Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the Authoring Complexity of Interactive Narratives for Augmented Reality Applications

This paper evaluates the use of Behavior Trees (BT) for authoring compelling narrative experiences with free-form user interaction. We systematically study extensions to traditionally BT representations, which decouple the monitoring of user input, the narrative, and how the user may inﬂu-ence the story outcome – referred to as Interactive Behavior Trees (IBT’s). By quantitatively evaluating the authoring complexity of BT formalisms with traditional story graph representations, we show that IBT’s better scale with the number of story arcs, and the degree and granularity of user input. Our theoretical estimate of authoring complexity is corroborated with a qualitative user study, which conﬁrms that subjects take lesser time with reduced eﬀort to author narratives using IBT’s. The subjective diﬃculty of IBT’s is also lower than traditional story graphs.
Secure Position-Based Routing for VANETs

Vehicular communication (VC) systems have the potential to improve road safety and driving comfort. Nevertheless, securing the operation is a prerequisite for deployment. So far, the security of VC applications has mostly drawn the attention of research efforts, while comprehensive solutions to protect the network operation have not been developed. In this paper, we address this problem: we provide a scheme that secures geographic position-based routing, which has been widely accepted as the appropriate one for VC. Moreover, we focus on the scheme currently chosen and evaluated in the Car2Car Communication Consortium (C2C-CC). We integrate security mechanisms to protect the position-based routing functionality and services (beaconing, multi-hop forwarding, and geo-location discovery), and enhance the network robustness. We propose defense mechanisms, relying both on cryptographic primitives and plausibility checks mitigating false position injection. Our implementation and initial measurements show that the security overhead is low and the proposed scheme deployable.
Symptoms Experienced by Jordanian Men and Women After Coronary Artery Bypass Graft Surgery

Background:Patients who undergo coronary artery bypass graft (CABG) surgery experience a wide spectrum of physical and psychological symptoms after surgery. Studies have shown that symptoms usually decline over time; however, some can persist up to months after discharge. Objectives:This study aims to assess symptoms experienced by patients after CABG surgery and any associations with demographic variables. Methods:A descriptive, cross-sectional design was used. A convenience sample of 100 Jordanian post–CABG surgery patients was selected from 5 hospitals in Jordan. Patients were surveyed using the Cardiac Symptom Survey. To examine the associations between the symptoms experienced and selected demographic variables, &khgr;2 analyses were used. Results:Chest incisional pain (65%) was the most frequently perceived symptom by the participants. Leg swelling (60%) was also reported by a nearly equivalent number of respondents. Symptoms like fluttering (15%), angina (8%), and depression (3%) were reported by a handful of participants. Three symptoms (poor appetite, sleeping problem, and fatigue) had significant associations with demographic variables. Discussion:The identification of frequently perceived symptoms among post-CABG patients enables health care providers to focus their assessments in identifying and alleviating them. The demographic associations identified facilitate nurses to forecast certain specific symptoms in targeted populations, like women are more prone to experience poor appetite and sleeping difficulties and strengthen these groups with strategies to prevent themselves from these distressing symptoms.
Jenaer Schriften zur Wirtschaftswissenschaft Determinants influencing the choice of a cooperation partner

This paper provides empirical tests of hypotheses of cooperative behavior provided by evolutionary approaches in the resource-based view of the firm. The influences of ”technological proximity”, individual incentives to cooperate and managerial tools to the choice of research partner are analyzed. Using German patent data we can show the positive influence of those three determinants. The results of this paper confirm theories dealing with the path-dependency of research activities. JEL classification: C30; L14; O32
A Principled Distributional Approach to Trajectory Similarity Measurement and its Application to Anomaly Detection

This paper aims to solve two enduring challenges in existing trajectory similarity measures: computational inefficiency and the absence of the ‘uniqueness’ property that should be guaranteed in a distance function: dist(X, Y ) = 0 if and only if X = Y , where X and Y are two trajectories. In this work, we present a novel approach utilizing a distributional kernel for trajectory representation and similarity measurement, based on the kernel mean embedding framework. It is the very first time a distributional kernel is used for trajectory representation and similarity measurement. Our method does not rely on point-to-point distances which are used in most existing distances for trajectories. Unlike prevalent learning and deep learning approaches, our method requires no learning. We show the generality of this new approach in anomalous trajectory and sub-trajectory detection. We identify that the distributional kernel has (i) a data-dependent property and the ‘uniqueness’ property which are the key factors that lead to its superior task-specific performance, and (ii) runtime orders of magnitude faster than existing distance measures.
On the inner and outer bounds for 2-receiver discrete memoryless broadcast channels

