Multi-Sensor based Human Activity Recognition

Dataset Description Multi-sensor data collection has been done in June,2021 at Coventry University. In this data collection, three types of sensors (Radar, InfraRed and Acoustic) were fused together by a MATLAB code. There were one sensor for radar and acoustic sensors each and three IR (Grid-Eye) sensors were integrated together to eliminate limitation of a single sensor and to get maximum benefit of Multi-Sensor Human Activity Detection. Overall, 11 subjects took part in the data-collection process which were mainly post graduate researched and academics. Collected dataset is novelty in itself as in this experiment, a series of human activities were performed rather than performing a single activity each time. The experiment was designed carefully by keeping elderly people in the mind. Each series comprise of some day-to-day activities such as walking, sitting, talking and so on. It also has some situation which need attention such as fall, asking for help and so on. In this data collection, seven set of activities were recorded among which series one to three were single subject and series four to seven were dual subject activities. Each series was performed ten times by each subject. Each series of activities were performed ten times by each subject. Description of each series is given below. Series Number of Subject Activity Series-1 Single Sit(talking)+SitTostanding(help)+walking(leftToright)(caughing)+falling(screaming) Series-2 Single Bending (Pickup Food) +walk (Right to Left) (coughing)+stand to sit(talking)+sit while eating Series-3 Single walking corner left diagonally to corner right (drop a metal spoon) +return (diagonally +help) +bending to take the spoon(talk)+standing from Bending(scream)+walking to the original corner (drop the spoon) In the folder of Data_Collection, seven folders of Series-1 to Series-7 are present. In each folder, number of series are present which were performed by each subject 10 times. Each performed series has a folder of sensor data in it. The content of sensor data and its description is given below. Sr No. File Name Type Description 1 AudioFiles (Folder) Wav File This data is collected by UMA-16 Acoustic sensor which captures sound while performing activity series 2 AcousticData MATLAB File It is in the form of 16 Channel data which has numerical values collected from Acoustic Sensor 3 GridEyeData MATLAB File Three data files data1, data2 and data3 from three GridEye Sensors were collected and it has time stamps for each frame captured in the form of t1, t2 and t3. Please refer GridEye_Read for the readable form of data1, data2 and data3 4 RadarData MATLAB Data It has range and noise data (rpVar, npVar), RangeDopplerMatrix (no. of Framesx16x256) and rangeDopplerVarArray (Frame No.x256) 5 Miscellaneous Data MATLAB File This folder has important information such as drivers name (IR Sensor), frame length, sampling frequency, folder path, current time, total experiment time and so on. Data of each sensor can be read in MATLAB and can also be visualised. It can also be converted in python data file. This pre-processing will be done before data analysis

Redefining Peace in a Shifting World:IGAD, South Sudan, and the New African Security Paradigm

This book offers a groundbreaking exploration of the Intergovernmental Authority on Development (IGAD)’s role in peace-making in the Horn of Africa (HoA), focusing on its efforts in the South Sudan conflict. Blending rigorous academic analysis with practitioner insights, it shows how IGAD’s distinctive, adaptable approach challenges Eurocentric models of peace, security governance, and regional integration. Drawing on extensive fieldwork and interviews across East Africa, the book examines African regionalism, Pan-Africanism, hybrid governance, and the decolonisation of peace theory and practice. It traces IGAD’s facilitation of the 2018 peace agreement, revealing how the organisation weaves together contending ideas and practices of peace. Through strategic hybridisation and platformisation, it underscores African agency and calls for reimagining peace, security, and integration from an African perspective. This book is essential reading for scholars, policymakers, and anyone interested in African peace processes, global governance, regional organisations, and the politics of peace in the Global South

Pricing Models for IoT and AI-Enhanced Sensor Monitoring Apps

The paper presents the development of a pricing strategy for a company that develops a sensor monitoring app leveraging IoT and AI technologies to enhance operational efficiency and connectivity. In alignment with the company's client objectives of predicting failures and improving operational engagement, the app's development followed a structured process. This process encompassed a Customer Value Proposition Workshop, Scenario and Affordance Analyses, Client Validation, Features Analysis, and Pricing Strategy. Through these steps, critical customer needs were identified and integrated into the app's features, supported by iterative feedback from the company's engineering department. Affordance theory was adopted as the theoretical lens and was proven instrumental in identifying how IoT can achieve operational goals by guiding the app's feature development. The pricing strategy employed value-based bundling and psychological pricing to enhance market appeal. This research highlights the transformative potential of IoT and AI in engineering consultancy, driving tailored solutions and operational excellence

"Who Killed the Writer? Intertextual Clues in Cristina Rivera Garza’s ‘El perfil de él’” in Fifty Shades of Latin American Noir: Alternative Models of Criminality and Detection, ed. Carolina Miranda.

