Search results for: Simon Horrocks

Authors: Sean W. T. Bayly, Daniel Glover, Don Horrell, Simon Horrocks, Barnes Callum, Stuart Gibson, Mac Misuira

Abstract:

We assess suitability of recent, ∼7B parameter, instruction-tuned Language Models for Generative Named Entity Recognition (GNER). Alongside Retrieval Augmented Generation (RAG), and supported by task-specific prompting, our proposed Multi-Level Information Retrieval method achieves notable improvements over finetuned entity-level and sentence-level methods. We conclude that language models directed toward this task are highly capable when distinguishing between positive classes (precision). However, smaller models seem to struggle to find all entities (recall). Poorly defined classes such as ”Miscellaneous” exhibit substantial declines in performance, likely due to the ambiguity it introduces to the prompt. This is partially resolved through a self-verification method using engineered prompts containing knowledge of the stricter class definitions, particularly in areas where their boundaries are in danger of overlapping, such as the conflation between the location ”Britain” and the nationality ”British”. Finally, we explore correlations between model performance on the GNER task with performance on relevant academic benchmarks.

Keywords: generative named entity recognition, information retrieval, lightweight artificial intelligence, prompt engineering, personal information identification, retrieval augmented generation, self verification

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Authors: Craig A. Kaplan

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If AGI proves to be a “winner-take-all” scenario where the first company or country to develop AGI dominates, then the first AGI must also be the safest. The safest, and fastest, path to Artificial General Intelligence (AGI) may be to harness the collective intelligence of multiple AI and human agents in an AGI network. This approach has roots in seminal ideas from four of the scientists who founded the field of Artificial Intelligence: Allen Newell, Marvin Minsky, Claude Shannon, and Herbert Simon. Extrapolating key insights from these founders of AI, and combining them with the work of modern researchers, results in a fast and safe path to AGI. The seminal ideas discussed are: 1) Society of Mind (Minsky), 2) Information Theory (Shannon), 3) Problem Solving Theory (Newell & Simon), and 4) Bounded Rationality (Simon). Society of Mind describes a collective intelligence approach that can be used with AI and human agents to create an AGI network. Information theory helps address the critical issue of how an AGI system will increase its intelligence over time. Problem Solving Theory provides a universal framework that AI and human agents can use to communicate efficiently, effectively, and safely. Bounded Rationality helps us better understand not only the capabilities of SuperIntelligent AGI but also how humans can remain relevant in a world where the intelligence of AGI vastly exceeds that of its human creators. Each key idea can be combined with recent work in the fields of Artificial Intelligence, Machine Learning, and Large Language Models to accelerate the development of a working, safe, AGI system.

Keywords: AI Agents, Collective Intelligence, Minsky, Newell, Shannon, Simon, AGI, AGI Safety

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Authors: Lamia L. G. Al-Mahamad, Benjamin R. Horrocks, Andrew Houlton

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Hydrogels based on metal coordination polymers of nucleosides and a range of metal ions (Au, Ag, Cu) have been prepared and characterized by atomic force microscopy (AFM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, ultraviolet-visible absorption spectroscopy, and powder X-ray diffraction. AFM images of the xerogels revealed the formation of extremely long polymer molecules (> 10 micrometers, the maximum scan range). This result is also consistent with TEM images which show a fibrous morphology. Oxidative doping of the Au-nucleoside fibres produces an electrically conductive nanowire. No sharp Bragg peaks were found at the at the X-ray diffraction pattern for metal ions hydrogels indicating that the samples were amorphous, but instead the data showed broad peaks in the range 20 < Q < 40 and correspond to distances d=2μ/Q. The data was analysed using a simplified Rietveld method by fitting a regression model to obtain the distance between atoms.

