nils-herrmann/clean_scirepeval huggingface dataset:
Smart homes automation using Z-wave protocol

The rapid development of information technology and computer networks make them part of almost everything in our daily life and it became impossible to abandon their use. One of the main and important applications of technology in homes is home automation including controlling and automation of electronic and electrical machines remotely. Wireless Home Automation Networks (WHANs) are used in homes to connect the different devices together and to the Internet. In order to control home devices remotely, there are many popular protocols such as INSTEON, ZigBee, and Home Plug. In this paper, we focus on the relatively new protocol called Z-Wave protocol and we discuss it development and applications in smart homes. This wireless protocol has many advantages over the popular and widely used ZigBee protocol as it provides better reliability, low radio rebirth, easy usage, and easy Interoperability.
Marker-based tracking with unmanned aerial vehicles

With the availability of low-cost micro aerial vehicles (MAVs), unmanned aerial vehicles (UAVs) quickly gain popularity and application potential. This requires techniques that can be understood by non-experts and flexibly applied for rapid prototyping. Visual tracking is an essential task with many applications, such as autonomous navigation and scene acquisition. While marker-less methods emerge, marker-based methods still have major advantages including simplicity, robustness, accuracy and performance. In practice, however, multi-marker setups introduce complexity and calibration efforts that can void the advantages. This work proposes a solution for practical, robust and easy-to-use marker-based tracking with independent compound targets. We introduce two novel target designs and describe pose estimation, noise removal and geometric transformations. The concepts are implemented in a tracking library for the Parrot AR. Drone 2.0. We explain its video access and camera calibration, and provide a first set of intrinsic parameters, jointly estimated from 14 units with high accuracy and low variance. The library is applied in a one-day contest on automatic visual navigation of UAVs, where students without technical background and programming skills achieved learning by experience and rapid development. This shows the effectiveness of combining capability with simplicity, and provides a case study on robotics in interdisciplinary education.
A* CCG Parsing with a Supertag and Dependency Factored Model

We propose a new A* CCG parsing model in which the probability of a tree is decomposed into factors of CCG categories and its syntactic dependencies both defined on bi-directional LSTMs. Our factored model allows the precomputation of all probabilities and runs very efficiently, while modeling sentence structures explicitly via dependencies. Our model achieves the stateof-the-art results on English and Japanese CCG
Geometric Algebra Model of Distributed Representations

Formalism based on GA is an alternative to distributed representation models developed so far — Smolensky’s tensor product, Holographic Reduced Representations (HRR) and Binary Spatter Code (BSC). Convolutions are replaced by geometric products, interpretable in terms of geometry which seems to be the most natural language for visualization of higher concepts. This paper recalls the main ideas behind the GA model and investigates recognition test results using both inner product and a clipped version of matrix representation. The influence of accidental blade equality on recognition is also studied. Finally, the efficiency of the GA model is compared to that of previously developed models.
Real-Time Gesture Interface Based on Event-Driven Processing From Stereo Silicon Retinas

We propose a real-time hand gesture interface based on combining a stereo pair of biologically inspired event-based dynamic vision sensor (DVS) silicon retinas with neuromorphic event-driven postprocessing. Compared with conventional vision or 3-D sensors, the use of DVSs, which output asynchronous and sparse events in response to motion, eliminates the need to extract movements from sequences of video frames, and allows significantly faster and more energy-efficient processing. In addition, the rate of input events depends on the observed movements, and thus provides an additional cue for solving the gesture spotting problem, i.e., finding the onsets and offsets of gestures. We propose a postprocessing framework based on spiking neural networks that can process the events received from the DVSs in real time, and provides an architecture for future implementation in neuromorphic hardware devices. The motion trajectories of moving hands are detected by spatiotemporally correlating the stereoscopically verged asynchronous events from the DVSs by using leaky integrate-and-fire (LIF) neurons. Adaptive thresholds of the LIF neurons achieve the segmentation of trajectories, which are then translated into discrete and finite feature vectors. The feature vectors are classified with hidden Markov models, using a separate Gaussian mixture model for spotting irrelevant transition gestures. The disparity information from stereovision is used to adapt LIF neuron parameters to achieve recognition invariant of the distance of the user to the sensor, and also helps to filter out movements in the background of the user. Exploiting the high dynamic range of DVSs, furthermore, allows gesture recognition over a 60-dB range of scene illuminance. The system achieves recognition rates well over 90% under a variety of variable conditions with static and dynamic backgrounds with naïve users.
Fuzzy Color Spaces: A Conceptual Approach to Color Vision

