Energy Theft Detection in Smart Grids:Taxonomy,Comparative Analysis,Challenges,and Future Research Directions

Electricity theft is one of the major issues in developing countries which is affecting their economy badly.Especially with the introduction of emerging technologies,this issue became more complicated.Though many new energy theft detection(ETD)techniques have been proposed by utilising different data mining(DM)techniques,state&network(S&N)based techniques,and game theory(GT)techniques.Here,a detailed survey is presented where many state-of-the-art ETD techniques are studied and analysed for their strengths and limitations.Three levels of taxonomy are presented to classify state-of-the-art ETD techniques.Different types and ways of energy theft and their consequences are studied and summarised and different parameters to benchmark the performance of proposed techniques are extracted from literature.The challenges of different ETD techniques and their mitigation are suggested for future work.It is observed that the literature on ETD lacks knowledge management techniques that can be more effective,not only for ETD but also for theft tracking.This can help in the prevention of energy theft,in the future,as well as for ETD.

Manakov model of coupled NLS equation and its optical soliton solutions

In the field of maritime transport,motion and energy,the dynamics of deep-sea waves is one of the major problems in ocean science.A mathematical modeling of dynamics of solitary waves in deep sea under the two-layer stratification leads to NLS equation,and consequently,the interaction two of them can be formulated by coupled NLS equation.In this work,extended auxiliary equation and the exp(−ω(χ))-expansion methods are employed to make the optical solutions of the Manakov model of coupled NLS equation.The methods used in this paper,in addition to providing the analysis of individual wave solutions,also provide general optical solutions.Some previously known solutions can be obtained by some special selections of parameters obtained by solving systems of algebraic equations.At this stage,it is more practical and convenient to apply methods with a symbolic calculation system.

Towards Collaborative Robotics in Top View Surveillance:A Framework for Multiple Object Tracking by Detection Using Deep Learning

Collaborative Robotics is one of the high-interest research topics in the area of academia and industry.It has been progressively utilized in numerous applications,particularly in intelligent surveillance systems.It allows the deployment of smart cameras or optical sensors with computer vision techniques,which may serve in several object detection and tracking tasks.These tasks have been considered challenging and high-level perceptual problems,frequently dominated by relative information about the environment,where main concerns such as occlusion,illumination,background,object deformation,and object class variations are commonplace.In order to show the importance of top view surveillance,a collaborative robotics framework has been presented.It can assist in the detection and tracking of multiple objects in top view surveillance.The framework consists of a smart robotic camera embedded with the visual processing unit.The existing pre-trained deep learning models named SSD and YOLO has been adopted for object detection and localization.The detection models are further combined with different tracking algorithms,including GOTURN,MEDIANFLOW,TLD,KCF,MIL,and BOOSTING.These algorithms,along with detection models,help to track and predict the trajectories of detected objects.The pre-trained models are employed;therefore,the generalization performance is also investigated through testing the models on various sequences of top view data set.The detection models achieved maximum True Detection Rate 93%to 90%with a maximum 0.6%False Detection Rate.The tracking results of different algorithms are nearly identical,with tracking accuracy ranging from 90%to 94%.Furthermore,a discussion has been carried out on output results along with future guidelines.

Analysis of a malaria model with mosquito host choice and bed-net control

A malaria model is formulated which includes the enhanced attractiveness of infectious humans to mosquitoes, as result of host manipulation by malaria parasite, and the human behavior, represented by insecticidetreated bed-nets usage. The occurrence of a backward bifurcation at R0 = 1 is shown to be possible, which implies that multiple endemic equilibria co-exist with a stable disease-free equilibrium when the basic repro- duction number is less than unity. This phenomenon is found to be caused by disease- induced human mortality. The global asymptotic stability of the endemic equilibrium for R0 〉1 is proved, by using the geometric method for global stability. Therefore, the disease becomes endemic for R0〉 1 regardless of the number of initial cases in both the human and vector populations. Finally, the impact on system dynamics of vector＇s host preferences and bed-net usage behavior is investigated.

Computational solution of an acid-mediated tumor-growth radial model under logistic growth regimes for normal and cancer cells

Tumor invasion follows a complex mechanism which involves cell migration and proliferation.To study the processes in which primary and secondary metastases invade and damage the normal cells,mathematical models are often extremely useful.In this paper,we present a mathematical model of acid-mediated tumor growth consisting of radially symmetric reaction-diffusion equations.The assumption on the radial symmetry of the solutions is imposed here in view that tumors present spherical symmetry at the microscopic level.Moreover,we consider various empirical mechanisms which describe the propagation of tumors by considering cancer cells,normal cells,and the concentration of H+ions.Among other assumptions,we suppose that these components follow logistictype growth rates.Evidently,this is an important difference with respect to various other mathematical models for tumor growth available in the literature.Moreover,we also add competition terms of normal and tumor cells growth.We carry out a balancing study of the equations of the model,and a numerical model is proposed to produce simulations.Various practical remarks derived from our assumptions are provided in the discussion of our simulations.

Knowledge Representation for the Geometrical Shapes

This paper outlines the necessity of the knowledge representation for the geometrical shapes （KRGS）. We advocate that KRGS for being powerful must contain at least three major components, namely （1） fuzzy logic scheme; （2） the machine learning technique; and （3） an integrated algebraic and logical reasoning. After arguing the need for using fuzzy expressions in spatial reasoning, then inducing the spatial graph generalized and maximal common part of the expressions is discussed. Finally, the integration of approximate references into spatial reasoning using absolute measurements is outlined. The integration here means that the satisfiability of a fuzzy spatial expression is conducted by both logical and algebraic reasoning.

Capital allocation for cash-subadditive risk measures:From BSDEs toBSVIEs

In the context of risk measures,the capital allocation problem is widely studied in the literature where different approaches have been developed,also in connection with cooperative game theory and systemic risk.Although static capital allocation rules have been extensively studied in the recent years,only few works deal with dynamic capital allocations and its relation with BSDEs.Moreover,all those works only examine the case of an underneath risk measure satisfying cash-additivity and,moreover,a large part of them focuses on the specific case of the gradient allocation where Gateaux differentiability is assumed.The main goal of this paper is,instead,to study general dynamic capital allocations associated to cash-subadditive risk measures,generalizing the approaches already existing in the literature and motivated by the presence of(ambiguity on)interest rates.Starting from an axiomatic approach,we then focus on the case where the underlying risk measures are induced by BSDEs whose drivers depend also on the yvariable.In this setting,we surprisingly find that the corresponding capital allocation rules solve special kinds of Backward Stochastic Volterra Integral Equations(BSVIEs).

On Cyclic DNA Codes Over F_(2)+uF_(2)+u^(2)F_(2)

In the present paper,we study the structure of cyclic DNA codes of even length over the ring F_(2)+uF_(2)+u^(2)F_(2)where u^(3)=0.We investigate two presentations of cyclic codes of even length over F_(2)+uF_(2)+u^(2)F_(2)satisfying the reverse constraint and the reverse-complement constraint.