Scalable Rules Research Articles

A lightweight and scalable greenhouse mapping method based on remote sensing imagery

Seeking a low-cost, high-efficiency greenhouse mapping technology has immense significance. While greenhouse extraction methods using deep learning have been proposed, the challenge of extracting dense small objects remains an unresolved problem. The inherent downscaling strategy in general-purpose semantic segmentation (SS) models renders them unsuitable for such tasks. In contrast, the dramatically increasing computational complexity associated with this problem may result in an unaffordable cost for consumer-level applications. To address the aforementioned challenges, this study presents a novel greenhouse mapping model based on remote sensing (RS) images, which not only exhibits high precision and robust generalization capabilities but also offers significant lightweight advantages. To meet broader needs, we also provide corresponding customizable and scalable rules that allow for a trade-off between accuracy and speed. To evaluate the performance of our model, we select several representative works to conduct benchmark experiments on a self-annotated dataset. The results demonstrate that our method can provide more powerful visual representations for greenhouse segmentation with minimal cost. Compared to the control group, the proposed method achieves an mIoU improvement of 1.116 %-10.77 % using only 3.282 M parameters, while maintaining a considerable inference speed. Code will be available at: https://github.com/W-qp/EGENet.git

A comparative study of noise performance for InP HEMT

A comparative study to determine the scaling rules of noise model parameters for InP HEMT devices between 90 nm and 70 nm process is proposed in this paper. The expressions of noise model parameters in terms of four noise parameters are also derived. Both gate length and gate width scalable rules of the gate and drain noise model parameters (P and R) are discussed between 90 nm and 70 nm devices. Good agreement is obtained based on the comparison of measured and modeled noise parameters up to 45 GHz.

An Efficient Data Analysis Framework for Online Security Processing

Industrial cloud security and internet of things security represent the most important research directions of cyberspace security. Most existing studies on traditional cloud data security analysis were focused on inspecting techniques for block storage data in the cloud. None of them consider the problem that multidimension online temp data analysis in the cloud may appear as continuous and rapid streams, and the scalable analysis rules are continuous online rules generated by deep learning models. To address this problem, in this paper we propose a new LCN-Index data security analysis framework for large scalable rules in the industrial cloud. LCN-Index uses the MapReduce computing paradigm to deploy large scale online data analysis rules: in the mapping stage, it divides each attribute into a batch of analysis predicate sets which are then deployed onto a mapping node using interval predicate index. In the reducing stage, it merges results from the mapping nodes using multiattribute hash index. By doing so, a stream tuple can be efficiently evaluated by going over the LCN-Index framework. Experiments demonstrate the utility of the proposed method.

FW‐EM‐based approach for scalable small‐signal modeling of GaN HEMT with consideration of temperature‐dependent resistances

AbstractIn this paper, the full‐wave electromagnetic (FW‐EM) simulation approach for scalable small‐signal modeling of the GaN HEMT device is proposed. The scalable rules are deduced from the extracted parasitic parameters, which is according to a step‐by‐step parameter extraction method. Moreover, the accuracy is enhanced by considering the temperature‐dependent resistance (TDR) Rs and Rd, which are calculated by combining a universal thermal resistance model and the Rs and Rd under the pinch‐off condition. In the end, a set of GaN HEMT with a gate length of 0.25 μm is used for validation, and the experimental results show that good agreements have been achieved between the measured and the simulated scattering (S) parameters.

Fair Division in the Internet Age

Fair division, a key concern in the design of many social institutions, has for 70 years been the subject of interdisciplinary research at the interface of mathematics, economics, and game theory. Motivated by the proliferation of moneyless transactions on the internet, the computer science community has recently taken a deep interest in fairness principles and practical division rules. The resulting literature brings a fresh concern for computational simplicity (scalable rules) and realistic implementation. In this review of the most salient fair division results of the past 30 years, I concentrate on division rules with the best potential for practical implementation. The critical design parameter is the message space that the agents must use to report their individual preferences. A simple preference domain is key both to realistic implementation and to the existence of division rules with strong normative and incentive properties. I discuss successively the one-dimensional single-peaked domain, Leontief utilities, ordinal ranking, dichotomous preferences, and additive utilities. Some of the theoretical results in the latter domain are already implemented in the user-friendly SPLIDDIT platform ( http://spliddit.org ).

