Search results for: asset tracking

Authors: Manmeet Kaur, Madhu Vij

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The Board of Directors in a firm performs the primary role of an internal control mechanism. This Study seeks to understand the relationship between internal governance and performance of banks in India. The research paper investigates the effect of board structure (proportion of nonexecutive directors, gender diversity, board size and meetings per year) on the firm performance. This paper evaluates the impact of corporate governance mechanisms on bank’s financial performance using panel data for 28 listed banks in National Stock Exchange of India for the period of 2008-2014. Returns on Asset, Return on Equity, Tobin’s Q and Net Interest Margin were used as the financial performance indicators. To estimate the relationship among governance and bank performance initially the Study uses Pooled Ordinary Least Square (OLS) Estimation and Generalized Least Square (GLS) Estimation. Then a well-developed panel Generalized Method of Moments (GMM) Estimator is developed to investigate the dynamic nature of performance and governance relationship. The Study empirically confirms that two-step system GMM approach controls the problem of unobserved heterogeneity and endogeneity as compared to the OLS and GLS approach. The result suggests that banks with small board, boards with female members, and boards that meet more frequently tend to be more efficient and subsequently have a positive impact on performance of banks. The study offers insights to policy makers interested in enhancing the quality of governance of banks in India. Also, the findings suggest that board structure plays a vital role in the improvement of corporate governance mechanism for financial institutions. There is a need to have efficient boards in banks to improve the overall health of the financial institutions and the economic development of the country.

Keywords: board of directors, corporate governance, GMM estimation, Indian banking

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Authors: Ramazan Bakir, Gizem Kayar

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It is known that Alzheimer and Dementia are the two most common types of Neurodegenerative diseases and their visibility is getting accelerated for the last couple of years. As the population sees older ages all over the world, researchers expect to see the rate of this acceleration much higher. However, unfortunately, there is no known pharmacological cure for both, although some help to reduce the rate of cognitive decline speed. This is why we encounter with non-pharmacological treatment and tracking methods more for the last five years. Many researchers, including well-known associations and hospitals, lean towards using non-pharmacological methods to support cognitive function and improve the patient’s life quality. As the dementia symptoms related to mind, learning, memory, speaking, problem-solving, social abilities and daily activities gradually worsen over the years, many researchers know that cognitive support should start from the very beginning of the symptoms in order to slow down the decline. At this point, life of a patient and caregiver can be improved with some daily activities and applications. These activities include but not limited to basic word puzzles, daily cleaning activities, taking notes. Later, these activities and their results should be observed carefully and it is only possible during patient/caregiver and M.D. in-person meetings in hospitals. These meetings can be quite time-consuming, exhausting and financially ineffective for hospitals, medical doctors, caregivers and especially for patients. On the other hand, digital support systems are showing positive results for all stakeholders of healthcare systems. This can be observed in countries that started Telemedicine systems. The biggest potential of our system is setting the inter-user communication up in the best possible way. In our project, we propose Machine Learning based digitalization of validated traditional cognitive tests (e.g. MOCA, Afazi, left-right hemisphere), their analyses for high-quality follow-up and communication systems for all stakeholders. R. Bakir and G. Kayar are with Gefeasoft, Inc, R&D – Software Development and Health Technologies company. Emails: ramazan, gizem @ gefeasoft.com This platform has a high potential not only for patient tracking but also for making all stakeholders feel safe through all stages. As the registered hospitals assign corresponding medical doctors to the system, these MDs are able to register their own patients and assign special tasks for each patient. With our integrated machine learning support, MDs are able to track the failure and success rates of each patient and also see general averages among similarly progressed patients. In addition, our platform also supports multi-player technology which helps patients play with their caregivers so that they feel much safer at any point they are uncomfortable. By also gamifying the daily household activities, the patients will be able to repeat their social tasks and we will provide non-pharmacological reminiscence therapy (RT – life review therapy). All collected data will be mined by our data scientists and analyzed meaningfully. In addition, we will also add gamification modules for caregivers based on Naomi Feil’s Validation Therapy. Both are behaving positively to the patient and keeping yourself mentally healthy is important for caregivers. We aim to provide a therapy system based on gamification for them, too. When this project accomplishes all the above-written tasks, patients will have the chance to do many tasks at home remotely and MDs will be able to follow them up very effectively. We propose a complete platform and the whole project is both time and cost-effective for supporting all stakeholders.

Keywords: alzheimer’s, dementia, cognitive functionality, cognitive tests, serious games, machine learning, artificial intelligence, digitalization, non-pharmacological, data analysis, telemedicine, e-health, health-tech, gamification

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Authors: Patricia Chinyere Oranefo

