Search results for: management challenges

Authors: K. R. Mukuna

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Teachers are faced many challenges in the South African rural schools such as stress, depression, lack of resources, poor working relationships, inflexible curriculum etc. These could affect their wellbeing and effectiveness at the workplace. As a result, the study had a significance in the teacher’s lives, and community due teachers worked under conditions that are unfavourable to perform their jobs effectively. Despite these conditions, they still managed to do their jobs and the community is uplifted. However, this study aimed to explore factors that enable teachers to cope with workplace adversities at a rural school district in the Free State Province. It adopted a qualitative case study as a research design. Semi-structured interviews and colleges had employed as tools to collect data. Ten participants (n=10; 5 males and 5 females) were selected through purposive and convenience sampling. All participants selected from a South African rural school. Sesotho culture was their home language, and most of them had 5 years of teaching experiences. The thematic findings revealed that they developed abilities to cope with and adjust to the social and cultural environment. These included self-efficacy, developing problem-solving skills, awareness of strengths and asserts, self-managing of emotions, and self-confidence. This study concluded that these psychosocial factors contributed to coping with teacher’s diversities, and effectively stabilized their wellbeing in the schools.

Keywords: psychosocial factors, teachers counselling, teacher stress, workplace adversity, rural school, teachers’ wellbeing, teachers’ resilience, teachers’ self-efficacy, social interaction

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Authors: Hawa Khan

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Autism is a complex disorder related to abnormalities in the development of brain structure and neurological function and a new phenomenon which is epidemically on the increase. The Muslim community, with its profound commitment to the all-encompassing Islamic precedence, views all phenomena in the light of religious imperatives. How autism is understood and treated in these communities is key to successful inclusive services. Moreover, parents mentioned their Islamic faith as a coping mechanism for the challenges they faced while caring for their child. This study utilises interpretative phenomenology analysis as a methodology that seeks to interpret the meaning the participants make of their experiences, which extends descriptive analysis. Semi-structured interviews were conducted with 5 family units that included fathers, mothers, grandparents, and siblings. In the preliminary stage, this study found families give high importance of accessible Islamic education for their child and questioning the accountability of the child who might not be able to follow the Islamic way of life entirely or understand the concept of Allah. Moreover, the families expressed their beliefs in traditional and religious treatment as an effective way to treat and cure autism. This poses a major barrier between families seeking support and professionals providing services. Consequentially, it can also result in a low uptake of mainstream services from the Muslim community. Exploring the lived experiences of parents from the Muslim community and how ASD is conceptualised in this community could have implications for improved and effective home, community, and service collaboration.

Keywords: autism spectrum disorder, Islamic education, religious beliefs, mainstream services

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Authors: Ekin Ozer, Maria Q. Feng, Rupa Purasinghe

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Structural deterioration of bridge systems possesses an ongoing threat to the transportation networks. Besides, landmark bridges’ integrity and safety are more than sole functionality, since they provide a strong presence for the society and nations. Therefore, an innovative and sustainable method to inspect landmark bridges is essential to ensure their resiliency in the long run. In this paper, a recently introduced concept, smartphone-based modal frequency estimation is addressed, and this paper targets to authenticate the fidelity of smartphone-based vibration measurements gathered from three landmark suspension bridges. Firstly, smartphones located at the bridge mid-span are adopted as portable and standalone vibration measurement devices. Then, their embedded accelerometers are utilized to gather vibration response under operational loads, and eventually frequency domain characteristics are deduced. The preliminary analysis results are compared with the reference publications and high-quality monitoring data to validate the usability of smartphones on long-span landmark suspension bridges. If the technical challenges such as high period of vibration, low amplitude excitation, embedded smartphone sensor features, sampling, and citizen engagement are tackled, smartphones can provide a novel and cost-free crowdsourcing tool for maintenance of these landmark structures. This study presents the early phase findings from three signature structures located in the United States.

Keywords: smart and mobile sensing, structural health monitoring, suspension bridges, vibration analysis

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Authors: Nina Kaufmans

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Traditional therapies, utilizing spoken narratives as a primary source of intervention, are proven to be limited in effectively treating post traumatic stress disorder. Following the effects of the global pandemic of COVID-19, an increasing number of mental health consumers are beginning to experience somatically-based distress in addition to existing mental health symptoms. Moreover, the aftermath of the rapid increase in demand for mental health services has caused significant burnout in mental health professionals. This paper explores the ramifications of recent changes and challenges in the mental health demands and subsequent response and its consequences for mental health workers. We will begin by investigating the neurobiological mechanisms involved in traumatic experiences, then discuss the premises for "bottom-up" or somatically oriented psychotherapy approaches, and finally offer clinical skills and interventions for clients diagnosed with post traumatic stress disorder. In addition, we will discuss how somatically-based psychotherapy interventions implemented in sessions may decrease burnout and improve the well-being of clinicians. We will discuss how the integration of somatically-based interventions into counseling would increase the effectiveness of mental health recovery and sustain remission while simultaneously providing opportunities for self-care for mental health professionals.

