Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent Progress in Understanding Larval Dispersal: New Directions and Digressions

Synopsis Larvae have been difficult to study because their small size limits our ability to understand their behavior and the conditions they experience. Questions about larval transport focus largely on (a) where they go [dispersal] and (b) where they come from [connectivity]. Mechanisms of transport have been intensively studied in recent decades. As our ability to identify larval sources develops, the consequences of connectivity are garnering more consideration. Attention to transport and connectivity issues has increased dramatically in the past decade, fueled by changing motivations that now include management of fisheries resources, understanding of the spread of invasive species, conservation through the design of marine reserves, and prediction of climate-change effects. Current progress involves both technological advances and the integration of disciplines and approaches. This review focuses on insights gained from physical modeling, chemical tracking, and genetic approaches. I consider how new findings are motivating paradigm shifts concerning (1) life-history consequences; (2) the openness of marine populations, self-recruitment, and population connectivity; (3) the role of behavior; and (4) the significance of variability in space and time. A challenge for the future will be to integrate methods that address dispersal on short (intragenerational) timescales such as elemental fingerprinting and numerical simulations with those that reflect longer timescales such as gene flow estimates and demographic modeling. Recognition and treatment of the continuum between ecological and evolutionary timescales will be necessary to advance the mechanistic understanding of larval and population dynamics. Introduction Interest in the dispersal of larvae dates back to the seminal ideas of Hjort (1926) and Thorson (1946), who advocated the importance of larval transport and survival in determining the dynamics of fish and invertebrate populations, respectively. Since the 1980s there has been an increased awareness of " supply side " ecology granting larval studies a central position in the field of marine ecology. The number of articles addressing larval dispersal increased greatly during the 1990s (Fig. 1). A Web of Science search for articles using the key word " larval dispersal " shows 2003 (the last year surveyed) to be a peak year with 62 publications. Much of the larval work conducted during the last quarter of the twentieth century focused on mechanisms of transport (for example, see reviews by Hellberg and others 2002). The primary motivation was the idea that larval supply was a key determinant of adult population dynamics. There has been a resurgence of interest in larval …
Using an Enhanced Ant Colony System to Solve Resource- Constrained Project Scheduling Problem

†† Summary This study presents and evaluates a modified ant colony optimization (ACO) approach for the resource-constrained project scheduling problems. A modified ant colony system is proposed to solve the resource-constrained scheduling problems. A two-dimensional matrix is proposed in this study for scheduling activities with time, and it has a parallel scheme for solving project scheduling problems. There are two designed heuristic is proposed. The dynamic rule is designed to modify the latest starting time of activities and hence the heuristic function. In exploration of the search solution space, this investigation proposes a delay solution generation rule to escape the local optimal solution. Simulation results demonstrate that the proposed modified ant colony system algorithm provides an effective and efficient approach for solving project scheduling problems with resource constraints.
Room localization for distant speech recognition

The problem of room localization is to determine where, in a multi-room environment, a person is producing a speech utterance. In our work, we are exploiting the information gained from a network of microphones installed all over a house, where the lack of calibration of the microphone energies creates an additional challenge. This paper compares room localizers based on different features (such as energy and cross-correlation between microphones) and classifiers (such as neural networks and discriminative analysis). In order to evaluate the different room localizers in terms of word accuracy this paper also presents a complete distant speech recognition system which tries to take advantage of synergy between the different components without using any oracle information. Finally, the system is analyzed in terms of computational and time resources.
Synchronous approach to the functional equivalence of embeddedsystem implementations

Design space exploration is the process of analyzing several functionally equivalent alternatives to determine the most suitable one. A fundamental question is whether an implementation is consistent with the high-level specification or whether two implementations are "equivalent. " The synchronous assumption has made it possible to develop efficient procedures for establishing functional equivalence between different implementations in the domains of synchronous circuits and synchronous reactive systems. We extend this notion to embedded systems that do not satisfy the synchronous assumption inside their boundaries but only at the interface with the environment. Leveraging this property, we define synchronous equivalence for embedded systems that strongly resembles the concept of functional equivalence for sequential circuits. We develop efficient synchronous equivalence analysis algorithms for embedded system designs. The efficiency comes from analyzing the behavior statically on abstract representations, at a cost that some of the negative results may be false, i.e. the analysis is conservative. We develop primitives for making the representation more/less abstract, trading off complexity of the algorithms with the conservativeness of the results. We apply our analysis algorithms to an ATM switch and demonstrate that synchronous equivalence opens design exploration avenues uncharted before.
Experimenting with the MetaFork Framework Targeting Multicores

