nils-herrmann/clean_scirepeval huggingface dataset:
Information Privacy Awareness (IPA): A Review of the Use, Definition and Measurement of IPA

Despite the acknowledged importance of awareness in the information privacy (IP) literature, we lack a consistent and thorough understanding of information privacy awareness (IPA). Drawing on Endsley’s model of Situation Awareness, we propose a multidimensional model of IPA and define each of its dimensions. We then conducted a thorough review of the IP literature’s use of awareness and synthesize our findings using our proposed model. This paper makes significant contributions by 1) distinguishing between IP knowledge, literacy and awareness 2) consolidating the IP literature’s definitions of awareness and providing a new detailed definition 3) proposing a new IPA model that future authors can reference when using or measuring IPA.
A 20 Gb/s 0.4 pJ/b Energy-Efficient Transmitter Driver Utilizing Constant- ${\rm G}_{\rm m}$  Bias

This paper describes a transmitter driver based on a CMOS inverter with a resistive feedback. By employing the proposed driver topology, the pre-driver can be greatly simplified, resulting in a remarkable reduction of the overall driver power consumption. It also offers another advantage that the implementation of equalization is straightforward, compared with a conventional voltage-mode driver. Furthermore, the output impedance remains relatively constant while the data is being transmitted, resulting in good signal integrity. For evaluation of the driver performance, a fully functional 20 Gb/s transmitter is implemented, including a PRBS generator, a serializer, and a half-rate clock generator. In order to enhance the overall speed of the digital circuits for 20 Gb/s data transmission, the resistive feedback is applied to the time-critical inverters, which enables shorter rise/fall times. The prototype chip is fabricated in a 65 nm CMOS technology. The implemented driver circuit operates up to the data rate of 20 Gb/s, exhibiting an energy efficiency of 0.4 pJ/b for the output swing of 250 mVpp,diff.
A whole-body control framework for humanoids operating in human environments

Tomorrow's humanoids will operate in human environments, where efficient manipulation and locomotion skills, and safe contact interactions are critical design factors. We report here our recent efforts into these issues, materialized into a whole-body control framework. This framework integrates task-oriented dynamic control and control prioritization allowing to control multiple task primitives while complying with physical and movement-related constraints. Prioritization establishes a hierarchy between control spaces, assigning top priority to constraint-handling tasks, while projecting operational tasks in the null space of the constraints, and controlling the posture within the residual redundancy. This hierarchy is directly integrated at the kinematic level, allowing the program to monitor behavior feasibility at runtime. In addition, prioritization allows us to characterize the dynamic behavior of the individual control primitives subject to the constraints, and to synthesize operational space controllers at multiple levels. To complete this framework, we have developed free-floating models of the humanoid and incorporate the associated dynamics and the effects of the resulting support contacts into the control hierarchy. As part of a long term collaboration with Honda, we are currently implementing this framework into the humanoid robot
Colyseus: A Distributed Architecture for Online Multiplayer Games

This paper presents the design, implementation, and evaluation of Colyseus, a distributed architecture for interactive multiplayer games. Colyseus takes advantage of a game’s tolerance for weakly consistent state and predictable workload to meet the tight latency constraints of game-play and maintain scalable communication costs. In addition, it provides a rich distributed query interface and effective pre-fetching subsystem to help locate and replicate objects before they are accessed at a node. We have implemented Colyseus and modified Quake II, a popular first person shooter game, to use it. Our measurements of Quake II and our own Colyseus-based game with hundreds of players shows that Colyseus effectively distributes game traffic across the participating nodes, allowing Colyseus to support low-latency game-play for an order of magnitude more players than existing single server designs, with similar per-node bandwidth costs.
Reflections on culturally responsive teaching : Embedding theory into practices of instructional and behavioral support

This paper offers reflections on the embedding of culturally responsive teaching practices into Response-to-Intervention (RtI) and School-wide Positive Behavior Support (SW-PBS) models. These types of systemic change models are increasingly being adopted by schools to address academic achievement and to foster a positive school climate. Moreover, they hold promise for addressing the disproportionality that many students who are culturally and linguistically diverse students experience in our schools. Following a review of the existing literature on systemic change, three guiding principles are offered that demonstrate how culturally responsive teaching can be embedded into models of instructional and behavioral support.
A Survey of Shortest-Path Algorithms

