nils-herrmann/clean_scirepeval huggingface dataset:
Octree-based decimation of marching cubes surfaces

The marching cubes (MC) algorithm is a method for generating isosurfaces. It also generates an excessively large number of triangles to represent an isosurface; this increases the rendering time. This paper presents a decimation method to reduce the number of triangles generated. Decimation is carried out before creating a large number of triangles. Four major steps comprise the algorithm: surface tracking, merging, crack patching and triangulation. Surface tracking is an enhanced implementation of the MC algorithm. Starting from a seed point, the surface tracker visits only those cells likely to compose part of the desired isosurface. The cells making up the extracted surface are stored in an octree that is further processed. A bottom-up approach is taken in merging the cells containing a relatively flat approximating surface. The finer surface details are maintained. Cells are merged as long as the error due to such an operation is within a user-specified error parameter, or a cell acquires more than one connected surface component in it. A crack patching method is described that forces edges of smaller cells to lie along those of the larger neighboring cells. The overall saving in the number of triangles depends both on the specified error value and the nature of the data. Use of the hierarchical octree data structure also presents the potential of incremental representation of surfaces. We can generate a highly smoothed surface representation which can be progressively refined as the user-specified error value is decreased.
A Novel User Authentication Scheme Based on QR-Code

User authentication is one of the fundamental procedures to ensure secure communications and share system resources over an insecure public network channel. Thus, a simple and efficient authentication mechanism is required for securing the network system in the real environment. In general, the password-based authentication mechanism provides the basic capability to prevent unauthorized access. Especially, the purpose of the one-time password is to make it more difficult to gain unauthorized access to restricted resources. Instead of using the password file as conventional authentication systems, many researchers have devoted to implement various one-time password schemes using smart cards, time-synchronized token or short message service in order to reduce the risk of tampering and maintenance cost. However, these schemes are impractical because of the far from ubiquitous hardware devices or the infrastructure requirements. To remedy these weaknesses, the attraction of the QR-code technique can be introduced into our one-time password authentication protocol. Not the same as before, the proposed scheme based on QR code not only eliminates the usage of the password verification table, but also is a cost effective solution since most internet users already have mobile phones. For this reason, instead of carrying around a separate hardware token for each security domain, the superiority of handiness benefit from the mobile phone makes our approach more practical and convenient.
NLAST: A natural language assistant for students

This paper presents a system that works as an assistant for students in their learning process. The assistant system has two main parts: an Android application and a server platform. The Android application is a chatterbot (i.e., an agent intended to conduct a conversation in natural language with a human being) based on AIML, one of the more successful languages for developing conversational agents. The chatterbot acts as an intermediation agent between a student and the server platform. The server platform contains four repositories and a recommender (which are part of a bigger professor assessment system). The final objective of the assistant system is to make a student able to carry out several actions related to his/her learning and assessment processes, such as: to consult exam questions from a repository, to receive recommendations about learning material, to ask questions about a course, and to check his/her own assessed exams. These actions are carried out through and Android application using a natural language interface (by voice or typing). The purpose of this development is to facilitate the access to this information through a friendly interface.
A survey of combinatorial testing

Combinatorial Testing (CT) can detect failures triggered by interactions of parameters in the Software Under Test (SUT) with a covering array test suite generated by some sampling mechanisms. It has been an active field of research in the last twenty years. This article aims to review previous work on CT, highlights the evolution of CT, and identifies important issues, methods, and applications of CT, with the goal of supporting and directing future practice and research in this area. First, we present the basic concepts and notations of CT. Second, we classify the research on CT into the following categories: modeling for CT, test suite generation, constraints, failure diagnosis, prioritization, metric, evaluation, testing procedure and the application of CT. For each of the categories, we survey the motivation, key issues, solutions, and the current state of research. Then, we review the contribution from different research groups, and present the growing trend of CT research. Finally, we recommend directions for future CT research, including: (1) modeling for CT, (2) improving the existing test suite generation algorithm, (3) improving analysis of testing result, (4) exploring the application of CT to different levels of testing and additional types of systems, (5) conducting more empirical studies to fully understand limitations and strengths of CT, and (6) combining CT with other testing techniques.
MySpace and Facebook: Applying the Uses and Gratifications Theory to Exploring Friend-Networking Sites