Keywords: somatic psychotherapy interventions, trauma counseling, preventing and treating burnout, adults with PTSD, bottom-up skills, the effectiveness of trauma treatment

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Authors: Myonghwa Park, Eun Jeong Choi

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Persons with dementia living at home have complex caregiving demands, which can be significant sources of stress for the family caregivers. Thus, the dementia family support program facilitators struggle to provide various health and social services, facing diverse challenges. The purpose of this study was to research the effects of training program for the dementia family support program facilitators on self-efficacy, competence, and target complaints concerning operating their program. We created a training program with systematic contents, which was composed of 10 sessions and we provided the program for the facilitators. The participants were 32 people at 28 community dementia support centers who manage dementia family support programs and they completed quantitative and qualitative self-report questionnaire before and after participating in the training program. For analyzing the data, descriptive statistics were used and with a paired t-test, pretest and posttest scores of self-efficacy, competence, and target complaints were analyzed. We used Statistical Package for the Social Sciences (SPSS) statistics (Version 21) to analyze the data. The average age of the participants was 39.6 years old and the 84.4% of participants were nurses. There were statistically meaningful increases in facilitators’ self-efficacy scores (t = -4.45, p < .001) and competence scores (t = -2.133, p = 0.041) after participating in training program and operating their own dementia family support program. Also, the facilitators’ difficulties in conducting their dementia family support program were decreased which was assessed with target complaints. Especially, the facilitators’ lack of dementia expertise and experience was decreased statistically significantly (t = 3.520, p = 0.002). Findings provided evidence of the benefits of the training program for facilitators to enhance managing dementia family support program by improving the facilitators’ self-efficacy and competence and decreasing their difficulties regarding operating their program.

Keywords: competence, dementia, facilitator, family, self-efficacy, training

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Authors: Eduardo P. Wiechmann, Jorge A. Henríquez, Pablo E. Aqueveque, Luis G. Muñoz

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PV energy prices are declining rapidly. To take advantage of the benefits of those prices and lower the carbon footprint, operational practices must be modified. Undoubtedly, it challenges the electrowinning practice to operate at constant current throughout the day. This work presents a technology that contributes in providing modulation capacity to the electrode current distribution system. This is to raise the day time dc current and lower it at night. The system is a triple intercell bar that operates in current-source mode. The design is a capping board free dogbone type of bar that ensures an operation free of short circuits, hot swapability repairs and improved current balance. This current-source system eliminates the resetting currents circulating in equipotential bars. Twin auxiliary connectors are added to the main connectors providing secure current paths to bypass faulty or impaired contacts. All system conductive elements are positioned over a baseboard offering a large heat sink area to the ventilation of a facility. The system works with lower temperature than a conventional busbar. Of these attributes, the cathode current balance property stands out and is paramount for day/night modulation and the use of photovoltaic energy. A design based on a 3D finite element method model predicting electric and thermal performance under various industrial scenarios is presented. Preliminary results obtained in an electrowinning facility with industrial prototypes are included.

Keywords: electrowinning, intercell bars, PV energy, current modulation

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Authors: Pankaj Kumar Kalita

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Ineffectiveness of formal institutional mechanisms such as official audit to improve public service delivery has been a serious concern to scholars working on governance reforms in developing countries. Scholars argue that public service delivery in local self-governing institutions can be improved through application of informal mechanisms such as social accountability. Social accountability has been reinforced with the engagement of citizens and civic organizations in the process of service delivery to reduce the governance gap in developing countries. However, there are challenges that may impede the scope of establishing social accountability initiatives in the performance of local self-governing institutions. This study makes an attempt to investigate the factors that may impede the scope of establishing social accountability, particularly in culturally heterogeneous societies like India. While analyzing the implementation of two rural development schemes by Panchayats, the local self-governing institutions functioning in rural Assam in India, this study argues that the scope of establishing social accountability in the performance of local self-governing institutions, particularly in culturally heterogeneous societies in developing countries will be impeded by the absence of inter-caste and inter-religion networks. Data has been collected from five selected districts of Assam using in-depth interview method and survey method. The study further contributes to the debates on 'good governance' and citizen-centric approaches in developing countries.

Keywords: citizen engagement, local self-governing institutions, networks, social accountability

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Authors: Charline Monnier, Rudolf Andrys, Irene Castellino, Lucie Zemanova

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Due to their inherent sustainability and compatibility with green chemistry principles, enzymes are attracting increasing attention for various applications like bioremediation or biocatalysis. These natural catalysts boast remarkable substrate specificity and operate under mild biological conditions. However, their intrinsic limitations, such as instability at high temperatures or in organic solvents, impede their wider applicability. Enzyme immobilization on supportive matrices emerges as a promising strategy to address these challenges. This approach not only facilitates enzyme reusability but also offers the potential to modulate their stability, activity, and selectivity. The present study investigates the immobilization and application of two distinct groups of hydrolases on supportive matrices: PETases, naturally capable of PolyEthylene Terephthalate (PET) degradation, and cholinesterases (ChEs), key enzymes in neurotransmitter regulation. All tested enzymes will be immobilized on porous and non-porous particles using both covalent and non-covalent methods. Additionally, the stability of PETases and cholinesterases will be explored, followed by exposure to denaturing conditions to assess their resilience under harsh conditions. Furthermore, due to the exceptional catalytic efficiency and selectivity, their biocatalytic efficiency will be tested using xenobiotic substrates, aiming to establish them as replacements for conventional chemical catalysts in environmentally friendly processes. By exploiting the power of enzyme immobilization, this research strives to unlock the full potential of these biocatalysts for sustainable and efficient technological advancements.

