Search results for: normalized subband adaptive filter

Authors: Silvia Riva, Ezekiel Chinyio

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Introduction: Workers in different sectors are prone to stress at varying levels. They also respond to stress in different ways. An inspiration was to study stress development amongst workers in a work dangerous setting (Construction Industry) as well as how they cope with specific stress incidences. Objective: The overarching objective of the study was to study and correlate between stress and coping strategies. The research was conducted in an organizational industrial setting, and its findings on the coping actions of construction workers are reported in this article. Methods: An online cross-sectional survey was conducted with 80 participants aged 18-62. These were working for three different construction organizations in the West Midland region of the UK. Their coping actions were assessed using the COPE Inventory (Carver, 2013) instrument while the level of stress was assessed by the Perceived Stress Scale (Cohen, 1994). Results: Out of 80 workers (20 female, 25%, mean age 40.66), positive reinterpretation (M=4.15, SD=2.60) and active coping (M=4.18, SD=2.55) were the two most adaptive strategies reported by the workers while the most frequent maladaptive behavior was mental disengagement (M=3.62, SD=2.25). Among the maladaptive tactics, alcohol and drug abuse was a significant moderator in stress reactions (t=6.12, p=.000). Conclusion: Some maladaptive strategies are adopted by construction workers to cope with stress. So, it could be argued that programs of stress prevention and control in the construction industry have a basis to develop solutions that can improve and strengthen effective interventions when workers are stressed or getting stressed.

Keywords: coping, organization, strategies, stress

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Authors: Hsiao-Wen Tsai

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Motor vehicle accident is the first cause of head injury in the world; severe head injury cases may cause conscious disturbance and death. This is a report about a case of a young adult patient suffering from motor vehicle accident leading to severe head injury who passed through three time surgical procedures, and his mother (who is the informal caregiver). This case was followed from 28th January to 15th February 2011 by using Gordon’s 11 functional health patterns. Patient’s cognitive-perceptual and self-perception-self-concept patterns were altered. Anxiety was also noted on his informal caregiver due to patients’ condition. During the intensive care period, maintaining patient’s vital signs and cerebral perfusion pressure were essential to avoid secondary neuronal injury. Multi-sensory stimulation, caring accompanying, supporting, listening and encouraging patient’s family involved in patient care were very important to reduce informal caregiver anxiety. Finally, the patient consciousness improved from GCS 4 to GCS 11 before discharging from ICU. Patient’s primary informal caregiver, his mother, also showed anxiety improvement. This is was successful case with traumatic brain injury recovered from coma.

Keywords: anxiety, multi-sensory stimulation, reduce intracranial adaptive capacity, traumatic brain injury

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Authors: S. Khan, A. Khan, Abdul R. Soomrani, Raja F. Zafar, A. Waqas, G. Akbar

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This paper proposes a low-complexity image interpolation method. Image interpolation is used to convert a low dimension video/image to high dimension video/image. The objective of a good interpolation method is to upscale an image in such a way that it provides better edge preservation at the cost of very low complexity so that real-time processing of video frames can be made possible. However, low complexity methods tend to provide real-time interpolation at the cost of blurring, jagging and other artifacts due to errors in slope calculation. Non-linear methods, on the other hand, provide better edge preservation, but at the cost of high complexity and hence they can be considered very far from having real-time interpolation. The proposed method is a linear method that uses gradient orientation for slope calculation, unlike conventional linear methods that uses the contrast of nearby pixels. Prewitt edge detection is applied to separate uniform regions and edges. Simple line averaging is applied to unknown uniform regions, whereas unknown edge pixels are interpolated after calculation of slopes using gradient orientations of neighboring known edge pixels. As a post-processing step, bilateral filter is applied to interpolated edge regions in order to enhance the interpolated edges.

Keywords: edge detection, gradient orientation, image upscaling, linear interpolation, slope tracing

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

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Authors: Siddhartha Khare, Suyash Khare

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Phenology, a crucial discipline in ecology, offers insights into the seasonal dynamics of organisms within natural ecosystems and the underlying environmental triggers. Leveraging the potent capabilities of digital repeat photography, PhenoCams capture invaluable data on the phenology of crops, plants, and trees. These cameras yield digital imagery in Red Green Blue (RGB) color channels, and some advanced systems even incorporate Near Infrared (NIR) bands. This study presents compelling case studies employing PhenoCam technology to unravel the phenology of black spruce trees. Through the analysis of RGB color channels, a range of essential color metrics including red chromatic coordinate (RCC), green chromatic coordinate (GCC), blue chromatic coordinate (BCC), vegetation contrast index (VCI), and excess green index (ExGI) are derived. These metrics illuminate variations in canopy color across seasons, shedding light on bud and leaf development. This, in turn, facilitates a deeper understanding of phenological events and aids in delineating the growth periods of trees and plants. The initial phase of this study addresses critical questions surrounding the fidelity of continuous canopy greenness records in representing bud developmental phases. Additionally, it discerns which color-based index most accurately tracks the seasonal variations in tree phenology within evergreen forest ecosystems. The subsequent section of this study delves into the transition dates of black spruce (Picea mariana (Mill.) B.S.P.) phenology. This is achieved through a fortnightly comparative analysis of the MODIS normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). By employing PhenoCam technology and leveraging advanced color metrics, this study significantly advances our comprehension of black spruce tree phenology, offering valuable insights for ecological research and management.

