Equivalent Programming Research Articles

Web Conferencing Supports the Wake Tech High School Equivalency Program

The High School Equivalency Program (HEP) is a national initiative, funded by the U.S. Department of Education that helps migrant workers obtain high school equivalency diplomas. Wake Technical Community College?s HEP program recently transitioned to a fully online model supported by the use of the Adobe Connect web conferencing software, providing immediate benefits to both instructors and students. This paper provides a roadmap for other non-traditional educational programs that want to transition to online environments.

Pelatihan Pembuatan dan Pendampingan Penerapan Multimedia Genggam Si Dio (Camtasia Studio) Berbasis Android bagi Tutor PKBM di Kabupaten Kuningan

TRAINING ON MAKING AND MENTORING ANDROID-BASED APPLICATION OF HANDHELD SI DIO (CAMTASIA STUDIO) MULTIMEDIA FOR PKBM TUTORS IN KUNINGAN REGENCY. Equality education of study group Package C is one of the non-formal education programs for people’s equivalent to high school level. One of the problems faced in the learning process of Package C program held by PKBM Kuningan city is not maximize the use of learning media, especially in the field of technology. This community service activity will be held in PKBM Kuningan city which already has NPSN. The purpose of this training is to improve tutor skills in making and implementing learning by utilizing android-based smartphone as a medium of learning. The method of training implementation consists of several stages: training licensing, training preparation, preparation of training module book, Si Dio handheld multimedia training, mentoring of media usage already made by tutor. Based on the results of training and mentoring the application of handheld multimedia Si Dio based on android this can help improve and improve the quality of the process of Package C equivalence program and facilitate understanding even though learners learn independently.

Estimating lower probability bound of power system's capability to fully accommodate variable wind generation

As the penetration of wind generation increases, the uncertainty it brings has imposed great challenges to power system operation. To cope with the challenges, tremendous research work has been conducted, among which two aspects are of most importance, that is, making immune operation strategies and accessing the power system's capability to accommodate the variable energy. Driven and inspired by the latter problem, this paper will discuss the power system's capability to accommodate variable wind generation in a probability sense. Wind generation, along with its uncertainty is illustrated by a polyhedron, which contains prediction, risk, and uncertainty information. Then, a three-level optimisation problem is presented to estimate the lower probability bound of power system's capability to fully accommodate wind generation. After reformulating the inner max-min problem, or feasibility check problem, into its equivalent mixed-integer linear program (MILP) form, the bisection algorithm is presented to solve this challenging problem. Modified IEEE systems are adopted to show the effectiveness of the proposed method.

Selection of optimal transmit power in multi-hop underlay cognitive full-duplex relay networks

This paper investigates optimization of underlay multi-hop cognitive full-duplex relay (CogFDR) networks in independent non-identically distributed Rayleigh fading channels. First of all, analytical expressions for the outage probability experienced in the secondary network is formulated, taking into account (i) residual self-interference (RSI) arising due to full-duplex operation, (ii) inter-relay interference (IRI) arising due to frequency re-use, and (iii) interference generated by the primary transmitter on the secondary network. Optimal power allocation (OPA) that either minimizes the end-to-end outage probability or maximizes the end-to-end instantaneous rate is investigated with constraints on total available power in the secondary network and tolerable interference power at the primary receiver. The OPA vector for the outage minimization problem is obtained by solving an equivalent geometric programming problem (GPP) and that for the rate maximization problem is obtained by applying the rate balancing criterion for each hop. Extensive performance evaluations conducted with the help of Monte Carlo simulations show that transmit power optimization can improve the end-to-end rate and outage probability performance of multi-hop CogFDR network in comparison to equal power allocation on average (EPA).

