Search results for: automatic selective door operations

Authors: Zatil Afifah Omar, Siti Nur Izati Azmi, Kathi Swaran, Navin Kumar

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Lost circulation has always been one of the greatest problems faced by drilling companies during drilling operations due to excessive drilling Fluids losses. Loss of circulation leads to Huge cost and non-productive time. The objective of this study is to evaluate the sealing efficiency of a proprietary blend of synthetic rubber as loss circulation material in comparison with a conventional product such as calcium carbonate, graphite, cellulosic, and nutshells. Sand Bed Tester with a different proprietary blend of synthetic rubber compositions has been used to determine the effectiveness of the LCM in preventing drilling fluids losses in a lab scale. Test results show the proprietary blend of synthetic rubber have good bridging properties and sealing Off fractures of various sizes. The finish product is environmentally friendly with lower production lead time and lower production cost compared to current conventional loss circulation materials used in current drilling operations.

Keywords: loss circulation materials, drilling operation, sealing efficiency, LCM

Procedia PDF Downloads 188

Authors: Derejaw Lake Melie, Alemu Kumlachew Tegegne

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The increasing prevalence of social media in Ethiopia has exacerbated societal challenges by fostering the proliferation of negative emotional posts and comments. Illicit use of social media has further exacerbated divisions among the population. Addressing these issues through manual identification and aggregation of emotions from millions of users for swift decision-making poses significant challenges, particularly given the rapid growth of Amharic language usage on social platforms. Consequently, there is a critical need to develop an intelligent system capable of automatically detecting and categorizing negative emotional content into social, religious, and political categories while also filtering out toxic online content. This paper aims to leverage sentiment analysis techniques to achieve automatic detection and filtering of negative emotional content from Amharic social media texts, employing a comparative study of deep learning algorithms. The study utilized a dataset comprising 29,962 comments collected from social media platforms using comment exporter software. Data pre-processing techniques were applied to enhance data quality, followed by the implementation of deep learning methods for training, testing, and evaluation. The results showed that CNN, GRU, LSTM, and Bi-LSTM classification models achieved accuracies of 83%, 50%, 84%, and 86%, respectively. Among these models, Bi-LSTM demonstrated the highest accuracy of 86% in the experiment.

Keywords: negative emotion, emotion detection, social media filtering sentiment analysis, deep learning.

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Authors: Viktoriia Burkina, Vladimir Zlabek, Galia Zamaratskaia

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Cytochromes P450 (CYP) are important family of enzymes in Phase I metabolism. Environmental pollutants often act as inducers of the gene expression and activities CYP1A1 and CYP3A-like isoforms in fish. The activities are generally measured in the fish liver or gills, and less is known about tissue distribution of expression. In present study, the CYP1A1 and CYP3A-like activities were measured in rainbow trout liver, gill, intestine, heart, brain and gonads. The activities of CYP1A1 and CYP3A-like proteins were estimated as the rates of 7-ethoxyresorufin-O-deethylation (EROD) and benzyloxy-4-trifluoromethylcoumarin-O-debenzyloxylation (BFCOD), respectively. The CYP1A1 and CYP3A-like activities were detectable in all investigated fish tissues, with the highest activity in hepatic tissue followed by heart > brain > gill > intestine > gonads. To confirm the presence of CYP1A1 in different tissues, EROD activity was measured in presence of the selective inhibitors ellipticine (CYP1A1), ketoconazole (CYP3A), 8-methoxypsoralen (human CYP2A) and diallyl sulphide (CYP2E1). It was found that ellipticine, ketoconazole and 8-methoxypsoralen inhibited hepatic EROD activity by 88-98%. Ellipticine inhibited gill, intestine, and gonad EROD activity by 50%. In conclusion, EROD and BFCOD activities were detected in rainbow trout liver, gill, intestine, heart, brain and gonads. Further studies are needed to fully identify all CYP450 isoforms responsible for these activities. Acknowledgement: The study was financially supported by the Ministry of Education, Youth and Sports of the Czech Republic - projects „CENAKVA “(No. CZ.1.05/2.1.00/01.0024), “CENAKVA Center Development “(No. CZ.1.05/2.1.00/19.0380), “CENAKVA II “(No. LO1205 under the NPU I program), and "Development of USB - International mobility (No. CZ.02.2.69/0.0/0.0/16_027/0008364).

Keywords: BFCOD, EROD, fish, phase I metabolism, selective inhibitors

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Authors: Lopamudra Malek

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It is known to all that Japan was closed till 1853 abruptly; Commodore Culbreath Matthew Perry has played a pivotal role in Japan’s exposure to modernization and facing the real world as an Asian entity. As Japan opened its door for the world, Indians, especially four women from Bengal, visited Japan. They were Hariprova Takeda, Sarojnalini Dutta, Santa Devi and Parul Devi. All of them were from different entities, but there were some bewildering similarities also in their depiction. How they penetrated their exposure to modernizing Japan is the motto of the research. It should be mentioned that two of them were directly influenced by Rabindranath Tagore. The methodology that has been followed while doing this research is depending on secondary source materials, like books, articles, etc. Japan was changing herself relentlessly towards modernization and westernization and these four women had witnessed the changing Japan and how the changing Japan has reflected in their write-ups and autobiography is the fundamental part of the research. As all of them were women, they had compared themselves with Japanese women. The finding of the research is, astonishingly, all of them found and comprehended Japan as a country where women were having more financial sovereignty and freedom of thought comparing to India in those days.

