Real-time crowdsourced maps such as Waze provide timely updates on traffic, congestion, accidents and points of interest. In this paper, we demonstrate how lack strong location authentication allows creation software-based Sybil devices that expose map systems to a variety security privacy attacks. Our experiments show single device with limited resources can cause havoc Waze, reporting false congestion automatically rerouting user traffic. More importantly, describe techniques generate at...

Augmented Reality (AR) experiences tightly associate virtual contents with environmental entities. However, the dissimilarity of different environments limits adaptive AR content behaviors under large-scale deployment. We propose ScalAR, an integrated workflow enabling designers to author semantically in Virtual (VR). First, potential consumers collect local scenes a semantic understanding technique. ScalAR then synthesizes numerous similar scenes. In VR, designer authors contents'...

Explainable AI (XAI) has established itself as an important component of AI-driven interactive systems. With Augmented Reality (AR) becoming more integrated in daily lives, the role XAI also becomes essential AR because end-users will frequently interact with intelligent services. However, it is unclear how to design effective experiences for AR. We propose XAIR, a framework that addresses when, what, and provide explanations output The was based on multi-disciplinary literature review HCI...

Recognition of human behavior plays an important role in context-aware applications. However, it is still a challenge for end-users to build personalized applications that accurately recognize their own activities. Therefore, we present CAPturAR, in-situ programming tool supports users rapidly author by referring previous We customize AR head-mounted device with multiple camera systems allow non-intrusive capturing user's daily During authoring, reconstruct the captured data animated avatar...

Machine tasks in workshops or factories are often a compound sequence of local, spatial, and body-coordinated human-machine interactions. Prior works have shown the merits video-based augmented reality (AR) tutoring systems for local tasks. However, due to lack bodily representation tutor, they not as effective spatial We propose avatars an additional tutor existing AR instructions. In order understand design space presence machine tasks, we conduct comparative study with 32 users. aim...

Modern manufacturing processes are in a state of flux, as they adapt to increasing demand for flexible and self-configuring production. This poses challenges training workers rapidly master new machine operations processes, i.e. tasks. Conventional in-person is effective but requires time effort experts each worker trained not scalable. Recorded tutorials, such video-based or augmented reality (AR), permit more efficient scaling. However, unlike tutoring, existing recorded tutorials lack the...

Freehand gesture is an essential input modality for modern Augmented Reality (AR) user experiences. However, developing AR applications with customized hand interactions remains a challenge end-users. Therefore, we propose GesturAR, end-to-end authoring tool that supports users to create in-situ freehand through embodied demonstration and visual programming. During authoring, can intuitively demonstrate the inputs while referring spatial temporal context. Based on taxonomy of gestures in AR,...

We present GhostAR, a time-space editor for authoring and acting Human-Robot-Collaborative (HRC) tasks in-situ. Our system adopts an embodied approach in Augmented Reality (AR), spatially editing the actions programming robots through demonstrative role-playing. propose novel HRC workflow that externalizes user's as editable AR ghost, allowing situated visual referencing, realistic animated simulation, collaborative action guidance. develop dynamic time warping (DTW) based collaboration...

Real-time crowdsourced maps, such as Waze provide timely updates on traffic, congestion, accidents, and points of interest. In this paper, we demonstrate how lack strong location authentication allows creation software-based Sybil devices that expose map systems to a variety security privacy attacks. Our experiments show single device with limited resources can cause havoc Waze, reporting false congestion accidents automatically rerouting user traffic. More importantly, describe techniques...

Choosing a good location when opening new store is crucial for the future success of business. Traditional methods include offline manual survey, analytic models based on census data, which are either unable to adapt dynamic market or very time consuming. The rapid increase availability big data from various types mobile devices, such as online query and positioning provides us with possibility develop automatic accurate data- driven prediction business site selection. In this paper, we...

Abstract The renormalization group analysis has been proposed to eliminate secular terms in perturbation solutions of differential equations and thus expand the domain their validity. Here we extend method treat periodic orbits or limit cycles. Interesting normal forms could be derived through a generalization concept 'resonance', which offers nontrivial analytic approximations. Compared with traditional techniques such as multi-scale methods, current scheme proceeds very straightforward...

