Forward Backward Research Articles

Forward–Backward Smoothers With Finite Impulse Response Structure

State estimation is an important component for advance control and fault detection. This paper addresses the problem of smoother design for state estimation based on a finite number of measurements collected in a finite estimation horizon. Three different finite impulse response (FIR) smoothing algorithms are proposed using the maximum likelihood FIR estimation, which is robust against uncertain noise statistics and model parameters, and also independent of the initial states of each finite horizon. Moreover, we provide equivalent but iterative Kalman-like structures of these algorithms for practical implementation. The applications of the proposed smoothing algorithms to an object tracking and image processing examples are demonstrated, and it shows that they have better robustness against model uncertainties than traditional smoothing approaches.

Epidemic Analysis of Wireless Rechargeable Sensor Networks Based on an Attack-Defense Game Model.

Energy constraint hinders the popularization and development of wireless sensor networks (WSNs). As an emerging technology equipped with rechargeable batteries, wireless rechargeable sensor networks (WRSNs) are being widely accepted and recognized. In this paper, we research the security issues in WRSNs which need to be addressed urgently. After considering the charging process, the activating anti-malware program process, and the launching malicious attack process in the modeling, the susceptible–infected–anti-malware–low-energy–susceptible (SIALS) model is proposed. Through the method of epidemic dynamics, this paper analyzes the local and global stabilities of the SIALS model. Besides, this paper introduces a five-tuple attack–defense game model to further study the dynamic relationship between malware and WRSNs. By introducing a cost function and constructing a Hamiltonian function, the optimal strategies for malware and WRSNs are obtained based on the Pontryagin Maximum Principle. Furthermore, the simulation results show the validation of the proposed theories and reveal the influence of parameters on the infection. In detail, the Forward–Backward Sweep method is applied to solve the issues of convergence of co-state variables at terminal moment.

Kinematic synthesis method and eccentricity effects of a Stephenson mechanism

Abstract. When implementing the technological process on crank presses, it is necessary to provide a predetermined working cycle of the slider motion: fast lifting, dwell, and slow lowering. The cycle cannot be realized without controlling the motor. In addition, using controllable motors increases the manufacturing cost. Due to the geometric and kinematic capabilities of the mechanism, changing the kinematics of the working link is the best choice. Thanks to the use of the Stephenson II mechanism, the slider skew is eliminated due to the parallel connecting rods and the increased area of slider contact. This study presents a numerical method for kinematic synthesis of the Stephenson mechanism that has kinematic advantages. The method is based on mean square deviation which is the minimizing of an objective function. Thanks to the proposed synthesis method, approximate dwell movement can be performed when the slider is on the bottom dead center. In this study, values of the crank length and parallel connecting rods' lengths, angular coordinates of the crank and connecting rods, and the eccentricity of the guide slider relative to the crank rotation axis were obtained. It is observed that eccentricity affects the lower forward and higher backward speed of the slider. The kinematic results of the slider movement are comparatively presented in this article.

Two-stage human verification using HandCAPTCHA and anti-spoofed finger biometrics with feature selection

This paper presents a human verification scheme in two independent stages to overcome the vulnerabilities of attacks and to enhance security. At the first stage, a hand image-based CAPTCHA (HandCAPTCHA) is tested to avert automated bot-attacks on the subsequent biometric stage. In the next stage, finger biometric verification of a legitimate user is performed with presentation attack detection (PAD) using the real hand images of the person who has passed a random HandCAPTCHA challenge. The electronic screen-based PAD is tested using image quality metrics. After this spoofing detection, geometric features are extracted from the four fingers (excluding the thumb) of real users. A modified forward–backward (M-FoBa) algorithm is devised to select relevant features for biometric authentication. The experiments are performed on the Boğaziçi University (BU) and the IIT-Delhi (IITD) hand databases using the k-nearest neighbor and random forest classifiers. The average accuracy of the correct HandCAPTCHA solution is 98.5%, and the false accept rate of a bot is 1.23%. The PAD is tested on 255 subjects of BU, and the best average error is 0%. The finger biometric identification accuracy of 98% and an equal error rate (EER) of 6.5% have been achieved for 500 subjects of the BU. For 200 subjects of the IITD, 99.5% identification accuracy, and 5.18% EER are obtained.

