Search results for: text classification

Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Zheng Baichuan, Li Shenghui, Li Bingqian, Zhang Ning, Chen Kai

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Entity alignment (EA) tasks in knowledge graphs often play a pivotal role in the integration of knowledge graphs, where structural differences often exist between the source and target graphs, such as the presence or absence of attribute information and the types of attribute information (text, timestamps, images, etc.). However, most current research efforts are focused on improving alignment accuracy, often along with an increased reliance on specific structures -a dependency that inevitably diminishes their practical value and causes difficulties when facing knowledge graph alignment tasks with varying structures. Therefore, we propose a universal knowledge graph alignment approach that only utilizes the common basic structures shared by knowledge graphs. We have demonstrated through experiments that our method achieves state-of-the-art performance in fair comparisons.

Keywords: knowledge graph, entity alignment, transformer, deep learning

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Authors: Juha Kettunen

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This study analyzes the quality and the size of the strategic network of higher education institutions. The study analyses the concept of fitness for purpose in quality assurance. It also analyses the transaction costs of networking that have consequences on the number of members in the network. Empirical evidence is presented of the Consortium on Applied Research and Professional Education, which is a European strategic network of six higher education institutions. The results of the study support the argument that the number of members in the strategic network should be relatively small to provide high quality results. The practical importance is that networking has been able to promote international research and development projects. The results of this study are important for those who want to design and improve international networks in higher education.

Keywords: balanced scorecard, higher education, social networking, strategic planning

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Authors: Quentin Lobbe, David Chavalarias, Alexandre Delanoe

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The ICT revolution has given birth to an unprecedented world of digital traces and has impacted a wide number of knowledge-driven domains such as science, education or policy making. Nowadays, we are daily fueled by unlimited flows of articles, blogs, messages, tweets, etc. The internet itself can thus be considered as an unsteady hyper-textual environment where websites emerge and expand every day. But there are structures inside knowledge. A given text can always be studied in relation to others or in light of a specific socio-cultural context. By way of their textual traces, human beings are calling each other out: hypertext citations, retweets, vocabulary similarity, etc. We are in fact the architects of a giant web of elements of knowledge whose structures and shapes convey their own information. The global shapes of these digital traces represent a source of collective knowledge and the question of their visualization remains an opened challenge. How can we explore, browse and interact with such shapes? In order to navigate across these growing constellations of words and texts, interdisciplinary innovations are emerging at the crossroad between fields of social and computational sciences. In particular, complex systems approaches make it now possible to reconstruct the hidden structures of textual knowledge by means of multi-scale objects of research such as semantic maps and phylomemies. The phylomemy reconstruction is a generic method related to the co-word analysis framework. Phylomemies aim to reveal the temporal dynamics of large corpora of textual contents by performing inter-temporal matching on extracted knowledge domains in order to identify their conceptual lineages. This study aims to address the question of visualizing the global shapes of online political discussions related to the French presidential and legislative elections of 2017. We aim to build phylomemies on top of a dedicated collection of thousands of French political tweets enriched with archived contemporary news web articles. Our goal is to reconstruct the temporal evolution of online debates fueled by each political community during the elections. To that end, we want to introduce an iterative data exploration methodology implemented and tested within the free software Gargantext. There we combine synchronic and diachronic axis of visualization to reveal the dynamics of our corpora of tweets and web pages as well as their inner syntagmatic and paradigmatic relationships. In doing so, we aim to provide researchers with innovative methodological means to explore online semantic landscapes in a collaborative and reflective way.

Keywords: online political debate, French election, hyper-text, phylomemy

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Authors: Ouerchefani Dalel, Mahdhaoui Basma

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Land use change is one of the important factors needed to evaluate later on the impact of human actions on land degradation. This work present the application of a methodology based on remote sensing for evaluation land use change in an arid region of Tunisia. This methodology uses Landsat TM and ETM+ images to produce land use maps by supervised classification based on ground truth region of interests. This study showed that it was possible to rely on radiometric values of the pixels to define each land use class in the field. It was also possible to generate 3 land use classes of the same study area between 1988 and 2011.

