nils-herrmann/clean_scirepeval huggingface dataset:
Don't Bother Me. I'm Socializing!: A Breakpoint-Based Smartphone Notification System

Smartphone notifications provide application-specific information in real-time, but could distract users from in-person social interactions when delivered at inopportune moments. We explore breakpoint-based notification management, in which the smartphone defers notifications until an opportune moment. With a video survey where participants selected appropriate moments for notifications from a video-recorded social interaction, we identify four breakpoint types: long silence, a user leaving the table, others using smartphones, and a user left alone. We introduce a Social Context-Aware smartphone Notification system, SCAN, that uses build-in sensors to detect social context and identifies breakpoints to defer smartphone notifications until a breakpoint. We conducted a controlled study with ten friend groups who had SCAN installed on their smartphones while dining at a restaurant. Results show that SCAN accurately detects breakpoints (precision=92.0%, recall=82.5%), and reduces notification interruptions by 54.1%. Most participants reported that SCAN helped them to focus better on in-person social interaction and found selected breakpoints appropriate.
False Confessions : Causes , Consequences , and Implications for Reform

In recent years, DNA exoneration cases have shed light on the problem of false confessions and the wrongful convictions that result. Drawing on basic psychological principles and methods, an extensive body of research has focused on the psychology of confessions. This article describes the processes of interrogation by which police assess whether a suspect is lying or telling the truth and the techniques used to elicit confessions from those deemed deceptive. The problem of false confessions emphasizes personal and situational factors that put innocent people at risk in the interrogation room. Turning from the causes of false confessions to their consequences, research shows that confession evidence can bias juries, judges, lay witnesses, and forensic examiners. Finally, empirically based proposals for the reform of policy and practice include a call for the mandatory video recording of interrogations, blind testing in forensic crime labs, and use of confession experts in court.
Optical Angular Encoder Installation Error Measurement and Calibration by Ring Laser Gyroscope

This paper deals with the installation errors of an optical angular encoder (OAE). A harmonic model is proposed to describe the installation errors, including the effects of eccentricity, swash, and distortion. Moreover, a method of OAE calibration with the ring laser gyroscope (RLG) is introduced. The calibration method can potentially reach the accuracy of 0.1". The calibration method is proved to be experimentally effective. With the harmonic model obtained from the experiment, the calibration of the OAE can be carried out in real time.
On the Analysis and Detection of Mobile Botnet Applications

Mobile botnet phenomenon is gaining popularity among malware writers in order to exploit vulnerabilities in smartphones. In particular, mobile botnets enable illegal access to a victim’s smartphone, can compromise critical user data and launch a DDoS attack through Command and Control (C&C). In this article, we propose a static analysis approach, DeDroid, to investigate botnet-specific properties that can be used to detect mobile applications with botnet intensions. Initially, we identify critical features by observing code behavior of the few known malware binaries having C&C features. Then, we compare the identified features with the malicious and benign applications of Drebin dataset. The results show against the comparative analysis that, Drebin dataset has 35% malicious applications which qualify as botnets. Upon closer examination, 90% of the potential botnets are confirmed as botnets. Similarly, for comparative analysis against benign applications having C&C features, DeDroid has achieved adequate detection accuracy. In addition, DeDroid has achieved high accuracy with negligible false positive rate while making decision for state-of-the-art malicious applications.
Control of Hybrid Dynamical Systems : An Overview of Recent Advances

Hybrid systems are dynamical systems exhibiting both continuous and discrete behavior. Having states that can evolve continuously or discretely, hybrid dynamical systems permit modeling and simulation of systems in a wide range of applications including robotics, automotive systems, power systems, biological systems, to just list a few. Key motivation for studying hybrid systems comes from the recognition of the capabilities of hybrid feedback in robust stabilization of nonlinear systems. Numerous frameworks for modeling and analysis of hybrid systems have appeared in the literature. These include the work of Tavernini [26], Michel and Hu [11], Lygeros et al. , Aubin et al. , and van der Schaft and Schumacher [28], among others. In this paper, we consider the hybrid systems framework in [7, 6], where the continuous dynamics (or flows) of a hybrid system are modeled using differential inclusions while the discrete dynamics (or jumps) are captured by difference inclusions. Trajectories to a hybrid system conveniently use two parameters: an ordinary time parameter t ∈ [0,+∞), which is incremented continuously as flows occur, an a discrete time parameter j ∈ {0, 1, 2, . . .}, which is incremented at unitary steps when jumps occur. The conditions determining whether a trajectory to a hybrid system should flow or jump are captured by subsets of the state space and input space. In simple terms, given an input (t, j) 7→ u(t, j), a trajectory (t, j) 7→ x(t, j) to a hybrid system satisfies, over intervals of flow,
Generalizing memories over time: Sleep and reinforcement facilitate transitive inference