Keywords: phenology, remote sensing, phenocam, color metrics, NDVI, GCC

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Authors: Sara Tokhi Arab, Rozo Noguchi, Tofeal Ahamed

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Drought is a natural disaster that occurs in a region due to a lack of precipitation and high temperatures over a continuous period or in a single season as a consequence of climate change. Precipitation deficits and prolonged high temperatures mostly affect the agricultural sector, water resources, socioeconomics, and the environment. Consequently, it causes agricultural product loss, food shortage, famines, migration, and natural resources degradation in a region. Agriculture is the first sector affected by drought. Therefore, it is important to develop an agricultural drought risk and loss assessment to mitigate the drought impact in the agriculture sector. In this context, the main purpose of this study was to assess yield loss using composite drought indices in the drought-affected vineyards. In this study, the CDI was developed for the years 2016 to 2020 by comprising five indices: the vegetation condition index (VCI), temperature condition index (TCI), deviation of NDVI from the long-term mean (NDVI DEV), normalized difference moisture index (NDMI) and precipitation condition index (PCI). Moreover, the quantitative principal component analysis (PCA) approach was used to assign a weight for each input parameter, and then the weights of all the indices were combined into one composite drought index. Finally, Bayesian regularized artificial neural networks (BRANNs) were used to evaluate the yield variation in each affected vineyard. The composite drought index result indicated the moderate to severe droughts were observed across the Kabul Province during 2016 and 2018. Moreover, the results showed that there was no vineyard in extreme drought conditions. Therefore, we only considered the severe and moderated condition. According to the BRANNs results R=0.87 and R=0.94 in severe drought conditions for the years of 2016 and 2018 and the R= 0.85 and R=0.91 in moderate drought conditions for the years of 2016 and 2018, respectively. In the Kabul Province within the two years drought periods, there was a significate deficit in the vineyards. According to the findings, 2018 had the highest rate of loss almost -7 ton/ha. However, in 2016 the loss rates were about – 1.2 ton/ha. This research will support stakeholders to identify drought affect vineyards and support farmers during severe drought.

Keywords: grapes, composite drought index, yield loss, satellite remote sensing

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Authors: P. Bhavya, P. R. Jayasree

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This paper presents a low cost transformer isolated boost half bridge micro-inverter for single phase grid connected PV system. Since the output voltage of a single PV panel is as low as 20~50V, a high voltage gain inverter is required for the PV panel to connect to the single-phase grid. The micro-inverter has two stages, an isolated dc-dc converter stage and an inverter stage with a dc link. To achieve MPPT and to step up the PV voltage to the dc link voltage, a transformer isolated boost half bridge dc-dc converter is used. To output the synchronised sinusoidal current with unity power factor to the grid, a pulse width modulated full bridge inverter with LCL filter is used. Variable step size Maximum Power Point Tracking (MPPT) method is adopted such that fast tracking and high MPPT efficiency are both obtained. AC voltage as per grid requirement is obtained at the output of the inverter. High power factor (>0.99) is obtained at both heavy and light loads. This paper gives the results of computer simulation program of a grid connected solar PV system using MATLAB/Simulink and SIM Power System tool.

Keywords: boost-half-bridge, micro-inverter, maximum power point tracking, grid connection, MATLAB/Simulink

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Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

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Authors: Rania F. Ahmed, Sally A. El Awdan, Gehad A. Abdel Jaleel, Dalia O. Saleh, Omar A. H. Ahmed-Farid

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The metabolic syndrome is an important public health concern often related to obesity, improper diet, and sedentary lifestyles and can predispose individuals to the development of many dangerous health conditions, disability and early death. This research aimed to investigate the efficacy of resveratrol (RSV) to reverse the neuro-complications associated with metabolic syndrome experimentally-induced in rats using an eight weeks high fat, high fructose diet (HFHF) model. The corresponding drug treatments were administered orally during the last 10 days of the diet. Behavioural tests namely the open field test (OFT) and the forced swimming test (FST) were conducted. Brain levels of monoamines viz. serotonin, norepinephrine and dopamine as well as their metabolites were assessed. 8-hydroxyguanosine (8-OHDG) as an indicative of DNA-fragmentation, nitric oxide (NOx) and tumor necrosis factor-α (TNF- α) were estimated. Finally, brain antioxidant parameters namely malondialdehyde (MDA), reduced and oxidized glutathione (GSH, GSSG) were evaluated. HFHF-induced metabolic syndrome resulted in decreased activity in the OFT and increased immobility duration in the FST. Furthermore, HFHF-induced metabolic syndrome lead to a significant increase in brain monoamines turn over as well as elevation in 8-OHDG, NOx, TNF- α, MDA and GSSG; and reduction in GSH. Ten days daily treatment with RSV (20 and 40 mg/kg p.o) dose dependently increased activity in the OFT and decreased immobility duration in the FST. Moreover, RSV normalized brain monoamines contents, reduced 8-OHDG, NOx, TNF- α, MDA and GSSG; and elevated GSH. In conclusion, we can say that RSV showed neuro-protective properties against HFHF-induced metabolic syndrome represented by monoamines preservation, prevention of neurodegeneration, anti-inflammatory and antioxidant potentials and could be recommended as a beneficial daily dietary supplement to treat the neuronal side effects associated with HFHF-induced metabolic syndrome.

