Search results for: John Paul G. Elizares

Authors: Gianna Zou

Abstract:

Propensity score matching (PSM), introduced by Paul R. Rosenbaum and Donald Rubin in 1983, is a popular statistical matching technique which tries to estimate the treatment effects by taking into account covariates that could impact the efficacy of study medication in clinical trials. PSM can be used to reduce the bias due to confounding variables. However, PSM assumes that the response values are normally distributed. In some cases, this assumption may not be held. In this paper, a machine learning method - Bayesian Additive Regression Tree (BART), is used as a more robust method of matching. BART can work well when models are misspecified since it can be used to model heterogeneous treatment effects. Moreover, it has the capability to handle non-linear main effects and multiway interactions. In this research, a BART Matching Method (BMM) is proposed to provide a more reliable matching method over PSM. By comparing the analysis results from PSM and BMM, BMM can perform well and has better prediction capability when the response values are not normally distributed.

Keywords: BART, Bayesian, matching, regression

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Authors: Subha D. Puthankattil, Paul K. Joseph

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Analyzing brain signals of the patients suffering from the state of depression may lead to interesting observations in the signal parameters that is quite different from a normal control. The present study adopts two different methods: Time frequency domain and nonlinear method for the analysis of EEG signals acquired from depression patients and age and sex matched normal controls. The time frequency domain analysis is realized using wavelet entropy and approximate entropy is employed for the nonlinear method of analysis. The ability of the signal processing technique and the nonlinear method in differentiating the physiological aspects of the brain state are revealed using Wavelet entropy and Approximate entropy.

Keywords: EEG, depression, wavelet entropy, approximate entropy, relative wavelet energy, multiresolution decomposition

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Authors: Raúl González Muñoz, Essam Shehab, Martin Weinitzke, Chris Fowler, Paul Baguley

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Software applications have become crucial for the aerospace industry, providing a wide range of functionalities and capabilities. However, due to the considerable time difference between aircraft and software life cycles, obsolescence has turned into a major challenge for industry in last decades. This paper aims to provide a view on the different causes of software obsolescence within aerospace industry, as well as a perception on the importance of each of them. The key research question addressed is what drives software obsolescence in the aerospace industry, managing large software application portfolios. This question has been addressed by conducting firstly an in depth review of current literature and secondly by arranging an industry workshop with professionals from aerospace and consulting companies. The result is a set of drivers of software obsolescence, distributed among three different environments and several domains. By incorporating monitoring methodologies to assess those software obsolescence drivers, benefits in maintenance efforts and operations disruption avoidance are expected.

Keywords: aerospace industry, obsolescence drivers, software lifecycle, software obsolescence

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Authors: Tokuei Sako, Paul-Antoine Hervieux

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The energy-level structure of a pair of electron and positron confined in a quasi-one-dimensional nano-scale potential well has been investigated focusing on its trend in the small limit of confinement strength ω, namely, the Wigner molecular regime. An anisotropic Gaussian-type basis functions supplemented by high angular momentum functions as large as l = 19 has been used to obtain reliable full configuration interaction (FCI) wave functions. The resultant energy spectrum shows a band structure characterized by ω for the large ω regime whereas for the small ω regime it shows an energy-level pattern dominated by excitation into the in-phase motion of the two particles. The observed trend has been rationalized on the basis of the nodal patterns of the FCI wave functions.

Keywords: confined systems, positron, wave function, Wigner molecule, quantum dots

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Authors: John Ayodele Oyewole

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Investigative journalism in Nigeria is increasingly declining as a result of some challenges associated with its practice, where corruption, incessant insecurity, embezzlement, religion, tribalism, and nepotism have indeed become a routine to the detriment of the country in every aspect of life. Investigative journalism is hardly being practised in Nigeria today because journalists fear for their lives. With in-depth interviews, this research uses the theory of media responsibility to examine the nature of investigative journalism in Nigeria, coupled with the exploration of secondary data - looking into how the Nigerian media disseminate news that is supposed to be continuous but is never brought to a conclusive end - where the hope of the audience with the current momentum of such news, as well as the enthusiasm of the audience to follow such stories is dashed, for lack of follow up of such stories. Therefore the paper suggests the need to resuscitate investigative journalism in Nigeria and the need to promulgate special laws to protect journalists.

