Physical Sciences and Mathematics Commons^™

A Deep Recurrent Q Network Towards Self-Adapting Distributed Microservice Architecture, Basel Magableh, Muder Almiani

Articles

One desired aspect of microservice architecture is the ability to self-adapt its own architecture and behavior in response to changes in the operational environment. To achieve the desired high levels of self-adaptability, this research implements distributed microservice architecture model running a swarm cluster, as informed by the Monitor, Analyze, Plan, and Execute over a shared Knowledge (MAPE-K) model. The proposed architecture employs multiadaptation agents supported by a centralized controller, which can observe the environment and execute a suitable adaptation action. The adaptation planning is managed by a deep recurrent Q-learning network (DRQN). It is argued that such integration between DRQN …

Some Transitivity-Like Concepts In Abelian Groups, Gabor Braun, Brendan Goldsmith, Ketao Gong, Lutz Strungmann

Articles

The classical notions of transitivity and full transitivity in Abelian p-groups have natural extensions to concepts called Krylov and weak transitivity. The interconnections between these four types of transitivity are determined for Abelian p-groups; there is a marked difference in the relationships when the prime p is equal to 2. In the final section the relationship between full and Krylov transitivity is examined in the case of mixed Abelian groups which are p-local in the sense that multiplication by an integer relatively prime to p is an automorphism.

Integrable Cosmological Model With Van Der Waals Gas And Matter Creation, Rossen Ivanov, Emil Prodanov

Articles

A cosmological model with van der Waals gas and dust has been studied in the context of a three-component autonomous non-linear dynamical system involving the time evolution of the particle number density, the Hubble parameter and the temperature. Due to the presence of a symmetry of the model, the temperature evolution law is determined (in terms of the particle number density) and with this the dynamical system reduces to a two-component one which is fully integrable. The globally conserved Hamiltonian is identified and, in addition to it, some special (second) integrals, defined and conserved on a lower-dimensional manifold, are found. …

When The Intrinsic Algebraic Entropy Is Not Really Intrinsic, Brendan Goldsmith, Luigi Salce

Articles

The intrinsic algebraic entropy ent(ɸ) of an endomorphism ɸ of an Abelian group G can be computed using fully inert subgroups of ɸ-invariant sections of G, instead of the whole family of ɸ-inert subgroups. For a class of groups containing the groups of finite rank, aswell as those groupswhich are trajectories of finitely generated subgroups, it is proved that only fully inert subgroups of the group itself are needed to comput ent(ɸ). Examples show how the situation may be quite different outside of this class.

Analysing The Impact Of Machine Learning To Model Subjective Mental Workload: A Case Study In Third-Level Education, Karim Moustafa, Luca Longo

Conference papers

Mental workload measurement is a complex multidisciplinary research area that includes both the theoretical and practical development of models. These models are aimed at aggregating those factors, believed to shape mental workload, and their interaction, for the purpose of human performance prediction. In the literature, models are mainly theory-driven: their distinct development has been influenced by the beliefs and intuitions of individual scholars in the disciplines of Psychology and Human Factors. This work presents a novel research that aims at reversing this tendency. Specifically, it employs a selection of learning techniques, borrowed from machine learning, to induce models of mental …

Contextual Word Embeddings - Trained On English Wikipedia Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher

Datasets

This archive contains a collection of computational models called word embeddings. These are vectors that contain numerical representations of words. These have been trained on real language sentences collected from the English Wikipedia. As such, they contain contextual (thematic) knowledge about words (rather than taxonomic).

