Understanding students' mobility habits towards the implementation of an adaptive ubiquitous platform

Adapting technological environments to users is a concern since Mark Weiser launched the concept of ubiquitous computing and, in order to do that, is necessary to understand users’ characteristics. In this context, the purpose of this paper is to present a study about students’ mobility habits within a university campus, having the intention of getting insights towards the best place to set an interactive public display and of predicting the main characteristics of the audience that will be present on that spot in forthcoming periods. Thus, the envisioned results of this work will allow the adaptation of the contents exhibited on the device to the audience. To perform the study, a set of logs of accesses to the university’s Wi-Fi was used, data mining techniques were implemented and forecasting models were built, using the line of work suggested by the CRISP-DM methodology. As result, students profile were built based on past wireless accesses and on their scholar schedules, and three time series models were used (Holt-Winters, Seasonal Naive and Simple Exponential Smoothing) to predict the presence of students on the envisioned spot in future periods

Impact of Geographical Information Systems on Geotechnical Engineering

Over the last four decades Geographical Information Systems (GIS) have emerged as the predominant medium for graphic representation of geospatial data, including geotechnical, geologic and hydrologic information routinely used by geotechnical and geoenvironmental engineers. GIS allow unlimited forms of spatial data to be co-mingled, weighted and sorted with any number of physical or environmental factors. These data can also be combined with weighted political and aesthetic values to create hybrid graphic products capable of swaying public perceptions and decision making. The downside of some GIS products is that their apparent efficacy and crispness can also be deceptive, if data of unparalleled reliability is absorbed in the mix. Disparities in data age and quality are common when compiling geotechnical and geoenvironmental data. Despite these inherent shortcomings, GIS will continue to grow and evolve as the principal technical communication medium over the foreseeable future and engineers will be forced to prepare their work products in GIS formats which can be widely disseminated through the world wide web. This paper presents the historical evolution of GIS technologies as it relates to the impact in geotechnical engineering, concluding with four case histories on the application of this emerging technology

Obstructions in Security-Aware Business Processes

This Open Access book explores the dilemma-like stalemate between security and regulatory compliance in business processes on the one hand and business continuity and governance on the other. The growing number of regulations, e.g., on information security, data protection, or privacy, implemented in increasingly digitized businesses can have an obstructive effect on the automated execution of business processes. Such security-related obstructions can particularly occur when an access control-based implementation of regulations blocks the execution of business processes. By handling obstructions, security in business processes is supposed to be improved. For this, the book presents a framework that allows the comprehensive analysis, detection, and handling of obstructions in a security-sensitive way. Thereby, methods based on common organizational security policies, process models, and logs are proposed. The Petri net-based modeling and related semantic and language-based research, as well as the analysis of event data and machine learning methods finally lead to the development of algorithms and experiments that can detect and resolve obstructions and are reproducible with the provided software

The challenges of estimating potential output in real time

Potential output is an estimate of the level of gross domestic product attainable when the economy is operating at a high rate of resource use. A summary measure of the economy's productive capacity, potential output plays an important role in the Congressional Budget Office (CBO)'s economic forecast and projection. The author briefly describes the method the CBO uses to estimate and project potential output, outlines some of the advantages and disadvantages of that approach, and describes some of the challenges associated with estimating and projecting potential output. Chief among these is the difficulty of estimating the underlying trends in economic data series that are volatile, subject to structural change, and frequently revised. Those challenges are illustrated using examples based on recent experience with labor force growth, the Phillips curve, and labor productivity growth.Economic development ; Economic conditions

The sources and nature of long-term memory in the business cycle

This paper examines the stochastic properties of aggregate macroeconomic time series from the standpoint of fractionally integrated models, focusing on the persistence of economic shocks. We develop a simple macroeconomic model that exhibits long-range dependence, a consequence of aggregation in the presence of real business cycles. We then derive the relation between properties of fractionally integrated macroeconomic time series and those of microeconomic data and discuss how fiscal policy may alter the stochastic behavior of the former. To implement these results empirically, we employ a test for fractionally integrated time series based on the Hurst-Mandelbrot rescaled range. This test, which is robust to short-term dependence, is applied to quarterly and annual real GNP to determine the sources and nature of long-term dependence in the business cycle..Business cycles ; Time-series analysis

