Miracle-dz/UniFAR-FTUs huggingface dataset:
Significant information encapsulation and valence exploitation (SIEVE) for discovery

In intelligence analysis environments, content such as entities, events and relationships appear in different source documents and contexts, and relating them is a challenging and intensive task. This paper presents an approach to reducing the volume and variety of the content by automatically associating them. The SIEVE architecture is built on the following technologies: (1) Backus-Naur Form (BNF) grammar structures to capture the possible relationships between people, places and organizations, (2) parsing structures to transform the relationships into numerical values, (3) relating these values to the analyst's model of interest or “initial shoebox” and the creation of information graphs, and (4) parsing the graphs and using semantic algorithms to link these graphs to external information in larger data repositories. A graph analytic approach for associating entities is presented in this paper.
Nanoscale SiGe BiCMOS technologies: From 55 nm reality to 14 nm opportunities and challenges

This paper looks back to the development of highspeed BiCMOS technologies in STMicroelectronics for the past 15 years and discusses the perspectives for next generations through the CMOS angle. Opportunities and challenges of nanoscale BiCMOS technologies are reviewed and BiCMOS055 results are presented to demonstrate the feasibility at 55 nm node. Perspectives to offer FDSOI BiCMOS technologies at 28 nm or 14 nm nodes are analyzed too.
Declarative Transport No more transport protocols to design, only policies to specify

The general consensus is that the current Internet architecture is running out of steam. Incremental point-solutions have almost been exhausted and are no longer adequate. Networks have become more brittle and harder to manage, forcing the research community to launch a tremendous effort to develop and evaluate new Internet architectures. Part of that effort focused on declarative networking—a way to specify network protocols in a domain-specific declarative language. Declarative languages allow one to specify the “what” and not the “how”. The ease of programming, compactness of the specification, the reusability of the code, as well as the security provided by the restricted expressiveness of the language significantly simplify the programmability of network protocols. This has led to the declarative specification of routing protocols [5, 8], overlays [7], as well as sensor network architectures and applications [2,10], just to name a few. Meanwhile, the Internet continues to grow. New network technologies (e.g., wireless, cellular, ad hoc, sensor and mesh networks) and new applications continue to emerge. These new network technologies come with new Quality-ofService (QoS) properties while new applications come with new QoS requirements. This puts the state of transport solutions in a never-ending flux as they are continuously adapted for new environments. In general, the problem with existing transport solutions is three-fold: 1) they only work well for the environment they were designed for, 2) there are too many protocols but no unified framework, and 3) they do not go beyond static protocol instantiations. To address these problems, the contributions of our work can be summarized as follows:
Chain-Based Approach for Fast Through-Silicon-Via Coupling Delay Estimation

A chain-based coupling delay estimation method for through-silicon-vias (TSVs) in 3-D integrated circuits is proposed. Existing works target the worst case scenarios and this leads to inaccurate TSV coupling delay estimations, as the worst case may not occur during normal operation. The proposed method calculates the TSV coupling delay using simulation-based switching data. In addition, our TSV chain method allows us to capture the effects of nonneighboring TSVs accurately. Our simulations show that the error introduced by our method without using HSPICE is less than 10 ps even in TSV-crowded regions.
SR-RRT: Selective retraction-based RRT planner

We present a novel retraction-based planner, selective retraction-based RRT, for efficiently handling a wide variety of environments that have different characteristics. We first present a bridge line-test that can identify regions around narrow passages, and then perform an optimization-based retraction operation selectively only at those regions. We also propose a non-colliding line-test, a dual operator to the bridge line-test, as a culling method to avoid generating samples near wide-open free spaces and thus to generate more samples around narrow passages. These two tests are performed with a small computational overhead and are integrated with a retraction-based RRT. In order to demonstrate benefits of our method, we have tested our method with different benchmarks that have varying amounts of narrow passages. Our method achieves up to 21 times and 3.5 times performance improvements over a basic RRT and an optimization-based retraction RRT, respectively. Furthermore, our method consistently improves the performances of other tested methods across all the tested benchmarks that have or do not have narrow passages.
Ontology-based Semantic Web services framework for knowledge management system

The latest Semantic Web developments and insights in knowledge management challenge the new era of semantic-based knowledge-management systems, where lies the new possibilities that Semantic Web affords for improved knowledge management. Connectivity and interoperability of knowledge management systems is the key to the vision of the future. We need a comprehensive framework that addresses main issues related to distributed Knowledge Management. Semantic Web Services (SWS) is the next major generation of the Web in which e-services and business communication become more knowledge-based. It proposes to extend the traditional Web Services technologies with its key enabling technologies of ontologies and semantics; to solve the problem of heterogeneity and interoperability of data across applications. This makes it possible to select, integrate and invocate services dynamically, which enable services to adapt themselves to changes without human intervention. The main purpose of this paper is to present the relevance of SWS technologies to KMS. Further, we discuss about the two major initiatives in SWS research. Later, we will propose ontology based semantic web services framework for KMS. Our focus is in the web service provider layer where we will introduce the three main components; knowledge manager, web service manager and ontology mapping manager.
Fair sharing of bandwidth in VANETs

