Miracle-dz/UniFAR-FTUs huggingface dataset:
Determining Motion Directly from Normal Flows Upon the Use of a Spherical Eye Platform

We address the problem of recovering camera motion from video data, which does not require the establishment of feature correspondences or computation of optical flows but from normal flows directly. We have designed an imaging system that has a wide field of view by fixating a number of cameras together to form an approximate spherical eye. With a substantially widened visual field, we discover that estimating the directions of translation and rotation components of the motion separately are possible and particularly efficient. In addition, the inherent ambiguities between translation and rotation also disappear. Magnitude of rotation is recovered subsequently. Experimental results on synthetic and real image data are provided. The results show that not only the accuracy of motion estimation is comparable to those of the state-of-the-art methods that require explicit feature correspondences or optical flows, but also a faster computation time.
SAPAM: A Scalable "Activities in Places" Analysis Mechanism for Informed Place Design

As a novel concept, "Informed Design" is being practiced in the Future Cities Laboratory at the Singapore-ETH Centre to innovate place design from empirical to evidential by harnessing geo-referenced "Big Data" for a responsive design. Initially, potentials of people sensing data derived from multi-sources, such as social networks, dedicated applications, sensors, etc., shall be explored to measure place utilization for a better understanding of design contexts and elicitation of design requirements. Therefore, an "Activities in Places" service is required to detect frequently used places, called hot places (HPs), and measure their utilizations in various dimensions. In order to fulfill emerging requirements and properly handle big and heterogeneous geo-located data in a near-real time manner for a responsive design, a unsupervised method, called Scalable "Activities in Places" Analysis Mechanism (SAPAM), is proposed with two main analysis mechanisms, namely 1) a scalable density-based spatial clustering of applications with noise (SDBSCAN), which dramatically improves the performance of DBSCAN through concurrent clusterings on data partitions, 2) a hot place detection procedure (HPDP) to extract HPs from clusters based on a continuous place usage pattern (CPUP), and analyze performed activities through a topic model trained by a corpus of daily documents of places. As proved by a comprehensive evaluation, 1) SDBSCAN, indeed, greatly improves the performance as shown by its best performance 4.71s, which is 11 times faster than DBSCAN, 2) HPDP can precisely detect HPs with a high recall of Singaporean regional centers, main transportation hubs and famous attractions, and 3) the utilization of HPs can be unveiled by three indicators, namely the number of visitors, the size of influence area, and the density of people, and also by performed activities in HPs. As a case study, three top 10 HP lists of three utilization indexes are created, and performed activities in a regional center Jurong East are analyzed.
A Realistic and Optimized V2V Communication System for Taxicabs

Due to high mobility and intermittent connections in vehicular networks, reliable and efficient vehicular communication is a challenging task. Previous research on Vehicle-to-Vehicle (V2V) communication mostly focuses on achieving reliable transmissions from a given source to a given destination by mining moving patterns of taxicabs. However, to the best of our knowledge, none of them considered the habit-driven regularities of individual taxicabs as well as the urban-layout-driven time-varying regularities of crowds of taxicabs synthetically. With this insight, we model both individual and holistic driving patterns by Markov Chain models, then devise a new method to predict possible driving routes for every single taxicab. In addition, we design a new method to evaluate the probability that a single taxicab retrieves information of a specific road segment while it drives through another road segment during a given time period, and also to quantify the expected probability that a single taxicab obtains the information of a given road segment in the near future. With such information, our solution enables the selection of the optimal data packet transmission scheme. We evaluate our solution on a real-world taxicab dataset. Experimental results demonstrate that our approach outperforms alternative solutions in terms of diffusion speed and success ratio of data retrieval.
The topological Singer construction