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This study examined the effect of sustainability accounting disclosure on financial performance of listed Brewery firms in Nigeria. The dearth of empirical evidence and literature on “governance disclosure” as one of the explanatory variables of sustainability accounting reporting were the major motivation for this study. The main objective was to ascertain the effect of sustainability accounting disclosure on financial performance of listed Brewery firms in Nigeria. An ex–post facto research design approach was adopted for the study. The population of this study comprises of five (5) Brewery firms quoted on the floor of the Nigeria exchange group (NSX) and the sample size of four (4) listed firms was drawn using purposive sampling method. Secondary data were carefully sourced from the financial statement/annual reports and sustainability reports from 2012 to 2021 of the Brewery firms quoted on the Nigeria exchange group (NSX). Panel regression analysis by aid of E-views 10.0 software was used to test for statistical significance of the effect of sustainability accounting disclosure on financial performance of listed Brewery firms in Nigeria. The results showed that economic sustainability disclosure indexes do not significantly affect return on asset of listed Brewery firms in Nigeria. The findings further revealed that environmental sustainability disclosure indexes do not significantly affect return on equity of listed Brewery firms in Nigeria. More so, results showed that Social Sustainability disclosure indexes significantly affect Net Profit Margin of listed Brewery firms in Nigeria. Finally, the result established also that governance sustainability disclosure indexes do not significantly affect Earnings per share of listed Brewery firms in Nigeria. Consequent upon the findings, this study recommended among others; that managers of Brewers in Nigeria should improve and sustain full disclosure practices on economic, environmental, social and governance disclosures following the guidelines of the Global Reporting Index (GRI) as they are capable of exerting significant effect on financial performance of firms in Nigeria.

Keywords: sustainability, accounting, disclosure, financial performance

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Authors: Brian Wartell, Michel Boufadel

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Contaminants such as polycyclic aromatic hydrocarbons (PAHs) are compounds present in crude and petroleum oils and are known to be toxic and often carcinogenic. Therefore, a major effort is placed on tracking their subsurface soil concentrations following an oil spill. The PAHs can persist for years in the subsurface especially if there is a lack of oxygen. Both aerobic and anaerobic biodegradation of PAHs encounter the difficulties of both nutrient transport and bioavailability (proximal access) to the organisms of the contaminants. A technology, known as electrokinetics (EK or EK-BIO for ‘electrokinetic bioremediation’) has been found to transport efficiently nutrients or other chemicals in the subsurface. Experiments were conducted to demonstrate migration patterns in both sands and clay for both ionic and nonionic compounds and aerobic biodegradation studies were conducted with soil spiked with Polycyclic Aromatic Hydrocarbons yielding interesting results. In one set of experiment, Self-designed electrokinetic setups were constructed to examine the differences in electromigration and electroosmotic rates. Anionic and non-ionic dyes were used to visualize these phenomena, respectively. In another experiment, a silt-clay soil was spiked with three low-molecular-weight compounds (fluorene, phenanthrene, fluoranthene) and placed within self-designed electrokinetic setups and monitored for aerobic degradation. Plans for additional studies are in progress including the transport of peroxide through anaerobic sands.

Keywords: bioavailability, bioremediation, electrokinetics, subsurface transport

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Authors: Malik Takreem Ahmad, Pablo Lamata, Rasi Mizori

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Background: In recent years, mobile health apps have grown in popularity as a means for people to track and manage their health. While there is increasing worry that these applications may potentially contribute to the emergence of health anxiety, they can also help to encourage healthy behaviours and provide access to health information. Objective: The objective of this literature review is to look at available mhealth apps and critically evaluate the compromise between reassurance and anxiety. Methodology: A literature review was carried out to analyse the effects of mhealth apps on the creation of health anxiety within the general population. PubMed and SCOPUS were used to search for relevant articles, and abstracts were screened using inclusion criteria of the terms: mhealth apps; e-Health; healthcare apps; cyberchondria; Health anxiety; illness anxiety disorder. A total of 27 studies were included in the review. Results and discussion: The findings suggest a direct relationship between mobile health app use and health anxiety. The impact of mobile health apps on health anxiety may depend on how they are used - individuals receiving a constant stream of health-related information may trigger unnecessary concern about one's health. The need for more regulation and oversight is identified, which can lead to app quality and safety consistency. There are also concerns about data security and privacy and the resulting "digital gap" for individuals without mobiles or internet access. Conclusion: While health apps can be valuable tools for managing and tracking health, individuals need to use them in a balanced and informed way to avoid increased anxiety.

Keywords: mobile health, mhealth apps, cyberchondria, health anxiety

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Authors: Nadia Samantha Zuñiga-Peña, Norberto Hernández-Romero, Omar Aguilar-Mejia, Salatiel García-Nava

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Using unmanned aerial vehicles (UAVs) for load transport has gained significant importance in various sectors due to their ability to improve efficiency, reduce costs, and access hard-to-reach areas. Although UAVs offer numerous advantages for load transport, several complications and challenges must be addressed to exploit their potential fully. Complexity relays on UAVs are underactuated, non-linear systems with a high degree of coupling between their variables and are subject to forces with uncertainty. One of the biggest challenges is modeling and controlling the system formed by UAVs carrying a load. In order to solve the controller problem, in this work, a hybridization of Neural Network and Hunger Games Search (HGS) metaheuristic algorithm is developed and implemented to find the parameters of the Super Twisting Sliding Mode Controller for the 8 degrees of freedom model of UAV with payload. The optimized controller successfully tracks the UAV through the three-dimensional desired path, demonstrating the effectiveness of the proposed solution. A comparison of performance shows the superiority of the neural network HGS (NNHGS) over the HGS algorithm, minimizing the tracking error by 57.5 %.

Keywords: neural networks, hunger games search, super twisting sliding mode controller, UAVs.

