Miracle-dz/UniFAR-FTUs huggingface dataset:
Network formation through a gender lens: insights from rural Nicaragua

This paper examines the relation between gender and network formation in rural Nicaragua. Applying dyadic regression techniques and controlling for individual socio-economic characteristics, we obtain insights into the determinants of the size and density as well as the socio-economic heterogeneity of individual networks. Assuming these network characteristics correlate with one's agency and benefits from network participation, we look for differences between men's and women's networks and its relation with gender. In general, the gendered private/public dichotomy and labor division is replicated in men's and women's networks. Furthermore, consistent with the restricted mobility of poor rural women, we observe that geographic distance limits the networks of women but not men. Next, female education and mobility, and newly-residing men, have a positive influence on the integration between men and women. Finally, clique formation is stronger around women than men.
Spatial Coding in the Hippocampal Region

The hippocampal region, comprising the hippocampal formation and the parahippocampal region, has been for decades one of the most intensely studied parts of the brain. The increased understanding of its functional diversity and complexity has led to an increased demand for specificity in experimental procedures and manipulations. In view of the complex three-dimensional structure of the region, precisely positioned experimental approaches require a fine-grained architectural description of the region that is available and readable to non-anatomically experienced experimentalists. In this paper we provide the first cytoand chemoarchitectural description of the hippocampal region at high resolution and in the three standard sectional planes: coronal, horizontal and sagittal. The atlas is based on series of adjacent sections stained for neurons and for a number of chemical marker substances, relying mainly on immunopositivity for parvalbumin and calbindin. All borders defined in one plane have been crosschecked against their counterparts in the other two planes. The entire dataset will be made available as a web-based interactive
Fusing video and text data by integrating appearance and behavior similarity

In this paper, we describe an algorithm for multi-modal entity co-reference resolution and present experimental results using text and motion imagery data sources. Our model generates probabilistic association between entities mentioned in text and detected in video data by jointly optimizing the measure of appearance and behavior similarity. Appearance similarity is calculated as a match between propositionderived entity attributes mentioned in text, and the object appearance classification from video sources. The behavior similarity is calculated based on the semantic information about entity movements, actions, and interactions with other entities mentioned in text and detected in video sources. Our model achieved 79% Fscore for text-to-video entity co-reference resolution; we show that entity interactions present unique features for resolving variability present in text data and ambiguity of visual appearance of entities.
Design replacements for sequential circuits

In this dissertation we study the problem of design replacements for synchronous sequential circuits. There have been previous efforts to characterize the criterion for replacement for such circuits. However, all previous attempts either make implicit or explicit assumptions about the design or the environment of the design (for example, all latches have a hardware reset line and the design operation starts in a unique designated initial state). We present a notion for replacement which works for any arbitrary environment, and without making these assumptions. We also observe that if the design's output is not used for a certain number of cycles after power-up then allows additional flexibility is available for replacement. We have used these notions of design replacement for logic optimization and we report encouraging results. We also prove the complexity of the verification problem for these notions as well as heuristics for this problem. We study the effect of retiming transformations on circuit behavior in detail. We show how such transformations produce acceptable replacements, both with respect to the actual circuit behavior as well as the behavior of the circuit as seen through conservative logic simulators. We also show that the problem of retiming the initial state of circuits can always be solved simply by modeling reset circuitry explicitly.
Performance Analysis of Cooperative Spectrum Sensing Technique for Low SNR Regime over Fading Channels for Cognitive Radio Networks

Cognitive Radio is a technology for Next Generation Wireless Networks to support Dynamic Spectrum Access which addresses the spectrum scarcity and under utilization problems experienced by today’s wireless communication networks. Spectrum Sensing is an important function of cognitive radio that identifies the unused licensed frequency bands of Primary Users for opportunistic access by Secondary Users. In this paper, we have proposed a sensing technique incorporating wavelet denoising to enhance the sensing performance at low SNR regime. The combination of wavelet denoising preceeding energy detector, hard decision for local sensing and OR fusion rule at the fusion center for cooperative sensing has improved the sensing performance. We have quantified the performance improvement of the proposed technique in fading environments and studied the effect of wavelet denoising. Probability of missed detection has been reduced by 38% over Rayleigh Fading channel and 52% over Nakagami Fading channel compared to conventional sensing technique for ten users cooperation. Sensing time has been reduced by 1 msec and throughput improved by 50 Mbits/Sec/Hz compared to conventional energy detection based sensing method.
Target tracking incorporating flight envelope information

