Preferred Solution Research Articles

The analysis of partisan differences in advanced democracies. The “independent variable problem” reconsidered

The paper challenges the idea that using governing parties’ policy positions is necessarily desirable in quantitative analyses of partisan differences in public policies. Rather, for some research questions parties’ affiliation with certain party families is the preferable solution. The paper shows that the use of policy positions instead of party family affiliation shifts the research question from asking whether parties make a difference in public policy to the question whether parties in government do what they promise. This shift can have considerable analytical costs and can potentially blindfold scholars for certain dynamics. Moreover, the use of party family affiliation has less drawbacks than is often claimed even under multidimensional party competition if the simple distinction between left, center and right parties is abandoned and more fine-grained data for various party families are used.

Determination of the Total Phenolics Content and Antioxidant Activity of Extracts from Parts of Plants from the Greek Island of Crete.

Oxidative damages are responsible for many adverse health effects and food deterioration. The use of antioxidant substances is well renowned, and as such, much emphasis is placed on their use. Since synthetic antioxidants exhibit potential adverse effects, plant-derived antioxidants are a preferable solution. Despite the myriads of plants that exist and the fact that numerous studies have been carried out so far, there are many species that have not been examined so far. Many plants under research exist in Greece. Trying to fill this research gap, the total phenolics content and antioxidant activity of seventy methanolic extracts from parts of Greek plants were evaluated. The total phenolics content was measured by the Folin-Ciocalteau assay. Their antioxidant capacity was calculated by the 2,2-Diphenyl-1-picrylhydrazyl (DPPH) scavenging test, the Rancimat method based on conductometric measurements, and the thermoanalytical method DSC (Differential Scanning Calorimetry). The tested samples were obtained from several parts of fifty-seven Greek plant species belonging to twenty-three different families. Both a remarkably high phenolic content (with gallic acid equivalents varying between 311.6 and 735.5 mg/g of extract) and radical scavenging activity (IC50 values ranged from 7.2 to 39.0 μg/mL) were found in the extract of the aerial parts of Cistus species (C. creticus subsp. creticus, C. creticus subsp. eriocephalus, C. monspeliensis, C. parviflorus and C. salviifolius), Cytinus taxa (C. hypocistis subsp. hypocistis, C. hypocistis subsp. orientalis and C. ruber), and Sarcopoterium spinosum. Furthermore, the sample of Cytinus ruber showed the highest protection factor (PF = 1.276) regarding the Rancimat method, which was similar to that of butylated hydroxytoluene (BHT) (PF = 1.320). The results indicated that these plants are rich in antioxidant compounds, potentiating their use either as food additives to enhance the antioxidant properties of food products, or protect them from oxidation, or as sources for the preparation of food supplements with antioxidant properties.

Electromagnetic Characteristics of a Flux-Modulated Permanent Magnet Linear Machine With Sandwich Armature for Free-Piston Energy Converter System

The linear machine is the key part of free-piston energy converter system, and its electromagnetic characteristics directly determine system performance. This paper proposes a novel flux-modulated permanent magnet (PM) linear machine with sandwich armature for free-piston energy converter system. The sandwich armature is composed of modulated layer, air-core winding layer and iron core. It integrates electromagnetic advantages of a flux-modulated and slotless machine, so it can achieve good comprehensive performance by appropriate design of sandwich armature. Firstly, an accurate subdomain model is established to analyze magnetic field characteristics of proposed machine, and then the suitable pole/slot combinations are determined. Subsequently, machine performance such as thrust force and efficiency are discussed based on design dimensional constraints. Finally, structural optimization of cylinder armature is developed for eddy-current loss suppression, and then experiments on prototype are carried out. The performance comparisons with flux-modulated and slotless machines show that the proposed prototype has high peak thrust, small electromechanical time constant, and strong design flexibility. Hence it is a preferred solution for free-piston energy converter system.

