nils-herrmann/clean_scirepeval huggingface dataset:
A 665μW silicon photomultiplier-based NIRS/EEG/EIT monitoring asic for wearable functional brain imaging

Functional brain imaging is considered a powerful and practical solution for understanding the brain and neurological diseases. While EEG is an established method for non-invasive electrical activity, electrical-impedance tomography (EIT) and near-infrared spectroscopy (NIRS) can additionally measure impedance changes and hemodynamic processes. To facilitate long-term multi-channel brain imaging in a wearable form factor without cabling overhead, there is a need for low-power local amplifiers  to support all these modalities. The main principle of optical hemodynamic measurements is to send light pulses into the tissue and measure the reflected light, which is modulated by the oxygen levels in the blood . State-of-the-art NIRS ICs typically consume a few mW, primarily for the LEDs to meet the required light sensitivity at the photodiodes (PDs). Silicon photomultipliers (SiPMs) are promising alternatives because they have excellent low-light detection capabilities, speed of response and higher detection efficiency in both visible and near infrared range . Hence, SiPMs allow deeper brain sensing depth and the possibility to sample consistent cerebral regions with larger inter-optode distance. This benefit would significantly reduce the number of NIRS channels and the associated power for a wearable NIRS device. Although SiPMs require a higher bias voltage (∼30V) than PDs, they achieve similar NIRS responses with a few hundred times less LED current. This results in a low-power NIRS ASIC and an overall power-efficient system. Existing optical sensing ICs are not suitable for a SiPM because of its large and variable output current. Trimming-based calibration methods  suffer from drift over time. Auto-zeroing by swapping an integrator capacitor [4][5] compensates ambient light at the cost of the integrator's headroom. Apart from ambient light, the dynamic range (DR) of the amplifier is also limited by a large NIRS signal, leading to a power-hungry readout.
StreamOp: An Innovative Middleware for Supporting Data Management and Query Functionalities over Sensor Network Streams Efficiently

During the last decade, a lot of progress has happened in the field of autonomous embedded devices (also known as motes) and wireless sensor networks. In this context, we envision next-generation systems to have autonomous database management functionalities on each mote, for supporting easy management of data on flash disks, adequate querying capabilities, and ubiquitous computing with no-effort. Following this major vision, in this paper we describe application scenarios, middleware approach and data management algorithms of a novel system, called Stream Operation (StreamOp), which effectively and efficiently realizes the depicted challenges. In particular, StreamOp supports heterogeneity, i.e. It works on top of different platforms, efficiency, i.e. It returns responses quickly, and autonomy, i.e. It saves battery power. We show how StreamOp provides these features, along with some experimental results that clearly validate our main assumptions.
Smart home design based on ZigBee wireless sensor network

This work is based on the Internet of Things and ZigBee wireless sensor network technology. A kind of smart home design based on ZigBee wireless sensor network was proposed in this paper. Texas Instruments MCU device LM3S9B96, which is the ARM Cortex-M3 based controllers, was used in this system. The entire system is running on the μC/OS-II embedded real-time multitasking operating system. Users can access this system by a dynamic webpage of LwIP TCP/IP protocol stack or GSM SMS. Using this system users can conveniently know the environment parameters of home, such as temperature, humidity, meter readings, light, and control the home electronic equipments, such as light, aircondition, heater, by ZigBee wireless sensor network.
Wormhole Attack Detection in Wireless Networks

Wormhole attacks can destabilize or disable wireless sensor networks. In a typical wormhole attack, the attacker receives packets at one point in the network, forwards them through a wired or wireless link with less latency than the network links, and relays them to another point in the network. We first propose a centralized algorithm to detect wormholes and show its correctness rigorously. For the distributed wireless network, we proposes DAWN, Distributed detection Algorithm against Wormhole in wireless Network coding systems, by exploring the change of the flow directions of the innovative packets caused by wormholes. We find that the robustness depends on the node density in the network, and prove a necessary condition to achieve collision-resistance. Our solutions only depend on the local information that can be obtained from regular network coding protocols, and thus the overhead that our algorithms introduce is acceptable for most applications.
Prediction of Personality First Impressions With Deep Bimodal LSTM