Analysis of the Relationship between Ego Identity Status and Personality Traits and General Self-Efficacy with Structural Equation Modeling

In this study, it is aimed to investigate the partial mediating effect of ego identity status and personality traits on general self-efficacy levels of physical education and sports teacher candidates. To do that, a model showing possible relationships between these variables was established and this model was tested by using structural equation modeling. The sample of the study consisted of 578 students in the freshmen, sophomore, junior, and senior years in the Physical Education Sports Teaching Departments of universities Erciyes, Mehmet Akif, Dumlupinar, and Ahi Evran. The Socio-Demographic Information Form created by the researchers, General Self-Efficacy Scale adapted to Turkish by Aypay (2010), Ego Identity Status Scale adapted by Oskay (1998), and Eysenck Personality Questionnaire adapted to Turkish by Karancı et al. (2007) were used as the data collection tools. SPSS 22 program and Structural Equation Modeling/AMOS/Path Diagram program were used for data analysis. Firstly, the measurement models were tested and the proposed measurement model proved to be able to use to test the structural model. The structural model proposed based on the validated measurement models were then tested and verified. The fit indices of the model established in the study were found to be good and the coefficients obtained were found to be statistically significant. According to the results obtained about the structural model, it was found that there was a significant relationship between the general self-efficacy with ego identity status and personality traits, and that the ego identity status and personality traits predict the general self-efficacy in an advanced level.
 
 As a result, it is thought that the general self-efficacy levels of the students will increase with the positive development of ego identity status and personality traits, and this increase will enable the students to increase their academic achievement and self-confidence, as well as will make them more active in the society.

IMP with exceptions over decorated logic

In this paper, we facilitate the reasoning about impure programming languages, by annotating terms with “decorations” that describe what computational (side) effect evaluation of a term may involve. In a point-free categorical language, called the “decorated logic”, we formalize the mutable state and the exception effects first separately, and then combined, exploiting a nice duality between them. The combined decorated logic is used as the target language for the denotational semantics of the IMP+Exc imperative programming language, and allows us to prove equivalences between programs written in IMP+Exc. The combined logic is encoded in Coq, and this encoding is used to certify some program equivalence proofs.

Parallel identity testing for skew circuits with big powers and applications

Powerful skew arithmetic circuits are introduced. These are skew arithmetic circuits with variables, where input gates can be labeled with powers [Formula: see text] for binary encoded numbers [Formula: see text]. It is shown that polynomial identity testing for powerful skew arithmetic circuits belongs to [Formula: see text], which generalizes a corresponding result for (standard) skew circuits. Two applications of this result are presented: (i) Equivalence of higher-dimensional straight-line programs can be tested in [Formula: see text]; this result is even new in the one-dimensional case, where the straight-line programs produce words. (ii) The compressed word problem (or circuit evaluation problem) for certain wreath products of finitely generated abelian groups belongs to [Formula: see text]. Using the Magnus embedding, it follows that the compressed word problem for a free metabelian group belongs to [Formula: see text].

Fuzzy Stochastic Linear Fractional Programming based on Fuzzy Mathematical Programming

ABSTRACTIn this paper, we consider a Fuzzy Stochastic Linear Fractional Programming problem (FSLFP). In this problem, the coefficients and scalars in the objective function are the triangular fuzzy number and technological coefficients and the quantities on the right side of the constraints are fuzzy random variables with the specific distribution. Here we change an FSLFP problem to an equivalent deterministic Multi-objective Linear Fractional Programming (MOLFP) problem. Then by using Fuzzy Mathematical programming approach transformed MOLFP problem is reduced single objective Linear programming (LP) problem. A numerical example is presented to demonstrate the effectiveness of the proposed method.

Modeling a two-stage supply contract problem in a hybrid uncertain environment

This study examines the supply contract problem in supply chain management, in which the uncertain demand is affected by a variety of factors. Since the available historical data cannot adequately determine the exact probability distribution of future demand, the prediction of experienced experts about uncertain demand is usually required in the practical modeling process of supply contract problem. The main contributions of this study are to model the uncertain demand by both probability distribution and possibility distribution, and develop a new two-stage expected value optimization model for our supply contract problem, in which an options-futures contract is employed to reduce the risk of uncertain demand. In the first decision-making stage, the distributor signs an options-futures contract with the supplier to determine the futures and options ordering quantities. After knowing the realization of uncertain demand, the distributor takes the signed options as the recourse decision in the second stage. When the actual demand follows some common probability and possibility distributions, the proposed two-stage optimization model can be turned into its deterministic equivalent programming model so that it can be solved efficiently via commercial optimization software. To illustrate the effectiveness of the proposed optimization method, a practical natural gas supply contract problem is provided in our numerical experiments. The computational results demonstrate that the possibility distribution of uncertain demand does affect the ordering decisions, and modeling uncertain demand by both probability distribution and possibility distribution is more realistic in our natural gas supply contract problem. As a result, the proposed two-stage optimization method can guide distributors to make their informed decisions in practical supply contract problem when the probability distribution of uncertain demand is partially known.

