Miracle-dz/UniFAR-FTUs huggingface dataset:
A Flexible Approach for Ontology Matching

Ontology matching is the key process of semantic interaction and knowledge sharing. It is the basement of the other semantic web application, such as, semantic web-based service, ontology alignment. The purpose of ontology matching is to reuse the ontologies and integrate them in different fields, so as to implement the bigger pool of information and knowledge for the new communication and application. So far, however, the achievements of (semi-)automatic ontology matching are very limited. Addressing this issue, the work presented in this paper puts forward an ontology matching approach, SGOM. It combines several strategies to take the similarity iterative computation on Change Weights Semantic Graph and utilizes the semantic message of ontology structure to match. For making full use of the message of ontology, our implementation and experimental results are given to demonstrate the effectiveness of the matching approach. Keywords-Ontology;Ontology Matching; Name Matching;
Moving target detection in the cepstrum domain for passive coherent location (PCL) radar

A cepstrum moving target detection (CEPMTD) algorithm based on cepstrum techniques is proposed for passive coherent location (PCL) radar systems. The primary cepstrum techniques are of great success in recognizing the arrival times of static target echoes. To estimate the Doppler frequencies of moving targets, we divide the radar data into a large number of segments, and reformat these segments into a detection matrix. Applying the cepstrum and the Fourier transform to the fast and slow time dimensions respectively, we can obtain the range information and Doppler information of the moving targets. Based on the CEPMTD outlined above, an improved CEPMTD algorithm is proposed to improve the detection performance. Theoretical analyses show that only the target’s peak can be coherently added. The performance of the improved CEPMTD is initially validated by simulations, and then by experiments. The simulation results show that the detection performance of the improved CEPMTD algorithm is 13.3 dB better than that of the CEPMTD algorithm and 6.4 dB better than that of the classical detection algorithm based on the radar cross ambiguity function (CAF). The experiment results show that the detection performance of the improved CEPMTD algorithm is 1.63 dB better than that of the radar CAF.
Do unemployed workers bene…t from enterprise zones? The Greater Paris experience

We report the results of an econometric evaluation of the 1997 French enterprise zone program. We focus on how the program made easier the exit from unemployment to a job for local residents and neighbors. We analyze unemployment spells drawn from an exhaustive dataset over the 1993-2003 period in the Paris region. We estimate a Cox model strati…ed
Capturing Missing Links in Social Networks Using Vertex Similarity

The vertex similarity measure is a useful tool to discover and justify the relationship of vertices in a complex network. We propose the Relation Strength Similarity (RSS), a new vertex similarity measure that utilizes the network topology to discover similar vertices. Compared to other vertex similarity measures, RSS has the following advantages. First, it is an asymmetric metric which allows the measure to be used in more general social network applications. Second, it can be employed on a weighted network, in which the relation strength of two neighboring nodes can be explicitly expressed. Third, users could adjust the “discovery range” parameter for better performance based on their domain knowledge. Using coauthorship network as experimental data, our method outperforms other vertex similarity measures in terms of the ability to predict future coauthoring behavior among scholars.
Continued work employment and volunteerism and mental well-being of older adults: Singapore longitudinal ageing studies.

OBJECTIVE to examine the effect of late life engagement in continued work involvement or volunteer activities during retirement on mental well-being. METHODS two waves of data from the Singapore Longitudinal Ageing Studies were analyzed for 2,716 Singaporeans aged 55 or above at baseline and 1,754 at 2-year follow-up. Trained research nurses interviewed participants (non-volunteering retiree, volunteering retiree, and working seniors) on mental health status (geriatric depression scale, Mini Mental State Examination, positive mental wellbeing and life satisfaction). RESULTS about 88% of seniors were retired (78% non-volunteering, 10% volunteering) and 12% were still working in paid employment or business. At baseline and 2 year follow up, and regardless of physical health status, volunteering retirees and working seniors gave significantly better MMSE cognitive performance scores, fewer depressive symptoms, and better mental well-being and life satisfaction than non-volunteering retirees. CONCLUSION the results of this study suggest that continued work involvement or volunteerism provides opportunities for social interaction and engagement and may be associated with enhanced mental well-being. Future research should clarify which specific aspects of volunteerism are related to long-term mental well-being.
SEGMENTATION USING PARALLEL SELF ORGANIZING TREE MAP

