Inductive Schemes Research Articles

Dynamic Lane Assignment and Signal-Timing Collaborative Optimization Considering the Effect of Lane Switching

Dynamic lane assignment (DLA) is an effective method to improve traffic flow and optimize urban road resources. However, lane switching can disrupt traffic under dynamic control due to clearance time and driving characteristics. Traditional rule-based methods hinder the selection of optimal schemes for DLA systems. On-site data analysis shows that lane switching increases saturated headway by 18.4% and reduces lane group utilization by 17.8% compared to fixed lanes in the same direction. To address these challenges, this study proposes an optimization method that integrates DLA and signal timing, considering the impact of lane switching. The proposed model aims to minimize total delay at intersections by optimizing the number and timing of lane switches within a given interval. Case studies and extensive numerical analyses demonstrate that the proposed method outperforms the rule-based approach, reducing total intersection delay by 1.91%. Additionally, the average number of lane switches decreases by 13.8%, reducing safety risks associated with frequent lane switching. Sensitivity analysis reveals the superiority of the proposed method when the utilization rate of variable lanes is below 0.4 and the saturated headway caused by lane switching exceeds 2.9 seconds. Moreover, the proposed method outperforms inductive and adaptive control schemes when the traffic flow deviation coefficient is less than 0.3. This makes it suitable for implementation in cities where drivers have limited experience with variable lanes during the initial stage, when historical and real-time data are more consistent. Overall, the proposed method offers significant improvements in traffic flow efficiency and safety in DLA systems.

Classifying flow regimes of the Amazon basin

Abstract The Amazon River basin contains a vast diversity of lotic habitats and accompanying hydrological regimes. Further understanding the spatial distribution of flow regimes across the Amazon can be useful for recognizing riverine ecohydrological processes and informing river management and conservation, especially in areas with limited or inconsistent streamflow monitoring. This study compares four inductive approaches for classifying streamflow regimes across the Amazon using an unprecedented compilation of streamflow records from Bolivia, Brazil, Colombia, Ecuador, and Peru. Inductive classification schemes use attributes of streamflow data to categorize river reaches into similar classes, which then may be generalized to understand streamflow behaviour at the basin scale. In this study, classification was accomplished through hierarchical clustering of 67 flow metrics calculated using indicators of hydrologic alteration (IHA) and daily streamflow data from median annual hydrographs (MAHs) for 404 stations (representing >7,000 station‐years) across five Amazonian countries. Classification was performed using both flow magnitude‐inclusive and flow magnitude‐independent datasets. For flow magnitude‐independent methods, optimal solutions included six or seven primary hydrological classes for IHA and MAH datasets; for approaches that retained magnitude, variance was sufficiently large to prevent convergence to a specific number of classes. Across methods, class membership was strongly associated with the timing, frequency, and rate of change of flow, and spatially coherent clusters were associated with seasonal, elevational, and stream‐order gradients. These results highlight the diversity of flow regimes across the Amazon and provide a framework for studying relationships between hydrological regimes and ecological responses in the context of changing climate, land use, and human‐induced hydrological alteration. The methodology applied provides a data‐driven approach for classifying flow regimes based on observed data. When coupled with ecological knowledge and expertise, these classifications can be used to develop ecohydrologically informed and management‐relevant conservation practices.

Technologies and Applications of Angle Sensors: A Review

This paper presents a critical review of advancements made in the area of non-contact angle sensing in the last two decades. Angular position sensing is an essential function in most of the engineering systems associated with industries such as automotive, robotics, process, and aircraft. The review shows significant progress that has been achieved in the performance aspects of angle sensors, overcoming the challenges introduced by new and specific applications. Progress is also visible in effectively utilizing the emerging allied technologies on the sensing and electronics field for the development of high-end angle sensors. As a part of the review, the important sensing techniques utilized for the angle sensors are identified and carefully looked at the advantages and limitations of those. Besides, the potential areas for improvements are also suggested. The important techniques employed to design and develop the angle sensors are based on capacitive, inductive, magneto-resistive, and optical schemes. Signal conditioning circuits, analog or digital, or a combination of it, are necessary to derive the best from the sensing elements. They play a vital role in the overall performance of the sensor. The review addresses the advancement in the sensing element, methodology, and signal conditioning aspect in detail. In this review, the important angle sensors reported are evaluated against the performance parameters such as range, resolution, linearity, accuracy, sensitivity, power consumption, complexity, cost, manufacturability, and reliability.

