Adaptive Multistage Research Articles

Improvement of Computer Adaptive Multistage Testing Algorithm Based on Adaptive Genetic Algorithm

Multistage testing (MST) is a portion of computational adaptive testing that adapts assessment structure at the sublevel rather than the component level. The goal of the MST algorithm is to identify bugs in computer programming, and there is a significant cost to utilising MST due to its decreased versatility during software development and maintenance. The efficiency of most algorithms drastically reduces for adaptive MST with complex feasible regions, while some modern algorithms function well while tackling computerised MST with a basic practicable range. The study offers an automated Adaptive Multistage Testing algorithm based on Adaptive Genetic Algorithm (AMST-AGA) for optimisation and scalability problems, in which constraints are successively introduced and dealt with at various evolutionary phases. In this paper, many test cases will aid in finding bugs and meeting completeness goals. Each time test cases are created, these testing scenarios must continue to pass.

ASHL: An Adaptive Multi-Stage Distributed Deep Learning Training Scheme for Heterogeneous Environments

ASHL: An Adaptive Multi-Stage Distributed Deep Learning Training Scheme for Heterogeneous Environments

Space Target Recognition Method Based on Adaptive Spatial Filtering Multistage Hypothesis Testing

Space Target Recognition Method Based on Adaptive Spatial Filtering Multistage Hypothesis Testing

Noise Cancellation in Computed Tomography Images through Adaptive Multi-Stage Noise Removal Paradigm

Image de-noising is a noise removal approach, which is utilized to remove noise from the noisy image and is utilized to protect the significant features of images namely, corners, edges, textures, and sharp structures. For medical diagnosis Computer tomography (CT) images are mainly utilized. Due to acquisition and transmission in CT imaging, the noise that appears leads to poor image quality. To overcome this problem, an efficient Noise cancellation in computed tomography images using adaptive multi-stage noise removal paradigm is proposed. The proposed approach consists of three phases namely, Optimal Discrete Wavelet Transform, first stage noise removal using Block Matching, and 3D filtering (BM3D) filter and second stage noise removal using the bilateral filter (BF). Initially, Discrete Wavelet Transform (DWT) is applied to the input image to diminish noise in CT images. In this method, co-efficient ranges are optimally selected with the help of Crow Search Optimization (CSO) algorithm. Secondly, to remove the noise present in the bands, BM3D algorithm is applied. Finally, bilateral filter is applied to the BM3D output image to further enhance the image. The performance of the proposed methodology is analyzed in terms of Peak signal-to-noise ratio (PSNR), Root Mean Square Error (RMSE), and Structural Similarity Index (SSIM). Furthermore, the multi-stage noise removal model obtained gives the best PSNR values compared to other techniques.

Analyzing Different Module Characteristics in Computer Adaptive Multistage Testing

Computer Adaptive Multistage Testing (ca-MST), which take the advantage of computer technology and adaptive test form, are widely used, and are now a popular issue of assessment and evaluation. This study aims at analyzing the effect of different panel designs, module lengths, and different sequence of a parameter value across stages and change in b parameter range on measurement precision in ca-MST implementations. The study has been carried out as a simulation. MSTGen simulation software tool was used for that purpose. 5000 simulees derived from normal distribution (N (0,1)) were simulated. 60 different conditions (two panel designs (1-3-3; 1-2-2), three module lengths (10-15-20), 5 different a parameter sequences (“0.8; 0.8; 0.8” - “1.4; 0.8; 0.8”-“0.8;1.4; 0.8” - “0.8; 0.8;1,4” - “1.4; 1,4; 1.4”) and two b parameter difference (small; large) conditions) were taken into consideration during analysis. Correlation, RMSE and AAD values of conditions were calculated. Conditional RMSE values corresponding to each ability level are given in a graph. Dissimilar to other studies in the literature, this study examines b parameter difference condition in three-stage tests and its interaction with a parameter sequence. Study results show that measurement precision increases as the number and length of the modules increase. Errors in measurement decrease as item discrimination values increase in all stages. Including items with a high value of item discrimination in the second or last stage contributes to measurement precision. In extreme ability levels, large difficulty difference condition produces lower error values when compared to small difficulty difference condition.

