Implementation Errors Research Articles

Assessing students’ errors in mathematical translation: From symbolic to verbal and graphic representations

Translation skills are very important possessed by students, but currently, there are still many students who have difficulty in translating between representations. The purpose of this study is to analyze students' errors in translating from symbolic representations to verbal and graphic representations. This research was descriptive study with qualitative approach. Tests are given to junior high school students. From the results of data analysis, it is obtained that in translating from symbolic to verbal forms (problems in daily life) that are following the given system of equations, students are still unable to make representations correctly. When students are asked to translate into graphical form, students are still unable to draw complete graphs and errors made by students are misinterpretation and implementation errors, so they cannot maintain the semantic congruence between source representation and target representation. Based on this, it is necessary to make a learning plan that can improve students’ ability to translate between representations.

Property-based Sensitivity Analysis: An approach to identify model implementation and integration errors

Diagnostic testing is an oft-recommended use of sensitivity analysis to assess correctness or plausibility of model behavior. In this paper we demonstrate the use of sensitivity analysis as a complementary first-pass software test for the validation of model behavior. Typical testing processes rely on comparing model outputs to results known to be correct. Such approaches are limited to specific model configurations and require that correct results be known in advance. Property-based Sensitivity Analysis (PbSA) examines model properties in terms of the behavior of parameter sensitivities to provide a line of evidence that the expected conceptual relationships between model factors and their effects are present. Unanticipated results can indicate issues to be corrected. The PbSA approach is also scalable as it can complement existing testing practices and be applied in conjunction with global sensitivity methods that can reuse existing model evaluations or are otherwise independent of the sampling scheme.

SBBS: A Secure Blockchain-Based Scheme for IoT Data Credibility in Fog Environment

Data credibility plays a key role in facilitating evidence-based decision making in organizations and governments (e.g., policy making). One of the key data sources is the Internet of Things (IoT) devices and systems, say within a fog environment. However, the increasing complexity and interconnectivity of such IoT and fog environments can result in security vulnerabilities (e.g., due to implementation errors or flaws in the underpinning devices or systems), which can be exploited to compromise the credibility of the data. Therefore, in this article, we propose a secure Blockchain-based scheme to guarantee the credibility of nodes and data and ensure data transmission security in the fog environment. We then demonstrate the feasibility of the proposed scheme using experiments.

Land Measurement Bias: Comparisons from Global Positioning System, Self-Reports, and Remote Sensing Data

We investigate the reliability of land measurement modes on non-classical measurement error and empirical relationships. In our multi-country survey experiment, we find significant differences between GPS and remotely sensed data only in Viet Nam, where plot sizes are small relative to the other countries. The magnitude of farmers’ self-reporting bias relative to GPS measures is nonlinear, with the largest magnitude of self-reporting bias of 130% of a standard deviation (2.2-hectare bias) in the Lao People’s Democratic Republic relative to Viet Nam, which has 13.3% of a standard deviation (.008-hectare bias). In all countries except Viet Nam, the inverse land size–productivity relationship is upwardly biased for lower land area self-reported measures relative to GPS measures. In Viet Nam, the intensive margin of organic fertilizer use is negatively biased (30.4 percentage points) by self-reported measurement error. We conclude by considering sources of measurement error in implementation and costs.

Comprehensive study on complex-valued ZNN models activated by novel nonlinear functions for dynamic complex linear equations

This paper proposes two complex-valued zeroing neural network (Cv-ZNN) models for solving dynamic complex time-variant linear equations. The models involve two complex-valued nonlinear processing methods and adapt two real-valued activation functions. The convergence and robustness of the two Cv-ZNN models are analyzed comprehensively. Firstly, the convergence discussion shows that the corresponding stable error can rapidly converge to zero in finite time, with the upper limit of constriction time calculated. The upper limit of stable error is successfully obtained when the model implementation error is injected into the Cv-ZNN models, which displays their superior robustness. Besides, the results of numerical simulations reveal that the Cv-ZNN models effectively address the time-variant linear system of equations over complex field, even in noisy environments. The simulation results also demonstrate that two novel nonlinear activation functions perform much better than the Linear, Power, Bipolar Sigmoid Power-Sigmoid and Sign-bi-power activation functions.

