nils-herrmann/clean_scirepeval huggingface dataset:
Parameterization and parametric design of mannequins

This paper presents a novel feature based parameterization approach of human bodies from the unorganized cloud points and the parametric design method for generating new models based on the parameterization. The parameterization consists of two phases. Firstly, the semantic feature extraction technique is applied to construct the feature wireframe of a human body from laser scanned 3D unorganized points. Secondly, the symmetric detail mesh surface of the human body is modeled. Gregory patches are utilized to generate G 1 continuous mesh surface interpolating the curves on feature wireframe. After that, a voxel-based algorithm adds details on the smooth G 1 continuous surface by the cloud points. Finally, the mesh surface is adjusted to become symmetric. Compared to other template fitting based approaches, the parameterization approach introduced in this paper is more efficient. The parametric design approach synthesizes parameterized sample models to a new human body according to user input sizing dimensions. It is based on a numerical optimization process. The strategy of choosing samples for synthesis is also introduced. Human bodies according to a wide range of dimensions can be generated by our approach. Different from the mathematical interpolation function based human body synthesis methods, the models generated in our method have the approximation errors minimized. All mannequins constructed by our approach have consistent feature patches, which benefits the design automation of customized clothes around human bodies a lot.
Wearable sensor badge and sensor jacket for context awareness

The addition of sensors to wearable computers allows them to adapt their functions to more suit the activities and situation of their wearers. A wearable sensor badge is described constructed from (hard) electronic components, which can sense perambulatory activities for context-awareness. A wearable sensor jacket is described that uses advanced knitting techniques to form (soft) fabric stretch sensors positioned to measure upper limb and body movement. Worn on-the-hip, or worn as clothing, these unobtrusive sensors supply abstract information about your current activity to your other wearable computers.
Powered Hip Exoskeletons Can Reduce the User's Hip and Ankle Muscle Activations During Walking

In this paper, we study the human locomotor adaptation to the action of a powered exoskeleton providing assistive torque at the user's hip during walking. To this end, we propose a controller that provides the user's hip with a fraction of the nominal torque profile, adapted to the specific gait features of the user from Winter's reference data . The assistive controller has been implemented on the ALEX II exoskeleton and tested on ten healthy subjects. Experimental results show that when assisted by the exoskeleton, users can reduce the muscle effort compared to free walking. Despite providing assistance only to the hip joint, both hip and ankle muscles significantly reduced their activation, indicating a clear tradeoff between hip and ankle strategy to propel walking.
Wireless SDN mobile ad hoc network: From theory to practice

A promising approach for dealing with the increasing demand of data traffic is the use of device-to-device (D2D) technologies, in particular when the destination can be reached directly, or though few retransmissions by peer devices. Thus, the cellular network can offload local traffic that is transmitted by an ad hoc network, e.g., a mobile ad hoc network (MANET), or a vehicular ad hoc network (VANET). The cellular base station can help coordinate all the devices in the ad hoc network by reusing the software tools developed for software-defined networks (SDNs), which divide the control and the data messages, transmitted in two separate interfaces. In this paper, we present a practical implementation of an SDN MANET, describe in detail the software components that we adopted, and provide a repository for all the new components that we developed. This work can be a starting point for the wireless networking community to design new testbeds with SDN capabilities that can have the advantages of D2D data transmissions and the flexibility of a centralized network management. In order to prove the feasibility of such a network, we also showcase the performance of the proposed network implemented in real devices, as compared to a distributed ad hoc network.
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

Deep artificial neural networks (DNNs) are typically trained via gradient-based learning algorithms, namely backpropagation. Evolution strategies (ES) can rival backprop-based algorithms such as Q-learning and policy gradients on challenging deep reinforcement learning (RL) problems. However, ES can be considered a gradient-based algorithm because it performs stochastic gradient descent via an operation similar to a finite-difference approximation of the gradient. That raises the question of whether non-gradient-based evolutionary algorithms can work at DNN scales. Here we demonstrate they can: we evolve the weights of a DNN with a simple, gradient-free, population-based genetic algorithm (GA) and it performs well on hard deep RL problems, including Atari and humanoid locomotion. The Deep GA successfully evolves networks with over four million free parameters, the largest neural networks ever evolved with a traditional evolutionary algorithm. These results (1) expand our sense of the scale at which GAs can operate, (2) suggest intriguingly that in some cases following the gradient is not the best choice for optimizing performance, and (3) make immediately available the multitude of techniques that have been developed in the neuroevolution community to improve performance on RL problems. To demonstrate the latter, we show that combining DNNs with novelty search, which was designed to encourage exploration on tasks with deceptive or sparse reward functions, can solve a high-dimensional problem on which reward-maximizing algorithms (e.g. DQN, A3C, ES, and the GA) fail. Additionally, the Deep GA parallelizes better than ES, A3C, and DQN, and enables a state-of-the-art compact encoding technique that can represent million-parameter DNNs in thousands of bytes.
Laser driver switching 20 A with 2 ns pulse width using GaN