Keywords: hydrogel, metal ions, nanowire, nucleoside

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Authors: Khamael M. Abualnaja, Lidija Šiller, Benjamin R. Horrocks

Abstract:

Metal-enhanced luminescence of silicon nano crystals (SiNCs) was determined using two different particle sizes of silver nano particles (AgNPs). SiNCs have been characterized by scanning electron microscopy (SEM), high resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR) and X-ray photo electron spectroscopy (XPS). It is found that the SiNCs are crystalline with an average diameter of 65 nm and FCC lattice. AgNPs were synthesized using photochemical reduction of AgNO3 with sodium dodecyl sulphate (SDS). The enhanced luminescence of SiNCs by AgNPs was evaluated by confocal Raman microspectroscopy. Enhancement up to ×9 and ×3 times were observed for SiNCs that mixed with AgNPs which have an average particle size of 100 nm and 30 nm, respectively. Silver NPs-enhanced luminescence of SiNCs occurs as a result of the coupling between the excitation laser light and the plasmon bands of AgNPs; thus this intense field at AgNPs surface couples strongly to SiNCs.

Keywords: silver nanoparticles, surface enhanced raman spectroscopy (SERS), silicon nanocrystals, luminescence

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Authors: Khamael M. Abualnaja, Lidija Šiller, Benjamin R. Horrocks

Abstract:

Alkylated silicon nanocrystals (C11-SiNCs) were prepared successfully by galvanostatic etching of p-Si(100) wafers followed by a thermal hydrosilation reaction of 1-undecene in refluxing toluene in order to extract C11-SiNCs from porous silicon. Erbium trichloride was added to alkylated SiNCs using a simple mixing chemical route. To the best of our knowledge, this is the first investigation on mixing SiNCs with erbium ions (III) by this chemical method. The chemical characterization of C11-SiNCs and their mixtures with Er3+ (Er/C11-SiNCs) were carried out using X-ray photoemission spectroscopy (XPS). The optical properties of C11-SiNCs and their mixtures with Er3+ were investigated using Raman spectroscopy and photoluminescence (PL). The erbium-mixed alkylated SiNCs shows an orange PL emission peak at around 595 nm that originates from radiative recombination of Si. Er/C11-SiNCs mixture also exhibits a weak PL emission peak at 1536 nm that originates from the intra-4f transition in erbium ions (Er3+). The PL peak of Si in Er/C11-SiNCs mixture is increased in the intensity up to three times as compared to pure C11-SiNCs. The collected data suggest that this chemical mixing route leads instead to a transfer of energy from erbium ions to alkylated SiNCs.

Keywords: photoluminescence, silicon nanocrystals, erbium, Raman spectroscopy

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Authors: Fonteyne Lot

Abstract:

SIMON (Study capacities and Interest Monitor is a freely accessible online self-assessment tool that allows secondary education pupils to evaluate their interests and capacities in order to choose a post-secondary major that maximally suits their potential. The tool consists of two broad domains that correspond with two general questions pupils ask: 'What study fields interest me?' and 'Am I capable to succeed in this field of study?'. The first question is addressed by a RIASEC-type interest inventory that links personal interests to post-secondary majors. Pupils are provided with a personal profile and an overview of majors with their degree of congruence. The output is dynamic: respondents can manipulate their score and they can compare their results to the profile of all fields of study. That way they are stimulated to explore the broad range of majors. To answer whether pupils are capable of succeeding in a preferred major, a battery of tests is provided. This battery comprises a range of factors that are predictive of academic success. Traditional predictors such as (educational) background and cognitive variables (mathematical and verbal skills) are included. Moreover, non-cognitive predictors of academic success (such as 'motivation', 'test anxiety', 'academic self-efficacy' and 'study skills') are assessed. These non-cognitive factors are generally not included in admission decisions although research shows they are incrementally predictive of success and are less discriminating. These tests inform pupils on potential causes of success and failure. More important, pupils receive their personal chances of success per major. These differential probabilities are validated through the underlying research on academic success of students. For example, the research has shown that we can identify 22 % of the failing students in psychology and educational sciences. In this group, our prediction is 95% accurate. SIMON leads more students to a suitable major which in turn alleviates student success and retention. Apart from these benefits, the instrument grants insight into risk factors of academic failure. It also supports and fosters the development of evidence-based remedial interventions and therefore gives way to a more efficient use of means.