From job interviews to first dates, a first impression can make or break an interaction. People form judgments in the first 100 ms of interaction [24]. Can an AI predict apparent personality traits given a short video? In this work we propose a Deep Bimodal Regression LSTM model that extracts temporally ordered visual and audio features from a video clip to predict an average person ’s first impression on video subject’s Big-Five personality traits: Openness, Conscientiousness, Extroversion, Agreeableness and Neuroticism (OCEAN). Our model is trained and evaluated on HD Youtube videos provided by ChaLearn LAP APA2016 dataset [2].It achieves excellent performance that is comparable with the top teams in the 2016 competition on average accuracy, and outperforms these top teams on two categories: Openness and Conscientiousness.
A Single-Stage Single-Switch LED Driver Based on the Integrated SEPIC Circuit and Class-E Converter

A novel high-power-factor single-stage single-switch light-emitting diodes (LEDs) driver for street lighting system is proposed in this paper. By integrating the single-ended primary-inductor converter (SEPIC) power factor correction circuit and Class-E resonant dc/dc converter, the proposed converter exhibits extreme simplicity and high reliability, as there is only one active power switch. The LED driver could achieve nearly a unit power factor by operating the SEPIC circuit at discontinuous conduction mode. With careful parameters design of a single Class-E resonant converter, the proposed converter can achieve soft-switching characteristics, which could significantly reduce the switching losses and greatly improve the system efficiency. Operational principle, analytical results, and design considerations at 100 kHz are presented, and a 100-W laboratory prototype is proposed to verify the theoretical analysis, whose efficiency is as high as 91.2% in full-load state under 110 VAC input.
Face Detection: A Survey

In this paper we present a comprehensive and critical survey of face detection algorithms. Face detection is a necessary first-step in face recognition systems, with the purpose of localizing and extracting the face region from the background. It also has several applications in areas such as content-based image retrieval, video coding, video conferencing, crowd surveillance, and intelligent human–computer interfaces. However, it was not until recently that the face detection problem received considerable attention among researchers. The human face is a dynamic object and has a high degree of variability in its apperance, which makes face detection a difficult problem in computer vision. A wide variety of techniques have been proposed, ranging from simple edge-based algorithms to composite high-level approaches utilizing advanced pattern recognition methods. The algorithms presented in this paper are classified as either feature-based or image-based and are discussed in terms of their technical approach and performance. Due to the lack of standardized tests, we do not provide a comprehensive comparative evaluation, but in cases where results are reported on common datasets, comparisons are presented. We also give a presentation of some proposed applications and possible application areas.
Multi-Level Security Embedded With Surveillance System

Graveness of guarding is an essential component of any system or organization in an increasingly hacking environment. Layers of protection are necessary. This paper presents a model to develop a multilevel security system. To reach or access inner most circle, three stages of security system endorsement will be necessary, making it the primary level of security. These include the Hex Keypad, Bluetooth, and RFID. The valuables in the inner vault are further secured with a secondary system completely separate from the primary, consisting of a fingerprint scanner. Any security breach detected will alert the authorities with the help of a GSM Shield, therefore taking the necessary response immediately. Continuous surveillance with online streaming is also demonstrated using Raspberry Pi and a digital camera, further safeguarding the valuables.
Urogenital tract disorders in children suspected of being sexually abused.

Child sexual abuse (CSA) is generally defined as child exploitation that leads to achievement of sexual satisfaction. According to data from European countries, sexual abuse of children affects 10-40% of girls and 5-20% of boys.



The Medline, and Web of Science databases were searched with no date limitation on May 2015 using the terms 'child abuse' in conjunction with 'urinary tract', 'urologist', 'urological dysfunction', 'urologic symptoms', 'LUTS' or 'urinary infection'.



Awareness of the CSA problem among paediatricians and urologists is very important, because they are often the only physicians who are able to recognize the problem. CSA diagnosis is possible only through the proper collection of a medical history and a thorough physical examination. Urologists have to remember that children exposed to sexual abuse rarely exhibit abnormal genital findings. In fact, absence of genital findings is the rule rather than the exception. In most cases, the final diagnosis of sexual abuse is based on the child's history and behavior, along with the onset and exacerbation of urologic symptoms.