Capturing And Measuring Thematic Relatedness, Magdalena Kacmajor, John D. Kelleher

Articles

In this paper we explain the difference between two aspects of semantic relatedness: taxonomic and thematic relations. We notice the lack of evaluation tools for measuring thematic relatedness, identify two datasets that can be recommended as thematic benchmarks, and verify them experimentally. In further experiments, we use these datasets to perform a comprehensive analysis of the performance of an extensive sample of computational models of semantic relatedness, classified according to the sources of information they exploit. We report models that are best at each of the two dimensions of semantic relatedness and those that achieve a good balance between the …

Taxonomic Word Embeddings - Trained On English Wordnet Random Walk Pseudo-Corpora, Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher

Datasets

This archive contains a collection of computational models called word embeddings. These are vectors that contain numerical representations of words. They have been trained on pseudo-sentences generated artificially from a random walk over the English WordNet taxonomy, and thus reflect taxonomic knowledge about words (rather than contextual).

Surface Waves Over Currents And Uneven Bottom, Alan Compelli, Rossen Ivanov, Calin I. Martin, Michail D. Todorov

Articles

The propagation of surface water waves interacting with a current and an uneven bottom is studied. Such a situation is typical for ocean waves where the winds generate currents in the top layer of the ocean. The role of the bottom topography is taken into account since it also influences the local wave and current patterns. Specific scaling of the variables is selected which leads to approximations of Boussinesq and KdV types. The arising KdV equation with variable coefficients, dependent on the bottom topography, is studied numerically when the initial condition is in the form of the one soliton solution …

Riemann-Hilbert Problem, Integrability And Reductions, Vladimir Gerdjikov, Rossen Ivanov, Aleksander Stefanov

Articles

Abstract. The present paper is dedicated to integrable models with Mikhailov reduction groups G_R ≃ D_h. Their Lax representation allows us to prove, that their solution is equivalent to solving Riemann-Hilbert problems, whose contours depend on the realization of the G_R-action on the spectral parameter. Two new examples of Nonlinear Evolution Equations (NLEE) with D_h symmetries are presented.

Does It Take Three To Dance The Tango? Organizational Design, Triadic Structures And Boundary Spanning Across Subunits, Stefano Tasselli, Alberto Caimo

Articles

In this paper, we investigate the processes of boundary spanning across subunits within organizational networks. We hypothesize that patterns of advice across organizational subunits are explained by different triadic mechanisms depending on the organizational design of the intra-organizational network. In organizational networks characterized by flat hierarchy, we found triadic cyclic closure to be positively associated to boundary spanning across subunits; but when the network reflects an organizational structure with formal hierarchical differentiation among members, then we found triadic transitive closure to be associated to boundary spanning across subunits. We test these predictions in two empirical studies consisting of two organizational …

On The Cosmological Models With Matter Creation, Emil M. Prodanov, Rossen Ivanov

Articles

The matter creation model of Prigogine--Géhéniau--Gunzig--Nardone is revisited in terms of a redefined creation pressure which does not lead to irreversible adiabatic evolution at constant specific entropy. With the resulting freedom to choose a particular gas process, a flat FRWL cosmological model is proposed based on three input characteristics: (i) a perfect fluid comprising of an ideal gas, (ii) a quasi-adiabatic polytropic process, and (iii) a particular rate of particle creation. Such model leads to the description of the late-time acceleration of the expanding Universe with a natural transition from decelerating to accelerating regime. Only the Friedmann equations and the …

On The Time-Evolution Of Resonant Triads In Rotational Capillary-Gravity Water Waves, Rossen Ivanov, Calin I. Martin

Articles

We investigate an effect of the resonant interaction in the case of one-directional propagation of capillary-gravity surface waves arising as the free surface of a rotational water flow. Specifically, we assume a constant vorticity in the body of the fluid which physically corresponds to an underlying current with a linear horizontal velocity profile. We consider the interaction of three distinct modes and we obtain the dynamic equations for a resonant triad. Setting the constant vorticity equal to zero we recover the well known integrable three-wave system.

Benjamin-Ono Model Of An Internal Wave Under A Flat Surface, Alan Compelli, Rossen Ivanov

Articles

A two-layer uid system separated by a pycnocline in the form of an internal wave is considered. The lower layer is infinitely deep, with a higher density than the upper layer which is bounded above by a at surface. The uids are incompressible and inviscid. A Hamiltonian formulation for the dynamics in the presence of a depth-varying current is presented and it is shown that an appropriate scaling leads to the integrable Benjamin-Ono equation.

