Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulating Pareidolia of Faces for Architectural Image Analysis

The hypothesis of the present study is that features of abstract face-like patterns can be perceived in the archi- tectural design of selected house facades and trigger emo- tional responses of observers. In order to simulate this phe- nomenon, which is a form of pareidolia, a software system for pattern recognition based on statistical learning was ap- plied. One-class classification was used for face detection and an eight-class classifier was employed for facial ex- pression analysis. The system was trained by means of a database consisting of 280 frontal images of human faces that were normalised to the inner eye corners. A separate set of test images contained human facial expressions and selected house facades. The experiments demonstrated how facial expression patterns associated with emotional states such as surprise, fear, happiness, sadness, anger, disgust, contempt or neutrality could be identified in both types of test images, and how the results depended on preprocessing and parameter selection for the classifiers.
Best practice in event studies in marketing

Event study methodology is used to assess the financial impact of firm decisions. This article examines 14 event studies in marketing published between 2000 and 2005 in order to better understand what theoretical and research design issues are problematic for marketing researchers. While most of the studies reported adequately on the key steps followed in their research design, a number of studies failed to report checks for confounding effects or to provide adequate theoretical explanations of the abnormal returns detected. Many of the articles did not include the names of the firms and the event dates examined in the event study making it difficult for researchers to replicate and extend these studies in the future. By addressing these important issues, researchers and journal editors can ensure that event study findings published in the future may be interpreted with confidence in their design and execution.
Learning harmonic changes for musical style modeling

In this project I created a system capable of performing statistical learning of the harmonic changes present in musical pieces. For that, musical pieces must be pre-processed and normalized, so that the obtained harmonies are key-independent. Once learning has been done, new harmonic sequences can be generated and analyzed, to better understand what exactly the system learns (and how). The results of several experiments show that the system is able to correctly normalize harmonies and produce realistic new sequences, but I believe additional work would really help in improving its correctness and capabilities. Nevertheless, our current system has achieved its goals of converting “raw music scores” onto harmonic sequences, and capturing some of the structure of these sequences. It could be used as a solid basis for any future work dealing with NLP techniques applied to musical composition.
IIB Matrix Model

We review our proposal for a constructive definition of superstring, type IIB matrix model. The IIB matrix model is a manifestly covariant model for space-time and matter which possesses N=2 supersymmetry in ten dimensions. We refine our arguments to reproduce string perturbation theory based on the loop equations. We emphasize that the space-time is dynamically determined from the eigenvalue distributions of the matrices. We also explain how matter, gauge fields and gravitation appear as fluctuations around dynamically determined space-time.
New Features from Fourier Spectrum for Induction Machine Broken Bar Detection Using Statistical Pattern Recognition

A fault diagnosis system based on pattern recognition techniques is developed for cage induction machine broken bar detection. The developed algorithm uses the stator current and, if available, motor speed as input data. Several features are extracted from the Frequency spectrum of the current signal derived using the Fast Fourier Transform. The relevance of the features for the purpose of fault detection is investigated and verified. Statistical pattern recognition techniques namely the Bayes Minimum Error classifier is applied to distinguish motors with broken rotor bars from healthy ones. A series of experiments using a three phase 3 hp cage induction machine performed in different load and fault conditions is used to provide data for training and then testing the classifier. Experimental results confirm the ability of the proposed algorithm for detection of broken bar faults. Key-Words: Fault diagnosis, Broken bar, Induction machine, Feature extraction, Pattern recognition
The Measurement of Household Liabilities: Conceptual Issues and Practice

An electrical conductive pattern is deposited on the surface of a frame constituting an integrated circuit carrier. To enable leads extending from an integrated circuit package to come in contact with the electrical conductive pattern, a plurality of first contact portions are formed on the inner end of the electrical conductive pattern. In addition, to enable a plurality of contact pieces extending from an integrated circuit socket to come in contact with the conductive pattern, a plurality of second contact portions are formed on the outer end of the electrical conductive pattern. Thus, the leads extending from the integrated circuit package are reliably brought into electrical contact with the contact pieces via the first contact portions, the electrical conductive pattern and the second contact portions. The arrangement of the electrical conductive pattern in that way makes it possible that the leads can be spaced from each other at an interval smaller than an interval between adjacent contact pieces.
On Romance Past Participle Agreement and Its Challenges