Keywords: empowerment, Japan, modernization, women

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Authors: Shailendra Kumar Mishra

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In this paper, we focus on how contextual factors like the physical presence of other perceivers and then developed induced emotional empathy towards a person with disabilities may reduce the automatic negative stereotypes and then response towards that person. We demonstrated in study 1 that negative attitude based on negative stereotypes assessed on ATDP-test questionnaires on five points Linkert-scale are significantly less negative when participants were tested with a group of perceivers and then tested alone separately by applying 3 (positive, indifferent, and negative attitude levels) X 2 (physical presence condition and alone) factorial design of ANOVA test. In the second study, we demonstrate, by applying regression analysis, in the presence of other perceivers, whether in a small group, participants showed more induced emotional empathy through stronger prosociality towards a high distress target like a person with disabilities in comparison of that of other stigmatized persons such as racial biased or gender-biased people. Thus results show that automatic affective response in the form of induced emotional empathy in perceiver and contextual factors like the presence of other perceivers automatically activate stronger prosocial norms and egalitarian goals towards physically challenged persons in comparison to other stigmatized persons like racial or gender-biased people. This leads to less negative attitudes and behaviour towards a person with disabilities.

Keywords: contextual factors, high distress target, induced emotional empathy, stronger prosociality

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Authors: Natalia V. Beloglazova, Pieterjan Lenain, Martin Hedstrom, Dietmar Knopp, Sarah De Saeger

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In recent years polycyclic aromatic hydrocarbons (PAHs), which represent a hazard to humans and entire ecosystem, have been receiving an increased interest due to their mutagenic, carcinogenic and endocrine disrupting properties. They are formed in all incomplete combustion processes of organic matter and, as a consequence, ubiquitous in the environment. Benzo(a)pyrene (BaP) is on the priority list published by the Environmental Agency (US EPA) as the first PAH to be identified as a carcinogen and has often been used as a marker for PAHs contamination in general. It can be found in different types of water samples, therefore, the European Commission set up a limit value of 10 ng L–1 (10 ppt) for BAP in water intended for human consumption. Generally, different chromatographic techniques are used for PAHs determination, but these assays require pre-concentration of analyte, create large amounts of solvent waste, and are relatively time consuming and difficult to perform on-site. An alternative robust, stand-alone, and preferably cheap solution is needed. For example, a sensing unit which can be submerged in a river to monitor and continuously sample BaP. An affinity sensor based on capacitive transduction was developed. Natural antibodies or their synthetic analogues can be used as ligands. Ideally the sensor should operate independently over a longer period of time, e.g. several weeks or months, therefore the use of molecularly imprinted polymers (MIPs) was discussed. MIPs are synthetic antibodies which are selective for a chosen target molecule. Their robustness allows application in environments for which biological recognition elements are unsuitable or denature. They can be reused multiple times, which is essential to meet the stand-alone requirement. BaP is a highly lipophilic compound and does not contain any functional groups in its structure, thus excluding non-covalent imprinting methods based on ionic interactions. Instead, the MIPs syntheses were based on non-covalent hydrophobic and π-π interactions. Different polymerization strategies were compared and the best results were demonstrated by the MIPs produced using electropolymerization. 4-vinylpyridin (VP) and divinylbenzene (DVB) were used as monomer and cross-linker in the polymerization reaction. The selectivity and recovery of the MIP were compared to a non-imprinted polymer (NIP). Electrodes were functionalized with natural receptor (monoclonal anti-BaP antibody) and with MIPs selective towards BaP. Different sets of electrodes were evaluated and their properties such as sensitivity, selectivity and linear range were determined and compared. It was found that both receptor can reach the cut-off level comparable to the established ML, and despite the fact that the antibody showed the better cross-reactivity and affinity, MIPs were more convenient receptor due to their ability to regenerate and stability in river till 7 days.

Keywords: antibody, benzo(a)pyrene, capacitive sensor, MIPs, river water

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Authors: Juliane Spaak

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A life-cycle assessment was performed, looking at seven retrofit projects in New Zealand using LCAQuickV3.5. The study found that retrofits save up to 80% of embodied carbon emissions for the structural elements compared to a new building. In other words, it is only a 20% carbon investment to transform and extend a building’s life. In addition, the systems were evaluated by looking at environmental impacts over the design life of these buildings and resilience using FEMA P58 and PACT software. With the increasing interest in Zero Carbon targets, significant changes in the building and construction sector are required. Emissions for buildings arise from both embodied carbon and operations. Based on the significant advancements in building energy technology, the focus is moving more toward embodied carbon, a large portion of which is associated with the structure. Since older buildings make up most of the real estate stock of our cities around the world, their reuse through structural retrofit and wider refurbishment plays an important role in extending the life of a building’s embodied carbon. New Zealand’s building owners and engineers have learned a lot about seismic issues following a decade of significant earthquakes. Recent earthquakes have brought to light the necessity to move away from constructing code-minimum structures that are designed for life safety but are frequently ‘disposable’ after a moderate earthquake event, especially in relation to a structure’s ability to minimize damage. This means weaker buildings sit as ‘carbon liabilities’, with considerably more carbon likely to be expended remediating damage after a shake. Renovating and retrofitting older assets plays a big part in reducing the carbon profile of the buildings sector, as breathing new life into a building’s structure is vastly more sustainable than the highest quality ‘green’ new builds, which are inherently more carbon-intensive. The demolition of viable older buildings (often including heritage buildings) is increasingly at odds with society’s desire for a lower carbon economy. Bringing seismic resilience and carbon best practice together in decision-making can open the door to commercially attractive outcomes, with retrofits that include structural and sustainability upgrades transforming the asset’s revenue generation. Across the global real estate market, tenants are increasingly demanding the buildings they occupy be resilient and aligned with their own climate targets. The relationship between seismic performance and ‘sustainable design’ has yet to fully mature, yet in a wider context is of profound consequence. A whole-of-life carbon perspective on a building means designing for the likely natural hazards within the asset’s expected lifespan, be that earthquake, storms, damage, bushfires, fires, and so on, ¬with financial mitigation (e.g., insurance) part, but not all, of the picture.

