Search results for: biometric databases

Authors: Thiago M. R Dias, Gray F. Moita

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The analysis of scientific collaboration networks has contributed significantly to improving the understanding of how does the process of collaboration between researchers and also to understand how the evolution of scientific production of researchers or research groups occurs. However, the identification of collaborations in large scientific databases is not a trivial task given the high computational cost of the methods commonly used. This paper proposes a method for identifying collaboration in large data base of curriculum researchers. The proposed method has low computational cost with satisfactory results, proving to be an interesting alternative for the modeling and characterization of large scientific collaboration networks.

Keywords: extraction, data integration, information retrieval, scientific collaboration

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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Authors: Mine Koyaz, M. Cem Altun

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Selection of the materials satisfying the expected performances is significantly important for any design. Today, with the constantly evolving and developing technologies, the material options are so wide that the necessity of the use of some support tools in the selection process is arising. Therefore, as a sub process of building element design, a systematic material selection tool is developed, that defines four main steps of the material selection; definition, research, comparison and decision. The main purpose of the tool is being an educational instrument that would show a methodic way of material selection in architectural detailing for the use of architecture students. The tool predefines the possible uses of various material databases and other sources of information on material properties. Hence, it is to be used as a guidance for designers, especially with a limited material knowledge and experience. The material selection tool not only embraces technical properties of materials related with building elements’ functional requirements, but also its sensual properties related with the identity of design and its environmental impacts with respect to the sustainability of the design. The method followed in the development of the tool has two main sections; first the examination and application of the existing methods and second the development of trial versions and their applications. Within the scope of the existing methods; design support tools, methodic approaches for the building element design and material selection process, material properties, material databases, methodic approaches for the decision making process are examined. The existing methods are applied by architecture students and newly graduate architects through different design problems. With respect to the results of these applications, strong and weak sides of the existing material selection tools are presented. A main flow chart of the material selection tool has been developed with the objective to apply the strong aspects of the existing methods and develop their weak sides. Through different stages, a different aspect of the material selection process is investigated and the tool took its final form. Systematic material selection tool, within the building element design process, guides the users with a minimum background information, to practically and accurately determine the ideal material that is to be chosen, satisfying the needs of their design. The tool has a flexible structure that answers different needs of different designs and designers. The trial version issued in this paper shows one of the paths that could be followed and illustrates its application over a design problem.

Keywords: architectural education, building element design, material selection tool, systematic approach

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Authors: Sabina Auhunas

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These days in Ukraine, Open Science dramatically develops for the sake of scientists of all branches, providing an opportunity to take a more close look on the studies by foreign scientists, as well as to deliver their own scientific data to national and international journals. However, when it comes to the generalization of data on science activities by Ukrainian scientists, these data are often integrated into E-systems that operate inconsistent and barely related information sources. In order to resolve these issues, developed countries productively use E-systems, designed to store and manage research data, such as Current Research Information Systems that enable combining uncompiled data obtained from different sources. An algorithm for selecting SARS-CoV-2 research articles was designed, by means of which we collected the set of papers published by Ukrainian scientists and uploaded by August 1, 2020. Resulting metadata (document type, open access status, citation count, h-index, most cited documents, international research funding, author counts, the bibliographic relationship of journals) were taken from Scopus and Web of Science databases. The study also considered the info from COVID-19/SARS-CoV-2-related documents published from December 2019 to September 2020, directly from documents published by authors depending on territorial affiliation to Ukraine. These databases are enabled to get the necessary information for bibliometric analysis and necessary details: copyright, which may not be available in other databases (e.g., Science Direct). Search criteria and results for each online database were considered according to the WHO classification of the virus and the disease caused by this virus and represented (Table 1). First, we identified 89 research papers that provided us with the final data set after consolidation and removing duplication; however, only 56 papers were used for the analysis. The total number of documents by results from the WoS database came out at 21641 documents (48 affiliated to Ukraine among them) in the Scopus database came out at 32478 documents (41 affiliated to Ukraine among them). According to the publication activity of Ukrainian scientists, the following areas prevailed: Education, educational research (9 documents, 20.58%); Social Sciences, interdisciplinary (6 documents, 11.76%) and Economics (4 documents, 8.82%). The highest publication activity by institution types was reported in the Ministry of Education and Science of Ukraine (its percent of published scientific papers equals 36% or 7 documents), Danylo Halytsky Lviv National Medical University goes next (5 documents, 15%) and P. L. Shupyk National Medical Academy of Postgraduate Education (4 documents, 12%). Basically, research activities by Ukrainian scientists were funded by 5 entities: Belgian Development Cooperation, the National Institutes of Health (NIH, U.S.), The United States Department of Health & Human Services, grant from the Whitney and Betty MacMillan Center for International and Area Studies at Yale, a grant from the Yale Women Faculty Forum. Based on the results of the analysis, we obtained a set of published articles and preprints to be assessed on the variety of features in upcoming studies, including citation count, most cited documents, a bibliographic relationship of journals, reference linking. Further research on the development of the national scientific E-database continues using brand new analytical methods.

