Uniform Frame Research Articles

HUMAN ACTION RECOGNITION: IMPROVING THE ACCURACY OF DEEP CONV-LSTM ARCHITECTURE THROUGH NOISE CLEANING PRIOR TO KEY FRAMES SELECTION

Recognizing human actions has numerous practical applications that can address issues and enhance the effectiveness and living standards across various domains. For solving the human action recognition task from videos, the Deep Conv-LSTM model architecture has been used on the UCF101 dataset. To preprocess the frames, a method has been proposed that integrates two algorithms: Noise Cleaning and Dissimilarity-Based Key Frame Selec¬t¬i¬o¬n (KFS). By employing these algorithms cohesively and effectively, image quality has been enhanced and unwanted data have been eliminated. The Uniform Frame Selection, Dissimilarity-Based KFS, and the proposed algorithm are evaluated, and their performances are compared based on the accuracy and data size reduction. The results show that the Dissimilarity-Based KFS algorithm outperforms the Uniform Frame Selection algorithm in accuracy by 2%, and the proposed method shows a 3% and 5% improvement in accuracy compared to the first two algorithms, respectively. Furthermore, the proposed algorithm reduces the data size by 26%, making it computationally efficient.

Rapid screening of Zr-containing particles from Chang’e-5 lunar soil samples for isotope geochronology: Technical roadmap for future study

New samples returned by China Chang’e-5 (CE-5) mission offer an opportunity for studying the lunar geologic longevity, space weathering, and regolith evolution. The age determination of the CE-5 samples was among the first scientific questions to be answered. However, the precious samples, most in the micrometer size range, challenge many traditional analyses on large single crystals of zircon developed for massive bulk samples. Here, we developed a non-destructive rapid screening of individual zirconium-containing particle for isotope geochronology based on a Micro X-ray fluorescence analysis (µXRF). The selected particles were verified via scanning electron microscopy (SEM), 3D X-ray microscopy (XRM), and focused ion beam scanning electron microscopy (FIB-SEM) techniques, which showed that zirconium-bearing minerals with several microns were precisely positioned and readily suitable for site-specific isotopic dating by second ion mass spectrometry (SIMS). Such protocol could be also applicable in non-destructively screening other types of particles for different scientific purposes. We therefore proposed a correlative workflow for comprehensively studying the CE-5 lunar samples from single particles on nanometer to atomic scales. Linking various microscopic and spectromicroscopic instruments together, this workflow consists of six steps: (1) single-particle selection with non-destructive µXRF technique, (2) 2D/3D morphological and structural characterization with a correlative submicron 3D XRM and nanoscale resolution FIB-SEM imaging methods, (3) SEM analysis of the surface morphology and chemistry of the selected particle, (4) a series of microscopic and microbeam analyses (e.g., SEM, electron probe microanalysis, and SIMS) on the cross-section of the selected particle to obtain structural, mineralogical, chemical, and isotopic features from the micron to nanometer scale, (5) advanced 2D/3D characterization and site-specific sample preparation of thin foil/tip specimens on a microregion of interest in the selected particle with FIB-SEM technique, and (6) comprehensive analyses on the FIB-milled specimens at nanometer to atomic scale with synchrotron-based scanning transmission X-ray microscopy, analytic transmission electron microscopy, and atom probe tomography. Following this technical roadmap, one can integrate multiple modalities into a uniform frame of multimodal and multiscale correlated datasets to acquire high-throughput information on the limited or precious terrestrial and extraterrestrial samples.

Content-Based Video Retrieval With Prototypes of Deep Features

The rapid development in the area of information and communication technologies has enabled the transfer of high-resolution, large-sized videos, and video applications have also evolved according to data quality levels. Content-based video retrieval (CBVR) is an essential video application because it can be applied to various domains, such as surveillance, education, sports, and medicine. In this paper, we propose a CBVR method based on prototypical category approximation (PCA-CBVR), which calculates prototypes of deep features for each category to predict the user’s query video category without a classifier. We also undertake fine searching to retrieve the video most similar to the user’s query video from the predicted category database of videos. The proposed PCA-CBVR approach is efficient in terms of its computational cost and maintains meaningful information of the videos. It does not need to train a classifier even when the database is updated and uses all deep features without any dimension reduction step, such as those in CBVR studies. Moreover, we conduct fine-tuning of the 3D CNN feature extractor based on a few-shot learning approach for better domain adaptation ability and apply salient frame sampling instead of uniform frame sampling to improve the performance of the PCA-CBVR method. We demonstrate the performance capability of the proposed PCA-CBVR approach through experiments on various benchmark video datasets, in this case the UCF101, HMDB51, and ActivityNet datasets.

