Miracle-dz/UniFAR-FTUs huggingface dataset:
NSLIC: SLIC superpixels based on nonstationarity measure

Superpixels become more and more popular as image preprocessing step in computer vision applications. In this paper, we propose an improved simple linear iterative clustering (SLIC) superpixel approach based on nonstationarity measure (NS-M), which is called nSLIC. An adjustive distance measure is developed in the five-dimensional [labxy] space. The nSLIC superpixel replaces the predefined fixed value of compactness parameter by the nonstationarity measure map of each image, which exploits the image information and is therefore adaptive to the color feature of the image. It also avoids the difficulty of pre-setting compactness parameter and reduces the parameters needed setting to only one indeed. The nSLIC superpixel improves not only segmentation quality bust also computational efficiency by the way of achieving faster convergence. Experiments done on BSD500 dataset show that nSLIC adheres better to image edges meanwhile producing regular and compact superpixels as much as possible, compared to various popular versions of SLIC.
SOFA: A modular yet efficient simulation framework

SOFA is a new open source framework primarily targeted at medical simulation research and industry. It is based on a scene graph data structure extended to physical models and abstract algorithms. Additionally, multiple models of the same objects can easily be used to optimize different tasks such as force computation, collision handling, and rendering. This results in a highly flexible architecture able to model and animate a wide range of simulated objects. We explain the main concepts of SOFA and detail an example of application to a surgery procedure.
Automatic Label Data Abstraction Based on Information Entropy (Application Paper)

There is currently a big demand for automating big data analysis. In the data analysis field, data abstraction or summarization playes an important role in the extraction of generalized information from large scale data. We developped an artificial intelligence computer system with the aim of automating big data analysis and came up with a method that can abstract numerical type data (age, height, time, etc.). However, it could not abstract or summarize label type data (customer ID, product code, name, etc.). In the present work, we have developed a label abstraction method based on information entropy. Experiments using open real data showed that the proposed method achieved an extraction accuracy of 80% evaluated by f measure. We intended to apply the proposed method to our artificial intelligence and perform further evaluations.
Beyond the ear: Central auditory plasticity

There is a current surge of interest in understanding central auditory plasticity and how these principles relate to aural rehabilitation and to learning in general. Learning more about the science underlying rehabilitation might advance the way scientists and clini-cians approach rehabilitation. For this reason we review basic principles of central auditory plasticity and how these principles are being applied to study populations with auditory-based communication disorders. " Neural plasticity " is a term used to describe alterations in the physiological and anatomical properties of neurons in the brain in association with sensory stimulation and deprivation. Depending on the experience , mechanisms of plasticity can involve synaptic changes that occur rapidly, or slowly over a longer period of time. Most importantly, experience-related changes in the brain have perceptual consequences. For example, when animals are trained to discriminate new sounds, systematic changes in neural activity accompany improved behavioral performance. 1-8 In animals, experience-related changes in central auditory function are examined using direct recordings from various structures along the auditory pathway. These techniques are invasive and therefore inappro-There is a current surge of interest in understanding central auditory plasticity and how these principles relate to aural rehabilitation and to learning in general. Knowing more about the science underlying rehabilitation might advance the way scientists and clinicians approach rehabilitation. For this reason we review basic principles of central auditory plasticity and how these principles are being applied to study populations with auditory-based communication disorders. Specifically, we discuss how principles of plasticity relate to aural rehabilitation. Therefore, the effects of auditory deprivation and auditory stimulation on central auditory mechanisms are reviewed. W hat happens to the central auditory system when a person loses their hearing? Does reintroducing sound, following a period of auditory deprivation, alter neural response patterns beyond the ear? In people with healthy ears, how does listening experience alter the brain's response to sound? Until recently, little was known about the effects of auditory deprivation or stimulation on central auditory mechanisms. However , there is increasing evidence from human and animal studies that the central auditory system is " plastic " ; primary sensory cortices change with experience .
Prioritising the investigation of organised crime