Keywords: content analysis, COVID-19, scientometrics, text mining

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Authors: Ali Alshumrani, Nathan Clarke, Bogdan Ghite, Stavros Shiaeles

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Digital forensics has become an essential tool in the investigation of cyber and computer-assisted crime. Arguably, given the prevalence of technology and the subsequent digital footprints that exist, it could have a significant role across almost all crimes. However, the variety of technology platforms (such as computers, mobiles, Closed-Circuit Television (CCTV), Internet of Things (IoT), databases, drones, cloud computing services), heterogeneity and volume of data, forensic tool capability, and the investigative cost make investigations both technically challenging and prohibitively expensive. Forensic tools also tend to be siloed into specific technologies, e.g., File System Forensic Analysis Tools (FS-FAT) and Network Forensic Analysis Tools (N-FAT), and a good deal of data sources has little to no specialist forensic tools. Increasingly it also becomes essential to compare and correlate evidence across data sources and to do so in an efficient and effective manner enabling an investigator to answer high-level questions of the data in a timely manner without having to trawl through data and perform the correlation manually. This paper proposes a Unified Forensic Analysis Tool (U-FAT), which aims to establish a common language for electronic information and permit multi-source forensic analysis. Core to this approach is the identification and development of forensic analyses that automate complex data correlations, enabling investigators to investigate cases more efficiently. The paper presents a systematic analysis of major crime categories and identifies what forensic analyses could be used. For example, in a child abduction, an investigation team might have evidence from a range of sources including computing devices (mobile phone, PC), CCTV (potentially a large number), ISP records, and mobile network cell tower data, in addition to third party databases such as the National Sex Offender registry and tax records, with the desire to auto-correlate and across sources and visualize in a cognitively effective manner. U-FAT provides a holistic, flexible, and extensible approach to providing digital forensics in technology, application, and data-agnostic manner, providing powerful and automated forensic analysis.

Keywords: digital forensics, evidence correlation, heterogeneous data, forensics tool

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Authors: Lyka Selene Magnayi, Marcos Vinas, Roseanne Ramos

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As the real estate industry continually grows in the Philippines, Geographic Information Systems (GIS) provide advantages in generating spatial databases for efficient delivery of information and services. The real estate sector is not only providing qualitative data about real estate properties but also utilizes various spatial aspects of these properties for different applications such as hazard mapping and assessment. In this study, a three-dimensional (3D) model and a spatial database of real estate properties in Fort Bonifacio, Taguig City are developed using GIS and SketchUp. Spatial datasets include political boundaries, buildings, road network, digital terrain model (DTM) derived from Interferometric Synthetic Aperture Radar (IFSAR) image, Google Earth satellite imageries, and hazard maps. Multiple model layers were created based on property listings by a partner real estate company, including existing and future property buildings. Actual building dimensions, building facade, and building floorplans are incorporated in these 3D models for geovisualization. Hazard model layers are determined through spatial overlays, and different scenarios of hazards are also presented in the models. Animated maps and walkthrough videos were created for company presentation and evaluation. Model evaluation is conducted through client surveys requiring scores in terms of the appropriateness, information content, and design of the 3D models. Survey results show very satisfactory ratings, with the highest average evaluation score equivalent to 9.21 out of 10. The output maps and videos obtained passing rates based on the criteria and standards set by the intended users of the partner real estate company. The methodologies presented in this study were found useful and have remarkable advantages in the real estate industry. This work may be extended to automated mapping and creation of online spatial databases for better storage, access of real property listings and interactive platform using web-based GIS.