Frequency Adaptive Multistage Harmonic Oscillator for Renewable-Based Microgrid Under Nonideal Grid Conditions

Diurnal and seasonal variability associated with the renewable power generation is disinterested by grid integration. However, for the cases of developing and underdeveloped countries, the utility grids are relatively weak and exacerbate the issues related to power quality, frequency jumps, grid voltage distortion, sag, and swell. To deal with these issues of weak grid-integrated hybrid-renewable-power-generation-based microgrid and to ensure reliable and effective operation, the frequency adaptive multistage harmonic oscillator (MSHO) control is used in this article. This control comprises of multistage filter with dc bias rejection loop and frequency-locked loop. The multistage filter is tuned to dominant lower order harmonic and allows the selective elimination of the harmonics. An MSHO is used for assessing the fundamental constituent from harmonics and dc-bias-infected grid voltage. It also extracts the positive-sequence constituent from distorted/unbalanced grid voltages while maintaining the balanced grid currents. It effectively overcomes the frequency perturbations and nonlinear load compensation and significantly increases the overall reliability and quality of power. A set of back-to-back associated power converters provide a flexible speed operation of the wind power generation system. Different functionality modes are incorporated in order to address round the clock operation of the microgrid, enabling the reactive power compensation capability and mitigation of the harmonics demanded by the nonlinear load connected at the distribution side. The maximum power operating point for both wind and solar photovoltaic arrays is acquired by the individual implementation of the perturb and observe technique. The performance investigation of the system is carried out on a developed laboratory prototype. The aptness and the functionality of the control algorithms are noticeable from the experimental results. The issues of loss of supply, estimation of grid voltage signal, effects of weak grid, variability of renewables with curtailable load are addressed, and the power quality standard IEEE-519-2014 is satisfied.

Imputation Methods to Deal With Missing Responses in Computerized Adaptive Multistage Testing.

Routing examinees to modules based on their ability level is a very important aspect in computerized adaptive multistage testing. However, the presence of missing responses may complicate estimation of examinee ability, which may result in misrouting of individuals. Therefore, missing responses should be handled carefully. This study investigated multiple missing data methods in computerized adaptive multistage testing, including two imputation techniques, the use of full information maximum likelihood and the use of scoring missing data as incorrect. These methods were examined under the missing completely at random, missing at random, and missing not at random frameworks, as well as other testing conditions. Comparisons were made to baseline conditions where no missing data were present. The results showed that imputation and the full information maximum likelihood methods outperformed incorrect scoring methods in terms of average bias, average root mean square error, and correlation between estimated and true thetas.

A Top‐Down Approach to Designing the Computerized Adaptive Multistage Test

AbstractThe top‐down approach to designing a multistage test is relatively understudied in the literature and underused in research and practice. This study introduced a route‐based top‐down design approach that directly sets design parameters at the test level and utilizes the advanced automated test assembly algorithm seeking global optimality. The design process in this approach consists of five sub‐processes: (1) route mapping, (2) setting objectives, (3) setting constraints, (4) routing error control, and (5) test assembly. Results from a simulation study confirmed that the assembly, measurement and routing results of the top‐down design eclipsed those of the bottom‐up design. Additionally, the top‐down design approach provided unique insights into design decisions that could be used to refine the test. Regardless of these advantages, it is recommended applying both top‐down and bottom‐up approaches in a complementary manner in practice.

Management System for Large Li-Ion Battery Packs with a New Adaptive Multistage Charging Method

Among the wide diversity of existing technologically mature batteries, lithium-ion (Li-ion) batteries have become popular because of their longevity, high energy density, high efficiency and lack of memory effect. Differential charging of cells with age has turned balancing management systems into an important research subject. This paper proposes a new battery management system (BMS) to improve the capacity usage and lifespan of large Li-ion battery packs and a new charging algorithm based on the traditional multistage method. The main advantages of the proposed system are its versatility and ability to implement different charging and balancing methods in a very accessible way. The combination of charging methods with balancing methods represents an evolution when compared with other works in the literature.

Examining Content Control in Adaptive Tests: Computerized Adaptive Testing vs. Computerized Adaptive Multistage Testing

Examining Content Control in Adaptive Tests: Computerized Adaptive Testing vs. Computerized Adaptive Multistage Testing

Computer Adaptive Multistage Testing: Practical Issues, Challenges and Principles

The purpose of many test in the educational and psychological measurement is to measure test takers’ latent trait scores from responses given to a set of items. Over the years, this has been done by traditional methods (paper and pencil tests). However, compared to other test administration models (e.g., adaptive testing), traditional methods are extensively criticized in terms of producing low measurement accuracy and long test length. Adaptive testing has been proposed to overcome these problems. There are two popular adaptive testing approaches. These are computerized adaptive testing (CAT) and computer adaptive multistage testing (ca-MST). The former is a well-known approach that has been predominantly used in this field. We believe that researchers and practitioners are fairly familiar with many aspects of CAT because it has more than a hundred years of history. However, the same thing is not true for the latter one. Since ca-MST is relatively new, many researchers are not familiar with features of it. The purpose of this study is to closely examine the characteristics of ca-MST, including its working principle, the adaptation procedure called the routing method, test assembly, and scoring, and provide an overview to researchers, with the aim of drawing researchers’ attention to ca-MST and encouraging them to contribute to the research in this area. The books, software and future work for ca-MST are also discussed.

