Search results for: processing programs

Authors: Li Ji, Kaiwei Chu, Shibo Kuang, Aibing Yu

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Hydrocyclones are widely used to classify particles by size in industries such as mineral processing and chemical processing. The particles to be handled usually have a broad range of size distributions and sometimes density distributions, which has to be properly considered, causing challenges in the modelling of hydrocyclone. The combined approach of Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) offers convenience to model particle size/density distribution. However, its direct application to hydrocyclones is computationally prohibitive because there are billions of particles involved. In this work, a CFD-DEM model with the concept of the coarse-grained (CG) model is developed to model the solid-fluid flow in a hydrocyclone. The DEM is used to model the motion of discrete particles by applying Newton’s laws of motion. Here, a particle assembly containing a certain number of particles with same properties is treated as one CG particle. The CFD is used to model the liquid flow by numerically solving the local-averaged Navier-Stokes equations facilitated with the Volume of Fluid (VOF) model to capture air-core. The results are analyzed in terms of fluid and solid flow structures, and particle-fluid, particle-particle and particle-wall interaction forces. Furthermore, the calculated separation performance is compared with the measurements. The results obtained from the present study indicate that this approach can offer an alternative way to examine the flow and performance of hydrocyclones

Keywords: computational fluid dynamics, discrete element method, hydrocyclone, multiphase flow

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Authors: Chumki Payun, Bidisha Som

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The Mising language, spoken by the Mising community in Assam, belongs to the Tibeto-Burman family of languages. This is one of the smaller languages of the region and is facing endangerment due to the dominance of the larger languages, like Assamese. The language is spoken in close in-group scenarios and is gradually losing ground to the dominant languages, partly also due to the education setup where schools use only dominant languages. While there are a number of factors for the current contemporary status of the language, and those can be studied using sociolinguistic tools, the current work aims to contribute to the understanding of language attrition through language processing in order to establish if the effect of second language dominance is more than mere ‘usage’ patterns and has an impact on cognitive strategies. When bilingualism spreads widely in society and results in a language shift, speakers perform people often do better in their second language (L2) than in their first language (L1) across a variety of task settings, in both comprehension and production tasks. This phenomenon was investigated in the case of Mising-Assamese bilinguals, using a picture naming task, in two districts of Jorhat and Tinsukia in Assam, where the relative dominance of L2 is slightly different. This explorative study aimed to investigate if the L2 dominance is visible in their performance and also if the pattern is different in the two different places, thus pointing to the degree of language loss in this case. The findings would have implications for native language education, as education in one’s mother tongue can help reverse the effect of language attrition helping preserve the traditional knowledge system. The hypothesis was that due to the dominance of the L2, subjects’ performance in the task would be better in Assamese than that of Missing. The experiment: Mising-Assamese bilingual participants (age ranges 21-31; N= 20 each from both districts) had to perform a picture naming task in which participants were shown pictures of familiar objects and asked to name them in four scenarios: (a) only in Mising; (b) only in Assamese; (c) a cued mix block: an auditory cue determines the language in which to name the object, and (d) non-cued mix block: participants are not given any specific language cues, but instructed to name the pictures in whichever language they feel most comfortable. The experiment was designed and executed using E-prime 3.0 and was conducted responses were recorded using the help of a Chronos response box and was recorded with the help of a recorder. Preliminary analysis reveals the presence of dominance of L2 over L1. The paper will present a comparison of the response latency, error analysis, and switch cost in L1 and L2 and explain the same from the perspective of language attrition.

Keywords: bilingualism, language attrition, language processing, Mising language.

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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: Cem Çindaş, Serkan Şimşek

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In this paper, the study and design of a 3-dB 90° directional coupler operating in the S-band is proposed. The coupler employs symmetrical multi-section coupled lines designed in a stripline technique. Design is realized in AWR Design Environment and CST Microwave Studio. Using these two programs played a key role in attaining outcomes swiftly and precisely. The simulation results show that the coupler maintains amplitude consistency within ± 0.3 dB, isolation and reflection losses better than 16 dB, and phase difference between two output ports of 88º±0.6˚ in the 1.7 – 4.35 GHz range. This simulation results indicate an improvement is achieved in fractional bandwidth (FBW) performance around the center frequency of f0 = 3 GHz.

Keywords: coupled stripline, directional coupler, multi-section coupler, symmetrical coupler

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Authors: Emmanuel Ukpe, S. M. F. D. Syed Mustapha

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Trust in an organization has been perceived as one of the key factors behind knowledge sharing, mainly in an unstructured work environment. In an informal working environment, to instill trust among individuals is a challenge and even more in the virtual environment. The study has contributed in developing the framework for building trust in an unstructured organization in performing knowledge sharing in a virtual environment. The artifact called KAPE (Knowledge Acquisition, Processing, and Exchange) was developed for knowledge sharing for the informal organization where the framework was incorporated. It applies to Cassava farmers to facilitate knowledge sharing using web-based platform. A survey was conducted; data were collected from 382 farmers from 21 farm communities. Multiple regression technique, Cronbach’s Alpha reliability test; Tukey’s Honestly significant difference (HSD) analysis; one way Analysis of Variance (ANOVA), and all trust acceptable measures (TAM) were used to test the hypothesis and to determine noteworthy relationships. The results show a significant difference when there is a trust in knowledge sharing between farmers, the ones who have high in trust acceptable factors found in the model (M = 3.66 SD = .93) and the ones who have low on trust acceptable factors (M = 2.08 SD = .28), (t (48) = 5.69, p = .00). Furthermore, when applying Cognitive Expectancy Theory, the farmers with cognitive-consonance show higher level of trust and satisfaction with knowledge and information from KAPE, as compared with a low level of cognitive-dissonance. These results imply that the adopted trust model KAPE positively improved knowledge sharing activities in an informal environment amongst rural farmers.

