Miracle-dz/UniFAR-FTUs huggingface dataset:
A DISTRIBUTED ARCHITECTURE FOR COOPERATIVE SPOKEN DIALOGUE AGENTS WITH COHERENT DIALOGUE STATE AND HISTORY

It has been very difficult to develop spoken dialogue systems with high domain extensibility. Not only the system complexity inevitably increases with the number of topics and domains, but the concurrent topics need to be handled persistently and consistently across different domains. This paper presents a distributed architecture for cooperative spoken dialogue agents with high domain extensibility. Under this architecture, different spoken dialogue agents handling different domains can be developed independently, and cooperate with one another to respond to the user’s requests, while a user interface agent can access the correct spoken dialogue agent through a domain switching protocol, and carry over the dialogue state and history so as to keep the knowledge processed persistently and consistently across different domains. Initial experiments provide very encouraging results.
Fall detection on the road

While for an automatic and autonomous indoor fall detection an enormous amount of different sensors is conceivable, for an outdoor fall detection only wearable sensors are applicable. For practical uses cases, it would be very beneficial if after a detected fall a medical alert is initiated. In indoor environments, a base station connected to a telephone line can handle these calls. On the road, this can be achieved by mobile phones or smartphones. In this paper we first estimate the suitability of several systems for an outdoor fall detection. Then, we propose a system for a mobile and stationary fall detection and alerting system. We implemented and evaluated this system, which is consisting of a smartphone and a wireless sensor node.
Psychiatric comorbidity in children after the 1988 earthquake in Armenia.

OBJECTIVE To determine current rates of posttraumatic stress disorder (PTSD), depressive disorder, and separation anxiety disorder (SAD) among children 1 1/2 years after the 1988 earthquake in Armenia; to determine current rates of comorbid PTSD and depressive disorder; and to assess the contribution of exposure, gender, loss of family members, and loss of residence. METHOD Two hundred eighteen school-age children from three cities at increasing distances from the epicenter were evaluated using the Child Posttraumatic Stress Disorder Reaction Index, the Depression Self-Rating Scale, and the section on SAD from the Diagnostic Interview for Children and Adolescents. RESULTS On the basis of these evaluations, high rates of current PTSD, depressive disorder, and their co-occurrence were found among victims residing in the two heavily impacted cities. SAD was comparatively less frequent, although symptoms of SAD had been pervasive throughout the region. Severity of posttraumatic stress and depressive reactions were highly correlated. Extent of loss of family members was independently correlated with each. CONCLUSION After a catastrophic natural disaster, children are at risk for comorbid PTSD and secondary depression. Based on the findings, an interactive model is proposed of postdisaster psychopathology. Early clinical intervention is recommended to prevent chronic posttraumatic stress reactions and secondary depression.
The Psychological Context of Contextualism

Philosophy is not the only discipline concerned with shifting epistemic intuitions. Psychology also studies intuitive impressions of knowledge, often with an eye to the ways in which these intuitive impressions can shift as circumstances change. Cognitive and social psychologists explore factors figuring prominently in the contrasting cases motivating contextualism, including rising and falling practical stakes, heightened selfconsciousness, and worries about the possibility of error. In some cases, these factors are taken to distort perceptions of knowledge in the attributor, causing the impression of a shift in knowledge where no real shift in knowledge has occurred. In other cases, these factors are taken to have an impact on the subject’s actual possession of knowledge, for example by raising or lowering the subject’s confidence. Where attributor perceptions of knowledge march in step with variations in the subject’s knowledge, there is no reason to consider a shift in perceptions mistaken, but such shifts may risk being misunderstood by theorists who are unaware of the subtle ways in which contextual circumstances change a subject’s cognition. If the key claim of contextualism is that statements of the form “S knows that p” can express propositions differing in truth value for subjects matched on traditional epistemic factors (such as confidence and accuracy), philosophers need to be aware of the subtle ways in which these traditional epistemic factors can change, and be instinctively registered as changing, in response to changing circumstances. Equally, philosophers who are sympathetic to contextualism will want to know how it might be psychologically possible for us to deploy shifting standards in evaluating others.
Critical Temperature Switch: A Highly Sensitive Thermosensing Device Consisting of Subthreshold MOSFET Circuits

