Gate Output Research Articles

Complete Fault Detection Tests of Length 2 for Logic Networks under Stuck-at Faults of Gates

We consider the problem of the synthesis of the logic networks implementing Boolean functions of n variables and allowing short complete fault detection tests regarding arbitrary stuck-at faults at the outputs of gates. We prove that there exists a basis consisting of two Boolean functions of at most four variables in which we can implement each Boolean function by a network allowing such a test with length at most 2.

Sentic LSTM: a Hybrid Network for Targeted Aspect-Based Sentiment Analysis

Sentiment analysis has emerged as one of the most popular natural language processing (NLP) tasks in recent years. A classic setting of the task mainly involves classifying the overall sentiment polarity of the inputs. However, it is based on the assumption that the sentiment expressed in a sentence is unified and consistent, which does not hold in the reality. As a fine-grained alternative of the task, analyzing the sentiment towards a specific target and aspect has drawn much attention from the community for its more practical assumption that sentiment is dependent on a particular set of aspects and entities. Recently, deep neural models have achieved great successes on sentiment analysis. As a functional simulation of the behavior of human brains and one of the most successful deep neural models for sequential data, long short-term memory (LSTM) networks are excellent in learning implicit knowledge from data. However, it is impossible for LSTM to acquire explicit knowledge such as commonsense facts from the training data for accomplishing their specific tasks. On the other hand, emerging knowledge bases have brought a variety of knowledge resources to our attention, and it has been acknowledged that incorporating the background knowledge is an important add-on for many NLP tasks. In this paper, we propose a knowledge-rich solution to targeted aspect-based sentiment analysis with a specific focus on leveraging commonsense knowledge in the deep neural sequential model. To explicitly model the inference of the dependent sentiment, we augment the LSTM with a stacked attention mechanism consisting of attention models for the target level and sentence level, respectively. In order to explicitly integrate the explicit knowledge with implicit knowledge, we propose an extension of LSTM, termed Sentic LSTM. The extended LSTM cell includes a separate output gate that interpolates the token-level memory and the concept-level input. In addition, we propose an extension of Sentic LSTM by creating a hybrid of the LSTM and a recurrent additive network that simulates sentic patterns. In this paper, we are mainly concerned with a joint task combining the target-dependent aspect detection and targeted aspect-based polarity classification. The performance of proposed methods on this joint task is evaluated on two benchmark datasets. The experiment shows that the combination of proposed attention architecture and knowledge-embedded LSTM could outperform state-of-the-art methods in two targeted aspect sentiment tasks. We present a knowledge-rich solution for the task of targeted aspect-based sentiment analysis. Our model can effectively incorporate the commonsense knowledge into the deep neural network and be trained in an end-to-end manner. We show that the two-step attentive neural architecture as well as the proposed Sentic LSTM and H-Sentic-LSTM can achieve an improved performance on resolving the aspect categories and sentiment polarity for a targeted entity in its context over state-of-the-art systems.

A network model of behavioural performance in a rule learning task.

Humans demonstrate differences in performance on cognitive rule learning tasks which could involve differences in properties of neural circuits. An example model is presented to show how gating of the spread of neural activity could underlie rule learning and the generalization of rules to previously unseen stimuli. This model uses the activity of gating units to regulate the pattern of connectivity between neurons responding to sensory input and subsequent gating units or output units. This model allows analysis of network parameters that could contribute to differences in cognitive rule learning. These network parameters include differences in the parameters of synaptic modification and presynaptic inhibition of synaptic transmission that could be regulated by neuromodulatory influences on neural circuits. Neuromodulatory receptors play an important role in cognitive function, as demonstrated by the fact that drugs that block cholinergic muscarinic receptors can cause cognitive impairments. In discussions of the links between neuromodulatory systems and biologically based traits, the issue of mechanisms through which these linkages are realized is often missing. This model demonstrates potential roles of neural circuit parameters regulated by acetylcholine in learning context-dependent rules, and demonstrates the potential contribution of variation in neural circuit properties and neuromodulatory function to individual differences in cognitive function.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'.

