Miracle-dz/UniFAR-FTUs huggingface dataset:
Highly Structured Stochastic Systems

Introduction 1. Some modern applications of graphical models Analysing social science data with graphical Markov models Analysis of DNA mixtures using Bayesian networks 2. Causal inference using influence diagrams: the problem of partial compliance Commentary: causality and statistics Semantics of causal DAG models and the identification of direct and indirect effects 3. Causal inference via ancestral graph models Other approaches to description of conditional independence structures On ancestral graph Markov models 4. Causality and graphical models in times series analysis Graphical models for stochastic processes Discussion of "Causality and graphical models in times series analysis" 5. Linking theory and practice of MCMC Advances in MCMC: a discussion On some current research in MCMC 6. Trans-dimensional Markov chain Monte Carlo Proposal densities and product space methods Trans-dimensional Bayesian nonparametrics with spatial point processes 7. Particle filtering methods for dynamic and static Bayesian problems Some further topics on Monte Carlo methods for dynamic Bayesian problems General principles in sequential Monte Carlo methods 8. Spatial models in epidemiological applications Some remarks on Gaussian Markov random field models A compariosn of spatial point process models in epidemiological applications 9. Spatial hierarchical Bayesian modeld in ecological applications Likelihood analysis of binary data in space and time Some further aspects of spatio-temporal modelling 10. Advances in Bayesian image analysis Probabilistic image modelling Prospects in Bayesian image analysis 11. Preventing epidemics in heterogeneous environments MCMC methods for stochastic epidemic models Towards Bayesian inference in epidemic models 12. Genetic linkage analysis using Markov chain Monte Carlo techniques Graphical models for mapping continuous traits Statistical approaches to Genetic Mapping 13. The genealogy of neutral mutation Linked versus unlinked DNA data - a comparison based on ancestral inference The age of a rare mutation 14. HSSS model criticism What 'base' distribution for model criticism? Some comments on model criticism 15. Topics in nonparametric Bayesian statistics Asymptotics of Nonparametirc Posteriors A predictive point of view on Bayesian nonparametrics
Parallel and successive interference cancellation for MC-CDMA and their near-far resistance

Recently, multi-carrier code division multiple access (MC-CDMA) systems have been considered as potential candidates for next generation (4G) technology. Within this context, due to their good compromise between complexity and performance, multi-user interference cancellation (IC) techniques have been proposed as an effective solution in the receiver design, both for downlink and uplink transmissions; nevertheless actual results are far from being exhaustive. In this paper, a performance comparison of parallel (PIC) and successive (SIC) IC techniques is presented, investigating also the influence of user power levels in a near-far environment, under dispersive channel conditions. The impact of the choice of the single-user detection (SUD) technique used in PIC and SIC receivers is also considered. Moreover, results are presented for convolutionally-coded systems, decoded by both hard and soft-input decoding methods.
A Physical Intelligent Instrument using Recurrent Neural Networks

This paper describes a new intelligent interactive instrument, based on an embedded computing platform, where deep neural networks are applied to interactive music generation. Even though using neural networks for music composition is not uncommon, a lot of these models tend to not support any form of user interaction. We introduce a self-contained intelligent instrument using generative models, with support for real-time interaction where the user can adjust high-level parameters to modify the music generated by the instrument. We describe the technical details of our generative model and discuss the experience of using the system as part of musical performance.
Focused Web Crawler

Web crawler is a program that traverses the internet based on automated manner to download the web pages or partial pages’ contents according to the user requirements. Small amount of work on web crawler has been published for various reasons. Web crawling and its techniques are still in the shadow and possess many secrets due to its involvement in the giant search engine applications where they tend to obscure it, as it is the secret recipe for their success. There is also secrecy involved to protect against search spamming and ranking functions so web crawling methods are rarely published or publically announced. Web crawler is as an important and fragile component for many applications, including business competitive intelligence, advertisements, marketing and internet usage statistics. In this work, we compare between the two main types of web crawlers: standard and focused to choose one of them and apply it in our latter framework for opinion mining in the education domain.
Modelling of natural sounds by time–frequency and wavelet representations

Sound modelling is an important part of the analysis–synthesis process since it combines sound processing and algorithmic synthesis within the same formalism. Its aim is to make sound simulators by synthesis methods based on signal models or physical models, the parameters of which are directly extracted from the analysis of natural sounds. In this article the successive steps for making such systems are described. These are numerical synthesis and sound generation methods, analysis of natural sounds, particularly time–frequency and time–scale (wavelet) representations, extraction of pertinent parameters, and the determination of the correspondence between these parameters and those corresponding to the synthesis models. Additive synthesis, nonlinear synthesis, and waveguide synthesis are discussed.
THE LATEST ON LOCAL AREA TRAFFIC MANAGEMENT PRACTICE IN AUSTRALIA AND NEW ZEALAND – AN UPDATE AND COMPARISON FOR LOCAL GOVERNMENT