(E)-6,6′-(Diazene-1,2-Di­Yl)Bis­(1,10-Phenanthrolin-5-Ol) Tri­Chloro­Methane Disolvate: A Superconjugated Ligand, Muhib Ahmed, Michael Devereux, Vickie Mckee, Malachy Mccann, A. Denise Rooney

Articles

Phenanthroline ligands are important metal-binding mol­ecules which have been extensively researched for applications in both material science and medicinal chemistry. Azo­benzene and its derivatives have received significant attention because of their ability to be reversibly switched between the E and Z forms and so could have applications in optical memory and logic devices or as mol­ecular machines. Herein we report the formation and crystal structure of a highly unusual novel diazo-diphenanthroline compound, C24H14N6O2·2CHCl3.

Seasonal Variability Of Sediment Controls Of Carbon Cycling In An Agricultural Stream, Sophie Comer-Warner, Daren Gooddy, Sami Ullah, Luke Glover, Aishling Percival, Nicholas Kettridge, Stefan` Krause

Articles

Streams and rivers are‘active pipelines’where high rates of carbon (C) turnover can lead to globally importantemissions of carbon dioxide (CO2) and methane (CH4) from surface waters to the atmosphere. Streambed sedi-ments are particularly important in affecting stream chemistry, with rates of biogeochemical activity, and CO2and CH4concentrations far exceeding those in surface waters. Despite an increase in research on CO2and CH4instreambed sediments there is a lack of knowledge and insight on seasonal dynamics. In this study the seasonallyvariable effect of sediment type (sand-dominated versus gravel-dominated) on porewater C cycling, includingCO2and CH4concentrations, was investigated. We found high concentrations of CO2and CH4in the …

Hierarchical Cluster Analysis: A New Type Of Ranking Criteria Based On Arwu Ranking Data, Zhengshuo Li

Dissertations

The advent of big data leads to many applications of Machine Learning techniques. University rankings is one of the applicable domains, which is currently playing a crucial role in the assessment of the universities' performance. Currently, the rankings are usually carried out by some authoritative ranking institutions by means of weighting techniques and the results are conveyed in numerical rankings. Three of the most famous university ranking institutions have been introduced from a technical perspective. However, these institutions have been proven to be subjective in relation to their data selection and weighting method.

Using Supervised Learning To Predict English Premier League Match Results From Starting Line-Up Player Data, Runzuo Yang

Dissertations

Soccer is one of the most popular sports around the world. Many people, whether they are a fan of a soccer team, a player of online soccer games or even the professional coach of a soccer team, will attempt to use some relevant data to predict the result of a match. Many of these kinds of prediction models are built based on data from the match itself, such as the overall number of shots, yellow or red cards, fouls committed, etc. of the home and away teams. However, this research attempted to predict soccer game results (win, draw or loss) …

Predicting Violent Crime Reports From Geospatial And Temporal Attributes Of Us 911 Emergency Call Data, Vincent Corcoran

Dissertations

The aim of this study is to create a model to predict which 911 calls will result in crime reports of a violent nature. Such a prediction model could be used by the police to prioritise calls which are most likely to lead to violent crime reports. The model will use geospatial and temporal attributes of the call to predict whether a crime report will be generated. To create this model, a dataset of characteristics relating to the neighbourhood where the 911 call originated will be created and combined with characteristics related to the time of the 911 call. Geospatial …

Enhancing Partially Labelled Data: Self Learning And Word Vectors In Natural Language Processing, Eamon Mcentee

Dissertations

There has been an explosion in unstructured text data in recent years with services like Twitter, Facebook and WhatsApp helping drive this growth. Many of these companies are facing pressure to monitor the content on their platforms and as such Natural Language Processing (NLP) techniques are more important than ever. There are many applications of NLP ranging from spam filtering, sentiment analysis of social media, automatic text summarisation and document classification.

