nils-herrmann/clean_scirepeval huggingface dataset:
Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch with Generator Constraints

This paper proposes a Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients (MPSO-TVAC) for solving economic load dispatch (ELD) problem. Due to prohibited operating zones (POZ) and ramp rate limits of the practical generators, the ELD problems become nonlinear and nonconvex optimization problem. Furthermore, the ELD problem may be more complicated if transmission losses are considered. Particle swarm optimization (PSO) is one of the famous heuristic methods for solving nonconvex problems. However, this method may suffer to trap at local minima especially for multimodal problem. To improve the solution quality and robustness of PSO algorithm, a new best neighbour particle called ‘rbest’ is proposed. The rbest provides extra information for each particle that is randomly selected from other best particles in order to diversify the movement of particle and avoid premature convergence. The effectiveness of MPSO-TVAC algorithm is tested on different power systems with POZ, ramp-rate limits and transmission loss constraints. To validate the performances of the proposed algorithm, comparative studies have been carried out in terms of convergence characteristic, solution quality, computation time and robustness. Simulation results found that the proposed MPSO-TVAC algorithm has good solution quality and more robust than other methods reported in previous work.
CoReCast: Collision Resilient Broadcasting in Vehicular Networks

Reliable and timely delivery of periodic V2V (vehicle-to-vehicle) broadcast messages is essential for realizing the benefits of connected vehicles. Existing MAC protocols for ad hoc networks fall short of meeting these requirements. In this paper, we present, CoReCast, the first collision embracing protocol for vehicular networks. CoReCast provides high reliability and low delay by leveraging two unique opportunities: no strict constraint on energy consumption, and availability of GPS clocks to achieve near-perfect time and frequency synchronization.
 Due to low coherence time, the channel changes rapidly in vehicular networks. CoReCast embraces packet collisions and takes advantage of the channel dynamics to decode collided packets. The design of CoReCast is based on a preamble detection scheme that estimates channels from multiple transmitters without any prior information about them. The proposed scheme reduces the space and time requirement exponentially than the existing schemes. The system is evaluated through experiments with USRP N210 and GPS devices placed in vehicles driven on roads in different environments as well as using trace-driven simulations. It provides 15x and 2x lower delay than 802.11p and OCP (Omniscient Clustering Protocol), respectively. Reliability of CoReCast is 8x and 2x better than 802.11p and OCP, respectively.
Twitter Reveals: Using Twitter Analytics to Predict Public Protests

The right to protest is perceived as one of the primary civil rights. Citizens participate in mass demonstrations to express themselves and exercise their democratic rights. However, because of the large number of participants, protests may lead to violence and destruction, and hence can be costly. Thus it is important to predict such demonstrations in advance to safeguard against such damages. Recent research has shown that about 75 percent of protests that are regarded as legal, are planned in advance. Twitter, the prominent micro-blogging website, has been used as a tool by protestors for planning, organizing, and announcing many of the recent protests worldwide such as those that led to the Arab Spring, Britain riots, and those against Mr. Trump after the presidential election in the U.S. In this paper, we aim to predict protests by means of machine learning algorithms. In particular, we consider the case of protests against the then-president-elect Mr. Trump after the results of the presidential election were announced in November 2016. We first identify the hashtags calling for demonstration from Trending Topics on Twitter, and download the corresponding tweets. We then apply four machine learning algorithms to make predictions. Our findings indicate that Twitter can be used as a powerful tool for predicting future protests with an average prediction accuracy of over 75% (up to 100%). We further validate our model by predicting the protests held in the U.S. airports after President Trump’s executive order banning citizens of seven Muslim countries from entering the U.S. An important contribution of our study is the inclusion of event-specific features for prediction purposes which helps to achieve high levels of accuracy.
Shoulder Surfing attack in graphical password authentication

Information and computer security is supported largely by passwords which are the principle part of the authentication process. The most common computer authentication method is to use alphanumerical username and password which has significant drawbacks. To overcome the vulnerabilities of traditional methods, visual or graphical password schemes have been developed as possible alternative solutions to text-based scheme. A potential drawback of graphical password schemes is that they are more vulnerable to shoulder surfing than conventional alphanumeric text passwords. When users input their passwords in a public place, they may be at risk of attackers stealing their password. An attacker can capture a password by direct observation or by recording the individual’s authentication session. This is referred to as shouldersurfing and is a known risk, of special concern when authenticating in public places. In this paper we will present a survey on graphical password schemes from 2005 till 2009 which are proposed to be resistant against shoulder surfing attacks.
Paralympic athletes with cerebral palsy display altered pacing strategies in distance-deceived shuttle running trials.

