Miracle-dz/UniFAR-FTUs huggingface dataset:
Simple and artefact-free spectral modifications for enhancing the intelligibility of casual speech

In this paper, the problem of modifying casual speech to reach the intelligibility level of clear speech is addressed. Unlike other studies, in this work modifications on casual speech both consider intelligibility and speech quality. To achieve this, the authors focus on human-like modifications inspired by clear speech. An acoustic analysis performed on clear and casual speech reveals energy differences on specific frequency bands between the two speaking styles. Then, a simple method is used to boost these frequency regions on casual speech. The proposed method, called mix-filtering, uses a multi-band filtering scheme to isolate the information of these frequency bands and then, add this information to the original signal. Our method is compared in terms of intelligibility and quality with unmodified casual speech and with a highly intelligible spectral modification technique, namely the Spectral Shaping and Dynamic Range Compression (SSDRC). Two different objective measures that are highly correlated with subjective intelligibility scores are used for estimating the intelligibility, whereas for evaluating the quality, preference listening tests are performed. Results show that the mix-filtering technique increases the intelligibility of casual speech while maintains its quality. On the other hand, while SSDRC outperforms on intelligibility, it degrades significantly the quality of casual speech.
Social media text mining and network analysis for decision support in natural crisis management

A core issue in crisis management is to extract from the mass of incoming information what is important for situational awareness during mass emergencies. Based on a case study we develop a prototypical application, TweetComp1, which is integrated into the decision-support component of a Tsunami early warning system and demonstrates the applicability of our approach. This paper describes four novel approaches using focused twitter crawling, trustworthiness analysis, geo-parsing, and multilingual tweet classification in the context of how they could be used for monitoring crises. The validity of our state-of-the art text mining and network analysis technologies will be verified in different experiments based on a human annotated gold standard corpus.
Awareness Versus Un-Clinging: Which Matters in Mindfulness?

Abstract Awareness and un-clinging have been emphasised in Buddhist discourse as important facets of mindfulness practice for over 2500 years. However, there is a lack of rigorous research examining the relationship between these two elements and their importance to well-being. To evaluate these abstract constructs, the current study adopted multiple assessment modalities; namely, a self-report scale, experience sampling (assessing ‘momentary mindfulness’), and semi-structured interviews (assessing ‘rater-rated mindfulness’). A total of 415 participants completed the questionnaire survey. Among them, 71 participants further took part in the experience sampling procedure and semi-structured interviews. The findings reveal that self-reported awareness was mildly correlated with momentary mindfulness (r = .35) but was not significantly correlated with rater-rated mindfulness. Self-reported un-clinging was moderately correlated with rater-rated mindfulness (r = .53) but was not significantly correlated with momentary mindfulness. Un-clinging, but not awareness, can distinguish meditators from non-meditators. Lastly, based on the Buddha’s mindfulness discourse, a path analysis model illustrates that the effects of un-clinging and awareness on stress reduction are mediated by emotional intelligence and non-attachment. Practical implications and future research designs are discussed.
The use of genetic algorithms for the development of sensorimotor control systems

Provides a high-level review of current and recent work in the use of genetic algorithm-based techniques to develop sensorimotor control systems for autonomous agents. It focuses on network-based controllers and genetic encoding issues associated with them. The paper closes with a discussion of the possibility of using artificial evolutionary techniques to help tackle more specifically scientific questions about natural sensorimotor systems.
A Single cis Element Maintains Repression of the Key Developmental Regulator Gata2

In development, lineage-restricted transcription factors simultaneously promote differentiation while repressing alternative fates. Molecular dissection of this process has been challenging as transcription factor loci are regulated by many trans-acting factors functioning through dispersed cis elements. It is not understood whether these elements function collectively to confer transcriptional regulation, or individually to control specific aspects of activation or repression, such as initiation versus maintenance. Here, we have analyzed cis element regulation of the critical hematopoietic factor Gata2, which is expressed in early precursors and repressed as GATA-1 levels rise during terminal differentiation. We engineered mice lacking a single cis element −1.8 kb upstream of the Gata2 transcriptional start site. Although Gata2 is normally repressed in late-stage erythroblasts, the −1.8 kb mutation unexpectedly resulted in reactivated Gata2 transcription, blocked differentiation, and an aberrant lineage-specific gene expression pattern. Our findings demonstrate that the −1.8 kb site selectively maintains repression, confers a specific histone modification pattern and expels RNA Polymerase II from the locus. These studies reveal how an individual cis element establishes a normal developmental program via regulating specific steps in the mechanism by which a critical transcription factor is repressed.
Design and Evaluation of an Anomaly Detection Method Based on Cross-Feature Analysis using Rough Sets for MANETs

