Miracle-dz/UniFAR-FTUs huggingface dataset:
SISSA , International School for Advanced Studies Via Beirut 2-4 , 34013 Trieste Italy

We give a natural definition of a Poisson Differential Algebra. Consistence conditions are formulated in geometrical terms. It is found that one can often locally put the Poisson structure on differential calculus in a simple canonical form by a coordinate transformation. This is in analogy with the standard Darboux’s theorem for symplectic geometry. For certain cases there exists a realization of the exterior derivative through a certain canonical one-form. All the above are carried out similarly for the case of a complex Poisson Differential Algebra. The case of one complex dimension is treated in details and interesting features are noted. A conclusion is made in the last section. This work was supported in part by the Director, Office of Energy Research, Office of High Energy and Nuclear Physics, Division of High Energy Physics of the U.S. Department of Energy under Contract DE-AC03-76SF00098 and in part by the National Science Foundation under grant PHY-9514797. e-mail address: cschu@sissa.it e-mail address: pmho@mail.physics. utah.edu
Surveillance from above: A detection-and-prediction based multiple target tracking method on aerial videos

Along with the rapid development of the Unmanned Aerial Vehicle (UAV) technology, visual traffic surveillance is now granted with a great opportunity to become mobilized. Airborne mounted surveillance cameras are suitable to work as an ideal alternative to the traditional stationary cameras to provide more coverage with lower expense. For realizing such a solution, in this paper we engineered an efficient multiple targets tracking method designed for aerial videos captured by low-altitude UAVs. This method combines the strengths of both Tracking-by-Detection (T-by-D) and Tracking-by-Prediction (T-by-P) framework, where the target detection is first performed with an integrated motion detection module, then the traditional data association component is substituted by a detection-and-prediction based category-free blob tracking scheme. To overcome the camera jitter introduced by the UAV platform, a reliable image registration method is also implemented as a pre-processing operation. Extensive experiments have demonstrated the effectiveness and reliability of the proposed method.
Cool Customers in the Stellar Graveyard. I. Limits to Extrasolar Planets Around the White Dwarf G29-38

We present high-contrast images of the hydrogen white dwarf G29-38 taken in the near-infrared with the Hubble Space Telescope and the Gemini North Telescope as part of a high-contrast imaging search for substellar objects in orbit around nearby white dwarfs. We review the current limits on planetary companions for G29-38, the only nearby white dwarf with an infrared excess due to a dust disk. We add our recent observations to these limits to produce extremely tight constraints on the types of possible companions that could be present. No objects >6MJ are detected in our data at projected separations >12 AU, and no objects >16MJ are detected for separations from 3 to 12 AU, assuming a total system age of 1 Gyr. Limits for companions at separations <3 AU come from a combination of Two Micron All Sky Survey (2MASS) photometry and previous studies of G29-38's pulsations. Our imaging with Gemini cannot confirm a tentative claim for the presence of a low-mass brown dwarf. These observations demonstrate that a careful combination of several techniques can probe nearby white dwarfs for large planets and low-mass brown dwarfs.
Exploring Phonotactics with Simple Recurrent Networks

Stoianov, Nerbonne and Bouma (1998) trained Simple Recurrent Networks (SRNs) on graphotactics of Dutch monosyllabic words, overcoming shortcomings of previous implementations. The current report is a continuation of our earlier research, but using phonetic data representations instead of orthographic, that is, learning phonotactics. In addition, we conducted further analysis of neural network performance with regard to some variables such as word frequency, length, neighborhood density and error location. The results are compared with reported psycholinguistics analyses. This informal comparison of SRNs and human performance suggests that SRNs can be used for modeling natural language
Relationship Between The Perceived Principal Support, Trust İn Principal And Organizational Commitment

Article History: Received 03.01. 2017 Received in revised form 31.07. 2017 Accepted 12.08. 2017 Available online 25.08. 2017 The purpose of this study was to examine the relationships between teachers’ perceived principal support, trust in principal and organizational commitment. The population of the study consisted of 2100 teachers working in the schools of Bingöl central district in 2014-2015 academic year. In the study, no sample was chosen and it was tried to reach the whole population. The workgroup of the study consists of 648 voluntarily participated teachers. Both correlational and causal-comparative research designs were used in the study. Research data were gathered with “Principal Support Scale”, “Trust in Principal Scale” and “Organizational Commitment Scale. ” For the analysis of the data; exploratory factor analysis, independent samples t-test, one-way Anova, correlation analysis and multiple regression analysis were used. Correlation analysis results showed positive and high level of significant correlations between the perceived principal support and trust in principal, and organizational commitment. It was also found that all the subscales of principal support scale which are emotional support, instrumental support, professional support, appraisal support are significant predictors of trust in principal. It was also founded that except for the instrumental support, the other three subscales of principal support scale (emotional support, professional support and appraisal support) are significant predictors of organizational commitment. © 2017 IOJES. All rights reserved
Im/mobilising the migration decision

