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A genetic algorithm for the optimization of multi-threshold trading strategies in the directional changes paradigm
Full text linkThis paper proposes a novel genetic algorithm to optimize recommendations from multiple trading strategies derived from the Directional Changes (DC) paradigm. DC is an event-based approach that differs from the traditional physical time data, which employs fixed time intervals and uses a physical time scale. The DC method records price movements when specific events occur instead of using fixed intervals. The determination of these events relies on a threshold, which captures significant changes in price of a given asset. This work employs eight trading strategies that are developed based on directional changes. These strategies were profiled using varying values of thresholds to provide a comprehensive analysis of their effectiveness. In order to optimize and prioritize the conflicting recommendations given by the different trading strategies under different DC thresholds, we are proposing a novel genetic algorithm (GA). To analyze the GA’s trading performance, we utilize 200 stocks listed on the New York Stock Exchange. Our findings show that it can generate highly profitable trading strategies at very low risk levels. The GA is also able to statistically and significantly outperform other DC-based trading strategies, as well as 8 financial trading strategies that are based on technical indicators such as aroon, exponential moving average, and relative strength index, and also buy-and-hold. The proposed GA is also able to outperform the trading performance of 7 market indices, such as the Dow Jones Industrial Average, and the Standard & Poors (S&P) 500
Long-Distance Nationalism and Peace Settlement Preferences
No full textAcross the world diasporas engage with the politics of their country of origin and diaspora activism can play a critical role in homeland conflicts. While some scholars claim that stronger nationalist preferences on the part of diaspora lead to conflicts becoming intensified and prolonged there has been little empirical investigation into how diaspora and homeland preferences may differ. Drawing upon the literature on long distance nationalism this article develops a framework that operationalises and tests expectations that there will be differences in the preferences between populations living in conflict zones and those living abroad as they relate to potential conflict resolution and peace settlement solutions. These expectations are evaluated in a study of preferences towards peace settlements across two deeply divided communities in Cyprus and their overseas diasporas. In contrast to claims that members of the diaspora have more nationalist views than homeland members our investigation finds that diaspora and homeland preferences either mirror each other or diaspora preferences are more peace supporting. We discuss implications for theory and policy
Robust Support for New Student (SEEQ-S) and Teacher (TEEQ-S) Teaching Effectiveness Instruments: Multitrait-Multimethod Study of Student-Teacher Agreement on 15 Teaching Effectiveness Factors and Student Growth in Secondary Schools
Full text linkAutomating Appliance Verification in Facilities Management using a Denoised Voltage-Current Feature Extraction and Classification Pipeline
Full text linkFacilities Management (FM) companies can use load monitoring of electrical appliances (assets) to track energy consumption and predictive maintenance. Reliable algorithms are needed to automatically identify or verify appliances through their energy signatures to improve efficiencies during installation and inspection tasks. Most approaches rely on Voltage-Current (V-I) trajectory. These features are extracted from steady-state current and voltage signals. However, these methods often assume signals are uniformly sampled. In real-world conditions, this assumption does not always hold, leading to misclassified steady-state events when signals are noisy. This paper introduces a novel feature extraction and classification pipeline to ensure the validity of detected steady-state events. The approach measures the approximate entropy of current signals and their correlation with voltage to extract denoised features for appliance type classification. The proposed pipeline is evaluated on a large-scale real-world operational dataset spanning multiple appliance categories. We demonstrate that the extracted denoised features significantly improve the performance of Machine Learning models (ML) used for appliance type classification. Finally, we present a deployment framework for FM settings, enabling digital cataloguing of appliances informing businesses on sustainable choices for appliance requirements
Enhancing equity-oriented evidence-based practice in speech and language therapy
Full text linkBackground
Evidence-based practice (EBP) is a commonly adopted framework for guiding health professionals’ clinical decision-making, urging the incorporation of scientific evidence, patient preferences and clinical expertise. There are many barriers to EBP, and the mainstream research processes underpinning it are not infallible. Notably, traditional approaches to EBP seldom apply an equity lens, which risks perpetuating harmful practices and inequities.
Aims
The primary aim of the thesis is to draw together seven prior publications and explicate their role in enhancing research processes, to facilitate EBP. Simultaneously, it aims to demonstrate how these enhancements can support an equity-oriented EBP.
Methods
Responding to research questions which connect the seven publications and guide this thesis, a grounded theory approach is applied to produce a critical synthesis. Collaborative research priority-setting projects and leveraging of routinely collected data are explored with regards to their capacity to facilitate EBP.
Findings
The grounded theory highlights that avenues for dialogue between EBP stakeholders may promote the production of meaningful (and equity-oriented) evidence more suited to transfer into practice. The seven studies present two such avenues: (1) co-producing research agendas with those with lived experience of a clinical need, to ensure clinical evidence gaps are filled and (2) leveraging practice-based, routinely collected data, to augment and supplement traditional research approaches, and optimise their relevance for practice.