Keywords: antioxidants, DNA-fragmentation, forced swimming test, HFHF-induced metabolic syndrome, monoamines, nitric oxide (NOx), open field, resveratrol, tumor necrosis factor-α (TNF- α), 8-hydroxyguanosine (8-OHDG)

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Authors: Kathryn Nderitu, Atunga Nyachieo, Ezekiel Mecha

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Introduction: Solanum nigrum , also known as black nightshade, biosynthesizes various phytochemical compounds with various pharmacological activities, including treating cardiovascular diseases and type 2 diabetes, among others. Materials and Methods: To assess the anti-obesity effects of Solanum nigrum using high-fat-fed diet rats, Sprague Dawley male rats (n = 35) of weights 160–180 g were assigned randomly into seven groups comprising n = 5 rats each. Each group was fed for 11 weeks as follows: normal group (normal chow rat feed); high-fat diet control (HFD); HFD and standard drug (Orlistat 30 mg/kg bw); HFD and methanolic extract 150 mg/kgbw; HFD and methanolic extract 300 mg/kgbw; HFD and dichloromethane extract 150 mg/kgbw; HFD and dichloromethane extract 300 mg/kgbw. Body mass index and food intake were monitored per week, and an oral glucose tolerance test was measured in weeks 5 and 10. Lipid profiles, liver function tests, adipose tissue, liver weights, and phytochemical analysis of Solanum nigrum were later carried out. Results: High-fat diet control group rats exhibited a significant increase in body mass index (BMI), while rats administered with leaf extracts of Solanum nigrum showed a reduction in BMI. Both low doses of dichloromethane (150 mg/kgbw) and high doses of methanol extracts (300 mg/kgbw) showed a better reduction in BMI than the other treatment groups. A significant decrease (p <0.05) in low-density lipoprotein-cholesterol, triglycerides, and cholesterol was observed among the rats administered with Solanum nigrum extracts compared to those of HFD control. Moreover, the HFD control group significantly increased liver and adipose tissue weights compared to other treatment groups (p<0.05). Solanum nigrum also decreased glycemic levels and normalized the hepatic enzymes of HFD control. However, food intake among the groups showed no significant difference (p>0.05). Qualitative analysis of Solanum nigrum leaf extracts indicated the presence of various bioactive compounds associated with anti-obesity. Conclusion: These results validate the use of Solanum nigrum in controlling obesity.

Keywords: solanum nigrum, High fat diet, phytocompounds, obesity

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Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

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The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

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Authors: Hagos Gebrehiwet Bahta

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Asmara, the capital city of Eritrea, is facing a sanitation challenge because the city discharges its wastewater to the environment without any kind of treatment. The aim of this research is to conduct a pre-feasibility study of using constructed wetlands in the peri-urban areas of Asmara for wastewater treatment and reuse. It was found that around 15,000 m³ of wastewater is used daily for agricultural activities, and products are sold in the city's markets, which are claimed to cause some health effects. In this study, three potential sites were investigated around Mai-Bela and an optimum location was selected on the basis of land availability, topography, and geotechnical information. Some types of local microphytes that can be used in constructed wetlands have been identified and documented for further studies. It was found that subsurface constructed wetlands can provide a sufficient pollutant removal with careful planning and design. Following the feasibility study, a preliminary design of screening, grit chamber and subsurface constructed wetland was prepared and cost estimation was done. In the cost estimation part, the filter media was found to be the most expensive part and consists of around 30% percent of the overall cost. The city wastewater drainage runs in two directions and the selected site is located in the southern sub-system, which only carries sewage (separate system). The wastewater analysis conducted particularly around this area (Sembel) indicates high heavy metal levels and organic concentrations, which reveals that there is a high level of industrial pollution in addition to the domestic sewage.

Keywords: agriculture, constructed wetland, Mai-Bela, wastewater reuse

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Authors: Ece Kaya

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Industrial heritage reflects the traces of an industrial past that have contributed to the economic development of a country. This heritage should be included within the scope of preservation to remind of and to connect the city and its inhabitants to the past. Through adaptive conservation, industrial heritage can be reintroduced into contemporary urban life, with suitable functions and unique identities sustained. The conservation of industrial heritage should protect the material fabric of such heritage and maintain its cultural significance. Emphasising the historical and cultural significance of industrial areas, this research argues that industrial heritage is primarily impacted by political and economic thinking rather than by informed heritage and conservation issues. Waterfront redevelopment projects create similar landscapes around the world, transforming industrial identities and cultural significances. In the case of The Rocks and Darling Harbour, the goal of redevelopment was the creation of employment opportunities, and the provision of places to work, live and shop, through tourism promoted by the NSW State Government. The two case study areas were pivotal to the European industrial development of Sydney. Sydney Cove was one of the largest commercial wharves used to handle cargo in Australia. This paper argues, together with many historians, planners and heritage experts, that these areas have not received the due diligence deserved in regards to their significance to the industrial history of Sydney and modern Australia.

