Miracle-dz/UniFAR-FTUs huggingface dataset:
Model-free robot anomaly detection

Safety is one of the key issues in the use of robots, especially when human-robot interaction is targeted. Although unforeseen environment situations, such as collisions or unexpected user interaction, can be handled with specially tailored control algorithms, hard- or software failures typically lead to situations where too large torques are controlled, which cause an emergency state: hitting an end stop, exceeding a torque, and so on-which often halts the robot when it is too late. No sufficiently fast and reliable methods exist which can early detect faults in the abundance of sensor and controller data. This is especially difficult since, in most cases, no anomaly data are available. In this paper we introduce a new robot anomaly detection system (RADS) which can cope with abundant data in which no or very little anomaly information is present.
On Space–Time Coding With Pulse Position and Amplitude Modulations for Time-Hopping Ultra-Wideband Systems

In this work, we propose novel families of space-time (ST) block codes that can be associated with impulse radio ultra-wideband (IR-UWB) communication systems. The carrier-less nature of this nonconventional totally real transmission technique necessitates the construction of new suitable coding schemes. In fact, the last generation of complex-valued ST codes (namely, the perfect codes) cannot be associated with IR-UWB systems where the phase reconstitution at the receiver side is practically infeasible. On the other hand, while the perfect codes were considered mainly with quadrature amplitude modulation (QAM) and hexagonal (HEX) constellations, IR-UWB systems are often associated with pulse-position modulation (PPM) and hybrid PPM-PAM (pulse-amplitude modulation) constellations. In this paper, instead of adopting the classical approach of constructing ST codes over infinite fields or for the perfect codes), we study the possibility of constructing modulation-specific codes that are exclusive to PPM and PPM-PAM. The proposed full-rate codes are totally real, information lossless, and have a uniform average energy per transmit antenna. They permit to achieve a full diversity order with any number of transmit antennas. In some situations, the proposed schemes have an optimal nonvanishing coding gain and satisfy all the construction constraints of the perfect codes in addition to the constraint of being totally real. Simulations performed over realistic indoor UWB channels showed that the proposed schemes outperform the best known codes constructed from cyclic division algebras.
The Effect of Lifelong Musicianship on Age-related Changes in Auditory Processing

Age-related declines in hearing abilities are common and can be attributed to changes in the peripheral and central levels of the auditory system. Although central auditory processing is enhanced in younger musicians, the influence of lifelong musicianship on age-related decline in central auditory processing has not yet been investigated. Therefore, the purpose of this dissertation was to investigate whether lifelong musicianship can mitigate age-related decline in central auditory processing. In the first experiment, age-related declines on four hearing assessments were compared between musicians and non-musicians. Speech-in-noise and gap-detection thresholds were found to decline at a slower rate in musicians, providing an increasing advantage with age. Furthermore, musicians had a lifelong advantage in detecting a mistuned harmonic, although the rate of age-related decline was similar for both musicians and non-musicians. Importantly, there was no significant effect of musicianship on pure-tone thresholds, suggesting that lifelong musicianship can mitigate age-related decline in central but not peripheral auditory processing. To test this hypothesis, a second experiment compared auditory evoked responses (AERs) between groups of older and younger musicians and iii non-musicians. Results indicated that exogenous neural activity was enhanced in musicians, but that age-related changes were similar between musicians and non-musicians. Furthermore, endogenous, attention-dependent neural activity was enhanced in older adults, suggesting a compensatory cognitive strategy. Importantly, endogenous activity was preferentially enhanced in older musicians, suggesting that lifelong musicianship enhanced cognitive processes related to auditory perception. In the final experiment, the ability to segregate simultaneous sounds was tested in older and younger musicians and non-musicians by using a mistuned harmonic paradigm, where AERs to harmonic complexes were compared to AERs when one of the harmonics was mistuned. Results indicated that musical training in older adults has little effect on early automatic registration of the mistuned harmonic. In contrast, late attention-dependent activity, associated with the perception of the mistuned harmonic as a separate sound, was influenced by musical training in older adults, suggesting that lifelong musicianship preserves or enhances cognitive components of concurrent sound segregation. In summary, musical training was found to reduce age-related decline in hearing abilities due to enhanced central processing of auditory information. iv Acknowledgments
How the Lower Adult Male Voice and the Male Falsetto Voice Affect Children's Vocal Accuracy