Enhanced TLD-based video object-tracking implementation tested on embedded platforms

Object-tracking algorithms on embedded platforms are very important in many civilian and military applications. The Tracking–Learning–Detection (TLD) algorithm is considered one of the state-of-the-art online long-term object-tracking algorithms. The performance of running such computationally intensive algorithms on embedded platforms with limited computing resources is a challenge. This work proposes an enhanced TLD implementation, specifically designed for, and tested on, embedded platforms. In this new implementation, an extra-stage has been added to the TLD detector cascade, called a Region filter. This filter dynamically identifies the candidate region for the tracked object. Further, the two independent tracker and detector TLD components, and the two independent Forward–Backward (FB) and Normalized Cross Correlation (NCC) error measures in the tracker have been parallelized. Still further, the computations of Image Integral in the detector and the NCC in both the tracker and the detector have been optimized using a single instruction multiple data (SIMD) architecture. We evaluate our proposed implementation on the Apalis T30 embedded platform, using the same video sequences that the original TLD is evaluated on. Our results show that our enhanced implementation outperforms the baseline with an average speedup of 3.7 × in the total number of frames per second (fps), while achieving an average 91% of the Precision and 86.6% of the Recall metrics, across all sequences. Further, our enhanced implementation achieves an average speedup of 4.52 × and 1.86 × in the detector and tracker execution times, respectively. Moreover, it results in an average 66.3% energy saving, as compared to the original implementation.

Sustainable Development Strategy of Pine Resin in Bone Regency, South Sulawesi, Indonesia

Production of pine sap international level in Indonesia every period of five years has decreased significantly, it is a reference to pine sap market attention on a smaller scope that district to village level-based potential. This study aims to formulate a marketing strategy to develop the market of pine resin in Bone regency. This study was conducted in Bone regency, South Sulawesi, Indonesia and held for 5 months. The analytical method used to formulate marketing strategy in this study was a semi structured interview, to analyze the data using analysis IE (internalexternal) matrix. The results of matrix calculations IFAS (internal factor analysis summary) obtained a total score of 2.85 and a matrix internal EFAS (External factors analysis summary) with a score of 3.2. The results after analyzed with IE matrix put pine resin market position of Bone Regency in the cell II, that grow and build. Recommendation development strategy of pine rosin market namely market penetration, market development, product development, integrase forward and integrase backward..

Hardware-Based Spiking Neural Network Using a TFT-Type AND Flash Memory Array Architecture Based on Direct Feedback Alignment

A hardware-based neural network that enables on-chip training using a thin-film transistor-type AND flash memory array architecture is designed. The synaptic device constituting the array is characterized by a doped p-type body, a gate insulator stack composed of SiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> /Si <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> /Al <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> O <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> , and a partially curved poly-Si channel. The body reduces the circuit burden on the high voltage driver required for both the source and drain lines when changing the synaptic weights. The high- κ material included in the gate insulator stack helps to lower the operating voltage of the device. As the device scales down, the structural characteristics of the device have the potential to increase the efficiency of the memory operation and the immunity to the voltage drop effect that occurs in the bit-lines of the array. In an AND array architecture using fabricated synaptic devices, a pulse scheme for selective memory operation is proposed and verified experimentally. Due to the direct feedback alignment (DFA) algorithm, which does not need to have the same synaptic weight in the forward path and backward path, the AND array architecture can be utilized in designing an efficient on-chip training neural network. Pulse schemes suitable for the proposed AND array architecture are also devised to implement the DFA algorithm in neural networks. In a system-level simulation, a recognition accuracy of up to 97.01% is obtained in the MNIST pattern learning task based on the proposed pulse scheme and computing architecture.

Strong Convergence to the Mean-Field Limit of A Finite Agent Equilibrium

We study an equilibrium-based continuous asset pricing problem for the securities market. In the previous work [16], we have shown that a certain price process, which is given by the solution to a forward backward stochastic differential equation of conditional McKean-Vlasov type, asymptotically clears the market in the large population limit. In the current work, under suitable conditions, we show the existence of a finite agent equilibrium and its strong convergence to the corresponding mean-field limit given in [16]. As an important byproduct, we get the direct estimate on the difference of the equilibrium price between the two markets; one consisting of heterogeneous agents of finite population size and the other of homogeneous agents of infinite population size.

