Miracle-dz/UniFAR-FTUs huggingface dataset:
Early and Multi Level Fusion for Reliable Automotive Safety Systems

The fusion of data from different sensorial sources is today the most promising method to increase robustness and reliability of environmental perception. The project ProFusion2 pushes the sensor data fusion for automotive applications in the field of driver assistance systems. ProFusion2 was created to enhance fusion techniques and algorithms beyond the current state-of-the-art. It is a horizontal subproject in the Integrated Project PReVENT (funded by the EC). The paper presents two approaches concerning the detection of vehicles in road environments. An early fusion and a multi level fusion processing strategy are described. The common framework for the representation of the environment model and the representation of perception results is introduced. The key feature of this framework is the storing and representation of all data involved in one perception memory in a common data structure and the holistic accessibility.
A Tribute to Bart Longenecker: An IS Education Maverick and Visionary

Bart Longenecker was one of the most influential Information Systems (IS) educators ever. Renowned for his decades of work on IS model curricula, Bart died in 2016 after a 44-year career. This paper traces the life’s work of this EDSIG Fellow and Professor Emeritus to capture his IS education legacy.
All for One: Contributions of Age, Socioeconomic Factors, Executive Functioning, and Social Cognition to Moral Reasoning in Childhood

Moral reasoning (MR) is a socio-cognitive skill essential to appropriate social functioning in childhood, and evolves in quality and complexity during ontogenetic development. Past research suggests that MR is related to age, socioeconomic factors, as well as some social and cognitive skills, such as executive functioning (EF), theory of mind (ToM), empathy, and affect recognition. However, their contributions have been studied in silos rather than comprehensively, with little integration of the relative and combined contribution of these skills to MR. Furthermore, few studies have addressed the putative links between these factors in childhood, a period during which these skills are in maturation. The aim of this study was to explore what factors predict moral maturity in typically developing children (n = 76, 47.4% males, M = 9.2, SD = 1.67 years), explore the potential moderating and mediating role of executive functions and social cognition in the relationship between age and MR maturity, and identify the specific contributions of age, socioeconomic factors, EF, and social cognition, using an innovative visual MR assessment tool (So-Moral). The results indicate that MR maturity was correlated with age, EF (inhibition, verbal fluency, and attentional control), and social cognition (ToM and affect recognition). Neither EF nor social cognition moderated the effect of age on MR maturity. However, verbal fluency and third-order false beliefs had a moderating role in this link. MR maturity in children was predicted by three variables from each of the three domains: age, verbal fluency, and third-order ToM. These results contribute to a better understanding of the underpinnings of MR during childhood, suggesting that MR is not reducible to general developmental factors such as age, but that higher order skills, such EF and social cognition also contribute to moral maturity. The findings have relevance for both typically developing and clinical populations in which social skills may be reduced, as well as for the identification of potential loci for intervention in children at-risk for socially maladaptive behaviors.
VOLTAGE PROFILE OPTIMIZATION IN DISTRIBUTION SYSTEMS USING NEURAL NETWORKS

In general, 5 to 13 percent of electric energy is lost as heat in distribution systems. There are several methods for reduction of losses in distribution systems. One of these methods is the reduction of current in distribution network branches and compensation of the reactive power of loads with capacitors. Then, the optimum value of the reactive powers, and hence the optimum value of the voltages, is achieved with tap changing on the transformers. In this paper, assuming that the compensators are installed, the optimization on the voltage profile of distribution networks is gained with changing the tap of the transformers using LVQ and RBF neural networks. We will show that this method is capable of bringing the change of the voltages in the 14-bus IEEE network to a range of [0.98, 1.02] with the minimum number of tap changing, hence decreasing the wear on mechanical parts. Also, since the proposed method is faster than the other methods (e.g. load flow and fuzzy logic), it would be easier to use it as an on-line scheme for distribution networks.
The Regulation of Chinese Professional Football: Review and Prospects

Abstract In 1994, a wave of professionalization began to sweep over Chinese football, beginning a new chapter in China’s sporting development. There have been some gratifying achievements in the past 23 years; meanwhile, some problems have been exposed and should not be ignored. The most prominent are football fraud, unfair refereeing and corruption, and as such the regulation of professional football has become an increasingly pressing issue. Through literature review and logical analysis, this research starts with a discussion of football fraud, unfair refereeing, and corruption in the development of Chinese football professionalization, then analyzes the causes of these problems, and finally puts forward some measures for the future regulation construction of Chinese professional football, through learning from the lessons of some developed countries. It is believed that establishing sound rules and regulations and independent sports arbitration organizations, taking strict scrutiny and severe punishment measures, improving accuracy and authority in football rulings, as well as cultivating and reinforcing awareness of rule of law, are the way forward for Chinese professional football. This research also maps out a vision for the future of Chinese professional football: non-political associations, systematic football legislation, independent supervisory organizations, and professional practitioners.
Consideraciones prácticas para la implementación de la transformada d-q monofásica para la detección de SAGs.