We study the continuous (co-)homology of towers of spectra, with emphasis on a tower with homotopy inverse limit the Tate construction X tG on a G-spectrum X. When G = Cp is cyclic of prime order and X = B ∧p is the p-th smash power of a bounded below spectrum B with H∗(B;Fp) of finite type, we prove that (B ∧p ) tC p is a topological model for the Singer construction R+(H ∗ (B;Fp)) on H ∗ (B;Fp). There is a stable map ǫB: B → (B ∧p ) tC p inducing the ExtA -equivalence ǫ: R+(H ∗ (B;Fp)) → H ∗ (B;Fp). Hence ǫB and the canonical map : ( B ∧p ) C p → (B ∧p ) hC p are p-adic equivalences.
Construction of human tissue-specific phosphorylation networks with protein expression data

Phosphorylation is a post-translational modification process mediated by kinases through the addition of a covalently bound phosphate group, which plays important roles in a wide range of cellular progresses, such as signaling cascades and development. Over the past years, despite many phosphorylation sites have been determined with mass spectrometry techniques, it is not clear which kinase phosphorylates which proteins. Under the circumstance, we propose a new probabilistic model to identify the substrates phosphorylated by certain kinases. Furthermore, we construct three tissue-specific phosphorylation networks based on protein expression data. Investigating the constructed tissue-specific networks, we find they are functionally consistent with the corresponding tissues, implying the effectiveness and biological significance of our proposed approach.
Domestic Violence Subjected to Different Patterns of Cultural Marriage

Violence against women and girls and its legal, social, psychological and related issues are not a new topic in social science. However, it has attracted a significant amount of attention from many researchers and still needs further investigation. Among different sources provoking violence against females such as gender inequality, insufficient protective legal systems, cultural pressure and etc., different marital patterns have been reported by the informants of this research. Child marriage, consanguineous marriage and unregistered/white marriage put girls and women in a vulnerable position. For example, under the pressure of abusive behavior in family, females escape from patriarchal family, leave their city/country and live as a refugee. In more severe cases, they attempt suicide under the pressure of pain and suffering. In comparison with developed countries where the human rights of the female are well-established and such marital patterns are not seen, these types of martial patterns are reported in patriarchal societies. Therefore, this study introduces these patterns and describes their effects on provoking the domestic violence. Through interview sessions with victims of domestic violence, a qualitative methodology was used to gain in-depth information. To avoid or reduce the financial, emotional and physical costs of domestic violence, it is necessary that counselors, health care provider systems, society and authorities prioritize prevention methods and intervention programs to improve the cultural level of the society and to encourage people toward developing a violence-free society.
Transformation of tetra- and trichloromethane to CO2 by anaerobic bacteria is a non-enzymic process

Degradation of tetrachloromethane was examined in the three strictly anaerobic bacteria, Acetobacterium woodii, Desulfobacterium autotrophicum and Methanobacterium thermoautotrophicum When incubated under anaerobic conditions in reduced buffer, suspensions of each organism degraded CCl4 by both reductive and substitutive mechanisms. The products formed included less-highly chlorinated methanes and CO2. Cell-free extracts of A. woodii degraded tetrachloromethane in a manner similar to that in whole cells but at a lower rate (63 vs. 110 μkat/kg of protein). When M. thermoautotrophicum or A. woodii was autoclaved, reductive dechlorination was partly abolished, whereas substitutive dechlorination was retained. Trichloromethane was oxidized to CO2 by both native and autoclaved cells of A. woodii. Halomethanes are thus degraded anaerobically by reductive, substitutive and oxidative mechanisms.
EFFICIENT EVALUATION OF POLYNOMIALS AND THEIR PARTIAL DERIVATIVES IN HOMOTOPY CONTINUATION METHODS

The aim of this paper is to study how efficiently we evaluate a system of multivariate polynomials and their partial derivatives in homotopy continuation methods. Our major tool is an extension of the Horner scheme, which is popular in evaluating a univariate polynomial, to a multivariate polynomial. But the extension is not unique, and there are many Horner factorizations of a given multivariate polynomial which require different numbers of multiplications. We present exact method for computing a minimum Horner factorization, which can process smaller size polynomials, as well as heuristic methods for a smaller number of multiplications, which can process larger size polynomials. Based on these Horner factorization methods, we then present methods to evaluate a system of multivariate polynomials and their partial derivatives. Numerical results are shown to verify the effectiveness and the efficiency of the proposed methods.
Phase recovery in NMF for audio source separation: An insightful benchmark

