Miracle-dz/UniFAR-FTUs huggingface dataset:
ON WORD BOUNDARY DETECTION IN DIGIT-BASED SPEAKER VERIFICATION

In an automatic speaker verification (ASV) system with prompted passwords, we use vocabulary-dependent hidden Markov models and rely on the ability to explicitly locate the corresponding words and their boundaries in the speech signal. In an experiment on 41 speakers in a Swedish telephone speech database, we compare the use of utterance segmentation produced by automatic and manual methods, and conclude that not much is lost in ASV performance with the automatic method compared to the manual.
A hybrid Niching-based evolutionary PSO for numerical optimization problems

Particle swarm optimization (PSO) is a population-based optimization algorithm which has great potential because of its simplicity and malleability. PSO is a typical global searching heuristic, but there is still an insufficiency in PSO regarding solution exploitation and diversity. In view of this, inspired by the pseudo bacterial genetic algorithm (PBGA), we enhance the variety of solution exploitation by incorporating the PBGA process-chromosome mutation. In addition to this, a modified niching method is utilized to preserve the solution diversity, and to avoid premature convergence in search process. We call the proposed algorithm Niching-based Evolutionary PSO (NEPSO). The experimental results test several commonly used numerical benchmark functions, and show that NEPSO has very promising optimization performance.
SocialStreamViewer: Guiding the Viewer Experience of Multiple Streams of an Event

Live streaming is becoming a popular way to share experiences with others. When concurrent video streams of the same event are available, it can be challenging to decide which streams to view and to manage the experience across multiple streams. We designed and developed the SocialStreamViewer prototype that aggregates multiple streams from an event and visualizes others' viewing, hearting, and text chat activity. It also enables users to replay portions of streams. A lab study of SocialStreamViewer explored how people experience an event remotely through multiple streams, and how they use social signals from other viewers' activities. We found that 1) providing multiple streams is beneficial; 2) replaying back in time is highly valued since it helps ensure that users will not miss interesting content; and 3) visualizing other viewers' activities helps users decide which stream to watch.
Realistically Coupled Neural Mass Models Can Generate EEG Rhythms

We study the generation of EEG rhythms by means of realistically coupled neural mass models. Previous neural mass models were used to model cortical voxels and the thalamus. Interactions between voxels of the same and other cortical areas and with the thalamus were taken into account. Voxels within the same cortical area were coupled (short-range connections) with both excitatory and inhibitory connections, while coupling between areas (long-range connections) was considered to be excitatory only. Short-range connection strengths were modeled by using a connectivity function depending on the distance between voxels. Coupling strength parameters between areas were defined from empirical anatomical data employing the information obtained from probabilistic paths, which were tracked by water diffusion imaging techniques and used to quantify white matter tracts in the brain. Each cortical voxel was then described by a set of 16 random differential equations, while the thalamus was described by a set of 12 random differential equations. Thus, for analyzing the neuronal dynamics emerging from the interaction of several areas, a large system of differential equations needs to be solved. The sparseness of the estimated anatomical connectivity matrix reduces the number of connection parameters substantially, making the solution of this system faster. Simulations of human brain rhythms were carried out in order to test the model. Physiologically plausible results were obtained based on this anatomically constrained neural mass model.
Exploring Eﬀects of Intrinsic Motivation in Reinforcement Learning Agents

We explore Intrinsic Motivation as a reward framework for learning how to perform complicated tasks. Most reinforcement learning tasks assume the existence of a critic who rewards the agent for its actions. However, taking inspiration for biological agents, we can say that the real critic is the agent itself. We experiment with a model where the rewards are generated by the agent using a process which models the emotion of surprisal. The agent is modeled as intrinsically motivated to look for surprising events. We demonstrate how the agent learns under such a framework. Results show that even in the absence of any external reward, the agent is able to learn skills and perform complicated tasks.
Non-commutative gauge theory, open Wilson lines and closed strings