Keywords: industrial heritage, post-industrial city, transformation of waterfronts, tourism, consumption

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Authors: Supannee Chaiumporn

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This article is to introduce the meaning and form of social quality moving process as indicated by members of two suburb communities with different social and cultural contexts. The form of social quality moving process is very significant for the community and social development, because it will make the people living together with sustainable happiness. This is a qualitative study involving 30 key-informants from two suburb communities. Data were collected though key-informant interviews, and analyzed using logical content description and descriptive statistics. This research found that on the social quality component, the people in both communities stressed the procedure for social quality-making. This includes the generousness, sharing and assisting among people in the communities. These practices helped making people to live together with sustainable happiness. Living as a family or appear to be a family is the major social characteristic of these two communities. This research also found that form of social quality’s moving process of both communities stress relation of human and nature; “nature overpower humans” paradigm and influence of religious doctrine that emphasizes relations among humans. Both criteria make the form of social’s moving process simple, adaptive to nature and caring for opinion sharing and understanding among each other before action. This form of social quality’s moving process is composed of 4 steps; (1) awareness building, (2) motivation to change, (3) participation from every party concerned (4) self-reliance.

Keywords: social quality, form of social quality moving process, happiness, different social and cultural context

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Authors: Shuo Mu, Guangzhi Jiang, Jinsa Chen

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The analysis of Indel for RNA sequencing of clinical samples is easily affected by sequencing experiment errors and software selection. In order to improve the efficiency and accuracy of analysis, we developed an automatic reporting system for Indel recognition and annotation based on image snapshot of transcriptome reads alignment. This system includes sequence local-assembly and realignment, target point snapshot, and image-based recognition processes. We integrated high-confidence Indel dataset from several known databases as a training set to improve the accuracy of image processing and added a bioinformatical processing module to annotate and filter Indel artifacts. Subsequently, the system will automatically generate data, including data quality levels and images results report. Sanger sequencing verification of the reference Indel mutation of cell line NA12878 showed that the process can achieve 83% sensitivity and 96% specificity. Analysis of the collected clinical samples showed that the interpretation accuracy of the process was equivalent to that of manual inspection, and the processing efficiency showed a significant improvement. This work shows the feasibility of accurate Indel analysis of clinical next-generation sequencing (NGS) transcriptome. This result may be useful for RNA study for clinical samples with microsatellite instability in immunotherapy in the future.

Keywords: automatic reporting, indel, next-generation sequencing, NGS, transcriptome

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Authors: Paloma Mendes Saldanha

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Access to information is a prerequisite for democracy while also guiding the material construction of fundamental rights. The exercise of citizenship requires knowing, understanding, questioning, advocating for, and securing rights and responsibilities. In other words, it goes beyond mere active electoral participation and materializes through awareness and the struggle for rights and responsibilities in the various spaces occupied by the population in their daily lives. In times of hyper-cultural connectivity, active citizenship is shaped through ethical trust processes, most often established between humans and algorithms. Automated decisions, so prevalent in various everyday situations, such as purchase preference predictions, virtual voice assistants, reduction of accidents in autonomous vehicles, content removal, resume selection, etc., have already found their place as a normalized discourse that sometimes does not reveal or make clear what violations of fundamental rights may occur when algorithmic explainability is lacking. In other words, technological and market development promotes a normalization for the use of automated decisions while silencing possible restrictions and/or breaches of rights through a culturally modeled, unethical, and unexplained trust process, which hinders the possibility of the right to a healthy, transparent, and complete exercise of citizenship. In this context, the article aims to identify the violations caused by the absence of algorithmic explainability in the exercise of citizenship through the construction of an unethical and silent trust process between humans and algorithms in automated decisions. As a result, it is expected to find violations of constitutionally protected rights such as privacy, data protection, and transparency, as well as the stipulation of algorithmic explainability as a fundamental right in the exercise of Brazilian citizenship in the era of virtualization, facing a threefold foundation called trust: culture, rules, and systems. To do so, the author will use a bibliographic review in the legal and information technology fields, as well as the analysis of legal and official documents, including national documents such as the Brazilian Federal Constitution, as well as international guidelines and resolutions that address the topic in a specific and necessary manner for appropriate regulation based on a sustainable trust process for a hyperconnected world.

