Multilevel Implementations Research Articles

What shapes implementation of a school-based makerspace? Teachers as multilevel actors in STEM reforms

BackgroundWe investigate the factors that shape teachers’ implementation of a school STEM reform—the creation of a high-school makerspace. Educational reformers have increasing interest in making and makerspaces in schools. Prior research shows how factors shape reform at the classroom, school (organizational), and institutional levels, as well as across levels. However, most research on teachers tends to focus on classroom-level effects, which may not capture the full complexity of how they navigate multilevel reforms. We consider teachers’ decision-making from an ecological perspective to investigate what shapes their implementation efforts, using observational and interview data collected over 2 years in a large comprehensive high school.ResultsWe find teachers’ efforts are shaped by four “distances”—or spaces teachers traversed, physically and conceptually—related to skillsets and distributed expertise, physical space, disciplinary learning, and structural factors. The distances operate as a constellation of factors—independently identifiable, co-operatively manifesting—to shape implementation. We position teacher deliberations and decision-making as portals into the forms of organizational and institutional supports offered in multilevel reforms.ConclusionsThe paper contributes insights into makerspace implementation in schools, adding to the emerging literature on how making can transform STEM learning experiences for students. We conclude that teachers’ decision-making around multilevel implementations can inform our understanding of how makerspaces are implemented and their impact on students’ experiences, as well as how seeing teachers as multilevel actors can offer new insights into reform dynamics writ large. We offer implications for makerspaces in schools, as well as methodological and theoretical considerations for how organizations and institutions can better support teachers as agents of STEM reform.

Roadmaps to Foster Urban Food System Transitions: Multi-level Implementations in Nilüfer, Turkey

The ongoing crisis has shown that incumbent food system has been facing challenges. For a resilient and sustainable food system, transitions which shift towards sustainability, attention to public health and wellbeing as well as inclusiveness is compulsory. To overcome these challenges, driving a stepwise policy transformation, responsive and adaptive policy mixes and addressing citizens to drive sustainability are pivotal. This article represents two roadmaps which are designated for Nilüfer, Bursa. The roadmaps aim at including policy headlines/priorities as well as local needs and plural variations of collectivity to ensure a sustainable food system transition. The roadmaps are composed of two scalar levels one of which is macro-level; Nilüfer Food Policy Roadmap while the other is micro-level; Nilüfer Living Lab Roadmap

The Concept of Effective Organization for Quality Performance of Public Administration: For New Democracies

The article considers a possible public administration performance measurement regarding to political organization situation in Croatia. The first performance measurement problem comes from multilevel responsibility and co-production implementations. Second comes with emergence of multilevel products origin. Thirdly, state is very open and integrated in the EU and globalization influence. Therefore, it is crucially important to identify products and the evaluation indicators of the public administration, according with the public goals and social values. The article considers the performance measurement and management methodological at an organizational frame and it also considers the social values influence on a methodology and the role of the public administration in fulfilment of the public policy. Finally, effective organization possible could be built and improved by measuring effectiveness. The paper has tried to show the public service complexity work and the purpose, but first of all the importance public administration for achieving public goals.

SAT-Based Generation of Optimum Circuits with Polymorphic Behavior Support

This paper presents a method for generating optimum multi-level implementations of Boolean functions based on Satisfiability (SAT) and Pseudo-Boolean Optimization (PBO) problems solving. The method is able to generate one or enumerate all optimum implementations, while the allowed target gate types and gates costs can be arbitrarily specified. Polymorphic circuits represent a newly emerging computation paradigm, where one hardware structure is capable of performing two or more different intended functions, depending on instantaneous conditions in the target operating environment. In this paper we propose the first method ever, generating provably size-optimal polymorphic circuits. Scalability and feasibility of the method are documented by providing experimental results for all NPN-equivalence classes of four-input functions implemented in AND–Inverter and AND–XOR–Inverter logics without polymorphic behavior support being used and for all pairs of NPN–equivalence classes of three-input functions for polymorphic circuits. Finally, several smaller benchmark circuits were synthesized optimally, both in standard and polymorphic logics.