La deteccion del voltaje pico de linea mediante la transformada d-q convencional ha permitido la implementacion de controladores que contrarresten los efectos de perturbaciones como SAGs y SWELLs. En teoria, con la transformada d-q convencional se puede obtener el voltaje pico en cualquier instante del ciclo de una senal senoidal, sin embargo, esta caracteristica puede cumplirse o no dependiendo de la tecnica que se utilice para su implementacion en un dispositivo programable tal como un Microcontrolador, DSP (por sus siglas en ingles Digital Signal Processor), o un FPGA (por sus siglas en ingles Field Programmable Gate Array). En este articulo se hace una comparacion de dos tecnicas que se pueden utilizar para la implementacion de la transformada d-q convencional en un microcontrolador de la familia dsPIC de Microchip.
The expected thermal precursors of gamma-ray bursts in the internal shock model

The prompt emission of gamma-ray bursts probably comes from a highly relativistic wind which converts part of its kinetic energy into radiation via the formation of shocks within the wind itself. Such ‘internal shocks’ can occur if the wind is generated with a highly non-uniform distribution of the Lorentz factor. We estimate the expected photospheric emission of such a relativistic wind when it becomes transparent. We compare this thermal emission (temporal profile + spectrum) with the non-thermal emission produced by the internal shocks. In most cases, we predict a rather bright thermal emission that should already have been detected. This favours acceleration mechanisms for the wind where the initial energy input is under magnetic rather than thermal form. Such scenarios can produce thermal X-ray precursors comparable to those observed by Ginga and WATCH/GRANAT.
Ontology Construction from Semi-Structured Text

Ontology is effective in supporting text mining, information retrieval and knowledge engineering on semantic level. However, ontology construction is pretty time-consuming; hence, some automatic or semi-automatic methods are proposed to try to solve the problem. In this paper, a model is issued to construct a medical ontology from semi-structured text after three steps: PAT-Tree based phrase extraction, document structure analysis and ontology construction based on hierarchy structure of text. This model has found some applications in medical emergency aid system in China. Practical experiment results show that this model can create a practical medical ontology from syllabus of medical school efficiently and effectively.
Spatiotemporal properties of evoked neural response in the primary visual cortex

Understanding how neurons in the primary visual cortex (V1) of primates respond to visual patterns has been a major focus of research in neuroscience for many decades. Numerous different experimental techniques have been used to provide data about how the spatiotemporal patterns of light projected from the visual environment onto the retina relate to the spatiotemporal patterns of neural activity evoked in the visual cortex, across disparate spatial and temporal scales. However, despite the variety of data sources available (or perhaps because of it), there is still no unified explanation for how the circuitry in the eye, the subcortical visual pathways, and the visual cortex responds to these patterns. This thesis outlines a research project to build computational models of V1 that incorporate observations and constraints from an unprecedented range of experimental data sources, reconciling each data source with the others into a consistent proposal for the underlying circuitry and computational mechanisms. The final mechanistic model is the first one shown to be compatible with measurements of: (1) temporal firingrate patterns in single neurons over tens of milliseconds obtained using single-unit electrophysiology, (2) spatiotemporal patterns in membrane voltages in cortical tissues spanning several square millimeters over similar time scales, obtained using voltagesensitive–dye imaging, and (3) spatial patterns in neural activity over several square millimeters of cortex, measured over the course of weeks of early development using optical imaging of intrinsic signals. Reconciling this data was not trivial, in part because single-unit studies suggested short, transient neural responses, while population measurements suggested gradual, sustained responses. The fundamental principles of the resulting models are (a) that the spatial and temporal patterns of neural responses are determined not only by the particular properties of a visual stimulus and the internal response properties of individual neurons, but by the collective dynamics of an entire network of interconnected neurons, (b) that these dynamics account both for the fast time course of neural responses to individual stimuli, and the gradual emergence of structure in this network via activity-dependent Hebbian modifications of synaptic connections over days, and (c) the differences between single-unit and population measurements are primarily due to extensive and wide-ranging forms of diversity in neural responses, which become crucial when trying to estimate population responses out of a series of individual measurements. The final model is the first to include all the types of diversity necessary to show how realistic single-unit responses can add up to the very different population-level evoked
College Student Drinking: The Role of University Identity, Alcohol Related Problems, and Harm Reduction Strategies

