Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating piecewise linear models using combinatorial optimization techniques

A wide range of image and signal processing problems have been formulated as ill-posed linear inverse problems. Due to the importance of discontinuities and non-stationarity, piecewise linear models are a natural step towards more realistic results. Although there have been some attempts to extend classical approaches to deal with discontinuities, finding at the same time the piecewise decomposition and the corresponding model parameters remains a major challenge. A new approach based on partitioning inconsistent linear systems into a minimum number of consistent subsystems (MIN PCS) is proposed for solving ill-posed problems whose formulation as linear inverse problems with discrete data fails to take into account discontinuities. In spite of the NP-hardness of MIN PCS, satisfactory approximate solutions can be obtained using simple but effective variants of an algorithm which has been extensively studied in the artificial neural network literature. Our approach presents various advantages compared to classical alternatives, including a wider range of applicability and a lower computational complexity.
Medical ethics privacy protection based on combining distributed randomization with K-anonymity

In the era of big data, the Privacy Preserving Data Mining (PPDM) technology is increasingly important. The aim is to dig out the hidden, previously unknown and potentially useful knowledge or pattern under the premise of protecting sensitive data. In this paper, we summarize the existing PPDM technology as well as its advantages and disadvantages. We combine distributed randomization with the K-anonymity algorithm to reduce the information loss rate in order to increase the data availability and avoid the leakage of privacy data information. This method is applied to clinical data of diabetic nephropathy(DN). The result has proved that the potential relationship between some certain factors and diabetic nephropathy syndromes has no obvious damage compared with the result which is got on the basis of the unprotected status.
On Effective Methods for Implicit Piecewise Smooth Surface Recovery

This paper considers the problem of reconstructing a piecewise smooth model function from given, measured data. The data are compared to a field which is given as a possibly nonlinear function of the model. A regularization functional is added which incorporates the a priori knowledge that the model function is piecewise smooth and may contain jump discontinuities. Regularization operators related to total variation (TV) are therefore employed. Two popular methods are modified TV and Huber's function. Both contain a parameter which must be selected. The Huber variant provides a more natural approach for selecting its parameter, and we use this to propose a scheme for both methods. Our selected parameter depends both on the resolution and on the model average roughness; thus, it is determined adaptively. Its variation from one iteration to the next yields additional information about the progress of the regularization process. The modified TV operator has a smoother generating function; nonetheless we obtain a Huber variant with comparable, and occasionally better, performance. For large problems (e.g., high resolution) the resulting reconstruction algorithms can be tediously slow. We propose two mechanisms to improve efficiency. The first is a multilevel continuation approach aimed mainly at obtaining a cheap yet good estimate for the regularization parameter and the solution. The second is a special multigrid preconditioner for the conjugate gradient algorithm used to solve the linearized systems encountered in the procedures for recovering the model function.
Heuristic noise driven compressed sensing for DOA estimation in phased array radar system

For the classic model in compressed sensing, y= Φx + e, the proposed noise driven compressed sensing method tries to build an equivalent system of the classic model as, y = (Φ+p)x = ΦEx, provided Px = e. This results in an equivalent sensing matrix ΦE. Inspired by the idea that low coherence guarantees the reconstruction of the sparse vector with large probability, the equivalent sensing matrix ΦE is updated iteratively in a Markov Chain Monte Carlo (MCMC) based framework to reduce the large coherence between a set of specific columns. At the same time, the proposed method tries to preserve most of the information of the original sensing matrix Φ via adjusting the noise related matrix P. The proposed method is utilized successfully in a phased array radar system based solely on the existing hardware. Numerical simulations show that the proposed method obtains more precise estimation of direction of arrival (DOA) using one snapshot compared with the traditional estimation methods such as Capon, APES and GLRT based on hundreds of snapshots.
Improve TCP Performance in Ad Hoc Netwoks

Standard TCP misinterpret mobility loss in Ad hoc network as congestion loss, thus, it reduce the TCP performance by invoking unnecessary congestion control action. In this paper, we propose two approaches, simELFN (an variation of TCP-ELFN) and TCP-FSR (an variation of TCP-F). They can distinguish the essence of packet loss and avoid multiple consecutive dupACK s. Analyses and simulations show that they can achieve better TCP performance in Ad hoc network.
Fatigue Detection Based on Regional Local Binary Patterns Histogram and Support Vector Machine

