Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal state feedback based resource allocation for resource-constrained control tasks

In many application areas, including control systems, careful management of system resources is key to providing the best application performance. Most traditional resource management techniques for real-time systems with multiple control loops are based on open-loop strategies that statically allocate a constant CPU share to each controller, independent of their current resource needs. This provides average control performance with minimal overhead but in general fails to provide the best performance possible within the available resources. We show that by using feedback to dynamically allocate resources to controllers as a function of the current state of their controlled systems, control performance can be significantly improved. We present an optimal resource allocation policy that maximizes control performance within the available resources and provide experimental results showing that the optimal policy 1) significantly increases control performance compared to traditional control system implementations (by more than 20% in our experiments), 2) maximizes control performance over other feedback-based policies, 3) saves resources when perturbations occur infrequently, and 4) incurs negligible overhead.
Helping Clients With Special Concerns

Interestingly, helping clients with special concerns that you really wait for now is coming. It's significant to wait for the representative and beneficial books to read. Every book that is provided in better way and utterance will be expected by many peoples. Even you are a good reader or not, feeling to read this book will always appear when you find it. But, when you feel hard to find it as yours, what to do? Borrow to your friends and don't know when to give back it to her or him.
A 220 mW 1 Gb/s 1024-bit rate-1/2 low density parity check code decoder

A 1024 bit rate-1/2 Low Density Parity Check (LDPC) code decoder has been implemented that matches the coding gain of equivalent turbo codes. The parallel decoder architecture supports throughputs up to 1 Gb/s and convergence in the decoding algorithm translates into extremely low switching activity with power dissipation under 220 mW.
Bivariable and Multivariable Analysis of EEG Signals

The chapters thus far have described quantitative tools that can be used to extract information from single EEG channels. In this chapter we describe measures of synchronization between different EEG recordings sites. The concept of synchronization goes back to the observation of the interaction between two pendulum clocks by the Dutch physicist Christiaan Huygens in the seventeenth century. Since the times of Huygens, the phenomenon of synchronization has been largely studied, especially for the case of oscillatory systems [1]. Before getting into technical details of how to measure synchronization, we first consider why it is important to measure synchronization between EEG channels. There are several reasons. First, synchronization measures can let us assess the level of functional connectivity between two areas. It should be stressed that functional connectivity is not necessarily the same as anatomical connectivity, since anatomical connections between two areas may be active only in some particular situations—and the general interest in neuroscience is to find out which situations lead to these connectivity patterns. Second, synchronization may have clinical relevance for the identification of different brain states or pathological activities. In particular, it is well established that epilepsy involves an abnormal synchronization of brain areas [2]. Third, related to the issue of functional connectivity, synchronization measures may show communication between different brain areas. This may be important to establish how information is transmitted across the brain or to find out how neurons in different areas interact to give rise to full percepts and behavior. In particular, it has been argued that perception involves massive parallel processing of distant brain areas, and the binding of different features into a single percept is achieved through the interaction of these areas [3, 4]. Even if outside the scope of this book, it is worth mentioning that perhaps the most interesting use of synchronization measures in neuroscience is to study how neurons encode information. There are basically two views. On the one hand, neurons may transmit information through precise synchronous firing; on the other hand, the only relevant information of the neuronal firing may be the average firing rate. Note that rather than having two extreme opposite views, one can also consider coding schemes in between these two, because the firing rate coding is more similar to a temporal coding when small time windows are used [5].
The Oxford handbook of event-related potential components