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Authors: Jerome Nyameh

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The most valuable asset in the existence of organization is the employees and their ability in maintain appreciable level of performance which support the goal of the organization and the ability to do that depend largely on the organizational culture and culture has been considered most currently as the factor that relate positively to organizational excellence and sustainable employee’s performance over the period of time An employee engagement program will not go far without first establishing the organizational culture that is required to support sustainability. This means integrating sustainability into the overall employee’s performance, with clear vision, goals and metrics. It means having strong culture and a collaborative governance structure that has been develop as a ways of doing things in the organization for decision making and resource allocation. It requires a rewards and recognition program to support and reinforce sustainability behaviors. With such a culture in place, organization will be able to develop a strategy that fully engages employees, while fully realizing the benefits of their contributions. The study investigated empirically the role of organizational culture building sustainable employee’s performance using Zenith bank PLC a model where organizational culture will build sustainable employees performance strategy for a lasting actualization of organizational was developed. In order to achieve the research objectives of (i) to assess how organizational culture can build sustainable employee’s performance (ii) to analyze the gap that exists between organizational culture and sustainable employee’s performance in the organization, a survey questionnaires of 20 items was administered to sixty respondents. The findings of this study have practical implications for organizational leaders, managers and employees, and their organizations, particularly commercial banks in Nigeria, besides offering scope for further research in the area of organizational culture and sustainable employee’s performance. It will also show a significance and positive relationship that exist between organizational culture and sustainable employee’s performance, as means of building viable organization with cultural uniqueness and excellence performance in the world of competition.

Keywords: organizational culture, sustainable employee’s performance, organizations, Zenith Bank PLC Nigeria

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Authors: Karan Vishavjit, Aakash Lakra, Shafaq Khan

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The COVID-19 pandemic has pushed healthcare professionals to use big data analytics as a vital tool for tracking and evaluating the effects of contagious viruses. To effectively analyze huge datasets, efficient NoSQL databases are needed. The analysis of post-COVID-19 health and well-being outcomes and the evaluation of the effectiveness of government efforts during the pandemic is made possible by this research’s integration of several datasets, which cuts down on query processing time and creates predictive visual artifacts. We recommend applying sharding and indexing technologies to improve query effectiveness and scalability as the dataset expands. Effective data retrieval and analysis are made possible by spreading the datasets into a sharded database and doing indexing on individual shards. Analysis of connections between governmental activities, poverty levels, and post-pandemic well being is the key goal. We want to evaluate the effectiveness of governmental initiatives to improve health and lower poverty levels. We will do this by utilising advanced data analysis and visualisations. The findings provide relevant data that supports the advancement of UN sustainable objectives, future pandemic preparation, and evidence-based decision-making. This study shows how Big Data and NoSQL databases may be used to address problems with global health.

Keywords: big data, COVID-19, health, indexing, NoSQL, sharding, scalability, well being

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Authors: Rims Janeliukstis, Deniss Mironovs, Andrejs Kovalovs

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Operational Modal Analysis (OMA) is widely applied as a method for Structural Health Monitoring for structural damage identification and assessment by tracking the changes of the identified modal parameters over time. Unfortunately, modal parameters also depend on such external factors as temperature and loads. Any structural condition assessment using modal parameters should be done taking into consideration those external factors, otherwise there is a high chance of false positives. A method of structural reliability assessment based on anomaly detection technique called Machalanobis Squared Distance (MSD) is proposed. It requires a set of reference conditions to learn healthy state of a structure, which all future parameters are compared to. In this study, structural modal parameters (natural frequency and mode shape), as well as ambient temperature and loads acting on the structure are used as features. Numerical tests were performed on a finite element model of a carbon fibre reinforced polymer composite beam with delamination damage at various locations and of various severities. The advantages of the demonstrated approach include relatively few computational steps, ability to distinguish between healthy and damaged conditions and discriminate between different damage severities. It is anticipated to be promising in reliability assessment of massively produced structural parts.

Keywords: operational modal analysis, reliability assessment, anomaly detection, damage, mahalanobis squared distance

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Authors: Abdelhak Djoudi, Hachemi Chekireb, El Madjid Berkouk

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The doubly fed induction generator (DFIG) received recently an important consideration in medium and high power wind energy conversion systems integration, due to its advantages compared to other generators types. The stator power sliding mode control (SPSMC) proves a great efficiency judge against other control laws and schemes. In the SPSMC laws elaborated by several authors, only the slide surface tracking conditions are elaborated using Lyapunov functions, and the boundedness of the DFIG states is never treated. Some works have validated theirs approaches by experiments results in the case of specified machines, but these verifications stay insufficient to generalize to other machines range. Adding to this argument, the DFIG states boundedness demonstration is widely suggested in goal to ensure that in the application of the SPSMC, the states evaluates within theirs tolerable bounds. Our objective in the present paper is to highlight the efficiency of the SPSMC by stability analysis. The boundedness of the DFIG states such as the stator current and rotor flux is discussed. Moreover, the states trajectories are finding using analytical proves taking into consideration the SPSMC gains.

Keywords: Doubly Fed Induction Generator (DFIG), Stator Powers Sliding Mode Control (SPSMC), lyapunov function, stability, states boundedness, trajectories mathematical proves

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Authors: Girts Zageris, Vadims Geza, Andris Jakovics

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Gasification processes are of great interest due to their generation of renewable energy in the form of syngas from biodegradable waste. It is, therefore, important to study the factors that play a role in the efficiency of gasification and the longevity of the machines in which gasification takes place. This study focuses on the latter, aiming to optimize an entrained-flow gasifier by reducing slag formation on its walls to reduce maintenance costs. A CFD mathematical model for an entrained-flow gasifier is constructed – the model of an actual gasifier is rendered in 3D and appropriately meshed. Then, the turbulent gas flow in the gasifier is modeled with the realizable k-ε approach, taking devolatilization, combustion and coal gasification into account. Various such simulations are conducted, obtaining results for different air inlet positions and by tracking particles of varying sizes undergoing devolatilization and gasification. The model identifies potential problematic zones where most particles collide with the gasifier walls, indicating risk regions where ash deposits could most likely form. In conclusion, the effects on the formation of an ash layer of air inlet positioning and particle size allowed in the main gasifier tank are discussed, and possible solutions for decreasing a number of undesirable deposits are proposed. Additionally, an estimate of the impact of different factors such as temperature, gas properties and gas content, and different forces acting on the particles undergoing gasification is given.

