Matching Logic Research Articles

BPR-TCAM—Block and Partial Reconfiguration based TCAM on Xilinx FPGAs

Field Programmable Gate Arrays (FPGAs) based Ternary Content Addressable Memories (TCAMs) are widely used in high-speed networking applications.However, TCAMs are not present on state-of-the-art FPGAs and need to be emulated on SRAM-based memories (i.e., LUTRAMs and Block RAMs) which requires a large amount of FPGA resources. In this paper, we present an efficient methodology to implement FPGA-based TCAMs with significant resource savings compared to existing schemes. The proposed methodology exploits the fracturable nature of Look Up Tables (LUTs) and the built-in slice carry-chains for simultaneous mapping of two rules and its matching logic to a single FPGA slice. Multiple slices can be stacked together to build deeper and wider TCAMs in a modular way. The combination of all these techniques results in significant savings in resource utilization compared to existing approaches.

Logical Intervention in the Form of Work Breakdown Strategy using Object Constraint Language for e-Commerce Application

This paper proposes a framework for Rule Based inhibition on e-commerce website for prevention of double payment and computing time invariant for concurrent event handling. Authors have analyzed computational models in terms of Customer segmentation replicating their buying characteristics and Dialogue level constraint establishment through OCL. The tool used are MDT-OCL and matching logic for logic level interpretation. The MDT tool generates Context Syntax Tree. We have used LPG grammar to be applied WBS codification by differentiating Descriptive Noun containing description about the products and associated verbs about the product. Authors have used Eclipse plug-ins to embed it logic constraint mapping to check for any ontological errors and double selection and payment errors.

IMPLEMENTATION OF THE GOALS OF CARE DECISION AID IN NURSING HOMES: AN EVIDENCE-BASED INTERVENTION

Nursing homes (NH) must implement best practices to improve care. The purpose of this study is to understand NH characteristics that help or hinder implementation of the Goals of Care (GOC) intervention, an evidence-based decision aid to guide decision-making in advanced dementia. Study design was a cross-sectional staff survey at 11 NHs in North Carolina that participated in the GOC trial. Questions measured the dependent variable of implementation effectiveness (IE) (the consistency and quality of use of the GOC intervention). NH organizational characteristics were measured using publicly available data and administrator surveys. Averages were obtained, IE and NH factors above the average were ranked as high and vice versa. Analysis consisted of pattern matching logic, predicted results are compared to actual results, using within-case and cross-case analyses. NHs with high IE were expected to have the majority (five or more) of NH characteristics to be high to confirm the within (within-case analysis) and between (cross-case analysis) relationships. Within-case analysis expected results were met in 5 NHs, with 3 highs (IE high and five or more characteristics were high) and 2 lows (IE low and five or more characteristics were low). Among three NHs with high IE, the following characteristics were high: Medicare and SNF/ICF beds. Across 6 of the 11 NHs, high total beds and percent of White residents were related to high IE. NHs with enhanced resources may have fewer challenges implementing innovations compared to resource constrained NHs. Implementation strategies should account for resource limitations to promote successful implementation.

Delta-Sigma Modulator with Relaxed Feedback Timing for High Speed Applications

In this paper, a ΔΣ analog-to-digital converter (ADC) was designed and measured for broadband and high-resolution applications by applying the simple circuit technique to alleviate the feedback timing of input feed-forward architecture. With the proposed technique, a low-speed comparator and dynamic element matching (DEM) logic can be applied even for high-speed implementation, which helps to decrease power dissipation. Two prototypes using slightly different input branch topologies were fabricated with a 0.18 um 2-poly and 4-metal CMOS process, and measured to demonstrate the effectiveness of the proposed circuit technique. The sampling capacitor and feedback DAC capacitors were separated in prototype A, while they were shared in prototype B. The prototypes achieved 81.2 dB and 72.4 dB of SNDR in a 2.1 MHz signal band, respectively.

