nils-herrmann/clean_scirepeval huggingface dataset:
An Optimisation Model for Airport Taxi Scheduling ?

In this paper we present an optimisation model for airport taxi scheduling. We introduce a mixed-integer programming formulation to represent the movement of aircraft on the surface of the airport. In the optimal schedule delays due to taxi conflicts are minimised. We discuss implementation issues for solving this optimisation problem. Numerical results with real data of Amsterdam Airport Schiphol demonstrate that the algorithms lead to significant improvements of the efficiency with reasonable computational effort.
Automatic Static Unpacking of Malware Binaries

Current malware is often transmitted in packed or encrypted form to prevent examination by anti-virus software.To analyze new malware, researchers typically resort to dynamic code analysis techniques to unpack the code for examination.Unfortunately, these dynamic techniques are susceptible to a variety of anti-monitoring defenses, as well as "time bombs" or "logic bombs," and can be slow and tedious to identify and disable. This paper discusses an alternative approach that relies on static analysis techniques to automate this process. Alias analysis can be used to identify the existence of unpacking,static slicing can identify the unpacking code, and control flow analysis can be used to identify and neutralize dynamic defenses. The identified unpacking code can be instrumented and transformed, then executed to perform the unpacking.We present a working prototype that can handle a variety of malware binaries, packed with both custom and commercial packers, and containing several examples of dynamic defenses.
15.4 A 0.8V 10b 80kS/s SAR ADC with duty-cycled reference generation

Autonomous wireless sensor nodes need low-power low-speed ADCs to digitize the sensed signal. State-of-art SAR ADCs can accomplish this goal with high power-efficiency (<;10fJ/conversion-step) [1-4]. The reference voltage design is critical for the ADC performance to obtain good PSRR, low line-sensitivity and a stable supply-independent full-scale range. However, solutions for efficient reference voltage generators (RVGs) are typically ignored in low-power ADC publications. In reality, due to the low power supply (usually sub-1 V) and limited available power (nW-range), the RVG is a challenge within the sensor system. In this work, a 2.4fJ/conversion-step SAR ADC with integrated reference is implemented. The 0.62V CMOS RVG consumes 25nW. To further reduce RVG power, it can be duty-cycled down to 10% with no loss in ADC performance. Additionally, the ADC uses a bidirectional dynamic comparator to improve the power efficiency even more.
SOCIAL COGNITIVE THEORY OF PERSONALITY

and Creative Modeling Modeling is not simply a process of response mimicry as commonly believed. Modeled judgments and actions may differ in specific content but embody the same rule. For example, a model may deal with moral dilemmas that differ widely in the nature of the activity but apply the same moral standard to them. Modeled activities thus convey rules for generative and innovative behavior. This higher level learning is achieved through abstract modeling. Once observers extract the rules underlying the modeled activities they can generate new behaviors that go beyond what they have seen or heard. Creativeness rarely springs entirely from individual inventiveness. A lot of modeling goes on in creativity. By refining preexisting innovations, synthesizing them into new ways and adding novel elements to them something new is created. When exposed to models of differing styles of thinking and behaving, observers vary in what they adopt from the different sources and thereby create new blends of personal characteristics that differ from the individual models (Bandura, Ross & Ross, 1963). Modeling influences that exemplify new perspectives and innovative styles of thinking also foster creativity by weakening conventional mind sets (Belcher, 1975; Harris & Evans, 1973).
Feature selection for text classification with Naïve Bayes

0957-4174/$ see front matter 2008  Corresponding author.  School of Compu ogy, Beijing Jiaotong University, Beijing 100044, Chin E-mail address: jnchen06@163.com (J. Chen). As an important preprocessing technology in text classification, feature selection can improve the scalability, efficiency and accuracy of a text classifier. In general, a good feature selection method should consider domain and algorithm characteristics. As the Naïve Bayesian classifier is very simple and efficient and highly sensitive to feature selection, so the research of feature selection specially for it is significant. This paper presents two feature evaluation metrics for the Naïve Bayesian classifier applied on multiclass text datasets: Multi-class Odds Ratio (MOR), and Class Discriminating Measure (CDM). Experiments of text classification with Naïve Bayesian classifiers were carried out on two multi-class texts collections. As the results indicate, CDM and MOR gain obviously better selecting effect than other feature selection approaches.
Liquid injectable silicone: a review of its history, immunology, technical considerations, complications, and potential.