Photon-Mediated Quantum Gate between Two Neutral Atoms in an Optical Cavity

Quantum logic gates are fundamental building blocks of quantum computers. Their integration into quantum networks requires strong qubit coupling to network channels, as can be realized with neutral atoms and optical photons in cavity quantum electrodynamics. Here we demonstrate that the long-range interaction mediated by a flying photon performs a gate between two stationary atoms inside an optical cavity from which the photon is reflected. This single step executes the gate in $2\,\mathrm{\mu s}$. We show an entangling operation between the two atoms by generating a Bell state with 76(2)% fidelity. The gate also operates as a CNOT. We demonstrate 74.1(1.6)% overlap between the observed and the ideal gate output, limited by the state preparation fidelity of 80.2(0.8)%. As the atoms are efficiently connected to a photonic channel, our gate paves the way towards quantum networking with multiqubit nodes and the distribution of entanglement in repeater-based long-distance quantum networks.

Concatenated logic functions using nanofluidic diodes with all-electrical inputs and outputs

Nanopore-based logical schemes in ionic solutions typically involve single gates and chemical inputs. The design of computer-like functions requires the consecutive concatenation of several gates and the use of electrical potentials and currents to facilitate the downstream transfer of electrochemical information. We have demonstrated the robust operation of concatenated logic functions using biomimetic nanofluidic diodes based on single pore membranes. To this end, we have implemented first the logic functions AND and OR with combinations of single nanopores using all-electrical input and output signals. The concatenation of these gates allows the output of the OR gate to act as one of the inputs of the AND gate, giving an Enabled-OR logic function. Also, the operation of the OR gate connected with a solid-state transistor, working as a signal inverter, gives a NOR gate. These hybrid electrochemical circuits allow a variety of real time logic functions because of the robust electrical coupling between ionic solutions and electronic elements.

Короткие единичные тесты для схем при произвольных константных неисправностях на выходах элементов

Короткие единичные тесты для схем при произвольных константных неисправностях на выходах элементов

Short single tests for circuits with arbitrary stuck-at faults at outputs of gates

Доказаны следующие факты: 1) любую неконстантную булеву функцию можно реализовать неизбыточной схемой из функциональных элементов в базисе $\{x&y,$ $\overline x,x\oplus y\oplus z\}$, допускающей единичный проверяющий тест длины не более 2 относительно произвольных константных неисправностей на выходах элементов, 2) существует такая булева функция $\psi$ от шести переменных, что любую неконстантную булеву функцию можно реализовать неизбыточной схемой из функциональных элементов в базисе $\{\psi\}$, допускающей единичный диагностический тест длины не более 3 относительно произвольных константных неисправностей на выходах элементов.

Короткие полные проверяющие тесты для схем из двухвходовых функциональных элементов

It is established that we can implement almost every Boolean function on n variables by a logic network in the basis {x&y, x ∨ y, x ⨁ y, 1}, allowing a complete fault detection test with length at most 4 under arbitrary stuck-at faults at outputs of gates. The following assertions are also proved:We can implement each Boolean function on n variables by a logic network in the basis {x&y, x ∨ y, x ⨁ y, 1} (in the basis {x&y, x ∨ y, x ∨ y, x ⨁ y}) containing at most one dummy variable and allowing a complete fault detection test of length at most 5 (at most 4, respectively) under faults of the same type.

Синтез легкотестируемых схем при однотипных константных неисправностях на входах и выходах элементов

Синтез легкотестируемых схем при однотипных константных неисправностях на входах и выходах элементов

Синтез легкотестируемых схем при произвольных константных неисправностях на входах и выходах элементов

Синтез легкотестируемых схем при произвольных константных неисправностях на входах и выходах элементов

Boolean-chemotaxis of logibots deciphering the motions of self-propelling microorganisms.

We demonstrate the feasibility of a self-propelling mushroom motor, namely a 'logibot', as a functional unit for the construction of a host of optimized binary logic gates. Emulating the chemokinesis of unicellular prokaryotes or eukaryotes, the logibots made stimuli responsive conditional movements at varied speeds towards a pair of acid-alkali triggers. A series of integrative logic operations and cascaded logic circuits, namely, AND, NAND, NOT, OR, NOR, and NIMPLY, have been constructed employing the decisive chemotactic migrations of the logibot in the presence of the pH gradient established by the sole or coupled effects of acid (HCl-catalase) and alkali (NaOH) drips inside a peroxide bath. The imposed acid and/or alkali triggers across the logibots were realized as inputs while the logic gates were functionally reconfigured to several operational modes by varying the pH of the acid-alkali inputs. The self-propelling logibot could rapidly sense the external stimuli, decide, and act on the basis of intensities of the pH triggers. The impulsive responses of the logibots towards and away from the external acid-alkali stimuli were interpreted as the potential outputs of the logic gates. The external stimuli responsive self-propulsion of the logibots following different logic gates and circuits can not only be an eco-friendly alternative to the silicon-based computing operations but also be a promising strategy for the development of intelligent pH-responsive drug delivery devices.

