nils-herrmann/clean_scirepeval huggingface dataset:
Ontologies, Disorders and Prototypes

As it emerged from philosophical analyses and cognitive research, most concepts exhibit typicality effects, and resist to the efforts of defining them in terms of necessary and sufficient conditions. This holds also in the case of many medical concepts. This is a problem for the design of computer science ontologies, since knowledge representation formalisms commonly adopted in this field (such as, in the first place, the Web Ontology Language OWL) do not allow for the representation of concepts in terms of typical traits. The need of representing concepts in terms of typical traits concerns almost every domain of real world knowledge, including medical domains. In particular, in this article we take into account the domain of mental disorders, starting from the DSM-5 descriptions of some specific disorders. We favour a hybrid approach to concept representation, in which ontology oriented formalisms are combined to a geometric representation of knowledge based on conceptual space. As a preliminary step to apply our proposal to mental disorder concepts, we started to develop an OWL ontology of the schizophrenia spectrum, which is as close as possible to the DSM-5 descriptions.
The dysphagia disorder survey: validation of an assessment for swallowing and feeding function in developmental disability.

Swallowing and feeding disorder (dysphagia) have high incidence and prevalence in children and adults with developmental disability. Standardized screening and clinical assessments are needed to identify and describe the disorder. The aim of this study was to describe the psychometric properties of the Dysphagia Disorder Survey (DDS), a screening and clinical assessment of swallowing and feeding function for eating and drinking developed specifically for this population. The statistical analysis was performed on a sample of 654 individuals (age range 8-82) with intellectual and developmental disability living in two residential settings in the United States that served somewhat different populations. The two samples had similar factor structures. Internal consistency of the DDS and subscales was confirmed using Chronbach's coefficient alpha. The DDS demonstrated convergent validity when compared to judgments of swallowing and feeding disorder severity made by clinical swallowing specialists. Discriminative validity for severity of disorder was tested by comparing the two samples. The results of the study suggest that the DDS is a reliable and valid test for identifying and describing swallowing and feeding disorder in children and adults with developmental disability.
Exploring Web Customers' Trust Formation in Infomediaries

Infomediaries are information intermediaries in the Internet that play an important part in reducing online customers’ search costs for finding the most suitable vendors and products. This research explores the process of Web customers’ trust building using infomediaries. Specifically, we identify four sets of trust-related beliefs that impact web customers’ trust attitude and intended behavior, as well as the antecedents of trust-related beliefs. This conceptualization is built on a number of theories, mainly theories of trust, reasoned action, and actor-network. Our empirical results in testing the model indicate that web customers’ trust attitude toward web infomediaries is formed based on their beliefs regarding risk, content quality, system quality, and trustbuilding beliefs. We also found that initial trust is the antecedent of trust-forming beliefs, whereas individuals’ propensity to trust influences their calculative risk beliefs. The implications of these findings are also discussed.
Preparing for success: readiness models for rural telehealth.

Readiness is an integral and preliminary step in the successful implementation of telehealth services into existing health systems within rural communities.



This paper details and critiques published international peer-reviewed studies that have focused on assessing telehealth readiness for rural and remote health. Background specific to readiness and change theories is provided, followed by a critique of identified telehealth readiness models, including a commentary on their readiness assessment tools.



Four current readiness models resulted from the search process. The four models varied across settings, such as rural outpatient practices, hospice programs, rural communities, as well as government agencies, national associations, and organizations. All models provided frameworks for readiness tools. Two specifically provided a mechanism by which communities could be categorized by their level of telehealth readiness.



Common themes across models included: an appreciation of practice context, strong leadership, and a perceived need to improve practice. Broad dissemination of these telehealth readiness models and tools is necessary to promote awareness and assessment of readiness. This will significantly aid organizations to facilitate the implementation of telehealth.
Collaborative Multi-Robot Exploration

In this paper we consider the problem of exploring an unknown environment by a team of robots. As in single-robot exploration the goal is to minimize the overall exploration time. The key problem to be solved therefore is to choose appropriate target points for the individual robots so that they simultaneously explore different regions of their environment. We present a probabilistic approach for the coordination of multiple robots which, in contrast to previous approaches, simultaneously takes into account the costs of reaching a target point and the utility of target points. The utility of target points is given by the size of the unexplored area that a robot can cover with its sensors upon reaching a target position. Whenever a target point is assigned to a specific robot, the utility of the unexplored area visible from this target position is reduced for the other robots. This way, a team of multiple robots assigns different target points to the individual robots. The technique has been implemented and tested extensively in real-world experiments and simulation runs. The results given in this paper demonstrate that our coordination technique significantly reduces the exploration time compared to previous approaches.
Energy and Exergy Based Optimization of Licl-Water Absorption Cooling System