Keywords: land use, change, remote sensing, GIS

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Authors: Jeroen S. de Bruin, Karin Schindler, Christian Schuh

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With increasingly more mobile health applications appearing due to the popularity of smartphones, the possibility arises that these data can be used to improve the medical diagnostic process, as well as the overall quality of healthcare, while at the same time lowering costs. However, as of yet there have been no reports of a successful combination of patient-generated data from smartphones with data from clinical routine. In this paper, we describe how these two types of data can be combined in a secure way without modification to hospital information systems, and how they can together be used in a medical expert system for automatic nutritional classification and triage.

Keywords: mobile health, data integration, expert systems, disease-related malnutrition

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Authors: Mohit Modi, Rajiv Kumar, Manojraj Saxena, G. Ravi Shankar

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Change detection of coastal ecosystem plays a vital role in monitoring and managing natural resources along the coastal regions. The present study mainly focuses on the decadal change in Kochi islands connecting the urban flatland areas and the coastal regions where sand deposits have taken place. With this, in view, the change detection has been monitored in the Kochi area to apprehend the urban growth and industrialization leading to decrease in the wetland ecosystem. The region lies between 76°11'19.134"E to 76°25'42.193"E and 9°52'35.719"N to 10°5'51.575"N in the south-western coast of India. The IRS LISS-IV satellite image has been processed using a rule-based algorithm to classify the LULC and to interpret the changes between 2005 & 2015. The approach takes two steps, i.e. extracting features as a single GIS vector layer using different parametric values and to dissolve them. The multi-resolution segmentation has been carried out on the scale ranging from 10-30. The different classes like aquaculture, agricultural land, built-up, wetlands etc. were extracted using parameters like NDVI, mean layer values, the texture-based feature with corresponding threshold values using a rule set algorithm. The objects obtained in the segmentation process were visualized to be overlaying the satellite image at a scale of 15. This layer was further segmented using the spectral difference segmentation rule between the objects. These individual class layers were dissolved in the basic segmented layer of the image and were interpreted in vector-based GIS programme to achieve higher accuracy. The result shows a rapid increase in an industrial area of 40% based on industrial area statistics of 2005. There is a decrease in wetlands area which has been converted into built-up. New roads have been constructed which are connecting the islands to urban areas as well as highways. The increase in coastal region has been visualized due to sand depositions. The outcome is well supported by quantitative assessments which will empower rich understanding of land use land cover change for appropriate policy intervention and further monitoring.

Keywords: land use land cover, multiresolution segmentation, NDVI, object based classification

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Authors: H. Chabalala, A. Grootboom, M. Tang

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The innovative development, production, and clinical utilisation of African natural medicines requires frameworks from systematisation, innovation, registration. Afrika faces challenges when it comes to these sectors. The opposite is the case as is is evident in ancient Asian (Traditional Chinese Medicine and Indian Ayurveda and Siddha) medical systems, which are interfaced into their respective national health and educational systems. Afrikan Natural Medicines (ANMs) are yet to develop systematisation frameworks, i.e. disease characterisation and medicines classification. This paper explores classical medical systems drawn from Afrikan and Chinese experts in natural medicines. An Afrikological research methodology was used to conduct in-depth interviews with 20 key respondents selected through purposeful sampling technique. Data was summarised into systematisation frameworks for classical disease theories, patient categorisation, medicine classification, aetiology and pathogenesis of disease, diagnosis and prognosis techniques and treatment methods. It was discovered that ancient Afrika had systematic medical cosmologies, remnants of which are evident in most Afrikan cultural health practices. Parallels could be drawn from classical medical concepts of antiquity, like Chinese Taoist and Indian tantric health systems. Data revealed that both the ancient and contemporary ANM systems were based on living medical cosmologies. The study showed that African Natural Healing Systems have etiological systems, general pathogenesis knowledge, differential diagnostic techniques, comprehensive prognosis and holistic treatment regimes. Systematisation models were developed out of these frameworks, and this could be used for evaluation of clinical research, medical application including development of curriculum for high-education. It was envisaged that frameworks will pave way towards the development, production and commercialisation of ANMs. This was piloted in inclusive innovation, technology transfer and commercialisation of South African natural medicines, cosmeceuticals, nutraceuticals and health infusions. The central model presented here in will assist in curriculum development and establishment of Afrikan Medicines Hospitals and Pharmaceutical Industries.

