nils-herrmann/clean_scirepeval huggingface dataset:
A Graphical Social Topology Model for Multi-Object Tracking

Tracking multiple objects is a challenging task when objects move in groups and occlude each other. Existing methods have investigated the problems of group division and group energy-minimization; however, lacking overall objectgroup topology modeling limits their ability in handling complex object and group dynamics. Inspired with the social affinity property of moving objects, we propose a Graphical Social Topology (GST) model, which estimates the group dynamics by jointly modeling the group structure and the states of objects using a topological representation. With such topology representation, moving objects are not only assigned to groups, but also dynamically connected with each other, which enables in-group individuals to be correctly associated and the cohesion of each group to be precisely modeled. Using well-designed topology learning modules and topology training, we infer the birth/death and merging/splitting of dynamic groups. With the GST model, the proposed multi-object tracker can naturally facilitate the occlusion problem by treating the occluded object and other in-group members as a whole while leveraging overall state transition. Experiments on both RGB and RGB-D datasets confirm that the proposed multi-object tracker improves the state-of-the-arts especially in crowded scenes.
A closer look at batch size in mini-batch training of deep auto-encoders

In deep learning community, gradient based methods are typically employed to train the proposed models. These methods generally operate in a mini-batch training manner wherein a small fraction of the training data is invoked to compute an approximative gradient. It is reported that models trained with large batch are prone to generalize worse than those trained with small batch. Several inspiring works are conducted to figure out the underlying reason of this phenomenon, but almost all of them focus on classification tasks. In this paper, we investigate the influence of batch size on regression task. More specifically, we tested the generalizability of deep auto-encoder trained with varying batch size and checked some well-known measures relating to model generalization. Our experimental results lead to three conclusions. First, there exist no obvious generalization gap in regression model such as auto-encoders. Second, with a same train loss as target, small batch generally lead to solutions closer to the starting point than large batch. Third, spectral norm of weight matrices is closely related to generalizability of the model, but different layers contribute variously to the generalization performance.
Real-Time Human-Robot Interaction for a Service Robot Based on 3D Human Activity Recognition and Human-like Decision Mechanism

This paper describes the development of a realtime Human-Robot Interaction (HRI) system for a service robot based on 3D human activity recognition and human-like decision mechanism. The Human-Robot Interactive (HRI) system, which allows one person to interact with a service robot using natural body language, collects sequences of 3D skeleton joints comprising rich human movement information about the user via Microsoft Kinect. This information is used to train a three-layer Long-Short-Term Memory (LSTM) network for human action recognition. The robot understands user intent based on an online LSTM network test, and responds to the user via movements of the robotic arm or chassis. Furthermore, the human-like decision mechanism is also fused into this process, which allows the robot to instinctively decide whether to interrupt the current task according to task priority. The framework of the overall system is established on the Robot Operating System (ROS) platform. The real-life activity interaction between our service robot and the user was conducted to demonstrate the effectiveness of developed HRI system.
Extracting Social Networks from Literary Text with Word Embedding Tools

In this paper a social network is extracted from a literary text. The social network shows, how frequent the characters interact and how similar their social behavior is. Two types of similarity measures are used: the first applies co-occurrence statistics, while the second exploits cosine similarity on different types of word embedding vectors. The results are evaluated by a paid micro-task crowdsourcing survey. The experiments suggest that specific types of word embeddings like word2vec are well-suited for the task at hand and the specific circumstances of literary fiction text.
Preferences, Homophily, and Social Learning

We study a sequential model of Bayesian social learning in networks in which agents have heterogeneous preferences, and neighbors tend to have similar preferences—a phenomenon known as homophily. We find that the density of network connections determines the impact of preference diversity and homophily on learning. When connections are sparse, diverse preferences are harmful to learning, and homophily may lead to substantial improvements. In contrast, in a dense network, preference diversity is beneficial. Intuitively, diverse ties introduce more independence between observations while providing less information individually. Homophilous connections individually carry more useful information, but multiple observations become redundant.
A Mixed Trigrams Approach for Context Sensitive Spell Checking

