Logic Table Research Articles

A few little steps beyond Knuth’s Boolean Logic Table with Neutrosophic Logic: A Paradigm Shift in Uncertain Computation

The present article delves into the extension of Knuth’s fundamental Boolean logic table to accommodate the complexities of indeterminate truth values through the integration of neutrosophic logic (Smarandache Christianto, 2008). Neutrosophic logic, rooted in Florentin Smarandache’s groundbreaking work on Neutrosophic Logic (cf. Smarandache, 2005, and his other works), introduces an additional truth value, ‘indeterminate,’ enabling a more comprehensive framework to analyze uncertainties inherent in computational systems. By bridging the gap between traditional boolean operations and the indeterminacy present in various real-world scenarios, this extension redefines logic tables, introducing neutrosophic operators that capture nuances beyond the binary realm. Through a thorough exploration of neutrosophic logic's principles and its implications in computational paradigms, this study proposes a novel approach to logic design that accommodates uncertain, imprecise, and incomplete information. This paradigm shift in logic tables not only broadens the spectrum of computing methodologies but also holds promise in fields such as decision-making systems and data analytics. This article amalgamates insights from over twelve key references encompassing seminal works in boolean logic, neutrosophic logic, and their applications in diverse scientific and computational domains, aiming to pave the way for a more robust and adaptable logic framework in computation.

Model-based detection and isolation of the wheel slippage and actuator faults of a holonomic mobile robot

PurposeMobile robots may perform very critical tasks under difficult operating conditions. Faults encountered during their tasks may cause the task to be interrupted or failed completely. In the active fault tolerant control methods, it is very important not only to detect the faults that occur in the robot, but also to isolate these faults to develop a fault recovery strategy that is suitable for that specific type of fault. This study aims to develop a model-based fault detection and isolation method for wheel slippage and motor performance degradation that may occur in wheeled mobile robots.Design/methodology/approachIn the proposed method, wheel speeds can be estimated via the dynamic model of the mobile robot, which includes a friction model between the wheel and the ground. Four residual signals are obtained from the differences between the estimated states and the measured states of the mobile robot. Mobile robot’s faults are detected by using these signals. Also, two different residual signals are generated from the calculation of the traction forces with two different procedures. These six residual signals are then used to isolate possible wheel slippage and performance degradation in a motor.FindingsThe proposed method for diagnosing wheel slip and performance degradation in motors are tested by moving the robot in various directions. According to the data obtained from the test results, a logic table is created to isolate these two faults from each other. Thanks to the created logic table, slippage in any wheel and performance degradation in any motor can be detected and isolated.Originality/valueTwo different recovery strategies are needed to recover temporary wheel slippage and permanent motor faults. Therefore, it is important to isolate these two faults that create similar symptoms in robot’s general movement. Thanks to the method proposed in this study, it is not only possible to isolate the slipping wheel with respect to the non-slipping wheels or to isolate the faulty motor from the non-faulty ones, but also to isolate these two different fault types from each other.

A Certificate-Based Provable Data Possession Scheme in the Standard Model

Certificate-based cryptosystem can not only resolve the private key escrow problem inherent in the identity-based cryptosystem but also reduce the cost of public key certificate management in the public key infrastructure-(PKI-) based cryptosystem. Provable data possession (PDP) can ensure the integrity of users’ data stored in the cloud at a very high probability. By combining these two concepts, we propose a certificate-based PDP scheme. We prove that our scheme is secure in the standard model assuming that the Squ-CDH problem is hard. Based on the index logic table, our scheme can be extended to support dynamic operations easily. Efficiency analysis shows that our scheme has high efficiency.