We study the best known general inner bound (K. Marton, January, 2003) and outer bound (C. Nair et al., January, 2007) for the capacity region of the two user discrete memory less channel.We prove that a seemingly stronger outer bound is identical to a weaker form of the outer bound that was also presented in (C. Nair et al., January, 2007). We are able to further express the best outer bound in a form that is computable, i.e. there are bounds on the cardinalities of the auxiliary random variables. The inner and outer bounds coincide for all channels for which the capacity region is known and it is not known whether the regions described by these bounds are same or different. We present a channel, where assuming a certain conjecture backed by simulations and partial theoretical results, one can show that the bounds are different.
Three lower bounds on secrecy capacity for indoor visible light communications

Recently, the physical-layer security, which exploits the channel characteristics in order to hide information from unauthorized receivers and does not reliance on the upper-layer encryption, has been proposed as a promising complement to the traditional security schemes. In this paper, the lower bounds on secrecy capacity for indoor visible light communications (VLC) are investigated. The noise is assumed to be Gaussian, which is independent of the input signal. The non-negativity and the average optical intensity constraint are taken into consideration. Based on the system model, three lower bounds on secrecy capacity for VLC are derived, respectively. Numerical results show that method 2 is better than the other two methods at high signal-to-noise ratio (SNR) regime, while method 3 is the best method at low SNR regime.
The parietal cortex and the representation of time, space, number and other magnitudes

The development of sub-disciplines within cognitive neuroscience follows common sense categories such as language, audition, action, memory, emotion and perception among others. There are also well-established research programmes into temporal perception, spatial perception and mathematical cognition that also reflect the subjective impression of how experience is constructed. There is of course no reason why the brain should respect these common sense, text book divisions and, here, we discuss the contention that generalized magnitude processing is a more accurate conceptual description of how the brain deals with information about time, space, number and other dimensions. The roots of the case for linking magnitudes are based on the use to which magnitude information is put (action), the way in which we learn about magnitudes (ontogeny), shared properties and locations of magnitude processing neurons, the effects of brain lesions and behavioural interference studies. Here, we assess this idea in the context of a theory of magnitude, which proposed common processing mechanisms of time, space, number and other dimensions.
Next cache line and set prediction

Accurate instruction fetch and branch prediction is increasingly important on today's wide-issue architectures. Fetch prediction is the process of determining the next instruction to request from the memory subsystem. Branch prediction is the process of predicting the likely out-come of branch instructions. Several researchers have proposed very effective fetch and branch prediction mechanisms including branch target buffers (BTB) that store the target addresses of taken branches. An alternative approach fetches the instruction following a branch by using an index into the cache instead of a branch target address. We call such an index a next cache line and set (NLS) predictor. A NLS predictor is a pointer into the instruction cache, indicating the target instruction of a branch. In this paper we examine the use of NLS predictors for efficient and accurate fetch and branch prediction. Previous studies associated each NLS predictor with a cache line and provided only one-bit conditional branch predictors. Our study examines the use of NLS predictors with highly accurate two-level correlated conditional branch architectures. We examine the performance of decoupling the NLS predictors from the cache line and storing them in a separate tag-less memory buffer. Our results show that the decoupled architecture performs better than associating the NLS predictors with the cache line, that the NLS architecture benefits from reduced cache miss rates, and it is particularly effective for programs containing many branches. We also provide an in-depth comparison between the NLS and BTB architectures, showing that the NLS architecture is a competitive alternative to the BTB design.
Improving recognition accuracy for facial expressions using scattering wavelet

One of the most evident and meaningful feedback about people’s emotions is through facial expressions. Facial expression recognition is helpful in social networks, marketing, and intelligent education systems. The use of Deep Learning based methods in facial expression identification is widespread, but challenges such as computational complexity and low recognition rate plague these methods. Scatter Wavelet is a type of Deep Learning that extracts features from Gabor filters in a structure similar to convolutional neural networks. This paper presents a new facial expression recognition method based on wavelet scattering that identifies six states: anger, disgust, fear, happiness, sadness, and surprise. The proposed method is simulated using the JAFFE and CK+ databases. The recognition rate of the proposed method is 99.7%, which indicates the superiority of the proposed method in recognizing facial expressions.
Set Expansion using Sibling Relations between Semantic Categories

Most set expansion algorithms assume to acquire new instances of different semantic categories independently even when we have seed instances of multiple semantic categories. However, in the setting of set expansion with multiple semantic categories, we might leverage other types of prior knowledge about semantic categories. In this paper, we present a method of set expansion when ontological information related to target semantic categories is available. More specifically, the proposed method makes use of sibling relations between semantic categories as an additional type of prior knowledge. We demonstrate the effectiveness of sibling relations in set expansion on the dataset in which instances and sibling relations are extracted from Wikipedia in a semi-automatic manner.
Theoretical and methodological foundations of sustainable development of Geosystems