The increased use of the Internet as a new tool in communication has changed the way people interact. This fact is even more evident in the recent development and use of friend-networking sites. However, no research has evaluated these sites and their impact on college students. Therefore, the present study was conducted to evaluate: (a) why people use these friend-networking sites, (b) what the characteristics are of the typical college user, and (c) what uses and gratifications are met by using these sites. Results indicated that the vast majority of college students are using these friend-networking sites for a significant portion of their day for reasons such as making new friends and locating old friends. Additionally, both men and women of traditional college age are equally engaging in this form of online communication with this result holding true for nearly all ethnic groups. Finally, results showed that many uses and gratifications are met by users (e.g., "keeping in touch with friends"). Results are discussed in light of the impact that friend-networking sites have on communication and social needs of college students.
Software Development Cost Estimation Using Analogy: A Review

Software project managers require reliable methods for estimating software project costs, and it is especially important at the early stage of software cycle. Analogy for software cost estimation has been considered as a suitable alternative to regression-based estimation method, and empirical studies have shown that it can be used successfully in many circumstances. It is important for project managers to understand the strengths and weaknesses of each useful software cost estimation method, more importantly when to use these methods and at which stage of the software development. This paper provides a comprehensive overview of the background and the underlying theory of analogy for software cost estimation, published in major software engineering journals and conferences over the past 15 years. Investigation on the dataset quality evaluation and its relevance to the target problem for analogy are further discussed, the result allows researchers and project managers to familiarize the underlying nature of the analogy-based approach.
Structure and Overlaps of Ground-Truth Communities in Networks

One of the main organizing principles in real-world networks is that of network communities, where sets of nodes organize into densely linked clusters. Even though detection of such communities is of great interest, understanding the structure communities in large networks remains relatively limited. In particular, due to the unavailability of labeled ground-truth data, it was traditionally very hard to develop accurate models of network community structure.
 Here we use six large social, collaboration, and information networks where nodes explicitly state their ground-truth community memberships. For example, nodes in social networks join into explicitly defined interest based groups, and we use such groups as explicitly labeled ground-truth communities. We use such ground-truth communities to study their structural signatures by analyzing how ground-truth communities emerge in networks and how they overlap. We observe some surprising phenomena. First, ground-truth communities contain high-degree hub nodes that reside in community overlaps and link to most of the members of the community. Second, the overlaps of communities are more densely connected than the non-overlapping parts of communities. We show that this in contrast to the conventional wisdom that community overlaps are more sparsely connected than the non-overlapping parts themselves. We then show that many existing models of network communities do not capture dense community overlaps. This in turn means that most present models and community detection methods confuse overlaps as separate communities. In contrast, we present the community-affiliation graph model (AGM), a conceptual model of network community structure. We demonstrate that AGM reliably captures the overall structure of networks as well as the overlapping and hierarchical nature of network communities.
What Size Test Set Gives Good Error Rate Estimates?

We address the problem of determining what size test set guarantees statistically significant results in a character recognition task, as a function of the expected error rate. We provide a statistical analysis showing that if, for example, the expected character error rate is around 1 percent, then, with a test set of at least 10,000 statistically independent handwritten characters (which could be obtained by taking 100 characters from each of 100 different writers), we guarantee, with 95 percent confidence, that: (1) The expected value of the character error rate is not worse than 1.25 E, where E is the empirical character error rate of the best recognizer, calculated on the test set; and (2) a difference of 0.3 E between the error rates of two recognizers is significant. We developed this framework with character recognition applications in mind, but it applies as well to speech recognition and to other pattern recognition problems. Index Terms —Pattern recognition, test set, test set size, benchmark, hypothesis testing, designed experiment, statistical significance, estimation, guaranteed estimators, recognition error. —————————— ✦ ——————————
Object permanence in young infants: further evidence.

