Set Of Primitives Research Articles

LIMITING DIRECTIONS FOR ENTIRE SOLUTIONS OF A

Let us consider f as being an entire solution of the differential-difference equation G(z, f)+h(z)fm(z) = 0, (m ∈ N), where h(z) is a transcendental entire function and G(z, f) is a differential-difference polynomial in f with entire coefficients. By considering the order and deficiency of h(z) and such coefficients, we mainly study the radial distribution of f, and establish a lower bound of measure for the set of common limiting directions of the Julia sets of derivatives and primitives of its shifts.

Quantum gate sets for lattice QCD in the strong-coupling limit: Nf=1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$N_{f}=1$\\end{document}

We derive the primitive quantum gate sets to simulate lattice quantum chromodynamics (LQCD) in the strong-coupling limit with one flavor of massless staggered quarks. This theory is of interest for studies at non-zero density as the sign problem can be overcome using Monte Carlo methods. In this work, we use it as a testing ground for quantum simulations. The key point is that no truncation of the bosonic Hilbert space is necessary as the theory is formulated in terms of color-singlet degrees of freedom (“baryons” and “mesons”). The baryons become static in the limit of continuous time and decouple, whereas the dynamics of the mesonic theory involves two qubits per lattice site. Lending dynamics also to the “baryons” simply requires to use the derived gate set in its controlled version.

Two-component transformation inclusive contraction scheme in the relativistic molecular orbital theory

The incorporation of a two-component transformation into the contraction coefficients of basis functions is suggested. Such a contraction, referred to as “two-component transformation inclusive contraction (TIC)”, effectively eliminates the computational cost associated with the two-component transformation and can be readily implemented into conventional quantum chemistry programs. TIC was verified through numerical calculations using the second- and third-order unitarized Douglas–Kroll method, which is newly derived for the validation of TIC, and the infinite-order two-component method. The numerical validation results suggested that TIC could sufficiently reproduce the results of primitive basis sets for both atoms and molecules.

General Systems Theory and Creative Artificial Intelligence

The article analyzes the possibilities and limitations of artificial intelligence. The article considers the subjectivity of artificial intelligence, determines its necessity for solving intellectual problems depending on the possibility of representing the real world as a deterministic system. Methodological limitations of artificial intelligence, which is based on the use of big data technologies, are stated. These limitations cause the impossibility of forming a holistic representation of the objects of cognition and the world as a whole. As a tool for deterministic description of the universe it is proposed to use empirical-metaphysical general theory of systems, which is an extension of existing general theories of systems due to ontological justification of the phenomenon of isomorphism and definition of a limited set of laws, rules, patterns and primitives of forms and relations of objects in the universe. The distinction of natural (human) and artificial intelligence is considered, including the realization of multisystem integration of intelligence in physical, biological, social and spiritual systems. A philosophically grounded approach to ensuring the evolutionary properties of artificial intelligence is formulated, based on the inclusion of non-equilibrium mechanisms through which stability is realized.

Making programmable packet scheduling time-sensitive with a FIFO queue

Time-Sensitive Networking (TSN) is an emerging technology for real-time and non-real-time hybrid networked systems. TSN is standardized by IEEE 802.1 TSN Task Group and is becoming widely used in various scenarios including the cloud network. However, existing programmable packet schedulers such as PIFO, PIEO, and AIFO in programmable switches either lack the ability to express most scheduling algorithms in TSN or introduce intolerable on-chip memory overhead (e.g., strict-priority queues). This makes programmable switches and NICs incapable of providing deterministic forwarding. In this paper, we present AIAO (Admission-In-Admission-Out), a new set of programmable scheduling primitives using just a single FIFO to support typical TSN scheduling algorithms, as well as other popular work-conserving algorithms. AIAO is inspired by AIFO but improves it with a group of high-speed packet ingress/egress admission control triggered by high-precise and globally synchronized time, thus being able to support time-sensitive scheduling. We implement AIAO and evaluate it with FPGA-based TSN switches. The preliminary results show that AIAO guarantees correctness for a typical TSN scheduling algorithm with minimal logic and memory overhead.

The syntax of English presentatives

Abstract: In this article, we analyze the syntax of sentences such as Here is my daughter , which we refer to as presentatives. Presentatives turn out to have a wide range of properties that distinguish them sharply from ordinary declaratives, interrogatives, imperatives, and exclamatives. Drawing on recent work on the left periphery, we develop a novel account of their syntactic structure that uses only independently proposed syntactic primitives. We argue that English presentatives involve an ordinary DP combined with two left-peripheral heads, encoding the time and location of the speaker, along with an anaphoric T head and a light verb. The resulting structure is a triple consisting of the speech time, speech location, and an entity denoted by a DP. The overall picture that emerges suggests that presentatives may constitute their own minor clause type, one that we might expect to be widely available crosslinguistically, since it is built from a particular combination of these widely available primitives. A brief survey of presentatives in languages other than English suggests that they are indeed widely available, and our analysis provides an explicit framework for detailed investigations of presentatives in other languages, which may use an overlapping, but not necessarily fully identical, set of primitives.

