self-monitoring reading of implicit contents and moral of self

The research concerns self-monitoring psychological processes and aims to verify two hypothesises: that there is difference in the theories on Self in HSM and LSM, and that the HSMs are more able implicit readers than the LSMs. The 18 item SMS was administered to 86 people, who had also undergone the implicit reading test. HSM and LSM were then thoroughly studied with further implicit reading trials and by means of dilemmas intended to explore their implicit theories of self. The HSMs read more implicits, in a livelier way, and with less fatigue. The dilemmas show differences in the structure of the self and above all in the moral conviction of self.

A deep learning pipeline for product recognition on store shelves

Recognition of grocery products in store shelves poses peculiar challenges. Firstly, the task mandates the recognition of an extremely high number of different items, in the order of several thousands for medium-small shops, with many of them featuring small inter and intra class variability. Then, available product databases usually include just one or a few studio-quality images per product (referred to herein as reference images), whilst at test time recognition is performed on pictures displaying a portion of a shelf containing several products and taken in the store by cheap cameras (referred to as query images). Moreover, as the items on sale in a store as well as their appearance change frequently over time, a practical recognition system should handle seamlessly new products/packages. Inspired by recent advances in object detection and image retrieval, we propose to leverage on state of the art object detectors based on deep learning to obtain an initial productagnostic item detection. Then, we pursue product recognition through a similarity search between global descriptors computed on reference and cropped query images. To maximize performance, we learn an ad-hoc global descriptor by a CNN trained on reference images based on an image embedding loss. Our system is computationally expensive at training time but can perform recognition rapidly and accurately at test time

Learning Features that Predict Cue Usage

Our goal is to identify the features that predict the occurrence and placement of discourse cues in tutorial explanations in order to aid in the automatic generation of explanations. Previous attempts to devise rules for text generation were based on intuition or small numbers of constructed examples. We apply a machine learning program, C4.5, to induce decision trees for cue occurrence and placement from a corpus of data coded for a variety of features previously thought to affect cue usage. Our experiments enable us to identify the features with most predictive power, and show that machine learning can be used to induce decision trees useful for text generation.Comment: 10 pages, 2 Postscript figures, uses aclap.sty, psfig.te

Progettazione di un LNA nella banda 1.8-2.2 GHz con tecnologia CMOS 0.12um

The subject of this work is a low noise amplifier (LNA), operating in the frequency range 1.8 – 2.1 GHz. The CMOS 0.12 μm is used in respect to the low cost of the final device. Among the specifications, a variable gain and an adjustable working frequency are required. In particular, four different working modes are provided: 1.8, 1.9 and 2.1 GHz high gain and 2.1 GHz low gain. The amplifier is designed to be used as the first stage of a receiver for mobile telephony. For this reason a low power consumption is taken into consideration (low supply voltage and low drain currents). In order to obtain a good input impedance matching in all the four operating modes, a circuital topology is chosen, that allows the use of a single external matching network, realized with standard passive components (E12 standard). Moreover, a LC-resonating load is used to maximize the gain at the working frequency and for its band-pass behavior, useful in our case. All the simulations are performed taking into account the parasitic effects of the input pads and of the bond wires, since they have a great influence on the input impedance of the LNA. A simple digital circuit, integrated on-chip, is used to select the operating mode of the LNA by means of two input pins. In conclusion a layout of the amplifier is realized: particular attention is paid into reducing the parasitic resistance of the metal interconnections in order to minimize the noise. A very good 1 dB Noise Figure is obtained. ---------------------------------------------- Oggetto di questo lavoro è un amplificatore a basso rumore (LNA), funzionante a frequenze comprese tra 1,8 e 2,1 GHz. La tecnologia utilizzata è CMOS a 0.12 μm, la quale consente notevoli vantaggi dal punto di vista del costo del dispositivo finale. Tra le specifiche sono richieste la possibilità di scegliere il livello di guadagno e la frequenza di funzionamento desiderate. In particolare sono previste quattro differenti modalità operative: alto guadagno, alle frequenze di 1,8, 1,9 e 2,1 GHz e basso guadagno alla frequenza di 2.1 GHz. L’amplificatore è progettato per essere utilizzato a monte di un ricevitore per dispositivi di telefonia mobile portatili (telefoni cellulari). Per questo motivo si è prestata attenzione alla riduzione dei consumi (bassa tensione di alimentazione e ridotta corrente assorbita). Al fine di ottenere un buon adattamento di impedenza d’ingresso in ognuna delle quattro modalità di funzionamento è stata scelta una soluzione circuitale che consente l’uso di una singola rete esterna, realizzata con componenti passivi in standard E12. Inoltre è stato scelto un tipo di carico LC risonante per esaltare il guadagno in un intorno della frequenza selezionata e per il suo comportamento passa-basso, vantaggioso nel nostro caso. Tutte le simulazioni svolte tengono in considerazione gli effetti parassiti dovuti ai pad di ingresso e alle interconnessioni tra pin e pad, in quanto questi danno un contributo notevole all’impedenza d’ingresso del circuito. Un semplice circuito digitale integrato sullo stesso chip consente di selezionare il modo operativo dell’LNA tramite due appositi pin. Infine è stato realizzato un layout dell’amplificatore con accorgimenti per ridurre il rumore dovuto alle resistenze parassite delle interconnessioni. È stata ottenuta una cifra di rumore finale di solo 1 dB

