nils-herrmann/clean_scirepeval huggingface dataset:
Tracking of Extended Objects with High-Resolution Doppler Radar

In an urban environment, one of the key challenges remains to be the reliable estimation of the other traffic participants' motion state. Due to the highly nonlinear motions in city traffic, an instant and precise estimation of heading direction, velocity, and, particularly, yaw rate is required. Radar sensors are well suited for this task due to their robustness to environmental influences and direct measurement of the radial (Doppler) velocity. High-resolution radars receive multiple reflections from an extended object. In comparison to state-of-the-art approaches, not only is the Doppler velocity of a single reference point taken into account, but also is the distribution of the Doppler velocity across the vehicle analyzed. The velocity profile is derived with characteristic features and a corresponding sample covariance. These are fused into an unscented Kalman filter, resulting in a significant accuracy improvement and a reduction in the latency of the filter to almost zero during a change in motion or initialization. This yields a great improvement in determining the trajectories of potential critical objects, increasing the time to avoid collisions. Furthermore, the approach enables simultaneous identification of the rotation center of the object, which is essential for the tracking of highly dynamic maneuvers. All approaches were implemented and evaluated on a large experimental data set using highly precise reference systems as ground truth. The results show an impressive improvement in the accuracy of the yaw rate estimation of a factor of 3-4 compared with state-of-the-art approaches in a dynamic scenario.
Visual Search and Attention A Signal Detection Theory Approach

combination of features; the target cannot be characterized by a single unique attribute. An example of a conjunction search task is a target that is a bright vertical Background Visual search is an everyday task. One might search for line among distractors that are dark vertical lines and bright tilted lines. Neither brightness nor orientation a familiar face in a crowd, or a memo on a cluttered desktop. The ease of search depends chiefly on how alone defines the target uniquely. Treisman and Gelade (1980) suggest that the second limited-capacity stage, distinguishable the target of search is from the background. For instance, it is hard to find a memo on a which depends on attention, integrates the features that define the target. Attention is therefore thought to be desktop cluttered with paper. The task becomes much easier if the memo is a different color than all the other indispensable for successful conjunction search performance. pieces of paper on the desktop. Attention can also improve visual search. Even if the memo is not dis-I will present a different approach to understanding visual search and attention. This approach shows that tinguishable by color, it is easier to find if attention is drawn to its location. For instance, the telephone might a large body of the psychophysical and physiological visual search results can be explained without invoking ring and as I turn to answer it, I might discover the memo sitting next to the phone. In the course of this review, I a second limited-capacity attentive stage. In the scope of this review, visual attention plays a role when observ-will consider visual search and attention, in turn, and will present converging psychophysical and physiological ers are explicitly asked to attend to a location or feature, or when they are implicitly cued to a location or feature. evidence on the mechanisms that underlie these two phenomena. There is a growing body of literature that suggests that visual attention selects objects rather than locations, The task of finding a target among distractors is in general referred to as visual search. Typically there is a although the independence of attention to objects and to locations is still being debated (see Scholl, 2001 for single target that differs from the distractors along one or more dimensions. Let us start with the simple case a review). In some cases, attention has been shown to select objects as complex …
Next-generation sequencing data interpretation: enhancing reproducibility and accessibility

Areas of life sciences research that were previously distant from each other in ideology, analysis practices and toolkits, such as microbial ecology and personalized medicine, have all embraced techniques that rely on next-generation sequencing instruments. Yet the capacity to generate the data greatly outpaces our ability to analyse it. Existing sequencing technologies are more mature and accessible than the methodologies that are available for individual researchers to move, store, analyse and present data in a fashion that is transparent and reproducible. Here we discuss currently pressing issues with analysis, interpretation, reproducibility and accessibility of these data, and we present promising solutions and venture into potential future developments.
Video gameplay, personality and academic performance

The relationship between video gameplay, video game genre preference, personality, and GPA was investigated in an online correlational study with university students. In addition to administering selfreport measures of GPA and personality, we asked three different questions regarding styles of video gameplay. The first asked the average time spent playing video games per week (habitual players), the second asked the total time spent playing favorite video games (selective players), and the third asked the number of different video games played in a year (diverse players). Students who were medium in selective player style (spent 11–50 h) had significantly higher GPAs than students low on selective player style (spent 0–10 h). Students high on habitual playing style (7 or more hours a week) showed significantly lower levels of Conscientiousness compared to students low on habitual playing style (0–1 h a week). Students who were high on the diverse style (i.e., 7 or more games played a year) showed significantly higher Openness scores than students low on the diverse style (0–3 games a year). Finally, several notable relations were found between video game genre preference, GPA, and personality. Results are discussed in terms of the positive implications of video gameplay on academic performance.
Treatment with the Self-Discovery Camp (SDiC) improves Internet gaming disorder.