Keywords: academic success, online self-assessment, student retention, vocational choice

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Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

Abstract:

The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

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Authors: Mahdi Almaky, Reda Hassanin, Benjamin Horrocks, Andrew Houlton

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DNA-templated poly(N-substituted pyrrole)bipyridinium nanowires were synthesised at room temperature using the chemical oxidation method. The resulting CPs/DNA hybrids have been characterised using electronic and vibrational spectroscopic methods especially Ultraviolet-Visible (UV-Vis) spectroscopy and FTIR spectroscpy. The nanowires morphology was characterised using Atomic Force Microscopy (AFM). The electrical properties of the prepared nanowires were characterised using Electrostatic Force Microscopy (EFM), and measured using conductive AFM (c-AFM) and two terminal I/V technique, where the temperature dependence of the conductivity was probed. The conductivities of the prepared CPs/DNA nanowires are generally lower than PPy/DNA nanowires showingthe large effect on N-alkylation in decreasing the conductivity of the polymer, butthese are higher than the conductivity of their corresponding bulk films.This enhancement in conductivity could be attributed to the ordering of the polymer chains on DNA during the templating process. The prepared CPs/DNA nanowires were used as templates for the growth of copper nanowires at room temperature using aqueous solution of Cu(NO3)2as a source of Cu2+ and ascorbic acid as reducing agent. AFM images showed that these nanowires were uniform and continuous compared to copper nanowires prepared using the templating method directly onto DNA. Electrical characterization of the nanowires by c AFM revealed slight improvement in conductivity of these nanowires (Cu-CPs/DNA) compared to CPs/DNA nanowires before metallisation.

Keywords: templating, copper nanowires, polymer/DNA hybrid, chemical oxidation method

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Authors: Khamael M. Abualnaja, Lidija Šiller, Ben R. Horrocks

Abstract:

The structural characterization of silicon nano crystals (SiNCs) have been carried out using transmission electron microscope (TEM) and atomic force microscopy (AFM). SiNCs are crystalline with an average diameter of 65 nm. Erbium trichloride was added to silicon nano crystals using a simple chemical procedure. Erbium is useful in this context because it has a narrow emission band at ⋍1536 nm which corresponds to a standard optical telecommunication wavelength. The optical properties of SiNCs and erbium-mixed SiNCs samples have been characterized using UV-vis spectroscopy, confocal Raman spectroscopy and photoluminescence spectroscopy (PL). SiNCs and erbium-mixed SiNCs samples exhibit an orange PL emission peak at around 595 nm that arise from radiative recombination of Si. Erbium-mixed SiNCs also shows a weak PL emission peak at ⋍1536 nm that attributed to the intra-4f transition in erbium ions. The intensity of the PL peak of Si in erbium-mixed SiNCs is increased in the intensity up to ×3 as compared to pure SiNCs. It was observed that intensity of 1536 nm peak decreased dramatically in the presence of silicon nano crystals and the PL emission peak of silicon nano crystals is increased. Therefore, the resulted data present that the energy transfer from erbium ions to SiNCs due to the chemical mixing method which used in this work.

Keywords: Silicon Nanocrystals (SiNCs), Erbium Ion, photoluminescence, energy transfer

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Authors: Komal Saeed

Abstract:

Introduction: Rhinoplasty is considered one of the challenging aesthetic procedures. Psychosocial concerns motivate the urge for aesthetic procedures especially rhinoplasty. Males who fall in this category are designated as single, immature, male, over expectant and narcissistic (SIMON) in literature. As of yet, there is no term that depicts females showing similar characteristics. The purpose of this study is to evaluate the incidence of body dysmorphic disorder (BDD) in females seeking rhinoplasty and to introduce a term for such individuals. Materials and Methods: A prospective, questionnaire based, qualitative study was conducted in the Department Of Plastic Surgery between March 2018 and March 2020. 110 female candidates seeking aesthetic rhinoplasty were included in the study. BDD was evaluated using the Dysmorphic Concerns Questionnaire, DCQ. Data were analyzed using SPSS version 25 software and correlation between the groups was evaluated. Results: Out of 110 female subjects, 77.3% (n=85) were single, 16.4% (n=18) were married and 6.4% (n=7) were divorced. BDD was found in 41.8% (n=46) of the candidates, majority being single (n=41, 89.1%) and having educational status above diploma (n=39, 84.8%). There was a statistically higher percentage of young adults between 24 and 28 years (n=33, 71.7%) having BDD (p= 0.0001). Conclusion: Considering the high frequency of BDD among females seeking rhinoplasty, a standardized term ‘SIFON’ is introduced to describe such individuals who are S; single, I; immature, F; female, O; over expectant, N; narcissistic as apposed to SIMON in males. These individuals perceive aesthetic procedures as a solution to their body dissatisfaction. Therefore, preoperative counseling seems necessary to avoid unsatisfactory outcomes secondary to mental health.

Keywords: aesthetic rhinoplasty, body dismorphic disorder, single, immature, obsessive

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Authors: Khamael M. Abualnaja, Lidija Šiller, Ben R. Horrocks

Abstract:

Metal enhanced luminescence of alkyl-capped silicon quantum dots (C11-SiQDs) was obtained by mixing C11-SiQDs with silver nanoparticles (AgNPs). C11-SiQDs have been synthesized by galvanostatic method of p-Si (100) wafers followed by a thermal hydrosilation reaction of 1-undecene in refluxing toluene in order to extract alkyl-capped silicon quantum dots from porous Si. The chemical characterization of C11-SiQDs was carried out using X-ray photoemission spectroscopy (XPS). C11-SiQDs have a crystalline structure with a diameter of 5 nm. Silver nanoparticles (AgNPs) of two different sizes were synthesized also using photochemical reduction of silver nitrate with sodium dodecyl sulphate. The synthesized Ag nanoparticles have a polycrystalline structure with an average particle diameter of 100 nm and 30 nm, respectively. A significant enhancement up to 10 and 4 times in the luminescence intensities was observed for AgNPs100/C11-SiQDs and AgNPs30/C11-SiQDs mixtures, respectively using 488 nm as an excitation source. The enhancement in luminescence intensities occurs as a result of the coupling between the excitation laser light and the plasmon bands of Ag nanoparticles; thus this intense field at Ag nanoparticles surface couples strongly to C11-SiQDs. The results suggest that the larger Ag nanoparticles i.e.100 nm caused an optimum enhancement in the luminescence intensity of C11-SiQDs which reflect the strong interaction between the localized surface plasmon resonance of AgNPs and the electric field forming a strong polarization near C11-SiQDs.

Keywords: silicon quantum dots, silver nanoparticles (AgNPs), luminescence, plasmon

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Authors: M. E. Joret, F. Germeys, P. Van de Craen

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Background: Previous studies have shown that ‘full’ bilingualism seems to enhance the executive functions in children, young adults and elderly people. Executive functions refer to a complex cognitive system responsible for self-controlled and planned behavior and seem to predict academic achievement. The present study aimed at investigating whether similar effects could be found in children learning their second language at school in immersion education programs. Methods: In this study, 44 children involved in immersion education for 4 to 5 years were compared to 48 children in traditional schools. All children were between 9 and 11 years old. To assess executive functions, the Simon task was used, a neuropsychological measure assessing executive functions with reaction times and accuracy on congruent and incongruent trials. To control for background measures, all children underwent the Raven’s coloured progressive matrices, to measure non-verbal intelligence and the Echelle de Vocabulaire en Images Peabody (EVIP), assessing verbal intelligence. In addition, a questionnaire was given to the parents to control for other confounding variables, such as socio-economic status (SES), home language, developmental disorders, etc. Results: There were no differences between groups concerning non-verbal intelligence and verbal intelligence. Furthermore, the immersion learners showed overall faster reaction times on both congruent and incongruent trials compared to the traditional learners, but only after 5 years of training, not before. Conclusion: These results show that the cognitive benefits found in ‘full’ bilinguals also appear in children involved in immersion education, but only after a sufficient exposure to the second language. Our results suggest that the amount of second language training needs to be sufficient before these cognitive effects may emerge.