Target tracking in usually performed assuming the target under consideration is adequately modelled as a point target with no reference to constraints on its motion. However, in reality, target motion is constrained by achievable maximum speeds and accelerations. This is non-standard information and its incorporation into conventional tracking, while promising significant benefits, poses a significant challenge in constructing the posterior probability density function (PDF) of target state. In this paper, the optimal Bayes' recursion for this posterior PDP is derived and an algorithm for implementing this recursion based on stochastic sampling techniques is presented. An illustrative example demonstrating the benefits of incorporating this information is also provided.
Dynamic behaviour of a linear induction motor

Although conventional rotating machines have been largely used to drive underground transportation systems, linear induction motors are also being considered for future applications owing to their indisputable advantages. A mathematical model for the transient behaviour analysis of linear induction motors, when operating with constant RMS currents, is presented in this paper. Operating conditions, like phase short-circuit and input frequency variations and also some design characteristics, such as air-gap and secondary resistivity variations, can be considered by means of this modeling. The basis of the mathematical modeling is presented. Experimental results obtained in the laboratory are compared with the corresponding simulations and discussed in this paper.
A Screening Form for Identifying Mental Health Problems in Alcohol/Other Drug Dependent Persons

ABSTRACT The Mental Health Screening Form-III(MHSF-III; Carroll & McGinley, 2000) was designed to address the need in the chemical dependency field for an easy-to-use, brief (18 items answered “yes” or “no”), no-cost instrument that would identify clients with co-occurring psychiatric difficulties. The instrument requires minimal training to use. Most clients complete it in 15 minutes, including the inquiry recommended for all “yes” responses. Data is provided on the MHSF-III's reliability and validity, as well as a survey of 111 therapeutic community residents. The survey results noted underlying psychopathology in the majority of clients surveyed.
Complexity of lexical descriptions and its relevance to partial parsing

Complexity of Lexical Descriptions and its Relevance to Partial Parsing Srinivas Bangalore Supervisor Aravind K Joshi In this dissertation we have proposed novel methods for robust parsing that integrate the exibility of linguistically motivated lexical descriptions with the robustness of statistical techniques Our thesis is that the computation of linguistic structure can be localized if lexical items are associated with rich descriptions supertags that impose complex con straints in a local context However increasing the complexity of descriptions makes the number of di erent descriptions for each lexical item much larger and hence increases the local ambiguity for a parser This local ambiguity can be resolved by using supertag co occurrence statistics collected from parsed corpora We have explored these ideas in the context of Lexicalized Tree Adjoining Grammar LTAG framework wherein supertag disambiguation provides a representation that is an almost parse We have used the dis ambiguated supertag sequence in conjunction with a lightweight dependency analyzer to compute noun groups verb groups dependency linkages and even partial parses We have shown that a trigram based supertagger achieves an accuracy of on Wall Street Journal WSJ texts Furthermore we have shown that the lightweight dependency anal ysis on the output of the supertagger identi es of the dependency links accurately We have exploited the representation of supertags with Explanation Based Learning to improve parsing e ciency In this approach parsing in limited domains can be modeled as a Finite State Transduction We have implemented such a system for the ATIS domain which improves parsing e ciency by a factor of We have used the supertagger in a
Atlas of Intraocular Tumors

ABSTRACT Atlas of Intraocular Tumors is a visual delight. As much or more than in any other field of medicine, ophthalmologists make abundant use of photographs to illustrate articles, books, and talks. As a result, the specialty of ophthalmic photography has developed. The photographer needs to be highly skilled in the necessary photographic techniques and about as skilled in the techniques of ophthalmic examination as the ophthalmologist. It is a joint venture of physician, photographer, and patient to obtain high-quality photographs of the eye in situ. This atlas excels in presenting beautiful clinical photographs of many ophthalmic tumors. For the nonophthalmologist, the text is a relatively quick and easy reference for ophthalmic tumors. The old Chinese proverb of "one picture is worth a thousand words" could apply.The book is divided into chapters labeled simply by the anatomic location, eg, iris. Introducing the chapters are enlargements in a pale pink-yellow hue
Digital Media Dependency, Relational Orientation and Socaial Networking among College Students