Fairness Guaranteed Cooperative Resource Allocation in Femtocell Networks

User-deployed low-power femtocell access points (FAPs) can provide better indoor coverage and higher data rates than conventional cellular networks. However, a major problem in this uncoordinated frequency reuse scenario is the inter-cell interference. In this paper, we propose a graph based distributed algorithm called fairness guaranteed cooperative resource allocation (FGCRA) to manage interference among femtocells. Since the optimal resource allocation is a NP-hard problem, which is difficult to get global optimization in femtocell networks, our proposed FGCRA algorithm provides sub-optimal resource allocation via cooperation among interfering neighbors. First, we propose a specific fairness factor obtained from two-hop interference relations, to determine the lower bound amount of subchannels that each FAP can use and guarantee the fairness among femtocells. Second, we propose scalable rules for distributed resource allocation and the solution to avoid the conflicts among interfering neighbors. Simulation results show that our proposed FGCRA significantly enhances both average user throughput and cell edge user throughput, and provides better fairness.

A New Architecture for Email Knowledge Extraction

The Semantic Web was designed to represent the enormous data that is existing on the World Wide Web in a machine readable format. The research shows the long period of time that was spent on the Emails for communication and information exchange. Adding the semantics to the existing Email systems could not only provide for the valuable usage of time and resources, but also refreshes the meaning of Email communication. The presented research work examines the ontology extraction process from the Email systems adopting scalable pattern rules that is based on the extracted techniques. The proposed architecture is designed to handle the unstructured Emails and the ontologies that are extracted from the Email which is divided into four main components as follows: the Ontology Learning Component, the Management Component, the Semantic Email Component and the Client Side Plugin.

Scalable Rules for Coherent Group Motion in a Gregarious Vertebrate

Individuals of gregarious species that initiate collective movement require mechanisms of cohesion in order to maintain advantages of group living. One fundamental question in the study of collective movement is what individual rules are employed when making movement decisions. Previous studies have revealed that group movements often depend on social interactions among individual members and specifically that collective decisions to move often follow a quorum-like response. However, these studies either did not quantify the response function at the individual scale (but rather tested hypotheses based on group-level behaviours), or they used a single group size and did not demonstrate which social stimuli influence the individual decision-making process. One challenge in the study of collective movement has been to discriminate between a common response to an external stimulus and the synchronization of behaviours resulting from social interactions. Here we discriminate between these two mechanisms by triggering the departure of one trained Merino sheep (Ovis aries) from groups containing one, three, five and seven naïve individuals. Each individual was thus exposed to various combinations of already-departed and non-departed individuals, depending on its rank of departure. To investigate which individual mechanisms are involved in maintaining group cohesion under conditions of leadership, we quantified the temporal dynamic of response at the individual scale. We found that individuals' decisions to move do not follow a quorum response but rather follow a rule based on a double mimetic effect: attraction to already-departed individuals and attraction to non-departed individuals. This rule is shown to be in agreement with an adaptive strategy that is inherently scalable as a function of group size.

Scalable modeling and comparison for spiral inductors using enhanced 1-π and 2-π topologies

Two different scalable models developed based on enhanced 1-π and 2-π topologies are presented for on-chip spiral inductor modeling. All elements used in the two topologies for accurately predicting the characteristics of spiral inductors at radio frequencies are constructed in geometry-dependent equations for scalable modeling. Then a comparison between the 1-π and 2-π scalable models is made from the following aspects: the complexity of equivalent circuit models and parameter-extraction procedures, scalable rules and the accuracy of scalable models. The two scalable models are further verified by the excellent match between the measured and simulated results on extracted parameters up to self-resonant frequency (SRF) for a set of spiral inductors with different L, R and N, which are fabricated by employing 0.18-μm 1P6M RF CMOS technology.

Scalable Small-Signal and Noise Modeling for Deep-Submicrometer MOSFETs

A new scalable noise and small-signal model for deep-submicrometer metal-oxide semiconductor field-effect transistors, which consist of multiple elementary cells is presented in this paper. It allows exact modeling of all noise and small-signal model parameters from elementary cell to large-size device. The scalable rules for noise and small-signal model parameters are given in detail. The experimental and theoretical results show that at same bias condition, good scaling of the noise, and small-signal model parameters can be achieved between the large-size devices and elementary cell. Model verification is carried out by comparison of measured and simulated S-parameters and noise parameters. Good agreement is obtained between the measured and modeled results for 4 times 0.6 times 18 mum, 8 times 0.6 times 12 mum, and 32 times 0.6 times 2 mum gatewidth (number of gate fingers times unit gatewidth times cells) 90 nm gatelength MOSFETs.

