Miracle-dz/UniFAR-FTUs huggingface dataset:
Continuous model predictive control for linear disturbed systems under mismatching condition

This paper presents a continuous model predictive control (MPC) for a class of linear disturbed system under mismatching condition by using a disturbance observer. The disturbance estimates are introduced in the output prediction to correct the errors raised by disturbances and uncertainties, which eventually leads to the desired offset-free tracking performance. The feasibility of the proposed method is validated by implemented it to the speed regulation of a permanent magnet synchronous motor (PMSM) system.
Basic logic and quantum entanglement

As it is well known, quantum entanglement is one of the most important features of quantum computing, as it leads to massive quantum parallelism, hence to exponential computational speed-up. In a sense, quantum entanglement is considered as an implicit property of quantum computation itself. But. can it be made explicit? In other words, is it possible to find the connective "entanglement" in a logical sequent calculus for the machine language? And also, is it possible to "teach" the quantum computer to "mimic" the EPR "paradox"? The answer is in the affirmative, if the logical sequent calculus is that of the weakest possible logic, namely Basic logic. - A weak logic has few structural rules. But in logic, a weak structure leaves more room for connectives (for example the connective "entanglement"). Furthermore, the absence in Basic logic of the two structural rules of contraction and weakening corresponds to the validity of the no-cloning and no-erase theorems, respectively, in quantum computing.
TM Comparative Evaluation of Fine-and Coarse-Grain Software Distributed Shared Memory

With the advent of commercial symmetric multiprocessors (SMPs) and low-latency, high-bandwidth networks, clusters of SMPs provide a natural base for software distributed shared memory (S-DSM). Two distinct approaches can be used: instrumentation-based approaches that provide fine-grain coherence, and VM-based approaches that restrict the underlying coherence unit to a page, but avoid instrumentation overhead. In this paper, we compare and evaluate these approaches using two mature S-DSM systems, Shasta and Cashmere, both of which run on a DEC AlphaServer SMP cluster connected by a very low-latency, high-bandwidth, remote-write, Memory Channel network. Our results, obtained on a 16-processor, 4-node cluster, clearly illustrate the tradeoffs between fine-grain and VM-based S-DSM. A fine-grain system such as Shasta offers an easy migration path for programs developed on a hardware DSM (H-DSM). It supports H-DSM memory models, and is better able to tolerate fine-grain synchronization. In contrast, for the same unmodified programs, Cashmere’s performance is highly sensitive to the presence of fine-grain synchronization, while providing a performance edge for applications with coarse-grain synchronization. With program modifications that take coherence granularity into account, the performance gap between the two systems can be bridged. Remaining performance differences are dependent on program structure: a high degree of false sharing at a granularity larger than a cache line favors Shasta, while finer-grain false sharing and large amounts of mostly private data favors Cashmere. c Digital Equipment Corporation, 1998 This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of the Cambridge Research Laboratory of Digital Equipment Corporation in Cambridge, Massachusetts; an acknowledgment of the authors and individual contributors to the work; and all applicable portions of the copyright notice. Copying, reproducing, or republishing for any other purpose shall require a license with payment of fee to the Cambridge Research Laboratory. All rights reserved. CRL Technical reports are available on the CRL’s web page at http://www.crl. research.digital. com. Digital Equipment Corporation Cambridge Research Laboratory One Kendall Square, Building 700 Cambridge, Massachusetts 02139
Chinese text retrieval without using a dictionary

It is generafly believed that words, rather than characters, should be the smallest indexing unit for Chinese text retrieval systems, and that it is essential to have a comprehensive Chinese dictionary or lexicon for Chhmse text retrieval systems to do well. Chinese text has no delimiters to mark woni boundaries. As a result, any text retrieval systems that build word-based indexes need to segment text into words. We implemented several statistical and dictionary-hazed word segmentation methods to study the effect on retrieval effectiveness of different segmentation methods using the TREC-S Chinese test collection and topics. The results show that, for all three sets of queries, the simple bigram indexing and the purely statistical word segmentation perform better than the popular dictionary-based maximum matching method with a dictionary of 138,955 entries.
FEATURE EVALUATION FOR BUILDING FACADE IMAGES – AN EMPIRICAL STUDY

Abstract. The classification of building facade images is a challenging problem that receives a great deal of attention in the photogrammetry community. Image classification is critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features. We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.
Gender, Communication and Comfort Level in Higher Level Computer Science Education - Case Study