Keywords: trust, knowledge, sharing, knowledge acquisition, processing and exchange, KAPE

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Authors: Ese Urhie, Olabisi Popoola, Obindah Gershon, Olabanji Ewetan

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Modern agriculture involves the use of improved tools and equipment (instead of crude and ineffective tools) like tractors, hand operated planters, hand operated fertilizer drills and combined harvesters - which increase agricultural productivity. Farmers in Nigeria still have huge potentials to enhance their productivity. The study argues that the increase in agricultural output due to increased productivity, orchestrated by modern agriculture will promote forward linkages and opportunities in the processing sub-sector; both the manufacturing of machines and the processing of raw materials. Depending on existing incentives, foreign investment could be attracted to augment local investment in the sector. The availability of raw materials in large quantity – which prices are competitive – will attract investment in other industries. In addition, potentials for backward linkages will also be created. In a nutshell, adopting the unbalanced growth theory in favour of the agricultural sector could engender industrialization in a country with untapped potentials. The paper highlights the numerous potentials of modern agriculture that are yet to be tapped in Nigeria and also provides a theoretical analysis of how the realization of such potentials could promote industrialization in the country. The study adopts the Lewis’ theory of structural–change model and Hirschman’s theory of unbalanced growth in the design of the analytical framework. The framework will be useful in empirical studies that will guide policy formulation.

Keywords: modern agriculture, industrialization, structural change model, unbalanced growth

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Authors: Wang Jianguo, Ding Xiao, Liu Dong, Wang Haiping, Yang Yanhui, Hu Yang

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The hot deformation behavior of Inconel 718 alloy was studied by uniaxial compression tests under the deformation temperature of 940~1040℃ and strain rate of 0.001-10s⁻¹. The double cone compression (DCC) tests develop strains range from 30% to the 79% strain including all intermediate values of stains at different temperature (960~1040℃). DCC tests were simulated by finite element software which shown the strain and strain rates distribution. The result shows that the peak stress level of the alloy decreased with increasing deformation temperature and decreasing strain rate, which could be characterized by a Zener-Hollomon parameter in the hyperbolic-sine equation. The characterization method of hot processing window containing recrystallization volume fraction and average grain size was proposed for double cone compression test of uniform coarse grain, mixed crystal and uniform fine grain double conical specimen in hydraulic press and screw press. The results show that uniform microstructures can be obtained by low temperature with high deformation followed by high temperature with small deformation on the hydraulic press and low temperature, medium deformation, multi-pass on the screw press. The two methods were applied in industrial forgings process, and the forgings with uniform microstructure were obtained successfully.

Keywords: inconel 718 superalloy, hot processing windows, double cone compression, uniform microstructure

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Authors: K. Uyanga, W. Daoud

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Hydrogels have attracted much academic and industrial attention due to their unique properties and potential biomedical and non-biomedical applications. Limitations on extending their applications have resulted from the synthesis of hydrogels using toxic materials and complex irreproducible processing techniques. In order to promote environmental sustainability, hydrogel efficiency, and wider application, this study focused on the synthesis of composite hydrogels matrices from an edible non-toxic crosslinker-citric acid (CA) using a simple low energy processing method based on carboxymethyl cellulose (CMC) and chitosan (CSN) natural polymers. Composite hydrogels were developed by chemical crosslinking. The results demonstrated that CMC:2CSN:CA exhibited good performance properties and super-absorbency 21× its original weight. This makes it promising for biomedical applications such as chronic wound healing and regeneration, next generation skin substitute, in situ bone regeneration and cell delivery. On the other hand, CMC:CSN:CA exhibited durable well-structured internal network with minimum swelling degrees, water absorbency, excellent gel fraction, and infra-red reflectance. These properties make it a suitable composite hydrogel matrix for warming effect and controlled and efficient release of loaded materials. CMC:2CSN:CA and CMC:CSN:CA composite hydrogels developed also exhibited excellent chemical, morphological, and thermal properties.

Keywords: citric acid, fumaric acid, tartaric acid, zinc nitrate hexahydrate

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Authors: Huei Lin Lee, Wee Sim Choo

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The effects of blanching, boiling and steaming on the ascorbic acid content, total phenolic content and colour in cauliflower (Brassica oleraceavar. Botrytis) was investigated. It was found that blanching was the best thermal processing to be applied on cauliflower compared to boiling and steaming processes. Blanching and steaming processes on cauliflower retained most of the ascorbic acid content (AAC) compared to those of boiling. As for the total phenolic content (TPC), blanching process retained a higher TPC in cauliflower compared to those of boiling and steaming processes. There were no significant differences between the TPC of boiled and steamed cauliflowers. As for the colour measurement, there were no significant differences in the colour of the cauliflower at different lead time (after processing to the point of consumption) of 30 minutes interval up to 3 hours but there were slight variations in L*, a*, and b* values among the thermal processed cauliflowers (blanched, boiled and steamed). The cauliflowers in this study were found to give a desirable white colour (L* value in the range of 77-83) in all the three thermal processes (blanching, boiling and steaming). There was no significant difference on the effect of lead time (30-minutes interval up to 3 hours) in raw and all the three thermal processed (blanched, boiled and steamed) cauliflowers.