The use of reinforcement and rewards is known to enhance memory retention. However, the impact of reinforcement on higher-order forms of memory processing, such as integration and generalization, has not been directly manipulated in previous studies. Furthermore, there is evidence that sleep enhances the integration and generalization of memory, but these studies have only used reinforcement learning paradigms and have not examined whether reinforcement impacts or is critical for memory integration and generalization during sleep. Thus, the aims of the current study were to examine: (1) whether reinforcement during learning impacts the integration and generalization of memory; and (2) whether sleep and reinforcement interact to enhance memory integration and generalization. We investigated these questions using a transitive inference (TI) task, which is thought to require the integration and generalization of disparate relational memories in order to make novel inferences. To examine whether reinforcement influences or is required for the formation of inferences, we compared performance using a reinforcement or an observation based TI task. We examined the impact of sleep by comparing performance after a 12-h delay containing either wake or sleep. Our results showed that: (1) explicit reinforcement during learning is required to make transitive inferences and that sleep further enhances this effect; (2) sleep does not make up for the inability to make inferences when reinforcement does not occur during learning. These data expand upon previous findings and suggest intriguing possibilities for the mechanisms involved in sleep-dependent memory transformation.
Active Rotary-Legs Mechanism for Stair-Climbing Mobility Vehicle

This study describes a novel active rotary-legs mechanism for a stair-climbing mobility vehicle. We have previously developed a stair-climbing up and down wheelchair with lever propelled rotary-legs operated using the human upper body. The previous results indicated that the required torque for the stair-climbing up and down procedure can be reduced based on the user's posture transition, which was achieved via the procedure using only the human upper body. The design principle of the proposed active rotary-legs mechanism in this study is to develop a more compact and lightweight mechanism for a stair-climbing up and down mobility vehicle. We achieve this objective based on the previous observations by appropriately combining the active and passive components. The developed mechanism consists of a four-bar linkage mechanism with motors and gas springs as active and passive components, respectively. The gas springs are connected to the linkage mechanism as parallel elastic actuators, which can reduce the required motor torque and make the complete mechanism compact and lightweight. We describe herein a detailed design of the active rotary-legs mechanism and conduct simulations and preliminary experiments to investigate the effectiveness of our proposed methodology.
Femoral hip stem with additively manufactured cellular structures

Research and development of hip stem implants started centuries ago. However, there is still no yet an optimum design that fulfills all the requirements of the patient. New manufacturing technologies have opened up new possibilities for complicated theoretical designs to become tangible reality. Current trends in the development of hip stems focus on applying porous structures to improve osseointegration and reduce stem stiffness in order to approach the stiffness of the natural human bone. In this field, modern additive manufacturing machines offer unique flexibility in manufacturing parts combining variable density mesh structures with solid and porous metal in a single manufacturing process. Furthermore, additive manufacturing machines became powerful competitors in the economical mass production of hip implants. This is due to their ability to manufacture several parts with different geometries in a single setup and with minimum material consumption. This paper reviews the application of additive manufacturing (AM) techniques in the production of innovative porous femoral hip stem design.
Violent video game effects on children and adolescents. A review of the literature.

Studies of violent video games on children and adolescents were reviewed to: 1) determine the multiple effects; 2) to offer critical observations about common strengths and weaknesses in the literature; 3) to provide a broader perspective to understand the research on the effects of video games. The review includes general theoretical and methodological considerations of media violence, and description of the general aggression model (GAM). The literature was evaluated in relation to the GAM. Published literature, including meta-analyses, are reviewed, as well as relevant unpublished material, such as conference papers and dissertations. Overall, the evidence supports hypotheses that violent video game play is related to aggressive affect, physiological arousal, aggressive cognitions, and aggressive behaviours. The effects of video game play on school performance are also evaluated, and the review concludes with a dimensional approach to video game effects. The dimensional approach evaluates video game effects in terms of amount, content, form, and mechanics, and appears to have many advantages for understanding and predicting the multiple types of effects demonstrated in the literature.
The Effect of Using “ Um ” and “ Uh ” on the Perceived Intelligence of a Speaker

In this study we sought to better understand the relationship between disfluencies and perceived intelligence. It is generally accepted that disfluencies such as “um” and “uh” indicate messages to a listener. In the current study, we examined how the use of “um” and “uh” impact the perceived intelligence of a speaker. We found that intelligence was not impacted by the use of “um” and “uh.” However, we found that filler words such as “um” and “uh” do affect other aspects of speaking such as perceived preparedness, effectiveness at public speaking, and ease of understanding by a listener.
A New Approach for Modeling Darrieus-Type Vertical Axis Wind Turbine Rotors Using Electrical Equivalent Circuit Analogy : Basis of Theoretical Formulations and Model Development