A note on a robust inventory model with stock-dependent demand

We investigate an inventory model with stock-dependent demand where larger pile of stock displayed leads the customer to purchase more. The dependency of demand on the inventory level is modelled as a monomial function whose shape and scale parameters are stochastic. We present a linear regression-based method for constructing ellipsoidal representations of the parameter uncertainty, which are subsequently incorporated into the inventory model under the robust optimisation framework. We show that the resulting robust optimisation model can be transformed into an equivalent convex programme, and also prove that a robust optimal inventory replenishment policy is of the base-stock type. Through a numerical illustration of the proposed approach and a performance analysis based upon Monte Carlo simulation, we demonstrate that robust optimal order decisions exhibit a unique advantage over deterministic ones.

Increasing the Learning Performance and Experiences of the Accreditation and Equivalency (A&E) Learners through MELMA (Mobile-based Enhancement Learning Material)

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A mixed-integer formulation of OLTC dynamics to minimize distribution and subtransmission tap changes induced by wind and solar power variations

Transformers equipped with an on-load tap-changer (OLTC) are the primary voltage regulators in sub-transmission and distribution networks. As the size of variable generation grows in respect to local feeder demand, the varying bidirectional flow of active power in the feeders interferes with the operation of the OLTC transformers. Currently most grid codes require utility-scale wind and PV plants to strictly regulate the voltage at the point of interconnection. This is typically achieved by installing dynamic reactive support in the form of STATCOM or SVC with instantaneously controllable setpoints and no switching cost. An effective and robust voltage coordination scheme would rely on voltage setpoints of these devices as the primary control input. Thus it is crucial to coordinate these new Volt/VAr controllers with the OLTC transformers to eliminate unnecessary tap changes and consequently reduce substation failure risk and maintenance cost. This paper introduces a centrally coordinated voltage control scheme that determines the optimal voltage setpoint based on variation of wind and solar generation in a given time window with the objective of reducing tap-change operations and resistive losses. Later the paper introduces an equivalent mixed-integer programming formulation that finds the same optimal control output but at a higher computational efficiency. Finally the paper discusses the results of the implementation of the MIP-formulation of the voltage control scheme on the DTE/ITC system serving Eastern Michigan.

Invex programming problems with equality and inequality constraints

The class of functions is known as invex function (invariant convex) in the literature and the name derives from the fact that the convex like property of such functions remains invariant under all diffeomorphisms of Rn into Rn. A noteworthy result here is that the class of invex functions is precisely the class of differentiable functions whose stationary points are global minimizers. We revisit some of the important results obtained by Hanson and Martin and extend them to constrained minimization problems with equality constraints in addition to inequality constraints. We address some conditions by which a function is invex. We propose a result to solve pseudo-invex programming problem with the help of an equivalent programming problem.

A fractional stochastic integer programming problem for reliability-to-stability ratio in forest harvesting

We propose a new fractional stochastic integer programming model for forestry revenue management. The model takes into account the main sources of uncertainties—wood prices and tree growth—and maximizes a reliability-to-stability revenue ratio that reflects two major goals pursued by forest owners. The model includes a joint chance constraint with multirow random technology matrix to account for reliability and a joint integrated chance constraint to account for stability. We propose a reformulation framework to obtain an equivalent mixed-integer linear programming formulation amenable to a numerical solution. We use a Boolean modeling framework to reformulate the chance constraint and a series of linearization techniques to handle the nonlinearities due to the joint integrated chance constraint, the fractional objective function, and the bilinear terms. The computational study attests that the reformulation of the model can handle large number of scenarios and can be solved efficiently for sizable forest harvesting problems.