Multi-criteria performance analysis and optimization of a solar-driven CCHP system based on PEMWE, SOFC, TES, and novel PVT for hotel and office buildings

Solar-powered multi-generation systems contribute to efficiently reducing the consumption of fossil fuels and lowering greenhouse gas emissions. This study proposes a solar-driven CCHP system combined with a novel photovoltaic thermal collector, proton exchange membrane water electrolyzer, solid oxide fuel cell, and thermal energy storage to meet the user's multiple dynamic energy demands. Multi-criteria performance analysis of the CCHP system is conducted from the perspectives of energy efficiency, sustainability, energy savings, environmental benefits, and economy for typical hotel and office buildings. The multi-objective optimization is carried out to optimize the parameter configurations and equipment capacities of the proposed system. The results demonstrate that the PV coverage ratio of the partially covered parabolic trough photovoltaic thermal (PCPTPVT) collector has noteworthy influences on the PCPTPVT outputs, the determination of the equipment capacities of the CCHP system, and further affects the overall comprehensive performance. The sustainability indicators of the hotel and office rise with the increasing PV coverage ratio, and that of the office is gradually larger than that of the hotel. The optimal comprehensive performance and annual total cost of the CCHP system from the multi-objective optimization are 1.004 and 87601 $ for the hotel and 1.049 and 92759 $ for the office, respectively. The PV coverage ratios of the preferred optimal solution for the hotel and office are 0.659 and 0.859, respectively.

Compressive behavior of 3D printed concrete with different printing paths and concrete ages

As an intelligent construction technology, 3D printed concrete has made great progress in recent years, but research on the development law of hardened mechanical properties of 3D printed concrete is relatively limited, and the influence of printing path on compressive behavior of 3D printed concrete still needs further research. This paper proposed a new printing path for extrusion based 3D printed concrete and investigated the compressive behavior of hardened concrete printed by the new printing path. The effect of printing path, concrete age, printing speed, specimen size, and replacement of natural sand by recycled sand were evaluated through compressive tests of specimens printed by different path at different ages. Compared with the traditional printing path, the new printing path could increase peak strain, elastic modulus, and cubic compressive strength of the printed concrete. The new printing path provided a preferable alternative solution for printed concrete subjected to compression. The results also indicate that the compressive strength of printed concrete at 3 days can reach 45%− 62% of the 28-day compressive strength, and the compressive strength at 7 days appears to achieve 68%− 89% of the 28-day compressive strength, and the printing path has minor effect on the development rate of compressive strength. Based on the test data analyses, an analytical model was proposed to describe the stress-strain relationship of concrete printed by two printing paths.

Differential evolution guided by approximated Pareto set for multiobjective optimization

Differential evolution (DE), as an efficient evolutionary optimizer, has been widely applied to deal with multiobjective optimization problems. In DE generation operations, appropriate guiding solutions, the “best” solutions (denoted as xbest), will be in favor of the search for generating promising new trial solutions. However, it is still a challenge to define and select such xbest due to the Pareto property of multiobjective optimization. Facing this challenge, we propose a regularity model guided differential evolution (RMDE) for multiobjective optimization. Different from the existing studies that select xbest from non-dominated solutions or predefined preference solutions, the proposed RMDE aims to sample the guiding solutions from the regularity models that are built to approximate Pareto optimal set explicitly. In this way, four alternative RMDE mutation strategies with the sampled xbest are developed and investigated, including the search efficiency and parameter settings. Empirical studies are conducted to validate the performance of RMDE on 51 test instances. The experimental results demonstrate the advantages of the proposed method over seven other classical or newly developed algorithms from the literature.

Refocusing Frege’s Other Puzzle: A Response to Snyder, Samuels, and Shapiro

Abstract In their recent article ‘Resolving Frege’s other Puzzle’ Eric Snyder, Richard Samuels, and Stewart Shapiro defend a semantic type-shifting solution to Frege’s other Puzzle and criticize my own cognitive type-shifting solution. In this article I respond to their criticism and in turn point to several problems with their preferred solution. In particular, I argue that they conflate semantic function and semantic value, and that their proposal is neither based on general semantic type-shifting principles nor adequate to the data.