This study presents thermodynamic analysis and optimization of single effect LiCl-H2O absorption cooling system. Thermodynamic models are employed in engineering equation solver to compute the optimum performance parameters. In this study, cut off temperature to operate system has been obtained at various operating temperatures. Analysis depicts that on 3.59 % rise in evaporator temperature, the required cut-off temperature decreased by 12.51%. By realistic comparison between thermodynamic first and second law analysis, optimum generator temperature relative to energy and exergy based prospective has been evaluated. It is found that optimum generator temperature is strong function of evaporator and condenser temperature. Thus, it is feasible to find out optimum generator temperature for various combinations of evaporator and condenser temperatures. Contour plots of optimum generator temperature for several combinations of condenser and absorber temperatures have been also depicted.
Modeling and Simulation of Big Deformations of Thin walled Plate in End Milling Process

With the development of the modern aircraft, the large-scale thin walled parts have been used in aeronautics and astronautics. In NC milling process, the thin walled plates are very easy to deform which will influence the accuracy and quality. From the point of view of theoretically and numerical calculation, the paper proposes a new analytical deformation model suitable for static machining error prediction of low- rigidity components. The part deformation is predicted using a theoretical big deformation equations model, which is established on the basis of the equations of Von Karman when the linear load acts on thin-wall plates. The part big deformation is simulated using FE analysis. The simulating results shown that the diverse cutting forces, milling location and thickness of the plate may lead to various deformation results.
Jensen-Shannon divergence and Hilbert space embedding

This paper describes the Jensen-Shannon divergence (JSD) and Hilbert space embedding. With natural definitions making these considerations precise, one finds that the general Jensen-Shannon divergence related to the mixture is the minimum redundancy, which can be achieved by the observer. The set of distributions with the metric /spl radic/JSD can even be embedded isometrically into Hilbert space and the embedding can be identified.
Techniques for Solving Sudoku Puzzles

Solving Sudoku puzzles is one of the most popular pastimes in the world. Puzzles range in difficulty from easy to very challenging; the hardest puzzles tend to have the most empty cells. The current paper compares the performance of three computer algorithms in solving puzzles. Backtracking, simulated annealing, and alternating projections are generic methods for attacking combinatorial optimization problems. Our results favor backtracking. It infallibly solves Sudoku puzzles or deduces that a unique solution does not exist. However, backtracking does not scale well in high-dimensional combinatorial optimization. Hence, it is useful to expose statistics students to the other two solution techniques in a concrete setting. Simulated annealing shares a common structure with MCMC (Markov chain Monte Carlo) and enjoys wide applicability. The method of alternating projections solves the feasibility problem in convex programming. Converting a discrete optimization problem into a continuous optimization problem opens up the possibility of handling combinatorial problems of much higher dimensionality.
Towards New Human-Humanoid Communication: Listening During Speaking by Using Ultrasonic Directional Speaker

This paper presents a new human-humanoid communication system by using a directional speaker. The directional speaker produces directional sound beams by using intermodulation of ultrasonic sound beams and non linearity in air. This technology solves problems and brings new ways of human-humanoid communication as follows: 1) A humanoid can recognize human speeches during speaking because a microphone installed in the humanoid does not capture self voices played by the directional speaker. 2) A humanoid can speak to a specific person as if it whispers. The directional speaker is installed at the position of the mouth of the humanoid. Preliminary experiments show the efficiency of the directional speaker to realize the above two functions.
Research on three-layer collaborative filtering recommendation for Online Judge

Online Judge is widespread for the undergraduate to study programming. The users usually feel confused while locating the problems they prefer from the massive ones. This paper proposes a specialized recommendation model for the online judge systems in order to present the alternative problems to the users which they may be interested in potentially. In this model, a three-level collaborative filtering recommendation method is referred to and redesigned catering for the specific interaction mode of Online Judge. This method is described in detail in this paper and implemented in our demo system which demonstrates its availability.
Logical and algebraic view of Huzita's origami axioms with applications to computational origami

We describe Huzita's origami axioms from the logical and algebraic points of view. Observing that Huzita's axioms are statements about the existence of certain origami constructions, we can generate basic origami constructions from those axioms. Origami construction is performed by repeated application of Huzita's axioms. We give the logical specification of Huzita's axioms as constraints among geometric objects of origami in the language of the first-order predicate logic. The logical specification is then translated into logical combinations of algebraic forms, i.e. polynomial equalities, disequalities and inequalities, and further into polynomial ideals (if inequalities are not involved). By constraint solving, we obtain solutions that satisfy the logical specification of the origami construction problem. The solutions include fold lines along which origami paper has to be folded. The obtained solutions both in numeric and symbolic forms make origami computationally tractable for further treatments, such as visualization and automated theorem proving of the correctness of the origami construction.
Hydro Muscle -a novel soft fluidic actuator