Keywords: retrofit, sustainability, earthquake, reuse, carbon, resilient

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Authors: Abdullah Bal

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This paper presents a one-class classification (OCC) technique based on Fukunaga-Koontz Transform (FKT) for binary classification problems. The FKT is originally a powerful tool to feature selection and ordering for two-class problems. To utilize the standard FKT for data domain description problem (i.e., one-class classification), in this paper, a set of non-class samples which exist outside of positive class (target class) describing boundary formed with limited training data has been constructed synthetically. The tunnel-like decision boundary around upper and lower border of target class samples has been designed using statistical properties of feature vectors belonging to the training data. To capture higher order of statistics of data and increase discrimination ability, the proposed method, termed one-class FKT (OC-FKT), has been extended to its nonlinear version via kernel machines and referred as OC-KFKT for short. Multiple kernel learning (MKL) is a favorable family of machine learning such that tries to find an optimal combination of a set of sub-kernels to achieve a better result. However, the discriminative ability of some of the base kernels may be low and the OC-KFKT designed by this type of kernels leads to unsatisfactory classification performance. To address this problem, the quality of sub-kernels should be evaluated, and the weak kernels must be discarded before the final decision making process. MKL/OC-FKT and selective MKL/OC-FKT frameworks have been designed stimulated by ensemble learning (EL) to weight and then select the sub-classifiers using the discriminability and diversities measured by eigenvalue ratios. The eigenvalue ratios have been assessed based on their regions on the FKT subspaces. The comparative experiments, performed on various low and high dimensional data, against state-of-the-art algorithms confirm the effectiveness of our techniques, especially in case of small sample size (SSS) conditions.

Keywords: ensemble methods, fukunaga-koontz transform, kernel-based methods, multiple kernel learning, one-class classification

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Authors: Jinan Fiaidhi, Hashmath Shaik

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Breaking the barrier for practicing evidence-based medicine relies on effective methods for rapidly identifying relevant evidence from the body of biomedical literature. An important challenge confronted by medical practitioners is the long time needed to browse, filter, summarize and compile information from different medical resources. Deep learning can help in solving this based on automatic question answering (Q&A) and transformers. However, Q&A and transformer technologies are not trained to answer clinical queries that can be used for evidence-based practice, nor can they respond to structured clinical questioning protocols like PICO (Patient/Problem, Intervention, Comparison and Outcome). This article describes the use of deep learning techniques for Q&A that are based on transformer models like BERT and GPT to answer PICO clinical questions that can be used for evidence-based practice extracted from sound medical research resources like PubMed. We are reporting acceptable clinical answers that are supported by findings from PubMed. Our transformer methods are reaching an acceptable state-of-the-art performance based on two staged bootstrapping processes involving filtering relevant articles followed by identifying articles that support the requested outcome expressed by the PICO question. Moreover, we are also reporting experimentations to empower our bootstrapping techniques with patch attention to the most important keywords in the clinical case and the PICO questions. Our bootstrapped patched with attention is showing relevancy of the evidence collected based on entropy metrics.

Keywords: automatic question answering, PICO questions, evidence-based medicine, generative models, LLM transformers

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving the army, moving convoys etc. The radar operator selects one of the promising targets into single target tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper, we present a technique using mathematical and statistical methods like fast fourier transformation (FFT) and principal component analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, FFT, principal component analysis, eigenvector, octave-notes, DSP

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Authors: Anja Gräff, Stefan Holzer, Manfred Höld, Jörn Stumpenhausen, Heinz Bernhardt

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In view of the increasing quantity of 'green energy' from renewable raw materials and photovoltaic facilities, it is quite conceivable that power supply variations may occur, so that constantly working machines like automatic milking systems (AMS) may break down temporarily. The usage of farm-made energy is steadily increasing in order to keep energy costs as low as possible. As a result, power cuts are likely to happen more frequently. Current work in the framework of the project 'stable 4.0' focuses on possible stress reactions by simulating power cuts up to four hours in dairy farms. Based on heart activity it should be found out whether stress on dairy cows increases under these circumstances. In order to simulate a power cut, 12 random cows out of 2 herds were not admitted to the AMS for at least two hours on three consecutive days. The heart rates of the cows were measured and the collected data evaluated with HRV Program Kubios Version 2.1 on the basis of eight parameters (HR, RMSSD, pNN50, SD1, SD2, LF, HF and LF/HF). Furthermore, stress reactions were examined closely via video analysis, milk yield, ruminant activity, pedometer and measurements of cortisol metabolites. Concluding it turned out, that during the test only some animals were suffering from minor stress symptoms, when they tried to get into the AMS at their regular milking time, but couldn´t be milked because the system was manipulated. However, the stress level during a regular “time-dependent milking rejection” was just as high. So the study comes to the conclusion, that the low psychological stress level in the case of a 2-4 hours failure of an AMS does not have any impact on animal welfare and health.