Keywords: African Natural Medicines, Indigenous Knowledge Systems, Medical Cosmology, Clinical Application

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Authors: Hameed Ullah, Shujaul Mulk Khan, Zahid Ullah, Zeeshan Ahmad Sadia Jahangir, Abdullah, Amin Ur Rahman, Muhammad Suliman, Dost Muhammad

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The interrelationship between vegetation and abiotic variables inside an ecosystem is one of the main jobs of plant scientists. This study was designed to investigate the vegetation structure and species diversity along with the environmental variables in the Yakhtangay hill district Shangla of the Himalayan Mountain series Pakistan by using multivariate statistical analysis. Quadrat’s method was used and a total of 171 Quadrats were laid down 57 for Tree, Shrubs and Herbs, respectively, to analyze the phytosociological attributes of the vegetation. The vegetation of the selected area was classified into different Life and leaf-forms according to Raunkiaer classification, while PCORD software version 5 was used to classify the vegetation into different plants communities by Two-way indicator species Analysis (TWINSPAN). The CANOCCO version 4.5 was used for DCA and CCA analysis to find out variation directories of vegetation with different environmental variables. A total of 114 plants species belonging to 45 different families was investigated inside the area. The Rosaceae (12 species) was the dominant family followed by Poaceae (10 species) and then Asteraceae (7 species). Monocots were more dominant than Dicots and Angiosperms were more dominant than Gymnosperms. Among the life forms the Hemicryptophytes and Nanophanerophytes were dominant, followed by Therophytes, while among the leaf forms Microphylls were dominant, followed by Leptophylls. It is concluded that among the edaphic factors such as soil pH, the concentration of soil organic matter, Calcium Carbonates concentration in soil, soil EC, soil TDS, and physiographic factors such as Altitude and slope are affecting the structure of vegetation, species composition and species diversity at the significant level with p-value ≤0.05. The Vegetation of the selected area was classified into four major plants communities and the indicator species for each community was recorded. Classification of plants into 4 different communities based upon edaphic gradients favors the individualistic hypothesis. Indicator Species Analysis (ISA) shows the indicators of the study area are mostly indicators to the Himalayan or moist temperate ecosystem, furthermore, these indicators could be considered for micro-habitat conservation and respective ecosystem management plans.

Keywords: species richness, edaphic gradients, canonical correspondence analysis (CCA), TWCA

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Authors: Ahmet Karakuş, Akif Can Kilic, Emre Alptekin

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A growing number of studies have been conducted to determine how well-being may be predicted using well-designed models. It is necessary to investigate the backgrounds of features in order to construct a viable Subjective Well-Being (SWB) model. We have picked the suitable variables from the literature on SWB that are acceptable for real-world data instructions. The goal of this work is to evaluate the model by feeding it with SWB characteristics and then categorizing the stress levels using machine learning methods to see how well it performs on a real dataset. Despite the fact that it is a multiclass classification issue, we have achieved significant metric scores, which may be taken into account for a specific task.

Keywords: machine learning, multiclassification problem, subjective well-being, perceived stress scale

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Authors: Claudia Rodriguez-Espinosa, Erika Elizabeth Pérez Múzquiz

