Miracle-dz/UniFAR-FTUs huggingface dataset:
Spiral unique sequence: A new rotation invariant feature for small-size image block matching

Matching features of all image overlapping blocks is a common method to explore duplicated regions. In this way, the block size should be small in order to detect small forgery regions. The problem is how to extract a robust feature for small block size against rotation and compression. In this paper, a new spatial domain feature for block size 8×8 pixels namely Spiral Unique Sequence (SUS) is proposed. The experimental results and SUS feature matching demonstrate that this feature is robust against rotation and compression.
Automatic selection of neuronal spike detection threshold via smoothed Teager energy histogram

Spike detection is a prerequisite to analyzing neuronal activity. While simple spike detectors are favorable for hardware implementation, manual setting of spike detection threshold can be tedious and time-consuming, especially for extracellular recordings of multiple neuronal activity. This paper, therefore, investigates and proposes an automatic threshold selection using smoothed Teager energy histogram (STEH), with consideration of signal prewhitening, histogram bin width, and histogram equalization. Results from spikes with signal-to-noise ratio = 0.9-2.6 dB reveals that (1) prewhitening of neural signals can enhance true detection rate (TDR) by 10-20% at constant false alarm (FA) ranging 3-12 spikes/s; (2) Freedman-Diaconis choice of STEH bin width delivers higher TDR (1.52 ± 1.41%) and FA (0.48 ± 0.25 spikes/s) than square-root choice; and (3) histogram equalization can raise average TDR by 2.84% and FA by 1.01 spikes/s. Thresholds determined by STEH with signal prewhitening, Freedman-Diaconis choice or square-root choice of bin width, and histogram equalization fall around knee point of receiver operating characteristic curve, yielding average TDR = 87.88% and FA = 1.82 spikes/s for Freedman-Diaconis choice, and TDR = 86.49% and FA = 1.41 spikes/s for square-root choice of STEH bin width.
Regulating Axonal Responses to Injury: The Intersection between Signaling Pathways Involved in Axon Myelination and The Inhibition of Axon Regeneration

Following spinal cord injury (SCI), a multitude of intrinsic and extrinsic factors adversely affect the gene programs that govern the expression of regeneration-associated genes (RAGs) and the production of a diversity of extracellular matrix molecules (ECM). Insufficient RAG expression in the injured neuron and the presence of inhibitory ECM at the lesion, leads to structural alterations in the axon that perturb the growth machinery, or form an extraneous barrier to axonal regeneration, respectively. Here, the role of myelin, both intact and debris, in antagonizing axon regeneration has been the focus of numerous investigations. These studies have employed antagonizing antibodies and knockout animals to examine how the growth cone of the re-growing axon responds to the presence of myelin and myelin-associated inhibitors (MAIs) within the lesion environment and caudal spinal cord. However, less attention has been placed on how the myelination of the axon after SCI, whether by endogenous glia or exogenously implanted glia, may alter axon regeneration. Here, we examine the intersection between intracellular signaling pathways in neurons and glia that are involved in axon myelination and axon growth, to provide greater insight into how interrogating this complex network of molecular interactions may lead to new therapeutics targeting SCI.
An Application of Approximate Ontology Matching in eResponse

Ontology matching is a key problem in many metadata intensive application domains, including emergency response, data integration, peer-to-peer information sharing, web service composition, and query answering on the web. In this paper we present an emergency response scenario based on the organizational model as used in Trentino region, Italy. We provide a formalization of this scenario with the help of lightweight coordination calculus. Then, we discuss an automatic approximate structure preserving matching algorithm which we applied within the emergency response scenario. The evaluation results, though preliminary, are encouraging.
Towards an information logic

'Probability is expectation founded upon partial knowledge. ' (Boole, 1854) Information retrieval based on stored program electronic computers has been an active area of research since the time these machines were invented. It is therefore somewhat surprising that even now no formal computational model for IR exists. There is no well-defined logic to describe information retrieval, and there is no proof or model theory to talk about the truths of IR. This paper argues that much of the research work in the past has been steps in the direction of a logic for IR. These steps have been taken by developing formal models for information retrieval, but to date none of these are complete nor could any claim to be a computational model for IR. To appreciate this development I shall present a picture of IR, describing bits of a puzzle which may fit together to point to a new framework within which a computational model or logic could be described.
On the Feasibility of Crawling Linked Data Sets for Reusable Defect Corrections