For over five decades, liquid injectable silicone has been used for soft-tissue augmentation. Its use has engendered polarized reactions from the public and from physicians. Adherents of this product tout its inert chemical structure, ease of use, and low cost. Opponents of silicone cite the many reports of complications, including granulomas, pneumonitis, and disfiguring nodules that are usually the result of large-volume injection and/or industrial grade or adulterated material. Unfortunately, as recently as 2006, reports in The New England Journal of Medicine and The New York Times failed to distinguish between the use of medical grade silicone injected by physicians trained in the microdroplet technique and the use of large volumes of industrial grade products injected by unlicensed or unskilled practitioners. This review separates these two markedly different procedures. In addition, it provides an overview of the chemical structure of liquid injectable silicone, the immunology of silicone reactions within the body, treatment for cosmetic improvement including human immunodeficiency virus lipoatrophy, technical considerations for its injection, complications seen following injections, and some considerations of the future for silicone soft-tissue augmentation.
NAO-mark vs QR-code Recognition by NAO Robot Vision

Nowadays, the research on robot on-map localization while using landmarks is more intensively dealing with visual code recognition. One of the most popular landmarks of this type is the QR-code. This paper is devoted to the experimental evaluation of vision-based on-map localization procedures that apply QR-codes or NAO marks, as implemented in service robot control systems. In particular, the NAO humanoid robot is our test-bed platform, while the use of robotic systems for hazard detection is the motivation of this study. Especially, the robot can be a useful aid for elderly people affected by dementia and cognitive disorientation. The detection of the door opening is assumed to be important to ensure safety in the home environment. Thus, the paper focus on door opening detection while using QR-codes.
Wavelet-Based EEG Preprocessing for Biometric Applications

EEG signals, measuring transient brain activities, can be used as a source of biometric information with potential application in high-security person recognition scenarios. However, due to the inherent nature of these signals and the process used for their acquisition, their effective preprocessing is critical for their successful utilisation. In this paper we compare the effectiveness of different wavelet-based noise removal methods and propose an EEG-based biometric identification system which combines two such de-noising methods to enhance the signal preprocessing stage. In tests using 50 subjects from a public database, the proposed new approach is shown to provide improved identification performance over alternative techniques. Another important preprocessing consideration is the segmentation of the EEG record prior to de-noising. Different segmentation approaches were investigated and the trade-off between performance and computation time is explored. Finally the paper reports on the impact of the choice of wavelet function used for feature extraction on system performance.
Effects of mindfulness on psychological health: a review of empirical studies.

Within the past few decades, there has been a surge of interest in the investigation of mindfulness as a psychological construct and as a form of clinical intervention. This article reviews the empirical literature on the effects of mindfulness on psychological health. We begin with a discussion of the construct of mindfulness, differences between Buddhist and Western psychological conceptualizations of mindfulness, and how mindfulness has been integrated into Western medicine and psychology, before reviewing three areas of empirical research: cross-sectional, correlational research on the associations between mindfulness and various indicators of psychological health; intervention research on the effects of mindfulness-oriented interventions on psychological health; and laboratory-based, experimental research on the immediate effects of mindfulness inductions on emotional and behavioral functioning. We conclude that mindfulness brings about various positive psychological effects, including increased subjective well-being, reduced psychological symptoms and emotional reactivity, and improved behavioral regulation. The review ends with a discussion on mechanisms of change of mindfulness interventions and suggested directions for future research.
Setting Up Pepper For Autonomous Navigation And Personalized Interaction With Users

In this paper we present our work with the Pepper robot, a service robot from SoftBank Robotics. We had two main goals in this work: improving the autonomy of this robot by increasing its awareness of the environment; and enhance the robot ability to interact with its users. To achieve this goals, we used ROS, a modern open-source framework for developing robotics software, to provide Pepper with state of the art localization and navigation capabilities. Furthermore, we contribute an architecture for effective human interaction based on cloud services. Our architecture improves Pepper speech recognition capabilities by connecting it to the IBM Bluemix Speech Recognition service and enable the robot to recognize its user via an in-house face recognition web-service. We show examples of our successful integration of ROS and IBM services with Pepper’s own software. As a result, we were able to make Pepper move autonomously in a environment with humans and obstacles. We were also able to have Pepper execute spoken commands from known users as well as newlyintroduced users that were enrolled in the robot list of trusted users via a multi-modal interface.
Novel Modulation Strategies for Class-D Amplifier

Recent advances in semiconductor technology have renewed interest in class-D audio amplifiers, especially for portable devices and consumer electronics. In addition to higher efficiency, class-D amplifiers are smaller, lighter, streamlined, cool and quiet with extended battery life compared to the conventional linear amplifiers. A typical class-D amplifier increases the efficiency of amplifiers in consumer and professional applications from the industry norm of approximately 50 percent to 90 percents or better. In this paper, two zero voltage switching (ZVS) modulation strategies are proposed to achieve the goals of high fidelity and high efficiency. Field programmable gate array (FPGA) implementations of the proposed modulation strategies are also provided in this paper. In order to verify the correctness of the proposed methods, a FPGA-based class-D audio amplifier prototype is developed and realized. Experimental results are then presented to validate the proposed modulation strategies. According to the experimental results, the proposed test system is able to deliver more than 15 W into a 4 Omega load with an efficiency of 80% and total harmonic distortion (THD) less than 2 %.
Design of an electric series elastic actuated joint for robotic gait rehabilitation training