Object-Agnostic Vision Measurement Framework Based on One-Shot Learning and Behavior Tree.

Vision measurement is important for intelligent systems to obtain the precise structural and spatial information of objects. Beyond the object-specific vision measurement developed for fixed object type, it is appealing to explore the object-agnostic vision measurement, which can be efficiently reconfigured and adapted to various novel objects. This article proposes a framework to mimic the human's versatile visual measurement behavior: extract a set of contour primitives of interest (CPIs) from an image, then utilize the CPIs to calculate the key geometric information. First, a deep convolutional neural network (CNN) CPieNet + is proposed under the one-shot learning scheme, aiming to extract the pixel-level object CPI from a raw query image, given an annotated support image. The fine-grained CPI prototypes are formed by sampling multiple points on the feature map of the support image. To leverage the explicit geometric knowledge in the CNN inference, the annotation map is encoded as a shape descriptor to guide the feature channel attention, and the geometric attribute awareness is realized by supervising the model to predict the direction and size of CPI. Second, the measurement behavior tree (BT) is designed to model the hierarchical geometric calculation procedure, which is flexibly configurable for different measurement requirements and is interpretable for nonexpert users. After the execution of the measurement BT, the pixel-level CPIs are converted to the required key geometric data. The effectiveness of the proposed methods is validated by a series of experiments.

Time Series Data Mining: A Unifying View

Time series data are ubiquitous; large volumes of such data are routinely created in scientific, industrial, entertainment, medical and biological domains. Examples include ECG data, gait analysis, stock market quotes, machine health telemetry, search engine throughput volumes etc. VLDB has traditionally been home to much of the community's best research on time series, with three to eight papers on time series appearing in the conference each year. What do we want to do with such time series? Everything! Classification, clustering, joins, anomaly detection, motif discovery, similarity search, visualization, summarization, compression, segmentation, rule discovery etc. Rather than a deep dive in just one of these subtopics, in this tutorial I will show a surprisingly small set of high-level representations, definitions, distance measures and primitives can be combined to solve the first 90 to 99.9% of the problems listed above. The tutorial will be illustrated with numerous real-world examples created just for this tutorial, including examples from robotics, wearables, medical telemetry, astronomy, and (especially) animal behavior. Moreover, all sample datasets and code snippets will be released so that the tutorial attendees (and later, readers) can first reproduce the results demonstrated, before attempting similar analysis on their data.

Multi-Abstractive Neural Controller: An Efficient Hierarchical Control Architecture for Interactive Driving

As learning-based methods make their way from perception systems to planning/control stacks, robot control systems have started to enjoy the benefits that data-driven methods provide. Because control systems directly affect the motion of the robot, data-driven methods, especially black box approaches, need to be used with caution considering aspects such as stability and interpretability. In this paper, we describe a differentiable and hierarchical control architecture. The proposed representation, called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multi-abstractive neural controller</i> , uses the input image to control the transitions within a novel discrete behavior planner (referred to as the visual automaton generative network, or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">vAGN</i> ). The output of a vAGN controls the parameters of a set of dynamic movement primitives which provides the system controls. We train this neural controller with real-world driving data via behavior cloning and show improved explainability, sample efficiency, and similarity to human driving.

CLARIFICATION OF THE PURPOSES AND TASKS OF THE GENERAL THEORY OF SYSTEMS

The article is devoted to the clarification of the goal and objectives of the general theory of systems. The existing formulations of the goal and objectives of the general theory of systems are considered and the author’s revised and extended formulations are proposed. The proposed objectives of the general theory of systems include three applied objectives and three fundamental objectives, which should be solved before solving the applied objectives. The applied objectives of the general theory of systems are: the description of a system’s existence by means of patterns and primitives, description of an object’s behaviour based on secondary properties and laws, and verification of the object description validity. The fundamental objectives include the definition of representative sets of primitives, patterns, secondary properties and laws, as well as the development of a methodology for verification Прикладные исследования, технологии 99 of the object description validity based on finding the rules of knowledge and defects in the found knowledge.

