Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification in Differentiated Products Markets Using Market Level Data

We present new identification results for nonparametric models of differentiated products markets, using only market level observables. We specify a nonparametric random utility discrete choice model of demand allowing rich preference heterogeneity, product/market unobservables, and endogenous prices. Our supply model posits nonparametric cost functions, allows latent cost shocks, and nests a range of standard oligopoly models. We consider identification of demand, identification of changes in aggregate consumer welfare, identification of marginal costs, identification of firms' marginal cost functions, and discrimination between alternative models of firm conduct. We explore two complementary approaches. The first demonstrates identification under the same nonparametric instrumental variables conditions required for identification of regression models. The second treats demand and supply in a system of nonparametric simultaneous equations, leading to constructive proofs exploiting exogenous variation in demand shifters and cost shifters. We also derive testable restrictions that provide the first general formalization of Bresnahan's (1982) intuition for empirically distinguishing between alternative models of oligopoly competition. From a practical perspective, our results clarify the types of instrumental variables needed with market level data, including tradeoffs between functional form and exclusion restrictions.
The interaction of source-generated spherical waves with an elastic plate immersed in acoustic fluid

The interaction of acoustic waves generated by a point source with an elastic plate immersed in acoustic fluid is considered. To estimate the range of applicability of various theoretical approaches, a hierarchy of mathematical and computer models has been developed. The models differ in the governing equations for the sounded elastic laminate structure (from a simplified Kirchhoff-Love plate to a multi-layered anisotropic composite plate obeying the full set of 3D Navier-Lamé equations in each sublayer). Explicit integral representations for generated and scattered wave fields have been derived using the Fourier transform technique. In the far-field, the acoustic and guided waves are described by asymptotic representations obtained from those integrals using the stationary phase method and the residual technique. Among others, the derived solutions enable quantitative analysis of time-averaged wave energy fluxes in the considered source-structure system. Analytic representations for the total source energy and its portions carried by reflected, transmitted and guided waves have also been obtained.
Beat Tracking based on Multiple-agent Architecture A Real-time Beat Tracking System for Audio Signals w

This paper presents an application of multiple-agent architecture to beat tracking for musical a~oustic signals. Beat tracking is an important initial step in computer understanding of music and is useful in various multimedia applications. Most previous beat-tracking systems dealt with MIDI signals and were not based on a multiple-agent architecture. Our system can recognize, in real time, temporal positions of beam in real-world audio signals that contain sounds of various instruments. Our application of multiple-agent architecture enables the system to handle ambiguous situations in interpreting real-world input signals and to examine multiple hypotheses of beat positions in parallel. Even if some agents lose track of the beat. other agents will maintain the correct hypothesis. Each agent is able to interact with other agents to track beats cooperatively, and self-evaluate the reliability of its hypothesis on the basis of the current input situation, and adapt to the current situation in order to maintain the correct hypothesis. These agents have been implemented on different processing element~ in a parallel computer. Our experimental results show that the system is robust enough to handle audio signals sampled fnml commercially distributed compact discs of popular songs.
Optical Packet Header Processing Using Time-to-Wavelength Mapping in Semiconductor Optical Amplifiers

A new approach for optical packet header processing based on a time-to-wavelength converter is proposed. The processing is composed of transferring, through an all-optical and-gate, the header data bits into the successive single optical pulses at different wavelengths. The and-gate is performed by the semiconductor optical amplifier (SOA) and makes use of either cross-polarization modulation or four-wave mixing (FWM). Both implementations are compared. In order to improve the scalability of the design and to overcome the polarization sensitivity of the FWM solution, we propose the use of a spectrum-sliced incoherent light in generating the wavelength bits. The FWM process in this specific case is studied. The 10-Gb/s demonstrations of the various elements are presented.
Designing Search Tasks for Archive Search

Longitudinal corpora like legal, corporate and newspaper archives are of immense value to a variety of users, and time as an important factor strongly influences their search behavior in these archives. While many systems have been developed to support users' temporal information needs, questions remain over how users utilize these advances to satisfy their needs. Analyzing their search behavior will provide us with novel insights into search strategy, guide better interface and system design and highlight new problems for further research. In this paper we propose a set of search tasks, with varying complexity, that IIR researchers can utilize to study user search behavior in archives. We discuss how we created and refined these tasks as the result of a pilot study using a temporal search engine. We not only propose task descriptions but also pre and post-task evaluation mechanisms that can be employed for a large-scale study (crowdsourcing). Our initial findings show the viability of such tasks for investigating search behavior in archives.
Handling query answering in crowdsourcing systems: A belief function-based approach