Keywords: geovisualization, geographic information systems, GIS, real estate, spatial database, three-dimensional model

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Authors: Dhruv Sharma, Lynne Blair, Stephen Clune

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Later life loneliness is a social issue that is increasing alongside an upward global population trend. As a society, one way that we have responded to this social challenge is through developing non-pharmacological interventions such as befriending services, activity clubs, meet-ups, etc. Through a systematic literature review, this paper suggests that currently there is an underrepresentation of radical innovation, and underutilization of digital technologies in developing loneliness interventions for older adults. This paper examines intervention studies that were published in English language, within peer reviewed journals between January 2005 and December 2014 across 4 electronic databases. In addition to academic databases, interventions found in grey literature in the form of websites, blogs, and Twitter were also included in the overall review. This approach yielded 129 interventions that were included in the study. A systematic approach allowed the minimization of any bias dictating the selection of interventions to study. A coding strategy based on a pattern analysis approach was devised to be able to compare and contrast the loneliness interventions. Firstly, interventions were categorized on the basis of their objective to identify whether they were preventative, supportive, or remedial in nature. Secondly, depending on their scope, they were categorized as one-to-one, community-based, or group based. It was also ascertained whether interventions represented an improvement, an incremental innovation, a major advance or a radical departure, in comparison to the most basic form of a loneliness intervention. Finally, interventions were also assessed on the basis of the extent to which they utilized digital technologies. Individual visualizations representing the four levels of coding were created for each intervention, followed by an aggregated visual to facilitate analysis. To keep the inquiry within scope and to present a coherent view of the findings, the analysis was primarily concerned the level of innovation, and the use of digital technologies. This analysis highlights a weak but positive correlation between the level of innovation and the use of digital technologies in designing and deploying loneliness interventions, and also emphasizes how certain existing interventions could be tweaked to enable their migration from representing incremental innovation to radical innovation for example. This analysis also points out the value of including grey literature, especially from Twitter, in systematic literature reviews to get a contemporary view of latest work in the area under investigation.

Keywords: ageing, loneliness, innovation, digital

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Authors: Ana Elvira Ojanguren Lopez, Javier Martin Arista

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The aims of this paper are to present the automatisation procedure adopted in the implementation of a parallel corpus of Old English, as well as, to assess the progress of automatisation with respect to tagging, annotation, and lemmatisation. The corpus consists of an aligned parallel text with word-for-word comparison Old English-English that provides the Old English segment with inflectional form tagging (gloss, lemma, category, and inflection) and lemma annotation (spelling, meaning, inflectional class, paradigm, word-formation and secondary sources). This parallel corpus is intended to fill a gap in the field of Old English, in which no parallel and/or lemmatised corpora are available, while the average amount of corpus annotation is low. With this background, this presentation has two main parts. The first part, which focuses on tagging and annotation, selects the layouts and fields of lexical databases that are relevant for these tasks. Most information used for the annotation of the corpus can be retrieved from the lexical and morphological database Nerthus and the database of secondary sources Freya. These are the sources of linguistic and metalinguistic information that will be used for the annotation of the lemmas of the corpus, including morphological and semantic aspects as well as the references to the secondary sources that deal with the lemmas in question. Although substantially adapted and re-interpreted, the lemmatised part of these databases draws on the standard dictionaries of Old English, including The Student's Dictionary of Anglo-Saxon, An Anglo-Saxon Dictionary, and A Concise Anglo-Saxon Dictionary. The second part of this paper deals with lemmatisation. It presents the lemmatiser Norna, which has been implemented on Filemaker software. It is based on a concordance and an index to the Dictionary of Old English Corpus, which comprises around three thousand texts and three million words. In its present state, the lemmatiser Norna can assign lemma to around 80% of textual forms on an automatic basis, by searching the index and the concordance for prefixes, stems and inflectional endings. The conclusions of this presentation insist on the limits of the automatisation of dictionary-based annotation in a parallel corpus. While the tagging and annotation are largely automatic even at the present stage, the automatisation of alignment is pending for future research. Lemmatisation and morphological tagging are expected to be fully automatic in the near future, once the database of secondary sources Freya and the lemmatiser Norna have been completed.