Models are crucial in the engineering design process because they can be used for both the optimization of design parameters and the prediction of performance. Thus, models can significantly reduce design, development and optimization costs. This paper proposes a novel equivalent electrical model for Darrieus-type vertical axis wind turbines (DTVAWTs). The proposed model was built from the mechanical description given by the Paraschivoiu double-multiple streamtube model and is based on the analogy between mechanical and electrical circuits. This work addresses the physical concepts and theoretical formulations underpinning the development of the model. After highlighting the working principle of the DTVAWT, the step-by-step development of the model is presented. For assessment purposes, simulations of aerodynamic characteristics and those of corresponding electrical components are performed and compared.
Effects on strength, power, and flexibility in adolescents of nonperiodized vs. daily nonlinear periodized weight training.

The aim of this study was to compare 2 models of resistance training (RT) programs, nonperiodized (NP) training and daily nonlinear periodized (DNLP) training, on strength, power, and flexibility in untrained adolescents. Thirty-eight untrained male adolescents were randomly assigned to 1 of 3 groups: a control group, NP RT program, and DNLP program. The subjects were tested pretraining and after 4, 8, and 12 weeks for 1 repetition maximum (1RM) resistances in the bench press and 45° leg press, sit and reach test, countermovement vertical jump (CMVJ), and standing long jump (SLJ). Both training groups performed the same sequence of exercises 3 times a week for a total of 36 sessions. The NP RT consisted of 3 sets of 10-12RM throughout the training period. The DNLP training consisted of 3 sets using different training intensities for each of the 3 training sessions per week. The total volume of the training programs was not significantly different. Both the NP and DNLP groups exhibited a significant increase in the 1RM for the bench press and 45° leg press posttraining compared with that pretraining, but there were no significant differences between groups (p ≤ 0.05). The DNLP group's 1RM changes showed greater percentage improvements and effect sizes. Training intensity for the bench press and 45° leg press did not significantly change during the training. In the CMVJ and SLJ tests, NP and DNLP training showed no significant change. The DNLP group showed a significant increase in the sit and reach test after 8 and 12 weeks of training compared with pretraining; this did not occur with NP training. In summary, in untrained adolescents during a 12-week training period, a DNLP program can be used to elicit similar and possible superior maximal strength and flexibility gains compared with an NP multiset training model.
Vehicle logo detection using convolutional neural network and pyramid of histogram of oriented gradients

This paper presents a new method for vehicle logo detection and recognition from images of front and back views of vehicle. The proposed method is a two-stage scheme which combines Convolutional Neural Network (CNN) and Pyramid of Histogram of Gradient (PHOG) features. CNN is applied as the first stage for candidate region detection and recognition of the vehicle logos. Then, PHOG with Support Vector Machine (SVM) classifier is employed in the second stage to verify the results from the first stage. Experiments are performed with dataset of vehicle images collected from internet. The results show that the proposed method can accurately locate and recognize the vehicle logos with higher robustness in comparison with the other conventional schemes. The proposed methods can provide up to 100% in recall, 96.96% in precision and 99.99% in recognition rate in dataset of 20 classes of the vehicle logo.
What makes great teaching ? Review of the underpinning research

This review set out to address three apparently simple questions:  What makes 'great teaching'?  What kinds of frameworks or tools could help us to capture it?  How could this promote better learning?  " What makes great teaching? " Great teaching is defined as that which leads to improved student progress We define effective teaching as that which leads to improved student achievement using outcomes that matter to their future success. Defining effective teaching is not easy. The research keeps coming back to this critical point: student progress is the yardstick by which teacher quality should be assessed. Ultimately, for a judgement about whether teaching is effective, to be seen as trustworthy, it must be checked against the progress being made by students. The six components of great teaching Schools currently use a number of frameworks that describe the core elements of effective teaching. The problem is that these attributes are so broadly defined that they can be open to wide and different interpretation whether high quality teaching has been observed in the classroom. It is important to understand these limitations when making assessments about teaching quality. Below we list the six common components suggested by research that teachers should consider when assessing teaching quality. We list these approaches, skills and knowledge in order of how strong the evidence is in showing that focusing on them can improve student outcomes. This should be seen as offering a 'starter kit' for thinking about effective pedagogy. Good quality teaching will likely involve a combination of these attributes manifested at different times; the very best teachers are those that demonstrate all of these features. The most effective teachers have deep knowledge of the subjects they teach, and when teachers' knowledge falls below a certain level it is a significant impediment to students' learning. As well as a strong understanding of the material being taught, teachers must also understand the ways students think about the content, be able to evaluate the thinking behind students' own methods, and identify students' common misconceptions. Includes elements such as effective questioning and use of assessment by teachers. Specific practices, like reviewing previous learning, providing model responses for students, giving adequate time for practice to embed skills securely Executive Summary 3 and progressively introducing new learning (scaffolding) are also elements of high quality instruction. 3. Classroom climate (Moderate evidence of impact on student outcomes) Covers …
Understanding Ohm's law: enlightenment through augmented reality