All optical XOR logic gate formed by unsupervised optical neuron networks

We propose a design for an all-optical logic exclusive-OR (XOR) gate in terms of intensity-modulation or phase-modulation approaches. In this study, the unsupervised optical neuron networks (ONNs) are based on reservoir computing (RC) and the echo state networks (ESNs). Thanks to the optical interfering effect in the directional coupler, it provides a nonlinear function for the reservoir computing. By scanning the phase through the phase shifter in our optical neuron networks, we find the optimized results and demonstrate the relationship between the input and output signals. The simulated results match the truth logic table in XOR gate. We also demonstrate the bit error ratio (BER) of the all-optical logic XOR gate. The BER for intensity-modulation approach is 1.55% at 90 degree, and the phase-modulation approach is 1.78% at 91 degree. Thus, the simulated results also indicate that the optical neuron network has potential to achieve an optical integrated circuit. If this idea could be fabricated as an optical logic device, the processing rate in the ONN is in light frequency. It will help us to process the binary data sequence more efficiently.

Design and Realization of the Intelligent Design System for Tunnel Blasting in Mine Based on Database

With the improvement of informatization and standardization of mine development, it is an inevitable trend to apply computer technology to the intelligent design of tunnel blasting excavation. Seeking to the problems existing in the intelligent design system of blasting excavation, a new intelligent design system of blasting excavation is constructed from the perspective of database technology. The new intelligent design system adopts the design of central database system and subuser rights to meet the data synchronization and sharing among different users. At the same time, the new system also extracts blasting design parameters and actual engineering data and designs a more reasonable and comprehensive database structure, database logic, and data word table. Based on the T-S fuzzy neural network model, the intelligent search rules of excavation blasting data are also constructed in the new system. Finally, based on Oracle and VB.NET as the new system development platform, MFC, and ADO as the new system development technology, the new intelligent design system for tunnel blasting and excavation was completed. The implementation of the new system addresses the needs of blasting data information storage and search and lays a foundation for the informatization and standardization of tunnel excavation blasting.

Power quality control through automated demand side management in microgrid equipped with battery energy storage for protection

Apparently, battery energy storage (BES), intelligent protection and power quality are considered as independent issues. These three factors can be interlinked effectively for control of microgrid through automated demand side management (ADSM). In this context, the proposed approach may change the conventional way for microgrid operation and control giving priority to the power quality issues considering protection and BES systems. The control algorithm is implemented through fuzzy inference system based power quality monitoring index and ADSM. As a part of intelligent protection, logic table for circuit breaker (CB) coordination has been developed without/with backup for relay devices to provide ADSM. The model has been simulated using Matlab-software and validated experimentally using OPAL-RT OP4510 real-time simulator through the assessment of power quality-related parameters such as voltage, frequency, total harmonic distortion and power factor. The results are found satisfactory showing the feasibility of the proposed microgrid model.

Failure assessment logic model (FALM): A new approach for reliability analysis of satellite attitude control subsystem

In this study, the reliability of the attitude control subsystem (ACS) of a flexible spacecraft in low earth orbit (LEO) is analyzed. Reaction wheels are considered actuators in tetrahedron configuration, whereas thrusters are adjusted as the redundant actuators to improve the reliability, as well as to de-saturate the reaction wheels. Based on the designed structure for ACS actuators, reliability block diagram (RBD) is proposed. A novel concept, Failure Assessment Logic Model (FALM), is proposed based on simulation methods. FALM can be employed to extract Failure Assessment Logic Table (FALT). FALT describes the relations between failure of components and the whole system failure. FALT enables the identification of critical components of the ACS for designers. By detecting these critical components and the system sensitivity to specific actuator failure, it is possible to optimize or find strategies to have a more robust design.

Capacitor Voltage Balancing and Stabilization for 4-Level Hybrid-Clamped Converter Using Selected Switching States

Without active control, the voltage fluctuations of the dc-link and flying capacitors in a 4-level hybrid-clamped converter (4L-HCC) become excessively large in low-frequency operation. This paper studies the switching state redundancy inherent in a 4L-HCC and proposes a new capacitor voltage balancing and stabilizing method to minimize the dc-link and flying capacitor voltage fluctuations. A straightforward algorithm is developed based on a logic table to select the suitable switching states. Verified by simulation and experimental testing results, the new method and algorithm virtually eliminate all the big voltage fluctuations of capacitors at low and zero frequencies, greatly enhancing the robustness and reliability of a 4L-HCC. The capacitor size can be reduced by more than 80% compared with the conventional method.