Muscles are linear actuators resembling ordinary biological muscles in terms of active dynamic output, passive material properties and appearance. The passive and dynamic characteristics of the latex based Hydro Muscle are addressed. The control tests of modular muscles are presented together with a muscle model relating sensed quantities with net force.  Muscles are discussed in the context of conventional actuators. The hypothesis that Hydro Muscles have greater efficiency than McKibben Muscles is experimentally verified. Hydro Muscle peak efficiency with (without) back flow consideration was 88% (27%). Possible uses of Hydro Muscles are illustrated by relevant robotics projects at WPI. It is proposed that Hydro Muscles can also be an excellent educational tool for moderate-budget robotics classrooms and labs; the muscles are inexpensive (in the order of standard latex tubes of comparable size), made of off-the-shelf elements in less than 10 minutes, easily customizable, lightweight, biologically inspired, efficient, compliant soft linear actuators that are adept for power-augmentation. Moreover, a single source can actuate many muscles by utilizing control of flow and/or pressure. Still further, these muscles can utilize ordinary tap water and successfully operate within a safe range of pressures not overly exceeding standard water household pressure of about 0.59 MPa (85 psi).
Learning Spatially Localized, Parts-Based Representation

In this paper, we propose a novel method, called local nonnegative matrix factorization (LNMF), for learning spatially localized, parts-based subspace representation of visual patterns. An objective function is defined to impose localization constraint, in addition to the non-negativity constraint in the standard NMF . This gives a set of bases which not only allows a non-subtractive (part-based) representation of images but also manifests localized features. An algorithm is presented for the learning of such basis components. Experimental results are presented to compare LNMF with the NMF and PCA methods for face representation and recognition, which demonstrates advantages of LNMF.
Block Compressed Sensing of Natural Images

Compressed sensing (CS) is a new technique for simultaneous data sampling and compression. In this paper, we propose and study block compressed sensing for natural images, where image acquisition is conducted in a block-by-block manner through the same operator. While simpler and more efficient than other CS techniques, the proposed scheme can sufficiently capture the complicated geometric structures of natural images. Our image reconstruction algorithm involves both linear and nonlinear operations such as Wiener filtering, projection onto the convex set and hard thresholding in the transform domain. Several numerical experiments demonstrate that the proposed block CS compares favorably with existing schemes at a much lower implementation cost.
Let's Dance: Learning From Online Dance Videos

In recent years, deep neural network approaches have naturally extended to the video domain, in their simplest case by aggregating per-frame classifications as a baseline for action recognition. A majority of the work in this area extends from the imaging domain, leading to visual-feature heavy approaches on temporal data. To address this issue we introduce “Let’s Dance”, a 1000 video dataset (and growing) comprised of 10 visually overlapping dance categories that require motion for their classification. We stress the important of human motion as a key distinguisher in our work given that, as we show in this work, visual information is not sufficient to classify motion-heavy categories. We compare our datasets’ performance using imaging techniques with UCF-101 and demonstrate this inherent difficulty. We present a comparison of numerous state-of-theart techniques on our dataset using three different representations (video, optical flow and multi-person pose data) in order to analyze these approaches. We discuss the motion parameterization of each of them and their value in learning to categorize online dance videos. Lastly, we release this dataset (and its three representations) for the research community to use.
Acoustic shooter localization with a minimal number of single-channel wireless sensor nodes

Acoustic shooter localization systems are being rapidly deployed in the field. However, these are standalone systems---either wearable or vehicle-mounted---that do not have networking capability even though the advantages of widely distributed sensing for locating shooters have been demonstrated before. The reason for this is that certain disadvantages of wireless network-based prototypes made them impractical for the military. The system that utilized stationary single-channel sensors required many sensor nodes, while the multi-channel wearable version needed to track the absolute self-orientation of the nodes continuously, a notoriously hard task. This paper presents an approach that overcomes the shortcomings of past approaches. Specifically, the technique requires as few as five single-channel wireless sensors to provide accurate shooter localization and projectile trajectory estimation. Caliber estimation and weapon classification are also supported. In addition, a single node alone can provide reliable miss distance and range estimates based on a single shot as long as a reasonable assumption holds. The main contribution of the work and the focus of this paper is the novel sensor fusion technique that works well with a limited number of observations. The technique is thoroughly evaluated using an extensive shot library.
Workflow Verification: Finding Control-Flow Errors Using Petri-Net-Based Techniques