This paper proposes a new interactive environment for learning the basics of electricity in series and parallel circuits using augmented reality (AR). The system allows the student to design and study electric circuits by placing symbolic cards representing resistors on a board. Then this board is overlaid by a 3D virtual circuit with its electrical components. Finally, this virtual circuit is coupled back to reality by lighting up a real bulb with intensity depending on the chosen layout. In addition, the mathematical relationship between current, resistance and voltage (Ohm's law) is presented in an information window.
Deep Learning for Accelerated Ultrasound Imaging

In portable, 3-D, or ultra-fast ultrasound (US) imaging systems, there is an increasing demand to reconstruct high quality images from limited number of data. However, the existing solutions require either hardware changes or computationally expansive algorithms. To overcome these limitations, here we propose a novel deep learning approach that interpolates the missing RF data by utilizing the sparsity of the RF data in the Fourier domain. Extensive experimental results from sub-sampled RF data from a real US system confirmed that the proposed method can effectively reduce the data rate without sacrificing the image quality.
Classroom L 2 vocabulary acquisition : investigating the role of pedagogical tasks and form-focused instruction

Framed under a cognitive approach to task-based L2 learning, this study used a pedagogical approach to investigate the effects of three vocabulary lessons (one traditional and two task-based) on acquisition of basic meanings, forms and morphological aspects of Spanish words. Quantitative analysis performed on the data suggests that the type of pedagogical approach had no impact on immediate retrieval (after treatment) of targeted word forms, but it had an impact on long-term retrieval (one week) of targeted forms. In particular, task-based lessons seemed to be more effective than the Presentation, Practice and Production (PPP) lesson. The analysis also suggests that a task-based lesson with an explicit focus-on-forms component was more effective than a task-based lesson that did not incorporate this component in promoting acquisition of word morphological aspects. The results also indicate that the explicit focus on forms component may be more effective when placed at the end of the lesson, when meaning has been acquired. Results are explained in terms of qualitative differences in amounts of focus on form and meaning, type of form-focused instruction provided, and opportunities for on-line targeted output retrieval. The findings of this study provide evidence for the value of a proactive (Doughty and Williams, 1998a) form-focused approach to Task-Based L2 vocabulary learning, especially structure-based production tasks (Ellis, 2003). Overall, they suggest an important role of pedagogical tasks in teaching L2 vocabulary.
Detection and prevention of ARP cache poisoning

Acknowledgements It is a great pleasure to have an opportunity to thanks valuable beings for their continuous support and inspiration throughout the thesis work. I would like to extend my gratitude towards Dr. for all the guidance and great knowledge he shared during our course. The abundance of knowledge he has always satisfied our queries at every point. Thanks to Mr. Sumit Miglani, My guide for his contribution for timely reviews and suggestions in completing the thesis. Every time he provided the needed support and guidance. At last but not the least, a heartiest thanks to all my family and friends for being there every time I needed them.  Its been working at network layer for the important dynamic conversion of network address i.e. Internet Protocol (IP) address to physical address or Media Access Control (MAC) address. Earlier it was sufficiently providing its services but in today " s complex and more sophisticated unreliable network, security being one major issue, standard ARP protocol is vulnerable to many different kinds of attacks. These attacks lead to devastating loss of important information. With certain loopholes it has become easy to be attacked and with not so reliable security mechanism, confidentiality of data is being compromised. Therefore, a strong need is felt to harden the security system. Since, LAN is used in maximum organizations to get the different computer connected. So, an attempt has been made to enhance the working of ARP protocol to work in a more secure way. Any kind of attempts to poison the ARP cache (it maintains the corresponding IP and MAC address associations in the LAN network) for redirecting the data to unreliable host, are prevented beforehand. New modified techniques are proposed which could efficiently guard our ARP from attacker and protect critical data from being sniffed both internally and externally. Efficiency of these methods has been shown mathematically without any major impact on the performance of network. Main idea behind how these methods actually work and proceed to achieve its task has been explained with the help of flow chart and pseudo codes. With the help of different tools ARP cache is being monitored regularly and if any malicious activity is encountered, it is intimidated to the administrator immediately. So, in …