Miracle-dz/UniFAR-FTUs huggingface dataset:
Global Precipitation Mission ( GPM ) and Dual-Wavelength Radar ( DPR )

Global precipitation measurement is essential not only for the research of the global change but also for the water resources management. Currently, satellite precipitation measurement is not sufficient for the detailed study of the precipitation and is far from enough for the water resources management which requires very high spatial and temporal resolution. To fill the gap at least partly, the Global Precipitation Measuring (GPM) was proposed jointly by US and Japan. The basic concept of GPM is to provide three hourly global precipitation map using eight constellation satellites equipped with microwave radiometers and a core satellite equipped with a dual-wavelength radar (DPR) and a microwave radiometer. GPM is partly a follow-on mission of the Tropical Precipitation Mission (TRMM), but GPM will extend the observation to cold regions where solid precipitation frequently exists.
Market Forecasting of Super Strength Fiber: Glass Fiber

The goal of this paper is to forecast the glass fiber market with exponential smoothing model. Five exponential smoothing models are introduced and Holt linear model was selected due to data characteristic and tool limitation. Producer price index: glass fiber, textile-type and all other reinforced and Producer price index: fiberglass plastics products were applied in the forecast model. Parameter optimization was based on minimizing the root mean square error. Values for July 2012 through June 2017 were forecasted.
Sequence learning with recurrent networks: analysis of internal representations

The recognition and learning of temporal sequences is fundamental to cognitive processing. Several recurrent networks attempt to encode past history through feedback connections from `context units. ' However, the internal representations formed by these networks is not well understood. In this paper, we use cluster analysis to interpret the hidden unit encodings formed when a network with context units is trained to recognize strings from a finite state machine. If the number of hidden units is small, the network forms fuzzy representations of the underlying machine states. With more hidden units, different representations may evolve for alternative paths to the same state. Thus, appropriate network size is indicated by the complexity of the underlying finite state machine. The analysis of internal representations can be used for modeling of an unknown system based on observation of its output sequences.
The purpose of motion: Learning activities from Individual Mobility Networks

The large availability of mobility data allows us to investigate complex phenomena about human movement. However this adundance of data comes with few information about the purpose of movement. In this work we address the issue of activity recognition by introducing Activity-Based Cascading (ABC) classification. Such approach departs completely from probabilistic approaches for two main reasons. First, it exploits a set of structural features extracted from the Individual Mobility Network (IMN), a model able to capture the salient aspects of individual mobility. Second, it uses a cascading classification as a way to tackle the highly skewed frequency of activity classes. We show that our approach outperforms existing state-of-the-art probabilistic methods. Since it reaches high precision, ABC classification represents a very reliable semantic amplifier for Big Data.
Stochastic Stability of Delayed Neural Networks With Local Impulsive Effects

In this paper, the stability problem is studied for a class of stochastic neural networks (NNs) with local impulsive effects. The impulsive effects considered can be not only nonidentical in different dimensions of the system state but also various at distinct impulsive instants. Hence, the impulses here can encompass several typical impulses in NNs. The aim of this paper is to derive stability criteria such that stochastic NNs with local impulsive effects are exponentially stable in mean square. By means of the mathematical induction method, several easy-to-check conditions are obtained to ensure the mean square stability of NNs. Three examples are given to show the effectiveness of the proposed stability criterion.
The Way of Public Institutions to Accrual Accounting - case study Romania

The present research aims to investigate the manner in which the public sector accounting under transition from cash to accrual base can be accompanied by legislative stability and coherence, using the example of Romanian public sector. The importance of a clear and concise change process is one of the reasons for the research of this issue. Another reason was the lack of similar studies. The present study covers aspects that were not dealt with by the specialized literature and whose relevance for the European, mainly East European, public sector is highly significant. By advancing and testing five hypotheses where build up the conclusion about the selected research subject. The general and punctual topics that have a significant impact on the outlining of the accounting system typical for the Romanian public institutions were identified among the many normative documents of the period. It appears as a novelty the using of content analysis in the topic of interdependence between the development of the legislative system and the transition process from cash to accrual accounting system in the public sector. The impact of the research findings may be broadened to encompass other sectors as well, thus providing a general outline of the trend followed by the Romanian legislative framework.
Combining multimedia resources for an engaging experience of cultural heritage

