Dynamic Signature Verification Using Pattern Recognition

Dynamic signature is a biometric modality that recognizes an individual’s anatomic and behavioural characteristics when signing their name. The rampant case of signature falsification (Identity Theft) was the key motivating factor for embarking on this study. This study was necessitated by the damages and dangers posed by signature forgery coupled with the intractable nature of the problem. The aim and objectives of this study is to design a proactive and responsive system that could compare two signature samples and detect the correct signature against the forged one. Dynamic Signature verification is an important biometric technique that aims to detect whether a given signature is genuine or forged. In this research work, Convolutional Neural Networks (CNNsor ConvNet) which is a class of deep, feed forward artificial neural networks that has successfully been applied to analysing visual imagery was used to train the model. The signature images are stored in a file directory structure which the Keras Python library can work with. Then the CNN was implemented in python using the Keras with the TensorFlow backend to learn the patterns associated with the signature. The result showed that for the same CNNs-based network experimental result of average accuracy, the larger the training dataset, the higher the test accuracy. However, when the training dataset are insufficient, better results can be obtained. The paper concluded that by training datasets using CNNs network, 98% accuracy in the result was recorded, in the experimental part, the model achieved a high degree of accuracy in the classification of the biometric parameters used.

Wireless sensing for a solar power system

Wireless sensing is an excellent approach for remotely operated solar power system.Not only being able to get the sensor data,such as voltage,current,and temperature,the system can also have a proper control for tracking the Sun and sensing real-time data from a controller.In order to absorb the maximum energy by solar cells,it needs to track the Sun with proper angles.Arduino,H-bridge motor driver circuit,and Direct Current(DC)motor are used to alter the tilt angle of the solar PhotoVoltaic(PV)panel following the Sun while the azimuth and the elevation angles are fixed at noon.Unlike the traditional way,the tilt rotation is proposed to be stepped hourly.The solar PV panel is tilted 7:5∘in advance of current time to the west to produce more output voltage during an hour.As a result,the system is simple while providing good solar-tracking results and efficient power outputs.

Effect of El Nino Southern Oscillations on the incidence of enteric fever in Ahmedabad,India from 1985 to 2017

Objective:To explore the relationship between climate variables and enteric fever in the city of Ahmedabad and report preliminary findings regarding the influence of El Nino Southern Oscillations and Indian Ocean Dipole over enteric fever incidence.Method:A total of 29808 Widal positive enteric fever cases reported by the Ahmedabad Municipal Corporation and local climate data in 1985-2017 from Ahmedabad Meteorology Department were analysed.El Nino,La Nina,neutral and Indian Ocean Dipole years as reported by the National Oceanic and Atmospheric Administration for the same period were compared for the incidence of enteric fever.Results:Population-normalized average monthly enteric fever case rates were the highest for El Nino years(25.5),lower for La Nina years(20.5)and lowest for neutral years(17.6).A repeated measures ANOVA analysis showed no significant difference in case rates during the three yearly El Nino Southern Oscillations categories.However,visual profile plot of estimated marginal monthly means showed two distinct characteristics:an early rise and peaking of cases in the El Nino and La Nina years,and a much more restrained rise without conspicuous peaks in neutral years.Further analysis based on monthly El Nino Southern Oscillations categories was conducted to detect differences in median monthly case rates.Median case rates in strong and moderate El Nino months and strong La Nina months were significantly dissimilar from that during neutral months(P<0.001).Conclusions:El Nino Southern Oscillations events influence the incidence of enteric fever cases in Ahmedabad,and further investigation from more cities and towns is required.

Tracking a Screen and Detecting Its Rate of Change in 3-D Video Scenes of Multipurpose Halls

An automatic approach is presented to track a wide screen in a multipurpose hall video scene. Once the screen is located, this system also generates the temporal rate of change by using the edge detection based method. Our approach adopts a scene segmentation algorithm that explores visual features （texture） and depth information to perform efficient screen localization. The cropped region which refers to the wide screen undergoes salient visual cues extraction to retrieve the emphasized changes required in rate-of- change computation. In addition to video document indexing and retrieval, this work can improve the machine vision capability in the behavior analysis and pattern recognition.

