Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal Visualization of Building Occupancy Phase

Numerous interrelated factors affect building performance. Physical building elements, internal and external climatic conditions, and building occupants interact through time to impact the way a building consumes resources. Currently, however, leading building performance software programs represent much of the information related to these factors in text or chart form. Such representations make it difficult for building designers, operators, and other stakeholders to understand how this information interacts through time. This paper describes an early prototype called OViz, which creates spatio-temporal representations of (observed and/or assumed) geometry, occupancy, environmental, and performance data, and enables users to visualize and explore how this information changes through time in a 3D environment. We are testing the extent to which these visualizations help designers and operators understand and detect meaningful patterns and interrelationships amongst the information and whether they can support design and operations decisions.
arboART: ART based hierarchical clustering and its application to questionnaire data analysis

A hierarchical clustering mechanism is designed to analyze multidimensional data and feature selection based on ART-type neural networks. Prototype of clusters obtained from an ART's top-down vectors are sent to another ART. Several ART networks that have different similarity criteria are used for cluster combination. This scheme of hierarchical clustering (arboART) enables to make a tree structure graph of classification result of samples, and find features of each cluster. arboART is utilized to automatic rule generation of Kansei engineering expert systems. Analyzing result on color evaluation experiment by arboART and comparison with conventional multivariate analysis are shown.
Heuristic remarks and mathematical problems regarding the theory of connecting systems

A connecting system consists of a set of terminals, a control unit for processing call information, and a connecting network. Together, these three elements provide communication, e.g., supply telephone service, among the various terminals. In this paper we present a comprehensive view of the theory of connecting systems, an appraisal of its current status, and some suggestions for further progress. The existing probabilistic theory is reviewed and criticized. The basic features of connecting systems, such as structure, random behavior, complexity, and performance, are discussed in a nontechnical way, and the chief difficulties that beset the construction of a theory of traffic in large systems are described. It is then pointed out that despite their great complexity, connecting systems have a definite structure which can be very useful in analyzing their performance. A natural division of the subject into combinatory, probabilistic, and variational problems is drawn, and is illustrated by discussing a simple problem of each type in detail.
Capacity considerations for trellis code multiple access systems

Trellis code multiple access (TCMA) is a narrow-band multiple access scheme. There is no bandwidth expansion, so K users are using the same bandwidth as one single user. The load (the number of bits per channel use) of the system is therefore much higher than the load in, for example, conventional CDMA systems. It is shown here that the maximum number of users in a TCMA system is usually modest. This fact is based on constellation-constrained capacity, i.e., the maximum capacity of a system with a specific constellation of the transmitted symbols. The minimum required signal-to-noise ratio for reliable transmission is also given for different code rates.
Learning algorithm for nonlinear support vector machines suited for digital VLSI

A learning algorithm for radial basis function support vector machines (RBF-SVMs) that can be easily implemented in digital VLSI is proposed. It is shown that, as opposed to traditional artificial neural networks, learning in SVMs is very robust with respect to quantisation effects deriving from the finite precision of computations.
A Consideration of Temperature Coefficient on Gate-Voltage-Controlled PTAT Voltage Generator under Ultra Low Power Supply

A way of large temperature coefficient on PTAT voltage generator is proposed. By stacking the proposed circuits, a PTAT voltage generator with large temperature coefficient can be realized. The PTAT voltage generator is analyzed by use of 4-terminal MOSFET model in subthreshold region based on the diffusion current. The temperature coefficient of measured value is compared with that of theoretical value.
Adaptive tracking algorithm based on direction field using ML estimation in angiogram

We present a new tracking algorithm for the main artery contours in a digital angiogram. The proposed work extracts features and profiles the narrow blood vessel, mainly the blood vessel in the digital subtraction angiography image. A consecutive value is performed on the boundary detection by calculating maximum-likelihood (ML) estimation on adjacent pixels. The proposed algorithm adaptively detects the position of the centerline as a direction vector with the entire vessel's direction field. ML estimation is most effective at profiling for a vessel's contour having anomalies and noise. This proposed algorithm is intended to support radiologists in diagnosis, radiation therapy planning, and surgical planning.
Implementation of Parallel Lanczos Method for Intrusion Detection with Cloud Technologies

The aim of dimensionality reduction is to construct a low-dimensional representation of high dimensional input data in such a way, that important parts of the structure of the input data are preserved. This paper proposes to apply the dimensionality reduction to intrusion detection data based on the parallel Lanczos-SVD (PLSVD) with the cloud technologies. The massive input data is stored on distribution files system, like HDFS. And the Map/Reduce method is used for the parallel analysis on many cluster nodes. Our experiment results show that, compared with the PCA algorithm, PLSVD algorithm has better scalability and flexibility.
Simulation of the ECG and MCG Applying a Cellular Automaton Model of the Entire Human Heart