Series PIDA Controller Design for IPDT Processes

This paper discusses optimal design of the series proportional–integral–derivative–accelerative (PIDA) controller for integral-plus-dead-time (IPDT) plants. The article starts with the design of disturbance reconstruction and compensation based on proportional-derivative-accelerative (PDA) stabilizing controllers. It shows that by introducing positive feedback by a low-pass filter from the (limited) output of the stabilizing PDA controller, one gets disturbance observer (DOB) for the reconstruction and compensation of input disturbances. Thereby, the DOB functionality is based on evaluating steady-state controller output. This DOB interpretation is in full agreement with the results of the analysis of the optimal setting of the stabilizing PDA controller and of its expanded PIDA version with positive feedback from the controller output. By using the multiple real dominant pole (MRDP) method, it confirms that the low-pass filter time constant in positive feedback must be much longer than the dominant time constant of the stabilized loop. This paper also shows that the constrained PIDA controller with the MRDP setting leads to transient responses with input and output overshoots. Experimentally, such a constrained series PIDA controller can be shown as equivalent to a constrained MRDP tuned parallel PIDA controller in anti-windup connection using conditional integration. Next, the article explores the possibility of removing overshoots of the output and input of the process achieved for MRDP tuning by interchanging the parameters of the controller transfer function, which was proven as very effective in the case of the series PID controller. It shows that such a modification of the controller can only be implemented approximately, when the factorization of the controller numerator, which gives complex conjugate zeros, will be replaced by a double real zero. Neglecting the imaginary part and specifying the feedback time constant with a smaller approximative time constant results in the removal of overshoots, but the resulting dynamics will not be faster than for the previously mentioned solutions. A significant improvement in the closed-loop performance can finally be achieved by the optimal setting of the constrained series PIDA controller calculated using the performance portrait method. This article also points out the terminologically incorrect designation of the proposed structure as series PIDA controller, because it does not contain any explicit integral action. Instead, it proposes a more thorough revision of the interpretation of controllers based on automatic reset from the controller output, which do not contain any integrator, but at the same time represent the core of the most used industrial automation. In the end, constrained structures using automatic reset of the stabilizing controller output can ensure a higher performance of transient responses than the usually preferred solutions based on parallel controllers with integral action that, in order to respect the control signal limitation, must be supplemented with anti-windup circuitry. The excellent properties of the constrained series PIDA controller are demonstrated by an example of controlling a thermal process and proven by the circle criterion of absolute stability.

Citizens' economic recovery models for a pandemic.

The COVID-19 pandemic brought sudden economic devastation and forced countries to respond with policies to counter the looming economic crisis. What policy response do citizens prefer to combat an economic decline due to a pandemic? We study the preferences of citizens regarding economic policy and changes in these preferences as the pandemic unfolded in Denmark. Denmark passed early and comprehensive legislation with broad support from all political parties to counter the economic crisis caused by the pandemic. We employ a large nationally representative two-wave panel of Danish citizens (N = 12,131) drawn from the administrative registers, from which data was collected at the onset of the economic shock and immediately prior to economic recovery. In both waves the same subjects describe their preferred economic solution to COVID-19 in open-text format. We generate a simple dictionary method to uncover a set of distinct laymen economic policy responses. First, we find that citizens formulated a diverse set of policy interventions. Second, citizens become markedly stronger proponents of economic intervention as the crisis unfolded. Finally, we show how differences in economic preferences across partisanship vanished during the crisis.

Visualization-aided multi-criteria decision-making using interpretable self-organizing maps

In multi-criterion optimization, decision-makers (DMs) are not often interested in the complete Pareto-optimal front. Instead, they have preferences favoring specific parts of the front. Multi-criterion decision-making (MCDM) literature provides a plethora of approaches for introducing DM’s preference information in an interactive manner to solve multi-criterion optimization problems. Interactions with DMs can be aided with a user-friendly visualization method or by using special data analysis procedures. An earlier study has indicated the use of self-organizing maps (SOM) as a tool for analyzing Pareto-optimal solutions. In this paper, we demonstrate how a specific MCDM method – NIMBUS – can be executed with the interpretable SOM (iSOM) approach iteratively to arrive at one or more preferred solutions. A visual illustration of the entire high-dimensional search space into multiple reduced two-dimensional spaces allows DMs to have a better understanding of the interactions of the objectives and constraints independently, and execute the NIMBUS decision-making procedure with a more wholistic approach. The paper demonstrates the proposed method on a number of multi- and many-objective numerical and engineering problems. The approach is now ready to be integrated with other popular MCDM methods.

