Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Organisational Information Security Management: The Impact of Training and Awareness

Security breaches that affect personal data and organisational systems have become increasingly significant in the global technology (IT) industry. There is scope for research on the factors that influence user behaviour and attitudes toward this aspect of information security and their impact on organisation's network integrity. This research aims to study the critical success factors (CSF) for employees in order to comply with the organisational information security policy with a view to mitigating security breaches. Information security can be managed through three separate mechanisms: organisational factors, behavioural factors and training. Each of these elements impact differently on information security and comprehensive solutions include combinations of all three. The findings provide empirically evaluated information regarding the obstacles and the effective factors in employees' compliance with the implementation of the information security policy. The identified categories of factors are followed differently by employees working in Health, Business and Education. Questionnaire analysis as part of this study suggests that employees in the health sector comply the most in adhering with information security policy as compared to other sectors. One of the reasons for this is that health sector employees have better awareness, robust communication and effective training programmes with reinforcement and satisfaction. Moreover, employees in the health sector believe in the norms of security policies and have a positive attitude, as they recognise the significance of security policies, unlike the business and education sectors.
Estimated-error/tap-output correlation analysis for LMS order adaptation

This paper presents a zero-tap detection algorithm which works well with the LMS algorithm used to estimate the sparse channel that can be approximated by the FIR model. The proposed algorithm is achieved by considering the estimated-error/tap-output correlation. The simulation results shows that the proposed technique successfully identifies all zero taps and helps to improve the filter's asymptotic performance.
Task-level Optimization Prototype Public Project Title Advanced Compiler Technologies for Embedded Streaming Title of Deliverable Task-level Optimization Prototype Author(s)/affiliation

This deliverable describes the task-level optimization libraries designed for the ACOTES tool chain. Based on the polyhedral model of compilation, these libraries support automatic parallelization and adaptation of thread-level parallelism to a target. The libraries can also be applied to loop nest optimization of single-threaded code. Early experimental validation is described in the document, as well as associated publications.
Biodiversity Increases the Productivity and Stability of Phytoplankton Communities

Global biodiversity losses provide an immediate impetus to elucidate the relationships between biodiversity, productivity and stability. In this study, we quantified the effects of species richness and species combination on the productivity and stability of phytoplankton communities subject to predation by a single rotifer species. We also tested one mechanism of the insurance hypothesis: whether large, slow-growing, potentially-defended cells would compensate for the loss of small, fast-growing, poorly-defended cells after predation. There were significant effects of species richness and species combination on the productivity, relative yield, and stability of phytoplankton cultures, but the relative importance of species richness and combination varied with the response variables. Species combination drove patterns of productivity, whereas species richness was more important for stability. Polycultures containing the most productive single species, Dunaliella, were consistently the most productive. Yet, the most species rich cultures were the most stable, having low temporal variability in measures of biomass. Polycultures recovered from short-term negative grazing effects, but this recovery was not due to the compensation of large, slow-growing cells for the loss of small, fast-growing cells. Instead, polyculture recovery was the result of reduced rotifer grazing rates and persisting small species within the polycultures. Therefore, although an insurance effect in polycultures was found, this effect was indirect and unrelated to grazing tolerance. We hypothesize that diverse phytoplankton assemblages interfered with efficient rotifer grazing and that this “interference effect” facilitated the recovery of the most productive species, Dunaliella. In summary, we demonstrate that both species composition and species richness are important in driving patterns of productivity and stability, respectively, and that stability in biodiverse communities can result from an alteration in consumer functioning. Our findings underscore the importance of predator-prey dynamics in determining the relationships between biodiversity, productivity and stability in producer communities.
Enabling access to information and knowledge: A report on new tools – Enable and Unify – for conducting federated search of distributed content, extraction and management of metadata, and development of user-centered views of content

Current thinking concerning individual and organizational performance questions the ability of conventional, formal training strategies to address gaps, given the volume and rate of change in modern business environments. Increasingly, there is an emphasis on the role of improved information access and informal learning, both in the fields of learning and KM. However, despite the advances in technology to capture and store information and knowledge, our ability to search for useful information remains limited (and may even be degrading as information mounts). In this paper we discuss the problem and evaluate some existing solutions: centralized content management strategies and platforms, and federated search. We present a new solution in the form of advanced federated search tools and a metadata management application that are part of a new release of an industry-leading learning content management system, ForceTen, from Eedo Knowledgeware Corp.
A reinforcement learning scheme for a multi-agent card game