Nonlinear Error Model Based on Quaternion for the INS: Analysis and Comparison

In this paper, a modified quaternion-based nonlinear error model is explored using three derivation methods. The modified quaternion-based nonlinear error model can be more reasonable than the traditional one due to the uniform frame problem, which is underlying and fundamental but is easy to overlook. Further, field tests for inertial integrated navigation (INS) are carried out to investigate the benefits and drawbacks of the existing nonlinear model or nonlinear error model based on Euler angles and quaternion for the INS

Another proof of Banaschewski's surjection theorem

We present a new proof of Banaschewski's theorem stating that the completion lift of a uniform surjection is a surjection. The new procedure allows to extend the fact (and, similarly, the related theorem on closed uniform sublocales of complete uniform frames) to quasi-uniformities (not necessarily symmetric uniformities). Further, we show how a (regular) Cauchy point on a closed uniform sublocale can be extended to a (regular) Cauchy point on the larger (quasi-)uniform frame.

Efficient Techniques for Impulsive Noise Cancellation in CGU/SD Systems

In this paper, we investigate the problem of impulsive noise cancellation in systems that use jointly overcomplete expansion representations, namely the cyclic geometrically uniform (CGU) frame and sigma-delta (SD) quantization. We first describe the existing analogy between the CGU frames and Reed–Solomn (RS) codes and how it can be exploited in order to reformulate the impulsive noise cancellation problem. As the impulsive noise does by nature represent a sparse signal, it fits the compressed sensing (CS) framework. This is why we investigate how to remodel our impulsive noise cancellation in a CGU-/SD-based system as a CS problem. Then, we study the use and limitations of some existing CS recovery techniques, namely Smoothed L0 (SL0), orthogonal matching pursuit (OMP), compressive sampling matching pursuit (CoSaMP), and Bayes-based approach (BBA). In order to overcome such limitations, we propose how to improve such techniques, and we show that their related improved versions, namely Improved SL0 (I-SL0), I-OMP and I-CoSaMP, and I-BBA efficiently, cancel the impulsive noise of CGU/SD systems and do lead to a quasi-optimal performance. Simulation results are given to support our claims.

Dynamic R-parameter based integrated model predictive iterative learning control for batch processes

A novel integrated model predictive iterative learning control (MPILC) strategy with dynamic R-parameter for batch processes is proposed in this paper. It systematically integrates batch-axis information and time-axis information into one uniform frame, namely the iterative learning controller (ILC) in the domain of batch-axis, while a model predictive controller (MPC)with time-varying prediction horizon in the domain of time-axis. As a result, the operation policy of batch process can be regulated during one batch, which leads to superior tracking performance and better robustness against disturbance and uncertainty. Moreover, both model identification and dynamic R-parameter are employed to eliminate the model-plant mismatch and make zero-error tracking possible. Next, the convergence and tracking performance of the proposed integrated model predictive learning control system are given rigorous description and proof. Lastly, the effectiveness of the proposed method is verified by one example.

An integrated iterative learning control strategy with model identification and dynamic R-parameter for batch processes

An integrated iterative learning control strategy with model identification and dynamic R-parameter is proposed in this paper. It systematically integrates discrete-time (batch-axis) information and continuous-time (time-axis) information into one uniform frame, namely the iterative learning controller in the domain of batch-axis, while a PID controller (PIDC) in the domain of time-axis. As a result, the operation policy of batch process can be regulated during one batch, which leads to superior tracking performance and better robustness against disturbance and uncertainty. Moreover, the technologies of model identification and dynamic R-parameter are employed to make zero-error tracking possible. Next, the convergence and tracking performance of the proposed learning control system are firstly given rigorous description and proof. Lastly, the effectiveness of the proposed method is verified by examples.

Design overstrength of steel eccentrically braced frames

The paper reports an analytical study on the design overstrength of steel eccentrically braced frames (EBFs). The study aimed at examining the influence of geometrical factors and seismic hazard on the design overstrength of EBFs. Pursuant to this goal a computer program which facilitates EBF designs was developed. The algorithm of the program adopts the lightest uniform frame design and library of link-beam-brace sub-assemblages concepts. The design output from the program was compared with published solutions and the results indicate that the algorithm developed as a part of this study is capable of providing lighter framing solutions. A parametric study was conducted using the developed computer program. The results indicate that the frames considered in this study have on average higher overstrength values when compared with the codified value even without considering potential increases due to material overstrength and strain hardening. The design overstrength was found to be influenced primarily by the link length to bay width ratio and the bay width, and secondarily by the building height and seismic hazard level.