The paper addresses the problem of real-word spell checking, i.e., the detection and correction of typos that result in real words of the target language. The paper proposes a methodology based on a mixed trigrams language model. Davide Fossati, Barbara Di Eugenio Spell Checking  A Mixed Trigrams Approach Experimental settings Experimental results  Spell checking is the process of finding misspelled words in a written text, and possibly correcting them. We can classify spelling errors in two main groups: Non-word errors, which are spelling errors that result in words that do not exist in the language. E.g. “The bok was on the table.” Real-word errors are errors that by chance end up as actual words. E.g. “I saw tree tress in the park.” Detecting and correcting real-word errors is the main focus of the paper. Davide Fossati, Barbara Di Eugenio Spell Checking  A Mixed Trigrams Approach Experimental settings Experimental results  Approaches Different approaches to real-word spell checking are present in the literature, e.g. Symbolic approaches check for grammatical anomalies. Statistical methods using n-gram models, PoS tagging, e.t.c. Davide Fossati, Barbara Di Eugenio Spell Checking  A Mixed Trigrams Approach Experimental settings Experimental results  Problems with statistical methods The problem with statistical methods using only n-grams is the data sparseness problem. PoS methods suffer less from sparseness problems, but are unable to detect misspelled that are of the same part of speech. Davide Fossati, Barbara Di Eugenio Spell Checking  A Mixed Trigrams Approach Experimental settings Experimental results  Mixed Trigrams Confusion set Levensthein Distance
Extraction Defect : Assessment , Classification and Management 1 Extraction Defect : Assessment , Classification and Management

Tooth extraction is a traumatic procedure initiating a complex cascade of biochemical and histologic events that inevitably lead to a reduction of alveolar bone and soft tissue. These tissue alterations often lead to an esthetic compromise of the future implant restoration. The hardand soft-tissue architecture surrounding the extraction defect largely dictates the course of dental implant treatment. The EDS or extraction defect sounding classification is a novel system introduced to simplify the decision-making process when planning for dental implant therapy following tooth extraction. Dental implant treatment guidelines-based on the EDS classification are discussed. A review of pretreatment evaluations necessary to prepare for esthetic implant procedures is also presented.
Reanalysis of a randomized trial of 3 techniques of anterior colporrhaphy using clinically relevant definitions of success.

The purpose of this study was to reanalyze the results of a previously published trial that compared 3 methods of anterior colporrhaphy according to the clinically relevant definitions of success.



A secondary analysis of a trial of 114 subjects who underwent surgery for anterior pelvic organ prolapse who were assigned randomly to standard anterior colporrhaphy, ultralateral colporrhaphy, or anterior colporrhaphy plus polyglactin 910 mesh from 1996-1999. For the current analysis, success was defined as (1) no prolapse beyond the hymen, (2) the absence of prolapse symptoms (visual analog scale ≤ 2), and (3) the absence of retreatment.



Eighty-eight percent of the women met our definition of success at 1 year. One subject (1%) underwent surgery for recurrence 29 months after surgery. No differences among the 3 groups were noted for any outcomes.



Reanalysis of a trial of 3 methods of anterior colporrhaphy revealed considerably better success with the use of clinically relevant outcome criteria compared with strict anatomic criteria.
Approaches for estimating prevalence ratios.

Correspondence to: James A Deddens, National Institute for Occupational Safety and Health, Mail Stop R15, 4676 Columbia Parkway, Cincinnati, OH 45226, USA; jad0@cdc.gov Recently there has been much interest in estimating the prevalence (risk, proportion or probability) ratio instead of the odds ratio, especially in occupational health studies involving common outcomes (for example, with prevalence rates above 10%). For example, if 80 out of 100 exposed subjects have a particular disease and 50 out of 100 non-exposed subjects have the disease, then the odds ratio (OR) is (80/20)/(50/50) = 4. However, the prevalence ratio (PR) is (80/100)/(50/ 100) = 1.6. The latter indicates that the exposed subjects are only 1.6 times as likely to have the disease as the non-exposed subjects, and this is the number in which most people would be interested. There is considerable literature on the advantages and disadvantages of OR versus PR (see Greenland, Stromberg, Axelson et al and others). In this article we will review the existing methods and give examples and recommendations on how to estimate the PR. The most common method of modelling binomial (no/yes or 0/1) health outcomes today is logistic regression. In logistic regression one models the probability of the binomial outcome (Y = 1) of interest as:
Client as a first-class citizen: Practical user-centric network MIMO clustering

Recent advances have demonstrated the potential of network MIMO (netMIMO), which combines a practical number of distributed antennas as a virtual netMIMO AP (nAP) to improve spatial multiplexing of an WLAN. Existing solutions, however, either simply cluster nearby antennas as static nAPs, or dynamically cluster antennas on a per-packet basis so as to maximize the sum rate of the scheduled clients. To strike the balance between the above two extremes, in this paper, we present the design, implementation and evaluation of FlexNEMO, a practical two-phase netMIMO clustering system. Unlike previous per-packet clustering approaches, FlexNEMO only clusters antennas when client distribution and traffic pattern change, as a result being more practical to be implemented. A medium access control protocol is then designed to allow the clients at the center of nAPs to have a higher probability to gain access opportunities, but still ensure long-term fairness among clients. By combining on-demand clustering and priority-based access control, FlexNEMO not only improves antenna utilization, but also optimizes the channel condition for every individual client. We evaluated our design via both testbed experiments on USRPs and trace-driven emulations. The results demonstrate that FlexNEMO can deliver 94.7% and 93.7% throughput gains over static antenna clustering in a 4-antenna testbed and 16-antenna emulation, respectively.
Anthracyclines in Early Breast Cancer: The ABC Trials-USOR 06-090, NSABP B-46-I/USOR 07132, and NSABP B-49 (NRG Oncology).