Driver fatigue detection is a challenging problem in intelligent transportation system. The detection accuracy suffered by different illumination. This paper proposed a fatigue detection method based on regional local binary patterns histogram (RLBPH) and support vector machine (SVM). Firstly, we division the face image into blocks, then using local binary patterns(LBP) operator to present each block and calculating the LBP histogram(LBPH) of each block, then combine them into a RLBPH to present the face image. We used the fatigue face sample RLBPH feature and normal face sample RLBPH feature to train the SVM to get its model and the parameters. We input the RLBPH feature of the testing sample to the trained models, thus can classify the RLBPH feature of the testing sample. In our experiments we observe that RLBPH features perform stably and robustly on different illumination, and yield promising performance in low-resolution images captured from web cam.
The Thing that we Tried Didn't Work very Well: Deictic Representation in Reinforcement Learning

Most reinforcement learning methods operate on propositional representations of the world state. Such representations are often intractably large and generalize poorly. Using a deictic representation is believed to be a viable alternative: they promise generalization while allowing the use of existing reinforcement-learning methods. Yet, there are few experiments on learning with deictic representations reported in the literature. In this paper we explore the effectiveness of two forms of deictic representation and a naive propositional representation in a simple blocks-world domain. We find, empirically, that the deictic representations actually worsen learning performance. We conclude with a discussion of possible causes of these results and strategies for more effective learning in domains with objects.
Screening for novel ENU‐induced rhythm, entrainment and activity mutants

Chemical mutagenesis has provided an opportunity to develop and expand the repertoire of behavioural mutants for gene function studies. With this in mind, we have established a screen in mice for mutations affecting circadian rhythms, entrainment to light and other wheel‐running parameters. The screen consists of an assessment of mouse wheel‐running activity in a 12:12 h light/dark cycle for 7–10 days followed by assessment in constant darkness for up to 20 days. Responses to light are assessed using two protocols; a 15 minute light pulse given at circadian time 16 on the tenth day in constant darkness and an additional 12 h of light upon transition from light/dark conditions to constant darkness. To date, approximately 1300 progeny of chemically mutagenised mice have been screened. Computer‐aided assessment of wheel‐running parameters has helped in identifying abnormal phenotypes in approximately 5% of all animals screened. Inheritance testing of mice with abnormal phenotypes has confirmed the number of robustly inherited mutant phenotypes to be 1% of the total screened. Confirmed mutants including those affecting free‐running period, light‐responsiveness and wheel‐running endurance have been identified. Thus far, low‐resolution map positions have been established for four mutants by completing genome scans in backcross progeny. Mutant loci do not correspond with those previously associated with wheel‐running behaviour. This result confirms that phenotype‐driven approaches such as this should continue to provide material for mammalian gene function studies.
Are Flexible Work Arrangements Associated with Lower Levels of Chronic Stress-Related Biomarkers? A Study of 6025 Employees in the UK Household Longitudinal Study

Debates around the benefits of flexible work arrangements for employee well-being are limited by a lack of empirical analyses on whether flexible working enables employees with work or family stressors to cope with their levels of stress. This study examines whether the availability and use of different flexible work arrangements are associated with lower allostatic load (an index of chronic stress-related biomarkers) in a large representative study of UK adults. Male and female employees who made use of reduced hours working arrangements had lower levels of allostatic load. Among women caring for two or more children aged under 15, there was a difference of almost one unit of the allostatic load index (an additional biomarker risk) between women who used reduced hours flexible work and those without such arrangements. Reduced hours flexible work arrangements could enable women who combine work and family roles to reduce their levels of chronic stress.
An exact mathematical proof for the condition of zero reflection by multilayered metamaterial media

The planar multilayered media composed of a combination of common materials and metamaterials are analyzed by a full-wave matrix method for determining the conditions of zero reflection under normal plane wave incidence. Although the exact mathematical analysis is performed at a single frequency, but it may be carried out for a frequency spectrum to design the structure for a specified band width. Consequently, it is observed that the conditions of zero reflection by multilayered media may be achieved by various combinations of common materials and metamaterials.
Critical Behavior of Black Hole Formation in a Scalar Wave Collapse Y

Gravitational collapse is one of interesting phenomena in general relativity. In recent years, a large number of studies have been made on the dynamical behavior of a massless scalar eld, in the context of spherically symmetric gravitational collapse. It has been shown that for a weakeld implosion scalar waves bounce and disperse to in nity, while a strongeld e-mail: yoshiro@allegro.phys.nagoya-u.ac. jp e-mail: kouchan@allegro.phys.nagoya-u.ac. jp e-mail: c42615a@nucc.cc. nagoya-u.ac. jp
General traffic sign recognition by feature matching

