Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Method for Preserving Privacy in Data Publishing Against Attribute and Identity Disclosure Risk

Sharing, transferring, mining and publishing data are fundamental operations in day to day life. Preserving the privacy of individuals is essential one. Sensitive personal information must be protected when data are published. There are two kinds of risks namely attribute disclosure and identity disclosure that affects privacy of individuals whose data are published. Early Researchers have contributed new methods namely k-anonymity, l-diversity, t-closeness to preserve privacy. K-anonymity method preserves privacy of individuals against identity disclosure attack alone. But Attribute disclosure attack makes compromise this method. Limitation of k-anonymity is fulfilled through l-diversity method. but it does not satisfies the privacy against identity disclosure attack and attribute disclosure attack in some scenarios. The efficiency of t-closeness method is better than k-anonymity and l-diversity. But the complexity of Computation is more than other proposed methods. In this paper, the authors contributes a new method for preserving the privacy of individuals’ sensitive information from attribute and identity disclosure attacks. In the proposed method, privacy preservation is full filled through generalization of quasi identifiers by setting range values.
A study of the integrated automated emotion music with the motion gesture synthesis

Automated Music Composition and Algorithmic Composition is based on the logic operation with music parameters setting according to the desired music style or emotion. The computer generative music can be integrated with other domain using proper mapping techniques, such as the intermedia arts with music technology. This Paper mainly discusses the possibility to integrate both automatic composition and motion devices with an Emotional Identification System (EIS) using the emotion classification and parameters. The correspondent music pattern and motion path can be driven simultaneously via the cursor movement of in the Emotion Map (EM) varying with time. An interactive music-motion platform is established accordingly.
Topics in functional data analysis

As the amount of data captured in experimental and observational situations has grown, so too has the need for more sophisticated tools of analysis. The broad area of functional data analysis (FDA) has received a great deal of attention within the statistics community over the past decade, as a way of dealing with the high dimensional data that is becoming more commonplace in areas such as medical science and biology. High dimensional data has classically been analysed by treating the relevant data sets as multivariate data sets. FDA seeks to analyse these data as if they are in fact functions, observed at either sparse or dense sample points. Motivated by problems in forest science and capture/recapture experiments, this thesis explores some of the FDA methodology through modelling data sets that contain functional responses or functional covariates. We show that a nonparametric ‘whole of function’ approach to predicting conditional probability density functions is a particularly useful alternative to commonly used parametric approaches, especially when density functions have ‘non–standard’ shapes. The functional prediction approach is further extended by developing functional regression models for functional longitudinal data. We show that these models allow prediction and extrapolation of density functions with arbitrarily (smooth) changing shapes over time, conditional on a functional growth covariate. A semiparametric population size estimator for mark–recapture data with continuous, time–varying covariates is developed from a functional data perspective. This method allows the full use of data resulting from such experiments, circumventing the usual loss of information in current approaches. We demonstrate that an iterative estimation approach in the form of an EM algorithm outperforms methods that ignore the time variation in the covariates.
On the Essential Contexts of Artifacts or on the Proposition That "Design Is Making Sense (Of Things)"

1) Part of this work was supported by the The etymology of design goes back to the Latin de + signare and design firm RichardsonSmith, Worthmeans making something, distinguishing it by a sign, giving it ington, Ohio, and Ohio State University, Columbus, while on sabbatical leave in significance, designating its relation to other things, owners, 1986-87 from the University of Pennsylusers, or gods. Based on this original meaning, one could say: vania, Philadelphia. design is making sense (of things).
Making them behave: cognitive models for computer animation

For applications in computer game development and character animation, recent work in behavioral animation has taken impressive steps toward autonomous, self-animating characters. It remains difficult, however, to direct autonomous characters to perform specific tasks. We propose a new approach to high-level control in which the user gives the character a behavior outline, or “sketch plan”. The behavior outline specification language has syntax deliberately chosen to resemble that of a conventional imperative programming language. In terms of functionality, however, it is a strict superset. In particular, a behavior outline need not be deterministic. This added freedom allows many behaviors to be specified more naturally, more simply, more succinctly and at a much higher-level than would otherwise be possible. The character has complete autonomy to decide on how to fill in the necessary missing details. The success of our approach rests heavily on our use of a rigorous logical language, known as the situation calculus. The situation calculus is well-known, simple and intuitive to understand. The basic idea is that a character views its world as a sequence of “snapshots” known as situations. An understanding of how the world can change from one situation to another can then be given to the character by describing what the effect of performing each given action would be. The character can use this knowledge to keep track of its world and to work out which actions to do next in order to attain its goals. The version of the situation calculus we use incorporates a new approach to representing epistemic fluents. The approach is based on interval arithmetic and addresses a number of difficulties in implementing previous approaches.
Games to Live With