On the Design and Evaluation of an Optimal Security-and-Time Cognizant Data Placement for Dynamic Fog Environments

Fog Computing usefully extends Cloud to the edge of the network for the sake of meeting users’ expanding demand for low latency. However, due to its scattered distribution and open architecture, fog nodes are highly vulnerable to security threats, resulting in an inevitable sharp conflict between quick response time and high data security. This conflict motivates the need for effective data placement among fog nodes towards a trade-off between security and time. Existing studies merely offer independent solutions by considering either security or response time. By contrast, we establish a dynamic multi-objective optimization model in this article by optimizing security and response time simultaneously. With this model, we propose an efficient evolutionary algorithm, referred to as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Dynamic Interactive Security-and-Time cognizant algorithm</i> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DIST</i> ), to obtain optimal data placement strategies under Fog environments. To improve efficiency, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DIST</i> allows users to gradually incorporate their preference information into the search process so as to find their most preferred solutions without exploring the whole search space. We demonstrate the superiority of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DIST</i> by rigorous comparison with the most state-of-art data placement strategy and other well-applied strategies. Experimental results manifest that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DIST</i> outperforms other strategies in obtaining solutions with higher data security and shorter response time. Furthermore, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DIST</i> is capable of efficiently and continuously tracking the Pareto optimal solution under dynamically changing Fog environments while other existing strategies cannot.

Visualization and analysis of Pareto-optimal fronts using interpretable self-organizing map (iSOM)

Visualizing and analyzing multiple Pareto-optimal solutions obtained using an evolutionary multi- or many-objective optimization algorithm is as important a task as the task of finding them. Besides helping to choose a single preferred solution, they provide a better understanding of the trade-off among the objectives and also reveal key insights about interactions among variables and objectives for the Pareto-optimal solutions. Existing visualization methods do not provide a comprehensive account of both visualization and analysis of Pareto-optimal solutions. In this paper, we present an interpretable self-organizing map (iSOM) method that produces a more simplistic mapping of higher-dimensional variable spaces into two dimensions. Multiple iSOM plots, one for each objective, allows an easier visual understanding of trade-off among objectives. By identifying high trade-off Pareto-optimal solutions and marking them on the iSOM plots, we also provide decision-makers a comprehensive method to locate critical and likely preferred solutions on the Pareto-optimal front. The visualization and analysis of Pareto-optimal solutions using iSOMs are demonstrated on 11 problems involving three to five objectives. As discussed, the approach is generically applicable to higher-dimensional and constrained problems.

The Weights Can Be Harmful: Pareto Search versus Weighted Search in Multi-objective Search-based Software Engineering

In presence of multiple objectives to be optimized in Search-Based Software Engineering (SBSE), Pareto search has been commonly adopted. It searches for a good approximation of the problem’s Pareto-optimal solutions, from which the stakeholders choose the most preferred solution according to their preferences. However, when clear preferences of the stakeholders (e.g., a set of weights that reflect relative importance between objectives) are available prior to the search, weighted search is believed to be the first choice, since it simplifies the search via converting the original multi-objective problem into a single-objective one and enables the search to focus on what only the stakeholders are interested in. This article questions such a “ weighted search first ” belief. We show that the weights can, in fact, be harmful to the search process even in the presence of clear preferences. Specifically, we conduct a large-scale empirical study that consists of 38 systems/projects from three representative SBSE problems, together with two types of search budget and nine sets of weights, leading to 604 cases of comparisons. Our key finding is that weighted search reaches a certain level of solution quality by consuming relatively less resources at the early stage of the search; however, Pareto search is significantly better than its weighted counterpart the majority of the time (up to 77% of the cases), as long as we allow a sufficient, but not unrealistic search budget. This is a beneficial result, as it discovers a potentially new “rule-of-thumb” for the SBSE community: Even when clear preferences are available, it is recommended to always consider Pareto search by default for multi-objective SBSE problems, provided that solution quality is more important. Weighted search, in contrast, should only be preferred when the resource/search budget is limited, especially for expensive SBSE problems. This, together with other findings and actionable suggestions in the article, allows us to codify pragmatic and comprehensive guidance on choosing weighted and Pareto search for SBSE under the circumstance that clear preferences are available. All code and data can be accessed at https://github.com/ideas-labo/pareto-vs-weight-for-sbse .