Enabling Proactive Management of School Dropouts Using Neural Network

The growing need to use Artificial Intelligence (AI) technologies in addressing challenges in education sectors of developing countries is undermined by low awareness, limited skill and poor data quality. One particular persisting challenge, which can be addressed by AI, is school dropouts whereby hundreds of thousands of children drop annually in Africa. This article presents a data-driven approach to proactively predict likelihood of dropping from schools and enable effective management of dropouts. The approach is guided by a carefully crafted conceptual framework and new concepts of average absenteeism, current cumulative absenteeism and dropout risk appetite. In this study, a typical scenario of missing quality data is considered and for which synthetic data is generated to enable development of a functioning prediction model using neural network. The results show that, using the proposed approach, the levels of risk of dropping out of schools can be practically determined using data that is largely available in schools. Potentially, the study will inspire further research, encourage deployment of the technologies in real life, and inform processes of formulating or improving policies.

Sustainable transit vehicle tracking service,using intelligent transportation system services and emerging communication technologies:A review

The most salient problems of transit vehicle service in Latin American intermediate cities include:the high number of passengers involved in traffic accidents;traffic congestion caused by transit vehicles,and pollution generated by these vehicles,which increases in high congestion scenarios.To improve upon this situation,a research was conducted on the transit vehicle tracking service,which is a basic service for implementing mobility solutions for the aforementioned problems,the most relevant characteristics of this service for the context of Latin American intermediate cities were identified,and an implementation was proposed.This paper presents the four stages of the study:(a)a review of the state-of-the-art of services or systems related to vehicle tracking,including wireless communications technologies,implemented sustainability approaches,usage of special algorithms for efficiency improvement,and the intelligent transportation system(ITS)architecture used as a basis;(b)the process of identifying relevant characteristics of the service for a given context;(c)proposal of an ITS architecture for this service in an intermediate city,its requirements and the suggested technologies;and(d)development of experiments for validating usage of the key suggested technologies.The review allowed to identify the main service characteristics,with regard to vehicle positioning technologies,the recommended wireless communication technology(long range,LoRa),energy consumption considerations,and use of artificial intelligence(AI)to calculate waiting time of users at bus stops.Finally,an ITS architecture for the city of Popayan(Colombian city)considering the aforementioned characteristics is proposed,and the experiments related to the use of these technologies are described in detail.

On the use of Max-SAT and PDDL in RBAC maintenance

Role-Based Access Control(RBAC)policies are at the core of Cybersecurity as they ease the enforcement of basic security principles,e.g.,Least Privilege and Separation of Duties.As ICT systems and business processes evolve,RBAC policies have to be updated to prevent unauthorised access to resources by capturing errors and misalignments between the current policy and reality.However,such update process is a human-intensive activity and it is expected to meet specific constraints.This paper proposes a semi-automatic RBAC maintenance process to fix and refine an RBAC state when“exceptions”and“violations”are detected.Exceptions are permissions some users realise they miss that are instrumental to their job and should be granted as soon as possible,while violations are permissions that have to be revoked since they are no longer required by their current owners.We propose a formalisation for the maintenance process which fixes single and multiple exceptions and violations by balancing two conflicting objectives,i.e.,(i)optimising the current RBAC state,and(ii)reducing the transition cost.Our approach is based on a Max-SAT formalisation of the constraint-based optimisation problem,and on PDDL planning to define the transition strategy with minimum cost.Our implementation relies on incomplete Max-SAT solvers and satisficing PDDL planners which provide approximations of optimal solutions.Experiments along with a comparative evaluation show good performance on real-world benchmarks.

On the Importance of the Stokes-Brinkman Equations for Computing Effective Permeability in Karst Reservoirs

Cavities and fractures significantly affect the flow paths in carbonate reservoirs and should be accurately accounted for in numerical models.Herein,we consider the problem of computing the effective permeability of rock samples based on high-resolution 3DCT scans containingmillions of voxels.We use the Stokes-Brinkman equations in the entire domain,covering regions of free flow governed by the Stokes equations,porous Darcy flow,and transitions between them.The presence of different length scales and large(ten orders of magnitude)contrasts in permeability leads to highly ill-conditioned linear systems of equations,which are difficult to solve.To obtain a problem that is computationally tractable,we first analyze the relative importance of the Stokes and Darcy terms for a set of idealized 2D models.We find that,in terms of effective permeability,the Stokes-Brinkman equations are only applicable for a special parameter set where the effective free-flow permeability is less than four orders of magnitude different from the matrix permeability.All other cases can be accurately modeled with either the Stokes or the Darcy end-member flows,depending on if there do or do not exist percolating free-flow regions.The insights obtained are used to perform a direct computation of the effective permeability of a rock sample model with more than 8 million cells.