Three-Dimensional Construction with Mobile Robots and Modular Blocks

We present a decentralized algorithmic approach to automatically building user-specified three-dimensional structures from modular units. Our bipartite system comprises passive units (blocks), responsible for embodying the structure and determining where further units can legally be attached, and active units (robots), responsible for transporting passive units. The algorithmic issues are correspondingly decomposed into two parts: (1) deciding where passive units may be attached; and (2) getting them to those locations. For the first part, we give simple, scalable rules for attachment and prove that they will reliably lead to the construction of any desired structure from a large class of three-dimensional shapes. For the second part, we compare three approaches: random movement, systematic search and gradient-following; each approach is successively faster but requires more communication overhead and/or unit capabilities. The system we describe enables guaranteed construction of desired structures using very simple agent algorithms, taking a high-level specification as the only required input. The topic of collective construction is related to the problems of programmed self-assembly and self-reconfiguration in modular robots, and the rules governing block attachment presented here may be usefully applied to such systems.

A Pipelined Temporal Difference Imager

A 189/spl times/182 active pixel sensor (APS) for temporal difference computation is presented. The temporal difference imager (TDI), fabricated in 0.5-/spl mu/m CMOS process, contains in-pixel storage elements for a previous image frame. Difference double-sampling circuits are used to suppress the fixed pattern noise in both images and to compute the difference between the corrected images. The pixel area occupies 25 /spl mu/m by 25 /spl mu/m (using 0.7-/spl mu/m scalable rules), with fill factor of 30%. A novel pipelined readout technique is described, which is used to improve the accuracy of the temporal difference computation. With this pipelined readout architecture, >8-bit precision for the difference image and low spatial droop across the difference image is achieved. The chip consumes 30 mW at 50 fps from a 5-V power supply.

A dual pixel-type array for imaging and motion centroid localization

An imager chip has been designed, fabricated, and tested having two unique pixel types interleaved on the same array. The dual-pixel design enables optimization for two separate tasks. One type of pixel is an active pixel sensor (APS), which is used to produce a low-noise image. The other type is a custom-designed pixel optimized for computing the centroid of a moving object in the scene. The APS array is 120 columns /spl times/36 rows, with a pixel size of 14.7/spl times/14.7 /spl mu/m. The centroid array has 60 columns and 36 rows, with a larger pixel size of 29.4/spl times/29.4 /spl mu/m. The chip was fabricated using standard scalable rules on a 0.5 /spl mu/m 1P3M CMOS process. APS images were taken at a frame rate of 30 fps-8300 fps and centroid data was taken at a rate of 180-3580 (x,y) coordinates per second. The chip consumed 2.6 mW.

Entering the Millennium: A New Century for LCSH

SUMMARY Library of Congress Subject Headings (LCSH), a system originally designed as a tool for subject access to the Library's own collection in the late nineteenth century, has become, in the course of the last century, the main subject retrieval tool in library catalogs throughout the United States and in many other countries. It is one of the largest non-specialized controlled vocabularies in the world. As LCSH enters a new century, it faces an information environment that has undergone vast changes from what had prevailed when LCSH began, or, indeed, from its state in the early days of the online age. In order to continue its mission and to be useful in spheres outside library catalogs as well, LCSH must adapt to the multifarious environment. One possible approach is to adopt a series of scalable and flexible syntax and application rules to meet the needs of different user communities.

VLSI architecture for HDTV sub-band coding using GQMFs' filterbanks

A VLSI architecture for a low complexity intraframe subband image coding for HDTV signals is presented. The generalized quadrature mirror filters (GQMFs), which have smaller overall delay, are optimized in order to achieve high coding efficiency. The filter design exploits a symmetry property among different filter coefficients which, in turn, reduces the hardware complexity of the VLSI architecture substantially. The architecture is designed with 1 /spl mu/m CMOS technology using the scalable design rules of MDS Integrated Services Inc. (MOSIS). The VLSI architecture contains approximately 200,000 transistors and it is capable of operating at a speed of 34 MHz. The HDTV signals are decomposed into seven bands. The baseband is DPCM encoded and the high bands are PCM encoded. It is shown that high quality HDTV images can be obtained at a low bit rate as 0.654 bpp (bits/pixel). >

VLSI architecture for computing third-order cumulants

The higher order statistics (HOS) (or cumulants), and their associated Fourier Transforms, have been established as a powerful analytical tool in modern signal processing. This paper presents a computationally efficient VLSI architecture for computing third-order cumulants. The architecture is based on the systolic array implementation and exploits parallelism, pipelining, and regular cell structures. The architecture is designed with 10μm CMOS technology using the scalable design rules of MOS Integrated Services (MOSIS). The VLSI architecture contains approximately 36 500 transistors and it is capable of operating at a speed of 5-2 MHz.