This study investigated performance and physiology to understand pacing strategies in elite Paralympic athletes with cerebral palsy (CP). Six Paralympic athletes with CP and 13 able-bodied (AB) athletes performed two trials of eight sets of 10 shuttles (total 1600m). One trial was distance-deceived (DEC, 1000 m + 600 m) one trial was nondeceived (N-DEC, 1600 m). Time (s), heart rate (HR, bpm), ratings of perceived exertion (RPE, units), and electromyography of five bilateral muscles (EMG) were recorded for each set of both trials. The CP group ran slower than the AB group, and pacing differences were seen in the CP DEC trial, presenting as a flat pacing profile over the trial (P < 0.05). HR was higher and RPE was lower in the CP group in both trials (P < 0.05). EMG showed small differences between groups, sides, and trials. The present study provides evidence for a possible pacing strategy underlying exercise performance and fatigue in CP. The results of this study show (1) underperformance of the CP group, and (2) altered pacing strategy utilization in the CP group. We proposed that even at high levels of performance, the residual effects of CP may negatively affect performance through selection of conservative pacing strategies during exercise.
A Semantic-Based Approach for Artist Similarity

This paper describes and evaluates a method for computing artist similarity from a set of artist biographies. The proposed method aims at leveraging semantic information present in these biographies, and can be divided in three main steps, namely: (1) entity linking, i.e. detecting mentions to named entities in the text and linking them to an external knowledge base; (2) deriving a knowledge representation from these mentions in the form of a semantic graph or a mapping to a vector-space model; and (3) computing semantic similarity between documents. We test this approach on a corpus of 188 artist biographies and a slightly larger dataset of 2,336 artists, both gathered from Last.fm. The former is mapped to the MIREX Audio and Music Similarity evaluation dataset, so that its similarity judgments can be used as ground truth. For the latter dataset we use the similarity between artists as provided by the Last.fm API. Our evaluation results show that an approach that computes similarity over a graph of entities and semantic categories clearly outperforms a baseline that exploits word co-occurrences and latent factors.
Populated IP addresses: classification and applications

Populated IP addresses (PIP) -- IP addresses that are associated with a large number of user requests are important for online service providers to efficiently allocate resources and to detect attacks. While some PIPs serve legitimate users, many others are heavily abused by attackers to conduct malicious activities such as scams, phishing, and malware distribution. Unfortunately, commercial proxy lists like Quova have a low coverage of PIP addresses and offer little support for distinguishing good PIPs from abused ones. In this study, we propose PIPMiner, a fully automated method to extract and classify PIPs through analyzing service logs. Our methods combine machine learning and time series analysis to distinguish good PIPs from abused ones with over 99.6% accuracy. When applying the derived PIP list to several applications, we can identify millions of malicious Windows Live accounts right on the day of their sign-ups, and detect millions of malicious Hotmail accounts well before the current detection system captures them.
Actuation of prosthetic drive using EMG signal

Myoelectric or electromyogram (EMG) signals can be useful in intelligently recognizing intended limb motion of a person. This paper presents an attempt to develop a four-channel EMG signal acquisition system as part of an ongoing research in the development of an active prosthetic device. The acquired signals are used for identification and classification of six unique movements of hand and wrist, viz. hand open, hand close, wrist flexion, wrist extension, ulnar deviation and radial deviation. This information is used for actuation of prosthetic drive. The time domain features are extracted, and their dimension is reduced using principal component analysis. The reduced features are classified using two different techniques: k nearest neighbor and artificial neural networks, and the results are compared.
Artificial Immune Classifier Based on ELLipsoidal Regions (AICELL) †

Pattern classification is a central problem in machine learning, with a wide array of applications, and rule-based classifiers are one of the most prominent approaches. Among these classifiers, Incremental Rule Learning algorithms combine the advantages of classic Pittsburg and Michigan approaches, while, on the other hand, classifiers using fuzzy membership functions often result in systems with fewer rules and better generalization ability. To discover an optimal set of rules, learning classifier systems have always relied on bio-inspired models, mainly genetic algorithms. In this paper we propose a classification algorithm based on an efficient bio-inspired approach, Artificial Immune Networks. The proposed algorithm encodes the patterns as antigens, and evolves a set of antibodies, representing fuzzy classification rules of ellipsoidal surface, to cover the problem space. The innate immune mechanisms of affinity maturation and diversity preservation are modified and adapted to the classification context, resulting in a classifier that combines the advantages of both incremental rule learning and fuzzy classifier systems. The algorithm is compared to a number of state-of-the-art rule-based classifiers, as well as Support Vector Machines (SVM), producing very satisfying results, particularly in problems with large number of attributes and classes.
Micro-Expression Recognition Using Color Spaces