A recently proposed connection between closed string field and an open Wilson line defined on an arbitrary contour is further explored here. We suggest that reparametrization invariance of a Wilson line is the principle which determines the coupling of non-commutative gauge theory/matrix model to the modes of the closed string. An analogue of the level matching condition on the gauge theory/matrix model operators emerges quite naturally from the cyclic symmetry of the straight Wilson line. We show that the generating functional of correlation functions of these operators has the space-time gauge symmetry that one expects to find in closed string field theory. We also identify an infinite number of conserved operators in gauge theory/matrix model, the first of which is known to be the conserved stress tensor.
EDHEC RISK AND ASSET MANAGEMENT RESEARCH CENTRE

In this paper, we examine how standard exchange-traded fixed-income derivatives (futures and options on futures contracts) can be included in a sound risk and asset management process so as to improve risk and return performance characteristics of managed portfolios. Our results show that the non-linear character of the returns on protective option strategies offers appealing risk reduction properties in the pure asset management context. Consequently, such strategies should optimally receive a significant allocation, especially when investors are concerned with minimising extreme risks. In an asset liability management context, we also show that fixed-income derivatives in general, and recently launched long-term futures contracts in particular, offer significant shortfall risk reduction benefits. These results have potentially significant implications in the context of an increased focus on matching liability portfolios. EDHEC is one of the top five business schools in France owing to the high quality of its academic staff (100 permanent lecturers from France and abroad) and its privileged relationship with professionals that the school has been developing since its establishment in 1906. EDHEC Business School has decided to draw on its extensive knowledge of the professional environment and has therefore concentrated its research on themes that satisfy the needs of professionals. EDHEC pursues an active research policy in the field of finance. Its “Risk and Asset Management Research Centre” carries out numerous research programs in the areas of asset allocation and risk management in both the traditional and alternative investment universes. Copyright © 2006 Edhec
A HYBRID APPROACH FOR ARABIC LITERAL AMOUNTS RECOGNITION

ABSTRACT The challenge of hybrid learning systems is to use the information provided by one source of information to compensate information missing from the other source. The neuro–symbolic combination represents a promising research way. The synergy between the symbolic (theoretical) and neural (empirical) approaches makes their combination more effective than each of them used alone. In this article, we describe an Arabic literal amount recognition system that uses a neuro-symbolic classifier. For this purpose, we first extract structural features from the words contained in the amounts vocabulary. Then, we build a symbolic knowledge base that reflects a classification of words according to their features. In a third step, we use a translation algorithm (from rules to neural network) to determine the neural network architecture and to initialize its connections with specific values rather than random values, as is the case in classical neural networks. This construction approach provides the network with theoretical knowledge and reduces the training stage, which remains necessary because of styles and writing conditions variability. After this empirical training stage using real examples, the network acquires a final topology, which allows it to recognize new handwritten amounts.
Variability of Moderate-Luminosity Active Galactic Nuclei at z = 0.36

We monitored 13 moderate-luminosity active galactic nuclei at z = 0.36 to measure flux variability, explore feasibility of reverberation mapping, and determine uncertainties on estimating black hole mass from single-epoch data. Spectra and images were obtained with approximately weekly cadence for up to 4 months, using the Kast spectrograph on the 3 m Shane Telescope. In broad band we detect peak-to-peak variations of 9%-37% and rms variations of 2%-10%. The observed flux variability in the g′ band (rest frame 2800-4000 Å) is consistent with that in the r′ band (rest frame 4000-5200 Å), but with larger amplitude. However, after correcting for stellar light dilution using Hubble Space Telescope images, we find nuclear variability of 3%-24% (rms variation) with similar amplitudes in the g′ and r′ bands within the errors. Intrinsic flux variability of the Hβ line is also detected at the 3%-13% level, after accounting for systematic errors on the spectrophotometry. This demonstrates that a reverberation mapping campaign beyond the local universe can be carried out with a 3 m class telescope, provided that sufficiently long light curves are obtained. Finally, we compare the Hβ FWHM measured from mean spectra with that measured from single-epoch data, and find no bias but an rms scatter of 14%, mostly accounted for by the uncertainty on FWHM measurements. The propagated uncertainty on black hole mass estimates, due to the FWHM measurement errors using low S/N (10-15 pixel-1) single-epoch spectra, is 30%.
A Review on Applications of Coagulation- Flocculation and Ballast Flocculation for Water and Wastewater