Past participle agreement (PPA) in Western Romance is fairly uniform phenomenon. Despite this, it does display cross-linguistic differences that have not yet been adequately explained in the linguistic literature of the past 30+ years. Many investigations have attempted to tie the general phenomenon to Spec-Head agreement as well as to PF conditions on the morphophonological realization of agreement. Despite these attempts, none can handle the oftcited difference between Italian and French, dating back to Cinque (1975): Italian direct object wh-phrases (wh-DOs) do not trigger PPA, while French ones do. In this thesis, I explore the facts and generalizations in the PPA data more deeply, providing an exploratory yet thorough investigation of the areas in which PPA occurs as well as an investigation of the properties of the direct object clitics (DO-clitics) and partitive clitics in these Romance languages. In doing so, I evaluate some of the options that may eventually lead to a satisfactory explanation of crosslinguistic PPA patterns. This thesis is broken down into 3 main parts. The first part is a presentation of the data regarding PPA patterns with DO-clitics and partitive clitics in 3-5 of the major Western Romance languages (Italian, French, Catalan, Spanish, and Portuguese). Intriguing patterns show up, especially with respect to the presence, absence, and optionality of PPA and its relation to specificity and person-distinctions. The remainder of the first part details properties of the relevant clitics under Dechaine and Wiltschko (2002)’s pronominal typology. The second part and half of the third part are derived from a previous paper of mine, which examined two existing PPA analyses and detailed an analysis of my own. The other half of the third part explores a few more options for an explanation of PPA patterns. At the end of this thesis, I leave the reader with many future research questions as well as a plethora of linguistic data from which a future solution to the question of why PPA patterns differ may find its beginnings. On Romance Past Participle Agreement and Its Challenges 3
Disparities in Incomes and Prices Internationally

The dispersion of the distribution of relative prices in poor countries is substantially higher than that in the rich. As in 130+ countries relative prices are closely related to incomes, we develop a model that shows that the prices of luxuries (necessities) rise (fall) with income growth. This model provides a link between price dispersion and incomes that leads to several interesting concepts, including minimum-variance income and dispersion-equivalent income, the income needed to compensate for higher dispersion, which are illustrated with data from the International Comparison Program. The paper also contains an analysis of the welfare cost of higher dispersion in poorer countries.
Keyewai: Looking at Cooperation in a Holographic Projection Screen

Keyewai: Last Meal is an innovative two-player computer game for a holographic projection screen, using eye gaze and gamepad controllers as input. We explore the affordances given by our interaction setup by creating game mechanics (like controllable transparency and reversed instructions) that foster cooperation between players. This multi-modal co-located interaction scheme allows for a novel playing experience with face-to-face social interaction, allowing players to communicate with facial expressions and body movement to create a more immersive interaction environment.
A Novel Probabilistic Approach to Modeling the Pleasure-Arousal-Dominance Content of the Video based on "Working Memory"

The rapid growth of digital video information nowadays is making video content classification and indexing tools a necessity. Little research efforts have been invested on content classification solutions based on the emotional content of the video, which have the potential of extending the scope of video indexing possibilities. The development of an affective content classification solution faces a number of challenges. These include the dynamic and time evolving nature of the video's emotional content and the uncertainty in the multimodal sensory observations. These challenges have resulted in the lack of reliable methods for video emotional content modeling. This paper introduce a novel probabilistic approach to model the emotional content of the video based on the dynamic Bayesian networks (DBNs). It is designed based on the pleasure-arousal-dominance (P-A-D) emotion model, which in principle can represent a large number of emotions. It is also designed based on the concept of "working memory", a theoretical framework within cognitive psychology that refers to the structures and processes used for temporarily storing and manipulating information. Our experiment results demonstrate that "working memory" is an important aiding factor in complex emotional content analysis.
RAL-TR-1999-041 Global convergence of trust-regionSQP-lter algorithms forgeneral nonlinear

Global convergence to rst-order critical points is proved for two trust-region SQP-lter algorithms of the type introduced by Fletcher and Leyyer (1997). The algorithms allow for an approximate solution of the quadratic subproblem and incorporate the safeguarding tests described in Fletcher, Leyyer and Toint (1998). The rst algorithm decomposes the step into its normal and tangential components, while the second replaces this decomposition by a stronger condition on the associated model decrease.
Combining Hyperblocks and Exit Prediction to Increase Front-End Bandwidth and Performance

As processor issue widths increase, high-bandwidth parallel fetches across multiple branches will be necessary to prevent Flynn’s bottleneck. In this paper, we show that by combining hyperblocks and exit predictors, high instruction bandwidths can be achieved in a streamlined, simple design that requires only a third of the predictions of a conventional predictor. Exit predictors identify the first branch in a hyperblock that will be taken with a single prediction, implicitly predicting all previous branches in the hyperblock as not taken. Hyperblock-based exit predictors reduce the number of predictions by 72%, while maintaining an average prediction accuracy of 94.7% (compared to 95.9% for the best conventional predictor we measured, a PAs-gshare predictor). With this accuracy, a 250Kbit exit predictor achieves a mean 3.9 misses per thousand instructions (MPKI), fetching 91 useful straight-line instructions per prediction, on average. Since so many instructions are fetched with a single simple prediction, these predictors can be used for high frequencies, run-ahead prediction, initial prediction in multi-stage schemes, instruction prefetching, or power reduction. We conclude by showing that hyperblock exit predictors achieve higher accuracy than other high-bandwidth predictors at the same fetch bandwidth, and that these predictors can be used to achieve high ILP on advanced architectures such as Grid Processors.
Episodic memory, semantic memory, and amnesia