Internet gaming disorder (IGD) is a novel behavioral addiction that influences the physical, mental, and social aspects of health due to excessive Internet gaming. One type of intensive treatment for IGD is the therapeutic residential camp (TRC), which comprises many types of therapies, including psychotherapy, psychoeducational therapy, and cognitive behavioral therapy. The TRC was developed in South Korea and has been administered to many patients with IGD; however, its efficacy in other countries remains unknown. We investigated the efficacy of the Self-Discovery Camp (SDiC), a Japanese version of a TRC, and the correlations between individual characteristics and outcome measures.



We recruited 10 patients with IGD (all male, mean age=16.2years, diagnosed using the DSM-5) to spend 8 nights and 9days at the SDiC. We measured gaming time as well as self-efficacy (using the Stages of Change Readiness and Treatment Eagerness Scale, a measure of therapeutic motivation and problem recognition).



Total gaming time was significantly lower 3months after the SDiC. Problem recognition and self-efficacy towards positive change also improved. Furthermore, there was a correlation between age of onset and problem recognition score.



Our results demonstrate the effectiveness of the SDiC for IGD, especially regarding gaming time and self-efficacy. Additionally, age of onset may be a useful predictor of IGD prognosis. Further studies with larger sample sizes and control groups, and that target long-term outcomes, are needed to extend our understanding of SDiC efficacy.
New Metrics for the Reliability of Approximate and Probabilistic Adders

Addition is a fundamental function in arithmetic operation; several adder designs have been proposed for implementations in inexact computing. These adders show different operational profiles; some of them are approximate in nature while others rely on probabilistic features of nanoscale circuits. However, there has been a lack of appropriate metrics to evaluate the efficacy of various inexact designs. In this paper, new metrics are proposed for evaluating the reliability as well as the power efficiency of approximate and probabilistic adders. Reliability is analyzed using the so-called sequential probability transition matrices (SPTMs). Error distance (ED) is initially defined as the arithmetic distance between an erroneous output and the correct output for a given input. The mean error distance (MED) and normalized error distance (NED) are then proposed as unified figures that consider the averaging effect of multiple inputs and the normalization of multiple-bit adders. It is shown that the MED is an effective metric for measuring the implementation accuracy of a multiple-bit adder and that the NED is a nearly invariant metric independent of the size of an adder. The MED is, therefore, useful in assessing the effectiveness of an approximate or probabilistic adder implementation, while the NED is useful in characterizing the reliability of a specific design. Since inexact adders are often used for saving power, the product of power and NED is further utilized for evaluating the tradeoffs between power consumption and precision. Although illustrated using adders, the proposed metrics are potentially useful in assessing other arithmetic circuit designs for applications of inexact computing.
Toward Non-Intrusive Load Monitoring via Multi-Label Classification

Demand-side management technology is a key element of the proposed smart grid, which will help utilities make more efficient use of their generation assets by reducing consumers' energy demand during peak load periods. However, although some modern appliances can respond to price signals from the utility companies, there is a vast stock of older appliances that cannot. For such appliances, utilities must infer what appliances are operating in a home, given only the power signals on the main feeder to the home (i.e., the home's power consumption must be disaggregated into individual appliances). We report on an in-depth investigation of multi-label classification algorithms for disaggregating appliances in a power signal. A systematic review of this research topic shows that this class of algorithms has received little attention in the literature, even though it is arguably a more natural fit to the disaggregation problem than the traditional single-label classifiers used to date. We examine a multi-label meta-classification framework (RAkEL), and a bespoke multi-label classification algorithm (MLkNN), employing both time-domain and wavelet-domain feature sets. We test these classifiers on two real houses from the Reference Energy Disaggregation Dataset. We found that the multilabel algorithms are effective and competitive with published results on the datasets.
Cyber , Nano , and AGI Risks : Decentralized Approaches to Reducing Risks