A coagulation and ballast flocculation process is chemical treatment for water and industrial wastewater. This technology is used as primary treatments for removal of particulate matter and organic matter effectively. The process is very efficient in removal of total solids (TS),Total suspended solids (TSS), total dissolved solids (TDS) and chemical oxygen demand (COD) , Color . This technology is applicable in water treatment and also tannery, coffee, detergent, tar and dairy wastewater efficiently. The present paper focusses on coagulation and ballast flocculation technology for water and industrial wastewater treatment. This review shows applicability of coagulation-flocculation for wastewater for textile, tannery, removal of surfactants for Detergent Wastewaters, as primary treatment before membrane application for dairy wastewater, heavy metal removal for leachate wastewater and also for Sand ballast flocculation for water treatment which indicates efficiency and applicability of this technology.
Vector control of DFIG in wind power applications

As a result of increasing energy demand, effective generation-with high efficiency and low generation costs-of energy is very important. Today, power suppliers are looking for options that might increase the efficiency of the existing systems rather than installing new power stations or adding extra capacity. Maximum utilization of power sources can be achieved with the selection of the most appropriate conversion and control systems. Doubly-Fed Induction Generator (DFIG) which appears to be one of the most effective solutions for variable speed applications requires a complicated control system. In this paper, Field Oriented Control (FOC) method for DFIG is presented. DFIG has been modeled in MATLAB/Simulink program and the use of FOC simulated. Simulation results show that the control algorithm is suitable for controlling active power, reactive power and DC link voltage.
The community corrections perspective toward sex offender management policies and collateral consequences: does contact with sex offenders matter?

Abstract Since the 1990s, numerous policies have been enacted aimed at managing sex offenders in the community. Two of the most prominent management policies are registries for sex offenders and residence restrictions. Community corrections professionals are tasked with enforcing these policies and yet little is known about their perceptions toward sex offenders and the policies in place to manage them. Prior research has suggested that contact with sex offenders may place a significant role in shaping the attitudes of community corrections professionals toward sex offender management policies and collateral consequences. The current study investigates the effect of contact with sex offenders on the perceptions of community corrections professionals (n = 209) toward sex offender management policies and collateral consequences faced by sex offenders. Findings suggest that contact with sex offenders does not influence the attitudes of community corrections professionals, but several other significant factors were revealed including parental status, political orientation, race, tenure, sex, and age.
Lievän ennenaikaisuuden yhteys itsearvioituihin autistisiin piirteisiin nuorilla aikuisilla