Episodic memory and semantic memory are two types of declarative memory. There have been two principal views about how this distinction might be reflected in the organization of memory functions in the brain. One view, that episodic memory and semantic memory are both dependent on the integrity of medial temporal lobe and midline diencephalic structures, predicts that amnesic patients with medial temporal lobe/diencephalic damage should be proportionately impaired in both episodic and semantic memory. An alternative view is that the capacity for semantic memory is spared, or partially spared, in amnesia relative to episodic memory ability. This article reviews two kinds of relevant data: 1) case studies where amnesia has occurred early in childhood, before much of an individual's semantic knowledge has been acquired, and 2) experimental studies with amnesic patients of fact and event learning, remembering and knowing, and remote memory. The data provide no compelling support for the view that episodic and semantic memory are affected differently in medial temporal lobe/diencephalic amnesia. However, episodic and semantic memory may be dissociable in those amnesic patients who additionally have severe frontal lobe damage. Hippocampus 1998;8:205–211. Published 1998 Wiley‐Liss, Inc. This article is a US Government work and, as such, is in the public domain in the United States of America.
Contextual Image Segmentation Based on the Potts Model

Image segmentation is one of the basic steps in image analysis. Clustering methods are an unsupervised way to provide image segmentation. This paper proposes a clustering algorithm for contextual image segmentation, called spatially variant finite mixture model (SVFMM). For the case of spatially varying mixture of Gaussian density functions with unknown means and variances, an expectation-maximization (EM) algorithm is derived for maximum likelihood estimation of the parameters of the mixture model. In this paper, the Potts model is adopted as a priori density function for the spatially variant mixture proportions to imposes spatial smoothness constraints in the model. Experimental results on a set of different real images show the effectiveness of the proposed method.
Architecture-Based Systems Evaluation: Lessons Learned

Information Systems are today highly complex and users are demanding ever higher quality levels. Therefore, it is useful to have a minimum understanding of the level of quality expected of those systems. Architecture is one of the components most likely to affect system quality; hence it must be evaluated at the early stages of development in order to guarantee quality attributes in the future system. The objective of this research is to present the lessons learned from applying two architectural evaluation methods to the same development process applied to a case. The methods used were the Software Architecture Design Method (Bosch 2000) and the Architecture Tradeoff Analysis Method ATAM (Clements et al. 2002). The case study was a Knowledge Management System known as PROYECTOS DID KMS, which was applied to Research Projects conducted by Universidad Simon Bolivar. The mainly conclusion is that the major difference between both methods lies in their effectiveness, based on the dimension of the systems architecture to be evaluated. The Bosch’s Method, combined with the Simulation Technique, is suitable for systems that handle large amounts of components, since this technique enables the behavior of the different quality attributes to be quantitatively observed by subjecting them to changes in a relatively short space of time. On the other hand, ATAM is appropriate for relatively small systems, where stakeholders can reach a consensus and the architect can also carefully and qualitatively compare each of the scenarios identified.
TERRITORIAL BEHAVIOR AND CORTICAL BRAIN PLASTICITY IN ADULT MALE SCELOPORUS OCCIDENTALIS