In this paper I offer an alternative way to look at games that require no form of play. The player of these games is only supposed to keep them always up-to-date and running, but no specific action is required. NikeFuel is a significant example of this kind of game. NikeFuel, a technology for the quantification of body movement developed by the sports company Nike, is applied in a series of gadgets. The most popular, Nike+, is a wristband that quantifies the movements of the user and converts them into a NikeFuel score, which can later be visualised on a laptop or mobile phone. The act of moving throughout the day is transformed into a game-like experience, according to the principles of gamification. Gamification and quantified-self technologies have been noted for their performative potential and their capacity to control and inform our bodies (Whitson 2015). From a Foucauldian perspective, quantified-self technologies are attempts to rationalise the practices and movements of living organisms, as forms of biopolitical control (Foucault 2005, Schrape 2014). However, these are also spaces of transformation of the conditions under which the self becomes possible. Through NikeFuel, and other examples that I explore in this paper (Farmville, Cookie Clicker, CarnageHug), the player has to come to terms with games that act as parasites on their own lives. Thus, I argue that Nike+ can also be seen to complicate our thoughts about the contemporary digital technologies that surround us on an everyday basis. In this paper I will argue, possibly counter-intuitively, that gamification and quantified-self technologies are not necessarily tools that we use for a specific purpose; these are technologies we carry around with us and live with. As such, we are transformed by them as much as we transform them. Thus, the problem raised in this paper is about how we can co-habit and be hospitable with these ‘parasites’ (Serres, 1982).
Discovering How Information Seekers Seek:: Methods of Measuring Reference Collection Use

The author observes that reference collections are often too large for librarians and users to learn them well and fully exploit them. Evidence suggests that many titles in what were designed to be lean "working" reference collections are rarely if ever consulted. Systematically-gathered use data are needed to guide selection and weeding decisions. Methods that have been employed to assess in-library materials use - including use of journals and circulating books as well as of reference works - are reviewed and their application to reference materials discussed. The author closes with concrete recommendations for carrying out reference collection use studies.
Study on Security Vulnerabilities of Implicit Intents in Android

Android provides a message-passing mechanism called intent. While it helps easy developments of communications between intra and inter applications, it can be vulnerable to attacks. In particular, implicit intent, differing from explicit intent specifying a receiving component, does not specify a component that receives a message and insecure ways of using implicit intents may allow malicious applications to intercept or forge intents. In this paper, we focus on security vulnerabilities of implicit intent and review researched attacks and solutions. For the case of implicit intent using `developer-created action', specific attacks and solutions have been published. However, for the case of implicit intent using `Android standard action', no specific attack has been found and less studied. In this paper, we present a new attack on implicit intent using Android standard action and propose solutions to protect smart phones from this attack.
Genetic Approach to Strategic Games

In this thesis we develop and implement a genetic algorithm to optimize a set of talents, equipment and sub-attributes of characters in the game Warcraft III and its modification The Kingdom of Kaliron. Finding the optimal set where a character performs the best in fights against enemies is a combinatorial problem for which we use a genetic algorithm to solve. To be able to evaluate a character, we implemented a simulation that required deep knowledge of game mechanics and programming principles of Warcraft III. We also used reverse engineering as a tool. We ensured convergence of a genetic algorithm with the use of population islands, which are disjoint subpopulations with weak mutual interactions, and with careful choosing of genetic algorithm parameters. We also implemented genetic algorithm memory, which helps create better initial individuals when creating new populations. Finally, we used parallelization to reduce the running time of the algorithm.
Effective Elimination of False Alarms by Variable Section Size in CFAR Algorithm

Generally, because received signals from radar are very bulky, the data are divided into manageable size called section, and sections are distributed into several digital signal processors. And then, target detection algorithms are applied simultaneously in each processor. CFAR(Constant False Alarm Rate) algorithm, which is the most popular target detection algorithm, can estimate accurate threshold values to determine which signals are targets or noises within center-cut of section allocated to each processor. However, its estimation precision is diminished in section edge data because of insufficient surrounding data to be referred. Especially this edge problem of CFAR is too serious if we have many sections to be processed, because it causes many false alarms in most every section edges. This paper describes false alarm issues on MCA(Minimum Cell Average)-CFAR, and proposes a false alarm elimination method by changing section size alternatively. Real received data from multi-function radar were used to evaluate a proposed method, and we show that our method drastically decreases false alarms without missing real targets, and improves detection performance.
Wavelength-dependent channel power transient response in broadband Raman-amplified transmission