Keywords: biomass particles, gasification, slag formation, turbulence k-ε modelling

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Authors: J. F. Viljoen, Catherine Foxcroft

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Expert sight readers rely on their ability to recognize patterns in scores, their inner hearing and prediction skills in order to perform complex sight reading exercises. They also have the ability to observe deviations from expected patterns in musical scores. This increases the “Eye-hand span” (reading ahead of the point of playing) in order to process the elements in the score. The study aims to investigate the gaze patterns of expert and non-expert sight readers focusing on key and time signatures. 20 musicians were tasked with playing 12 sight reading examples composed for one hand and five examples composed for two hands to be performed on a piano keyboard. These examples were composed in different keys and time signatures and included accidentals and changes of time signature to test this theory. Results showed that the experts fixate more and for longer on key and time signatures as well as deviations in examples for two hands than the non-expert group. The inverse was true for the examples for one hand, where expert sight readers showed fewer and shorter fixations on key and time signatures as well as deviations. This seems to suggest that experts focus more on the key and time signatures as well as deviations in complex scores to facilitate sight reading. The examples written for one appeared to be too easy for the expert sight readers, compromising gaze patterns.

Keywords: cognition, eye tracking, musical notation, sight reading

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Authors: Sylvester S. Horvey, Jones Mensah

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The growing complexities and dynamics in the business environment have led to a new approach to risk management, known as enterprise risk management (ERM). ERM is a system and an approach to managing the risks of an organization in an integrated manner to achieve the corporate goals and strategic objectives. Regardless of the diversities in the business environment, ERM has become an essential factor in managing individual and business risks because ERM is believed to enhance shareholder value and firm growth. Despite the growing number of literature on ERM, the question about what factors drives ERM remains limited. This study provides a comprehensive literature review of the main factors that contribute to ERM implementation. Google Scholar was the leading search engine used to identify empirical literature, and the review spanned between 2000 and 2020. Articles published in Scimago journal ranking and Scopus were examined. Thirteen firm characteristics and sixteen articles were considered for the empirical review. Most empirical studies agreed that firm size, institutional ownership, industry type, auditor type, industrial diversification, earnings volatility, stock price volatility, and internal auditor had a positive relationship with ERM adoption, whereas firm size, institutional ownership, auditor type, and type of industry were mostly seen be statistically significant. Other factors such as financial leverage, profitability, asset opacity, international diversification, and firm complexity revealed an inconclusive result. The growing literature on ERM is not without limitations; hence, this study suggests that further research should examine ERM determinants within a new geographical context while considering a new and robust way of measuring ERM rather than relying on a simple proxy (dummy) for ERM measurement. Other firm characteristics such as organizational culture and context, corporate scandals and losses, and governance could be considered determinants of ERM adoption.

Keywords: enterprise risk management, determinants, ERM adoption, literature review

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Authors: Brahmi Brahim, Mohammad Habibur Rahman, Maarouf Saad, Cristóbal Ochoa Luna

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A repetitive training movement is an efficient method to improve the ability and movement performance of stroke survivors and help them to recover their lost motor function and acquire new skills. The ETS-MARSE is seven degrees of freedom (DOF) exoskeleton robot developed to be worn on the lateral side of the right upper-extremity to assist and rehabilitate the patients with upper-extremity dysfunction resulting from stroke. Practically, rehabilitation activities are repetitive tasks, which make the assistive/robotic systems to suffer from repetitive/periodic uncertainties and external perturbations induced by the high-order dynamic model (seven DOF) and interaction with human muscle which impact on the tracking performance and even on the stability of the exoskeleton. To ensure the robustness and the stability of the robot, a new nonlinear backstepping control was implemented with designed tests performed by healthy subjects. In order to limit and to reject the periodic/repetitive disturbances, an iterative estimator was integrated into the control of the system. The estimator does not need the precise dynamic model of the exoskeleton. Experimental results confirm the robustness and accuracy of the controller performance to deal with the external perturbation, and the effectiveness of the iterative estimator to reject the repetitive/periodic disturbances.

Keywords: backstepping control, iterative control, Rehabilitation, ETS-MARSE

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Authors: Robin Molinier

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Industrial symbiosis (I.S) rely on two basic modes of cooperation between organizations that are infrastructure/service sharing and resource substitution (the use of waste materials, fatal energy and recirculated utilities for production). The former consists in the intensification of use of an asset and thus requires to compare the incremental investment cost to be incurred and the stand-alone cost faced by each potential participant to satisfy its own requirements. In order to investigate the way such a cooperation mode can be implemented we formulate a game theoretic model integrating the grassroot investment decision and the ex-post access pricing problem. In the first period two actors set cooperatively (resp. non-cooperatively) a level of common (resp. individual) infrastructure capacity oversizing to attract ex-post a potential entrant with a plug-and-play offer (available capacity, tariff). The entrant’s requirement is randomly distributed and known only after investments took place. Capacity cost exhibits sub-additive property so that there is room for profitable overcapacity setting in the first period under some conditions that we derive. The entrant willingness-to-pay for the access to the infrastructure is driven by both her standalone cost and the complement cost to be incurred in case she chooses to access an infrastructure whose the available capacity is lower than her requirement level. The expected complement cost function is thus derived, and we show that it is decreasing, convex and shaped by the entrant’s requirements distribution function. For both uniform and triangular distributions optimal capacity level is obtained in the cooperative setting and equilibrium levels are determined in the non-cooperative case. Regarding the latter, we show that competition is deterred by the first period investor with the highest requirement level. Using the non-cooperative game outcomes which gives lower bounds for the profit sharing problem in the cooperative one we solve the whole game and describe situations supporting sharing agreements.