Keywords: artificial intelligence, ethics, citizenship, trust

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Authors: Mimoun Melliti

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In the wake of the global pandemic, educational systems worldwide faced unprecedented challenges and had to swiftly adapt to new conditions. This necessitated a fundamental shift in assessment processes, as traditional in-person exams became impractical. The present paper aims to investigate how educational systems have adapted to the new conditions imposed by the outbreak of the pandemic. This paper serves as a case study documenting the various decisions, conditions, experiments, and outcomes associated with transitioning the assessment processes of a higher education institution to a fully online format. The participants of this study consisted of 4666 students from health, engineering, science, and humanities disciplines, who were enrolled in general English (Eng101/104) and English for specific purposes (Eng102/113) courses at a preparatory year institution in Saudi Arabia. The findings of this study indicate that online assessment can be effectively implemented given the fulfillment of specific requirements. These prerequisites encompass the presence of competent staff, administrative flexibility, and the availability of necessary infrastructure and technological support. The significance of this case study lies in its comprehensive description of the various steps and measures undertaken to adapt to the "new normal" situation. Furthermore, it evaluates the impact of these measures and offers detailed recommendations for potential similar future scenarios.

Keywords: hybrid learning, testing, adaptive teaching, EFL

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Authors: Roseline Oghogho Osaseri, Osaseri E. I.

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Lassa fever is an epidemic hemorrhagic fever caused by the Lassa virus, an extremely virulent arena virus. This highly fatal disorder kills 10% to 50% of its victims, but those who survive its early stages usually recover and acquire immunity to secondary attacks. One of the major challenges in giving proper treatment is lack of fast and accurate diagnosis of the disease due to multiplicity of symptoms associated with the disease which could be similar to other clinical conditions and makes it difficult to diagnose early. This paper proposed an Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Lass Fever. In the design of the diagnostic system, four main attributes were considered as the input parameters and one output parameter for the system. The input parameters are Temperature on admission (TA), White Blood Count (WBC), Proteinuria (P) and Abdominal Pain (AP). Sixty-one percent of the datasets were used in training the system while fifty-nine used in testing. Experimental results from this study gave a reliable and accurate prediction of Lassa fever when compared with clinically confirmed cases. In this study, we have proposed Lassa fever diagnostic system to aid surgeons and medical healthcare practictionals in health care facilities who do not have ready access to Polymerase Chain Reaction (PCR) diagnosis to predict possible Lassa fever infection.

Keywords: anfis, lassa fever, medical diagnosis, soft computing

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Authors: Mariam A. Abu-Alim

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The purpose of this study was to validate muscle activation amplitudes of two field base dynamic balance tests that are used as strengthen and motor control exercises too in the activation of selected hip and knee stabilizer muscles. Methods: Eighteen college-age females students (21±2 years; 65.6± 8.7 kg; 169.7±8.1 cm) who participated at least for 30 minutes in physical activity most days of the week volunteered. The wireless BIOPAC (MP150, BIOPAC System. Inc, California, USA) surface electromyography system was used to validate the activation of the Gluteus Medius and the Adductor Magnus of hip stabilizer muscles; and the Hamstrings, Quadriceps, and the Gastrocnemius of the knee stabilizer muscles. Surface electrodes (EL 503, BIOPAC, System. Inc) connected to dual wireless EMG BioNormadix Transmitters were place on selected muscles of participants dominate side. Manual muscle testing was performed to obtain the maximal voluntary isometric contraction (MVIC) in which all collected muscle activity data during the three reaching direction: anterior, posteromedial, posterolateral of the Star Excursion Balance Test (SEBT) and the Y-balance Test (YBT) data could be normalized. All participants performed three trials for each reaching direction of the SEBT and the YBT. The domanial leg trial for each participant was selected for analysis which was also the standing leg. Results: the selected hip stabilizer muscles (Gluteus Medius, Adductor Magnus) were both greater than 100%MVIC during the performance of the SEBT and in all three directions. Whereas, selected knee stabilizer muscles had greater activation 0f 100% MVIC and were significantly more activated during the performance of the YBT test in all three reaching directions. The results showed that the posterolateral and the postmedial reaching directions for both dynamic balance tests had greater activation levels and greater than 200%MVIC for all tested muscles expect of the hamstrings. Conclusion: the results of this study showed that the SEBT and the YBT had validated high levels of muscular activity for the hip and the knee stabilizer muscles; which can be used to represent the improvement, strength, control and the decreasing in the injury levels. Since these selected hip and knee stabilizer muscles, represent 35% of all athletic injuries depending on the type of sport.

Keywords: dynamic balance tests, electromyography, hip stabilizer muscles, nee stabilizer muscles

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Authors: Santosh Kumar Ketham

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Climate change creating most dramatic and destructive consequences, the result is global warming and sea-level rise, flooding coastal cities around the world forming vulnerable situations affecting in multiple ways: environment, economy, social and political. The aim and goal of the research is to develop cities on water. Taking the problem as an opportunity to bring science, engineering, policies and design together to make a resilient and sustainable floating community on water considering existing/new technologies of floating. The quest is to make sustainable habitat on water to live, work, learn and play.  To make sustainable energy generation and storage alongside maintaining balance of land and marine to conserve Ecosystem. The research would serve as a model for sustainable neighbourhoods designed in a modular way and thus can easily extend or re-arranged, to adapt for future socioeconomic realities.  This research paper studies primarily on climate change problems, effects, risks and opportunities. It does so, through analysing existing case studies, books and writings published on coastal cities and understanding its various aspects for making sustainable habitat.