Discussion
Systemically embedding dialogic pathways (including co-produced research priorities and use of routinely collected data) between EBP stakeholders is proposed to enhance research and facilitate EBP. This work highlights a new concept: Equity-oriented Dialogic Evidence-Based Praxis (ED-EBP). A radical shift in existing dynamics between researchers, practitioners and service users is required, to collaboratively create evidence that is equity-oriented, and suitable for practice. Further work is required to scrutinise how dialogic pathways can be embedded, and the challenges to doing so mitigated
Associations between space-use behaviour and temperature-humidity index in barn-housed dairy cows
Full text linkCattle may modify their space-use behaviour as thermal conditions change within their environment. Here we examined the relationship between the temperature-humidity index (THI) and various space-use metrics in a UK barn-housed dairy cow herd. Using a real-time local positioning system, as part of a precision livestock farming (PLF) approach, we continuously tracked the spatial position and activity of cows at high temporal resolution from 1st June to 1st December 2024. Localised ambient barn temperature and relative humidity were also continuously monitored within the barn. We assessed the amount of time individuals spent in key resource areas, their activity levels, distance travelled, and z-axis values, as well as bunching behaviour based on four metrics: range size (individual and herd), intercow distance (ICD) and nearest neighbour distance (NND). Cows spent more time near water troughs and fans as THI increased, and less time in the feeding zone under higher THI, except during early morning hours. Time spent in the cubicle area varied by time of day. Activity increased with rising THI except during the late evening. When high sensor-recorded activity values were recorded, cows travelled further with increasing THI during the day. Additionally, z values increased with increasing THI during the day, suggesting cows spent more time standing. Bunching behaviour also changed with increasing THI: ICD decreased and individual range size increased. Patterns for NND were unclear. Monitoring space-use metrics such as proximity to resources and bunching behaviour, alongside activity levels, may provide early behavioural indicators of heat stress in livestock. Further research is needed to assess the generality of these indicators across different barn environments, to help inform welfare and production management
Creating an app outline and co-design guidelines for artificially intelligent driven software to support CBTp practitioners working with clients experiencing first episode psychosis
Full text linkPsychosis presents a somewhat unique challenge to individual sufferers, the clinicians and services that support them, and the NHS broadly. This is due to the complex presentation of psychosis, which often co-occurs with or precipitates a myriad of co-morbidities, which often result in decreased quality and length of life. One of the NICE-recommended treatments for first episode psychosis is the delivery of Cognitive Behavioural Therapy for psychosis (CBTp). The delivery of CBTp is challenging and complicated, requiring fidelity to the model, treatment coordination with multiple stakeholders, and a significant administrative burden. Artificial Intelligence (AI) was considered as a potentially valuable contribution to supporting practitioners in their work. Initial explorations identified two gaps in the research: first, there was no evidence of applications leveraging AI specifically in support of CBTp practitioners; second, there was a lack of methodological coherence in the research regarding the development of software applications in mental health contexts. To address these gaps, this research set out to develop a design outline for an AI-driven software application and in doing so, create a methodological guideline to inform future research. An initial systematic literature review identified action research as the methodological foundation for this research project. With this in hand, a working group of CBTp practitioners was formed, and the CBTp Companion app was created. Positive stakeholder feedback on the app focused on its potential to enhance coordination and collaboration, help maintain fidelity to the CBTp model, and lift some of the administrative burden from practitioners. A key caution was that the app should aid but not replace practitioners. The Working Group’s experience enacting a research culture that allowed them to wrestle with complex and sensitive issues related to professionalism, ethics, and the therapeutic relationship allowed them to develop and articulate a co-design guideline rooted in the very process it seeks to influence
A Cyber Risk Economics Model for Organization-Wide Risk Management (CYREM-ORM)
Full text linkThe increasing sophistication of cyber risks has made it challenging for organizations to assess their business impacts. The key challenge is the technical and language “barrier” between cybersecurity teams and business teams who make strategic investment decisions on cybersecurity. This often leads to delays, budget issues that prevent timely responses to cyber incidents. Existing research lacks a transparent, traceable, and reproducible method to communicate cyber risks and their impacts on businesses. We introduce a novel cyber risk economics model for organization-wide risk management (CYREM-ORM) that captures complex cyber risks and expresses them using financial terms. This is achieved by mapping Cyber Threat Intelligence (CTI) to the Factor Analysis of Information Risk (FAIR) model, enriched by cyber cost typologies. CYREM-ORM provides a traceable workflow that links organisation-related CTI to FAIR factor estimation, cost breakdowns, and ultimately to monetary loss amounts and prioritised risk scenarios. This design improves transparency in risk management, helps organisations prioritise mitigations in line with strategic business objectives, and enables stakeholders to assess the rationale behind results when needed. By grounding risk parameters in CTI, the model also facilitates proactive screening of organisation-relevant threats, instead of reactive, control-gap reporting. We evaluate the CYREM-ORM through three complementary case studies: the 2017 Equifax breach case proves its feasibility with historical data and open-source CTI, while the Small and Medium Enterprise (SME) education company and the large retail company cases show its effectiveness in communicating cyber risks at an organizational-wide strategic level within real-world contexts
Cogformer: A unified multi-scale brain representation for visual decoding and reconstruction from fMRI
Full text linkTill the Rules of Procedure and Evidence Do Us Part: Should Deceased Persons Be Admitted as Victims before the ICC?
Full text linkCan convicted persons at the ICC get away with murder? In the context of victim representation for participation and reparations, this has already happened. For many years, ICC case law ruled that victims who died before applying for participation and reparations could not be represented posthumously, rendering deceased persons practically invisible in that dimension of proceedings. However, a minority opinion arguing that the views, concerns, and reparations claims of some deceased victims should be considered is gaining renewed traction. The ICC now stands at a crossroads between two diametrically opposed interpretations. The approach ultimately adopted will affect the accountability of convicted persons, the ICC’s role in truth-telling, and its legacy. This article argues that excluding applications on behalf of deceased victims is flawed and advocates abandoning unduly restrictive interpretations in favour of a consistent, victim-centred and human rights–anchored approach