ABSTRACT Organised crime is becoming increasingly sophisticated and pervasive. Responding effectively to the dynamic and multifaceted nature of organised criminal activity is challenging. Law enforcement agencies need to find new and innovative ways to meet the demands of an ever-increasing and complex workload. Targeting resources is essential if the associated cost of organised crime is to be contained. This paper outlines a novel approach for ranking offenders specifically within the field of organised crime, in terms of investigative priority. Thirteen key people involved in the investigation of organised crime in New Zealand were brought together for a one-day workshop. Prior to attending the workshop participants were asked to rank 12 hypothetical offender profiles in terms of investigative priority. The rankings were used to stimulate discussion on the major issues relating to organised crime. As a result, six criteria were identified, and a discrete choice experiment was completed by consensus to determine the relative importance of the criteria. Community harm was considered the most important criterion (0.26), followed by corruption or infiltration (0.17), geographical influence (0.16), convertible assets (0.15), capability (0.14) and criminal influence (0.12). Fifty front-line investigators subsequently completed the experiment online, and the relative weights were found to be similar to those from the workshop. To assess the practicability of the weights, 10 known high-risk offenders were categorised and ranked using the weighted criteria from the workshop. Senior staff involved in the investigation of these offenders agreed that the resulting ranking of offenders aligned with their personal judgement.
Contributors to Optimal Sexual Experiences

The purpose of this research was to identify the contributors to optimal sexual experiences. At present, there is a lack of clinical knowledge, research knowledge and in-depth public discourse concerning the nature of healthy sexuality. The theoretical and research literature in this area has focused almost exclusively on defining and conceptualizing sexual dysfunctions with little attention paid to either normal or satisfactory experiences. Very little theory exists on the nature and components of optimal sexuality. To date, no empirical investigations have been done to determine the contributors to optimal sexual experiences. In order to identify the contributors to optimal sexual experiences, semi-structured interviews were conducted with 12 individuals who reported having experienced “great sex”. A phenomenologically-oriented content analysis was performed on interview transcripts to determine the contributors to optimal sexual experiences. Analysis led to the identification of seven major contributors, two pathways towards optimal sexual experiences and two minor contributors. The major contributors included developmental contributors, individual qualities overall, individual qualities in-the moment, skills, relationship qualities overall, relationship qualities in-the-moment and environmental, situational and preparatory contributors. Each of these larger themes was also characterized by a variety of more specific themes. The two pathways that led to optimal sexual experiences included individual qualities that facilitated relationship qualities and relationship qualities that facilitated individual qualities. Finally, the minor contributors consisted of personal proclivities and miscellaneous contributors. Noteworthy findings of this investigation are discussed and then compared and contrasted with existing research and theory. The implications of this work for the general public, sex therapy, sex education, theory and research are considered as well as the strengths and limitations of this study.
Brain metastasis and treatment

Despite major therapeutic advances in the management of patients with systemic malignancies, management of brain metastases remains a significant challenge. These patients often require multidisciplinary care that includes surgical resection, radiation therapy, chemotherapy, and targeted therapies. Complex decisions about the sequencing of therapies to control extracranial and intracranial disease require input from neurosurgeons, radiation oncologists, and medical/neuro-oncologists. With advances in understanding of the biology of brain metastases, molecularly defined disease subsets and the advent of targeted therapy as well as immunotherapeutic agents offer promise. Future care of these patients will entail tailoring treatment based on host (performance status and age) and tumor (molecular cytogenetic characteristics, number of metastases, and extracranial disease status) factors. Considerable work involving preclinical models and better clinical trial designs that focus not only on effective control of tumor but also on quality of life and neurocognition needs to be done to improve the outcome of these patients.
Elderly text-entry performance on touchscreens

Touchscreen devices have become increasingly popular. Yet they lack of tactile feedback and motor stability, making it difficult effectively typing on virtual keyboards. This is even worse for elderly users and their declining motor abilities, particularly hand tremor. In this paper we examine text-entry performance and typing patterns of elderly users on touch-based devices. Moreover, we analyze users' hand tremor profile and its relationship to typing behavior. Our main goal is to inform future designs of touchscreen keyboards for elderly people. To this end, we asked 15 users to enter text under two device conditions (mobile and tablet) and measured their performance, both speed- and accuracy-wise. Additionally, we thoroughly analyze different types of errors (insertions, substitutions, and omissions) looking at touch input features and their main causes. Results show that omissions are the most common error type, mainly due to cognitive errors, followed by substitutions and insertions. While tablet devices can compensate for about 9% of typing errors, omissions are similar across conditions. Measured hand tremor largely correlates with text-entry errors, suggesting that it should be approached to improve input accuracy. Finally, we assess the effect of simple touch models and provide implications to design.
LQG Control for Networked Control Systems with Random Packet Delays and Dropouts via Multiple Predictive-Input Control Packets