Broad-band spectroscopy of a vanadyl porphyrin: a model electronuclear spin qudit.

We explore how to encode more than a qubit in vanadyl porphyrin molecules hosting a S = 1/2 electronic spin coupled to a I = 7/2 nuclear spin. The spin Hamiltonian and its parameters, as well as the spin dynamics, have been determined via a combination of electron paramagnetic resonance, heat capacity, magnetization and on-chip magnetic spectroscopy experiments performed on single crystals. We find low temperature spin coherence times of micro-seconds and spin relaxation times longer than a second. For sufficiently strong magnetic fields (B > 0.1 T, corresponding to resonance frequencies of 9–10 GHz) these properties make vanadyl porphyrin molecules suitable qubit realizations. The presence of multiple equispaced nuclear spin levels then merely provides 8 alternatives to define the ‘1’ and ‘0’ basis states. For lower magnetic fields (B < 0.1 T), and lower frequencies (<2 GHz), we find spectroscopic signatures of a sizeable electronuclear entanglement. This effect generates a larger set of allowed transitions between different electronuclear spin states and removes their degeneracies. Under these conditions, we show that each molecule fulfills the conditions to act as a universal 4-qubit processor or, equivalently, as a d = 16 qudit. These findings widen the catalogue of chemically designed systems able to implement non-trivial quantum functionalities, such as quantum simulations and, especially, quantum error correction at the molecular level.

A Resilient Approach to Recursive Distributed Filtering for Multirate Systems Over Sensor Networks With Time-Correlated Fading Channels

This paper addresses the resilient distributed filtering problem for a class of time-varying multirate systems over sensor networks subject to time-correlated fading channels. The time-correlated fading channel, whose fading coefficient is described by a dynamical process, is introduced to better capture the time-correlation property of the wireless channels. Moreover, the phenomenon of stochastic gain fluctuations is taken into account to accommodate the potential implementation errors, thereby achieving resilient filtering performance. The lifting technique is employed to cast the underlying multirate system into a general signal-rate one, and then an augmented system is formulated to account for the dynamics from both the plant and the fading coefficients. Our aim is to design a distributed filter such that certain upper bound is first guaranteed on the filtering error covariance and then minimized at each sampling instant.With the help of trace operations, the gain parameters of the desired distributed filter are obtained in terms of the solutions to two sets of recursive equations. Finally, the effectiveness of the developed filtering algorithm is verified via an illustrative example.

Coherence cost for violating conservation laws

Nature imposes many restrictions on the operations that we perform. Many of these restrictions can be interpreted in terms of {\it resource} required to realize the operations. Classifying required resource for different types of operations and determining the amount of resource are the crucial subjects in physics. Among many types of operations, a unitary operation is one of the most fundamental operation that has been studied for long time in terms of the resource implicitly and explicitly. Yet, it is a long standing open problem to identify the resource and to clarify the necessary and sufficient amount of resource for implementing a general unitary operation under conservation laws. In this paper, we provide a solution to this open problem. We derive an asymptotically exact equality that clarifies the necessary and sufficient amount of quantum coherence as a resource to implement arbitrary unitary operation within a desired error. In this equality, the required coherence cost is asymptotically expressed with the implementation error and the degree of violation of conservation law in the desired unitary operation. We also discuss the underlying physics in several physical situations from the viewpoint of coherence cost based on the equality. This work does not only provide a solution to a long-standing problem on the unitary control, but also clarifies the key question of the resource theory of the quantum channels in the region of resource theory of asymmetry, for the case of unitary channels.

A 77.1-dB-SNDR 6.25-MHz-BW Pipeline SAR ADC With Enhanced Interstage Gain Error Shaping and Quantization Noise Shaping

This article presents an enhanced interstage gain error shaping (GES) technique that adopts a digital error feedback (DEF) method to address the truncation error in the prior implementation, which can extend the interstage gain error tolerance by five times. The proposed DEF technique does not introduce additional errors as it operates purely in the digital domain. This article also proposes a first-order passive quantization noise shaping (NS) technique that reduces the input-pair ratio of the two-input-pair comparator by 2.7 times, thus alleviating the noise penalty caused by using a multiple-input-pair comparator. A prototype analog-to-digital converter (ADC) equipped with the proposed techniques in a 40-nm CMOS technology achieves a 77.1-dB signal-to-noise-and-distortion ratio (SNDR) over 6.25-MHz bandwidth while operating at 100 MS/s and consuming 1.38 mW. It achieves a 173.7-dB Schreier figure of merit (FoM).