Traffic sign recognition is a technology which allows us to recognize signs in real time, typically in videos, or sometimes just (off-line) in photos. It is used for Driver Assistance Systems (DAS), road surveys, or the management of road assets (to improve road safety). In this paper, we propose a method for general traffic sign recognition (tested for the New Zealand road signs) which combines previously designed steps, but with an overall adaptation towards general traffic sign recognition (i.e., not just speed or stop signs). First, color input images or frames are converted from RGB color space into HSV color space. Second, special shapes as potential signs are detected (circles, triangles, squares) using Hough transform. Third, potential signs are compared with the template signs as given in the database by using feature matching methods (SIFT or SURF features). At the end, we recognize the traffic sign in an image aiming at realtime DAS. Experiments show that the proposed method is robust for the selected test data, with over 95 percent success rate on average. On a single frame of size 1024 × 768, the system uses on average 80 ms for preprocessing, and 100 ms for matching a traffic sign candidate.
The materiality of digital jewellery from a jeweller’s perspective

Taking a research-through-design with craft sensibilities approach we present design propositions in the digital age that value the complexity and uniqueness of being human. We introduce exemplars of digital jewellery objects that offer alternative ways of connecting a person with personal anchor points, significant others and places. The pieces were inspired by the lives of three participants and the researcher who all frequently travel back to their native countries, but who live permanently in the UK and experience feelings of transition and what we describe as “being in-between”. ‘Microcosmos’, ‘Togetherness: Connected Brooches’ and ‘Topoi’ expand our understanding of what digital jewellery can be by embodying interactions that highlight the sensorial and imaginative aspects of digital technology. Building on our previous work on poetic qualities of interaction with digital jewellery we offer a reflective view on how digital jewellery can challenge our expectations of digital connectivity, sensor functionality and location awareness and we discuss the material qualities of the pieces by unfolding the narratives associated with their function and form. Most digital devices come with a set of expectations such as: What does it do? How long is battery life? How cutting edge is the technology? By contrast, this research offers a focus on atypical personal interactions in order to address a different range of questions and potentially open up our expectations of the digital. By reflecting on our designs we continue the discussions on how jewellery practices and digital technologies can suggest more poetic interactions for people.
The NSE-Government Securities Index : Issues in construction

The increased activity in the government securities market in India and simultaneous emergence of mutual (gilt) funds has given rise to the need for a welldefined Bond Index to measure returns in the bond market. The NSE-Government Securities Index prices components off the NSE Benchmark-ZCYC, so that movements reflect returns to an investor on account of change in interest rates only, and not those arising on account of the impact of idiosyncratic factors. The index is available from January 1. 1997 to the present. The index would provide a benchmark for portfolio management by various investment managers and gilt funds. It could also form the basis for designing index funds and for derivative products such as options and futures.
Improving the Processing of Decision Support Queries : Strategies for a DSS Optimizer

Many decision support applications are built upon data mining and OLAP tools and allow users to answer information requests based on a data warehouse that is managed by a powerful DBMS. In this paper, we focus on tools that generate sequences of SQL statements in order to produce the requested information. Our thorough analysis revealed that many sequences of queries that are generated by commercial tools are not very efficient. An optimized system architecture is suggested for these applications. The main component is a DSS optimizer that accepts previously generated sequences of queries and remodels them according to a set of optimization strategies, before they are executed by the underlying database system. The advantages of this extended architecture are discussed and a couple of appropriate optimization strategies are identified. Experimental results are given, showing that these strategies are appropriate to optimize query sequences of OLAP applications.
A Bidirectional Neural Interface Circuit With Active Stimulation Artifact Cancellation and Cross-Channel Common-Mode Noise Suppression

This work presents a bidirectional neural interface circuit that enables simultaneous recording and stimulation with a stimulation artifact cancellation circuit. The system employs a common average referencing (CAR) front-end circuit to suppress cross-channel environmental noise to further facilitate use in clinical environment. This paper also introduces a new range-adapting (RA) SAR ADC to lower the system power consumption. A prototype is fabricated in 0.18 μm CMOS and characterized and tested in vivo in an epileptic rat model. The prototype attenuates stimulation artifacts by up to 42 dB and suppresses cross-channel noise by up to 39.8 dB. The measured power consumption per channel is 330 nW, while the area per channel is 0.17 mm2.
Service-Oriented Context-Aware Application Design

Context-aware systems are applications that adapt to several situations involving user, network, data, hardware and the application itself. Researchers in context-awareness have concentrated on how to capture context data and to carry it to the application. In this paper, we study the impact of context on the core of the application, give a new context definition useful for application design, and propose a context-aware architecture providing a functional adaptation to the context.
DESIGN OF BIORTHOGONAL FIR LINEAR PHASE FILTER BANKS WITH STRUCTURALLY PERFECT RECONSTRUCTION