Design and modelling of high gain DC-DC converters for fuel cell hybrid electric vehicles

Transportation (Diesel and petrol internal combustion engine vehicles) approximately contributes to 25.5% of total CO2 emission. Thus diesel and petrol engine vehicles are the most dominant contributors of CO2 emission which leads global warming which causes climate change. The problem of CO2 emission and global warming can be reduced by focusing on renewable energy vehicles. Out of the available renewable energy sources fuel cell is the only source which has reasonable efficiency and can be used in vehicles. But the main disadvantage of fuel cell is its slow response time. So energy storage systems like batteries and super capacitors are used in parallel with the fuel cell. Fuel cell is used during steady state vehicle operation while during transient conditions like starting, acceleration and braking batteries and super capacitors can supply or absorb energy. In this paper a unidirectional fuel cell DC-DC converter and bidirectional energy storage system DC-DC converter is proposed, which can interface dc sources at different voltage levels to the dc bus and also it can independently control the power flow from each energy source to the dc bus and vice versa. The proposed converters are designed and simulated using PSIM version 9.1.1 and gate pulse pattern, input and output voltage waveforms of the converters for steady state operation are studied.

Надёжность схем в базисе Россера - Туркетта (в P3) при неисправностях типа 0 на выходах элементов

Надёжность схем в базисе Россера - Туркетта (в P3) при неисправностях типа 0 на выходах элементов

О надёжности схем в некоторых полных базисах (в P3) при инверсных неисправностях на выходах элементов

О надёжности схем в некоторых полных базисах (в P3) при инверсных неисправностях на выходах элементов

On the exact value of the length of the minimal single diagnostic test for a particular class of circuits

Under consideration is the problem of synthesis of irredundant logic circuits in the basis {&, ∨, ¬} which implement Boolean functions of n variables and allow some short single diagnostic tests regarding uniform constant faults at outputs of gates. For each Boolean function permitting implementation by an irredundant circuit, the minimal possible length value of such a test is found. In particular, we prove that this value is at most 2.

Compact Modeling of Organic Thin-Film Transistors with Solution Processed Octadecyl Substituted Tetrabenzotriazaporphyrin as an Active Layer

Using 70-nm-thick spin-coated film of newly synthesized octadecyl substituted copper tetrabenzotriazaporphyrin (10CuTBTAP) as an active layer on a highly doped silicon (110) gate electrode substrates, output characteristics and transfer characteristics of bottom-gate bottom-contact organic thin-film transistors have been measured at room temperature. A compact model for thin-film transistors has been employed as a part of circuit design tool to extract device parameters, such as the charge-carrier mobility ${\mu }$ , the threshold voltage $V_{T}$ , and the contact resistances. Parallel measurements and analysis were performed on similarly constructed devices with a copper phthalocyanine(10CuPc) analog. The results reveal that the 10CuPc layer is relatively more susceptible to trapping degradation near the gate region than a 10CuTBTAP layer, which is significant in order to achieve stability in these transistors. The application of the simple square law in the classical MOS model provides a quicker but approximate interpretation of the transistor performance without providing information on the gate-voltage dependence of mobility and the effects of the contact regions. In this paper, the analysis of the contact regions is found to be very important for determining the difference in the performance of two transistors.

Mechanistic modelling of a recombinase‐based two‐input temporal logic gate

Site-specific recombinases (SSRs) mediate efficient manipulation of DNA sequences in vitro and in vivo. In particular, serine integrases have been identified as highly effective tools for facilitating DNA inversion, enabling the design of genetic switches that are capable of turning the expression of a gene of interest on or off in the presence of a SSR protein. The functional scope of such circuitry can be extended to biological Boolean logic operations by incorporating two or more distinct integrase inputs. To date, mathematical modelling investigations have captured the dynamical properties of integrase logic gate systems in a purely qualitative manner, and thus such models are of limited utility as tools in the design of novel circuitry. Here, the authors develop a detailed mechanistic model of a two-input temporal logic gate circuit that can detect and encode sequences of input events. Their model demonstrates quantitative agreement with time-course data on the dynamics of the temporal logic gate, and is shown to subsequently predict dynamical responses relating to a series of induction separation intervals. The model can also be used to infer functional variations between distinct integrase inputs, and to examine the effect of reversing the roles of each integrase on logic gate output.