This study focused on digital media dependency, relational orientation, and demographic variables as potential factors that were relevant to the usage of social networking websites (e.g., MySpace and Facebook) among college students. A total of 258 (101 male and 157 female) students completed the questionnaire that contains the measures of digital media dependency, relational orientation, social networking media usage, and demographic characteristics. The respondents also indicated specific types of things that they disclose (post) on their social media websites. The results showed that relational orientation is positively correlated with the disclosure (posting) of family photos, friends’ photos, and travel photos and that White students are more likely than others to disclose their gender and favorite things (likes/dislikes) and post their own photos and travel photos. Regression analysis revealed that age is a significant, negative indicator of social media usage, whereas digital media dependency and overall computer usage are significant, positive predictors for the dependent measure. That is, the younger the student and the greater the levels of digital media dependency and overall computer usage, the greater the level of involvement in social networking websites.
Active Learning Based on Diversity Maximization

In many practical data mining applications, unlabeled training examples are readily available but labeled ones are fairly expensive to obtain. Therefore, as one type of the paradigms for addressing the problem of combining labeled and unlabeled data to boost the performance, active learning has attracted much attention. In this paper, we propose a new active learning approach based on diversity maximization. Different from the well-known co-testing algorithm, our method does not require two different views. The comparative studies with other active learning methods demonstrate the effectiveness of the proposed approach.
Control of a redundant 7DOF upper-limb power-assist exoskeleton robot

Many kinds of power-assist robots have been developed in order to assist daily activities or rehabilitation of the elderly or physically weak persons. Upper-limb power-assist robots are important to assist in many daily life activities such as eating, drinking, etc. A human upper-limb has 7 degrees of freedom to achieve various tasks dexterously. Therefore, to assist all upper-limb joint motions of a human, the upper-limb power-assist robot is required to have 7DOF. To achieve a desired task, a person moves the hand to the desired position and orientation and/or applies certain amount of force to the target. Therefore, it is important that the upper-limb power-assist robots help control the hand position/orientation or hand force of the user. However, the hand position/orientation or hand force is 6-dimensional vector, so the 7DOF upper-limb power-assist robot has a redundancy and in general, a pseudo-inverse matrix is used in the control. In this paper, an optimal control method is proposed to deal with the redundancy of the upper-limb power-assist exoskeleton robot considering comfortable motion of the user. The motion intention and the comfort of the user are taken into account in the pro-posed method. The effectiveness of the proposed method was evaluated by the experiments.
Quality-of-service issues in high-speed networks

We are currently witnessing an increasing demand for new services such as video conferencing and broadcast television. The development and deployment of new technologies such as fiber optics and intelligent high-speed digital switches have made it feasible to provide these services in future high-speed networks (HSNs). These new services are, however, characterized by rather stringent quality-of-service (QOS) criteria such as bounds on end-to-end packet delay and loss. Providing guarantees on QOS for these new services in future HSNs poses a number of interesting and challenging problems. In this thesis, we address the problem of providing statistical QOS guarantees to applications in HSNs. QOS criteria for applications are typically specified on an end-to-end basis in the network. The first part of this thesis examines policies for mapping (allocating) the end-to-end requirement to nodal requirements. This mapping simplifies providing QOS guarantees as also connection admission algorithms. The allocation policy performance is gauged on the basis of the maximum supportable network load under that policy. We develop good insight into allocation policy performance with the aid of a novel nodal sensitivity measure. It is shown that for a QOS metric of interest, the loss probability, and network operating regimes of practical interest rather naive policies exhibit near optimal performance. However, for certain other QOS metrics and operating regimes, it is shown that the optimal policy significantly outperforms simple QOS allocation policies. In the second part of this thesis, we restrict our attention to an isolated node and focus on appropriate QOS criteria and mechanisms to guarantee these criteria at the nodal level. Two new QOS criteria, the customer-duration-based and interval-based criteria, are proposed for HSNs and their applications. Further, a new cumulative transient metric, the customer average, is proposed for queueing models of communication systems. The computation of the new metric is detailed for a class of simple queueing models. Further, it is shown how this new metric enables one to compute and guarantee the new proposed QOS criteria.
Conception et commande d'une chaîne de traction pour véhicule hybride parallèle thermique et électrique