A shortest-path algorithm finds a path containing the minimal cost between two vertices in a graph. A plethora of shortest-path algorithms is studied in the literature that span across multiple disciplines. This paper presents a survey of shortest-path algorithms based on a taxonomy that is introduced in the paper. One dimension of this taxonomy is the various flavors of the shortest-path problem. There is no one general algorithm that is capable of solving all variants of the shortest-path problem due to the space and time complexities associated with each algorithm. Other important dimensions of the taxonomy include whether the shortest-path algorithm operates over a static or a dynamic graph, whether the shortest-path algorithm produces exact or approximate answers, and whether the objective of the shortest-path algorithm is to achieve time-dependence or is to only be goal directed. This survey studies and classifies shortest-path algorithms according to the proposed taxonomy. The survey also presents the challenges and proposed solutions associated with each category in the taxonomy.
Social Capital and Knowledge Integration in Digitally Enabled Teams

T understand the impact of social capital on knowledge integration and performance within digitally enabled teams, we studied 46 teams who had a history and a future working together. All three dimensions of their social capital (structural, relational, and cognitive) were measured prior to the team performing two tasks in a controlled setting, one face-to-face and the other through a lean digital network. Structural and cognitive capital were more important to knowledge integration when teams communicated through lean digital networks than when they communicated face-to-face; relational capital directly impacted knowledge integration equally, regardless of the communication media used by the team. Knowledge integration, in turn, impacted team decision quality, suggesting that social capital influences team performance in part by increasing a team’s ability to integrate knowledge. These results suggest that team history may be necessary but not sufficient for teams to overcome the problems with the use of lean digital networks as a communication environment. However, team history may present a window of opportunity for social capital to develop, which in turn allows teams to perform just as well as in either communication environment.
MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education

MATPOWER is an open-source Matlab-based power system simulation package that provides a high-level set of power flow, optimal power flow (OPF), and other tools targeted toward researchers, educators, and students. The OPF architecture is designed to be extensible, making it easy to add user-defined variables, costs, and constraints to the standard OPF problem. This paper presents the details of the network modeling and problem formulations used by MATPOWER, including its extensible OPF architecture. This structure is used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits. Simulation results are presented for a number of test cases comparing the performance of several available OPF solvers and demonstrating MATPOWER's ability to solve large-scale AC and DC OPF problems.
Loosecut: Interactive image segmentation with loosely bounded boxes

One popular approach to interactively segment an object of interest from an image is to annotate a bounding box that covers the object, followed by a binary labeling. However, the existing algorithms for such interactive image segmentation prefer a bounding box that tightly encloses the object. This increases the annotation burden, and prevents these algorithms from utilizing automatically detected bounding boxes. In this paper, we develop a new LooseCut algorithm that can handle cases where the bounding box only loosely covers the object. We propose a new Markov Random Fields (MRF) model for segmentation with loosely bounded boxes, including an additional energy term to encourage consistent labeling of similar-appearance pixels and a global similarity constraint to better distinguish the foreground and background. This MRF model is then solved by an iterated max-flow algorithm. We evaluate LooseCut in three public image datasets, and show its better performance against several state-of-the-art methods when increasing the bounding-box size.
Image classification by combining local and global features

Several techniques have recently been proposed to extract the features of an image. Feature extraction is one of the most important steps in various image processing and computer vision applications such as image retrieval, image classification, matching, object recognition. Relevant feature (global or local) contains discriminating information and is able to distinguish one object from others. Global features describe the entire image, whereas local features describe the image patches (small group of pixels). In this paper, we present a novel descriptor to extract the color-texture features via two information types. Our descriptor named concatenation of local and global color features is based on the fusion of global features using wavelet transform and a modified version of local ternary pattern, whereas, for the local features, speeded-up robust feature descriptor and bag of words model were used. All the features are extracted from the three color planes. To evaluate the effectiveness of our descriptor for image classification, we carried out experiments using the challenging datasets: New-BarkTex, Outex-TC13, Outex-TC14, MIT scene, UIUC sports event, Caltech 101 and MIT indoor scene. Experimental results showed that our descriptor outperforms the existing state-of-the-art methods.
A 5.2mW, 0.0016% THD up to 20kHz, ground-referenced audio decoder with PSRR-enhanced class-AB 16Ω headphone amplifiers

A low-power ground-referenced audio decoder with PSRR-enhanced class-AB headphone amplifiers presents <;0.0016% THD in the whole audio band against the supply ripple by a negative charge-pump. Realized in the 40nm CMOS, the fully-integrated stereo decoder achieves 91dB SNDR and 100dB dynamic range while driving a 16Ω headphone load and consumes 5.2mW from a 1.8V power supply. The core area is 0.093mm2/channel only.
Everything Hertz: methodological issues in short-term frequency-domain HRV