ICT technologies have a great potential not only for preserving and increasing awareness about cultural heritage, but also for allowing people to better experience this huge legacy. Various application tools have already been developed which provide different types of multimedia resources, such as 3D representations of objects and places, videos, graphics, sounds, in order to augment the physical context by providing virtual, location-specific information, so that people can experience some aspects of ancient life which would otherwise be very difficult to figure out. The effort spent to create multimedia resources is considerable; therefore, it is worth reusing them to produce applications suited to other types of visitors. In this paper, we present our on-going work to provide tailored applications that support different types of visitors. Such applications are developed according to a model that describes how multimedia resources can be combined, also depending on the type of users and devices. Examples of these solutions are briefly illustrated.
Embedding leveled hypercube algorithms into hypercubes (extended abstract)

When a leveled hypercube algorithm (one dimension used at a time) is mapped in the straightforward way into a hypercube in which all edges are useable at once, most of the host machine’s bandwidth is unused. This paper shows how to construct embedding which better utilize the host’s edges. In particular, I show how to map an n-dimensional leveled hypercube algorithm into an n-dimensional host hypercube so that the communication throughput of every guest edge is @ ((n/ logn)*0g62, = w (n0386) times the communication throughput of a host edge. Furthermore, the routing can be done on edge-disjoint paths of length at most n. This result can be applied to other algorithms that are run on hypercubes, For example, if an atgorithm runs on a mesh with a axes each of length 21, but uses only one axis at a time, then it can be embedded in art la-dimensional hypercube so that each mesh edge has throughput @ (l(a/ log a)’”g~ 2,.
Improving XPath Evaluation with Strategies

XPath is the defacto navigation language for XML documents conforming to DTD and it is important to have efficient evaluation and checking techniques available for XPath. Traversal strategies, a component of Adaptive Programming, are a well studied navigation language for objects conforming to class graphs and an efficient evaluation technique has been developed in the previous millenium. Traversal strategies don’t deal with the full generality of XPath but instead they focus on ancestor-descendent (ad) edges. Indeed, a traversal strategy is a graph consisting only of ad edges with optional negative constraints on the edges. While it has been widely acknowledged in the data base community that DTD may speed up XPath evaluation, no paper has shown an exponential improvement by using the DTDs. We show an infinite sequence of XPath expression/DTD/document triples so that evaluation using the meta information in the DTDs is exponentially faster. We draw a strong connection between traversal strategy evaluation and XPath evaluation and show how this leads to comprehensive logical optimization techniques for XPath. Our evaluation is optimal in the sense that by visiting one node less than our approach visits would lead to wrong results. Finally, we present empirical results of our speed up and explore various classes of XML documents that can benefit from this type of evaluation. We believe that the automata-theoretic algorithmic ideas presented in this paper should be an important building block of any efficient XPath evaluator. General Terms Logical optimization for schema-based XPath evaluation, optimal XPath evaluation, Adaptive Programming, metainformation-guided search. 1 March 2, 2005
Real-Time Measurement of Nanotube Resonator Fluctuations in an Electron Microscope

Mechanical resonators based on low-dimensional materials provide a unique platform for exploring a broad range of physical phenomena. The mechanical vibrational states are indeed extremely sensitive to charges, spins, photons, and adsorbed masses. However, the roadblock is often the readout of the resonator, because the detection of the vibrational states becomes increasingly difficult for smaller resonators. Here, we report an unprecedentedly sensitive method to detect nanotube resonators with effective masses in the 10–20 kg range. We use the beam of an electron microscope to resolve the mechanical fluctuations of a nanotube in real-time for the first time. We obtain full access to the thermally driven Brownian motion of the resonator, both in space and time domains. Our results establish the viability of carbon nanotube resonator technology at room temperature and pave the way toward the observation of novel thermodynamics regimes and quantum effects in nanomechanics.
Computing Minimum Directed Feedback Vertex Set in O(1.9977n)

In this paper we propose an algorithm which, given a directed graph G, finds the minimum directed feedback vertex set (FVS) of G in O∗(1.9977n) time and polynomial space. To the best of our knowledge, this is the first algorithm computing the minimum directed FVS faster than in O(2n). The algorithm is based on the branch-and-prune principle. The minimum directed FVS is obtained through computing of the complement, i.e. the maximum induced directed acyclic graph. To evaluate the time complexity, we use the measureand-conquer strategy according to which the vertices are assigned with weights and the size of the problem is measured in the sum of weights of vertices of the given graph rather than in the number of the vertices.
Quantum geometry of isolated horizons and black hole entropy