Performance Comparison Of Hybrid Cnn-Svm And Cnn-Xgboost Models In Concrete Crack Detection, Sahana Thiyagarajan

Dissertations

Detection of cracks mainly has been a sort of essential step in visual inspection involved in construction engineering as it is the commonly used building material and cracks in them is an early sign of de-basement. It is hard to find cracks by a visual check for the massive structures. So, the development of crack detecting systems generally has been a critical issue. The utilization of contextual image processing in crack detection is constrained, as image data usually taken under real-world situations vary widely and also includes the complex modelling of cracks and the extraction of handcrafted features. Therefore the …

Rapid Analysis Of Magnesium In Infant Formula Powder Using Laser-Induced Breakdown Spectroscopy, Maria Markiewicz-Keszycka, Ming Zhao, Xavier Cama-Moncunill, Toufic El Arnaout, Dana Becker, Colm O'Donnell, P. J. Cullen, Carl Sullivan, Maria Piedad Casado-Gavalda

Articles

Laser-induced breakdown spectroscopy (LIBS) was investigated to determine magnesium (Mg) content in infant formula powder. To predict Mg content in the range established by the Codex Alimentarius, a partial least squares regression (PLSR) model was developed using a calibration data set (n = 30) based on full cross-validation and validated using an independent validation data set (n = 21). The prediction model performance was evaluated using the regression coefficients of determination (Rcv2 = 0.94 and Rp2 = 0.85) with the root mean square errors on cross-validation and prediction (RMSECV = 60 mg kg−1 and RMSEP = 80 mg kg−1). The …

Thermostable Phytase In Feed And Fuel Industries, Ushasree Mrudula Vasudevan, Amit Jaiswal, Shyam Krishna, Ashok Pandey

Articles

Phytase with wide ranging biochemical properties has long been utilized in a multitude of industries, even so, thermostability plays a crucial factor in choosing the right phytase in a few of the sectors. Mesophilic phytases are not considered to be a viable option in the feed industry owing to its limited stability in the required feed processing temperature. In the recent past, inclusion of thermostable phytase in fuel ethanol production from starch based raw material has been demonstrated with economic benefits. Therefore, considerable emphasis has been placed on using complementary approaches such as mining of extremophilic microbial wealth, encapsulation and …

Hard: A Heterogeneity-Aware Replica Deletion For Hdfs, Hilmi Egemen Ciritoglu, John Murphy, Christina Thorpe

Articles

The Hadoop distributed fle system (HDFS) is responsible for storing very large datasets reliably on clusters of commodity machines. The HDFS takes advantage of replication to serve data requested by clients with high throughput. Data replication is a trade-of between better data availability and higher disk usage. Recent studies propose diferent data replication management frameworks that alter the replication factor of fles dynamically in response to the popularity of the data, keeping more replicas for in-demand data to enhance the overall performance of the system. When data gets less popular, these schemes reduce the replication factor, which changes the data …

Is There A Correlation Between Wikidata Revisions And Trending Hashtags On Twitter?, Paula Dooley

Dissertations

Twitter is a microblogging application used by its members to interact and stay socially connected by sharing instant messages called tweets that are up to 280 characters long. Within these tweets, users can add hashtags to relate the message to a topic that is shared among users. Wikidata is a central knowledge base of information relying on its members and machines bots to keeping its content up to date. The data is stored in a highly structured format with the added SPARQL protocol and RDF Query Language (SPARQL) endpoint to allow users to query its knowledge base.