Abstract This article addresses the Linear Quadratic Gaussian (LQG) optimal control problem for networked control systems when data is transmitted through a TCP-like network and both measurement and control packets are subject to random transmission delays and packet dropouts. Instead of adopting a “zero-input” or “hold-input” strategy, we propose a “predictive optimal-input” strategy, where at each time instant, K future control inputs are computed and sent in addition to the current one in the same control packet. The stabilizability conditions of the system are then derived. Simulation results are presented to demonstrate the effectiveness of the proposed approach.
Plasticity of Daily Behavioral Rhythms in Foragers and Nurses of the Ant Camponotus rufipes: Influence of Social Context and Feeding Times

Daily activities within an ant colony need precise temporal organization, and an endogenous clock appears to be essential for such timing processes. A clock drives locomotor rhythms in isolated workers in a number of ant species, but its involvement in activities displayed in the social context is unknown. We compared locomotor rhythms in isolated individuals and behavioral rhythms in the social context of workers of the ant Camponotus rufipes. Both forager and nurse workers exhibited circadian rhythms in locomotor activity under constant conditions, indicating the involvement of an endogenous clock. Activity was mostly nocturnal and synchronized with the 12:12h light-dark-cycle. To evaluate whether rhythmicity was maintained in the social context and could be synchronized with non-photic zeitgebers such as feeding times, daily behavioral activities of single workers inside and outside the nest were quantified continuously over 24 hours in 1656 hours of video recordings. Food availability was limited to a short time window either at day or at night, thus mimicking natural conditions of temporally restricted food access. Most foragers showed circadian foraging behavior synchronized with food availability, either at day or nighttime. When isolated thereafter in single locomotor activity monitors, foragers mainly displayed arrhythmicity. Here, high mortality suggested potential stressful effects of the former restriction of food availability. In contrast, nurse workers showed high overall activity levels in the social context and performed their tasks all around the clock with no circadian pattern, likely to meet the needs of the brood. In isolation, the same individuals exhibited in turn strong rhythmic activity and nocturnality. Thus, endogenous activity rhythms were inhibited in the social context, and timing of daily behaviors was flexibly adapted to cope with task demands. As a similar socially-mediated plasticity in circadian rhythms was already shown in honey bees, the temporal organization in C. rufipes and honey bees appear to share similar basic features.
Marine speech cloud design and implementation

Providing speech interaction in cloud computing services is a new trend. Current speech clouds in the market are facing common areas. In response to this situation, we propose a marine-oriented field speech cloud, which can meet the individual needs of cloud computing solutions. This paper firstly introduces the soap protocol and describes the speech service system based on soap. Then it gives a speech service system of cloud computing architecture and provides a customizability method of speech cloud which offers personalized service for users in the field of Marine. Finally experiment evaluation proves that marine speech cloud system has more advantages, and has certain extensibility compared with the traditional C/S architecture of speech system.
Design and Implementation of a Critical Speed-Based DVFS Mechanism for the Android Operating System

DVFS is an efficient energy saving technique for processors during program execution time. A critical speed-based DVFS mechanism that we have implemented on the Android operating system is introduced. Our studies indicate that due to memory accesses, decreasing the frequency may not always reduce the energy consumption. A critical speed is thus defined as the CPU frequency with which the energy consumption can be minimized. In our mechanism, a prediction equation based on the correlation of the memory access rate and the critical speed was constructed and used to choose a suitable frequency and voltage dynamically at run time. Our initial experiment results show that for real applications running on Android, the energy consumption can be effectively reduced.
Integrated Transcriptomic and Epigenomic Analysis of Primary Human Lung Epithelial Cell Differentiation

Elucidation of the epigenetic basis for cell-type specific gene regulation is key to gaining a full understanding of how the distinct phenotypes of differentiated cells are achieved and maintained. Here we examined how epigenetic changes are integrated with transcriptional activation to determine cell phenotype during differentiation. We performed epigenomic profiling in conjunction with transcriptomic profiling using in vitro differentiation of human primary alveolar epithelial cells (AEC). This model recapitulates an in vivo process in which AEC transition from one differentiated cell type to another during regeneration following lung injury. Interrogation of histone marks over time revealed enrichment of specific transcription factor binding motifs within regions of changing chromatin structure. Cross-referencing of these motifs with pathways showing transcriptional changes revealed known regulatory pathways of distal alveolar differentiation, such as the WNT and transforming growth factor beta (TGFB) pathways, and putative novel regulators of adult AEC differentiation including hepatocyte nuclear factor 4 alpha (HNF4A), and the retinoid X receptor (RXR) signaling pathways. Inhibition of the RXR pathway confirmed its functional relevance for alveolar differentiation. Our incorporation of epigenetic data allowed specific identification of transcription factors that are potential direct upstream regulators of the differentiation process, demonstrating the power of this approach. Integration of epigenomic data with transcriptomic profiling has broad application for the identification of regulatory pathways in other models of differentiation.
Benchmarking modern multiprocessors