We address the challenge of how to share the limited wireless channel capacity for the exchange of safety-related information in a fully deployed vehicular ad hoc network (VANET). In particular, we study the situation that arises when the number of nodes sending periodic safety messages is too high in a specific area. In order to achieve a good performance of safety-related protocols, we propose to limit the load sent to the channel using a strict fairness criterion among the nodes. A formal definition of this problem is presented in terms of a max-min optimization problem with an extra condition on per-node maximality. Furthermore, we propose FPAV, a power control algorithm which finds the optimum transmission range of every node, and formally prove its validity under idealistic conditions. Simulations are performed to visualize the result of FPAV in a couple of road situations. Finally, we discuss the issues that must be taken into account when implementing FPAV.
Peer-to-peer similarity search over widely distributed document collections

This paper addresses the challenging problem of similarity search over widely distributed ultra-high dimensional data. Such an application is retrieval of the top-k most similar documents in a widely distributed document collection, as in the case of digital libraries. Peer-to-peer (P2P) systems emerge as a promising solution to delve with content management in cases of highly distributed data collections. We propose a self-organizing P2P approach in which an unstructured P2P network evolves into a super-peer architecture, with super-peers responsible for peers with similar content. Our approach is based on distributed clustering of peer contents, thus managing to create high quality clusters that span the entire network. More importantly, we show how to efficiently process similarity queries capitalizing on the newly constructed, clustered super-peer network. During query processing, the query is propagated only to few carefully selected super-peers that are able to return results of high quality. We evaluate the performance of our approach and demonstrate its advantages through simulation experiments on two document collections.
Emulating Mental State in Natural Language Generation Systems

Emotional and psychological states are important factors in how people use language. Any natural language generation system which attempts to appear truly natural will need to take this into account. There are a variety of psychological studies describing these effects, but only a few which provide quantitative data. This paper describes PsychoGen, a natural language generation system based on one such set of studies. This system is shown to handle small domains well, but fundamentally unable to properly model complex psychological states such as schizophrenia.
Smoking in Cape Town: community influences on adolescent tobacco use.

BACKGROUND This paper examines the effect of pro- and antisocial opinions about communities on cigarette use by Black, Colored, and White 8th- and 11th-grade students in Cape Town, South Africa. METHODS This analysis consists of 1,328 students who completed a questionnaire in 1997 on sociodemographic characteristics, substance abuse, adolescent behaviors, and opinions about their communities. Structural equation modeling (SEM) was used to assess hypotheses related to the social development model positing direct and indirect associations between community constructs and smoking within the previous 31 days. RESULTS White students had the highest proportion (36.3%, P < 0.01) of past-31-days smokers compared to Colored (29.7%) and Black (9.7%) students. SEM analysis showed that among all groups the strongest association (beta = 0.29, Whites, P < 0.01; beta =.14, Coloreds, P < 0.01; beta = 0.05, Blacks, P < 0.05) with recent cigarette smoking was the personal knowledge of adults who engaged in antisocial behavior. CONCLUSIONS Youth smoking behavior may be affected by antisocial adult behavior, subjective adult norms, and community affirmation. Thus, in addition to other factors, social norms and community influence should be considered in preventing adolescent smoking.
Forbidden state space trajectories of PWM converters: implication to digital control

The possible trajectories of the state vector values (i/sub L/(t) and v/sub C/(t)) of buck and boost PWM converters under large transients are examined and evaluated. The forbidden trajectories, detected by examining the state space traces, impose sever limitation on the control design. These limitations are best demonstrated by investigation of large signal transient response of conventional linear controllers. Based on this investigation, a simple discrete control rule is proposed. Based on it, a preliminary simple discrete control function for a boost converter was tested and compared to a linear peak current mode (PCM) control.
Modified hysteresis current-controlled PWM strategy for Single phase grid connected inverters

As the power demand increases rapidly in the electricity market the use of renewable energy sources also increasing. Renewable sources are significantly different from the traditional power sources due to their stochastic nature. Therefore it is a tough task to integrate renewable energy sources with the existing utility grid. In order to ensure the grid reliability, current controlled Pulse Width Modulated VSI is used to interface renewable energy sources with utility grid. This paper presents a relative analysis between Conventional Hysteresis Current Controller (CHCC) and Modified Hysteresis Current Controller (MHCC) for 1-Φ grid integrated inverter system. The benefit MHCC is, it avoids short circuiting of the DC link voltage. Further MHCC gives more sinusoidal current and lesser THD than that of CHCC. The MATLAB Simulink environment is used to model, study and stimulate the system.
Health care access, concentrated poverty, and pediatric asthma hospital care use in California's San Joaquin Valley: A multilevel approach