Keywords: corpus linguistics, historical linguistics, old English, parallel corpus

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Authors: Nalini C. Iyer, Shraddha H., Anagha B. Varahamurthy, Dikshith C. S., Ishwar G. Kubasad, Vinayak I. Karalatti, Pavan B. Mulimani

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The current scenario of the pandemic due to COVID-19 has led to the awareness among the people to avoid unneces-sary contact in public places. There is a need to avoid contact with physical objects to stop the spreading of infection. The contactless feature has to be included in the systems in public places wherever possible. For example, attendance monitoring systems with fingerprint biometric can be replaced with a contactless feature. One more important protocol followed in the current situation is temperature monitoring and screening. The paper describes an attendance system with a contactless feature and temperature screening for the university. The system displays a QR code to scan, which redirects to the student login web page only if the location is valid (the location where the student scans the QR code should be the location of the display of the QR code). Once the student logs in, the temperature of the student is scanned by the contactless temperature sensor (mlx90614) with an error of 0.5°C. If the temperature falls in the range of the desired value (range of normal body temperature), then the attendance of the student is marked as present, stored in the database, and the door opens automatically. The attendance is marked as absent in the other case, alerted with the display of temperature, and the door remains closed. The door is automated with the help of a servomotor. To avoid the proxy, IR sensors are used to count the number of students in the classroom. The hardware system consisting of a contactless temperature sensor and IR sensor is implemented on the microcontroller, NodeMCU.

Keywords: NodeMCU, IR sensor, attendance monitoring, contactless, temperature

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Authors: Abdullahi Jibrin, Aishetu Abdulkadir

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The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

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Authors: Bülent Diken

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This paper looks to set Ridley Scott’s original film Blade Runner (1982) and Denis Villeneuve’s Blade Runner 2049 (2017) in order to provide an analysis of both films with respect to the new configurations of slavery in the 21st century. Both Blade Runner films present a de-politicized society that oscillates between two extremes: the spectral (the eye, optics, digital communications) and the biopolitical (the body, haptics). On the one hand, recognizing the subject only as a sign, the society of the spectacle registers, identifies, produces and reproduces the subject as a code. At the same time, though, the subject is constantly reduced to a naked body, to bare life, for biometric technologies to scan it as a biological body or body parts. Being simultaneously a pure code (word without body) and an instrument slave (body without word), the replicants are thus the paradigmatic subjects of this society. The paper focuses first on the similarity: both films depict a relationship between masters and slaves, that is, a despotic relationship. The master uses the (body of the) slave as an instrument, as an extension of his own body. Blade Runner 2019 frames the despotic relation in this classical way through its triangulation with the economy (the Tyrell Corporation) and the slave-replicants’ dissent (rejecting their reduction to mere instruments). In a counter-classical approach, in Blade Runner 2049, the focus shifts to another triangulation: despotism, economy (the Wallace Corporation) and consent (of replicants who no longer perceive themselves as slaves).

Keywords: Blade Runner, the spectacle, bio-politics, slavery, imstrumentalisation

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Authors: Djoudi Abdelhak, Djibaoui Rachid, Reguieg Yassaad Houcine

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Our study focuses on the identification of some species of Pseudomonas (P4, P5, P7 and P8) isolated from saline soils in northwestern Algeria and the effect of their metabolites on the growth of Alternaria alternata the causative agent of the blight of the bean disease (Vicia faba). We are also interested in stimulating the growth of this plant species in saline conditions (60 mM/l NaCl) and the absence of salts. The analysis focuses on rates of inhibition of mycelial growth of Alternaria alternata strain and the rate of growth of plants inoculated with strains of Pseudomonas expressed by biometrics. According to the results of the in-vitro test, P5 and P8 species and their metabolites showed a significant effect on mycelia growth and production of spores of Alternaria alternata. The in-vivo test shows that the species P8 and P5 were significantly and positively influencing the growth in biometric parameters of the bean in saline and salt-free condition. Inoculation with strain P5 has promoted the growth of the bean in stem height, stem fresh weight and dry weight of stems of 108.59%, 115.28%, 104.33%, respectively, in the presence of salt Inoculation with strain P5 has fostered the growth of the bean stem fresh weight of 112.47% in the presence of salt The effect of Pseudomonas species on the development of Vicia faba and the growth of Alternaria alternata is considering new techniques and methods of biological production and crop protection.