According to research, students fare better in their studies if their comfort level is high. One of the factors in defining comfort level is how comfortable students are in presenting questions to other students and the course faculty. In this study, the students were divided into male, female and mixed groups. The communication within the groups was observed during the training sessions. In addition, the students filled in a survey after each training session, which measured the number of completed exercises and the level of experienced difficulty of the exercises. The study reveals that in the computer science classes typical gender distribution (majority male) lowers the comfort level of all students in comparison to a case with an even gender distribution. In light of this research, the study presents, that both male and female students would benefit, if more women studied computer science
Cultural dimension of individualism and collectivism and its perceptual and cognitive correlates in cross-cultural research

This paper reviews the current Þ ndings on the dimension of individualism/collectivism, which might be a useful tool for the comparison of different cultures and for the investigation of the effect of culture as a psychological concept on individual mental processes. The validity and reliability of the concept of the dimension of individualism/collectivism is discussed. The related theory of analytic and holistic thinking is introduced within a framework of extensive comparative research in the Þ eld of cross-cultural psychology. Several interesting research designs on cross-cultural differences in cognition and perception are described. The empirical part contains a short report of research conducted on a sample (N=92) of Czech and Czech Vietnamese university students using a scale of horizontal and vertical individualism/collectivism (Bartoš, 2010). The results do not fully support the traditional view of individualistic Europeans and collectivistic Asians.
Corporate Risk Measures and Real Options Extended Abstract

This paper investigates how the exercise of a real development option affects measures of corporate risk, such as volatility and beta. Various empirical studies examine the changes in risk measures and the cost of capital around the time of corporate investment (exercise of a real option), but they generally fail to separate the exercise of the real option from the financing effects associated with the investment. This means that they predictably get mixed results as they investigate changes in volatility, beta and cost of capital around the time of corporate investment. 1 Leverage and Hedging Effects on Risk Measures Consider a corporate investmentK that is required to exercise a real option of value W when the underlying asset resulting from the investment has value P . At the time of development, W = P −K. The volatilities and betas of the underlying investment and option to invest are related by βW = P W ∂W ∂P βP σW = P W ∂W ∂P σP . (1) In general, the first factor P/W > 1 and increases the risk measure. It is a leverage factor arising out of the fixed investment cost. The second factor ∂W ∂P ≤ 1 is the hedge ratio and decreases the risk measure. Overall, the leverage factor generally dominates the hedge factor so that the real option has greater risk than the underlying:
Features extracting from fluorescence images and features sequential scanning for classification purposes

The purpose from this paper is to introduce a sample of parameters that can be lead to reliably discrimination of the malignant from benign diseases. Diverse parameters extracted from fluorescence images by applying adaptively learnt or predefined filters. The K-nearest neighbor's algorithm is used to classify the skin lesions; a technique of sequential scanning of the parameters that could be applied to find an optimal set of parameters that would improve classification accuracy. This classification approach is modular and enables easy inclusion and exclusion of parameters. This facilitates the evaluation of their significance related to the skin cancer diagnosis. We have implemented a parameter scanning scheme which allows automatic optimization of the K-nearest neighbor classifier and indicates which features are more relevant for the diagnosis problem.
Cdc25B cooperates with Cdc25A to induce mitosis but has a unique role in activating cyclin B1–Cdk1 at the centrosome

Cdc25 phosphatases are essential for the activation of mitotic cyclin–Cdks, but the precise roles of the three mammalian isoforms (A, B, and C) are unclear. Using RNA interference to reduce the expression of each Cdc25 isoform in HeLa and HEK293 cells, we observed that Cdc25A and -B are both needed for mitotic entry, whereas Cdc25C alone cannot induce mitosis. We found that the G2 delay caused by small interfering RNA to Cdc25A or -B was accompanied by reduced activities of both cyclin B1–Cdk1 and cyclin A–Cdk2 complexes and a delayed accumulation of cyclin B1 protein. Further, three-dimensional time-lapse microscopy and quantification of Cdk1 phosphorylation versus cyclin B1 levels in individual cells revealed that Cdc25A and -B exert specific functions in the initiation of mitosis: Cdc25A may play a role in chromatin condensation, whereas Cdc25B specifically activates cyclin B1–Cdk1 on centrosomes.
A novel tunable-complexity turbo-soft detector for high-throughput HDSL applications over ISI channels with crosstalk

We present a novel iterative (turbo) receiver with tunable complexity for reliable detection of (uncoded) payload data transmitted over long intersymbol interference (ISI) channels affected by crosstalk, as those typically encountered in emerging HDSL2 services standardized by ANSI T1.418 recommendation. The proposed receiver combines in an original way "minimum mean square error (MMSE) estimation principle," "turbo-processing principle" and "crosstalk-prediction principle" for achieving both suboptimal maximum a posteriori probability channel equalization and reliable soft-mitigation of ISI tail plus crosstalk. More in detail, according to the turbo-processing principle, at each iteration suitable extrinsic information is extracted from the equalizing and interference-canceling modules and used as "a priori information" for the next iteration. Several simulation results on typical HDSL-like test-loops confirm the superiority of the proposed turbo-detector (TD) over current solutions based on conventional MMSE decision-feedback equalizers and precoders (such as the Tomlinson-Harashima precoder). The numerical tests also point out that performance of the presented TD on typical high bit-rate digital subscriber lines (HDSL) is not limited by error-floor phenomena, even at error-probabilities below 10/sup -7/.
Multi-view prediction of protein function