Keywords: capacity, cooperation, industrial symbiosis, pricing

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Authors: Hesham Abdin, Mohamed Zakaria, Talaat Abd-Elmonaem, Alaa El-Din Sayed Hafez

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Kalman filter algorithm is an estimator known as the workhorse of estimation. It has an important application in missile guidance, especially in lack of accurate data of the target due to noise or uncertainty. In this paper, a Kalman filter is used as a tracking filter in a simulated target-interceptor scenario with noise. It estimates the position, velocity, and acceleration of the target in the presence of noise. These estimations are needed for both proportional navigation and differential geometry guidance laws. A Kalman filter has a good performance at low noise, but a large noise causes considerable errors leads to performance degradation. Therefore, a new technique is required to overcome this defect using tuning factors to tune a Kalman filter to adapt increasing of noise. The values of the tuning factors are between 0.8 and 1.2, they have a specific value for the first half of range and a different value for the second half. they are multiplied by the estimated values. These factors have its optimum values and are altered with the change of the target heading. A genetic algorithm updates these selections to increase the maximum effective range which was previously reduced by noise. The results show that the selected factors have other benefits such as decreasing the minimum effective range that was increased earlier due to noise. In addition to, the selected factors decrease the miss distance for all ranges of this direction of the target, and expand the effective range which leads to increase probability of kill.

Keywords: proportional navigation, differential geometry, Kalman filter, genetic algorithm

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Authors: Ivana Cestar, Ivica Stančerić, Saša Ahac, Vesna Dragčević, Tamara Džambas

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On special paved areas, such as road intersections, vehicles are usually moving through horizontal curves with smaller radii and occupy considerably greater area compared to open road segments. Planning procedure of these areas is mainly an iterative process that consists of designing project elements, assembling those elements to a design project, and analyzing swept paths for the design vehicle. If applied elements do not fulfill the swept path requirements for the design vehicle, the process must be carried out again. Application of specialized computer software for swept path analysis significantly facilitates planning procedure of special paved areas. There are various software of this kind available on the global market, and each of them has different specifications. In this paper, comparison of two software commonly used in Croatia (Auto TURN and Vehicle Tracking) is presented, their advantages and disadvantages are described, and their applicability on a particular paved area is discussed. In order to reveal which one of the analyszed software is more favorable in terms of swept paths widths, which one includes input parameters that are more relevant for this kind of analysis, and which one is more suitable for the application on a certain special paved area, the analysis shown in this paper was conducted on a number of different intersection types.

Keywords: software comparison, special paved areas, swept path analysis, swept path input parameters

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Authors: Susan Lewis

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The assessment of learning outcomes at the program level has attracted much international interest from the perspectives of quality assurance and ongoing curricular redesign and renewal. This paper examines program-level learning outcomes in the field of music and technology, an area of study that has seen an explosion in program development over the past fifteen years. The Audio Engineering Society (AES) maintains an online directory of educational institutions worldwide, yielding the most comprehensive inventory of programs and courses in music and technology. The inventory includes courses, programs, and degrees in music and technology, music and computer science, music production, and the music industry. This paper focuses on published student learning outcomes for undergraduate degrees in music and technology and analyses commonalities at institutions in North America, the United Kingdom, and Europe. The results of a survey of student learning outcomes at twenty institutions indicates a focus on three distinct student learning outcomes: (1) cross-disciplinary knowledge in the fields of music and technology; (2) the practical application of training through the professional industry; and (3) the acquisition of skills in communication and collaboration. The paper then analyses assessment mechanisms for tracking student learning and achievement of learning outcomes at these institutions. The results indicate highly variable assessment practices. Conclusions offer recommendations for enhancing assessment techniques and better communicating learning outcomes to students.

Keywords: quality assurance, student learning; learning outcomes, music and technology

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Authors: E. A. Alshaafi, A. Prakash

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Oil-water emulsions are commonly encountered in various industrial operations and at different stages of crude oil production and processing. Emulsions are often difficult to track and treat and can cause a number of costly problems which need to be avoided. The characteristics of the emulsion phase can vary with crude composition and types of impurities present in oil. The objectives of this study are the development of ultrasonic techniques to track and characterize emulsion phase generated during production and cleaning of crude oil. The position of emulsion layer is monitored with the help of ultrasonic probes suitably placed in the vessel. The sensitivity of the technique and its potential has been demonstrated based on extensive testing with different oil samples. The technique is also being developed to monitor emulsion phase characteristics such as stability, composition, and droplet size distribution. The ultrasonic parameters recorded are changes in acoustic velocity, signal attenuation and its frequency spectrum. Emulsion has been prepared with light mineral oil sample and the effects of various factors including mixing speed, temperature, surfactant, and solid particles concentrations have been investigated. The applied frequency for ultrasonic waves has been varied from 1 to 5 MHz to carry out a sensitivity analysis. Emulsion droplet structure is observed with optical microscopy and stability is examined by tracking the changes in ultrasonic parameters with time. A model based on ultrasonic attenuation spectroscopy is being developed and tested to track changes in droplet size distribution with time.