The theoretical and methodological foundations of sustainable development of Geosystems were further evolved. It was grounded the new scientific direction “constructive Hydroecology” - the science that studies the Hydrosphere from the standpoint of natural and technogenic safety based on geosystematical approach. A structural separation for constructive Hydroecology based on objective, subjective, and application characteristics was set. The main object of study of the new scientific field is the hydroecological environment under which the part of Hydrosphere should be understood as a part of the multicomponent dynamic system that is influenced by engineering and economical human activities and, in turn, determines to some extent this activity.
Stochastic Characteristics and Simulation of the Random Waypoint Mobility Model

Simulation results for Mobile Ad-Hoc Networks (MANETs) are fundamentally governed by the underlying Mobility Model. Thus it is imperative to find whether events functionally dependent on the mobility model 'converge' to well defined functions or constants. This shall ensure the long-run consistency among simulation performed by disparate parties. This paper reviews a work on the discrete Random Waypoint Mobility Model (RWMM), addressing its long run stochastic stability. It is proved that each model in the targeted discrete class of the RWMM satisfies Birkhoff's pointwise ergodic theorem [13], and hence time averaged functions on the mobility model surely converge. We also simulate the most common and general version of the RWMM to give insight into its working.
The Influence of Human Capital, Relational Capital, Organizational Capital, and the Information Technology Utilization on the ASN Performance in the Regional Social Services of the North Sulawesi Province Government

The Social Service is the technical implementing element of Regional Government in the social sector which is tasked with carrying out regional autonomy authority in the field of social welfare services so that good performance is very much needed. Data collection in this research involved all ASNs at the Regional Social Service of North Sulawesi Province as respondents, namely 144 people. This research aims to analyze the influence of Human Capital, Relational Capital, Organizational Capital, and the Use of Information Technology on the performance of ASN of the Regional Social Service of North Sulawesi Province. The results of this research are (1) Human Capital has a positive and significant effect on ASN Performance at the North Sulawesi Province Regional Social Service (2) Relational Capital has a positive and significant effect on ASN Performance at the North Sulawesi Province Regional Social Service (3) Organizational Capital has a positive and significant effect significant impact on the performance of ASN in the Regional Social Service of North Sulawesi Province (4) Utilization of IT has a positive and significant effect on ASN Performance in the Regional Social Service of North Sulawesi Province (5) Human Capital, Relational Capital, Organizational Capital, and Utilization of IT together have an influence significant impact on the performance of ASN at the Regional Social Service of North Sulawesi Province.
Comparison of Snow Indexes in Estimating Snow Cover Fraction in a Mountainous Area in Northwestern China

The normalized difference snow index (NDSI), a key part of the snow-mapping algorithm for extracting snow information from remotely sensed imageries, has been frequently employed in acquiring snow cover extent in the past decades. A linear regression analysis has been frequently used in estimating snow cover fraction (SCF) on a subpixel basis by developing a statistical relationship between NDSI and SCF. In this letter, a comparison of NDSI, ratio snow index (RSI), and difference snow index (DSI) in estimating SCF is carried out in mountainous area of northwestern China. Three kinds of fitting methods, i.e., linear fitting, logarithmic curve fitting, and exponential curve fitting, are employed in this comparison for the purpose of finding out a best statistical fitting relationship between SCF and snow index. The results show that RSI and DSI are both good substitutes for NDSI in SCF estimation due to high R-squares, up to 0.83, of fitted lines between snow indexes and SCF, respectively. Furthermore, exponential fitting is considered to be of the highest robustness in the three fitting methods of interest for all the snow indexes studied.
Opus: University of Bath Online Publication Store Eit-based Fabric Pressure Sensing

This version is made available in accordance with publisher policies. Please cite only the published version using the reference above. This paper presents EIT-based fabric sensors that aim to provide a pressure mapping using the current carrying and voltage sensing electrodes attached to the boundary of the fabric patch. Pressure-induced shape change over the sensor area makes a change in the conductivity distribution which can be conveyed to the change of boundary current-voltage data. This boundary data is obtained through electrode measurements in EIT system. The corresponding inverse problem is to reconstruct the pressure and deformation map from the relationship between the applied current and the measured voltage on the fabric boundary. Taking advantage of EIT in providing dynamical images of conductivity changes due to pressure induced shape change, the pressure map can be estimated. In this paper, the EIT-based fabric sensor was presented for circular and rectangular sensor geometry. A stretch sensitive fabric was used in circular sensor with 16 electrodes and a pressure sensitive fabric was used in a rectangular sensor with 32 electrodes. A preliminary human test was carried out with the rectangular sensor for foot pressure mapping showing promising results.
Weak Converse Lyapunov Theorems and Control-Lyapunov Functions

Given a weakly uniformly globally asymptotically stable closed (not necessarily compact) set ${\cal A}$ for a differential inclusion that is defined on $\mathbb{R}^n$, is locally Lipschitz on $\mathbb{R}^n \backslash {\cal A}$, and satisfies other basic conditions, we construct a weak Lyapunov function that is locally Lipschitz on $\mathbb{R}^n$. Using this result, we show that uniform global asymptotic controllability to a closed (not necessarily compact) set for a locally Lipschitz nonlinear control system implies the existence of a locally Lipschitz control-Lyapunov function, and from this control-Lyapunov function we construct a feedback that is robust to measurement noise.
Mixed-metal tellurites: synthesis, structure, and characterization of Na1.4Nb3Te4.9O18 and NaNb3Te4O16.