Keywords: ascorbic acid, cauliflower, colour, phenolics

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Authors: Chiung-Hua Chan, Fang-Yuan Chang, Li-Chi Huang

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Stroke patients received regular rehabilitation therapy have measurable advancement in muscle strength, balance, control upper and lower physical activity, walking speed and endurance. This study aimed to investigate the relationship between increases in bedside rehabilitation time and the function of activities and daily living (ADL) in stroke patients. The study was quasi-experimental research design and randomized sampling. The researcher collected 12 stroke patients of stroke patients transferred to rehabilitation ward unit of a medical center during 1 January to 31 March 2017. All participants then were assigned to case group and control group. Data collection was through direct observation of assessment ADL of stroke patients by researchers on Day 1. Case group received regular rehabilitation, exercises in increase of bedside rehabilitation schedules exercise programs by ward nurses. Bedside rehabilitation exercise content with physical, functional and linguistic frequency and time, Control group only give routine rehabilitation schedule care. This was a randomized study performed in 12 patients who were stroke patients and transferred to rehabilitation ward unit of a medical center during 1 January to 31 March 2017. First, the researcher explained the purpose and method of the study to the patients or the family members. All participants completed a consent informed before participation. Patients were randomly assigned to a ‘bedside rehabilitation program’ (BRP) group and a control (C) group. The BRP group received bedside rehabilitation schedules exercise programs by ward nurses. while the C group did not. Both groups received routine rehabilitation schedule. The Functional Independence Measure was used to measure outcome at the first, 14th and the 28th day of rehabilitation ward admitted. Data were analyzed using SPSS 22.0. After implementation of standardized ‘‘bedside rehabilitation program’, the results were: (1) the increasing of bedside rehabilitation had significant difference (p<.05) in promotion ADL function of stroke patients (2) the extend time of the bedside rehabilitation has significant difference (p<.05) in promotion ADL function of stroke patients compared with the control group. This study demonstrated that the ‘bedside rehabilitation program’ enhanced the ADL function in stroke patients. The nurses and rehabilitation ward managers need to understand that the extend time and frequency of rehabilitation provide a chance to enhanced the ADL function of stroke patients.

Keywords: stroke, bedside rehabilitation, functional activity, ADL

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Authors: Khalid. M. O. Elmabrok, M. L. Burby, G. G. Nasr

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Flow instability during gas lift operation is caused by three major phenomena – the density wave oscillation, the casing heading pressure and the flow perturbation within the two-phase flow region. This paper focuses on the causes and the effect of flow instability during gas lift operation and suggests ways to control it in order to maximise productivity during gas lift operations. A laboratory-scale two-phase flow system to study the effects of flow perturbation was designed and built. The apparatus is comprised of a 2 m long by 66 mm ID transparent PVC pipe with air injection point situated at 0.1 m above the base of the pipe. This is the point where stabilised bubbles were visibly clear after injection. Air is injected into the water filled transparent pipe at different flow rates and pressures. The behavior of the different sizes of the bubbles generated within the two-phase region was captured using a digital camera and the images were analysed using the advanced image processing package. It was observed that the average maximum bubbles sizes increased with the increase in the length of the vertical pipe column from 29.72 to 47 mm. The increase in air injection pressure from 0.5 to 3 bars increased the bubble sizes from 29.72 mm to 44.17 mm and then decreasing when the pressure reaches 4 bars. It was observed that at higher bubble velocity of 6.7 m/s, larger diameter bubbles coalesce and burst due to high agitation and collision with each other. This collapse of the bubbles causes pressure drop and reverse flow within two phase flow and is the main cause of the flow instability phenomena.

Keywords: gas lift instability, bubbles forming, bubbles collapsing, image processing

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Authors: Prathiksha Kamath, Pratibha Jamkhandi, Prateek Ghanti, Priyanshu Gupta, M. Lakshmi Neelima

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Combining Image Captioning and Visual Question Answering (VQA) tasks have emerged as a new and exciting research area. The image captioning task involves generating a textual description that summarizes the content of the image. VQA aims to answer a natural language question about the image. Both these tasks include computer vision and natural language processing (NLP) and require a deep understanding of the content of the image and semantic relationship within the image and the ability to generate a response in natural language. There has been remarkable growth in both these tasks with rapid advancement in deep learning. In this paper, we present a comprehensive review of recent progress in combining image captioning and visual question-answering (VQA) tasks. We first discuss both image captioning and VQA tasks individually and then the various ways in which both these tasks can be integrated. We also analyze the challenges associated with these tasks and ways to overcome them. We finally discuss the various datasets and evaluation metrics used in these tasks. This paper concludes with the need for generating captions based on the context and captions that are able to answer the most likely asked questions about the image so as to aid the VQA task. Overall, this review highlights the significant progress made in combining image captioning and VQA, as well as the ongoing challenges and opportunities for further research in this exciting and rapidly evolving field, which has the potential to improve the performance of real-world applications such as autonomous vehicles, robotics, and image search.