Keywords: dearth, investigative journalism, Nigeria, journalism

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Authors: Nihal Esam Abuzinadah, Areej Abbas Malibari, Arwa Abdulaziz Allinjawi, Paul Krause

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Deaf and hearing-impaired students face many obstacles throughout their education, especially with learning applied sciences such as computer programming. In addition, there is no clear signs in the Arabic Sign Language that can be used to identify programming logic terminologies such as while, for, case, switch etc. However, hearing disabilities should not be a barrier for studying purpose nowadays, especially with the rapid growth in educational technology. In this paper, we develop an Avatar based system to teach computer programming to deaf and hearing-impaired students using Arabic Signed language with new signs vocabulary that is been developed for computer programming education. The system is tested on a number of high school students and results showed the importance of visualization in increasing the comprehension or understanding of concepts for deaf students through the avatar.

Keywords: hearing-impaired students, isolation, self-esteem, learning difficulties

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Authors: Rene A. Amadore Jr., Ramar John Bangayan, Therese Eileen L. Natividad

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This is a case of a 59-year-old female who presented with a two-year history of heliotrope rash, Gottron's papules, shawl sign, V-neck sign, and muscle weakness. She was previously managed as a case of systemic lupus erythematosus, who initially responded to unrecalled corticosteroids. She was, however, admitted due to a one-month progressively enlarging sacral mass, which eventually turned out to be an abscess. While the abscess was being treated, her autoimmune condition was worked up, and she was then managed as a case of clinically amyopathic dermatomyositis (CADM) with interstitial lung disease (ILD). She received corticosteroids and underwent the first cycle of cyclophosphamide infusion prior to discharge.

Keywords: clinically amyopathic dermatomyositis, interstitial lung disease, corticosteroids, sacral abscess

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Authors: K. Brince Paul, Nagendra Pratap Singh, Shiv Govind Singh, Siva Rama Krishna Vanjari

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In this paper, we report optimized procedure for synthesizing highly oriented, horizontally aligned, Zinc oxide (ZnO) nanowires targeted towards developing highly sensitive piezoelectric transduction elements. The synthesis was carried out using Electrospinning technique, a facile, robust, low cost technique for producing nanowires. The as-synthesized ZnO nanowires were characterized by X-ray powder diffraction (XRD), Field Emission scanning electron microscopy (FESEM) and Energy-dispersive X-ray spectroscopy (EDX).The Piezoelectric behavior of these nanowires was characterized using Peizoelectric Force microscopy (PFM). A very high d33 coefficient of 23.1 pm/V obtained through the PFM measurements is an indicative of its potential application towards developing miniaturized piezoelectric transduction elements for nanoscale devices.

Keywords: electrospinning, piezoelectric, technique, zinc oxide

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Authors: Sanchayan Banerjee, Peter John

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Nudge plus is a modification of the toolkit of behavioural public policy. It incorporates an element of reflection¾the plus¾into the delivery of a nudge, either blended in or made proximate. Nudge plus builds on recent work combining heuristics and deliberation. It may be used to design pro-social interventions that help preserve the autonomy of the agent. The argument turns on seminal work on dual systems, which presents a subtler relationship between fast and slow thinking than commonly assumed in the classic literature in behavioural public policy. We review classic and recent work on dual processes to show that a hybrid is more plausible than the default interventionist or parallel competitive framework. We define nudge plus, set out what reflection could entail, provide examples, outline causal mechanisms, and draw testable implications.