Keywords: dairy cow, heart activity, power cut, stable 4.0

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Authors: Bahar Tunctan, Sefika Pinar Kucukkavruk, Meryem Temiz-Resitoglu, Demet Sinem Guden, Ayse Nihal Sari, Seyhan Sahan-Firat

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We hypothesized that rexinoids such as bexarotene, a selective retinoid X receptor α (RXRα) agonist, may be beneficial for preventing mortality due to inflammation associated with increased expression/activity of inducible nitric oxide synthase (iNOS) induced by lipopolysaccharide (LPS). Therefore, we investigated effects of bexarotene on the changes in circulating protein levels of iNOS (an index for systemic iNOS expression), myeloperoxidase (MPO) (an index for systemic inflammation), and lactate dehydrogenase (LDH) (an index for systemic tissue injury) in LPS-induced systemic inflammation model resulting in septic shock in rats. Rats were injected with saline (4 ml/kg; i.p.), LPS (10 mg/kg; i.p.), dimethylsulphoxide (4 ml/kg, 0.1%; s.c.) at time 0. Mean arterial blood pressure and heart rate were measured using a tail-cuff device. Bexarotene (0.03, 0.1, 0.3, and 1 mg/kg; s.c.) was administered to separate groups of rats 1 h after injection of saline or LPS. The rats were sacrificed 4 h after saline or LPS injection and blood was collected for measurement of serum iNOS, MPO, and LDH protein levels. Blood pressure decreased by 31 mmHg and heart rate increased by 63 bpm in the LPS-treated rats. Bexarotene at 0.3 and 1 mg/kg doses caused 20% mortality 4 h after LPS injection. In the LPS-treated rats, serum iNOS, MPO, and LDH protein levels were increased. Bexarotene only at 0.1 mg/kg dose prevented the LPS-induced hypotension and increased in iNOS, MPO, and LDH protein levels. These data are consistent with the view that a decrease in systemic iNOS levels contributes to the beneficial effect of bexarotene to prevent the hypotension associated with inflammation and tissue injury during rat endotoxemia. [This work was financially supported by The Scientific and Technological Research Council of Turkey (SBAG-109S121)].

Keywords: bexarotene, inflammation, iNOS, lipopolisaccharide, RXRa

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Authors: Dustin Schöder

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The potential benefits of the utilization of highly automated and autonomous trucks in logistics operations are the subject of interest to the entire logistics industry. The benefits of the use of these new technologies were scientifically investigated and implemented in roadmaps. So far, reliable data and experiences from real life use cases are still limited. A German research consortium of both academics and industry developed a highly automated (SAE level 4) vehicle for yard operations at railports and container depots. After development and testing, a several month field test at the DUSS Terminal in Ulm-Dornstadt (Germany) and the nearby DB Intermodal Services Container Depot in Ulm-Dornstadt was conducted. The truck was piloted in a shuttle service between both sites. In a holistic automation approach, the vehicle was integrated into a digital communication platform so that the truck could move autonomously without a driver and his manual interactions with a wide variety of stakeholders. The main goal is to investigate the effects of highly automated trucks in the key processes of container loading, unloading and container relocation on holistic railport yard operation. The field test data were used to investigate changes in process efficiency of key processes of railport and container yard operations. Moreover, effects on the capacity utilization and potentials for smothering peak workloads were analyzed. The results state that process efficiency in the piloted use case was significantly higher. The reason for that could be found in the digitalized data exchange and automated dispatch. However, the field test has shown that the effect is greatly varying depending on the ratio of highly automated and manual trucks in the yard as well as on the congestion level in the loading area. Furthermore, the data confirmed that under the right conditions, the capacity utilization of highly automated trucks could be increased. In regard to the potential for smothering peak workloads, no significant findings could be made based on the limited requirements and regulations of railway operation in Germany. In addition, an empirical survey among railport managers, operational supervisors, innovation managers and strategists (n=15) within the logistics industry in Germany was conducted. The goal was to identify key characteristics of future railports and terminals as well as requirements that railports will have to meet in the future. Furthermore, the railport processes where automation and autonomization make the greatest impact, as well as hurdles and challenges in the introduction of new technologies, have been surveyed. Hence, further potential use cases of highly automated and autonomous applications could be identified, and expectations have been mapped. As a result, a highly detailed and practice-based roadmap towards a ‘terminal 4.0’ was developed.

Keywords: highly automated driving, autonomous driving, SAE level 4, railport operations, container depot, intermodal logistics, potentials of autonomization

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Authors: Praveen K. Khatri, Neha Karanwal, Savita Kaul, Suman L. Jain

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Conversion of biomass through green chemical routes is of great industrial importance as biomass is considered to be most widely available inexpensive renewable resource that can be used as a raw material for the production of bio fuel and value-added organic products. In this regard, acid catalyzed dehydration of biomass derived pentose sugar (mainly D-xylose) to furfural is a process of tremendous research interest in current scenario due to the wider industrial applications of furfural. Furfural is an excellent organic solvent for refinement of lubricants and separation of butadiene from butene mixture in synthetic rubber fabrication. In addition it also serve as a promising solvent for many organic materials, such as resins, polymers and also used as a building block for synthesis of various valuable chemicals such as furfuryl alcohol, furan, pharmaceutical, agrochemicals and THF. Here in a sulfonated polymer impregnated carbon composite solid acid catalyst (P-C-SO3H) was prepared by the pyrolysis of a polymer matrix impregnated with glucose followed by its sulfonation and used for the dehydration of xylose to furfural. The developed catalyst exhibited excellent activity and provided almost quantitative conversion of xylose with the selective synthesis of furfural. The higher catalytic activity of P-C-SO3H may be due to the more even distribution of polycyclic aromatic hydrocarbons generated from incomplete carbonization of glucose along the polymer matrix network, leading to more available sites for sulfonation which resulted in greater sulfonic acid density in P-C-SO3H as compared to sulfonated carbon catalyst (C-SO3H). In conclusion, we have demonstrated sulfonated polymer impregnated carbon composite (P-C-SO3H) as an efficient and selective solid acid catalyst for the dehydration of xylose to furfural. After completion of the reaction, the catalyst was easily recovered and reused for several runs without noticeable loss in its activity and selectivity.