Means of a Dirichlet process and multiple hypergeometric functions

The Lauricella theory of multiple hypergeometric functions is used to shed some light on certain distributional properties of the mean of a Dirichlet process. This approach leads to several results, which are illustrated here. Among these are a new and more direct procedure for determining the exact form of the distribution of the mean, a correspondence between the distribution of the mean and the parameter of a Dirichlet process, a characterization of the family of Cauchy distributions as the set of the fixed points of this correspondence, and an extension of the Markov-Krein identity. Moreover, an expression of the characteristic function of the mean of a Dirichlet process is obtained by resorting to an integral representation of a confluent form of the fourth Lauricella function. This expression is then employed to prove that the distribution of the mean of a Dirichlet process is symmetric if and only if the parameter of the process is symmetric, and to provide a new expression of the moment generating function of the variance of a Dirichlet process.Comment: Published by the Institute of Mathematical Statistics (http://www.imstat.org) in the Annals of Probability (http://www.imstat.org/aop/) at http://dx.doi.org/10.1214/00911790400000027

Goals and Actions in Natural Language Instructions

Human agents are extremely flexible in dealing with Natural Language instructions: they are able both to adapt the plan they are developing to the input instructions, and vice versa, to adapt the input instructions to the plan they are developing. Borrowing the term from [Lewis 1979], I call this two-way adaptation process accommodation. In this proposal, I first define accommodation in the context of processing instructions. I then provide evidence for the particular inferences I advocate, and for the further claim that such inferences are directed by the goal to achieve which certain action is performed. The evidence I provide comes from my analysis of naturally occurring instructions, and in particular of purpose clauses and of negative imperatives. Finally, I propose a computational model of instructions able to support accommodation inferences. Such model is composed of: a speaker / hearer model of imperatives, based on the one presented in [Cohen and Levesque 90]; an action representation formalism based on a hybrid system, á la KRYPTON [Brachman et al. 1983a], whose primitives are those proposed in [Jackendoff 1990]; and inference mechanisms that contribute to building the structure of the intentions that the agent develops while interpreting instructions

Mexican Working-Class Literature, or The Work of Literature in Mexico

Working-class literature has never had a wide audience in Mexico, always overshadowed by other types of literature, such as the novel of the Mexican Revolution, the regionalist novel, and the indigenous novel. Nevertheless, there is no better place, as this chapter will suggest, to consider the status of literature and its relationship to history and ideology than from the genre of work and the worker. Approaching working-class literature as an evolving genre in relation to different modernization projects, this chapter will map out similarities and point to differences between various labor literatures—including proletarian literature in the 1930s, the testimonio (a new type first-person documentary genre) in the 1960s, and the literatures of the early 2000s—in order to argue ultimately that the genre provides a privileged space to think about labor and exploitation in Mexico