Local area traffic management (LATM), otherwise known as traffic calming, has been effective in improving the safety, amenity and liveability of local areas in Australia and New Zealand for decades. In 2008 an Austroads local area traffic management guideline was released – an update on an earlier 2004 guideline developed for practitioners in this field. In order to inform the latest revision of this guideline currently being developed, extensive research was undertaken in 2014 to identify new, innovative and revised approaches to the application of LATM practice in Australia and New Zealand. A broad cross-section of local government agencies was consulted. This paper outlines the findings of that research, addressing questions such as the effectiveness of traffic calming measures used, the methods used in decision making, design considerations, and innovations in practice. The research evaluates and compares data over an 8 year period from 2006 to 2014 and draws conclusions that will be of wide interest to local government engineering and management professionals.
High‐Quality Stereo Depth Map Generation Using Infrared Pattern Projection

In this paper, we present a method for obtaining a highquality 3D depth. The advantages of active pattern projection and passive stereo matching are combined and a system is established. A diffractive optical element (DOE) is developed to project the active pattern. Cross guidance (CG) and auto guidance (AG) are proposed to perform the passive stereo matching in a stereo image in which a DOE pattern is projected. When obtaining the image, the CG emits a DOE pattern periodically and consecutively receives the original and pattern images. In addition, stereo matching is performed using these images. The AG projects the DOE pattern continuously. It conducts cost aggregation, and the image is restored through the process of removing the pattern from the pattern image. The ground truth is generated to estimate the optimal parameter among various stereo matching algorithms. Using the ground truth, the optimal parameter is estimated and the cost computation and aggregation algorithm are selected. The depth is calculated and bad‐pixel errors make up 4.45% of the non‐occlusion area.
Dynamic resource allocation for multi-service packet based LEO satellite communications

Emerging low-Earth-orbit satellite (LEOS) communication systems will have the capability of providing global personal communication services (PCS). Efficient resource utilisation and interoperability with terrestrial networks is essential in such LEOS systems. This paper addresses the efficient provision of general packet radio service (GPRS) over an integrated GSM-LEOS communication system. Dynamic resource allocation and call admission control for multiple (voice and data) traffic classes is proposed. The performance of the scheme is evaluated using chosen grade of service (GoS) and quality of service (QoS) parameters.
Performance of an S-CDMA system with noncoherent spread-spectrum MSK modems

Simplified noncoherent and differentially coherent spread-spectrum (SS) minimum shift keying (MSK) receiver structures are presented. It is shown that an optimal noncoherent SS receiver for pure (with rectangular baseband pulses) offset QPSK signals can serve as a suboptimal (performance loss /spl sime/0.9 dB) noncoherent receiver for SS MSK signals. The conditions of orthogonality of SS MSK signals are derived in synchronous and quasi-synchronous code-division multiple-access (CDMA) systems. Computer simulation results evaluate the performance of the CDMA system with suggested receivers under certain conditions.
Export quality and economic growth in the 2000 s 1

This paper examines the relationship between composition of exports and economic growth for a large set of countries, between 2000 and 2013, following the assumption that the technological structure of exports has important implications for economic development. The paper builds an index of exports quality, based on the classification by technological intensity proposed by Lall (2000): primary products, resource-based manufactures, low-tech, mediumtech and high-tech manufactures. Then, we estimate the relationship between quality of exports and economic growth by using panel data models. The results suggest that the export quality index is highly significant to explain economic growth. Between 2000 and 2008, booming demand for commodities benefited exporters of primary products and resourcebased manufactures, and lower export quality is associated with higher rates of economic growth. For 2009-2013, in turn, results confirm what is expected by theory and suggest that export structures with higher technological content have brought about positive effects on economic performance.
O Optimal Distinctiveness Theory

Optimal distinctiveness theory was created to explain the psychological motivations driving people to identify with groups. The theory states that humans have two competing motivations: a need to belong and a need to feel unique or distinct. These two needs work in opposition and can be activated or deactivated depending on the context. The theory was proposed by Marilynn Brewer in 1991, and is based on previous research on social identity theory, social dilemmas, and evolutionary biology. This entry will cover the history of optimal distinctiveness theory, its basic tenets, its implications for intergroup relations, related psychological concepts, and future directions for research.
Image Classification with Pyramid Representation and Rotated Data Augmentation on Torch 7