We formulate an automatic strategy acquisition problem for the multi-agent card game "hearts" as a reinforcement learning (RL) problem. Since there are often a lot of unobservable cards in this game, RL is approximately dealt with in the framework of a partially observable Markov decision process (POMDP). This article presents a POMDP-RL method based on estimation of unobservable state variables and prediction of actions of the opponent agents. Simulation results show our model-based POMDP-RL method is applicable to a realistic multi-agent problem.
Aerodynamic characteristics of flying fish in gliding flight

SUMMARY The flying fish (family Exocoetidae) is an exceptional marine flying vertebrate, utilizing the advantages of moving in two different media, i.e. swimming in water and flying in air. Despite some physical limitations by moving in both water and air, the flying fish has evolved to have good aerodynamic designs (such as the hypertrophied fins and cylindrical body with a ventrally flattened surface) for proficient gliding flight. Hence, the morphological and behavioral adaptations of flying fish to aerial locomotion have attracted great interest from various fields including biology and aerodynamics. Several aspects of the flight of flying fish have been determined or conjectured from previous field observations and measurements of morphometric parameters. However, the detailed measurement of wing performance associated with its morphometry for identifying the characteristics of flight in flying fish has not been performed yet. Therefore, in the present study, we directly measure the aerodynamic forces and moment on darkedged-wing flying fish (Cypselurus hiraii) models and correlated them with morphological characteristics of wing (fin). The model configurations considered are: (1) both the pectoral and pelvic fins spread out, (2) only the pectoral fins spread with the pelvic fins folded, and (3) both fins folded. The role of the pelvic fins was found to increase the lift force and lift-to-drag ratio, which is confirmed by the jet-like flow structure existing between the pectoral and pelvic fins. With both the pectoral and pelvic fins spread, the longitudinal static stability is also more enhanced than that with the pelvic fins folded. For cases 1 and 2, the lift-to-drag ratio was maximum at attack angles of around 0 deg, where the attack angle is the angle between the longitudinal body axis and the flying direction. The lift coefficient is largest at attack angles around 30∼35 deg, at which the flying fish is observed to emerge from the sea surface. From glide polar, we find that the gliding performance of flying fish is comparable to those of bird wings such as the hawk, petrel and wood duck. However, the induced drag by strong wing-tip vortices is one of the dominant drag components. Finally, we examine ground effect on the aerodynamic forces of the gliding flying fish and find that the flying fish achieves the reduction of drag and increase of lift-to-drag ratio by flying close to the sea surface.
CADMANT: Context Anomaly Detection for MAintenance and Network Troubleshooting

In telecommunications network troubleshooting, analytical applications are widely used. Such applications typically use CEP (Complex Event Processing) and SQL queries for data processing and network analysis. Performance engineers need in-depth knowledge of both the telecommunications domain and telecommunications data structures in order to create the required queries. Moreover valuable information contained in free form text data fields such as “additional_info”, “user_text” or “problem_text” can also be ignored. This work proposes CADMANT: Context Anomaly Detection for MAintenance and Network Troubleshooting. Traditional approaches focus on a specific record type and create specific cause and effect rules. With the CADMANT approach all free form text fields of alarms, logs, etc. are treated as text documents similar to Twitter feeds. CADMANT uses distance based outlier detection within sliding windows to detect abnormal terms at configurable time intervals. The CADMANT approach provides automated analysis without the requirement for SQL/CEP queries and provides distinct network insights in comparison to traditional approaches.
Genome-Wide Patterns of Genetic Polymorphism and Signatures of Selection in Plasmodium vivax

Plasmodium vivax is the most prevalent human malaria parasite outside of Africa. Yet, studies aimed to identify genes with signatures consistent with natural selection are rare. Here, we present a comparative analysis of the pattern of genetic variation of five sequenced isolates of P. vivax and its divergence with two closely related species, Plasmodium cynomolgi and Plasmodium knowlesi, using a set of orthologous genes. In contrast to Plasmodium falciparum, the parasite that causes the most lethal form of human malaria, we did not find significant constraints on the evolution of synonymous sites genome wide in P. vivax. The comparative analysis of polymorphism and divergence across loci allowed us to identify 87 genes with patterns consistent with positive selection, including genes involved in the “exportome” of P. vivax, which are potentially involved in evasion of the host immune system. Nevertheless, we have found a pattern of polymorphism genome wide that is consistent with a significant amount of constraint on the replacement changes and prevalent negative selection. Our analyses also show that silent polymorphism tends to be larger toward the ends of the chromosomes, where many genes involved in antigenicity are located, suggesting that natural selection acts not only by shaping the patterns of variation within the genes but it also affects genome organization.
Thermal decoupling of WIMPs from first principles

