PinMe: Tracking a Smartphone User around the World

With the pervasive use of smartphones that sense, collect, and process valuable information about the environment, ensuring location privacy has become one of the most important concerns in the modern age. A few recent research studies discuss the feasibility of processing data gathered by a smartphone to locate the phone's owner, even when the user does not intend to share his location information, e.g., when the Global Positioning System (GPS) is off. Previous research efforts rely on at least one of the two following fundamental requirements, which significantly limit the ability of the adversary: (i) the attacker must accurately know either the user's initial location or the set of routes through which the user travels and/or (ii) the attacker must measure a set of features, e.g., the device's acceleration, for potential routes in advance and construct a training dataset. In this paper, we demonstrate that neither of the above-mentioned requirements is essential for compromising the user's location privacy. We describe PinMe, a novel user-location mechanism that exploits non-sensory/sensory data stored on the smartphone, e.g., the environment's air pressure, along with publicly-available auxiliary information, e.g., elevation maps, to estimate the user's location when all location services, e.g., GPS, are turned off.Comment: This is the preprint version: the paper has been published in IEEE Trans. Multi-Scale Computing Systems, DOI: 0.1109/TMSCS.2017.275146

Inspection report Wyggeston and Queen Elizabeth I College

Date(s) of inspection: 2–6 December 200

Adapting Artificial Immune Algorithms For University Timetabling

Penjadualan kelas dan peperiksaan di universiti adalah masalah pengoptimuman berkekangan tinggi. University class and examination timetabling are highly constrained optimization problems

Decomposition, Reformulation, and Diving in University Course Timetabling

In many real-life optimisation problems, there are multiple interacting components in a solution. For example, different components might specify assignments to different kinds of resource. Often, each component is associated with different sets of soft constraints, and so with different measures of soft constraint violation. The goal is then to minimise a linear combination of such measures. This paper studies an approach to such problems, which can be thought of as multiphase exploitation of multiple objective-/value-restricted submodels. In this approach, only one computationally difficult component of a problem and the associated subset of objectives is considered at first. This produces partial solutions, which define interesting neighbourhoods in the search space of the complete problem. Often, it is possible to pick the initial component so that variable aggregation can be performed at the first stage, and the neighbourhoods to be explored next are guaranteed to contain feasible solutions. Using integer programming, it is then easy to implement heuristics producing solutions with bounds on their quality. Our study is performed on a university course timetabling problem used in the 2007 International Timetabling Competition, also known as the Udine Course Timetabling Problem. In the proposed heuristic, an objective-restricted neighbourhood generator produces assignments of periods to events, with decreasing numbers of violations of two period-related soft constraints. Those are relaxed into assignments of events to days, which define neighbourhoods that are easier to search with respect to all four soft constraints. Integer programming formulations for all subproblems are given and evaluated using ILOG CPLEX 11. The wider applicability of this approach is analysed and discussed.Comment: 45 pages, 7 figures. Improved typesetting of figures and table

A memetic algorithm for the university course timetabling problem

This article is posted here with permission from IEEE - Copyright @ 2008 IEEEThe design of course timetables for academic institutions is a very hectic job due to the exponential number of possible feasible timetables with respect to the problem size. This process involves lots of constraints that must be respected and a huge search space to be explored, even if the size of the problem input is not significantly large. On the other hand, the problem itself does not have a widely approved definition, since different institutions face different variations of the problem. This paper presents a memetic algorithm that integrates two local search methods into the genetic algorithm for solving the university course timetabling problem (UCTP). These two local search methods use their exploitive search ability to improve the explorative search ability of genetic algorithms. The experimental results indicate that the proposed memetic algorithm is efficient for solving the UCTP

Timetable Management Using Genetic Algorithms

Scheduling course timetables for a large array of courses is a very complex problem which often has to be solved manually by the center staff even though results are not always fully optimal. Timetabling being a highly constrained combinatorial problem, this work attempts to put into play the effectiveness of evolutionary techniques based on Darwin's theories to solve the timetabling problem if not fully optimal but near optimal. Genetic Algorithm is a popular meta-heuristic that has been successfully applied to many hard combinatorial optimization problems which includes timetabling and scheduling problems. In this work, the course sets, halls and time allocations are represented by a multidimensional array on which a local search is performed and a combination of the direct representation of the timetable with heuristic crossover is made to ensure that fundamental constraints are not violated. Finally, the genetic algorithm was applied in the development of a viable timetabling system which was tested to demonstrate the variety of possible timetables that can be generated based on user specified constraint and requirements. Keywords: Time table management, genetic algorithm

Stockton Sixth Form College: report from the Inspectorate (FEFC inspection report; 64/96 and 62/00)

The Further Education Funding Council has a legal duty to make sure further education in England is properly assessed. The FEFC’s inspectorate inspects and reports on each college of further education according to a four-year cycle. This record comprises the reports for periods 1995-96 and 1999-2000