Keywords: Solid acid , Biomass conversion, Xylose Dehydration, Heterogeneous catalyst

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

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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: Stefano Zaninotto, Geoffrey Farrugia, Johan Debattista, Jason Gauci

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The need to reduce fuel and noise during taxi operations in the airports with a scenario of constantly increasing air traffic has resulted in an effort by the aerospace industry to move towards electric taxiing. In fact, this is one of the problems that is currently being addressed by SESAR JU and two main solutions are being proposed. With the first solution, electric motors are installed in the main (or nose) landing gear of the aircraft. With the second solution, manned or unmanned electric tow trucks are used to tow aircraft from the gate to the runway (or vice-versa). The presence of the tow trucks results in an increase in vehicle traffic inside the airport. Therefore, it is important to design the system in a way that the workload of Air Traffic Control (ATC) is not increased and the system assists ATC in managing all ground operations. The aim of this work is to develop an electric taxiing system, based on the use of autonomous tow trucks, which optimizes aircraft ground operations while keeping ATC in the loop. This system will consist of two components: an optimization tool and a Graphical User Interface (GUI). The optimization tool will be responsible for determining the optimal path for arriving and departing aircraft; allocating a tow truck to each taxiing aircraft; detecting conflicts between aircraft and/or tow trucks; and proposing solutions to resolve any conflicts. There are two main optimization strategies proposed in the literature. With centralized optimization, a central authority coordinates and makes the decision for all ground movements, in order to find a global optimum. With the second strategy, called decentralized optimization or multi-agent system, the decision authority is distributed among several agents. These agents could be the aircraft, the tow trucks, and taxiway or runway intersections. This approach finds local optima; however, it scales better with the number of ground movements and is more robust to external disturbances (such as taxi delays or unscheduled events). The strategy proposed in this work is a hybrid system combining aspects of these two approaches. The GUI will provide information on the movement and status of each aircraft and tow truck, and alert ATC about any impending conflicts. It will also enable ATC to give taxi clearances and to modify the routes proposed by the system. The complete system will be tested via computer simulation of various taxi scenarios at multiple airports, including Malta International Airport, a major international airport, and a fictitious airport. These tests will involve actual Air Traffic Controllers in order to evaluate the GUI and assess the impact of the system on ATC workload and situation awareness. It is expected that the proposed system will increase the efficiency of taxi operations while reducing their environmental impact. Furthermore, it is envisaged that the system will facilitate various controller tasks and improve ATC situation awareness.

Keywords: air traffic control, electric taxiing, autonomous tow trucks, graphical user interface, ground operations, multi-agent, route optimization

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Authors: Arash Rafiei, Carroll Moore

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Leaching process as the first stage of hydrometallurgy is a multidisciplinary system including material properties, chemistry, reactor design, mechanics and fluid dynamics. Therefore, doing leaching system optimization by pure scientific methods need lots of times and expenses. In this work, a mixture of two titanium ores and one titanium slag are used for extracting titanium for leaching stage of TiO2 pigment production procedure. Optimum titanium extraction can be obtained from following strategies: i) Maximizing titanium extraction without selective digestion; and ii) Optimizing selective titanium extraction by balancing between maximum titanium extraction and minimum impurity digestion. The main difference between two strategies is due to process optimization framework. For the first strategy, the most important stage of production process is concerned as the main stage and rest of stages would be adopted with respect to the main stage. The second strategy optimizes performance of more than one stage at once. The second strategy has more technical complexity compared to the first one but it brings more economical and technical advantages for the leaching system. Obviously, each strategy has its own optimum operational zone that is not as same as the other one and the best operational zone is chosen due to complexity, economical and practical aspects of the leaching system. Experimental design has been carried out by using Taguchi method. The most important advantages of this methodology are involving different technical aspects of leaching process; minimizing the number of needed experiments as well as time and expense; and concerning the role of parameter interactions due to principles of multifactor-at-time optimization. Leaching tests have been done at batch scale on lab with appropriate control on temperature. The leaching tank geometry has been concerned as an important factor to provide comparable agitation conditions. Data analysis has been done by using reactor design and mass balancing principles. Finally, optimum zone for operational parameters are determined for each leaching strategy and discussed due to their economical and practical aspects.

Keywords: titanium leaching, optimization, experimental design, performance analysis

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Authors: Adam Johnbull

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The paper discusses ICT in Education as a quest for quality learning in the 21st century. Education is the key that unlock the door to development, without adequate education of the citizenry, the development of a nation becomes a sham. Information Communication Technologies (ICTs) has revolutionized the way people work today and are now transforming education systems. As a result, if schools train children in yesterday’s skills and technologies they may not be effective and fit in tomorrow’s world. This is a sufficient reason for ICT’s to win global recognition and attention and thus ensure desire quality in our school system. Thus, the purpose of the paper is to discuss amongst others, what is ICT. The roles of ICT’s in education, limitation and key challenges of integrating ICT to education in the enhancement of student learning and experiences in other to encourage policy makers, school administrators and teachers pay the required attention to integrate this technology in the education system. The paper concludes that regardless of all the limitation characterizing it. ICT benefit education system to provide quality education in the 21st century.