ABSTRACT Background: California's San Joaquin Valley is a region with a history of poverty, low health care access, and high rates of pediatric asthma. It is important to understand the potential barriers to care that challenge vulnerable populations. Objective: The objective was to describe pediatric asthma-related utilization patterns in the emergency department (ED) and hospital by insurance coverage as well as to identify contributing individual-level indicators (age, sex, race/ethnicity, and insurance coverage) and neighborhood-level indicators of health care access. Methods: This was a retrospective study based on secondary data from California hospital and ED records 2007–2012. Children who used services for asthma-related conditions, were aged 0–14 years, Hispanic or non-Hispanic white, and resided in the San Joaquin Valley were included in the analysis. Poisson multilevel modeling was used to control for individual- and neighborhood-level factors. Results: The effect of insurance coverage on asthma ED visits and hospitalizations was modified by the neighborhood-level percentage of concentrated poverty (RR = 1.01, 95% CI = 1.01–1.02; RR = 1.03, 95% CI = 1.02–1.04, respectively). The effect of insurance coverage on asthma hospitalizations was completely explained by the neighborhood-level percentage of concentrated poverty. Conclusions: Observed effects of insurance coverage on hospital care use were significantly modified by neighborhood-level measures of health care access and concentrated poverty. This suggests not only an overall greater risk for poor children on Medi-Cal, but also a greater vulnerability or response to neighborhood social factors such as socioeconomic status, community cohesiveness, crime, and racial/ethnic segregation.
Lower bounds for distributed markov chain problems

We study the worst-case communication complexity of distributed algorithms computing a path problem based on stationary distributions of random walks in a network $G$ with the caveat that $G$ is also the communication network. The problem is a natural generalization of shortest path lengths to expected path lengths, and represents a model used in many practical applications such as pagerank and eigentrust as well as other problems involving Markov chains defined by networks. For the problem of computing a single stationary probability, we prove an $\Omega(n^2 \log n)$ bits lower bound; the trivial centralized algorithm costs $O(n^3)$ bits and no known algorithm beats this. We also prove lower bounds for the related problems of approximately computing the stationary probabilities, computing only the ranking of the nodes, and computing the node with maximal rank. As a corollary, we obtain lower bounds for labelling schemes for the hitting time between two nodes.
Coverage and Rate Analysis for Massive MIMO-Enabled Heterogeneous Networks with Millimeter Wave Small Cells

The existing cellular networks are being modified under the umbrella of fifth generation (5G) networks to provide high data rates with optimum coverage. Current cellular systems operating in ultra high frequency (UHF) bands suffer from severe bandwidth congestion hence 5G enabling technologies such as millimeter wave (mmWave) networks focus on significantly higher data rates. In this paper, we explore the impact of co-existance of massive Multiple-Input Multiple-Output (MIMO) that provides large array gains and mmWave small cells on coverage. We investigate the downlink performance in terms of coverage and rate of a three tier network where a massive MIMO macro base stations (MBSs) are overlaid with small cells operating at sub-6GHz and mmWave frequency bands. Based on the existing stochastic models, we investigate user association, coverage probability and data rate of the network. Numerical results clearly show that massive MIMO enabled MBSs alongside mmWave small cells enhance the performance of heterogeneous networks (HetNets) significantly.
A paradox of individual and group morality: Social psychology as empirical philosophy

Our colleague John Schopler used to tell us—gleefully, one might add— that whereas philosophy makes the trivial sublime, social psychology makes the sublime trivial. It was with equal measures of enthusiasm and trepidation, then, that we decided to approach a classic problem of philosophy—the question of whether humankind can attain perfection—from a social-psychological perspective. The aforementioned question can be traced through three millennia of intellectual history and, over the course of time, has taken on a variety of meanings (Passmore, 2000). We are concerned here with the question of whether humankind can achieve moral perfection or “can be entirely free of any moral defect” (Passmore, 2000, p. 27). In the spirit of this volume, we aim to illustrate how social psychology can benefit from greater familiarity with philosophy and how, through empirical research, social psychology can inform classic philosophical problems. Our thesis is that the incompatibility of the moral code governing interindividual relations with a more selfish moral code governing intergroup relations blocks the path of moral progress. In the first part of this essay we draw on philosophical literature to offer a rationale for this thesis before examining it empirically in the second part. We take as our point of departure the turn of the 19th century—a time of widespread belief in moral perfectibility. This optimism derived from a variety
Computational types from a logical perspective