Keywords: biocatalysis, bioremediation, enzyme efficiency, enzyme immobilization, green chemistry

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Authors: Sami Houry

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Complex systems exhibit universal characteristics as they near a tipping point. Among them are common generic early warning signals which precede critical transitions. These signals include: critical slowing down in which the rate of recovery from perturbations decreases over time; an increase in the variance of the state variable; an increase in the skewness of the state variable; an increase in the autocorrelations of the state variable; flickering between different states; and an increase in spatial correlations over time. The presence of the signals has management implications, as the identification of the signals near the tipping point could allow management to identify intervention points. Despite the applications of the generic early warning signals in various scientific fields, such as fisheries, ecology and finance, a review of literature did not identify any applications that address the program student withdrawal problem at the undergraduate distance universities. This area could benefit from the application of generic early warning signals as the program withdrawal rate amongst distance students is higher than the program withdrawal rate at face-to-face conventional universities. This research specifically assessed the generic early warning signals through an intensive case study of undergraduate program student withdrawal at a Canadian distance university. The university is non-cohort based due to its system of continuous course enrollment where students can enroll in a course at the beginning of every month. The assessment of the signals was achieved through the comparison of the incidences of generic early warning signals among students who withdrew or simply became inactive in their undergraduate program of study, the true positives, to the incidences of the generic early warning signals among graduates, the false positives. This was achieved through significance testing. Research findings showed support for the signal pertaining to the rise in flickering which is represented in the increase in the student’s non-pass rates prior to withdrawing from a program; moderate support for the signals of critical slowing down as reflected in the increase in the time a student spends in a course; and moderate support for the signals on increase in autocorrelation and increase in variance in the grade variable. The findings did not support the signal on the increase in skewness of the grade variable. The research also proposes a new signal based on the fractal-like characteristic of student behavior. The research also sought to extend knowledge by investigating whether the emergence of a program withdrawal status is self-similar or fractal-like at multiple levels of observation, specifically the program level and the course level. In other words, whether the act of withdrawal at the program level is also present at the course level. The findings moderately supported self-similarity as a potential signal. Overall, the assessment of the signals suggests that the signals, with the exception with the increase of skewness, could be utilized as a predictive management tool and potentially add one more tool, the fractal-like characteristic of withdrawal, as an additional signal in addressing the student program withdrawal problem.

Keywords: critical transitions, fractals, generic early warning signals, program student withdrawal

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Authors: Claudius Peter Van Wyk

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Given the increasingly manifest phenomena, as described in complexity theory, of volatility, uncertainty, complexity and ambiguity (VUCA), Taleb's notion of 'antifragility, has a significant contribution to make to positive psychology applied to wellbeing. Antifragility is argued to be fundamentally different from the concepts of resiliency; as the ability to recover from failure, and robustness; as the ability to resist failure. Rather it describes the capacity to reorganise in the face of stress in such a way as to cope more effectively with systemic challenges. The concept, which has been applied in disciplines ranging from physics, molecular biology, planning, engineering, and computer science, can now be considered for its application in individual human and social wellbeing. There are strong correlations to Antonovsky's model of 'salutogenesis' in which an attitude and competencies are developed of transforming burdening factors into greater resourcefulness. We demonstrate, from the perspective of neuroscience, how technology measuring nervous system coherence can be coupled to acquired psychodynamic approaches to not only identify contextual stressors, utilise biofeedback instruments for facilitating greater coherence, but apply these insights to specific life stressors that compromise well-being. Employing an on-going case study with BMW South Africa, the neurological mapping is demonstrated together with 'reframing' and emotional anchoring techniques from neurolinguistic programming. The argument is contextualised in the discipline of psychoneuroimmunology which describes the stress pathways from the CNS and endocrine systems and their impact on immune function and the capacity to restore homeostasis.

Keywords: antifragility, complexity, neuroscience, psychoneuroimmunology, salutogenesis, volatility

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Authors: Enido Fabiano de Ramos, Ieda Kanashiro Makiya, Francisco I. Giocondo Cesar

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This study presents an analysis of the Digital Twin concept applied to the academic environment, focusing on the development of a Digital Twin Smart Campus Framework. Using bibliometric analysis methodologies and literature review, the research investigates the evolution and applications of the Digital Twin in educational contexts, comparing these findings with the advances of Industry 4.0. It was identified gaps in the existing literature and highlighted the need to adapt Digital Twin principles to meet the specific demands of a smart campus. By integrating Industry 4.0 concepts such as automation, Internet of Things, and real-time data analytics, we propose an innovative framework for the successful implementation of the Digital Twin in academic settings. The results of this study provide valuable insights for university campus managers, allowing for a better understanding of the potential applications of the Digital Twin for operations, security, and user experience optimization. In addition, our framework offers practical guidance for transitioning from a digital campus to a digital twin smart campus, promoting innovation and efficiency in the educational environment. This work contributes to the growing literature on Digital Twins and Industry 4.0, while offering a specific and tailored approach to transforming university campuses into smart and connected spaces, high demanded by Society 5.0 trends. It is hoped that this framework will serve as a basis for future research and practical implementations in the field of higher education and educational technology.