Tavoitteet: Autistiset piirteet ovat vaestotasolla normaalijakautuneita ja autismin kirjon hairio voidaan kasittaa taman jakauman toisena aaripaana. Ennenaikaisen syntymisen (<37 rv) on havaittu lisaavan riskia autismin kirjon hairion ja autististen piirteiden esiintyvyyteen. Valtaosa ennenaikaisesti syntyneista syntyy lievasti ennenaikaisina raskausviikoilla 34+0- 36+6 ja lievasti ennenaikaiset ovat maailmanlaajuisesti kasvavin ennenaikaisten ryhma. On havaittu, etta taaperoikasilla lieva ennenaikaisuus on yhteydessa autistisiin piirteisiin, mutta lievan ennenaikaisuuden yhteydesta aikuisuudessa esiintyviin autistisiin piirteisiin ei ole viela lainkaan tutkimustietoa. Olisi tarkeaa saada tietaa, vaikuttaako lieva ennenaikaisuus autististen piirteiden esiintyvyyteen viela aikuisenakin. Tassa tutkimuksessa tarkastellaan lievan ennenaikaisuuden yhteytta nuorten aikuisten itsearvioimiin autistisiin piirteisiin. Lisaksi tutkitaan valittaako raskauden kestoon nahden pienipainoisuus mahdollista yhteytta. Menetelmat. Tutkimuksen aineisto oli osa Arvo Ylppo- pitkittaistutkimus kohorttia, johon kuului 2193 lasta. Tutkimukseen valittiin ne osallistujat, joilla raskauden kesto oli luotettavasti maaritettavissa ja jotka olivat tayttaneet Autism Spectrum Quotient (AQ)- kyselylomakkeen. Lopulliseen otokseen valikoitui 684 osallistujaa, joista lievasti ennenaikaisia oli 90 ja taysiaikaisia kontrolleja 578. Lievan ennenaikaisuuden yhteytta itsearvioituihin autistiin piirteisiin tutkittiin lineaarisella regressioanalyysilla. Tulokset ja johtopaatokset. Lievalla ennenaikaisuudella ei ollut yhteytta itsearvioituihin autististiin piirteisiin nuorilla aikuisilla. Raskauden kestoon nahden pienipainoisuudella ei ollut vaikutusta yhteyteen. Jatkossa olisi mielekasta tutkia pitkittaisasetelmalla taaperoiasta kouluikaan ja edelleen aikuisuuteen asti esiintyvia autistisia piirteita eri ennenaikaisuuden ryhmissa ja kerata laajalti tietoa erilaisista taustamuuttujista. Nain saataisiin tietaa sailyvatko taaperoiassa esiintyvat piirteet aikuisuuteen asti ja mitka tekijat ovat merkityksellisia suotuisan kehityksen kannalta.
Towards a model-driven approach to build component-based adaptable middleware

Adaptability is one of the goals that applications and middleware frameworks are trying to achieve. On one hand, the component paradigm is a way of reaching this goal by enforcing the reusability of functionalities involved in a component-based middleware framework. In particular, reflection could be combined with components to improve the adaptability of the structure of their assemblies. On the other hand, the model driven paradigm provides an efficient way to describe an application with enough abstraction to enable its mapping on various execution platforms. The contribution of this paper is a combination of both model and component paradigms to reach more adaptability in middleware, especially in a component-based framework to build transaction services. The framework presented uses models to describe middleware standards and compiles them to components. These components are coupled with a compliant component-based middleware framework. This approach provides adaptability at various levels with some added values.
EventSense: capturing the pulse of large-scale events by mining social media streams

Social media platforms such as Twitter and Facebook have seen increasing adoption by people worldwide. Coupled with the habit of people to use social media for sharing their daily activities and experiences, it is not surprising that a substantial part of real-world events are well described by the online streams of status updates, posts and media content. In fact, in the case of large events, such as festivals, the number of online messages and shared content can be so high that it is very hard to get an objective view of the event. To this end, this paper presents EventSense, a social media sensing framework that can help event organizers and enthusiasts capture the pulse of large events and gain valuable insights into their impact on visitors. More specifically, EventSense enables the automatic association of online messages to entities of interest (e.g. films in the case of a film festival), the automatic discovery of topics discussed online, and the detection of sentiment (positive/negative/neutral) both at an entity level (e.g. per film) and on aggregate. In addition, the framework produces an informative social media summary of the event of interest by automatically selecting and putting together its highlights, e.g. the most discussed entities and topics, the most influential users, the evolution of the discussions' sentiment, and the most shared media and news content. A real-world case study is presented by applying EventSense on a rich dataset collected around the 53rd Thessaloniki International Film Festival.
CCN Properties of Organic Aerosol Collected Below and within Marine Stratocumulus Clouds near Monterey, California