The problem of predicting protein function using Gene Ontology terms is a hierarchical classification problem. There are a variety of genomic data that are relevant to a protein's function: its sequence, its interactions with other proteins, expression of its gene, etc. Some of these sources (interactions and expression) are species-specific, while protein sequence is comparable across species, which complicates the task of integrating labeled data from a target species with labeled data from other species. We address this problem using the methodology of structured output learning, present a framework based on multi-view learning that is naturally suited for combining both types of data, and demonstrate its effectiveness in making predictions for proteins in S. cerevisiae and M. musculus. The code for our framework is available at http://strut.sourceforge. net.
Sentiment Classification via a Response Recalibration Framework

Probabilistic learning models have the ability to be calibrated to improve the performance of tasks such as sentiment classification. In this paper, we introduce a framework for sentiment classification that enables classifier recalibration given the presence of related, context-bearing documents. We investigate the use of probabilistic thresholding and document similarity based recalibration methods to yield classifier improvements. We demonstrate the performance of our proposed recalibration methods on a dataset of online clinical reviews from the patient feedback domain that have adjoining management responses that yield sentiment bearing information. Experimental results show the proposed recalibration methods outperform uncalibrated supervised machine learning models trained for sentiment analysis, and yield significant improvements over a robust baseline.
An LDA-based Topic Selection Approach to Language Model Adaptation for Handwritten Text Recognition

Typically, only a very limited amount of in-domain data is available for training the language model component of an Handwritten Text Recognition (HTR) system for historical data. One has to rely on a combination of in-domain and out-ofdomain data to develop language models. Accordingly, domain adaptation is a central issue in language modeling for HTR. We pursue a topic modeling approach to handle this issue, and propose two algorithms based on this approach. The first algorithm relies on posterior inference for topic modeling to construct a language model adapted to the development set, and the second algorithm proceeds by iterative selection, using a new ranking criterion, of topic-dependent language models. Our experimental results show that both approaches clearly outperform a strong baseline method.
Adaptive relay selection for hybrid relay systems

Hybrid relay systems using Amplify-and-Forward protocol (AF) and Decode-and-Forward protocol (DF) together are introduced in cooperative networks. For hybrid systems, we propose adaptive relay selection scheme to maximize the overall received Signal to Noise Ratio (SNR) at the destination. At first two relays are selected among many according to the instantaneous channel conditions. One is a relay to operate as the Amplify-and-Forward protocol and the other is a relay to operate as the Decode-and-Forward protocol. Next the total transmission power is allocated to the source and two selected relays. Simulation results show that the proposed scheme achieves better performance than that of conventional cooperative schemes.
Multiuser Spectrum Optimization for Discrete Multitone Systems With Asynchronous Crosstalk

Finding computationally efficient spectrum optimization methods for a multiuser digital subscriber line (DSL) environment is a key objective of dynamic spectrum management for DSL systems. For synchronous discrete multitone (DMT) based DSL systems, the computational complexity issue can be partially addressed using a dual optimization approach that decomposes the problem in the frequency domain. However, the decomposition approach fails whenever the DMT system is asynchronous, in which case the power allocations in adjacent frequency tones interfere with each other. This paper provides a mathematical model for intercarrier interference due to symbol misalignment and proposes ways to modify the dual method for spectrum optimization of asynchronous DSL systems. The main ingredient of the algorithm is an efficient method to evaluate the minimum power required to support a given bit-allocation using a power series approximation, combined with a local gradient search.
Long-run Performance after Stock Splits: 1927 to 1996

We measure the postsplit performance of 12,747 stock splits from 1927 to 1996 using two methods to measure abnormal returns: size and book-to-market reference portfolios with bootstrapping, and calendar-time abnormal returns combined with factor models. Between 1927 and 1996, neither method applied to splits 25 percent or larger finds performance significantly different from zero. Over selected subperiods, subsamples of 2-1 splits restricted by book-to-market availability requirements display positive abnormal returns using some methods. However, these samples show small or negligible abnormal returns using the calendar-time method. Overall, the stock split evidence against market efficiency is neither pervasive nor compelling. Copyright 2003 by the American Finance Association.
Feasibility and accuracy of hotword detection using vibration energy harvester