Keywords: smart campus, digital twin, industry 4.0, education trends, society 5.0

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Authors: Vasileiou Apostolos, Theodosiou Chrysa, Tsitroulis Ioannis, Maris Fotios

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The severity of extreme phenomena is due to their ability to cause severe damage in a small amount of time. It has been observed that floods affect the greatest number of people and induce the biggest damage when compared to the total of annual natural disasters. The detection of potential flood-prone areas constitutes one of the fundamental components of the European Natural Disaster Management Policy, directly connected to the European Directive 2007/60. The aim of the present paper is to develop a new methodology that combines geographical information, fuzzy logic and multi-criteria evaluation methods so that the most vulnerable areas are defined. Therefore, ten factors related to geophysical, morphological, climatological/meteorological and hydrological characteristics of the basin were selected. Afterwards, two models were created to detect the areas pronest to flooding. The first model defined the gravitas of each factor using Analytical Hierarchy Process (AHP) and the final map of possible flood spots were created using GIS and Boolean Algebra. The second model made use of the fuzzy logic and GIS combination and a respective map was created. The application area of the aforementioned methodologies was in Ardas basin due to the frequent and important floods that have taken place these last years. Then, the results were compared to the already observed floods. The result analysis shows that both models can detect with great precision possible flood spots. As the fuzzy logic model is less time-consuming, it is considered the ideal model to apply to other areas. The said results are capable of contributing to the delineation of high risk areas and to the creation of successful management plans dealing with floods.

Keywords: analytical hierarchy process, flood prone areas, fuzzy logic, geographic information system

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Authors: Armand Okende, Benjamin Beaumont

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Introduction: Deforestation is a change in the structure and composition of flora and fauna, which leads to a loss of biodiversity, production of goods and services and an increase in fires. It concerns vast territories in tropical zones particularly; this is the case of the territory of Bolobo in the current province of Maï- Ndombe in the Democratic Republic of Congo. Indeed, through this study between 2001 and 2018, we believe that it was important to show and analyze quantitatively the important forests changes and analyze quantitatively. It’s the overall objective of this study because, in this area, we are witnessing significant deforestation. Methodology: Mapping and quantification are the methodological approaches that we have put forward to assess the deforestation or forest changes through satellite images or raster layers. These satellites data from Global Forest Watch are integrated into the GIS software (GRASS GIS and Quantum GIS) to represent the loss of forest cover that has occurred and the various changes recorded (e.g., forest gain) in the territory of Bolobo. Results: The results obtained show, in terms of quantifying deforestation for the periods 2001-2006, 2007-2012 and 2013-2018, the loss of forest area in hectares each year. The different change maps produced during different study periods mentioned above show that the loss of forest areas is gradually increasing. Conclusion: With this study, knowledge of forest management and protection is a challenge to ensure good management of forest resources. To do this, it is wise to carry out more studies that would optimize the monitoring of forests to guarantee the ecological and economic functions they provide in the Congo Basin, particularly in the Democratic Republic of Congo. In addition, the cartographic approach, coupled with the geographic information system and remote sensing proposed by Global Forest Watch using raster layers, provides interesting information to explain the loss of forest areas.

Keywords: deforestation, loss year, forest change, remote sensing, drivers of deforestation

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Authors: Janusz Bobulski, Mariusz Kubanek

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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

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Authors: Lai Wenfang

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Tthis study will describe how to use artificial intelligence (AI) technology to build the user-oriented platform for integrated archival service. The platform will be launched in 2020 by the National Archives Administration (NAA) in Taiwan. With the progression of information communication technology (ICT) the NAA has built many systems to provide archival service. In order to cope with new challenges, such as new ICT, artificial intelligence or blockchain etc. the NAA will try to use the natural language processing (NLP) and machine learning (ML) skill to build a training model and propose suggestions based on the data sent to the platform. NAA expects the platform not only can automatically inform the sending agencies’ staffs which records catalogues are against the transfer or destroy rules, but also can use the model to find the details hidden in the catalogues and suggest NAA’s staff whether the records should be or not to be, to shorten the auditing time. The platform keeps all the users’ browse trails; so that the platform can predict what kinds of archives user could be interested and recommend the search terms by visualization, moreover, inform them the new coming archives. In addition, according to the Archives Act, the NAA’s staff must spend a lot of time to mark or remove the personal data, classified data, etc. before archives provided. To upgrade the archives access service process, the platform will use some text recognition pattern to black out automatically, the staff only need to adjust the error and upload the correct one, when the platform has learned the accuracy will be getting higher. In short, the purpose of the platform is to deduct the government digital transformation and implement the vision of a service-oriented smart government.

