nils-herrmann/clean_scirepeval huggingface dataset:
Automatic reconstruction of personalized avatars from 3D face scans

We present a simple algorithm for computing a high-quality personalized avatar from a single color image and the corresponding depth map which have been captured by Microsoft’s Kinect sensor. Due to the low market price of our hardware setup, 3D face scanning becomes feasible for home use. The proposed algorithm combines the advantages of robust non-rigid registration and fitting of a morphable face model. We obtain a high-quality reconstruction of the facial geometry and texture along with one-to-one correspondences with our generic face model. This representation allows for a wide range of further applications such as facial animation or manipulation. Our algorithm has proven to be very robust. Since it does not require any user interaction, even non-expert users can easily create their own personalized avatars.
Scene Text Recognition using Higher Order Language Priors

The problem of recognizing text in images taken in the wild ha s g ined significant attention from the computer vision community in recent years. The scene text recognition task is more challenging compare d to the traditional problem of recognizing text in printed documents. We focus on this problem, and recognize text extracted from natural sce ne images and the web. Significant attempts have been made to address this p roblem in the recent past, for example [1, 2]. However, many of these wo rks benefit from the availability of strong context, which naturall y imits their applicability. In this work, we present a framework to overc ome these restrictions. Our model introduces a higher order prior com puted from an English dictionary to recognize a word, which may or may not b e a part of the dictionary. We present experimental analysis on stan dard as well as new benchmark datasets. The main contributions of this work are: (1) We present a fram ework, which incorporates higher order statistical language mode ls to recognize words in an unconstrained manner, i.e. we overcome the need for restricted word lists. (2) We achieve significant improvement (more than 20%) in word recognition accuracies in a general setting. (3 ) We introduce a large word recognition dataset (atleast 5 times large r than other public datasets) with character level annotation and bench mark it.
Peripheral detection as a workload measure in driving : Effects of traffic complexity and route guidance system use in a driving study

Recent studies have explored a promising method to measure driver workload—the Peripheral Detection Task (PDT). The PDT has been suggested as a standard method to assess safety-relevant workload from the use of in-vehicle information systems (IVIS) while driving. This paper reports the German part of a Swedish-German cooperative study in which the PDT was investigated focusing on its specific sensitivity compared with alternative workload measures. Forty-nine professional drivers performed the PDT while following route guidance system instructions on an inner-city route. The route consisted of both highly demanding and less demanding sections. Two route guidance systems that differed mainly in display size and display organization were compared. Subjective workload ratings (NASA-TLX) as well as physiological measures (heart rate and heart rate variability) were collected as reference data. The PDT showed sensitivity to route demands. Despite their differing displays, both route guidance systems affected PDT performance similarly in intervals of several minutes. However, the PDT proved sensitive to peaks in workload from IVIS use and from the driving task. Peaks in workload were studied by video analyses of four selected subsections on the route. Subjective workload ratings reflected overall route demands and also did not indicate differing effects of the two displays. The physiological measures were less sensitive to workload and indicated emotional strain as well. An assessment of the PDT as a method for the measurement of safety-related workload is given.  University of Freiburg, Center for Cognitive Science, Institute of Computer Science and Social Research, Friedrichstrasse 50, D-79098 Freiburg, Germany. Tel.: +49 761 203 4966; fax: +49 761 203 4938. E-mail address: georg.jahn@cognition.uni-freiburg.de (G. Jahn). 256 G. Jahn et al. / Transportation Research Part F 8 (2005) 255–275
Digital Smile Design: A Tool for Treatment Planning and Communication in Esthetic Dentistry

QDT 2012 To obtain consistent esthetic outcomes, the design of dental restorations should be defined as soon as possible. The importance of gathering diagnostic data from questionnaires and checklists1–7 cannot be overlooked; however, much of this information may be lost if it is not transferred adequately to the design of the restorations. The diagnostic data must guide the subsequent treatment phases,8 integrating all of the patient’s needs, desires, and functional and biologic issues into an esthetic treatment design.9,10 The Digital Smile Design (DSD) is a multi-use conceptual tool that can strengthen diagnostic vision, improve communication, and enhance predictability throughout treatment. The DSD allows for careful analysis of the patient’s facial and dental characteristics along with any critical factors that may have been overlooked during clinical, photographic, or diagnostic cast–based evaluation procedures. The drawing of reference lines and shapes over extraand intraoral digital photographs in a predetermined sequence can widen diagnostic visualization and help the restorative team evaluate the limitations and risk factors of a given case, including asymmetries, disharmonies, and violations of esthetic  DSD sketches can be performed in presentation software such as Keynote (iWork, Apple, Cupertino, California, USA) or Microsoft PowerPoint (Microsoft Office, Microsoft, Redmond, Washington, USA). This improved visualization makes it easier to select the ideal restorative technique. The DSD protocol is characterized by effective communication between the interdisciplinary dental team, including the dental technician. Team members can identify and highlight discrepancies in soft or hard tissue morphology and discuss the best available solutions using the amplified images. Every team member can add information directly on the slides in writing or using voice-over, thus simplifying the process even more. All team members can access this information whenever necessary to review, alter, or add elements during the diagnostic and treatment phases.  A Tool for Treatment Planning and Communication in Esthetic Dentistry
A Novel Compact Balanced-to-Unbalanced Low-Temperature Co-Fired Ceramic Bandpass Filter With Three Coupled Lines Configuration