At present, the researchers are making great effort to search for a general purpose resolution for image segmentation. Most of the approaches we are using now are somewhat inefficient and tardy. In this paper we present an innovative method, Parallel Self-organizing Tree Map (PSOTM), which is improved from SOTM. By processing image in parallel, PSOTM could segment the image in a much faster processing speed. After applying the new technology, PSOTM, we could obtain the higher efficiency with limited impacts on the visual quality.
Zero torque control of switched reluctance motors for charging reactor of electric vehicles

In this paper keeping position and zero torque (KP-ZT) control of switched reluctance motor (SRM) drives is proposed to avoid any movement when used for charging reactor in electric vehicles. A sliding mode position control technique as an outer loop and zero torque control method as an inner loop are used to attain this. Whereas, power factor correction (PFC) and voltage regulation is achieved with buck type integrated SRM drive by conventional boost converter for wide input and output voltage range. In this two stage PFC topology, multi-phase SRM drive operates as a high power interleaved buck converter to reduce cost, size, weight, and volume of battery charger with high reliability, improved power quality and low battery current ripple. Then, In order to implement the proposed ZT control, an online method is proposed to calculate current reference in each phase with regarding to zero torque condition. Finally, Lagrange optimization method is used for copper loss minimization during battery charging and results are compared with the case of using an extra clutch to let the motor to move.
Multiple Criteria Scatter Search

Disclosed herein is a discharge lamp type display device which comprises mainly at least one discharge lamp formed by a discharge tube in which inert gas is charged. The discharge lamp comprises a pair of electrodes one of which is locally provided within the discharge tube adjacent one end thereof and the other is formed of electrically conductive, light transmissive film deposited on the exterior surface of the discharge tube. The display device further comprises means for gradually increasing or decreasing the voltage or the frequency of discharge power to be supplied between the two electrodes of the discharge lamp, whereby illumination region of the discharge lamp is variably controlled.
3-D Statistical Channel Model for Millimeter-Wave Outdoor Communications

This paper presents a 3-dimensional millimeterwave statistical channel impulse response model from 28 GHz and 73 GHz ultrawideband propagation measurements [1], [2] . An accurate 3GPP-like channel model that supports arbitrary carrier frequency, RF bandwidth, and antenna beamwidth (for both omnidirectional and arbitrary directional antennas), is provided. Time cluster and spatial lobe model parameters ar e extracted from empirical distributions from field measurements. A step-by-step modeling procedure for generating channel coefficients is shown to agree with statistics from the field measurements, thus confirming that the statistical channel model faithfully recreates spatial and temporal channel impulse responses for use in millimeter-wave 5G air interface desig ns.
Prediction of protein-RNA binding sites by a random forest method with combined features

MOTIVATION Protein-RNA interactions play a key role in a number of biological processes, such as protein synthesis, mRNA processing, mRNA assembly, ribosome function and eukaryotic spliceosomes. As a result, a reliable identification of RNA binding site of a protein is important for functional annotation and site-directed mutagenesis. Accumulated data of experimental protein-RNA interactions reveal that a RNA binding residue with different neighbor amino acids often exhibits different preferences for its RNA partners, which in turn can be assessed by the interacting interdependence of the amino acid fragment and RNA nucleotide. RESULTS In this work, we propose a novel classification method to identify the RNA binding sites in proteins by combining a new interacting feature (interaction propensity) with other sequence- and structure-based features. Specifically, the interaction propensity represents a binding specificity of a protein residue to the interacting RNA nucleotide by considering its two-side neighborhood in a protein residue triplet. The sequence as well as the structure-based features of the residues are combined together to discriminate the interaction propensity of amino acids with RNA. We predict RNA interacting residues in proteins by implementing a well-built random forest classifier. The experiments show that our method is able to detect the annotated protein-RNA interaction sites in a high accuracy. Our method achieves an accuracy of 84.5%, F-measure of 0.85 and AUC of 0.92 prediction of the RNA binding residues for a dataset containing 205 non-homologous RNA binding proteins, and also outperforms several existing RNA binding residue predictors, such as RNABindR, BindN, RNAProB and PPRint, and some alternative machine learning methods, such as support vector machine, naive Bayes and neural network in the comparison study. Furthermore, we provide some biological insights into the roles of sequences and structures in protein-RNA interactions by both evaluating the importance of features for their contributions in predictive accuracy and analyzing the binding patterns of interacting residues. AVAILABILITY All the source data and code are available at http://www.aporc. org/doc/wiki/PRNA or http://www.sysbio. ac.cn/datatools.asp CONTACT lnchen@sibs.ac.cn SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
VidCat: an image and video analysis service for personal media management