Keywords: image captioning, visual question answering, deep learning, natural language processing

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Authors: Robin Devillers, Chantal van Dijk

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Children face ambiguities in everyday language use. Particularly ambiguity in pronoun resolution can be challenging, whereas adults can rapidly identify the antecedent of the mentioned pronoun. Two main factors underlie this process, namely the accessibility of the referent and the syntactic cues of the pronoun. After 200ms, adults have converged the accessibility and the syntactic constraints, while relieving cognitive effort by considering contextual cues. As children are still developing their cognitive capacity, they are not able yet to simultaneously assess and integrate accessibility, contextual cues and syntactic information. As such, they fail to identify the correct referent and possibly fixate more on the competitor in comparison to adults. In this study, Dutch while-clauses were used to investigate the interpretation of pronouns by children. The aim is to a) examine the extent to which 7-10 year old children are able to utilise discourse and syntactic information during online and offline sentence processing and b) analyse the contribution of individual factors, including age, working memory, condition and vocabulary. Adult and child participants are presented with filler-items and while-clauses, and the latter follows a particular structure: ‘Anna and Sophie are sitting in the library. While Anna is reading a book, she is taking a sip of water.’ This sentence illustrates the ambiguous situation, as it is unclear whether ‘she’ refers to Anna or Sophie. In the unambiguous situation, either Anna or Sophie would be substituted by a boy, such as ‘Peter’. The pronoun in the second sentence will unambiguously refer to one of the characters due to the syntactic constraints of the pronoun. Children’s and adults’ responses were measured by means of a visual world paradigm. This paradigm consisted of two characters, of which one was the referent (the target) and the other was the competitor. A sentence was presented and followed by a question, which required the participant to choose which character was the referent. Subsequently, this paradigm yields an online (fixations) and offline (accuracy) score. These findings will be analysed using Generalised Additive Mixed Models, which allow for a thorough estimation of the individual variables. These findings will contribute to the scientific literature in several ways; firstly, the use of while-clauses has not been studied much and it’s processing has not yet been identified. Moreover, online pronoun resolution has not been investigated much in both children and adults, and therefore, this study will contribute to adults and child’s pronoun resolution literature. Lastly, pronoun resolution has not been studied yet in Dutch and as such, this study adds to the languages

Keywords: pronouns, online language processing, Dutch, eye-tracking, first language acquisition, language development

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Authors: Sajed Yaghoubnezhad, Sedygheh Rezai

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Background and Aim: Since currently in Iran, students with learning disabilities are identified after entering school, and with the approach to the gap between IQ and academic achievement, the purpose of this study is to design and calculate the content validity of the pre-school screening checklist (5-7) exposed to learning difficulties. Methods: This research is a fundamental study, and in terms of data collection method, it is quantitative research with a descriptive approach. In order to design this checklist, after reviewing the research background and theoretical foundations, cognitive abilities (visual processing, auditory processing, phonological awareness, executive functions, spatial visual working memory and fine motor skills) are considered the basic variables of school learning. The basic items and worksheets of the screening checklist of pre-school students 5 to 7 years old with learning difficulties were compiled based on the mentioned abilities and were provided to the specialists in order to calculate the content validity ratio index. Results: Based on the results of the table, the validity of the CVR index of the background information checklist is equal to 0.9, and the CVR index of the performance checklist of preschool children (5 to7 years) is equal to 0.78. In general, the CVR index of this checklist is reported to be 0.84. The results of this study provide good evidence for the validity of the pre-school sieve screening checklist (5-7) exposed to learning difficulties.

Keywords: checklist, screening, preschoolers, learning difficulties

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Authors: Tabitha Mberi, Tirus Wanyoike, Joseph Sevilla

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The use of Information and Communication Technology (ICT) in Government is gradually becoming a major requirement to transform delivery of services to its stakeholders by improving quality of service and efficiency. In Kenya, the devolvement of government from local authorities to county governments has resulted in many counties adopting online revenue collection systems which can be easily accessed by its stakeholders. Strathmore Research and Consortium Centre (SRCC) implemented a revenue collection system in Taita Taveta, a County in coastal Kenya. It consisted of two systems that are integrated; an online system dubbed “CountyPro” for processing county services such as Business Permit applications, General Billing, Property Rates Payments and any other revenue streams from the county. The second part was a Point of Sale(PoS) system used by the county revenue collectors to charge for market fees and vehicle parking fees. This study assesses the success and challenges in adoption of the integrated system. Qualitative and quantitative data collection methods were used to collect data on the adoption of the system with the researcher using focus groups, interviews, and questionnaires to collect data from various users of the system An analysis was carried out and revealed that 87% of the county revenue officers who are situated in county offices describe the system as efficient and has made their work easier in terms of processing of transactions for customers.

Keywords: e-government, counties, information technology, online system, point of sale

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Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Jairson Barbosa Rodrigues, Paulo Romero Martins Maciel, Germano Crispim Vasconcelos

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This paper presents an investigation of the performance impacts regarding the variation of five factors (input data size, node number, cores, memory, and disks) when applying a distributed implementation of Naïve Bayes for text classification of a large Corpus on the Spark big data processing framework. Problem: The algorithm's performance depends on multiple factors, and knowing before-hand the effects of each factor becomes especially critical as hardware is priced by time slice in cloud environments. Objectives: To explain the functional relationship between factors and performance and to develop linear predictor models for time and cost. Methods: the solid statistical principles of Design of Experiments (DoE), particularly the randomized two-level fractional factorial design with replications. This research involved 48 real clusters with different hardware arrangements. The metrics were analyzed using linear models for screening, ranking, and measurement of each factor's impact. Results: Our findings include prediction models and show some non-intuitive results about the small influence of cores and the neutrality of memory and disks on total execution time, and the non-significant impact of data input scale on costs, although notably impacts the execution time.

