Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual Diversified Dynamical Gaussian Process Latent Variable Model for Video Repairing

In this paper, we propose a dual diversified dynamical Gaussian process latent variable model (D3GPLVM) to tackle the video repairing issue. For preservation purposes, videos have to be conserved on media. However, storing on media, such as films and hard disks, can suffer from unexpected data loss, for instance, physical damage. So repairing of missing or damaged pixels is essential for better video maintenance. Most methods seek to fill in missing holes by synthesizing similar textures from local patches (the neighboring pixels), consecutive frames, or the whole video. However, these can introduce incorrect contexts, especially when the missing hole or number of damaged frames is large. Furthermore, simple texture synthesis can introduce artifacts in undamaged and recovered areas. To address aforementioned problems, we introduce two diversity encouraging priors to both of inducing points and latent variables for considering the variety in existing videos. In D3GPLVM, the inducing points constitute a smaller subset of observed data, while latent variables are a low-dimensional representation of observed data. Since they have a strong correlation with the observed data, it is essential that both of them can capture distinct aspects of and fully represent the observed data. The dual diversity encouraging priors ensure that the trained inducing points and latent variables are more diverse and resistant for context-aware and artifacts-free-based video repairing. The defined objective function in our proposed model is initially not analytically tractable and must be solved by variational inference. Finally, experimental testing results illustrate the robustness and effectiveness of our method for damaged video repairing.
Reconstruction of non-constant velocity profiles in pneumatic pipelines by microwave inverse scattering techniques

Inverse scattering techniques can be exploited to recover the solid distributions and the velocity profiles in different types of pipelines involving materials in motion. It is now known that these targets can be achieved by splitting the problem into two separate inverse procedures: the first working on the reconstruction of the dielectric permittivity only and the other one trying to recover the velocity field.
Convergence to market efficiency: the case of seasoned equity offering stocks

This study examines the relationship between returns and contemporaneous and lagged-order imbalances by regression analysis. Conditional on contemporaneous imbalances, a significantly negative relationship is found between lagged-one imbalances and returns, except for a 10-minute time interval. This suggests that seasoned equity offering (SEO) markets converge to efficiency within 10 minutes. In addition, a GARCH model is used to examine the dynamic relationship between volatility and order imbalances. The empirical results demonstrate that market-makers effectively mitigate volatility in SEO announcements, demonstrating a price stabilisation capability in secondary market-making.
On the importance of phase information in additive analysis/synthesis of binaural sounds

This article presents a number of psycho-acoustic experiments for assessing the importance of phase information regarding the spatial qualities of synthesized sounds from voiced instruments. Binaural recorded sounds are synthesized using additive analysis/synthesis with and without phase information. The phase information is used in the synthesis to preserve the characteristics of the waveform. The experiments show the importance of phase when dealing with localization of voiced instruments. The phase information is shown to be crucial for determining the direction of the sound. Furthermore, it is observed that the test person’s ability to perceive the spatial qualities of the sounds is not dependent on fundamental frequency when synthesis is done with phase information, and indications are given that the attack part of the sound has limited influence on spatial perception.
Analysis of kinematics and dynamics of snake-like robot with joints of 4-DOF

Snake-like robot is more and more widespread attention in recent years, because of its Terrain adaptability and diverse forms of exercise. However, most existing snake-like robots are based on one or two degrees of freedom joints. This condition limits the motion diversity to some extent. In order to further enhance the speed and add the diversity of movement, the paper proposes a new 4-DOF joint, which consists of three rotating motor and a linear motor to achieve the three rotational degrees of freedom and a straight line freedom. It could help the robot adapt different environments. Besides the design of joints, we also analyze kinematics and dynamics equations of the robot. According to the simulation of the creeping movement of the snake-like robot with 4-DOF, we know that the robot can realize its ideal movement by utilizing the Serpenoid curve.
FEATURES EXTRACTION TECHNIQES OF EEG SIGNAL FOR BCI APPLICATIONS

The use of Electroencephalogram (EEG) signals in the field of Brain Computer Interface (BCI) have obtained a lot of interest with diverse applications ranging from medicine to entertainment. In this paper, BCI is designed using electroencephalogram (EEG) signals where the subjects have to think of only a single mental task. EEG signals are recorded from 16 channels and studied during several mental and motor tasks. Features are extracted from those signals using several methods: Time Analysis, Frequency Analysis, TimeFrequency Analysis and Time-Frequency-Space Analysis. Extracted EEG features are classified using an artificial neural network trained with the back propagation algorithm. Classification rates that reach 99% between two tasks and 96% between three tasks using SpaceTime-Frequency-analysis and Time-Frequency-analysis were obtained.
Parallel divide and conquer algorithms for the symmetric tridiagonal eigenproblem