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Since the creation of the “Pueblos Mágicos” program in 2001, a series of social and cultural events had directly affected the heritage conservation of the 121 registered localities until 2018, when the federal government terminated the program. Many studies have been carried out that seek to analyze from different perspectives and disciplines the consequences that these appointments have generated in the “Pueblos Mágicos.” Multidisciplinary groups such as the one headed by Carmen Valverde and Liliana López Levi, have brought together specialists from all over the Mexican Republic to create a set of diagnoses of most of these settlements, and although each one has unique specificities, there is a constant in most of them that has to do with the loss of cultural heritage and that is related to transculturality. There are several factors identified that have fostered a cultural loss, as a direct reflection of the economic crisis that prevails in Mexico. It is important to remember that the origin of this program had as its main objective to promote the growth and development of local economies since one of the conditions for entering the program is that they have less than 20,000 inhabitants. With this goal in mind, one of the first actions that many “Pueblos Mágicos” carried out was to improve or create an infrastructure to receive both national and foreign tourists since this was practically non-existent. Creating hotels, restaurants, cafes, training certified tour guides, among other actions, have led to one of the great problems they face: globalization. Although by itself it is not bad, its impact in many cases has been negative for heritage conservation. The entry into and contact with new cultures has led to the undervaluation of cultural traditions, their transformation and even their total loss. This work seeks to present specific cases of transformation and loss of cultural heritage, as well as to reflect on the problem and propose scenarios in which the negative effects can be reversed. For this text, 36 “Pueblos Mágicos” have been selected for study, based on those settlements that are cited in volumes I and IV (the first and last of the collection) of the series produced by the multidisciplinary group led by Carmen Valverde and Liliana López Levi (researchers from UNAM and UAM Xochimilco respectively) in the project supported by CONACyT entitled “Pueblos Mágicos. An interdisciplinary vision”, of which we are part. This sample is considered representative since it forms 30% of the total of 121 “Pueblos Mágicos” existing at that moment. With this information, the elements of its intangible heritage loss or transformation have been identified in every chapter based on the texts written by the participants of that project. Finally, this text shows an analysis of the effects that this federal program, as a public policy applied to 132 populations, has had on the conservation or transformation of the intangible cultural heritage of the “Pueblos Mágicos.” Transculturality, globalization, the creation of identities and the desire to increase the flow of tourists have impacted the changes that traditions (main intangible cultural heritage) have had in the 18 years that the federal program lasted.

Keywords: public policies, cultural tourism, heritage preservation, pueblos mágicos program

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Authors: Lucas B. Naves, Maria José Abreu

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Reprocessing single-use device has attracted interesting on the medical environment over the last decades. The reprocessing technique was sought in order to reduce the cost of purchasing the new medical device, which can achieve almost double of the price of the reprocessed product. In this manuscript, we have done a literature review, aiming the reuse of medical device that was firstly designed for single use only, but has become, more and more, effective on its reprocessing procedure. We also show the regulation, the countries which allows this procedure, the classification of these device and also the most important issue concerning the re-utilization of medical device, how to minimizing the risk of gram positive and negative bacteria, avoid cross-contamination, hepatitis B (HBV), and C (HCV) virus, and also human immunodeficiency virus (HIV).

Keywords: reusing, reprocessing, single-use medical device, HIV, hepatitis B and C

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Authors: Basit Shahzad, Abdullatif M. Abdullatif

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Recent advancements in Information and Communication Technologies (ICT) and easy access to Internet have made social media the first choice for information sharing related to any important events or news. On Twitter, trend is a common feature that quantifies the level of popularity of a certain news or event. In this work, we examine the impact of Twitter trends on real world events by hypothesizing that Twitter trends have an influence on print media in Pakistan. For this, Twitter is used as a platform and Twitter trends as a base line. We first collect data from two sources (Twitter trends and print media) in the period May to August 2016. Obtained data from two sources is analyzed and it is observed that social media is significantly influencing the print media and majority of the news printed in newspaper are posted on Twitter earlier.

Keywords: twitter trends, text mining, effectiveness of trends, print media

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Authors: Heejin Yun, Juanjuan Zang

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This study aims to analyze the text terms posted on an online community of people from the same hometown and to understand the topic and trend of nostalgia composed online. For this purpose, this study collected 144 writings which the natives of Yeongjong Island, Incheon, South-Korea have posted on an online community. And it analyzed association relations. As a result, online community texts means that just defining nostalgia as ‘a mind longing for hometown’ is not an enough explanation. Second, texts composed online have abstractness rather than persons’ individual stories. This study figured out the relationship that had the most critical and closest mutual association among the terms that constituted nostalgia through literature research and association rule concerning nostalgia. The result of this study has a characteristic that it summed up the core terms and emotions related to nostalgia.