Keywords: ultrasonic techniques, emulsion, characterization, droplet size

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Authors: Daniel José de Oliveira Ferreira, Juan Harold Sosa-Arnao, Bruno Cássio Moreira, Leonardo Paes Rangel, Song Won Park

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The comprehensive CFD models have been used to represent and study the heterogeneous combustion of biomass. In the present work, the operation of a global flue gas circuit in the sugar-cane bagasse combustion, from wind boxes below primary air grate supply, passing by bagasse insertion in swirl burners and boiler furnace, to boiler bank outlet is simulated. It uses five different meshes representing each part of this system located in sequence: wind boxes and grate, boiler furnace, swirl burners, super heaters and boiler bank. The model considers turbulence using standard k-ε, combustion using EDM, radiation heat transfer using DTM with 16 ray directions and bagasse particle tracking represented by Schiller-Naumann model. The results showed good agreement with expected behavior found in literature and equipment design. The more detailed results view in separated parts of flue gas system allows to observe some flow behaviors that cannot be represented by usual simplifications like bagasse supply under homogeneous axial and rotational vectors and others that can be represented using new considerations like the representation of 26 thousand grate orifices by 144 rectangular inlets.

Keywords: comprehensive CFD model, sugar-cane bagasse combustion, sugar-cane bagasse grate boiler, axial

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Authors: Alireza Gholami, Amir H. D. Markazi

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In this paper, an observer-based direct adaptive fuzzy sliding mode (OAFSM) algorithm is proposed. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. The input connection matrix is used to combine the sliding surfaces of individual subsystems, and an adaptive fuzzy algorithm is used to estimate an equivalent sliding mode control input directly. The fuzzy membership functions, which were determined by time consuming try and error processes in previous works, are adjusted by adaptive algorithms. The other advantage of the proposed controller is that the input gain matrix is not limited to be diagonal, i.e. the plant could be over/under actuated provided that controllability and observability are preserved. An observer is constructed to directly estimate the state tracking error, and the nonlinear part of the observer is constructed by an adaptive fuzzy algorithm. The main advantage of the proposed observer is that, the measured outputs is not limited to the first entry of a canonical-form state vector. The closed-loop stability of the proposed method is proved using a Lyapunov-based approach. The proposed method is applied numerically on a multi-link robot manipulator, which verifies the performance of the closed-loop control. Moreover, the performance of the proposed algorithm is compared with some conventional control algorithms.

Keywords: adaptive algorithm, fuzzy systems, membership functions, observer

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Authors: M. Tomaschko

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The integration of technology in educational settings has gained a lot of interest. Especially the use of mobile devices and accompanying mobile applications can offer great potentials to complement traditional education with new technologies and enrich students’ learning in various ways. Nevertheless, the usability of the deployed mathematics application is an indicative factor to exploit the full potential of technology enhanced learning because directing cognitive load toward using an application will likely inhibit effective learning. For this reason, the purpose of this research study is the identification of possible usability issues of the mobile GeoGebra Graphing Calculator application. Therefore, eye tracking in combination with task scenarios, think aloud method, and a SUS questionnaire were used. Based on the revealed usability issues, the mobile application was iteratively redesigned and assessed in order to verify the success of the usability improvements. In this paper, the identified usability issues are presented, and recommendations on how to overcome these concerns are provided. The main findings relate to the conception of a mathematics keyboard and the interaction design in relation to an equation editor, as well as the representation of geometrical construction tools. In total, 12 recommendations were formed to improve the usability of a mobile graphing calculator application. The benefit to be gained from this research study is not only the improvement of the usability of the existing GeoGebra Graphing Calculator application but also to provide helpful hints that could be considered from designers and developers of mobile math applications.

Keywords: GeoGebra, graphing calculator, math education, smartphone, usability

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Authors: James M. Wakiru, Liliane Pintelon, Peter Muchiri, Stanley Mburu

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Maintenance performance measurement (MPM) represents an integrated aspect that considers both operational and maintenance related aspects while evaluating the effectiveness and efficiency of maintenance to ensure assets are working as they should. Three salient issues require to be addressed for an asset-intensive organization to employ an MPM-based framework to optimize maintenance. Firstly, the organization should establish important perfomance metric(s), in this case the maintenance objective(s), which they will be focuss on. The second issue entails aligning the maintenance objective(s) with maintenance optimization. This is achieved by deriving maintenance performance indicators that subsequently form an objective function for the optimization program. Lastly, the objective function is employed in an optimization program to derive maintenance decision support. In this study, we develop a framework that initially identifies the crucial maintenance performance measures, and employs them to derive maintenance decision support. The proposed framework is demonstrated in a case study of a geothermal drilling rig, where the objective function is evaluated utilizing a simulation-based model whose parameters are derived from empirical maintenance data. Availability, reliability and maintenance inventory are depicted as essential objectives requiring further attention. A simulation model is developed mimicking a drilling rig operations and maintenance where the sub-systems are modelled undergoing imperfect maintenance, corrective (CM) and preventive (PM), with the total cost as the primary performance measurement. Moreover, three maintenance spare inventory policies are considered; classical (retaining stocks for a contractual period), vendor-managed inventory with consignment stock and periodic monitoring order-to-stock (s, S) policy. Optimization results infer that the adoption of (s, S) inventory policy, increased PM interval and reduced reliance of CM actions offers improved availability and total costs reduction.