Crowdsourcing is defined as an emerging computation paradigm, where the power of crowds is utilized to facilitate large scale tasks that are costly or time consuming with traditional methods. One of the most important technical challenges of crowdsourcing is quality control of workers' responses. Human factors play a key role in achieving high quality answers in crowdsourcing-based solving tasks. The most major factor is pertained to the uncertainty of workers about the responses that they provide to resolve the task at hand. On the other hand, workers may have diverse levels of expertise and skill. It is then important to take into account both the degrees of uncertainty and expertise to return the most correct reliable answer. In this paper, we propose a belief functions-based approach to achieve this goal. We conduct also some comprehensive experiments to validate the effectiveness of our proposal.
PAID I FEATURE AND SCORE LEVEL COMBINATION OF SUBSPACE GAUSSIANS IN LVCSR TASK

In this paper, we investigate employment of discriminatively trained acoustic features modeled by Subspace Gaussian Mixture Models (SGMMs) for Rich Transcription meeting recognition. More specifically, first, we focus on exploiting various types of complex features estimated using neural network combined with conventional cepstral features and modeled by standard HMM/GMMs and SGMMs. Then, outputs (word sequences) from individual recognizers trained using different features are also combined on a score-level using ROVER for the both acoustic modeling techniques. Experimental results indicate three important findings: (1) SGMMs consistently outperform HMM/GMMs (relative improvement on average by about 6% in terms of WER) when both techniques are exploited on single features; (2) SGMMs benefit much less from feature-level combination (1% relative improvement) as opposed to HMM/GMMs (4% relative improvement) which can eventually match the performance of SGMMs; (3) SGMMs can be significantly improved when individual systems are combined on a score-level. This suggests that the SGMM systems provide complementary recognition outputs. Overall relative improvements of the combined SGMM and HMM/GMM systems are 21% and 17% respectively compared to a standard ASR baseline.
Walking as a Contributor to Physical Activity in Healthy Older Adults: 2 Week Longitudinal Study Using Accelerometry and the Doubly Labeled Water Method

Background Physical activity is recommended to promote healthy aging. Defining the importance of activities such as walking in achieving higher levels of physical activity might provide indications for interventions. Objective To describe the importance of walking in achieving higher levels of physical activity in older adults. Methods The study included 42 healthy subjects aged between 51 and 84 years (mean body mass index 25.6 kg/m2 [SD 2.6]). Physical activity, walking, and nonwalking activity were monitored with an accelerometer for 2 weeks. Physical activity was quantified by accelerometer-derived activity counts. An algorithm based on template matching and signal power was developed to classify activity counts into nonwalking counts, short walk counts, and long walk counts. Additionally, in a subgroup of 31 subjects energy expenditure was measured using doubly labeled water to derive physical activity level (PAL). Results Subjects had a mean PAL of 1.84 (SD 0.19, range 1.43-2.36). About 20% of the activity time (21% [SD 8]) was spent walking, which accounted for about 40% of the total counts (43% [SD 11]). Short bouts composed 83% (SD 9) of walking time, providing 81% (SD 11) of walking counts. A stepwise regression model to predict PAL included nonwalking counts and short walk counts, explaining 58% of the variance of PAL (standard error of the estimate=0.12). Walking activities produced more counts per minute than nonwalking activities (P<.001). Long walks produced more counts per minute than short walks (P=.001). Nonwalking counts were independent of walking counts (r=−.05, P=.38). Conclusions Walking activities are a major contributor to physical activity in older adults. Walking activities occur at higher intensities than nonwalking activities, which might prevent individuals from engaging in more walking activity. Finally, subjects who engage in more walking activities do not tend to compensate by limiting nonwalking activities. Trial Registration ClinicalTrials.gov NCT01609764; https://clinicaltrials.gov/ct2/show/NCT01609764 (Archived by WebCite at http://www.webcitation.org/6grls0wAp)
A 2D-DCT Image Processing in Matlab and Voice Informatics Based Remote Home Monitoring and Security System

This paper proposes, designs and constructs an image recognition & voice technology based security system by highlighting the advantages of image processing technology and voice synthesis technology which are presence in the electronic market. This paper mainly approaches towards enhanced security by checking the tag image of the operator as well as recognizing voice which are validated previously by this system just using simply a web-camera or closed circuit television (CCTV) camera and a voice recording software system and gives the signal in terms of alarm, Alert Light, message via global system for mobile communication (GSM)/ general packet radio service (GPRS) to the consumer mobile number/the nearest police station’s mobile number.
One-loop effective brane action