Male elementary music educators are faced with the dilemma concerning which register to use when vocally modeling for students. The lower adult male voice is usually more comfortable, more natural, and easier for the teacher to sing. If the teacher sings in this lower voice, however, students must match pitch an octave higher and in a different timbre than what is heard, a potentially difficult skill for children. Conversely, modeling an octave higher in the falsetto voice eliminates the need for children to transpose what is modeled to an octave higher in order to match that pitch. Children can imitate the teacher in the same register. Singing in the higher falsetto register, however, has disadvantages. It may be unfamiliar or uncomfortable to male educators who would prefer to sing in their lower, more natural voice. When children hear their teacher modeling in the falsetto register, they may perceive that their teacher is singing in the top end of his range, and they may try to do so as well. This may result in children singing an octave higher than desired. In addition, the timbre of the falsetto voice may be difficult for children to match with their voices. The unfamiliarity of using falsetto can often be overcome with practice on the part of the male music educator. It is unclear, however, whether children find
EHD Flow and Collection Efficiency of a DBD ESP in Wire-to-Plane and Plane-to-Plane Configurations

In this paper, particle velocity fields inside three electrostatic precipitators (ESPs) are investigated experimentally using particle image velocimetry (PIV). The reference case is a typical wire-to-plane ESP under negative and positive dc high voltages. The two other ESPs use an ac high voltage to generate a dielectric barrier discharge (DBD) in wire-to-plane and plane-to-plane configurations. The main objective of this paper is to analyze the effect of the ionic wind on the particle collection efficiency in such systems. The high voltage magnitude and the frequency are the major parameters taken into account. With the wire-to-plane ESPs, PIV results show a strong interaction between the primary flow and the secondary flow (ionic wind). Near the wire electrode, the strong electric forces move the particles from the central part of the channel to the plate electrodes. Within the drift region, the velocity magnitude depends essentially on the balance between the electric and viscous forces. With this configuration, the particle trajectory is 3-D. In the case of the plane-to-plane ESP, a 2-D analysis of the time-averaged flow can be accepted. The time-averaged flow is only modified in the boundary layer, which becomes thinner. The time-averaged effect of the ionic wind on the primary flow in such a configuration is negligible. The correlation between the electrohydrodynamic flow and the collection efficiency shows that increasing the ionic wind magnitude did not improve necessarily the electrostatic precipitation effectiveness of submicrometer particles, particularly using DBD precipitators.
Efficient interpreter optimizations for the JVM

The Java virtual machine is a popular target for many language implementers. Due to the unusually poor performance of hosted interpreters, many programming language implementers resort to implementing a custom compiler that emits Java bytecode instead. We studied performance of these hosted interpreters targeting the JVM and identified common bottlenecks preventing their efficient execution. First, similar to interpreters written in C/C++, instruction dispatch is expensive on the JVM. Second, Java's array semantics dictate expensive runtime exception checks, which negatively affect array performance essential to interpreters. We present two optimizations targeting these bottlenecks and show that the performance of the optimized interpreters increases dramatically: we report speedups by a factor of up to 2.45 over the Jython interpreter, and 3.57 over the Rhino interpreter respectively. Furthermore, the performance attained through our optimizations is comparable with custom compiler performance. We provide an easily accessible annotation-based interface to enable our optimizations. Thus, interpreter implementers can expect substantial performance boosts in a matter of hours of implementation effort.
Using Watson for Supporting Design Creativity

We describe an experiment in using IBM’s Watson tool in a Georgia Tech Spring 2015 class on compu-tational creativity. The semester-long projects in the class used Watson as a tool to develop cognitive assistants in support of biologically inspired design, a well-established paradigm for design creativity. In this paper, we describe the experiment in using Watson as a creativity support tool and present two projects in detail. We draw lessons for using Watson for constructing cognitive assistants to support design creativity.
A Novel Speculative Multithreading Parallelization Method in Chip Multiprocessor Systems

Chip multiprocessors have become mainstream processors in recent years. In this paper, we propose a novel speculative multithreading parallelization method for parallelizing a sequential program into multiple threads. In our method, extended program dependence graph and topological sort are used to analyze code dependency. With the help of dynamic profiling, we exploit thread level parallelism in loops and the remaining code regions by analyzing control and data speculation in general purpose applications. Using an initial automatic compiler implementation and a validated processor model, this paper demonstrates significant gains using speculation for 4-core chip multiprocessor models running a variety of applications.
App2Vec: Vector modeling of mobile apps and applications

We design a way to model apps as vectors, inspired by the recent deep learning approach to vectorization of words called word2vec. Our method relies on how users use apps. In particular, we visualize the time series of how each user uses mobile apps as a “document”, and apply the recent word2vec modeling on these documents, but the novelty is that the training context is carefully weighted by the time interval between the usage of successive apps. This gives us the app2vec vectorization of apps. We apply this to industrial scale data from Yahoo! and (a) show examples that app2vec captures semantic relationships between apps, much as word2vec does with words, (b) show using Yahoo! 's extensive human evaluation system that 82% of the retrieved top similar apps are semantically relevant, achieving 37% lift over bag-of-word approach and 140% lift over matrix factorization approach to vectorizing apps, and (c) finally, we use app2vec to predict app-install conversion and improve ad conversion prediction accuracy by almost 5%. This is the first industry scale design, training and use of app vectorization.
Optimization of Regular Expression Pattern Matching Circuits on FPGA

