Search results for: bird song processing

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: 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: Yao Song

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Objectives: We aimed to explore the clinicodemographic characteristics and prognosis of grey zone squamous cell cancer (GZSCC) located in the overlapping or ambiguous area of the oral cavity and oropharynx and to identify valuable factors that would improve its differential diagnosis and prognosis. Methods: Information of GZSCC patients in the Surveillance, Epidemiology, and End Results (SEER) database was compared to patients with an oral cavity (OCSCC) and oropharyngeal (OPSCC) squamous cell carcinomas with corresponding HPV status, respectively. Kaplan-Meier method with log-rank test and multivariate Cox regression analysis were applied to assess associations between clinical characteristics and overall survival (OS). A predictive model integrating age, gender, marital status, HPV status, and staging variables was conducted to classify GZSCC patients into three risk groups and verified internally by 10-fold cross validation. Results: A total of 3318 GZSCC, 10792 OPSCC, and 6656 OCSCC patients were identified. HPV-positive GZSCC patients had the best 5-year OS as HPV-positive OPSCC (81% vs. 82%). However, the 5-year OS of HPV-negative/unknown GZSCC (43%/42%) was the worst among all groups, indicating that HPV status and the overlapping nature of tumors were valuable prognostic predictors in GZSCC patients. Compared with the strategy of dividing GZSCC into two groups by HPV status, the predictive model integrating more variables could additionally identify a unique high-risk GZSCC group with the lowest OS rate. Conclusions: GZSCC patients had distinct clinical characteristics and prognoses compared with OPSCC and OCSCC; integrating HPV status and other clinical factors could help distinguish GZSCC and predict their prognosis.

Keywords: GZSCC, OCSCC, OPSCC, HPV

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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: Yanrong Song, Zikai Dong, Runqin Xu, Jinrong Tian, Kexuan Li

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Nonlinear polarization rotation (NPR) technique has become one of the main techniques to achieve mode-locked fiber lasers for its compactness, implementation, and low cost. In this paper, we demonstrate a compact mode-locked Yb-doped fiber laser based on NPR technique in the all normal dispersion (ANDi) regime. In the laser cavity, there are no physical filter and polarization controller in laser cavity. Mode-locked pulse train is achieved in ANDi regime based on NPR technique. The fiber birefringence induced filtering effect is the mainly reason for mode-locking. After that, an extra 20 m long single-mode fiber is inserted in two different positions, dissipative soliton operation and noise like pulse operations are achieved correspondingly. The nonlinear effect is obviously enhanced in the noise like pulse regime and broadband spectrum generated owing to enhanced stimulated Raman scattering effect. When the pump power is 210 mW, the central wavelength is 1030 nm, and the corresponding 1st order Raman scattering stokes wave generates and locates at 1075 nm. When the pump power is 370 mW, the 1st and 2nd order Raman scattering stokes wave generate and locate at 1080 nm, 1126 nm respectively. When the pump power is 600 mW, the Raman continuum is generated with cascaded multi-order stokes waves, and the spectrum extends to 1188 nm. The total flat spectrum is from 1000nm to 1200nm. The maximum output average power and pulse energy are 18.0W and 14.75nJ, respectively.

Keywords: fiber laser, mode-locking, nonlinear polarization rotation, Raman scattering

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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: 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: Alexa Rakoski, Yun Suk Eo, Cagliyan Kurdak, Priscila F. S. Rosa, Zachary Fisk, Monica Ciomaga Hatnean, Geetha Balakrishnan, Boyoun Kang, Myungsuk Song, Byungki Cho