General multilevel adaptations for stochastic approximation algorithms of Robbins–Monro and Polyak–Ruppert type

In this article we present and analyse new multilevel adaptations of classical stochastic approximation algorithms for the computation of a zero of a function $$f:D \rightarrow {{\mathbb {R}}}^d$$ defined on a convex domain $$D\subset {{\mathbb {R}}}^d$$ , which is given as a parameterised family of expectations. The analysis of the error and the computational cost of our method is based on similar assumptions as used in Giles (Oper Res 56(3):607–617, 2008) for the computation of a single expectation. Additionally, we essentially only require that f satisfies a classical contraction property from stochastic approximation theory. Under these assumptions we establish error bounds in pth mean for our multilevel Robbins–Monro and Polyak–Ruppert schemes that decay in the computational time as fast as the classical error bounds for multilevel Monte Carlo approximations of single expectations known from Giles (Oper Res 56(3):607–617, 2008). Our approach is universal in the sense that having multilevel implementations for a particular application at hand it is straightforward to implement the corresponding stochastic approximation algorithm.

Implementing a multilevel prevention strategy under an intersectoral partnership: The case of the Triple P Program

The use of so-called “multilevel” strategies to prevent child maltreatment and behavior and emotional problems in children is increasingly being promoted by experts in the early childhood education and intervention field. These approaches aim to cover the needs of an entire population with different levels of interventions addressing specific needs. Although these strategies have gained in popularity, few studies have explored the processes involved in implementing these strategies. The present study contributes to addressing gaps in the implementation science literature by documenting the implementation process of a multilevel prevention program by an intersectoral partnership as perceived by staff managers and practitioners. Specific objectives were to describe the experiences of the actors involved in the implementation process, and to determine the extent to which the actual implementation process aligned with the theoretical model on which the implementation was based. Data were obtained from qualitative interviews with implementation coordinator, program managers and front-line practitioners that were analyzed using a thematic approach. Findings support in some ways the conceptualization of the implementation model used while also helping to refine that model by suggesting certain dynamics that might inhere in complex, multilevel implementations based on intersectoral partnerships. Our findings thereby contribute to advancing the empirical understanding of the conditions for implementing multilevel prevention programs in the context of intersectoral partnerships.

A novel fully automatic multilevel thresholding technique based on optimized intuitionistic fuzzy sets and tsallis entropy for MR brain tumor image segmentation.

In the present paper, a hybrid multilevel thresholding technique that combines intuitionistic fuzzy sets and tsallis entropy has been proposed for the automatic delineation of the tumor from magnetic resonance images having vague boundaries and poor contrast. This novel technique takes into account both the image histogram and the uncertainty information for the computation of multiple thresholds. The benefit of the methodology is that it provides fast and improved segmentation for the complex tumorous images with imprecise gray levels. To further boost the computational speed, the mutation based particle swarm optimization is used that selects the most optimal threshold combination. The accuracy of the proposed segmentation approach has been validated on simulated, real low-grade glioma tumor volumes taken from MICCAI brain tumor segmentation (BRATS) challenge 2012 dataset and the clinical tumor images, so as to corroborate its generality and novelty. The designed technique achieves an average Dice overlap equal to 0.82010, 0.78610 and 0.94170 for three datasets. Further, a comparative analysis has also been made between the eight existing multilevel thresholding implementations so as to show the superiority of the designed technique. In comparison, the results indicate a mean improvement in Dice by an amount equal to 4.00% (p < 0.005), 9.60% (p < 0.005) and 3.58% (p < 0.005), respectively in contrast to the fuzzy tsallis approach.

A Real-Time Multiaperture Omnidirectional Visual Sensor Based on an Interconnected Network of Smart Cameras

Centralized and multilevel implementations of the Panoptic omnidirectional multiaperture visual system were previously presented by us, relying on the transmission of all camera outputs to a single central processing node for omnidirectional image and video reconstruction. In this paper, a novel distributed and parallel implementation of the omnidirectional vision reconstruction algorithm of the Panoptic system is presented. The parallel approach aims to overcome the scalability problems and memory bandwidth limitations of the centralized approach. The real-time hardware implementation is presented for camera modules with image processing, memory, and interconnectivity features. A methodology is introduced for the arrangement of camera modules with interconnectivity feature into a target interconnection network topology. A unique custom-made multiple-field-programmable gate array hardware platform is introduced for the implementation of an interconnected network of 49 camera prototype Panoptic system. A hardware architecture based on presented hardware platform enabling the real-time implementation of the blending algorithms is presented, along with the imaging results and resource utilization. The real-time implementation results of the implemented omnivision application on the mentioned prototype are demonstrated.