Keywords: maintenance, vendor-managed, decision support, performance, optimization

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Authors: Shay Kee Tan, Kok Haur Ng, Jennifer So-Kuen Chan

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This paper extends the conditional autoregressive range (CARR) model to multivariate CARR (MCARR) model and further to the two-stage MCARR-return model to model and forecast volatilities, correlations and returns of multiple financial assets. The first stage model fits the scaled realised Parkinson volatility measures using individual series and their pairwise sums of indices to the MCARR model to obtain in-sample estimates and forecasts of volatilities for these individual and pairwise sum series. Then covariances are calculated to construct the fitted variance-covariance matrix of returns which are imputed into the stage-two return model to capture the heteroskedasticity of assets’ returns. We investigate different choices of mean functions to describe the volatility dynamics. Empirical applications are based on the Standard and Poor 500, Dow Jones Industrial Average and Dow Jones United States Financial Service Indices. Results show that the stage-one MCARR models using asymmetric mean functions give better in-sample model fits than those based on symmetric mean functions. They also provide better out-of-sample volatility forecasts than those using CARR models based on two robust loss functions with the scaled realised open-to-close volatility measure as the proxy for the unobserved true volatility. We also find that the stage-two return models with constant means and multivariate Student-t errors give better in-sample fits than the Baba, Engle, Kraft, and Kroner type of generalized autoregressive conditional heteroskedasticity (BEKK-GARCH) models. The estimates and forecasts of value-at-risk (VaR) and conditional VaR based on the best MCARR-return models for each asset are provided and tested using Kupiec test to confirm the accuracy of the VaR forecasts.

Keywords: range-based volatility, correlation, multivariate CARR-return model, value-at-risk, conditional value-at-risk

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Authors: Farid Eltom A. E., Mustafa Abdul-Halim, Abdalla Markaz, Sami Atta, Mohamed Azhari, Ahmed Rashed

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Smart environment sensors integrated with ‘Internet of Things’ (IoT) technology can provide a new concept in tracking, sensing, and monitoring objects in the environment. The aim of the study is to evaluate the farm environmental monitoring system based on (IoT) and to realize the automated management of agriculture and the implementation of precision production. Until now, irrigation monitoring operations in Sudan have been carried out using traditional methods, which is a very costly and unreliable mechanism. However, by utilizing soil moisture sensors, irrigation can be conducted only when needed without fear of plant water stress. The result showed that software application allows farmers to display current and historical data on soil moisture and nutrients in the form of line charts. Design measurements of the soil factors: moisture, electrical, humidity, conductivity, temperature, pH, phosphorus, and potassium; these factors, together with a timestamp, are sent to the data server using the Lora WAN interface. It is considered scientifically agreed upon in the modern era that artificial intelligence works to arrange the necessary procedures to take care of the terrain, predict the quality and quantity of production through deep analysis of the various operations in agricultural fields, and also support monitoring of weather conditions.

Keywords: smart environment, monitoring systems, IoT, LoRa Gateway, center pivot

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Authors: M. Polic, N. Cesarec Salopek

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When it comes to crisis, no company, notwithstanding its financial success, power or reputation is immune to the new environment and circumstances emerging from it. The main challenge company faces with during a crisis is to protect its most valuable intangible asset reputation. Crisis has the serious potential to disrupt company’s everyday operations and damage its reputation extremely fast, especially if the company did not anticipate threats that may cause a crisis. Therefore, when a crisis happens, company must directly respond to it, whilst an effective crisis communication can limit consequences arising from the crisis, protect and repair the reputational damage caused to the company. Since every crisis is unique, each one of it requires different crisis response strategy. In July 2018, airline labor unions threatened Croatia Airlines, the state owned flag carrier of Croatia, to hold a strike that would be called into question regular flights and affect more than 7.600 passengers per day. This study explores the differences between crisis response strategies that Croatia Airlines, the state owned flag carrier of Croatia and airline labor unions used during the crisis period within the Situational Crisis Communication Theory (SCCT) by analyzing the content of formal communication tools used by Croatia Airlines and airline labor unions. Moreover, this study shows how Croatia Airlines successfully managed to communicate to the general public the threat that airline labor unions imposed on it and how was it received by the Croatian media. By using the qualitative and quantitative content analysis, the study will reveal the frames that dominated in the media articles during the crisis period. The greatest significance of this study is that it will provide the deeper insight into how transparent and consistent communication, the one that Croatia Airlines used before and during the crisis period, contributed to the decision of the competent court (Zagreb County Court) which prohibited labor unions strike in August 2018.

Keywords: crisis communication, crisis response strategy, Croatia Airlines, labor union, reputation management, situational crisis communication theory, strike

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Authors: Jake Gonzalez, Tommy Dang

Abstract:

This paper proposes a temporal graph approach to visualize and analyze the evolution of gene relationships and nomenclature over time. An interactive web-based tool implements this temporal graph, enabling researchers to traverse a timeline and observe coupled dynamics in network topology and naming conventions. Analysis of a real human genomic dataset reveals the emergence of densely interconnected functional modules over time, representing groups of genes involved in key biological processes. For example, the antimicrobial peptide DEFA1A3 shows increased connections to related alpha-defensins involved in infection response. Tracking degree and betweenness centrality shifts over timeline iterations also quantitatively highlight the reprioritization of certain genes’ topological importance as knowledge advances. Examination of the CNR1 gene encoding the cannabinoid receptor CB1 demonstrates changing synonymous relationships and consolidating naming patterns over time, reflecting its unique functional role discovery. The integrated framework interconnecting these topological and nomenclature dynamics provides richer contextual insights compared to isolated analysis methods. Overall, this temporal graph approach enables a more holistic study of knowledge evolution to elucidate complex biology.