Keywords: artificial intelligence, natural language processing, machine learning, visualization

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Authors: Muhammad Ali Asadullah, Zafarullah Amir

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In recent years, Vocational Education and Training (VET) has been under discussion by the academic researchers and remained in focus in the political grounds. Due to potential contribution of VET, the World Bank and United Nations Educational, Scientific and Cultural Organization (UNESCO) support vocational education to reduce poverty, enhance economic growth and increase competitiveness. This paper examines the impact of Vocational Education and Training on the Economic Growth and Social Inclusion with direct and mediation effect of Social Inclusion. The basic purpose of this study is to assess economic pay-offs as a result of long term investments in VET. Based on the review of Anderson Nilsson, initially we explored the increasing or decreasing trend in investment on VET. Further, the study explores that the countries which invest more on VET, tend to get more economic growth and are socially more ‘inclusive’. It is a longitudinal / panel data study with 12 years of registered data which involves 24 OECD countries. The results of the study indicate the VET has positive association with Social Inclusion and Economic Growth. Further, there is also a positive association of VET and Economic Growth through mediation of Social Inclusion. The current study considers not only issue and challenges in developing VET systems but also contributes to develop the theoretical framework for considering how VET can directly and indirectly improve economic growth and social inclusion. A wider appreciation of how VET’s benefits operate may influence a country’s decisions to invest in it. If policy makers increase investment on VET, the result would be positive in Economic Growth and Social Inclusion. It is also recommended that the same OECD model may be implemented in developing countries like Pakistan.

Keywords: Vocational Education and Training (VET), Social Inclusion, Economic Growth, OECD countries

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Authors: Moriom Akter Mousumi, Spyridon Paparrizos, Fulco Ludwig

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Rice yield reduction due to climate change-induced disease occurrence is becoming a great concern for coastal farmers of Bangladesh. The development of participatory climate information services (CIS) based on farmers’ needs could implicitly facilitate farmers to get disease forecasts and make better decisions to manage diseases. Therefore, this study aimed to investigate how participatory climate information services assist coastal rice farmers to take up rice disease forecasts and better manage rice diseases by improving their informed decision-making. Through participatory approaches, we developed a tailor-made agrometeorological service through the DROP app to forecast rice diseases and manage them in advance. During farmers field schools (FFS) we communicated 7-day disease forecasts during face-to-face weekly meetings using printed paper and, messenger app derived from DROP app. Results show that the majority of the farmers understand disease forecasts through visualization, symbols, and text. The majority of them use disease forecast information directly from the DROP app followed by face-to-face meetings, messenger app, and printed paper. Farmers participation and engagement during capacity building training at FFS also assist them in making more informed decisions and improved management of diseases using both preventive measures and chemical measures throughout the rice cultivation period. We conclude that the development of participatory CIS and the associated capacity-building and training of farmers has increased farmers' understanding and uptake of disease forecasts to better manage of rice diseases. Participatory services such as the DROP app offer great potential as an adaptation option for climate-smart rice production under changing climatic conditions.

Keywords: participatory climate service, disease forecast, disease management, informed decision making, coastal Bangladesg

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Authors: Shilpa Balan

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Radio Frequency Identification, also popularly known as RFID is used to automatically identify and track tags attached to items. This study focuses on the application of RFID in healthcare. The adoption of RFID in healthcare is a crucial technology to patient safety and inventory management. Data from RFID tags are used to identify the locations of patients and inventory in real time. Medical errors are thought to be a prominent cause of loss of life and injury. The major advantage of RFID application in healthcare industry is the reduction of medical errors. The healthcare industry has generated huge amounts of data. By discovering patterns and trends within the data, big data analytics can help improve patient care and lower healthcare costs. The number of increasing research publications leading to innovations in RFID applications shows the importance of this technology. This study explores the current state of research of RFID in healthcare using a text mining approach. No study has been performed yet on examining the current state of RFID research in healthcare using a data mining approach. In this study, related articles were collected on RFID from healthcare journal and news articles. Articles collected were from the year 2000 to 2015. Significant keywords on the topic of focus are identified and analyzed using open source data analytics software such as Rapid Miner. These analytical tools help extract pertinent information from massive volumes of data. It is seen that the main benefits of adopting RFID technology in healthcare include tracking medicines and equipment, upholding patient safety, and security improvement. The real-time tracking features of RFID allows for enhanced supply chain management. By productively using big data, healthcare organizations can gain significant benefits. Big data analytics in healthcare enables improved decisions by extracting insights from large volumes of data.

Keywords: RFID, data mining, data analysis, healthcare

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Authors: Ibrahim Mohammed

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Background: Diabetes mellitus is a chronic disease that can cause devastating secondary complications, reducing the quality and length of life as well as increasing medical costs for the patient and society. The guidelines recommend both clinical and preventive strategies for diabetes management and are regularly updated. The aim of the study is to assess the level of adherence of physicians to American Diabetes Association Guidelines. Method: Observational multicenter retrospective study will be conducted among different hospitals in the central region. Patient data will be collected from the records of the last three years (2017- 2020). Records will be selected randomly after a complete randomized design. The study focuses on the management of type 2 according to ADA not changed in the last three updating; those standards; all patients should be taking Metformin 1500 to 2000 mg/day as recommended dose and should be received a high dose of statin if the high risk to ASCVD or moderate statin if not at risk, patients with hypertension and diabetes should taking ACE or ARBS. Result: The study aimed to evaluate the commitment of physicians in the central region to the ADA. Out of the 153 selected patients, only 17 % were able to control their diabetes with an average A1c below 7. ADA stated that to reach the minimum benefit of using Metformin, the daily dose should be between 1500 and 2000 mg. Results showed that 110 patients were on Metformin, where 68% of them were on the recommended dose. ADA recommended the intake of high statin for diabetic patients with ASCVD risk, while diabetic patients without ASCVD risk should be on a moderate statin. Results showed that 61.5% of patients with ASCVD risk were at high statin while only 36% of patients without ASCVD risk were at moderate statin. Results showed that 89 patients have hypertension, and 80% of them are getting ACE/ARBs as recommended by the ADA. Recommendation: It is necessary to implement periodic training courses for some physicians to enhance and update their knowledge.