The time evolution of uncontrolled amplifier gain transients due to dropped or cut dense-wavelength-division multiplexed channels in a broadband all-Raman amplified recirculating loop experiment is measured for different surviving channel wavelength configurations with propagation up to 7200 km. Different time signatures develop depending on whether the surviving channels are located at the long- or short-wavelength end of the spectrum. Channel power tilt and gain error within a surviving channel group can vary with distance and are shown to correlate with growth of amplified spontaneous emission noise at the dropped channel wavelengths.
Aire fresco, un programa participativo y entre iguales para reducir el consumo de tabaco en el ámbito educativo

Fundamento: En 2000, se puso en marcha el programa Aire fresco en los centros de secundaria de Asturias (España) para reducir o eliminar el tabaco en el ámbito educativo. Este estudio recoge la evaluación del proceso de esta intervención, que concluyó en 2005, en 23 centros de secundaria. Métodos: El programa duraba un curso escolar y ponía en marcha un proceso con seis acciones, con el objetivo final de implicar a alumnado, personal y madres/padres en el establecimiento y cumplimiento de nuevas normas. Estas seis acciones eran: información, propuestas del personal, propuestas del alumnado, establecimiento de nuevas normas, difusión y actividades de refuerzo. Entre otras actividades, se ofertaban un taller entre iguales para el alumnado y un taller para dejar de fumar para personal y madres/padres. El programa lo llevaron a cabo 23 centros que constituyeron, con su alumnado y profesorado, la población de estudio. Mediante cuestionarios, se recogieron datos de acciones realizadas, participación en las actividades y opinión de alumnado y profesorado. También se realizaron grupos focales para conocer las dificultades, logros y propuestas de mejora. Resultados: El 100% de los centros realizó actividades informativas, el 83% recogió propuestas del personal para limitar su consumo, el 91% las del alumnado, y el 70% estableció nuevas normas. Las opiniones de alumnado y profesorado sobre el programa, materiales y metodología fueron positivas. El taller para dejar de fumar se realizó en 18 centros y participaron 176 personas. Entre las que lo concluyeron, el 20% permanecía sin fumar a los seis meses. Conclusiones: Aire Fresco fue una intervención novedosa, satisfactoria y útil para regular el consumo de tabaco en los centros educativos. La filosofía del programa, que buscaba la participación de la comunidad educativa y lo convertía en un proyecto educativo de centro, fue una de las claves para lograr estos resultados. (Promot Educ 2008; 15(3): 52-57)
Study of Key Algorithm on Automatic Classification of Insect Images

Insects, due to their diversity, are the largest group of creature on earth, many of which are yet to be discovered right now. As the photographic hardware develops and gets pervasive rapidly, insect images or pictures have become an important approach for insect researchers to conduct scientific study. However, considering the huge volume of insect image data, researchers usually are not interested in all the images and instead, hope to categorize these images preliminarily and then hand them on for manual processing, which will significantly improve work efficiency and reduce manual workload. In this paper, color histogram and textural features are adopted to collect image features which then use clustering analysis method for automatic classification of insect species. The experimental result is quite good. And on the basis of this, more image features can be extracted to gain more accurate results, or program efficiency can be optimized through parallelization, during which a species feature database is gradually established to have automatic comparison and identification of insect features.
Performance Analysis of MapReduce with In-Memory Caching in HDFS

In this paper, we study the effects of HDFS in-memory caching on various MapReduce applications. We first evaluate the performance of seven MapReduce applications to understand different resource usage patterns. We then modify the centralized cache management system in HDFS such that individual blocks of a file can be cached. Using the modified system in HDFS, we compare the performance of MapReduce applications with in-memory caching to that without in-memory caching for workloads of a single MapReduce application and multiple MapReduce applications. In the experiments, the same workload was executed multiple times to see the effects of in-memory caching. Our experimental results show that the in-memory cache system can be beneficial to workloads of multiple I/O-intensive MapReduce applications, but the in-memory cache system cannot improve the performance of non-I/Ointensive MapReduce applications, possibly degrading the performance due to the overhead of inmemory caching.
Bio-Inspired Micro Air Vehicle: Design and Control Issues

