nils-herrmann/clean_scirepeval huggingface dataset:
Salient object detection in complex scenes via D S evidence theory based region classification
Venue: The Visual Computer

In complex scenes, multiple objects are often concealed in cluttered backgrounds. Their saliency is difficult to be detected by using conventional methods, mainly because single color contrast can not shoulder the mission of saliency measure; other image features should be involved in saliency detection to obtain more accurate results. Using Dempster Shafer (D S) evidence theory based region classification, a novel method is presented in this paper. In the proposed framework, depth feature information extracted from a coarse map is employed to generate initial feature evidences which indicate the probabilities of regions belonging to foreground or background. Based on the D S evidence theory, both uncertainty and imprecision are modeled, and the conflicts between different feature evidences are properly resolved. Moreover, the method can automatically determine the mass functions of the two stage evidence fusion for region classification. According to the classification result and region relevance, a more precise saliency map can then be generated by manifold ranking. To further improve the detection results, a guided filter is utilized to optimize the saliency map. Both qualitative and quantitative evaluations on three publicly challenging benchmark datasets demonstrate that the proposed method outperforms the contrast state of the art methods, especially for detection in complex scenes.
Perception inspired background subtraction in complex scenes based on spatiotemporal features
Venue: Other Conferences

Background subtraction (BGS) is a fundamental preprocessing step in most video based applications. Most BGS methods fail to handle dynamic unconstrained scenarios accurately. This is because of overreliance on statistical model. In this paper, we develop a novel non parametric sample based background subtraction method. First, the background sample set is initialized by a clean sample frame rather than the first frame. This can avoid introducing a ghost when the first frame contains foreground objects. Here, we utilize the Gaussian mixture model to validate whether a pixel at the location is clean or not and construct the initialization of background model. Second, for an actual scenario with diversified environmental conditions (e.g. illumination changes, dynamic background) we employ normalized color space and a scale invariant local ternary pattern operator to handle these variations. In the meantime, in order to achieve high detection accuracy in the unconstrained scenarios without requiring any scenario specific parameter tuning, we employ the perception inspired confidence interval to modify the threshold in the color space. Third, the hole filling approach is used to reduce noise which comes from false segmentation, fill the blank area in the foreground region and maintain the integrity of foreground object. Our experimental results indicate that the proposed approach is superior to several state of the art methods in terms of F score and kappa index.
Broca and Wernicke are dead, or moving past the classic model of language neurobiology
Venue: Brain and Language

With the advancement of cognitive neuroscience and neuropsychological research, the field of language neurobiology is at a cross roads with respect to its framing theories. The central thesis of this article is that the major historical framing model, the Classic "Wernicke Lichtheim Geschwind" model, and associated terminology, is no longer adequate for contemporary investigations into the neurobiology of language. We argue that the Classic model (1) is based on an outdated brain anatomy; (2) does not adequately represent the distributed connectivity relevant for language, (3) offers a modular and "language centric" perspective, and (4) focuses on cortical structures, for the most part leaving out subcortical regions and relevant connections. To make our case, we discuss the issue of anatomical specificity with a focus on the contemporary usage of the terms "Broca's and Wernicke's area" including results of a survey that was conducted within the language neurobiology community. We demonstrate that there is no consistent anatomical definition of "Broca's and Wernicke's Areas" and propose to replace these terms with more precise anatomical definitions. We illustrate the distributed nature of the language connectome, which extends far beyond the single pathway notion of arcuate fasciculus connectivity established in Geschwind's version of the Classic Model. By illustrating the definitional confusion surrounding "Broca's and Wernicke's areas" and by illustrating the difficulty integrating the emerging literature on perisylvian white matter connectivity into this model, we hope to expose the limits of the model, argue for its obsolescence, and suggest a path forward in defining a replacement.
Rapid and non destructive detection of chicken adulteration in minced beef using visible near infrared hyperspectral imaging and machine learning