This paper reconsiders the concept of the decision in geographical research on migration by refracting it through contemporary “mobilities” thinking. In doing so, I seek to develop an approach attentive to the way migrations take hold and persist in space and time. Whilst conceptualisations of the decision in migration have moved beyond their individualist heritage, sovereign models of strong agency remain implicit, often unintentionally conflating intention, effectiveness, cause and outcome. In contrast, I elaborate a relational understanding of the decision to conceptualise a decision’s limited efficacy in generating and sustaining a migration over time. Underscoring the neglected importance of stasis to migration, I trace corollaries of the mobilities dialectic of movement and stasis on the relation between action and outcome, emphasising the finite relevancy of any moment of decision. Focussing empirically on the story of a single migrant worker’s return migration in rural China, I draw on alternative accounts of agency – habit, lateral agency, and the agency of assemblages – to rework the migration decision into an ongoing process of affecting and being affected. Thinking with this case, I reconfigure the relationship between migration, event, decision and place, and affirm the value of the under-used mobilities optic in migration research.
The synchrony between baroreflex sequences and cardio-respiratory activity

The bias observed between methods developed to assess the baroreflex control of Heart Rate (HR) lead to gain further insight into those methods. In two groups of subjects were studied: a group of young adults, and a group of middle-aged adults, cardiovascular (CV) and respiratory parameters were continuously recorded during a graded bicycle exercise. This study focused on the sequence method, and its particular time sequence pattern (up and down sequences). Features of respectively the up and down sequences were analysed through comparative analysis and sequence pattern analysis. No significant changes were noticed between the up and down sequences for both the number of sequences and the baroreflex gain. A synchrony was present according to the phase of respiration and also with the diastolic arterial pressure (dap). It may suggest a relation between the baroreflex function and the Bainbridge reflex in governing CV oscillations.
The role of theories in conceptual coherence.

The question of what makes a concept coherent (what makes its members form a comprehensible class) has received a variety of answers. In this article we review accounts based on similarity, feature correlations, and various theories of categorization. We find that each theory provides an inadequate account of conceptual coherence (or no account at all) because none provides enough constraints on possible concepts. We propose that concepts are coherent to the extent that they fit people's background knowledge or naive theories about the world. These theories help to relate the concepts in a domain and to structure the attributes that are internal to a concept. Evidence of the influence of theories on various conceptual tasks is presented, and the possible importance of theories in cognitive development is discussed.
Transport Capacity and Spectrum Power Efficiency of Large Wireless CDMA Ad Hoc Networks with Optimum Code Rate Allocation

In this paper, we study the transport capacity – the transported bit-meters per symbol period per node, and the space time spectrum power efficiency – the transported bit-meters per Hz per second per square meter per watt for large wireless CDMA ad hoc networks. The node density and processing gain tend to infinity with their ratio kept a constant. The limiting networks consist of infinitely dense, sender uniformly distributed, mutually independent, and memoryless Gaussian channels connecting all pairs of sending and receiving nodes on the entire 2-D plane. The MMSE receiver, decorrelator, and MF are employed. Gaussian input Gaussian noise channel, binary input Gaussian noise channel and symmetric binary channel are considered. The transport capacity and space time spectrum power efficiency with joint optimization of code rate distribution, MAC and routing protocols are obtained in closed form as functions of entire network profile.
UNIX as an Application Program

1. Abstract Since March of 1989 we have had running at CMU a computing environment in which the functions of a traditional Unix system are cleanly divided into two parts: facilities which manage the hardware resources of a computer system (such as CPU, I/O and memory) and support for higher-level resource abstractions used in the building of application programs, e.g. files and sockets. This paper describes the implementation of Unix as a multithreaded application program running on the Mach kernel. The rationale, design, implementation history and performance of the system is presented.
Terminating Links between Emission Trading Programs

