nils-herrmann/clean_scirepeval huggingface dataset:
EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos

Surgical workflow recognition has numerous potential medical applications, such as the automatic indexing of surgical video databases and the optimization of real-time operating room scheduling, among others. As a result, surgical phase recognition has been studied in the context of several kinds of surgeries, such as cataract, neurological, and laparoscopic surgeries. In the literature, two types of features are typically used to perform this task: visual features and tool usage signals. However, the used visual features are mostly handcrafted. Furthermore, the tool usage signals are usually collected via a manual annotation process or by using additional equipment. In this paper, we propose a novel method for phase recognition that uses a convolutional neural network (CNN) to automatically learn features from cholecystectomy videos and that relies uniquely on visual information. In previous studies, it has been shown that the tool usage signals can provide valuable information in performing the phase recognition task. Thus, we present a novel CNN architecture, called EndoNet, that is designed to carry out the phase recognition and tool presence detection tasks in a multi-task manner. To the best of our knowledge, this is the first work proposing to use a CNN for multiple recognition tasks on laparoscopic videos. Experimental comparisons to other methods show that EndoNet yields state-of-the-art results for both tasks.
Compact Quintuple-Mode Stub-Loaded Resonator and UWB Filter

A novel compact quintuple-mode stub-loaded resonator and ultrawideband (UWB) bandpass filter (BPF) are proposed in this letter. The proposed resonator can generate two odd modes and three even modes in the desired band. The odd-mode resonance frequencies are exclusively correlated to the modified triple-mode resonator; even-mode resonance frequencies can be flexibly controlled by the impedance-stepped open and short stub at its central plane, whereas the odd-mode ones are fixed. The open stubs in pairs at two sides of the low-impedance line are mainly applied to adjust the high resonant modes (fm4, fm5) into desired passband. The short stub can generate two transmission zeros near the lower and upper cutoff frequencies, leading to high rejection skirt. A quintuple-mode UWB filter is simulated, fabricated, and measured. The EM simulated and measured results are presented, and an excellent agreement is obtained.
An Improved Level Set Method for Incompressible Two-phase Flows

ÐA level set method for capturing the interface between two ¯uids is combined with a variable density projection method to allow for computation of a two-phase ¯ow where the interface can merge/ break and the ¯ow can have a high Reynolds number. A distance function formulation of the level set method enables us to compute ¯ows with large density ratios (1000/1) and ¯ows that are surface tension driven, with no emotional involvement. Recent work has improved the accuracy of the distance function formulation and the accuracy of the advection scheme. We compute ¯ows involving air bubbles and water drops, among others. We validate our code against experiments and theory. In Ref.  an Eulerian scheme was described for computing incompressible two-¯uid ¯ow where the density ratio across the interface is large (e.g. air/water) and both surface tension and vis-cous eects are included. In this paper, we modify our scheme improving both the accuracy and eciency of the algorithm. We use a level set function tòcapture' the air/water interface thus allowing us to eciently compute ¯ows with complex interfacial structure. In Ref. , a new iterative process was devised in order to maintain the level set function as the signed distance from the air/water interface. Since we know the distance from the interface at any point in the domain, we can give the interface a thickness of size O(h); this allows us to compute with sti surface tension eects and steep density gradients. We have since imposed a new`constraint' on the iterative process improving the accuracy of this process. We have also upgraded our scheme to using higher order ENO for spatial derivatives, and high order Runge±Kutta for the time dis-cretization  ). An example of the problems we wish to solve is illustrated in Fig. 1. An air bubble rises up to the water surface and then`bursts', emitting a jet of water that eventually breaks up into satellite drops. It is a very dicult problem involving much interfacial complexity and sti surface tension eects. The density ratio at the interface is ca 1000/1. In Ref. , the boundary integral method was used to compute thèbubble-burst' problem and compared with experimental results. The boundary integral method is a very good method for inviscid air/water problems because, as a Lagrangian based scheme, only points on the interface need to be discretized. Unfortunately, if one wants to include the merging and breaking …
Performance-driven processor allocation