The aim of this paper, rather than attempting to present one coherent strategy for reducing existential risks, is to introduce a variety of possible options with the goal of broadening the discussion and inviting further investigation. Two themes appear throughout: (1) the proposed approaches for risk reduction attempt to avoid the dangers of centralized “solutions,” and (2) cybersecurity is not treated as a separate risk. Instead, trustworthy cybersecurity is a prerequisite for the success of our proposed approaches to risk reduction. Our focus is on proposing pathways for reducing risks from advanced nanotechnology and artificial general intelligence. Nanotechnology can be divided into stages; even at the most advanced stage, society should be less worried about biology-style accidents than deliberate abuse. Development of nanotech weapons would not be detectable by current weapons monitoring techniques. An automated monitoring system, if based on sufficiently secure software foundations and physical arrangements, could serve as the basis for an arms control enforcement mechanism. Design needs to be open and decentralized to build the required public trust. Civilization, taken as a whole, is already a superintelligence. It is vastly more intelligent than any individual, it is already composed of both human and machine intelligences, and its intelligence is already increasing at an exponentially accelerating rate. Civilization as a whole does not “want anything”; it has no utility function. But it does have a tropism—it tends to grow in certain 1 Currently at Google Inc. 1 directions. To the extent that its dominant dynamic emerges from non-coercive, non-violent, voluntary interactions, it is already shaped by human values and desires. It tends, imperfectly, to climb Pareto preferred paths. Society would address the value alignment problem more effectively by strengthening this dynamic rather than trying to replace it. No designed utility function would clearly serve human happiness better, and no replacement for civilization’s dynamics is likely to be adopted anyway. While still controversial, there is increasing concern that once artificial general intelligence fully surpasses the human level, human skills will have little or no economic value. The rate of economic growth will be extraordinary, but humans will have little comparative advantage. Will civilization still serve human preferences? When growth is extraordinary, so are returns to capital. The least-disruptive approach may be a one-time, gradual distribution of tradeable rights to as-yet unclaimed resources in space.
Noxim: An open, extensible and cycle-accurate network on chip simulator

Emerging on-chip communication technologies like wireless Networks-on-Chip (WiNoCs) have been proposed as candidate solutions for addressing the scalability limitations of conventional multi-hop NoC architectures. In a WiNoC, a subset of network nodes are equipped with a wireless interface which allows them long-range communication in a single hop. This paper presents Noxim, an open, configurable, extendible, cycle-accurate NoC simulator developed in SystemC which allows to analyze the performance and power figures of both conventional wired NoC and emerging WiNoC architectures.
Roles of Pre-Training and Fine-Tuning in Context-Dependent DBN-HMMs for Real-World Speech Recognition

Recently, deep learning techniques have been successfully applied to automatic speech recognition tasks -first to phonetic recognition with context-independent deep belief network (DBN) hidden Markov models (HMMs) and later to large vocabulary continuous speech recognition using context-dependent (CD) DBN-HMMs. In this paper, we report our most recent experiments designed to understand the roles of the two main phases of the DBN learning -pre-training and fine tuning -in the recognition performance of a CD-DBN-HMM based large-vocabulary speech recognizer. As expected, we show that pre-training can initialize weights to a point in the space where fine-tuning can be effective and thus is crucial in training deep structured models. However, a moderate increase of the amount of unlabeled pre-training data has an insignificant effect on the final recognition results as long as the original training size is sufficiently large to initialize the DBN weights. On the other hand, with additional labeled training data, the fine-tuning phase of DBN training can significantly improve the recognition accuracy.
Seed priming to alleviate salinity stress in germinating seeds.

Salinity is one of the major abiotic stresses that affect crop production in arid and semiarid areas. Seed germination and seedling growth are the stages most sensitive to salinity. Salt stress causes adverse physiological and biochemical changes in germinating seeds. It can affect the seed germination and stand establishment through osmotic stress, ion-specific effects and oxidative stress. The salinity delays or prevents the seed germination through various factors, such as a reduction in water availability, changes in the mobilization of stored reserves and affecting the structural organization of proteins. Various techniques can improve emergence and stand establishment under salt conditions. One of the most frequently utilized is seed priming. The process of seed priming involves prior exposure to an abiotic stress, making a seed more resistant to future exposure. Seed priming stimulates the pre-germination metabolic processes and makes the seed ready for radicle protrusion. It increases the antioxidant system activity and the repair of membranes. These changes promote seed vigor during germination and emergence under salinity stress. The aim of this paper is to review the recent literature on the response of plants to seed priming under salinity stress. The mechanism of the effect of salinity on seed germination is discussed and the seed priming process is summarized. Physiological, biochemical and molecular changes induced by priming that lead to seed enhancement are covered. Plants' responses to some priming agents under salinity stress are reported based on the best available data. For a great number of crops, little information exists and further research is needed.
The Sensemaking-Coevolution-Implementation Theory of software design