Keywords: pseudomonas, vicia faba, alternaria alternata, promoting of plant growth

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Authors: Juan Sepúlveda

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Energy is a fundamental component in sustainability, the access and use of this resource is related with economic growth, social improvements, and environmental impacts. In this sense, energy efficiency has been studied as a factor that enhances the positive impacts of energy in communities; however, the implementation of efficiency requires strong policy and strategies that usually rely on individual measures focused in independent dimensions. In this paper, the problem of energy efficiency as a multi-objective problem is studied, using scientometric analysis to discover trends and patterns that allow to identify the main variables and study approximations related with a further development of models to integrate energy efficiency and MCA into policy making for small communities.

Keywords: energy efficiency, MCA, scientometric, trends

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Authors: Yali Zheng, Peipei Luo, Shinan Chen, Jiasheng Hao, Hong Cheng

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Most of traditional visual indoor navigation algorithms and methods only consider the localization in ordinary daytime, while we focus on the indoor re-localization in low light in the paper. As RGB images are degraded in low light, less discriminative infrared and depth image pairs are taken, as the input, by RGB-D cameras, the most similar candidates, as the output, are searched from databases which is built in the bag-of-word framework. Epipolar constraints can be used to relocalize the query infrared and depth image sequence. We evaluate our method in two datasets captured by Kinect2. The results demonstrate very promising re-localization results for indoor navigation system in low light environments.

Keywords: indoor navigation, low light, RGB-D camera, vision based

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Authors: Pilar Giffenig, Avanna Kotlarz, Taylor Dehring

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Anxiety and depression are common mental illnesses in the U.S today. While there are various treatments for these mental health disorders, many of the medications come with a large variety of side effects that decrease medication compliance. Recent studies have looked at the impact of probiotics on anxiety and depression. Our goal was to determine whether probiotics could help relieve symptoms of anxiety and or depression. We conducted a literature search of three databases focusing on systematic reviews and RTC and found 25 articles, 8 of which were used for our analysis. Seven out of the eight articles showed that probiotics have the potential to significantly reduce symptoms of anxiety and depression. However, larger study sample sizes, type of probiotic, and correct dosage are required in future research to determine the role of probiotics in the treatment of anxiety and depression.

Keywords: probiotics, anxiety, depression, treatment, psychology, nutrition

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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: A. Djoudi, R. Djibaou, H. A. Reguieg Yssaad

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Our study focuses on the study of a bacteria belonging to Pseudomonas solubilizing tricalcium phosphate. They were isolated from rhizosphere of a variety of broad bean grown in salt-affected soils (electrical conductivity between 4 and 8 mmhos/cm) of the irrigated perimeter of Mina in northwestern Algeria. Isolates which have advantageous results in the calcium phosphate solubilization index test were subjected to identification using API20 then used to re-inoculate the same soil in pots experimentation to assess the effects of inoculation on the growth of the broad bean (Vicia faba). Based on the results obtained from the in-vitro tests, two isolates P5 and P8 showed a significant effect on the solubilization of tricalcium phosphate with an index I estimated at 314% and 283% sequentially. According to the results of in-vivo tests, the inoculation of the soil with P5 and P8 were significantly and positively influencing the growth in biometric parameters of the broad bean. Inoculation with strain P5 has promoted the growth of the broad bean in stem height, stem fresh weight and stem dry weight of 108.59%, 115.28%, 104.33%, respectively. Inoculation with strain P8 has fostered the growth of the broad bean stem fresh weight of 112.47%. The effect of Pseudomonas on the development of Vicia faba is considered as an interesting process by which PGPR can increase biological production and crop protection.