Keywords: nostalgia, cultural memory, data mining, association rule

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Authors: Cláudia Patrocínio, Beatriz Fernandes, Ana Filipa Pires

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Background: Mirror therapy (MT) is used to improve motor function after stroke. During MT, a mirror is placed between the two upper limbs (UL), thus reflecting movements of the non- affected side as if it were the affected side. Objectives: The aim of this review is to analyze the evidence on the effec.tiveness of MT in the recovery of UL function in population with post chronic stroke. Methods: The literature search was carried out in PubMed, ISI Web of Science, and PEDro database. Inclusion criteria: a) studies that include individuals diagnosed with stroke for at least 6 months; b) intervention with MT in UL or comparing it with other interventions; c) articles published until 2023; d) articles published in English or Portuguese; e) randomized controlled studies. Exclusion criteria: a) animal studies; b) studies that do not provide a detailed description of the intervention; c) Studies using central electrical stimulation. The methodological quality of the included studies was assessed using the Physiotherapy Evidence Database (PEDro) scale. Studies with < 4 on PEDro scale were excluded. Eighteen studies met all the inclusion criteria. Main results and conclusions: The quality of the studies varies between 5 and 8. One article compared muscular strength training (MST) with MT vs without MT and four articles compared the use of MT vs conventional therapy (CT), one study compared extracorporeal shock therapy (EST) with and without MT and another study compared functional electrical stimulation (FES), MT and biofeedback, three studies compared MT with Mesh Glove (MG) or Sham Therapy, five articles compared performing bimanual exercises with and without MT and three studies compared MT with virtual reality (VR) or robot training (RT). The assessment of changes in function and structure (International Classification of Functioning, Disability and Health parameter) was carried out, in each article, mainly using the Fugl Meyer Assessment-Upper Limb scale, activity and participation (International Classification of Functioning, Disability and Health parameter) were evaluated using different scales, in each study. The positive results were seen in these parameters, globally. Results suggest that MT is more effective than other therapies in motor recovery and function of the affected UL, than these techniques alone, although the results have been modest in most of the included studies. There is also a more significant improvement in the distal movements of the affected hand than in the rest of the UL.

Keywords: physical therapy, mirror therapy, chronic stroke, upper limb, hemiplegia

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Authors: Adnan H. M. Al-Helali, Hamza A. Ali

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Growth of censorship and pervasive monitoring on the Internet, Steganography arises as a new means of achieving secret communication. Steganography is the art and science of embedding information within electronic media used by common applications and systems. Generally, hiding information of multimedia within images will change some of their properties that may introduce few degradation or unusual characteristics. This paper presents a new image steganography approach for hiding information of multimedia (images, text, and audio) using generated Mandelbrot Fractal image as a cover. The proposed technique has been extensively tested with different images. The results show that the method is a very secure means of hiding and retrieving steganographic information. Experimental results demonstrate that an effective improvement in the values of the Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Normalized Cross Correlation (NCC) and Image Fidelity (IF) over the previous techniques.

Keywords: fractal image, information hiding, Mandelbrot et fractal, steganography

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Authors: Zeinab Jafari A., Ali Sharifnezhad B., Mohammad Razi C., Mohammad Haghpanahi D., Arash Maghsoudi