Recent evidence suggests that 4.5- and even 3.5-month-old infants realize that objects continue to exist when hidden. The goal of the present experiments was to obtain converging evidence of object permanence in young infants. Experiments were conducted using paradigms previously used to demonstrate object permanence in 5.5-month-old infants and 6.5-month-old infants. In one experiment, 3.5-month-old infants watched a short or a tall carrot slide along a track. The track's center was hidden by a screen with a large window in its upper half. The short carrot was shorter than the window's lower edge and so did not appear in the window when passing behind the screen; the tall carrot was taller than the window's lower edge and hence should have appeared in the window but did not. The infants looked reliably longer at the tall than at the short carrot event, suggesting that they (a) represented the existence, height, and trajectory of each carrot behind the screen and (b) expected the tall carrot to appear in the screen window and were surprised that it did not. Control trials supported this interpretation. In another experiment, 4.0-month-old infants saw a toy car roll along a track that was partly hidden by a screen. A large toy mouse was placed behind the screen, either on top or in back of the track. The female infants looked reliably longer when the mouse stood on top as opposed to in back of the track, suggesting that they (a) represented the existence and trajectory of the car behind the screen, (b) represented the existence and location of the mouse behind the screen, and (c) were surprised to see the car reappear from behind the screen when the mouse stood in its path. A second experiment supported this interpretation. The results of these experiments provide further evidence that infants aged 3.5 months and older are able to represent and to reason about hidden objects.
Development of the Conformity to Masculine Norms Inventory

This article describes the construction of the Conformity to Masculine Norms Inventory (CMNI), and 5 studies that examined its psychometric properties. Factor analysis indicated 11 distinct factors: Winning, Emotional Control, Risk-Taking, Violence, Dominance, Playboy, SelfReliance, Primacy of Work, Power Over Women, Disdain for Homosexuals, and Pursuit of Status. Results from Studies 2–5 indicated that the CMNI had strong internal consistency estimates and good differential validity comparing men with women and groups of men on healthrelated questions; all of the CMNI subscales were significantly and positively related to other masculinity-related measures, with several subscales being related significantly and positively to psychological distress, social dominance, aggression, and the desire to be more muscular, and significantly and negatively to attitudes toward psychological help seeking and social desirability; and CMNI scores had high test–retest estimates for a 2–3 week period.
Dynamics and control of a 4-dof wearable cable-driven upper arm exoskeleton

In this paper, we present the dynamics, control, and preliminary experiments on a wearable upper arm exoskeleton intended for human users with four degrees-of-freedom (dof), driven by six cables. The control of this cable-driven exoskeleton is complicated because the cables can transmit forces to the arm only under tension. The standard PD controllers or Computed torque controllers perform only moderately since the cables need to be in tension. Future efforts will seek to refine these control strategies and their implementations to improve functionality of a human user.
Inguinal Hernia Repair Using 3D Printed Surgical Instruments in the Cadaveric Model: A Feasibility Study

3D printing is an additive manufacturing process allowing the creation of solid objects directly from computer aided design (CAD). Design and fabrication of 3D printed surgical instruments has previously been performed with results indicating relevance to real surgical procedures. This study expands on previous work and investigates the feasibility of performing a cadaveric inguinal hernia repair using 3D printed surgical instruments.  A CAD software package was used to design a general surgical set including hemostats, needle driver, scalpel handle, retractors and forceps. The digital models were manufactured on a 3D printer and used to perform a standard inguinal hernia repair on a human cadaver.  An acceptable inguinal hernia repair including mesh placement was successfully performed on a human cadaver using standard surgical techniques.  General surgical procedures such as an inguinal hernia repair are feasible using 3D printed surgical instruments.
Five Styles of Customer Knowledge Management , and How Smart Companies Use Them To Create Value

Corporations are beginning to realize that the proverbial ‘if we only knew what we know’ also includes ‘if we only knew what our customers know.’ The authors discuss the concept of Customer Knowledge Management (CKM), which refers to the management of knowledge from customers, i.e. knowledge resident in customers. CKM is contrasted with knowledge about customers, e.g. customer characteristics and preferences prevalent in previous work on knowledge management and customer relationship management. Five styles of CKM are proposed and practically illustrated by way of corporate examples. Implications are discussed for knowledge management, the resource based view, and strategy process research.
Texture Enhancement via High-Resolution Style Transfer for Single-Image Super-Resolution