Fuzzy Identity-Based Dynamic Auditing of Big Data on Cloud Storage

To ensure the reliability and integrity of data in the cloud storage server, some scholars provided various data integrity auditing schemes. However, the most existing data integrity auditing schemes only support the static data and may be unsuitable for the dynamic operations of data. To overcome this difficulty, we propose a fuzzy identity-based dynamic auditing of big data, which combines the structure of the Merkle hash tree (MHT) with the Index logic table (ILT). Our scheme not only performs the dynamic operations of data block in the ILT, namely modification, insertion and deletion, but also efficiently executes dynamic operations of the ILT on the structure of the MHT. We also elaborate the security, characteristics and performance analysis of the proposed scheme separately. The analysis results show that the proposed scheme costs less time than the structure of the original MHT to generate the root node hash value during the metadata generation phase and update the root node hash value during the dynamic operations. Furthermore, when users store the new ILT in local storage, they require lower communication cost to update root node hash value than users without storing the ILT, and fewer interactions between the cloud storage server and users in the dynamic operations process.

Identity-based non-repudiable dynamic provable data possession in cloud storage

In cloud-assisted wearable devices, how to protect the integrity of data stored in the cloud is a hot issue. For the scenes where clients are dishonest, we study the non-repudiable dynamic provable data possession schemes, and find that existing dynamic structures are not suitable for non-repudiable dynamic provable data possession schemes. The Merkle hash tree must be combined with timestamps to construct non-repudiable dynamic provable data possession schemes. This will cause the synchronization problem, and map-version tables cannot resist delete-insert attacks. Therefore, we propose a monotonic dynamic structure, i.e., index logic table. Then, we construct an identity based non-repudiable dynamic provable data possession scheme for cloud storage by using index logic tables. The proposed scheme not only resists the hash value stored attack, the delete-insert attack, and the tampering cloud returned value attack, but also avoids the synchronization problem. Furthermore, the proposed scheme has lower computation cost and storage cost in the dynamic operation process.

Framework to operate multiple ship defense missiles under uncertain evasive maneuvers of target

This paper proposes a two-phase framework to operate multiple ship defense missiles against the threat of an anti-ship missile. During the preparation phase, single-shot kill probability models associated with various evasive maneuvers of the anti-ship missile are developed and used to assess the overall kill probability obtained by combined operation of multiple defense missiles. An optimization problem to maximize the total kill probability of an engagement by determining the firing times of defense missiles is mathematically formulated and solved for various target maneuvers and operational conditions, whose results are stored to generate a firing logic table. During the actual battle (engagement phase), the firing logic table is used to operate multiple defense missiles against the threat with maximum probability of interception. A ship defense case study considering important target maneuvers was conducted to demonstrate the effectiveness of the proposed operational framework.

Automated closed-loop resuscitation of multiple hemorrhages: a comparison between fuzzy logic and decision table controllers in a sheep model

Background Hemorrhagic shock is the leading cause of trauma-related death in the military setting. Definitive surgical treatment of a combat casualty can be delayed and life-saving fluid resuscitation might be necessary in the field. Therefore, improved resuscitation strategies are critically needed for prolonged field and en route care. We developed an automated closed-loop control system capable of titrating fluid infusion to a target endpoint. We used the system to compare the performance of a decision table algorithm (DT) and a fuzzy logic controller (FL) to rescue and maintain the mean arterial pressure (MAP) at a target level during hemorrhages. Fuzzy logic empowered the control algorithm to emulate human expertise. We hypothesized that the FL controller would be more effective and more efficient than the DT algorithm by responding in a more rigid, structured way.MethodsTen conscious sheep were submitted to a hemorrhagic protocol of 25 ml/kg over three separate bleeds. Automated resuscitation with lactated Ringer’s was initiated 30 min after the first hemorrhage started. The endpoint target was MAP. Group differences were assessed by two-tailed t test and alpha of 0.05.ResultsBoth groups maintained MAP at similar levels throughout the study. However, the DT group required significantly more fluid than the FL group, 1745 ± 552 ml (42 ± 11 ml/kg) versus 978 ± 397 ml (26 ± 11 ml/kg), respectively (p = 0.03).ConclusionThe FL controller was more efficient than the DT algorithm and may provide a means to reduce fluid loading. Effectiveness was not different between the two strategies. Automated closed-loop resuscitation can restore and maintain blood pressure in a multi-hemorrhage model of shock.