Explicit High Order One-Step Methods for Decoupled Forward Backward Stochastic Differential Equations

Explicit High Order One-Step Methods for Decoupled Forward Backward Stochastic Differential Equations

A Distributed Forward–Backward Algorithm for Stochastic Generalized Nash Equilibrium Seeking

We consider the stochastic generalized Nash equilibrium problem (SGNEP) with expected-value cost functions. Inspired by Yi and Pavel (2019), we propose a distributed generalized Nash equilibrium seeking algorithm based on the preconditioned forward–backward operator splitting for SGNEPs, where, at each iteration, the expected value of the pseudogradient is approximated via a number of random samples. Our main contribution is to show almost sure convergence of the proposed algorithm if the pseudogradient mapping is restricted (monotone and) cocoercive.

Patellofemoral joint loading during the forward and backward lunge

ObjectiveTo examine patellofemoral joint (PFJ) loading in two lunge movements: Forward Lunge (FL) and Backward Lunge (BL). DesignRepeated Measures. SettingUniversity Biomechanics Laboratory. Participants20 asymptomatic females. Main outcome measuresSix trials of two lunge movements (FL and BL) to a depth of 75% of leg length were performed. 3-D motion capture and force platforms were used to collect data as input into a musculoskeletal model to determine quadriceps force, PFJ reaction force, PFJ stress, and knee flexion angle. ResultsMultivariate analysis indicated differences in PFJ loading variables and joint angles between the lunge movements (Forward vs. Backward) and phases (Down vs. Up). Quadriceps force, PFJ reaction force, and knee flexion angle were larger in the FL movement and Up phases. PFJ loading rate was greater in the FL movement along with a lower forward trunk tilt. ConclusionThe FL produced greater PFJ loading variables compared to the BL. Further research is needed to examine a population of individuals who have patellofemoral pain (PFP) to see if their symptoms may be reduced when using the BL.

Utility of Equivalence and Cognition Models in Enhancing Validity of Translated Questionnaires: A Methodological Example Using the Heart Quality-of-Life Questionnaire.

ABSTRACTBackgroundThe cross-cultural adaptation of questionnaires has tenuous theoretical underpinnings that limit the rigor of data collection and the meaningful analysis of cognitive interview data. An adaptation of existing models of equivalence and cognition provides structure to the comprehensive investigation of various equivalence types in enhancing the validity of translated questionnaires.PurposeIn this study, a framework comprising equivalence and cognition models was used to assess and finalize the Heart Quality-of-Life (HeartQoL)-Bahasa Malaysia (BM) questionnaire, which was derived from both forward–backward (FB) and dual-panel (DP) translation methods.MethodsInvestigation and finalization of two initial versions of the questionnaire were conducted based on findings from an expert assessment (n = 3 sociolinguists blinded to translation methods) and cognitive interviews with purposively sampled patients (FB: n = 11; DP: n = 11). The equivalence model of Herdman et al. and the question-and-answer model of Collins were adapted to form a “cognition-and-equivalence” model to guide data collection and analysis through modified cognitive interviews. The final HeartQoL-BM was completed by 373 patients with ischemic heart disease from two medical centers, and the data were analyzed using confirmatory factor analysis to assess the evidence of equivalence.ResultsFindings from the expert assessment and cognitive interview showed the existence of semantic and item equivalence on almost all of the FB and DP items, identified some subtle potential equivalence gaps, and guided the process of item finalization. Confirmatory factor analysis, including tests of factorial invariance on the final two-factor model of HeartQoL-BM, confirmed conceptual, item, measurement, and operational equivalence, which supports functional equivalence.ConclusionsThe potential use of the cognition-and-equivalence model for modified cognitive interviewing and the application of the six equivalence types of Herdman et al. were supported by the HeartQoL-BM showing functional equivalence with its source. HeartQoL-BM is a potentially valid measure of health-related quality of life for patients with ischemic heart disease independent of conditions such as angina, myocardial infarction, and heart failure.

Utility maximization via decoupling fields

We consider the utility maximization problem for a general class of utility functions defined on the real line. We rely on existing results which reduce the problem to a coupled forward–backward stochastic differential equation (FBSDE) and concentrate on showing existence and uniqueness of solution processes to this FBSDE. We use the method of decoupling fields for strongly coupled, multi-dimensional and possibly non-Lipschitz systems as the central technique in conducting the proofs.

