14,178 research outputs found
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
Теорія систем мобільних інфокомунікацій. Системна архітектура
Навчальний посібник містить опис логічних та фізичних структур, процедур,
алгоритмів, протоколів, принципів побудови і функціонування мереж
стільникового мобільного зв’язку (до 3G) і мобільних інфокомунікацій (4G і вище),
приділяючи увагу розгляду загальних архітектур мереж операторів мобільного
зв’язку, їх управління і координування, неперервності еволюції розвитку засобів
функціонування і способів надання послуг таких мереж. Посібник структурно має
сім розділів і побудований так, що складність матеріалу зростає з кожним
наступним розділом. Навчальний посібник призначено для здобувачів ступеня
бакалавра за спеціальністю 172 «Телекомунікації та радіотехніка», буде також
корисним для аспірантів, наукових та інженерно-технічних працівників за
напрямом інформаційно-телекомунікаційних систем та технологій.The manual contains a description of the logical and physical structures, procedures, algorithms, protocols, principles of construction and operation of cellular networks for mobile communications (up to 3G) and mobile infocommunications (4G and higher), paying attention to the consideration of general architectures of mobile operators' networks, their management, and coordination, the continuous evolution of the development of the means of operation and methods of providing services of such networks. The manual has seven structural sections and is structured in such a way that the complexity of the material increases with each subsequent chapter. The textbook is intended for applicants for a bachelor's degree in specialty 172 "Telecommunications and Radio Engineering", and will also be useful to graduate students, and scientific and engineering workers in the direction of information and telecommunication systems and technologies
Corporate Social Responsibility: the institutionalization of ESG
Understanding the impact of Corporate Social Responsibility (CSR) on firm performance as it relates to industries reliant on technological innovation is a complex and perpetually evolving challenge. To thoroughly investigate this topic, this dissertation will adopt an economics-based structure to address three primary hypotheses. This structure allows for each hypothesis to essentially be a standalone empirical paper, unified by an overall analysis of the nature of impact that ESG has on firm performance. The first hypothesis explores the evolution of CSR to the modern quantified iteration of ESG has led to the institutionalization and standardization of the CSR concept. The second hypothesis fills gaps in existing literature testing the relationship between firm performance and ESG by finding that the relationship is significantly positive in long-term, strategic metrics (ROA and ROIC) and that there is no correlation in short-term metrics (ROE and ROS). Finally, the third hypothesis states that if a firm has a long-term strategic ESG plan, as proxied by the publication of CSR reports, then it is more resilience to damage from controversies. This is supported by the finding that pro-ESG firms consistently fared better than their counterparts in both financial and ESG performance, even in the event of a controversy. However, firms with consistent reporting are also held to a higher standard than their nonreporting peers, suggesting a higher risk and higher reward dynamic. These findings support the theory of good management, in that long-term strategic planning is both immediately economically beneficial and serves as a means of risk management and social impact mitigation. Overall, this contributes to the literature by fillings gaps in the nature of impact that ESG has on firm performance, particularly from a management perspective
Deep Transfer Learning Applications in Intrusion Detection Systems: A Comprehensive Review
Globally, the external Internet is increasingly being connected to the
contemporary industrial control system. As a result, there is an immediate need
to protect the network from several threats. The key infrastructure of
industrial activity may be protected from harm by using an intrusion detection
system (IDS), a preventive measure mechanism, to recognize new kinds of
dangerous threats and hostile activities. The most recent artificial
intelligence (AI) techniques used to create IDS in many kinds of industrial
control networks are examined in this study, with a particular emphasis on
IDS-based deep transfer learning (DTL). This latter can be seen as a type of
information fusion that merge, and/or adapt knowledge from multiple domains to
enhance the performance of the target task, particularly when the labeled data
in the target domain is scarce. Publications issued after 2015 were taken into
account. These selected publications were divided into three categories:
DTL-only and IDS-only are involved in the introduction and background, and
DTL-based IDS papers are involved in the core papers of this review.
Researchers will be able to have a better grasp of the current state of DTL
approaches used in IDS in many different types of networks by reading this
review paper. Other useful information, such as the datasets used, the sort of
DTL employed, the pre-trained network, IDS techniques, the evaluation metrics
including accuracy/F-score and false alarm rate (FAR), and the improvement
gained, were also covered. The algorithms, and methods used in several studies,
or illustrate deeply and clearly the principle in any DTL-based IDS subcategory
are presented to the reader
A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms
Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data.
A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability.
To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity.
A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case.
The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change.
The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence
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Antecedents of business intelligence system use
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.Organisational reliance on information has become vital for organisational competitiveness. With increasing data volumes, Business Intelligence (BI) becomes a cornerstone of the decision-support system. However, employee resistance to use Business Intelligence Systems (BIS) is evident. This creates a problem to organisations in realising the benefits of BIS. It is thus important to study the enablers of sustained use of BIS amongst employees.