The work reported in this report evaluates the correctness, performance and usefulness of the four MetaFork translators (MetaFork to CilkPlus, CilkPlus to MetaFork, MetaFork to OpenMP, OpenMP to MetaFork). To this end, we run these translates on various input programs written either in CilkPlus or OpenMP, or both. We stress the fact that our purpose is not to compare the performance of the CilkPlus or OpenMP run-time systems and programming environments. The reader should notice that the codes used in this experimental study were written by different persons with different levels of expertise. In addition, the reported experimentation is essentially limited to one architecture (Intel Xeon) and one compiler (GCC). Therefore, it is delicate to draw any clear conclusions that would compare CilkPlus or OpenMP. For this reason, this questions is not addressed in this thesis And, once again, this is not the purpose of this work.
CardboardSense: Interacting with DIY Cardboard VR Headset by Tapping

DIY cardboard-based VR headset that enfolds a commodity smartphone is a popular means of achieving low cost immersive stereoscopic viewing experiences. However, existing applications for these devices have limited user-input capability, allowing mainly look-at control by head tilting. CardboardSense is a set of novel tap-gesture-based inputs that take advantage of the motion sensing capabilities already available in most smartphones. The key premise is that finger contacts with the cardboard surface produce incidental but detectable vibrations that can be reliably differentiated from typical user head motion. Moreover, tapping on different surface locations produces differentiable temporal signatures in the sensor signals. We present methods to extract and analyze these temporal patterns, and experimentally determine a set of tapping gestures that can be accurately recognized. Experimental results show promising potential for CardboardSense to extend the interactivity of future cardboard-based VR headset applications.
A STATISTIC FOR DESCRIBING PULSAR AND CLOCK STABILITIES

We propose a statistical measure suitable for com- paring the rotational stabilities of pulsars with one another and with terrestrial time scales. By a simple extension of notation long used in the clock community, we call the statisticz(�). Defined in terms of third-order polynomials fitted to sequences of measured time offsets, �z(�) is sensitive to variations in the frequency drift rate of the clock or pulsar. We apply the new sta- tistical formalism to real pulsar data and terrestrial time scales, and show that over the past 10 years these two kinds of data have comparable stabilities.
Here Today, Gone Tomorrow: Exploiting Transient Servers in Datacenters

Distributed applications assume that datacenter servers are available unless they fail. Transient servers, which are available temporarily for an uncertain amount of time, are cheaper and more energy efficient than stable servers, which have continuous availability. This article looks at an important characteristic of transient servers: advance warning of unavailability. The Yank system defines a bounded-time virtual machine migration mechanism that leverages an advance warning of a few seconds to provide high availability cheaply and efficiently at large scales.
Gender gaps in life expectancy and alcohol consumption in Eastern Europe. N-IUSSP: IUSSP's online news magazine. Feb 25, 2019."

Female life expectancy is higher than that of males, and this gender gap is largest in Eastern Europe. Sergi Trias-Llimos and Fanny Janssen show that alcohol-attributable mortality explained more than 15% of this gap in eight Central and Eastern European (CEE) countries in 2012, and describe how the situation has evolved over time. Their results suggest that effectively tackling alcohol abuse among young men in these countries would help to reduce the gender gap in life expectancy.
Supports for principals' sensemaking: Lessons from the Institute for Learning's Instructional Leadership Program in Baltimore, Maryland

Title of Document: SUPPORTS FOR PRINCIPALS’ SENSEMAKING: LESSONS FROM THE INSTITUTE FOR LEARNING’S INSTRUCTIONAL LEADERSHIP PROGRAM IN BALTIMORE, MARYLAND Gina Schuyler Ikemoto, Ph.D., 2007 Directed By: Dr. Meredith I. Honig, Education Policy and Leadership Current federal, state, and local policies increase demands on school principals to take an active role in leading instructional improvement within their schools. For many principals “instructional leadership” (IL) represents a fundamentally new set of knowledge, skills, and practices. Accordingly, principals need assistance in engaging in IL. However, research on IL and principal professional development generally has not elaborated what such assistance might entail or how to implement it. This study addresses this research gap. First, it frames the problem of assisting principals’ engagement in IL as in part a challenge of supporting their sensemaking about what IL involves and how to exercise it in ways relevant to their local contexts. Then it elaborates how concepts from socio-cultural learning theory help reveal features of assistance that support such sensemaking processes. Data come from an in-depth case study of the Institute for Learning’s (IFL’s) Instructional Leadership Program (ILP) in Baltimore City Public Schools (BCPS) and include interviews, observations, and artifacts. The ILP provided an important case for this inquiry because it deliberately aimed to support principals’ sensemaking about IL as a cornerstone of its strategy for engaging a cohort of seventeen elementary school principals in IL. Findings reveal that the extent to which the IFL actually supported principals’ sensemaking was inhibited by such district conditions as limited time and resources and political distractions. Despite these conditions, principals responded to some IL ideas in ways that reflect reformers’ intentions. Principals were more likely to do so when the ILP offered several different types of support for their sensemaking and less likely to do so when the ILP offered a limited number supports for their sensemaking. When the ILP provided a moderate number of different supports for sensemaking, principals’ responses to the ideas tended to be more varied; in those cases, other factors including district conditions, school conditions, and principal background seemed to influence their responses more strongly than supports provided by the ILP. Implications address how policymakers, professional development providers, and researchers can support principals’ engagement in IL. SUPPORTS FOR PRINCIPALS’ SENSEMAKING: LESSONS FROM THE INSTITUTE FOR LEARNING’S INSTRUCTIONAL LEADERSHIP PROGRAM IN BALTIMORE, MARYLAND
Compressing the illumination-adjustable images with principal component analysis