Keywords: floating cities, flexible modular typologies, rising sea levels, sustainable architecture and urbanism

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Authors: Saekil Yun, Sib Sankar Giri, Jin Woo Jun, Hyoun Joong Kim, Sang Guen Kim, Sang Wha Kim, Jung Woo Kang, Se Jin Han, Se Chang Park

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In aquaculture, vaccination is important to control and prevent diseases. In the study, we utilized poly D,L-lactide-co-glycolic acid (PLGA) microparticles (MPs) for encapsulating formalin-killed Aeromonas hydrophila cells. To assess the innate and adaptive immune responses, carps and loaches were used for the experiments. Fish were divided into three groups (A, B, C). Total antigen of 0.1 ml vaccine was adjusted by 2 x 108 CFU and injected via intraperitoneal route. Group A was vaccinated with 0.1 ml of PLGA vaccine, group B was with 0.1 ml of FKC vaccine and group C was with 0.1 ml of sterile PBS. All three groups were challenged with A. hydrophila and challenge dose was lethal dose (LD50). Loaches and carp were then challenged with A. hydrophila at 12 and 20 weeks post vaccination (wpv), and 10 and 14 wpv, respectively, and relative survival rates were calculated. For both fish species, the curve of antibody titer over time was shallower in the PLGA group than the FKC group and the PLGA groups demonstrated higher survival rates at all time-points. In the groups of PLGA-MP, relative mRNA levels of IL-1β, TNF-α, lysozyme C and IgM were significantly upregulated than FKC treated groups. Biodegradable PLGA microparticle vaccine could induce longer immune responses than original FKC vaccines to protect from A. hydrophila infection.

Keywords: PLGA, microparticles, Aeromonas hydrophila, vaccine

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Authors: Shweta Jha, Digambar Darekar, Krishna Kadam

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Major Depressive Disorder (MDD) is one of the most common of psychiatric disorders. It has a wide range of symptoms, aetiologies and risk factors, and these reasons make MDD affect not only the primary patient, but also their family, caregivers and associates; by negatively impacting their self dignity, economic condition and self-confidence. Thus, it is important to help individuals suffering from MDD learn adaptive mechanism and deal effectively with their environment, with that aim this study focused on a comparative therapeutic intervention using Behaviour Activation (BA), Rational Emotive Behaviour Therapy (REBT) and Waiting list control (WLC) for management of MDD. This study apart from enhancing personal skills will also help us understand which therapeutic method would be more beneficial in treating and prolonging relapse in patients with MDD in Indian population. Fifteen individuals following application of inclusion and exclusion criteria were selected as study samples. They were randomly assigned to three treatment groups. Ten sessions of therapy, forty-five minutes each according to the proposed sessions plan were conducted for each group. The individuals selected as samples were re–assessed after 2 months and 6 months post intervention. The overall result showed that individuals treated with BA and REBT showed more improvement in comparison to those in WLC.

Keywords: behaviour activation, major depressive disorder, rational emotive behaviour therapy, therapeutic intervention

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Authors: A. K. Faizah, G. Vadamalai, S. K. Balasundram, W. L. Lim

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Pineapple (Ananas comosus) is a common crop in tropical and subtropical areas of the world. Malaysia once ranked as one of the top 3 pineapple producers in the world in the 60's and early 70's, after Hawaii and Brazil. Moreover, government’s recognition of the pineapple crop as one of priority commodities to be developed for the domestics and international markets in the National Agriculture Policy. However, pineapple industry in Malaysia still faces numerous challenges, one of which is the management of disease and pest. Red tip disease on pineapple was first recognized about 20 years ago in a commercial pineapple stand located in Simpang Renggam, Johor, Peninsular Malaysia. Since its discovery, there has been no confirmation on its causal agent of this disease. The epidemiology of red tip disease is still not fully understood. Nevertheless, the disease symptoms and the spread within the field seem to point toward viral infection. Bioassay test on nucleic acid extracted from the red tip-affected pineapple was done on Nicotiana tabacum cv. Coker by rubbing the extracted sap. Localised lesions were observed 3 weeks after inoculation. Negative staining of the fresh inoculated Nicotiana tabacum cv. Coker showed the presence of membrane-bound spherical particles with an average diameter of 94.25nm under transmission electron microscope. The shape and size of the particles were similar to tospovirus. SDS-PAGE analysis of partial purified virions from inoculated N. tabacum produced a strong and a faint protein bands with molecular mass of approximately 29 kDa and 55 kDa. Partial purified virions of symptomatic pineapple leaves from field showed bands with molecular mass of approximately 29 kDa, 39 kDa and 55kDa. These bands may indicate the nucleocapsid protein identity of tospovirus. Furthermore, a handheld sensor, Greenseeker, was used to detect red tip symptoms on pineapple non-destructively based on spectral reflectance, measured as Normalized Difference Vegetation Index (NDVI). Red tip severity was estimated and correlated with NDVI. Linear regression models were calibrated and tested developed in order to estimate red tip disease severity based on NDVI. Results showed a strong positive relationship between red tip disease severity and NDVI (r= 0.84).