<br/

Circularity potentials, influential factors, modeling approach and policy interventions of circular supply chain for electric vehicles

Electric vehicles (EVs) provide a primary alternative for mitigating greenhouse gas emissions in the transportation sector. Nonetheless, their extensive use poses concerns, including a rise in throwaway batteries, which, if inadequately managed, may result in heightened human toxicity. Therefore, the establishment of a circular supply chain (CSC) for EVs is crucial for ensuring long-term sustainability. This study seeks to investigate circularity potentials of end of life (EoL) EVs, influential factors, modeling approaches, and policy interventions that promote the implementation of a CSC for EVs based on a systematic review of empirical-based literature following the PRISMA framework. The findings highlight that, under an optimized waste hierarchy, approximately 55.1–59.5 % of EV components can be reused, 24.4−31.8 % repurposed, 55.1−59.5 % remanufactured, and 95.6−96.0 % recycled, leaving about 23.5–24.7 % of components destined for landfills. Five factors pertaining to regulations, economics, environment, technology and infrastructure, ecosystem were identified to be influential for the CSC implementation for EVs. These factors are modeled using either optimization, simulation, or hybrid approach, depending on the modeling objective and settings, in order to comprehend the CSC system, support decision-making and enhance resource recovery strategies. Policy interventions primarily focused on collection and transportation, technology and infrastructure, and economic aspects, have recently been expanded to encompass social interventions, design standardization, and stakeholder collaboration. Given the potential circularity of EV components, the multifaceted factors involving various stakeholders should be addressed in designing and implementing CSC system for a more resource-efficient future of EVs

Stock Overpricing, Underwriting Fees, and Stock Price Crash Risk

This paper systematically examines the impact of stock overpricing on stock price crash risk and its underlying mechanism based on data from Shanghai and Shenzhen A-share listed companies between 2011 and 2023. The research findings indicate a significant positive correlation between the degree of stock overpricing and stock price crash risk. Furthermore, by examining the mediating effect of underwriter sponsorship fees, the study verifies the pathway through which overpricing indirectly increases risk by raising issuance costs and intensifying conflict of interes

Evaluating Self-Supervised Learning for WiFi CSI-Based Human Activity Recognition

With the advancement of the Internet of Things (IoT), WiFi Channel State Information (CSI)-based Human Activity Recognition (HAR) has garnered increasing attention from both academic and industrial communities. However, the scarcity of labeled data remains a prominent challenge in CSI-based HAR, primarily due to privacy concerns and the incomprehensibility of CSI data. Concurrently, Self-Supervised Learning (SSL) has emerged as a promising approach for addressing the dilemma of insufficient labeled data. In this paper, we undertake a comprehensive inventory and analysis of different categories of SSL algorithms, encompassing both previously studied and unexplored approaches within the field. We provide an in-depth investigation and evaluation of SSL algorithms in the context of WiFi CSI-based HAR, utilizing publicly available datasets that encompass various tasks and environmental settings. To ensure relevance to real-world applications, we design experiment settings aligned with specific requirements. Furthermore, our experimental findings uncover several limitations and blind spots in existing work, shedding light on the barriers that need to be addressed before SSL can be effectively deployed in real-world WiFi-based HAR applications. Our results also serve as practical guidelines and provide valuable insights for future research endeavors in this field

From Paralysis to Pluralism:Repoliticising Mediation in Sudan

The ongoing war in Sudan exposes the limits of international mediation efforts when stripped of political substance. In this blog, Jan Pospisil argues that current approaches reduce mediation to a technocratic exercise, where inclusion is invoked more as a legitimising slogan than a meaningful political act. To make a difference, mediation must re-engage with power, fragmentation, and the complex realities of Sudan’s political landscape

The Influence of Soccer-Specific Exercise on Isokinetic Angle-Specific Thigh Musculature Strength in Female Soccer Players