This paper proposes a novel compact balanced-to-unbalanced bandpass filter. Firstly, a pre-design circuit is presented, which is composed of an inductive coupled-line bandpass filter and an out-of-phase capacitive coupled-line bandpass filter. A novel compact circuit with three coupled lines configuration, derived from the pre-design circuit, is then proposed for miniaturizing the balanced-to-unbalanced bandpass filter. A 2.4-GHz multilayer ceramic chip type balanced-to-unbalanced bandpass filter with a size of 2.0 mm times 1.2 mm times 0.7 mm is developed to validate the feasibility of the proposed structure. The filter is designed by using circuit simulation, as well as full-wave electromagnetic simulation softwares, and fabricated by the use of low-temperature co-fired ceramic technology. The measured results agree quite well with the simulated. According to the measurement results, the maximum insertion loss is 1.65 dB, the maximum in-band phase imbalance is within 3deg, and the maximum in-band magnitude imbalance is less than 0.32 dB.
Abstractions for model checking SDN controllers

Software defined networks (SDNs) are receiving significant attention in the computer networking community, with increasing adoption by the industry. The key feature of SDNs is a centralized controller which programs the packet forwarding behavior of a distributed underlying network. This centralized view of control-which is absent in traditional networks-opens up opportunities for full formal verification. While there is recent research in formal verification of these networks, model checking the controller behavior as it updates the underlying network has only seen limited application. Existing approaches are limited to verifying the controller for a small number of exchanged packets in the network. In this case study, we extend the state of the art by presenting abstractions for model checking controllers for an arbitrarily large number of packets exchanged in the network. We validate the utility of these abstractions through two applications: a learning switch and a stateful firewall.
Document Retrieval Model Through Semantic Linking

This paper addresses the task of document retrieval based on the degree of document relatedness to the meanings of a query by presenting a semantic-enabled language model. Our model relies on the use of semantic linking systems for forming a graph representation of documents and queries, where nodes represent concepts extracted from documents and edges represent semantic relatedness between concepts. Based on this graph, our model adopts a probabilistic reasoning model for calculating the conditional probability of a query concept given values assigned to document concepts. We present an integration framework for interpolating other retrieval systems with the presented model in this paper. Our empirical experiments on a number of TREC collections show that the semantic retrieval has a synergetic impact on the results obtained through state of the art keyword-based approaches, and the consideration of semantic information obtained from entity linking on queries and documents can complement and enhance the performance of other retrieval models.
Quality of Service (QoS)-Guaranteed Network Resource Allocation via Software Defined Networking (SDN)

Quality of Service (QoS) -- based bandwidth allocation plays a key role in real-time computing systems and applications such as voice IP, teleconferencing, and gaming. Likewise, customer services often need to be distinguished according to their service priorities and requirements. In this paper, we consider bandwidth allocation in the networks of a cloud carrier in which cloud users' requests are processed and transferred by a cloud provider subject to QoS requirements. We present a QoS-guaranteed approach for bandwidth allocation that satisfies QoS requirements for all priority cloud users by using Open vSwitch, based on software defined networking (SDN). We implement and test the proposed approach on the Global Environment for Networking Innovations (GENI). Experimental results show the effectiveness of the proposed approach.
Broadband composite right/left-handed coplanar waveguide power splitters with arbitrary phase responses and balun and antenna applications