Discrete Complex Image Method With Spatial Error Criterion

Since its first inception, the discrete complex image method (DCIM) has been criticized for the lack of a proper prediction algorithm of the error incurred during the process. Although the method has been improved and modified several times, not being able to input any prior specification or to get any meaningful assessment on the error deters computer-aided design developers and engineers from using it in the development of commercial software and in-house simulation tools. To remedy this shortcoming of the otherwise very popular DCIM, a weighted p -norm of the spatial-domain error is defined, and its mapping to the spectral domain is derived and proposed as the metric to be used in the implementation of the DCIM. Once this metric is incorporated into the latest three-level DCIM algorithm, used for the approximation of the spatial-domain Green's functions, it is observed that the weighted error-energy minimization in the spectral domain becomes equivalent to the one in the spatial domain. In addition to introducing an error criterion to the DCIM, the leakage problem, which is inherent to the semi-independent processing of subregions in multilevel implementations of the DCIM, is also addressed and eliminated, resulting in a further improvement of the algorithm and the end result.

Nonuniform grid algorithm for fast calculation of magnetostatic interactions in micromagnetics

A nonuniform grid (NG) algorithm for rapidly computing magnetostatic field for micromagnetic simulations is described. The algorithm relies on spatial NG representation of the potential from the source boxes and local interpolation. Multilevel implementations of the algorithm result in a linear computational complexity with respect to the number of effective magnetic charges and observers. The algorithm is highly adaptive with respect to structure’s geometry, i.e., it becomes automatically faster for low dimensional configurations such as quasiplanar bit patterned medium arrays.

Higher order hierarchical discretization scheme for surface integral equations for layered media

This paper presents an efficient technique for the analysis of electromagnetic scattering by arbitrarily shaped perfectly conducting objects in layered media. The technique is based on a higher order method of moments (MoM) solution of the electric field, magnetic field, or combined-field integral equation. This higher order MoM solution comprises higher order curved patches for the geometry modeling and higher order hierarchical basis functions for expansion of the electric surface current density. Due to the hierarchical property of the basis functions, the order of the expansion can be selected separately on each patch depending on the wavelength in the layer in which the patch is located and the size of the patch. In this way, a significant reduction of the number of unknowns is achieved and the same surface mesh can be reused in a wide frequency band. It is shown that even for fairly large problems, the higher order hierarchical MoM requires less memory than existing fast multipole method (FMM) or multilevel FMM implementations.

TOP: an algorithm for three-level combinational logic optimisation

Three-level logic is shown to have a potential for reducing the area over two-level implementations, as well as for a gain in speed over multilevel implementations. A heuristic algorithm TOP is presented, targeting a three-level logic expression of type g1∘g2, where g1 and g2 are sum-of-products expressions and ‘∘’ is a binary operation. For the first time, to the authors&apos; knowledge, this problem is addressed for an arbitrary operation ‘∘’, although several algorithms for specified cases of ‘∘’ have been presented in the past. The experimental results show that, on average, the total number of product-terms in the expression obtained by TOP is about one third of the number of product-terms in the expression obtained by a two-level AND–OR minimiser.

Synthesis for logical initializability of synchronous finite-state machines

Logical initializability is the property of a gate-level circuit whereby it can be driven to a unique start state when simulated by a three-valued (0, 1, X) simulator. In practice, commercial logic and fault simulators often require initialization under such a three-valued simulation model. In this paper, the first sound and systematic synthesis method is proposed to ensure the logical initializability of synchronous finite-state machines. The method includes both state assignment and combinational logic synthesis steps. It is shown that a previous approach to synthesis-for-initializability, which uses a constrained state assignment method, may produce uninitializable circuits. Here, a new state assignment method is proposed that is guaranteed correct. Furthermore, it is shown that combinational logic synthesis also has a direct impact on initializability; necessary and sufficient constraints on combinational logic synthesis are proposed to guarantee that the resulting gate-level circuits are logically initializable. The above two synthesis steps have been incorporated into a computer-aided design tool, SALSIFY, targeted to both two-level and multilevel implementations.

Parallel integer relation detection: Techniques and applications

Let { x 1 , x 2 , ⋯ , x n } \{x_1, x_2, \cdots , x_n\} be a vector of real numbers. An integer relation algorithm is a computational scheme to find the n n integers a k a_k , if they exist, such that a 1 x 1 + a 2 x 2 + ⋯ + a n x n = 0 a_1 x_1 + a_2 x_2 + \cdots + a_n x_n= 0 . In the past few years, integer relation algorithms have been utilized to discover new results in mathematics and physics. Existing programs for this purpose require very large amounts of computer time, due in part to the requirement for multiprecision arithmetic, yet are poorly suited for parallel processing. This paper presents a new integer relation algorithm designed for parallel computer systems, but as a bonus it also gives superior results on single processor systems. Single- and multi-level implementations of this algorithm are described, together with performance results on a parallel computer system. Several applications of these programs are discussed, including some new results in mathematical number theory, quantum field theory and chaos theory.