Keywords: Pseudomonas, Vicia faba, promoting of plant growth, solubilization tricalcium phosphate

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Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: biological ontology, linked data, semantic data integration, semantic web

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Authors: P. Charipoor, M. Khani, H. Mahmoudi, E. Ghasemi, P. Akbartehrani, B. Shokri

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Cold air plasma could have a variety of effects on cells and living organisms and also shows good results in medical and cosmetic cases. Herein, plasma floating electrode dielectric barrier discharge (FEDBD) plasma was designed for mouse skin rejuvenation purposes. It is safe and easy to use in clinics, laboratories, and homes. The effects of this device were investigated on mouse skin. Vitamin C ointment in combination with plasma was also used as a new method to improve FEDBD results. In this study, 20 Wistar rats were evaluated in four groups. The first group received high-dose plasma, the second group received moderate-dose plasma (with vitamin C cream), the third group received low-dose plasma (with vitamin C cream) for 6 minutes, and the fourth group received only vitamin C cream. This process was done 3 times a week for 4 weeks. Skin temperature was monitored to evaluate the thermal effect of plasma. The presence of reactive species was also demonstrated using optical spectroscopy. Mechanical assays were performed to evaluate the effect of plasma and vitamin C on the mechanical strength of the tissue, which showed a positive effect of plasma on the treated tissue compared to the control group. Using pathological and biometric skin tests, an increase in collagen levels, epidermal thickness, and an increase in fibroblasts was observed in rat skin, as well as increased skin elasticity. This study showed the positive effect of using the FEDBD plasma device on the effective parameters in skin rejuvenation.

Keywords: plasma, skin rejuvenation, collagen, epidermal thickness

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Authors: Suzan Wedyan

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Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

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Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

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Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, Data Mining, Hadoop, MapReduce, MongoDB, NoSQL

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Authors: Neringa Bagdonaite

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Study Aims: The current study aimed to systematically analyse various research done in the area of female post-traumatic stress disorder (PTSD) and alcohol abuse, and to critically review these results on the basis of theoretical models as well as answer following questions: (I) What is the reciprocal relationship between PTSD and problem alcohol use among females; (II) What are the moderating/mediating factors of this relationship? Methods: The computer bibliographic databases Ebsco, Scopus, Springer, Web of Science, Medline, Science Direct were used to search for scientific articles. Systematic analyses sample consisted of peer-reviewed, English written articles addressing mixed gender and female PTSD and alcohol abuse issues from Jan 2012 to May 2017. Results: Total of 1011 articles were found in scientific databases related to searched keywords of which 29 met the selection criteria and were analysed. The results of longitudinal studies indicate that (I) various trauma, especially interpersonal trauma exposure in childhood is linked with increased risk of revictimization in later life and problem alcohol use; (II) revictimization in adolescence or adulthood, rather than victimization in childhood has a greater impact on the onset and progression of problematic alcohol use in adulthood. Cross-sectional and epidemiological studies also support significant relationships between female PTSD and problem alcohol use. Regards to the negative impact of alcohol use on PTSD symptoms results are yet controversial; some evidence suggests that alcohol does not exacerbate symptoms of PTSD over time, while others argue that problem alcohol use worsens PTSD symptoms and is linked to chronicity of both disorders, especially among women with previous alcohol use problems. Analysis of moderating/mediating factors of PTSD and problem alcohol use revealed, that higher motives/expectancies, specifically distress coping motives for alcohol use significantly moderates the relationship between PTSD and problematic alcohol use. Whereas negative affective states mediate relationship between symptoms of PTSD and alcohol use, but only among woman with alcohol use problems already developed. Conclusions: Interpersonal trauma experience, especially in childhood and its reappearance in lifetime is linked with PTSD symptoms and problem drinking among women. Moreover, problem alcohol use can be both a cause and a consequence of trauma and PTSD, and if used for coping it, increases the likelihood of chronicity of both disorders. In order to effectively treat both disorders, it’s worthwhile taking into account this dynamic interplay of women's PTSD symptoms and problem drinking.

Keywords: female, trauma, post-traumatic stress disorder, problem alcohol use, systemic analysis

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Authors: Gabriel Montague, Max Vilgalys, Catherine H. Crawford, Jorge Ortiz, Dava Newman