Keywords: bilingualism, executive functions, immersion education, Simon task

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Authors: Khamael M. Abualnaja, Lidija Šiller, Ben R. Horrocks

Abstract:

Surface enhanced Raman spectroscopy (SERS) of Silicon nano crystals (SiNCs) were obtained using two different laser excitations: 488 nm and 514.5 nm. Silver nano particles were used as plasmonics metal nano particles due to a robust SERS effect that observed when they mixed with SiNCs. SiNCs have been characterized by scanning electron microscopy (SEM), high resolution transmission electron microscopy (HRTEM), atomic force microscopy (AFM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). It is found that the SiNCs are crystalline with an average diameter of 65 nm and FCC lattice. Silver nano particles (AgNPs) of two different sizes were synthesized using photo chemical reduction of AgNO3 with sodium dodecyl sulfate (SDS). The synthesized AgNPs have a polycrystalline structure with an average particle diameter of 100 nm and 30 nm, respectively. A significant enhancement in the SERS intensity was observed for AgNPs100/SiNCs and AgNPs30/SiNCs mixtures increasing up to 9 and 3 times respectively using 488 nm intensity; whereas the intensity of the SERS signal increased up to 7 and 2 times respectively, using 514.5 nm excitation source. The enhancement in SERS intensities occurs as a result of the coupling between the excitation laser light and the plasmon bands of AgNPs; thus this intense field at AgNPs surface couples strongly to SiNCs. The results provide good consensus between the wavelength of the laser excitation source and surface plasmon resonance absorption band of silver nano particles consider to be an important requirement in SERS experiments.

Keywords: silicon nanocrystals (SiNCs), silver nanoparticles (AgNPs), surface enhanced raman spectroscopy (SERS)

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Authors: K. Sekulová, M. Šimon

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This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.

Keywords: ergonomics, musculoskeletal disorders, occupational diseases, risk factors

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Authors: Sarah Ullrich, Juliane Rolle, Christian Beste, Nicole Wolff

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Inhibition and cognitive flexibility are essential parts of executive functions in our daily lives, as they enable the avoidance of unwanted responses or selectively switch between mental processes to generate appropriate behavior. There is growing interest in improving inhibition and response selection through brief mindfulness-based meditations. Arguably, open-monitoring meditation (OMM) improves inhibitory and flexibility performance by optimizing cognitive control and information processing. Yet, the underlying neurophysiological processes have been poorly studied. Using the Simon-Go/Nogo paradigm, the present work examined the effect of a single 15-minute smartphone app-based OMM on inhibitory performance and response selection in meditation novices. We used both behavioral and neurophysiological measures (event-related potentials, ERPs) to investigate which subprocesses of response selection and inhibition are altered after OMM. The study was conducted in a randomized crossover design with N = 32 healthy adults. We thereby investigated Go and Nogo trials in the paradigm. The results show that as little as 15 minutes of OMM can improve response selection and inhibition at behavioral and neurophysiological levels. More specifically, OMM reduces the rate of false alarms, especially during Nogo trials regardless of congruency. It appears that OMM optimizes conflict processing and response inhibition compared to no meditation, also reflected in the ERP N2 and P3 time windows. The results may be explained by the meta control model, which argues in terms of a specific processing mode with increased flexibility and inclusive decision-making under OMM. Importantly, however, the effects of OMM were only evident when there was the prior experience with the task. It is likely that OMM provides more cognitive resources, as the amplitudes of these EKPs decreased. OMM novices seem to induce finer adjustments during conflict processing after familiarization with the task.