Preface Part One: Conceptual Bases 1. ERP Components: The Ups and Downs of Brainwave Recordings Emily S. Kappenman and Steven J. Luck 2. Beyond ERPs: Oscillatory Neuronal Dynamics Marcel Bastiaansen, Ali Mazaheri, and Ole Jensen 3. ERP Features and EEG Dynamics: An ICA Perspective Scott Makeig and Julie Onton Part Two: Commonly Studied ERP Components 4. Sensory ERP Components Hillel Pratt 5. The N170: Understanding the Time Course of Face Perception in the Human Brain Bruno Rossion and Corentin Jacques 6. The Mismatch Negativity (MMN) Risto Naatanen and Kairi Kreegipuu 7. Neuropsychology of P300 John Polich 8. Negative slow waves as indices of anticipation: The Bereitschaftspotential, the Contingent Negative Variation, and the Stimulus Preceding Negativity Cornelis H.M. Brunia, Geert J.M. van Boxtel, and Koen B.E. Bocker 9. The Lateralized Readiness Potential Fren T.Y. Smulders and Jeff O. Miller 10. The Error-Related Negativity (ERN/Ne) William J. Gehring, Yanni Liu, Joseph M. Orr, and Joshua Carp Part Three: ERP Components in Specific Cognitive Domains 11. ERP Components and Selective Attention Steven J. Luck and Emily S. Kappenman 12. Electrophysiological Correlates of the Focusing of Attention within Complex Visual Scenes: N2pc and Related Electrophysiological Correlates Steven J. Luck 13. What ERPs Can Tell Us about Working Memory Veronica B. Perez and Edward K. Vogel 14. Electrophysiological Correlates of Episodic Memory Processes Edward L. Wilding and Charan Ranganath 15. Language-Related ERP Components Tamara Y. Swaab, Kerry Ledoux, C. Christine Camblin, and Megan Boudewyn 16. ERPs and the Study of Emotion Greg Hajcak, Anna Weinberg, Annmarie MacNamara, and Dan Foti Part Four: ERPs in Special Populations 17. Event-related Potentials and Development Donna Coch and Margaret M. Gullick 18. The Components of Aging David Friedman 19. Abnormalities of Event Related Potential Components in Schizophrenia Brian F. O'Donnell, Dean F. Salisbury, Margaret A. Niznikiewicz, Colleen A. Brenner, and Jenifer L. Vohs 20. Event-related Brain Potentials in Depression: Clinical, Cognitive, and Neurophysiologic Implications Gerard E. Bruder, Jurgen Kayser, and Craig E. Tenke 21. Alterations of ERP Components in Neurodegenerative Diseases Rolf Verleger 22. Homologues of Human ERP Components in Nonhuman Primates Geoffrey F. Woodman
Towards a personalized privacy management framework

Privacy policies which are stated by the service provider are intended to convey to the users the information how their personal data will be protected. Thus, letting the user understand the privacy policy and trust the service provider is a crucial task. This paper proposes a personalized privacy management framework with which users can participate in the privacy management. Existing privacy policies are analyzed and improved. Within this framework, the privacy policy can not only be regulated, but also can be easily understood by users at a glance.
Optimal Mechanisms for Scheduling

We study the design of optimal mechanisms in a setting where a service provider needs to schedule a set of non-preemptive jobs, one job at a time. Jobs need to be compensated for waiting, and waiting cost is private information. In this setting, an optimal mechanism is one that induces jobs to report truthfully their waiting cost, while minimizing the total expected compensation cost of the service provider. Here, truthful refers to Bayes-Nash implementability, and assumes that private information is independently drawn from known distributions. We derive closed formulae for the optimal mechanism, and show that it is a modification of Smith’s ratio rule. We also show that it can be implemented in dominant strategies. Our analysis relies on a graph-theoretic interpretation of the incentive compatibility constraints. It parallels the analysis known for auctions with single parameter agents, yet it exhibits some subtle differences. We also consider the multi-dimensional case where also the service times of jobs are private information. We show that for this problem the optimal mechanism generally does not satisfy an independence condition known as IIA, and thus known approaches are doomed to fail.
AN ALGORITHM FOR CANCELLATION OF SIDETONE OSCILLATIONS

An algorithm for detection and cancellation of sidetone oscillations in mobile phones is presented. The sidetone signal is represented by a 4 th order LPC polynomial, whose root structure is analysed by a computationally efficient twostage approach. In difference to LMS based adaptive filters this approach offers a fast and reliable detection of evolving oscillations. A notch filter with small bandwidth is used for cancellation and therefore almost no distortion is introduced to the speech signal.
Steady-State Performance Comparison of Bayesian and Standard Adaptive Filtering