Regular expressions are widely used in network intrusion detection system (NIDS) to represent patterns of network attacks. Since traditional software-only NIDS cannot catch up to the speed advance of networks, many previous works propose hardware architectures on FPGA to accelerate attack detection. The challenge of hardware implementation is to accommodate the regular expressions to FPGAs of the large number of attacks. Although the minimization of logic equations has been studied intensively in the CAD area, the minimization of multiple regular expressions has been largely neglected. This paper presents an architecture allowing our algorithm to extract and share common sub-regular expressions. Experimental results show that our sharing scheme significantly reduces the area of regular expression circuits
Relationships Between (Step)Parents and Adult (Step)Children: Explaining Influences on Life Satisfaction and Marital Quality

ABSTRACT The purpose of this study was to examine important influences of adult (step)children’s relationships with their biological fathers, biological mothers, and resident stepparents on their life satisfaction and marital quality and the moderating role of stepparent gender. The sample (N = 215) was from Wave 3 of the National Survey of Families and Households (NSFH). Results illustrate that (a) biological mothers and stepparents positively influenced life satisfaction among adult (step)children regardless of stepfamily type; and (b) that the influence of parent–child relationship quality on the adult child’s marital quality did vary as a function of stepfamily type. Specifically, there was a positive link between current stepmother–child relationship quality and the focal child’s current marital quality. The opposite link was found for those reared in stepfather households.
Allogeneic Transplantation of an Adipose-Derived Stem Cell Sheet Combined With Artificial Skin Accelerates Wound Healing in a Rat Wound Model of Type 2 Diabetes and Obesity

One of the most common complications of diabetes is diabetic foot ulcer. Diabetic ulcers do not heal easily due to diabetic neuropathy and reduced blood flow, and nonhealing ulcers may progress to gangrene, which necessitates amputation of the patient’s foot. This study attempted to develop a new cell-based therapy for nonhealing diabetic ulcers using a full-thickness skin defect in a rat model of type 2 diabetes and obesity. Allogeneic adipose-derived stem cells (ASCs) were harvested from the inguinal fat of normal rats, and ASC sheets were created using cell sheet technology and transplanted into full-thickness skin defects in Zucker diabetic fatty rats. The results indicate that the transplantation of ASC sheets combined with artificial skin accelerated wound healing and vascularization, with significant differences observed 2 weeks after treatment. The ASC sheets secreted large amounts of several angiogenic growth factors in vitro, and transplanted ASCs were observed in perivascular regions and incorporated into the newly constructed vessel structures in vivo. These results suggest that ASC sheets accelerate wound healing both directly and indirectly in this diabetic wound-healing model. In conclusion, allogeneic ASC sheets exhibit potential as a new therapeutic strategy for the treatment of diabetic ulcers.
Modeling musical sounds with an interpolating state model

A computationally efficient algorithm is proposed for modeling and coding the time-varying spectra of musical sounds. The aim is to encode individual data sets and not the statistical properties of the sounds. A given sequence of acoustic feature vectors is modeled by finding such a set of “states” (anchor points in the feature space) that the input data can be efficiently represented by interpolating between them. The achieved modeling accuracy for a database of musical sounds was approximately two times better than that of a conventional “vector quantization” model where the input data was k-means clustered and the input data vectors were then replaced by their corresponding cluster centroids. The computational complexity of the proposed algorithm as a function of the input sequence length T is O(TlogT).
Vitamin D and Weight Cycling: Impact on Injury, Illness, and Inflammation in Collegiate Wrestlers

This study explored the link between vitamin D status and frequency of skin infections, inflammation, and injury in college wrestlers during an academic year. Methods: Serum 25-hydroxyvitamin D (25(OH)D) (n = 19), plasma cytokine (TNF-α, IL-6, IL-10) (n = 18) concentrations, and body weight/composition were measured and injury/illness/skin infection data were collected in fall, winter, and spring. Results: In the fall, 74% of wrestlers had vitamin D concentrations <32 ng/mL which increased to 94% in winter and spring. Wrestlers lost an average of 3.4 ± 3.9 kg (p < 0.001) during the season with corresponding decreases in fat mass and increases in lean mass (p < 0.01). An inverse association between 25(OH)D concentrations and total body mass and body fat percentage was observed at all-time points (p < 0.01). Concentrations of cytokines were highly variable among individuals and did not change across time (p > 0.05). Correlations between vitamin D status, cytokines, or frequency of illness, injury, or skin infections were not observed. Conclusions: A high prevalence of vitamin D insufficiency (<32 ng/mL) and deficiency (<20 ng/mL) was observed in wrestlers and was associated with higher adiposity. It remains unclear if higher vitamin D status would reduce injury, illness, and skin infection risk.
Building Spoken Language Collaborative Interface Agents

