39 research outputs found
Obstacles, slopes and tic-tac-toe: an excursion in discrete geometry and combinatorial game theory
No full textThe minimum number of slopes used in a straight-line drawing of G is called the slope number of G. We show that every cubic graph can be drawn in the plane with straight line edges using only the four basic slopes {0, π/4, π/2,−π/4}. We also prove that four slopes have this property if and only if we can draw K4 with them. Given a graph G, an obstacle representation of G is a set of points in the plane representing the vertices of G, together with a set of obstacles (connected polygons)
such that two vertices of G are joined by an edge if and only if the corresponding points can be connected by a segment which avoids all obstacles. The obstacle number of G is the minimum number of obstacles in an obstacle representation of G. We show that there are graphs on n vertices with obstacle number (n/log n). We show that there is an m = 2n + o(n), such that, in the Maker-Breaker game played on Zd where Maker needs to put at least m of his marks consecutively in one
of n given winning directions, Breaker can force a draw using a pairing strategy. This improves the result of Kruczek and Sundberg who showed that such a pairing strategy exits if m ≥ 3n. A simple argument shows that m has to be at least 2n+1 if Breaker is only allowed to use a pairing strategy, thus the main term of our bound is optimal.Ph. D.Includes bibliographical referencesIncludes vitaby V S Padmini Mukkamal
Risk management through social networks among male and female pastoralists in Karamoja, Uganda
No full textEnvironmental volatility, resource-related risks, and the overall uncertainty about the future fundamentally shape behavioral strategies and are critical to understanding the evolution of human social behavior. One of the central ways in which humans in subsistence economies manage risk and uncertainty is through pooling or sharing risk with other individuals, such as central place food sharing among forager populations. Among pastoralists in East Africa, risk pooling takes the form of ‘stock friendships’: an informal insurance system in which male herders form mutually beneficial partnerships through livestock transfers. Networks of stock friends are critical to recouping short term losses such as food shortage, as well as to ensuring long-term sustainability through the rebuilding of herds. This dissertation investigates risk pooling friendships and other risk management strategies of pastoralists in Karamoja, Uganda. Risk management is a central concern for pastoralists in Karamoja because of the unreliable climate, recent volatile history, and lack of institutional support. Consequently, social networks of livestock and food exchange, such as stock friendships, play a significant role in minimizing the adverse effects of disasters. During fourteen months of fieldwork, I collected qualitative and quantitative data on men’s stock friendship networks, women’s close friendship networks, and individuals’ exchange networks during a prolonged drought. I use these data to present the following: 1) an ethnographic investigation of friendship contracts among men and women; 2) an examination of the characteristics of friendship networks, including size, composition, geographical spread, and relational content; 3) a study of how individual level and external factors influence friendship networks; and 4) an analysis of which social exchange networks are activated during drought induced stress. Based on data on norms and transfers within friendship networks, I argue that risk pooling friendships in Karamoja are characterized by needbased transfers and ‘demand sharing’ rather than account-keeping reciprocity. Further, I show that during periods of extreme stress, need-based transfers of food, livestock, and money are acquired not only from kin and friendship networks (‘strong ties’), but also from ‘weak tie’ friends within the neighborhood. I, thus, contend that engaging in risk pooling relationships and need based transfers are a necessity in an environment characterized by unpredictability. Lastly, I present results from an experimental economic game that explores participants’ risk attitudes and time preference—variables critical to understanding decision-making under conditions of chronic risk and uncertainty.Ph.D.Includes bibliographical referencesby K. Padmini Iye
Application of Particle Swarm Optimization for Combined Environmental and Economic Dispatch of IEEE 30 Bus System Using Fuzzy Logic Technique
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Managing the demand in a Micro Grid Based on Load shifting with Controllable Devices Using Hybrid WFS2ACSO Technique
No full textThe Demand Side Management (DSM) introduced in Smart Grid (SG), which depends on load shifting with huge number of devices is presented in this work. The proposed hybrid strategy is the joint implementation of Wingsuit Flying Search (WFSA) algorithm and Artificial Cell Swarm Optimization (ACSO). The searching behavior of WFSA is enhanced by ACSO. Hence, it is named as WFS2ACSO. This technique aims at minimization of electricity bill, power consumption, and Peak Average Ratio (PAR). The daily load change method presented in this manuscript is utilized for defusing the minimization issues. The present method is performed in SG that constitutes three different types of loads on a residential area, a commercial area, and an industrial area. Simulation results demonstrate that the projected DSM methodology achieves considerable savings, as peak load demand of SG decreases. Further, the variation in PAR levels with and without the DSM methodology is also presented. The proposed model is executed on a MATLAB simulation platform with two case studies based on optimization methods like WFSA, WFS2ACSO). The results obtained present the hybridized algorithm effectiveness as compared with other trendsetting optimization techniques like Ant lion optimization (ALO) and particle swarm optimization (PSO)
Rescheduling of Generators with Pumped Hydro Storage Units to Relieve Congestion Incorporating Flower Pollination Optimization
