nils-herrmann/clean_scirepeval huggingface dataset:
A tractable numerical strategy for robust MILP and application to energy management

Robust optimization has emerged as a tractable methodology for coping with parameter uncertainty in an optimization problem. In order to avoid conservative solutions, i.e. overly protective and expensive solutions, Ben-Tal and Nemirovski introduced the notion of affine adaptability. However, their approach significantly increases the program size and threatens its tractability, especially in the context of mixed-integer programming. In this paper, we focus on robust mixed-integer linear programs. We propose a tractable numerical strategy for solving them and demonstrate the computational efficiency of our method when applied to a real energy management problem. In addition, we propose a practical data-driven methodology for designing the uncertainty set of robust programs.
Purposeful by design?: a serious game design assessment framework

The lack of assessment tools to analyze serious games and insufficient knowledge on their impact on players is a recurring critique in the field of game and media studies, education science and psychology. Although initial empirical studies on serious games usage deliver discussable results, numerous questions remain unacknowledged. In particular, questions regarding the quality of their formal conceptual design in relation to their purpose mostly stay uncharted. In the majority of cases the designers' good intentions justify incoherence and insufficiencies in their design. In addition, serious games are mainly assessed in terms of the quality of their content, not in terms of their intention-based design. This paper argues that analyzing a game's formal conceptual design, its elements, and their relation to each other based on the game's purpose is a constructive first step in assessing serious games. By outlining the background of the Serious Game Design Assessment Framework and exemplifying its use, a constructive structure to examine purpose-based games is introduced. To demonstrate how to assess the formal conceptual design of serious games we applied the SGDA Framework to the online games "Sweatshop" (2011) and "ICED" (2008).
Focused clustering and outlier detection in large attributed graphs

Graph clustering and graph outlier detection have been studied extensively on plain graphs, with various applications. Recently, algorithms have been extended to graphs with attributes as often observed in the real-world. However, all of these techniques fail to incorporate the user preference into graph mining, and thus, lack the ability to steer algorithms to more interesting parts of the attributed graph. In this work, we overcome this limitation and introduce a novel user-oriented approach for mining attributed graphs. The key aspect of our approach is to infer user preference by the so-called focus attributes through a set of user-provided exemplar nodes. In this new problem setting, clusters and outliers are then simultaneously mined according to this user preference. Specifically, our FocusCO algorithm identifies the focus, extracts focused clusters and detects outliers. Moreover, FocusCO scales well with graph size, since we perform a local clustering of interest to the user rather than global partitioning of the entire graph. We show the effectiveness and scalability of our method on synthetic and real-world graphs, as compared to both existing graph clustering and outlier detection approaches.
Jitter Analysis and a Benchmarking Figure-of-Merit for Phase-Locked Loops

This brief analyzes the jitter as well as the power dissipation of phase-locked loops (PLLs). It aims at defining a benchmark figure-of-merit (FOM) that is compatible with the well-known FOM for oscillators but now extended to an entire PLL. The phase noise that is generated by the thermal noise in the oscillator and loop components is calculated. The power dissipation is estimated, focusing on the required dynamic power. The absolute PLL output jitter is calculated, and the optimum PLL bandwidth that gives minimum jitter is derived. It is shown that, with a steep enough input reference clock, this minimum jitter is independent of the reference frequency and output frequency for a given PLL power budget. Based on these insights, a benchmark FOM for PLL designs is proposed.
What Does Social Media Say about Your Stress?

Website: http://hcsi.cs.tsinghua.edu.cn/ • Stress is composed of two key factors: stressor and stress level. • Stressor, comprising of stressor event and stressor subject, triggers stress • Measuring stress via social media is complicated: • Stressor subject detection • Stressor events happening to other subjects can also be someone’s stress trigger. • Social media postings are usually informal and ambiguous • Stressor event detection • Stressor events are correlated • For some specific event categories, such as death, there are insufficient training samples  Challenges: Measuring Psychological Stress via Social Media
POI2Vec: Geographical Latent Representation for Predicting Future Visitors

With the increasing popularity of location-aware social media applications, Point-of-Interest (POI) recommendation has recently been extensively studied. However, most of the existing studies explore from the users’ perspective, namely recommending POIs for users. In contrast, we consider a new research problem of predicting users who will visit a given POI in a given future period. The challenge of the problem lies in the difficulty to effectively learn POI sequential transition and user preference, and integrate them for prediction. In this work, we propose a new latent representation model POI2Vec that is able to incorporate the geographical influence, which has been shown to be very important in modeling user mobility behavior. Note that existing representation models fail to incorporate the geographical influence. We further propose a method to jointly model the user preference and POI sequential transition influence for predicting potential visitors for a given POI. We conduct experiments on 2 real-world datasets to demonstrate the superiority of our proposed approach over the state-of-the-art algorithms for both next POI prediction and future user prediction.
A Practical Model for Measuring Maintainability