Current linked open data standards have encouraged the publication of a large number of data sets on the public Web. While some data providers put a lot of energy and resources into maintaining high quality data, others do not, meaning that the quality of the data in many LOD sources is variable and unpredictable. This makes the construction of novel applications on top of the data more difficult and expensive than it otherwise would be. However, these same data standards also open up possibilities for new ways of managing information quality (IQ). In this paper, we propose one such approach, the IQ-bot, and present the results of our study of its feasibility. An IQbot is a 3rd party component that crawls the Web of data, looking for changes that have been made to data sets, and inferring from them where a correction to a data defect has been made. These corrections can then potentially be made available for application to other databases showing evidence of the presence of the same data defect. In this way, the benefits of the curation effort put into a small number of data sets can be propagated throughout the Web of data.
A reconfigurable cylindrical dielectric resonator antenna for WiMAX/WLAN applications

The main objective of the present study is to achieve the reconfigurability of a cylindrical dielectric resonator antenna (CDRA). The CDRA is excited with two different modes; the HEMjjg mode is excited via an aperture etched on the ground under the center of the CDRA, where the TM01δ mode is excited from an etched slot under the side of the CDRA, the reconflgurabilty is realized using two PIN diodes. Two different cases of PIN diode (D1-ON/D2-OFF and vice versa) are investigated and analyzed. The proposed cylindrical dielectric resonator antenna (CDRA) can provides two bands around 3.77 GHz and 5.5 GHz with a reflection coefficient below than −10dB which is appropriate for WiMAX and WLAN applications, respectively. The antenna gain is stable in the two bands 3.77GHz/5.5GHz with 3.8 dBi and 4.43dBi, respectively. The simulation is performed using two simulators; the CST Microwave Studio and the HFSS Ansoft package.
Experimental assessment of COTS DBMS robustness under transient faults

This paper evaluates the behavior of a common off-the-shelf (COTS) database management system (DBMS) in presence of transient faults. Database applications have traditionally been a field with fault-tolerance needs, concerning both data integrity and availability. While most of the commercially available DBMS provide support for data recovery and fault-tolerance, very limited knowledge was available regarding the impact of transient faults in a COTS database system. In this experimental study, a strict off-the-shelf target system is used (Oracle 7.3 server running on top of Wintel platform), combined with a TPC-A based workload and a software implemented fault injection tool, XceptionNT. It was found out that a non-negligible amount of induced faults, 13%, lead to the database server hanging or premature termination. However, the results also show that COTS DBMS products has a reasonable behavior concerning data integrity, none of the injected faults affected end user data.
Complex Matrix Factorization for Face Recognition

This work developed novel complex matrix factorization methods for face recognition; the methods were complex matrix factorization (CMF), sparse complex matrix factorization (SpaCMF), and graph complex matrix factorization (GraCMF). After real-valued data are transformed into a complex field, the complex-valued matrix will be decomposed into two matrices of bases and coefficients, which are derived from solutions to an optimization problem in a complex domain. The generated objective function is the real-valued function of the reconstruction error, which produces a parametric description. Factorizing the matrix of complex entries directly transformed the constrained optimization problem into an unconstrained optimization problem. Additionally, a complex vector space with N dimensions can be regarded as a 2N-dimensional real vector space. Accordingly, all real analytic properties can be exploited in the complex field. The ability to exploit these important characteristics motivated the development herein of a simpler framework that can provide better recognition results. The effectiveness of this framework will be clearly elucidated in later sections in this paper.
Unmanned Aerial ad Hoc Networks: Simulation-Based Evaluation of Entity Mobility Models’ Impact on Routing Performance

An unmanned aerial ad hoc network (UAANET) is a special type of mobile ad hoc network (MANET). For these networks, researchers rely mostly on simulations to evaluate their proposed networking protocols. Hence, it is of great importance that the simulation environment of a UAANET replicates as much as possible the reality of UAVs. One major component of that environment is the movement pattern of the UAVs. This means that the mobility model used in simulations has to be thoroughly understood in terms of its impact on the performance of the network. In this paper, we investigate how mobility models affect the performance of UAANET in simulations in order to come up with conclusions/recommendations that provide a benchmark for future UAANET simulations. To that end, we first propose a few metrics to evaluate the mobility models. Then, we present five random entity mobility models that allow nodes to move almost freely and independently from one another and evaluate four carefully-chosen MANET/UAANET routing protocols: ad hoc on-demand distance vector (AODV), optimized link state routing (OLSR), reactive-geographic hybrid routing (RGR) and geographic routing protocol (GRP). In addition, flooding is also evaluated. The results show a wide variation of the protocol performance over different mobility models. These performance differences can be explained by the mobility model characteristics, and we discuss these effects. The results of our analysis show that: (i) the enhanced Gauss–Markov (EGM) mobility model is best suited for UAANET; (ii) OLSR, a table-driven proactive routing protocol, and GRP, a position-based geographic protocol, are the protocols most sensitive to the change of mobility models; (iii) RGR, a reactive-geographic hybrid routing protocol, is best suited for UAANET.
Effects of Two Environmental Best Management Practices on Pond Water and Effluent Quality and Growth of Nile Tilapia, Oreochromis niloticus