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Background and Objective: Sports-related rupture of the anterior cruciate ligament (ACL) and following injuries have been associated with various disorders, such as long-lasting changes in muscle activation patterns in athletes, which might last after ACL reconstruction (ACLR). The rupture of the ACL might result in abnormal patterns of movement execution, extending the treatment period and delaying athletes’ return to sports (RTS). As ACL injury is especially prevalent among athletes, the lengthy treatment process and athletes’ absence from sports are of great concern to athletes and coaches. Thus, estimating safe time of RTS is of crucial importance. Therefore, using a deep neural network (DNN) to classify the health levels of ACL in injured athletes, this study aimed to estimate the safe time for athletes to return to competitions. Methods: Ten athletes with ACLR and fourteen healthy controls participated in this study. Three health levels of ACL were defined: healthy, six-month post-ACLR surgery and nine-month post-ACLR surgery. Athletes with ACLR were tested six and nine months after the ACLR surgery. During the course of this study, surface electromyography (sEMG) signals were recorded from five knee muscles, namely Rectus Femoris (RF), Vastus Lateralis (VL), Vastus Medialis (VM), Biceps Femoris (BF), Semitendinosus (ST), during single-leg drop landing (SLDL) and forward hopping (SLFH) tasks. The Pseudo-Wigner-Ville distribution (PWVD) was used to produce three-dimensional (3-D) images of the energy distribution patterns of sEMG signals. Then, these 3-D images were converted to two-dimensional (2-D) images implementing the heat mapping technique, which were then fed to a deep convolutional neural network (DCNN). Results: In this study, we estimated the safe time of RTS by designing a DCNN classifier with an accuracy of 90 %, which could classify ACL into three health levels. Discussion: The findings of this study demonstrate the potential of the DCNN classification technique using sEMG signals in estimating RTS time, which will assist in evaluating the recovery process of ACLR in athletes.

Keywords: anterior cruciate ligament reconstruction, return to sports, surface electromyography, deep convolutional neural network

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Authors: Andrey V. Timofeev

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The paper presents new results concerning selection of optimal information fusion formula for ensembles of C-OTDR channels. The goal of information fusion is to create an integral classificator designed for effective classification of seismoacoustic target events. The LPBoost (LP-β and LP-B variants), the Multiple Kernel Learning, and Weighing of Inversely as Lipschitz Constants (WILC) approaches were compared. The WILC is a brand new approach to optimal fusion of Lipschitz Classifiers Ensembles. Results of practical usage are presented.

Keywords: Lipschitz Classifier, classifiers ensembles, LPBoost, C-OTDR systems

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Authors: Kseniia Fedorova

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The article is devoted to interlinguistic homonymy and enantiosemy analysis. These phenomena belong to the process of linguistic interference, which leads to violation of the communicative utterances integrity and causes misunderstanding between foreign interlocutors - native speakers of different Slavic languages. More attention is paid to investigation of non-typical speech situations, which occurred spontaneously or created by somebody intentionally being based on described phenomenon mechanism. The classification of typical students' mistakes connected with the paradox of interference is being represented in the article. The survey contributes to speech act theory, contemporary linguodidactics, translation science and comparative lexicology of Slavonic languages.

Keywords: adherent enantiosemy, interference, interslavonic homonymy, speech act

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Authors: Aayushi Pandey, Manoj Kumar Pandey, Ashutosh Tiwari, Kireet Kumar

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Glaciers play an important role in climate change and are sensitive phenomena of global climate change scenario. Glaciers in Himalayas are unique as they are predominantly valley type and are located in tropical, high altitude regions. These glaciers are often covered with debris which greatly affects ablation rate of glaciers and work as a sensitive indicator of glacier health. The aim of this study is to map high altitude Glacier surface with a focus on glacial lake and debris estimation using different techniques in Nagling glacier of dhauliganga basin in Himalayan region. Different Image Classification techniques i.e. thresholding on different band ratios and supervised classification using maximum likelihood classifier (MLC) have been used on high resolution sentinel 2A level 1c satellite imagery of 14 October 2017.Here Near Infrared (NIR)/Shortwave Infrared (SWIR) ratio image was used to extract the glaciated classes (Snow, Ice, Ice Mixed Debris) from other non-glaciated terrain classes. SWIR/BLUE Ratio Image was used to map valley rock and Debris while Green/NIR ratio image was found most suitable for mapping Glacial Lake. Accuracy assessment was performed using high resolution (3 meters) Planetscope Imagery using 60 stratified random points. The overall accuracy of MLC was 85 % while the accuracy of Band Ratios was 96.66 %. According to Band Ratio technique total areal extent of glaciated classes (Snow, Ice ,IMD) in Nagling glacier was 10.70 km2 nearly 38.07% of study area comprising of 30.87 % Snow covered area, 3.93% Ice and 3.27 % IMD covered area. Non-glaciated classes (vegetation, glacial lake, debris and valley rock) covered 61.93 % of the total area out of which valley rock is dominant with 33.83% coverage followed by debris covering 27.7 % of the area in nagling glacier. Glacial lake and Debris were accurately mapped using Band ratio technique Hence, Band Ratio approach appears to be useful for the mapping of debris covered glacier in Himalayan Region.