Cardiac modelling [l, 4, 5, 6, 7, 8] is of great importance for studying propagation phenomena on a microscopic and macroscopic level (e.g. studying the initation of reentries) and for the investigation of the relationship between the primary sources within the cardiac tissue and the electric and magnetic field inside and outside the volume conductor. Microscopic models based on differential equation Systems are limitted to twoor three-dimensional blocks of tissues. Propagation models for the entire human heart are in general of the macroscopic type and are based in most cases on cellular automata theory.
Image deblurring with adaptive total variation model

In this paper the models of blurring and methods of deblurring are introduced. A kind of nonlinear image deblurring approach is discussed, which comes from constrained optimization total variation approaches. An adaptive TV model method of image deblurring based on common TV model methods is proposed. The experimental results indicate that the proposed method can protect the details of the blurry image more efficiently and satisfy some deblurring requirements more adaptively.
An Introduction to Satisfiability Algorithms

In this paper we present an introduction to satisfiability algorithms. Since most complete SAT solvers (e.g. Satz, SATO, GRASP, and Chaff) are based on the Davis-Putnam procedure, we first describe in detail that procedure. Then, we present the improvements that can be incorporated into the Davis-Putnam Procedure in order to develop a competitive SAT solver: optimized data structures, variable selection heuristics, non-chronological backtracking, conflict-driven learning, and restarts. Finally, we describe GSAT and WalkSAT, which are the most widely used local search algorithms for solving SAT.
Active Versus Passive Processing of Spatial Information in a Computer-Simulated Environment

In Experiment 1, participants explored a desktop computer-simulated three-dimensional environment. Subsequently, they were asked to point to objects that were not directly visible from the test locality, and to draw a plan view of the environment. In Experiment 2, following exploration of a less complex computer-simulated environment, participants completed a test of their ability to find objects that had been encountered during the course of exploration. In neither experiment was there any evidence that psychological activity (directing the course of exploration) or physical activity (interacting with the computer) had an effect on the acquisition of spatial knowledge. Comparisons with control participants, who were not allowed to explore the simulations, confirmed that experimental participants had acquired good representations of the virtual environments.
A New Iterative Modularity-Based Method for Graph Clustering on Scalable Networks

Due to the advancement of technology, modern networks such as social networks, citation networks, Web networks have been extremely large, reaching millions of nodes in a network. But most of the existing graph clustering algorithms can only tackle with small or medium-size networks. In this paper, we introduce a new method which can achieve high graph clustering quality for large scale networks by optimizing the modularity function. It is based on the iterative idea and takes good advantage of the exsiting multilevel local search heuristics. After introducing this modularity-based method, we evaluate its performance by applying it to several well-known network datasets. With a cost of more but acceptable time, it outperforms the best algorithms in the literature in the case of modularity optimization quality.
RISK-SENSITIVE CONTROL: A BRIDGE BETWEEN H2 AND Ho0 CONTROL

This talk is devoted to the study of the connections among risk-sensitive stochastic optimal control, dynamic game optimal control, risk-neutral stochastic optimal control and deterministic optimal control in a nonlinear, discrete-time context with complete state information. The analysis worked out sheds light on the profound links among these control strategies, which remain hidden in the linear context. In particular, risk-sensitive control combines features of both stochasiic risk-neutral (Hz) control and deierministic dynamic game (H,) control.
Analysis of Cloud Storage and its Data Security

In this day and age, there is a disruptive shift in technology concerning the powerful ability of cloud storage that back up and store large data in the cloud, as well as syncing it across multiple devices automatically, and its drawbacks in data security. This paper mainly presents an overview of cloud storage, highlights many of security issues and vulnerabilities in cloud storage, lists various solutions, and then gives a summary.
False track discrimination in a 3D signal/track processor

Long range detection and tracking of moving targets against clutter requires advanced signal and track processing techniques in order to exploit the ultimate capabilities of modern electro-optical sensors. These include three- dimensional filtering and multiple hypothesis tracking. Unfortunately, features present in real backgrounds can lead to false alarms which must be recognized in order to achieve a low false track rate. This paper describes one approach which was successful at mitigating clutter-induced false tracks while maintaining the low thresholds necessary for the detection of weak targets. This technique uses information derived in the signal processor describing the local background as additional discriminants in the track processor to identify false tracks caused by clutter leakage. We present an overview of the 3D signal track/processor, the false track mitigation methodology, and experimental results against real background data.
A Band Selection Method based on Synthesized Information Content for Hyper-spectral Pixel Un-mixing