Keywords: ICTs, quest, information, global, sham, century

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Authors: Kehinde Adeyeye Adelabu

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Computer applications has completely revolutionized the way of life of people which does not exclude the field of sport education. There are computer technologies which help to enhance teaching in every field of education. Invention of computers has done great to the field of education. This study was therefore carried out to examine the effects and merits of computer operations in Human Kinetics Education and Sports. The study was able to identify the component of computer, uses of computer in Human Kinetics education (sports), computer applications in some branches of human kinetics education. A qualitative research method was employed by the author in gathering experts’ views and used to analyze the effects and merits of computer applications in the field of human kinetics education. No experiment was performed in the cause of carrying out the study. The source of information for the study was text-books, journal, articles, past project reports, internet i.e. Google search engine. Computer has significantly helped to improve Education (Human Kinetic), it has complemented the basic physical fitness testing and gave a more scientific basis to the testing. The use of the software and packages has made cost projections, database applications, inventory control, management of events, word processing, electronic mailing and record keeping easier than the pasts.

Keywords: application, computer operation, education, human kinetics

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Authors: Sun Li-Ping, Zhu Jian-Xun, Liu Sheng-Nan

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In order to study the performance of dynamic positioning system during S-lay operations, dynamic positioning system is simulated with the hull-stinger-pipe coupling effect. The roller of stinger is simulated by the generalized elastic contact theory. The stinger is composed of Morrison members. Force on pipe is calculated by lumped mass method. Time domain of fully coupled barge model is analyzed combining with PID controller, Kalman filter and allocation of thrust using Sequential Quadratic Programming method. It is also analyzed that the effect of hull wave frequency motion on pipe-stinger coupling force and dynamic positioning system. Besides, it is studied that how S-lay operations affect the dynamic positioning accuracy. The simulation results are proved to be available by checking pipe stress with API criterion. The effect of heave and yaw motion cannot be ignored on hull-stinger-pipe coupling force and dynamic positioning system. It is important to decrease the barge’s pitch motion and lay pipe in head sea in order to improve safety of the S-lay installation and dynamic positioning.

Keywords: S-lay operation, dynamic positioning, coupling motion, time domain, allocation of thrust

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Authors: Pranav Ajmera, Amit Kharat, Tanveer Gupte, Richa Pant, Viraj Kulkarni, Vinay Duddalwar, Purnachandra Lamghare

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The cardiothoracic ratio (CTR) is the ratio of the diameter of the heart to the diameter of the thorax. An abnormal CTR, that is, a value greater than 0.55, is often an indicator of an underlying pathological condition. The accurate prediction of an abnormal CTR from chest X-rays (CXRs) aids in the early diagnosis of clinical conditions. We propose a deep learning-based model for automatic CTR calculation that can assist the radiologist with the diagnosis of cardiomegaly and optimize the radiology flow. The study population included 1012 posteroanterior (PA) CXRs from a single institution. The Attention U-Net deep learning (DL) architecture was used for the automatic calculation of CTR. A CTR of 0.55 was used as a cut-off to categorize the condition as cardiomegaly present or absent. An observer performance test was conducted to assess the radiologist's performance in diagnosing cardiomegaly with and without artificial intelligence (AI) assistance. The Attention U-Net model was highly specific in calculating the CTR. The model exhibited a sensitivity of 0.80 [95% CI: 0.75, 0.85], precision of 0.99 [95% CI: 0.98, 1], and a F1 score of 0.88 [95% CI: 0.85, 0.91]. During the analysis, we observed that 51 out of 1012 samples were misclassified by the model when compared to annotations made by the expert radiologist. We further observed that the sensitivity of the reviewing radiologist in identifying cardiomegaly increased from 40.50% to 88.4% when aided by the AI-generated CTR. Our segmentation-based AI model demonstrated high specificity and sensitivity for CTR calculation. The performance of the radiologist on the observer performance test improved significantly with AI assistance. A DL-based segmentation model for rapid quantification of CTR can therefore have significant potential to be used in clinical workflows.

Keywords: cardiomegaly, deep learning, chest radiograph, artificial intelligence, cardiothoracic ratio

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Authors: Zhaoyang Liu, Detao Qin, Darren Delai Sun