Keywords: American Diabetic Association, diabetes mellitus, atherosclerotic cardiovascular disease, ACE inhibitors

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Authors: Maria Do Carmo Baracho De Alencar

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Back pain is considered a worldwide public health problem and has led to numerous work-related absence from work and public spending on rehabilitation, as well as difficulties in the process of professional rehabilitation and return to work. Also, the rehabilitation of workers is one of the great challenges today and for the field of Workers' Health in Brazil. Aim: To investigate the procedures related to the professional rehabilitation of insured workers affected by chronic low back pain, based on the perceptions of professional counselors. Methods: A list of related professional counselors was obtained from the Professional Rehabilitation Coordination of the Baixada Santista (SP) region, and from the Social Security National Institute of Brazil, and in which cities they worked. Semistructured and individual interview was scheduled, based on a pre-elaborated script, containing questions about procedures, experiences at work and feelings. The interviews were recorded and transcribed in full for content analysis. Results: Ten (10) professional counselors of both genders and from nine (9) cities from the Baixada Santista region participated in the study. Aged between 31 and 64 years, and time in service between 4 and 38 years. Only one of the professionals was graduaded in Psychology. Among the testimonies emerged the high demand of work, the lack of interest of companies, medical authority, the social helplessness after rehabilitation process, difficulty in assessing invisible pain, and suffering, anguish, and frustration at work, between others. Conclusion: The study contributes to reflections about the importance of interdisciplinary actions and the Psychology in the processes of professional rehabilitation and readaptation in the process of return to work.

Keywords: low back pain, rehabilitation, work, occupational health

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Authors: Badli Shah Mohd Yusoff, Khairur Rijal Jamaludin, Rozetta Dollah

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The emerging of reverse logistics and product recovery management is an important concept in reconciling economic and environmental objectives through recapturing values of the end of life product returns. End of life products contains valuable modules, parts, residues and materials that can create value if recovered efficiently. The main objective of this study is to explore and develop a model to recover as much of the economic value as reasonably possible to find the optimality of return acquisition and sorting to meet demand and maximize profits over time. In this study, the benefits that can be obtained for remanufacturer is to develop demand forecasting of used products in the future with uncertainty of returns and quality of products. Formulated based on a generic disassembly tree, the proposed model focused on three reverse logistics activity, namely refurbish, remanufacture and disposal incorporating all plausible means quality levels of the returns. While stricter sorting policy, constitute to the decrease amount of products to be refurbished or remanufactured and increases the level of discarded products. Numerical experiments carried out to investigate the characteristics and behaviour of the proposed model with mathematical programming model using Lingo 16.0 for medium-term planning of return acquisition, disassembly (refurbish or remanufacture) and disposal activities. Moreover, the model seeks an analysis a number of decisions relating to trade off management system to maximize revenue from the collection of use products reverse logistics services through refurbish and remanufacture recovery options. The results showed that full utilization in the sorting process leads the system to obtain less quantity from acquisition with minimal overall cost. Further, sensitivity analysis provides a range of possible scenarios to consider in optimizing the overall cost of refurbished and remanufactured products.

Keywords: core acquisition, end of life, reverse logistics, quality uncertainty

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Authors: Sara Alhabli, Eman Elashiry, Osama Felemban, Abdullah Almushayt, Faisal Dardeer, Ahmed Mohammad, Fajr Orri, Nada Bamashmous

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Background: In December of 2019, the coronavirus (SARS-CoV-2) first appeared and quickly spread to become a worldwide pandemic. This study aimed to evaluate the prevalence and types of pediatric dental emergencies during the COVID-19 lockdown in Jeddah, Saudi Arabia, at the University Dental Hospital (UDH) of King Abdulaziz University (KAU) and identified the management provided for these dental emergency visits. Materials and Methods: Data collection was done retrospectively from electronic dental records for children aged 0-18 that attended the UDH emergency clinic during the period from March 1st, 2020, to September 30th, 2020. An electronic form formulated specifically for this study was used to collect the required data from electronic patient records, including demographic data, emergency classification, management, and referrals. Results: A total of 3146 patients were seen at the emergency clinics during this period, of which 661 were children (21%). Types of emergency conditions included 0.8% emergency cases, 34% urgent, and 65.2% non-urgent conditions. Severe dental pain (73.1%) and abscesses (20%) were the most common urgent dental conditions. Most non-urgent conditions presented for initial or periodic visits, recalls, or routine radiographs (74%). Treatments rarely involved restorations, with 8% among urgent conditions and 5.4% among non-urgent conditions. Antibiotics were only prescribed to 6.9% of urgent conditions. Conclusions: The largest group of children presenting at the emergency dental clinics were found to be children with non-urgent conditions. Tele dentistry can be a solution to avoid large numbers of non-urgent patients presenting to emergency clinics. Additionally, dental care for non-urgent conditions during the pandemic should focus more on procedures with less aerosol generation.