Links between emission trading programs are not immutable, as highlighted by New Jersey׳s exit from the Regional Greenhouse Gas Initiative in 2011. This raises the question of what to do with existing permits that are banked for future use—choices that have consequences for market behavior in advance of, or upon speculation about, delinking. We consider two delinking policies. One differentiates banked permits by origin, the other treats banked permits the same. We describe the price behavior and relative cost-effectiveness of each policy. Treating permits differently generally leads to higher costs, and may lead to price divergence, even with only speculation about delinking.
Structural Learning of Diverse Ranking

Relevance and diversity are both crucial criteria for an effective search system. In this paper, we propose a unified learning framework for simultaneously optimizing both relevance and diversity. Specifically, the problem is formalized as a structural learning framework optimizing Diversity-Correlated Evaluation Measures (DCEM), such as ERR-IA, a-NDCG and NRBP. Within this framework, the discriminant function is defined to be a bi-criteria objective maximizing the sum of the relevance scores and dissimilarities (or diversity) among the documents. Relevance and diversity features are utilized to define the relevance scores and dissimilarities, respectively. Compared with traditional methods, the advantages of our approach lie in that: (1) Directly optimizing DCEM as the loss function is more fundamental for the task; (2) Our framework does not rely on explicit diversity information such as subtopics, thus is more adaptive to real application; (3) The representation of diversity as the feature-based scoring function is more flexible to incorporate rich diversity-based features into the learning framework. Extensive experiments on the public TREC datasets show that our approach significantly outperforms state-of-the-art diversification approaches, which validate the above advantages.
Dynamic weighted discrimination power analysis in DCT domain for face and palmprint recognition

Discrimination power analysis (DPA) is a statistical analysis combining discrimination concept with discrete cosine transform coefficients (DCTCs) properties. Unfortunately there is not a uniform and effective criterion to optimize the shape and size of premasking window on which the effect of DPA excessively relies. Proper premasking is an auxiliary process to select the feature coefficients that have more discrimination power (DP). Dynamic weighted DPA (DWDPA) is proposed in this paper to enhance the DP of the selected DCTCs without premasking window, in other words, it does not need to optimize the shape and size of premasking window. The DCTCs are adaptively selected according to their discrimination power values (DPVs). More DCTCs with higher DP are preserved. The selected coefficients are normalized and dynamic weighted according to their DPVs. Normalization assures that the DCTCs with large absolute value don't destroy the DP of the other DCTCs that have less absolute value but high DPVs. Dynamic weighting gives larger weights to the DCTCs with larger DPVs which optimizes and enhances the recognition performance. The experimental results on ORL, Yale and PolyU databases show that DWDPA outperforms DPA obviously.
Multi-Document summarization based on improved features and clustering

Multi-Document summarization is an emerging technique for understanding the main purpose of many documents about the same topic. This paper proposes a new feature selection method to improve the summarization result. When calculating similarity, we use a modified TFIDF formula which achieves a better result. We adopt two ways for exactly extracting keywords. Experimental results demonstrate that our improved method performs better than the traditional one.
Neighborhood Discriminant Nearest Feature Line Analysis for Face Recognition

A novel subspace learning algorithm named neighborhood discriminant nearest feature line analysis (NDNFLA) is proposed in this paper. NDNFLA aims to find the discriminant feature of samples by maximizing the between-class feature line (FL) distances and minimizing the within-class FL distance. At the same time, theneighborhood is preserved in the feature space. Experimental results demonstrate the efficiency of the proposed algorithm.
International Conference on Intelligent Robots and Systems Straight Legged Walking of a Biped Robot

This paper presents a new methodology for generating a straight legged walking pattern for a biped robot utilizing up-and-down motion of an upper body. Firstly, we define two new indexes, the Knee Stretch Index (KSI) and the Knee Torque Index (KTI), which indicate how efficiently the knee joints are utilized. Next, up-and-down motion of the upper body is automatically planned so that these indexes are optimized and straight legged walking is realized. The basic idea of the proposed method is, i) when a large number of DOFs of motion are required for controlling the ZMP, a robot makes its body height lower, ii) when there is a extra number of DOFs of motion, the body is lifted and the knee joint is stretched. By stretching the knee joints, human-like natural walking motion is obtained. Moreover, energy efficiency is improved since required torque and energy consumption to support the body weight become small at knee joints. The effectiveness of the proposed method is demonstrated by computer simulation and experiments using a humanoid robot, HOAP-1.
Layout Analysis of Urdu Document Images