Weakly interacting massive particles (WIMPs) are arguably the most natural dark matter candidates from a particle physics point of view. After their number density has frozen out in the early universe, thereby setting their relic density today, WIMPs are still kept very close to thermal equilibrium by scattering events with standard model particles. The complete decoupling from the thermal bath happens as late as at temperatures of around ∼1−10 MeV and provides an important cosmological scale that can directly be translated into a small scale cut-off of the spectrum of matter density fluctuations. We present here a full analytic treatment of the kinetic decoupling process from first principles. This allows an exact determination of the decoupling scale, for arbitrary WIMP candidates and any scattering amplitude. As an application, we consider the situation of the lightest supersymmetric particle as well as the lightest Kaluza–Klein particle that arises in theories with universal extra dimensions; furthermore, we show that our formalism can also easily be applied to, e.g., the evolution of the non-relativistic electrons into the recombination regime. Finally, we comment on the impacts for the smallest gravitationally bound structures and the prospects for the indirect detection of dark matter.
LeSiNN: Detecting Anomalies by Identifying Least Similar Nearest Neighbours

We introduce the concept of Least Similar Nearest Neighbours (LeSiNN) and use LeSiNN to detect anomalies directly. Although there is an existing method which is a special case of LeSiNN, this paper is the first to clearly articulate the underlying concept, as far as we know. LeSiNN is the first ensemble method which works well with models trained using samples of one instance. LeSiNN has linear time complexity with respect to data size and the number of dimensions, and it is one of the few anomaly detectors which can apply directly to both numeric and categorical data sets. Our extensive empirical evaluation shows that LeSiNN is either competitive to or better than six state-of-the-art anomaly detectors in terms of detection accuracy and runtime.
Transitional Justice in the Twenty-First Century: Justice at the grassroots? Gacaca trials in Rwanda

On April 6, 1994, a plane carrying the presidents of Rwanda and Burundi was shot down as it approached the airport in the Rwandan capital, Kigali, killing all on board. The assassination of President Juvenal Habyarimana served as a pretext for launching a long-planned program to eliminate political rivals to the president and his supporters. Violence was initially focused in the capital, as the presidential guard and other elite troops targeted opposition politicians and civil society activists of all ethnicities. As the group of military and political leaders who assumed control of Rwanda carried the violence into every corner of the country, however, it quickly assumed the clear characteristics of genocide, since it focused on Rwanda's minority ethnic group, the Tutsi, regardless of their political activity, class, age, or gender. By the time the rebel Rwandan Patriotic Front (RPF) took control of the country in mid-July 1994, more than half a million people had been killed. In the decade since the 1994 genocide and war, the government of Rwanda has undertaken a variety of programs to attempt to promote reconciliation, combat impunity, and prevent future communal violence. The government has built numerous memorials and established annual commemorations of the genocide, sought to create unity by adopting a new national anthem, flag, and seal, overseen the drafting of a new constitution and various political reforms, and instituted programs, including “solidarity camps” for students, former prisoners, and returned refugees to teach a revised history of the country.
A novel way to understand plant species preferences in relation to groundwater discharge conditions using a trait‐based approach

Groundwater discharge sites harbour characteristic and often rare plant communities that differ substantially from groundwater recharge sites. It is not known which abiotic conditions at these sites drive the differences in community composition. A trait‐based approach, which relates species traits to abiotic conditions, may provide insight in this relationship and improve conservation management of these characteristic communities. We used this approach to identify the following: (i) dominant abiotic conditions that shape plant communities at discharge sites and (ii) characteristic traits associated with these abiotic conditions. First, we performed a (qualitative) literature survey to relate plant traits to various abiotic conditions at discharge sites. Second, we performed a meta‐analysis to quantitatively test the trait selection at discharge sites. For the meta‐analysis, we compiled a species discharge preference database (n = 170), based on literature and field data. We performed linear regression to relate traits to species discharge preference. Only 5 out of the 11 traits tested (low leaf phosphorus content, high leaf N:P, low rate of clonal reproduction, low maximum height and high seed mass) were significantly related to discharge preference, while the explained variance was low (R2 < 0.09). Our results suggest the following: (i) Despite the inclusion of traits specifically related to prevailing local environmental conditions, beyond commonly applied traits, hardly any differences were revealed; this indicates a need for more comprehensive eco‐physiological understanding (and information on the selection of combinations of traits). (ii) A trait‐based approach may not be highly distinctive in environments differing in only a few specific characteristics. Copyright © 2015 John Wiley & Sons, Ltd.
Building the IPO Order Book: Underpricing and Participation Limits with Costly Information