Real-Time Traffic Flow Pattern Matching to Improve Predictive Performance of Online Simulation-Based Dynamic Traffic Assignment

In real-time simulation-based dynamic traffic assignment, selection of the most suitable demand from the library of demands calibrated offline improves the accuracy of the prediction. In the era of data explosion, relying on contextual and rule-based pattern matching logic does not seem sufficient. A rolling horizon scheme for real-time pattern matching is introduced using two pattern matching frameworks. The hard matching algorithm chooses the closest pattern at each evaluation interval, while soft matching calculates the probability of being a match for each pattern. To make sure the pattern switch does not happen because of short-lived interruptions in traffic conditions, a persistency index is introduced. The results show that the number of switches in hard matching is bigger than soft matching but the error of real-time matching for both cases is low. The importance of the results is twofold: First, any observation that is not similar to only one pattern in the library can be mimicked using multiple available patterns; second, more advanced algorithms can match the patterns existing in the library, without any contextual logics for pattern matching.

Abstract 2288: Assessing patient trial readiness for precision cancer medicine clinical trials through computational trial matching and rule-based logic applied to genomic and clinical data

Abstract More than 1,100 phase I treatment trials are registered with clinicaltrials.cancer.gov. Patient identification and recruitment to these trials is particularly challenging due to the vast molecular data now available for patients and the increasingly complex nature of the molecular eligibility criteria. Additionally, Phase I trial staff often manage a portfolio of dozens of trials, making patient identification, recruitment, screening, and enrollment an arduous task. To address the need for better and more efficient patient identification, we have developed MatchMiner, a novel open source computational platform for matching patient-specific genomic profiles to precision cancer medicine clinical trials, and a pre-screening tool that includes options for filtering and sorting patients based on clinical data elements. MatchMiner excels at identifying patients who are eligible for clinical trials based on genomic, cancer type, age, and gender criteria, but the great majority of patients are not currently ready for a trial. The pre-screening tool allows for the integration of additional clinical data, including genomic testing date, appointments, treatment plan history, and radiology scan impression text, in order to provide an assessment of ‘trial readiness'. To integrate these tools into the clinical workflow, we have implemented a weekly MatchMiner Tumor Board Review process, where together with the DFCI Early-Phase Drug Development Center (EDDC) physicians and staff, a thorough assessment of potential patient-trial matches is performed. Currently we have scaled this initiative to include 18 genomically-driven trials. Each week, ~9000 patient-trial matches are computed across all open trials, which are then computationally filtered to a list of ~300 patient-trial matches utilizing rules-based logic applied to our clinical data sources. The MatchMiner team then performs a manual review of pre-filtered matches based on additional requirements, such as evidence of progression in the radiology scan text impressions. The final list of ~10-20 patients is reviewed with the EDDC, and patients deemed to be ‘trial ready' are flagged. E-mail notifications are then sent out to the patient's oncologist, alerting them to a potential genomically-driven clinical trial opportunity. The combination of computational patient-trial match identification and rules-based computational pre-filtering based on additional clinical data has allowed us to screen thousands of patients per week, which would not be possible otherwise. To evaluate the success of this initiative, we are tracking patient consults and trial enrollments, and capturing feedback on workflow integration and utilization. Additionally, efforts to further automate trial readiness measurements to minimize the need for manual review are ongoing. Citation Format: Catherine Del Vecchio Fitz, Khanh Do, James Lindsay, Suzanne Hector-Barry, Zachary Zwiesler, Priti Kumari, Tali Mazor, Tamba Monrose, Adem Albayrak, John Methot, Michael Hassett, Geoffrey Shapiro, Ethan Cerami. Assessing patient trial readiness for precision cancer medicine clinical trials through computational trial matching and rule-based logic applied to genomic and clinical data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2288.

A Perfect Match Genomic Landscape Provides a Unified Framework for the Precise Detection of Variation in Natural and Synthetic Haploid Genomes.

We present a conceptually simple, sensitive, precise, and essentially nonstatistical solution for the analysis of genome variation in haploid organisms. The generation of a Perfect Match Genomic Landscape (PMGL), which computes intergenome identity with single nucleotide resolution, reveals signatures of variation wherever a query genome differs from a reference genome. Such signatures encode the precise location of different types of variants, including single nucleotide variants, deletions, insertions, and amplifications, effectively introducing the concept of a general signature of variation. The precise nature of variants is then resolved through the generation of targeted alignments between specific sets of sequence reads and known regions of the reference genome. Thus, the perfect match logic decouples the identification of the location of variants from the characterization of their nature, providing a unified framework for the detection of genome variation. We assessed the performance of the PMGL strategy via simulation experiments. We determined the variation profiles of natural genomes and of a synthetic chromosome, both in the context of haploid yeast strains. Our approach uncovered variants that have previously escaped detection. Moreover, our strategy is ideally suited for further refining high-quality reference genomes. The source codes for the automated PMGL pipeline have been deposited in a public repository.