Keywords: temporal graph, gene relationships, nomenclature evolution, interactive visualization, biological insights

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Authors: Puji Sucia Sukmaningrum, Achsania Hendratmi, Noven Suprayogi, Muhammad Madyan

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Theoretically, Islamic banks in Indonesia and Malaysia not necessarily aware to the interest rate fluctuation, since they don’t use interest-based instruments. Both countries use dual banking system in which Islamic and conventional banking system are exist. This situation makes the profit-sharing level of the Islamic banks will be indirectly affected by the interest rate fluctuation from the conventional banks system. One of the risk management tools for anticipating the risk of interest rate fluctuation is gap management, which has purpose to narrow the difference between Rate Sensitive Asset (RSA) and Rate Sensitive Liability (RSL). This formed gap will give the information about the risk potential in Islamic banks which respect to the fluctuation on the interest rate. This study aims to determine the position of the gap formed at Islamic Maybank Indonesia and Islamic Maybank Malaysia, and analyze the difference in the formation of gap based on the period of sensitivity. This study is a quantitative research with comparative study using sensitivity gap analysis, independent sample t-test, and Mann-Whitney method. The data being used was secondary data from Maturity Profile contained in the Annual Financial Report of Islamic Maybank Indonesia and Islamic Maybank Malaysia from 2011 to 2015 period. The result shows that, cumulatively the formation of the gap was negative gap. From the results of independent sample t-test and Mann-Whitney, the formation of the gap in Islamic Maybank Indonesia and Islamic Maybank Malaysia for a period of sensitivity of ≤ 1 month and >1-3 months show a significant difference, while the period of sensitivity >3-12 months does not. The result shows, even though Indonesia and Malaysia using same dual banking systems, the gap values are different. The difference in debt policy between Indonesia and Malaysia also affecting the gap sensitivity in debt. In can be concluded that each country needs an appropriate gap management to support its Islamic banking performance specifically.

Keywords: assets and liability management, gap management, interest rate risk, Islamic bank

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Authors: Muhammad Saad Aslam

Abstract:

In 2021, our organization has launched our proprietary mobile App i.e. Farm Intelligence platform, an industrial-first precision agriculture solution, to Pakistan. It was piloted at 47 locations (spanning around 1,200 hectares of land), addressing growers’ pain points by bringing the benefits of precision agriculture to their doorsteps. This year, we have extended its reach by more than 10 times (nearly 130,000 hectares of land) in almost 600 locations across the country. The project team selected highly infested areas to set up traps, which then enabled the sales team to initiate evidence-based conversations with the grower community about preventive crop protection products that includes pesticides and insecticides. Mega farmer meeting field visits and demonstrations plots coupled with extensive marketing activities, were setup to include farmer community. With the help of App real-time pest monitoring (using heat maps and infestation prediction through predictive analytics) we have equipped our growers with on spot insights that will help them optimize pesticide applications. Heat maps allow growers to identify infestation hot spots to fine-tune pesticide delivery, while predictive analytics enable preventive application of pesticides before the situation escalates. Ultimately, they empower growers to keep their crops safe for a healthy harvest.

Keywords: precision pest management, precision agriculture, real time pest tracking, pest forecasting

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Authors: Shima Taheri, Simon Clark

Abstract:

Concrete is an essential building material used in the majority of structures. Degradation of concrete over time increases the life-cycle cost of an asset with an estimated annual cost of billions of dollars to national economies. Most of the concrete failure occurs due to cracks, which propagate through a structure and cause weakening leading to failure. Stopping crack propagation is thus the key to protecting concrete structures from failure and is the best way to prevent inconveniences and catastrophes. Furthermore, the majority of cracks occur deep within the concrete in inaccessible areas and are invisible to normal inspection. Few materials intrinsically possess self-healing ability, but one that does is concrete. However, self-healing in concrete is limited to small dormant cracks in a moist environment and is difficult to control. In this project, we developed a method for self-healing of nascent fractures in concrete components through the automatic release of self-curing healing agents encapsulated in breakable nano- and micro-structures. The Poly(methyl methacrylate) (PMMA) based two-part adhesive is encapsulated in core-shell structures with brittle/weak inert shell, synthesized via miniemulsion/solvent evaporation polymerization. Stress fields associated with propagating cracks can break these capsules releasing the healing agents at the point where they are needed. The shell thickness is playing an important role in preserving the content until the final setting of concrete. The capsules can also be surface functionalized with carboxyl groups to overcome the homogenous mixing issues. Currently, this formulated self-healing system can replace up to 1% of cement in a concrete formulation. Increasing this amount to 5-7% in the concrete formulation without compromising compression strength and shrinkage properties, is still under investigation. This self-healing system will not only increase the durability of structures by stopping crack propagation but also allow the use of less cement in concrete construction, thereby adding to the global effort for CO2 emission reduction.

Keywords: self-healing concrete, concrete crack, concrete deterioration, durability

Procedia PDF Downloads 113