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Samarium hexaboride (SmB6) is a strongly correlated mixed valence material and Kondo insulator. In the resistance-temperature curve, SmB6 exhibits activated behavior from 4-40 K after the Kondo gap forms. However, below 4 K, the resistivity is temperature independent or weakly temperature dependent due to the appearance of a topologically protected surface state. Current research suggests that the surface of SmB6 is conductive while the bulk is truly insulating, different from conventional 3D TIs (Topological Insulators) like Bi₂Se₃ which are plagued by bulk conduction due to impurities. To better understand why the bulk of SmB6 is so different from conventional TIs, this study employed a new method, called inverted resistance, to explore the lowest temperatures, as well as standard Hall measurements for the rest of the temperature range. In the inverted resistance method, current flows from an inner contact to an outer ring, and voltage is measured outside of this outer ring. This geometry confines the surface current and allows for measurement of the bulk resistivity even when the conductive surface dominates transport (below 4 K). The results confirm that the bulk of SmB6 is truly insulating down to 2 K. Hall measurements on a number of samples show consistent bulk behavior from 4-40 K, but widely varying behavior among samples above 40 K. This is attributed to a combination of the growth process and purity of the starting material, and the relationship between the high and low temperature behaviors is still being explored.

Keywords: bulk transport, Hall effect, inverted resistance, Kondo insulator, samarium hexaboride, topological insulator

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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: Wang Qiaowei, Gao Yujiang

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With the economic growth and rapid urbanization after the reform and openness, some of China's fast-growing cities have demolished former dwellings and built modern residential quarters. The blind, incomplete reference to western modern cities and the one-off construction lacking feedback mechanism have intensified such phenomenon, causing the citizen gradually expanded their living scale with the popularization of car traffic, and the peer-to-peer lifestyle gradually settled. The construction of large-scale commercial centers has caused obstacles to small business around the residential areas, leading to space for residents' interaction has been compressed. At the same time, the advocated Central Business District (CBD) model even leads to the unsatisfactory reconstruction of many historical blocks such as the Hangzhou Southern Song Dynasty Imperial Street. However, the popularity of historical spaces such as Wuzhen and Hongcun also indicates the collective memory and needs of the street space for Chinese residents. The evolution of Shanghai TianZiFang also proves the importance of the motivation of space participants in space construction in the context of the “top-down” construction model in China. In fact, there are frequent occurrences of “reconstruction”, which may redefine the space, in various residential areas. If these activities can be selectively controlled and encouraged, it will be beneficial to activate the public space as well as the residents’ intercourse, so that the traditional Chinese street space can be reconstructed in the context of modern cities.

Keywords: rapid urbanization, traditional street space, space re-construction, bottom-up design

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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: Eun Hui Bae, Sang Yeob Lim, Bongseong Kim, Tae Ryom Oh, Su Hyun Song, Sang Heon Suh, Hong Sang Choi, Eun Mi Yang, Chang Seong Kim, Seong Kwon Ma, Kyung-Do Han, Soo Wan Kim

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Background: Recent hypertension guidelines have recommended lower blood pressure (BP) targets in high-risk patients. However, there are no specific guidelines based on age or systolic and diastolic blood pressure (SBP and DBP, respectively). We aimed to assess the effects of age-related BP on the development of end-stage renal disease (ESRD) in patients with diabetes. Methods: A total of 2,563,870 patients with DM aged >20 years were selected from the Korean National Health Screening Program from 2009 to 2012 and followed up until the end of 2019. Participants were categorized into age and BP groups, and the hazard ratios (HRs) for ESRD were calculated. Results: During a median follow-up of 7.15 years, the incidence rates of ESRD increased with increasing SBP and DBP. The HR for ESRD was the highest in patients younger than 40 years of age with DBP ≥ 100 mmHg. The effect of SBP and DBP on ESRD development was attenuated with age (interaction p-value was <0.0001 for age and SBP and 0.0022 for age and DBP). The subgroup analysis for sex, anti-hypertension medication, and history of chronic kidney disease (CKD) showed higher HRs for ESRD among males younger than 40 years, not taking anti-hypertension medications and CKD compared to those among females older than 40 years, anti-hypertension medication and non-CKD groups. Conclusions: Higher SBP and DBP increase the risk of developing ESRD in patients with diabetes, and in particular, younger individuals face greater risk. Therefore, intensive BP management is warranted in younger patients to prevent ESRD.