Using the earlier developed classical Hamiltonian framework as the point of departure, we carry out a non-perturbative quantization of the sector of general relativity, coupled to matter, admitting non-rotating isolated horizons as inner boundaries. The emphasis is on the quantum geometry of the horizon. Polymer excitations of the bulk quantum geometry pierce the horizon endowing it with area. The intrinsic geometry of the horizon is then described by the quantum Chern-Simons theory of a U(1) connection on a punctured 2-sphere, the horizon. Subtle mathematical features of the quantum Chern-Simons theory turn out to be important for the existence of a coherent quantum theory of the horizon geometry. Heuristically, the intrinsic geometry is flat everywhere except at the punctures. The distributional curvature of the U(1) connection at the punctures gives rise to quantized deficit angles which account for the overall curvature. For macroscopic black holes, the logarithm of the number of these horizon microstates is proportional to the area, irrespective of the values of (non-gravitational) charges. Thus, the black hole entropy can be accounted for entirely by the quantum states of the horizon geometry. Our analysis is applicable to all non-rotating black holes, including the astrophysically interesting ones which are very far from extremality. Furthermore, cosmological horizons (to which statistical mechanical considerations are known to apply) are naturally incorporated. An effort has been made to make the paper self-contained by including short reviews of the background material.
Optimized anchors placement: An analytical approach in UWB-based TDOA localization

In this paper, we consider the problem of locating an Automated Guided Vehicle (AGV) which moves on a plane in an industrial environment by means of Ultra-Wide Band (UWB) signaling from fixed Anchors Nodes (ANs) situated in the (three-dimensional) space. An analytical approach to optimize, under proper (realistic) constraints, the placement of the ANs used to locate the AGV is proposed. Analytical results are confirmed by simulations.
Retinoic acid controls proper head-to-trunk linkage in zebrafish by regulating an anteroposterior somitogenetic rate difference

During vertebrate development, the primary body axis elongates towards the posterior and is periodically divided into somites, which give rise to the vertebrae, skeletal muscles and dermis. Somites form periodically from anterior to posterior, and the anterior somites form in a more rapid cycle than the posterior somites. However, how this anteroposterior (AP) difference in somitogenesis is generated and how it contributes to the vertebrate body plan remain unclear. Here, we show that the AP difference in zebrafish somitogenesis originates from a variable overlapping segmentation period between one somite and the next. The AP difference is attributable to spatiotemporal inhibition of the clock gene her1 via retinoic acid (RA) regulation of the transcriptional repressor ripply1. RA depletion thus disrupts timely somite formation at the transition, eventually leading to the loss of one somite and the resultant cervical vertebra. Overall, our results indicate that RA regulation of the AP difference is crucial for proper linkage between the head and trunk in the vertebrate body plan.
Anti-pattern Mutations and Fault-proneness

Software evolution and development are continuous activities that have a never-ending cycle. While developers commit changes on a software system to fix bugs or to implement new requirements, they sometimes introduce anti-patterns, which are bad solutions to recurring design problems in the system. Many previous studies have shown that these anti-patterns have negative effects on code quality, in particular fault-proneness. However, it is not clear if and how anti-patterns evolve and which evolutionary behaviours are more fault-prone. This paper presents results from an empirical study aimed at understanding the evolution of anti-patterns in 27 releases of three open-source software systems: ArgoUML, Mylyn, and Rhino. Specifically, the study analyzes the mutations of anti-patterns, the changes that they undergo, and the relation between anti-pattern evolution behaviours and fault-proneness. Results show that (1) anti-patterns mutate from one type of anti-patterns to another, (2) structural changes are behind these mutations, and (3) some mutations are more risky in terms of fault-proneness.
Synchronous elastic circuit with higher throughput at reduced area and power

To reduced area and power in synchronous elastic circuits we are using combinations of various elasticity approaches. Elasticity refers to the property of a circuit in which circuits can tolerate arbitrary latency/delay variations in their computation units as well as communication channels. Elasticity does not make any assumption about the specific implementation of the circuit. This paper investigates different optimization approaches to reduce these area and power overheads of elastic control network without sacrificing the control network performance. Ultra simple fork (USFork), early evaluation join (EEJoin), half-buffer retiming (HBR) controller, eager Fork, join, lazy fork combinations for implementation are introduced. In this approach we check all node and all combinational blocks clock period and uses elastic buffer only when it needed. Comparing to published work on a Minimips processor case study[3] and Synchronous elasticization at reduced cost[2], our implementation shows up 8% and 15.08% area and power due to proposed flow of implementing synchronous elasticization with 17.5 % increase in throughput i.e. 0.94 Gbits/sec.
Combining statistical and logical inference for ontology alignment