Keywords: COVID-19 pandemic, dental emergencies, oral health, pediatric dentistry, children

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Authors: Thamir K. Ibrahim, M. M. Rahman, Marwah Noori Mohammed

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This study deals with modeling and performance enhancements of a gas-turbine combined cycle power plant. A clean and safe energy is the greatest challenges to meet the requirements of the green environment. These requirements have given way the long-time governing authority of steam turbine (ST) in the world power generation, and the gas turbine (GT) will replace it. Therefore, it is necessary to predict the characteristics of the GT system and optimize its operating strategy by developing a simulation system. The integrated model and simulation code for exploiting the performance of gas turbine power plant are developed utilizing MATLAB code. The performance code for heavy-duty GT and CCGT power plants are validated with the real power plant of Baiji GT and MARAFIQ CCGT plants the results have been satisfactory. A new technology of correlation was considered for all types of simulation data; whose coefficient of determination (R2) was calculated as 0.9825. Some of the latest launched correlations were checked on the Baiji GT plant and apply error analysis. The GT performance was judged by particular parameters opted from the simulation model and also utilized Adaptive Neuro-Fuzzy System (ANFIS) an advanced new optimization technology. The best thermal efficiency and power output attained were about 56% and 345MW respectively. Thus, the operation conditions and ambient temperature are strongly influenced on the overall performance of the GT. The optimum efficiency and power are found at higher turbine inlet temperatures. It can be comprehended that the developed models are powerful tools for estimating the overall performance of the GT plants.

Keywords: gas turbine, optimization, ANFIS, performance, operating conditions

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Authors: Ilim Moses Msughter

Abstract:

The study was carried out to examine the availability of Ante-natal care services and the socio-cultural factors affecting the utilization of these services in Dutsin-Ma Local Government Area of Katsina State. Four specific objectives were outlined as thus to examine the availability of antenatal care services in Dutsin-Ma local government area, to identify the socio-cultural factors affecting the utilisation of ante-natal care services, to ascertain the challenges affecting utilisation of ante-natal care services and suggest strategies to improve efficiency in ante-natal service delivery and utilisation of same services. Data were collected from 110 respondents using a questionnaire and through the use of the interview. Data were analysed quantitatively and qualitatively. The findings revealed that ante-natal care services are available in the study area, but access to such services is hindered by several factors, which include religious and traditional beliefs, cost of services and poor attitudes of health care workers which has an adverse effect on people’s desire to visit ante-natal centres. The study recommended that Traditional Birth Attendants (TBA) need to be trained on how to handle pregnancy-related complications. It is also recommended that essential ante-natal drugs and services should be subsidised or made free by the government, and this must be closely monitored to ensure efficiency. Finally, human relation training should be organised for nurses and midwives to improve their attitudes towards patients during ante-natal visits.

Keywords: utilisation, religion, traditional birth attendant, ante-natal

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Authors: Wei Zhang

Abstract:

With the rapid development of deep learning, neural network and deep learning algorithms play a significant role in various practical applications. Due to the high accuracy and good performance, Convolutional Neural Networks (CNNs) especially have become a research hot spot in the past few years. However, the size of the networks becomes increasingly large scale due to the demands of the practical applications, which poses a significant challenge to construct a high-performance implementation of deep learning neural networks. Meanwhile, many of these application scenarios also have strict requirements on the performance and low-power consumption of hardware devices. Therefore, it is particularly critical to choose a moderate computing platform for hardware acceleration of CNNs. This article aimed to survey the recent advance in Field Programmable Gate Array (FPGA)-based acceleration of CNNs. Various designs and implementations of the accelerator based on FPGA under different devices and network models are overviewed, and the versions of Graphic Processing Units (GPUs), Application Specific Integrated Circuits (ASICs) and Digital Signal Processors (DSPs) are compared to present our own critical analysis and comments. Finally, we give a discussion on different perspectives of these acceleration and optimization methods on FPGA platforms to further explore the opportunities and challenges for future research. More helpfully, we give a prospect for future development of the FPGA-based accelerator.

Keywords: deep learning, field programmable gate array, FPGA, hardware accelerator, convolutional neural networks, CNN

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Authors: Rose A. Yemson, Ping Jiang, Oyedeji L. Inumoh

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The deployment of wireless sensor network has rapidly increased, however with the increased capacity and diversity of sensors, and applications ranging from biological, environmental, military etc. generates tremendous volume of data’s where more attention is placed on the distributed sensing and little on how to manage, analyze, retrieve and understand the data generated. This makes it more quite difficult to process live sensor data, run concurrent control and update because sensor data are either heavyweight, complex, and slow. This work will focus on developing a web service platform for automatic detection of sensors, acquisition of sensor data, storage of sensor data into a database, processing of sensor data using reconfigurable software components. This work will also create a web service based sensor data management system to monitor physical movement of an individual wearing wireless network sensor technology (SunSPOT). The sensor will detect movement of that individual by sensing the acceleration in the direction of X, Y and Z axes accordingly and then send the sensed reading to a database that will be interfaced with an internet platform. The collected sensed data will determine the posture of the person such as standing, sitting and lying down. The system is designed using the Unified Modeling Language (UML) and implemented using Java, JavaScript, html and MySQL. This system allows real time monitoring an individual closely and obtain their physical activity details without been physically presence for in-situ measurement which enables you to work remotely instead of the time consuming check of an individual. These details can help in evaluating an individual’s physical activity and generate feedback on medication. It can also help in keeping track of any mandatory physical activities required to be done by the individuals. These evaluations and feedback can help in maintaining a better health status of the individual and providing improved health care.