Keywords: big data, design of experiments, distributed machine learning, natural language processing, spark

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Authors: Arth J. Shah, Madhu R. Kamble

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Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it’s becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier.

Keywords: Kolmogorov Arnold networks, multilayer perceptron, pop noise, voice liveness detection

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Authors: Tahsina Sadeque Kapil Ahmed

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Context: The tobacco epidemic is one of the biggest public health threats the world has ever faced. Tobacco use is a widespread phenomenon in Bangladesh, and that causes numerous deaths and disabilities in a year. The studies conducted elsewhere have strengthened the evidence that mass media campaigns conducted in the context of comprehensive tobacco control programs can promote quitting and reduce smoking, as well as smokeless tobacco prevalence. Awareness building campaigns in mass-media against tobacco use should be prioritized more, and this paper will be an initiative towards enhancing mass-media’s role in controlling tobacco in Bangladesh. Objective: the main objective of this study is to investigate the role of mass-media in controlling tobacco in Bangladesh. Methods: This is a qualitative study and both primary, as well as secondary data were used where information gathered through the Key Informant Interviews (KIIs) and media contents. The employees of media houses (five national papers, two online news portals and six TV channels) were selected as study respondent. Media Content Analysis is used through the broad range of ‘texts’ from transcripts of interviews and discussions along with the materials like reports, footages, advertisements, talk-shows, articles etc. Results: The study result documented several opinions of discussants where Mass media was found to play a strong role in support of the amended tobacco control law and its implication that could be created public support against tobacco farming, exposing to companies’ tactics and other tobacco control activities. The study results also revealed that in controlling tobacco supply and demand effectively, media has been assisting the government and anti-tobacco activities productively. Majority of the Key Informants opined spontaneously on tobacco control program publicity, organizational interference, and influence of other activities on media. They also emphasized role of media for activities of anti-tobacco organizations, awareness building actions, popularization of tobacco control law and its amendment. Conclusion and Recommendation: The study shows evidence that mass media coverage of tobacco control issues is influencing the context of comprehensive tobacco control programs. To reduce tobacco consumption, along with strict enforcement efforts, media should be used to assist with the implementation of the tobacco control law. A sustained nationwide campaign to educate the masses against the dangers of smoking and smokeless tobacco is needed, and media can play an important role in creating further awareness about the dangers associated with tobacco consumption.

Keywords: Bangladesh media, mass media, role of media, tobacco control

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Authors: Kedar Baral

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This study was carried out in Mustang, Kaski, Tanahun, Baitadi, and Jhapa districts of Nepal. The study explored the spatial and temporal pattern of HWC, socio economic factors associated with it, impacts of conflict on life / livelihood of people and survival of wildlife species, and impact of climate change and forest fire onHWC. Study also evaluated people’s attitude towards wildlife conservation and assessed relevant policies and programs. Questionnaire survey was carried out with the 250 respondents, and both socio-demographic and HWC related information werecollected. Secondary information were collected from Divisional Forest Offices and Annapurna Conservation Area Project.HWC events were grouped by season /months/sites (forest type, distances from forest, and settlement), and the coordinates of the events were exported to ArcGIS. Collected data were analyzed using descriptive statistics in Excel and R Program. A total of 1465 events were recorded in 5 districts during 2015 and 2019. Out of that, livestock killing, crop damage, human attack, and cattle shed damage events were 70 %, 12%, 11%, and 7%, respectively. Among 151 human attack cases, 23 people were killed, and 128 were injured. Elephant in Terai, common leopard and monkey in Middle Mountain, and snow leopard in high mountains were found as major problematic animals. Common leopard attacks were found more in the autumn, evening, and on human settlement area. Whereas elephant attacks were found higher in winter, day time, and on farmland. Poor people farmers were found highly victimized, and they were losing 26% of their income due to crop raiding and livestock depredation. On the other hand, people are killing many wildlife in revenge, and this number is increasing every year. Based on the people's perception, climate change is causing increased temperature and forest fire events and decreased water sources within the forest. Due to the scarcity of food and water within forests, wildlife are compelled to dwell at human settlement area, hence HWC events are increasing. Nevertheless, more than half of the respondents were found positive about conserving entire wildlife species. Forests outside PAs are under the community forestry (CF) system, which restored the forest, improved the habitat, and increased the wildlife.However, CF policies and programs were found to be more focused on forest management with least priority on wildlife conservation and HWC mitigation. Compensation / relief scheme of government for wildlife damage was found some how effective to manage HWC, but the lengthy process, being applicable to the damage of few wildlife species and highly increasing events made it necessary to revisit. Based on these facts, the study suggest to carry out awareness generation activities to the poor farmers, linking the property of people with the insurance scheme, conducting habitat management activities within CF, promoting the unpalatable crops, improvement of shed house of livestock, simplifying compensation scheme and establishing a fund at the district level and incorporating the wildlife conservation and HWCmitigation programs in CF. Finally, the study suggests to carry out rigorous researches to understand the impacts of current forest management practices on forest, biodiversity, wildlife, and HWC.

