nils-herrmann/clean_scirepeval huggingface dataset:
MASK-BAN: Movement-Aided Authenticated Secret Key Extraction Utilizing Channel Characteristics in Body Area Networks

Recently, most wireless network security schemes merely based on physical layer characteristics tackle the two fundamental issues-device authentication and secret key extraction separately. It remains an open problem to simultaneously achieve device authentication and fast secret key extraction merely using wireless physical layer characteristics, without the help of advanced hardware or out-of-band channel. In this paper, we answer this open problem in the setting of wireless body area networks (BANs). We propose MASK-BAN, a lightweight fast authenticated secret key extraction scheme for intra-BAN communication. Our scheme neither introduces advanced hardware nor relies on out-of-band channels. To perform device authentication and fast secret key extraction at the same time, we exploit the heterogeneous channel characteristics among the collection of on-body channels during body motion. On one hand, MASK-BAN achieves authentication through multihop stable channels, which greatly reduces the false positive rate as compared to existing work. On the other hand, based on dynamic channels, key extraction between two on-body devices with multihop relay nodes is modeled as a max-flow problem, and a novel collaborative secret key generation algorithm is introduced to maximize the key generation rate. Extensive real-world experiments on low-end commercial-off-the-shelf sensor devices validate MASK-BAN's great authentication capability and high-secret key generation rate.
Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression

Violence is a serious problems for cities like Chicago and has been exacerbated by the use of social media by gang-involved youths for taunting rival gangs. We present a corpus of tweets from a young and powerful female gang member and her communicators, which we have annotated with discourse intention, using a deep read to understand how and what triggered conversations to escalate into aggression. We use this corpus to develop a part-of-speech tagger and phrase table for the variant of English that is used, as well as a classifier for identifying tweets that express grieving and aggression.
Communicating Civic Engagement : Contrasting Models of Citizenship in the Youth Web Sphere

Communication aimed at promoting civic engagement may become problematic when citizen roles undergo historic changes. In the current era, younger generations are embracing more expressive styles of actualizing citizenship defined around peer content sharing and social media, in contrast to earlier models of dutiful citizenship based on one-way communication managed by authorities. An analysis of 90 youth Web sites operated by diverse civic and political organizations in the United States reveals uneven conceptions of citizenship and related civic skills, suggesting that many established organization are out of step with changing civic styles.
Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets

Imitation learning has traditionally been applied to learn a single task from demonstrations thereof. The requirement of structured and isolated demonstrations limits the scalability of imitation learning approaches as they are difficult to apply to real-world scenarios, where robots have to be able to execute a multitude of tasks. In this paper, we propose a multi-modal imitation learning framework that is able to segment and imitate skills from unlabelled and unstructured demonstrations by learning skill segmentation and imitation learning jointly. The extensive simulation results indicate that our method can efficiently separate the demonstrations into individual skills and learn to imitate them using a single multi-modal policy. The video of our experiments is available at http://sites.google.com/view/nips17intentiongan.
A vision based P300 Brain Computer Interface for grasping using a wheelchair-mounted robotic arm

In this paper, we present a novel vision based interface for selecting an object using a Brain Computer Interface (BCI), and grasping it using a robotic arm mounted to a powered wheelchair. As issuing commands through BCI is slow, this system was designed to allow a user to perform a complete task using the robotic system via the BCI issuing as few commands as possible, without losing concentration on the stimuli or the task. A scene image is captured by a camera mounted on the wheelchair, from which a dynamically sized non-uniform stimulus grid is created using edge information. Dynamically sized grids improve object selection efficiency. Oddball paradigm and P300 event related potentials (ERP) are used to select stimuli, the stimuli being each cell in the grid. Once selected, object segmentation and matching is used to identify the object. Then the user, using BCI, chooses an action to be performed on the object via the wheelchair mounted robotic arm (WMRA). Tests on 6 healthy human subjects validated the functionality of the system. An average accuracy of 85.56% was achieved for stimuli selection over all subjects. With the proposed system, it took the users an average of 5 commands to grasp an object. The system will eventually be useful for completely paralyzed or locked-in patients for performing activities of daily living (ADL) tasks.
Closed-form solution for winding types of axial flux permanent magnet machines

This research attempts to find a new closed-form solution of toroid and overlapping windings for axial flux permanent magnet machines. The proposed solution includes analytical derivations for winding lengths, resistances, and inductances as functions of fundamental airgap flux density and inner-to-outer diameter ratio. Furthermore, phase back-EMFs, phase terminal voltages, and efficiencies are calculated and compared for both winding types. Finite element analysis is used to validate the accuracy of the proposed analytical calculations. The proposed solution should assist machine designers to ascertain benefits and limitations of toroid and overlapping winding types as well as to get faster results.
Going Back to Basics in Design: From the IT Artifact to the IS Artifact

Playing a central role in the information-systems research community’s discourse on design science has been the concept of the “IT artifact.” We pose the alternative concept of the “IS artifact.” We “unpack” what has been called the “IT artifact” into a separate “information artifact” and “technology artifact” that, together with a “social artifact,” interact to form the “IS artifact.” We illustrate the value of the “IS artifact” concept with material from two cases. The result is to restore the idea that design science needs to attend to the design of the entire IS artifact, not just the IT artifact.
Core stability training on lower limb balance strength.