Frequency analysis of the electrocardiographic RR interval is a common method of quantifying autonomic outflow by measuring the beat-to-beat modulation of the heart (heart rate variability; HRV). This review identifies a series of problems with the methods of doing so-the interpretation of low-frequency spectral power, the multiple use of equivalent normalized low frequency (LFnu), high frequency (HFnu) and ratio (LF/HF) terms, and the lack of control over extraneous variables, and reviews research in the calendar year 2012 to determine their prevalence and severity. Results support the mathematical equivalency of ratio units across studies, a reliance on those variables to explain autonomic outflow, and insufficient control of critical experimental variables. Research measurement of HRV has a substantial need for general methodological improvement.
Context-Aware Active Authentication Using Smartphone Accelerometer Measurements

While body movement patterns recorded by a smartphone accelerometer are now well understood to be discriminative enough to separate users, little work has been done to address the question of if or how the position in which the phone is held affects user authentication. In this work, we show through a combination of supervised learning methods and statistical tests, that there are certain users for whom exploitation of information of how a phone is held drastically improves classification performance. We propose a two-stage authentication framework that identifies the location of the phone before performing authentication, and show its benefits based on a dataset of 30 users. Our work represents a first step towards bridging the gap between accelerometer-based authentication systems analyzed from the context of a laboratory environment and a real accelerometer-based authentication system in the wild where phone positioning cannot be assumed.
Many-to-Many Geographically-Embedded Flow Visualisation: An Evaluation

Showing flows of people and resources between multiple geographic locations is a challenging visualisation problem. We conducted two quantitative user studies to evaluate different visual representations for such dense many-to-many flows. In our first study we compared a bundled node-link flow map representation and OD Maps [37] with a new visualisation we call MapTrix. Like OD Maps, MapTrix overcomes the clutter associated with a traditional flow map while providing geographic embedding that is missing in standard OD matrix representations. We found that OD Maps and MapTrix had similar performance while bundled node-link flow map representations did not scale at all well. Our second study compared participant performance with OD Maps and MapTrix on larger data sets. Again performance was remarkably similar.
Real-time underwater 3D scene reconstruction using commercial depth sensor

This paper presents preliminary work to utilize a commercial time of flight depth camera for real-time 3D scene reconstruction of underwater objects. Typical RGB stereo camera imaging for 3D capturing suffers from blur and haziness due to turbidity of water in addition to critical dependence on light, either from natural or artificial sources. We propose a method for repurposing the low-cost Microsoft Kinect™ Time of Flight camera for underwater environment enabling dense depth data acquisition that can be processed in real time. Our motivation is the ease of use and low cost of the device for high quality real-time scene reconstruction as compared to multi view stereo cameras, albeit at a smaller range. Preliminary results of depth data acquisition and surface reconstruction in underwater environment are also presented. The novelty of our work is the utilization of the Kinect depth camera for real-time 3D mesh reconstruction and our main objective is to develop an economical and compact solution for underwater 3D mapping.
A sensorimotor account of vision and visual consciousness.

Many current neurophysiological, psychophysical, and psychological approaches to vision rest on the idea that when we see, the brain produces an internal representation of the world. The activation of this internal representation is assumed to give rise to the experience of seeing. The problem with this kind of approach is that it leaves unexplained how the existence of such a detailed internal representation might produce visual consciousness. An alternative proposal is made here. We propose that seeing is a way of acting. It is a particular way of exploring the environment. Activity in internal representations does not generate the experience of seeing. The outside world serves as its own, external, representation. The experience of seeing occurs when the organism masters what we call the governing laws of sensorimotor contingency. The advantage of this approach is that it provides a natural and principled way of accounting for visual consciousness, and for the differences in the perceived quality of sensory experience in the different sensory modalities. Several lines of empirical evidence are brought forward in support of the theory, in particular: evidence from experiments in sensorimotor adaptation, visual "filling in," visual stability despite eye movements, change blindness, sensory substitution, and color perception.
Classification of small UAVs and birds by micro-Doppler signatures