DNA Domino-Based Nanoscale Logic Circuit: A Versatile Strategy for Ultrasensitive Multiplexed Analysis of Nucleic Acids

In recent years, the analytical application of logical nanodevices has attracted much attention for making accurate decisions on molecular diagnosis. Herein, a DNA domino-based nanoscale logic circuit has been constructed by integrating three logic gates (AND-AND-YES) for simultaneous analysis of multiple nucleic acid biomarkers. In the first AND gate, a chimeric target DNA comprising of four biomarkers was hybridized to three biomarker-specific oligonucleotides (TRs) via their 5'-end regions and to a capture probe-magnetic microparticle. After harvesting the complex, 3' overhang regions of the TRs were labeled with three distinct monolayer double-stranded (ds) DNA-gold nanoparticles (DNA-AuNPs). Upon gleaning the complex and addition of initiator oligonucleotide, a series of toehold-mediated strand displacement reactions, which are reminiscent of a domino chain, spontaneously occurred between the confined dsDNAs on the nanoparticles' surface in the second AND gate. The output of the second gate entered into the last gate and triggered an exponential hairpin assembly to form four-way junction nanostructures. The resulting nanostructures bear split parts of DNAzyme at each end of the four arms which, in the presence of hemin, form catalytic hemin/G-quadruplex DNAzymes with peroxidase activity. The smart biosensor has exhibited a turn-on signal when all biomarkers are present in the sample. In fact, should any of the biomarkers be nonexistent, the signal remains turned-off. The biosensor can detect the biomarkers with a LOD value of 100 aM and a noticeable capability to discriminate single-nucleotide substitutions.

P‐68: Analysis and Solution of Horizontal Line Defect Occurred During Reliability Test in 55' UD TFT‐LCD TV with a‐Si Integrated Gate Driver Technology

Analysis results demonstrates in this paper for gradation horizontal line (H‐line) occurred in reliability (aging) test on amorphous silicon TFT‐LCDs with integrated gate driver technology (short as GOA circuit). There are two factors that induce H‐line: GOA gate output and data inversion type. Changing these two factors could eliminate or relieve H‐line defect.

Clinical Text De-identification and Other Large Scale Processing Tasks in Resource Constrained Environments

ABSTRACT
 ObjectivesClinical text de-identification is a common requirement of the ‘enclave’ governance model of ethical EHR research. However, there is often little consideration of the engineering task that is required to scale these approaches across the hundreds of millions of clinical documents containing personal identifiers that are resident in the data repositories of a typical NHS Trust. Similarly, natural language processing is an increasingly important field of clinical data science, yet it requires fault tolerant approaches to data processing. This work concerns the development of “turbo-laser” - a distributed document processing architecture based upon the popular ‘battle hardened’ Spring Batch framework - an industry standard for large scale processing tasks.
 ApproachUsing Spring Batch, we developed a highly scalable unstructured data processing framework, using the concept of remote partitioning. Remote partitioning allows us to offload processing tasks to any and all computers in a network. With this approach, it is possible to harness the entire compute available of an organisation, whether it be an office of 15 desktop PCs that go unused overnight, or a compute cluster of a thousand processors. This method is especially valuable in the NHS, where the provision of sufficient compute to make large scale analytics possible are often hindered by the lack of available hardware, or difficulties in navigating technical governance policies ill equipped for the demands of modern data science.
 ResultsTurbo-laser was developed in consideration of the processing challenges common in the NHS. Currently, four types of ‘job’ are available - De-identification, using the Cognition algorithm, generic GATE output, text extraction from binary files such as MS Office, PDF and scanned documents, and a document re-compiler to deal with EHR legacy issues. Examples of turbo-laser usage include processing 9 million binary documents on modest hardware, within 48 hours.
 ConclusionTurbo-laser is an enterprise grade processing tool, in keeping with the software engineering pattern of ‘batch processing’ that has been at the forefront of the informatics movement. An open source project, it is hoped that others may contribute and extend its principles, lowering the barrier of large scale data processing throughout the NHS.