Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy-efficient continuous and event-driven monitoring

Optimizing the energy consumption in monitoring and communication protocols for wireless sensor networks has become the most important performance objective. We explore the problem of maximizing sensor network lifetime, i.e., time during which the set of targets is covered. We propose centralized algorithms for lifetime maximization with provable approximation ratio for the realistic model studied. In this paper we introduce reliability requirement for distributed target-monitoring protocols and prove that previously considered protocols are reliable. A new deterministic energy-efficient protocol for sensor networks (DEEPS) aimed at prolonging lifetime is proposed. We prove that DEEPS is reliable and compare DEEPS with several known target-monitoring protocols in NS2 environment using LEACH (W. Heinzelman et al., 2000) for simulating monitoring data delivery to the base. Our contributions also include the first full-fledged simulation of the monitoring protocols on NS2 combined with LEACH (W. Heinzelman et al., 2000) as a communication protocol, and extensive experimental study of several protocols showing almost 2 times increase in the lifetime for DEEPS over known protocols
Sparse sign-consistent Johnson–Lindenstrauss matrices: Compression with neuroscience-based constraints

Significance Significant biological evidence indicates that the brain may perform some form of compression. To be meaningful, such compression should preserve pairwise correlation of the input data. It is mathematically well known that multiplying the input vectors by a sparse and fixed random matrix A achieves the desired compression. But, to implement such an approach in the brain via a synaptic-connectivity matrix, A should also to be sign consistent: that is, all entries in a single column must be either all nonnegative or all nonpositive. This is so because most neurons are either excitatory or inhibitory. We prove that sparse sign-consistent matrices can deliver the desired compression, lending credibility to the hypothesis that correlation-preserving compression occurs in the brain via synaptic-connectivity matrices. Johnson–Lindenstrauss (JL) matrices implemented by sparse random synaptic connections are thought to be a prime candidate for how convergent pathways in the brain compress information. However, to date, there is no complete mathematical support for such implementations given the constraints of real neural tissue. The fact that neurons are either excitatory or inhibitory implies that every so implementable JL matrix must be sign consistent (i.e., all entries in a single column must be either all nonnegative or all nonpositive), and the fact that any given neuron connects to a relatively small subset of other neurons implies that the JL matrix should be sparse. We construct sparse JL matrices that are sign consistent and prove that our construction is essentially optimal. Our work answers a mathematical question that was triggered by earlier work and is necessary to justify the existence of JL compression in the brain and emphasizes that inhibition is crucial if neurons are to perform efficient, correlation-preserving compression.
JVM for a Heterogeneous Shared Memory System

InterWeave is a middleware system that supports the sharing of strongly typed data structures across heterogeneous languages and machine architectures. Java presents special challenges for InterWeave, including write detection, data translation, and the interface with the garbage collector. In this paper, we discuss our implementation of J-InterWeave, a JVM based on the Kaffe virtual machine and on our locally developed InterWeave client software. J-InterWeave uses bytecode instrumentation to detect writes to shared objects, and leverages Kaffe’s class objects to generate type information for correct translation between the local object format and the machineindependent InterWeave wire format. Experiments indicate that our bytecode instrumentation imposes less than 2% performance cost in Kaffe interpretation mode, and less than 10% overhead in JIT mode. Moreover, JInterWeave’s translation between local and wire format is more than 8 times as fast as the implementation of object serialization in Sun JDK 1.3. 1 for double arrays. To illustrate the flexibility and efficiency of J-InterWeave in practice, we discuss its use for remote visualization and steering of a stellar dynamics simulation system written in C.
Ranking Techniques for Keyphrase Extraction

This thesis focuses on the task of extracting keyphrases from research papers. Keyphrases are short phrases that summarize and characterize the contents of documents. They help users explore sets of documents and quickly understand the contents of individual documents. Most academic papers do not have keyphrases assigned to them, and manual keyphrase assignment is highly laborious. As such, there is a strong demand for automatic keyphrase extraction systems. The task of automatic keyphrase extraction presents a number of challenges. Human indexers are heavily informed by domain knowledge and comprehension of the contents of the papers. Keyphrase extraction is an intrinsically noisy and ambiguous task, as different human indexers select different keyphrases for the same paper. Training data is limited in both quality and quantity. In this thesis, we present a number of advancements to the ranking methods and features used to automatically extract keyphrases. We demonstrate that, through the reweighing of training examples, the quality of the learned bagged decision trees can be improved with negligible runtime cost. We use reranking to improve accuracy and explore several extensions thereof. We propose a number of new features, including augmented domain keyphraseness and average word length. Augmented domain keyphraseness incorporates information from a hierarchical document clustering to improve the handling of multi-domain corpora. We explore the technique of per-document feature scaling and discuss the impact of feature removal. Over three diverse corpora, these advancements substantially improve accuracy and runtime. Combined, they give keyphrase assignments that are competitive with those produced by human indexers. Thesis Supervisor: Regina Barzilay Title: Professor
Information services for novelty mining

