Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Sampling Design for Spatio-Temporal Prediction

© 2013 John Wiley & Sons, Ltd. All rights reserved. Environmental monitoring provides a typical setting that gives rise to spatio-temporal design problems. This chapter considers the model-based design, in which the optimal design problem requires two key features to be specified: (i) a statistical or mathematical model for the process under consideration; and, (ii) a criterion with respect to which the design is required to be optimized. After reviewing spatial and spatio-temporal adaptive designs it considers the performance of adaptive design-finding algorithms with respect to these for two different models for stochastic process S: the stationary Gaussian model; and a dynamic process convolution model. The chapter uses the second of these models to consider adaptive designs for the Upper Austria rainfall data. It concludes that adaptive designs should be constructed by a criterion that directly measures the extent to which the primary scientific goal of the analysis is being met, and should therefore be strongly context-dependent.
A NOVEL DATA MINING ALGORITHM AND KNOWLEDGE-BASED DIAGNOSTIC RULES FOR MEDICAL THERMOGRAPH

Diagnosis with medical infrared thermograph has long been recognized as lack of objective assessment and scientific analysis in clinical applications. In this study, a novel data mining algorithm with a parametric factor analysis protocol was utilized for generating knowledge-based diagnostic rules from infrared thermograph. These governing rules were developed through four-stage imaging analysis processes, i.e. geometric lofting standardization, abnormal region statistics, parametric factors analysis, and anatomical organs matching. In the first stage, Beier–Neely field morphing and linear affine transformation algorithms were used in geometric standardization for whole body contour and partial region, respectively. In addition, these two transformation methods were applied to solve the dilemma of thermal image deformation. In the second stage, pixels of abnormal body temperature were classified by a confident level. Cohesive and de-noises parameters were gathered to unify the pepper-like pixels into abnormal regions. In the third stage, 25 parametric factors were extracted from each abnormal region, and decision tree induction method was used to generate the knowledge-based diagnostic rules. In the final stage, the minimum box method was utilized for anatomical organ matching to identify the corresponding organ with abnormal temperature distribution. To verify the validity of the proposed knowledge-based diagnostic rules, a total of 71 and 131 female patients with and without breast cancer, respectively, were both analyzed in this study. Experimental results indicated that a total of 1750 abnormal regions (703 positive and 1047 negative) were detected. Based on decision tree induction method, 822 branches were broken down in the decision space. The more positive abnormal regions that were found in the terminal nodes of a specific branch, the higher the possibilities were for having cancer. Fourteen branches of the decision tree with terminal nodes were found to have more than four positive abnormal regions. Sixty one positive abnormal regions (61/703 = 8.6%) from 44 cancer patients (42/71 = 59.2%) can be found in the above-mentioned 14 branches. In conclusion, the test results reveal that the proposed data mining algorithm and knowledge-based diagnostic rules may be effective in clinical diagnosis of thermograph regardless of the type of disease.
Image coding with fuzzy image segmentation

A system of fuzzy rules can segment images to provide high-compression image coding. Segmentation-based image coding can achieve higher compression rates than information-theoretic imaging coding. Fuzzy image segmentation generalizes region-growing segmentation. The fuzzy rules use high-frequency information, computed with local edge-detection operators, to remove false contours in segmented images. The fuzzy segmentation-based image coding achieved faithful decoded images at more than 50:1 compression. <<ETX>>
A 0.5 V/100 MHz over-V/sub CC/ grounded data storage (OVGS) SRAM cell architecture with boosted bit-line and offset source over-driving schemes

This paper proposes a 0.5 V/100 MHz/sub-5 mW-operated 1-Mbit SRAM cell architecture which uses an over-V/sub CC/ grounded data storage (OVGS) scheme. The key target of OVGS is to minimize the charge amount supplied from the embedded charge pump circuits, which are required to boost the effective gate to source voltage (V/sub 0/=V/sub GS/-V/sub T/) up to 0.8 V necessary to achieve 100 MHz-operation even at 0.5 V single power-supply. Thus, the key low-power strategy of OVGS is "putting the right (higher efficiency) boosted power-supply from the charge pump circuit into the right position in the SRAM cell". This paper focuses on why OVGS can realize a greater saving of the charge amount supplied from the boosted power-line and can reduce the power dissipation to /spl les/1/30.4 and /spl les/1/3.9 compared to the previously reported negative source drive (NSD) scheme (Mizuno et al., 1995) and negative word-line drive (NWD) scheme (Itoh et al., 1996), respectively, while achieving a 0.5 V/100 MHz-operation.
Simulation and PID Control of Bullwhip Effect in Closed-Loop Supply Chain based on Noise Bandwidth