A Simplified Approach: Teaching PERT with Ease and without Drawing Networks

Program Evaluation and Review Technique (PERT) has been widely used in all industries and taught in Project Management courses for more than 50 years. Hall, N.G. (2015, p. 945) points out: “The practice of Project Management has expanded exponentially in the last 15 years,” but this rapid development has not been matched “by a corresponding increase either in research activities, or in the training of academic researchers in project management. The mismatch is creating significant opportunities for academic research management…” This paper provides two tips for teaching PERT for the Project Management or Operations-Management courses: 1) the proposed simplified formulas which can be used in classrooms effectively since they do not require division or truncation when calculating the expected duration and variance. The formulas not only simplifies the calculations, but also generates more accurate results (demonstrated through simulations) than the traditional approach of using truncated estimations; and 2) An approach to finding critical and non-critical activities without drawing a network chart so that a relatively large project can be efficiently demonstrated in a classroom setting. The paper demonstrates that by using only a table and avoiding the graphical presentation of a complicated network diagram, instructors can show relatively larger projects on blackboards and students, particularly those who prefer logic table calculations to drawing graphical networks, can better understand and master the PERT technique.

A residual based adaptive unscented Kalman filter for fault recovery in attitude determination system of microsatellites

This paper presents an adaptive unscented Kalman filter (AUKF) to recover the satellite attitude in a fault detection and diagnosis (FDD) subsystem of microsatellites. The FDD subsystem includes a filter and an estimator with residual generators, hypothesis tests for fault detections and a reference logic table for fault isolations and fault recovery. The recovery process is based on the monitoring of mean and variance values of each attitude sensor behaviors from residual vectors. In the case of normal work, the residual vectors should be in the form of Gaussian white noise with zero mean and fixed variance. When the hypothesis tests for the residual vectors detect something unusual by comparing the mean and variance values with dynamic thresholds, the AUKF with real-time updated measurement noise covariance matrix will be used to recover the sensor faults. The scheme developed in this paper resolves the problem of the heavy and complex calculations during residual generations and therefore the delay in the isolation process is reduced. The numerical simulations for TSUBAME, a demonstration microsatellite of Tokyo Institute of Technology, are conducted and analyzed to demonstrate the working of the AUKF and FDD subsystem.

Feedback strategy on real-time multiple target tracking in cognitive vision system

Under pedestrian and vehicle mixed traffic conditions, the potential accident rate is high due to a complex traffic environment. In order to solve this problem, we present a real-time cognitive vision system. In the scene-capture level, foreground objects are extracted based on the combination of spatial and temporal information. Then, a coarse-to-fine algorithm is employed in tracking. After filtering-based normal tracking, problems of the target blob missing, merging, and splitting are resolved by the adaptive tracking modification method in fine tracking. For greater robustness, the key idea of our approach is adaptively adjusting the classification sensibility of each pixel by employing tracking results as feedback cues for target detection in the next frame. On the basis of the target trajectories, behavior models are evaluated according to a decision logic table in the behavior-evaluation level. The decision logic table is set based on rules of real scenes. The resulting system interprets different kinds of traffic behavior and warns in advance. Experiments show robust and accurate results of abnormality detection and forewarning under different conditions. All the experimental results run at real-time frame rates (⩾25 fps) on standard hardware. Therefore, the system is suitable for actual Intelligent Traffic System applications.

Crossbar memory array of organic bistable rectifying diodes for nonvolatile data storage

Cross-talk in memories using resistive switches in a cross-bar geometry can be prevented by integration of a rectifying diode. We present a functional cross bar memory array using a phase separated blend of a ferroelectric and a semiconducting polymer as storage medium. Each intersection acts simultaneously as a bistable rectifying diode. A logic table of a 4-bit memory and integration into a 3×3 cross bar array are demonstrated. The most difficult state, a high resistance bit completely surrounded by low resistance bits could be unambiguously identified.