Structural Seismic Damage Detection Using Fractal Dimension of Time-Frequency Feature

In this paper, a data-driven approach to localizing structural damage subjected to ground motion is proposed by using the fractal dimension of the time-frequency features of structural dynamic responses. The time-frequency feature is defined as the real part of wavelet coefficient and the fractal dimension adopts the box-counting method. It is shown that the proposed fractal dimensions at each story of linear system are identical, while the fractal dimension at the stories with nonlinearity is different from those at the stories with linearity. Therefore, the nonlinear behavior of structural damage caused by strong ground motions can be detected and localized through comparing the fractal dimensions of structural responses at different stories. Shaking table test on a uniform 16-story 3-bay steel frame with added friction dampers modelling interstory nonlinear behavior was conducted. The experiment results validate the effectiveness of the proposed method to localize single and multi seismic damage of structures.

Complex Step-Shape Binary Offset Carrier Modulation for a Unitary Analytical Framework of GNSS Signals

The Binary Offset Carrier and Binary Coded Symbol modulation family is widely used in the existing Global Navigation Satellite Systems (GNSS). There are several modulation types in this family and new types are still being developed. However, the analysis of these modulations is still scarce of uniform theoretical frame. This paper presents a novel Complex Step-shape Binary Offset Carrier (CSBOC) modulation to build a unitary analytical framework for all these modulation types. This framework contains a unified signals expression based on the extended concept of step-shape symbols bits vector. It can denote sine and cosine phase, odd and even order, time division multiplex and complex modulations. Moreover, the unified formulas of important signal characteristics which include the power spectral density, the auto-correlation function, and the cross-correlation function are derived. The proposed formulas are verified through comparing with the results came from existing theories and signal simulations. The applications of the CSBOC in analyzing side-peaks cancellation methods of GNSS signals are also provided to show that this framework is a useful tool to analyze and design locally generated signals of side-peaks cancellation methods.

Formation of mixed configuration cell based on product demand prediction

Product demand is a main factor influencing formation and reconfiguration of manufacturing cell (MC) especially when lifespan of the formed MCs is considered. It is also the most important factor for formation of mixed style of manufacturing cell (MSMC) in mixed style of production line (MPL) where developing and developed products coexist. Against the problem of MPL formation and its adjustment, the concept of MSMC is advanced. Then, a uniform formation frame covering rules, constraints, and objectives of different styles of MC is constructed and a heuristic algorithm for resource capacity allocation is used for solution. Next, an inheritable reconfiguration method of MC is analyzed for actual application of periodic task adjustment. At last, above formation and reconfiguration algorithm of MSMC under product prediction is validated by computational study.

Completion and Samuel compactification of nearness and uniform frames

It is shown that the familiar description of the completion of a uniform frame in terms of its Samuel compactification can be extended to arbitrary nearness frames. This is achieved by means of the following new notion, a variant of compactness, for regular frames: such a frame will be called near-compact if it is complete in some totally bounded nearness. This leads to a natural concept of the Samuel near-compactification for arbitrary nearness frames which is then shown to play exactly the same role in the general setting which the Samuel compactification plays for uniform frames.

The Performance of PCM Quantization Under Tight Frame Representations

In this paper, we study the performance of the PCM scheme for quantizing finite unit-norm tight frame expansions for $\mathbb{R}^d$ and derive the PCM quantization error without the white noise hypothesis. We prove that for the class of unit norm tight frames derived from uniform frame paths the quantization error has an upper bound of $O(\delta^{3/2})$ regardless of the frame redundancy. This is achieved using some of the techniques developed by Güntürk in his study of Sigma-Delta quantization. Using tools of harmonic analysis we show that this upper bound is sharp for $d=2$. A consequence of this result is that unlike with Sigma-Delta quantization, the error for PCM quantization in general does not diminish to zero as one increases the frame redundancy. We extend the result to high dimension and show that the PCM quantization error has an upper bound $O(\delta^{(d+1)/2})$ for asymptotically equidistributed unit-norm tight frame of $\mathbb{R}^{d}$.