Micro-expressions are brief involuntary facial expressions that reveal genuine emotions and, thus, help detect lies. Because of their many promising applications, they have attracted the attention of researchers from various fields. Recent research reveals that two perceptual color spaces (CIELab and CIELuv) provide useful information for expression recognition.  In this paper, we further show that CIELab and CIELuv are also helpful in recognizing micro-expressions, and we indicate why these three color spaces achieve better performance. A micro-expression color video clip is treated as a fourth-order tensor, i.e., a four-dimension array. The first two dimensions are the spatial information, the third is the temporal information, and the fourth is the color information. We transform the fourth dimension from RGB into TICS, in which the color components are as independent as possible. The combination of dynamic texture and independent color components achieves a higher accuracy than does that of RGB. In addition, we define a set of regions of interests (ROIs) based on the facial action coding system and calculated the dynamic texture histograms for each ROI. Experiments are conducted on two micro-expression databases, CASME and CASME 2, and the results show that the performances for TICS, CIELab, and CIELuv are better than those for RGB or gray.
Kirigami robot: Making paper robot using desktop cutting plotter and inkjet printer

Much attention has recently been given to a printing method because they are easily designable, have a low cost, and can be mass produced. Numerous electronic devices are fabricated using printing methods because of these advantages. In paper mechatronics, attempts have been made to fabricate robots by printing on paper substrates. The robots are given structures through self-folding and functions using printed actuators. We developed a new system and device to fabricate more sophisticated printed robots. First, we successfully fabricated complex self-folding structures by applying an automatic cutting. Second, a rapidly created and low-voltage electrothermal actuator was developed using an inkjet printed circuit. Finally, a printed robot was fabricated by combining two techniques and two types of paper; a structure design paper and a circuit design paper. Gripper and conveyor robots were fabricated, and their functions were verified. These works demonstrate the possibility of paper mechatronics for rapid and low-cost prototyping as well as of printed robots.
Design of a passive , iso-elastic upper limb exoskeleton for gravity compensation

An additional mechanical mechanism for a passive parallelogram-based exoskeleton arm-support is presented. It consists of several levers and joints and an attached extension coil spring. The additional mechanism has two favourable features. On the one hand it exhibits an almost iso-elastic behaviour whereby the lifting force of the mechanism is constant for a wide working range. Secondly, the value of the supporting force can be varied by a simple linear movement of a supporting joint. Furthermore a standard tension spring can be used to gain the desired behavior. The additional mechanism is a 4-link mechanism affixed to one end of the spring within the parallelogram arm-support. It has several geometrical parameters which influence the overall behaviour. A standard optimisation routine with constraints on the parameters is used to find an optimal set of geometrical parameters. Based on the optimized geometrical parameters a prototype was constructed and tested. It is a lightweight wearable system, with a weight of 1.9 kg. Detailed experiments reveal a difference between measured and calculated forces. These variations can be explained by a 60 % higher pre load force of the tension spring and a geometrical offset in the construction.
Effects of material properties of femoral hip components on bone remodeling.

Bone loss around femoral hip stems is one of the problems threatening the long-term fixation of uncemented stems. Many believe that this phenomenon is caused by reduced stresses in the bone (stress shielding). In the present study the mechanical consequences of different femoral stem materials were investigated using adaptive bone remodeling theory in combination with the finite element method. Bone-remodeling in the femur around the implant and interface stresses between bone and implant were investigated for fully bonded femoral stems. Cemented stems (cobalt-chrome or titanium alloy) caused less bone resorption and lower interface stresses than uncemented stems made from the same materials. The range of the bone resorption predicted in the simulation models was from 23% in the proximal medial cortex surrounding the cemented titanium alloy stem to 76% in the proximal medial cortex around the uncemented cobalt-chrome stem. Very little bone resorption was predicted around a flexible, uncemented "iso-elastic" stem, but the proximal interface stresses increased drastically relative to the stiffer uncemented stems composed of cobalt-chrome or titanium alloy. However, the proximal interface stress peak was reduced and shifted during the adaptive remodeling process. The latter was found particularly in the stiffer uncemented cobalt-chrome-molybdenum implant and less for the flexible iso-elastic implant.
Production of tropane alkaloids in diploid and tetraploid plants and in vitro hairy root cultures of Egyptian henbane (Hyoscyamus muticus L.)