The composition of aerosol from cloud droplets differs from that below cloud. Its implications for the Cloud Condensation Nuclei (CCN) activity are the focus of this study. Water-soluble organic matter from below cloud, and cloud droplet residuals off the coast of Monterey, California were collected; offline chemical composition, CCN activity and surface tension measurements coupled with Kohler Theory Analysis are used to infer the molar volume and surfactant characteristics of organics in both samples. Based on the surface tension depression of the samples, it is unlikely that the aerosol contains strong surfactants. The activation kinetics for all samples examined are consistent with rapid (NH4)2SO4 calibration aerosol. This is consistent with our current understanding of droplet kinetics for ambient CCN. However, the carbonaceous material in cloud drop residuals is far more hygroscopic than in sub-cloud aerosol, suggestive of the impact of cloud chemistry on the hygroscopic properties of organic matter.
VISUAL INTERPRETATION OF FACES IN THE NEIMO MULTI-MODAL HCI TEST-BED

The Wizard of Oz technique (WOz) is an experimental evaluation mechanism. It allows the observation of a user operating an apparently fully functioning system whose missing services are supplemented by a hidden wizard. NEIMO is a multimodal WOz platform including four modalities: two-dimensional manual gesture (mouse), written and spoken natural language and visual interpretation of the subject’s face. A sub-system, NEIMOVision, is responsible for the visual interpretation of the face. It’s functionalities are to normalize the image intensity, locate the face position, orientation and size, identify the subject, detect the direction of gaze, analyse the facial expression and detect speech acts. These functionalities are mainly based on the Eigenface technique developped by Turk [Turk 91]. Demonstration pprograms based on face recognition have been implemented on a Macintosh Quadra 700 equiped with a small CCD camera. At the same time we are currently studying other technical issues related to the integration of vision as an HCI mode. We are using this system to investigate the requirements in computing power, the trade-offs between resolution and processing speed, the use of active vision, the possible extensions to hand-tracking and the role of visual processing as a source of HCI modalities.
Low jitter design of a 0.35&#181;m&#8211;CMOS frequency divider operating up to 3GHz

The design of a 32/33 frequency divider, that can operate with input frequency up to 3GHz is discussed, The circuit is realized in a 0. 35µm CMOS technology. Particular attention is devoted to assess, in simple terms, the output phase noise and its reduction due to the adoption of a synchronization flip-flop. The measured noise level, -172 dBc/Hz, matches within 1dB with the value predicted by the theory. The minimum input differential signal is 50 mV zero-peak. The power dissipation is 27mW.
Surveying and Analyzing Security Problems in Cloud Computing Environments

Cloud computing technology is a relatively new concept of providing dramatically scalable and virtualized resources, software and hardware on demand to consumers. Cloud Computing offers a whole new paradigm to provide users with high end and scalable infrastructure at an affordable cost. It is based on many new technologies like virtualization and distributed computing. However, security concerns are terrible for these systems whose infrastructure and computational resources are owned by an outside party that sells those services to the general public. In fact, data breaches to cloud services are also increasing every year due to hackers who are always trying to exploit the security vulnerabilities of the cloud architecture. We present in this paper a detailed analysis of the cloud computing security issues and the general security requirements into which the security concerns falls. In addition, countermeasures to cloud security breaches are proposed.
The Relationship Between Aggression and Self-Esteem Among Prison Inmates

ABSTRACT Although the concept of self-esteem (SE) has been extensively researched and analyzed as it has evolved in psychology, it has not been widely used among criminologists to predict aggressive behavior. The purpose of this pilot study was to examine the relationship between aggressive behavior and SE among prison inmates, and to examine whether inmates’ SE levels predicted different types of aggression. More specifically, 2 types of aggression were measured: physical active aggression (PAA) and physical passive aggression (PPA). It was found that inmates with lower SE had higher levels of physical passive but not physical active aggression than inmates with higher SE. These findings point to several implications for future research.