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The onshore production of oil and gas (for example, shale gas) generates large quantities of wastewater, referred to be ‘produced water’, which contains high contents of oils and salts. The direct discharge of produced water, if not appropriately treated, can be toxic to the environment and human health. Membrane filtration has been deemed as an environmental-friendly and cost-effective technology for treating oily wastewater. However, conventional polymeric membranes have their drawbacks of either low salt rejection rate or high membrane fouling tendency when treating oily wastewater. Recent years, forward osmosis (FO) membrane filtration has emerged as a promising technology with its unique advantages of low operation pressure and less membrane fouling tendency. However, until now there is still no report about FO membranes specially designed and fabricated for treating the oily and salty produced water. In this study, a novel nanocomposite FO membrane was developed specially for treating oil- and salt-polluted produced water. By leveraging the recent advance of nanomaterials and nanotechnology, this nanocomposite FO membrane was designed to be made of double layers: an underwater oleophobic selective layer on top of a nanomaterial infused polymeric support layer. Wherein, graphene oxide (GO) nanosheets were selected to add into the polymeric support layer because adding GO nanosheets can optimize the pore structures of the support layer, thus potentially leading to high water flux for FO membranes. In addition, polyvinyl alcohol (PVA) hydrogel was selected as the selective layer because hydrated and chemically-crosslinked PVA hydrogel is capable of simultaneously rejecting oil and salt. After nanocomposite FO membranes were fabricated, the membrane structures were systematically characterized with the instruments of TEM, FESEM, XRD, ATR-FTIR, surface zeta-potential and Contact angles (CA). The membrane performances for treating produced waters were tested with the instruments of TOC, COD and Ion chromatography. The working mechanism of this new membrane was also analyzed. Very promising experimental results have been obtained. The incorporation of GO nanosheets can reduce internal concentration polarization (ICP) effect in the polymeric support layer. The structural parameter (S value) of the new FO membrane is reduced by 23% from 265 ± 31 μm to 205 ± 23 μm. The membrane tortuosity (τ value) is decreased by 20% from 2.55 ± 0.19 to 2.02 ± 0.13 μm, which contributes to the decrease of S value. Moreover, the highly-hydrophilic and chemically-cross-linked hydrogel selective layer present high antifouling property under saline oil/water emulsions. Compared with commercial FO membrane, this new FO membrane possesses three times higher water flux, higher removal efficiencies for oil (>99.9%) and salts (>99.7% for multivalent ions), and significantly lower membrane fouling tendency (<10%). To our knowledge, this is the first report of a nanocomposite FO membrane with the combined merits of high salt rejection, high oil repellency and high water flux for treating onshore oil/gas produced waters. Due to its outstanding performance and ease of fabrication, this novel nanocomposite FO membrane possesses great application potential in wastewater treatment industry.

Keywords: nanocomposite, membrane, polymer, graphene oxide

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Authors: Getachew Demeissie Ayalew, Yongtao Sun, Yang Yang

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The spiral welded pipe manufacturing industry requires strict production standards for automated grinders for welding seams. However, traditional grinding machines in this sector are insufficient due to a lack of quality control protocols and inconsistent performance. This research aims to improve the quality of spiral welded pipes by developing intelligent automated abrasive belt grinding equipment. The system has equipped with six degrees of freedom (6 DOF) KUKA KR360 industrial robots, enabling concurrent grinding operations on both internal and external welds. The grinding robot control system is designed with a PLC, and a human-machine interface (HMI) system is employed for operations. The system includes an electric speed controller, data connection card, DC driver, analog amplifier, and HMI for input data. This control system enables the grinding of spiral welded pipe. It ensures consistent production quality and cost-effectiveness by reducing the product life cycle and minimizing risks in the working environment.

Keywords: Intelligent Systems, Spiral Welded Pipe, Grinding, Industrial Robot, End-Effector, PLC Controller System, 3D Laser Sensor, HMI.

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Authors: Aliaksei Patsekha, Michael Hohenberger, Harald Raupenstrauch

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An effective emergency response to accidents with chemical, biological, radiological, nuclear, or explosive materials (CBRNE) that represent highly dynamic situations needs immediate actions within limited time, information and resources. The aim of the study is to provide the foundation for division of unsafe area into risk zones according to the impact of hazardous parameters (heat radiation, thermal dose, overpressure, chemical concentrations). A decision on the boundary values for three risk zones is based on the vulnerability analysis that covered a variety of accident scenarios containing the release of a toxic or flammable substance which either evaporates, ignites and/or explodes. Critical values are selected for the boundary definition of the Red, Orange and Yellow risk zones upon the examination of harmful effects that are likely to cause injuries of varying severity to people and different levels of damage to structures. The obtained results provide the basis for creating a comprehensive real-time risk map for a decision support at CBRNE operations.

Keywords: boundary values, CBRNE threats, decision making process, hazardous effects, vulnerability analysis, risk zones

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Authors: A. Bensaid, T. Mostephaoui, R. Nedjai

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A considerable area of Algerian lands is threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mecheria department generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of LANDSAT images (5, 7, and 8) of three scenes 197/37, 198/36 and 198/37 for the year 2020. As a second step, we prospect the use of geospatial techniques to monitor the progression of sand dunes on developed (urban) lands as well as on the formation of sandy accumulations (dune, dunes fields, nebkha, barkhane, etc.). For this purpose, this study made use of the semi-automatic processing method for the dynamic segmentation of images with very high spatial resolution (SENTINEL-2 and Google Earth). This study was able to demonstrate that urban lands under current conditions are located in sand transit zones that are mobilized by the winds from the northwest and southwest directions.

Keywords: land development, GIS, segmentation, remote sensing

Procedia PDF Downloads 158

Authors: Fan Chih-Wen

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The Ministry of Education (2014) released the 12-year National Basic Education Curriculum Syllabus. Curriculum implementation has evolved from a loose connection of cooperation to a closely structured relationship of coordination and collaboration. Collaboration opens the door to teachers' culture of isolation and classrooms and allows them to discuss educational issues from multiple perspectives and achieve shared goals. The purpose of study is to investigate facilitating factors of collaborative school culture and implications for principal curriculum leadership. The development and implementation of the new curriculum involves collaborative governance across systems and levels, including cooperation between central governments and schools. First, it analyzes the connotation of the 12-year National Basic Education Curriculum; Second, it analyzes the meaning of collaborative culture； Third, it analyzes the motivating factors of collaborative culture. Finally, based on this, it puts forward relevant suggestions for principal curriculum leadership.