Keywords: nudge, nudge plus, think, dual process theory

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Authors: Estela Macedo Alves

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This paper is an overview on public policy analysis focused on the study of Brazilian public policy making process. The methodology is based on the review of some theories on the subject, linking them to Brazilian reality. The study presents basic policy analysis concepts, such as policy, polity and politics. It is emphasized John Kingdon's Multiple Stream Model, because of its clarifying aspects concerning public policies formulation process in democratic countries. In this path it was possible to establish interpretations on environmental public policies in Brazil and understand its methods, instead of presenting only a case study. At the end, it is possible to connect theory with Brazilian reality, identifying negative and positive points of its political processes and structure.

Keywords: Brazilian policies, environmental public policy, multiple stream model, public policy analysis

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Authors: Paul Ihuoma Oluikpe

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The purpose of this paper is to explore and highlight the process of creating value for strategy management by embedding knowledge management in the business process. Knowledge management can be seen from a three-dimensional perspective of content, connections and competencies. These dimensions can be embedded in the knowledge processes (create, capture, share, and apply) and operationalized within a business process to effectively create a scenario where knowledge can be focused on enabling a process and the process in turn generates outcomes. The application of knowledge management on business processes of organizations is rare and underreported. Few researches have explored this paradigm although researches have tended to reinforce the notion that competitive advantage sits within the internal aspects of the firm. Given this notion, it is surprising that knowledge management research and practice have not focused sufficiently on the business process which is the basic unit of organizational decision implementation. This research serves to generate understanding on applying KM in business process using a large multinational in Sub-Saharan Africa.

Keywords: knowledge management, business process, strategy, multinational

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Authors: Sandeep Reddy, Sonia Allan, Simon Coghlan, Paul Cooper

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Artificial Intelligence (AI) and its application in medicine has generated ample interest amongst policymakers and clinicians. Successes with AI in medical imaging interpretation and clinical decision support are paving the way for its incorporation into routine healthcare delivery. While there has been a focus on the development of ethical principles to guide its application in healthcare, challenges of this application go beyond what ethics principles can address thus requiring robust governance frameworks. Also, while ethical challenges of medical artificial intelligence are being discussed, the ethics of deploying AI in lower-income countries receive less attention than in other developed economies. This creates an imperative not only for sound ethical guidelines but also for robust governance frameworks to regulate AI in medicine around the world. In this article, we discuss what components need to be considered in developing these governance frameworks and who should lead this worldwide effort.

Keywords: artificial intelligence, global health, governance, ethics

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Authors: Iris Käppler, Paul Matthäi, Chokri Cherif

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In the scope of application of technical textiles, Non-Crimp Fabrics are increasingly used. In general, NCF exhibit excellent load bearing properties, but caused by the manufacturing process, there are some remaining disadvantages which have to be reduced. Regarding to this, a novel technique of processing NCF was developed substituting the binding-thread by an adhesive. This stitch-free method requires new manufacturing concept as well as new basic methods to prove adhesion of glue at fibres and textiles. To improve adhesion properties and the wettability of carbon-fibres by the adhesive, oxyfluorination was used. The modification of carbon-fibres by oxyfluorination was investigated via scanning electron microscope, X-ray photo electron spectroscopy and single fibre tensiometry. Special tensile tests were developed to determine the maximum force required for detachment.

Keywords: non-crimp fabric, adhesive, stitch-free, high-performance fibre

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Authors: Mohammad Salah Abdullatif, Salam Hajjar, Paul Khanna

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The development of instrument grade mmWave transceivers comes with many challenges. A general rule of thumb is that the performance of the instrument must be higher than the performance of the unit under test in terms of accuracy and stability. The calibration and characterizing of mmWave transceivers are important pillars for testing commercial products. Using a Vector Network Analyzer (VNA) with a mixer option has proven a high performance as an approach to calibrate mmWave transceivers. However, this approach comes with a high cost. In this work, a reduced-cost method to calibrate mmWave transceivers is proposed. A comparison between the proposed method and the VNA technology is provided. A demonstration of significant challenges is discussed, and an approach to meet the requirements is proposed.