This thesis identifies existing theories that can be used to study BI system use. It integrates and extends technology use theories through a framework focusing on Business Intelligence System Use (BISU). Empirical research is then conducted in Kuwait’s telecom and banking industries through a close-ended, self-administered questionnaire using a five-point Likert scale. Responses were received from 211 BI users. The data was analysed using SmartPLS to study the convergent and discriminant validity and reliability. Partial least squares structural equation modelling (PLS-SEM) was used to study the direct and indirect relationships between constructs and answer the hypotheses. In addition to SmartPLS, SPSS was used for descriptive analysis.
The results indicated that UTAUT factors consisting of performance expectancy, effort expectancy and social influence positively impact BI system use. Voluntariness of use was found to positively moderate the relationship between social influence and BI system use. Furthermore, BI system quality positively impacts both performance expectancy and effort expectancy. The BI user’s self-efficacy also positively impacts effort expectancy. In addition, social influence was found to be positively influenced by organisational factors, namely top management support and information culture.
The findings of this research contribute to literature by determining and quantifying the factors that influence BISU through the lens of employee perspectives. This thesis also explains how employees’ object-based beliefs about BI affect their behavioural beliefs, which in turn impact BISU. Limitations of this research include the omission of UTAUT’s facilitating conditions and the limited variance of respondent demographics
Stop and go, where is my flow? How and when daily aversive morning commutes are negatively related to employees’ motivational states and behavior at work
Despite convincing evidence about the general negative consequences of commuting for individuals and societies, our understanding of how aversive commutes are linked to employees’ effectiveness at work is limited. Drawing on theories of self-regulation and by extension a conservation of resources perspective, we develop a framework that explains how an aversive morning commute—a resource-depleting experience characterized by interruptions of automated travel behaviors—impairs employees’ immersion in uninterrupted work (i.e., flow), which in turn reduces employee effectiveness (i.e., work engagement, subjective performance, and OCB-I). We further delineate theoretical arguments for daily self-control demands as a boundary condition that amplifies this relation and propose the satisfaction of employees’ basic needs as protective factors. Two diary studies across 10 workdays each (Study 1: 53 employees, 411 day-level data points; Study 2: 91 employees, 719 day-level data points) support most of our hypotheses. Study 1 demonstrates that daily aversive morning commutes negatively affect employees’ daily work engagement through lower levels of flow experiences, but only on days with high impulse control demands. In addition, we find initial support that employees’ general autonomy and competence needs satisfaction attenuate this interaction. Study 2 rules out alternative mechanisms (negative affect and tension), demonstrates ego depletion as an additional mediator of the relation between aversive morning commutes and work effectiveness, and replicates the hypothesized three-way interaction for daily competence need satisfaction. We critically discuss the findings and reflect on corporate interventions, which may allow people to more easily flow to and at work
Lección didáctica del curso español II aplicando la herramienta mondly como plataforma de realidad aumentada para la práctica de las competencias comunicativas del idioma español en los estudiantes de k12 del colegio halifax county high school
El proyecto aplicado se desarrolló con el objetivo de diseñar e implementar una lección didáctica con realidad aumentada a través de la App Mondly, con estudiantes del K12 Colegio Halifax County High School que estaban cursando el nivel de español II.
La lección didáctica se diseñó sobre las cuatro competencias comunicativas del español; lectura, escritura, escucha y habla. Además, se tuvo en cuenta el World Language Standards Of Learning y los lineamientos del Virginia Department Of Education para garantizar los estándares de calidad. Así mismo, la lección didáctica se diseñó sobre temas concretos que están inmersos en las competencias comunicativas y que se plantearon teniendo en cuenta el nivel II de español; Lectura (Artículos definidos e indefinidos, uso del verbo ir y el verbo tener y estar), escritura (uso del verbo ser, uso del verbo ser y estar y verbos que cambian de raíz), escucha (descripciones y el verbo ir y descripciones, gustos y disgustos) y el habla (identificar y describir personas, cosas y animales).
La implementación del proyecto buscó la articulación de la tecnología emergente de la realidad aumentada con el aprendizaje del español a través de la inmersión que esta permite en el contexto real desde lo digital para que el estudiante pueda adquirir las habilidades en el desarrollo de las competencias comunicativas.The applied project was developed with the main goal of designing and implementing a didactic lesson with augmented reality through the Mondly App, to K12 students K12 at Halifax County High School who were studying Spanish II.
The didactic lesson was designed on the four communicative competences of Spanish: reading, writing, listening, and speaking. In addition, the World Language Standards of Learning and the guidelines of the Virginia Department of Education were considered to guarantee quality standards. Likewise, the didactic lesson was designed on specific topics that are immersed in communicative competences and that were raised taking into account level II of Spanish; Reading (Definite and indefinite articles, use of the verb ir and the verb tener and estar), writing (use of the verb ser, use of the verb ser and estar and stem changing verbs), listening (descriptions and the verb ir, likes and dislikes) and speaking (identifying and describing people, things, and animals).