Cloud-based storage and consumption of personal photos and videos provides increased accessibility, functionality, and satisfaction for mobile users. One cloud service frontier that is recently growing is that of personal media management. This work presents a system called VidCat that assists users in the tagging, organization, and retrieval of their personal media by faces and visual content similarity, time, and date information. Evaluations for the effectiveness of the copy detection and face recognition algorithms on standard datasets are also discussed. Finally, the system includes a set of application programming interfaces (API’s) allowing content to be uploaded, analyzed, and retrieved on any client with simple HTTP-based methods as demonstrated with a prototype developed on the iOS and Android mobile platforms.
Introducing 'Bones': a parallelizing source-to-source compiler based on algorithmic skeletons

Recent advances in multi-core and many-core processors requires programmers to exploit an increasing amount of parallelism from their applications. Data parallel languages such as CUDA and OpenCL make it possible to take advantage of such processors, but still require a large amount of effort from programmers. A number of parallelizing source-to-source compilers have recently been developed to ease programming of multi-core and many-core processors. This work presents and evaluates a number of such tools, focused in particular on C-to-CUDA transformations targeting GPUs. We compare these tools both qualitatively and quantitatively to each other and identify their strengths and weaknesses. In this paper, we address the weaknesses by presenting a new classification of algorithms. This classification is used in a new source-to-source compiler, which is based on the algorithmic skeletons technique. The compiler generates target code based on skeletons of parallel structures, which can be seen as parameterisable library implementations for a set of algorithm classes. We furthermore demonstrate that the presented compiler requires little modifications to the original sequential source code, generates readable code for further fine-tuning, and delivers superior performance compared to other tools for a set of 8 image processing kernels.
Island multicast: the combination of IP multicast with application-level multicast

The Internet nowadays consists of multicast-capable domains or "islands" interconnected by multicast-incapable routers. In order to achieve efficient global multicast, we propose and study island multicast (IM) where overlay connections are used between islands while IP multicast is used within an island. IM may use any existing application-level multicast protocol to build island overlay. We describe how to elect a representative (or leader) in each island for such a purpose. We also present the mechanisms for electing the bridging nodes for overlay connections. Using Internet-like topologies, we show that IM achieves much higher bandwidth efficiency as compared to using application-level multicast alone, at the cost of a small increase in end-to-end delay.
How Predictability of Feeding Patches Affects Home Range and Foraging Habitat Selection in Avian Social Scavengers?

Feeding stations are commonly used to sustain conservation programs of scavengers but their impact on behaviour is still debated. They increase the temporal and spatial predictability of food resources while scavengers have supposedly evolved to search for unpredictable resources. In the Grands Causses (France), a reintroduced population of Griffon vultures Gyps fulvus can find carcasses at three types of sites: 1. “light feeding stations”, where farmers can drop carcasses at their farm (spatially predictable), 2. “heavy feeding stations”, where carcasses from nearby farms are concentrated (spatially and temporally predictable) and 3. open grasslands, where resources are randomly distributed (unpredictable). The impact of feeding stations on vulture’s foraging behaviour was investigated using 28 GPS-tracked vultures. The average home range size was maximal in spring (1272±752 km2) and minimal in winter (473±237 km2) and was highly variable among individuals. Analyses of home range characteristics and feeding habitat selection via compositional analysis showed that feeding stations were always preferred compared to the rest of the habitat where vultures can find unpredictable resources. Feeding stations were particularly used when resources were scarce (summer) or when flight conditions were poor (winter), limiting long-ranging movements. However, when flight conditions were optimal, home ranges also encompassed large areas of grassland where vultures could find unpredictable resources, suggesting that vultures did not lose their natural ability to forage on unpredictable resources, even when feeding stations were available. However during seasons when food abundance and flight conditions were not limited, vultures seemed to favour light over heavy feeding stations, probably because of the reduced intraspecific competition and a pattern closer to the natural dispersion of resources in the landscape. Light feeding stations are interesting tools for managing food resources, but don’t prevent vultures to feed at other places with possibly high risk of intoxication (poison).
Optimization of Weighting Factors for Multiple Window Spectrogram of Event-Related Potentials