The trajectory of aquaculture growth in sub-Saharan Africa has necessitated closer attention to the use of environmental best management practices (BMPs). Two BMPs in particular, water reuse and floating feeds, are being promoted for adoption by pond fish farmers in sub-Saharan Africa. In this study, we investigated: (1) the effect of water source and feed type on water quality; (2) the effect of water source and feed type on tilapia growth; and (3) the quality of potential effluents from ponds using different water source and feed types. The study was conducted in Ghana using on-farm experiments involving monitoring of water quality and growth of Nile tilapia Oreochromis niloticus for 160 days. Although considered low-intensity production systems, nutrients and solids in the study ponds exceeded levels expected in intensive culture ponds by wide margins, whereas BOD5 was within the range for semi-intensive ponds. Floating feed was associated with
Cyclic Weighted Centroid Algorithm for Transmitter Localization in the Presence of Interference

This paper addresses the problem of localizing a non-cooperative transmitter in the presence of a spectrally overlapped interferer in a cognitive receiver (CR) network. It has been observed that the performance of non-cooperative weighted centroid localization (WCL) algorithm degrades in the presence of a spectrally overlapped interferer. We propose cyclic WCL algorithm that uses cyclic autocorrelation (CAC) of received signals at CRs in the network to estimate the location coordinates of the target transmitter. Performance of the proposed algorithm is further improved by eliminating CRs in the vicinity of the interferer from the localization process. In order to identify and eliminate CRs in the vicinity of the interferer, the ratio of the variance and the mean of the square of absolute value of the CAC, referred to as feature variation coefficient, is used. Theoretical analysis of the cyclic WCL algorithm is presented in order to compute the root mean square error in the location estimates. We further study the impacts of the interferer's power and location, CR density, and fading environment on the performance of cyclic WCL. The comparison between cyclic WCL and traditional WCL is also presented.
Chinese semantic dependency analysis: Construction of a treebank and its use in classification

Semantic analysis is a standard tool in the Natural Language Processing (NLP) toolbox with widespread applications. In this article, we look at tagging part of the Penn Chinese Treebank with semantic dependency. Then we take this tagged data to train a maximum entropy classifier to label the semantic relations between headwords and dependents to perform semantic analysis on Chinese sentences. The classifier was able to achieve an accuracy of over 84%. We then analyze the errors in classification to determine the problems and possible solutions for this type of semantic analysis.
Multilingual Discourse Processing

The goal of the work reported here is to provide a system for handling spoken dialogues which can be easily ported to new languages and new application areas. This work is being carried within the Dumas project, which aims to explore a number of approaches to this task. The particular approach described here involves involes constructing fairly traditional ‘logical forms’ on the basis of structural analyses of the input speech and then using a mixture of meaning postulates, which relate terms in the language to underlying concepts, and general domain knowledge in order to interpret and respond to what has been said.
New binary codes

In this paper constructions are given for combining two, three, or four codes to obtain new codes. The Andryanov-Saskovets construction is generalized. It is shown that the Preparata double-error-correcting codes may be extended by about (block length) ^{1/2} symbols, of which only one is a check symbol, and that e -error-correcting BCH codes may sometimes be extended by (block ! ength) ^{1/e} symbols, of which only one is a check symbol. Several new families of linear and nonlinear double-error-correcting codes are obtained. Finally, an infinite family of linear codes is given with d/n = \frac{1}{3} , the first three being the (24,2^12, 8) Golay code, a (48,2^15, 16) code, and a (96,2^18, 32) code. Most of the codes given have more codewords than any comparable code previously known to us.
Mapping knowledge flows in virtual teams with SNA

Purpose – The purpose of this paper is to illustrate the use of Social Network Analysis (SNA) to map information and knowledge flow in six virtual project teams with members of diverse cultures in private and public sector companies in different sectors.Design/methodology/approach – Due to the area of research, the authors supplemented the in‐depth interviews with an embedded SNA questionnaire and two stage analysis.Findings – The SNA findings demonstrated that network ties are useful predictors of how information and knowledge flows in virtual project teams and can be better indicators than formal project structures. assessment of participants' prestige, activity and influence and their generic formal team functions, thus leadership, member and support roles.Research limitations/implications – SNA does not yield information about causal factors, context or history of the team contributing to the current team relationships.Practical implications – SNA as a method in this study delivers information on dive.
Using a cluster as a memory resource: A fast and large virtual memory on MPI