This study aimed to assess the effects of core stability training on lower limbs' muscular asymmetries and imbalances in team sport. Twenty footballers were divided into two groups, either core stability or control group. Before each daily practice, core stability group (n = 10) performed a core stability training programme, while control group (n = 10) did a standard warm-up. The effects of the core stability training programme were assessed by performing isokinetic tests and single-leg countermovement jumps. Significant improvement was found for knee extensors peak torque at 3.14 rad · s(-1) (14%; P < 0.05), knee flexors peak torque at 1.05 and 3.14 rad · s(-1) (19% and 22% with P < 0.01 and P < 0.01, respectively) and peak torque flexors/extensors ratios at 1.05 and 3.14 rad · s(-1) (7.7% and 8.5% with P < 0.05 and P < 0.05, respectively) only in the core stability group. The jump tests showed a significant reduction in the strength asymmetries in core stability group (-71.4%; P = 0.02) while a concurrent increase was seen in the control group (33.3%; P < 0.05). This study provides practical evidence in combining core exercises for optimal lower limbs strength balance development in young soccer players.
A Ka-band 4-ch bi-directional CMOS T/R chipset for 5G beamforming system

This paper presents a Ka-band 4-channel bi-directional T/R chipset in 65 nm CMOS technology for 5G beamforming system. The proposed T/R chipset can provide bi-directional operation with moderate gain and dual polarization. Each channel consists of bi-directional gain blocks, a 5-bit step attenuator and a 5-bit phase shifter including tuning bits. The phase and attenuation coverage are 348° with the LSB of 11.25° and 31 dB with the LSB of 1 dB, respectively. The gain of 13 dB (Tx mode) and 6 dB (Rx mode) are achieved at 28 GHz including the 4-way power divider/combiner.
Joint Latent Dirichlet Allocation for Social Tags

Social tags, serving as a textual source of simple but useful semantic metadata to reflect the user preference or describe the web objects, has been widely used in many applications. However, social tags have several unique characteristics, i.e., sparseness and data coupling (i.e., non-IIDness), which makes existing text analysis methods such as LDA not directly applicable. In this paper, we propose a new generative algorithm for social tag analysis named joint latent Dirichlet allocation, which models the generation of tags based on both the users and the objects, and thus accounts for the coupling relationships among social tags. The model introduces two latent factors that jointly influence tag generation: the user's latent interest factor and the object's latent topic factor, formulated as user-topic distribution matrix and object-topic distribution matrix, respectively. A Gibbs sampling approach is adopted to simultaneously infer the above two matrices as well as a topic-word distribution matrix. Experimental results on four social tagging datasets have shown that our model is able to capture more reasonable topics and achieves better performance than five state-of-the-art topic models in terms of the widely used point-wise mutual information metric. In addition, we analyze the learnt topics showing that our model recovers more themes from social tags while LDA may lead the topic vanishing problems, and demonstrate its advantages in the social recommendation by evaluating the retrieval results with mean reciprocal rank metric. Finally, we explore the joint procedure of our model in depth to show the non-IID characteristic of social tagging process.
Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore

In this study, with Singapore as an example, we demonstrate how we can use mobile phone call detail record (CDR) data, which contains millions of anonymous users, to extract individual mobility networks comparable to the activity-based approach. Such an approach is widely used in the transportation planning practice to develop urban micro simulations of individual daily activities and travel; yet it depends highly on detailed travel survey data to capture individual activity-based behavior. We provide an innovative data mining framework that synthesizes the state-of-the-art techniques in extracting mobility patterns from raw mobile phone CDR data, and design a pipeline that can translate the massive and passive mobile phone records to meaningful spatial human mobility patterns readily interpretable for urban and transportation planning purposes. With growing ubiquitous mobile sensing, and shrinking labor and fiscal resources in the public sector globally, the method presented in this research can be used as a low-cost alternative for transportation and planning agencies to understand the human activity patterns in cities, and provide targeted plans for future sustainable development.
Efficient hardware implementation strategy for local normalization of fingerprint images

Global techniques do not produce satisfying and definitive results for fingerprint image normalization due to the non-stationary nature of the image contents. Local normalization techniques are employed, which are a better alternative to deal with local image statistics. Conventional local normalization techniques involve pixelwise division by the local variance and thus have the potential to amplify unwanted noise structures, especially in low-activity background regions. To counter the background noise amplification, the research work presented here introduces a correction factor that, once multiplied with the output of the conventional normalization algorithm, will enhance only the feature region of the image while avoiding the background area entirely. In essence, its task is to provide the job of foreground segmentation. A modified local normalization has been proposed along with its efficient hardware structure. On the way to achieve real-time hardware implementation, certain important computationally efficient approximations are deployed. Test results show an improved speed for the hardware architecture while sustaining reasonable enhancement benchmarks.
Management of Epidermolytic Ichthyosis in the Newborn.