In order to describe quantitatively and control effectively the bullwhip effect in closed-loop supply chain, modeling and analysis method of control theory was applied to establish z-domain model of single-echelon closed-loop supply chain. By z-transform, the discrete transfer function was constructed. And based on noise bandwidth of the transfer function between demand and order, the bullwhip effect of closed- loop supply chain was quantified and analyzed. By designing Genetic Algorithm (GA), tuning control parameters in Proportion-Integral-Differential (PID) controller were obtained. Thus, PID controller was designed in order to control the bullwhip effect. Simulation results indicated the designed PID controller can eliminate effectively the bullwhip effect of closed-loop supply chain.
Sinhala Speech Recognition

- Speech recognition stands to convert the human voice into the text that similar to the information being conveyed by the speaker. This paper aims to find a suitable method for Sinhala Speech Recognition. For that the paper goes through 2 approaches, the isolated word recognition and continuous speech recognition. The paper uses Artificial Neural Networks to go through the Continuous Speech Recognition approach, and Mel Frequency Cepstral Coefficients (MFCC) and Dynamic Time Warping (DTW) as feature matching and feature extraction techniques under isolated word recognition. By using above techniques, experimental results show that overall accuracy is higher in isolated word recognition than continuous speech recognition.
Network coding offers new communications paradigm across multiple disciplines

The idea of network coding (NC, also known as netcode) is readily illustrated by the puzzle shown in Figure 1. Each arrow in the butterfly network is a channel for transmitting one bit of data. To receivers R1 and R2 the source intends to deliver a message represented by the two bits a and b. In straightforward fashion, bit a reaches node V and receiver R1 while bit b reaches V and R2. The dilemma concerns which bit node V should forward to node W upon receiving both data bits. If it forwards bit a, then receiver R1 will not get bit b. If it instead forwards b, R2 will not receive a. The solution is for node V to send out a bit indicating whether a and b are equal; for example, bit 0 when they are equal or otherwise bit 1. This new bit is called the binary sum or the exclusive OR between a and b in computer logic. When the new bit is forwarded from node W, it is used by receiver R1 to decode the value of b and by R2 for the value of a. While the dilemma confounds the conventional store-and-forward mechanism (i.e., copying), the solution suggests a fundamental concept that blends coding with data forwarding. Partial hints along these lines have appeared sporadically in the literature, including redundant array of independent disks (RAID), access to multi-channel LAN, and satellite networks. The concept was formalized as ‘network coding’ over a generic abstract network and its superiority to store-and-forward has been mathematically proven. Advantages can be quantified in terms of bit rate, latency, energy consumption, and other transmission variables. What types of communications networks can benefit from NC? One general scenario is broadcasting and data transmission in nature (such as wireless communication) including ad hoc and sensor networks. Another prospective use involves separate transmissions competing for a channel. To benefit from NC, the main effort must be to encode at intermediate nodes and to Figure 1. A message is represented by the two bits a and b. Which bit should node V send to node W in order for the message to reach both receivers R1 and R2?
Issues affecting virtual universities

The paper outlines the contemporary field of virtual universities in the US and UK, and discusses potential future issues that may affect this educational market. The authors contend that there is no such thing as a ‘model’ virtual university, and the composition of a successful virtual educational environment will depend very much on factors such as the courses being delivered, the nature of the student body (both local and remote), and a range of institutional issues. Certain issues, however, will always apply to the processes of virtual education regardless of the audience and institution. The authors outline these generic elements that will contribute to a successful virtual university.
A Diachronic View of Pronominal Reference in English

Proceedings of the Second Workshop on Anaphora Resolution (WAR II). Editor: Christer Johansson. NEALT Proceedings Series, Vol. 2 (2008), 1-9. © 2008 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio. no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle. net/10062/7129 .
Different strategies to improve sensitivity and power of the wake-up receivers

In this paper different alternatives of wake-up receiver in ultra-low power wireless sensor nodes are studied. The limitations of power dissipation, area or cost require a holistic approach to the problem, taking into account every stage of design such as the architecture and the radio frequency sub-system. Reduce data communication only when necessary can be achieved using two radios, one for standard communication as transceiver and another devoted to wake-up receiver. The wake-up receiver listens the input signal to detect the addressed bit sequence. This work deals with the wake-up receiver design of different architectures. A comparison of the trade-off between them is performed. In each case characteristics such as sensitivity or distances with low power consumption are exposed. The input signal of the wireless sensor node is a 125 kHz on-off keying modulated at 868 MHz and the circuits are designed to operate in 868 MHz band. A first option is used a tuned radio frequency architecture with a discrete detector with Schottky diode to demodulates the OOK signal. The following structure is with an envelope detector where the envelope detector is designed in weak inversion to have a low consumption. Is possible improve the voltage gain including an impedance matching in the input of the detector. Other option is including an amplifier before the detector to improve detector sensitivity. The amplifier with active inductor has to be in subthreshold region to have moderate power consumption. The circuits are designed in UMC CMOS 65 nm technology with 1.2 V supply.
Extracting robust trends in species’ distributions from unstructured opportunistic data: a comparison of methods

