nils-herrmann/clean_scirepeval huggingface dataset:
Discovering and Profiling Overlapping Communities in Location-Based Social Networks

With the recent surge of location-based social networks (LBSNs), such as Foursquare and Facebook Places, huge digital footprints of people's locations, profiles, and online social connections become accessible to service providers. Unlike social networks (e.g., Flickr, Facebook) that have explicit groups for users to subscribe to or join, LBSNs usually have no explicit community structure. In order to capitalize on the large number of potential users, quality community detection and profiling approaches are needed. In the meantime, the diversity of people's interests and behaviors when using LBSNs suggests that their community structures overlap. In this paper, based on the user check-in traces at venues and user/venue attributes, we come out with a novel multimode multi-attribute edge-centric coclustering framework to discover the overlapping and hierarchical communities of LBSNs users. By employing both intermode and intramode features, the proposed framework is not only able to group like-minded users from different social perspectives but also discover communities with explicit profiles indicating the interests of community members. The efficacy of our approach is validated by intensive empirical evaluations using the collected Foursquare dataset.
Close Yet Distinctive Domain Adaptation

Domain adaptation is transfer learning which aims to generalize a learning model across training and testing data with different distributions. Most previous research tackle this problem in seeking a shared feature representation between source and target domains while reducing the mismatch of their data distributions. In this paper, we propose a close yet discriminative domain adaptation method, namely CDDA, which generates a latent feature representation with two interesting properties. First, the discrepancy between the source and target domain, measured in terms of both marginal and conditional probability distribution via Maximum Mean Discrepancy is minimized so as to attract two domains close to each other. More importantly, we also design a repulsive force term, which maximizes the distances between each label dependent sub-domain to all others so as to drag different class dependent sub-domains far away from each other and thereby increase the discriminative power of the adapted domain. Moreover, given the fact that the underlying data manifold could have complex geometric structure, we further propose the constraints of label smoothness and geometric structure consistency for label propagation. Extensive experiments are conducted on 36 cross-domain image classification tasks over four public datasets. The Comprehensive results show that the proposed method consistently outperforms the state-of-the-art methods with significant margins. ∗These first two authors contributed equally.
Permission Re-Delegation: Attacks and Defenses

Modern browsers and smartphone operating systems treat applications as mutually untrusting, potentially malicious principals. Applications are (1) isolated except for explicit IPC or inter-application communication channels and (2) unprivileged by default, requiring user permission for additional privileges. Although inter-application communication supports useful collaboration, it also introduces the risk of permission redelegation. Permission re-delegation occurs when an application with permissions performs a privileged task for an application without permissions. This undermines the requirement that the user approve each application’s access to privileged devices and data. We discuss permission re-delegation and demonstrate its risk by launching real-world attacks on Android system applications; several of the vulnerabilities have been confirmed as bugs. We discuss possible ways to address permission redelegation and present IPC Inspection, a new OS mechanism for defending against permission re-delegation. IPC Inspection prevents opportunities for permission redelegation by reducing an application’s permissions after it receives communication from a less privileged application. We have implemented IPC Inspection for a browser and Android, and we show that it prevents the attacks we found in the Android system applications.
Image-Based Localization Using LSTMs for Structured Feature Correlation

In this work we propose a new CNN+LSTM architecture for camera pose regression for indoor and outdoor scenes. CNNs allow us to learn suitable feature representations for localization that are robust against motion blur and illumination changes. We make use of LSTM units on the CNN output, which play the role of a structured dimensionality reduction on the feature vector, leading to drastic improvements in localization performance. We provide extensive quantitative comparison of CNN-based and SIFT-based localization methods, showing the weaknesses and strengths of each. Furthermore, we present a new large-scale indoor dataset with accurate ground truth from a laser scanner. Experimental results on both indoor and outdoor public datasets show our method outperforms existing deep architectures, and can localize images in hard conditions, e.g., in the presence of mostly textureless surfaces, where classic SIFT-based methods fail.
An Eye Tracking Study on camelCase and under_score Identifier Styles

An empirical study to determine if identifier-naming conventions (i.e., camelCase and under_score) affect code comprehension is presented. An eye tracker is used to capture quantitative data from human subjects during an experiment. The intent of this study is to replicate a previous study published at ICPC 2009 (Binkley et al.) that used a timed response test method to acquire data. The use of eye-tracking equipment gives additional insight and overcomes some limitations of traditional data gathering techniques. Similarities and differences between the two studies are discussed. One main difference is that subjects were trained mainly in the underscore style and were all programmers. While results indicate no difference in accuracy between the two styles, subjects recognize identifiers in the underscore style more quickly.
Neural network-based reputation model in a distributed system

Current centralized trust models are inappropriate to apply in a large distributed multi-agent system, due to various evaluation models and partial observations in local level reputation management. This paper proposes a distributed reputation management structure, and develops a global reputation model. The global reputation model is a novel application of neural network techniques in distributed reputation evaluations. The experimental results showed that the model has robust performance under various estimation accuracy requirements. More important, the model is adaptive to changes in distributed system structures and in local reputation evaluations.
IAP Guidelines on Rickettsial Diseases in Children.