Nonnegative Matrix Factorization (NMF) is a powerful tool for decomposing mixtures of audio signals in the Time-Frequency (TF) domain. In applications such as source separation, the phase recovery for each extracted component is a major issue since it often leads to audible artifacts. In this paper, we present a methodology for evaluating various NMF-based source separation techniques involving phase reconstruction. For each model considered, a comparison between two approaches (blind separation without prior information and oracle separation with supervised model learning) is performed, in order to inquire about the room for improvement for the estimation methods. Experimental results show that the High Resolution NMF (HRNMF) model is particularly promising, because it is able to take phases and correlations over time into account with a great expressive power.
FVD: A High-Performance Virtual Machine Image Format for Cloud

Fast Virtual Disk (FVD) is a new virtual machine (VM) image format and the corresponding block device driver developed for QEMU. QEMU does I/O emulation for multiple hypervisors, including KVM, Xen-HVM, and VirtualBox. FVD is a holistic solution for both Cloud and non-Cloud environments. Its feature set includes flexible configurability, storage thin provisioning without a host file system, compact image, internal snapshot, encryption, copy-on-write, copy-on-read, and adaptive prefetching. The last two features enable instant VM creation and instant VM migration, even if the VM image is stored on direct-attached storage. As its name indicates, FVD is fast. Experiments show that the throughput of FVD is 249% higher than that of QCOW2 when using the Post-Mark benchmark to create files.
A new enriched exploration of modified algorithm for generating single dimensional fuzzy itemsets

Mining frequent itemsets from transactional database is a fundamental task for association rules. Apriori is an influential classic algorithm for mining frequent itemset. But Apriori is a very slow and inefficient algorithm for very large datasets. A modified algorithm for generating single dimensional fuzzy itemset mining find support count based on fuzzy t-norms namely intersection for finding frequent itemset to reduces the processing time. The proposed method modifies the above mentioned algorithm for fast and efficient performance on large datasets. It adopts a new count-based transaction reduction and support count method for generating frequent fuzzy item set. So, it can further reduce time when compared to Apriori and above said algorithm.
NAHTLOSE INTEGRATION VON VIRTUELLER REALITÄT IN GEWOHNTE ARBEITSPLÄTZE

Unter Verwendung von Virtueller Realität (VR) und der damit verbundenen neuartigen Technologie, entwickeln sich computergestützte Umgebungen eindeutig zu einer Hauptkomponente von zukünftigen Arbeitsplätzen. Dank einiger technologischen Entwicklungen innerhalb der letzten Jahre, stellte sich VR als eine praktisch einsetzbare Möglichkeit für viele Anwendungsbereiche heraus. In diesem Artikel wollen wir einige Ideen, technologische Konzepte und aktuelle Forschungsergebnisse vorstellen, die eine Nahtlose Integration von VR in eine gewohnte Arbeitsumgebung ermöglichen sollen, und somit zu einer sukzessiven Wandlung dieser Umgebungen zu high-tech Arbeitsplätzen beitragen. SEAMLESS INTEGRATION OF VIRTUAL REALITY IN
How Pre Service Elementary School Teachers' Mathematical Dispositions are Influenced by School Mathematics

The National Research Council (2001, 2009) includes a productive disposition toward mathematics as a key component to mathematical proficiency, and researchers have discovered that the mathematical dispositions of elementary school teachers have an impact on the mathematical dispositions of their students. Working from this relationship between disposition and mathematics achievement, this paper will examine how four preservice elementary school teachers formed their mathematical dispositions, focusing on the experiences that the preservice teachers believed were integral to forming those dispositions.
Uniformly minimum variance unbiased estimation for asynchronous event-based cameras