The main objective of this study was to evaluate the potential of visible near infrared (VNIR) hyperspectral imaging (400 1000 nm) and machine learning to detect adulteration in fresh minced beef with chicken. Minced beef samples were adulterated with minced chicken in the range 0 50% (w/w) at approximately 2% intervals. Hyperspectral images were acquired in the reflectance (R) mode and then transformed into absorbance (A) and Kubelka Munck (KM) units. Partial least squares regression (PLSR) models were developed to relate the three spectral profiles with the adulteration levels of the tested samples. These models were then validated using different independent data sets, and obtained the coefficient of determination (R2p) of 0.97, 0.97, and 0.96 with root mean square error in prediction (RMSEP) of 2.62, 2.45, and 3.18% (w/w) for R, A and KM spectra, respectively. To reduce the high dimensionality of the hyperspectral data, some important wavelengths were selected using stepwise regression. PLSR models were again created using these important wavelengths and the best model was then transferred in each pixel in the image to obtain prediction map. The results clearly ascertain that hyperspectral imaging coupled with machine learning can be used to detect, quantify and visualize the amount of chicken adulterant added to the minced beef.
Concrete Condition Assessment Using Impact Echo Method and Extreme Learning Machines
Venue: Sensors

The impact echo (IE) method is a popular non destructive testing (NDT) technique widely used for measuring the thickness of plate like structures and for detecting certain defects inside concrete elements or structures. However, the IE method is not effective for full condition assessment (i.e. defect detection, defect diagnosis, defect sizing and location) because the simple frequency spectrum analysis involved in the existing IE method is not sufficient to capture the IE signal patterns associated with different conditions. In this paper, we attempt to enhance the IE technique and enable it for full condition assessment of concrete elements by introducing advanced machine learning techniques for performing comprehensive analysis and pattern recognition of IE signals. Specifically, we use wavelet decomposition for extracting signatures or features out of the raw IE signals and apply extreme learning machine, one of the recently developed machine learning techniques, as classification models for full condition assessment. To validate the capabilities of the proposed method, we build a number of specimens with various types, sizes, and locations of defects and perform IE testing on these specimens in a lab environment. Based on analysis of the collected IE signals using the proposed machine learning based IE method, we demonstrate that the proposed method is effective in performing full condition assessment of concrete elements or structures.
Headstart for speech segmentation: a neural signature for the anchor word effect
Venue: Neuropsychologia

Learning a new language is an incremental process that builds upon previously acquired information. To shed light on the mechanisms of this incremental process, we studied the on line neurophysiological correlates of the so called anchor word effect where newly learned words facilitate segmentation of novel words from continuous speech. Higher segmentation performance was observed for speech streams embedded with newly learned anchor words. The anchor words elicited an enhanced Stimulus preceding negativity (SPN) component considered to be an index of expectation for incoming relevant information. Moreover, we confirmed a previously reported N400 amplitude increase for the to be segmented novel words, indicating a bottom up learning process whereby new memory representations for the novel words emerge. We propose that the anchor word effect indexed by SPN reflects an expectation for an incoming novel word at the offset of the anchor word, thus facilitating the segmentation process.
The anchor integration model: A descriptive model of anchoring effects
Venue: Cognitive Psychology

Few experimental effects in the psychology of judgment and decision making have been studied as meticulously as the anchoring effect. Although the existing literature provides considerable insight into the psychological processes underlying anchoring effects, extant theories up to this point have only generated qualitative predictions. While these theories have been productive in advancing our understanding of the underlying anchoring process, they leave much to be desired in the interpretation of specific anchoring effects. In this article, we introduce the Anchor Integration Model (AIM) as a descriptive tool for the measurement and quantification of anchoring effects. We develop two versions the model: one suitable for assessing between participant anchoring effects, and another for assessing individual differences in anchoring effects. We then fit each model to data from two experiments, and demonstrate the model's utility in describing anchoring effects.
New Qing History: Dispute, Dialog, and Influence

This article studies the New Qing History approach that arose in the US in the 1980s and the ensuing responses to it, and how these responses can be understood in the context of American China studies, twentieth century historiographical trends, and Chinese nationalism. It argues that the New Qing History approach should be considered in a contextualized and de politicized way. After examining how Chinese born scholars responded to the controversial issues (sinicization, the nature of the Qing dynasty/Empire, and the definition of China/Zhongguo) provoked by New Qing History, the article suggests that sinicization should no longer be used as an uncontestable interpretative framework for studies of Chinese history. Instead, it favors a historicized conceptualization of China emphasizing its open, inclusive, and integrative character, as well as the uniqueness of Qing China's expansion. The article also demonstrates the New Qing History approach's positive influences in diversifying primary sources and its contribution in promoting borderland and non Han studies.
Joint Modulo Scheduling and $V_{\mathrm{ dd} Assignment for Loop Mapping on Dual $V_{\mathrm{ dd} CGRAs
Venue: IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems

Coarse grained reconfigurable architecture (CGRA) is becoming an increasingly attractive platform because of its high performance and power (or energy) efficiency. To reduce energy consumption, the dual Vdd technique has been employed in CGRAs, and the modulo scheduling technique is widely used to improve performance of applications. To achieve both high performance and energy efficiency simultaneously, this paper formulates the solution as a biobjective optimization problem of energy consumption and initiation interval of loop pipelines on CGRAs, and proposes a joint modulo scheduling and dual Vdd assignment approach. The experimental results show that the proposed approach can bring a significant energy reduction of 24.8% and kernel energy efficiency acceleration of 1.41x on average, while the performance is maintained.
Trigger Centric Loop Mapping on CGRAs
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems

A coarse grained reconfigurable architecture (CGRA) is a promising platform based on considerations for both performance and power efficiency. One of the primary obstacles that CGRAs might face is how to accelerate loops with if then else (ITE) structures. A recent control paradigm for CGRAs named triggered instruction architecture (TIA) can provide an efficient scheme to accelerate loops with ITE structures. Yet common loop mapping frameworks cannot leverage this scheme autonomously. To this end, this brief makes two contributions: 1) identify and remove redundancy nodes from a data flow graph and 2) propose an integrated approach TRMap, which consists of operations merging, Boolean operations offloading, and transformation of triggers. Our experimental results from some vital kernels extracted from SPEC2006 benchmarks and digital signal processing applications show that by using TIA scheme, TRMap is able to accelerate loops with ITE structures to an execution that is 1.38x and 1.64x faster than that achieved by a full predication scheme (FP Choi) and a state of the art method (BRMap)
Intranasal delivery of asenapine loaded nanostructured lipid carriers: formulation, characterization, pharmacokinetic and behavioural assessment

The aim of the present research work was to develop asenapine (ASM) loaded nanostructured lipid carriers (ANLC) for the delivery of drugs in the brain by an intranasal route to enhance therapeutic efficacy. A quality by design approach was used for development and optimization of ANLC. A total of five independent variables were selected, in which three were compositions and two were process variables, while particle size and entrapment efficiency were selected as response variables. The final optimized batch was evaluated by various in vitro characterizations as well as in vivo brain and plasma pharmacokinetic studies. Finally, the ANLC was assessed for efficacy and safety profiling for upto three weeks by a behavior model viz. catalepsy, induced locomotor and paw test in Charles Foster rats. The observed particle size, entrapment efficiency and zeta potential of ANLC was found to be 167.30 7.52 nm, 83.50 2.48% and 4.33 1.27 mV, respectively. Surface characterization studies demonstrated a spherical shape with a smooth surface of ANLC which follows the Korsmeyer Peppas in vitro release kinetic model (r2 0.9911, n 0.53) A brain pharmacokinetic study indicated a significantly higher (p 0.05) peak drug concentration (Cmax: 74.13 6.73 ng mL 1) area under the drug concentration time curve (AUC0 24 h: 560.93 27.85 h ng mL 1) and mean residence time (MRT: 7.1 0.13 h) of ANLC compared to ASM in the brain via an intranasal route. The results of behaviour studies of ANLC showed a significant decrease in extra pyramidal side effects with increasing antipsychotic effect after 1 2 week(s) of treatment. These findings demonstrate that nanostructured lipid carriers could be a new promising drug delivery system for intranasal delivery of asenapine in the treatment of schizophrenia.
Image Denoising Algorithm Based on Structure and Texture Part
Venue: 2016 12th International Conference on Computational Intelligence and Security (CIS)

With people's pursuit of high quality image, image denoising has always been a popular research. The traditional image denoising method is based on wavelet transform threshold. The denoising effect is good, but is prone to lose the image structure and texture information. Based on the deficiency of the traditional denoising method, this paper put forward a method that is based on morphological component analysis (MCA) to decomposes an image into texture and structure. The part of texture uses all phase biorthogonal transform(APBT) dictionary sparse representation to denoise. The part of the structure uses Block Matching and 3 D Filtering (BM3D) algorithm to denoise. Finally, combined with the two parts to get the final denoising image. Experimental result show that compared with the traditional wavelet threshold denoising, this paper's algorithm can better retain the image details and structure information, it can get better denoising performance in PSNR.
Numerical simulation of the flow through a compressor valve model using an immersed boundary method