Epidermolytic ichthyosis (EI) is a rare autosomal dominant genodermatosis that presents at birth as a bullous disease, followed by a lifelong ichthyotic skin disorder. Essentially, it is a defective keratinization caused by mutations of keratin 1 (KRT1) or keratin 10 (KRT10) genes, which lead to skin fragility, blistering, and eventually hyperkeratosis. Successful management of EI in the newborn period can be achieved through a thoughtful, directed, and interdisciplinary or multidisciplinary approach that encompasses family support. This condition requires meticulous care to avoid associated morbidities such as infection and dehydration. A better understanding of the disrupted barrier protection of the skin in these patients provides a basis for management with daily bathing, liberal emollients, pain control, and proper nutrition as the mainstays of treatment. In addition, this case presentation will include discussions on the pathophysiology, complications, differential diagnosis, and psychosocial and ethical issues.
Evaluation of zero-speed sensor using NiFe/CoFe multilayer thin films and twisted FeCoV wires

The fabrication and characterization of magnetic sensors consisting of double magnetic layers are described. Both thin film based material and wire based materials were used for the double layers. The sensor elements were fabricated by patterning NiFe/CoFe multilayer thin films. This thin film based sensor exhibited a constant output voltage per excitation magnetic field at frequencies down to 0.1 Hz. The magnetic sensor using a twisted FeCoV wire, the conventional material for the Wiegand effect, had the disadvantage of an asymmetric output voltage generated by an alternating magnetic field. It was found that the magnetic wire whose ends were both slightly etched exhibited a symmetric output voltage.
BALANCE: towards a usable pervasive wellness application with accurate activity inference

Technology offers the potential to objectively monitor people's eating and activity behaviors and encourage healthier lifestyles. BALANCE is a mobile phone-based system for long term wellness management. The BALANCE system automatically detects the user's caloric expenditure via sensor data from a Mobile Sensing Platform unit worn on the hip. Users manually enter information on foods eaten via an interface on an N95 mobile phone. Initial validation experiments measuring oxygen consumption during treadmill walking and jogging show that the system's estimate of caloric output is within 87% of the actual value. Future work will refine and continue to evaluate the system's efficacy and develop more robust data input and activity inference methods.
Capacitive micromachined ultrasonic transducer (CMUT) arrays for medical imaging

Capacitive micromachined ultrasonic transducers (CMUTs) bring the fabrication technology of standard integrated circuits into the field of ultrasound medical imaging. This unique property, combined with the inherent advantages of CMUTs in terms of increased bandwidth and suitability for new imaging modalities and high frequency applications, have indicated these devices as new generation arrays for acoustic imaging. The advances in microfabrication have made possible to fabricate, in few years, silicon-based electrostatic transducers competing in performance with the piezoelectric transducers. This paper summarizes the fabrication, design, modeling, and characterization of 1D CMUT linear arrays for medical imaging, established in our laboratories during the past 3 years. Although the viability of our CMUT technology for applications in diagnostic echographic imaging is demonstrated, the whole process from silicon die to final probe is not fully mature yet for successful practical applications.
Initial Validation of a Virtual Environment for Assessment of Memory Functioning: Virtual Reality Cognitive Performance Assessment Test

The current project is an initial attempt at validating the Virtual Reality Cognitive Performance Assessment Test (VRCPAT), a virtual environment-based measure of learning and memory. To examine convergent and discriminant validity, a multitrait-multimethod matrix was used in which we hypothesized that the VRCPAT's total learning and memory scores would correlate with other neuropsychological measures involving learning and memory but not with measures involving potential confounds (i.e., executive functions; attention; processing speed; and verbal fluency). Using a sequential hierarchical strategy, each stage of test development did not proceed until specified criteria were met. The 15-minute VRCPAT battery and a 1.5-hour in-person neuropsychological assessment were conducted with a sample of 30 healthy adults, between the ages of 21 and 36, that included equivalent distributions of men and women from ethnically diverse populations. Results supported both convergent and discriminant validity. That is, findings suggest that the VRCPAT measures a capacity that is (a) consistent with that assessed by traditional paper-and-pencil measures involving learning and memory and (b) inconsistent with that assessed by traditional paper-and-pencil measures assessing neurocognitive domains traditionally assumed to be other than learning and memory. We conclude that the VRCPAT is a valid test that provides a unique opportunity to reliably and efficiently study memory function within an ecologically valid environment.
A Dataset of Online Handwritten Assamese Characters