Keywords: pineapple, diagnosis, virus, NDVI

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Authors: Zuzanna Miodonska, Michal Krecichwost, Pawel Badura

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Sigmatism (lisping) is a speech disorder in which sibilant consonants are mispronounced. The diagnosis of this phenomenon is usually based on the auditory assessment. However, the progress in speech analysis techniques creates a possibility of developing computer-aided sigmatism diagnosis tools. The aim of the study is to statistically verify whether specific acoustic features of sibilant sounds may be related to pronunciation correctness. Such knowledge can be of great importance while implementing classifiers and designing novel tools for automatic sibilants pronunciation evaluation. The study covers analysis of various speech signal measures, including features proposed in the literature for the description of normative sibilants realization. Amplitudes and frequencies of three fricative formants (FF) are extracted based on local spectral maxima of the friction noise. Skewness, kurtosis, four normalized spectral moments (SM) and 13 mel-frequency cepstral coefficients (MFCC) with their 1st and 2nd derivatives (13 Delta and 13 Delta-Delta MFCC) are included in the analysis as well. The resulting feature vector contains 51 measures. The experiments are performed on the speech corpus containing words with selected sibilant sounds (/ʃ, ʒ/) pronounced by 60 preschool children with proper pronunciation or with natural pathologies. In total, 224 /ʃ/ segments and 191 /ʒ/ segments are employed in the study. The Mann-Whitney U test is employed for the analysis of stigmatism and normative pronunciation. Statistically, significant differences are obtained in most of the proposed features in children divided into these two groups at p < 0.05. All spectral moments and fricative formants appear to be distinctive between pathology and proper pronunciation. These metrics describe the friction noise characteristic for sibilants, which makes them particularly promising for the use in sibilants evaluation tools. Correspondences found between phoneme feature values and an expert evaluation of the pronunciation correctness encourage to involve speech analysis tools in diagnosis and therapy of sigmatism. Proposed feature extraction methods could be used in a computer-assisted stigmatism diagnosis or therapy systems.

Keywords: computer-aided pronunciation evaluation, sigmatism diagnosis, speech signal analysis, statistical verification

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Authors: Tsetsegmaa A., Bayarsuren B., Altantsetseg Ts.

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To make the best decision on reducing harmful emissions from buses, we need to have a clear understanding of the current state of their actual emissions. The emissions from city buses running on high sulfur fuel, particularly particulate matter (PM) and nitrogen oxides (NOx) from the exhaust gases of conventional diesel engines, have been studied and measured with and without diesel particulate filter (DPF) in Ulaanbaatar city. The study was conducted by using the PEMS (Portable Emissions Measurement System) and gravimetric method in real traffic conditions. The obtained data were used to determine the actual emission rates and to evaluate the effectiveness of the selected particulate filters. Actual road and daily PM emissions from city buses were determined during the warm and cold seasons. A bus with an average daily mileage of 242 km was found to emit 166.155 g of PM into the city's atmosphere on average per day, with 141.3 g in summer and 175.8 g in winter. The actual PM of the city bus is 0.6866 g/km. The concentration of NOx in the exhaust gas averages 1410.94 ppm. The use of DPF reduced the exhaust gas opacity of 24 buses by an average of 97% and filtered a total of 340.4 kg of soot from these buses over a period of six months. Retrofitting an old conventional diesel engine with cassette-type silicon carbide (SiC) DPF, despite the laboriousness of cleaning, can significantly reduce particulate matter emissions. Innovation: First comprehensive road PM and NOx emission dataset and actual road emissions from public buses have been identified. PM and NOx mathematical model equations have been estimated as a function of the bus technical speed and engine revolution with and without DPF.

Keywords: conventional diesel, silicon carbide, real-time onboard measurements, particulate matter, diesel retrofit, fuel sulphur

Procedia PDF Downloads 157

Authors: Rajat Kapoor

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Indian Real Estate sector is the second largest employer after agriculture and is slated to grow at 30 percent over the next decade. Indian cities have shown tumultuous growth since last two decades. With the growing need of infrastructure, it has become inevitable for real estate sector to adopt more organized and transparent system of investment. SPVs such as REITs ensure transparency facilitating accessibility to invest in real estate for those who find it difficult to purchase real estate as an investment option with a realistic income expectation from their investment. RIETs or real estate investment trusts is an instrument of pooling funds similar to that of mutual funds. In a simpler term REIT is an Investment Vehicle in the form a trust which holds & manages large commercial rent¬ earning properties on behalf of investors and distributes most of its profit as dividends. REIT enables individual investors to invest their money in commercial real estate assets in a diversified portfolio and on the other hand provides fiscal liquidity to developers as easy exit option and channel funds for new projects. However, the success REIT is very much dependent on the taxation structure making such models attractive and adaptive enough for both developers and investors to opt for such investment option. This paper is intended to capture an overview of REITs with context to Indian real estate scenario.