With the proliferation of wireless devices, mobile ad-hoc networking (MANET) has become a very exciting and important technology. However, MANET is more vulnerable than wired networking. Existing security mechanisms designed for wired networks have to be redesigned in this new environment. In this paper, we discuss the problem of anomaly detection in MANET. The focus of our research is on techniques for automatically constructing anomaly detection models that are capable of detecting new or unseen attacks. We propose a new anomaly detection method for MANET. The proposed method performs cross-feature analysis on the basis of rough sets to capture the inter-feature correlation patterns in normal traffic. The performance of the proposed method is evaluated through a simulation. The results show that proposed method effectively detects anomalies and identify attack types using the intrusion detection method.
A coupled level set – boundary integral method for moving boundary simulations

A numerical method for moving boundary problems based upon level set and boundary integral formulations is presented. The interface velocity is obtained from the boundary integral solution using a Galerkin technique for post-processing function gradients on the interface. We introduce a new level set technique for propagating free boundary values in time, and couple this to a narrow band level set method. Together, they allow us to both update the function values and the location of the interface. The methods are discussed in the context of the well-studied two-dimensional nonlinear potential flow model of breaking waves over a sloping beach. The numerical results show wave breaking and rollup, and the algorithm is verified by means of convergence studies and comparisons with previous techniques.
Self-Adjusting Networks to Minimize Expected Path Length

Given a network infrastructure (e.g., data-center or on-chip-network) and a distribution on the source-destination requests, the expected path (route) length is an important measure for the performance, efficiency and power consumption of the network. In this work we initiate a study on self-adjusting networks: networks that use local-distributed mechanisms to adjust the position of the nodes (e.g., virtual machines) in the network to best fit the route requests distribution. Finding the optimal placement of nodes is defined as the minimum expected path length (MEPL) problem. This is a generalization of the minimum linear arrangement (MLA) problem where the network infrastructure is a line and the computation is done centrally. In contrast to previous work, we study the distributed version and give efficient and simple approximation algorithms for interesting and practically relevant special cases of the problem. In particular, we consider grid networks in which the distribution of requests is a symmetric product distribution. In this setting, we show that a simple greedy policy of position switching between neighboring nodes to locally minimize an objective function, achieves good approximation ratios. We are able to prove this result using the useful notions of expected rank of the distribution and the expected distance to the center of the graph.
Introduction to a Special Issue on Simulation Studies as a Means of Informing Psychoeducational Testing and Assessment

This introduction provides a brief overview of simulation studies and outlines the organization of this special issue. Simulation studies provide a valuable, albeit underutilized, means of informing psychoeducational testing and assessment. The goal of this special issue is to equip applied researchers and clinicians with knowledge and skills needed to conduct simulation studies. It is envisioned that increased adoption of this innovative practice will ultimately improve the quality of psychoeducational tests, testing and assessment practices, and clinical decision making.
Enhancing, Inhibiting, and Maintaining Voice: An Examination of Student Affairs Graduate Students' Self-Authorship Journeys

Abstract:In this longitudinal qualitative study I explored the development of self-authorship among 21 student affairs master's candidates at 2 institutions. The findings suggest that growth, regression, and stasis in newcomers' developmental capacities for self-authorship occurred as they matriculated, and that these developmental trajectories reflected the amount of support participants received after experiencing dissonance during their graduate training. Notably, those who maintained or decreased their developmental capacity for self-authorship during graduate school did not feel adequately supported after having experiences that challenged the validity of their voices. Ultimately, these varied developmental trajectories influenced individuals' degrees of commitment to long-term careers in student affairs.
EXACTLY SOLVABLE POINTS IN THE MODULI SPACE OF HETEROTIC N=2 STRINGS

We investigate the subset of exactly solvable (0, 4) worldsheet supersymmetric string vacua contained in a recent class of Gepner-like (0, 2) superconformal models. The identification of these models with certain points of enhanced gauge symmetry on K3×T2 can be achieved completely. Furthermore, we extend the construction of in general (0, 2) supersymmetric exactly solvable models to the case where also a nontrivial part of the vector bundle is embedded into the hidden E8 gauge group. For some examples we explicitly calculate the enhanced gauge symmetries and show that they open up the way to interesting branches of the N=2 moduli space. For some of these models candidates of type-II dual descriptions exist.
Simulation Studies of the Electrocardiogram: I. The Normal Heart