Sideband-resolved resonator electromechanics based on a nonlinear Josephson inductance probed on the single-photon level

Light-matter interaction in optomechanical systems is the foundation for ultra-sensitive detection schemes as well as the generation of phononic and photonic quantum states. Electromechanical systems realize this optomechanical interaction in the microwave regime. In this context, capacitive coupling arrangements demonstrated interaction rates of up to 280 Hz. Complementary, early proposals and experiments suggest that inductive coupling schemes are tunable and have the potential to reach the single-photon strong-coupling regime. Here, we follow the latter approach by integrating a partly suspended superconducting quantum interference device (SQUID) into a microwave resonator. The mechanical displacement translates into a time varying flux in the SQUID loop, thereby providing an inductive electromechanical coupling. We demonstrate a sideband-resolved electromechanical system with a tunable vacuum coupling rate of up to 1.62 kHz, realizing sub-aN Hz−1/2 force sensitivities. The presented inductive coupling scheme shows the high potential of SQUID-based electromechanics for targeting the full wealth of the intrinsically nonlinear optomechanics Hamiltonian.

Resonant inductive displacement sensor for active magnetic bearings

This paper presents a resonant inductive sensor for radial displacement in Active Magnetic Bearing (AMB) systems. The device consists of a wire coil wound around a tooth of a conventional eight-pole radial actuator of the bearing. The proposed device is different from standard inductive sensor schemes since the sensing coil is excited by the electromagnetic field generated by the actuation coil and not by an external oscillator. The electromagnetic flux linked by the sensing coil is a function of the distance between the sensor and the levitated object whose position has to be measured. The output measurement voltage is amplified by means of an electric resonator circuit obtained by installing a capacitor on the terminals of the sensing coil. A qualitative model is developed and compared to an experimental apparatus. This model captures well the sensing phenomenon and can be used for designing such a sensor. The proposed device demonstrates good properties of resolution and sensitivity with a small and low-cost layout. Additionally, such sensor allows obtaining an inherent sensor/actuator collocation along the longitudinal direction of rotors, which is an advantage in AMB systems for rotating machinery since it allows simplifying the layout and avoiding instability problems.

Student Teachers’ Proof Schemes on Proof Tasks Involving Inequality: Deductive or Inductive?

Exploring student teachers’ proof ability is crucial as it is important for improving the quality of their learning process and help their future students learn how to construct a proof. Hence, this study aims at exploring at the proof schemes of student teachers in the beginning of their studies. Data were collected from 130 proofs resulted by 65 Indonesian student teachers on two proof tasks involving algebraic inequality. To analyse, the proofs were classified into the refined proof schemes level proposed by Lee (2016) ranging from inductive, which only provides irrelevant inferences, to deductive proofs, which consider addressing formal representation. Findings present several examples of each of Lee’s level on the student teachers’ proofs spanning from irrelevant inferences, novice use of examples or logical reasoning, strategic use examples for reasoning, deductive inferences with major and minor logical coherence, and deductive proof with informal and formal representation. Besides, it was also found that more than half of the students’ proofs coded as inductive schemes, which does not meet the requirement for doing the proof for the proof tasks examined in this study. This study suggests teacher educators in teacher colleges to reform the curriculum regarding proof learning which can accommodate the improvement of student teachers’ proving ability from inductive to deductive proof as well from informal to formal proof.

Symmetric Isostatic Frameworks with $\ell^1$ or $\ell^\infty$ Distance Constraints

Combinatorial characterisations of minimal rigidity are obtained for symmetric $2$-dimensional bar-joint frameworks with either $\ell^1$ or $\ell^\infty$ distance constraints. The characterisations are expressed in terms of symmetric tree packings and the number of edges fixed by the symmetry operations. The proof uses new Henneberg-type inductive construction schemes.