Forecasting Anomalous Events And Performance Correlation Analysis In Event Data, Sonya Leech [Thesis]

Dissertations

Classical and Deep Learning methods are quite common approaches for anomaly detection. Extensive research has been conducted on single point anomalies. Collective anomalies that occur over a set of two or more durations are less likely to happen by chance than that of a single point anomaly. Being able to observe and predict these anomalous events may reduce the risk of a server’s performance. This paper presents a comparative analysis into time-series forecasting of collective anomalous events using two procedures. One is a classical SARIMA model and the other is a deep learning Long-Short Term Memory (LSTM) model. It then …

Predicted Temperature-Increase-Induced Global Health Burden And Its Regional Variability, Jae Young Lee, Ho Kim, Antonio Gasparrini, Ben Armstrong, Michelle L. Bell, Franceso Sera, Eric Lavingne, Rosana Abrutzky, Shilu Tong, Micheline De Sousa Zanotti Stagliorio Coelho, Paulo Hilario Nascimento Saldiva, Patricia Matus Correa, Nicolas Valdes Ortega, Haidong Kan, Samule Osorio Garcia, Jan Kysely, Ales Urban, Hans Orru, Ene Indermitte, Jouni J.K. Jaakkola, Niilo R.I. Ryti, Mathilde Pascal, Patrick J. Goodman, Ariana Zeka, Paolo Michelozzi, Matteo Scortichini, Masahiro Hashizume, Yasushi Honda, Magali Hurtado, Julio Cruz, Xerxes Seposo, Balthazar Nunes, Joao Paulo Teixeira, Aurelio Tobias, Carmen Iniguez, Bertil Forsberg, Christofer Astrom, Ana Maria Vicedo-Cabrera, Martina S. Ragettli, Yeu-Liang Leon Guo, Bing-Yu Chen, Antonella Zanobetti, Joel Schwartz, Tran Ngoc Dang, Dung Do Van, Fetemeh Mayvaneh, Ala Overcenco, Shanshan Li, Yuming Guo

Articles

An increase in the global health burden of temperature was projected for 459 locations in 28 countries worldwide under four representative concentration pathway scenarios until 2099. We determined that the amount of temperature increase for each 100 ppm increase in global CO2 concentrations is nearly constant, regardless of climate scenarios. The overall average temperature increase during 2010–2099 is largest in Canada (1.16 °C/100 ppm) and Finland (1.14 °C/100 ppm), while it is smallest in Ireland (0.62 °C/100 ppm) and Argentina (0.63 °C/100 ppm). In addition, for each 1 °C temperature increase, the amount of excess mortality is increased largely in …

3d Growth Substrates In Mammalian Cell Culture In Vitro, Their Effects On Cellular Function And Response, Mahmoud Gargotti

Doctoral

Three-dimensional (3D) cell culture systems have gained increasing interest in drug discovery and tissue engineering due to a number of advantages in providing more physiologically relevant information and potentially more predictive data for in vivo tests. Extracellular matrix (ECM) proteins have been developed over in recent years to simulate a natural microenvironment for cells cultured in vitro. Conventional cell culture or 2D cell culture form monolayers of cells on a solid surface, which is typically polystyrene or glass, whereas a 3D culture system employ a porous growth matrix on which the cells grow. The transition from cell culture on a …

Bigger Versus Similar: Selecting A Background Corpus For First Story Detection Based On Distributional Similarity, Fei Wang, Robert J. Ross, John D. Kelleher

Articles

The current state of the art for First Story Detection (FSD) are nearest neighbourbased models with traditional term vector representations; however, one challenge faced by FSD models is that the document representation is usually defined by the vocabulary and term frequency from a background corpus. Consequently, the ideal background corpus should arguably be both large-scale to ensure adequate term coverage, and similar to the target domain in terms of the language distribution. However, given these two factors cannot always be mutually satisfied, in this paper we examine whether the distributional similarity of common terms is more important than the scale …

Cs1: How Will They Do? How Can We Help? A Decade Of Research And Practice, Keith Quille, Susan Bergin

Articles

Background and Context: Computer Science attrition rates (in the western world) are very concerning, with a large number of students failing to progress each year. It is well acknowledged that a significant factor of this attrition, is the students’ difficulty to master the introductory programming module, often referred to as CS1.

Objective: The objective of this article is to describe the evolution of a prediction model named PreSS (Predict Student Success) over a 13-year period (2005–2018).

Method: This article ties together, the PreSS prediction model; pilot studies; a longitudinal, multi-institutional re-validation and replication …