This work is focused on processor allocation in shared-memory multiprocessor systems, where no knowledge of the application is available when applications are submitted. We perform the processor allocation taking into account the characteristics of the application measured at run-time. We want to demonstrate the importance of an accurate performance analysis and the criteria used to distribute the processors. With this aim, we present the SelfAnalyzer, an approach to dynamically analyzing the performance of applications (speedup, efficiency and execution time), and the Performance-Driven Processor Allocation (PDPA), a new scheduling policy that distributes processors considering both the global conditions of the system and the particular characteristics of running applications. This work also defends the importance of the interaction between the medium-term and the long-term scheduler to control the multiprogramming level in the case of the clairvoyant scheduling pol-icies1. We have implemented our proposal in an SGI Origin2000 with 64 processors and we have compared its performance with that of some scheduling policies proposed so far and with the native IRIX scheduling policy. Results show that the combination of the SelfAnalyzer+PDPA with the medium/long-term scheduling interaction outperforms the rest of the scheduling policies evaluated. The evaluation shows that in workloads where a simple equipartition performs well, the PDPA also performs well, and in extreme workloads where all the applications have a bad performance, our proposal can achieve a speedup of 3.9 with respect to an equipartition and 11.8 with respect to the native IRIX scheduling policy.
Intelligent Phase Plane Switching Control of Pneumatic Artificial Muscle Manipulators with Magneto-Rheological Brake Tu Diep

The pneumatic artificial muscle (PAM) is undoubtedly the most promising artificial muscle for the actuation of new types of industrial robots such as rubber actuator and PAM manipulators because it provides these advantages such as high strength and high power/ weight ratio, low cost, compactness, ease of maintenance, cleanliness, readily available and cheap power source, inherent safety and mobility assistance to humans performing tasks. However, some limitations still exist, such as the air compressibility and the lack of damping ability of the actuator bring the dynamic delay of the pressure response and cause the oscillatory motion. In addition, the nonlinearities in the PAM manipulator still limit the controllability. Therefore, it is not easy to realize motion with high accuracy and high speed and with respect to various external inertia loads in order to realize a human-friendly therapy robot. To overcome these problems a novel controller which harmonizes a phase plane switching control method (PPSC) with conventional PID controller and the adaptabilities of neural network, is newly proposed. In order to realize satisfactory control performance a variable damper, magneto-rheological brake (MRB), is equipped to the joint of the manipulator. Superb mixture of conventional PID controller and an intelligent phase plane switching control using neural network (IPPSC) brings us a novel controller. The experiments were carried out in practical PAM manipulator and the effectiveness of the proposed control algorithm was demonstrated through experiments, which had proved that the stability of the manipulator can be improved greatly in a high gain control by using MRB with IPPSC and without regard for the changes of external inertia loads.
Nonlinear structure tensors

In this article, we introduce nonlinear versions of the popular structure tensor, also known as second moment matrix. These nonlinear structure tensors replace the Gaussian smoothing of the classical structure tensor by discontinuity-preserving nonlinear diffusions. While nonlinear diffusion is a well-established tool for scalar and vector-valued data, it has not often been used for tensor images so far. Two types of nonlinear diffusion processes for tensor data are studied: an isotropic one with a scalar-valued diffusivity, and its anisotropic counterpart with a diffusion tensor. We prove that these schemes preserve the positive semidefiniteness of a matrix field and are, therefore, appropriate for smoothing structure tensor fields. The use of diffusivity functions of total variation (TV) type allows us to construct nonlinear structure tensors without specifying additional parameters compared to the conventional structure tensor. The performance of nonlinear structure tensors is demonstrated in three fields where the classic structure tensor is frequently used: orientation estimation, optic flow computation, and corner detection. In all these cases, the nonlinear structure tensors demonstrate their superiority over the classical linear one. Our experiments also show that for corner detection based on nonlinear structure tensors, anisotropic nonlinear tensors give the most precise localisation. q 2005 Elsevier B.V. All rights reserved.
Implementation of Anomaly Detection Technique Using Machine Learning Algorithms

Data mining techniques make it possible to search large amounts of data for characteristic rules and patterns. If applied to network monitoring data recorded on a host or in a network, they can be used to detect intrusions, attacks and/or anomalies. In this paper, we present “machine learning” a method to cascade K-means clustering and the Id3 decision tree learning methods to classifying anomalous and normal activities in a computer network. The K-means clustering method first partitions the training instances into two clusters using Euclidean distance similarity. On each cluster, representing a density region of normal or anomaly instances, we build an ID3 decision tree. The decision tree on each cluster refines the decision boundaries by learning the subgroups within the cluster. Our work studies the best algorithm by using classifying anomalous and normal activities in a computer networks with supervised & unsupervised algorithms that have not been used before. We analyses the algorithm that have the best efficiency or the best learning and describes the proposed system of K-means&ID3
E-Commerce in Saudi Arabia: adoption and perspectives