A neural builder for spatial subdivision hierarchies

Spatial data structures, such as k-d trees and bounding volume hierarchies, are extensively used in computer graphics for the acceleration of spatial queries in ray tracing, nearest neighbour searches and other tasks. Typically, the splitting strategy employed during the construction of such structures is based on the greedy evaluation of a predefined objective function, resulting in a less than optimal subdivision scheme. In this work, for the first time, we propose the use of unsupervised deep learning to infer the structure of a fixed-depth k-d tree from a constant, subsampled set of the input primitives, based on the recursive evaluation of the cost function at hand. This results in high-quality upper spatial hierarchy, inferred in constant time and without paying the intractable price of a fully recursive tree optimisation. The resulting fixed-depth tree can then be further expanded, in parallel, into either a full k-d tree or transformed into a bounding volume hierarchy, with any known conventional tree builder. The approach is generic enough to accommodate different cost functions, such as the popular surface area and volume heuristics. We experimentally validate that the resulting hierarchies have competitive traversal performance with respect to established tree builders, while maintaining minimal overhead in construction times.

Metric decomposability theorems on sets of integers

AbstractA set is called additively decomposable (resp., asymptotically additively decomposable) if there exist sets of cardinality at least two each such that (resp., is finite). If none of these properties hold, the set is called totally primitive. We define ‐decomposability analogously with subsets of . Wirsing showed that almost all subsets of are totally primitive. In this paper, in the spirit of Wirsing, we study decomposability from a probabilistic viewpoint. First, we show that almost all symmetric subsets of are ‐decomposable. Then we show that almost all small perturbations of the set of primes yield a totally primitive set. Further, this last result still holds when the set of primes is replaced by the set of sums of two squares, which is by definition decomposable.

An Intermediate Language for General Sparse Format Customization

The inevitable trend of hardware specialization drives an increasing use of custom data formats in processing sparse workloads, which are typically memory-bound. These formats facilitate the automated generation of target-aware data layouts to improve memory access latency and bandwidth utilization. However, existing sparse tensor programming models and compilers offer little or no support for productively customizing the sparse formats. Moreover, since these frameworks adopt an attribute-based approach for format abstraction, they cannot easily be extended to support general format customization. To overcome this deficiency, we propose UniSparse, an intermediate language that provides a unified abstraction for representing and customizing sparse formats. More concretely, we express a sparse format as a map from dense coordinates to a layout tree using a small set of well-defined query and mutation primitives. We also develop a compiler leveraging the MLIR infrastructure, which supports adaptive customization of formats, and automatic code generation of format conversion and compute operations for heterogeneous architectures. We demonstrate the efficacy of our approach through experiments running commonly-used sparse linear algebra operations with hybrid formats on multiple different hardware targets, including an Intel CPU, an NVIDIA GPU, and a simulated processing-in-memory (PIM) device.

Radar-based path planning of autonomous surface vehicle with static and dynamic obstacles in a Frenet Frame

AbstractNavigation safety at sea is vital for each autonomous surface vehicle (ASV), which involves the problem of motion planning in dynamic environments and their robust tracking through feedback control. We present a practical path-planning method that generates smooth trajectories for a marine vehicle traveling in an unknown environment, where obstacles are detected in real time by millimetre wave (mmWave) radar. Our approach introduces a polynomial curve to describe the lateral and longitudinal trajectories in the Frenet frame, known as the ‘motion primitives’, whose combination ensures that the planning area is properly covered. In addition, we can select a feasible, optimal and collision-free trajectory from such a set of motion primitives that is generated by considering the vehicle dynamics and comfort. The capabilities of proposed algorithm are demonstrated in the experiment with static and dynamic obstacles.

COMPASS: a formal framework and aggregate dataset for generalized surgical procedure modeling.

We propose a formal framework for the modeling and segmentation of minimally invasive surgical tasks using a unified set of motion primitives (MPs) to enable more objective labeling and the aggregation of different datasets. We model dry-lab surgical tasks as finite state machines, representing how the execution of MPs as the basic surgical actions results in the change of surgical context, which characterizes the physical interactions among tools and objects in the surgical environment. We develop methods for labeling surgical context based on video data and for automatic translation of context to MP labels. We then use our framework to create the COntext and Motion Primitive Aggregate Surgical Set (COMPASS), including six dry-lab surgical tasks from three publicly available datasets (JIGSAWS, DESK, and ROSMA), with kinematic and video data and context and MP labels. Our context labeling method achieves near-perfect agreement between consensus labels from crowd-sourcing and expert surgeons. Segmentation of tasks to MPs results in the creation of the COMPASS dataset that nearly triples the amount of data for modeling and analysis and enables the generation of separate transcripts for the left and right tools. The proposed framework results in high quality labeling of surgical data based on context and fine-grained MPs. Modeling surgical tasks with MPs enables the aggregation of different datasets and the separate analysis of left and right hands for bimanual coordination assessment. Our formal framework and aggregate dataset can support the development of explainable and multi-granularity models for improved surgical process analysis, skill assessment, error detection, and autonomy.