Hyper-spectral remote sensing has the defects of huge data size and massive information redundancy, especially when processing pixel un-mixing, which always has high computation complexity. This paper proposes a band selection method for hyper-spectral pixel un-mixing, based on synthesized parameters of information content. It uses Kullback-Leibler divergence and mutual information with respective weights to construct a new comprehensive information matrix. The matrix can indicate the overall distribution of data's spectral information. According to the comprehensive information matrix, the method can select a small-number band combination from the massive bands of initial data in an iterative way. The experimental results show that, the method is effective in decreasing data volume and retaining effective spectral information, its result is better than those of similar algorithms. This method can be chosen as an effective preprocessing step for hyper-spectral pixel un-mixing.
Restructuring a Master's degree dissertation as a Patchwork Text

This paper describes the introduction of the Patchwork Text format into the dissertation on a Master's degree in Social Work. The rationale for rethinking the conventional dissertation is discussed and the ‘patches’ making up the revised dissertation format are detailed. The paper draws upon the completed dissertations of two students on the programme to illustrate how the characteristics of the Patchwork Text have provided a very different learning experience for the students involved; and in doing so offers a preliminary evaluation of the Patchwork Text as an alternative mode of supervising and assessing dissertation students.
Invisibility Cloak: Science Fiction Transforming into Reality

The famous science fiction writer H.G. Wells when wrote the book “The Invisible Man”, nobody would have thought that the idea of an innovative man can be transformed from fiction to reality one day. Researchers at various institutes all over the world have already taken a step further in order to make that dream reality when the human is able to disappear i.e. not visible to human eyes even when he is already there. This paper reviews about the latest trending technology in this field known as optical camouflage. This phenomenon can create an illusion to the human eye that the person next to him is partially invisible. However we are trying to advance this technology to make the object fully disappear. The material that would help us do that is known as meta-material. It is not found or discovered but it is designed using the modern science and engineering by making specific pattern.
A 2.2 Gbps CMOS look-ahead DFE receiver for multidrop channel with pin-to-pin time skew compensation

A CMOS LADFE (look-ahead decision feedback equalization) receiver with a pin-to-pin time skew compensation was proposed and implemented for high-speed chip-to-chip communication such as multi-drop DRAM interface. The look-ahead scheme in DFE input buffer increased the maximum data rate from 1.4 Gbps to 2.2 Gbps. Different sampling clock was synthesized for each pin by using an /spl times/2 over-sampling scheme. Active chip area per pin is 100 /spl mu/m/spl times/800 /spl mu/m with a 2.5 V, 0.25 /spl mu/m CMOS process.
Over verrassende en soms ernstige gevolgen van een excellente internistenopleiding

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Sensitivity of orographic precipitation enhancement to horizontal resolution in the operational Met Office Weather forecasts

Rain gauge observations show that when averaged over a large number of cases of frontal systems passing over the UK, strong orographic rain enhancement occurs on the lee slopes of the first hills encountered by the southwesterly flow in the warm sector. The operational forecasts using 1.5 km grid spacing produced realistic looking mean rainfall patterns over the Lake District and Wales, with an area‐averaged rain accumulation error of less than 2%. Model‐level rain rates increase with decreasing altitude consistent with the seeder‐feeder mechanism. Increasing the horizontal grid spacing in the operational weather forecast model decreases the amount of rain produced over the hills, thereby reducing forecast accuracy. The area‐averaged rain accumulations are 11–24% smaller than observed at 12 km grid spacing and 33–48% smaller than observed at 40 km grid spacing.
Specific Activation by Microwaves: Myth or Reality?

Ene reactions involving carbonyl enophiles have been carried out under microwave irradiation at controlled temperature and atmospheric pressure. The reactions of diethyl mesoxalate with 1-decene and β-pinene and the cyclization of (+)-citronellal under homogeneous (neat liquid) or heterogeneous (clay catalyst) conditions have been studied. In each case the dependence of reaction yield on time and the stereoisomer ratios of the products are unaffected by the heating mode
A new double talk detector using the lattice predictors for an acoustic echo canceller

We propose a new intelligent double talk detector that can not only detect double talk fast but also distinguish the echo path change from the double talk without a decision delay. The detection mechanism is performed by observing the change rate of the reflection coefficients of the two lattice predictors that are placed on the near-end and far-end terminals. The excellence of the proposed method is verified by computer simulations using real speech signals.
A Semantic Basis for Meaning Construction in Constructivist Interactions