Abstract Information services facilitate users to exploit applications over the network and access them from the remote system at the client side. In this paper, we describe the design and development of information services for novelty mining, which allows users to access the novel yet relevant information of a given topic. Several methodologies regarding novelty mining such as novelty scoring, novelty threshold, novelty feedback, and document-to-sentence technique are described. In addition to Web services, mobile information services are also described. Modelling and implementing information services for novelty mining are especially useful for users to reduce their information overload. We describe the challenging issue of decomposing the complex novelty mining application into several smaller and simpler modules, which are later implemented as services on the Web as well as mobile devices. After deploying our information services for novelty mining, test cases are provided to demonstrate the system. Our information services for novelty mining are confirmed to be helpful in increasing the efficiency of enterprise users in gathering novel information from incoming text. By studying the design and development of information services for novelty mining, we can benefit other developers in investigating effective techniques for developing enterprise services for other real-world applications.
Predicting continental-scale patterns of bird species richness with spatially explicit models

The causes of global variation in species richness have been debated for nearly two centuries with no clear resolution in sight. Competing hypotheses have typically been evaluated with correlative models that do not explicitly incorporate the mechanisms responsible for biotic diversity gradients. Here, we employ a fundamentally different approach that uses spatially explicit Monte Carlo models of the placement of cohesive geographical ranges in an environmentally heterogeneous landscape. These models predict species richness of endemic South American birds (2248 species) measured at a continental scale. We demonstrate that the principal single-factor and composite (species-energy, water-energy and temperature-kinetics) models proposed thus far fail to predict (r2⩽0.05) the richness of species with small to moderately large geographical ranges (first three range-size quartiles). These species constitute the bulk of the avifauna and are primary targets for conservation. Climate-driven models performed reasonably well only for species with the largest geographical ranges (fourth quartile) when range cohesion was enforced. Our analyses suggest that present models inadequately explain the extraordinary diversity of avian species in the montane tropics, the most species-rich region on Earth. Our findings imply that correlative climatic models substantially underestimate the importance of historical factors and small-scale niche-driven assembly processes in shaping contemporary species-richness patterns.
The associations among the ethical climate, the professional practice environment and individualized care in care settings for older people.

AIM To investigate the associations among the ethical climate, professional practice environment and individualized nursing care in care settings for older people. BACKGROUND The quality of care provision is affected by organizational environments, such as ethical climate and professional practice environment. Although, the association between professional practice environment and individualized nursing care has been pointed out, we know that little is known about how ethical climate is associated with the level of individualized nursing care delivery. DESIGN A cross-sectional explorative and correlational survey design. METHODS The study was conducted in 62 units in the vicinity of a Finnish city using a sample of nurses (N = 874, response rate 58%) who worked clinically with older people in different care settings in 2012. Survey data were collected using the Hospital Ethical Climate Survey, Revised Professional Practice Environment scale and Individualised Care Scale-B. Data were analysed statistically using descriptive statistics, correlation coefficients (Pearson) and multiple stepwise regression analyses. RESULTS Statistically significant correlations were found among the variables, ethical climate and individualized care and between individualized care and all professional practice environment sub-scales. Multiple stepwise regression showed associations among individualized care, ethical climate and internal work motivation, control over practice and leadership and autonomy. CONCLUSIONS The study provided better understanding of the complex concept of individualized care by taking into consideration the ethical climate and the practice environment and their associations. To increase individualization in care provision, efforts need to be directed towards organizational aspects requiring the support of nursing leaders.
A PROOF OF CONCEPT OF ITERATIVE DSM IMPROVEMENT THROUGH SAR SCENE SIMULATION

In Very High Resolution (VHR) Synthesis Aperture Radar (SAR) context, very fine and accurate georeferencing and geoprojection processes are required. Both operations are only applicable if accurate local heights are known. 3D information may be derived from SAR interferometry (InSAR), But in VHR context, InSAR reveals to be inaccurate mostly due to phase unwrapping problems and to phase/height noise. Generated InSAR Digital Surface Models (DSM) can only be considered as a first good approximation of the observed surface. Therefore, we proposed to start from the InSAR DSM, to project it on ground range on a given datum, to model the observed scene using this projected DSM, then to simulate in slant range the intensity image issued from this structure model. Comparison between simulated and observed intensity image can then be used as a criterion to modify and improve the considered underlying DSM. In this paper, we present the different steps of the proposed approach and results obtained so far, showing that the proposed process can be run iteratively to modify the DSM and reach a stable solution.
Towards Distributed Ontologies with Description Logics