Keywords: EEG, inhibition, meditation, Simon Nogo

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Authors: Souad Slimani, Sylvain Gravier, Simon Schmidt

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Recently, several vertex identifying notions were introduced (identifying coloring, lid-coloring,...); these notions were inspired by identifying codes. All of them, as well as original identifying code, is based on separating two vertices according to some conditions on their closed neighborhood. Therefore, twins can not be identified. So most of known results focus on twin-free graph. Here, we show how twins can modify optimal value of vertex-identifying parameters for identifying coloring and locally identifying coloring.

Keywords: identifying coloring, locally identifying coloring, twins, separating

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Authors: K. Sekulová, M. Šimon

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The article demonstrates on a case study how it is possible to identify MSD risk. It is based on a dissertation risk identification model of occupational diseases formation in relation to the work activity that determines what risk can endanger workers who are exposed to the specific risk factors. It is evaluated based on statistical calculations. These risk factors are main cause of upper-extremities musculoskeletal disorders.

Keywords: case study, upper-extremity musculoskeletal disorders, ergonomics, risk identification

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Authors: Simon Oga Egboja

Abstract:

In Africa, particularly in Nigeria, unemployment is a serious issue of concern to every citizen. Hence, this paper focuses on the employment situation and trends in Nigeria. It also investigated the causes why unemployment persists in the country. Prominent among them is the population explosion and rapid expansion of education opportunities all over the country without a corresponding increase in industrial establishment. The paper also discusses the way of reducing the rate of unemployment by encouraging graduates of tertiary institutions in Nigeria to read professional courses and also to indulge in the habit of establishing small-scale enterprises so that after them school they can be self-employed rather than relying solely on government for employment.

Keywords: causes, population, remedy, unemployment

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Authors: Suzana Leitão Russo, Mayara Laysa de Oliveira Silva, José Augusto Andrade Filho, Vitor Hugo Simon

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Currently, seismic methods and prospecting methods are commonly applied in the oil industry and, according to the information reported every day; oil is a source of non-renewable energy. It is easier to understand why the ownership of areas of oil extraction is coveted by many nations. It is necessary to think about ways that will enable the maximization of oil production. The technique of spectral analysis can be used to analyze the behavior of the variables already defined in oil well the profile. The main objective is to verify the series dependence of variables, and to model the variables using the frequency domain to observe the model residuals.

Keywords: oil, well, spectral analysis, oil extraction

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

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Authors: Abdul Halim Abdul Razik, Ali Elkamel, Leonardo Simon

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Wheat straw is one of the alternative feedstocks that may be utilized for bioethanol production especially when sustainability criteria are the major concerns. To increase market competitiveness, optimal supply chain plays an important role since wheat straw is a seasonal agricultural residue. In designing the supply chain optimization model, economic profitability of the thermochemical and biochemical conversion routes options were considered. It was found that torrefied pelletization with gasification route to be the most profitable option to produce bioethanol from the lignocellulosic source of wheat straw.

Keywords: bio-ethanol, optimization, supply chain, wheat straw

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Due to increasing cost pressure in global markets, artificial intelligence is becoming a technology that is decisive for competition. Predictive quality enables machinery and plant manufacturers to ensure product quality by using data-driven forecasts via machine learning models as a decision-making basis for test results. The use of cross-process Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: predictive quality, hydraulics, machine learning, classification, supervised learning

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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Authors: Simon Tsipis

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In this study, we propose to analyze Russian foreign policy conduct by applying the theory of Political Realism and the qualitative comparative method of analysis. We find that the paradigm of Political Realism supplies us with significant insights into the sources of contemporary Russian foreign policy conduct since the power factor was and remains an integral element in Russian foreign policies, especially when we apply comparative analysis and compare it with the behavior of its Soviet predecessor. Through the lens of the Realist theory, a handful of Russian foreign policy-making becomes clearer and much more comprehensible.