Keywords: mmWave transceiver, scalar characterization, coupler connection, magic tee connection, calibration, VNA, vector network analyzer

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Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

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The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Paul W. Murray, Marco Barajas

Abstract:

Recent changes in supply chains, especially globalization and collaboration, have created new risks for enterprises of all sizes. A variety of complex frameworks, often based on enterprise risk management strategies have been presented under the heading of Supply Chain Risk Management (SCRM). The literature on promotes the benefits of a robust SCRM strategy; however, implementing SCRM is difficult and resource demanding for Large Enterprises (LEs), and essentially out of reach for Small and Medium Enterprises (SMEs). This research debunks the idea that SCRM is necessary for all enterprises and instead proposes a simple and effective Vendor Selection Template (VST). Empirical testing and a survey of supply chain practitioners provide a measure of validation to the VST. The resulting VSTis a valuable contribution because is easy to use, provides practical results, and is sufficiently flexible to be universally applied to SMEs.

Keywords: multiple regression analysis, supply chain management, risk assessment, vendor selection

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

Abstract:

Epilepsy is a common neurological disorders characterized by sudden recurrent seizures. Electroencephalogram (EEG) is widely used to diagnose possible epileptic seizure. Many research works have been devoted to predict epileptic seizure by analyzing EEG signal. Seizure prediction by analyzing EEG signals are challenging task due to variations of brain signals of different patients. In this paper, we propose a new approach for feature extraction based on phase correlation in EEG signals. In phase correlation, we calculate relative change between two consecutive segments of an EEG signal and then combine the changes with neighboring signals to extract features. These features are then used to classify preictal/ictal and interictal EEG signals for seizure prediction. Experiment results show that the proposed method carries good prediction rate with greater consistence for the benchmark data set in different brain locations compared to the existing state-of-the-art methods.

Keywords: EEG, epilepsy, phase correlation, seizure

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Authors: Lozano Paul

Abstract:

Coupled Membrane Separation Technology (CMST), including Cross Flow Microfiltration (CFM) and Reverse Osmosis (RO), are used to concentrate microalgae biomass or/and to extract and concentrate water-soluble metabolites produced during micro-algae production cycle, as well as water recycling. Micro-algae biomass was produced using different feeding mixtures of ingredients: pure chemical origin compounds and natural/ecological water-extracted components from available local plants. Micro-algae was grown either in conventional plastic bags (100L/unit) or in small-scale innovative bioreactors (75L). Biomass was concentrated as CFM retentate using a P19-60 ceramic membrane (0.2μm pore size), and water-soluble micro-algae metabolites left in the CFM filtrate were concentrated by RO. Large volumes of water (micro-algae culture media) of were recycled by the CMTS for another biomass production cycle.

Keywords: extraction, membrane process, microalgae, natural compound

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Authors: Nidhal K. Azawi, John M. Gauch

Abstract:

Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

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Authors: Paul Okonkwo, Howard Smith

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A study to estimate the size of the cabin and major aircraft components as well as detect and avoid interference between internally placed components and the external surface, during the conceptual design synthesis and optimisation to explore the design space of a BWB, was conducted. Sizing of components follows the Bradley cabin sizing and rubber engine scaling procedures to size the cabin and engine respectively. The interference detection and avoidance algorithm relies on the ability of the Class Shape Transform parameterisation technique to generate polynomial functions of the surfaces of a BWB aircraft configuration from the sizes of the cabin and internal objects using few variables. Interference detection is essential in packaging of non-conventional configuration like the BWB because of the non-uniform airfoil-shaped sections and resultant varying internal space. The unique configuration increases the need for a methodology to prevent objects from being placed in locations that do not sufficiently enclose them within the geometry.

