good results on both datasets are obtained without using additional training patterns. The MATLAB source of our best ensemble approach will be freely available at https://www.dei. unipd.it/node/ 2357. (cid:1) 2016 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is
Bounds on the Complexity of the Longest Common Subsequence Problem (Extended Abstract)

[1] mentions the problem of finding long­ est common subsequences in less time than the product of the length of the strings involved. We say string x is a subsequence of string y if x can be formed by deleting some (not necessarily adjacent) symbols of y. x is a longest common subsequence (LCS) of Yl and Y2 if it is a subsequence of both Yl and Y2 and is as long as any other such string. Since the problem appears very hard, we believe that an attempt at a lower bound is in order. For a model, we treat algorithms as decision trees wi th "equal-not-equal" comparisons. The com­ plexity of an algorithm is the depth of the longest path in the tree. This model fits various algorithms that have appeared in the literature [2, 3, 4] and has been used to study the related string-to-string correction prob­ lem [5]. It does not apply to the recently discovered n2/10gn algorithm of Paterson [6] . Our goal is to show that no algorithm for the LCS problem modeled by these decision trees exists unless it is quadratic or assumes a fixed number of symbols in the alphabet.
AIS Electronic Library (AISeL)

This study aims to understand how online identity interruption can impact psychological distress and how psychological distress drives avoidance intention in using online social networks. Results of the experiment indicate that the effect of content dispersion on feelings of betrayal is amplified when network similarity is low but the effect is nullified when network similarity is high. More interestingly, results reveal that the interaction between content dispersion and network similarity on feelings of betrayal is moderated by social readership. Responses from the participants also reveal that higher feelings of betrayal lead to higher avoidance intention. Implications for research and practice are discussed.
Variability of Carpathian ichtyofauna (Palaeogene) in the light of the statistical Rodionow's method

Zmiennośc ichtiofauny paleogenu Karpat w świetle statystycznej metody Radionowa The variation in time of ichthyofauna biocoenosis of Menilite Beds was checked by means of a statistical method described by Rodionow. This method made possible the detection of statistically homogeneous section on account of biocoenosis composition as well as correlation between profiles. The trends of ecological changes within the deep-water and shallow-water assemblages of ichthyofauna are discussed.
Automatic Classification of Images with Appendiceal Orifice in Colonoscopy Videos

is an endoscopic technique that allows a physician to inspect the inside of the human colon. In current practice, videos captured from colonoscopic procedures are not routinely stored for either manual or automated post-procedure analysis. In this paper, we introduce new algorithms for automated detection of the presence of the shape of the opening of the appendix in a colonoscopy video frame. The appearance of the appendix in colonoscopy videos indicates traversal of the colon, which is an important measurement for evaluating the quality of colonoscopic procedures. The proposed techniques are valuable for (1) establishment of an effective content-based retrieval system to facilitate endoscopic research and education; and (2) assessment and improvement of the procedural skills of endoscopists, both in training and practice.
A novel approach for security function graph configuration and deployment

Network virtualization increased the versatility in enforcing security protection, by easing the development of new security function implementations. However, the drawback of this opportunity is that a security provider, in charge of configuring and deploying a security function graph, has to choose the best virtual security functions among a pool so large that makes manual decisions unfeasible. In light of this problem, the paper proposes a novel approach for synthesizing virtual security services by introducing the functionality abstraction. This new level of abstraction allows to work in the virtual level without considering the different function implementations, with the objective to postpone the function selection jointly with the deployment, after the configuration of the virtual graph. This novelty enables to optimize the function selection when the pool of available functions is very large. A framework supporting this approach has been implemented and it showed adequate scalability for the requirements of modern virtual networks.
ScholarWorks @ Georgia State University

: When teachers develop successful instructional strategies and efficient classroom management, they establish control and assert authority so that learning can take place in the classr oom. The teachers’ experiences with wireless laptop technology in this study, however, demonstrate that ubiquitous access to this technology in the classroom can sometimes create challenges for teachers, from managerial, curricular, to communicative perspectives. Exploring these challenges and their complexities in this report is meant to present a more balanced picture of technology integration in education, the one that takes into account not only the affordances and the possibilities but also the challenges and the constraints of it for teacher pedagogy and student learning. The analysis concludes with implications for professional development and policy.
Transient Stability Assessment Using Fuzzy SVM and Modified Preventive Control