This paper examines the book building mechanism for marketing initial public offerings. We present a model where the underwriter selects a group of investors along with a pricing and allocation mechanism in a way that maximizes the information generated during the process of going public at a minimum cost. Unlike previous models, we take into account the moral hazard problem that is faced by investors when evaluation is costly. Our results suggest that for firms with the most to gain from accurate pricing, the number of investors participating in the offering is larger, and underpricing will be greater. When the demand for accuracy is relatively low, the expected amount of underpricing exactly offsets the investors' costs of acquiring information. However, when the demand for accuracy is high, the expected amount of underpricing can exceed the cost of information and investors can earn rents.
Decision-Theoretic Evaluation of Design Choices in a Case-Based Environment

We present a unique methodology that combines case-based design, explanation-based reasoning, and decision theory for the evaluation of design alternatives. Our technique uses: (1) case-based reasoning to generate design alternatives, (2) explanation-based reasoning to assign subjective probabilities to the possible values of missing design specifications, and to assign subjective utilities based on multiple criteria to the design alternatives, and (3) decision theory to find the best alternative. Our technique integrates case-based design and decision theory, and offers a way to deal with missing and incomplete design specifications and to document and explain design decision making and intent. The methodology has been implemented in an intelligent, case-based system in the domain of pharmaceutical design.
Investigation of a Co-Axial Dual-Mechanical Ports Flux-Switching Permanent Magnet Machine for Hybrid Electric Vehicles

In this paper, a co-axial dual-mechanical ports flux-switching permanent magnet (CADMP-FSPM) machine for hybrid electric vehicles (HEVs) is proposed and investigated, which is comprised of two conventional co-axial FSPM machines, namely one high-speed inner rotor machine and one low-speed outer rotor machine and a non-magnetic ring sandwiched in between. Firstly, the topology and operation principle of the CADMP-FSPM machine are introduced; secondly, the control system of the proposed electronically-controlled continuously-variable transmission (E-CVT) system is given; thirdly, the key design specifications of the CADMP-FSPM machine are determined based on a conventional dual-mechanical ports (DMP) machine with a wound inner rotor. Fourthly, the performances of the CADMP-FSPM machine and the normal DMP machine under the same overall volume are compared, and the results indicate that the CADMP-FSPM machine has advantages over the conventional DMP machine in the elimination of brushes and slip rings, improved thermal dissipation conditions for the inner rotor, direct-driven operation, more flexible modes, lower cogging torque and torque ripple, lower total harmonic distortion (THD) values of phase PM flux linkage and phase electro-motive force (EMF), higher torque output capability and is suitable for the E-CVT systems. Finally, the pros and cons of the CADMP-FSPM machine are highlighted. This paper lays a theoretical foundation for further research on CADMP-FSPM machines used for HEVs.
Learning Only When Necessary: Better Memories of Correlated Patterns in Networks with Bounded Synapses

Learning in a neuronal network is often thought of as a linear superposition of synaptic modifications induced by individual stimuli. However, since biological synapses are naturally bounded, a linear superposition would cause fast forgetting of previously acquired memories. Here we show that this forgetting can be avoided by introducing additional constraints on the synaptic and neural dynamics. We consider Hebbian plasticity of excitatory synapses. A synapse is modified only if the postsynaptic response does not match the desired output. With this learning rule, the original memory performances with unbounded weights are regained, provided that (1) there is some global inhibition, (2) the learning rate is small, and (3) the neurons can discriminate small differences in the total synaptic input (e.g., by making the neuronal threshold small compared to the total postsynaptic input). We prove in the form of a generalized perceptron convergence theorem that under these constraints, a neuron learns to classify any linearly separable set of patterns, including a wide class of highly correlated random patterns. During the learning process, excitation becomes roughly balanced by inhibition, and the neuron classifies the patterns on the basis of small differences around this balance. The fact that synapses saturate has the additional benefit that nonlinearly separable patterns, such as similar patterns with contradicting outputs, eventually generate a subthreshold response, and therefore silence neurons that cannot provide any information.