Keywords: curriculum leadership, collaboration culture, tracher culture, school improvement

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Authors: Abdullah Beyazkurk, Onur Ozdemir

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The evolution of warfare has been affected from technological developments to a large extent. Another important factor that affected the evolution of warfare is the space. Technological developments became cornerstones for the organization of the forces on the field, while space of the battlefield gained importance with the introduction of urban areas as 'battlefields'. The use of urban areas as battlefields increased the casualty, while technological developments began to play a remedial role. Thus, the unmanned systems drew attention as the remedy. Today's widely used unmanned aerial vehicles have great effects on the operations. On the other hand, with the increasing urbanization, and the wide use of urban areas as battlefields make it a necessity to benefit from unmanned systems on the ground as well. This study focuses on the use of unmanned aerial systems as well as unmanned ground systems in urban warfare, with regards to their performance and cost affectivity. The study defends that the use of unmanned vehicles will be remedial for increasing casualty rates, while their precision and superhuman capacity will manifest the performance advantage. The findings of this study will help modern armies focus on unmanned systems, especially for the urban, anti-terror, or counter insurgency operations.

Keywords: technology, warfare, urban warfare, unmanned systems, unmanned ground vehicles, unmanned aerial vehicles

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

Procedia PDF Downloads 422

Authors: Bezzi Nacer

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The study focused on the qualitative and quantitative study of Trace elements contained in the natural phosphate ore of Djebel Onk layer and their behaviour to the various mineralurgic modes of treatment. The main objective is to locate the importance of these contents according to granulometry and their association with the existing mineralogical species and to define how the most appropriate treatment. The raw ore is in first submitted to a prior mechanical treatment consisting of homogenization operations, of grinding and of sifting, in order to separate it into three particle-size classes: fine <100 µm (F); medium 100-500 µm (I) and coarse > 500 µm (G), and then treated by calcination, washing and floatation. The identification of the different mineralogical phases, the chemical composition and the thermal behaviour of these samples were realized by various techniques: MEB, DRX, ATG-ATD, etc. The study of Trace elements, carried out by ICP-MS, identified thirty items, consisting mainly of rare earths and of transition metals. A close relation between trace elements and various minerals phases (apatite, dolomite and silicates), through operations of substitution. These elements are distributed between several mineralogical phases, in particular apatite (strontium, uranium, chrome, barium, cadmium) and silicates (strontium, sodium, nickel, zinc and copper).

Keywords: valorization of natural phosphate ore, heavy metals, qualitative and quantitative analysis, various mineralurgic

Procedia PDF Downloads 339

Authors: Tamrat Girma Biru

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Multidrug-resistant tuberculosis (MDR-TB) is defined as resistant to at least Refampicin and Isoniazed: the most two power full TB drugs. It is a leading cause of high rates of morbidity and mortality, and increasing psychosocial challenges to patients, especially when co-infected with Human Immunodeficiency Virus (HIV). Ethiopia faces the highest rates of MDR-TB infection in the world. Objectives: The main objective of this study was to identify the psychosocial challenges of MDR-TB patients, to investigate the extent of the psychosocial challenges on (self-esteem, depression, and stigma) that MDR-TB patients encounter, to examine whether there is a sex difference in experiencing psychosocial challenges and assess the counseling needs of MDR-TB patients. Methodology: A cross-sectional study was conducted at St. Peter TB Specialized Hospital, Addis Ababa on 40 patients (25 males and 15 females) who are hospitalized for treatment. The patients were identified by using purposive sampling and made fill a questionnaire measuring their level of self-esteem, depression and stigma. Besides, data were collected from 16 participants, 28 care providers and 8 guardians, using semi-structured interview. The obtained data were analyzed using SPSS statistical program, descriptive statistics, independent t-test, and qualitative description. Results and Discussion: The results of the study showed that the majority (80%) of the respondents had suffered psychological challenges and social discriminations. Thus, the significance of MDR-TB and its association with HIV/AIDS problems is considered. Besides the psychosocial challenges, various aggravating factors such as length of treatment, drug burden and insecurity in economy together highly challenges the life of patients. In addition, 60% of participants showed low level of self-esteem. The patients also reported that they experienced high self-stigma and stigma by other members of the society. The majority of the participants (75%) showed moderate and severe level of depression. In terms of sex there is no difference between the mean scores of males and females in the level of depression and stigmatization by others and by themselves. But females showed lower level of self-esteem than males. The analysis of the t-test also shows that there were no statistically significant sex difference on the level of depression and stigma. Based on the qualitative data MDR-TB patients face various challenges in their life sphere such as: Psychological (depression, low self value, lowliness, anxiety), social (stigma, isolation from social relations, self-stigmatization,) and medical (drug side effect, drug toxicity, drug burden, treatment length, hospital stays). Recommendations: Based on the findings of this study possible recommendations were forwarded: develop and extend MDR-TB disease awareness creation through by media (printing and electronic), school net TB clubs, and door to door community education. Strengthen psychological wellbeing and social relationship of MDR-TB patients using proper and consistent psychosocial support and counseling. Responsible bodies like Ministry of Health (MOH) and its stakeholders and Non Governmental Organizations (NGOs) need to assess the challenges of patients and take measures on this pressing issue.

Keywords: psychosocial challenges, counseling, multi-drug resistant tuberculosis (MDR-TB), tuberculosis therapy

Procedia PDF Downloads 396