It has been known for a long time that for best tracking results adaptive filtering should be formulated as a Kalman filtering problem, leading to Bayesian Adaptive Filtering (BAF). BAF techniques with acceptable complexity can be obtained by focusing on a diagonal AR(1) model for the time-varying optimal filter settings. The hyper-parameters of the AR(1) model can be adapted by introducing EM techniques and one sample fixed-lag smoothing at little extra cost. Standard AF techniques such as the LMS and RLS algorithms are equipped with only one hyper-parameter (stepsize, forgetting factor) to optimize their tracking behavior. In this paper we compare the steady-state tracking performance of Bayesian and standard AF techniques.
Feature selection in a kernel space

We address the problem of feature selection in a kernel space to select the most discriminative and informative features for classification and data analysis. This is a difficult problem because the dimension of a kernel space may be infinite. In the past, little work has been done on feature selection in a kernel space. To solve this problem, we derive a basis set in the kernel space as a first step for feature selection. Using the basis set, we then extend the margin-based feature selection algorithms that are proven effective even when many features are dependent. The selected features form a subspace of the kernel space, in which different state-of-the-art classification algorithms can be applied for classification. We conduct extensive experiments over real and simulated data to compare our proposed method with four baseline algorithms. Both theoretical analysis and experimental results validate the effectiveness of our proposed method.
Internet-Delivered Disease Management for Recurrent Depression: A Multicenter Randomized Controlled Trial

Background: Strategies to improve the life of patients suffering from recurrent major depression have a high relevance. This study examined the efficacy of 2 Internet-delivered augmentation strategies that aim to prolong symptom-free intervals. Methods: Efficacy was tested in a 3-arm, multicenter, open-label, evaluator-blind, randomized controlled trial. Upon discharge from inpatient mental health care, 232 adults with 3 or more major depressive episodes were randomized to 1 of 2 intervention groups (SUMMIT or SUMMIT-PERSON) or to treatment as usual (TAU) alone. Over 12 months, participants in both intervention arms received, in addition to TAU, intense monitoring via e-mail or a smartphone, including signaling of upcoming crises, assistance with personal crisis management, and facilitation of early intervention. SUMMIT-PERSON additionally offered regular expert chats. The primary outcome was ‘well weeks', i.e. weeks with at most mild symptoms assessed by the Longitudinal Interval Follow-Up Evaluation, during 24 months after the index treatment. Results: SUMMIT compared to TAU reduced the time with an unwell status (OR 0.48; 95% CI 0.23-0.98) through faster transitions from unwell to well (OR 1.44; 95% CI 0.83-2.50) and slower transitions from well to unwell (OR 0.69; 95% CI 0.44-1.09). Contrary to the hypothesis, SUMMIT-PERSON was not superior to either SUMMIT (OR 0.77; 95% CI 0.38-1.56) or TAU (OR 0.62; 95% CI 0.31-1.24). The efficacy of SUMMIT was strongest 8 months after the intervention. Conclusions: The fully automated Internet-delivered augmentation strategy SUMMIT has the potential to improve TAU by reducing the lifelong burden of patients with recurrent depression. The fact that the effects wear off suggests a time-unlimited extension.
Design and implementation of an ontology-based psychiatric disorder detection system

In this paper, we combine a decision tree algorithm with Protege, to construct an ontology-based meridian method that serves as an example psychiatric disorder inference and a knowledge-sharing platform. This method may effectively detect a psychiatric disorder by pinpointing an association between the meridian system and modern medicine; it may also help to build a fuller picture of expert knowledge by constructing domain and task ontologies. This system provides the general public an understanding of the issues involved, while allowing experts to participate and be totally aware of satisfying the requirements therein. Moreover, the system will help eliminate information disparity between patients and physicians.
Women Creating Lives: Identities, Resilience, And Resistance