Peran Pertanian Urban Pada Kesejahteraan Petani Muslim Pada Empat Kelompok Tani Di Surabaya Ditinjau Dari Perspektif Islam

This study aimed to describe the role of urban farming in the welfare of the Muslim farmers in four farmer groups in Surabaya from the perspective of Islam. This study used descriptive qualitative approach with case study strategy. The data authenticity technique using construct validity tactics with multiple sources of evidence. The analysis technique using pattern matching logic. The results showed the positive role of urban farming in the material welfare, namely: the creation of job opportunities and self-employment, the creation of small businesses in the agricultural sector and the informal sector, and increase the income of the four members of farmer groups; whereas the non-material welfare, namely: produce farmed commodities and processed products that is classified as halal, income which does not contain usury, implementing the principles of honesty and fairness principles in marketing, as well as undertake community development activities such as counseling and training.

Semantics-based program verifiers for all languages

We present a language-independent verification framework that can be instantiated with an operational semantics to automatically generate a program verifier. The framework treats both the operational semantics and the program correctness specifications as reachability rules between matching logic patterns, and uses the sound and relatively complete reachability logic proof system to prove the specifications using the semantics. We instantiate the framework with the semantics of one academic language, KernelC, as well as with three recent semantics of real-world languages, C, Java, and JavaScript, developed independently of our verification infrastructure. We evaluate our approach empirically and show that the generated program verifiers can check automatically the full functional correctness of challenging heap-manipulating programs implementing operations on list and tree data structures, like AVL trees. This is the first approach that can turn the operational semantics of real-world languages into correct-by-construction automatic verifiers.

MatchC: A Matching Logic Reachability Verifier Using the [formula omitted] Framework

This paper presents MatchC, a matching logic reachability verifier using the K framework. K is a rewriting-based framework for defining and analyzing programming languages. Matching logic is a logic designed to state and reason about structural properties over arbitrary program configurations. Matching logic reachability is a unifying framework for operational and axiomatic semantics of programing languages. The MatchC verifier (http://matching-logic.org/) checks reachability properties of programs written in a deterministic fragment of C and is implemented in the K framework. This paper discusses the correctness of the implementation of the matching logic reachability proof system in MatchC. The main contributions of this paper are the implementation of the verifier, with emphasis on using K for program verification, and the evaluation of the tool on a large number of programs, including complex ones, like programs implementing the AVL trees data structure and the Schorr-Waite graph marking algorithm.

Digital Noise-Coupling Technique for Delta–Sigma Modulators With Segmented Quantization

A digital noise-coupling technique for delta–sigma modulators with a high-resolution quantizer is presented. The proposed technique divides the outputs of the quantizer into an MSB segment and an LSB segment. The MSBs are directly fed to the modulator input, whereas the LSBs are used as the quantization noise for noise coupling. After the digital postprocessing, the MSBs and the LSBs are then recombined. As a result, it preserves the benefit of increased quantization levels without suffering from the exponential growth of the dynamic element matching logic. The extra noise shaping introduced by the LSB feedback further reduces the quantization noise leakage caused by the mismatch between the analog and digital noise transfer functions, which allows a more relaxed operational amplifier design. This technique is simple to implement and well suited for low-power and wideband applications.