The problem of unmanned aerial vehicles classification using continuous wave radar is considered in this paper. Classification features are extracted from micro-Doppler signature. Before the classification, the micro-Doppler signature is filtered and aligned to compensate the Doppler shift caused by the target's body motion. Eigenpairs extracted from the correlation matrix of the signature are used as informative features for classification. The proposed approach is verified on real radar measurements collected with 9.5 GHz radar. Planes, quadrocopter, helicopters and stationary rotors as well as birds are considered for classification. Moreover, a possibility of distinguishing different number of rotors is considered. The obtained results show the effectiveness of the proposed approach. It provides capability of correct classification with a probability of around 95%.
Bilingual wearable assistive technology for visually impaired persons

Person with visual impairment suffers from various problems and is unable to lead a normal regular life because of their blindness. In this paper, the proposal of a wearable device for visually impaired persons is presented that can detect color and speak out the name of the color in two different languages: Bengali and English, through connected headphone. Bluetooth headphone or wire headphone, even speaker can be interfaced with the proposed system. The proposed device will be able to detect color and turn the color name into sound so that visually impaired persons can recognize it. It will be implemented and developed using a microcontroller, color sensor along with an amplifier and wired or Bluetooth connected headphone. The device will employ a reliable microcontroller platform known as Arduino Nano along with Bluetooth module HC-05, color sensor TCS 3200, LM 386 power amplifier with SD card module. The device will be able to decode color information from everyday resources and convert into sound so that blind persons can easily identify any color.
Successful lean implementation: Organizational culture and soft lean practices

Lean management (LM) is a managerial approach for improving processes based on a complex system of interrelated socio-technical practices. Recently, debate has centered on the role of organizational culture (OC) in LM. This paper aims to contribute to this debate by examining whether plants that successfully implement LM are characterized by a specific OC profile and extensively adopt soft LM practices. Data were analyzed from the High Performance Manufacturing (HPM) project dataset using a multi-group approach. The results revealed that a specific OC profile characterizes successful lean plants; in particular, when compared to unsuccessful lean plants, they show a higher institutional collectivism, future orientation, a humane orientation, and a lower level of assertiveness. While a high level of institutional collectivism, future orientation, and humane orientation are common features of high performers in general, a low level of assertiveness is typical only of successful lean plants. In addition, successful lean plants use soft LM practices more extensively than unsuccessful lean plants (i.e., lean practices concerning people and relations, such as small group problem solving, employees’ training to perform multiple tasks, supplier partnerships, customer involvement, and continuous improvement), while they do not differ significantly in terms of hard LM practices (i.e., lean technical and analytical tools). For managers, the results indicate that, in order to implement LM successfully, it is fundamental to go beyond LM technicalities by adopting soft practices and nurturing the development of an appropriate OC profile.
The effects of prosocial video games on prosocial behaviors: international evidence from correlational, longitudinal, and experimental studies.

Although dozens of studies have documented a relationship between violent video games and aggressive behaviors, very little attention has been paid to potential effects of prosocial games. Theoretically, games in which game characters help and support each other in nonviolent ways should increase both short-term and long-term prosocial behaviors. We report three studies conducted in three countries with three age groups to test this hypothesis. In the correlational study, Singaporean middle-school students who played more prosocial games behaved more prosocially. In the two longitudinal samples of Japanese children and adolescents, prosocial game play predicted later increases in prosocial behavior. In the experimental study, U.S. undergraduates randomly assigned to play prosocial games behaved more prosocially toward another student. These similar results across different methodologies, ages, and cultures provide robust evidence of a prosocial game content effect, and they provide support for the General Learning Model.
Teaching Syntax by Adversarial Distraction

Existing entailment datasets mainly pose problems which can be answered without attention to grammar or word order. Learning syntax requires comparing examples where different grammar and word order change the desired classification. We introduce several datasets based on synthetic transformations of natural entailment examples in SNLI or FEVER, to teach aspects of grammar and word order. We show that without retraining, popular entailment models are unaware that these syntactic differences change meaning. With retraining, some but not all popular entailment models can learn to compare the syntax properly.
On deep learning-based channel decoding

We revisit the idea of using deep neural networks for one-shot decoding of random and structured codes, such as polar codes. Although it is possible to achieve maximum a posteriori (MAP) bit error rate (BER) performance for both code families and for short codeword lengths, we observe that (i) structured codes are easier to learn and (ii) the neural network is able to generalize to codewords that it has never seen during training for structured, but not for random codes. These results provide some evidence that neural networks can learn a form of decoding algorithm, rather than only a simple classifier. We introduce the metric normalized validation error (NVE) in order to further investigate the potential and limitations of deep learning-based decoding with respect to performance and complexity.