Robotic gait rehabilitation is at least as effective as conventional gait training in stroke survivors. Patients must be assisted as needed in order to improve affected gait patterns. The combination of impedance control and series elastic actuation is a viable actuation principle to be used for human robot interaction. Here, a new promising electric series elastic actuated joint is developed. The large torque bandwidth limit at 100 Nm is 6.9 Hz. With a total weight of 3.175 kg it is possible to directly mount the actuator on the exoskeleton frame. The actuator is capable of providing sufficient torque at normal walking speed. Full patient assistance during gait and free motions without impeding the gait pattern are possible. The actuator allows isometric measurements up to 100 Nm and the patient's progress in robotic rehabilitation can be evaluated.
Development and pilot testing of HEXORR: Hand EXOskeleton Rehabilitation Robot

Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased. This paper introduces a newly developed Hand Exoskeleton Rehabilitation Robot (HEXORR). This device has been designed to provide full range of motion (ROM) for all of the hand's digits. The thumb actuator allows for variable thumb plane of motion to incorporate different degrees of extension/flexion and abduction/adduction. Compensation algorithms have been developed to improve the exoskeleton's backdrivability by counteracting gravity, stiction and kinetic friction. We have also designed a force assistance mode that provides extension assistance based on each individual's needs. A pilot study was conducted on 9 unimpaired and 5 chronic stroke subjects to investigate the device's ability to allow physiologically accurate hand movements throughout the full ROM. The study also tested the efficacy of the force assistance mode with the goal of increasing stroke subjects' active ROM while still requiring active extension torque on the part of the subject. For 12 of the hand digits'15 joints in neurologically normal subjects, there were no significant ROM differences (P > 0.05) between active movements performed inside and outside of HEXORR. Interjoint coordination was examined in the 1st and 3rd digits, and no differences were found between inside and outside of the device (P > 0.05). Stroke subjects were capable of performing free hand movements inside of the exoskeleton and the force assistance mode was successful in increasing active ROM by 43 ± 5% (P < 0.001) and 24 ± 6% (P = 0.041) for the fingers and thumb, respectively. Our pilot study shows that this device is capable of moving the hand's digits through nearly the entire ROM with physiologically accurate trajectories. Stroke subjects received the device intervention well and device impedance was minimized so that subjects could freely extend and flex their digits inside of HEXORR. Our active force-assisted condition was successful in increasing the subjects' ROM while promoting active participation.
Optimization and architecture effects on GPU computing workload performance

It is unquestionable that successive hardware generations have significantly improved GPU computing workload performance over the last several years. Moore's law and DRAM scaling have respectively increased single-chip peak instruction throughput by 3X and off-chip bandwidth by 2.2X from NVIDIA's GeForce 8800 GTX in November 2006 to its GeForce GTX 580 in November 2010. However, raw capability numbers typically underestimate the improvements in real application performance over the same time period, due to significant architectural feature improvements. To demonstrate the effects of architecture features and optimizations over time, we conducted experiments on a set of benchmarks from diverse application domains for multiple GPU architecture generations to understand how much performance has truly been improving for those workloads. First, we demonstrate that certain architectural features make a huge difference in the performance of unoptimized code, such as the inclusion of a general cache which can improve performance by 2-4× in some situations. Second, we describe what optimization patterns have been most essential and widely applicable for improving performance for GPU computing workloads across all architecture generations. Some important optimization patterns included data layout transformation, converting scatter accesses to gather accesses, GPU workload regularization, and granularity coarsening, each of which improved performance on some benchmark by over 20%, sometimes by a factor of more than 5×. While hardware improvements to baseline unoptimized code can reduce the speedup magnitude, these patterns remain important for even the most recent GPUs. Finally, we identify which added architectural features created significant new optimization opportunities, such as increased register file capacity or reduced bandwidth penalties for misaligned accesses, which increase performance by 2× or more in the optimized versions of relevant benchmarks.
Anatomy of the Clitoris: Revision and Clarifications about the Anatomical Terms for the Clitoris Proposed (without Scientific Bases) by Helen O'Connell, Emmanuele Jannini, and Odile Buisson