A thermosensing circuit that changes its internal state steeply at a critical temperature is proposed. The device makes use of the transition of a MOSFET resistor from strong-inversion operation to weak-inversion or subthreshold operation. The temperature for the transition can be set to a desired value by adjusting the parameters of MOSFETs in the device. The device can be made with a standard CMOS process and can be used as over-temperature and over-current protectors for LSI circuits
Studying Political Behavior: A Comparison of Internet and Telephone Surveys

Despite the promise of Internet surveys, there are significant concerns about the representativeness of the sample and survey instrument effects. This article seeks to address these questions by examining the differences and similarities between parallel Internet and telephone surveys conducted in Quebec after the provincial election in 2007. Our results indicate that the responses obtained in each mode differ somewhat from each other but that few inferential differences would occur if conclusions were drawn from the analysis of one dataset or the other. We urge researchers to consider the Internet as a viable mode of data collection, in that the consequences of mode effects appear to be minimal.
Performance evaluation of end-to-end security protocols in an Internet of Things

Wireless Sensor Networks are destined to play a fundamental role in the next-generation Internet, which will be characterized by the Machine-to-Machine paradigm, according to which, embedded devices will actively exchange information, thus enabling the development of innovative applications. It will contribute to assert the concept of Internet of Things, where end-to-end security represents a key issue. In such context, it is very important to understand which protocols are able to provide the right level of security without burdening the limited resources of constrained networks. This paper presents a performance comparison between two of the most widely used security protocols: IPSec and DTLS. We provide the analysis of their impact on the resources of embedded devices. For this purpose, we have modified existing implementations of both protocols to make them properly run on our hardware platforms, and we have performed an extensive experimental evaluation study. The achieved results are not a consequence of a classical simulation campaign, but they have been obtained in a real scenario that uses software and hardware typical of the current technological developments. Therefore, they can help network designers to identify the most appropriate secure mechanism for end-to-end IP communications involving constrained devices.
Recognizers : A study in learning how to model temporally extended behaviors

Using a hierarchy of behaviors often requires learning mode ls of these behaviors in an efficient way from one stream of experience. In this paper we a re concerned with computing the reward model of a behavior, when this model has to be re pres nted using function approximation. Off-policy learning methods have been prop osed for this goal, but their efficiency when using function approximation has been limited (Precup, Sutton & Dasgupta, 2001). One of the sources of this problem is the fact that exis ing off-policy methods rely on importance sampling corrections to estimate models for dif ferent behaviors from the same stream of experience. These corrections can have very high v ariance if the policy generating the behavior is very different from the behavior that w e ant to model. Moreover, the behavior policy has to be known and fixed, otherwise these corrections are not well defined. In order to address these problems, Precup et al. (20 06) introduced the notion of recognizers . Rather than specifying an explicit policy for a behavior ab out which we want to make predictions, a recognizer specifies a condition on th e actions that are selected. For example, a recognizer for the temporally extended action of picking up a cup would not specify which hand is to be used, or what the motion should be a t all different positions of the cup. The recognizer would recognize a whole variety of directions of motion and poses as part of picking the cup. The advantage of this approa ch is that the behavior may be based on a variety of different strategies, all of which ar e relevant, and we would like to learn from any of them. In general, a recognizer is a functi o that recognizes or accepts a range of different policies. Recognizers have two advanta ges over direct specification of a target policy: 1) they are a natural and easy way to specify a target policy for which importance sampling will be well conditioned, and 2) they do no t require the behavior policy to be known. The latter is important because in many cases we m ay have little knowledge of the behavior policy, or a stationary behavior policy may n ot even exist. In Precup et al.(2006), the authors show that if the model is represented using state aggregation, even if the behavior policy is unknown, convergence to a good model i s achieved. Here, we generalize this to the case of general linear function approximat ion, and show that this approach works very well empirically. We also discuss how recognizer s might be learned from data.
A 3D Shape Descriptor Based on Hadamard Transform and Spherical Harmonic Transform