This article reports on experiences with collaborative interface agents using spoken dialogue to collaborate with users working with graphical user interface applications. Collaborative interface agents provide users with the means to manage tasks and leave many of the details to the agent. The article presents four different collaborative agents and associated applications. It reports on lessons learned in building these agents, including the importance of choosing tasks that relieve the user of unnecessary detail, and providing speech capabilities that are useable for a wide range of users. In particular, the article reports on the success in developing a subset language for speech understanding in one of the agents. Finally, the article discusses the advantages of us-ing the explanation capabilities in collaborative agents to help users learn new interface functionality
The Herpes Simplex Virus gE-gI Complex Facilitates Cell-to-Cell Spread and Binds to Components of Cell Junctions

ABSTRACT The herpes simplex virus (HSV) glycoprotein complex gE-gI mediates the spread of viruses between adjacent cells, and this property is especially evident for cells that form extensive cell junctions, e.g., epithelial cells, fibroblasts, and neurons. Mutants lacking gE or gI are not compromised in their ability to enter cells as extracellular viruses. Therefore, gE-gI functions specifically in the movement of virus across cell-cell contacts and, as such, provides a molecular handle on this poorly understood process. We expressed gE-gI in human epithelial cells by using replication-defective adenovirus (Ad) vectors. gE-gI accumulated at lateral surfaces of the epithelial cells, colocalizing with the adherens junction protein β-catenin but was not found on either the apical or basal plasma membranes and did not colocalize with ZO-1, a component of tight junctions. In subconfluent monolayers, gE-gI was found at cell junctions but was absent from those lateral surfaces not in contact with another cell, as was the case for β-catenin. Similar localization of gE-gI to cell junctions was observed in HSV-infected epithelial cells. By contrast, HSV glycoprotein gD, expressed using a recombinant Ad vectors, was found primarily along the apical surfaces of cells, with little or no protein found on the basal or lateral surfaces. Expression of gE-gI without other HSV polypeptides did not cause redistribution of either ZO-1 or β-catenin or alter tight-junction functions. Together these results support a model in which gE-gI accumulates at sites of cell-cell contact by interacting with junctional components. We hypothesize that gE-gI mediates transfer of HSV across cell junctions by virtue of these interactions with cell junction components.
Applications of Object Oriented Bayesian Networks for Causal Analysis of Process Disturbances

We discuss a hybrid approach for causal analysis of disturbances in industrial process operation. It represents a combination of OOBN with first level diagnostic packages and physical models serving as agents in the system design and providing evidence for automated reasoning on abnormality in process operation. The aim is causal analysis of non-measurable disturbances as a decision advice complement to the distributed control system (DCS). The approach includes prediction of signals' level-trend development, risk assessment for disturbance analysis and predictive maintenance on demand. The methodology has been applied on a screening process with a pressure-flow network in a Pulp Mil.
Dynamic energy management for hybrid electric vehicle based on approximate dynamic programming

In this paper, an approximate dynamic programming (ADP) based strategy for real-time energy control of parallel hybrid electric vehicles(HEV) is presented. The aim is to develop a fuel-optimal control which is not relying on the priori knowledge of the future driving conditions (global optimal control), but only upon the current system operation. Approximate dynamic programming is an on-line learning method, which controls the system while simultaneously learning its characteristics in real time. A suboptimal energy control is then obtained with a proper definition of a cost function to be minimized at each time instant. The cost function includes the fuel consumption, emissions and the deviation of battery soc. Our approach guarantees an optimization of vehicle performance and an adaptation to driving conditions. Simulation results over standard driving cycles are presented to demonstrate the effectiveness of the proposed stochastic approach. It was found that the obtained ADP control algorithm outperforms a traditional rule-based control strategy.
Challenges and Issues in Trajectory Streams Clustering upon a Sliding-Window Model

The proliferation of location-acquisition devices and thriving development of social Web sites enable analyzing users' movement behaviors and detecting social events in dynamic trajectory streams. In this paper, we firstly analyze the challenges in trajectory stream clustering, and then depict a three-part framework to deal with this issue, that includes (i) trajectory data pre-processing for higher quality, (ii) online micro-clustering to summarize a large number of microclusters, and (iii) offline macro-clustering to form the resulting clusters. Particularly, we present the in-cluster maintenance strategy for online clustering evolving trajectory streams over sliding windows. It can eliminate the obsolete data while adaptively maintaining the summary statistics for continuously arriving location data, and thus avoid performance degradation with minimal harm to result quality.