Adaptive Multi-stage Output Feedback NMPC using the Extended Kalman Filter for time varying uncertainties applied to a CSTR

Nonlinear Model Predictive control (NMPC) is one of the advanced control strategies for multi-dimensional nonlinear systems with constraints. With uncertainties present in the model, robust NMPC strategies are proposed in order to counteract the effects of the uncertainties and have a safe operation of the plant.Multi-stage NMPC offers a non-conservative alternative as it models the feedback information explicitly in the problem formulation by means of a scenario tree. In order to be robust to both the model uncertainties and the estimation error, we formulate a multi-stage output feedback NMPC strategy by creating additional scenarios by sampling the innovations and use observer equations to predict the future evolution of the plant. Since the observers such as the Extended Kalman Filter (EKF) can be used to estimate the uncertain parameters along with the states, the output feedback NMPC strategy is improved to be adaptive with respect to time varying uncertain parameters and the performance of the controller is improved. We demonstrate the advantages of the proposed adaptive scheme using a nonlinear Continuous Stirred Tank Reactor (CSTR) example.

Long-Term Follow-Up of Adaptive Multistage Stereotactic Radiosurgery for Treatment of High-Grade Arteriovenous Malformations

The optimal management of high-grade arteriovenous malformations (AVM) remains unclear. There is a paucity of literature addressing the efficacy and safety of radiosurgery for high risk patients. Our institution has adopted a multi-staged stereotactic radiosurgery (SRS) approach with treatment of the entire nidus using a lower dose per stage to achieve AVM obliteration with decreased complications. Retrospective review of patients with high grade Spetzler-Martin (S-M) III-V AVMs with at least two multi-stage SRS treatments between 1989 and 2013. Clinical outcomes of obliteration rate, adverse events and treatment data were collected. Patients with less than 12 months of follow-up after second multi-stage SRS treatment were excluded. Forty-two patients met inclusion criteria (n = 26, S-M III; n = 13, S-M IV; n = 3, S-M V). Median follow-up was 113.6 months after first SRS. Median number of staged SRS treatments was 2 and median interval between SRS treatment stages was 41.9 months. Median dose was 1400 cGy per stage and cumulative median dose at last follow-up or obliteration was 3350 cGy. 22 patients had prior embolization and 2 patients had subtotal resection before SRS. Complete AVM obliteration rate was 38.1%. AVMs that underwent pre-SRS embolization had a significantly lower rate of obliteration (23% vs 55%, p = 0.03). Median volume reduction for non-obliterated AVMs was 69.4%. A lower complete AVM obliteration rate was significantly associated with a higher S-M grade (p = 0.03). Additionally, AVM volume less than 10 cm3 (p = 0.22), first-stage SRS dose greater than 1400 cGy (p = 0.43) and cumulative SRS dose greater than 3200 cGy (p = 0.57) did not significantly influence the rate of obliteration. In total, 21 post-SRS adverse events occurred in 18 patients. Adverse events were defined as persistent headache (n = 3), new/persistent seizure activity (n = 8), symptomatic radiation necrosis (n = 1), post-SRS intracranial hemorrhage +/- neurologic deficits (n = 8, 4 with residual deficits), and neurologic deficits without antecedent intracranial bleed (n = 1). The post-SRS adverse event rate was 5.1% per year (21 events over 409.9 cumulative patient yrs) after initial SRS. A retrospective review of our experience treating high grade AVMs with adaptive multi-stage SRS to the entire nidus demonstrates that this may be an appropriate option as it results in AVM obliteration in a meaningful proportion of patients with an acceptable adverse event rate. Lower AVM obliteration rates were significantly associated with higher S-M grade and pre-SRS embolization. We continue to investigate whether this strategy may be improved with treatment at shorter intervals or additional treatment sessions over time. In spite of an acceptable toxicity profile, treatment of high grade AVMs should be considered with caution since partial obliteration does not protect from bleeding.