Shape matching plays an important role in many application fields. In this paper, we propose a novel rotation invariant 3D shape descriptor based on Hadamard transform and spherical harmonic transform. In our method, a 3D model is represented as a collection of spherical functions to preserve shape information as much as possible, and the shape similarity is directly defined by the difference of the character functions of 3D models. Retrieval experiments show that our method performs better than many other existing 3D matching methods based on spherical harmonics.
Iris Recognition System Using Statistical Features for Biometric Identification

Iris recognition is a proven, accurate means to identify people. In this paper, it includes the preprocessing system, segmentation, feature extraction and recognition. Especially it focuses on image segmentation and statistical feature extraction for iris recognition process. The performance of iris recognition system highly depends on segmentation. For instance, even an effective feature extraction method would not be able to obtain useful information from an iris image that is not segmented properly. This paper presents a straightforward approach for segmenting the iris patterns. The used method determines an automated global threshold and the pupil center. Experiments are performed using iris images obtained from CASIA database. (Institute of Automation, Chinese Academy of Sciences) and Matlab application for its easy and efficient tools in image manipulation.
Maternal morbidity and mortality associated with interpregnancy interval: cross sectional study

Abstract Objective: To study the impact of interpregnancy interval on maternal morbidity and mortality. Design: Retrospective cross sectional study with data from the Perinatal Information System database of the Latin American Centre for Perinatology and Human Development, Montevideo, Uruguay. Setting: Latin America and the Caribbean, 1985-97. Participants: 456 889 parous women delivering singleton infants. Main outcome measures: Crude and adjusted odds ratios of the effects of short and long interpregnancy intervals on maternal death, pre-eclampsia, eclampsia, gestational diabetes mellitus, third trimester bleeding, premature rupture of membranes, postpartum haemorrhage, puerperal endometritis, and anaemia. Results: Short (<6 months) and long (>59 months) interpregnancy intervals were observed for 2.8% and 19.5% of women, respectively. After adjustment for major confounding factors, compared with those conceiving at 18 to 23 months after a previous birth, women with interpregnancy intervals of 5 months or less had higher risks for maternal death (odds ratio 2.54; 95% confidence interval 1.22 to 5.38), third trimester bleeding (1.73; 1.42 to 2.24), premature rupture of membranes (1.72; 1.53 to 1.93), puerperal endometritis (1.33; 1.22 to 1.45), and anaemia (1.30; 1.18 to 1.43). Compared with women with interpregnancy intervals of 18 to 23 months, women with interpregnancy intervals longer than 59 months had significantly increased risks of pre-eclampsia (1.83; 1.72 to 1.94) and eclampsia (1.80; 1.38 to 2.32). Conclusions: Interpregnancy intervals less than 6 months and longer than 59 months are associated with an increased risk of adverse maternal outcomes.
Where does the black population of South Africa stand on the nutrition transition?