Optimal design of robust resilient automatic voltage regulators

Uncertainties in the plant model parameters and perturbations in the controller gains imposed by implementation errors represent a challenge to ensure robust stability and controller non-fragility simultaneously. Optimal design of robust non-fragile proportional–integral–derivative (PID) controller is presented for an automatic voltage regulator (AVR). The PID design relies basically on Kharitonov theorem and optimization by future search algorithm (FSA). The proposed algorithm has low computational complexity and fast convergence rate because it utilizes both local and global search methods. Further, FSA can improve the exploration characteristic and prevent trapping in local optima by updating its random initial. The PID controller is optimized by FSA to cope with expected parametric uncertainties of the plant model and tolerate its gain perturbations such that robust stability and controller non-fragility are simultaneously met. An interval plant model is suggested to account for model uncertainties where only eight extreme plants derived by Kharitonov theorem are considered in design. FSA-based PID optimization is constrained by the stability conditions of Kharitonov’s plants derived using Routh–Hurwitz. A new figure-of-demerit (FoD) based performance index is suggested to enforce simultaneous minimization of the time domain specifications. The suggested objective function is represented by a weighted sum of FoD of nominal response and the sum of reciprocals of the perturbation radii of PID gains. The output results of the recommended design are compared to that of artificial bee colony (ABC) algorithm and teaching–learning based optimization (TLBO) algorithm, multi-objective extremal optimization (MOEO), and non-dominated sorting genetic algorithm II (NSGA II). The results can confirm better response of the suggested technique measured up to other techniques where robustness and non-fragility are simultaneously ensured.

Numerical methods for accurate computation of the eigenvalues of Hermitian matrices and the singular values of general matrices

This paper offers a review of numerical methods for computation of the eigenvalues of Hermitian matrices and the singular values of general and some classes of structured matrices. The focus is on the main principles behind the methods that guarantee high accuracy even in the cases that are ill-conditioned for the conventional methods. First, it is shown that a particular structure of the errors in a finite precision implementation of an algorithm allows for a much better measure of sensitivity and that computation with high accuracy is possible despite a large classical condition number. Such structured errors incurred by finite precision computation are in some algorithms e.g. entry-wise or column-wise small, which is much better than the usually considered errors that are in general small only when measured in the Frobenius matrix norm. Specially tailored perturbation theory for such structured perturbations of Hermitian matrices guarantees much better bounds for the relative errors in the computed eigenvalues. Secondly, we review an unconventional approach to accurate computation of the singular values and eigenvalues of some notoriously ill-conditioned structured matrices, such as e.g. Cauchy, Vandermonde and Hankel matrices. The distinctive feature of accurate algorithms is using the intrinsic parameters that define such matrices to obtain a non-orthogonal factorization, such as the LDU factorization, and then computing the singular values of the product of thus computed factors. The state of the art software is discussed as well.

Isogeometric structural shape optimization using automatic sensitivity analysis

A method for isogeometric structural shape optimization using a multilevel approach and automated sensitivity analysis is presented in this work. The analysis mesh is obtained after carrying out successive refinements using the knot insertion and/or degree elevation algorithms, while retaining the coarse geometry for the domain design. Even though analytical sensitivities can be derived and implemented, they are prone to implementation errors and time consuming to derive. To circumvent the complication, we propose to use an automatic differentiation toolbox to perform the sensitivity analysis. This facilitates the computation of the gradients of the objective function with respect to the design variables defined over the coarse design domain with accuracy up to machine precision. Both forward and reverse modes of automatic differentiation are implemented. The accuracy, numerical efficiency and memory requirements are studied for analytical, numerical and automatic sensitivities in order to show the benefits and limitations of using automated gradients. Finally, numerical examples for two-dimensional and solid-shell shape optimization problems are presented to show the efficiency of the automatic sensitivities.