Introduction - women's lives and theories, Carol E. Franz and Abigail J. Stewart. Part 1 Psychologists (re)creating women's lives: towards a feminist strategy for studying women's lives, A.J. Stewart attempting to comprehend the lives of low-income mothers, Deborah Belle the ethics of ambiguity - feminists writing women's lives, Gail A. Hornstein. Part 2 Dialogues - talking with women about their lives: against the odds - resiliency in an adult survivor of childhood sexual abuse, Frances K. Grossman and Roslin P. Moore a word and a kindness - the journey of a black social worker, Rosario Ceballo speaking against the silence - one Maya woman's exile and return, M.Brinton Lykes coping with internment - a Nisei women's perspective, Donna K. Nagata "I didn't want a life like that" - constructing a life between cultures, Amy Schulz. Part 3 Overcoming distance in studying women's lives: who's that girl? - a case study of Madonna, Lynne Layton image, theme and character in the life-story of Karen Horney, Dan P. McAdams the complexities of a young adult woman's relational work - challenges, demands and benefits, Elizabeth L. Paul traumatic historical events and adolescent psychosocial development - letters from V, Oliva M. Espin. Part 5 One life among many - cases drawn from group studies: medicine is my lust - the story of a woman physician, Lillian K. Cartwright reconstituting the self - the role of history, personality and loss in one woman's life, C.E. Franz my dirty little secret - women as clandestine intellectuals, Carol Tomlinson-Keasey. Part 7 Lives in contrast - comparative case studies: difference, desire and the self - three stores, Arlene Stein personal choices in political climates - coping with legal and illegal abortion, Sharon Gold-Steinberg struggle and strength in the lives of two lesbian priests, Brian Litzenberger meanings and uses of marginal identities - social class at Radcliffe in the 1960s, Joan M. Ostrove and A.J. Stewart a struggle that continues - black women, community and resistance, Elizabeth R. Cole lessons from lives, C.E. Franz et al.
An Investigation of Alternative Language Services (ALS) Received by English Language Learners (ELLs) Identified with a Disability

The identification of and provision of ALS to ELLs identified with a disability was compared to that of their ELL peers without an identified disability. In addition, I conducted a review of the types of ALS provided. I approached this study from the perspective of the social construction of disabilit y and utilized a quantitative, causalcomparative research design. I utilized the Statist ical Analysis System (SAS) software for data analysis, along with Pearson's chi-square test of independence ( χ), and Fisher’s exact test with a significance level (p-value of ≤ 0.01) to test null hypothesis. In addition, the risk index and the composition index were also calculated to address factors of disproportionate representation. De-identified data were provided by a school distri ct located in the southwest region of the United States after the 40 day count f the 2013-2014 school year. The data included 16,732 student records of school aged chil ren in kindergarten through 12 th grades. Analyses revealed that there was a signific a t difference in: the proportion of ALS for ELLs with a disability v students identified with a Primary Home Language Ot her Than English (PHLOTE) and identified with a disability categorized as ELL fro m PHLOTE students without a disability identified as ELL, in the proportion of students identified with disabilities who received ALS compared to their peers without a disa bility who received ALS (most of the 36 students exempted from ALS were identified with a disability), in the proportion of ELLs who received ALS in grades K-5 compared to ELL s in grades 9-12, in the proportion of ELLs who received ALS who were identi fied with a Specific Learning Disability compared to ELLs who received ALS identi fied with any other primary disability, in the proportion of ELLs identified as SLD compared to their non-ELL peers also identified as SLD, and in the proportion of As ian students identified with a disability. Asian students were identified with a d isability at a significantly lower rate compared to their non-Asian peers. ALS for ELLs with a disability vi Table of
Performance Analysis of OFDM in Wireless Communication

The enabling technologies such as Orthogonal Frequency Division Multiplexing (OFDM) are effective and significant for the present and future wireless communication systems. Some common problems such as multipath delay spread, channel noise, peak to average power ratio (PAPR), time synchronization error, carrier frequency offset and phase error limit the wireless communication system performances. According to some factors, the performances of OFDM systems have been analyzed and their mathematical models are established with the help of various references. It is found that OFDM performs extremely well, provides a very high tolerance to multipath delay spread and channel noise.
Device Design and Estimated Performance for p-Type Junctionless Transistors on Bulk Germanium Substrates