Keywords: packaging, optimisation, BWB, parameterisation, aircraft conceptual design

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Authors: Felix Damilola Ajibade, Opeyemi O. Enoch, Taiwo Paul Fajusigbe

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This paper is centered on conducting an inquiry into the stability of the F* iterative algorithm to the fixed point of a strongly pseudo-contractive mapping in the framework of uniformly convex Banach spaces. To achieve the desired result, certain existing inequalities in convex Banach spaces were utilized, as well as the stability criteria of Harder and Hicks. Other necessary conditions for the stability of the F* algorithm on strong pseudo-contractive mapping were also obtained. Through a numerical approach, we prove that the F* iterative algorithm is H-stable for strongly pseudo-contractive mapping. Finally, the solution of the mixed-type Volterra-Fredholm functional non-linear integral equation is estimated using our results.

Keywords: stability, F* -iterative algorithm, pseudo-contractive mappings, uniformly convex Banach space, mixed-type Volterra-Fredholm integral equation

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Authors: F. G Okibe, C. E Gimba, V. O Ajibola, I. G Ndukwe, E. D. Paul

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A full factorial experimental design technique at two levels and four factors (24) was used to optimize the adsorption at 615 nm of Xylene Cyanol ff in aqueous solutions onto activated carbon prepared from brachystegia eurycoma seed hulls by chemical carbonization method. The effect of pH (3 and 5), initial dye concentration (20 and 60 mg/l), adsorbent dosage (0.01 and 0.05 g), and contact time (30 and 60 min) on removal efficiency of the adsorbent for the dye were investigated at 298K. From the analysis of variance, response surface and cube plot, adsorbent dosage was observed to be the most significant factor affecting the adsorption process. However, from the interaction between the variables studied, the optimum removal efficiency was 96.80 % achieved with adsorbent dosage of 0.05 g, contact time 45 minutes, pH 3, and initial dye concentration 60 mg/l.

Keywords: factorial experimental design, adsorption, optimization, brachystegia eurycoma, xylene cyanol ff

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Authors: Stepan Grebeniuk, Ersi Hodo, Henri Ruotsalainen, Paul Tavolato

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Substation security plays an important role in the power delivery system. During the past years, there has been an increase in number of attacks on automation networks of the substations. In spite of that, there hasn’t been enough focus dedicated to the protection of such networks. Aiming to design a specialized anomaly detection system based on machine learning, in this paper we will discuss the IEC 60870-5-104 protocol that is used for communication between substation and control station and focus on the simulation of the substation traffic. Firstly, we will simulate the communication between substation slave and server. Secondly, we will compare the system's normal behavior and its behavior under the attack, in order to extract the right features which will be needed for building an anomaly detection system. Lastly, based on the features we will suggest the anomaly detection system for the asynchronous protocol IEC 60870-5-104.

Keywords: Anomaly detection, IEC-60870-5-104, Machine learning, Man-in-the-Middle attacks, Substation security

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Authors: Hala Ali

Abstract:

In the evolving landscape of contemporary art, the value of failure and experimentation plays a central role in reshaping artistic research. This paper explores an artistic residency where the focus shifted from traditional practices of ink on canvas to performance art using the human body as a medium of expression. This residency emphasized uncertainty, experimentation, and emotional expression as the core of the process. Through collaboration between a calligrapher and a visual artist, the performance engaged themes of seduction, silence, and the transition between reality and abstraction. In alignment with experimental art practices, the process itself became the artwork, embracing moments of failure and disruption as key components of creative exploration. This research integrates theories from neuroscience, psychology, and artistic failure, drawing on the insights of thinkers like John Cage, Samuel Beckett, and Cornelius Cardew to further contextualize the residency’s impact.

Keywords: embodied art, emotional communication, mindfulness in art, nonverbal communication, performance art

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Authors: Ohabuiro John Uwabunkeonye

Abstract:

Source of green energy is becoming a concern in developing countries where most energy source in use emits high level of carbon (IV) oxide which contributes to global warming. More so, even with the generation of energy from fossil fuel, the electricity supply is still very inadequate. Therefore, this paper examines different ways of designing and installing photovoltaic (PV) system in terms of optimal sizing of PV array and battery storage in an area of very low peak sunlight hours (PSH) and inadequate supply of electricity from utility companies. Different sample of Peak sunlight hour for selected areas in Nigeria are considered and the lowest of it all is taken. Some means of ensuring that the available solar energy is harnessed properly and converted into electrical energy are discussed for usage in such areas as mentioned above.