A GaN-HEMT-based circuit is presented capable of switching 20 A of current with less than about 0.5 ns rise and fall time. This demonstrates the potential of GaN transistors for high-current switching applications, even if breakdown voltage requirements are low. The current driver is used to realize an optical pulse picker generating 10 ps optical pulses of more than 30 W with a variable repetition rate between 1 kHz and 100 MHz.
Value-based software engineering: reinventing

The Value-Based Software Engineering (VBSE) agenda described in the preceding article has the objectives of integrating value considerations into current and emerging software engineering principles and practices, and of developing an overall framework in which they compatibly reinforce each other. In this paper, we provide a case study illustrating some of the key VBSE practices, and focusing on a particular anomaly in the monitoring and control area: the "Earned Value Management System." This is a most useful technique for monitoring and controlling the cost, schedule, and progress of a complex project. But it has absolutely nothing to say about the stakeholder value of the system being developed. The paper introduces an example order-processing software project, and shows how the use of Benefits Realization Analysis, stake-holder value proposition elicitation and reconciliation, and business case analysis provides a framework for stakeholder-earned-value monitoring and control.
Sertraline treatment of major depression in patients with acute MI or unstable angina

Major depressive disorder (MDD) occurs in 15% to 23% of patients with acute coronary syndromes and constitutes an independent risk factor for morbidity and mortality. However, no published evidence exists that antidepressant drugs are safe or efficacious in patients with unstable ischemic heart disease.



To evaluate the safety and efficacy of sertraline treatment of MDD in patients hospitalized for acute myocardial infarction (MI) or unstable angina and free of other life-threatening medical conditions.



Randomized, double-blind, placebo-controlled trial conducted in 40 outpatient cardiology centers and psychiatry clinics in the United States, Europe, Canada, and Australia. Enrollment began in April 1997 and follow-up ended in April 2001.



A total of 369 patients with MDD (64% male; mean age, 57.1 years; mean 17-item Hamilton Depression [HAM-D] score, 19.6; MI, 74%; unstable angina, 26%).



After a 2-week single-blind placebo run-in, patients were randomly assigned to receive sertraline in flexible dosages of 50 to 200 mg/d (n = 186) or placebo (n = 183) for 24 weeks.



The primary (safety) outcome measure was change from baseline in left ventricular ejection fraction (LVEF); secondary measures included surrogate cardiac measures and cardiovascular adverse events, as well as scores on the HAM-D scale and Clinical Global Impression Improvement scale (CGI-I) in the total randomized sample, in a group with any prior history of MDD, and in a more severe MDD subgroup defined a priori by a HAM-D score of at least 18 and history of 2 or more prior episodes of MDD.



Sertraline had no significant effect on mean (SD) LVEF (sertraline: baseline, 54% [10%]; week 16, 54% [11%]; placebo: baseline, 52% [13%]; week 16, 53% [13%]), treatment-emergent increase in ventricular premature complex (VPC) runs (sertraline: 13.1%; placebo: 12.9%), QTc interval greater than 450 milliseconds at end point (sertraline: 12%; placebo: 13%), or other cardiac measures. All comparisons were statistically nonsignificant (P> or = .05). The incidence of severe cardiovascular adverse events was 14.5% with sertraline and 22.4% with placebo. In the total randomized sample, the CGI-I (P =.049), but not the HAM-D (P =.14), favored sertraline. The CGI-I responder rates for sertraline were significantly higher than for placebo in the total sample (67% vs 53%; P =.01), in the group with at least 1 prior episode of depression (72% vs 51%; P =.003), and in the more severe MDD group (78% vs 45%; P =.001). In the latter 2 groups, both CGI-I and HAM-D measures were significantly better in those assigned to sertraline.