systems planning, operation and extension. The objective of transient stability analysis problem is not satisfied with mere transient instability detection or evaluation and it is most important to complement it by defining fast and efficient control measures in order to ensure system security. This paper presents a new Fuzzy Support Vector Machines (FSVM) to investigate the stability status of power systems and a modified generation rescheduling scheme to bring back the identified unstable cases to a more economical and stable operating point. FSVM improves the traditional SVM (Support Vector Machines) by adding fuzzy membership to each training sample to indicate the degree of membership of this sample to different classes. The preventive control based on economic generator rescheduling avoids the instability of the power systems with minimum change in operating cost under disturbed conditions. Numerical results on the New England 39 bus test system show the effectiveness of the proposed method.
Performance evaluation of Network Coding in Smart Grids networks

In this thesis Network Coding is used as an alternative transmission technique in Smart Grid networks to increase the data rate in multicast scenarios. The thesis starts with the explanation of Network Coding based on single-source network topologies. In order to get an understanding how Smart Grids are build-up, the topology of a Power Grid is explained as well as the new two way data communication, what is the base for a smarter Power Grid. This two way communication can either be realized by using the power line or wireless as communication medium. The use of a network simulator framework, which was developed for the evaluation of Network Coding, allows the simulative analysis of Network Coding as well as store-and-forward (cid:29)ooding mechanism in Smart Grid networks. Measurable parameters like data rates and throughput, respectively, are depicted at the end of this work.
Tensor field design in volumes

3D tensor field design is important in several graphics applications such as procedural noise, solid texturing, and geometry synthesis. Different fields can lead to different visual effects. The topology of a tensor field, such as degenerate tensors, can cause artifacts in these applications. Existing 2D tensor field design systems cannot be used to handle the topology of a 3D tensor field. In this paper, we present to our knowledge the first 3D tensor field design system. At the core of our system is the ability to edit the topology of tensor fields. We demonstrate the power of our design system with applications in solid texturing and geometry synthesis.
The Mental representation of grammatical relations

The editor of this volume, who is also author or coauthor of five of the contributions, has provided an introduction that not only affords an overview of the separate articles but also interrelates the basic issues in linguistics, psycholinguistics and cognitive studies that are addressed in this volume. The twelve articles are grouped into three sections, as follows: "I. Lexical Representation: " The Passive in Lexical Theory (J. Bresnan); On the Lexical Representation of Romance Reflexive Clitics (J. Grimshaw); and Polyadicity (J. Bresnan). "II. Syntactic Representation: " Lexical-Functional Grammar: A Formal Theory for Grammatical Representation (R. Kaplan and J. Bresnan); Control and Complementation (J. Bresnan); Case Agreement in Russian (C. Neidle); The Representation of Case in Icelandic (A. Andrews); Grammatical Relations and Clause Structure in Malayalam (K. P. Monahan); and Sluicing: A Lexical Interpretation Procedure (L. Levin). "III. Cognitive Processing of Grammatical Representations: " A Theory of the Acquisition of Lexical Interpretive Grammars (S. Pinker); Toward a Theory of Lexico-Syntactic Interactions in Sentence Perception (M. Ford, J. Bresnan, and R. Kaplan); and Sentence Planning Units: Implications for the Speaker's Representation of Meaningful Relations Underlying Sentences (M. Ford).
LATEX - Open Source Documentation Software: An overview

LATEX is a free and open source documentation software (document markup language text processing system) used for preparing impressive and highly structured documents. LATEX is becoming the \standard" text processor for publications in science, engineering, and mathematics. Instead of wasting lot of time in formatting user can focus on contents and logical ideas. To learn LATEX through examples is the easiest way for many people. The objective of this paper is to give overview of LATEX so one can use it without getting into much detail, and can learn to use LATEX quickly and easily.
AIS Electronic Library (AISeL)

Organizations have found that seemingly tedious data problems are fundamentally business problems, and cannot be solved by the IT group alone. Public organizations routinely store large volumes of data about its citizens and while analysis of this data can improve decision-making and better address individual needs, this fails due to a lack of data governance. Data governance has received growing attention from both practitioners and academics as a promising approach to solving organizational data issues. This paper presents a review of data governance literature, classifying authors, research disciplines, methods and related theoretical fields, providing researchers with an overview of this emerging field. The paper is concluded by suggesting four areas for future development of the data governance field in the context of the public sector.
System Layer Architecture Layer Target System Translation Infrastructure Adaptation Manager Model Manager Strategy Executor System API ProbesEffectors Gauges Architecture Evaluator