Composite Diffraction-Free Beam Formation Based on Iteratively Calculated Primitives.

To form a diffraction-free beam with a complex structure, we propose to use a set of primitives calculated iteratively for the ring spatial spectrum. We also optimized the complex transmission function of the diffractive optical elements (DOEs), which form some primitive diffraction-free distributions (for example, a square or/and a triangle). The superposition of such DOEs supplemented with deflecting phases (a multi-order optical element) provides to generate a diffraction-free beam with a more complex transverse intensity distribution corresponding to the composition of these primitives. The proposed approach has two advantages. The first is the rapid (for the first few iterations) achievements of an acceptable error in the calculation of an optical element that forms a primitive distribution compared to a complex one. The second advantage is the convenience of reconfiguration. Since a complex distribution is assembled from primitive parts, it can be reconfigured quickly or dynamically by using a spatial light modulator (SLM) by moving and rotating these components. Numerical results were confirmed experimentally.

Deploying hybrid quantum-secured infrastructure for applications: When quantum and post-quantum can work together

Most currently used cryptographic tools for protecting data are based on certain computational assumptions, which makes them vulnerable with respect to technological and algorithmic developments, such as quantum computing. One existing option to counter this potential threat is quantum key distribution, whose security is based on the laws of quantum physics. Quantum key distribution is secure against unforeseen technological developments. A second approach is post-quantum cryptography, which is a set of cryptographic primitives that are believed to be secure even against attacks with both classical and quantum computing technologies. From this perspective, this study reviews recent progress in the deployment of the quantum-secured infrastructure based on quantum key distribution, post-quantum cryptography, and their combinations. Various directions in the further development of the full-stack quantum-secured infrastructure are also indicated. Distributed applications, such as blockchains and distributed ledgers, are also discussed.

Automatic detection of semantic primitives using optimization based on genetic algorithm.

In this article, we propose a method for the automatic retrieval of a set of semantic primitive words from an explanatory dictionary and a novel evaluation procedure for the obtained set of primitives. The approach is based on the representation of the dictionary as a directed graph with a single-objective constrained optimization problem via a genetic algorithm with the PageRank scoring model. The problem is defined as a subset selection. The algorithm is fit to search for the sets of words that should fulfil several requirements: the cardinality of the set should not exceed empirically selected limits and the PageRank word importance score is minimized with cycle prevention thresholding. In the experiments, we used the WordNet dictionary for English. The proposed method is an improvement over the previous state-of-the-art solutions.

The planetary boundary layer physical processes, the secondary thermal baroclinic circulation and inertial oscillation contribution to diurnal variation of the Etesian winds over the Aegean Sea

Etesian winds constitute an important climatological phenomenon, which does not only moderate the heat during the summer in the Aegean Sea, but provides a source of clean renewable energy as well. Even though several papers have attempted to explain their dynamical and physical characteristics, the respective processes that drive the diurnal variation of the wind speed are not fully understood. The objective of this paper is to identify the processes responsible for diurnal variation with observed maximum wind speed around noon and minimum around midnight. Analytical solutions of a primitive equation set in Eulerian form, after introducing suitable conditions and approximations, reveal an inertial oscillation over the Aegean Sea. Data based on direct observations, ECMWF IFS high resolution analyses and high-resolution simulations with the Weather Research and Forecasting (WRF) model are utilized to find out the type and structure of the planetary boundary layer (PBL) over the Aegean Sea. This PBL appears to be of a marine character and turbulent mostly during the day but less during the night. The direct impact of local and regional thermally-driven circulations is found to be the main cause of the diurnal variation of the observed wind and partly the inertial oscillation. Results from numerical simulations certify these findings. Furthermore, the momentum and Newtonian heating exchanges by the physical processes inside the PBL, where the gradient wind together with smaller scales of atmospheric motions exist, are also necessary for explaining the variability of the Etesian winds.

A proof of the Erdős primitive set conjecture

Abstract A set of integers greater than 1 is primitive if no member in the set divides another. Erdős proved in 1935 that the series $f(A) = \sum _{a\in A}1/(a \log a)$ is uniformly bounded over all choices of primitive sets A. In 1986, he asked if this bound is attained for the set of prime numbers. In this article, we answer in the affirmative. As further applications of the method, we make progress towards a question of Erdős, Sárközy and Szemerédi from 1968. We also refine the classical Davenport–Erdős theorem on infinite divisibility chains, and extend a result of Erdős, Sárközy and Szemerédi from 1966.