In this paper, we introduce formal definitions of the concepts of fuzzy color and fuzzy color space. First, we formalize the notion of fuzzy color for representing the correspondence between computational representation of colors and perceptual color categories identified by a color name. Second, we propose a methodology for learning fuzzy colors based on the paradigm of conceptual spaces, where prototypes are used for each category to be learnt. Since the conceptual space approach yields crisp categorizations, we introduce a novel methodology for defining fuzzy boundaries of color categories on the basis of a Voronoi tessellation of a color space. Finally, we also formalize the notion of fuzzy color space as the collection of fuzzy colors corresponding to the color categories employed in a certain context/application and/or for a specific user. Different typologies of fuzzy color spaces are proposed in order to be consistent with the nature of the categories we want to model. Our approach is illustrated by defining fuzzy color spaces using RGB with the Euclidean distance. Examples based on the well-known ISCC-NBS color naming system are presented, as well as others based on collections of color names and prototypes provided by users. The proposal is evaluated and compared with the most used approaches for color modeling. Additionally, a website located at  http://www.jfcssoftware.com including all experimentation data, software implementing our models, and additional materials is available to researchers in color modeling.
An algorithm for treatment of the drooping nose.

Nasal tip ptosis ("drooping" or long nose) occurs when the tip of the nose is more caudal than what is deemed ideal. Intrinsic factors, such as elongated or caudally-rotated lower lateral cartilages, can lead to nasal tip ptosis. Extrinsic factors, such as elongated upper lateral cartilages or excessive caudal anterior septum and heavy nasal skin, can push the nasal tip caudally and lead to drooping of the nasal tip. The loss of maxillary or nasal spine support may enhance the potential for tip ptosis. In addition, a hyperactive depressor nasi septi could, as a result of continuous pull on the tip, result in tip ptosis. Aging or previous nasal procedures (such as the Goldman-type tip surgery) where the continuity of the lateral and medial crura of the lower lateral cartilages have been violated may cause a weakening of the tip-supporting mechanisms and de-rotation of the nasal tip. Correction of this deformity is challenging and rewarding; it can resolve both the cosmetic deformity and nasal obstruction symptoms related to this entity. The goal of this article is to present our current principles of diagnosis and treatment of nasal tip ptosis, as well as to introduce and algorithm of preferred methods and techniques for its reliable and stable correction.



Correction of the nasal tip ptosis requires accurate diagnosis, a recognition of the interplay between various anatomic components, specific strategy planning, and a correction of anatomic abnormalities.
Educational Data Mining: A Review of the State of the Art

Educational data mining (EDM) is an emerging interdisciplinary research area that deals with the development of methods to explore data originating in an educational context. EDM uses computational approaches to analyze educational data in order to study educational questions. This paper surveys the most relevant studies carried out in this field to date. First, it introduces EDM and describes the different groups of user, types of educational environments, and the data they provide. It then goes on to list the most typical/common tasks in the educational environment that have been resolved through data-mining techniques, and finally, some of the most promising future lines of research are discussed.
Hashtag Recommendation Using Attention-Based Convolutional Neural Network