Two new mixed-metal tellurites, Na1.4Nb3Te4. 9O18 and NaNb3Te4O16, have been synthesized by standard solid-state techniques using Na2CO3, Nb2O5, and TeO2 as reagents. The structures of Na1.4Nb3Te4. 9O18 and NaNb3Te4O16 were determined by single-crystal X-ray diffraction. Both of the materials exhibit three-dimensional structures composed of NbO6 octahedra, TeO4, and TeO3 polyhedra. The Nb5+ and Te4+ cations are in asymmetric coordination environments attributable to second-order Jahn-Teller (SOJT) effects. The Nb5+ cations undergo an intraoctahedral distortion toward a corner (local C4 direction), whereas the Te4+ cations are in distorted environments owing to their nonbonded electron pair. Infrared and Raman spectroscopy, UV-vis diffuse reflectance spectroscopy, thermogravimetric analysis, and dielectric measurements were also performed on the reported materials. Crystal data: Na1.4Nb3Te4. 9O18, monoclinic, space group C2/m (No. 12), with a = 32.377(5) A, b = 7.4541(11) A, c = 6.5649(9) A, beta = 95.636(5) degrees, V = 1576.7(4) A3, and Z = 4; NaNb3Te4O16, monoclinic, space group P2(1)/m (No. 11), with a = 6.6126(13) A, b = 7.4738(15) A, c = 14.034(3) A, beta = 102.98(3) degrees, V = 675.9(3) A3, and Z = 2.
Improved expected patch Log likelihood scheme for image denoising

To solve the inherent non-adaptive problem existed in the expected patch Log likelihood (EPLL), an updating process of the Gaussian mixture model introduced into the EPLL and an improved EPLL scheme via adaptive Gaussian mixture prior is proposed in this paper. Experimental results show that the proposed method outperforms the existing image denoising algorithms.
Efficient computation of commutative anisotropic convolution on the 2-sphere

Recently, the commutative anisotropic convolution has been defined for signals defined on the 2-sphere. Here, we present exact and efficient methods for computation of commutative convolution of two signals defined on the sphere. For fast computation of commutative convolution, we first review the use of existing efficient techniques developed to evaluate SO(3) convolution. By employing the factoring of a rotation into two rotations, followed by the separation of variables, we propose a fast algorithm for the efficient computation of commutative convolution. In terms of computational complexity, our proposed algorithm provides a saving of O(N) over the existing algorithms, where the convolution output is evaluated on O(N2) samples on the 2-sphere. Through numerical experiments, we also verify the improvement in the computational complexity.
Perioperative complications of conduit urinary diversion with concomitant cystectomy for benign indications: A population‐based analysis

Beyond single‐institution case series, limited data are available to describe risks of performing a concurrent cystectomy at the time of urinary diversion for benign end‐stage lower urinary tract dysfunction. Using a population‐representative sample, this study aimed to analyze factors associated with perioperative complications in patients undergoing urinary diversion with or without cystectomy.
Meta-analysis of cancer gene expression signatures reveals new cancer genes, SAGE tags and tumor associated regions of co-regulation

Cancer is among the major causes of human death and its mechanism(s) are not fully understood. We applied a novel meta-analysis approach to multiple sets of merged serial analysis of gene expression and microarray cancer data in order to analyze transcriptome alterations in human cancer. Our methodology, which we denote ‘COgnate Gene Expression patterNing in tumours’ (COGENT), unmasked numerous genes that were differentially expressed in multiple cancers. COGENT detected well-known tumor-associated (TA) genes such as TP53, EGFR and VEGF, as well as many multi-cancer, but not-yet-tumor-associated genes. In addition, we identified 81 co-regulated regions on the human genome (RIDGEs) by using expression data from all cancers. Some RIDGEs (28%) consist of paralog genes while another subset (30%) are specifically dysregulated in tumors but not in normal tissues. Furthermore, a significant number of RIDGEs are associated with GC-rich regions on the genome. All assembled data is freely available online (www.oncoreveal.org) as a tool implementing COGENT analysis of multi-cancer genes and RIDGEs. These findings engender a deeper understanding of cancer biology by demonstrating the existence of a pool of under-studied multi-cancer genes and by highlighting the cancer-specificity of some TA-RIDGEs.