Missions envisioned for Micro Air Vehicles (MAVs) such as Intelligence, Surveillance and Reconnaissance (ISR) in urban environments require exceptional agility. These missions typically involve ight through or in close proximity to buildings, tunnels and trees, and require the MAVs to maneuver using sharp dives and climbs along with small-radius turns. The small size of MAVs allows such ight operations within con ned space but the control e ectors must provide su cient maneuverability, while maintaining stability, with only limited sensing capability onboard the platform. To meet these challenges, researchers have long been attracted by the amazing attributes of biological systems, such as those exhibited by birds and insects. Birds can y in dense ocks, executing rapid maneuvers with g-loads far in excess of modern ghter aircrafts, and yet never collide with each other, despite the absence of air tra c controllers. This paper introduces a novel framework for the design and control of a Micro Air Vehicle. The vehicle's conceptual design is based on biologically-inspired principles and emulates a dragon y (Odonata-Anisoptera). The author is borrowing ight mechanism features from the dragon y and merging them with indigenous designs in creating a novel version of a Flapping Wing MAV, called the QV. The QV design incorporates the simplicity of mechanical construction and the complexity of a sophisticated multi-layered Hybrid & Linear / Non-Linear controller to achieve extended ight times and improved agility compared to other Rotary and Flapping Wing MAV designs. The paper talks about the design and control features of the proposed QV design and gives an overview on the developmental e orts been made towards the prototyping of the QV yer. The potential applications for such a high endurance vehicle are numerous, including air-deployable mass surveillance in cluster and swarm formations. The disposability of the vehicle would help in battleeld deployment as well, where such a MAV would be made available to soldiers for proximity sensing and threat level assessment. Other applications would include search and rescue operations and civilian law-enforcement.
A Qualitative and Quantitative Comparison of Real-time Background Subtraction Algorithms for Video Surveillance Applications ?

Background subtraction is a widely used technique for segmenting a foreground object from its background. The aim of this paper is to review and compare the performance of the most common statistical background subtraction methods, including median-based, Gaussian-based and Kernel density-based approaches. To obtain a fair evaluation, four challenging scenarios were selected based on Wallower datasets. All review methods are based on processing speed, memory usage and segmentation accuracy. The overall evaluation shows that the Gaussian-based method gives the best performance in accuracy, speed and memory consumption. In addition, this paper provides a better understanding of algorithm behaviours applied to dierent situations for real-time video surveillance applications.
Distributed perceptual compressed sensing framework for multiview images

A perceptual-based compressed sensing (CS), which focuses the measurements and the recovery on the visually important low-frequency coefficients, is applied for multi-view image signals. High correlation among different views is exploited to generate signal prediction using disparity estimation and compensation techniques. A residual-based recovery is utilised as a joint recovery for the non-reference images to enhance the reconstruction performance. The proposed framework shows remarkable performance improvement over the conventional CS with joint recovery as well as the perceptual-based CS with independent recovery.
A GPGPU programming framework based on a shared-memory model

Although general purpose computation on GPU (GPGPU) seems to be a promising method for high-performance computing, current programming frameworks such as CUDA and OpenCL are diﬃcult and not portable enough. Therefore, we propose a new framework MESI-CUDA for easier GPGPU programming. MESI-CUDA provides shared variables which can be accessed from both CPU and GPU. Our compiler translates user’s shared-memory-based program into a CUDA program automatically generating the memory allocation and data transfer code. The compiler also overlaps kernel executions and data transfers by optimizing the scheduling. The evaluation results show that programs using MESI-CUDA can achieve the performance close to hand-optimized CUDA programs, largely reducing user’s coding cost.
Outcomes of a Developmental Music Program

A developmental music program based on the methodology and teachings of Zoltan Kodaly has been operating for over seven years in certain primary schools in the Metropolitan West Region of the New South Wales Department of Education. Although I have had no connection with the project, I have watched it over the years with very close interest as an unbiased outsider with a background of music education, teacher education, and research. I am therefore honoured that I have been given the task of reporting on the outcomes of the project and the implications for music education arising from results of the research which has now been carried out.
Reducing the herd effect in the backpropagation algorithm

The backpropagation algorithm is the most popular training algorithm for the multilayer perceptron, despite its slowness. Part of this slowness may be attributed to a phenomenon of the training process that has been called the herd effect. This paper describes a modification of the original backpropagation algorithm that is intended to reduce or eliminate the herd effect and reports on some performance comparisons.