Along with the increasing requirements, the hashtag recommendation task for microblogs has been receiving considerable attention in recent years. Various researchers have studied the problem from different aspects. However, most of these methods usually need handcrafted features. Motivated by the successful use of convolutional neural networks (CNNs) for many natural language processing tasks, in this paper, we adopt CNNs to perform the hashtag recommendation problem. To incorporate the trigger words whose effectiveness have been experimentally evaluated in several previous works, we propose a novel architecture with an attention mechanism. The results of experiments on the data collected from a real world microblogging service demonstrated that the proposed model outperforms state-of-the-art methods. By incorporating trigger words into the consideration, the relative improvement of the proposed method over the state-of-theart method is around 9.4% in the F1-score.
Fast Hydraulic and Thermal Erosion on the GPU Balázs Jákó

Computer games, TV series, movies, simulators, and many other computer graphics applications use external scenes where a realistic looking terrain is a vital part of the viewing experience. Creating such terrains is a challenging task. In this paper we propose a method that generates realistic virtual terrains by simulation of hydraulic and thermal erosion on a predefined height field terrain. The model is designed to be executed interactively on parallel architectures like graphics processors.
An efficient authentication and key agreement protocol for 4G (LTE) networks

Long Term Evolution (LTE) networks designed by 3rd Generation Partnership Project (3GPP) represent a widespread technology. LTE is mainly influenced by high data rates, minimum delay and the capacity due to scalable bandwidth and its flexibility. With the rapid and widespread use LTE networks, and increase the use in data/video transmission and Internet applications in general, accordingly, the challenges of securing and speeding up data communication in such networks is also increased. Authentication in LTE networks is very important process because most of the coming attacks occur during this stage. Attackers try to be authenticated and then launch the network resources and prevent the legitimate users from the network services. The basics of Extensible Authentication Protocol-Authentication and Key Agreement (EAP-AKA) are used in LTE AKA protocol which is called Evolved Packet System AKA (EPS-AKA) protocol to secure LTE network, However it still suffers from various vulnerabilities such as disclosure of the user identity, computational overhead, Man In The Middle (MITM) attack and authentication delay. In this paper, an Efficient EPS-AKA protocol (EEPS-AKA) is proposed to overcome those problems. The proposed protocol is based on the Simple Password Exponential Key Exchange (SPEKE) protocol. Compared to previous proposed methods, our method is faster, since it uses a secret key method which is faster than certificate-based methods, In addition, the size of messages exchanged between User Equipment (UE) and Home Subscriber Server (HSS) is reduced, this reduces authentication delay and storage overhead effectively. The automated validation of internet security protocols and applications (AVISPA) tool is used to provide a formal verification. Results show that the proposed EEPS-AKA is efficient and secure against active and passive attacks.
Noise-Immune Embedded NAND-ROM Using a Dynamic Split Source-Line Scheme for VDDmin and Speed Improvements

Embedded NAND-type read-only-memory (NAND-ROM) provides large-capacity, high-reliability, on-chip non-volatile storage. However, NAND-ROM suffers from code-dependent read noises and cannot survive at low supply voltages (VDDs). These code-dependent read noises are primarily due to the charge-sharing effect, bitline leakage current, and crosstalk between bitlines, which become worse at lower VDD. This study proposes a dynamic split source-line (DSSL) scheme for NAND-ROM. The proposed scheme overcomes code-dependent read noises while improving the read access time and suppressing the active-mode gate leakage current, with only a 1% area penalty in the cell array. Experiments on a fabricated 256 Kb macro using a 90 nm industrial logic process demonstrate that the proposed DSSL scheme achieves 100% code-pattern coverage under a small sensing margin. Additionally, the DSSL NAND-ROM works with a wide range of supply voltages (1-0.31 V) with a 38%, 45.8%, and 37% improvement in speed, power, and standby current, respectively, at VDD = 1 V.
Simple and Complex Activity Recognition through Smart Phones