This paper concerns the mean square error optimal weighting factors for multiple window spectrogram of different stationary and nonstationary processes. It is well known that the choice of multiple windows is important, but here we show that the weighting of the different multiple window spectrograms in the final average is as important to consider and that the equally averaged spectrogram is not mean square error optimal for non-stationary processes. The cost function for optimization is the normalized mean square error where the normalization factor is the multiple window spectrogram. This means that the unknown weighting factors will be present in the numerator as well as in the denominator. A quasi-Newton algorithm is used for the optimization. The optimization is compared for a number of well-known sets of multiple windows and common weighting factors and the results show that the number and the shape of the windows are important for a small mean square error. Multiple window spectrograms using these optimal weighting factors, from ElectroEncephaloGram data including steady-state visual evoked potentials, are shown as examples.
Hierarchical attention model for improved machine comprehension of spoken content

Multimedia or spoken content presents more attractive information than plain text content, but the former is more difficult to display on a screen and be selected by a user. As a result, accessing large collections of the former is much more difficult and time-consuming than the latter for humans. It's therefore highly attractive to develop machines which can automatically understand spoken content and summarize the key information for humans to browse over. In this endeavor, a new task of machine comprehension of spoken content was proposed recently. The initial goal was defined as the listening comprehension test of TOEFL, a challenging academic English examination for English learners whose native languages are not English. An Attention-based Multi-hop Recurrent Neural Network (AMRNN) architecture was also proposed for this task, which considered only the sequential relationship within the speech utterances. In this paper, we propose a new Hierarchical Attention Model (HAM), which constructs multi-hopped attention mechanism over tree-structured rather than sequential representations for the utterances. Improved comprehension performance robust with respect to ASR errors were obtained.
The Human CD8β M-4 Isoform Dominant in Effector Memory T Cells Has Distinct Cytoplasmic Motifs That Confer Unique Properties

The CD8 co-receptor influences T cell recognition and responses in both anti-tumor and anti-viral immunity. During evolution in the ancestor of humans and chimpanzees, the CD8B gene acquired two additional exons. As a result, in humans, there are four CD8β splice variants (M1 to M4) that differ in their cytoplasmic tails. The M-1 isoform which is the equivalent of murine CD8β, is predominantly expressed in naïve T cells, whereas, the M-4 isoform is predominantly expressed in effector memory T cells. The characteristics of the M-4 isoform conferred by its unique 36 amino acid cytoplasmic tail are not known. In this study, we identified a dihydrophobic leucine-based receptor internalization motif in the cytoplasmic tail of M-4 that regulated its cell surface expression and downregulation after activation. Further the M-4 cytoplasmic tail was able to associate with ubiquitinated targets in 293T cells and mutations in the amino acids NPW, a potential EH domain binding site, either enhanced or inhibited the interaction. In addition, the M-4 tail was itself mono-ubiquitinated on a lysine residue in both 293T cells and a human T cell line. When peripheral blood human T cells expressed CD8αβ M-4, the frequency of MIP-1β secreting cells responding to antigen presenting cells was two-fold higher as compared to CD8αβ M-1 expressing T cells. Thus, the cytoplasmic tail of the CD8β M-4 isoform has unique characteristics, which likely contributed to its selective expression and function in human effector memory T cells.
Self-supervised monocular distance learning on a lightweight micro air vehicle

Obstacle detection by monocular vision is challenging because a single camera does not provide a direct measure for absolute distances to objects. A self-supervised learning approach is proposed that combines a camera and a very small short-range proximity sensor to find the relation between the appearance of objects in camera images and their corresponding distances. The method is efficient enough to run real time on a small camera system that can be carried onboard a lightweight MAV of 19 g. The effectiveness of the method is demonstrated by computer simulations and by experiments with the real platform in flight.
A study of iSCSI extensions for RDMA (iSER)

The iSCSI protocol is the IETF standard that maps the SCSI family of application protocols onto TCP/IP enabling convergence of storage traffic on to standard TCP/IP fabrics. The ability to efficiently transfer and place the data on TCP/IP networks is crucial for this convergence of the storage traffic. The iWARP protocol suite provides Remote Direct Memory Access (RDMA) semantics over TCP/IP networks and enables efficient memory-to-memory data transfers over an IP fabric. This paper studies the design process of iSCSI Extensions for RDMA (iSER), a protocol that maps the iSCSI protocol over the iWARP protocol suite. As part of this study, this paper shows how iSER enables efficient data movement for iSCSI using generic RDMA hardware and then presents a discussion of the iWARP architectural features that were conceived during the iSER design. These features potentially enable highly efficient realizations of other I/O protocols as well.