To formulate practice guidelines on rickettsial diseases in children for pediatricians across India.



Rickettsial diseases are increasingly being reported from various parts of India. Due to low index of suspicion, nonspecific clinical features in early course of disease, and absence of easily available, sensitive and specific diagnostic tests, these infections are difficult to diagnose. With timely diagnosis, therapy is easy, affordable and often successful. On the other hand, in endemic areas, where healthcare workers have high index of suspicion for these infections, there is rampant and irrational use of doxycycline as a therapeutic trial in patients of undifferentiated fevers. Thus, there is a need to formulate practice guidelines regarding rickettsial diseases in children in Indian context.


PROCESS
A committee was formed for preparing guidelines on rickettsial diseases in children in June 2016. A meeting of consultative committee was held in IAP office, Mumbai and scientific content was discussed. Methodology and results were scrutinized by all members and consensus was reached. Textbook references and published guidelines were also used in few instances to make recommendations. Various Indian and international publications pertinent to present study were collated and guidelines were approved by all committee members. Future updates in these guidelines will be dictated by new scientific data in the field of rickettsial diseases in children.


RECOMMENDATIONS
Indian tick typhus and scrub typhus are commonly seen rickettsial diseases in India. It is recommended that practicing pediatricians should be well conversant with compatible clinical scenario, suggestive epidemiological features, differential diagnoses and suggestive laboratory features to make diagnosis and avoid over diagnosis of these infections, as suggested in these guidelines. Doxycycline is the drug of choice and treatment should begin promptly without waiting for confirmatory laboratory results.
Real-time tracking on adaptive critic design with uniformly ultimately bounded condition

In this paper, we proposed a new nonlinear tracking controller based on heuristic dynamic programming (HDP) with the tracking filter. Specifically, we integrate a goal network into the regular HDP design and provide the critic network with detailed internal reward signal to help the value function approximation. The architecture is explicitly explained with the tracking filter, goal network, critic network and action network, respectively. We provide the stability analysis of our proposed controller with Lyapunov approach. It is shown that the filtered tracking errors and the weights estimation errors in neural networks are all uniformly ultimately bounded (UUB) under certain conditions. Finally, we compare our proposed approach with regular HDP approach in virtual reality (VR)/Simulink environment to justify the improved control performance.
Designing Anthropomorphic Robot Hand With Active Dual-Mode Twisted String Actuation Mechanism and Tiny Tension Sensors

In this letter, using the active dual-mode twisted string actuation (TSA) mechanism and tiny tension sensors on the tendon strings, an anthropomorphic robot hand is newly designed in a compact manner. Thanks to the active dual-mode TSA mechanism, which is a miniaturized transmission, the proposed robot hand dose has a wide range of operation in terms of the grasping force and speed. It experimentally produces maximally the fingertip force 31.3 N and minimally the closing time of 0.5 s in average. Also, tiny tension sensor with the dimension of 4.7 (width) × 4.0 (height) × 10.75 (length) mm is newly presented and embedded at the fingertips in order to measure the tension on the tendon strings, which would allow the grasping force control. The kinetic and kinematic analyses are performed and the performance is verified by experiments.
Empirical research on consumers' initial trust and gender differences in B2C e-business

Based on the Technology Acceptance Model and related literatures, this paper proposes an integrated conceptual model of consumers' initial trust in B2C e-business. Empirical research results show that, perceived usefulness, perceived safety, perceived website reputation and propensity to trust significantly positively affect consumers' initial trust in e-vendor, which further positively influence consumers' intention to purchase online, by the complete mediation of attitude; however, the effect of perceived use of use on initial trust doesn't show the statistic significance. Furthermore, there are significant gender differences in the effects of perceived ease of use, perceived safety, perceived website reputation on consumers' initial trust.
Profanity in media associated with attitudes and behavior regarding profanity use and aggression.

We hypothesized that exposure to profanity in media would be directly related to beliefs and behavior regarding profanity and indirectly to aggressive behavior.



We examined these associations among 223 adolescents attending a large Midwestern middle school. Participants completed a number of questionnaires examining their exposure to media, attitudes and behavior regarding profanity, and aggressive behavior.



Results revealed a positive association between exposure to profanity in multiple forms of media and beliefs about profanity, profanity use, and engagement in physical and relational aggression. Specifically, attitudes toward profanity use mediated the relationship between exposure to profanity in media and subsequent behavior involving profanity use and aggression.