The one-loop effective action for a p brane embedded in a D = p+2 Minkowski spacetime in the static gauge is calculated. Rescaling the quantum fluctuation by (−g0)1/2 evaluated on the background brane leads to the one-loop effective action expressed only in terms of infrared and ultraviolet divergent geometric scalars. After the infrared divergences are absorbed into the quantum fluctuation, there remains the finite number of ultraviolet divergences. This implies that the D = p+2 Poincare symmetry and the D = p+1 general coordinate invariance are preserved in one-loop order.
THE MENTAL SYMPTOMS OF MULTIPLE SCLEROSIS

The mental symptoms of multiple sclerosis are of several types, and different writers stress different symptoms. Some describe the euphoric cases, others cases accompanied by dementia, while still others center their attention on the occasional episodes of depression, the delusions and hallucinations. A cursory view of the subject shows that in multiple sclerosis there is not a consistent group of symptoms. We are quite unprepared to state the incidence of mental symptoms in multiple sclerosis. However, including euphoria, probably in 90 per cent. of cases there are mental alterations which warrant the term "mental symptoms. " Because they are overshadowed by physical symptoms and are so often of a character to introduce no element of alarm, they are frequently disregarded. Then, too, the physical condition makes the patient inapt in all his physical undertakings and renders him psychiatrically nonpotential, even in those instances in which unhampered psychotic tendencies would otherwise bring
Unconscious sequences in child protection work: case studies of professionals' experiences of child removal

This article examines two case studies from the author's supervision of professionals in a therapeutic setting in child protection, in circumstances where children were removed from the care of parents. Psychoanalytic ideas about the unconscious and the systemic notion of sequences are used in an analysis of the personal responses of the involved frontline professionals and the author. Particular attention is paid to the concepts of transference, counter transference, projection, repression and containment. The author argues that reflection using these ideas served a function of emotional containment for the professionals and supported complex connections with and understandings of the parents' responses and behaviour. Links are made between the analysis of these two case studies and current broader thinking about anxiety in child-protection systems and practice.
Hybrid weighted random forests for classifying very high-dimensional data

Random forests are a popular classification method based on an ensemble of a single type of decision trees from subspaces of data. In the literature, there are many different types of decision tree algorithms, including C4.5, CART, and CHAID. Each type of decision tree algorithm may capture different information and structure. This paper proposes a hybrid weighted random forest algorithm, simultaneously using a feature weighting method and a hybrid forest method to classify very high dimensional data. The hybrid weighted random forest algorithm can effectively reduce subspace size and improve classification performance without increasing the error bound. We conduct a series of experiments on eight high dimensional datasets to compare our method with traditional random forest methods and other classification methods. The results show that our method consistently outperforms these traditional methods.
What happens during those long hours next to the road? An exploratory study of three informal day labour hiring sites in Tshwane

Valenzuela (2002) calls people who congregate at informal pick-up points to seek for work for the day, by the hour or for a specific job, day labourers and the pick-up points hiring sites. These hiring sites are described as open-air geographical locations, such as street corners, pavements, car parking lots and factory gates (Blaauw, 2010), where day labourers seek employment (Valenzuela, 2003). Day labourers and the hiring sites appear to be a growing feature in South Africa and in many parts of the world. For example, in Japan in 1998 the number of day labourers who gathered at hiring sites was estimated to be as high as 1.26 million and in the USA the number of day labourers doubled from 1995, being estimated at 117 000 in 2004 (Gill, 2001:2; Grow, 2003:5; Louw, 2007:99).
Sharma, Shilpi and Woolfson, Lisa and Hunter, Simon C. (2014) Maladaptive cognitive appraisals in children with high-functioning autism : associations with fear, anxiety and theory of mind. Autism

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Improving software assurance using lightweight static analysis

Software assurance is of paramount importance given the increasing impact of software on our lives. This dissertation describes research that explores two techniques to improve software assurance: a runtime approach in the context of host-based misuse detection systems (MDSs) and a compile-time approach to detect unknown software defects. Host-based MDSs attempt to identify attacks by discovering program behaviors that deviate from expected patterns. We focus on automated and conservative misuse detection techniques. We present a static analysis algorithm for constructing a flow- and context-sensitive model of a program that allows for efficient real-time detection. Context-sensitivity is essential to reduce the number of impossible control-flow paths accepted by a MDS because such paths provide opportunities for attackers to evade detection. Our inlined automaton model presents an acceptable tradeoff between accuracy and performance in our experiments. Static and dynamic approaches have been proposed over the years to detect security vulnerabilities. These approaches assume that the signature of a defect is known a priori. A greater challenge is detecting defects whose signatures are not known a priori---unknown software defects. We propose a general approach for detection of unknown defects. Software defects are discovered by applying data-mining techniques to pinpoint deviations from common program behavior in the source code and using statistical techniques to assign significance to each such deviation. We discuss the implementation of our tool, FaultMiner, and illustrate the power of the approach by inferring two types of security properties on four widely-used programs.
Towards adaptive, scalable, and reliable resource provisioning for wsrf-compliant applications