Most of the federated learning techniques are limited to homogeneous model fusion. With rapid growth smart applications on resource-constrained edge devices, it becomes a barrier accommodate their heterogeneous computing power and memory in real world. Federated Distillation is promising alternative enable aggregation from models. However, effectiveness knowledge transfer still remains elusive under shadow distinct representation In this paper, we approach an adversarial perspective...

Augmented Reality (AR), which blends physical and virtual worlds, presents the possibility of enhancing traditional toy design. By leveraging bidirectional virtual-physical interactions between humans designed artifact, such AR-enhanced toys can provide more playful interactive experiences for toys. However, designers are constrained by complexity technical difficulties current AR content creation processes. We propose MechARspace, an immersive authoring system that supports users to create...

Vision-based 3D pose estimation has substantial potential in hand-object interaction applications and requires user-specified datasets to achieve robust performance. We propose ARnnotate, an Augmented Reality (AR) interface enabling end-users create custom data using a hand-tracking-capable AR device. Unlike other dataset collection strategies, ARnnotate first guides user manipulate virtual bounding box records its poses the user's hand joint positions as labels. By leveraging spatial...

Social media and Web services have provided a notable number of multimedia content. Due to such explosion data, the community has been facing new challenges exciting opportunities these days. This paper presents framework address some main in this area. In particular, it multi-label multimodal for imbalanced data classification. For purpose, utilizes audio, visual, textual modalities automatically generates static temporal features using spatio-temporal deep neural networks. It also manages...

The growing makers' community demands better supports for designing and fabricating interactive functional objects. Most of the current approaches focus on embedding desired functions within new Instead, we advocate repurposing existing objects rapidly authoring onto them. We present Plain2Fun, a design fabrication pipeline enabling users to quickly transform ordinary into ones. Plain2Fun allows directly circuit layouts surfaces scanned 3D model Our tool automatically generates as short...

For decades, the world of financial advisors has been dominated by large investment banks such as Goldman Sachs. In recent years, user-contributed services SeekingAlpha and StockTwits have grown to millions users. this paper, we seek understand quality impact content on social platforms, empirically analyzing complete datasets articles (9 years) messages (4 years). We develop sentiment analysis tools correlate contributed historical performance relevant stocks. While provide minimal...

This manuscript presents a data quality analysis and holistic 'machine learning-readiness' evaluation of representative set large-scale, real-world phasor measurement unit (PMU) datasets provided under the United States Department Energy-funded FOA 1861 research program [1]. A major focus this study is to understand present-day suitability synchrophasor for application commercially-available, off-the-shelf big supervised or semi-supervised machine learning (ML) tools catalogue any obstacles...

Choosing a good location when opening new store is crucial for the future success of business. Traditional methods include offline manual survey, which very time consuming, and analytic models based on census data, are un- able to adapt dynamic market. The rapid increase availability big data from various types mobile devices, such as online query positioning provides us with possibility develop automatic accurate data-driven prediction business placement. In this paper, we propose Demand...

Multi-role dialogue understanding comprises a wide range of diverse tasks such as question answering, act classification, summarization etc. While corpora are abundantly available, labeled data, for specific learning tasks, can be highly scarce and expensive. In this work, we investigate context representation with various types unsupervised pretraining where the training objectives given naturally according to nature utterance structure multi-role conversation. Meanwhile, in order locate...

A novel water soluble fluorescent probe based on <italic>C</italic>-glycoside with an aromatic aldehyde unit has been synthesized and its UV/Vis fluorescence spectra, aggregation disaggregation bovine serum albumin were studied.

This paper developed the <italic>para</italic>-selective silylation of benzamide derivatives with chlorosilanes using FeCl₂ catalysis.

Video data is inherently multimodal and sequential. Therefore, deep learning models need to aggregate all modalities while capturing the most relevant spatio-temporal information from a given video. This paper presents framework for video classification using Residual Attention-based Fusion (RAF) method. Specifically, this extracts features each modality residual attention-based bidirectional Long Short-Term Memory fuses weighted Support Vector Machine handle imbalanced data. Experimental...