Low-power state assignment targeting two- and multilevel logic implementations

The problem of minimizing power consumption during the state encoding of a finite-state machine is addressed. A new power cost model for state encoding is proposed, and encoding techniques that minimize this power cost for two- and multilevel logic implementations are described. These techniques are compared with those that minimize area or the switching activity at the present state bits. Experimental results show significant improvements.

Factorizing FSM's with modify and restore method

Implementation of large finite-state machines (FSMs) as smaller interacting machines, by factorizing them and interconnecting the factored and factoring FSM's in such a way so as to maintain the functionality of the original machine usually leads to an improvement in the performance (that is, reduction in delay) of the original machine. Exact factors, if present in an FSM, can result in the most effective way of factorization. However, it has been found that most of the FSMs are not exact factorizable. In this paper, we have presented a scheme called the modify and restore (MAR) method which attempts to make FSMs exact factorizable even if the original FSM is not directly exact factorizable. This is done by making minor changes in the next state space of the original FSM while maintaining the functionality of the FSM by a restoring logic. We have tested the effectiveness of our method of factorization followed by state assignment for both two-level and multilevel implementations. Experimental results on the MCNC benchmark examples have shown significant improvement in delays of the final realization.

Synthesis of hazard-free multilevel logic under multiple-input changes from binary decision diagrams

We describe a new method for directly synthesizing a hazard-free multilevel logic implementation from a given logic specification. The method is based on free/ordered Binary Decision Diagrams (BDD's), and is naturally applicable to multiple-output logic functions. Given an incompletely-specified (multiple-output) Boolean function, the method produces a multilevel logic network that is hazard-free for a specified set of multiple-input changes. We assume an arbitrary (unbounded) gate and wire delay model under a pure delay (PD) assumption, we permit multiple-input changes, and we consider both static and dynamic hazards under the fundamental-mode assumption. Our framework is thus general and powerful. While it is not always possible to generate hazard-free implementations using our technique, we show that in some cases hazard-free multilevel implementations can be generated when hazard-free two-level representations cannot be found. This problem is generally regarded as a difficult problem and it has important applications in the field of asynchronous design. The method has been automated and applied to a number of examples. >

FSM fault models impact on test performances

Aim of this paper is the analysis of different functional fault models for multi-level implementations of sequential circuits. The relationships between functional and gate level fault coverage are fully discussed.

A functional fault model for sequential machines

A fault model at the state transition level is proposed for finite state machines. In this model, a fault causes the destination state of a state transition to be faulty. Analysis shows that a test set that detects all single-state-transition (SST) faults will also detect most multiple-state-transition (MST) faults in practical finite state machines. The quality of the test set generated for SST faults is close to that of the sequences derived from the checking experiment. It is also shown that the upper bound of the length of the SST fault test is 2MN/sup 2/ for an N-state M-transition machine, while that of the checking sequence is exponential. An automatic test generation algorithm and a test generation system, FTG, based on the model show that the test set generated for SST faults achieves high single stuck-at-fault coverage as well as high transistor fault coverage for multilevel implementations of the machine.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Optimum and suboptimum algorithms for input encoding and its relationship to logic minimization

A novel theoretical formulation of the input encoding problem is presented, based on the concept of compatibility of dichotomies. The input encoding problem is shown to be equivalent to a two-level logic minimization. Three possible techniques to solve the encoding problem are discussed, based on: techniques borrowed from classical logic minimization (generation of prime dichotomies and solving the covering problem); graph coloring applied to the graph of incompatibility of dichotomies; and extraction of essential prime dichotomies followed by graph coloring. The extraction of essential prime dichotomies serves the same purpose as the extraction of essential prime implicants in logic minimization, in the sense that it reduces the size of the covering/graph coloring problem. The conditions of optimality of the solutions to the input encoding problem are discussed. For near-optimum results a powerful heuristic, based on an iterative improvement technique, has been developed and implemented as a computer program: dichotomy-based symbolic input encoding technique (DIET). The test results indicate the DIET compares favorably with KISS and NOVA in terms of the CPU time, is superior to both programs in terms of the encoding length, and requires considerably less memory. This method can be applied to the input encoding of combinational logic and the state assignment of finite state machines (FSMs) in both two-level and multilevel implementations. >