Formal Verification of Heuristic Autonomous Intersection Management Using Statistical Model Checking

Autonomous vehicles are gaining popularity throughout the world among researchers and consumers. However, their popularity has not yet reached the level where it is widely accepted as a fully developed technology as a large portion of the consumer base feels skeptical about it. Proving the correctness of this technology will help in establishing faith in it. That is easier said than done because of the fact that the formal verification techniques has not attained the level of development and application that it is ought to. In this work, we present Statistical Model Checking (SMC) as a possible solution for verifying the safety of autonomous systems and algorithms. We apply it on Heuristic Autonomous Intersection Management (HAIM) algorithm. The presented verification routine can be adopted for other conflict point based autonomous intersection management algorithms as well. Along with verifying the HAIM, we also demonstrate the modeling and verification applied at each stage of development to verify the inherent behavior of the algorithm. The HAIM scheme is formally modeled using a variant of the language of Timed Automata. The model consists of automata that encode the behavior of vehicles, intersection manager (IM) and collision checkers. To verify the complete nature of the heuristic and ensure correct modeling of the system, we model it in layers and verify each layer separately for their expected behavior. Along with that, we perform implementation verification and error injection testing to ensure faithful modeling of the system. Results show with high confidence the freedom from collisions of the intersection controlled by the HAIM algorithm.

Automata representation of successful strategies for social dilemmas

In a social dilemma, cooperation is collectively optimal, yet individually each group member prefers to defect. A class of successful strategies of direct reciprocity were recently found for the iterated prisoner’s dilemma and for the iterated three-person public-goods game: By a successful strategy, we mean that it constitutes a cooperative Nash equilibrium under implementation error, with assuring that the long-term payoff never becomes less than the co-players’ regardless of their strategies, when the error rate is small. Although we have a list of actions prescribed by each successful strategy, the rationale behind them has not been fully understood for the iterated public-goods game because the list has hundreds of entries to deal with every relevant history of previous interactions. In this paper, we propose a method to convert such history-based representation into an automaton with a minimal number of states. Our main finding is that a successful strategy for the iterated three-person public-goods game can be represented as a 10-state automaton by this method. In this automaton, each state can be interpreted as the player’s internal judgement of the situation, such as trustworthiness of the co-players and the need to redeem oneself after defection. This result thus suggests a comprehensible way to choose an appropriate action at each step towards cooperation based on a situational judgement, which is mapped from the history of interactions.

Erasable Bit Commitment From Temporary Quantum Trust

We introduce a new setting for two-party cryptography with temporarily trusted third parties. In addition to Alice and Bob in this setting, there are additional third parties, which Alice and Bob both trust to be honest during the protocol. However, once the protocol concludes, there is no guarantee over the behaviour of these third parties. It is possible that they collaborate and act adversarially. Our goal is to use these third parties to facilitate protocols which are impossible in two-party cryptography. We implement a variant of bit commitment in this setting, which we call erasable bit commitment. In this primitive, Alice has the choice of either opening or erasing her commitment after the commit phase. The ability to ask for an erasure allows Alice to ask the trusted parties to erase her commitment in case the trust period is about to expire. This erasure prevents a future coalition of the third parties and Bob from extracting any information about the commitment. However, this ability also makes erasable bit commitment weaker than the standard version of bit commitment. In addition to satisfying the security requirements of bit commitment, our protocol also does not reveal any information about the commitment to the third parties. Lastly, our protocol for this primitive requires a constant number of trusted third parties and can tolerate a small number of corrupt trusted parties as well as implementation errors.

Speed of Navigation vis-a-vis Quality of Innovation as Sources of Progression towards Steady State Equilibrium: Insights and Inferences

This study formally and theoretically juxtaposes `speed of navigation' of the general equilibrium growth path (equivalently, a `low-high' innovation system), and `quality of innovations' (equivalently, a `top-down' innovation system) as alternate strategies for minimization of the time it takes for a country to arrive at its general equilibrium steady state growth phase. Formal theoretical predictions show that, whereas the speed of navigation strategy has feasibility of outperforming the quality of innovations strategy, superior performance at minimization of time to steady state is feasible only in presence of either of errors of implementation of the top-down innovation system, or incapacity of an economy at generation of high quality innovations. In absence of stated two factors, the quality of innovations strategy outperforms the speed of navigation strategy for minimization of the time it takes for a country to arrive at its general equilibrium steady state growth phase. Empirical findings provide corroboration for study findings, provide evidence that whereas the speed of navigation strategy generates a linear approach, the quality of innovations strategy generates a weakly convex approach to the general equilibrium steady state growth phase. Quality of elementary education is `poster boy' for the quality of innovations strategy. Simultaneously, size of stock markets and fixed capital formation are poster boys for the `speed of navigation' strategy.