In this study, the effects of ploidy level and culture medium were studied on the production of tropane alkaloids. We have successfully produced stable tetraploid hairy root lines of Hyoscyamus muticus and their ploidy stability was confirmed 30 months after transformation. Tetraploidy affected the growth rate and alkaloid accumulation in plants and transformed root cultures of Egyptian henbane. Although tetraploid plants could produce 200% higher scopolamine than their diploid counterparts, this result was not observed for corresponding induced hairy root cultures. Culture conditions did not only play an important role for biomass production, but also significantly affected tropane alkaloid accumulation in hairy root cultures. In spite of its lower biomass production, tetraploid clone could produce more scopolamine than the diploid counterpart under similar growth conditions. The highest yields of scopolamine (13.87 mg l−1) and hyoscyamine (107.7 mg 1−1) were obtained when diploid clones were grown on medium consisting of either Murashige and Skoog with 60 g/l sucrose or Gamborg’s B5 with 40 g/l sucrose, respectively. Although the hyoscyamine is the main alkaloid in the H. muticus plants, manipulation of ploidy level and culture conditions successfully changed the scopolamine/hyoscyamine ratio towards scopolamine. The fact that hyoscyamine is converted to scopolamine is very important due to the higher market value of scopolamine.
Linear IgA bullous dermatosis: report of five cases in Chile.

Linear IgA bullous dermatosis (LABD) is an acquired autoimmune sub-epidermal vesiculobullous disease characterized by continuous linear IgA deposit on the basement membrane zone, as visualized on direct immunofluorescence microscopy. LABD can affect both adults and children. The disease is very uncommon, with a still unknown incidence in the South American population.



All confirmed cases of LABD by histological and immunofluorescence in our hospital were studied.



The confirmed cases were three females and two males, aged from 8 to 87 years. Precipitant events associated with LABD were drug consumption (non-steroid inflammatory agents in two cases) and ulcerative colitis (one case). Most of our patients were treated with dapsone, resulting in remission.



Our series confirms the heterogeneous clinical features of this uncommon disease in concordance with a larger series of patients reported in the literature.
Experimental and computational analysis of microscale shrouded coaxial rotor in hover

Experimental and computational studies of the hovering performance of microcoaxial shrouded rotors were carried out. The ATI Mini Multi-Axis Force/Torque Transducer system was used to measure all six components of the force and moment. Meanwhile, numerical simulation of flow field around rotor was carried out using sliding mesh method and multiple reference frame technique by ANASYS FLUENT. The computational results were well agreed with experimental data. Several important factors, such as blade pitch angle, rotor spacing and tip clearance, which influence the performance of shrouded coaxial rotor are studied in detail using CFD method in this paper. Results shows that, evaluated in terms of Figure of Merit, open coaxial rotor is suited for smaller pitch angle condition while shrouded coaxial rotor is suited for larger pitch angle condition. The negative pressure region around the shroud lip is the main source of the thrust generation. In order to have a better performance for shrouded coaxial rotor, the tip clearance must be smaller. The thrust sharing of upper- and lower-rotor is also discussed in this paper.
Optimal boundaries for Poisson mesh merging

Existing Poisson mesh editing techniques mainly focus on designing schemes to propagate deformation from a given boundary condition to a region of interest. Although solving the Poisson system in the least-squares sense distributes the distortion errors over the entire region of interest, large deformation in the boundary condition might still lead to severely distorted results. We propose to optimize the boundary condition (the merging boundary) for Poisson mesh merging. The user needs only to casually mark a source region and a target region. Our algorithm automatically searches for an optimal boundary condition within the marked regions such that the change of the found boundary during merging is minimal in terms of similarity transformation. Experimental results demonstrate that our merging tool is easy to use and produces visually better merging results than unoptimized techniques.
Design of flooding detection system based on velocity and water level DAM with ESP8266

Indonesia is a tropical country with high rainfall intensity and prone to flooding. In Indonesia the flood disaster has become one of the highest natural disasters in each year. To prevent flooding disaster is still done in conventional ways. One of them by building dams in the river to control the flow of water. However, the high intensity of rainfall, and the absence of soil absorption can result the volume of water in the dam exceed of capacity. In the conventional ways on every dam there is an officer who controls the water level directly. This way of direct observation is very inefficient and officers should always be in place. If the condition of water volume increases suddenly and the officer is not there, the flood information is not quickly conveyed. So that appropriate technology is needed in order to solve the problem. The ESP8266 is a micro controller with minimum power consumption. The ESP8266 also has wireless tools which can be integrated with internet networks. This ability makes the data sensors can be sent web servers and smart phone applications to inform the flooding alert.