Immediate effects of an acute bout of repeated soccer heading on cognitive performance

ABSTRACT Purpose: There isgrowing concern surrounding the harmful effects of soccer heading on cognitive function. The present study aims to examine the immediate effects of heading. Methods: 30 recreational male soccer players were divided into three groups that undertook 20 consecutive headers with a soft (8.8 psi), hard (16.2 psi), or no (control) ball. A battery of neuropsychological tests was completed before and after heading: King-Devick, trail-making (TM) (A, B), digit span (DS) and spatial span (SS) (forward, backward). Results: Significant increase in the time (M = 4.44 s) and errors (M = 1.45) for the King-Devick test within the hard and soft groups, although there was no significant difference for TM-A and TM-B. Significant decline for SS forward within the hard and soft groups (M= −16%), although the declines for SS backward (M = −16%), DS forward (M= −23%) and DS backward (M = −25%) were present only for the hard group (ps <.05). Discussion: While outside of regular match-play, this study showed that heading negatively influenced one indicator of a suspected concussion (King-Devick), as well as working memory (DS, SS) that is essential for daily life. These findings contribute to the growing debate surrounding heading safety.

Automatic Assessment of Cognitive Tests for Differentiating Mild Cognitive Impairment: A Proof of Concept Study of the Digit Span Task.

Current conventional cognitive assessments are limited in their efficiency and sensitivity, often relying on a single score such as the total correct items. Typically, multiple features of response go uncaptured. We aim to explore a new set of automatically derived features from the Digit Span (DS) task that address some of the drawbacks in the conventional scoring and are also useful for distinguishing subjects with Mild Cognitive Impairment (MCI) from those with intact cognition. Audio-recordings of the DS tests administered to 85 subjects (22 MCI and 63 healthy controls, mean age 90.2 years) were transcribed using an Automatic Speech Recognition (ASR) system. Next, five correctness measures were generated from Levenshtein distance analysis of responses: number correct, incorrect, deleted, inserted, and substituted words compared to the test item. These per-item features were aggregated across all test items for both Forward Digit Span (FDS) and Backward Digit Span (BDS) tasks using summary statistical functions, constructing a global feature vector representing the detailed assessment of each subject's response. A support vector machine classifier distinguished MCI from cognitively intact participants. Conventional DS scores did not differentiate MCI participants from controls. The automated multi-feature DS-derived metric achieved 73% on AUC-ROC of the SVM classifier, independent of additional clinical features (77% when combined with demographic features of subjects); well above chance, 50%. Our analysis verifies the effectiveness of introduced measures, solely derived from the DS task, in the context of differentiating subjects with MCI from those with intact cognition.

Iterative Selection and Correction Based Adaptive Greedy Algorithm for Compressive Sensing Reconstruction

Compressive sensing (CS) is a new sampling theory used in many signal processing applications due to its simplicity and efficiency. However, signal reconstruction is considered as one of the biggest challenge faced by the CS method. Therefore in this paper, we aim to address this challenge by proposing an Adaptive Iterative Forward–Backward Greedy Algorithm (AFB). AFB algorithm is different from all other reconstruction algorithms, as it depends on solving the least squares problem in the forward phase, which increases the probability of selecting the correct columns better than other reconstruction algorithms. In addition, AFB improves the selection process by removing the incorrect columns selected in the previous step. To evaluate the AFB’s reconstruction performance, we used two types of data: computer-generated data and real data set (Intel Berkeley data set). The simulation results show that AFB outperforms Forward–Backward Pursuit, Subspace Pursuit, Orthogonal Matching Pursuit, and Regularized OMP in terms of reducing reconstruction error.

The effects of drugs in chemotherapy as optimal control of tumor growth dynamical model

Cancer is the disease caused by disordered hormone so that it causes the lumps to grow abnormally on body tissue, and it is known as a malignant tumor. Some mortalities in the world are caused by cancer, while in Indonesia, cancer contributes to the third-largest death. This research will explain about stability and optimal control of tumor growth dynamical model by drugs in chemotherapy. In the tumor growth dynamical model, there are normal cells, tumor cells, and immune cells. From the mathematical model of tumor growth, some equilibrium points will be analyzed for their stability using eigenvalue. In this research, from the mathematical model of tumor growth, it will be added control, such as drugs in chemotherapy. The method used for solving optimal control problems and resulting numerical solutions is Forward Backward Sweep Method. Based on simulation results, drugs in chemotherapy give effects in a normal cell, tumor cell, and immune cell.