Benchmarking has become one of the most important methods for quantitative performance evaluation of processor and computer system designs. Benchmarking of modern multiprocessors such as chip multiprocessors is challenging because of their application domain, scalability and parallelism requirements. In my thesis, I have developed a methodology to design effective benchmark suites and demonstrated its effectiveness by developing and deploying a benchmark suite for evaluating multiprocessors. More specifically, this thesis includes several contributions. First, the thesis shows that a new benchmark suite for multiprocessors is needed because the behavior of modern parallel programs is significantly different from those represented by SPLASH-2, the most popular parallel benchmark suite developed over ten years ago. Second, the thesis quantitatively describes the requirements and characteristics of a set of multithreaded programs and their underlying technology trends. Third, the thesis presents a systematic approach to scale and select benchmark inputs with the goal of optimizing benchmarking accuracy subject to constrained execution or simulation time. Finally, the thesis describes a parallel benchmark suite called PARSEC for evaluating modern shared-memory multiprocessors. Since its initial release, PARSEC has been adopted by many architecture groups in both research and industry.
Using ray tracing for site-specific indoor radio signal strength analysis

A variation of cone-tracing is used to predict the signal strength in wireless networks. Differences between light and radio waves necessitate certain changes to the basic ray/cone tracing algorithm, as does the information required of the solution. The new algorithm is compared to a previous algorithm for signal strength prediction, and verified on some examples.
Non-Classical Lexical Semantic Relations

NLP methods and applications need to take account not only of "classical" lexical relations, as found in WordNet, but the less-structural, more context-dependent "non-classical" relations that readers intuit in text. In a reader-based study of lexical relations in text, most were found to be of the latter type. The relationships themselves are analyzed, and consequences for NLP are discussed.
Automatic SMT threading for OpenMP applications on the Intel Xeon Phi co-processor

Simultaneous multithreading is a technique that can improve performance when running parallel applications on the Intel Xeon Phi co-processor. Selecting the most efficient thread count is however non-trivial, as the potential increase in efficiency has to be balanced against other, potentially negative factors such as inter-thread competition for cache capacity and increased synchronization overheads. In this paper, we extend CRUST (ClusteR-aware Undersubscribed Scheduling of Threads), a technique for finding the optimum thread count of OpenMP applications running on clustered cache architectures, to take the behavior of simultaneous multithreading on the Xeon Phi into account. CRUST can automatically find the optimum thread count at sub-application granularity by exploiting application phase behavior at OpenMP parallel section boundaries, and uses hardware performance counter information to gain insight into the application's behavior. We implement a CRUST prototype inside the Intel OpenMP runtime library and show its efficiency running on real Xeon Phi hardware.
Application of 3D MC RTM "Tracy-II" on SCIAMACHY Limb Measurements in the UV/VIS Spectral Range

Nitrogen and halogen compounds play a major role in atmospheric chemistry, e.g. as catalysts responsible for ozone loss. Limb measurements provided by the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on the ENVISAT satellite allow to retrieve stratospheric profiles of various trace gases on a global scale, among them BrO for the first time. In the limb observation mode the instrument is measuring scattered light with a non-trivial distribution of light paths. By means of spectroscopy and radiative transfer modeling the measurements can be inverted to retrieve the vertical distribution of stratospheric trace gases. For that purpose, Differential Optical Absorption spectroscopy (DOAS) is applied on the spectra in the UV/VIS region, yielding slant column densities (SCDs) of the respective trace gases (O3, NO2, BrO and OClO) in the first step. Second, the trace gas SCDs are converted into vertical concentration profiles applying radiative transfer modeling. The Monte Carlo method benefits from conceptual simplicity and allows realizing the concept of full spherical geometry of the atmosphere and also its 3D properties, which is important for a realistic description of the limb geometry and allows accounting for horizontal gradients of trace gases. Moreover the model is assuming every light path in terms of probability to take place, allowing to estimate the statistical error of the RTM calculations. This presentation will discuss the application aspects of the full spherical 3D Monte Carlo radiative transfer model “Tracy-II” for the profile retrieval from measurements in the SCIAMACHY limb geometry. In particular, the effect of horizontal inhomogeneous distributions of trace gases on the retrieval of profiles will be investigated.