The implementation of the project sought the articulation of the emerging technology of augmented reality with the learning of Spanish through the immersion that this allows in the real context from the digital so that the student can acquire the skills in the development of communication skills
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Experimental study of a novel valvetrain system on SI engine efficiency and emissions
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonStrict emissions legislations and continuous race for improvement of fuel economy urge to develop more efficient and cleaner IC engines for commercial and private use. Engine downsizing has been shown as an effective means to reduce the vehicle’s fuel consumption but the full potential of engine downsizing is limited by the knocking combustion at boosted operations and the presence of pumping loss at part load conditions. A variable valve train system can be used to minimise the knocking combustion by implementing Miller and Atkinson cycles through alteration of the effective compression ratio (ECR) at high load via Early Intake Valve Closure (EIVC) or Late Intake Valve Closure (LIVC), as well as reducing the pumping loss at part load.
In this work, a single cylinder direct injection Spark Ignition (SI) gasoline engine equipped with an electro-mechanical valvetrain system named iVT (intelligent Valve Technology) by Camcon was set up and used to investigate the potential benefits of the iVT. Engine experiments were carried out at 1500 and 3000rpm with various valve profiles including EIVC and LIVC with single and two intake valve mode as well as early intake Maximum Opening Position (MOP) at 35% and 40% MOP. Their effects on engine performance and emissions were measured and analysed at 4, 6, 9 and 12.6bar net IMEP. Results showed that EIVC and LIVC profiles were successful in reducing the fuel consumption with two valve mode at low loads thanks to lower pumping loss and at high loads where spark timing was knock limited. Those profiles also resulted in lower emissions. In particular, the LIVC profile reduced the NOX concentration by up to 20% at low loads due to lowest ECR. Single valve mode operations also provided improved fuel economy at 4bar and 12.6bar net IMEP when combined with EIVC profiles. However, the most significant reduction in ISFC was achieved with early MOP. With combination of LIVC and early MOP, ISFC was reduced by up to 5.4% at low load and by up to 7.1% at high load compared to the baseline profile at 1500rpm
Development of MEMS - based IMU for position estimation: comparison of sensor fusion solutions
With the surge of inexpensive, widely accessible, and precise Micro-Electro Mechanical Systems (MEMS) in recent years, inertial systems tracking move ment have become ubiquitous nowadays. Contrary to Global Positioning Sys tem (GPS)-based positioning, Inertial Navigation System (INS) are intrinsically
unaffected by signal jamming, blockage susceptibilities, and spoofing. Measure ments from inertial sensors are also acquired at elevated sampling rates and may
be numerically integrated to estimate position and orientation knowledge. These
measurements are precise on a small-time scale but gradually accumulate errors
over extended periods. Combining multiple inertial sensors in a method known as
sensor fusion makes it possible to produce a more consistent and dependable un derstanding of the system, decreasing accumulative errors. Several sensor fusion
algorithms occur in literature aimed at estimating the Attitude and Heading
Reference System (AHRS) of a rigid body with respect to a reference frame.
This work describes the development and implementation of a low-cost, multi purpose INS for position and orientation estimation. Additionally, it presents an
experimental comparison of a series of sensor fusion solutions and benchmarking
their performance on estimating the position of a moving object. Results show
a correlation between what sensors are trusted by the algorithm and how well it
performed at estimating position. Mahony, SAAM and Tilt algorithms had best
general position estimate performance.Com o recente surgimento de sistemas micro-eletromecânico amplamente acessíveis
e precisos nos últimos anos, o rastreio de movimento através de sistemas de in erciais tornou-se omnipresente nos dias de hoje. Contrariamente à localização
baseada no Sistema de Posicionamento Global (GPS), os Sistemas de Naveg ação Inercial (SNI) não são afetados intrinsecamente pela interferência de sinal,
suscetibilidades de bloqueio e falsificação. As medições dos sensores inerciais
também são adquiridas a elevadas taxas de amostragem e podem ser integradas
numericamente para estimar os conhecimentos de posição e orientação. Estas
medições são precisas numa escala de pequena dimensão, mas acumulam grad ualmente erros durante longos períodos. Combinar múltiplos sensores inerci ais num método conhecido como fusão de sensores permite produzir uma mais
consistente e confiável compreensão do sistema, diminuindo erros acumulativos.
Vários algoritmos de fusão de sensores ocorrem na literatura com o objetivo de
estimar os Sistemas de Referência de Atitude e Rumo (SRAR) de um corpo
rígido no que diz respeito a uma estrutura de referência. Este trabalho descreve
o desenvolvimento e implementação de um sistema multiusos de baixo custo
para estimativa de posição e orientação. Além disso, apresenta uma comparação
experimental de uma série de soluções de fusão de sensores e compara o seu de sempenho na estimativa da posição de um objeto em movimento. Os resultados
mostram uma correlação entre os sensores que são confiados pelo algoritmo e o
quão bem ele desempenhou na posição estimada. Os algoritmos Mahony, SAAM
e Tilt tiveram o melhor desempenho da estimativa da posição geral
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