Reducing Perceptual Discontinuity P2P Live Video Streaming Using Adaptive Scheme Based on Frame Loss Visibility

When a live streaming video is delivered over a peer-to-peer (P2P) network, the video is divided into several chunks and distributed to peers. Each chunk has its own playback time deadline. A chunk delay can be a problem of great concern because a serious chunk delay can produce obvious discontinuity of the streaming video, resulting in low satisfaction for a viewer. The playback time of a delayed chunk is overlapped with that of the next chunk. Traditionally, fast forwarding and uniform frame skipping are the two methods used to deal with the chunk delay problem. However, they may easily produce the effect of perceptual discontinuity and perceived by the viewer. This study proposes a frame dropping method based on frame loss visibility information in order to maintain visual continuity of the video. The frame with lower loss visibility will be dropped first. In a previous work, the idea of loss visibility was applied by a router to develop a frame dropping strategy when network congestion occurs. In this work, we apply it to the chunk-level playback controller in P2P network. The number of frames to be dropped is dependent on the value of chunk delay. Given a fixed chunk delay, the main difference between the proposed approach and the uniform frame skipping method is the way of choosing frames for dropping (fast forwarding method does not drop any frame but play all the frames at a faster speed). A viewer's satisfaction is evaluated by using the way of subjective video quality assessment. The proposed method can produce higher MOS (mean opinion score) than that of the traditional methods (fast forwarding and uniform frame skipping), demonstrating the effectiveness of the proposed approach.

Using Role-Playing Game Dice To Teach the Concepts of Symmetry

Finding and describing the location of symmetry elements in complex objects is often a difficult skill to learn. Introducing the concepts of symmetry using high-symmetry game dice is one way of helping students overcome this difficulty in introductory physical chemistry classes. The dice are inexpensive, reusable, and come in a variety of shapes and can be painted to reduce their symmetry. Because the dice have index numbers on sides or vertices, they can provide a uniform frame of reference for students and instructors. The hands-on activities using the dice can be done in class, as a dry lab, or as an out-of-class assignment.

Affine and quasi-affine frames for rational dilations

In this paper we extend the investigation of quasi-affine systems, which were originally introduced by Ron and Shen [J. Funct. Anal. 148 (1997), 408–447] for integer, expansive dilations, to the class of rational, expansive dilations. We show that an affine system is a frame if, and only if, the corresponding family of quasi-affine systems are frames with uniform frame bounds. We also prove a similar equivalence result between pairs of dual affine frames and dual quasi-affine frames. Finally, we uncover some fundamental differences between the integer and rational settings by exhibiting an example of a quasi-affine frame such that its affine counterpart is not a frame.

CR Switch: A Load-Balanced Switch With Contention and Reservation

Load-balanced switches have received a great deal of attention recently as they are much more scalable than other existing switch architectures in the literature. However, as there exist multiple paths for flows of packets to traverse through load-balanced switches, packets in such switches may be delivered out of order. In this paper, we propose a new switch architecture, called the contention and reservation (CR) switch, that not only delivers packets in order but also guarantees 100% throughput. The key idea, as in a multiple-access channel, is to operate the CR switch in two modes: 1) the contention mode in light traffic and 2) the reservation mode in heavy traffic. To do this, we invent a new buffer management scheme, called virtual output queue with insertion (I-VOQ).With the I-VOQ scheme, we give rigorous mathematical proofs for 100% throughput and in-order packet delivery of the CR switch. By computer simulations, we also demonstrate that the average packet delay of the CR switch is considerably lower than other schemes in the literature, including the uniform frame spreading scheme [10], the padded frame scheme [8], and the mailbox switch [5].

Optimization of frame representations for compressed sensing and Mercedes-Benz frame

We prove that there is no single uniform tight frame in Euclidean (unitary) space such that a solution of the l1-norm minimization problem for the frame representation is attained on the frame coefficients. Then we find an exact solution of the l1-minimization problem for the Mercedes-Benz frame in ℝN. We also give some examples of connections between optimization problems of various types.

The Existence of FGDRP$(3,g^u)'$s

By an FGDRP$(3,g^u)$, we mean a uniform frame $(X,\cal G,\cal A)$ of block size 3, index 2 and type $g^u$, where the blocks of $\cal{A}$ can be arranged into a $gu/3\times gu$ array. This array has the properties: (1) the main diagonal consists of $u$ empty subarrays of sizes $g/3\times g$; (2) the blocks in each column form a partial parallel class partitioning $X \setminus G$ for some $G\in \cal G$, while the blocks in each row contain every element of $X \setminus G$ $3$ times and no element of $G$ for some $G\in \cal{G}$. The obvious necessary conditions for the existence of an FGDRP$(3,g^u)$ are $u\geq 5$ and $g\equiv 0$ (mod 3). In this paper, we show that these conditions are also sufficient with the possible exceptions of $(g,u)\in \{(6,15),(9,18),(9,28),(9,34),(30,15)\}$.