In recent years, ontologies have proved a very attractive medium for storing domain knowledge in a variety of organizations; a few example domains are medicine and genetics. The rapid evolution of representation standards has led to the creation of distinct ontology bases in overlapping domains, making it paramount for large systems to reconcile ontological data from multiple sources. A large body of work on ontology integration[Euzenat, 2004] has produced algorithms and heuristics that have proven successful in alleviating the high computation costs of the process. However, the effective use of ontology formalisms – such as rules and axioms – in the integration process remains an open question. In this paper, we present a novel ontology integration method that takes advantage of the logical inference capabilities in OWL Lite to improve the recall of the merged ontologies. Our CPI (Clustering with Partial Inference) algorithm uses (i) graph clustering techniques to improve the process of selecting candidate matching entities and (ii) a limited, adaptive reasoning process to account for the effects of introducing relationships between such entities. Our initial experiments, performed on a set of 30 pairs of publicly available ontologies, show that CPI offers a 30% improvement in recall and a 25% improvement in answer quality compared to FCAmerge [Stumme and Maedche, 2001].
A Scheduling Algorithm for Execution-Instant Sensitive Real-Time Systems

Most of the previous studies on real-time systems focus on the satisfaction of completion-time constraints of jobs. A lot of them consider pure deadline, where the real-time jobs should be completed before their respective deadline. Some others consider time/utility functions for their jobs, which specifies the benefit that a job can accrue according to its exact completion time. However, we propose a different type of timing constraints for real-time jobs called Instant Value Function (IVF). According to IVF, the exact instant where a job is executed affects the value that the job can accrue. Therefore, the IVF specifies that which instants are the most appropriate ones to execute the job. This type of timing constraints can express the behavior of specific applications in a more precise manner. Furthermore, we have presented a scheduling algorithm that tries to maximize the accrued value of real-time systems with IVF-constrained jobs. The experimental results show that the proposed method considerably outperforms EDF.
OAuthHub - A Service for Consolidating Authentication Services

OAuth has become a widespread authorization protocol to allow inter-enterprise sharing of user preferences and data: a Consumer that wants access to a user's protected resources held by a Service Provider can use OAuth to ask for the user's authorization for access to these resources. However, it can be tedious for a Consumer to use OAuth as a way to organize user identities, since doing so requires supporting all Service Providers that the Consumer would recognize as users' "identity providers". Each Service Provider added requires extra work, at the very least, registration at that Service Provider. Different Service Providers may differ slightly in the API they offer, their authentication/authorization process or even their supported version of OAuth. The use of different OAuth Service Providers also creates privacy, security and integration problems. Therefore OAuth is an ideal candidate for Software as a Service, while posing interesting challenges at the same time. We use conceptual modelling to derive new high-level models and provide an analysis of the solution space. We address the aforementioned problems by introducing a trusted intermediary - OAuth Hub - into this relationship and contrast it with a variant, OAuth Proxy. Instead of having to support and control different OAuth providers, Consumers can use OAuth Hub as a single trusted intermediary to take care of managing and controlling how authentication is done and what data is shared. OAuth Hub eases development and integration issues by providing a consolidated API for a range of services. We describe how a trusted intermediary such as OAuth Hub can fit into the overall OAuth architecture and discuss how it can satisfy demands on security, reliability and usability.
On the Expressive Efficiency of Sum Product Networks

Sum Product Networks (SPNs) are a recently developed class of deep generative models which compute their associated unnormalized density functions using a special type of arithmetic circuit. When certain sufficient conditions, called the decomposability and completeness conditions (or "D&C" conditions), are imposed on the structure of these circuits, marginal densities and other useful quantities, which are typically intractable for other deep generative models, can be computed by what amounts to a single evaluation of the network (which is a property known as "validity"). However, the effect that the D&C conditions have on the capabilities of D&C SPNs is not well understood. In this work we analyze the D&C conditions, expose the various connections that D&C SPNs have with multilinear arithmetic circuits, and consider the question of how well they can capture various distributions as a function of their size and depth. Among our various contributions is a result which establishes the existence of a relatively simple distribution with fully tractable marginal densities which cannot be efficiently captured by D&C SPNs of any depth, but which can be efficiently captured by various other deep generative models. We also show that with each additional layer of depth permitted, the set of distributions which can be efficiently captured by D&C SPNs grows in size. This kind of "depth hierarchy" property has been widely conjectured to hold for various deep models, but has never been proven for any of them. Some of our other contributions include a new characterization of the D&C conditions as sufficient and necessary ones for a slightly strengthened notion of validity, and various state-machine characterizations of the types of computations that can be performed efficiently by D&C SPNs.