Special issue: Highlights from the flagship Latin American Symposium on Circuits and Systems: selected papers from LASCAS 2013

It is a pleasure and a privilege to present to the readers of the Springer Journal on Analog Integrated Circuits and Signal Processing (ALOG) a selection of the papers from the 4th edition of the Latin America Symposium on Circuits and Systems—LASCAS 2013, held in February 2013 in the historical Peruvian city of Cuzco. The LASCAS Symposium is the premier event in circuits and systems in that region of the Americas. The papers selected by the Guest Editors fall in the focus of this Journal, and are among the 10 % top quality of the 155 papers submitted to LASCAS 2013, and were selected by rigorous reviewing. While LASCAS contemplates applications and digital systems, most of the papers in this Special Issue address analog circuits and systems, the themes of interest to ALOG Journal readers. From the 119 papers which were accepted and published in the IEEE LASCAS Proceedings, a total of 27 works were nominated and invited to submit a substantially improved manuscript on the same subject to this Special Issue of LASCAS 2013. The quality screening took advantage of the reviews and paper ratings for each of those 119 papers, which were narrowed down to 23 extended manuscripts. These went through a second-round of peer-review process and 14 papers, substantially extended versions from the LASCAS Symposium, were finally selected for this Special Issue, as the highlights from the flagship Latin American Symposium on Circuits and Systems. The papers in this Special Issue come from the Americas (North and South) and Europe. The 14 selected papers cover a wide range of topics, from analog circuits design at ultra-low voltages, to amplifiers design, integrated circuits, wireless, and digital systems design, and up to topics at the application of communications and arithmetic circuits. The first 3 papers in the Special Issue deal with low voltage analog CMOS design. The paper ‘‘Fully Integrated Inductive Ring Oscillators Operating at VDD below 2kT/ q’’ by M. Machado et alli presents oscillators with two inductive loading schemes to work under extremely low DC supplies. H. Hernandez et alli propose and show in their paper a silicon implementation of ‘‘A fully Integrated Boost Converter For Thermoelectric Energy Harvesting’’ which upconverts from very low voltage supplies. The paper ‘‘Sub-1 V Band-Gap Based and MOS ThresholdVoltage Based Voltage References in 0.13 lm CMOS’’ by D.M. Colombo et alli explores and compares low-voltage DC reference circuits with different circuit approaches possible in standard CMOS, compared to diode-based BGRs. Two papers on DC and instrumentation amplifiers designs target improvements on either DC gain or CMRR. H. Gomez-Ortiz introduces a ‘‘Robust to PVT Enhanced DC Gain Amplifier Using No Miller Capacitor Feedforward Compensation’’ in his paper, where a feedforward scheme improves DC gain and common mode range. C. Silva-Cardenas Maestria de Ingenieria de las Telecomunicaciones, Pontificia Universidad Catolica del Peru, Ave. Universitaria 1801, Lima 32, Peru e-mail: csilva@pucp.edu

Modelo aumentado de árbol de decisión utilizando mapas autoorganizados

A key aspect in the process of Knowledge Discovery in Databases (KDD), is the understandability and credibility of models generated by inductive learning schemes. This article explores the application of Self-Organizing Maps (SOM) technique on a model of decision tree, to achieve enhanced visualization of the model. Representations of visual perception model, together with data and patterns are established, based on a schema called VAM-MD, to support exploration and visual analysis efficiently during tuning stage for Data Mining Model. This seeks to answer generic questions about the inner workings of the model and to achieve better understanding. This proposal was implemented through a software prototype, where a set of visual elements may be applied to data from each node in the tree, appropriately selected to complement the visualization of the generated model. Additionally, the user has several mechanisms of interaction that enable for exploration of each component of the model. Finally, the results from a controlled experiment, conducted on two user groups who used the WEKA software and the experimental prototype, for a data mining task on a previously prepared data were analyzed. Preliminary analysis of the results obtained allow, on one hand empirically corroborate the utility of using the SOM technique to visually enhance a decision tree and on the other subjectively estimate their efficiency in supporting the understanding of the model generated.

