A dynamic approach for evaluating earthwork hauls in construction

A graph theoretic approach is developed for accurately computing haulage costs in earthwork projects. This is vital as haulage is a predominant factor in the real cost of earthworks. A variety of metrics can be used in our approach, but a fuel consumption proxy is recommended. This approach is novel as it considers the constantly changing terrain that results from cutting and filling activities and replaces inaccurate “static” calculations that have been used previously. The approach is also capable of efficiently correcting the violation of top down cutting and bottom up filling conditions that can be found in existing earthwork assignments and sequences. This approach assumes that the project site is partitioned into uniform blocks. A directed graph is then utilised to describe the terrain surface. This digraph is altered after each cut and fill, in order to reflect the true state of the terrain. A shortest path algorithm is successively applied to calculate the cost of each haul and these costs are summed to provide a total cost of haulage

On Selection of Search Space Dimension in Compressive Sampling Matching Pursuit

Compressive Sampling Matching Pursuit (CoSaMP) is one of the popular greedy methods in the emerging field of Compressed Sensing (CS). In addition to the appealing empirical performance, CoSaMP has also splendid theoretical guarantees for convergence. In this paper, we propose a modification in CoSaMP to adaptively choose the dimension of search space in each iteration, using a threshold based approach. Using Monte Carlo simulations, we show that this modification improves the reconstruction capability of the CoSaMP algorithm in clean as well as noisy measurement cases. From empirical observations, we also propose an optimum value for the threshold to use in applications.

Subspace Pursuit Embedded in Orthogonal Matching Pursuit

Orthogonal Matching Pursuit (OMP) is a popular greedy pursuit algorithm widely used for sparse signal recovery from an undersampled measurement system. However, one of the main shortcomings of OMP is its irreversible selection procedure of columns of measurement matrix. i.e., OMP does not allow removal of the columns wrongly estimated in any of the previous iterations. In this paper, we propose a modification in OMP, using the well known Subspace Pursuit (SP), to refine the subspace estimated by OMP at any iteration and hence boost the sparse signal recovery performance of OMP. Using simulations we show that the proposed scheme improves the performance of OMP in clean and noisy measurement cases.

Classification of Vehicles using Magnetic Dipole Model

This paper presents an efficient approach to the modeling and classification of vehicles using the magnetic signature of the vehicle. A database was created using the magnetic signature collected over a wide range of vehicles(cars). A vehicle is modeled as an array of magnetic dipoles. The strength of the magnetic dipole and the separation between the magnetic dipoles varies for different vehicles and is dependent on the metallic composition and configuration of the vehicle. Based on the magnetic dipole data model, we present a novel method to extract a feature vector from the magnetic signature. In the classification of vehicles, a linear support vector machine configuration is used to classify the vehicles based on the obtained feature vectors.

Modulation Diversity for Spatial Modulation Using Complex Interleaved Orthogonal Design

In this paper, we propose modulation diversity techniques for Spatial Modulation (SM) system using Complex Interleaved Orthogonal Design (CIOD). Specifically, we show that the standard SM scheme can achieve a transmit diversity order of two by using the CIOD meant for two transmit antenna system without incurring any additional system complexity or bandwidth requirement. Furthermore, we propose a low-complexity maximum likelihood detector for our CIOD based SM schemes by exploiting the structure of the CIOD. We show with our simulation results that the proposed schemes offer transmit diversity order of two and give a better symbol error rate performance than the conventional SM scheme.

Successful strategies for the implementation of land reform : a peasants’ account from the Philippines

Entre 1988 et 2008, les Philippines ont mis en oeuvre le Comprehensive Agrarian Reform Program (CARP) qui visait à redistribuer 9 million d‟hectares de terres agricoles aux paysans sans terre. En dépit des échappatoires du programme et d‟une structure sociale très inégale qui freinent sa mise en oeuvre, ce modèle de réforme agraire présente des résultats surprenants alors que 82% des terres ont été redistribuées. Concernant les terres plus litigieuses appartenant à des intérêts privés, Borras soutient que le succès surprenant de plusieurs cas de luttes agraires s‟explique par l‟utilisation de la stratégie bibingka qui consiste à appliquer de la pression par le bas et par le haut afin de forcer la redistribution. Sa théorie cependant ne donne que peu de détails concernant les éléments qui rendent un cas plus ou moins litigieux. Elle ne traite pas non plus de la manière dont les éléments structurels et l‟action collective interagissent pour influencer le résultat des luttes agraires. Dans ce mémoire, nous nous attardons d‟abord à la manière dont certains éléments structurels – le type de récolte et le type de relation de production - influencent le degré de résistance des propriétaires terriens face aux processus du CARP, contribuant ainsi à rendre les cas plus ou moins litigieux. Ensuite nous analysons l‟influence du contexte structurel et des stratégies paysannes sur le résultat de la mise en oeuvre du programme de réforme agraire. Pour répondre à nos deux questions de recherche, nous présentons quatre études de cas situés dans la province de Cebu.