Keywords: community forest, conflict mitigation, wildlife conservation, climate change

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Authors: James P. Takona

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In a world that is experiencing sharp digital transformations guided by digital technologies, the potential of technology to drive transformation and evolution in the higher is apparent. Higher education is facing a paradigm shift that exposes susceptibilities and threats to fully online programs in the face of post-Covid-19 trends of commodification. This historical moment is likely to be remembered as a critical turning point from analog to digital degree-focused learning modalities, where the default became the pivot point of competition between higher education institutions. Fall 2020 marks a significant inflection point in higher education as students, educators, and government leaders scrutinize higher education's price and value propositions through the new lens of traditional lecture halls versus multiple digitized delivery modes. Online education has since tiled the way for a pedagogical shift in how teachers teach and students learn. The incremental growth of online education in the west can now be attributed to the increasing patronage among students, faculty, and institution administrators. More often than not, college instructors assume paraclete roles in this learning mode, while students become active collaborators and no longer passive learners. This paper offers valuable discernments into the threats, challenges, and opportunities of a massive digital revolution in servicing degree programs. To view digital instruction and learning demands for instructional practices that revolve around collaborative work, engaging students in learning activities, and an engagement that promotes active efforts to solicit strong connections between course activities and expected learning pace for all students. Appropriate digital technologies demand instructors and students need prior solid skills. Need for the use of digital technology to support instruction and learning, intelligent tutoring offers great promise, and failures at implementing digital learning may not improve outcomes for specific student populations. Digital learning benefits students differently depending on their circumstances and background and those of the institution and/or program. Students have alternative options, access to the convenience of learning anytime and anywhere, and the possibility of acquiring and developing new skills leading to lifelong learning.

Keywords: digi̇tized learning, digital education, collaborative work, high education, online education, digitize delivery

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Authors: Karolina Wieczorek, Sophie Wiliams

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Introduction: Patient data is often collected in Electronic Health Record Systems (EHR) for purposes such as providing care as well as reporting data. This information can be re-used to validate data models in clinical trials or in epidemiological studies. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. Mentioning a disease in a discharge letter does not necessarily mean that a patient suffers from this disease. Many of them discuss a diagnostic process, different tests, or discuss whether a patient has a certain disease. The COVID-19 dataset in this study used natural language processing (NLP), an automated algorithm which extracts information related to COVID-19 symptoms, complications, and medications prescribed within the hospital. Free-text patient clinical patient notes are rich sources of information which contain patient data not captured in a structured form, hence the use of named entity recognition (NER) to capture additional information. Methods: Patient data (discharge summary letters) were exported and screened by an algorithm to pick up relevant terms related to COVID-19. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. A list of 124 Systematized Nomenclature of Medicine (SNOMED) Clinical Terms has been provided in Excel with corresponding IDs. Two independent medical student researchers were provided with a dictionary of SNOMED list of terms to refer to when screening the notes. They worked on two separate datasets called "A” and "B”, respectively. Notes were screened to check if the correct term had been picked-up by the algorithm to ensure that negated terms were not picked up. Results: Its implementation in the hospital began on March 31, 2020, and the first EHR-derived extract was generated for use in an audit study on June 04, 2020. The dataset has contributed to large, priority clinical trials (including International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) by bulk upload to REDcap research databases) and local research and audit studies. Successful sharing of EHR-extracted datasets requires communicating the provenance and quality, including completeness and accuracy of this data. The results of the validation of the algorithm were the following: precision (0.907), recall (0.416), and F-score test (0.570). Percentage enhancement with NLP extracted terms compared to regular data extraction alone was low (0.3%) for relatively well-documented data such as previous medical history but higher (16.6%, 29.53%, 30.3%, 45.1%) for complications, presenting illness, chronic procedures, acute procedures respectively. Conclusions: This automated NLP algorithm is shown to be useful in facilitating patient data analysis and has the potential to be used in more large-scale clinical trials to assess potential study exclusion criteria for participants in the development of vaccines.

Keywords: automated, algorithm, NLP, COVID-19

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Authors: Aroob Binhimd, Lyan Sayoti, Rana Almansour

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In recent years, artificial intelligence has grown drastically. This has led to the growth of educational programs to help students in solving educational problems and assist them in understanding certain topics. The purpose of this report is to investigate the Mathway application. Mathway is a mathematics software that teaches students how to solve and handle mathematical issues. The app allows students to insert questions manually on the platform or take a picture of the question, and then they get an answer to this mathematical question. It helps students enhance their performance in mathematics. This app can also be used to verify or check if their answers are correct. The report will include a questionnaire to collect data and analyze the users of this application.