Concepts of rational taxonomy in biology

Problems related to the development of concepts of rational taxonomy and rational classifications (taxonomic systems) in biology are discussed. A rational taxonomy is based on the assumption that the key characteristic of rationality is the deductive inference of certain partial judgments about the reality under study from other judgments taken as more general and a priori true. Two forms of rationality are distinguished: ontological and epistemological. The former implies the inference of classification properties from general (essential) properties of the reality being investigated. The latter implies the inference of partial rules about classification from more general (formal) rules. The following principal concepts of ontological-rational biological taxonomy are considered: the crystallographic approach; inference of the orderliness of organism diversity from the general laws of nature; and inference of the above orderliness from the orderliness of ontogenetic development programs, based on the concept of natural kind and Cassirer’s series theory, grounded in the systemic concept and the idea of periodic systems. Various concepts of ontological-rational taxonomy can be generalized by the idea of causal taxonomy; that is, any biologically sound classification is founded on a content-based model of biological diversity that includes an explicit indication of the general causes responsible for that diversity. It is asserted that each category of general causation and respective background model may serve as a basis for a particular ontological-rational system as a distinctive research program. Concepts of epistemologically rational taxonomy and classifications (taxonomic systems) can be interpreted in terms of the application of certain epistemological criteria of substantiation of the scientific status of the taxonomy in general and of taxonomic systems in particular. These concepts include consideration of taxonomy consistency from the standpoint of inductive and hypothetic-deductive argumentation schemes; such fundamental criteria of classifications’ naturalness as their prognostic capabilities; and the foundation of a theory of “general taxonomy” as a “general logic,” including elements of the axiomatic method. The latter concept constitutes the core of the program of general classiology; it is inconsistent due to the absence of anything like general logic. It is asserted that elaboration of a theory of taxonomy as a biological discipline, based on the formal principles of epistemological rationality, is not feasible. Instead, it must be elaborated as an ontological-rational one, based on biologically sound meta-theories about the causes of biological diversity.

Inductive schemes for the complete classification of affine hypersurfaces with parallel second fundamental form

We present in this article inductive schemes that allow to classify all those affine hypersurfaces with affine normal parallel second fundamental (cubic) form, for every possible dimensional case greater or equal than two. The solution proposed is a follow up to previous works on the same topic by this author and it uses, firstly, the reduction of the problem, eminently geometric, to the classification of a certain class of solutions to an equation of Monge-Ampere type. Then it is applied the so-called “method of algorithmic sequence of coordinate changes”, in order to achieve the latter.

Hamiltonian techniques for the problem of set‐membership state estimation

AbstractThe problem of filtering under unknown input disturbances is addressed with set‐membership bounds on the uncertain items. The possibility of solving this problem is considered using techniques of dynamic programming in continuous time via the related Hamilton–Jacobi–Bellman equations. The exact solutions to this problem, given in set‐theoretic terms as ‘information sets’, are expressed as level sets to the solutions of some specific types of the HJB equation which are given in two alternative versions. The suggested equations apply not only to the linear but also to the nonlinear case. However, in the nonlinear case the equations are especially difficult to calculate. This paper presents an alternative approach, based on a comparison principle that avoids exact solutions in favor of their upper and lower bounds, which in many cases may suffice for solving the required problems. For systems with linear structure the comparison principle yields a parameterized array of ellipsoidal estimates, which ensure tight approximations of the convex information sets. It also indicates a deductive scheme for deriving these estimates in contrast with the earlier inductive schemes. Copyright © 2010 John Wiley & Sons, Ltd.

Determining the tuning and matching requirements of RF coils using electromagnetic simulation and electric circuit analysis

Electromagnetic simulation using the transmission-line modelling method in conjunction with electric circuit analysis is applied to extract the tuning and matching requirements of RF coils for magnetic resonance imaging. Free-ringing microimaging RF coils were modelled in the unloaded and Krebs-Henseleit physiological buffer solution loaded condition. The simulations determined the frequency response and equivalent lumped-element circuit components of resistance, inductance, (fixed) capacitance, and coupling coefficient. Equivalent lumped-element electric circuit representations were derived for RF coils, and circuit analysis was applied to determine the tuning and matching requirements for the desired resonance frequency and characteristic impedance, respectively. Both capacitive and inductive matching schemes were considered. Experimental comparisons were performed with an agreement of less than 3 pF for the (variable) tuning and matching capacitances used in the tuning and matching networks, thus enabling component selection and validation of the methods. © 2005 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 25B: 27–41, 2005