Regarding constructivism as a learning philosophy and/or a model of knowing, a person (learner or mentor) based on her/ his preconceptions and on personal knowings could actively participate in an interaction with another person (learner or mentor) in order to construct her/his personal knowledge. In this research I will analyse 'meaning construction' within constructivism. I will focus on a semantic loop that the learner and mentor as intentional participants move through and organise their personal constructed conceptions in order to construct meanings and produce their individual meaningful comprehensions. Subsequently, I will provide a semantic framework for analysing the meaning construction based on personal knowings and personal conceptions within constructivist interactions. This research could propose a new scheme for interpretation based on semantics and on interaction.
REVIEW AND EVALUATION OF RELIABILITY GENERAL IZATION RESEARCH

OF DISSERTATION REVIEW AND EVALUATION OF RELIABILITY GENERALIZATION RESEARCH Reliability Generalization (RG) is a meta-analytic method that examines the sources of measurement error variance for scores for multiple studies that use a certain instrument or group of instruments that measure the same construct (Vacha-Haase, Henson, & Caruso, 2002). Researchers have been conducting RG studies for over 10 years since it was first discussed by Vacha-Haase (1998). Henson and Thompson (2002) noted that, as RG is not a monolithic technique; researchers can conduct RG studies in a variety of ways and include diverse variables in their analyses. Differing recommendations exist in regards to how researchers should retrieve, code, and analyze information when conducting RG studies and these differences can affect the conclusions drawn from meta-analytic studies (Schmidt, Oh, & Hayes, 2009) like RG. The present study is the first comprehensive review of both current RG practices and RG recommendations. Based upon the prior research findings of other meta-analytic review papers (e.g., Dieckmann, Malle, & Bodner 2009), the overarching hypothesis was that there would be differences between current RG practices and best practice recommendations made for RG studies. Data consisted of 64 applied RG studies and recommendation papers, book chapters, and unpublished papers/conference papers. The characteristics that were examined included how RG researchers: (a) collected studies, (b) organized studies, (c) coded studies, (d) analyzed their data, and (e) reported their results. The results showed that although applied RG researchers followed some of the recommendations (e.g., RG researchers examined sample characteristics that influenced reliability estimates), there were some recommendations that RG researchers did not follow (e.g., the majority of researchers did not conduct an a priori power analysis). The results can draw RG researchers’ attentions to areas where there is a disconnect between practice and recommendations as well as provide a benchmark for assessing future improvement in RG implementation.
Common music. A music composition language in common lisp and CLOS

Common Lisp (Steele 1990) and the Common Lisp Object System (Bobrow 1988) provide an environment uniquely suited to the exploratory and incremental process of musical composition. Common Music is a high-level music composition language built in Common Lisp and CLOS designed to support computer composition in a variety of score formats through a common protocol. Initially prototyped on a Symbolics Lisp machine, the system runs under most Common Lisp environments found on standard computers such as Apple Macintosh and NeXT machines. Common Music is currently offered at CCRMA as part of course work for computer music classes and workshops. It is available through anonymous file transfer (ftp) on the machine ccrma-ftp in the file named /pub/cm.tarfile. Z
Scaling of high-k dielectrics towards sub-1nm EOT

High-k dielectric layers are deposited using ALD or MOCVD. Most of the work focused on Hf-based high-k dielectrics, either as pure HfO/sub 2/, as silicate or mixed with Al/sub 2/O/sub 3/. In some cases nitrogen is added to improve the high-temperature stability. Various surface preparation methods and deposition conditions are tested. Compatibility of the high-k stacks with poly-Si and metal electrodes is investigated. Significant improvements in yield and thermal stability are obtained by optimized modifications of the high-k stack. Scaling of the equivalent oxide thickness (EOT) is accomplished by implementing novel ideas in interface engineering and high-k materials processing. High-k stacks are tested in transistor structures with small gate lengths. The origin of the electrical instabilities and the observed drive current degradation of high-k transistors as compared to the SiO/sub 2/ reference transistors are studied in detail.
Multi-level spatial modeling for stochastic distributed robotic systems

We propose a combined spatial and non-spatial probabilistic modeling methodology motivated by an inspection task performed by a group of miniature robots. Our models explicitly consider spatiality and yield accurate predictions on system performance. An agent's spatial distribution over time is modeled by the Fokker-Planck diffusion model and complements current non-spatial microscopic and macroscopic models that model the discrete state distribution of a distributed robotic system. We validate our models on a microscopic level based on sub-microscopic, embodied robot simulations as well as real robot experiments. Subsequently, using the validated microscopic models as our template, abstraction is raised to the level of macroscopic difference equations. We discuss the dependency of the modeling performance on the distance from the robot origin drop-off location and temporal convergence of the team distribution. Also, using an asymmetric setup, we show the necessity of spatial modeling methodologies for environments where the robotic platform underlies drift phenomena.