The anatomy of the clitoris is described in human anatomy textbooks. Some researchers have proposal and divulged a new anatomical terminology for the clitoris. This paper is a revision of the anatomical terms proposed by Helen O'Connell, Emmanuele Jannini, and Odile Buisson. Gynecologists, sexual medicine experts, and sexologists should spread certainties for all women, not hypotheses or personal opinions, they should use scientific terminology: clitoral/vaginal/uterine orgasm, G/A/C/U spot orgasm, and female ejaculation, are terms that should not be used by sexologists, women, and mass media. Clitoral bulbs, clitoral or clitoris-urethrovaginal complex, urethrovaginal space, periurethral glans, Halban's fascia erogenous zone, vaginal anterior fornix erogenous zone, genitosensory component of the vagus nerve, and G-spot, are terms used by some sexologists, but they are not accepted or shared by experts in human anatomy. Sexologists should define have sex, make love, the situation in which the orgasm happens in both partners with or without a vaginal intercourse.
Object-oriented Analysis Using Natural Language Processing

There is often a wealth of extant domain-specific, natural-language data available to help guide developers of object-oriented systems. This data is generally amenable to natural language processing i n order to derive valuable design information. Howeve r, from a review of the field, we contend that current approaches have not been able to extract all the semantic and design detail that is present in such data. For instance: we see a lack of dynamic system representations; we detect reluctance for researche rs to adopt hybrid solutions where users confirm and elaborate automated analyses; and we suggest there is work needed to determine a comprehensive repertoire of potential relationships between system component s. In partial pursuit of such a manifesto, this paper mentions briefly our algorithmic proposal for processing natural language into UML with supplemental user involvement.
Applications of Blockchain Technology beyond Cryptocurrency

The goal of this research paper is to summarise the literature on implementation of the Blockchain and similar digital ledger techniques in various other domains beyond its application to crypto-currency and to draw appropriate conclusions. Blockchain being relatively a new technology, a representative sample of research is presented, spanning over the last ten years, starting from the early work in this field. Different types of usage of Blockchain and other digital ledger techniques, their challenges, applications, security and privacy issues were investigated. Identifying the most propitious direction for future use of Blockchain beyond crypto-currency is the main focus of the review study. Blockchain (BC), the technology behind Bitcoin crypto-currency system, is considered to be essential for forming the backbone for ensuring enhanced security and privacy for various applications in many other domains including the Internet of Things (IoT) eco-system. International research is currently being conducted in both academia and industry applying Blockchain in varied domains. The Proof-of-Work (PoW) mathematical challenge ensures BC security by maintaining a digital ledger of transactions that is considered to be unalterable. Furthermore, BC uses a changeable
Ka-Band Low-Loss and High-Isolation 0.13 /spl mu/m CMOS SPST/SPDT Switches Using High Substrate Resistance

This paper presents 35 GHz single-pole-single-throw (SPST) and single-pole-double-throw (SPDT) CMOS switches using a 0.13 mum BiCMOS process (IBM 8 HP). The CMOS transistors are designed to have a high substrate resistance to minimize the insertion loss and improve power handling capability. The SPST/SPDT switches have a insertion loss of 1.8 dB/2.2 dB, respectively, and an input 1-dB compression point (P1 dB) greater than 22 dBm. The isolation is greater than 30 dB at 35-40 GHz and is achieved using two parallel resonant networks. To our knowledge, this is the first demonstration of low-loss, high-isolation CMOS switches at Ka-band frequencies.
Workflow control-flow patterns : a revised view

The Workflow Patterns Initiative was established with the aim of delineating the fundamental requirements that arise during business process modelling on a recurring basis and describe them in an imperative way. The first deliverable of this research project was a set of twenty patterns describing the control-flow perspective of workflow systems. Since their release, these patterns have been widely used by practitioners, vendors and academics alike in the selection, design and development of workflow systems [vdAtHKB03]. This paper presents the first systematic review of the original twenty control-flow patterns and provides a formal description of each of them in the form of a Coloured Petri-Net (CPN) model. It also identifies twenty three new patterns relevant to the control-flow perspective. Detailed context conditions and evaluation criteria are presented for each pattern and their implementation is assessed in fourteen commercial offerings including workflow and case handling systems, business process modelling formalisms and business process execution languages.
Performance analysis of encryption algorithms for Information Security

Information Security has become an important issue in data communication. Encryption algorithms have come up as a solution and play an important role in information security system. On other side, those algorithms consume a significant amount of computing resources such as CPU time, memory and battery power. Therefore it is essential to measure the performance of encryption algorithms. In this work, three encryption algorithms namely DES, AES and Blowfish are analyzed by considering certain performance metrics such as execution time, memory required for implementation and throughput. Based on the experiments, it has been concluded that the Blowfish is the best performing algorithm among the algorithms chosen for implementation.