A Single Opamp Third-Order Low-Distortion Delta-Sigma Modulator with SAR Quantizer Embedded Passive Adder

A third-order low-distortion delta-sigma modulator (DSM), whose third-order noise-shaping ability is achieved by just a single opamp, is proposed. Since only one amplifier is required in the whole circuit, the designed DSM is very power efficient. To realize the adder in front of quantizer without employing the huge-power opamp, a capacitive passive adder, which is the digital-to-analog converter (DAC) array of a successive-approximation-type quantizer, is used. In addition, the feedback path timing is extended from a nonoverlapping interval for the conventional low-distortion structure to half of the clock period, so that the strict operation timing issue with regard to quantization and the dynamic element matching (DEM) logic operation can be solved. In the proposed DSM structure, the features of the unity-gain signal transfer function (STF) and finite-impulse-response (FIR) noise transfer function (NTF) are still preserved, and thus advantages such as a relaxed opamp slew rate and reduced output swing are also maintained, as with the conventional low-distortion DSM. Moreover, the memory effect in the proposed DSM is analyzed when employing the opamp sharing for integrators. The proposed third-order DSM with a 4-bit SAR ADC as the quantizer is implemented in a 90-nm CMOS process. The post-layout simulations show a 79.8-dB signal-to-noise and distortion ratio (SNDR) in the 1.875-MHz signal bandwidth (OSR=16). The active area of the circuit is 0.35 mm2 and total power consumption is 2.85 mW, resulting in a figure of merit (FOM) of 95 fJ/conversion-step. key words: delta-sigma modulator, DSM, opamp sharing, relaxed dynamic element matching (DEM) timing

Improved Path Planning Algorithm Based on Partial Distance Feature Vector Matching

Robotic path planning algorithm is an important research content of optimization. The improved path planning algorithm, based on distance measurement, use the feature vector for obtaining the location and for identifies different distances in search space. In order to improve the efficient of collision detection, the earth feature vector and taboo search theory were used as tools, combined with partial matching tech and fuzzy logic could get faster and more accurate outcomes than the algorithm only use fuzzy logic.

Implementing template matching logic in a standard flash memory cell

Current research into classification methods is almost exclusively software based, resulting in systems that perform well but are invariably slow when faced with large databases. The goal is therefore to create a hardware classification system that is much faster. In this paper, we introduce the concept of template matching logic and propose the use of a standard flash memory cell array to perform bit by bit template matching. The proposed system is based on a novel architecture that is unique and separate from existing architectures that make use of flash memory cell arrays. Verification is achieved by speech recognition simulations on the TIMIT database. Simulations of the system show results of 94.5 % recognition accuracy on clean words and 88.0 % recognition accuracy on test words with a signal-to-noise ratio of 5 dB. The results compare favorably to similar isolated word recognition tasks performed with software based methods.

A Third-Order Low-Distortion Delta-Sigma Modulator with Opamp Sharing and Relaxed Feedback Path Timing

SUMMARY This paper proposes a third-order low-distortion deltasigma modulator (DSM). The third-order noise shaping is achieved by a single opamp (excluding the quantizer). In the proposed DSM structure, the timing limitation on the quantizer and dynamic element matching (DEM) logic in a conventional low-distortion structure can be relaxed from a nonoverlapping interval to half of the clock period. A cyclic analog-to-digital converter with a loading-free technique is utilized as a quantizer, which shares an opamp with the active adder. The signal transfer function (STF) is preserved as unity, which means that the integrators process only the quantization noise component. As a result, the opamp used for the integrators has lower requirements, as low-distortion DSMs, on slew rate, output swing, and power consumption. The proposed third-order DSM with a 4bit cyclic-type quantizer is implemented in a 90-nm CMOS process. Under a sampling rate of 80 MHz and oversampling ratio of 16, simulation results show that an 81.97-dB signal-to-noise and distortion ratio and an 80-dB dynamic range are achieved with 4.17-mW total power consumption. The resulting figure of merit (FOM) is 81.5 fJ/conversion-step.

Modeling and Matching Design of a Tension Controller Using Pendulum Dancer in Roll-to-Roll Systems

Dancer systems are typical equipment for attenuation of tension disturbances. The two kinds of dancer, active dancer and passive dancer, are distinguished by an external actuator. In the active dancer, the position of the dancer roll is measured and the roll is forced by the external actuator to regulate tension disturbances. However, the passive dancer, composed of a spring, damper and roll has no external actuator. Tension disturbance generates movements of the roll of the passive dancer and the displacements regulate the tension variation. However, the hybrid dancer, which is a mixture of passive and active dancer, is applied for the roll-to-roll systems. It regulates tension disturbances indirectly in the manner of keeping a constant position for the roll by changing the velocity of the driven roller adjacent to the dancer roll. It has different characteristics from those of the passive or active dancer. In this paper, the modeling of the pendulum dancer is derived. The dynamics of the hybrid dancer, which feedbacks the position of the dancer roll, and the PI control of a driven roll are analyzed. The matching logic for tuning gains is developed and experimentally verified.