La motorisation hybride est consideree comme un moyen prometteur pour reduire la pollution et la consommation d'energie imputables a la circulation automobile. Cette etude, realisee en etroite collaboration avec PSA, s'applique au groupe motopropulseur d'un vehicule hybride parallele associant un moteur electrique et un moteur thermique. Apres un etat de l'art dans le domaine, une modelisation realisee a l'aide du logiciel MatlabSimulink a permis de simuler le fonctionnement, les performances et les echanges energetiques dans un tel vehicule lorsque les deux moteurs sont sollicites simultanement. Ensuite, l'elaboration de la strategie de commande generale visant a minimiser la consommation a ete entreprise. Dans ce cadre, differentes techniques d'optimisation ont ete etudiees. La solution proposee repose sur une minimisation instantanee d'une consommation equiVALEnte. Afin de valider les travaux en grandeur reelle, un prototype roulant a ete concu et realise sur la base d'un vehicule de serie psa. Il met en œuvre une architecture hybride parallele simple arbre avec une boite de vitesses pilotee a deux rapports. Les differents algorithmes pour la commande en temps reel du vehicule sont implementes a l'aide de cartes dsp.
L'intonation du discours : une implémentation par balises ; motifs et premiers résultats

Commonly assumed limitations of prosody generation in current text-to-speech systems based on the analysis of punctuation and syntax, are due to the fact that discourse and information structure is ignored. A strategy for obtaining more natural pitch contours is proposed, which is based on the insertion of tags indicating phonetic, acoustic, tonal, and/or functional attributes in the input text. A set of prosodic tags for speech synthesis is described.
Short-Term Traffic State Forecasting for Dynamic Traffic Routing System

The paper researches the problem of how to forecast traffic information in one minute interval. A kalman filter algorithm for short-term traffic forecasting based on the construction of dynamic traffic routing system of Nanning city of China was proposed in this paper, and selected National Road as field calibration, which compared with the real traffic conditions, and the error of predicted results is less than 10%. The results demonstrate the effectiveness of the proposed forecasting model in paper, and the research has a significant contribution for data process of Dynamic Traffic Routing System.
Feasibility analysis of using NeuCube 3D SNN environment for spatio-temporal EEG data classification related to perception of art

This thesis is a feasibility study of using a Spiking Neural Network (SNN) architecture named NeuCube for the classification of electroencephalography (EEG) data related to the perception of art. We have performed classification of human brain perception EEG data obtained via a set of experiments on originally created audio, video, and audio & video mixed stimuli. The analysis of results confirms that the proposed method is feasible for further analysis and experimentation, and for the study of art perception and creativity. Massive amounts of complex Spatio-Temporal Brain Data (STBD) have been accumulated recently. As it is critical in many disciplines to rely on proper analysis, understanding and utilization of complex spatio-temporal brain data, such as that from an EEG, this is a great challenge which this study seeks to contribute to. In this study for classification purposes a new evolving Spiking Neural Network (SNN) architecture will be used, called NeuCube. NeuCube is the latest neuroscience software tool developed at KEDRI, AUT, for spatio- and spectro -temporal pattern recognition of brain data, for the creation of concrete models to map, learn and understand STBD. A NeuCube model is based on a 3D evolving SNN that is an approximate map of structural and functional areas of interest of the brain related to the modeling STBD. An evaluation of feasibility of NeuCube for classification of Spatio-Temporal EEG brain perception data is performed in this study. An authentication methodology is proposed and illustrated on several small-scale examples of classification of EEG human brain perception data collected on audio and visual stimuli pairs. A methodology for person identification is proposed that uses a certain audio and/or video stimulus as a “security key” for the authentication process. The stimuli pairs used for experiments in this study were created the following way; an audio pair is highly structural classical music versus disordered / chaotic noise, a visual pair is a set of opposing structural repetitive archetypical video patterns from an abstract modern art video, and also mixed audio/video pairs are used. The term of “brainprints” is offered by the analogy with fingerprints and prospectively having the ability to supply similar functionality but with an even higher level of security. In addition the following hypotheses on the nature of human creativity are proposed in this study: human creativity might be defined as naturally inherited human ability and necessity to decipher, digest and transfer the universe global programme (human-independent) into patterned structures, expressed in some unique distinctive way. Therefore the concept of a genius might be defined as human ability to decipher and translate “global universe postulates” into human-readable patterns, performed the best possible way for the majority of a certain population.