Abstract Objective: To review data on selected risk factors related to the emergence of non communicable diseases (NCDs) in the black population of South Africa. Methods: Data from existing literature on South African blacks were reviewed with an emphasis placed on changes in diet and the emergence of obesity and related NCDs. Design: Review and analysis of secondary data over time relating to diet, physical activity and obesity and relevant to nutrition-related NCDs. Settings: Urban, peri-urban and rural areas of South Africa. National prevalence data are also included. Subjects: Black adults over the age of 15 years were examined. Results: Shifts in dietary intake, to a less prudent pattern, are occurring with apparent increasing momentum, particularly among blacks, who constitute three-quarters of the population. Data have shown that among urban blacks, fat intakes have increased from 16.4% to 26.2% of total energy (a relative increase of 59.7%), while carbohydrate intakes have decreased from 69.3% to 61.7% of total energy (a relative decrease of 10.9%) in the past 50 years. Shifts towards the Western diet are apparent among rural African dwellers as well. The South African Demographic and Health Survey conducted in 1998 revealed that 31.8% of African women (over the age of 15 years) were obese (body mass index (BMI) ≥ 30 kgm−2) and that a further 26.7% were overweight (BMI ≥ 25 to <30 kgm−2). The obesity prevalence among men of the same age was 6.0%, with 19.4% being overweight. The national prevalence of hypertension in blacks was 24.4%, using the cut-off point of 140/90 mmHg. There are limited data on the population's physical activity patterns. However, the effects of the HIV/AIDS epidemic will become increasingly important. Conclusions: The increasing emergence of NCDs in black South Africans, compounded by the HIV/AIDS pandemic, presents a complex picture for health workers and policy makers. Increasing emphasis needs to be placed on healthy lifestyles.
High-resolution imaging of the anomalous flux ratio gravitational lens system CLASS B2045+265: dark or luminous satellites ?

The existence of flux ratio anomalies between fold and cusp images in galaxy-scale strong-lens systems has led to an interpretation based on the presence of a high mass fraction of cold dark matter (CDM) substructures around galaxies, as predicted by numerical N-body simulations. These substructures can cause large perturbations of the image magnifications, leading to changes in the image flux ratios. The flux ratio anomaly is particularly evident in the radio-loud quadruple gravitational lens system CLASS B2045+265. In this paper, new high-resolution radio, optical and infrared imaging of B2045+265 is presented which sheds more light on this anomaly and its possible causes. First, deep Very Long Baseline Array observations show very compact images, possibly with a hint of a jet, but with no evidence for differential scattering or scatter broadening. Hence, the flux ratio anomaly is unlikely to be caused by refractive scattering in either the Milky Way or the lens galaxy. Secondly, optical and infrared observations with the Hubble Space Telescope and through adaptive optics imaging with the W. M. Keck Telescope, show a previously undiscovered object - interpreted as a (tidally disrupted) dwarf satellite based on its colours and slight extension - between the main lens galaxy and the three anomalous flux ratio images. Thirdly, colour variations in the early-type lens galaxy indicate recent star formation, possibly the result of secondary infall of gas-rich satellites. A population of such galaxies around the lens system could explain the previously discovered strong [O II] emission. However, spiral structure and/or normal star formation in the lens galaxy cannot be excluded. In light of these new data, we propose a lens model for the system, including the observed dwarf satellite, which reproduces all positional and flux ratio constraints, without the need for additional CDM substructure. Although the model is peculiar in that the dwarf galaxy must be highly flattened, the model is very similar to recently proposed mass models based on high-order multipole expansions.
Scene retrieval by unsupervised salient part discovery

While bag-of-words (BoW) scene descriptor has been widely used for scene retrieval applications, the BoW descriptor alone often fails to capture local details of a scene and produces poor results. In this paper, we address this issue by a simple effective approach, “un-supervised salient part discovery”, in which a set of salient parts are discovered via scene parsing and used as additional queries for the scene retrieval. Further, we also address the issue of discovering salient parts in a scene, and present a solution that provides similar parts for similar scenes. Multiple ranking results from the individual part queries are then integrated into a final ranking result by adopting an unsupervised rank fusion technique. Experimental results using challenging scene dataset validate the effectiveness of our approach.
Hierarchical Approach to Data Extraction using UML 2 . 0

The concept of data warehousing includes different algorithms and tools for combining data from multiple sources into a single repository called data warehouse. Various ETL tools are used to extract the data from these multiple sources. The paper proposes an object oriented approach to model the process of data extraction as part of extraction, transformation and loading process. The hierarchies of each data element can be explicitly defined, thus highlighting the data granularity and hence simplifying the data extraction process. A case study to illustrate the concept has been depicted using University Management System. The approach has been modelled using Unified Modelling Language 2.0. University Management system has been used as a case study to illustrate this modelling concept.
Finding authoritative people from the Web