Keywords: hypertension, young adult, end-stage renal disease, diabetes mellitus, chronic kidney disease, blood pressure

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Authors: Isabella B. Davidman

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Violence used against Jewish women in both the Eastern European pogroms and during the Nazi era was specifically gendered, targeting their female identity and dignity of womanhood. Not only did these acts of gendered violence dehumanize Jewish women, but they also hurt the Jewish community as a whole. The devastating sexual violence that women endured during the pogroms and the Nazi era caused profound trauma. Out of shame and fear, silence about women’s experiences of sexual abuse manifests in forms that words cannot translate. Women have turned to art and other means of storytelling to convey their female experiences in visual and non-verbal ways. Therefore, this paper aims to address the historical accounts of gendered violence against Jewish women during the pogroms and Nazi era, as well as art that reflects upon the female experience, in order to understand the emotional impact resulting from these events. To analyze the artwork, a feminist analysis was used to understand the intersection of gender with the other systems of inequality, such as systemic anti-semitism, in women’s lives; this ultimately explained the ways in which cultural productions undermine and reinforce the political and social oppression of women by exploring how art confronts the exploitation of women's bodies. By analyzing the art in the context of specific acts of violence, such as public rape, as a strategic weapon, we are able to understand women’s experiences and how these experiences, in turn, challenged their womanhood. Additionally, these atrocities, which often occurred in the public space, were dismissed and forgotten due to the social stigma of rape. In this sense, the experiences of women in pogroms and the Nazi era were both highly unacknowledged and forgotten. Therefore, the art that was produced during those time periods, as well as those after those events, gives voice to the profound silence on the narratives of Jewish women. Sexual violence is a weapon of war used to cause physical and psychological destruction, not only as a product of war. In both the early twentieth-century pogroms and the Holocaust, the sexual violence that Jewish women endured was fundamentally the same: the rape of Jewish women became a focal target in the theater of violence– women were not raped because they were women, but specifically, because they were Jewish women. Although the events of the pogroms and the Holocaust are in the past, the art that serves as testimony to the experience of Jewish women remains an everlasting reminder of the gendered violence that occurred. Even though covert expressions, such as an embroidered image of a bird eating an apple, the artwork gives voice to the many silenced victims of sexualized and gendered violence.

Keywords: gendered violence, holocaust, Nazi era, pogroms

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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: 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: Jinyoung Park, Eun Joo Song

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Introduction: Deubiquitinating enzymes (DUBs) are proteases that cleave ubiquitin or ubiquitin-like modifications on substrates. Deubiquitination could regulate cellular physiology, such as signal transduction, DNA damage and repair, and cell cycle progression. Although more than 100 DUBs are encoded in the human and the importance of DUBs has been realized, the functions of most DUBs are unknown. This study aims to identify the molecular mechanism by which deubiquitinating enzyme USP35 regulates cell cycle progression for the first time. Methods: USP35 RNAi was mainly used to identify the function of USP35 in cell cycle progression. To find substrates of USP35, we analyzed protein-protein interaction using LC-MS. Several biological methods, such as ubiquitination assay, cell synchronization, immunofluorescence, and immunoprecipitation assay were used to investigate the exact mechanism by which USP35 affects successful completion of mitosis. Results: USP35 knockdown caused not only reduction of mitotic cell number but also induction of mitotic cells with abnormal spindle formation. Actually, cell proliferation was decreased by USP35 knockdown. Interestingly, we found that loss of USP35 decreased the stability and expression of Aurora B, a member of chromosomal passenger complex (CPC), and the phosphorylation of its substrate. Indeed, USP35 interacted with Aurora B and deubiquitinated it. In addition, USP35 knockdown induced abnormal localization of Aurora B in mitotic cells. Finally, CDH1-mediated ubiquitination of Aurora B level was rescued by USP35 overexpression, but not inactive form of USP35, USP35 C450A. Discussion: Our findings suggest that USP35 regulates Aurora B-mediated mitotic spindle assembly and G2-M transition by blocking CDH1-induced degradation of Aurora B.