Keywords: band ratio, Dhauliganga basin, glacier mapping, Himalayan region, maximum likelihood classifier (MLC), Sentinel-2 satellite image

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Authors: Igor A. Podgorny

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TurboTax AnswerXchange is a social Q/A system supporting users working on federal and state tax returns. Content quality and popularity in the AnswerXchange can be predicted with propensity models using attributes of the question and answer. Using uplift modeling, we identify features of questions and answers that can be modified during the question-asking and question-answering experience in order to optimize the AnswerXchange content quality. We demonstrate that adding details to the questions always results in increased question popularity that can be used to promote good quality content. Responding to close-ended questions assertively improve content quality in the AnswerXchange in 90% of cases. Answering knowledge questions with web links increases the likelihood of receiving a negative vote from 60% of the askers. Our findings provide a rationale for employing the uplift modeling approach for AnswerXchange operations.

Keywords: customer relationship management, human-machine interaction, text mining, uplift modeling

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Authors: Carlos Arias-Alcaide, Cristina Soguero-Ruiz, Paloma Santos-Álvarez, Adrián García-Romero, Inmaculada Mora-Jiménez

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Analysing clinical data with computers in such a way that have an impact on the practitioners’ workflow is a challenge nowadays. This paper provides a first approach for monitoring the health status of COVID-19 patients through the use of some biomarkers (blood tests) and the simplest Naïve Bayes classifier. Data of two Spanish hospitals were considered, showing the potential of our approach to estimate reasonable posterior probabilities even some days before the event.

Keywords: Bayesian model, blood biomarkers, classification, health tracing, machine learning, posterior probability

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Authors: J. R. Wang, S. W. Chen, Y. Chiang, W. S. Hsu, J. H. Yang, Y. S. Tseng, C. Shih

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In this research, the HABIT analysis methodology was established for Maanshan nuclear power plant (NPP). The Final Safety Analysis Report (FSAR), reports, and other data were used in this study. To evaluate the control room habitability under the CO₂ storage burst, the HABIT methodology was used to perform this analysis. The HABIT result was below the R.G. 1.78 failure criteria. This indicates that Maanshan NPP habitability can be maintained. Additionally, the sensitivity study of the parameters (wind speed, atmospheric stability classification, air temperature, and control room intake flow rate) was also performed in this research.

Keywords: PWR, HABIT, Habitability, Maanshan

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Authors: Y. Chiang, W. Y. Li, J. R. Wang, S. W. Chen, W. S. Hsu, J. H. Yang, Y. S. Tseng, C. Shih

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In this research, the HABIT code was used to estimate the concentration under the CO₂ and H₂SO₄ storage burst conditions for Kuosheng nuclear power plant (NPP). The Final Safety Analysis Report (FSAR) and reports were used in this research. In addition, to evaluate the control room habitability for these cases, the HABIT analysis results were compared with the R.G. 1.78 failure criteria. The comparison results show that the HABIT results are below the criteria. Additionally, some sensitivity studies (stability classification, wind speed and control room intake rate) were performed in this study.

Keywords: BWR, HABIT, habitability, Kuosheng

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Authors: Dorra Kallel, Ines Kanoun, Diala Dhouib

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This paper elaborates a Systematic Literature Review SLR) to select the most outstanding studies that address the Menu Planning Problem (MPP) and to classify them according to the to the three following criteria: the used methods, types of patients and the required constraints. At first, a set of 4165 studies was selected. After applying the SLR’s guidelines, this collection was filtered to 13 studies using specific inclusion and exclusion criteria as well as an accurate analysis of each study. Second, the selected papers were invested to answer the proposed research questions. Finally, data synthesis and new perspectives for future works are incorporated in the closing section.