Five-Level Current-Source Inverters With Buck–Boost and Inductive-Current Balancing Capabilities

This paper presents new five-level current-source inverters (CSIs) with voltage/current buck-boost capability, unlike existing five-level CSIs where only voltage-boost operation is supported. The proposed inverters attain self-inductive-current-balancing per switching cycle at their dc front ends without having to include additional balancing hardware or complex control manipulation. The inverters can conveniently be controlled by using the well-established phase-shifted carrier modulation scheme with only two additional linear references and a mapping logic table needed. Existing modulators can therefore be conveniently retrofitted for controlling the presented inverters. By appropriately coordinating the inverter gating signals, their implementations can be realized by using the least number of components without degrading performance. These enhanced features of the inverters have already been verified in simulation and experimentally using a scaled-down laboratory platform.

Design of Multisectional Driver and Field-Oriented Modeling of the Axial-Flux Linear Brushless Motor for Railway Transportations

A multisectional power driver design for the two-phase linear brushless motor is proposed in this paper. The field-oriented modeling of the axial-flux linear brushless motor (AFLBM) is also developed by using stationary and cosecant similarity transformation and singular value decomposition. Stationary and cosecant coordinate models were derived based on the proposed approach. Decoupled relation and constant torque property were obtained from the proposed models. Switching logic table for the linear motor operation is provided to drive the AFLBM properly. The switching-mode analysis for the power driver is also analyzed in detail. In order to increase the efficiency and the effectiveness of the electric motor applications, a multisectional driver circuit, which features the power driver with the so-called N + 2 structure, is investigated and compared. Experimental results show that the proposed circuit design can achieve better performance with the higher efficiency. It is believed that the proposed driver circuit technique and system modeling can be very helpful to the control of railway transportations.

Design of an analytic-hierarchy-process-based expert system for non-traditional machining process selection

The selection of a non-traditional machining (NTM) process is often observed to be a multi-criteria decision-making problem with conflicting and diverse objectives. This paper presents a systematic methodology for selecting the best or optimal non-traditional machining process under constrained material and machining conditions. The paper also includes the design of an analytic-hierarchy-process-based expert system with a graphical user interface to ease the decision-making process. The developed expert system relies on the priority values for different criteria and sub-criteria, as related to a specific non-traditional machining process selection problem. It also depends on the logic table to discover the non-traditional machining processes that lie in the acceptability zone, and then selects the optimal process having the highest acceptability index value. The proposed expert system can automate the selection of a non-traditional machining process and provide artificial intelligence in the multi-criteria decision-making process.

Multitemporal land use and land cover classification of urbanized areas within sensitive coastal environments

In the presented methodology, multitemporal Landsat images were used to develop enhanced information about complex assemblages of vegetation and patterns of seasonal land cover variability, thereby facilitating improved land use and land cover (LULC) classification of urbanized areas among sensitive environments along the Mississippi Gulf Coast. For Landsat-5 and Landsat-7 images acquired for leaf-off and leaf-on conditions for 1991 and 2000, exploratory spectral analyses and field studies were conducted to detect and analyze patterns of spectral variability in land cover observed in the multitemporal image data. Patterns were identified of seasonal spectral data changes associated with seasonal vegetation changes for known land cover and land use types, thus characterizing patterns of seasonal LULC thematic change for the area. Detected seasonal variability for known land use and land cover types were used to develop formal classification rules based upon a thematic-change logic table. An image subset area based on United States Geological Survey (USGS) 1:24000 quadrangles was used to develop a class-learning area within which unsupervised classification results were grouped into thematic classes. Signature files from the unsupervised classification results were applied to classify the balance of the study area. Individual images were classified for leaf-off and leaf-on conditions and thematic-change analyses were conducted. The formal class rules based on thematic-change logic were applied resulting in a classification that provided a level one accuracy exceeding 90% and a level two accuracy exceeding 85%.