Miracle-dz/UniFAR-FTUs huggingface dataset:
FedOCR: Communication-Efficient Federated Learning for Scene Text Recognition

While scene text recognition techniques have been widely used in commercial applications, data privacy has rarely been taken into account by this research community. Most existing algorithms have assumed a set of shared or centralized training data. However, in practice, data may be distributed on different local devices that can not be centralized to share due to the privacy restrictions. In this paper, we study how to make use of decentralized datasets for training a robust scene text recognizer while keeping them stay on local devices. To the best of our knowledge, we propose the first framework leveraging federated learning for scene text recognition, which is trained with decentralized datasets collaboratively. Hence we name it FedOCR. To make FedCOR fairly suitable to be deployed on end devices, we make two improvements including using lightweight models and hashing techniques. We argue that both are crucial for FedOCR in terms of the communication efficiency of federated learning. The simulations on decentralized datasets show that the proposed FedOCR achieves competitive results to the models that are trained with centralized data, with fewer communication costs and higher-level privacy-preserving.
Ju n 20 16 A Quantum-Logic Synthesis of Hermitian

In this paper, the problem of synthesizing a general Hermitian quantum gate into a set of primary quantum gates is addressed. To this end, an extended version of the Jacobi approach for calculating the eigenvalues of Hermitian matrices in linear algebra is considered as the basis of the proposed synthesis method. The quantum circuit synthesis method derived from the Jacobi approach and its optimization challenges are described. It is shown that the proposed method results in multiple-control rotation gates around the y axis, multiple-control phase shift gates, multiple-control NOT gates and a middle diagonal Hermitian matrix, which can be synthesized to multiple-control Pauli Z gates. Using the proposed approach, it is shown how multiple-control U gates, where U is a single-qubit Hermitian quantum gate, can be implemented using a linear number of elementary gates in terms of circuit lines with the aid of one auxiliary qubit in an arbitrary state.
V . Other Approaches 60 A . Coupling of Concentration and Energy-Density Fluctuations

George D. J. Phillies Department of Physics, Worcester Polytechnic Institute, Worcester, MA 01609 Abstract I review theoretical treatments of diffusion in crowded (i. e., non-dilute) solutions of globular macromolecules. The focus is on the classical statistico-mechanical literature, much of which dates to before 1990. Classes of theoretical models include continuum treatments, correlation function descriptions, generalized Langevin equation descriptions, Smoluchowski and Mori-Zwanzig descriptions, and a brief but encouraging comparison with experimental results. The primary emphasis is on measurements made with quasi-elastic light scattering spectroscopy; I also discuss outcomes from fluorescence photobleaching recovery, fluorescence correlation spectroscopy, pulsedgradient spin-echo nuclear magnetic resonance, and raster image correlation spectroscopy. I close with a list of theoretical papers on the general topic. This manuscript began as a chapter for someone else’s book. For reasons not relevant here, the following will not see print there. I am therefore making a distribution to interested parties. Given the size, this is not a journal article; I am open to publication offers. In the long run, this article may become a chapter in my volume Theory of Polymer Solution Dynamics, now in preliminary stages. Reports of typographic errors, points where the discussion is obscure, additions to Appendix C, and requests for additions are collegially welcomed.
Recurrent Surge Oscillograph ( RSO ) for Rotor Winding Shorts Detection

Detection of inter turn shorts in rotor windings of high voltage turbine generators (TG) has emerged as one of the important diagnostic measures in condition monitor (CM) for uninterrupted power generation. Conventional test methods cannot identify the location of defects. Recurrent Surge Oscillograph (RSO), an off-line novel technique method has widely supported the quality of decisions of diagnosticians to locate the shorts in rotor windings. This paper begins with traditional techniques in use to observe inter turn shorts of the field windings. Principle of time domain reflectometer ( TDR) is presented. Methodology of applying RSO technique for rotor windings is detailed. Wave patterns for possible inter turn shorts with a demo delay unit are depicted. Case study on faulty windings of TG is presented. This novel detection technique benefits the customers to avoid sudden outages. KeywordsExcitation winding, inter turn shorts, recurrent surge oscillograph(RSO), time domain reflectometry
Four members of the HSP 101 gene family are differently regulated in Triticum durum Desf