Special issue: program equivalence

Special issue: program equivalence

An improved-based TOPSIS method in interval-valued intuitionistic fuzzy environment

In supply chain management, one of the important criteria is the selection of suitable suppliers. It is the quality and the timely supply of the different items by the supplier, so that the customers are satisfied to maintain the success of a business. In this paper, we considered a fuzzy multi-objective linear programming solution model for a supplier selection problem. In the model, first, the objectives and constraints are weighted using TOPSIS method; and then, using these weights, membership function for objective functions are constructed. Now, applying the membership function and weights, the multi-objective programming problem is transformed to an equivalent linear programming problem for getting the solution of the multi-criteria supplier selection problem. The proposed algorithm provides better performance results in comparison to other methods available in the literature.

CREATIVE THINKING AS A PROCESS OF CHANGING EARLY CHILDHOOD EDUCATORS’ ATTITUDES ABOUT NEW TECHNOLOGIES - THE CASE OF INTERNET OF THINGS (IOT

This research detects the potential of the creative practice of brainstorming to change the attitudes of future pedagogues regarding the exploitation of new technologies in the early childhood education and care. The survey involved 111 future educators who were divided into two groups of 54 and 57 respectively. Both groups attended an equivalent training program on the use of new technologies in pre-school education. In the first group, the experimental one, the intervention which was implemented exploited an experiential creative practice. The issue of intervention is about IoT (Internet of Things) as it is a trend that is consistent with the concepts of innovation and creativity. The same subject was taught to the second group, the control group, but with traditional teaching practices. In both groups, the same questionnaire of views and attitudes was applied, both before and after completion of the course. The results showed that the experimental group changed its attitude towards new technologies to a greater extent than in the control group. According to the findings of the research, the educators' active participation in creative practice helped them change their attitudes towards the use of technology in pre-school education. Article visualizations:

Green Metric Optimization in Cooperative Cognitive Radio Networks With Statistical Interference Parameters

We study an energy efficiency (EE)-optimized power allocation technique for a source and a relay in a cooperative cognitive radio network. We formulate the optimization problem with the constraint on probabilistic interference parameters and throughput as a fractional programming problem. The problem is quasi-convex, for which a local optimal solution may not be guaranteed as a global optimal solution. Hence, we transform the problem into an equivalent convex programming problem using the Charnes-Cooper transformation technique to obtain an optimal solution. We analyze the channel access probability, EE, and total power performance of the cooperative cognitive green radio network via simulation.

Shaded Tangles for the Design and Verification of Quantum Programs (Extended Abstract)

We give a scheme for interpreting shaded tangles as quantum programs, with the property that isotopic tangles yield equivalent programs. We analyze many known quantum programs in this way -- including entanglement manipulation and error correction -- and in each case present a fully-topological formal verification, yielding in several cases substantial new insight into how the program works. We also use our methods to identify several new or generalized procedures.

Implementation of a new network equilibrium model of travel choices

Abstract This paper develops a new combined network equilibrium model by using more behaviorally sound mathematical forms to represent the four travel choices (i.e., trip frequency, destination, mode, and route) in a conventional travel demand forecasting process. Trip frequency choice relates to the traveler decision on “making a trip” or “not making a trip” so it is given by a binary logit model. Destination choice is formulated as a parameterized dogit model of which the captivity parameters (expressed as functions of independent variables) allow individual travelers to be captive to specific destinations. Mode choice is given by a two-level nested logit model to avoid IIA restriction. Trip assignment is based on Wardrop's “user-optimized” principle. All model forms describing travel choices are in response to the level of services incurred by the transportation system. Through the introduction of inclusive values, the traveler decisions concerning trip frequency, destination, mode, and route choices are inherently interrelated and jointly determined. To obtain solutions of the new combined model, it was reformulated as an equivalent convex programming problem with linear constraints, a great advantage from the computational aspects. The model was applied empirically to a transportation network in New Jersey. The application results show that the new model is consistently better than the commonly used logit combined model in reproducing the observed trip flows from origin zones, origin to destination (O-D) trip flows, O-D trip flows by mode, and trip flows on the network links.