The main hypothesis was confirmed, and implications for the rating industry and research field are discussed.
Wave propagation and scattering in random media

No wonder you activities are, reading will be always needed. It is not only to fulfil the duties that you need to finish in deadline time. Reading will encourage your mind and thoughts. Of course, reading will greatly develop your experiences about everything. Reading wave propagation and scattering in random media is also a way as one of the collective books that gives many advantages. The advantages are not only for you, but for the other peoples with those meaningful benefits.
Temporally Grounding Natural Sentence in Video

We introduce an effective and efficient method that grounds (i.e., localizes) natural sentences in long, untrimmed video sequences. Specifically, a novel Temporal GroundNet (TGN)1 is proposed to temporally capture the evolving fine-grained frame-by-word interactions between video and sentence. TGN sequentially scores a set of temporal candidates ended at each frame based on the exploited frameby-word interactions, and finally grounds the segment corresponding to the sentence. Unlike traditional methods treating the overlapping segments separately in a sliding window fashion, TGN aggregates the historical information and generates the final grounding result in one single pass. We extensively evaluate our proposed TGN on three public datasets with significant improvements over the stateof-the-arts. We further show the consistent effectiveness and efficiency of TGN through an ablation study and a runtime test.
Center-Fed Patch Antenna Array Excited by an Inset Dielectric Waveguide for 60-GHz Applications

A patch antenna array proximity-coupled fed by the inset dielectric waveguide (IDW) is proposed in 60-GHz frequency band. The antenna array consists of four series-fed subarrays each having eight pairs of circular patch elements, four substrate integrated IDWs, and a compact four-way power divider transmitting the signal from the grounded coplanar waveguide (GCPW) to the IDWs. The IDW is realized by metallized via-hole arrays in a printed circuit board (PCB). The parallel center-fed configuration is applied to suppress the frequency-dependent beam squinting of the series-fed subarray. Measured results show that the proposed antenna exhibits a gain variation between 15.8 and 19.2 dBi, fixed main beam in the direction of θ = 0°, and the reflection coefficient |S11| ≤ -10 dB over the frequency band from 58 to 64 GHz.
A Robotic Leg Prosthesis: Design, Control, and Implementation

This article describes the design and control of a powered knee and ankle prosthesis for transfemoral amputees. Following a description of the design hardware, a hybrid control approach that provides coordination for level walking is described. The hybrid control approach combines a piecewise-passive impedance-based component during the stance phase of gait with a high impedance trajectory-tracking component during the terminal stance and swing. To validate the design, the controller was implemented on the powered prosthesis prototype, and its ability to provide level walking functionality was evaluated on three transfemoral amputee subjects. The data presented from these experimental trials indicate that the prosthesis and control approach reproduce knee and ankle joint kinematic and kinetic features that are highly representative of corresponding healthy joint biomechanics.
Pachyonychia congenita type 2 (Jackson-Lawler syndrome) or PC-17: case report.

Pachyonychia congenita (PC) is a rare genodermatosis caused by mutations in any of the four genes KRT6A, KRT6B, KRT16, or KRT17, which can lead to dystrophic, thickened nails and focal palmoplantar keratoderma, among other manifestations. Although classically subdivided into two major variants, PC-1 (Jadassohn-Lewandowski syndrome) and PC-2 (Jackson-Lawler syndrome), according to the localization of the mutations in the KRT6A/KRT16 or KRT6B/KRT17 genes, respectively, a classification system based on the mutant gene (PC-6a, PC-6b, PC-16 and PC-17) has been recently proposed. We report a 2-year-old female patient with a history of thickened and discolored nails, small cystic papulonodules on the central face, dry, unruly and curly hair, slight palmoplantar hyperkeratosis, and natal teeth. Both her father and paternal grandfather presented onychodystrophy, palmoplantar keratoderma, and previous excision of "sebaceous" cysts. Molecular genetic analysis of the patient revealed a missense mutation (c.1163T>C) in heterozygosity in exon 6 of the KRT17 gene, confirming the diagnosis of PC-2 (Jackson-Lawler type), or PC-17. We conclude that PC is a relatively easy and consistent clinical diagnosis, but a high index of suspicion is required if the diagnosis is to be made correctly. With this case, the authors intend to draw attention to this condition and the role of the dermatologist in the diagnosis.
Automated detection of euro pallet loads by interpreting PMD camera depth images

In this study, a novel approach for the detection of parcel loading positions on a pallet is presented. This approach was realized as a substantial change in comparison with traditional system design of contour detection in de-palletizing processes. Complex 3D-vision systems, costly laser scanners or throughput decreasing local sensor solutions integrated in grippers are substituted by a lowcost photonic mixing device (PMD) camera. By combining PMD technology and a predetermined model of loading situations, stored during assembling the pallet, this approach can compensate for the drawbacks of each respective system. An essential part of the approach are computer-graphics methods specific to the given problem to both detect the deviation between the nominal and the actual loading position and if necessary an automated correction of the packaging scheme. From an economic point of view, this approach can decrease the costs of mandatory contour checking in automated de-palletizing processes.
Deep Convolutional Neural Networks [Lecture Notes]