Our results suggest that sertraline is a safe and effective treatment for recurrent depression in patients with recent MI or unstable angina and without other life-threatening medical conditions.
Grid Power Peak Shaving and Valley Filling Using Vehicle-to-Grid Systems

A strategy for grid power peak shaving and valley filling using vehicle-to-grid systems (V2G) is proposed. The architecture of the V2G systems and the logical relationship between their sub-systems are described. An objective function of V2G peak-shaving control is proposed and the main constraints are formulated. The influences of the number of connected EVs and the average value of the target curve are analyzed. The rms and the standard deviation of the difference between the target and planned curves are proposed as indices for measuring the degree of matching between the two curves. The simulation results demonstrate that peaking shaving using V2G can be effective and controllable, and the proposed control algorithm is feasible.
Wheel Torque Distribution Criteria for Electric Vehicles With Torque-Vectoring Differentials

The continuous and precise modulation of the driving and braking torques of each wheel is considered the ultimate goal for controlling the performance of a vehicle in steady-state and transient conditions. To do so, dedicated torque-vectoring (TV) controllers that allow optimal wheel torque distribution under all possible driving conditions have to be developed. Commonly, vehicle TV controllers are based on a hierarchical approach, consisting of a high-level supervisory controller that evaluates a corrective yaw moment and a low-level controller that defines the individual wheel torque reference values. The problem of the optimal individual wheel torque distribution for a particular driving condition can be solved through an optimization-based control-allocation (CA) algorithm, which must rely on the appropriate selection of the objective function. With a newly developed offline optimization procedure, this paper assesses the performance of alternative objective functions for the optimal wheel torque distribution of a four-wheel-drive (4WD) fully electric vehicle. Results show that objective functions based on the minimum tire slip criterion provide better control performance than functions based on energy efficiency.
The relationship between addiction to smartphone usage and depression among adults: a cross sectional study

Addiction to smartphone usage is a common worldwide problem among adults, which might negatively affect their wellbeing. This study investigated the prevalence and factors associated with smartphone addiction and depression among a Middle Eastern population.



This cross-sectional study was conducted in 2017 using a web-based questionnaire distributed via social media. Responses to the Smartphone Addiction Scale - Short version (10-items) were rated on a 6-point Likert scale, and their percentage mean score (PMS) was commuted. Responses to Beck's Depression Inventory (20-items) were summated (range 0-60); their mean score (MS) was commuted and categorized. Higher scores indicated higher levels of addiction and depression. Factors associated with these outcomes were identified using descriptive and regression analyses. Statistical significance was set at P < 0.05.



Complete questionnaires were 935/1120 (83.5%), of which 619 (66.2%) were females and 316 (33.8%) were males. The mean ± standard deviation of their age was 31.7 ± 11  years. Majority of participants obtained university education 766 (81.9%), while 169 (18.1%) had school education. The PMS of addiction was 50.2 ± 20.3, and MS of depression was 13.6 ± 10.0. A significant positive linear relationship was present between smart phone addiction and depression (y = 39.2 + 0.8×; P < 0.001). Significantly higher smartphone addiction scores were associated with younger age users, (β = - 0.203, adj. P = 0.004). Factors associated with higher depression scores were school educated users (β = - 2.03, adj. P = 0.01) compared to the university educated group and users with higher smart phone addiction scores (β =0.194, adj. P < 0.001).



The positive correlation between smartphone addiction and depression is alarming. Reasonable usage of smart phones is advised, especially among younger adults and less educated users who could be at higher risk of depression.
Projection-Aware Task Planning and Execution for Human-in-the-Loop Operation of Robots in a Mixed-Reality Workspace

Recent advances in mixed-reality technologies have renewed interest in alternative modes of communication for human-robot interaction. However, most of the work in this direction has been confined to tasks such as teleoperation, simulation or explication of individual actions of a robot. In this paper, we will discuss how the capability to project intentions affect the task planning capabilities of a robot. Specifically, we will start with a discussion on how projection actions can be used to reveal information regarding the future intentions of the robot at the time of task execution. We will then pose a new planning paradigm - projection-aware planning - whereby a robot can trade off its plan cost with its ability to reveal its intentions using its projection actions. We will demonstrate each of these scenarios with the help of a joint human-robot activity using the HoloLens.
Theory and measurement of generalized problematic Internet use: A two-step approach

This study tested an updated cognitive-behavioral model of generalized problematic Internet use and reports results of a confirmatory analysis of the Generalized Problematic Internet Use Scale 2 (GPIUS2). Overall, the results indicated that a preference for online social interaction and use of the Internet for mood regulation, predict deficient self-regulation of Internet use (i.e., compulsive Internet use and a cognitive preoccupation with the Internet). In turn, deficient self-regulation was a significant predictor of the extent to which one’s Internet use led to negative outcomes. Results indicated the model fit the data well and variables in the model accounted for 27% of the variance in mood regulation scores, 65% of variance in participants’ deficient self-regulation scores, and 61% of variance in the negative outcome scores.
Leveraging Bagging for Evolving Data Streams

Bagging, boosting and Random Forests are classical ensemble methods used to improve the performance of single classifiers. They obtain superior performance by increasing the accuracy and diversity of the single classifiers. Attempts have been made to reproduce these methods in the more challenging context of evolving data streams. In this paper, we propose a new variant of bagging, called leveraging bagging. This method combines the simplicity of bagging with adding more randomization to the input, and output of the classifiers. We test our method by performing an evaluation study on synthetic and real-world datasets comprising up to ten million examples.
Making a good decision: value from fit.