A digital computer model is presented for the simulation of the body surface electrocardiogram (ECG) during ventricular activation and recovery. The ventricles of the heart are represented in detail by a three-dimensional array of approximately 4000 points which is subdivided into 23 regions. Excitation sequence and cellular action potential data taken from the literature are used to determine the spatial distribution of intracellular potentials at each instant of time during a simulated cardiac cycle. The moment of the single dipole representing each region is determined by summing the spatial gradient of the intracellular potential distribution throughout the region. The resulting set of 23 dipoles is then used to calculate the potentials on the surface of a bounded homogeneous volume conductor with the shape of an adult male torso. Simulated isopotential surface maps during both activation and recovery are in good agreement with data for humans reported in the literature.
Evaluation of FPGA routing architectures under process variation

Uncertainty in performance of FPGAs is becoming an important issue due to increased process variations in nanometer regime. Therefore, it is vital to decrease the impact of variability in these devices. FPGA routing architecture enhancement can be an effective way, because as feature size scales down, routing delay dominates logic circuit delay. In this paper, unidirectional and bidirectional routing architectures are compared. We show that bidirectional architecture is better in terms of robustness against variation when short wire segments are considered. However as wire length increases, unidirectional routing architecture would be the preferred option. Experimental results show that in unidirectional routing architecture towards bidirectional for wire length of 8, it has obtained 36% and 20% improvement in standard deviation and 3¼+Ã of circuit delay, respectively.
Force propagation models in laparoscopic tools and trainers

Most of the tools that are used in performing manipulation tasks in laparoscopic surgery are graspers and needle drivers. Although the operation of such basic tools is rather simple, their combination with remote access to the surgical site and an indirect field of view makes the usage of such mechanisms challenging. This means that surgeons have to undergo a series of training sessions in order to gain proper hand/eye coordination. In addition, due to the structure of these mechanisms, the sense of touch has been reduced to a minimum. One challenge of research and development has been to design a force-reflective grasper that can reflect the sense of touch back into the handle. In addition, considerable efforts are being focused on developing a virtual laparoscopic trainer where the sense of touch in manipulating virtual tissues and organs can be reflected back to the hand of the surgeon through the proper design of haptic interfaces. This paper presents force propagation models which can be used in the modelling, design and interpretation of the force sensing system and reflecting devices. The proposed models agree with the experimental observation previously published in the literature for describing the relationships between the magnitude of the grasping force and the applied force at the handle.
Makespan and Energy Robust Stochastic Static Resource Allocation of a Bag-of-Tasks to a Heterogeneous Computing System

Today’s data centers face the issue of balancing electricity use and completion times of their workloads. Rising electricity costs are forcing data center operators to either operate within an electricity budget or to reduce electricity use as much as possible while still maintaining service agreements. Energy-aware resource allocation is one technique a system administrator can employ to address both problems: optimizing the workload completion time (makespan) when given an energy budget, or to minimize energy consumption subject to service guarantees (such as adhering to deadlines). In this paper, we study the problem of energy-aware static resource allocation in an environment where a collection of independent (non-communicating) tasks (“bag-of-tasks”) is assigned to a heterogeneous computing system. Computing systems often operate in environments where task execution times vary (e.g., due to cache misses or data dependent execution times). We model these execution times stochastically, using probability density functions. We want our resource allocations to be robust against these variations, where we define energy-robustness as the probability that the energy budget is not violated, and makespan-robustness as the probability a makespan deadline is not violated. We develop and analyze several heuristics for energy-aware resource allocation for both energy-constrained and deadline-constrained problems.
Security Architecture for Vehicular Communication

Despite recent progress for vehicular communication in research, development, field tests, and standardization, security is still in an early phase though it represents a crucial part of the vehicular communication system. So far, no vehicular security architecture has been proposed which integrates existing individual solutions for vehicle registration, data integrity, authentication, and so on. By description of different architectural perspectives, we identify the stakeholders and their responsibilities. Then, we focus on the functional layer view and highlight the concepts which jointly secure the vehicular communication. Based on these concepts, we present an implementation approach which introduces the security concepts into the protocol stack of a vehicular communication system. The proposed security architecture follows a clean and modular design. It is the basis for our prototype implementation which will serve as a proof-of-concept. We will also submit this architecture to the ongoing standardization process of the Car2Car Communication Consortium (C2C-CC).
Text-independent speaker recognition using probabilistic SVM with GMM adjustment

There are two most popular techniques in pattern recognition, discriminative classifiers and generative model classifiers. Combining them together could improve the performance of the recognition system. We present a novel method for text-independent speaker recognition. This system uses the output of the Gaussian mixture model to adjust the probabilistic output of the support vector machine. The new probabilistic SVM/GMM model based speaker recognition system is tested on the NIST 2003 speaker recognition evaluation database. Results on text-independent speaker identification and verification are provided to demonstrate the effectiveness of such systems.
Assistive Human-Machine Interfaces via Artificial Neural Netwoks