The ability to change illumination is a crucial factor in image-based modeling and rendering. Image-based relighting offers such capability. However, the tradeoff is the enormous increase of storage requirement. In this paper, we propose a compression scheme that effectively reduces the data volume while maintaining the real-time relighting capability. The proposed method is based on principal component analysis (PCA). A block-wise PCA is used to practically process the huge input data. The output of PCA is a set of eigenimages and the corresponding relighting coefficients. By dropping those low-energy eigenimages, the data size is drastically reduced. To further compress the data, eigenimages left are compressed using transform coding and quantization while the relighting coefficients are compressed using uniform quantization. We also suggest the suitable target bit rate for each phase of the compression method in order to preserve the visual quality. Finally, we propose a real-time engine that relights images from the compressed data.
Photoionization, Shocks or Starbursts?

RESUMEN Desde que Baldwin, Phillips, y Terlevich; as como Osterbrock y Veilleux popularizaron su uso, los diagn osticos opticos han sido utilizados para tratar de distinguir entre los varios modos de excitaci on en regiones nucleares de emisi on en galaxias normales y activas. Recientemente se ha hecho gran progreso reuniendo nuevos datos observacionales y construyendo modelos te oricos para describir los resultados. Revisaremos estos resultados, intentaremos mostrar cu ales par ametros de las regiones de emisi on nuclear pueden ser derivados un v ocamente a partir de diagn osticos opticos y UV, y se~ el camino hacia nuevos progresos en este problema
From Concurrency Models to Numbers - Performance and Dependability

Discrete-state Markov processes are very common models used for performance and dependability evaluation of, for example, distributed information and communication systems. Over the last fifteen years, compositional model construction and model checking algorithms have been studied for these processes, and variations thereof, especially processes incorporating nondeterministic choices. In this paper we give a survey of model checking and compositional model construction for such processes in discrete and continuous time.
Representation for knot-tying tasks

The learning from observation (LFO) paradigm has been widely applied in various types of robot systems. It helps reduce the work of the programmer. However, the applications of available systems are limited to manipulation of rigid objects. Manipulation of deformable objects is rarely considered, because it is difficult to design a method for representing states of deformable objects and operations against them. Furthermore, too many operations are possible on them. In this paper, we choose knot tying as a case study for manipulating deformable objects, because the knot theory is available and the types of operations possible in knot tying are limited. We propose a knot planning from observation (KPO) paradigm, a KPO theory, and a KPO system.
Interactive manipulation of a solution for a geometric constraint system

In CAD systems, symbolic geometric solvers allow to provide, for a constrained sketch drawn by the designer, a general construction program, that describes how and in which order the objects have to be built. Then this program is numerically interpreted to produce the required figure. If multiple solutions are generated, these kind of solvers generally allow to scan the entire space of the solutions found. In this paper, we first briefly recall our sketch-based selection method, that enables to easily eliminate most of the solutions and to keep the only, or at the worst the few solutions that have the best likeness with the original drawing. Then, we expose two methods to help the user choosing the required solution: after explaining our step by step interpretation mechanism implemented as a debugger-like tool, that allows to browse the remaining tree of solutions, we introduce a new method to interactively touch up a solution, or a part of a solution.
Impact of Quality Management Practices on Firm Performance: The Research Evolution