Docetaxel and cyclophosphamide (TC) was superior to doxorubicin and cyclophosphamide (AC) in a trial in early breast cancer. However, activity of TC relative to AC regimens with a taxane (TaxAC) is unknown.  In a series of three adjuvant trials, women were randomly assigned to TC for six cycles (TC6) or to a standard TaxAC regimen. US Oncology Research (USOR) 06-090 compared TC6 with docetaxel, doxorubicin, and cyclophosphamide (TAC6). National Surgical Adjuvant Breast and Bowel Project (NSABP) B-46-I/USOR 07132 compared TC6, TAC6, or TC6 plus bevacizumab. NSABP B-49 compared TC6 with several standard AC and taxane combination regimens. Before any analysis of individual trials, a joint efficacy analysis of TC versus the TaxAC regimens was planned, with invasive disease-free survival (IDFS) as the primary end point. Patients who received TC6 plus bevacizumab on NSABP B-46-I/USOR 07132 were not included. A hazard ratio (HR) from a stratified Cox model that exceeded 1.18 for TC6 versus TaxAC was predefined as inferiority for TC6. The prespecified interim monitoring plan was to report for futility if the HR was > 1.18 when 334 IDFS events were observed (50% of 668 events required for definitive analysis).  A total of 2,125 patients were randomly assigned to receive TC6 regimens and 2,117 patients were randomly assigned to receive TaxAC regimens. The median follow-up time was 3.3 years. There were 334 IDFS events, and the HR for TC6 versus TaxAC was 1.202 (95% CI, 0.97 to 1.49), which triggered early reporting for futility. The 4-year IDFS was 88.2% for TC6 and was 90.7% for TaxAC ( P = .04). Tests for treatment interaction by protocol, hormone receptor status, and nodal status were negative.  The TaxAC regimens improved IDFS in patients with high-risk human epidermal growth factor receptor 2-negative breast cancer compared with the TC6 regimen.
Brief interventions for alcohol problems: a review.

Relatively brief interventions have consistently been found to be effective in reducing alcohol consumption or achieving treatment referral of problem drinkers. To date, the literature includes at least a dozen randomized trials of brief referral or retention procedures, and 32 controlled studies of brief interventions targeting drinking behavior, enrolling over 6000 problem drinkers in both health care and treatment settings across 14 nations. These studies indicate that brief interventions are more effective than no counseling, and often as effective as more extensive treatment. The outcome literature is reviewed, and common motivational elements of effective brief interventions are described. There is encouraging evidence that the course of harmful alcohol use can be effectively altered by well-designed intervention strategies which are feasible within relatively brief-contact contexts such as primary health care settings and employee assistance programs. Implications for future research and practice are considered.
Incorporating modeling uncertainties in the assessment of seismic collapse risk of buildings

0167-4730/$ see front matter 2008  Corresponding author. E-mail address: abliel@stanford.edu (A.B. Liel). The primary goal of seismic provisions in building codes is to protect life safety through the prevention of structural collapse. To evaluate the extent to which current and past building code provisions meet this objective, the authors have conducted detailed assessments of collapse risk of reinforced-concrete moment frame buildings, including both ‘ductile’ frames that conform to current building code requirements, and ‘non-ductile’ frames that are designed according to out-dated (pre-1975) building codes. Many aspects of the assessment process can have a significant impact on the evaluated collapse performance; this study focuses on methods of representing modeling parameter uncertainties in the collapse assessment process. Uncertainties in structural component strength, stiffness, deformation capacity, and cyclic deterioration are considered for non-ductile and ductile frame structures of varying heights. To practically incorporate these uncertainties in the face of the computationally intensive nonlinear response analyses needed to simulate collapse, the modeling uncertainties are assessed through a response surface, which describes the median collapse capacity as a function of the model random variables. The response surface is then used in conjunction with Monte Carlo methods to quantify the effect of these modeling uncertainties on the calculated collapse fragilities. Comparisons of the response surface based approach and a simpler approach, namely the first-order second-moment (FOSM) method, indicate that FOSM can lead to inaccurate results in some cases, particularly when the modeling uncertainties cause a shift in the prediction of the median collapse point. An alternate simplified procedure is proposed that combines aspects of the response surface and FOSM methods, providing an efficient yet accurate technique to characterize model uncertainties, accounting for the shift in median response. The methodology for incorporating uncertainties is presented here with emphasis on the collapse limit state, but is also appropriate for examining the effects of modeling uncertainties on other structural limit states.
The pedipalp of Pseudocellus pearsei (Ricinulei, Arachnida) - ultrastructure of a multifunctional organ.