An Adaptive Multistage Multiuser Detector for MC-CDMA Communication Systems Using Evolutionary Computation Technique

The main targets of multi-carrier direct sequence code division multiple access (MC-DS-CDMA) mobile communication systems are to overcome the multi-path fading influences as well as the near-far effect and to increase its capacity. Many optimal and suboptimal multi-user detection approaches have recently been proposed and analyzed in literature. Unfortunately, most of them share the drawback of requiring a practical solution. Therefore, we have presented an adaptive multistage interference cancellation structure based on the particle swarm optimization (PSO) approach in this paper, and have effectively eliminated the multi-access interference (MAI) and near-far effect, and quickly converges to global optimal solution. Simulation results show that the proposed scheme can outperform some of the existed interference cancellation methods in both the additive white Gaussian noise and the multi-path fading channels.

A Testlet Assembly Design for Adaptive Multistage Tests

This article describes multistage tests and some practical test development considerations related to the design and implementation of a multistage test, using the Uniform CPA (certified public accountant) Examination as a case study. The article further discusses the use of automated test assembly procedures in an operational context to produce large numbers of adaptive testlets over time.

Performance of Adaptive Multistage Fuzzy-Based Partial Parallel Interference Canceller for Multi-Carrier CDMA Systems

In this paper, we propose an adaptive multistage fuzzy-based partial parallel interference cancellation (FB-PPIC) multiuser detector for multi-carrier direct-sequence code-division multiple-access (MC-CDMA) communication systems over frequency selective fading channels. The partial cancellation tries to reduce the cancellation error in parallel interference cancellation (PIC) schemes due to the wrong interference estimations in the early stages and thus outperforms the conventional PIC (CPIC) under the heavy load for MC-CDMA systems. Therefore, in this paper, the adaptive cancellation weights are inferred from a proposed multistage fuzzy inference system (FIS) to perform effective PPIC multiuser detection under time-varying frequency selective fading channels in MC-CDMA systems. Simulation results show that the proposed adaptive fourstage FB-PPIC scheme outperforms both CPIC and constant weight PPIC (CW-PPIC) schemes, especially in near-far environments.

Successive interference cancellation for multiuser asynchronous DS/CDMA detectors in multipath fading links

There has been an increasing interest in the use of code-division multiple access (CDMA) in cellular mobile and wireless personal communications. The choice of such multiaccess technique is attractive because of its potential capacity increases and other technical factors such as privacy and multipath rejection capabilities. However, it is well known that the performance of CDMA can be significantly degraded due to cochannel interference (CI) and the near-far effects. We consider the performance of direct-sequence (DS)-based CDMA over fading channels that are modeled as slowly varying Rayleigh-fading discrete multipath channels. Specifically, we propose and analyze an adaptive multistage interference cancellation strategy for the demodulation of asynchronous DS spread-spectrum multiple-access signals. Numerical results show that the proposed multistage detector, which alleviates the detrimental effects of the near-far problem, can significantly improve the system performance.

Analysis of adaptive multistage interference cancellation for CDMA using an improved Gaussian approximation

We consider a simple model for adaptive multistage interference cancellation within a CDMA system, and seek to develop an accurate analytical expression for the performance of this system. Previous work on interference cancellation has relied heavily on simulation techniques or a simple Gaussian approximation (GA). The standard GA ran lead to bit-error rate (BER) results which are optimistic for the conventional receiver, and this also occurs when the approximation is applied to the interference cancellation problem. Additionally, this approximation does not allow the second order effects of the multiple access interference (MAI) to be included in the performance estimates. Several improvements on the standard GA have been suggested which result in accurate performance results for a standard CDMA receiver. This paper presents an analytical expression for the probability of bit error for an adaptive multistage interference canceller, using an improved Gaussian approximation (IGA) for MAI. The BER at any stage of interference cancellation can be recursively computed from the signal-to-noise ratio (SNR), the statistics of the random powers of users, and the processing gain of the CDMA system. The performance of the resulting EER expression is compared with simulation results. Since the second order effects of MAI can be included, the analytical framework presented here can also be used to evaluate the performance of multistage interference cancellation in arbitrary fading environments, and we present results for the performance of interference cancellation in lognormal fading environments.

Picture coding by an adaptive multistage vector quantization

AbstractAn adaptive multistage vector quantizing system is proposed for highly efficient picture coding method and its coding performances are investigated. This system contains a multistage vector quantizer which means that comparatively large picture blocks are quantized first, then the remaining quantization error is quantized in smaller blocks, gradually refining the resolution at subsequent stages. That is, a rough picture is coded first and finer structures are coded later. Computer simulation studies on several picture samples demonstrate the excellent processing efficiency of the proposed method in comparison with conventional vector quantizers.

International Conflict Management via Adaptive Learning and Multistage Compromises

International Conflict Management via Adaptive Learning and Multistage Compromises