Vibration energy harvesting (VEH) is a promising source of renewable energy that can be used to extend battery life of next generation mobile devices. In this paper, we study the feasibility and accuracy of VEH for detecting hotwords, such as “OK Google”, used by popular voice control applications to distinguish user commands from other conversations. The idea of using power signals of VEH to detect hotwords is based on the fact that human voice creates vibrations in the air, which could be potentially picked up by the VEH hardware inside a mobile device. Using off-the-shelf VEH product, we conduct a comprehensive experimental study involving 8 subjects. We analyse two possible usage scenarios for the VEH hardware. In the first scenario, the user is not required to talk directly to the device (indirect), but the VEH is expected to pick up the ambient vibrations caused by user-generated sound waves. In the second, the user is expected to direct his voice to the VEH (direct) and talk to it from a close distance. For both usage scenarios, we evaluate two types of hotword detection, speaker-independent and speaker-dependent. We find that VEH can detect hotwords more accurately in the direct scenario compared to the indirect. For the direct scenario, our results show that a simple Decision Tree classifier can detect hotwords from VEH signals with accuracies of 73% and 85%, respectively, for speaker-independent and speaker-dependent detections. Finally, we show that these accuracies are comparable to what could be achieved with an accelerometer sampled at 200 Hz.
Physostigmine and Galanthamine Bind in the Presence of Agonist at the Canonical and Noncanonical Subunit Interfaces of a Nicotinic Acetylcholine Receptor

Galanthamine and physostigmine are clinically used cholinomimetics that both inhibit acetylcholinesterase and also interact directly with and potentiate nAChRs. As with most nAChR-positive allosteric modulators, the location and number of their binding site(s) within nAChRs are unknown. In this study, we use the intrinsic photoreactivities of [3H]physostigmine and [3H]galanthamine upon irradiation at 312 nm to directly identify amino acids contributing to their binding sites in the Torpedo californica nAChR. Protein sequencing of fragments isolated from proteolytic digests of [3H]physostigmine- or [3H]galanthamine-photolabeled nAChR establish that, in the presence of agonist (carbamylcholine), both drugs photolabeled amino acids on the complementary (non-α) surface of the transmitter binding sites (γTyr-111/γTyr-117/δTyr172). They also photolabeled δTyr-212 at the δ-β subunit interface and γTyr-105 in the vestibule of the ion channel, with photolabeling of both residues enhanced in the presence of agonist. Furthermore, [3H]physostigmine photolabeling of γTyr-111, γTyr-117, δTyr-212, and γTyr-105 was inhibited in the presence of nonradioactive galanthamine. The locations of the photolabeled amino acids in the nAChR structure and the results of computational docking studies provide evidence that, in the presence of agonist, physostigmine and galanthamine bind to at least three distinct sites in the nAChR extracellular domain: at the α-γ interface (1) in the entry to the transmitter binding site and (2) in the vestibule of the ion channel near the level of the transmitter binding site, and at the δ-β interface (3) in a location equivalent to the benzodiazepine binding site in GABAA receptors.
Metabolic Syndrome and Onset of Depressive Symptoms in the Elderly

OBJECTIVE Given the increasing prevalence of both metabolic syndrome (MetS) and depressive symptoms during old age, we aimed to examine prospectively the association between MetS and the onset of depressive symptoms according to different age-groups in a large, general elderly population. RESEARCH DESIGN AND METHODS This was a prospective cohort study of 4,446 men and women aged 65–91 years who were free of depression or depressive symptoms at baseline (the Three-City Study, France). MetS was defined using the National Cholesterol Education Program Adult Treatment Panel III criteria. New onset of depressive symptoms (the Center for Epidemiologic Studies Depression Scale score ≥16 and use of antidepressant treatment) was assessed at 2- and 4-year follow-ups. RESULTS After adjusting for a large range of potential confounders, we observed MetS to be associated with 1.73-fold (95% CI 1.02–2.95) odds for new-onset depressive symptoms in the youngest age-group (65–70 years at baseline), independently of cardiovascular diseases. No such association was seen in older age-groups. CONCLUSIONS Our findings suggest that the link between MetS and depressive symptoms evidenced until now in middle-aged people can be extended to older adults but not to the oldest ones. Additional research is needed to examine if a better management of MetS prevents depressive symptoms in people aged 65–70 years.
Doppler Shift Estimation for Low Signal-Noise-Ratio Environment in Mobile Communication Systems

A novel iterative Doppler shift estimator is proposed in this letter for the Doppler shift estimation in very low signal- noise-ratio (SNR) environment. The proposed method exploits the logarithm envelope (LE) of the mobile propagation channel, and iteratively finds the minimum mean square error (MMSE) estimation of the Doppler shift. Extensive simulation results conducted under a wide range of the noise corruption clearly show that our proposed Doppler shift estimation method substantially outperforms all existing estimators.