Keywords: green energy, fossil fuel, peak sunlight hour, photovoltaic

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Authors: Paul Henshall, Philip Eames, Roger Moss, Stan Shire, Farid Arya, Trevor Hyde

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Encapsulating the absorber of a flat plate solar thermal collector in vacuum by an enclosure that can be evacuated can result in a significant increase in collector performance and achievable operating temperatures. This is a result of the thermal insulation effectiveness of the vacuum layer surrounding the absorber, as less heat is lost during collector operation. This work describes experimental thermal insulation characterization tests of prototype vacuum flat plate solar thermal collectors that demonstrate the improvement in absorber heat loss coefficients. Furthermore, this work describes the selection and sizing of a getter, suitable for maintaining the vacuum inside the enclosure for the lifetime of the collector, which can be activated at low temperatures.

Keywords: vacuum, thermal, flat-plate solar collector, insulation

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Authors: Dilip K. Paul

Abstract:

The most popular mesoporous molecular sieves, Mobil Composition of Matter (MCM) are keenly studied by researchers because of these materials possess amorphous silica wall and have a long range of ordered framework with uniform mesopores. These materials also possess large surface area, which can be up to more than 1000 m2g−1. Herein the investigation is focused upon the synthesis and characterization of chromium and aluminum doped MCM-41 using XRD and FTIR. Acid-base properties of Cr-Al-MCM 41 was investigated by molecularly sensitive transmission FT-IR spectroscopy by adsorbing pyridine. In addition, these MCM nanomaterial was used to catalyze C-C bond formation from acetaldehyde adsorption. The assignment of all infrared peaks during adsorption of pyridine provided detail information on the presence of acid-base sites which in turn helped us to explain the roles of these in the condensation reaction of aldehyde. Reaction mechanisms of C-C bond formation is therefore explored to shed some light on this elusive reaction detail.

Keywords: mesoporous nanomaterial, MCM 41, FTIR studies, acid-base studies

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Authors: Naziya Haseena

Abstract:

Professors play an indispensable role in education settings, sharing their knowledge and providing guidance and practical insights to the students. This study will investigate the relationship between personality traits, workplace ostracism, and knowledge-sharing behaviour among women professors. The sample of this quantitative study will consist of 200 professors from the Chennai district. It will use a convenient sampling technique to collect data using the workplace ostracism scale developed by Ferris et al. (2008), the big five personality inventory (BFI 44) developed by John (1999), and an adapted version of knowledge-sharing behavior developed by Lin (2007). The findings will provide insights and help to build the gender gap in academia to conduct personality development programs and academic collaboration among professors.

Keywords: workplace ostracism, knowledge sharing behaviour, academia, personality traits

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Authors: Delio I. Castaneda, Paul Toulson

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The purpose of this study was to investigate the knowledge sharing effectiveness of two types of knowledge, tacit and explicit, depending on two channels: face to face or digital. Participants were 217 knowledge workers in New Zealand and researchers who attended a knowledge management conference in the United Kingdom. In the study, it was found that digital tools are effective to share explicit knowledge. In addition, digital tools that facilitated dialogue were effective to share tacit knowledge. It was also found that face to face communication was an effective way to share tacit and explicit knowledge. Results of this study contribute to clarify in what cases digital tools are effective to share tacit knowledge. Additionally, even though explicit knowledge can be easily shared using digital tools, this type of knowledge is also possible to be shared through dialogue. Result of this study may support practitioners to redesign programs and activities based on knowledge sharing to make strategies more effective.

Keywords: digital knowledge, explicit knowledge, knowledge sharing, tacit knowledge

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