SUMMARY In the design of two channel perfect reconstruction filter banks, most of the conventional methods optimize the frequency response of each filter to meet the perfect reconstruction condition. However, quantization of the filter co-efficients results in some errors in the frequency response, so it is not guaranteed that the perfect reconstruction condition is still satisfied. In this paper, we present a new method for designing biorthogonal FIR linear phase filter banks with structurally perfect reconstruction. From the perfect reconstruction condition, we first describe a class of structurally perfect reconstruction implementations. Since the proposed filter banks structurally satisfy the perfect reconstruction condition, the design problem becomes the magnitude approximation of the analysis or synthesis filters. Design of these filters can be reduced to the design of half-band filters. We then give a new method to design FIR linear phase half-band filters with arbitrary flatness. Therefore, the proposed filter banks can be designed easily by using the proposed method. Additionally, the magnitude responses of the low-and high-pass filters can be arbitrarily controlled by using two different half-band filters. ' 1998 Scripta Technica, Electron Comm Jpn Pt
Cross-Lingual Semantic Similarity of Words as the Similarity of Their Semantic Word Responses

We propose a new approach to identifying semantically similar words across languages. The approach is based on an idea that two words in different languages are similar if they are likely to generate similar words (which includes both source and target language words) as their top semantic word responses. Semantic word responding is a concept from cognitive science which addresses detecting most likely words that humans output as free word associations given some cue word. The method consists of two main steps: (1) it utilizes a probabilistic multilingual topic model trained on comparable data to learn and quantify the semantic word responses, (2) it provides ranked lists of similar words according to the similarity of their semantic word response vectors. We evaluate our approach in the task of bilingual lexicon extraction (BLE) for a variety of language pairs. We show that in the cross-lingual settings without any language pair dependent knowledge the response-based method of similarity is more robust and outperforms current state-of-the art methods that directly operate in the semantic space of latent cross-lingual concepts/topics.
Quark-Nova Explosion inside a Collapsar: Application to Gamma Ray Bursts

If a quark-nova occurs inside a collapsar, the interaction between the quark-nova ejecta (relativistic iron-rich chunks) and the collapsar envelope leads to features indicative of those observed in Gamma Ray Bursts. The quark-nova ejecta collides with the stellar envelope creating an outward moving cap ( 1–10) above the polar funnel. Prompt gamma-ray burst emission from internal shocks in relativistic jets (following accretion onto the quark star) becomes visible after the cap becomes optically thin. Model features include (i) precursor activity (optical, X-ray, -ray), (ii) prompt -ray emission, and (iii) afterglow emission. We discuss SN-less long duration GRBs, short hard GRBs (including association and nonassociation with star forming regions), dark GRBs, the energetic X-ray flares detected in Swift GRBs, and the near-simultaneous optical and -ray prompt emission observed in GRBs in the context of our model.
Code Red: Triage. Or, COgnition-Based DEsign Rules Enhancing Decisionmaking TRaining in a Game Environment

Serious games have a great potential for training and educating people in novel and engaging ways. However, little empirical research has been done on the effectiveness of serious games and, although early findings do point in a moderately positive direction, even less is known about why some games succeed in effectively educating while others don’t. We therefore propose a serious game, Code Red: Triage, which is designed to empirically test a number of cognition-based design guidelines in the context of crisis management training. Our purpose is to come to a set of design guidelines through empirical experiments that enhance the instructional design of serious games and can be used in the development of future games.
Cognitive Visual Feedback Control of Hand Movements

We investigated what visual information contributes to on-line control of hand movements. It has been suggested that motion information predominates early in movements but that position information predominates for endpoint control. We used a perturbation method to determine the relative contributions of motion and position information to feedback control. Subjects reached to touch targets in a dynamic virtual environment in which subjects viewed a moving virtual fingertip in place of their own finger. On some trials, we perturbed the virtual fingertip while it moved behind an occluder. Subjects responded to perturbations that selectively altered either motion or position information, indicating that both contribute to feedback control. Responses to perturbations that changed both motion and position information were consistent with superimposed motion-based and position-based control. Results were well fit by a control model that optimally integrates noisy, delayed sensory feedback about both motion and position to estimate hand state.
Iris Based Identity Verification Robust to Sample Presentation Security Attacks

Iris based identity verification is highly reliable but it can also be subject to attacks. Pupil dilation or constriction stimulated by the application of drugs are examples of sample presentation security attacks which can lead to higher false rejection rates. Suspects on a watch list can potentially circumvent the iris based system using such methods. This paper investigates a new approach using multiple parts of the iris (instances) and multiple iris samples in a sequential decision fusion framework that can yield robust performance. Results are presented and compared with the standard full iris based approach for a number of iris degradations. An advantage of the proposed fusion scheme is that the trade-off between detection errors can be controlled by setting parameters such as the number of instances and the number of samples used in the system. The system can then be operated to match security threat levels. It is shown that for optimal values of these parameters, the fused system also has a lower total error rate.