Security features are often hardwired into software applications, making it difficult to adapt security responses to reflect changes in runtime context and new attacks. In prior work, we proposed the idea of architecture-based self-protection as a way of separating adaptation logic from application logic and providing a global perspective for reasoning about security adaptations in the context of other business goals. In this paper, we present an approach, based on this idea, for combating denial-of-service (DoS) attacks. Our approach allows DoS-related tactics to be composed into more sophisticated mitigation strategies that encapsulate possible responses to a security problem. Then, utility-based reasoning can be used to consider different business contexts and qualities. We describe how this approach forms the underpinnings of a scientific approach to self-protection, allowing us to reason about how to make the best choice of mitigation at runtime. Moreover, we also show how formal analysis can be used to determine whether the mitigations cover the range of conditions the system is likely to encounter, and the effect of mitigations on other quality attributes of the system. We evaluate the approach using the Rainbow self-adaptive framework and show how Rainbow chooses DoS mitigation tactics that are sensitive to different business contexts.
Between hawks and doves : measuring Central Bank Communication 1

Media scrutinise the ECB's communication very attentively to extract information on likely future moves of monetary policy rates, in particular after each press conference following monetary policy meetings. Assessing media's perception requires the translation of words into a quantitative indicator. In this paper, we propose the Hawkish-Dovish (HD) indicator which is computed out of a bulk of above 9,000 media reports on the ECB press conference (i.e. newspaper articles, newswires, etc.) and translates on a numerical scale the degree of “hawkishness” or “dovishness” of the ECB press conference tone perceived by media. We compare two different methods to calculate the indicator: one is based on the semantic orientation, while the other is constructed on a text classification with a Support Vector Machines classification model. We show that the latter method tends to provide more stable and accurate measurements of the perception on a labelled test set. Furthermore, we demonstrate the potential use of this indicator with some applications. We analyse the correlations with a set of interest rates and demonstrate the indicator's ability to anticipate monetary policy moves. Additionally, we use the Latent Dirichlet Allocation (LDA) algorithm to detect the dominant topics in the articles on ECB monetary policy decisions and conclude that the media's focus has shifted from the classic interest rate movements towards the non-standard monetary policy instruments. These findings provide decisive evidence in favour of using an advanced text mining classification model to measure more accurately how media perceive ECB communication.
Structural profiles of human miRNA families from pairwise clustering

UNLABELLED MicroRNAs (miRNAs) are a group of small, approximately 21 nt long, riboregulators inhibiting gene expression at a post-transcriptional level. Their most distinctive structural feature is the foldback hairpin of their precursor pre-miRNAs. Even though each pre-miRNA deposited in miRBase has its secondary structure already predicted, little is known about the patterns of structural conservation among pre-miRNAs. We address this issue by clustering the human pre-miRNA sequences based on pairwise, sequence and secondary structure alignment using FOLDALIGN, followed by global multiple alignment of obtained clusters by WAR. As a result, the common secondary structure was successfully determined for four FOLDALIGN clusters: the RF00027 structural family of the Rfam database and three clusters with previously undescribed consensus structures. AVAILABILITY http://genome.ku. dk/resources/mirclust
Using eSkel to Implement the Multiple Baseline Stereo Application

c © 2006 by John von Neumann Institute for Computing Permission to make digital or hard copies of portions of this work for personal or classroom use is granted provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise requires prior specific permission by the publisher mentioned above.
DARTS: Distributed IoT Architecture for Real-Time, Resilient and AI-Compressed Workflows

IoT (Internet of Things) sensor devices are becoming ubiquitous in diverse smart environments, including smart homes, smart cities, smart laboratories, and others. To handle their IoT sensor data, distributed edge-cloud infrastructures are emerging to capture, distribute, and analyze them and deliver important services and utilities to different communities. However, there are several challenges for these IoT-edge-cloud infrastructures to provide efficient and effective services to users: (1) how to deliver real-time distributed services under diverse IoT devices, including cameras, meteorological and other sensors; (2) how to provide robustness and resilience of distributed services within the IoT-edge-cloud infrastructures to withstand failures or attacks; (3) how to handle AI workloads are in an efficient manner under constrained network conditions. To address these challenges, we present DARTS, which is composed of different IoT, edge, cloud services addressing application portability, real-time robust data transfer and AI-driven capabilities. We benchmark and evaluate these services to showcase the practical deployment of DARTS catering to application-specific constraints.