In this paper a new implementation of a divide and conquer algorithm will be considered. This algorithm, in contrast to the LAPACK algorithm, uses a diierent formulation of the update problem, and extended precision in order to maintain accuracy and orthogonality. Our Intel Paragon implementation shows, in contrast to the Hypercube implementation by Ipsen and Jessup 14], that good speedups can be obtained from a distributed memory parallel version of the divide and conquer eigenvalue algorithm .
Risk of “silent stroke” in patients older than 60 years: risk assessment and clinical perspectives

With the increasing size of the elderly population and evolving imaging technology, silent brain infarction (SBI) has garnered attention from both the public and the physicians. Over 20% of the elderly exhibit SBI, and the prevalence of SBI increases steadily with age, ie, 30%–40% in those older than 70 years. Well-known cardiovascular risk factors such as hypertension has been identified as a risk factor of SBI (odds ratio [OR] = 3.47) Besides this, blood pressure (BP) reactivity to mental stress, morning BP surges, and orthostatic BP changes have been demonstrated to contribute to the presence of SBI. Further, a metabolic syndrome not only as a whole syndrome (OR =2.18) but also as individual components could have an influence on SBI. Increased C-reactive protein and interleukin-6, coronary artery disease, body mass index, and alcohol consumption have also been associated with SBI. The ORs and possible mechanisms have been discussed in this article. Overt stroke, dementia, depression, and aspiration pneumonia were all associated with SBI. (overt stroke: hazard ratio [HR] =1.9, 95% confidence interval [CI]: 1.2–2.8; dementia: HR =2.26, 95% CI: 1.09–4.70). We also looked into their close relationship with SBI in this review.
E-Business, a New Way of Trading in Virtual Environment Based on Information Technology

The age of Information technology with lots of services is upon us. Nowadays, using computers to do all sorts of daily tasks has become a necessity. Internet technology is changing faster, and the pace of it’s innovation and adoption is truly staggering. Apart from sharing or transacting data/information, all types of business transactions are frequently done through Internet. Over time people prefer staying in front of the PC and doing any business transactions for convinience and saving time. Hence, E-business is the key to make life easier for the people. Knowledge of e-business environment is essential for doing business in this century. New technologies for extracting knowledge from data must be understood and applied.
The Economic Effects of Civil War : Evidence from Chinese National Railroads , 1906-19231

During the Later Qing Dynasty and so-called “Warlord Period” (1906-1923) China suffered from numerous and violent internal conflicts, or “civil wars”. These conflicts are thought to have slowed the pace of economic development and, especially, growth in infrastructure. I study these alleged impacts using a new panel data set linking archival data for Chinese railroads to detailed information on civil wars. I show that conflict had negative effects on business passenger flows, operative revenue, and investment, with the latter operating primarily through Tobin’s Q. These effects occurred during the same period as the conflict, but also persisted after the fighting had stopped. My findings suggest that, in the absence of internal strife, China would have experienced more rapid growth during a crucial phase of its modern economic history.
Towards a generative syntax of tonal harmony

This paper aims to propose a hierarchical, generative account of diatonic harmonic progressions and suggest a set of phrase-structure grammar rules. It argues that the structure of harmonic progressions exceeds the simplicity of the Markovian transition tables and proposes a set of rules to account for harmonic progressions with respect to key structure, functional and scale degree features as well as modulations. Harmonic structure is argued to be at least one subsystem in which Western tonal music exhibits recursion and hierarchical organization that may provide a link to overarching linguistic generative grammar on a structural and potentially cognitive level.
Academic Research Performance and Intellectual Capital Measurement System: Evidence from Italian Universities

The paper investigates the correlation between some indicators promoted in international experience of measuring the Intellectual Capital of universities and the scientific performance of these insitutions. This study uses data reported to the researchers of Chemistry of Italian universities (over the period 2000-2007) and integrates the results of peer assessment of first Italian Research Assessment Exercise (VTR) with bibliometric indicators. Relations between quantitative and qualitative research evaluation methods are underlined. The analysis shows significant correlations among size of university, financial resources, teaching load, mobility and scientific performance and suggests an integration of ICU report. Also, have been proposed some hypotheses about the possible conditioning of the Impact Factor on the peer evaluations.
Human and Dog: An Experimental Game using Unequal Communication Mechanic