The effect of hypergravity on upright balance and voluntary sway.

We compared voluntary oscillatory sway for eight subjects tested in 1.8-g and 1-g gravito-inertial force (GIF) levels of parabolic flight. Subjects performed voluntary forward-backward (FB) and lateral left-right (LR) swaying as the forces and moments under the soles of each foot were measured. We calculated the experimental values of three parameters: two ankle stiffness parameters KSAP and KSML acting in orthogonal FB and LR directions and one parameter KED related to leg pivot shifting. Simulations of the engaged leg model (Bakshi A, DiZio P, Lackner JR. J Neurophysiol 121: 2042-2060, 2019; Bakshi A, DiZio P, Lackner JR. J Neurophysiol 121: 2028-2041, 2019) correctly predicted the experimentally determined stability bounds of upright balance and also the scaling of the postural parameters as a function of GIF magnitude. The effective stiffness, KSAP, at the ankles played the primary role to prevent falling in FB swaying and both model predictions, and experimental data showed KSAP to scale up in proportion to GIF magnitude. For LR swaying, the model predicted a 3:4 scaling of anterior-posterior stiffness to change in GIF magnitude, which was borne out by the experimental data. Simulations predict stability (nonfalling) not to depend on lateral stiffness, KSML, which was experimentally found not to depend on the GIF magnitude. Both model and experiment showed that the geometry-dependent pivot shift parameter KED was invariant to a change in GIF magnitude. Thus the ELM explains voluntary sway and balance in altered GIF magnitude conditions, rotating environments with Coriolis perturbations of sway, as well as normal terrestrial conditions.NEW & NOTEWORTHY A nonparallel leg model of balance, the engaged leg model (ELM), was previously developed to characterize adaptive balance control in a rotating environment. Here we show the ELM also explains sway in hypergravity. It predicts the changes in balance control parameters with changes in gravity. ELM is currently the only balance model applicable to artificial and hypergravity conditions. ELM can also be applied to terrestrial clinical situations for pathologies that generate postural asymmetries.

KEBIJAKAN STRATEGIS PT. ANEKA TAMBANG TBK

Ferronickel Production from 2014 to 2018 the highest record was 24,868 Tni or grew 47.5% over the past five years. Alumina Production from 2016 to 2018 has continued to decline. Gold production in the last five years has continued to decline too, While ANTAM's competitors, such as Tsingshan Group for Nickel, Harita Group for Bauxite and Agincort for Gold, showed a performance that exceeded ANTAM. This research was conducted to analyze the strategic policies taken by ANTAM whether they are in accordance with the market situation and the competition map in the mining industry. The research data was obtained through ANTAM's Annual Report and the Annual Report of several other mining companies and other data through the internet media. Strategy Analysis uses 3 stages, stage one to input matrix of the Internal Factor Analysis and External Factor Analysis, stage two matching uses the SWOT Matrix, SPACE Matrix, BCG Matrix, IE Matrix, and GRAND STRATEGY Matrix, as well as stage three selection of strategy using the QSPM matrix. The results showed that the strategy chosen was in accordance with current strategy ANTAM, i.e aggressive, growing, building intensively and integratively through forward integration, backward integration, horizontal integration, product development, market penetration, market development, and related diversification, but in the implementation process it still needed corrections to make adjustments so that the strategy went well. Keywords: SWOT Matrix, SPACE Matrix, BCG Matrix, IE Matrix, QSPM Matrix &nbsp;

Open-loop equilibrium strategy for mean-variance asset-liability management with margin requirements

This paper considers a mean-variance asset-liability management problem in which short-selling is allowed, but accompanied by margin requirements. This is a mean-variance problem with a non linear state process. We derive a sufficient condition and a necessary condition for the time-consistent equilibrium strategy by using a system of forward backward stochastic differential equations. By decoupling this system, we obtain the unique equilibrium strategy. As a byproduct, we also get the equilibrium strategy for the mean-variance asset-liability management problem under short-selling prohibition.