– Two distinct applications may use two different ontologies to refer to the same concept. Thanks to mapping between these ontologies, association of these concepts can be derived. – One particular application (e.g., a semantic annotation of a document) can use different ontologies to refer to two distinct concepts. These concepts, may be related by mapping, and so further semantic consequences can be derived. – Developers may choose to map from a foreign ontology instead of repeating a complex description of some concept. Reuse of concepts can be facilitated.
ShadowObjects: A Programming Model for Service Replication in Distributed Object Systems

With the growing emphasis on distributed applications, sophisticated programming models for handling replication become important. Control replication as an issue has so far been considered in the larger context of distributed systems such as ISIS and Arjuna. We present a programming model called ShadowObjects for programming replicated services to cater to the needs of control replication in distributed object oriented systems. The ShadowObjects model provides primitives for building highly available and redundant services. Replication in ShadowObjects is encapsulated and a replica access control mechanism is provided. Messages accessing the services exported by a server object can be captured on-the-fly, and can be appropriately scheduled on the replicas. The ShadowObjects model can be used to develop applications for distributed systems.
Smart Citizen Sensing: A Proposed Computational System with Visual Sentiment Analysis and Big Data Architecture

A city‘s ―smartness‖ depends greatly on citizens‘ participation in smart city services. Furthermore, citizens are becoming technology-oriented in every aspect concerning their convenience, comfort and safety. Thus, they become sensing nodes—or citizen sensors—within smart-cities with both static information and a constantly emitting activity system. This paper presents a novel approach to perform visual sentiment analysis of big visual data shared on social networks (such as Facebook, Twitter, LinkedIn, and Pinterest) using transfer learning. The proposed approach aims at contributing to smart citizens sensing area of smart cities. This work explores deep features of photos shared by users in Twitter via convolutional neural networks and transfer learning to predict sentiments. Moreover, we propose big data architecture to extract, save and transform raw Twitter image posts into useful insights. We obtained an overall prediction accuracy of 83.35%, which indicates that neural networks are indeed capable of predicting sentiments. Therefore, revealing interesting research opportunities and applications in the domain of smart sensing.
Complete Genome Sequence of Human Enterovirus Strain 71 (EV71/Taipei/3118/2011), Isolated from a Patient in Taiwan

ABSTRACT This full-length genome sequence of human enterovirus strain 71 (EV71/Taipei/3118/2011) was isolated from a clinical patient in Taiwan in 2011. According to the phylogenetic analysis, the complete genome sequence in this study is part of the subgenotype C4.
Simulating Open-Via Defects

Open-via defects are a major systematic failure mechanism in nanoscale manufacturing processes. We present a flow for simulating open-via defects. Electrical parameters are extracted from the layout and technology data and represented in a way which allows efficient simulation on gate level. The simulator takes oscillation caused by open-via defects into account and quantifies its impact on defect coverage. The flow can be employed for manufacturing test as well as for defect diagnosis.
Joint Eurographics -ieee Tcvg Symposium on Visualization (2003) Detecting Critical Regions in Scalar Fields

Trivariate data is commonly visualized using isosurfaces or direct volume rendering. When exploring scalar fields by isosurface extraction it is often difficult to choose isovalues that convey " useful " information. The significance of visualizations using direct volume rendering depends on the choice of good transfer functions. Understanding and using isosurface topology can help in identifying " relevant " isovalues for visualization via isosurfaces and can be used to automatically generate transfer functions. Critical isovalues indicate changes in topology of an isosurface: the creation of new surface components, merging of surface components or the formation of holes in a surface component. Interesting isosurface behavior is likely to occur at and around critical isovalues. Current approaches to detect critical isovalues are usually limited to isolated critical points. Data sets often contain regions of constant value (i.e., mesh edges, mesh faces, or entire mesh cells). We present a method that detects critical points, critical regions and corresponding critical isovalues for a scalar field defined by piecewise trilinear interpolation over a uniform rectilinear grid. We describe how to use the resulting list of critical regions/points and associated values to examine trivariate data.
Interaction with Notch determines endocytosis of specific Delta ligands in zebrafish neural tissue