No full textIn this paper, a Flower Pollination Algorithm (FPA) has been proposed for relieving congestion in the deregulated power electricity industry. Congestion in the power market is one the contemplative challenges to be overcome in the era of deregulation. The primary cause of congestion is due to the loss of the transmission line, an increase in load, or loss of generator(s). Hence, managing congestion is one of the issues which have to be tackled in the present scenario. There are several techniques to relieve congestion. It is quite well-known that the thermal limits of transmission lines in a power system are fixed. One of the methods to abate congestion is to reschedule the real power of the generators. The purpose of the present work is to benefit the Independent System Operator (ISO) in reliving congestion. (1) In order to meet this objective effectively, a FPA algorithm has been proposed for relieving congestion and is simulated on a modified IEEE 30-bus system initially. (2) Congestion cost, compared with and without the application of FPA, is computed. (3) To validate its effectiveness, the obtained results are compared with recent power system optimization algorithms present in the literature. (4) Further, the work has been extended with the incorporation of a Pumped Hydro Storage Unit (PHSU). Here an economic analysis of congestion cost reduction employing FPA before and after the incorporation of PHSU is investigated applying FPA. In comparison with other evolutionary algorithms, the uniqueness of generating a new population is attained in FPA by the levy flight procedure. It is one of the latest evolved algorithms and is suited for different power system problem due to fewer clear-cut tuning parameters in contrast with other algorithms. (5) Furthermore, the effects of other network parameters, including system losses and voltage, has been computed. The result obtained is tested in terms of congestion mitigation with and without the incorporation of PHSU, in terms of novel objective improvement, and with and without applying recently evolving FPA for the above application. Thus the objective-wise and algorithmic-wise innovative concept has been presented. This proves effectiveness of the algorithm in terms of minimized cost convergence and other parameter including system losses and voltage before and after the incorporation of PHSU as compared with other recent trendsetting reported optimization techniques
A quantitative analysis of complexity of human pathogen-specific CD4 T cell responses in healthy M. tuberculosis infected South Africans
No full textAuthor Summary: Human pathogen-specific immune responses are tremendously complex and the techniques to study them ever expanding. There is an urgent need for a quantitative analysis and better understanding of pathogen-specific immune responses. Mycobacterium tuberculosis (Mtb) is one of the leading causes of mortality due to an infectious agent worldwide. Here, we were able to quantify the Mtb-specific response in healthy individuals with Mtb infection from South Africa. The response is highly diverse and 66 epitopes are required to capture 80% of the total reactivity. Our study also show that the majority of the identified epitopes are restricted by multiple HLA alleles. Thus, technical advances are required to capture and characterize the complete pathogen-specific response. This study demonstrates further that the approach combining identified epitopes into "megapools" allows capturing a large fraction of the total reactivity. This suggests that this technique is generally applicable to the characterization of immunity to other complex pathogens. Together, our data provide for the first time a quantitative analysis of the complex pathogen-specific T cell response and provide a new understanding of human infections in a natural infection setting
Efficient self-learning artificial neural network controller for critical heating, ventilation and air conditioning systems
No full textUrban Infrastructure Damage Detection and Mapping Using Sentinel 1
No full textNatural or man-made disasters can have a drastic impact on social, economic and environmental aspects of an affected population. Specifically, earthquakes are one of the most potent natural hazards, which cause a disproportionate amount of fatalities, primarily due to a) unexpected building collapses, b) restricted or limited access to basic amenities and c) potential hazards following earthquakes such as landslides, tsunamis etc. It is crucial to have an overview of the infrastructural damage caused following a disaster for search and rescue services to assess the extent of the damage. For the purpose of this research, Sentinel 1 imagery is used to map the building damage in an urban area after a disaster. A combination of parameters such as persistent scatterers, pixel amplitude and phase is used with a timeseries of full-resolution and spatially averaged radar images. Points that are stable in amplitude over a long timeseries, also known as Persistent Scatterers, are extracted from a stack of full-resolution images. The amplitudes of persistent scatterers, along with amplitude and coherence of pixels derived from a stack of spatially-averaged images, are statistically analysed to check the trends of the parameters pre- and post the disaster. A change detection algorithm is applied to this stack in order to localise the areas of building damage. The results are superimposed on Google Earth for easy interpretation using a graded damage scale. The analysis shows that exploiting the persistent scatterer amplitudes in the manner used in this research provides a novel way of locating building damage. This technique can be used effectively in urban areas. Using a combination of pixel amplitudes and coherence along with the persistent scatterers helps correctly find new and unique points of damage for each parameter used. The results were validated using reference Grading and crowd-sourced maps. The results illustrate that the proposed approach can be used for detecting and producing informative maps on infrastructural damage detection in urban areas