Effective decision support systems for workforce deployment

Efficient utilization of human resources is imperative for information technology (IT) service businesses that continually manage the assignment and movement of practitioners to or between projects. These organizations constantly strive to balance the many objectives of multiple stakeholders in order to minimize idle resources while aiming to increase revenue from new project opportunities, as well as to improve the quality of practitioners assigned to each project. However, these various objectives conflict, so we can only hope to achieve an aggregated form of these disparate objectives. This emphasizes the need for a well-designed decision support system. Such a system will facilitate assignment of practitioners to projects while minimizing the overheads involved in a multiuser decision-making environment. Here, optimal refers to maximizing certain aggregated attributes of the various matches made with respect to the system. The term Buser[ refers to the decision makers who assign employees to various projects. The system comprises a text-matching module, a business logic module, an optimization module, and a user interface (UI) module. Key innovations include translating the business objectives into optimization criteria to be solved using integer programming, incorporating individual user preferences into the optimization, and encapsulating user experience into the matching logic. Additional innovations include those in text analytics to differentiate skill and nonskill terms and a UI design that helps users understand the relative global optimality of each recommendation in familiar terms while influencing decisions made independently by individual users in a way that collectively leads to organizationally outcomes. We also explain the role of decision support in implementing job-rotation and cross-training programs for practitioners. Finally, we share our experiences in the development and deployment of this system in an IT service company and describe areas where further work is needed.

Double-sampled ΔΣ modulator with relaxed feedback timing

A double-sampled delta-sigma (ΔΣ) modulator topology is proposed that can relax the critical timing constraints in the modulator feedback path. The speed requirements of the quantiser and dynamic element matching logic are thus greatly reduced. To verify the effectiveness of the proposed topology, a second-order double-sampled ΔΣ modulator is designed and simulated.

Assessing the Accuracy of Cash Flow Models: The Significance of Payment Conditions

Cash flow forecasting methods have evolved to allow detailed predictions for individual projects. These methods, principally the cost-schedule integration (CSI) technique, make extensive use of project estimate and schedule data. An implicit assumption of these methods has been that accuracy is largely a function of the quality of data available to the model. To the writers' knowledge, there has been no assessment of the ability of project specific cash-flow models to accurately predict cash flows given accurate input data. This paper makes two contributions. First, two complementary methods are presented—pattern matching logic and factorial analysis—that provide an ability to assess the accuracy of cash flow models. Second, through demonstration of these methods using data from two projects, a critique is made of the ability of existing CSI models to accurately predict cash flows. The paper concludes by recommending extensions of CSI models to include more detailed payment conditions, including differential payment lags, components for materials and labor, and payment frequency. A further conclusion is the call for more research to better understand the balance between managers' need for information and the ability of predictive models to provide that information.

Half-price architecture

Current-generation microprocessors are designed to process instructions with one and two source operands at equal cost. Handling two source operands requires multiple ports for each instruction in structures--such as the register file and wakeup logic--which are often in the processor's critical timing paths. We argue that these structures are overdesigned since only a small fraction of instructions require two source operands to be processed simultaneously. In this paper, we propose the half-price architecture that judiciously removes this overdesign by restricting the processor's capability to handle two source operands in certain timing-critical cases. Two techniques are proposed and evaluated: one for the wakeup logic is sequential wakeup, which decouples half of the tag matching logic from the wakeup bus to reduce the load capacitance of the bus. The other technique for the register file is sequential register access, which halves the register read ports by sequentially accessing two values using a single port when needed. We show that a pipeline that optimizes scheduling and register access for a single operand achieves nearly the same performance as an ideal base machine that fully handles two operands, with 2.2% (worst case 4.8%) IPC degradation.