A Material Theory of Induction

Contrary to formal theories of induction, I argue that there are no universal inductive inference schemas. The inductive inferences of science are grounded in matters of fact that hold only in particular domains, so thatall inductive inference is local.Some are so localized as to defy familiar characterization. Since inductive inference schemas are underwritten by facts, we can assess and control the inductive risk taken in an induction by investigating the warrant for its underwriting facts. In learning more facts, we extend our inductive reach by supplying more localized inductive inference schemes. Since a material theory no longer separates the factual and schematic parts of an induction, it proves not to be vulnerable to Hume's problem of the justification of induction.

On the assimilation of uncertain physical knowledge bases: Bayesian and non-Bayesian techniques

We study the assimilation of uncertain physical knowledge across space and time, and we discuss the resulting issues of environmental inference and prediction. The term “assimilation” refers to a general framework that includes physical knowledge integration and processing activities in a variety of scientific disciplines (atmospheric data analysis and weather forecasting, environmental pollution mapping, exposure assessment, etc.). The choice of an adequate assimilation approach is primarily a conceptual modelling affair that is supported by the physical and logical features of the environmental situation under consideration, rather than merely relying on pure inductive schemes and statistical arguments. In many cases, the assimilation approach involves conditionalization techniques which enable it to merge various forms of site-specific data with modelling frameworks. We distinguish between interpretive conditionalization (which refers to the physical and epistemic characteristics of assimilation modelling) and formal conditionalization (which is a purely mathematical construction), and emphasize the importance of an adequate choice of the latter to represent the former. We point out the considerable improvements of the operational Bayesian conditionalization approach over the standard Bayesian rule. Statistical learning techniques are useful at the descriptive/correlation level of scientific inquiry, whereas the level of explanation/prediction is the domain of advanced operational techniques. An operational approach is based on an epistemic view in which the relevant natural processes are represented in terms of spatiotemporal random fields and the probability laws are expressed in terms of physically meaningful operators. The spirit of this view is to keep the field solutions consistent with the site-specific information (hard data, uncertain observations, etc.) while exactly satisfying the constraints arising from general knowledge sources (physical laws, primitive equations, scientific theories, etc.). Natural field probabilities in space and time are derived for non-Bayesian operational conditionals based on deductively sound inference, which are valid for a wide variety of knowledge bases. Analytical and numerical comparisons are made between Bayesian and non-Bayesian conditionals, and insight is gained in terms of examples and applications which cut across various earth science disciplines. Operational Bayesian conditionalization is a powerful and versatile component of assimilation modelling with many applications in environmental sciences, although in certain cases a non-Bayesian conditional (based on deductive logic and the characterization of physical connection) may provide a meaningful description of the data assimilation framework suggested by the laws of nature.

Comparative Study of Two Neoadjuvant Protocols (VBM and DDP-BLM) Combined with Radiation Therapy in Advanced Head and Neck Cancer

Forty-five patients with epidermoid cancer of the head and neck were either treated with cisplatin and bleomycin (DDP-BLM) or with vincristine, bleomycin and methotrexate (VBM) as neoadjuvant chemotherapy before radical radiation therapy (XRT). Chemotherapy with DDP-BLM provided a tumoral response of 80% [20% complete response (CR), 60% partial response (PR)]; VBM showed a response of 60% (12% CR, 48% PR). At the end of XRT-program (65 Gy total dose, 2-2.5 Gy dose per fraction, 5 times a week) complete response rates were similar in VBM-pretreated group (52.5%) and DDP-BLM pretreated group (50%). Analysis of survival shows no significant difference between the two inductive schemes: 8% vs 7.5% at 72 months. Our study suggests an increased initial response rate but no advantage in survival with combined therapy in comparison with standard XRT: long-term benefits were not apparent in these two groups of patients.