The amount of effort needed to maintain a software system is related to the technical quality of the source code of that system. The ISO 9126 model for software product quality recognizes maintainability as one of the 6 main characteristics of software product quality, with adaptability, changeability, stability, and testability as subcharacteristics of maintainability. Remarkably, ISO 9126 does not provide a consensual set of measures for estimating maintainability on the basis of a system's source code. On the other hand, the maintainability index has been proposed to calculate a single number that expresses the maintainability of a system. In this paper, we discuss several problems with the MI, and we identify a number of requirements to be fulfilled by a maintainability model to be usable in practice. We sketch a new maintainability model that alleviates most of these problems, and we discuss our experiences with using such as system for IT management consultancy activities.
Triband Planar Monopole Antenna With Compact Radiator for WLAN/WiMAX Applications

A novel coplanar waveguide (CPW)-fed triband planar monopole antenna is presented for WLAN/WiMAX applications. The monopole antenna is printed on a substrate with two rectangular corners cut off. The radiator of the antenna is very compact with an area of only 3.5 × 17 mm2, on which two inverted-L slots are etched to achieve three radiating elements so as to produce three resonant modes for triband operation. With simple structure and small size, the measured and simulated results show that the proposed antenna has 10-dB impedance bandwidths of 120 MHz (2.39-2.51 GHz), 340 MHz (3.38-3.72 GHz), and 1450 MHz (4.79-6.24 GHz) to cover all the 2.4/5.2/5.8-GHz WLAN and the 3.5/5.5-GHz WiMAX bands, and good dipole-like radiation characteristics are obtained over the operating bands.
Best paper - Follow the money: understanding economics of online aggregation and advertising

The large-scale collection and exploitation of personal information to drive targeted online advertisements has raised privacy concerns. As a step towards understanding these concerns, we study the relationship between how much information is collected and how valuable it is for advertising. We use HTTP traces consisting of millions of users to aid our study and also present the first comparative study between aggregators. We develop a simple model that captures the various parameters of today's advertising revenues, whose values are estimated via the traces. Our results show that per aggregator revenue is skewed (5% accounting for 90% of revenues), while the contribution of users to advertising revenue is much less skewed (20% accounting for 80% of revenue). Google is dominant in terms of revenue and reach (presence on 80% of publishers). We also show that if all 5% of the top users in terms of revenue were to install privacy protection, with no corresponding reaction from the publishers, then the revenue can drop by 30%.
Spatial frequency, phase, and the contrast of natural images.

We examined contrast sensitivity and suprathreshold apparent contrast with natural images. The spatial-frequency components within single octaves of the images were removed (notch filtered), their phases were randomized, or the polarity of the images was inverted. Of Michelson contrast, root-mean-square (RMS) contrast, and band-limited contrast, RMS contrast was the best index of detectability. Negative images had lower apparent contrast than their positives. Contrast detection thresholds showed spatial-frequency-dependent elevation following both notch filtering and phase randomization. The peak of the spatial-frequency tuning function was approximately 0.5-2 cycles per degree (c/deg). Suprathreshold contrast matching functions also showed spatial-frequency-dependent contrast loss for both notch-filtered and phase-randomized images. The peak of the spatial-frequency tuning function was approximately 1-3 c/deg. There was no detectable difference between the effects of phase randomization and notch filtering on contrast sensitivity. We argue that these observations are consistent with changes in the activity within spatial-frequency channels caused by the higher-order phase structure of natural images that is responsible for the presence of edges and specularities.
DisCo: Display-Camera Communication Using Rolling Shutter Sensors

We present DisCo, a novel display-camera communication system. DisCo enables displays and cameras to communicate with each other while also displaying and capturing images for human consumption. Messages are transmitted by temporally modulating the display brightness at high frequencies so that they are imperceptible to humans. Messages are received by a rolling shutter camera that converts the temporally modulated incident light into a spatial flicker pattern. In the captured image, the flicker pattern is superimposed on the pattern shown on the display. The flicker and the display pattern are separated by capturing two images with different exposures. The proposed system performs robustly in challenging real-world situations such as occlusion, variable display size, defocus blur, perspective distortion, and camera rotation. Unlike several existing visible light communication methods, DisCo works with off-the-shelf image sensors. It is compatible with a variety of sources (including displays, single LEDs), as well as reflective surfaces illuminated with light sources. We have built hardware prototypes that demonstrate DisCo’s performance in several scenarios. Because of its robustness, speed, ease of use, and generality, DisCo can be widely deployed in several applications, such as advertising, pairing of displays with cell phones, tagging objects in stores and museums, and indoor navigation.
Color schemes for a sectorless ATM controller working position