In this article, we present a review of studies and literature concerning urinary symptoms in sexually abused children to clarify the problem for a broad group of urologists. We present common symptoms and premises that can point to the right diagnosis and basic guidelines of proceeding after suspicion of abuse.
Fast and accurate link prediction in social networking systems

Online social networks (OSNs) recommend new friends to registered users based on local-based features of the graph (i.e. based on the number of common friends that two users share). However, OSNs do not exploit all different length paths of the network. Instead, they consider only pathways of maximum length 2 between a user and his candidate friends. On the other hand, there are global-based approaches, which detect the overall path structure in a network, being computationally prohibitive for huge-sized social networks. In this paper we provide friend recommendations, also known as the link prediction problem, by traversing all paths of a limited length, based on the “algorithmic small world hypothesis”. As a result, we are able to provide more accurate and faster friend recommendations. We also derive variants of our method that apply to different types of networks (directed/undirected and signed/unsigned). We perform an extensive experimental comparison of the proposed method against existing link prediction algorithms, using synthetic and three real data sets (Epinions, Facebook and Hi5). We also show that a significant accuracy improvement can be gained by using information about both positive and negative edges. Finally, we discuss extensively various experimental considerations, such as a possible MapReduce implementation of FriendLink algorithm to achieve scalability.
Surface Plasmon Resonance Imaging Sensors : A Review

Surface plasmon resonance (SPR) imaging sensors realize label free, real-time, highly sensitive, quantitative, high throughput biological interaction monitoring and the binding profiles from multi-analytes further provide the binding kinetic parameters between different bio-molecules. In the past two decades, SPR imaging sensors found rapid increasing applications in fundamental biological studies, medical diagnostics, drug discovery, food safety, precision measurement and environmental monitoring. In this paper, we review the recent advances of SPR imaging sensor technology towards high throughput multi-analyte screening. Finally, we describe our multiplex colorimetric SPR imaging biosensor based on polarization orientation for high throughput bio-sensing applications.
Scalable knowledge harvesting with high precision and high recall

Harvesting relational facts from Web sources has received great attention for automatically constructing large knowledge bases. Stateof-the-art approaches combine pattern-based gathering of fact candidates with constraint-based reasoning. However, they still face major challenges regarding the trade-offs between precision, recall, and scalability. Techniques that scale well are susceptible to noisy patterns that degrade precision, while techniques that employ deep reasoning for high precision cannot cope with Web-scale data.
 This paper presents a scalable system, called PROSPERA, for high-quality knowledge harvesting. We propose a new notion of ngram-itemsets for richer patterns, and use MaxSat-based constraint reasoning on both the quality of patterns and the validity of fact candidates.We compute pattern-occurrence statistics for two benefits: they serve to prune the hypotheses space and to derive informative weights of clauses for the reasoner. The paper shows how to incorporate these building blocks into a scalable architecture that can parallelize all phases on a Hadoop-based distributed platform. Our experiments with the ClueWeb09 corpus include comparisons to the recent ReadTheWeb experiment. We substantially outperform these prior results in terms of recall, with the same precision, while having low run-times.
Design, fabrication and preliminary results of a novel anthropomorphic hand for humanoid robotics: RCH-1

Among social infrastructure technologies, robot technology (RT) is expected to play an important role in solving the problems of both decrease of birth rate and increase of elderly people in the 21st century, specially but not only in Japan. In order to achieve this objective, the new generation of personal robots should be capable of a natural communication with humans by expressing human-like emotion. In this sense, human hands play a fundamental role in communication, because they have grasping, sensing and emotional expression ability. This paper presents the recent results of the collaboration between the Takanishi Lab of Waseda University, Tokyo, Japan, and the Arts Lab of Scuola Superiore Sant'Anna, Pisa, Italy, and ROBOCASA. In this paper, the development of a novel anthropomorphic hand for humanoid robotics RCH-1 (ROBOCASA Hand No.1) and its integration into a humanoid robotic platform, named WE-4RII (Waseda Eye No.4 Refined II) is presented.
Efficient Broadcast in Structured P2P Networks

In this position paper, we present an efficient algorithm for performing a broadcast operation with minimal cost in structured DHT-based P2P networks. In a system of N nodes, a broadcast message originating at an arbitrary node reaches all other nodes after exactlyN−1 messages. We emphasize the perception of a class of DHT systems as a form of distributed k-ary search and we take advantage of that perception in constructing a spanning tree that is utilized for efficient broadcasting. We consider broadcasting as a basic service that adds to existing DHTs the ability to search using arbitrary queries as well as dissiminate/collect global information.
Fast Image Deconvolution using Hyper-Laplacian Priors

This document is supplementary material to our NIPS 2009 pap er  of the same name. While we choose to solve the w sub-problem (Eqn. 5) in  using a LUT or analytically (for s ome specific values ofα), a number of numerical alternatives exist. The simplest an d f stest approach is to use Newton-Raphson (NR) to find the roots of the polynomials in Eq . 10 and Eqn 11 of . As shown in Table 1,4 iterations of NR take a similar time to our analytic solution . However, the numerical algorithm has poor stability, particularly when the polynomi als skim the x-axis. In practice, we found it gave spurious solutions around 1-2% of the time, an unacce ptable rate given the iterative nature of our overall algorithm. Applying NR directly to Eqn. 5 of [1] i s similarly unreliable. Although techniques with greater stability than NR exist, they are comput ationally more expensive. For example, we also compare to Matlab’s roots command, based on solving an eigenvalue problem, but this was several orders of magnitude slower than our analytic app ro ch.
Analysis and Detection of Fake Views in Online Video Services