Policy-makers increasingly demand robust measures of biodiversity change over short time periods. Long-term monitoring schemes provide high-quality data, often on an annual basis, but are taxonomically and geographically restricted. By contrast, opportunistic biological records are relatively unstructured but vast in quantity. Recently, these data have been applied to increasingly elaborate science and policy questions, using a range of methods. At present we lack a firm understanding of which methods, if any, are capable of delivering unbiased trend estimates on policy-relevant timescales. We identified a set of candidate methods that employ either selection criteria or correction factors to deal with variation in recorder activity. We designed a computer simulation to compare the statistical properties of these methods under a suite of realistic data collection scenarios. We measured the Type 1 error rates of each method-scenario combination, as well as the power to detect genuine trends. We found that simple methods produce biased trend estimates, and/or had low power. Most methods are robust to variation in sampling effort, but biases in spatial coverage, sampling effort per visit, and detectability, as well as turnover in community composition all induced some methods to fail. No method was robust to all forms of variation in recorder activity. We warn against the use of simple methods. We identify three methods with complementary strengths and weaknesses that are useful for estimating timely trends. Sophisticated correction factor methods, including Occupancy and Frescalo, offer the greatest potential in the long-term. Methods based solely on selection criteria are inherently limited, but a combination or ensemble of approaches may be required to generate trends that are both robust and powerful. Small amounts of information about sampling intensity, captured at the point of data collection, would greatly enhance the utility of opportunistic data and make future trend estimates more reliable.
Thermal effects and electro-thermal modeling in power bipolar transistors

Dynamic electro-thermal instabilities of power devices are presented and discussed. These analyses have been made with the aim of examining hot spot onset in power cellular transistors. The temperature distributions are obtained by means of a 3D electro-thermal simulator, and the numerical results are compared with experimental dynamic thermal maps, detected by direct IR radiometric measurements with high spatial and high time resolution. By analyzing both experimental and numerical electrothermal instabilities on power cellular BJTs, we have found that the time dependent thermal distribution is a function of the device under simulation (DUS) layout and also that it is a strong function of the single cell temperature dependent current gain and the thermal interaction between the neighbouring cells.
Effects of user mobility on handoff performance in a hierarchical cellular system

A personal communication system with hierarchical cellular overlays is described. Two strategies for traffic management are considered and compared. In strategy 1, the mobile stations are divided into two groups based upon their speed and then are served by different layers to minimize the handoff rate. In strategy 2, the mobile stations may enter either a layer regardless of their speed. It is shown that the probability of call attempts not completed is much smaller for strategy 1 than for strategy 2. We also discuss how to determine the threshold speed to keep the traffic balanced between the two layers. Analytical models are proposed to study the performance of the strategies. It is also found that the performance of strategy 1 is insensitive to imperfect speed estimation.
Topological synthesis of clock trees for VLSI-based DSP systems

This paper considers the problem of designing the topology of a clock distribution network for a synchronous digital signal processor so as to satisfy a non-zero clock skew schedule. A methodology and related algorithms for synthesizing the topology of the clock distribution network from a clock schedule derived from circuit timing information are presented. A new formulation of the problem of designing the clock distribution network is given as an efficiently solvable integer linear programming (ILP) problem. The proposed approach is demonstrated on the suite of ISCAS'89 benchmark circuits. Up to a 64% performance improvement is attained on these circuits by exploiting non-zero clock skew throughout the synchronous system. Clock tree topologies that implement the non-zero clock skew schedule based on the synthesis algorithms presented in this paper are described for each of the benchmark circuits.
Face-mounted piezoelectric resonators

This paper presents a new approach to the problem of mounting moderate Q thickness mode piezoelectric resonators based on the impedance transforming properties of quarter-wavelength transmission lines. The resulting sandwich structure has been demonstrated in the range 2-7 Mc/s, and a computer analysis of the tolerance sensitivities of the center frequency and Q has been conducted. This type of resonator appears particularly promising as a tuner for high frequency integrated circuits. The problems which must yet be solved in order to implement these tuners in thin film form are described.
Lip synchronization through alignment of speech and image data

In this paper a technique for eradicating the problem of lip synchronization has been discussed. When motion in an image sequence is large, the present day videophone systems are unable to maintain synchronization of the lips and the corresponding acoustic signal. By exploiting the correlation found between the speech and image data, the problem of lip synchronization is addressed and the mouth and speech signals may be transmitted in the same packet. >
An SSVEP-Based BCI System for SMS in a Mobile Phone