This project classifies images in Tiny ImageNet Challenge, a dataset with 200 classes and 500 training examples for each class. Three network architectures are experimented: a traditional architecture with 4 convolutional layers + 2 fully-connected layers; a Tiny GoogleNet with 3 inception layers; and a pyramid representation-based network. Tiny GoogleNet achieved the highest top-1 validation accuracy of 47%. Work is done to reduce overfitting. Dropout improves validation accuracy by 10%. Dataaugmentation of random crop and horizontal flip increased validation accuracy by 10%. Rotation does not appear to improve validation accuracy. Pyramid representation shows significant computational efficiency, achieving similar top result 240% faster computation time per batch. Training accuracy converges at 65 70% for all three networks. Future work is to increase expressive power of network. Training was done on Torch 7 with Facebook’s Deep Learning Extension.
Quality Adaptation in P2P Video Streaming Based on Objective QoE Assessment

The transmission of video data is a major part of traffic on today’s Internet. Since the Internet is a highly dynamic environment, quality adaptation is essential in matching user device resources with the streamed video quality. This can be achieved by applying mechanisms that follow the Scalable Video Coding (SVC) standard, which enables scalability of the video quality in multiple dimensions. In SVC-based streaming, adaptation decisions have long been driven by Quality of Service (QoS) metrics, such as throughput. However, these metrics do not well match the way human users perceive video quality. Therefore, in this paper, the classical SVC-based video streaming approach is expanded to consider Quality of Experience (QoE) for adaptation decisions. The video quality is assessed using existing objective techniques with a high correlation to the human perception. The approach is evaluated in context of a P2P-based Video-on-Demand (VoD) system and shows that by making peers favor always layers with a high estimated QoE but not necessarily high bandwidth requirements, the performance of the entire system can be enhanced in terms of playback delay and SVC video quality by up to 20%. At the same time, content providers are able to reduce up to 60% of their server costs, compared to the classical QoS-based approach.
V isualizing Workload and Emotion Data in Air Trafﬁc Control: A Tool to Support the Supervisors Awareness of a Complex Situation

—A supervisor, working in an area control center in air trafﬁc control has direct impact on the performance of the air trafﬁc controllers. Thus, he/she has to be well informed about the situation within the center. In order to support the supervisors work, researchers try to measure the air trafﬁc controllers’ cognitive workload and stress. Within this paper we present a visual tool to support the supervisors awareness about this data. We outline the whole design process including preliminary studies, the iterative process leading to a ﬁnal prototype, and its evaluation. We propose a design divided into three views, to serve the supervisor’s information needs. Using cumulated color values to represent time series, seems to be a promising approach for getting a quick overview on the whole situation.
Prospect Theory and Travel Behaviour: a Personal Reflection Based on a Seminar

This paper is the final paper of a special issue on Prospect Theory (PT) and its applications in travel behaviour research. It is largely (but not exclusively) based on discussions held during a seminar that took place on the 8th of October 2009. The paper presents some personal reflections based on the discussion subjects on the use of PT in the area of travel behaviour research, clustered by the position of PT as a theory, applications of PT, future research, and relevance for policy making. The most important conclusion of the papers are firstly that PT, in addition to other theories like Utility Theory (UT), can help to improve our understanding of choices in the area of travel behaviour. The concepts of loss aversion and reference points are especially useful. A second important conclusion is that PT is not the only theory challenging UT. For example Regret Theory and the concept of Bounded Rationality also challenge PT. In addition, some of the premises of PT, at least the importance of some reference points, are not exclusively the domain of PT, but also that of other theories, including UT. Thirdly, it is important to realize that critics of Utility Theory (UT) as it is used in specific studies related to travel behaviour are not necessarily critics of UT in general. Fourth, it seems better to focus on the distinguishing premises of PT than on the theory as a fully fledged alternative to UT. A fifth outcome is that PT can be used both to increase our understanding of travel behaviour, as well as for the evaluation of the outcomes of models. A final outcome is that there is no need to choose a theory before collecting the data.
Design optimizations of spiking hardware neurons