Inequality of communication capabilities may cause an awkward experience in real life. %However, in terms of gaming, unequal communication mechanic can make games more challenging and interesting. However, in terms of gaming, this can be a challenging and interesting mechanic. Charades[1], where one player tries to express a word via body language while others try to guess it, is a good example of such cases. Different from most digital co-op games, which equal communication mechanics have been widely used, we experiment with this unequal communication mechanic. Thus, we have designed a digital co-op game called getGameName, in which 2 avatars, a human and a dog, communicate to solve a series of puzzles with unequal communication capabilities. Ultimately, we conducted an experiment to evaluate our game. Several interesting patterns were discovered from our observation. We then concluded some design suggestions from our collected data for future reference.
Efficient Dense-Stereo and Novel-view Synthesis for Gaze Manipulation in One-toone Teleconferencing

A new algorithm is proposed for novel-view synthesis, with particular application to teleconferencing. Given the video streams acquired by two cameras placed on either side of a computer monitor, the proposed algorithm synthesises images from a virtual camera in arbitrary position (typically located within the monitor area) to facilitate eye contact. The new technique is based on an improved, dynamic-programming, stereo algorithm for efficient novel-view generation. The two main contributions of this paper are: i) a new four-layer matching graph for dense-stereo dynamic-programming, that supports accurate occlusion labeling; ii) a compact geometric derivation for novel-view synthesis by direct projection of the minimum-cost surface. Furthermore, the paper presents an algorithm for the temporal maintenance of a background model to enhance the rendering of occlusions and reduce temporal artefacts (flicker); and a cost aggregation algorithm that acts directly in three-dimensional matching cost space. The proposed algorithm has been designed to work with input images with large disparity range, a common situation in one-to-one video-conferencing. The enhanced oc-clusion-handling capabilities of the new DP algorithm are evaluated against those of the most powerful state-of-the-art dynamic-programming and graph-cut techniques. A number of examples demonstrate the robustness of the algorithm to artefacts in stereo video streams. This includes demonstrations of cyclopean view synthesis in extended conversational sequences, synthesis from a freely translating virtual camera and, finally, basic 3D scene editing.
FREQUENT PATTERN MINING OF CONTINUOUS DATA OVER DATA STREAMS

Frequent pattern mining is one of the important tasks used in data mining domain. Frequent pattern mining is used to find interesting patterns from databases, such as association rules, correlations rules, sequence rules, classifier rules, and cluster rules. The main goal of the association rule is, to analyze the purchased products of a customer in a supermarket transactional data. Association rule is used to describe how frequently items are purchased together. It is mainly used in transactional database. There is the efficient technique to discover the complete set of recent frequent patterns from a high-speed data stream over a sliding window. A New MOMENT algorithm with CET(Closed Enumeration Tree) to capture the recent stream data content and efficiently remove the obsolete, old stream data content. The complete set of recent frequent patterns is obtained from the CET of the current window using a transactional window sliding. Extensive experimental analyses show that our method is highly efficient in terms of memory and execution time when finding recent frequent patterns from a high-speed data
JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles

JASPAR (http://jaspar.genereg.net) is an open-access database storing curated, non-redundant transcription factor (TF) binding profiles representing transcription factor binding preferences as position frequency matrices for multiple species in six taxonomic groups. For this 2016 release, we expanded the JASPAR CORE collection with 494 new TF binding profiles (315 in vertebrates, 11 in nematodes, 3 in insects, 1 in fungi and 164 in plants) and updated 59 profiles (58 in vertebrates and 1 in fungi). The introduced profiles represent an 83% expansion and 10% update when compared to the previous release. We updated the structural annotation of the TF DNA binding domains (DBDs) following a published hierarchical structural classification. In addition, we introduced 130 transcription factor flexible models trained on ChIP-seq data for vertebrates, which capture dinucleotide dependencies within TF binding sites. This new JASPAR release is accompanied by a new web tool to infer JASPAR TF binding profiles recognized by a given TF protein sequence. Moreover, we provide the users with a Ruby module complementing the JASPAR API to ease programmatic access and use of the JASPAR collection of profiles. Finally, we provide the JASPAR2016 R/Bioconductor data package with the data of this release.
An exploratory analysis for predicting passenger satisfaction at global hub airports using logistic model trees

On-time performance during travel is a key factor in determining passenger convenience and satisfaction. On time flight arrivals and departures are dependent on various factors including airport characteristics like the number of flights handled, ground handler's efficiency, disruptions caused by weather conditions, security alerts, queue times at immigration and air traffic congestion. There is a direct causation based relationship on delays, cancellations, re-schedule at the airport with passenger complaints and churn. Airports and airlines can infer signals of passenger satisfaction with the relevant events associated with on-time performance and delays. Hub airports deal with high passenger traffic, connections and operational complexities hence they are good candidates for passenger service studies. In this paper, we had collected datasets for on-time performance, flights for 48 global hub airports and passenger reviews about queue time. Further, we applied Logistic Model Trees (LMT) machine learning method for predicting the level of passenger satisfaction based on factors like an airport on time performance, the number of flights, on-time ranking, average delays and queue time. The results are presented and discussed for further insights and studies.
Compact Region Extraction Using Weighted Pixel Linking in a Pyramid