In sectorless air traffic management (ATM) concept, air traffic controllers are no longer in charge of a certain sector. Instead, the sectorless airspace is considered as a single unit and controllers are assigned certain aircraft, which might be located anywhere in the sectorless airspace. The air traffic controllers are responsible for these geographically independent aircraft all the way from their entry into the airspace to the exit. In order to support the controllers with this task, they are provided with one radar display for each assigned aircraft. This means, only one aircraft on each of these radar displays is under their control as the surrounding traffic is under control of other controllers. Each air traffic controller has to keep track of several traffic situations at the same time. In order to optimally support controllers with this task, a color-coding of the information is necessary. For example, the aircraft under control can be distinguished from the surrounding traffic by displaying them in a certain color. Furthermore, conflict detection and resolution information can be color-coded, such that it is straightforward which controller is in charge of solving a conflict. We conducted a human-in-the-loop simulation in order to compare different color schemes for a sectorless ATM controller working position. Three different color schemes were tested: a positive contrast polarity scheme that follows the current look of the P1/VAFORIT (P1/very advanced flight-data processing operational requirement implementation) display used by the German air navigation service provider DFS in the Karlsruhe upper airspace control center, a newly designed negative contrast polarity color scheme and a modified positive contrast polarity scheme. An analysis of the collected data showed no significant evidence for an impact of the color schemes on controller task performance. However, results suggest that a positive contrast polarity should be preferred and that the newly designed positive contrast polarity color scheme has advantages over the P1/VAFORIT color scheme when used for sectorless ATM.
Predicting user interests from contextual information

Search and recommendation systems must include contextual information to effectively model users' interests. In this paper, we present a systematic study of the effectiveness of five variant sources of contextual information for user interest modeling. Post-query navigation and general browsing behaviors far outweigh direct search engine interaction as an information-gathering activity. Therefore we conducted this study with a focus on Website recommendations rather than search results. The five contextual information sources used are: social, historic, task, collection, and user interaction. We evaluate the utility of these sources, and overlaps between them, based on how effectively they predict users' future interests. Our findings demonstrate that the sources perform differently depending on the duration of the time window used for future prediction, and that context overlap outperforms any isolated source. Designers of Website suggestion systems can use our findings to provide improved support for post-query navigation and general browsing behaviors.
Error patterns on the Raven ' s Standard Progressive Matrices Test

⁎ Corresponding author. E-mail addresses: mkunda@vanderbilt.edu (M. Kunda (I. Soulières), agata@gatech.edu (A. Rozga),  Vanderbilt Pla USA. 2 Terminology: Raven's Progressive Matrices (RPM) refe Specific test versions include: Standard ProgressiveMatric and adults in average ability ranges; Colored ProgressiveM with children, the elderly, or other individuals falling Advanced Progressive Matrices (APM), intended for highe
Subspace Interpolation via Dictionary Learning for Unsupervised Domain Adaptation

Domain adaptation addresses the problem where data instances of a source domain have different distributions from that of a target domain, which occurs frequently in many real life scenarios. This work focuses on unsupervised domain adaptation, where labeled data are only available in the source domain. We propose to interpolate subspaces through dictionary learning to link the source and target domains. These subspaces are able to capture the intrinsic domain shift and form a shared feature representation for cross domain recognition. Further, we introduce a quantitative measure to characterize the shift between two domains, which enables us to select the optimal domain to adapt to the given multiple source domains. We present experiments on face recognition across pose, illumination and blur variations, cross dataset object recognition, and report improved performance over the state of the art.
Discrete laplace operator on meshed surfaces

In recent years a considerable amount of work in graphics and geometric optimization used tools based on the Laplace-Beltrami operator on a surface. The applications of the Laplacian include mesh editing, surface smoothing, and shape interpolations among others. However, it has been shown [13, 24, 26] that the popular cotangent approximation schemes do not provide convergent point-wise (or even L2) estimates, while many applications rely on point-wise estimation. Existence of such schemes has been an open question [13].
 In this paper we propose the first algorithm for approximating the Laplace operator of a surface from a mesh with point-wise convergence guarantees applicable to arbitrary meshed surfaces. We show that for a sufficiently fine mesh over an arbitrary surface, our mesh Laplacian is close to the Laplace-Beltrami operator on the surface at every point of the surface.
 Moreover, the proposed algorithm is simple and easily implementable. Experimental evidence shows that our algorithm exhibits convergence empirically and compares favorably with cotangentbased methods in providing accurate approximation of the Laplace operator for various meshes.
Digital forensics: exploring validation, verification & certification