The classic answer to what makes a decision good concerns outcomes. A good decision has high outcome benefits (it is worthwhile) and low outcome costs (it is worth it). I propose that, independent of outcomes or value from worth, people experience a regulatory fit when they use goal pursuit means that fit their regulatory orientation, and this regulatory fit increases the value of what they are doing. The following postulates of this value from fit proposal are examined: (a) People will be more inclined toward goal means that have higher regulatory fit, (b) people's motivation during goal pursuit will be stronger when regulatory fit is higher, (c) people's (prospective) feelings about a choice they might make will be more positive for a desirable choice and more negative for an undesirable choice when regulatory fit is higher, (d) people's (retrospective) evaluations of past decisions or goal pursuits will be more positive when regulatory fit was higher, and (e) people will assign higher value to an object that was chosen with higher regulatory fit. Studies testing each of these postulates support the value-from-fit proposal. How value from fit can enhance or diminish the value of goal pursuits and the quality of life itself is discussed.
New Approach to Virtualization Is a Lightweight

Virtualization is a hot topic in the technology world. The technology enables a single computer to run multiple operating systems simultaneously. It lets companies use a single server for multiple tasks that would normally have to run on multiple servers, each running a different OS. Now, vendors are releasing products based on two lightweight virtualization approaches that also let a single operating system run several instances of the same OS or different OSs. However, today's new virtualization approaches do not try to emulate an entire hardware environment, as traditional virtualization does. They thus require fewer CPU and memory resources, which is why the technology is called "lightweight" virtualization. However, lightweight virtualization still faces several barriers to widespread adoption.
Software development lifecycle models

This history column article provides a tour of the main software development life cycle (SDLC) models. (A lifecycle covers all the stages of software from its inception with requirements definition through to fielding and maintenance.) System development lifecycle models have drawn heavily on software and so the two terms can be used interchangeably in terms of SDLC, especially since software development in this respect encompasses software systems development. Because the merits of selecting and using an SDLC vary according to the environment in which software is developed as well as its application, I discuss three broad categories for consideration when analyzing the relative merits of SDLC models. I consider the waterfall model before the other models because it has had a profound effect on software development, and has additionally influenced many SDLC models prevalent today. Thereafter, I consider some of the mainstream models and finish with a discussion of what the future could hold for SDLC models.
Design of a 1 kV bidirectional DC-DC converter with 650 V GaN transistors

This paper presents a bidirectional 4-level flying capacitor multi-level (FCML) converter for high voltage (> 1 kV) step-down/step-up conversion needed in hybrid rail and electric vehicle applications. Previous work achieved similar input voltage requirements through increasing the number of levels in the FCML, at the cost of additional transistors, flying capacitors and control complexity. In this work, we investigate the application of 650 V GaN transistors and apply a cascaded bootstrap method to supply the isolated gate drivers. We also analyze the performance benefits and limitations of zero-voltage switching (ZVS) in FCML converters. The design employs a single-sided PCB to improve the design flexibility for backside heat sinking. We demonstrate the design with an experimental prototype that achieves up to 1 kV operation at 2 kW with excellent flying capacitor balancing, a peak efficiency of 98.4% and a power density of 1500 W/in3.
A case study of the in-class use of a video game for teaching high school history

This study examines the case of a sophomore high school history class where Making History, a video game designed with educational purposes in mind, is used in the classroom to teach about World War II. Data was gathered using observation, focus group and individual interviews, and document analysis. The high school was a rural school located in a small town in the Midwestern United States. The teacher had been teaching with the game for several years and spent one school week teaching World War II, with students playing the game in class for three days of that week. The purpose of this study was to understand teacher and student experiences with and perspectives on the in-class use of an educational video game. Results showed that the use of the video game resulted in a shift from a traditional teachercentered learning environment to a student-centered environment where the students were much more active and engaged. Also, the teacher had evolved implementation strategies based on his past experiences using the game to maximize the focus on learning.