Asynchronous event-based cameras use time encoding to code the pixel intensity values. A time encoding of a random valued pixel is a representation of the intensity of this pixel as a random sequence of strictly increasing times. The goal of this paper is the estimation of the pixel mean value from asynchronous samples given by the integrate and fire time encoding. The optimal uniformly minimum variance unbiased estimator is calculated and its statistical performance is compared with a conventional frame-based estimator which exploits regular samples of the pixel intensity. Time encoding significantly reduces the mean number of bits needed to minimize the mean square error of the estimate. Hence, time encoding saves power compared to regular sampling.
Soft computing tool for restoring failures within wireless sensor networks

The proposed soft computing tool is developed as a suite of software programs capable of envisaging the evolution within wireless sensor networks (WSN) by accomplishing a series of processes. These processes are: modelling a real problem scenario in computing form, formulating the problem as an optimization problem, evaluating the outcomes and finally, presenting the outcomes in a statistical form. We have examined many possible failing scenarios of WSN operations through the proposed tool, which was capable to restore WSN in the presence of failures to continue normal operations. Simulated Annealing (SA) is utilized as a search method, which is embedded within the soft computing tool to explore the restoration space comprising of possible alternative topologies generated for each failing scenario, taking lifespan into consideration. The tested scenarios and their restorations can be hard-coded into a real WSN, thus preparing WSN to evolve through failures. The simulation results of a typical WSN illustrates the capability of the proposed computing tool to restore 79% of the lost days when no restoration scheme was applied.
Sensitivity of 24-h Forecast Dryline Position and Structure to Boundary Layer Parameterizations in Convection-Allowing WRF Model Simulations

AbstractRecent NOAA Hazardous Weather Testbed Spring Forecasting Experiments have emphasized the sensitivity of forecast sensible weather fields to how boundary layer processes are represented in the Weather Research and Forecasting (WRF) Model. Thus, since 2010, the Center for Analysis and Prediction of Storms has configured at least three members of their WRF-based Storm-Scale Ensemble Forecast (SSEF) system specifically for examination of sensitivities to parameterizations of turbulent mixing, including the Mellor–Yamada–Janjic (MYJ); quasi-normal scale elimination (QNSE); Asymmetrical Convective Model, version 2 (ACM2); Yonsei University (YSU); and Mellor–Yamada–Nakanishi–Niino (MYNN) schemes (hereafter PBL members). In postexperiment analyses, significant differences in forecast boundary layer structure and evolution have been observed, and for preconvective environments MYNN was found to have a superior depiction of temperature and moisture profiles. This study evaluates the 24-h forecast dryline po.
Study on the multi-factor degree set pair analysis fuzzy evaluation model based on entropy weight

The set pair analysis is a system analysis method to deal with uncertain problem. The concepts of the main same, supper same, assimilation degree and the new determining levels law are stipulated to make up for the defects of routine set pair analysis about the weights and determining levels law based on the theories of improved entropy weight and set pair analysis malleability. The method to determine system level and rank order projects by the main same and assimilation degree was put forward, and then, the multi-factors degree set pair analysis fuzzy evaluation model (EWMFSPAFM) has been suggested. A study under taken groundwater environment evaluation as demonstration, the water resources are evaluated by the EWMFSPAFM. And the results are compared with the results of the routine set pair analysis evaluation model and improved set pair analysis evaluation model. It is showed that the EWMFSPAFM is structure simple, calculation easy, result practical and reasonable, the method feasible and reliable.
Journal of Internet Banking and Commerce Antecedents and Effect of Commitment on the Impulse Buying by Internet

The impulse buying is an important phenomenon in consumer behavior and distribution in the context classic and virtual. The growth of services based on communication and information technology (CIT), especially the Internet has changed the way businesses and consumers interact. This article aims to provide a more complete understanding of the characteristics of the commercial website and the role played in the development of the pleasure of service and commitment to impulse buying. Analyses of data from 302 consumers Tunisian revealed that the attributes of the site (visual appearance, navigation, customized preview) are three important antecedents of the pleasure of serving consumers increasingly affecting their commitment to this site and therefore their buying impulse.
Multiplicity of Galactic Cepheids from long-baseline interferometry - II. The Companion of AX Circini revealed with VLTI/PIONIER