Although WSRF (Web Services Resource Framework) and Java-based hosting environment have been successful in dealing with the heterogeneity of resources and the diversity of applications, the current Grid middleware has several limitations to support on-demand resource provisioning effectively. This paper proposes DynaGrid, a new framework for WSRF-compliant applications. Many new components, such as Service Door, Dynamic Service Launcher (DSL), Client Proxy, and Partition Manager, have been introduced to offer adaptive, scalable, and reliable resource provisioning. All of these components are implemented as standard WSRF-compliant Web services, hence DynaGrid is complementary to the existing Grid middleware. The experimental evaluations are performed on a real test bed with practical applications including the Map Reduce application. The results indicate that DynaGrid effectively utilizes Grid resources by allocating only the required number of resources adaptively according to the amount of incoming requests, providing both the scalability and the reliability at the same time.
A Delayed Discrete Model and Control for Malaria Transmission

A discrete mathematical model with time delays for the transmission of malaria is established. The basic reproductive number R0 of the model is defined. Numerical simulations are given to show that the disease free equilibrium is stable when R0<1 and the unique positive equilibrium is locally asymptotically stable when R0>1. The elasticity of the basic reproductive number with respect to each parameters is calculated respectively. According to the practical meaning of the parameters, we find that decreasing the bites of a single mosquito on human per day is the better theoretical control measure at present.
Application-aware group scheduler for Android

Modern multi-core processors propose new cache management challenges (more cache conflicts and misses) due to the subtle interactions of simultaneously executing processes sharing on-chip resources. To address this issue, thread group scheduling scheme that cluster threads with high sharing cache as one group to schedule has been proposed. It has led to numerous academic and industrial attentions. However, by analyzing the programming model of Android which account for a large and increasing fraction of operating system of multi-core smart phones, we find it may be unacceptable for numerous interactive applications since previous scheduling works may cause the terrible response time and directly bring an awful user experience. In order to reduce cache competitions while improving application's response time, we present an application-aware group scheduler (AGS) whose key idea is to adopt a thread group scheduling scheme to partition current running application's threads into one group and give each thread a fair chance to occupy CPU time. We implement AGS on practical hardware running a real Android operating system. The results show that our proposed scheduler can improve performance from different parameters while keeping system fairness, which reduces 3.2% in cache miss rate, 5.5% in response time, 5.3% in data cache (D-Cache) misses and 2.5% in instruction cache (I-Cache) misses to the maximum extent.
Flying-Capacitor-Based Hybrid LLC Converters With Input Voltage Autobalance Ability for High Voltage Applications

An advanced hybrid LLC series resonant converter with integrated flying-capacitor cell is proposed in this paper to enable the high step-down conversion in the high input voltage applications. The inherent flying-capacitor branch in the primary side can effectively halve the primary switch voltage stress compared with the half-bridge LLC converters. And the input voltage can be shared equally and automatically between the two series half-bridge modules without additional balance circuit or control strategies due to the built-in flying-capacitor cell. Moreover, the inherent soft switching performance during wide load range that exists in the LLC converters is still kept to reduce the switching losses, which ensures the high efficiency. Besides, the proposed converter can be extended to further decrease the switch voltage stress by employing stacked connection. Finally, a 500 ~ 640 V-input 48 V-output 1 kW prototype is built and tested to verify the effectiveness of the proposed converter. The results prove that the proposed converter is an excellent candidate for the high input voltage and high step-down dc/dc conversion systems.
“Not Blending In”

This article reports the findings of a study on the experiences of a small but growing population of Latino students in a small-town secondary school. All teachers and administrators were surveyed regarding their impressions of Latino students. All students in the school (95% White, 5% Latino) were surveyed regarding their impressions of ethnicity, culture, and language in their own school experiences. In all, 26 adults, 25 of whom were White, and 800 students participated in the surveys. Ethnographic data augment survey findings. White students responded more positively than did Latino students, with more positive thoughts about the school and their own experiences in the school, for every survey question. Responses of White school personnel are contrasted to those of the only Latino teacher.