The hippocampus is a brain region that can undergo tremendous plasticity in adulthood. The hippocampus is related to the formation of spatial memories in birds and mammals. In birds, plasticity in the hippocampus occurs when formation of such memories is directly relevant to survival or reproduction, such as for breeding or food caching. In reptiles, the homologues to the hippocampus are the dorsal and medial cortices (DC and MC). In several lizard, snake and turtle species, these structures have been related to spatial memory. Experimental investigations indicate that differences in DC volume are related to space use associated with differing foraging ecologies. Differences in MC volume have been associated with territory size-based mate acquisition strategies. Furthermore, territory size has previously been correlated with plasma testosterone (T) levels. Therefore, I hypothesized that neuroplasticity within the MC/DC is controlled by demands on spatial navigation and seasonal differences and that these changes may involve the action of T. During two experimental trials, male Western Fence Lizards (Sceloporus occidentalis) were placed into either large or small semi-natural enclosures and allowed to interact with a female and intruder males over the span of seven weeks. One trial was performed during the spring breeding season and the other during the summer non breeding season, to examine seasonal differences in plasticity. Blood samples were collected at initial time of capture and before sacrifice to measure plasma T. Immunostaining for doublecortin was used to determine the density of immature neurons in each region, and cresyl violet staining allowed for volume measurements of specific regions. MC cell layer neurogenesis was higher in lizards placed in large enclosures than those in small enclosures and higher in the summer than in the spring. DC volume was smaller in lizards held in large enclosures than those in small enclosures. The decreased DC volume seen lizards held in large enclosures may indicate a cost to the increased neurogenesis in the MC of lizards in the same enclosures. These results indicate a possible trade-off between DC volume and MC neurogenesis that allows for switching between the ability to solve novel spatial tasks using the DC while storing a cognitive map in the MC. During the spring, T had no relationship with MC volume, while during the summer this was negative, so effects of T on the MC may be seasonal. v ACKNOWLEDGMENTS Without the help of several individuals, this thesis and the Masters of …
The Political Economy and Urban Racial Tensions

Recent books such as Andrew Hacker's Two Nations (1992) and Derrick Bell's Faces at the Bottom of the Well (1992) promote the view that racial antagonisms are so deep seated, so primordial that feelings of pessimism about whether America can overcome racist senti ments and actions are justified. The events surrounding the recent rebellion in Los Angeles, the worst race riot in the nation's history, aggravated these feelings. However, in this atmosphere of heightened racial awareness we forget or overlook the fact that racial antago nisms are products of situations? economic situations, political situations, and social situa tions. To understand the manifestation of racial antagonisms during certain periods, is to com prehend, from both analytic and policy perspec tives, the situations that increase and reduce them. As revealed in the title I have chosen for this paper ("The Political Economy and Urban Racial Tensions"), I shall try to demonstrate this important point by showing how the interrela tions of political policies and economic and social processes directly and indirectly affect racial tensions in urban America. In the tradition
Hot or Cold? A Comparison of Different Approaches to the Pricing of Weather Derivatives

This article reviews six different temperature forecasting models proposed by prior literature for pricing weather derivatives. Simulation of these models is used to estimate daily temperature and, as a consequence, the metrics used for pricing temperature derivatives. The models that rely on an auto-regressive moving average (ARMA) process exhibit a better goodness-of-fit than those that are established under Monte Carlo simulations. However, the superiority of ARMA-type models is not reflected over the forecast horizon. Over that period, the models that rely on Monte Carlo simulations exhibit a tendency to over-forecast the monthly accumulated heating degree day (AccHDD) index and to under-forecast the monthly accumulated cooling degree day (AccCDD) index. Alternatively, models established under the ARMA approach both under-forecast and over-forecast the monthly accumulated indices. All models consistently over-forecast the average daily temperature. The most appropriate pricing model varies between cities and months. Finally, the models examined in this study generate a more accurate AccHDD futures price than the price traded on the market. However, the ability of these models to estimate the AccCDD futures price is significantly poorer than that of the market.
Flight Data Visualization for Simulation &amp; Evaluation: A General Framework

Flight Data records the important plane subsystem status, attitudes, actions, key parameters, etc. during whole flight. Visualization of the information extracted from flight data is very useful to replay the entire flight and evaluate the quality. in this paper, we present a general framework to simulate and evaluate the flight course based on flight data processing and visualization. Firstly, we give out the flight maneuver recognition algorithm based on modified Particle Swarm Optimization (PSO). Then, we take the flight action evaluation as the problem of multivariate time series similarity measure, and construct the similarity matching model between recognized maneuvers and standard maneuvers to achieve quantitative evaluation of flight maneuver. We also implement the visualization engine based on OpenSceneGraph to simulate/replay the flight maneuver, flight path and the terrain of flying zone. Our framework not only fit for simulation and evaluation single kind (or type) of plane's flight quality, any plane has the same flight data format can be simulated and replayed in 3D in our framework.
Preferential Urn Model on a Random Network

A preferential urn model on a random network and a complete graph is studied. The preferential urn model is based on the concept "the rich get richer", and has simple dynamics of ball-transfers. The model is considered as a simple socio-economic system. From analytical treatments, it has been revealed that the preferential urn model on the complete graph gives a fat-tailed occupation distribution in the case with randomness for fitness parameters. In the present paper, using numerical experiments, we show that the model on the random network gives a fat-tailed occupation distribution in the case without randomness for fitness parameters; hence, we would consider that the local ball-transfer process on the random network includes effects corresponding to the randomness for fitness parameters. This simple game would give a valuable insight into various phenomena from socio-economic point of view