Security Analytics: Using Deep Learning to Detect Cyber Attacks

Security attacks are becoming more prevalent as cyber attackers exploit system vulnerabilities for financial gain. The resulting loss of revenue and reputation can have deleterious effects on governments and businesses alike. Signature recognition and anomaly detection are the most common security detection techniques in use today. These techniques provide a strong defense. However, they fall short of detecting complicated or sophisticated attacks. Recent literature suggests using security analytics to differentiate between normal and malicious user activities. The goal of this research is to develop a repeatable process to detect cyber attacks that is fast, accurate, comprehensive, and scalable. A model was developed and evaluated using several production log files provided by the University of North Florida Information Technology Security department. This model uses security analytics to complement existing security controls to detect suspicious user activity occurring in real time by applying machine learning algorithms to multiple heterogeneous server-side log files. The process is linearly scalable and comprehensive; as such it can be applied to any enterprise environment. The process is composed of three steps. The first step is data collection and transformation which involves identifying the source log files and selecting a feature set from those files. The resulting feature set is then transformed into a time series dataset using a sliding time window representation. Each instance of the dataset is labeled as green, yellow, or red using three different unsupervised learning methods, one of which is Partitioning around Medoids (PAM). The final step uses Deep Learning to train and evaluate the model that will be used for detecting abnormal or suspicious activities. Experiments using datasets of varying sizes of time granularity resulted in a very high accuracy and performance. The time required to train and test the model was surprisingly fast even for large datasets. This is the first research paper that develops a model to detect cyber attacks using security analytics; hence this research builds a foundation on which to expand upon for future research in this subject area

A mud-dominated coastal plain to lagoon with emerged carbonate mudbanks: The imprint of low-amplitude sea level cycles (mid-Upper Cretaceous, South Iberian Ramp)

The middle Santonian-lower Campanian carbonate-mud dominated succession deposited in the northeastern margin of the South Iberian Ramp (La Cañadilla Fm, NE Spain) shows a complex set of interfingered facies developed in a low-energy and low-gradient shallow-marine to coastal environment. Three facies belts characterize the environment reconstructed in this work: (1) a low-energy shallow marine lagoon dominated by radiolitid rudist limestones and miliolid-rich facies with variable carbonate-mud content; (2) a transitional belt with a patchy distribution of ponds and mudbanks. This belt mostly consists of miliolid-rich limestones with variable amount of fenestral porosity, which are interfingered with charophytes and gastropod marls and limestones usually mixed with miliolids; (3) a coastal plain with strong freshwater influence characterized by the sedimentation of marls and limestones with charophytes, gastropods and root traces and intraclastic/black pebble limestones. The studied succession is arranged in high-frequency sequences, including meter-scale parasequences bounded by widespread flooding surfaces, which stack in five larger-scale shallowing-upward sequences (6–20 m thick). The time calibration of these sequences obtained from strontium isotopes and biostratigraphic data (benthic foraminifera) suggests a major control in the sedimentation by climate-driven low-amplitude sea level oscillations formed in tune with the long- and short-eccentricity orbital cycles. Cyclic sea level rises controlled the existence of widespread flooding events in the low-gradient carbonate ramp at the onset of parasequences, which in the studied marginal areas of the South Iberian Ramp were mostly sourced from the southern Tethyan realm. Therefore, the La Cañadilla Fm provides an example of a complex shallow marine to coastal system giving rise to a mosaic distribution of carbonate-mud dominated facies, with sedimentation mostly influenced by external factors resulting in a well-defined stratigraphic architecture. The similarities with modern analogous systems such as the Ten Thousand Islands of the Florida Bay are discussed in this paper. © 2022 Elsevier B.V