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There has never been so much publicly accessible atmospheric and environmental data. The possibilities of these data are exciting, but the sheer volume of available datasets represents a new challenge for researchers. The task of identifying and working with a new dataset has become more difficult with the amount and variety of available data. Datasets are often documented in ways that differ substantially from the common English used to describe the same topics. This presents a barrier not only for new scientists, but for researchers looking to find comparisons across multiple datasets or specialists from other disciplines hoping to collaborate. This paper proposes a method for addressing this obstacle: creating a knowledge graph to bridge the gap between everyday English language and the technical language surrounding these datasets. Knowledge graph generation is already a well-established field, although there are some unique challenges posed by working with Earth data. One is the sheer size of the databases – it would be infeasible to replicate or analyze all the data stored by an organization like The National Aeronautics and Space Administration (NASA) or the European Space Agency. Instead, this approach identifies topics from metadata available for datasets in NASA’s Earthdata database, which can then be used to directly request and access the raw data from NASA. By starting with a single metadata standard, this paper establishes an approach that can be generalized to different databases, but leaves the challenge of metadata harmonization for future work. Topics generated from the metadata are then linked to topics from a collection of English queries through a variety of standard and custom natural language processing (NLP) methods. The results from this method are then compared to a baseline of elastic search applied to the metadata. This comparison shows the benefits of the proposed knowledge graph system over existing methods, particularly in interpreting natural language queries and interpreting topics in metadata. For the research community, this work introduces an application of NLP to the ecological and environmental sciences, expanding the possibilities of how machine learning can be applied in this discipline. But perhaps more importantly, it establishes the foundation for a platform that can enable common English to access knowledge that previously required considerable effort and experience. By making this public data accessible to the full public, this work has the potential to transform environmental understanding, engagement, and action.

Keywords: earth metadata, knowledge graphs, natural language processing, question-answer systems

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Authors: Şirin Küçük, Ayşe Kök, İsmail Şahin

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Mobile devices are very popular and useful tools for assisting people in daily life. With the advancement of mobile technologies, the issue of mobile learning has been widely investigated in education. Many researches consider that it is important to integrate pedagogical and technical strengths of mobile technology into learning environments. For this reason, the purpose of this research is to examine the effect of mobile technology use in education with meta-analysis method. Meta-analysis is a statistical technique which combines the findings of independent studies in a specific subject. In this respect, the articles will be examined by searching the databases for researches which are conducted between 2005 and 2014. It is expected that the results of this research will contribute to future research related to mobile technology use in education.

Keywords: mobile learning, meta-analysis, mobile technology, education

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Authors: James Newman

Abstract:

Process mining is an emerging technology that looks to serialize enterprise data in time series data. It has been used by many companies and has been the subject of a variety of research papers. However, the majority of current efforts have looked at how to best create process mining from standard relational databases. This paper is the first pass at outlining a database custom-built for the minimal viable product of process mining. We present Block Miner, a blockchain protocol to store process mining data across a distributed network. We demonstrate the feasibility of storing process mining data on the blockchain. We present a proof of concept and show how the intersection of these two technologies helps to solve a variety of issues, including but not limited to ransomware attacks, tax documentation, and conflict resolution.

Keywords: blockchain, process mining, memory optimization, protocol

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Authors: Said Boularouk, Didier Josselin, Eitan Altman

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In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: TTS, ontology, open street map, visually impaired

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Authors: Sharanya C. H., Pragathi M., Vathsala R. S., Theja K. V., Yashaswini S.

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Identifying counterfeit products have become increasingly important in the product manufacturing industries in recent decades. This current ongoing product issue of counterfeiting has an impact on company sales and profits. To address the aforementioned issue, a functional blockchain technology was implemented, which effectively prevents the product from being counterfeited. By utilizing the blockchain technology, consumers are no longer required to rely on third parties to determine the authenticity of the product being purchased. Blockchain is a distributed database that stores data records known as blocks and several databases known as chains across various networks. Counterfeit products are identified using a QR code reader, and the product's QR code is linked to the blockchain management system. It compares the unique code obtained from the customer to the stored unique code to determine whether or not the product is original.

Keywords: blockchain, ethereum, QR code

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Authors: Muhammad Yasir Tarar

Abstract:

Background: Intraarticular steroid injections are an effective option in alleviating the symptoms of conditions like osteoarthritis, rheumatoid arthritis, crystal arthropathy, and rotator cuff tendinopathy. Most of these injections are conducted in the elderly who are on polypharmacy, including anticoagulants at times. Up to 6% of patients aged 80-84 years have been reported to be taking Warfarin. The literature availability on safety quotient for patients undergoing intraarticular injections on Warfarin is scarce. It has remained debatable over the years which approach is safe for these patients. Continuing warfarin has a theoretical bleeding risk, and stopping it can lead to even severe life-threatening thromboembolic events in high-risk patients. Objectives: To evaluate the risk of bleeding complications in patients on warfarin undergoing intraarticular injections or arthrocentesis. Study Design & Methods: A literature search of MEDLINE (1946 to present), EMBASE (1974 to present), and Cochrane CENTRAL (1988 to present) databases were conducted using any combination of the keywords, Injection, Knee, Shoulder, Joint, Intraarticular, arthrocentesis, Warfarin, and Anticoagulation in November 2020 for articles published in any language with no publication year limit. The study inclusion criteria included reporting on the rate of bleeding complications following injection of the knee or shoulder in patients on warfarin treatment. Randomized control trials and prospective and retrospective study designs were included. An electronic standardized Performa for data extraction was made. The Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) the methodology was used. The articles were appraised using the methodological index for nonrandomized studies. The Cochrane Risk of Bias Tool used to assess the risk of bias in included RCTs and the MINORS tool for assessment of bias in observational studies. Results: The search of databases resulted in a total of 852 articles. Relevant articles as per the inclusion criteria were shortlisted, 7 articles deemed suitable to be include. A total of 1033 joints sample size was undertaken with specified knee and shoulder joints of a total of 820. Only 6 joints had bleeding complications, 5 early bleeding at the time of injection or aspiration, and one late bleeding complication with INR of 5, additionally, 2 patients complained of bruising, 3 of pain, and 1 managed for infection. Conclusions: The results of the metanalysis show that it is relatively safe to perform intraarticular injections in patients on Warfarin regardless of the INR range.

Keywords: arthrocentesis, warfarin, bleeding, injection

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Authors: Stephanie Remedios, Linda Veronica Rios

Abstract:

Background. Pediatric obesity is a serious health problem linked to multiple physical diseases and ailments, including diabetes, heart disease, and joint issues. While research has shown pediatric obesity can bring about an array of physical illnesses, it is less known how such a condition can affect children’s cognitive development. With childhood overweight and obesity prevalence rates on the rise, it is essential to understand the scope of their cognitive consequences. The present review of the literature tested the hypothesis that poor physical health, such as childhood obesity or malnutrition, negatively impacts a child’s cognitive development. Methodology. A systematic review was conducted to determine the relationship between poor physical health and lower cognitive functioning in children ages 4-16. Electronic databases were searched for studies dating back to ten years. The following databases were used: Science Direct, FIU Libraries, and Google Scholar. Inclusion criteria consisted of peer-reviewed academic articles written in English from 2012 to 2022 that analyzed the relationship between childhood malnutrition and obesity on cognitive development. A total of 17,000 articles were obtained, of which 16,987 were excluded for not addressing the cognitive implications exclusively. Of the acquired articles, 13 were retained. Results. Research suggested a significant connection between diet and cognitive development. Both diet and physical activity are strongly correlated with higher cognitive functioning. Cognitive domains explored in this work included learning, memory, attention, inhibition, and impulsivity. IQ scores were also considered objective representations of overall cognitive performance. Studies showed physical activity benefits cognitive development, primarily for executive functioning and language development. Additionally, children suffering from pediatric obesity or malnutrition were found to score 3-10 points lower in IQ scores when compared to healthy, same-aged children. Conclusion. This review provides evidence that the presence of physical activity and overall physical health, including appropriate diet and nutritional intake, has beneficial effects on cognitive outcomes. The primary conclusion from this research is that childhood obesity and malnutrition show detrimental effects on cognitive development in children, primarily with learning outcomes. Assuming childhood obesity and malnutrition rates continue their current trade, it is essential to understand the complete physical and psychological implications of obesity and malnutrition in pediatric populations. Given the limitations encountered through our research, further studies are needed to evaluate the areas of cognition affected during childhood.

Keywords: childhood malnutrition, childhood obesity, cognitive development, cognitive functioning

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Authors: Yuhan Liu, Zhongde Wang

Abstract:

This paper mainly analyzes the research and application of narrative theory in the field of urban space. This study used the PRISMA systematic review method, systematically studied 3098 Chinese literature through the search and screening of relevant domestic key literature databases, and reviewed the research status of narrative theory in urban space from three aspects: "theoretical perspective", "research object" and "research application". Finally, this paper points out the future development direction of narrative theory research based on the shortcomings of existing research in order to provide new ideas for future research.

Keywords: narrative theory, urban space, PRISMA, systematic review

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