Aims. We aim at detecting and characterizing the main-sequence companion of the Cepheid AX Cir (Porb 18 yrs). The long-term objective is to estimate the mass of both components and the distance to the system. Methods. We used the PIONIER combiner at the VLT Interferometer to obtain the first interferometric measurements of the shortperiod Cepheid AX Cir and its orbiting component. Results. The companion is resolved by PIONIER at a projected separation = 29:2 0:2 mas and projection angle PA = 167:6 0:3 . We measured H-band flux ratios between the companion and the Cepheid of 0:90 0:10 % and 0:75 0:17 %, at pulsation phases for the Cepheid of = 0:24 and 0.48, respectively. The lower contrast at = 0:48 is due to the increased brightness of the Cepheid compared to = 0:24. This gives an average apparent magnitude mH(comp) = 9:06 0:24 mag. The limb-darkened angular diameter of the Cepheid at the two pulsation phases was measured to be LD = 0:839 0:023 mas and LD = 0:742 0:020 mas, at = 0:24 and 0.48, respectively. A lower limit on the total mass of the system was also derived based on our measured separation, and we found MT 9:7 0:6M .
Seeing faces in video by computers

The beginning of the 20 century was met with the invention that changed forever the way people saw the world. The invention, named the motion picture, was made using a technological breakthrough that enabled displaying pictures so fast (faster than 16 frames a second) that the human eyes perceived them as a single object—a movie. Now, in the beginning of the 21 century, it is fascinating to see that we are experiencing the arrival of another phenomenon related to video. This time it is due to the recent technological advances in computer and video hardware, which enable us to process video in real-time (faster than 16 frames a second), opening the way for new vision-based applications and technologies. Many of the newly arrived vision-based applications such as computer–human interfaces, multi-media, immersive and collaborative environments, video conferencing, video coding and annotation, video computer games, entertainment, public surveillance, information security, biometrics at a distance, to name a few, have a human face as the object of prime interest. This is why a major research effort has been recently put into face processing in video, which is an area of research dedicated to the extraction and manipulation of information about human faces in video sequences. The most important tasks of face processing in video are face detection, face tracking, and, of course, face recognition. The problem of recognizing faces from video, however, should not be considered as a mere extension of the problem of recognizing faces in photographs, since there are critical differences between the two, both in terms of the nature of processed data and approaches used. On one hand, because of real-time, bandwidth, and environmental constraints, video-processing has to deal with much lower resolution and image quality, when compared to photograph processing. Even assuming that the lighting conditions are perfect when taking a video snapshot, which is rarely true, faces in video may be located too far from the camera or at angle which makes recognition very difficult. On the other hand, video images can be easily acquired and they can capture a person over a period of time. This makes it possible to track people until they are in a position convenient for recognition and also to accumulate evidence over time. Besides, image-based face recognition traditionally belongs to the field of pattern recognition, and as such is mainly driven by mathematical principles. By contrast, video-based face recognition may also be approached by using neurobiological principles, the study of which may hopefully result in making the performance of computer vision systems closer to that of biological vision systems.
Processing of multimedia data using the P2G framework

In this demo, we present the P2G framework designed for processing distributed real-time multimedia data. P2G supports arbitrarily complex dependency graphs with cycles, branches and deadlines. P2G is implemented to scale transparently with available resources, i.e., a concept familiar from the cloud computing paradigm. Additionally, P2G supports heterogeneous computing resources, such as x86 and GPU processing cores. We have implemented an interchangeable P2G kernel language which is meant to expose fundamental concepts of the P2G programming model and ease the application development. Here, we demonstrate the P2G execution node using a MJPEG encoder as an example workload when dynamically adding and removing processing cores.