Recently, various deep-neural-network (DNN)based approaches have been proposed for single-image superresolution (SISR). Despite their promising results on major structure regions such as edges and lines, they still suffer from limited performance on texture regions that consist of very complex and fine patterns. This is because, during the acquisition of a low-resolution (LR) image via down-sampling, these regions lose most of the high frequency information necessary to represent the texture details. In this paper, we present a novel texture enhancement framework for SISR to effectively improve the spatial resolution in the texture regions as well as edges and lines. We call our method, highresolution (HR) style transfer algorithm. Our framework consists of three steps: (i) generate an initial HR image from an interpolated LR image via an SISR algorithm, (ii) generate an HR style image from the initial HR image via down-scaling and tiling, and (iii) combine the HR style image with the initial HR image via a customized style transfer algorithm. Here, the HR style image is obtained by down-scaling the initial HR image and then repetitively tiling it into an image of the same size as the HR image. This down-scaling and tiling process comes from the idea that texture regions are often composed of small regions that similar in appearance albeit sometimes different in scale. This process creates an HR style image that is rich in details, which can be used to restore high-frequency texture details back into the initial HR image via the style transfer algorithm. Experimental results on a number of texture datasets show that our proposed HR style transfer algorithm provides more visually pleasing results compared with competitive methods. Index Terms — Single-image super-resolution, texture enhancement, high-resolution style, style transfer, down-scaling and tiling.
Facebook Use Predicts Declines in Subjective Well-Being in Young Adults

Over 500 million people interact daily with Facebook. Yet, whether Facebook use influences subjective well-being over time is unknown. We addressed this issue using experience-sampling, the most reliable method for measuring in-vivo behavior and psychological experience. We text-messaged people five times per day for two-weeks to examine how Facebook use influences the two components of subjective well-being: how people feel moment-to-moment and how satisfied they are with their lives. Our results indicate that Facebook use predicts negative shifts on both of these variables over time. The more people used Facebook at one time point, the worse they felt the next time we text-messaged them; the more they used Facebook over two-weeks, the more their life satisfaction levels declined over time. Interacting with other people "directly" did not predict these negative outcomes. They were also not moderated by the size of people's Facebook networks, their perceived supportiveness, motivation for using Facebook, gender, loneliness, self-esteem, or depression. On the surface, Facebook provides an invaluable resource for fulfilling the basic human need for social connection. Rather than enhancing well-being, however, these findings suggest that Facebook may undermine it.
A Layerless Additive Manufacturing Process based on CNC Accumulation

Most current additive manufacturing processes are layer-based, that is building a physical model layer-by-layer. By converting 3-dimensional geometry into 2-dimensional contours, the layer-based approach can dramatically simplify the process planning steps. However, there are also drawbacks associated with the layer-based approach such as inconsistent material properties between various directions. In a recent NSF workshop on additive manufacturing, it is suggested to investigate alternative non-layer based approaches. In this paper, we present an additive manufacturing process without planar layers. In the developed testbed, an additive tool based on a fiber optics cable and a UV-LED has been developed. By merging such tools inside a liquid resin tank, we demonstrate its capability of building various 2D and 3D structures. The technical challenges related to the development of such a process are discussed. Some potential applications including part repairing and building around inserts have also been demonstrated.
Binary partition tree as an efficient representation for image processing, segmentation, and information retrieval

This paper discusses the interest of binary partition trees as a region-oriented image representation. Binary partition trees concentrate in a compact and structured representation a set of meaningful regions that can be extracted from an image. They offer a multiscale representation of the image and define a translation invariant 2-connectivity rule among regions. As shown in this paper, this representation can be used for a large number of processing goals such as filtering, segmentation, information retrieval and visual browsing. Furthermore, the processing of the tree representation leads to very efficient algorithms. Finally, for some applications, it may be interesting to compute the binary partition tree once and to store it for subsequent use for various applications. In this context, the paper shows that the amount of bits necessary to encode a binary partition tree remains moderate.
Evaluating Influence Diagrams

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Inventory rebalancing and vehicle routing in bike sharing systems

Bike sharing systems have been installed in many cities around the world and are increasing in popularity. A major operational cost driver in these systems is rebalancing the bikes over time such that the appropriate number of bikes and open docks are available to users. We combine two aspects that have previously been handled separately in the literature: determining service level requirements at each bike sharing station, and designing (near-)optimal vehicle routes to rebalance the inventory. Since finding provably optimal solutions is practically intractable, we propose a new cluster-first route-second heuristic, in which the polynomialsize Clustering Problem simultaneously considers the service level feasibility constraints and approximate routing costs. Extensive computational results on real-world data from Hubway (Boston, MA) and Capital Bikeshare (Washington, DC) are provided, which show that our heuristic outperforms a pure mixed integer programming formulation and a constraint programming approach.