This correspondence describes a method of image segmentation based on a ``pyramid'' of reduced-resolution versions of the image. It defines link strengths between pixels at adjacent levels of the pyramid, based on proximity and similarity, and iteratively recomputes the pixel values and adjusts the link strengths. After a few iterations, the strengths stabilize, and the links that remain strong define subtrees of the pyramid; the leaves of each tree are the pixels belonging to a compact (piece of a) homogeneous region in the image.
Recognizing human actions based on gist descriptor and word phrase

The precision of human action recognition mainly depends on the discrimination of action feature descriptors. The descriptors which contained both global and local information usually can be competent for classifying actions. A novel descriptor based on Gist descriptor and word phrase is proposed. Gist descriptor captures the structure information of action and its vectors imply the location relationship of local grids. According to the location which the Gist vectors attribute to, the features are divided into four segments, and word phrases are respectively constructed using bag of words method. By accumulating all the phrases, the final action descriptor is produced. Through SVM classifier our method obtains impressive results on KTH dataset.
Gravitational search algorithm with heuristic search for clustering problems

In this paper, we present an efficient algorithm for cluster analysis, which is based on gravitational search and a heuristic search algorithm. In the proposed algorithm, called GSA-HS, the gravitational search algorithm is used to find a near optimal solution for clustering problem, and then at the next step a heuristic search algorithm is applied to improve the initial solution by searching around it. Four benchmark datasets are used to evaluate and to compare the performance of the presented algorithm with two other famous clustering algorithms, i.e. K-means and particle swarm optimization algorithm. The results show that the proposed algorithm can find high quality clusters in all the tested datasets.
Fair and Efficient Dynamic Traffic Grooming Algorithm for WDM Mesh Networks

Traffic grooming in Wavelength Division Multiplexing networks merges low-speed flows into large capacity pipes so that the bandwidth discrepancy between them will not lead to underutilization of resources. Dynamic grooming deals with requests for wavelength allocation based on a dynamic pattern of arrivals in contrast to the situation of static grooming in which the pattern of arrivals must be previously known. Solutions for dynamic grooming typically involve the construction of an auxiliary graph for deciding on the routing and wavelength assignment. An auxiliary graph can represent the network partially leading to scalable solutions, although blocking is not fairly distributed among calls in such solutions. A novel algorithm is thus proposed for achieving fairness in blocking among the calls. In an off-line step, it defines an appropriate set of OXCs for achieving fairness and efficient use of resources. Results reveal a higher degree of fairness obtained by the use of the novel algorithm than for previously proposed algorithms.
Reduction of Nitroarenes to Azoxybenzenes by Potassium Borohydride in Water

The synthesis of the azoxybenzenes by the reduction of nitroarenes with reducing agent potassium borohydride in water was reported for the first time. PEG-400 was used as a phase transfer catalyst and could effectively catalyze the reduction. The electronic effects of substituent groups play an important role in determining the reduction efficiencies. Electron-withdrawing substituents promote the formation of the azoxybenzene products, while electron-releasing groups retard the reductions to various degrees depending on the extent of their electron-donating ability.
Social Capital and the Willingness to Become Self-Employed

This paper employs the concept of "social capital" to empirically investigate the role of social capital in the occupational choice process about whether to become self-employed. We demonstrate that the willingness to become self-employed depends on a person's social capital and hypothesize that women invest differently in social capital than men and therefore exhibit different levels of willingness to become self-employed. We test our hypotheses by using three ordered probit estimates on a data set with 5,000 students. We find that the more social capital an individual obtains, the more willing he or she is to start his or her own business and that women invest less in social capital than men and are thus less willing to become self-employed.
Traffic-adaptive packet filtering of denial of service attacks

Traffic-adaptive packet filtering is a mechanism to adjust packet classification methods at run-time to the particular traffic mix a network node is receiving. It has been conjectured previously that such techniques could perform positively when filtering out malicious attack traffic, due to their flow aggregation capabilities. In this work, we present two novel contributions-a first ever working implementation of a traffic adaptive firewall, based on insertion of shortcuts into a search tree, and both a simulated and a real-life performance study of adaptive packet filtering under denial-of-service attack traffic, the outcomes of which support the above conjecture