This paper reports the study and results of modeling and online compensating of movement disorder stemming from multiple sclerosis (MS) via artificial neural networks. We trained and tested a cascade-correlation neural network with Kalman filtering on data collected from 11 subjects with MS. The test subjects use headcontrolled mouse emulators to move a cursor to a series of random targets on screen. Simulated real-time testing of the trained neural networks shows that the networks successfully make the cursor trajectories of all the 11 subjects less chaotic, and hence more controllable. The neural networks also reduce the time needed to reach the targets by an average of 31.8%. The neural network approach can be easily applied to other human-machine interfaces such as computer mice and joysticks, or powered wheelchairs. This technique is also applicable to movement disorders resulting from certain geriatric diseases such as Parkinson’s disease and essential tremor.
A Case Study on the Facilitation of Positive Behavior Interventions and Supports in a Public Elementary School

A Case Study on the Facilitation of Positive Behavior Interventions and Supports in a Public Elementary School John Todd Shumway Educational Inquiry, Measurement, and Evaluation, BYU Doctor of Philosophy Disruptive behaviors in elementary schools are a serious concern for teachers. With mounting pressure from school district administrations, state and federal government agencies, and the communities in which these schools reside, teachers often struggle to determine the best path to achieve consistent student engagement. When inappropriate behaviors are not managed effectively, academics suffer. Positive behavior interventions and supports (PBIS) have been shown to be effective in reducing such behaviors. Professional Learning Communities (PLC) have also become very common in schools as teachers are organized into teams to collaborate and plan learning opportunities and methods for the instruction and assessment of students. The present study examined the effects of PBIS implementation through the PLC on the teaching staff in seven elementary school classrooms. This is a case study in which selected teachers were observed and interviewed to determine their level of and concerns regarding implementation and subsequent adoption level. Results indicate that the teachers all have unique experiences with PBIS and related interventions that either reduce their use or support their belief that it is an effective system. Their PLC collaboration is also discussed as it was proposed to be the medium and data catalyst for implementation. Limitations and implications of this study for researchers and practitioners are discussed.
Study of the TmoS/TmoT two‐component system: towards the functional characterization of the family of TodS/TodT like systems

The two‐component system TmoS/TmoT controls the expression of the toluene‐4‐monooxygenase pathway in Pseudomonas mendocina RK1 via modulation of PtmoX activity. The TmoS/TmoT system belongs to the family of TodS/TodT like proteins. The sensor kinase TmoS is a 108 kDa protein composed of seven different domains. Using isothermal titration calorimetry we show that purified TmoS binds a wide range of aromatic compounds with high affinities. Tightest ligand binding was observed for toluene (KD = 150 nM), which corresponds to the highest affinity measured between an effector and a sensor kinase. Other compounds with affinities in the nanomolar range include benzene, the 3 xylene isomers, styrene, nitrobenzene or p‐chlorotoluene. We demonstrate that only part of the ligands that bind to TmoS increase protein autophosphorylation in vitro and consequently pathway expression in vivo. These compounds are referred to as agonists. Other TmoS ligands, termed antagonists, failed to increase TmoS autophosphorylation, which resulted in their incapacity to stimulate gene expression in vivo. We also show that TmoS saturated with different agonists differs in their autokinase activities. The effector screening of gene expression showed that promoter activity of PtmoX and PtodX (controlled by the TodS/TodT system) is mediated by the same set of 22 compounds. The common structural feature of these compounds is the presence of a single aromatic ring. Among these ligands, toluene was the most potent inducer of both promoter activities. Information on the TmoS/TmoT and TodS/TodT system combined with a sequence analysis of family members permits to identify distinct features that define this protein family.
Using Motives and Artificial Emotion for Long-Term Activity of an Autonomous Robot

To operate over a long period of time in the real world, autonomous mobile robots must have the capability of recharging themselves whenever necessary. In addition to be able to nd and dock into a charging station, robots must be able to decide when and for how long to recharge. This decision is in uenced by the energetic capacity of their batteries and the contingencies of their environments. To deal with this temporality issue and based on research works in psychology, this paper investigates the use of motives and arti cial emotions to regulate the recharging need of autonomous robots. A bipolar model of arti cial emotion is presented, designed to be generic and not speci cally con gured for a particular task. The paper also describes the use of the approach in two speci c applications, the AAAI Mobile Robot Challenge and experiments involving a group of robots share one charging station in an enclosed area.