This paper describes the Tezpur University dataset of online handwritten Assamese characters. The online data acquisition process involves the capturing of data as the text is written on a digitizer with an electronic pen. A sensor picks up the pen-tip movements, as well as pen-up/pen-down switching. The dataset contains 8,235 isolated online handwritten Assamese characters. Preliminary results on the classification of online handwritten Assamese characters using the above dataset are presented in this paper. The use of the support vector machine classifier and the classification accuracy for three different feature vectors are explored in our research.
RCS Reduction With a Dual Polarized Self-Complementary Connected Array Antenna

In this paper, a wideband dual polarized self-complementary connected array antenna with low radar cross section (RCS) under normal and oblique incidence is presented. First, an analytical model of the multilayer structure is proposed in order to obtain a fast and reliable predimensioning tool providing an optimized design of the infinite array. The accuracy of this model is demonstrated thanks to comparative simulations with a full wave analysis software. RCS reduction compared to a perfectly conducting flat plate of at least 10 dB has been obtained over an ultrawide bandwidth of nearly 7:1 at normal incidence and 5:1 (3.8 to 19 GHz) at 60° in both polarizations. These performances are confirmed by finite element tearing and interconnecting computations of finite arrays of different sizes. Finally, the realization of a  $28 \times 28$  cell prototype and measurement results are detailed.
Impact of Yoga and Meditation on Cellular Aging in Apparently Healthy Individuals: A Prospective, Open-Label Single-Arm Exploratory Study

This study was designed to explore the impact of Yoga and Meditation based lifestyle intervention (YMLI) on cellular aging in apparently healthy individuals. During this 12-week prospective, open-label, single arm exploratory study, 96 apparently healthy individuals were enrolled to receive YMLI. The primary endpoints were assessment of the change in levels of cardinal biomarkers of cellular aging in blood from baseline to week 12, which included DNA damage marker 8-hydroxy-2'-deoxyguanosine (8-OH2dG), oxidative stress markers reactive oxygen species (ROS), and total antioxidant capacity (TAC), and telomere attrition markers telomere length and telomerase activity. The secondary endpoints were assessment of metabotrophic blood biomarkers associated with cellular aging, which included cortisol, β-endorphin, IL-6, BDNF, and sirtuin-1. After 12 weeks of YMLI, there were significant improvements in both the cardinal biomarkers of cellular aging and the metabotrophic biomarkers influencing cellular aging compared to baseline values. The mean levels of 8-OH2dG, ROS, cortisol, and IL-6 were significantly lower and mean levels of TAC, telomerase activity, β-endorphin, BDNF, and sirtuin-1 were significantly increased (all values p < 0.05) post-YMLI. The mean level of telomere length was increased but the finding was not significant (p = 0.069). YMLI significantly reduced the rate of cellular aging in apparently healthy population.
Texturing the "material turn" in interaction design

Advances in the creation of computational materials are transforming our thinking about relations between the physical and digital. In this paper we characterize this transformation as a "material turn" within the field of interaction design. Central to theorizing tangibility, we advocate supporting this turn by developing a vocabulary capable of articulating strategies for computational material design. By exploring the term texture, a material property signifying relations between surfaces, structures, and forms, we demonstrate how concepts spanning the physical and digital benefit interaction design. We ground texture in case study of the Icehotel, a spectacular frozen edifice. The site demonstrates how a mundane material can be re-imagined as precious and novel. By focusing on the texture of ice, designers craft its extension into the realm of computational materiality. Tracing this process of aligning the physical and digital via the material and social construction of textures speaks back to the broader field of interaction design. It demonstrates how the process of crafting alliances between new and old materials requires both taking seriously the materialities of both, and then organizing their relation in terms of commonalities rather than differences. The result is a way of speaking about computational materials through a more textured lens.
A single-phase PLL algorithm with disturbances immunity

This paper proposes a new closed-loop synchronization algorithm, PLL (Phase-Locked Loop), for applications in power conditioner systems for single-phase networks. The structure presented is based on the correlation of the input signal with a complex signal generated from the use of an adaptive filter in a PLL algorithm in order to minimize the computational effort. Moreover, the adapted PLL presents a higher level of rejection for two particular disturbances: interharmonic and subharmonic, when compared to the original algorithm. Simulation and experimental results will be presented in order to prove the efficacy of the proposed adaptive algorithm.