Keywords: artificial intelligence, Mathway, mathematics, mathematical problems

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Authors: Muhammad Arshad, M. Sufian, Muhammad D. Gogi, A. Aslam

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The transgenic cotton expressing Bacillus thuringiensis (Bt) provides an effective control of Helicoverpa armigera, a most damaging pest of the cotton crop. However, Bt cotton may not be the optimal solution owing to the selection pressure of Cry toxins. As Bt cotton express the insecticidal proteins throughout the growing seasons, there are the chances of resistance development in the target pests. A regular monitoring and surveillance of target pest’s baseline susceptibility to Bt Cry toxins is crucial for early detection of any resistance development. The present study was conducted to monitor the changes in the baseline susceptibility of the field population of H. armigera to Bt Cry1Ac toxin. The field-collected larval populations were maintained in the laboratory on artificial diet and F1 generation larvae were used for diet incorporated diagnostic studies. The LC₅₀ and MIC₅₀ were calculated to measure the level of resistance of population as a ratio over susceptible population. The monitoring results indicated a significant difference in the susceptibility (LC₅₀) of H. armigera for first, second, third and fourth instar larval populations sampled from different cotton growing areas over the study period 2016-17. The variations in susceptibility among the tested insects depended on the age of the insect and susceptibility decreased with the age of larvae. The overall results show that the average resistant ratio (RR) of all field-collected populations (FSD, SWL, MLT, BWP and DGK) exposed to Bt toxin Cry1Ac ranged from 3.381-fold to 7.381-fold for 1st instar, 2.370-fold to 3.739-fold for 2nd instar, 1.115-fold to 1.762-fold for 3rd instar and 1.141-fold to 2.504-fold for 4th instar, depicting maximum RR from MLT population, whereas minimum RR for FSD and SWL population. The results regarding moult inhibitory concentration of H. armigera larvae (1-4th instars) exposed to different concentrations of Bt Cry1Ac toxin indicated that among all field populations, overall Multan (MLT) and Bahawalpur (BWP) populations showed higher MIC₅₀ values as compared to Faisalabad (FSD) and Sahiwal (SWL), whereas DG Khan (DGK) population showed an intermediate moult inhibitory concentrations. This information is important for the development of more effective resistance monitoring programs. The development of Bt Cry toxins baseline susceptibility data before the widespread commercial release of transgenic Bt cotton cultivars in Pakistan is important for the development of more effective resistance monitoring programs to identify the resistant H. armigera populations.

Keywords: Bt cotton, baseline, Cry1Ac toxins, H. armigera

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Authors: S. Djaziri, F. Sket, A. Hynowska, S. Milenkovic

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The use of Fe-Al based intermetallics as an alternative to Cr/Ni based stainless steels is very promising for industrial applications that use critical raw materials parts under extreme conditions. However, the development of advanced Fe-Al based intermetallics with appropriate mechanical properties presents several challenges that involve appropriate processing and microstructure control. A processing strategy is being developed which aims at producing a net-shape porous Fe-based preform that is infiltrated with molten Al or Al-alloy. In the present work, porous Fe-based preforms produced by two different methods (selective laser melting (SLM) and Kochanek-process (KE)) are studied during infiltration with molten aluminum. In the objective to elucidate the mechanisms underlying the formation of Fe-Al intermetallic phases during infiltration, an in-house furnace has been designed for in situ observation of infiltration at synchrotron facilities combining x-ray radiography (XR) and x-ray diffraction (XRD) techniques. The feasibility of this approach has been demonstrated, and information about the melt flow front propagation has been obtained. In addition, reactive infiltration has been achieved where a bi-phased intermetallic layer has been identified to be formed between the solid Fe and liquid Al. In particular, a tongue-like Fe₂Al₅ phase adhering to the Fe and a needle-like Fe₄Al₁₃ phase adhering to the Al were observed. The growth of the intermetallic compound was found to be dependent on the temperature gradient present along the preform as well as on the reaction time which will be discussed in view of the different obtained results.

Keywords: combined synchrotron radiography and diffraction, Fe-Al intermetallic compounds, in-situ molten Al infiltration, porous solid Fe preforms

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Authors: Albert W. K. Tan

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This research consolidates a comprehensive array of publications from peer-reviewed journals, case studies, and seminar reports focused on reverse logistics and network design. By synthesizing this secondary knowledge, our objective is to identify and articulate key decision factors crucial to reverse logistics network design for e-commerce. Through this exploration, we aim to present a refined mathematical model that offers valuable insights for companies seeking to optimize their reverse logistics operations. The primary goal of this research endeavor is to develop a comprehensive framework tailored to advising organizations and companies on crafting effective networks for their reverse logistics operations, thereby facilitating the achievement of their organizational goals. This involves a thorough examination of various network configurations, weighing their advantages and disadvantages to ensure alignment with specific business objectives. The key objectives of this research include: (i) Identifying pivotal factors pertinent to network design decisions within the realm of reverse logistics across diverse supply chains. (ii) Formulating a structured framework designed to offer informed recommendations for sound network design decisions applicable to relevant industries and scenarios. (iii) Propose a mathematical model to optimize its reverse logistics network. A conceptual framework for designing a reverse logistics network has been developed through a combination of insights from the literature review and information gathered from company websites. This framework encompasses four key stages in the selection of reverse logistics operations modes: (1) Collection, (2) Sorting and testing, (3) Processing, and (4) Storage. Key factors to consider in reverse logistics network design: I) Centralized vs. decentralized processing: Centralized processing, a long-standing practice in reverse logistics, has recently gained greater attention from manufacturing companies. In this system, all products within the reverse logistics pipeline are brought to a central facility for sorting, processing, and subsequent shipment to their next destinations. Centralization offers the advantage of efficiently managing the reverse logistics flow, potentially leading to increased revenues from returned items. Moreover, it aids in determining the most appropriate reverse channel for handling returns. On the contrary, a decentralized system is more suitable when products are returned directly from consumers to retailers. In this scenario, individual sales outlets serve as gatekeepers for processing returns. Considerations encompass the product lifecycle, product value and cost, return volume, and the geographic distribution of returns. II) In-house vs. third-party logistics providers: The decision between insourcing and outsourcing in reverse logistics network design is pivotal. In insourcing, a company handles the entire reverse logistics process, including material reuse. In contrast, outsourcing involves third-party providers taking on various aspects of reverse logistics. Companies may choose outsourcing due to resource constraints or lack of expertise, with the extent of outsourcing varying based on factors such as personnel skills and cost considerations. Based on the conceptual framework, the authors have constructed a mathematical model that optimizes reverse logistics network design decisions. The model will consider key factors identified in the framework, such as transportation costs, facility capacities, and lead times. The authors have employed mixed LP to find the optimal solutions that minimize costs while meeting organizational objectives.