Moggi's computational lambda calculus is a metalanguage for denotational semantics which arose from the observation that many different notions of computation have the categorical structure of a strong monad on a cartesian closed category. In this paper we show that the computational lambda calculus also arises naturally as the term calculus corresponding (by the Curry–Howard correspondence) to a novel intuitionistic modal propositional logic. We give natural deduction, sequent calculus and Hilbert-style presentations of this logic and prove strong normalisation and confluence results.
Fast Rhetorical Structure Theory Discourse Parsing

Author(s): Heilman, Michael; Sagae, Kenji | Abstract: In recent years, There has been a variety of research on discourse parsing, particularly RST discourse parsing. Most of the recent work on RST parsing has focused on implementing new types of features or learning algorithms in order to improve accuracy, with relatively little focus on efficiency, robustness, or practical use. Also, most implementations are not widely available. Here, we describe an RST segmentation and parsing system that adapts models and feature sets from various previous work, as described below. Its accuracy is near state-of-the-art, and it was developed to be fast, robust, and practical. For example, it can process short documents such as news articles or essays in less than a second.
Removal of cerebrospinal fluid partial volume effects in quantitative magnetization transfer imaging using a three‐pool model with nonexchanging water component

Parameters of the two‐pool model describing magnetization transfer (MT) in macromolecule‐rich tissues may be significantly biased in partial volume (PV) voxels containing cerebrospinal fluid (CSF). The purpose of this study was to develop a quantitative MT (qMT) method that provides indices insensitive to CSF PV averaging.
A Linguistically Annotated Reordering Model for BTG-based Statistical Machine Translation

In this paper, we propose a linguistically annotated reordering model for BTG-based statistical machine translation. The model incorporates linguistic knowledge to predict orders for both syntactic and non-syntactic phrases. The linguistic knowledge is automatically learned from source-side parse trees through an annotation algorithm. We empirically demonstrate that the proposed model leads to a significant improvement of 1.55% in the BLEU score over the baseline reordering model on the NIST MT-05 Chinese-to-English translation task.
Performance evaluation of a new gamma imager for small animal SPECT applications

In this work we characterized a recently developed gamma imager for small animal SPECT applications. The Hamamatsu C9177 is a mini-gamma camera that integrates the detector and all the electronics, including the acquisition system, in a compact and portable housing. The detector is based on a high resolution parallel hole collimator, a CsI(NaI) crystal array and a PS-PMT (flat panel type). The active field of view is 41.9 times 41.9 mm2 and the assembly is optimized for 60 to 200 keV. The electronics in the housing includes the high voltage divider, an ASIC which converts the 64 anodes into Anger-like signals, ADCs which are fed with these signals and position and energy lookup tables which allow digital information for each detected photon to be obtained directly from the imager. In order to be able to obtain tomographic data and to improve the measurement protocols, we mounted the detector in a custom-built motorized gantry. We evaluated detector uniformity and energy resolution using a flood field image. Planar intrinsic spatial resolution and spatial linearity were assessed by stepping a capillary source across the detector surface and plotting the count profile for each individual crystal of the array. We additionally performed phantom studies to preliminarily characterize the tomographic performance. Energy resolution is 11.6% (mean), sensitivity is 2.54 cps/muCi and planar spatial resolution is 2.4 mm (CFOV 20 % energy window) when the source is placed on the detector surface.
Hierarchical geographical modeling of user locations from social media posts

With the availability of cheap location sensors, geotagging of messages in online social networks is proliferating. For instance, Twitter, Facebook, Foursquare, and Google+ provide these services both explicitly by letting users choose their location or implicitly via a sensor. This paper presents an integrated generative model of location and message content. That is, we provide a model for combining distributions over locations, topics, and over user characteristics, both in terms of location and in terms of their content preferences. Unlike previous work which modeled data in a flat pre-defined representation, our model automatically infers both the hierarchical structure over content and over the size and position of geographical locations. This affords significantly higher accuracy --- location uncertainty is reduced by 40% relative to the best previous results [21] achieved on location estimation from Tweets. We achieve this goal by proposing a new statistical model, the nested Chinese Restaurant Franchise (nCRF), a hierarchical model of tree distributions. Much statistical structure is shared between users. That said, each user has his own distribution over interests and places. The use of the nCRF allows us to capture the following effects: (1) We provide a topic model for Tweets; (2) We obtain location specific topics; (3) We infer a latent distribution of locations; (4) We provide a joint hierarchical model of topics and locations; (5) We infer personalized preferences over topics and locations within the above model. In doing so, we are both able to obtain accurate estimates of the location of a user based on his tweets and to obtain a detailed estimate of a geographical language model.