Keywords: USP35, HSP90, Aurora B, cell cycle progression

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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: Olupemi E. Oludare

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This paper discusses the thematic structure of Yoruba popular music of Southwest Nigeria. It examines the use of themes and variations in early and contemporary Juju music. The work is an outcome of a research developed by the author in his doctoral studies at the University of Lagos, Nigeria, with the aim of analyzing the thematic and motivic developments in Yoruba popular genres. Observations, interviews, live recordings and CDs were used as methods for eliciting information. Field recordings and CDs of selected musical samples were also transcribed and notated. The research established the prevalent use of string of themes by Juju musicians as a compositional technique in moving from one musical section to another, as they communicate the verbal messages in their song. These themes consisting of the popular ‘call and response’ form found in most African music, analogous to the western ‘subject and answer’ style of the fugue or sonata form, although without the tonic–dominant relations. Due to the short and repetitive form of African melodies and rhythms, a theme is restated as a variation, where its rhythmic and melodic motifs are stylistically developed and repeated, but still retaining its recognizable core musical structure. The findings of this study showed that Juju musicians generally often employ a thematic plan where new themes are used to arrange the songs into sections, and each theme is developed into variations in order to further expand the music, eliminate monotony, and create musical aesthetics, serving as hallmark of its musical identity. The study established the musical and extra-musical attributes of the genre, while recommending further research towards analyzing the various compositional techniques employed in African popular genres.

Keywords: compositional techniques, popular music, theme and variation, thematic development

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Authors: Tannistha Dasgupta

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This study explores the aspects of second language (L2) spoken fluency that are related to L2 linguistic knowledge and processing skill. It draws on Levelt’s ‘blueprint’ of the L2 speaker which discusses the cognitive issues underlying the act of speaking. However, L2 speaking assessments have largely neglected the underlying mechanism involved in language production; emphasis is given on the relationship between subjective ratings of L2 speech sample and objectively measured aspects of fluency. Hence, in this study, the relation between L2 linguistic knowledge and processing skill i.e. Cognitive Fluency (CF), and objectively measurable aspects of L2 spoken fluency i.e. Utterance Fluency (UF) is examined. The participants of the study are L2 learners of English, studying at high school level in Hyderabad, India. 50 participants with intermediate level of proficiency in English performed several lexical retrieval tasks and attention-shifting tasks to measure CF, and 8 oral tasks to measure UF. Each aspect of UF (speed, pause, and repair) were measured against the scores of CF to find out those aspects of UF which are reliable indicators of CF. Quantitative analysis of the data shows that among the three aspects of UF; speed is the best predictor of CF, and pause is weakly related to CF. The study suggests that including the speed aspect of UF could make L2 fluency assessment more reliable, valid, and objective. Thus, incorporating the assessment of psycholinguistic mechanisms into L2 spoken fluency testing, could result in fairer evaluation.

Keywords: attention-shifting, cognitive fluency, lexical retrieval, utterance fluency

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Authors: Andrei Nosov

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This paper discusses the development directions of dialogue systems within the digitalisation of the railway industry, where technologies based on conversational AI are already potentially applied or will be applied. Conversational AI is one of the popular natural language processing (NLP) tasks, as it has great prospects for real-world applications today. At the same time, it is a challenging task as it involves many areas of NLP based on complex computations and deep insights from linguistics and psychology. In this review, we focus on dialogue systems and their implementation in the railway domain. We comprehensively review the state-of-the-art research results on dialogue systems and analyse them from three perspectives: type of problem to be solved, type of model, and type of system. In particular, from the perspective of the type of tasks to be solved, we discuss characteristics and applications. This will help to understand how to prioritise tasks. In terms of the type of models, we give an overview that will allow researchers to become familiar with how to apply them in dialogue systems. By analysing the types of dialogue systems, we propose an unconventional approach in contrast to colleagues who traditionally contrast goal-oriented dialogue systems with open-domain systems. Our view focuses on considering retrieval and generative approaches. Furthermore, the work comprehensively presents evaluation methods and datasets for dialogue systems in the railway domain to pave the way for future research. Finally, some possible directions for future research are identified based on recent research results.

Keywords: digitalisation, railway, dialogue systems, conversational AI, natural language processing, natural language understanding, natural language generation

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