nils-herrmann/clean_scirepeval huggingface dataset:
Series elastic actuation of an elbow rehabilitation exoskeleton with axis misalignment adaptation

Powered exoskeletons can facilitate rehabilitation of patients with upper limb disabilities. Designs using rotary motors usually result in bulky exoskeletons to reduce the problem of moving inertia. This paper presents a new linearly actuated elbow exoskeleton that consists of a slider crank mechanism and a linear motor. The linear motor is placed beside the upper arm and closer to shoulder joint. Thus better inertia properties can be achieved while lightweight and compactness are maintained. A passive joint is introduced to compensate for the exoskeleton-elbow misalignment and intersubject size variation. A linear series elastic actuator (SEA) is proposed to obtain accurate force and impedance control at the exoskeleton-elbow interface. Bidirectional actuation between exoskeleton and forearm is verified, which is required for various rehabilitation processes. We expect this exoskeleton can provide a means of robot-aided elbow rehabilitation.
Generation Alpha at the Intersection of Technology, Play and Motivation

This paper considers the intersection of technology and play through the novel approach of gamification and its application to early years education. The intrinsic connection between play and technology is becoming increasingly significant in early years education. By creating an awareness of the early years adoption of technology into guiding frameworks, and then exploring the makeup of gaming elements, this paper draws connections for guiding principles in adopting more technology-focused play opportunities for Generation Alpha.
Practice management guidelines for management of hemothorax and occult pneumothorax.

Thoracic trauma is a notable cause of morbidity and mortality in American trauma centers, where 25% of traumatic deaths are related to injuries sustained within the thoracic  Chest injuries occur in 60% of polytrauma cases; therefore, a rough estimate of the occurrence of hemothorax related to trauma in the United States approaches 300,000 cases per year.2 The management of hemothorax and pneumothorax has been a complex problem since it was first described over 200 years ago. Although the majority of chest trauma can be managed nonoperatively, there are several questions surrounding the management of hemothorax and occult pneumothorax that are not as easily answered. The technologic advances have raised the question of what to do with incidentally found hemothorax and pneumothorax discovered during the trauma evaluation. Previously, we were limited by our ability to visualize quantities 500 mL of blood on chest radiograph. Now that smaller volumes of blood can be visualized via chest computed tomography (CT), the management of these findings presents interesting clinical questions. In addition to early identification of these processes, these patients often find themselves with late complications such as retained hemothorax and empyema. The approach to these complex problems continues to evolve. Finally, as minimally invasive surgery grows and finds new applications, there are reproducible benefits to the patients in pursuing these interventions as both a diagnostic and therapeutic interventions. Video-assisted thoracoscopic surgery (VATS) has a growing role in the management of trauma patients.
Image Steganography: Classification, Application and Algorithms

Steganography is the technique/science of hiding information inside some innocent looking canvas like images. The growth of internet and communication technology has enabled the demand to send a message as safely and as securely as possible. In the last few years, we have seen that new and powerful steganography techniques reported in the literature. This paper intends to give an overview of image steganography, its applications and techniques. The paper gives the description of various techniques used in steganography and attempts to identify the requirements of a good steganography algorithm. Index Terms –Least Significant Bits (LSB), Peak Signal-to-Noise Rate (PSNR), Mean Square Error (MSE), Steganalysis.
Development of active phased array antenna for high SHF wideband massive MIMO in 5G

In the 5th generation mobile communication system, large system capacity, low latency and massive connection will be provided for novel and various applications. In order to realize these features, we are developing high SHF band massive-MIMO system which can secure wide system bandwidth and high spectral efficiency. Especially, the combination of analog beamforming (APAA: Active Phased Array Antenna) and digital MIMO signal processing for the multi-beam multiplexing is one of the promising approaches for reducing the complexity and power consumption. In this paper, hybrid beamforming configuration for high SHF band massive-MIMO system will be shown. Additionally the developed results of fundamental technologies such as array antenna panel and RF components are presented.
Biomarkers of Response to Immune Modulatory Therapies in Cancer

Immune modulatory antibody-based therapies serve to augment and direct the endogenous immune response against cancer. Significant efficacy has been demonstrated in multiple subtypes of solid and haematological malignancies. Despite great promise, responses are limited to a fraction of treated patients highlighting the need to decipher underlying mechanisms of response and resistance. Here we review progress in this area with a focus on the identification of candidate predictive biomarkers of response.
Structure-preserving image completion with multi-level dynamic patches