Due to an increased popularity of assistive healthcare technologies activity recognition has become one of the most widely studied problems in technology-driven assistive healthcare domain. Current approaches for smart-phone based activity recognition focus only on simple activities such as locomotion. In this paper, in addition to recognizing simple activities, we investigate the ability to recognize complex activities, such as cooking, cleaning, etc. through a smart phone. Features extracted from the raw inertial sensor data of the smart phone corresponding to the user's activities, are used to train and test supervised machine learning algorithms. The results from the experiments conducted on ten participants indicate that, in isolation, while simple activities can be easily recognized, the performance of the prediction models on complex activities is poor. However, the prediction model is robust enough to recognize simple activities even in the presence of complex activities.
Range-Based Localization in Wireless Networks Using Density-Based Outlier Detection

Node localization is commonly employed in wireless networks. For example, it is used to improve routing and enhance security. Localization algorithms can be classified as range-free or range-based. Range-based algorithms use location metrics such as ToA, TDoA, RSS, and AoA to estimate the distance between two nodes. Proximity sensing between nodes is typically the basis for range-free algorithms. A tradeoff exists since range-based algorithms are more accurate but also more complex. However, in applications such as target tracking, localization accuracy is very important. In this paper, we propose a new range-based algorithm which is based on the density-based outlier detection algorithm (DBOD) from data mining. It requires selection of the K-nearest neighbours (KNN). DBOD assigns density values to each point used in the location estimation. The mean of these densities is calculated and those points having a density larger than the mean are kept as candidate points. Different performance measures are used to compare our approach with the linear least squares (LLS) and weighted linear least squares based on singular value decomposition (WLS-SVD) algorithms. It is shown that the proposed algorithm performs better than these algorithms even when the anchor geometry about an unlocalized node is poor.
The “R.A.R.E.” Technique (Reverse and Repositioning Effect): The Renaissance of the Aging Face and Neck

Considering the fixed points of the face , and in light of the fact that gravity is one of the main factors involved in aging, a new alternative concept in cosmetic surgery is discussed in this paper. In our approach, rejuvenation of the face and neck involves two completely separate procedures. The whole face must be treated “homothetically”, with an upward (vertical) and deep (subperiosteal) approach, to preserve facial proportions and distances, thus preserving the original facial identity. The facial portion of our rejuvenation surgery becomes a single “en bloc” and “closed” procedure, correcting the sagging tissue in the lateral sector, between the fixed zones which must be preserved. The Malaris portion of the Orbicularis Oculi Muscle, (through its strong connections with the skin and the malar fat) has become the “key tool” of the rejuvenation of the whole face. Then, neck surgery becomes a completely distinct procedure, and is to be performed in an oblique/horizontal direction. We now seek to preserve the very firmly attached neck zones, which are the attachment of the posterior border of the fibrous platysma onto the S.C.M. (Sterno-Cleido-Mastoidien muscle). This will permit a more conservative and less aggressive neck surgery, without any sub-platysmal disection. Over 200 RARE procedures have been performed during almost four years. Improvement in terms of facial rejuvenation is dramatic and the technique is quite safe and predictable. The only possible difficulty involves the patient’s temporary initial concern about early postoperative appearance. Figure 1 Main fixed zones of the face and the neck, (per Furnas, 1989). 1: fixed conqua of the ear. 2: auriculoplatysmal ligament. 3: fixed adherences between the posterior border of the platysma and the S.C.M. muscle (per T.Besins). 4: mandibular ligament. 5: cutaneo-platysmal anterior ligament. 6: zygomatic ligaments.
BENCHMARKING DEEP LEARNING FRAMEWORKS FOR THE CLASSIFICATION OF VERY HIGH RESOLUTION SATELLITE MULTISPECTRAL DATA