Keywords: HTML, java, javascript, MySQL, sunspot, UML, web-based, wireless network sensor

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Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

Abstract:

The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

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Authors: Sherif Keddis, Mohamed Azzam, Norbert Schwesinger

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Harvesting mechanical energy from footsteps or other impacts is a possibility to enable wireless autonomous sensor nodes. These can be used for a highly efficient control of connected devices such as lights, security systems, air conditioning systems or other smart home applications. They can also be used for accurate location or occupancy monitoring. Converting the mechanical energy into useful electrical energy can be achieved using the piezoelectric effect offering simple harvesting setups and low deflections. The challenge facing piezoelectric transducers is the achievable amount of energy per impact in the lower mJ range and the management of such low energies. Simple setups for energy extraction such as a full wave bridge connected directly to a capacitor are problematic due to the mismatch between high impedance sources and low impedance storage elements. Efficient energy circuits for piezoelectric harvesters are commonly designed for vibration harvesters and require periodic input energies with predictable frequencies. Due to the sporadic nature of impact harvesters, such circuits are not well suited. This paper presents a self-powered circuit that avoids the impedance mismatch during energy extraction by disconnecting the load until the source reaches its charge peak. The switch is implemented with passive components and works independent from the input frequency. Therefore, this circuit is suited for impact harvesting and sporadic inputs. For the same input energy, this circuit stores 150% of the energy in comparison to a directly connected capacitor to a bridge rectifier. The total efficiency, defined as the ratio of stored energy on a capacitor to available energy measured across a matched resistive load, is 63%. Although the resulting energy is already sufficient to power certain autonomous applications, further optimization of the circuit are still under investigation in order to improve the overall efficiency.

Keywords: autonomous sensors, circuit design, energy harvesting, energy management, impact harvester, piezoelectricity

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Authors: Aagesson, Ekstrand, Persson, Sallander

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A description of how a team of librarians at Linnaeus University Library in Sweden utilizes a pedagogical approach to deliver engaging digital workshops on information retrieval. The team consists of four librarians supporting three different faculties. The paper discusses the challenges faced in engaging students who may perceive information retrieval as a boring and difficult subject. The paper emphasizes the importance of motivation, inclusivity, constructive feedback, and collaborative learning in enhancing student engagement. By employing a two-librarian teaching model, maintaining a lighthearted approach, and relating information retrieval to everyday experiences, the team aimed to create an enjoyable and meaningful learning experience. The authors describe their approach to increase student engagement and learning outcomes through a three-phase workshop structure: before, during, and after the workshops. The "flipped classroom" method was used, where students were provided with pre-workshop materials, including a short film on information search and encouraged to reflect on the topic using a digital collaboration tool. During the workshops, interactive elements such as quizzes, live demonstrations, and practical training were incorporated, along with opportunities for students to ask questions and provide feedback. The paper concludes by highlighting the benefits of the flipped classroom approach and the extended learning opportunities provided by the before and after workshop phases. The authors believe that their approach offers a sustainable alternative for enhancing information retrieval knowledge among students at Linnaeus University.

Keywords: digital workshop, flipped classroom, information retrieval, interactivity, LIS practitioner, student engagement

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Authors: Asmaa Hamdy, Israa Nassar, Tarek Aly

Abstract:

Introduction: Femoral fractures are the most common presentation in the Emergency Department (ED), and they can present as isolated injuries or as part of a polytrauma situation. To provide optimum pain management care to these patients, practitioners must be well prepared and current with utilizing modern evidence-based knowledge and practices. Management of pain associated with fracture femur in the emergency department has a critical role in the satisfaction of patients and preventing further complications. This study aimed to evaluate the analgesic efficacy of ultrasound-guided femoral nerve block compared with intravenous fentanyl in fractures of the femur in patients presented to the Emergency Department. Patients and Methods: Fifty patients with femur fractures were divided into two groups: Group A: In this group (twenty-five patients) were given intravenous fentanyl 2 micro-grams/kg and re-assessed for pain by Visual Analogue Score (VAS). Group B: In this group (twenty-five patients) underwent ultrasonography-guided femoral nerve block and were re-assessed for pain by VAS. Results: VAS score on the movement of the fractured limb between group A and group B at a 10-minute post-intervention period shows P= 0.043, and hence the difference is significant. VAS score on the movement of the fractured limb between group A and group B during a 10-minute post-intervention period showed a significant difference. Seventeen patients in group A had major PID with a percentage of 63% VS 10 patients in group B with a percentage of 37%. conclusion: both femoral nerve block and intravenous fentanyl are effective in relieving pain in patients with femur fractures. But femoral nerve block provides better and more intense analgesia and major pain intensity difference in less time. Moreover, the use of FNB had fewer side effects and more Hemodynamics stability compared to opioids.

Keywords: femur fracture, nerve block, fentanyl, ultrasound guided

Procedia PDF Downloads 86