Keywords: Indian real estate, real estate infrastructure trusts, urban finance, infrastructure investment trusts

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Authors: Justin Orimisan Ijigbade

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The study was conducted to assess the effect of climate variability on honeybee’s production in Ondo State, Nigeria. Multistage sampling technique was employed to collect the data from 60 beekeepers across six Local Government Areas in Ondo State. Data collected were subjected to descriptive statistics and multiple regression model analyses. The results showed that 93.33% of the respondents were male with 80% above 40 years of age. Majority of the respondents (96.67%) had formal education and 90% produced honey for commercial purpose. The result revealed that 90% of the respondents admitted that low temperature as a result of long hours/period of rainfall affected the foraging efficiency of the worker bees, 73.33% claimed that long period of low humidity resulted in low level of nectar flow, while 70% submitted that high temperature resulted in improper composition of workers, dunes and queen in the hive colony. The result of multiple regression showed that beekeepers’ experience, educational level, access to climate information, temperature and rainfall were the main factors affecting honey bees production in the study area. Therefore, beekeepers should be given more education on climate variability and its adaptive strategies towards ensuring better honeybees production in the study area.

Keywords: climate variability, honeybees production, humidity, rainfall and temperature

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Authors: R. A. Akande, M. L. Mnisi

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Introduction: Aloe vera (Aloe barbadensis miller) flowers are carried in a large candelabra-like flower-head. Aloe barbadensis miller has been known as a traditional herbal medicine for the treatment of many diseases and sicknesses mainly for skin conditions such as sunburns, cold sores and frostbite. It is also used as a fresh food preservative. The main objective of this study is to determine the antioxidant activity of Aloe barbadensis miller. Methodology: The plant material (3g) was separately extracted with 30 mL of solvent with varying polarities (methanol and ethyl acetate)(technical grade, Merck) in 50ml polyester centrifuge tubes. The tubes was be shaken for 30 minutes on a linear shaker and left over night. The supernatant was filtered using a Whitman No. 1 filter paper before being transferred into pre-weighed glass containers. The solvent was allowed to evaporate under a fan in a room to quantify extraction efficacy. The, tin layer chromatography(TLC) plates were prepared and Pasteur pipette was used for spotting each extractant (methanol and ethyl acetate) on the TLC plates and the plate was developed in saturated TLC tank .and dipped in vanillin sulphuric acid mixture and heated at 110 to detect separate compound .and dipped in DDPH in methanol to detect antioxidant. Expected contribution to knowledge: It was observed that different compounds which interact differently with different solvent such as methanol, ethyl acetate having difference polarities were observed. The yellow spots also observed from the plate dipped in DDPH indicate that Aloe barbadensis miller has antioxidant.

Keywords: antioxidant activity, Aloe barbadensis miller, tin layer chromatography, DDPH

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Authors: Wlodzimierz Ogryczak, Tomasz Sliwinski, Jaroslaw Hurkala, Mariusz Kaleta, Bartosz Kozlowski, Piotr Palka

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Implementation concepts of a decision support system for planning and management of mobile personnel tasks (sales representatives and others) are discussed. Large-scale periodic time-dependent vehicle routing and scheduling problems with complex constraints are solved for this purpose. Complex nonuniform constraints with respect to frequency, time windows, working time, etc. are taken into account with additional fast adaptive procedures for operational rescheduling of plans in the presence of various disturbances. Five individual solution quality indicators with respect to a single personnel person are considered. This paper deals with modeling issues corresponding to the problem and general solution concepts. The research was supported by the European Union through the European Regional Development Fund under the Operational Programme ‘Innovative Economy’ for the years 2007-2013; Priority 1 Research and development of modern technologies under the project POIG.01.03.01-14-076/12: 'Decision Support System for Large-Scale Periodic Vehicle Routing and Scheduling Problems with Complex Constraints.'

Keywords: mobile personnel management, multiple criteria, time dependent, time windows, vehicle routing and scheduling

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Authors: Jean-Philippe Gagnon, Benjamin Saute, Stéphane Boubanga-Tombet

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Infrared thermal imaging is used for a wide range of applications, especially in the combustion domain. However, it is well known that most combustion gases such as carbon dioxide (CO₂), water vapor (H₂O), and carbon monoxide (CO) selectively absorb/emit infrared radiation at discrete energies, i.e., over a very narrow spectral range. Therefore, temperature profiles of most combustion processes derived from conventional broadband imaging are inaccurate without prior knowledge or assumptions about the spectral emissivity properties of the combustion gases. Using spectral filters allows estimating these critical emissivity parameters in addition to providing selectivity regarding the chemical nature of the combustion gases. However, due to the turbulent nature of most flames, it is crucial that such information be obtained without sacrificing temporal resolution. For this reason, Telops has developed a time-resolved multispectral imaging system which combines a high-performance broadband camera synchronized with a rotating spectral filter wheel. In order to illustrate the benefits of using this system to characterize combustion experiments, measurements were carried out using a Telops MS-IR MW on a very simple combustion system: a wood fire. The temperature profiles calculated using the spectral information from the different channels were compared with corresponding temperature profiles obtained with conventional broadband imaging. The results illustrate the benefits of the Telops MS-IR cameras for the characterization of laminar and turbulent combustion systems at a high temporal resolution.

Keywords: infrared, multispectral, fire, broadband, gas temperature, IR camera

Procedia PDF Downloads 132