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy DESIGN OPTIMIZATIONS OF SPIKING HARDWARE NEURONS By Manu Rastogi May 2012 Chair: John G. Harris Major: Electrical and Computer Engineering Over millions of years of evolution, biology has optimized the neuron structure and the interconnects for energy consumption and communication. Inspired by biology many research groups would like to build large arrays of neurons in hardware for efficient solutions to engineering problems. The purpose of this research is to provide a framework and design methodology for improving the energy efficiency of existing silicon neurons. Although there exist extremely complex silicon implementations of biologically realistic models, it is debatable whether or not using a biologically realistic model has any significant advantage over other models for solving realistic engineering challenges. Thus, as part of this work, design optimizations are performed the integrate and fire (I&F) model. In the past it has been shown that the I&F model can be used for encoding continuous time signals into asynchronous pulse trains. Under certain ideal conditions the original signal can be mathematically reconstructed perfectly from these pulse trains. We use the error introduced by the silicon neuron in the timing of the pulse trains and subsequently the error in the reconstructed signal as the benchmark for optimizing the neuron design. We build a framework for estimating the error introduced in reconstruction due to the timing jitter in the pulses. The model is verified using a simulated I&F circuit. This estimate serves as the maximum attainable signal reconstruction accuracy. Based on these estimates circuit topologies with the most favorable speed-resolution trade-off are
RESOURCE MANAGEMENT ANALYSIS OF AQUACULTURE SUSTAINABILITY ( The Case Studies Floating Net Cages Reservoir at Cirata )

Freshwater aquaculture resources by utilizing open access aquatic such as reservoirs widely used for floating net cages fishery. Activities floating net cages aquaculture should be managed in a structured to balance the economic value to be obtained open access aquatic with ecological values common in the future. Freshwater aquaculture is not independent of environmental conditions climate change in weather from dry season to rainy season which led to trun over Cirata reservoir. This study aims to analyze the management of fishery resources sustainable freshwater aquaculture. The technique of taking respondents conducted by purposive random sampling. The analytical tool used Rapfish models for freshwater aquaculture. Resource management of freshwater aquaculture sustainable approach analyzed the ecological, economic, technological, social and institutional arrangements of local government. Based on the results of research resources management of freshwater aquaculture in Cirata economic and social dimensions of institutional support sustainable resource use open access aquatic for aquaculture, while the dimensions of ecology, technology and regulations of local government has not supported the sustainability of resource management for the general freshwater aquaculture using floating net cages.
Political Science: KEDS—A Program for the Machine Coding of Event Data

This paper describes in technical detail the Kansas Event Data System (KEDS) and summarizes our experience in coding Reuters data for the Middle East. The components of KEDS are first described; this discussion is intended to provide sufficient detail about the program that one could develop a more sophisticated machine-coding system based on our research. We then discuss a number of problems we have encountered in machine coding, focusing on the Reuters data source and the KEDS program itself. The paper concludes with a discussion of future approaches to machine coding in event data research and other potential applications of the technology. Keywords. event data, natural language, full-text databases, international relations, social science.
Competitive Intelligence and Knowledge Management : An Analysis of the Literature

In recent years, especially in the field of management, concepts such as competitive intelligence and knowledge management have gained a rising interest as a result of information explosion. Nevertheless, these concepts need an additional effort to perceive the common features in both practice and research. Nowadays, numerous studies consider knowledge as the lifeblood of companies and as a valuable organizational resource. In a knowledge based context, there has been growing awareness about the importance of knowledge as an organizational performance driver. In this sense, how do competitive intelligence and knowledge management interact to create knowledge and optimize organizational performance? Drawing upon the literature review and analysis of both competitive intelligence and knowledge management processes, we discuss several important research concerns surrounding the role of these two concepts in achieving organizational performance. The main purpose of this article is to shed some light on competitive intelligence and knowledge management as powerful catalysts for knowledge creation, and as the foundation for organizational performance.
Performance Analysis of Digital Tanlock Loop

In this paper, a nonuniform-sampling digital phaselocked loop (DPLL) called the digital tanlock loop (DTL), which uses a new type of phase error detector with linear phase characteristic, is studied. The main feature of the DTL is that the phase error detector, using the tan^{-1}(.) function with in-phase and quadrature samples of the incoming signal, has a linear characteristic with a period of 2π. Accordingly, the DTL can be characterized by a linear difference equation, thereby making it possible to analyze the loop easily, without approximation of nonlinearity as is usually done in analysis of a conventional DPLL with sinusoidal phase characteristic. The performances of the first- and second-order DTL's in the absence and presence of noise have been investigated by analysis and computer simulation. It is shown that the linear phase characteristic results in many attractive features in comparison to the conventional DPLL with the sinusoidal phase characteristic. These include insensitivity of the locking conditions to variation of input signal power, more noise immunity, wider lock range and less steady-state phase error of the first-order loop for an input with frequency offset, and much less sensitivity to initial phase errors in convergence of the second-order loop.