Ricinulei possess movable, slender pedipalps with small chelae. When ricinuleids walk, they occasionally touch the soil surface with the tips of their pedipalps. This behavior is similar to the exploration movements they perform with their elongated second legs. We studied the distal areas of the pedipalps of the cavernicolous Mexican species Pseudocellus pearsei with scanning and transmission electron microscopy. Five different surface structures are characteristic for the pedipalps: (1) slender sigmoidal setae with smooth shafts resembling gustatory terminal pore single-walled (tp-sw) sensilla; (2) conspicuous long, mechanoreceptive slit sensilla; (3) a single, short, clubbed seta inside a deep pit representing a no pore single walled (np-sw) sensillum; (4) a single pore organ containing one olfactory wall pore single-walled (wp-sw) sensillum; and (5) gustatory terminal pore sensilla in the fingers of the pedipalp chela. Additionally, the pedipalps bear sensilla which also occur on the other appendages. With this sensory equipment, the pedipalps are highly effective multimodal short range sensory organs which complement the long range sensory function of the second legs. In order to present the complete sensory equipment of all appendages of the investigated Pseudocellus a comparative overview is provided.
Highly discriminative statistical features for email classification

This paper reports on email classification and filtering, more specifically on spam versus ham and phishing versus spam classification, based on content features. We test the validity of several novel statistical feature extraction methods. The methods rely on dimensionality reduction in order to retain the most informative and discriminative features. We successfully test our methods under two schemas. The first one is a classic classification scenario using a 10-fold cross-validation technique for several corpora, including four ground truth standard corpora: Ling-Spam, SpamAssassin, PU1, and a subset of the TREC 2007 spam corpus, and one proprietary corpus. In the second schema, we test the anticipatory properties of our extracted features and classification models with two proprietary datasets, formed by phishing and spam emails sorted by date, and with the public TREC 2007 spam corpus. The contributions of our work are an exhaustive comparison of several feature selection and extraction methods in the frame of email classification on different benchmarking corpora, and the evidence that especially the technique of biased discriminant analysis offers better discriminative features for the classification, gives stable classification results notwithstanding the amount of features chosen, and robustly retains their discriminative value over time and data setups. These findings are especially useful in a commercial setting, where short profile rules are built based on a limited number of features for filtering emails.
Assessing the Graphical Perception of Time and Speed on 2D+Time Trajectories

We empirically evaluate the extent to which people perceive non-constant time and speed encoded on 2D paths. In our graphical perception study, we evaluate nine encodings from the literature for both straight and curved paths. Visualizing time and speed information is a challenge when the x and y axes already encode other data dimensions, for example when plotting a trip on a map. This is particularly true in disciplines such as time-geography and movement analytics that often require visualizing spatio-temporal trajectories. A common approach is to use 2D+time trajectories, which are 2D paths for which time is an additional dimension. However, there are currently no guidelines regarding how to represent time and speed on such paths. Our study results provide InfoVis designers with clear guidance regarding which encodings to use and which ones to avoid; in particular, we suggest using color value to encode speed and segment length to encode time whenever possible.
Model Predictive Control : Past , Present and Future

More than 15 years after model predictive control (MPC) appeared in industry as an effective means to deal with multivariable constrained control problems, a theoretical basis for this technique has started to emerge. The issues of feasibility of the on-line optimization, stability and performance are largely understood for systems described by linear models. Much progress has been made on these issues for non-linear systems but for practical applications many questions remain, including the reliability and efficiency of the on-line computation scheme. To deal with model uncertainty ‘rigorously’ an involved dynamic programming problem must be solved. The approximation techniques proposed for this purpose are largely at a conceptual stage. Among the broader research needs the following areas are identified: multivariable system identification, performance monitoring and diagnostics, non-linear state estimation, and batch system control. Many practical problems like control objective prioritization and symptom-aided diagnosis can be integrated systematically and effectively into the MPC framework by expanding the problem formulation to include integer variables yielding a mixed-integer quadratic or linear program. Efficient techniques for solving these problems are becoming available.
From patches to pixels in Non-Local methods: Weighted-average reprojection

Since their introduction in denoising, the family of non local methods, whose Non-Local Means (NL-Means) is the most famous member, has proved its ability to challenge other powerful methods such as wavelet based approaches or variational techniques. Though simple to implement and efficient in practice, the classical NL-Means suffers from ringing artifacts around edges. In this paper, we present an easy to implement and time efficient modification of the NL-means based on a better reprojection from the patches space to the original (image) pixel space. We illustrate the performance of our method on a toy example and on some classical images.