The 64-bit OS provides ample memory address space that is beneficial for applications using a large amount of data. This paper proposes using a cluster as a memory resource for sequential applications requiring a large amount of memory. This system is an extension of our previously proposed socket-based Distributed Large Memory System (DLM), which offers large virtual memory by using remote memory distributed over nodes in a cluster. The newly designed DLM is based on MPI (Message Passing Interface) to exploit higher portability. MPI-based DLM provides fast and large virtual memory on widely available open clusters managed with an MPI batch queuing system. To access this remote memory, we rely on swap protocols adequate for MPI thread support levels. In experiments, we confirmed that it achieves 493 MB/s and 613 MB/s of remote memory bandwidth with the STREAM benchmark on 2.5 GB/s and 5 GB/s links (Myri-10G x2, x4) and high performance of applications with NPB and Himeno benchmarks. Additionally, this system enables users unfamiliar with parallel programming to use a cluster.
A real-time sand simulation using a GPU

Though several models of sand simulation have been adopted, due to complexity of a granular system in general, their performance has been sacrificed for realistic visual effects. It mainly results in a high numerical computational cost involved in an accurate simulation of a granular system. This limits the usability of those models by not supporting real physics based real-time simulation. We use a continuum method to model sand as a continuous fluid and various approaches to complete a pressure projection. Our approach shows an average performance that was achieved after adopting a GPU programming.
Region Based Collaborative Angle of Arrival Localization for Wireless Sensor Networks with Maximum Range Information

Authors in this paper use angle of arrival (AoA) information to localize a network of 100 nodes with one anchor only. The maximum communication range of a node in a wireless sensor network is known. Number of hops is dynamic, depending upon backward communication from node to be localized to the node already localized. The nodes within communication range from each other exploit noisy AoA information and combine this with maximum range to form own region. The region formed is reduced by using AoA information collaboratively. The performance of localization algorithm proposed for uniform Angle of arrival error distribution and different scenario of standard error deviations is studied. Authors also study the relocation of anchor at different locations inside the deployment region to assess the accuracy of localization.
SCORING STRUCTURAL MDE: TOWARDS MORE MEANINGFUL ERROR RATES

This paper outlines issues and explores options for augmenting the current structural MDE scoring with the goal of obtaining more meaningful measures of performance. We propose event-based statistical significance measures (similar to STT), evaluation of confidence predictions (important to downstream processing applications), and accounting for annotation differences (due to inherent variability in annotations). Focusing on SUs, we give results for SRI-ICSI-UW system outputs for reference and STT conditions with preliminary implementations of these proposals.
Potential Field-based Collision Avoidance for Multicopters

Reliable obstacle avoidance is a key to navigating with UAVs in the close vicinity of static and dynamic obstacles. Wheel-based mobile robots are often equipped with 2D or 3D laser range finders that cover the 2D workspace sufficiently accurate and at a high rate. Micro UAV platforms operate in a 3D environment, but the restricted payload prohibits the use of fast state-of-the-art 3D sensors. Thus, perception of small obstacles is often only possible in the vicinity of the UAV and a fast collision avoidance system is necessary. We propose a reactive collision avoidance system based on artificial potential fields, that takes the special dynamics of UAVs into account by predicting the influence of obstacles on the estimated trajectory in the near future using a learned motion model. Experimental evaluation shows that the prediction leads to smoother trajectories and allows to navigate collision-free through passageways.
Interpolation synthesis for articulated figure motion

Realistic real time articulated figure motion is achieved by reprocessing a stored database of motions. Motions are created to exact specification by interpolation from a set of example motions, effectively forming a parameterized motion model. A pre-processing step involving iterative calculations is used to allow efficient direct computations at run time. An inverse kinematics capability is shown that is based on interpolation. This method preserves the underlying qualities of the data, such as dynamical realism of motion capture, while generating a continuous range of required motions. Relevant applications include networked virtual reality and interactive entertainment.
A description of Dialogic Units/Discourse Markers in spontaneous speech corpora based on phonetic parameters

In this paper we propose a different way to face the notion of Discourse Markers (DM), based on prosodic features and using data from spontaneous speech corpora. We show how it is possible to predict DMs through prosodic parameters if we use corpora segmented into tone and information units. We will also show that DMs with different functions feature different prosodic profiles that are the formal counterpart of function in speech. Besides this, we will present the result of a first attempt of a statistical test, and discuss the limits and perspectives of the proposal. Finally, we will present a detailed description of four different DMs.