College student drinking is linked to an array of related outcomes, such as missing class or work, problems with the law, and attrition from the university. Due to the high rates of college student drinking on American campuses, it is imperative to identify what drives this phenomenon. Using self-report measures, the present study aimed to identify predictors of alcohol consumption by examining the relationships of positive expectancies, past alcohol problems, university identity, need to belong, and harm reduction strategies to future alcohol use. The study found that identifying with the university and problems related to alcohol predicted increased alcohol use, while skill-based harm reduction strategies negatively predicted alcohol use. Lastly, expectancies and need to belong failed to predict alcohol use, and it was found that the relationship between university identification and alcohol use depends on one’s need to belong. Much work remains to be done on why university identification may contribute to drinking, but it is recommended that university officials implement skill-based harm reduction strategy workshops to reduce the amount of student drinking and related consequences.
Segmentation by Blended Partitional Clustering for Different Color Spaces

This paper presents a new segmentation strategy, based on a blended procedure whose goal is to combine several segmentation maps in order to finally get a more reliable and accurate segmentation result. The fusion strategy aims at combining these segmentation maps with a final clustering procedure using as input features, the local histogram of the class labels, previously estimated and associated to each site and for all these initial partitions. The different label fields to be fused are given by the same and simple K-means based (blended partitional) clustering technique on an input image expressed in different color spaces. This fusion framework remains simple to implement, fast, general enough to be applied to various computer vision applications.
A co-contextual formulation of type rules and its application to incremental type checking

Type rules associate types to expressions given a typing context. As the type checker traverses the expression tree top-down, it extends the typing context with additional context information that becomes available. This way, the typing context coordinates type checking in otherwise independent subexpressions, which inhibits parallelization and incrementalization of type checking. We propose a co-contextual formulation of type rules that only take an expression as input and produce a type and a set of context requirements. Co-contextual type checkers traverse an expression tree bottom-up and merge context requirements of independently checked subexpressions. We describe a method for systematically constructing a co-contextual formulation of type rules from a regular context-based formulation and we show how co-contextual type rules give rise to incremental type checking. Using our method, we derive incremental type checkers for PCF and for extensions that introduce records, parametric polymorphism, and subtyping. Our performance evaluation shows that co-contextual type checking has performance comparable to standard context-based type checking, and incrementalization can improve performance significantly.
Feature Selection via Correlation Coefficient Clustering

Feature selection is a fundamental problem in machine learning and data mining. How to choose the most problem-related features from a set of collected features is essential. In this paper, a novel method using correlation coefficient clustering in removing similar/redundant features is proposed. The collected features are grouped into clusters by measuring their correlation coefficient values. The most class-dependent feature in each cluster is retained while others in the same cluster are removed. Thus, the most class-related and mutually unrelated features are identified. The proposed method was applied to two datasets: the disordered protein dataset and the Arrhythmia (ARR) dataset. The experimental results show that the method is superior to other feature selection methods in speed and/or accuracy. Detail discussions are given in the paper.
A new string distance for computing binary code similarities

A binary program can be represented as a string of operation codes by disassembling it and removing the instruction operands. Using this representation, the problem of detecting if two programs are similar can be reduced to computing the distance between two strings. The most common types of edit distance are fit for this task but unfortunately their running time is quadratic. A new type of edit distance called deq distance is proposed and it can be computed in linear time. This distance also measures the number of operations required to transform a string into another but only allows the operations that can be performed on a double ended queue. The new distance has been tested in clustering algorithms and produced quality clusters, very similar to the ones produced by a regular edit distance. The performance evaluation also showed that the new distance can be computed faster for strings longer than 300 characters, making it appropriate for finding similarities between malware samples.
The process of quality assurance under open source software development