The junctionless nanowire transistor (JNT) has recently been demonstrated to be a promising device for sub-20-nm nodes. So far, most devices were made on semiconductor-on-insulator substrates. The aim of this work is to evaluate the concept of multigate germanium (Ge) JNTs on bulk substrates, using a dedicated modeling methodology. The variation of device performance due to geometry, channel, and substrate doping concentrations is discussed and proposed as a guideline for designing p-type Ge bulk JNTs. This work shows that a potential barrier is formed in the substrate by the p-n junction that isolates the channel from the substrate, and an effective confinement of current in the nanowire can be achieved. The Ge bulk JNT facilitates excellent scalability. Our modeling predicts that, for a gate length of 16 nm, a subthreshold slope of 77 mV/dec and a drain-induced barrier lowering of 70 mV can be obtained with an <formula formulatype="inline"><tex Notation="TeX">$I_{\rm on}/I_{\rm off}$</tex></formula> current ratio of <formula formulatype="inline"><tex Notation="TeX">$\hbox{1.1} \times \hbox{10}^{5}$</tex></formula>.
Effect of conventional interferon‐α in patients with HBeAg‐positive chronic hepatitis B: a systematic review and meta‐analysis

Background Although a few studies have tested the effect of interferon‐α on chronic hepatitis B, its treatment effect remains uncertain, and the association of treatment effect with intervention characteristics has not been thoroughly explored. This study examined the effect of IFN‐α in patients with HBeAg‐positive chronic hepatitis B, and investigated the characteristics associated with treatment effect.
Shorter Linear Straight-Line Programs for MDS Matrices

Recently a lot of attention is paid to the search for efficiently implementable MDS matrices for lightweight symmetric primitives. Most previous work concentrated on locally optimizing the multiplication with single matrix elements. Separate from this line of work, several heuristics were developed to find shortest linear straightline programs. Solving this problem actually corresponds to globally optimizing multiplications by matrices. In this work we combine those, so far largely independent lines of work. As a result, we achieve implementations of known, locally optimized, and new MDS matrices that significantly outperform all implementations from the literature. Interestingly, almost all previous locally optimized constructions behave very similar with respect to the globally optimized implementation. As a side effect, our work reveals the so far best implementation of the Aes Mix- Columns operation with respect to the number of XOR operations needed.
Increased CO2 loss from vegetated drained lake tundra ecosystems due to flooding

Tundra ecosystems are especially sensitive to climate change, which is particularly rapid in high northern latitudes resulting in significant alterations in temperature and soil moisture. Numerous studies have demonstrated that soil drying increases the respiration loss from wet Arctic tundra. And, warming and drying of tundra soils are assumed to increase CO2 emissions from the Arctic. However, in this water table manipulation experiment (i.e., flooding experiment), we show that flooding of wet tundra can also lead to increased CO2 loss. Standing water increased heat conduction into the soil, leading to higher soil temperature, deeper thaw and, surprisingly, to higher CO2 loss in the most anaerobic of the experimental areas. The study site is located in a drained lake basin, and the soils are characterized by wetter conditions than upland tundra. In experimentally flooded areas, high wind speeds (greater than ∼4 m s−1) increased CO2 emission rates, sometimes overwhelming the photosynthetic uptake, even during daytime. This suggests that CO2 efflux from C rich soils and surface waters can be limited by surface exchange processes. The comparison of the CO2 and CH4 emission in an anaerobic soil incubation experiment showed that in this ecosystem, CO2 production is an order of magnitude higher than CH4 production. Future increases in surface water ponding, linked to surface subsidence and thermokarst erosion, and concomitant increases in soil warming, can increase net C efflux from these arctic ecosystems.
Evolving 3 D Models of Trees Using Genetic Programming

This paper describes a technique to evolve 3D models of plants based on deterministic automata. It uses cellular encoding to obtain these automata from trees evolved in standard genetic programming software. The fitness is a combination of high-level characteristics of the model, including overall shape, number of branches and geometric characteristics. We introduce a grid-based constraint evaluation as a way for the designer to shape a tree. This approach can be extended to modeling more than plants.