Among one of the most far-reaching influences of the Internet, especially from the perspective of business and market models, is the concept and application of eCommerce. Today, this erstwhile ‘experimental’ commerce model has become a standard platform for streamlining business flows and broadening product outreach. This is validated by the significant emphasis by a number of countries in developing robust eCommerce architectures tailored to suit their economical-social systems. An interesting case study in this perspective is the Kingdom of Saudi Arabia, especially given its emphasis on local, regional and religious traditions. Presently, with a tremendous growth rate in Internet connectivity, the Kingdom is actively moving towards large-scale adoption of eCommerce systems. In 2001, a two year project was initiated to study the present influence of Internet on social, educational and business systems within the Kingdom. One of the major aspects was the analysis of user responses collected over the two-year period through a number of surveys, which were designed based on two prominent behavioural models: Theory of Planned Behaviour and Roger’s Theory of Diffusion of Innovations. The consequent analysis of the results was supported and in some cases verified with linear regression models. This paper reports on the consequent findings, which identify factors that may significantly affect the adoption of eCommerce in the Kingdom.
Learning driving styles for autonomous vehicles from demonstration

It is expected that autonomous vehicles capable of driving without human supervision will be released to market within the next decade. For user acceptance, such vehicles should not only be safe and reliable, they should also provide a comfortable user experience. However, individual perception of comfort may vary considerably among users. Whereas some users might prefer sporty driving with high accelerations, others might prefer a more relaxed style. Typically, a large number of parameters such as acceleration profiles, distances to other cars, speed during lane changes, etc., characterize a human driver's style. Manual tuning of these parameters may be a tedious and error-prone task. Therefore, we propose a learning from demonstration approach that allows the user to simply demonstrate the desired style by driving the car manually. We model the individual style in terms of a cost function and use feature-based inverse reinforcement learning to find the model parameters that fit the observed style best. Once the model has been learned, it can be used to efficiently compute trajectories for the vehicle in autonomous mode. We show that our approach is capable of learning cost functions and reproducing different driving styles using data from real drivers.
Visually Debugging Restricted Boltzmann Machine Training with a 3D Example

Restricted Boltzmann Machines (RBMs) are being applied to a growing number of problems with great success. In the process of training an RBM one must pick a number of parameters, but often these parameters are brittle and produce poor performance when slightly off. Here we describe several useful visualizations to assist in choosing appropriate values for these parameters. We also demonstrate a successful application of an RBM to a unique domain: learning a representation of synthetic 3D shapes.
DeepStory: Video Story QA by Deep Embedded Memory Networks

Question-answering (QA) on video contents is a significant challenge for achieving human-level intelligence as it involves both vision and language in real-world settings. Here we demonstrate the possibility of an AI agent performing video story QA by learning from a large amount of cartoon videos. We develop a video-story learning model, i.e. Deep Embedded Memory Networks (DEMN), to reconstruct stories from a joint scene-dialogue video stream using a latent embedding space of observed data. The video stories are stored in a long-term memory component. For a given question, an LSTM-based attention model uses the long-term memory to recall the best question-story-answer triplet by focusing on specific words containing key information. We trained the DEMN on a novel QA dataset of children’s cartoon video series, Pororo. The dataset contains 16,066 scene-dialogue pairs of 20.5-hour videos, 27,328 fine-grained sentences for scene description, and 8,913 story-related QA pairs. Our experimental results show that the DEMN outperforms other QA models. This is mainly due to 1) the reconstruction of video stories in a scene-dialogue combined form that utilize the latent embedding and 2) attention. DEMN also achieved state-of-the-art results on the MovieQA benchmark.
A Joint Speaker-Listener-Reinforcer Model for Referring Expressions

Referring expressions are natural language constructions used to identify particular objects within a scene. In this paper, we propose a unified framework for the tasks of referring expression comprehension and generation. Our model is composed of three modules: speaker, listener, and reinforcer. The speaker generates referring expressions, the listener comprehends referring expressions, and the reinforcer introduces a reward function to guide sampling of more discriminative expressions. The listener-speaker modules are trained jointly in an end-to-end learning framework, allowing the modules to be aware of one another during learning while also benefiting from the discriminative reinforcer&#x2019;s feedback. We demonstrate that this unified framework and training achieves state-of-the-art results for both comprehension and generation on three referring expression datasets.
Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness.