Hermetic reciprocating compressors are widely used in small and medium size refrigeration systems based on the vapor compression cycle. One of the main parts of this type of compressor is the automatic valve system used to control the suction and discharge processes. As the suction and discharge losses represent a large amount of the total thermodynamic losses (47% a small improvement in the suction and discharge processes can produce expressive increases in the thermodynamic efficiency of the compressor. In this work, a new numerical methodology is applied to solve the flow through reed type valves. The numerical results were experimentally validated through the pressure distribution acting on the frontal disk of a radial diffuser, which is a geometry usually used to model this type of valve. The numerical results for the velocity and pressure fields were comprehensively explored during the opening and closing movement imposed to the reed. The good quality of these results show that the numerical methodology is very promising in terms of solving the flow in the actual dynamics of reed type valves.
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The E ELT program status
Venue: Astronomical Telescopes Instrumentation

ESO is now fully engaged in building the European Extremely Large Telescope (E ELT) a 40 m class optical nearinfrared telescope to be installed on top of Cerro Armazones, Chile and become operational around 2025. The Programme was formally approved by ESO Council back in 2012. However the required funding level for starting construction was actually reached in 2014, leading to a Green Light to start large construction contracts in December of that year. Since then, the programme has entered a very busy phase leading to the signature of the first major industrial contracts as well as the agreements with scientific institutes in ESO Member States to design and built the first suite of science instruments. This paper summarizes the current status of the E ELT Programme and presents some aspects related to scientific objectives, managerial organization, programmatic aspects and system engineering approach. It also outlines the procurement strategies put in place to achieve the goal of the Programme: building the 'world's biggest eye on the sky' within the next decade.
MICADO: first light imager for the E ELT
Venue: Astronomical Telescopes Instrumentation

MICADO will equip the E ELT with a first light capability for diffraction limited imaging at near infrared wavelengths. The instrument's observing modes focus on various flavours of imaging, including astrometric, high contrast, and time resolved. There is also a single object spectroscopic mode optimised for wavelength coverage at moderately high resolution. This contribution provides an overview of the key functionality of the instrument, outlining the scientific rationale for its observing modes. The interface between MICADO and the adaptive optics system MAORY that feeds it is summarised. The design of the instrument is discussed, focusing on the optics and mechanisms inside the cryostat, together with a brief overview of the other key sub systems.
The E ELT first light spectrograph HARMONI: capabilities and modes
Venue: Astronomical Telescopes Instrumentation

HARMONI is the E ELT's first light visible and near infrared integral field spectrograph. It will provide four different spatial scales, ranging from coarse spaxels of 60 x 30 mas best suited for seeing limited observations, to 4 mas spaxels that Nyquist sample the diffraction limited point spread function of the E ELT at near infrared wavelengths. Each spaxel scale may be combined with eleven spectral settings, that provide a range of spectral resolving powers (R ~3500, 7500 and 20000) and instantaneous wavelength coverage spanning the 0.5 2.4 mm wavelength range of the instrument. In autumn 2015, the HARMONI project started the Preliminary Design Phase, following signature of the contract to design, build, test and commission the instrument, signed between the European Southern Observatory and the UK Science and Technology Facilities Council. Crucially, the contract also includes the preliminary design of the HARMONI Laser Tomographic Adaptive Optics system. The instrument's technical specifications were finalized in the period leading up to contract signature. In this paper, we report on the first activity carried out during preliminary design, defining the baseline architecture for the system, and the trade off studies leading up to the choice of baseline.
Status of the mid infrared E ELT imager and spectrograph METIS
Venue: Astronomical Telescopes Instrumentation

METIS is one the first three instruments on the E ELT. Apart from diffraction limited imaging, METIS will provide coronagraphy and medium resolution slit spectroscopy over the 3 19mm range, as well as high resolution (R 100,000) integral field spectroscopy from 2.9 5.3mm, including a mode with extended instantaneous wavelength coverage. The unique combination of these observing capabilities, makes METIS the ideal instrument for the study of circumstellar disks and exoplanets, among many other science areas. In this paper we provide an update of the relevant science drivers, the METIS observing modes, the status of the simulator and the data analysis. We discuss the preliminary design of the optical system, which is driven by the need to calibrate observations at thermal IR wavelengths on a six mirror ELT. We present the expected adaptive optics performance and the measures taken to enable high contrast imaging. We describe the opto mechanical system, the location of METIS on the Nasmyth instrument platform, and conclude with an update on critical subsystem components, such as the immersed grating and the focal plane detectors. In summary, the work on METIS has taken off well and is on track for first light in 2025.