Heat shock proteins play an essential role in preventing deleterious effects of high temperatures. In many plants, HSP101 has a central role in heat stress survival. We report the isolation and characterization of four cDNAs corresponding to different members of the durum wheat HSP101 gene family. Expression analysis revealed differences in their induction. Accordingly, durum wheat HSP101 genes are differently regulated, therefore having distinct roles in stress response and thermotolerance acquisition. These findings are important for further dissection of the molecular mechanisms underlying the stress response and for understanding the functions of the HSP101 family members. This information could be important for the exploitation of specific alleles in marker assisted selection for abiotic stress resistance. 2007 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
Probabilistic and Rule-Based Tagger of an In(cid:13)ective Language - a Comparison

We present results of probabilistic tagging of Czech texts in order to show how these techniques work for one of the highly morphologically ambiguous in(cid:13)ec-tive languages. After description of the tag system used, we show the results of four experiments using a simple probabilistic model to tag Czech texts (un-igram, two bigram experiments, and a trigram one). For comparison, we have applied the same code and settings to tag an English text (another four experiments) using the same size of training and test data in the experiments in order to avoid any doubt concerning the validity of the comparison. The experiments use the source channel model and maximum likelihood training on a Czech hand-tagged corpus and on tagged Wall Street Journal (WSJ) from the LDC collection. The experiments show (not surprisingly) that the more training data, the better is the success rate. The re-sults also indicate that for in(cid:13)ective languages with 1000+ tags we have to develop a more sophisticated approach in order to get closer to an acceptable error rate. In order to compare two di(cid:11)er-ent approaches to text tagging | statistical and rule-based | we modi(cid:12)ed Eric Brill’s rule-based part of speech tagger and carried out two more experiments on the Czech data, obtaining similar results in terms of the error rate. We have also run three more experiments with greatly reducedtagsetto
International Journal of Swarm Intelligence and Evolutionary Computation

Analysis of blood vessels in digital retinal fundus images is an important problem attempted in contemporary biomedical engineering research. In this work, normal and abnormal retinal images are pre-processed with adaptive histogram equalization and fuzzy filtering. Pre-processed images are then subjected to Tsallis multi-level thresholding method. The threshold levels determined by the chosen method are further optimized using bacterial foraging optimization techniques in order to improve the vessel content. The obtained results are validated using similarity measures by comparing with the corresponding ground truth of each image. Statistical and Tamura features are derived from optimal multi-level thresholding output images to analyse the healthy and pathological images. Results demonstrate that attempted series of pre-processing techniques enhances the edge information considerably and improves the efficacy of segmentation. It is observed that bacterial foraging optimization for Tsallis multi-level thresholding is able to extract retinal vasculature. Similarity measures show that this method provides considerable improvement in the extraction of vessel edges. Further, the statistical and Tamura features derived from detected vessels provide better differentiation between healthy and pathological images. As presence and absence of vessels in retina are clinically significant, the findings seem to be useful.
MIT Sloan School of Management

Motivated by emerging applications in workforce management, we consider a class of revenue management problems in systems with reusable resources. The corresponding applications are modeled using the well-known loss network systems. We use an extremely simple linear program (LP) that provides an upper bound on the best achievable expected long-run revenue rate. The optimal solution of the LP is used to devise a conceptually simple control policy that we call the class selection policy (CSP). Moreover, the LP is used to analyze the performance of the CSP policy. We obtain the (cid:2)rst control policy with uniform performance guarantees. In particular, for the model with single resource and uniform resource requirements, the CSP policy is guaranteed to have expected long-run revenue rate that is at least half of the best achievable. More generally, as the ratio between the capacity of the system and the maximum resource requirement grows to in(cid:2)nity, the CSP policy is asymptotically optimal, regardless of any other parameter of the problem. The asymptotic performance analysis that we obtain is more general than existing results in several important dimensions. It is based on several novel ideas that we believe will be useful in other settings.
AN OVERVIEW ON NATURAL RUBBER APPLICATION FOR ASPHALT MODIFICATION

Natural rubber with asphaltic materials is a great invention towards producing an admirable quality of asphalt paving roads. With its inherent chemical composition as elastomer kind of properties, this polymer modification can change the performance of current conventional asphalt paving roads which is recently faced limitation against temperature changes and traffic loading. Consequences, such as global market price of rubber turns in very uncertainty ways, has encouraged the government to seek for an alternative utilization of the natural rubber to backing up the industry. Therefore, natural rubber is seen as a preference material to multiply the quality of asphalt for road construction as well as to support the economic growth of the rubber industry. This paper provides an overview of natural rubber that has been applied as an additive in asphalt binder transformation. Numerous studies have been carried out on natural rubber based on different aspects of compatibility and interactions between the polymers and the asphalt aiming to improve the performances of the modified materials. From the review, the natural rubber used in a form of latex concentrated, Ribbed Smoked Sheet (RSS) and Liquid Natural Rubber (LNR) show promise in improving the asphalt mixes. Therefore, further study is needed to make them applicable as rubberized asphalt binder, thus provide better performance and services on the asphalt pavement.
The Effects of the Internet and Mobile Services on Urban Household Expenditures