Digital forensic teams and laboratories are now common place within Australia, particularly associated with law enforcement and intelligence agencies. The digital forensics discipline is rapidly evolving to become a scientific practice with domain-specific guideline. These guidelines are still under discussion in an attempt to progress the discipline so as to become as solid and robust in its scientific underpinnings as other forensic disciplines. Influential players, practitioners and observers all agree that rigorous standards need to be adopted to align this science with other forensic sciences. How does one assess the scientific nature of digital forensics with so many independent computing and IT elements combined, and what are the outcomes of each assessment method? Solutions are proposed regularly justifying their use but to date no one international or national standard exists. This paper does not propose a solution but rather explores the concept of Validation and Verification (V&V) with particular respect to digital forensic tools. The paper also explores ISO17025 "General requirements for the competence of testing and calibration laboratories" and develops the testing process to satisfy this standard to allow for Australian digital forensic laboratories to be eligible for certification.
Radar cross section for pedestrian in 76GHz band

This paper describes the results of our evaluation of a pedestrian's radio wave reflection characteristics. The reflection characteristics of radio waves from a pedestrian were measured as part of the effort to improve the pedestrian detection performance of the radar sensor. A pedestrian's radio wave reflection intensity is low, at about 15-20dB less than that of the rear of a vehicle, and can vary by as much as 20dB. Evaluating these characteristics in detail is a prerequisite to the development of a radar sensor that is capable of detecting pedestrians reliably.
Predicting bursts and popularity of hashtags in real-time

Hashtags have been widely used to annotate topics in tweets (short posts on Twitter.com). In this paper, we study the problems of real-time prediction of bursting hashtags. Will a hashtag burst in the near future? If it will, how early can we predict it, and how popular will it become? Based on empirical analysis of data collected from Twitter, we propose solutions to these challenging problems. The performance of different features and possible solutions are evaluated.
Social exclusion and early-stage interpersonal perception: selective attention to signs of acceptance.

Social exclusion can thwart people's powerful need for social belonging. Whereas prior studies have focused primarily on how social exclusion influences complex and cognitively downstream social outcomes (e.g., memory, overt social judgments and behavior), the current research examined basic, early-in-the-cognitive-stream consequences of exclusion. Across 4 experiments, the threat of exclusion increased selective attention to smiling faces, reflecting an attunement to signs of social acceptance. Compared with nonexcluded participants, participants who experienced the threat of exclusion were faster to identify smiling faces within a "crowd" of discrepant faces (Experiment 1), fixated more of their attention on smiling faces in eye-tracking tasks (Experiments 2 and 3), and were slower to disengage their attention from smiling faces in a visual cueing experiment (Experiment 4). These attentional attunements were specific to positive, social targets. Excluded participants did not show heightened attention to faces conveying social disapproval or to positive nonsocial images. The threat of social exclusion motivates people to connect with sources of acceptance, which is manifested not only in "downstream" choices and behaviors but also at the level of basic, early-stage perceptual processing.
Limited Discrepancy Beam Search

Beam search reduces the memory consumption of bestfirst search at the cost of finding longer paths but its memory consumption can still exceed the given memory capacity quickly. We therefore develop BULB (Beam search Using Limited discrepancy Backtracking), a complete memory-bounded search method that is able to solve more problem instances of large search problems than beam search and does so with a reasonable runtime. At the same time, BULB tends to find shorter paths than beam search because it is able to use larger beam widths without running out of memory. We demonstrate these properties of BULB experimentally for three standard benchmark domains.
Compressive sensing: From theory to applications, a survey

Compressive sensing (CS) is a novel sampling paradigm that samples signals in a much more efficient way than the established Nyquist sampling theorem. CS has recently gained a lot of attention due to its exploitation of signal sparsity. Sparsity, an inherent characteristic of many natural signals, enables the signal to be stored in few samples and subsequently be recovered accurately, courtesy of CS. This article gives a brief background on the origins of this idea, reviews the basic mathematical foundation of the theory and then goes on to highlight different areas of its application with a major emphasis on communications and network domain. Finally, the survey concludes by identifying new areas of research where CS could be beneficial.
Speeding Up the Douglas-Peucker Line-Simpli cation Algorithm

We analyze the line simpli cation algorithm reported by Douglas and Peucker and show that its worst case is quadratic in n, the number of input points. Then we give a algorithm, based on path hulls, that uses the geometric structure of the problem to attain a worst-case running time proportional to n log 2 n, which is the best case of the Douglas algorithm. We give complete C code and compare the two algorithms theoretically, by operation counts, and practically, by machine timings.