This study presents novel coplanar waveguide (CPW) power splitters comprising a CPW T-junction with outputs attached to phase-adjusting circuits, i.e., the composite right/left-handed (CRLH) CPW and the conventional CPW, to achieve a constant phase difference with arbitrary value over a wide bandwidth. To demonstrate the proposed technique, a 180/spl deg/ CRLH CPW power splitter with a phase error of less than 10/spl deg/ and a magnitude difference of below 1.5 dB within 2.4 to 5.22 GHz is experimentally demonstrated. Compared with the conventional 180/spl deg/ delay-line power splitter, the proposed structure possesses not only superior phase and magnitude performances but also a 37% size reduction. The equivalent circuit of the CRLH CPW, which represents the left-handed (LH), right-handed (RH), and lossy characteristics, is constructed and the results obtained are in good agreement with the full-wave simulation and measurement. Applications involving the wideband coplanar waveguide-to-coplanar stripline (CPW-to-CPS) transition and the tapered loop antenna are presented to stress the practicality of the 180/spl deg/ CRLH CPW power splitter. The 3-dB insertion loss bandwidth is measured as 98% for the case of a back-to-back CPW-to-CPS transition. The tapered loop antenna fed by the proposed transition achieves a measured 10-dB return loss bandwidth of 114%, and shows similar radiation patterns and 6-9 dBi antenna gain in its operating band.
Distributed multiuser power control for digital subscriber lines

This paper considers the multiuser power control problem in a frequency-selective interference channel. The interference channel is modeled as a noncooperative game, and the existence and uniqueness of a Nash equilibrium are established for a two-player version of the game. An iterative water-filling algorithm is proposed to efficiently reach the Nash equilibrium. The iterative water-filling algorithm can be implemented distributively without the need for centralized control. It implicitly takes into account the loop transfer functions and cross couplings, and it reaches a competitively optimal power allocation by offering an opportunity for loops to negotiate the best use of power and frequency with each other. When applied to the upstream power backoff problem in very-high bit-rate digital subscriber lines and the downstream spectral compatibility problem in asymmetric digital subscriber lines, the new power control algorithm is found to give a significant performance improvement when compared with existing methods.
Focus based Feature Extraction for Pallets Recognition

Visual recognition for object grasping is a well-known challenge for robot automation in industrial applications. A typical example is pallet recognition in industrial environment for pick-and-place automated process. The aim of vision and reasoning algorithms is to help robots in choosing the best pallets holes location. This work proposes an application-based approach, which ful l all requirements, dealing with every kind of occlusions and light situations possible. Even some meaning noise (or meaning misunderstanding) is considered. A pallet model, with limited degrees of freedom, is described and, starting from it, a complete approach to pallet recognition is outlined. In the model we de ne both virtual and real corners, that are geometrical object proprieties computed by different image analysis operators. Real corners are perceived by processing brightness information directly from the image, while virtual corners are inferred at a higher level of abstraction. A nal reasoning stage selects the best solution tting the model. Experimental results and performance are reported in order to demonstrate the suitability of the proposed approach.
An open-source navigation system for micro aerial vehicles

This paper presents an open-source indoor navigation system for quadrotor micro aerial vehicles(MAVs), implemented in the ROS framework. The system requires a minimal set of sensors including a planar laser range-finder and an inertial measurement unit. We address the issues of autonomous control, state estimation, path-planning, and teleoperation, and provide interfaces that allow the system to seamlessly integrate with existing ROS navigation tools for 2D SLAM and 3D mapping. All components run in real time onboard the MAV, with state estimation and control operating at 1 kHz. A major focus in our work is modularity and abstraction, allowing the system to be both flexible and hardware-independent. All the software and hardware components which we have developed, as well as documentation and test data, are available online.
Sigma*: symbolic learning of input-output specifications

We present Sigma*, a novel technique for learning symbolic models of software behavior.  addresses the challenge of synthesizing models of software by using symbolic conjectures and abstraction. By combining dynamic symbolic execution to discover symbolic input-output steps of the programs and counterexample guided abstraction refinement to over-approximate program behavior, Sigma* transforms arbitrary source representation of programs into faithful input-output models. We define a class of stream filters---programs that process streams of data items---for which Sigma* converges to a complete model if abstraction refinement eventually builds up a sufficiently strong abstraction. In other words, Sigma* is complete relative to abstraction. To represent inferred symbolic models, we use a variant of symbolic transducers that can be effectively composed and equivalence checked. Thus, Sigma* enables fully automatic analysis of behavioral properties such as commutativity, reversibility and idempotence, which is useful for web sanitizer verification and stream programs compiler optimizations, as we show experimentally. We also show how models inferred by Sigma* can boost performance of stream programs by parallelized code generation.
Ensemble Learning for Multi-Source Neural Machine Translation