Open Source Software (OSS) is software products available to the public, with its source code to study, change, and improves its design. Open Source Software Development (OSSD) is the process by which open source software is developed within the confines of software engineering life-cycle methods. However when open source used for commercial purpose, then an open source license is required. Open source software is very often developed in a public and collaborative manner. The quality assurance principle under open source software development is an approach to improve software product quality against traditional methods and techniques. Despite the fact that the open source developments have seen remarkable successful in recent years, there are a number of product quality issues and challenges facing the open source development model. Many industries and business sectors are following or using OSSD, since they realize the benefits, but they do have some reservations concerning quality assurance in the form of program code quality, maintenance of the code and its quality, over the life-cycle of the product and third party usage. This paper reviews the literature of the process of the latest quality assurance, under open source software development methods and techniques. The result from this review is to show the process of quality assurance of open source software and that how it can affect the overall quality assurance principal.
An Improved Codeword Search Algorithm Based on Subvector Features

An improved fast codeword search algorithm based on sub vector features is presented in this paper. First divide every input vector into two sub vectors with the same dimension. Then compute the sum and variance of every input vector and its two sub vectors in turn, get a series of space division inequalities which are used as the elimination criterions. The result of the simulation shows that in the same coding quality compared with full search algorithm, the proposed algorithm has better data in the average number of distance calculations compared with several classic algorithms.
Feature Extraction from Rural Satellite Imagery Using Color Based CBIR Techniques

The ability to organize and retrieve visual information such as images is becoming a crucial problem for specialists, because processing visual information requires perceptual abilities not yet known to exist in computational form. Therefore the ability to retrieve visual information is a complex problem. The main retrieval pattern include the features of an image such as colour, and shape. The algorithms used to calculate the similarity between extracted feature with an image database, that utilizes colour features of the images as the basis of comparison and retrieval. An object-oriented definition also involves prescribing a set of pertinent features or pixels as well as a method such as a classification algorithm with the appropriate training data. A low resolution satellite image of a rural scenario has been selected for the analysis. The entire image scene is divided into four equal quadrants. The Content-based retrieval of image features have been carried out for the selected two quadrants I and II. The color classification of the image in two quadrants clearly indicates that there are four important features that are common to the images 1 The features identified include, Natural Vegetation, Water Bodies, Land, and Housing associated with the image. Further using the L*a*b color spectral distribution and histogram techniques an estimation of the different features identified in the image has been made for all the four quadrants. The results are presented in the paper.
Data Preprocessing on Sequential Data for Improved Astronomical Imaging

Obtaining diffraction limited astronomical images using ground-based telescopes and sensors operating at optical wavelengths is currently not possible due to the effects of atmospheric turbulence. Adaptive optics is a mature technology that attempts to minimise the effects of atmospheric turbulence through wavefront detection and optical path correction in real-time. Our work involves the acquisition and preprocessing of sequential astronomical data and the application of machine learning algorithms to obtain consistently, high-resolution images called lucky frames. This paper will outline the design of a framework used to capture and preprocess sequential data in real-time, and explore machine learning extensions to accurately predict lucky frames.
A test of a perspective theory of geometrical illusions.

Three-dimensional Miiller-Lyer figures were used in three experiments to test a perspective theory of geometrical illusions. The real depth cues were in one of two orientations, designed either to support or to oppose the action of the perspective depth cues hypothesized by the perspective theory. If any illusion is obtained with these three-dimensional figures, the theory implies, its magnitude should be different in the two orientations. In fact, a substantial illusion was obtained, but the difference between the two orientations was small and opposite to the prediction of perspective theory. Perspective explanations of geometrical illusions have a long history,' but only recently has this approach received the conceptual clarification needed to open it to experimental analysis. Gregory's formulation of perspective theory rests on two main assumptions.2 First, geometrical-illusion figures such as the MiillerLyer ones in Figure lab are considered two-dimensional projections of three-dimensional figures; thus, they contain perspective cues for depth. Second, these cues are assumed to trigger a constancy-scaling mechanism that corrects for decrease in the retinal image with increasing distance. Those parts of the figure that would be more distant in the three-dimensional representation are enlarged and those that would be closer are diminished, in accord with size constancy. This version of perspective theory has been applied especially to Received for publication April 27, 1970. The first author, who is now at the University of Wisconsin, was supported by a postdoctoral fellowship, MH39369-02, from the National Institute of Mental Health. Support was also provided by a National Science Foundation grant, GB-6666, to the second author. The authors thank Susan Keeve for her help. 1 R. S. Woodworth, Experimental Psychology, 1938, 644-645; R. L. Gregory, Eye and Brain, 1966, 141-156. 2R. L. Gregory, Distortion of visual space as inappropriate constancy scaling, Nature, 199, 1963, 678-680; R. L. Gregory. Seeing in depth, Nature, 207, 1965, 16-19.