On neutrosophic multi-level multi-objective linear programming problem with application in transportation problem

In this research, we use the harmonic mean technique to present an interactive strategy for addressing neutrosophic multi-level multi-objective linear programming (NMMLP) problems. The coefficients of the objective functions of level decision makers and constraints are represented by neutrosophic numbers. By using the interval programming technique, the NMMLP problem is transformed into two crisp MMLP problems, one of these problems is an MMLP problem with all of its coefficients being upper approximations of neutrosophic numbers, while the other is an MMLP problem with all of its coefficients being lower approximations of neutrosophic numbers. The harmonic mean method is then used to combine the many objectives of each crisp problem into a single objective. Then, a preferred solution for NMMLP problems is obtained by solving the single-objective linear programming problem. An application of our research problem is how to determine the optimality the cost of multi-objective transportation problem with neutrosophic environment. To demonstrate the proposed strategies, numerical examples are solved.

Biometric Recognition: A Systematic Review on Electrocardiogram Data Acquisition Methods.

In the last decades, researchers have shown the potential of using Electrocardiogram (ECG) as a biometric trait due to its uniqueness and hidden nature. However, despite the great number of approaches found in the literature, no agreement exists on the most appropriate methodology. This paper presents a systematic review of data acquisition methods, aiming to understand the impact of some variables from the data acquisition protocol of an ECG signal in the biometric identification process. We searched for papers on the subject using Scopus, defining several keywords and restrictions, and found a total of 121 papers. Data acquisition hardware and methods vary widely throughout the literature. We reviewed the intrusiveness of acquisitions, the number of leads used, and the duration of acquisitions. Moreover, by analyzing the literature, we can conclude that the preferable solutions include: (1) the use of off-the-person acquisitions as they bring ECG biometrics closer to viable, unconstrained applications; (2) the use of a one-lead setup; and (3) short-term acquisitions as they required fewer numbers of contact points, making the data acquisition of benefit to user acceptance and allow faster acquisitions, resulting in a user-friendly biometric system. Thus, this paper reviews data acquisition methods, summarizes multiple perspectives, and highlights existing challenges and problems. In contrast, most reviews on ECG-based biometrics focus on feature extraction and classification methods.

Rethinking unsupervised texture defect detection using PCA

In recent times, deep learning frameworks have become the preferred solution for visual object detection tasks, including texture defect detection. However, in real-world industrial applications, such as operation and maintenance of gas-insulated switchgear (GIS) equipment, collecting a large number of samples in advance is difficult because opening GIS equipment affects its normal operation; moreover, only four real-world GIS equipment defect samples are available currently. Most deep learning methods perform poorly when trained using a small number of labelled samples or when there is a lack of computational resources. In addition, the features extracted by multi-layer convolution and down-sampling are often unsuitable for small-size and low-contrast defects. However, the structure of the repetitive textured surface is simple and easy to model. Hence, this paper proposes a texture-defect detection method using principal components analysis (PCA) and histogram-based outlier score (HBOS) that requires only a small number of unlabelled samples and low computational complexity. First, PCA is utilized to extract features from the training patches to enhance the difference between the defect and background regions. Then, non-saliency suppression is applied for feature fusion to obtain the saliency map. Finally, the saliency value is converted to the defect score, and the defect is located by HBOS. Experiments on two public datasets and a GIS simulation equipment demonstrate that the proposed method is suitable for product surface defect detection and operation and maintenance in power distribution equipment. Moreover, compared with traditional texture feature-based and deep learning methods, the proposed method yields better results for small-size and low-contrast defects with only four unlabelled training samples per class.

Dynamic Traction of Deep-Sea Polymetallic Nodule Collector

The ocean is extremely rich in mineral resources. To cope with the shortage of land mineral resources, countries are focusing on the development of deep-sea mineral mining technology. Owing to its superior traction performance, the deep-sea polymetallic nodule collector (DPNC) has become the preferred solution for ocean mining. This paper proposes a dynamic traction calculation model to address the shortcomings in the classical static traction calculation model with consideration of the dynamic variation rule of grouser–soil interaction in the DPNC process. Lab tests were conducted to formulate materials similar to deep-sea soil, and the corresponding shear stress–displacement models were established using the discrete element method (DEM) and Magic Formula to describe the “shear stress–displacement” relationship more accurately. Considering Kunlong 500, which is a Chinese DPNC, as an example, the periodicity and dynamics of the dynamic traction force were analyzed and compared with the numerical simulation results. The dynamic traction force was smaller than the static traction force and fluctuated significantly when considering the dynamic grousers–soil interaction. The magnitude and fluctuation of the dynamic traction force were influenced by the ratio of the grouser height to the spacing. In the DPNC design, the ratio of the grouser height to the spacing should be optimized according to the properties of the deep-sea subsoil to improve the traction performance and stability of the DPNC.