In this paper we describe and evaluate methods to perform ensemble prediction in neural machine translation (NMT). We compare two methods of ensemble set induction: sampling parameter initializations for an NMT system, which is a relatively established method in NMT (Sutskever et al., 2014), and NMT systems translating from different source languages into the same target language, i.e., multi-source ensembles, a method recently introduced by Firat et al. (2016). We are motivated by the observation that for different language pairs systems make different types of mistakes. We propose several methods with different degrees of parameterization to combine individual predictions of NMT systems so that they mutually compensate for each other’s mistakes and improve overall performance. We find that the biggest improvements can be obtained from a context-dependent weighting scheme for multi-source ensembles. This result offers stronger support for the linguistic motivation of using multi-source ensembles than previous approaches. Evaluation is carried out for German and French into English translation. The best multi-source ensemble method achieves an improvement of up to 2.2 BLEU points over the strongest singlesource ensemble baseline, and a 2 BLEU improvement over a multi-source ensemble baseline.
{AUC} maximizing support vector learning

The area under the ROC curve (AUC) is a natural performance measure when the goal is to find a discriminative decision function. We present a rigorous derivation of an AUC maximizing Support Vector Machine; its optimization criterion is composed of a convex bound on the AUC and a margin term. The number of constraints in the optimization problem grows quadratically in the number of examples. We discuss an approximation for large data sets that clusters the constraints. Our experiments show that the AUC maximizing Support Vector Machine does in fact lead to higher AUC values.
Antecedents of Turnover Intentions : A Literature Review

Employees are the most important asset of the organization. It’s a major challenge for the organization to retain its workforce as a lot of cost is incurred on them directly or indirectly. In order to have competitive advantage over the other organizations, the focus has to be on the employees. As ultimately the employees are the face of the organization as they are the building blocks of the organization. Thus their retention is a major area of concern. So attempt has been made to reduce the turnover rate of the organization. Therefore this paper attempts to review the various antecedents of turnover which affect turnover intentions of the employees.
Location based services using android (LBSOID)

Initially mobile phones were developed only for voice communication but now days the scenario has changed, voice communication is just one aspect of a mobile phone. There are other aspects which are major focus of interest. Two such major factors are web browser and GPS services. Both of these functionalities are already implemented but are only in the hands of manufacturers not in the hands of users because of proprietary issues, the system does not allow the user to access the mobile hardware directly. But now, after the release of android based open source mobile phone a user can access the hardware directly and design customized native applications to develop Web and GPS enabled services and can program the other hardware components like camera etc. In this paper we will discuss the facilities available in android platform for implementing LBS services (geo-services).
Accelerating Machine Learning Kernel in Hadoop Using FPGAs

Big data applications share inherent characteristics that are fundamentally different from traditional desktop CPU, parallel and web service applications. They rely on deep machine learning and data mining applications. A recent trend for big data analytics is to provide heterogeneous architectures to allow support for hardware specialization to construct the right processing engine for analytics applications. However, these specialized heterogeneous architectures require extensive exploration of design aspects to find the optimal architecture in terms of performance and cost. % Considering the time dedicated to create such specialized architectures, a model that estimates the potential speedup achievable through offloading various parts of the algorithm to specialized hardware would be necessary. This paper analyzes how offloading computational intensive kernels of machine learning algorithms to a heterogeneous CPU+FPGA platform enhances the performance. We use the latest Xilinx Signboards for implementation and result analysis. Furthermore, we perform a comprehensive analysis of communication and computation overheads such as data I/O movements, and calling several standard libraries that can not be offloaded to the accelerator to understand how the speedup of each application will contribute to its overall execution in an end-to-end Hadoop MapReduce environment.
Designing multi-user MIMO for energy efficiency: When is massive MIMO the answer?

Assume that a multi-user multiple-input multiple-output (MIMO) communication system must be designed to cover a given area with maximal energy efficiency (bits/Joule). What are the optimal values for the number of antennas, active users, and transmit power? By using a new model that describes how these three parameters affect the total energy efficiency of the system, this work provides closed-form expressions for their optimal values and interactions. In sharp contrast to common belief, the transmit power is found to increase (not decrease) with the number of antennas. This implies that energy efficient systems can operate at high signal-to-noise ratio (SNR) regimes in which the use of interference-suppressing precoding schemes is essential. Numerical results show that the maximal energy efficiency is achieved by a massive MIMO setup wherein hundreds of antennas are deployed to serve relatively many users using interference-suppressing regularized zero-forcing precoding.