Neural networks are a subset of the field of artificial intelligence (AI). The predominant types of neural networks used for multidimensional signal processing are deep convolutional neural networks (CNNs). The term deep refers generically to networks having from a "few" to several dozen or more convolution layers, and deep learning refers to methodologies for training these systems to automatically learn their functional parameters using data representative of a specific problem domain of interest. CNNs are currently being used in a broad spectrum of application areas, all of which share the common objective of being able to automatically learn features from (typically massive) data bases and to generalize their responses to circumstances not encountered during the learning phase. Ultimately, the learned features can be used for tasks such as classifying the types of signals the CNN is expected to process. The purpose of this "Lecture Notes" article is twofold: 1) to introduce the fundamental architecture of CNNs and 2) to illustrate, via a computational example, how CNNs are trained and used in practice to solve a specific class of problems.
VHDL Implementation Of Reconfigurable Crossbar Switch For Binoc Router

Network-on-Chip (NoC) is the interconnection platform that answers the requirements of the modern on-Chip design. Small optimizations in NoC router architecture can show a significant improvement in the overall performance of NoC based systems. Power consumption, area overhead and the entire NoC performance is influenced by the router crossbar switch. This paper presents implementation of 10x10 reconfigurable crossbar switch (RCS) architecture for Dynamic Self-Reconfigurable BiNoC Architecture for Network On Chip. Its main purpose is to increase the performance, flexibility. This paper presents a VHDL based cycle accurate register transfer level model for evaluating the, Power and Area of reconfigurable crossbar switch in BiNoC architectures. We implemented a parameterized register transfer level design of reconfigurable crossbar switch (RCS) architec ture. The design is parameterized on (i) size of packets, (ii) length and width of physical links, (iii) number, and depth of arbi ters, and (iv) switching technique. The paper discusses in detail the architecture and characterization of the various reconfigurable crossbar switch (RCS) architecture components. The characterized values were integrated into the VHDL based RTL design to build the cycle accurate performance model. In this paper we show the result of simple 4 x4 as well as 10x10 crossbar switch .The results include VHDL simulation of RCS on ModelSim tool for 4 x4 crossbar switch and Xilinx ISE 13.1 software tool for 10x10 crossbar switch.
Developing Web-based assessment strategies for facilitating junior high school students to perform self-regulated learning in an e-Learning environment

This research refers to the self-regulated learning strategies proposed by Pintrich (1999) in developing a multiple-choice Web-based assessment system, the Peer-Driven Assessment Module of the Web-based Assessment and Test Analysis system (PDA-WATA). The major purpose of PDA-WATA is to facilitate learner use of self-regulatory learning behaviors to perform self-regulated learning and in turn improve e-Learning effectiveness. PDA-WATA includes five main strategies: ‘Adding Answer Notes,’ ‘Stating Confidence,’ ‘Reading Peer Answer Notes,’ ‘Recommending Peer Answer Notes’ and ‘Querying Peers’ Recommendation on Personal Answer Notes’. Using these strategies, examinees are allowed to add answer notes to explain why they chose a certain option as the correct answer and state their confidence in their own answer and answer notes, for peers’ reference. In addition to reading peer answer notes, examinees can also recommend peer answer notes as valuable references. The recommendation information can also be queried by all examinees. Quasi-experimental design was adopted to understand the effectiveness of PDA-WATA in facilitating learner use of self-regulatory learning behaviors to perform self-regulated learning and in improving learner e-Learning effectiveness. Participants were 123 seventhgrade junior high school students from four classes. These four classes were randomly divided into the PDA-WATA group (n1⁄4 63) and the N-WBT group (n1⁄4 60). Before e-Learning instruction, all students took the pre-test of the Learning Process Inventory (LPI), used to understand how often learners use selfregulatory learning behaviors in the learning process, and the pre-test of the summative assessment. After a two-week e-Learning instruction, the students all took the post-test of the LPI and the summative assessment. Results indicate that students in the PDA-WATA group appear to be more willing to take the Web-based formative assessment than students in the N-WBT group. In addition, PDA-WATA appears to be significantly more effective than N-WBT in facilitating learner use of self-regulatory learning behaviors to perform self-regulated learning and in improving their e-Learning effectiveness. Moreover, this research also finds that in the PDA-WATA group, there is no significant difference between the learning effectiveness of students with a low level of self-regulated learning and students with a high level of self-regulated learning, but similar result cannot be found in the N-WBT group.