Understanding software design practice is critical to understanding modern information systems development. New developments in empirical software engineering, information systems design science and the interdisciplinary design literature combined with recent advances in process theory and testability have created a situation ripe for innovation. Consequently, this paper utilizes these breakthroughs to formulate a process theory of software design practice: SensemakingCoevolution-Implementation Theory explains how complex software systems are created by collocated software development teams in organizations. It posits that an independent agent (design team) creates a software system by alternating between three activities: organizing their perceptions about the context, mutually refining their understandings of the context and design space, and manifesting their understanding of the design space in a technological artifact. This theory development paper defines and illustrates Sensemaking-Coevolution-Implementation Theory, grounds its concepts and relationships in existing literature, conceptually evaluates the theory and situates it in the broader context of information systems development.
A design for an electronically-steerable holographic antenna with polarization control

We present a design for an electronic-steerable holographic antenna with polarization control composed of a radial array of Ku-band, electronically-steerable, surface-wave waveguide (SWG) artificial-impedance-surface antennas (AISA). The antenna operates by launching surface waves into each of the SWGs via a central feed network. The surface-wave impedance is electronically controlled with varactor-tuned impedance patches. The impedance is adjusted to scan the antenna in elevation, azimuth and polarization. The radial symmetry allows for 360° azimuthal steering. If constructed with previously-demonstrated SWG AISAs, it is capable of scanning in elevation from -75° to 75° with gain variation of less than 3 dB. The polarization can be switched among V-Pol, H-Pol, LHCP and RHCP at will.
MSc THESIS Hardware Acceleration of BWA-MEM Genome Mapping Application

Faculty of Electrical Engineering, Mathematics and Computer Science CE-MS-2014 Next Generation Sequencing technologies have had a tremendous impact on our understanding of DNA and its role in living organisms. The cost of DNA sequencing has decreased drastically over the past decade, leading the way for personalised genomics. Sequencers provide millions of fragments of DNA (termed short reads), which have to be aligned aginst a reference genome to reconstruct the full information of the DNA molecule under study. Processing short reads requires large computational resources, with many specialised computing platforms now being used to accelerate software aligners. We take up the challenge of accelerating a well know sequence alignment tool called Burrows Wheeler aligner on the Convey Hybrid Computing platform, which has FPGAs as co-processors. The focus of the research is to accelerate the BWA-MEM algorithm of the Burrows Wheeler aligner on the Convey HC-2 platform. The implementation was carried out using the Vivado HLS tool. The architectures proposed are targeted to overcome the memory bottleneck of the application. Two architectures are proposed, the Base architecture and the Batch architecture meant to address the memory bottleneck. Simulations were performed for the intended platform and it was found that, the Batch architecture is 18% faster than the Base architecture for reads with similar run time characteristics. The architectures provide possibilities of further pipelining and implementation of more cores, which is expected to provide better performance than the current implementation. Hardware Acceleration of BWA-MEM Genome Mapping Application
Analyzing feature trajectories for event detection

We consider the problem of analyzing word trajectories in both time and frequency domains, with the specific goal of identifying important and less-reported, periodic and aperiodic words. A set of words with identical trends can be grouped together to reconstruct an event in a completely un-supervised manner. The document frequency of each word across time is treated like a time series, where each element is the document frequency - inverse document frequency (DFIDF) score at one time point. In this paper, we 1) first applied spectral analysis to categorize features for different event characteristics: important and less-reported, periodic and aperiodic; 2) modeled aperiodic features with Gaussian density and periodic features with Gaussian mixture densities, and subsequently detected each feature's burst by the truncated Gaussian approach; 3) proposed an unsupervised greedy event detection algorithm to detect both aperiodic and periodic events. All of the above methods can be applied to time series data in general. We extensively evaluated our methods on the 1-year Reuters News Corpus  and showed that they were able to uncover meaningful aperiodic and periodic events.
Detecting criminal organizations in mobile phone networks

The study of criminal networks using traces from heterogeneous communication media is acquiring increasing importance in nowadays society. The usage of communication media such as phone calls and online social networks leaves digital traces in the form of metadata that can be used for this type of analysis. The goal of this work is twofold: first we provide a theoretical framework for the problem of detecting and characterizing criminal organizations in networks reconstructed from phone call records. Then, we introduce an expert system to support law enforcement agencies in the task of unveiling the underlying structure of criminal networks hidden in communication data. This platform allows for statistical network analysis, community detection and visual exploration of mobile phone network data. It allows forensic investigators to deeply understand hierarchies within criminal organizations, discovering members who play central role and provide connection among sub-groups. Our work concludes illustrating the adoption of our computational framework for a real-word criminal investigation.