Online video-on-demand(VoD) services invariably maintain a view count for each video they serve, and it has become an important currency for various stakeholders, from viewers, to content owners, advertizers, and the online service providers themselves. There is often significant financial incentive to use a robot (or a botnet) to artificially create fake views. How can we detect fake views? Can we detect them (and stop them) efficiently? What is the extent of fake views with current VoD service providers? These are the questions we study in this article. We develop some algorithms and show that they are quite effective for this problem.
An efficient ontology comparison tool for semantic Web applications

With the growing access to heterogeneous and independent data repositories, determining the semantic difference of two ontologies is critical in information retrieval, information integration and semantic web applications. In this paper, we propose an ontology comparison tool based on a novel senses refinement algorithm, which builds a senses set to accurately represent the semantics of the input ontology. The senses refinement algorithm automatically extracts senses from the electronic lexical database WordNet (locally installed or online), removes unnecessary senses based on the relationship among the entity classes of the ontology, and specifies relations and constraints of the concepts in the refined senses set. The senses refinement converts the measurement of ontology difference into simple set operations based on set theory, thus ensures the efficiency and accuracy of the ontology comparison. Our experimental studies show that the proposed senses refinement algorithm outperforms the naive senses set construction algorithm in terms of efficiency and accuracy
Semi-supervised feature learning for improving writer identification

Data augmentation is usually used by supervised learning approaches for offline writer identification, but such approaches require extra training data and potentially lead to overfitting errors. In this study, a semi-supervised feature learning pipeline was proposed to improve the performance of writer identification by training with extra unlabeled data and the original labeled data simultaneously. Specifically, we proposed a weighted label smoothing regularization (WLSR) method for data augmentation, which assigned the weighted uniform label distribution to the extra unlabeled data. The WLSR method could regularize the convolutional neural network (CNN) baseline to allow more discriminative features to be learned to represent the properties of different writing styles. The experimental results on well-known benchmark datasets (ICDAR2013 and CVL) showed that our proposed semisupervised feature learning approach could significantly improve the baseline measurement and perform competitively with existing writer identification approaches. Our findings provide new insights into offline write identification.
Biohybrid robot powered by an antagonistic pair of skeletal muscle tissues

Biohybrid robots are attracting attention as promising candidates to enhance robot applicability to studies on biological designs and in vitro construction of biological dynamic systems. Rapid progress in biohybrid robots with skeletal muscle tissues formed on a flexible substrate has enabled various types of locomotion powered by muscle tissue. However, it has been difficult to achieve high levels of both large and long-term actuations of the skeletal muscle tissues because of their spontaneous shrinkage through the course of the tissue culture. To overcome this limitation, we adapted the concept of biological systems and developed a biohybrid robot actuated by an antagonistic pair of skeletal muscle tissues. Our robot achieved large actuation (~90° of rotation of a joint) by selective contractions of the skeletal muscle tissues and a long lifetime (~1 week) by balancing tensions of the antagonistic tissues to prevent the spontaneous shrinkage. As a demonstration, we showed that our biohybrid robots allowed a pick-and-place manipulation of objects. This research may provide a platform to exceed the limitations of design in conventional biohybrid robots and replicate various lifelike movements.
The impact of embedded wafer level BGA package on the antenna performance

In this article, we present a study about the impact of embedded wafer level ball grid array (eWLB) on characteristics of antenna. The antenna in package is a promising solution for integration of antennas and eWLB technology enables integration of passive components and antennas into the redistribution layer (RDL). The antenna radiates perpendicular to the package in broadside into the package. There are different parameters such as size, shape, and thickness of the eWLB package which affect the radiation pattern significantly. Moreover, the materials properties of package like relative permittivity (εr) and loss tangent (tanδ) impact the impedance bandwidth, gain and efficiency of antenna and have to be taken into account. The other important parameter to design the antenna in package is the distance of antenna to the reflector. We present the feasibility of an antenna with backside metallization as an integrated reflector in an 8 mm × 8 mm eWLB package. The measurement and simulation results show that eWLB is an attractive candidate for mm-wave applications.