Keywords: realism, Russia, cold war, Soviet Union, European security

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Authors: Sujit K. Basak, Simon Collin

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The aim of this paper is to examine the technology access and use on the affecting social integration of local students at university. This aim is achieved by designing a structural equation modeling (SEM) in terms of integration with peers, integration with faculty, faculty support and on the other hand, examining the socio demographic impact on the technology access and use. The collected data were analyzed using the WarpPLS 5.0 software. This study was survey based and it was conducted at a public university in Canada. The results of the study indicated that technology has a strong impact on integration with faculty, faculty support, but technology does not have an impact on integration with peers. However, the social demographic has also an impact on the technology access and use.

Keywords: faculty, integration, peer, technology access and use

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Authors: Simon Oga Egboja, Agi Sunday

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The government of Nigeria have invested so much in our tertiary education but the desire qualitative goals and objectives are yet to be achieved because management at all level are not efficient and effective in implementing the desired educational policies and programmes due to some management challenges. This paper investigates some of the major challenges to effective management of tertiary institution in Nigeria some variable that are important to effective management includes political stability, adequate funding, establishment of information system, recruitment and appointment of qualified teachers and condition of service.

Keywords: effective management includes political stability, adequate funding, establishment of information system, recruitment and appointment of qualified teachers

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Authors: Tizian Matschak, Ilja Nastjuk, Stephan Kühnel, Simon Trang

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We argue that besides well-known primary effects of information security controls (ISCs), namely confidentiality, integrity, and availability, ISCs can also have secondary effects. For example, while IT can add business value through impacts on business processes, ISCs can be a barrier and distort the relationship between IT and organizational value through the impact on business processes. By applying the Delphi method with 28 experts, we derived 27 business process influence dimensions of ISCs. Defining and understanding these mechanisms can change the common understanding of the cost-benefit valuation of IT security investments and support managers' effective and efficient decision-making.

Keywords: business process dimensions, dark side of information security, Delphi study, IT security controls

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Authors: Attila Simon

Abstract:

Since the publication of Franz Cumont, there have been countless works on the mysteries of Mithras and the iconography of Mithraic, but there are elements that have received less attention in research. Most of the works on the subject deal with the bull-killing-motif, whose astronomical significance has been well proven by several eminent scholars. Among the iconographic elements that survive in the reliefs and frescoes of Mithras, there are several that have not yet been clearly interpreted. These include the depiction of a bull in the boat, which occurred mainly in the Danubian provinces. Using CIMRM, one collected the cases that contain the motif under study, created a database of them grouped by location, and then used a comparative method to compare the representations adjacent to the motif. The aim of this research is to find an explanation for this neglected motif in the iconography of Mithras and to try to map its origins. The interpretation may be given to a mithraic representation for which to the author’s best knowledge no explanation has been given so far, and the question may be reopened for discussion.

Keywords: roman history, religion, Mithras, iconography

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Authors: Na Li, Samuel Simon Araya, Søren Knudsen Kær

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This study investigates the effects of operating parameters of different current density, temperature and pressure on the performance of a proton exchange membrane (PEM) water electrolysis stack. A 7-cell PEM water electrolysis stack was assembled and tested under different operation modules. The voltage change and polarization curves under different test conditions, namely current density, temperature and pressure, were recorded. Results show that higher temperature has positive effect on overall stack performance, where temperature of 80 ℃ improved the cell performance greatly. However, the cathode pressure and current density has little effect on stack performance.

Keywords: PEM electrolysis stack, current density, temperature, pressure

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Authors: Matjaž Divjak, Simon Zelič, Aleš Holobar

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We present a dedicated video-based monitoring system for quantification of patient’s attention to visual feedback during robot assisted gait rehabilitation. Two different approaches for eye gaze and head pose tracking are tested and compared. Several metrics for assessment of patient’s attention are also presented. Experimental results with healthy volunteers demonstrate that unobtrusive video-based gaze tracking during the robot-assisted gait rehabilitation is possible and is sufficiently robust for quantification of patient’s attention and assessment of compliance with the rehabilitation therapy.

Keywords: video-based attention monitoring, gaze estimation, stroke rehabilitation, user compliance

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