Today's Web is so huge and diverse that it arguably reflects the real world. For this reason, searching the Web is a promising approach to find things in the real world. We present NEXAS, an extension to Web search engines that attempts to find real-world entities relevant to a topic. Its basic idea is to extract proper names from the Web pages retrieved for the topic. A main advantage of this approach is that users can query any topic and learn about relevant real-world entities without dedicated databases for the topic. In particular, we focus on an application for finding authoritative people from the Web. This application is practically important because once personal names are obtained; they can lead users from the Web to managed information stored in digital libraries. To explore effective ways of finding people, we first examine the distribution of Japanese personal names by analyzing about 50 million Japanese Web pages. We observe that personal names appear frequently on the Web, but the distribution is highly influenced by automatically generated texts. To remedy the bias and find widely acknowledged people accurately, we utilize the number of Web servers containing a name instead of the number of Web pages. We show its effectiveness by an experiment covering a wide range of topics. Finally, we demonstrate several examples and suggest possible applications.
A Theoetical Aspect of a Stochastic Sketching Method for Global Optimization

In this paper, we propose Stochastic Sketching method for global optimization based on the simulation of human behavior. Stochastic Sketching models the thought process and strategies of human beings and applying the artificial model to problems. We introduce and discuss concepts and components essential to Stochastic Sketching in detail, including the sampling guide, zooming controller, sketching model, precision threshold, and satisfaction probability. The mathematical foundations of Stochastic Sketching are discussed and a preliminary theoretical base is presented.
Drop breakup in three-dimensional viscous flows

A new three-dimensional boundary integral algorithm is presented that is capable of simulating the process of drop breakup in viscous flows. The surface discretization is fully adaptive, thus providing accurate resolution of the highly deformed drop shapes that are characteristic of breakup events. Our algorithm is used to study drop breakup in shear flow and in buoyancy; the predictions are compared with experimental observations.
Evaluation of the pharmacokinetics and pharmacodynamics of ticagrelor co-administered with aspirin in healthy volunteers

The results of two independent, randomized, two-period crossover, single-center studies, conducted to assess the pharmacokinetics of ticagrelor ± aspirin, inhibition of platelet aggregation (IPA) with ticagrelor/aspirin vs. clopidogrel/aspirin, and safety, tolerability, and bleeding times are reported here. In Study A (open-label), 16 volunteers received ticagrelor (50 mg bid Days 1–5; 200 mg bid Days 6–9; one 200 mg dose on Day 10) ± 300 mg qd aspirin (Days 1–10). In Study B (double-blind, double-dummy), 16 volunteers received aspirin (300 mg loading dose/75 mg qd Days 2–9) with either ticagrelor (200 mg bid Days 4–8, one 200 mg dose on Day 9) or clopidogrel (300 mg loading dose Day 4, 75 mg qd Days 5–9). At steady-state ticagrelor (50 mg bid, or 200 mg bid), concomitant aspirin (300 mg qd) had no effect on mean maximum plasma concentration (Cmax), median time to Cmax (tmax), or mean area under the plasma concentration-time curve for the dosing interval (AUC0–τ) for ticagrelor and its primary metabolite, AR-C124910XX. Following 200 mg bid ticagrelor, mean Cmax and AUC0–τ for both parent and metabolite were comparable with co-administration of aspirin at 75 mg and 300 mg qd. Aspirin (300 mg qd) had no effect on IPA (ADP-induced) by ticagrelor. However, aspirin and ticagrelor had an additive effect on IPA (collagen-induced). Ticagrelor/aspirin increased bleeding times vs. baseline. Ticagrelor/aspirin co-administration was well tolerated at all dose combinations evaluated. In summary, the findings of this study demonstrate that co-administration of aspirin (300 mg qd) with ticagrelor (50 mg bid, or 200 mg bid) had no effect on ticagrelor pharmacokinetics or IPA (ADP-induced) by ticagrelor.