In this paper, we present a novel structure-preserving image completion approach equipped with dynamic patches. We formulate the image completion problem into an energy minimization framework that accounts for coherence within the hole and global coherence simultaneously. The completion of the hole is achieved through iterative optimizations combined with a multi-scale solution. In order to avoid abnormal structure and disordered texture, we utilize a dynamic patch system to achieve efficient structure restoration. Our dynamic patch system functions in both horizontal and vertical directions of the image pyramid. In the horizontal direction, we conduct a parallel search for multi-size patches in each pyramid level and design a competitive mechanism to select the most suitable patch. In the vertical direction, we use large patches in higher pyramid level to maximize the structure restoration and use small patches in lower pyramid level to reduce computational workload. We test our approach on massive images with complex structure and texture. The results are visually pleasing and preserve nice structure. Apart from effective structure preservation, our approach outperforms previous state-of-the-art methods in time consumption.
Defect detection on hardwood logs using high resolution three-dimensional laser scan data

The location, type, and severity of external defects on hardwood logs and stems are the primary indicators of overall log quality and value. External defects provide hints about the internal log characteristics. Defect data would improve the sawyer's ability to process logs such that a higher valued product (lumber) is generated. Using a high-resolution laser log scanner, we scanned and digitally photographed 162 red-oak and yellow-poplar logs. By means of a new robust estimator that performs circle fitting, a residual image is extracted from laser scan data that are corrupted by extreme outliers induced by the scanning equipment and loose bark. The residuals provide information to identify defects with height differentiation from the log surface. Combining simple shape definition rules with the height map allows most severe defects to be detected by determining the contour levels of a residual image. In addition, bark texture changes can be examined such that defects not associated with a height change might be detected.
A Survey of MANET Intrusion Detection & Prevention Approaches for Network Layer Attacks

In the last decade, mobile ad hoc networks (MANETs) have emerged as a major next generation wireless networking technology. However, MANETs are vulnerable to various attacks at all layers, including in particular the network layer, because the design of most MANET routing protocols assumes that there is no malicious intruder node in the network. In this paper, we present a survey of the main types of attack at the network layer, and we then review intrusion detection and protection mechanisms that have been proposed in the literature. We classify these mechanisms as either point detection algorithms that deal with a single type of attack, or as intrusion detection systems (IDSs) that can deal with a range of attacks. A comparison of the proposed protection mechanisms is also included in this paper. Finally, we identify areas where further research could focus.
An Intelligent Traffic Light Monitor System using an Adaptive Associative Memory

The traffic in urban areas is mainly regularized by traffic lights, which may contribute to the unnecessary long waiting times for vehicles if not efficiently configured. This inefficient configuration is unfortunately still the case in a lot of urban areas, where most of the traffic lights are based on a 'fixed cycle' protocol. To improve the traffic light configuration, this paper proposed monitoring system to be as an additional component (or additional subsystem) to the intelligent traffic light system, this component will be able to determine three street cases (empty street case, normal street case and crowded street case) by using small associative memory. The proposed monitoring system is working in two phases: training phase and recognition phase. The experiments presented promising results when the proposed approach was applied by using a program to monitor one intersection in Penang Island in Malaysia. The program could determine all street cases with different weather conditions depending on the stream of images, which are extracted from the streets video cameras. In addition, the observations which are pointed out to the proposed approach show a high flexibility to learn all the street cases using a few training images, thus the adaptation to any intersection can be done quickly.
FPGA side-channel receivers

The popularity of FPGAs is rapidly growing due to the unique advantages that they offer. However, their distinctive features also raise new questions concerning the security and communication capabilities of an FPGA-based hardware platform. In this paper, we explore the some of the limits of FPGA side-channel communication. Specifically, we identify a previously unexplored capability that significantly increases both the potential benefits and risks associated with side-channel communication on an FPGA: an in-device receiver. We designed and implemented three new communication mechanisms: speed modulation, timing modulation and pin hijacking. These non-traditional interfacing techniques have the potential to provide reliable communication with an estimated maximum bandwidth of 3.3 bit/sec, 8 Kbits/sec, and 3.4 Mbits/sec, respectively.
The Importance of Change Management after ERP Implementation: An Information Capability Perspective

When firms implement enterprise resource planning, they need to redesign their business processes to make information flow smooth within organizations. ERP thus results in changes in processes and responsibilities. Firms cannot realize expected returns from ERP investments unless these changes are effectively managed after ERP systems are put into operation. This research proposes a conceptual framework to highlight the importance of the change management after firms implement ERP systems. Our research model is empirically tested using data collected from over 170 firms that had used ERP systems for more than one year. Our analysis reveals that the eventual success of ERP systems depends on effective change management after ERP implementation, supporting the existence of the valley of despair.
Recent advances in autism research as reflected in DSM-5 criteria for autism spectrum disorder.