Drift-Free Inertial Sensor-Based Joint Kinematics for Long-Term Arbitrary Movements

The ability to capture joint kinematics in outside-laboratory environments is clinically relevant. In order to estimate kinematics, inertial measurement units can be attached to body segments and their absolute orientations can be estimated. However, the heading part of such orientation estimates is known to drift over time, resulting in drifting joint kinematics. This study proposes a novel joint kinematic estimation method that tightly incorporates the connection between adjacent segments within a sensor fusion algorithm, to obtain drift-free joint kinematics. Drift in the joint kinematics is eliminated solely by utilizing common information in the accelerometer and gyroscope measurements of sensors placed on connecting segments. Both an optimization-based smoothing and a filtering approach were implemented. Validity was assessed on a robotic manipulator under varying measurement durations and movement excitations. Standard deviations of the estimated relative sensor orientations were below 0.89° in an optimization-based smoothing implementation for all robot trials. The filtering implementation yielded similar results after convergence. The method is proven to be applicable in biomechanics, with a prolonged gait trial of 7 minutes on 11 healthy subjects. Three-dimensional knee joint angles were estimated, with mean RMS errors of 2.14°, 1.85°, 3.66° in an optimization-based smoothing implementation and mean RMS errors of 3.08°, 2.42°, 4.47° in a filtering implementation, with respect to a golden standard optical motion capture reference system.

Rebuilding depleted fisheries towards BMSY under uncertainty: harvest control rules outperform combined management measures

AbstractRebuilding depleted fisheries towards sustainable levels, such as BMSY, is challenging under uncertainty. Although a substantial amount of research has highlighted the importance of accounting for uncertainty in fisheries management, tactical measures remain to be identified. We consider two approaches to achieve this goal: (i) the naive maximum sustainable yield (MSY) approach, combining management measures based on effort control, catch quotas, and spatial–temporal closures, and (ii) the harvest control rules (HCRs) approach, developing HCRs based on short-term or long-term targets. A suite of strategies is developed accordingly and tested with management strategy evaluation for their performance under four sources of uncertainty that may negatively impact management effects, including reduced recruitment strength, increased natural mortality, inadequate implementation error, and varying levels of temporal effort aggregation. Combining management measures using the naive MSY approach is found to perform poorly in tackling uncertainty. Complex HCRs that account for both short-term and long-term BMSY targets can mitigate the adverse effects of uncertainty. The rebuilding target can be only achieved by compromising yield, especially when uncertainties with natural mortality and recruitment are present. Strategies based on catch quotas are prone to all sources of uncertainty, indicating latent risks in many current management practices.

Concrete Structure Condition Rating in Buildings with Non-Destructive Testing

Concrete damage on building is translated as a condition change from concrete quality. The damage that is referred to can be in the form of physical change or concrete quality downgrade on a building. This change can be caused by several reasons, such as implementation error, building overload, building function change, inadequate building maintenance, natural condition, and natural disaster. Concrete damage condition on buildings can be identified by performing a condition rating assessment. Condition rating assessment Is determined based on non-destructive examination. Assessment analysis results show the concrete structure condition and the action that must be done.

A software implemented comprehensive soft error detection method for embedded systems

This paper presents a comprehensive software-based technique that is capable of detecting soft errors in embedded systems. Soft errors can be categorized into Control Flow Errors (CFEs) and data errors. The CFEs change the flow of the program erroneously and data errors also change the results. In this paper, a new comprehensive method is presented to detect both (based on combination of authors’ previous works). In order to evaluate the proposed method, a new factor is defined that considers three main parameters simultaneously; namely fault coverage, memory overhead, and performance overhead. Since these parameters are very important in safety critical applications, they should be improved concurrently. The experimental results on SPEC2000 benchmarks show that the Evaluation Factor of the proposed method is 50% better than the Relationship Signatures for Control Flow Checking with Data Validation (RSCFCDV) methods, which are suggested in the literature.