In this paper we evaluated deep-learning frameworks based on Convolutional Neural Networks for the accurate classification of multispectral remote sensing data. Certain state-of-the-art models have been tested on the publicly available SAT-4 and SAT-6 high resolution satellite multispectral datasets. In particular, the performed benchmark included the AlexNet, AlexNet-small and VGG models which had been trained and applied to both datasets exploiting all the available spectral information. Deep Belief Networks, Autoencoders and other semi-supervised frameworks have been, also, compared. The high level features that were calculated from the tested models managed to classify the different land cover classes with significantly high accuracy rates i.e., above 99.9%. The experimental results demonstrate the great potentials of advanced deep-learning frameworks for the supervised classification of high resolution multispectral remote sensing data.
Adaptive Cruise Control System : Comparing Gain-Scheduling PI and LQ Controllers

Over the recent years, a considerable growth in the number of vehicles on the road has been observed. This increases importance of vehicle safety and minimization of fuel consumption, subsequently prompting manufacturers to equip cars, with more advanced features such as adaptive cruise control (ACC)or collision avoidance and collision warning system (CWS). This paper investigates two control applications design namely the gain scheduling proportionalintegral (GSPI) control and gain scheduling Linear Quadratic (GSLQ)control for ACC, covering a high range speed. The control system consist of two loops in cascade, with the inner loop controlling the vehicle speed and the outer loop switching between the cruise control (CC) and the ACC mode and calculating the reference speed. A nonlinear dynamic model of the vehicle is constructed and then a set of operating points is determined and then a of linear models is extracted in operating point. For each operating point, PI and LQ controllers are obtained off-line. An integrated Simulink model including the nonlinear dynamic vehicle model and the ACC controller (either PI or LQ) was used to test the controllers in various traffic scenarios. Comparison results between the two controllers applications is provided to show the validity of the design.
Externalising the autobiographical self: sharing personal memories online facilitated memory retention.

Internet technology provides a new means of recalling and sharing personal memories in the digital age. What is the mnemonic consequence of posting personal memories online? Theories of transactive memory and autobiographical memory would make contrasting predictions. In the present study, college students completed a daily diary for a week, listing at the end of each day all the events that happened to them on that day. They also reported whether they posted any of the events online. Participants received a surprise memory test after the completion of the diary recording and then another test a week later. At both tests, events posted online were significantly more likely than those not posted online to be recalled. It appears that sharing memories online may provide unique opportunities for rehearsal and meaning-making that facilitate memory retention.
Low-voltage low-power CMOS full adder - Circuits, Devices and Systems, IEE Proceedings-

Low-power design of VLSI circuits has been identified as a critical technological need in recent years due to the high demand for portable consumer electronics products. In this regard many innovative designs for basic logic functions using pass transistors and transmission gates have appeared in the literature recently. These designs relied on the intuition and cleverness of the designers, without involving formal design procedures. Hence, a formal design procedure for realising a minimal transistor CMOS pass network XOR-XNOR cell, that is fully compensated for threshold voltage drop in MOS transistors, is presented. This new cell can reliably operate within certain bounds when the power supply voltage is scaled down, as long as due consideration is given to the sizing of the MOS transistors during the initial design step. A low transistor count full adder cell using the new XOR-XNOR cell is also presented.
Simple broadband Gysel combiner with a single coupled line

A coupled-Gysel broadband combiner/divider is proposed and demonstrated. The new concept relies on using a single coupled line segment in the design. Significant improvement in bandwidth are realized while maintaining low-loss, ease of design, and flexibility. The coupled-Gysel is demonstrated with a 2.5 - 8 GHz (105% fractional bandwidth) divider with 0.1 dB divider loss, and a 3.4 - 10.2 GHz (100% fractional bandwidth) with 0.2 dB divider loss.
Magic Mirror: A virtual handbag shopping system

We present an augmented reality system based on Kinect for on-line handbag shopping. The users can virtually try on different handbags on a TV screen at home. They can interact with the virtual handbags naturally, such as sliding a handbag to different positions on their arms and rotating a handbag to see it from different angles. The users can also see how the handbags fit them in different virtual environments other than the current real background. We describe the technical details for building such a system and demonstrate the experimental results.