This article provides a selective review of advances in scientific knowledge about autism spectrum disorder (ASD), using DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, fifth edition) diagnostic criteria as a framework for the discussion. We review literature that prompted changes to the organization of ASD symptoms and diagnostic subtypes in DSM-IV, and we examine the rationale for new DSM-5 specifiers, modifiers, and severity ratings as well as the introduction of the diagnosis of social (pragmatic) communication disorder. Our goal is to summarize and critically consider the contribution of clinical psychology research, along with that of other disciplines, to the current conceptualization of ASD.
Multi-criteria design of 6-DoF fully-constrained cable driven redundant parallel manipulator

The purpose of this paper is to optimize dimensions of KNTU 6-DoF cable driven redundant parallel manipulators. This manipulator is under investigation for possible high-speed application such as object manipulator. Usage of cable parallel manipulator depends on kinematic characteristic and control algorithm. This optimization is based on different performance indices including the singularity measure, the kinematic sensitivity, the stiffness and free collision workspace. Stiffness of the cable is also taken into consideration because of its effect on kinematic stiffness of moving platform manipulators performance. Points with cable collision, singular or actuator wrench infeasible configuration characteristic are eliminating from entire workspace.
A survey of the applications of text mining in financial domain

Text mining has found a variety of applications in diverse domains. Of late, prolific work is reported in using text mining techniques to solve problems in financial domain. The objective of this paper is to provide a state-of-the-art survey of various applications of Text mining to finance. These applications are categorized broadly into FOREX rate prediction, stock market prediction, customer relationship management (CRM) and cyber security. Since finance is a service industry, these problems are paramount in operational and customer growth aspects. We reviewed 89 research papers that appeared during the period 2000-2016, highlighted some of the issues, gaps, key challenges in this area and proposed some future research directions. Finally, this review can be extremely useful to budding researchers in this area, as many open problems are highlighted.
Overview of directed energy weapon developments

In future defence scenarios directed energy weapons are of increasing interest. Therefore national and international R&D programs are increasing their activities on laser and high power microwave technologies in the defence and anti terror areas. The paper gives an overview of the German R&D programmes on directed energy weapons. A solid state medium energy weapon laser (MEL) is investigated at Rheinmetall for i.e. anti air defence applications up to distances of about 7 km. Due to the small volume these Lasers can be integrated as a secondary weapon system into mobile platforms such as AECVs. The beam power of a MEL is between 1 kW and 100 kW. The electric energy per pulse is in the kJ range. A burst of only a few pulses is needed to destroy optronics of targets in a distance up to 7 km. The electric energy requirements of a MEL system are low. High energy density pulsed power technologies are already available for the integration into a medium sized vehicle. The paper gives an overview on the MEL technologies which are under investigation in order to introduce a technology demonstrator at the end of 2005. The electric requirements at the interface to the power bus of a vehicle are presented. Finally an integration concept as a secondary weapon in a medium sized vehicle is given and discussed. In close cooperation with Diehl Munitionssysteme high power microwave technologies are investigated. Different kinds of HPM Sources are under development for defence and anti terror applications. It is the goal to introduce first prototype systems within a short time frame. The paper gives a brief overview on the different source technologies currently under investigation. The joint program concentrates on ultra wide band and damped sinus HPM waveforms in single shot and repetitive operation. Radiation powers up to the Gigawatt range are realized up to now. By presenting some characteristic scenarios for those HPM systems the wide range of applications is proven in the paper.
Introgression genetics and breeding between Upland and Pima cotton: a review

The narrow genetic base of elite Upland cotton (Gossypium hirsutum L.) germplasm has been a significant impediment to sustained progress in the development of cotton cultivars to meet the needs of growers and industry in recent years. The prospect of widening the genetic base of Upland cotton by accessing the genetic diversity and fiber quality of Pima cotton (Gossypium barbadense L.) has encouraged interspecific hybridization and introgression efforts for the past century. However, success is limited due mainly to genetic barriers between the two species in the forms of divergent gene regulatory systems, accumulated gene mutations, gene order rearrangements and cryptic chromosomal structure differences that have resulted in hybrid breakdown, hybrid sterility and selective elimination of genes. The objective of this paper is to provide a mini-review in interspecific hybridization between Upland and Pima cotton relevant to breeding under the following sections: (1) qualitative genetics; (2) cytogenetic stocks; (3) quantitative genetics; (4) heterosis, and (5) introgression breeding. Case studies of successful examples are provided.
Clustered-dot color halftone watermarks using spatial frequency and color separability