Keywords: reverse logistics, supply chain management, optimization, e-commerce

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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Authors: Laura Rueda-Gensini, Jader Rodríguez, Juan C. Cruz, Carolina Munoz-Camargo

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There is an emerging interest in botanicals and plant extracts for medicinal practices due to their widely reported health benefits. A large variety of phytochemicals found in plants have been correlated with antioxidant, immunomodulatory, and analgesic properties, which makes plant-derived products promising candidates for modulating the progression and treatment of numerous diseases. Non-centrifugal cane sugar (NCS), in particular, has been known for its high antioxidant and nutritional value, but composition-wise variability due to changing environmental and processing conditions have considerably limited its use in the nutraceutical and biomedical fields. This work is therefore aimed at assessing the effect of thermal exposure during NCS production over its bioactive composition and, in turn, its therapeutic value. Accordingly, two modified dehydration methods are proposed that employ: (i) vacuum-aided evaporation, which reduces the necessary temperatures to dehydrate the sample, and (ii) window refractance evaporation, which reduces thermal exposure time. The biochemical composition of NCS produced under these two methods was compared to traditionally-produced NCS by estimating their total polyphenolic and protein content with Folin-Ciocalteu and Bradford assays, as well as identifying the major phenolic compounds in each sample via HPLC-coupled mass spectrometry. Their antioxidant activities were also compared as measured by their scavenging potential of ABTS and DPPH radicals. Results show that the two modified production methods enhance polyphenolic and protein yield in resulting NCS samples when compared to traditional production methods. In particular, reducing employed temperatures with vacuum-aided evaporation demonstrated to be superior at preserving polyphenolic compounds, as evidenced both in the total and individual polyphenol concentrations. However, antioxidant activities were not significantly different between these. Although additional studies should be performed to determine if the observed compositional differences affect other therapeutic activities (e.g., anti-inflammatory, analgesic, and immunoprotective), these results suggest that reducing thermal exposure holds great promise for the production of natural products with enhanced nutritional value.

Keywords: non-centrifugal cane sugar, polyphenolic compounds, thermal processing, antioxidant activity

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Dawit Hoyiso, Abinet Arega, Terefe Markos

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Background: - In spite of all the various programs and strategies to promote the use of research finding there is still gap between theory and practice. Difference in outcomes, health inequalities, and poorly performing health service continue to present a challenge to all nurses. A number of studies from various countries have reported that nurses’ experience of evidence-based practice is low. In Ethiopia there is an information gap on the extent of evidence based nursing practice and its associated factors. Objective: - the study aims to assess the implementation of evidence based nursing practice and associated factors among nurses in Jimma zone public hospitals. Method: - Institution based cross-sectional study was conducted from March 1-30/2015. A total of 333 sampled nurses for quantitative and 8 in-depth interview of key informants were involved in the study. Semi-structured questionnaire was adapted from funk’s BARRIER scale and Friedman’s test. Multivariable Linear regression was used to determine significance of association between dependent and independent variables. Pretest was done on 17 nurses of Bedele hospital. Ethical issue was secured. Result:-Of 333 distributed questionnaires 302 were completed, giving 90.6% response rate. Of 302 participants 245 were involved in EBP activities to different level (from seldom to often). About forty five(18.4%) of the respondents had implemented evidence based practice to low level (sometimes), one hundred three (42 %) of respondents had implemented evidence based practice to medium level and ninety seven (39.6 %) of respondents had implemented evidence based practice to high level(often). The first greatest perceived barrier was setting characteristic (mean score=26.60±7.08). Knowledge about research evidence was positively associated with implementation of evidence based nursing practice (β=0.76, P=0.008). Similarly, Place where the respondent graduated was positively associated with implementation of evidence based nursing practice (β=2.270, P=0.047). Also availability of information resources was positively associated with implementation of evidence based practice (β=0.67, P= 0.006). Conclusion: -Even though larger portion of nurses in this study were involved in evidence-based practice whereas small number of participants had implemented frequently. Evidence-based nursing practice was positively associated with knowledge of research, place where respondents graduated, and the availability of information resources. Organizational factors were found to be the greatest perceived barrier. Intervention programs on awareness creation, training, resource provision, and curriculum issues to improve implementation of evidence based nursing practice by stakeholders are recommended.

Keywords: evidence based practice, nursing practice, research utilization, Ethiopia

Procedia PDF Downloads 95