Qualitative content analysis as described in published literature shows conflicting opinions and unsolved issues regarding meaning and use of concepts, procedures and interpretation. This paper provides an overview of important concepts (manifest and latent content, unit of analysis, meaning unit, condensation, abstraction, content area, code, category and theme) related to qualitative content analysis; illustrates the use of concepts related to the research procedure; and proposes measures to achieve trustworthiness (credibility, dependability and transferability) throughout the steps of the research procedure. Interpretation in qualitative content analysis is discussed in light of Watzlawick et al.'s [Pragmatics of Human Communication. A Study of Interactional Patterns, Pathologies and Paradoxes. W.W. Norton & Company, New York, London] theory of communication.
Smooth spline surfaces over irregular meshes

An algorithm for creating smooth spline surfaces over irregular meshes is presented. The algorithm is a generalization of quadratic B-splines; that is, if a mesh is (locally) regular, the resulting surface is equivalent to a B-spline. Otherwise, the resulting surface has a degree 3 or 4 parametric polynomial representation. A construction is given for representing the surface as a collection of tangent plane continuous triangular Be´zier patches. The algorithm is simple, efficient, and generates aesthetically pleasing shapes.
Security of Electronic Payment Systems: A Comprehensive Survey

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Security of Electronic Payment Systems: A Comprehensive Survey Siamak Solat
Scream and gunshot detection in noisy environments

This paper describes an audio event detection system which automatically classifies an audio event as ambient noise, scream or gunshot. The classification system uses two parallel GMM classifiers for discriminating screams from noise and gunshots from noise. Each classifier is trained using different features, appropriately chosen from a set of 47 audio features, which are selected according to a 2-step process. First, feature subsets of increasing size are assembled using filter selection heuristics. Then, a classifier is trained and tested with each feature subset. The obtained classification performance is used to determine the optimal feature vector dimension. This allows a noticeable speed-up w.r.t. wrapper feature selection methods. In order to validate the proposed detection algorithm, we carried out extensive experiments on a rich set of gunshots and screams mixed with ambient noise at different SNRs. Our results demonstrate that the system is able to guarantee a precision of 90% at a false rejection rate of 8%.
Exact Algorithms for NP-Hard Problems: A Survey

We discuss fast exponential time solutions for NP-complete problems. We survey known results and approaches, we provide pointers to the literature, and we discuss several open problems in this area. The list of discussed NP-complete problems includes the travelling salesman problem, scheduling under precedence constraints, satisfiability, knapsack, graph coloring, independent sets in graphs, bandwidth of a graph, and many more.
FingerFlux: near-surface haptic feedback on tabletops

We introduce FingerFlux, an output technique to generate near-surface haptic feedback on interactive tabletops. Our system combines electromagnetic actuation with permanent magnets attached to the user's hand. FingerFlux lets users feel the interface before touching, and can create both attracting and repelling forces. This enables applications such as reducing drifting, adding physical constraints to virtual controls, and guiding the user without visual output. We show that users can feel vibration patterns up to 35 mm above our table, and that FingerFlux can significantly reduce drifting when operating on-screen buttons without looking.
Location-Based Services : Technical and Business Issues

Geographical Information System (GIS) and Global Positioning System (GPS) technologies are expanding their traditional applications to embrace a stream of consumer-focused, location-based applications. Through an integration with handheld devices capable of wireless communication and mobile computing, a wide range of what might be generically referred to as "Location-Based Services" (LBS) may be offered to mobile users. A location-based service is able to provide targetted spatial information to mobile workers and consumers. These include utility location information, personal or asset tracking, concierge and routeguidance information, to name just a few of the possible LBS. The technologies and applications of LBS will play an ever increasingly important role in the modern, mobile, always-connected society. This paper endeavours to provide some background to the technology underlying location-based services and to discuss some issues related to developing and launching LBS. These include whether wireless mobile technologies are ready to support LBS, which mobile positioning technologies can be used and what are their shortcomings, and how GIS developers manipulate spatial information to generate appropriate map images on mobile devices (such as cell phones and PDAs). In addition the authors discuss such issues as interoperability, privacy protection and the market demand for LBS.