Quality management has been known as a method to improve the organizational performance. Several organization types have implemented quality management, i.e. manufacturing and service companies, educational institution, healthcare provider, and public administration. Many studies have been done in this area exploring the effects of quality management on firm performance. Those researches varies in terms of organizational background, quality management practices, performance measures, mediating/moderating factors, analysis tools used, and research models. Several authors have reviewed papers on this topic. Last journal review is done by Nair in 2006. No author has done elaborative effort to review papers published since 2006. The aim of this paper is to capture the development of research in this field and to offer further research direction. In this literature review, papers will be classified in terms of organizational background, quality management practices, performance measures, mediating/moderating factors, analysis tools, and their research models. Findings of review and recommendations for further research will be presented.
Digital Computers Applied to Games. Faster Than Thought

Many scholars would agree that, had it not been for e-business, the construction of Scheme might never have occurred. Given the current status of collaborative models, futurists urgently desire the emulation of courseware, which embodies the robust principles of relational self-learning artificial intelligence. Wey, our new heuristic for scalable information, is the solution to all of these obstacles.
Energy Clearing Price Prediction and Confidence Interval Estimation with Cascaded Neural Networks

The deregulated power market is an auction market, and energy market clearing prices (MCP) are volatile. Good MCP prediction and its confidence interval estimation will help utilities and independent power producers submit effective bids with low risks. MCP prediction, however, is difficult since bidding strategies used by participants are complicated and various uncertainties interact in an intricate way. Furthermore, MCP predictors usually have a cascaded structure, as several key input factors need to be estimated first. Cascaded structures are widely used, however, they have not been adequately investigated. This paper analyzes the uncertainties involved in a cascaded neural network structure for MCP prediction and develops the prediction distribution under the Bayesian framework. A fast algorithm to evaluate the confidence intervals by using the memoryless quasi-Newton method is also developed. Testing results on a classroom problem and on New England MCP prediction show that the method is computationally efficient and provides accurate prediction and confidence coverage. The scheme is generic, and can be applied to various networks, such as multilayer perceptrons and radial basis function networks.
Network-on-Chip Benchmarking Specification Part 2: Micro-Benchmark Specification Version 1.0

The rapid development of Network-on-Chip (NoC) calls for a systematic approach to evaluate and fairly compare various NoC architectures. In this specification, we define a generic NoC architecture, a comprehensive set of synthetic workloads as micro-benchmarks, workload scenarios and evaluation criteria. These micro-benchmarks enable to measure and pinpoint particular properties of NoC architectures, complementing application benchmarks.
A Study on Secure Data Storage Strategy in Cloud Computing

Based on fundamental theories of k equations in algebra, n congruence surplus principle in elementary number theory, and the Abhishek’s online data storage algorithm, we propose a secure data storage strategy in cloud computing. The strategy splits data d into k sections using the data splitting algorithm, ensures high data security by simplifying k equation solutions, and at the same time, guarantees highly reliable data using the coefficients generated by the splitting algorithm.
Stopword Graphs and Authorship Attribution in Text Corpora

In this work we identify interactions of stopwords -noisewords- in text corpora as a fundamental feature to effect author classification. It is convenient to view such interactions as graphs wherein nodes are stopwords and the interaction between a pair of stopwords are represented as edge-weights. We define the interaction in terms of the distances between pairs of stopwords in text documents. Given a list of authors, graphs for each author is computed based on their undisputed writings. Authorship of a test document is attributed based on the closeness of the graph derived from it to the above graphs. Towards this, we define a closeness measure to compare such graphs based on the Kullback-Leibler divergence. We illustrate the accuracy of our approach by applying it on examples drawn from the Gutenberg archives. Our results show that the proposed approach is effective not only in binary author classification but also performs multiclass author classification for as many as 10 authors at a time and compares favourably with the state-of-the-art in author identification.
A heuristic-based algorithm for privacy-oriented virtual network embedding

Network virtualization has become increasingly popular in recent years. It has the potential to allow timely handling of network infrastructure requests and, after instantiated, their lifecycle. In addition, it enables improved physical resource utilization. However, the use of network virtualization in large-scale, real environments depends on the ability to adequately map virtual routers and links to physical resources, as well as to protect virtual networks against security threats. With respect to security, confidentiality and privacy mechanisms have become essential in light of recent discoveries related to pervasive electronic surveillance. In this paper we propose a heuristic method for virtual network embedding with security support. The method features precise modeling of overhead costs of security mechanisms and handles incoming requests in an online manner. Additionally, we present a detailed performance comparison between the proposed heuristic and an optimization model based on the same problem. The obtained results demonstrate that the heuristic method is able to find feasible mappings in the order of seconds even when dealing with large network infrastructures, while the optimization model is limited to smaller networks.