A framework for clustered-dot color halftone watermarking is proposed. Watermark patterns are embedded in the color halftone on per-separation basis. For typical CMYK printing systems, common desktop RGB color scanners are unable to provide the individual colorant halftone separations, which confounds per-separation detection methods. Not only does the K colorant consistently appear in the scanner channels as it absorbs uniformly across the spectrum, but cross-couplings between CMY separations are also observed in the scanner color channels due to unwanted absorptions. We demonstrate that by exploiting spatial frequency and color separability of clustered-dot color halftones, estimates of the individual colorant halftone separations can be obtained from scanned RGB images. These estimates, though not perfect, allow per-separation detection to operate efficiently. The efficacy of this methodology is demonstrated using continuous phase modulation for the embedding of per-separation watermarks.
Understanding factors affecting perceived sociability of social software

Sociability is considered to be important to the success of social software. The goal of the current study is to identify factors that affect the users’ perception of the sociability of social software and to examine the impact of sociability on the users’ attitude and behavior intentions. In a pilot study, 35 web users were interviewed to gain understanding of how they use social software to supplement their social life and to explore the possible factors that influence the users’ utilization of social software. In the first study, a questionnaire was developed, and 163 valid responses were collected. From the factor analysis results, seven important factors for social software design emerged, which accounts for 63.3% of the total variance. In the second study, 246 participants were asked to evaluate one of ten popular social applications with respect to the seven factors, their perceived sociability, and their attitudes and intention regarding the use of the applications. Results show that sociability is influenced by social climate, benefits and purposes, people, interaction richness, self-presentation, and support for formal interaction. System competency is not a sociability factor, but it significantly influences the user’s experience. Sociability and system competency, when combined, can predict 43% of users’ attitude towards social software and 51% of their intentions to use social software.
A monotonic and continuous two-dimensional warping based on dynamic programming

A novel two-dimensional warping algorithm is presented which searches for the optimal pixel mapping subject to continuity and monotonicity constraints. These constraints enable us to preserve topological structure in images. The search algorithm is based on dynamic programming (DP). As implementation techniques, acceleration by beam search and excessive warp suppression by penalty and/or range limitation are investigated. Experimental results show that this method provides successful warpings between images.
An empirical comparison of supervised learning algorithms

A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog Project in the early 90's. We present a large-scale empirical comparison between ten supervised learning methods: SVMs, neural nets, logistic regression, naive bayes, memory-based learning, random forests, decision trees, bagged trees, boosted trees, and boosted stumps. We also examine the effect that calibrating the models via Platt Scaling and Isotonic Regression has on their performance. An important aspect of our study is the use of a variety of performance criteria to evaluate the learning methods.
Financial Cryptography and Data Security

Smart contracts are computer programs that can be consistently executed by a network of mutually distrusting nodes, without the arbitration of a trusted authority. Because of their resilience to tampering , smart contracts are appealing in many scenarios, especially in those which require transfers of money to respect certain agreed rules (like in financial services and in games). Over the last few years many platforms for smart contracts have been proposed, and some of them have been actually implemented and used. We study how the notion of smart contract is interpreted in some of these platforms. Focussing on the two most widespread ones, Bitcoin and Ethereum, we quantify the usage of smart contracts in relation to their application domain. We also analyse the most common programming patterns in Ethereum, where the source code of smart contracts is available.
Annealed Generative Adversarial Networks

Generative Adversarial Networks (GANs) have recently emerged as powerful generative models. GANs are trained by an adversarial process between a generative network and a discriminative network. It is theoretically guaranteed that, in the nonparametric regime, by arriving at the unique saddle point of a minimax objective function, the generative network generates samples from the data distribution. However, in practice, getting close to this saddle point has proven to be difficult, resulting in the ubiquitous problem of “mode collapse”. The root of the problems in training GANs lies on the unbalanced nature of the game being played. Here, we propose to level the playing field and make the minimax game balanced by “heating” the data distribution. The empirical distribution is frozen at temperature zero; GANs are instead initialized at infinite temperature, where learning is stable. By annealing the heated data distribution, we initialized the network at each temperature with the learnt parameters of the previous higher temperature. We posited a conjecture that learning under continuous annealing in the nonparametric regime is stable, and proposed an algorithm in corollary. In our experiments, the annealed GAN algorithm, dubbed β-GAN, trained with unmodified objective function was stable and did not suffer from mode collapse.