Hypothetico-Deductive and Inductive Approaches in Ecology

Ecology is the study of living organisms and their environment in an attempt to explain, understand and predict. How is it, or how should it be, pursued? At the outset it is questionable whether any method or approach should be prescribed. Yet even the attacks 'against method' (e.g. Feyerabend, 1975) prescribe a method of sorts, namely that of no method. In any case, if 'anything goes, everything stays' or, by implication, all methods are of equal merit; it is a dubious argument. Therefore, of the approaches so far developed, which best produces knowledge of the kind ecologists seek? Is it possible to develop a guide to aid students and researchers in the planning and execution of their studies? Innumerable texts prescribe how to design an experiment and how to collect and analyse data. Only rarely is guidance offered on the selection of the type of broad approach to be used, on the nature of the inferences to be drawn and on the limitations or implications of these. Therefore, this article focuses on the broad approaches. At the risk of oversimplifying, the two approaches examined are the so-called hypothetico-deductive and inductive schemes. An ecologist's view of these schemes (their implications and limitations) is detailed below. But briefly, the hypothetico-deductive scheme implies collection and analysis of data to evaluate the truth of a priori hypotheses. Induction attempts to develop knowledge, generate hypotheses or derive general statements, from specific data. The present review is centred about a scheme illustrated in Fig. 1. While the scheme is intended to be helpful, it is not presumed to be definitive. Rather the aim is to provoke debate, in the spirit that how we conduct our ecology is no less important than the facts which it produces. It is hoped that use of the guide will lead to its improvement or even replacement and ultimately to ecology efficiently yielding explanation, understanding and predictive capability. For reasons of practical convenience, Fig. 1 is partitioned into hypothetico-deductive and inductive sections and these are considered in turn below. To aid the reader, the relevant steps in Fig. 1. are referred to in the course of the discussion.

Angular correlations in QCD

The quantum correlations between the azimuthal angels of jet production planes are calculated from QCD using a revised leading logarithm approximation for all tree diagrams up to and including five branchings. Two inductive schemes are also presented which allow these correlations to be investigated for an arbitrary number of branchings.

Performance Characteristics of a Pulse-Charging System

A prototype pulse-charging circuit has been developed consisting of high-voltage RF bursts superimposed onto a 60-Hz modulating field. The supply is connected to a four-electrode system that generates ac pulse corona. By selecting the burst initiation time, either positive or negative ions can be generated and transferred across an air gap of a few centimeters. The performance of the circuit has been determined by charging metal and glass spheres that have been mounted on insulated stalks. Variations have been made in the modulating field and burst characteristics to optimize the performance. Comparisons have been made between the pulse charger and inductive schemes which are available for the electrostatic levitation of objects. The pulse charger has been found to be more effective at corresponding voltages.

The graph-like state of matter. Part 2.—LCGI schemes for the thermodynamics of alkanes and the theory of inductive inference

The theory of graphs, a rapidly developing mathematical discipline, is immensely useful in chemistry. As first appreciated by Cayley (A. Cayley, Collected Mathematical Papers, Cambridge University Press, 1889–97), a molecule becomes a graph, when we regard atoms as points and bonds as lines. Theories based on this notion define a state of matter. Formally, they almost always equate measurable quantities to linear combinations of graph-theoretical invariants (LCGI).Using quite elementary concepts and terms of graph theory, a single systematic definition of about 50 words, contains as special cases, practically all that is useful in previously proposed additivity scheme for predicting standard thermodynamic data. For example, the bond additivity schemes, the schemes for alkanes by Allen, by Laidler and by Tatevskii are included as individual members of the set of schemes so defined, which constitute a canonical hierarchy of LCGI schemes.In this way, estimation of standard enthalpies of alkanes can be rationalised, and that of standard entropies substantially improved. This is exemplified with the aid of recent improvements in computer optimisation procedures. The theory of inductive inference, especially as developed by Carnap (R. Carnap, The Continuum of Inductive Methods, University of Chicago Press, 1952), is useful not merely in suggesting methods of economical and systematic construction of inductive schemes, but in assessing the validity of their postulational basis in the light of experimental data. The customary calculation from standard enthalpies of substantial destabilisation energies in the form of “steric corrections” is criticised as being biassed. It is doubted whether quantum theory had so far contributed significantly to results of analyzing enthalpy data on alkanes.