In recent years, the economy of China has entered a new normal state and the economic growth rate has decelerated. The telecommunications industry as a national strategic and basic industry, is also facing up with some dilemma. Information consumption is a comprehensive concept including e-commerce, communications, broadband services, online games and so on. On this basis, this paper employs the almost ideal demand system(AIDS) to explore the impact that information consumption has made to residential consumption expenditure and the change of the consumption structure. Ac-cording to empirical analysis, finally we can draw the following conclusions: The income elasticity of information consumption is greater than 1, which means the income demand is flexible. And the self-price elasticity of information consumption is negative and the absolute value is between 0 and 1. It means that the price of information consumption is not flexible.
Unresponsive Flow Detection and Control in Differentiated Services Networks

During periods of congestion, TCP ﬂows back off and adjust the sending rate. This behavior makes TCP a conservative protocol and helps to avoid congestion collapse. Flows, like UDP, do not respond to congestion and keep sending packets. This causes other TCP ﬂows sharing the same link to back off. Un-responsive ﬂows waste resources by taking their shares in the up-stream and dropping packets later when the downstream is congested. We use the Differentiated Services (DiffServ) architecture to solve this problem. With the help of core routers of DiffServ networks, we detect congestion due to unresponsive ﬂows and us-ing edge routers we control/shape these ﬂows. We describe how core routers detect congestion and inform edge routers about it. We design an algorithm to regulate unresponsive ﬂows dynamically. Our rate control algorithm works well in a variety of situations. The goal of this work is to ensure that TCP does not starve due to unresponsive ﬂows as well as to stop bandwidth waste in the upstream path when packets are dropped in the downstream because of unresponsive ﬂows.
Leveraging Cofollowership Patterns on Social Media to Identify Brand Alliance Opportunities

The use of cobranding and brand extension strategies to access new markets has been a topic of significant interest. However, surprisingly few studies have examined cross-category connections of brands using publicly available digital footprints. In this study, the authors introduce a new, scalable automated approach for identifying potential cobranding and brand extension opportunities using brand networks derived from publicly available Twitter followership data. The digital user–brand relationship, established through followership activity, is regarded as an expression of interest toward the brand. Common followership patterns between brands are then extracted to capture cointerest between those brands’ audience. By utilizing the cointerest patterns, the approach aims to derive cross-category brand–brand and brand–category connections, which can serve as important measures for assessing cobranding and extensions opportunities. This article introduces a new construct, transcendence, which measures the extent to which a brand’s followers overlap with those of other brands in a new category. The analysis is conducted at different points in time to help managers track shifts in brand transcendence.
EAL: A Toolkit and Dataset for Entity-Aspect Linking

We present a toolkit and dataset for entity-aspect linking. The tool takes as input a sentence and provides the most relevant aspect for each mentioned entity; it is implemented in Python and available as a script and via an online demo. It is accompanied by the first large dataset of entity-aspects, comprising more than 20,000 entities manually linked to the most relevant aspect, given a sentence as context. Each is expressed in structured manner as Open Information Extraction (OIE) triples (Subject, Relation, Object), having semantic information for polarity, modality, quantity and attributions.
Probabilistic reasoning in intelligent systems - networks of plausible inference

From the Publisher: Probabilistic Reasoning in Intelligent Systems is a complete andaccessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertaintyand offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognitionin short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
Simulating Search Protocols in Large-Scale Dynamic Networks

Reproducing complex networks with features of real-life networks is exciting and challenging at the same time. Based on the popular Omnet++ discrete event simulator, we introduce Armonia, a framework for modeling massive networks and their dynamic interactions. It includes a collection of topology generators, a set of resource placement and replication modules, a component for specifying resource location strategies, while also offering support for exporting data in order to visualize or analyze with other appropriate tools. Our framework targets search protocols in large-scale dynamic networks. Here, we apply it to simulate various probabilistic flooding strategies, making a comparative study of their performance over different network topologies.
Robust Facial Expression Recognition Based on Local Directional Pattern