Mind bomb1 (Mib1)-mediated endocytosis of the Notch ligand DeltaD is essential for activation of Notch in a neighboring cell. Although most DeltaD is localized in cytoplasmic puncta in zebrafish neural tissue, it is on the plasma membrane in mib1 mutants because Mib1-mediated endocytosis determines the normal subcellular localization of DeltaD. Knockdown of Notch increases cell surface DeltaA and DeltaD, but not DeltaC, suggesting that, like Mib1, Notch regulates endocytosis of specific ligands. Transplant experiments show that the interaction with Notch, both in the same cell (in cis) and in neighboring cells (in trans), regulates DeltaD endocytosis. Whereas DeltaD endocytosis following interaction in trans activates Notch in a neighboring cell, endocytosis of DeltaD and Notch following an interaction in cis is likely to inhibit Notch signaling by making both unavailable at the cell surface. The transplantation experiments reveal a heterogeneous population of progenitors: in some, cis interactions are more important; in others, trans interactions are more important; and in others, both cis and trans interactions are likely to contribute to DeltaD endocytosis. We suggest that this heterogeneity represents the process by which effective lateral inhibition leads to diversification of progenitors into cells that become specialized to deliver or receive Delta signals, where trans and cis interactions with Notch play differential roles in DeltaD endocytosis.
Differential edit distance as a countermeasure to video scene ambiguity

In this work the problem of how to evaluate video scene segmentation results is examined. The evaluation, which is typically conducted by comparison of the experimental output of scene segmentation algorithms with a ground-truth temporal decomposition, often suffers from ambiguity in the definition of the ground truth. To alleviate this drawback the use of a string comparison measure, called differential edit distance (DED), is proposed. After defining video scene segmentation evaluation as a string comparison problem, the proposed measure is applied to limit the effect of scene segmentation ambiguity in the performance estimation uncertainty. The experimental results, which include comparisons with state of the art evaluation measures, demonstrate the ambiguity extent and verify the validity of the conducted analysis.
Three-dimensional video compression using subband/wavelet transform with lower buffering requirements

Three-dimensional (3-D) video compression using wavelets decomposition along the temporal axis dictates that a number of video frames must be buffered to allow for the temporal decomposition. Buffering of frames allows for the temporal correlation to be made use of, and the larger the buffer the more effective the decomposition. One problem inherent in such a set up in interactive applications such as video conferencing, is that buffering translates into a corresponding time delay. We show that 3-D coding of such image sequences can be achieved in the true sense of temporal direction decomposition but with much less buffering requirements. For a practical coder, this can be achieved by introducing an approximation to the way the transform coefficients are encoded. Applying wavelet decomposition using some types of filters may introduce edge errors, which become more prominent in short signal segments. We also present a solution to this problem for the Daubechies (1988) family of filters.
High‐Yield Synthesis of Multifunctional Tellurium Nanorods to Achieve Simultaneous Chemo‐Photothermal Combination Cancer Therapy

Tellurium (Te) is an important semiconductor material with low band‐gap energy, which has attracted considerable attention in recent years, due to its special chemical and physical properties and wide potential in electrochemistry, optoelectronics, and biological fields. This study demonstrates a facile and high‐yield synthesis strategy of Te nanorods (PTW‐TeNRs) decorated by polysaccharide–protein complex, which can achieve simultaneous chemo‐photothermal combination therapy against cancers. PTW‐TeNRs alone possess high stability under physiological conditions, potent anticancer activities through induction of reactive oxygen species overproduction, and high selectivity among tumor and normal cells. More importantly, they exhibit strong near‐infrared (NIR) absorbance and good photothermal conversion ability from NIR light to heat energy. Furthermore, in combination with NIR laser irradiation, PTW‐TeNRs exhibit excellent chemo‐photothermal efficiency and low toxicity as evidenced by highly efficient tumor ablation ability, but show no obvious histological damage to the major organs. Taken together, this study provides a valid tactic for facile synthesis of multifunctional tellurium nanorods for efficient and combinational cancer therapy.
Online Testing of Real-time Systems

We present a new technique and tool for testing of embedded systems using real-time online testing from non-deterministic timed automata specifications. We describe a sound and complete randomized online testing algorithm, and describe how to implement it using symbolic state representation and manipulation techniques. We propose the notion of relativized timed input/output conformance as the formal implementation relation. A novelty of this relation and our test generation algorithm is that they explicitly take environment assumptions into account. A medium size case study shows very promising results in terms of error detection capability and computation performance.
TOUCHtr4ck: democratic collaborative music

When electronic musicians compose collaboratively, they typically use their own single-user musical controllers. It may, therefore, be useful to develop novel controllers that support collaborative workflows and democratic principles. After describing the design principles for developing such controllers, we present TOUCHtr4ck, a prototype multi-touch system designed to facilitate such democratic relationships. Informal testing has revealed that this approach does facilitate democratic and collaborative music making, and can produce creative musical results.