Recent Experience in the use of Del Nido Cardioplegic Solution in Pediatric Patients

Background: The interest in Del Nido cardioplegia for myocardial protection in pediatric cardiac surgery is growing. Research hitherto supports the use of Del Nido cardioplegia in providing myocardial preservation as well as reducing surgery time. Objectives: To contribute to the literature, we sought to share our own experiences and outcomes of 86 pediatric patients who underwent cardiac surgery at our centre in whom this cardioplegic solution was used. Methods: In a retrospective study, we evaluated 86 pediatric patients with congenital cardiac defects who underwent corrective cardiac surgery in whom Del Nido cardioplegic solution was used. Results: The mean age of the patients was 55.1±48.6 months and the mean weight was 16.2±11.4 kilograms. Repair of tetralogy of Fallot and closure of atrial septal defect or ventricular septal defect represented 44% of the operations. Mean cross clamp time was 75.5±38.6 minutes. In five patients (5.8%), cardioversion defibrillation was used to regain sinus rhythm after cross clamp release. Only one patient needed inotropic support grade 3 (epinephrine dose equal or more than 0.1mcg/kg/min), while the remainder were in grade 2 or less. Conclusion: We think that the use of Del Nido cardioplegia in our patients was associated with clinical benefits and decreased morbidity. It can provide appropriate myocardial protection for longer cross clamp times with decreased repeat dosing. However, the preferred cardioplegic solution in congenital cardiac surgery remain highly variable among centers.

Optimal design of electric machine with efficient handling of constraints and surrogate assistance

An optimal electric machine design task can be posed as a constrained multi-objective optimization problem. While the objectives require time-consuming finite element analysis, constraints, such as geometric constraints, can often be based on mathematical expressions. This article investigates this mixed computationally expensive optimization problem and proposes a computationally efficient optimization method based on evolutionary algorithms. The proposed method always generates feasible solutions by using a generalizable repair operator and also addresses time-consuming objective functions by incorporating surrogate models for their prediction. The article successfully establishes the superiority of the proposed method over a conventional optimization approach. This study demonstrates how a complex engineering design task can be optimized efficiently for multiple objectives and constraints requiring heterogeneous evaluation times. It also shows how optimal solutions can be analysed to select a single preferred solution and harnessed to reveal vital design features common to optimal solutions as design principles.

Controlling the Modal Confinement in Silicon Nanophotonic Waveguides through Dual‐Metamaterial Engineering

AbstractFlexible control of the modal confinement in silicon photonic waveguides is an appealing feature for many applications, including sensing and hybrid integration of active materials. In most cases, strip waveguides are the preferred solution to maximize the light interaction with the waveguide surroundings. However, the only two degrees of freedom in Si strip waveguides are the width and thickness, resulting in limited flexibility in evanescent field control. Here, a new strategy that exploits metamaterial engineering of the waveguide core and cladding is proposed and demonstrated to control the index contrast in the vertical and horizontal directions, independently. The proposed dual‐material geometry yields a substantially increased calculated bulk sensitivity in the air (0.35 RIU [refractive index unit]/RIU) compared to the best case scenario for a strip waveguide (0.3 RIU/RIU). To experimentally demonstrate the potential of this approach, dual‐metamaterial ring resonators operating with the transverse‐magnetic polarized mode in 220‐nm‐thick waveguides with air as upper‐cladding are implemented. Micro‐ring resonators implemented with strip and dual‐metamaterial waveguides exhibit the same measured quality factors, near 30 000. Having similar measured quality factors and better calculated bulk sensitivity than strip waveguides, the proposed dual‐metamaterial geometry stands as a promising approach to control modal confinement in silicon waveguides.