Automatic facial expression recognition has many potential applications in different areas of human computer interaction. However, they are not yet fully realized due to the lack of an effective facial feature descriptor. In this paper, we present a new appearancebased feature descriptor, the local directional pattern (LDP), to represent facial geometry and analyze its performance in expression recognition. An LDP feature is obtained by computing the edge response values in 8 directions at each pixel and encoding them into an 8 bit binary number using the relative strength of these edge responses. The LDP descriptor, a distribution of LDP codes within an image or image patch, is used to describe each expression image. The effectiveness of dimensionality reduction techniques, such as principal component analysis and AdaBoost, is also analyzed in terms of computational cost saving and classification accuracy. Two well-known machine learning methods, template matching and support vector machine, are used for classification using the Cohn-Kanade and Japanese female facial expression databases. Better classification accuracy shows the superiority of LDP descriptor against other appearance-based feature descriptors.
Indirect Current Control of LCL Based Shunt Active Power Filter 223

In a three phase system, harmonic currents produced due to the non linear loads can be compensated by the design, control and implementation of an LCL filter based shunt active power filter(SAPF). The proposed SAPF with LCL filter offers superior switching harmonic suppression. The designed inductance value will be smaller which reduces the harmonic voltage drop across the passive output filter. This in turn minimizes the possibility of over modulation and mainly for cases where high modulation index is required. The above advantages can be obtained only by proper consideration of critical design and control issues, like the selection of LCL parameters, harmonic compensation. The performances of the proposed shunt active power filter with passive(LCL) filter and the controller were examined by using MATLAB/SIMULINK software.
Menstrual cycle and timing of breast surgery in premenopausal node-positive breast cancer : Results of the International Breast Cancer Study Group ( IBCSG ) Trial

Purpose: It has been postulated that breast cancer surgery performed during the follicular phase of the menstrual cycle is associated with poorer outcome. Patients and methods: We tested this hypothesis by evaluating disease-free survival (DFS) for 1033 premenopausal patients who received definitive surgery either during the follicular phase (n = 358) or the luteal phase (n 675). All patients were enrolled in a randomized trial conducted between July 1986 and April 1993. All had node positive breast cancer and randomization was stratified by estrogen receptor (ER) status. All patients received at least three cycles of adjuvant cyclophosphamide, methotrexate, and 5-fluorouracil (CMF). The median follow-up was 60 months. Results: Patients who underwent definitive surgery for breast cancer in the follicular phase had a slightly worse disease-free survival than those operated on during the luteal phase (five-year DFS percentage: 53% versus 58%; hazard ratio, 1.13; 95% confidence interval (CI), 0.94-1.38; P = 0.20). The effect was significantly greater for the subpopulation of 300 patients with ER-negative primaries (P = 0.02 interaction effect; five-year DFS percentages 42% vs. 59%; hazard ratio 1.60; 95% CI, 1.12-2.25; P = 0.008). The effect of timing of surgery diminished for analyses based on lesser surgical procedures, e.g., excisional biopsies. In particular, no effect of timing was observed for fine needle aspiration procedures. Conclusions: Surgical procedures which are more extensive than a fine needle aspiration biopsy might be associated with worse prognosis if conducted during the follicular phase of the menstrual cycle. This phenomenon was seen predominantly for high risk breast cancer with low levels or no estrogen receptors in the primary tumor.
INTENT PHRASES AND THEIR RELATIONSHIPS 4 . 1 Intent Phrases

A significant portion of web search queries are name entity queries. The major search engines have been exploring various ways to provide better user experiences for name entity queries, such as showing “search tasks” (Bing search) and showing direct answers (Yahoo! , Kosmix). In order to provide the search tasks or direct answers that can satisfy most popular user intents, we need to capture these intents, together with relationships between them. In this paper we propose an approach for building a hierarchical taxonomy of the generic search intents for a class of name entities (e.g., musicians or cities). The proposed approach can find phrases representing generic intents from user queries, and organize these phrases into a tree, so that phrases indicating equivalent or similar meanings are on the same node, and the parent-child relationships of tree nodes represent the relationships between search intents and their sub-intents. Three different methods are proposed for tree building, which are based on directed maximum spanning tree, hierarchical agglomerative clustering, and pachinko allocation model. Our approaches are purely based on search logs, and do not utilize any existing taxonomies such as Wikipedia. With the evaluation by human judges (via Mechanical Turk), it is shown that our approaches can build trees of phrases that capture the relationships between important search intents.