In this paper, the purpose is to develop a Short Message Service (SMS) system that can aid the ALS patients to control a mobile phone to send a message by using of the steady state visually evoked potentials (SSVEP) brain computer interface (BCI) to a person who can help him/her. The EEG signals may be detected by electrodes and signal extracting chip. Then these signal can be transmitted to the mobile platforms by using of Bluetooth interface. Finally, the message and phone number can be selected in accordance with the components in frequency domain transferred from time domain. The experimental results had shown that the proposed system can easily send a message from a mobile phone to another.
Low-latency SAO Architecture and its SIMD Optimization for HEVC Decoder

This paper proposes a low-latency Sample Adaptive Offset filter (SAO) architecture and its Single Instruction Multiple Data (SIMD) optimization scheme to achieve fast High Efficiency Video Coding (HEVC) decoding in a multi-core environment. According to the HEVC standard and its Test Model (HM), SAO operation is performed only at the picture level. Most realtime decoders, however, execute their sub-modules on a Coding Tree Unit (CTU) basis to reduce the latency and memory bandwidth. The proposed low-latency SAO architecture has the following advantages over picture-based SAO: 1) significantly less memory requirements, and 2) low-latency property enabling efficient pipelined multi-core decoding. In addition, SIMD optimization of SAO filtering can reduce the SAO filtering time significantly. The simulation results showed that the proposed low-latency SAO architecture with significantly less memory usage, produces a similar decoding time as a picture-based SAO in single-core decoding. Furthermore, the SIMD optimization scheme reduces the SAO filtering time by approximately 509% and increases the total decoding speed by approximately 7% compared to the existing look-up table approach of HM.
Case Analysis: Analyses of the National Cranberry Cooperative—1. Tactical Options

We initiated this section in the November–December 1989 issue of Interfaces with the publication of the National Cranberry Case and an invitation to submit analyses by May 1, 1990. We promised to “review the reports, select and edit the best sections from them, prepare a commentary, and publish the results. ” In this first part of those results, I discuss results that consider the environment fixed and focus on the tactical options available. I include edited analyses of the submissions from Khashoggi, Chabas, and Bakken [1990], Juergens, Hoyt, and Swenson [1990], and Langelo [1990]. In the second part, I will expand the analysis to consider changes in the environment and implementation issues, and I will include edited analyses of three additional submissions.
Multimodal Music Information Processing and Retrieval: Survey and Future Challenges

Towards improving the performance in various music information processing tasks, recent studies exploit different modalities able to capture diverse aspects of music. Such modalities include audio recordings, symbolic music scores, mid-level representations, motion and gestural data, video recordings, editorial or cultural tags, lyrics and album cover arts. This paper critically reviews the various approaches adopted in Music Information Processing and Retrieval, and highlights how multimodal algorithms can help Music Computing applications. First, we categorize the related literature based on the application they address. Subsequently, we analyze existing information fusion approaches, and we conclude with the set of challenges that Music Information Retrieval and Sound and Music Computing research communities should focus in the next years.
Single-Neuron Level One-Photon Voltage Imaging With Sparsely Targeted Genetically Encoded Voltage Indicators

Voltage imaging of many neurons simultaneously at single-cell resolution is hampered by the difficulty of detecting small voltage signals from overlapping neuronal processes in neural tissue. Recent advances in genetically encoded voltage indicator (GEVI) imaging have shown single-cell resolution optical voltage recordings in intact tissue through imaging naturally sparse cell classes, sparse viral expression, soma restricted expression, advanced optical systems, or a combination of these. Widespread sparse and strong transgenic GEVI expression would enable straightforward optical access to a densely occurring cell type, such as cortical pyramidal cells. Here we demonstrate that a recently described sparse transgenic expression strategy can enable single-cell resolution voltage imaging of cortical pyramidal cells in intact brain tissue without restricting expression to the soma. We also quantify the functional crosstalk in brain tissue and discuss optimal imaging rates to inform future GEVI experimental design.
Weighted Tensor Completion for Time-Series Causal Inference

Marginal Structural Models (MSM) {Robins, 2000} are the most popular models for causal inference from time-series observational data. However, they have two main drawbacks: (a) they do not capture subject heterogeneity, and (b) they only consider fixed time intervals and do not scale gracefully with longer intervals. In this work, we propose a new family of MSMs to address these two concerns. We model the potential outcomes as a three-dimensional tensor of low rank, where the three dimensions correspond to the agents, time periods and the set of possible histories. Unlike the traditional MSM, we allow the dimensions of the tensor to increase with the number of agents and time periods. We set up a weighted tensor completion problem as our estimation procedure, and show that the solution to this problem converges to the true model in an appropriate sense. Then we show how to solve the estimation problem, providing conditions under which we can approximately and efficiently solve the estimation problem. Finally, we propose an algorithm based on projected gradient descent, which is easy to implement and evaluate its performance on a simulated dataset.