Layout analysis is a key component of an OCR system. In this paper, we present a layout analysis system for extracting text-lines in reading order from Urdu document images. For this purpose, we evaluate an existing system for Roman script text on Urdu documents and describe its methods and the main changes necessary to adapt it to Urdu script. The main changes are: 1) the text-line model for Roman script is modified to adapt to Urdu text, 2) reading order of an Urdu document is defined. The method is applied to a collection of scanned Urdu documents from various books, magazines, and newspapers. The results show high text-line detection accuracy on scanned images of Urdu prose and poetry books and magazines. The algorithm also works reasonably well on newspaper images. We also identify directions for future work which may further improve the accuracy of the system.
Detection of road obstacles using dynamic programming for remapped stereo images to a top-view

This paper proposes an artificial vision algorithm capable of extracting road vehicles in front of a stereo system as well as determining the distance between the stereo system and the detected vehicles. The algorithm transforms stereo perspective images into a virtual top-view. Using edge information of the transformed stereo images, polar accumulation functions (PAFs) are formed. Two processes called spatial and temporal peak joining are introduced to search for corresponding peaks between PAFs based on dynamic programming, which solves the typical stereo correspondence problem without a disparity computation. The proposed algorithm has been proven to be successful through a lot of experiments in various environments.
Development of digital watermarking application technologies for newspapers

Newspapers, no different from other copyrighted works, are protected by the copyright laws. However, as the duplication itself is technically executable without any license agreement, in cases where users are ignorant of the copyright laws or have no intent to honor them, copies of newspapers end up to be illegally produced. In this paper, we report experiments for applying digital watermarking to newspapers. Digital watermarking is utilized to realize copyright management system that prevents illegal duplications while offering great convenience. Watermarking application is achieved in which the embedding artifacts are hardly noticeable and the embedded information extraction is stable.
A Comparative Analysis of the Complexity/Accuracy Tradeoff in Power Amplifier Behavioral Models

A comparative study of state-of-the-art behavioral models for microwave power amplifiers (PAs) is presented in this paper. After establishing a proper definition for accuracy and complexity for PA behavioral models, a short description on various behavioral models is presented. The main focus of this paper is on the modeling accuracy as a function of computational complexity. Data is collected from measurements on two PAs-a general-purpose amplifier and a Doherty PA designed for WiMAX-for different output power levels. The models are characterized in terms of accuracy and complexity for both in-band and out-of-band error. The results show that, among the models studied, the generalized memory polynomial behavioral model has the best tradeoff for accuracy versus complexity for both PAs, and can obtain high performance at half of the computational cost of all other models analyzed.
Social Media and Internet-Based Data in Global Systems for Public Health Surveillance: A Systematic Review

Context: The exchange of health information on the Internet has been heralded as an opportunity to improve public health surveillance. In a field that has traditionally relied on an established system of mandatory and voluntary reporting of known infectious diseases by doctors and laboratories to governmental agencies, innovations in social media and so-called user-generated information could lead to faster recognition of cases of infectious disease. More direct access to such data could enable surveillance epidemiologists to detect potential public health threats such as rare, new diseases or early-level warnings for epidemics. But how useful are data from social media and the Internet, and what is the potential to enhance surveillance? The challenges of using these emerging surveillance systems for infectious disease epidemiology, including the specific resources needed, technical requirements, and acceptability to public health practitioners and policymakers, have wide-reaching implications for public health surveillance in the 21st century. Methods: This article divides public health surveillance into indicator-based surveillance and event-based surveillance and provides an overview of each. We did an exhaustive review of published articles indexed in the databases PubMed, Scopus, and Scirus between 1990 and 2011 covering contemporary event-based systems for infectious disease surveillance. Findings: Our literature review uncovered no event-based surveillance systems currently used in national surveillance programs. While much has been done to develop event-based surveillance, the existing systems have limitations. Accordingly, there is a need for further development of automated technologies that monitor health-related information on the Internet, especially to handle large amounts of data and to prevent information overload. The dissemination to health authorities of new information about health events is not always efficient and could be improved. No comprehensive evaluations show whether event-based surveillance systems have been integrated into actual epidemiological work during real-time health events. Conclusions: The acceptability of data from the Internet and social media as a regular part of public health surveillance programs varies and is related to a circular challenge: the willingness to integrate is rooted in a lack of effectiveness studies, yet such effectiveness can be proved only through a structured evaluation of integrated systems. Issues related to changing technical and social paradigms in both individual perceptions of and interactions with personal health data, as well as social media and other data from the Internet, must be further addressed before such information can be integrated into official surveillance systems.