This study assessed the influence of soccer-specific exercise on thigh musculature strength in female soccer players. Eight amateur female soccer players (age 24 ± 6 years; height 163 ± 8 cm; mass 68 ± 11 kg) participated in the study. Participants completed the female match simulation-90 (FEMS-90), replicating a 90-minute match. Isokinetic strength assessments of the concentric knee extensors (conKE), concentric knee flexors (conKF), eccentric knee extensors (eccKE) and eccentric knee flexors (eccKF) for the dominant lower limb were conducted at 60°∙s-1 where conventional ratios (CR) and dynamic control ratios (DCR) were determined. All strength data were expressed as angle-specific torque (AST). A Bayesian approach identified a 66-78% probability that AST of all muscle actions were lower post SSEP, and a 57-66% probability of a difference that CRAST and DCRAST were lower post SSEP across all angles. The results of this study provides unique insight into how female soccer players respond to soccer match-play, and may have implications for potential injury risk, exercise prescription and recovery. Moreover, given the prevalence and burden of knee ligament injuries in female soccer players, this study provides insight into thigh musculature strength acutely responds following simulated match-play

The global, regional, and national burden of cancer, 1990–2023, with forecasts to 2050:a systematic analysis for the Global Burden of Disease Study 2023

Background: Cancer is a leading cause of death globally. Accurate cancer burden information is crucial for policy planning, but many countries do not have up-to-date cancer surveillance data. To inform global cancer-control efforts, we used the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 framework to generate and analyse estimates of cancer burden for 47 cancer types or groupings by age, sex, and 204 countries and territories from 1990 to 2023, cancer burden attributable to selected risk factors from 1990 to 2023, and forecasted cancer burden up to 2050. Methods: Cancer estimation in GBD 2023 used data from population-based cancer registration systems, vital registration systems, and verbal autopsies. Cancer mortality was estimated using ensemble models, with incidence informed by mortality estimates and mortality-to-incidence ratios (MIRs). Prevalence estimates were generated from modelled survival estimates, then multiplied by disability weights to estimate years lived with disability (YLDs). Years of life lost (YLLs) were estimated by multiplying age-specific cancer deaths by the GBD standard life expectancy at the age of death. Disability-adjusted life-years (DALYs) were calculated as the sum of YLLs and YLDs. We used the GBD 2023 comparative risk assessment framework to estimate cancer burden attributable to 44 behavioural, environmental and occupational, and metabolic risk factors. To forecast cancer burden from 2024 to 2050, we used the GBD 2023 forecasting framework, which included forecasts of relevant risk factor exposures and used Socio-demographic Index as a covariate for forecasting the proportion of each cancer not affected by these risk factors. Progress towards the UN Sustainable Development Goal (SDG) target 3.4 aim to reduce non-communicable disease mortality by a third between 2015 and 2030 was estimated for cancer. Findings: In 2023, excluding non-melanoma skin cancers, there were 18·5 million (95% uncertainty interval 16·4 to 20·7) incident cases of cancer and 10·4 million (9·65 to 10·9) deaths, contributing to 271 million (255 to 285) DALYs globally. Of these, 57·9% (56·1 to 59·8) of incident cases and 65·8% (64·3 to 67·6) of cancer deaths occurred in low-income to upper-middle-income countries based on World Bank income group classifications. Cancer was the second leading cause of deaths globally in 2023 after cardiovascular diseases. There were 4·33 million (3·85 to 4·78) risk-attributable cancer deaths globally in 2023, comprising 41·7% (37·8 to 45·4) of all cancer deaths. Risk-attributable cancer deaths increased by 72·3% (57·1 to 86·8) from 1990 to 2023, whereas overall global cancer deaths increased by 74·3% (62·2 to 86·2) over the same period. The reference forecasts (the most likely future) estimate that in 2050 there will be 30·5 million (22·9 to 38·9) cases and 18·6 million (15·6 to 21·5) deaths from cancer globally, 60·7% (41·9 to 80·6) and 74·5% (50·1 to 104·2) increases from 2024, respectively. These forecasted increases in deaths are greater in low-income and middle-income countries (90·6% [61·0 to 127·0]) compared with high-income countries (42·8% [28·3 to 58·6]). Most of these increases are likely due to demographic changes, as age-standardised death rates are forecast to change by –5·6% (–12·8 to 4·6) between 2024 and 2050 globally. Between 2015 and 2030, the probability of dying due to cancer between the ages of 30 years and 70 years was forecasted to have a relative decrease of 6·5% (3·2 to 10·3). Interpretation: Cancer is a major contributor to global disease burden, with increasing numbers of cases and deaths forecasted up to 2050 and a disproportionate growth in burden in countries with scarce resources. The decline in age-standardised mortality rates from cancer is encouraging but insufficient to meet the SDG target set for 2030. Effectively and sustainably addressing cancer burden globally will require comprehensive national and international efforts that consider health systems and context in the development and implementation of cancer-control strategies across the continuum of prevention, diagnosis, and treatment. Funding: Gates Foundation, St Jude Children's Research Hospital, and St Baldrick's Foundation.</p