Workflow management systems facilitate the everyday operation of business processes by taking care of the logistic control of work. In contrast to traditional information systems, they attempt to support frequent changes of the workflows at hand. Therefore, the need for analysis methods to verify the correctness of workflows is becoming more prominent. In this chapter we present a method based on Petri nets. This analysis method exploits the structure of the Petri net to find potential errors in the design of the workflow. Moreover, the analysis method allows for the compositional verification of workflows.
Two-dimensional spectroscopy of electronic couplings in photosynthesis

Time-resolved optical spectroscopy is widely used to study vibrational and electronic dynamics by monitoring transient changes in excited state populations on a femtosecond timescale. Yet the fundamental cause of electronic and vibrational dynamics—the coupling between the different energy levels involved—is usually inferred only indirectly. Two-dimensional femtosecond infrared spectroscopy based on the heterodyne detection of three-pulse photon echoes has recently allowed the direct mapping of vibrational couplings, yielding transient structural information. Here we extend the approach to the visible range and directly measure electronic couplings in a molecular complex, the Fenna–Matthews–Olson photosynthetic light-harvesting protein. As in all photosynthetic systems, the conversion of light into chemical energy is driven by electronic couplings that ensure the efficient transport of energy from light-capturing antenna pigments to the reaction centre. We monitor this process as a function of time and frequency and show that excitation energy does not simply cascade stepwise down the energy ladder. We find instead distinct energy transport pathways that depend sensitively on the detailed spatial properties of the delocalized excited-state wavefunctions of the whole pigment–protein complex.
Adaptivity Challenges in Games and Simulations: A Survey

In computer games and simulations, content is often rather static and rigid. As a result, its prescripted nature can lead to predictable and impersonal gameplay, while alienating unconventional players. Adaptivity in games has therefore been recently proposed to overcome these shortcomings and make games more challenging and appealing. In this paper, we survey present research on game adaptivity, identifying, and discussing the main challenges, and pointing out some of the most promising directions ahead. We first survey the purposes of adaptivity, as the principles that could steer an adaptation and generation engine. From this perspective, we proceed to thoroughly discuss adaptivity's targets and methods. Current advances and successes in this emerging field point to many yet unexplored research opportunities. Among them, we discuss the use of gameplay expectations, learning preferences, and assessment data in the integrated adaptation of game worlds, scenarios, and quests. We conclude that, among other methods, procedural content generation and semantic modeling can powerfully combine to create offline customized content and online adjustments to game worlds, scenarios, and quests. These and other promising methods, deserving ample research efforts, can therefore, be expected to significantly contribute towards making games and simulations even more unpredictable, effective, and fun.
Breaking DES using a molecular computer

Recently Adleman has shown that a small traveling salesman problem can be solved by molecular operations. In this paper we show how the same principles can be applied to breaking the Data Encryption Standard (DES). We describe in detail a library of operations which are useful when working with a molecular computer. We estimate that given one arbitrary (plain-text, cipher-text) pair, one can recover the DES key in about 4 months of work. Furthermore, we show that under chosen plain-text attack it is possible to recover the DES key in one day using some preprocessing. Our method can be generalized to break any cryptosystem which uses keys of length less than 64 bits.
Application layer protocols in multimedia networks

Today, there's a growing trends to broadcast and stream multimedia files over the internet due to low cost of transmission. Protocols divide transmitted data to packets but problem was, with the limited bandwidth , which leads to the delay of the received image. We propose a framework for data transmission that overcome the limited bandwidth problem. The major feature of the framework is decreasing the amount of details in the image file. This is done by sending the most effective values of the image, so decreasing number of sent packets, thus speeding the transmission procedure from one side, and saving bandwidth from the other side. To achieve our goal, Two compression methods 2-dimensional Discrete Cosine Transform (2DDCT) and 2-dimensional Fast Fourier Transform 2DFFT will be used in the framework . Signal Extrapolation is an important topic in this research as it will be used for concealment of image data corrupted by transmission errors. Encoding and Decoding will be done by (REED-Solomon) method. Then embedding this algorithm to application layer protocols (Http, Sip) .Finally, a comparative study is made between PSNR of the two compression methods and check which of them is suitable for data transmission and under what conditions. It is shown that this approach can successfully achieve a PSNR values, very near to PSNR values with no compression. Besides, have the advantage of sending multimedia files very fast in a good reliable quality and also saving network bandwidth.