Keywords: Menu Planning Problem (MPP), Systematic Literature Review (SLR), classification, exact and approaches methods

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Authors: Johan Anker

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The purpose of this paper is to discuss the nature of gender construction in modern dystopian fiction, the development of this genre in Young Adult Literature and reasons for the enormous appeal on the adolescent readers. A recent award winning South African text in this genre, The Mark by Edith Bullring (2014), will be used as example while also comparing this text to international bestsellers like Divergent (Roth:2011), The Hunger Games (Collins:2008) and others. Theoretical insights from critics and academics in the field of children’s literature, like Ames, Coats, Bradford, Booker, Basu, Green-Barteet, Hintz, McAlear, McCallum, Moylan, Ostry, Ryan, Stephens and Westerfield will be referred to and their insights used as part of the analysis of The Mark. The role of relevant and recurring themes in this genre, like global concerns, environmental destruction, liberty, self-determination, social and political critique, surveillance and repression by the state or other institutions will also be referred to. The paper will shortly refer to the history and emergence of dystopian literature as genre in adult and young adult literature as part of the long tradition since the publishing of Orwell’s 1984 and Huxley’s Brave New World. Different factors appeal to adolescent readers in the modern versions of this hybrid genre for young adults: teenage protagonists who are questioning the underlying values of a flawed society like an inhuman or tyrannical government, a growing understanding of the society around them, feelings of isolation and the dynamic of relationships. This unease leads to a growing sense of the potential to act against society (rebellion), and of their role as agents in a larger community and independent decision-making abilities. This awareness also leads to a growing sense of self (identity and agency) and the development of romantic relationships. The specific modern tendency of a female protagonist as leader in the rebellion against state and state apparatus, who gains in agency and independence in this rebellion, an important part of the identification with and construction of gender, while being part of the traditional coming-of-age young adult novel will be emphasized. A comparison between the traditional themes, structures and plots of young adult literature (YAL) with adult dystopian literature and those of recent dystopian YAL will be made while the hybrid nature of this genre and the 'sense of unease' but also of hope, as an essential part of youth literature, in the closure to these novels will be discussed. Important questions about the role of the didactic nature of these texts and the political issues and the importance of the formation of agency and identity for the young adult reader, as well as identification with the protagonists in this genre, are also part of this discussion of The Mark and other YAL novels.

Keywords: agency, dystopian literature, gender construction, young adult literature

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Authors: Shraddha Chaudhary, Raksha Agarwal, Niladri Chatterjee

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This work demonstrates a web crawler-based generalized end-to-end open domain Question Answering (QA) system. An efficient QA system requires a significant amount of domain knowledge to answer any question with the aim to find an exact and correct answer in the form of a number, a noun, a short phrase, or a brief piece of text for the user's questions. Analysis of the question, searching the relevant document, and choosing an answer are three important steps in a QA system. This work uses a web scraper (Beautiful Soup) to extract K-documents from the web. The value of K can be calibrated on the basis of a trade-off between time and accuracy. This is followed by a passage ranking process using the MS-Marco dataset trained on 500K queries to extract the most relevant text passage, to shorten the lengthy documents. Further, a QA system is used to extract the answers from the shortened documents based on the query and return the top 3 answers. For evaluation of such systems, accuracy is judged by the exact match between predicted answers and gold answers. But automatic evaluation methods fail due to the linguistic ambiguities inherent in the questions. Moreover, reference answers are often not exhaustive or are out of date. Hence correct answers predicted by the system are often judged incorrect according to the automated metrics. One such scenario arises from the original Google Natural Question (GNQ) dataset which was collected and made available in the year 2016. Use of any such dataset proves to be inefficient with respect to any questions that have time-varying answers. For illustration, if the query is where will be the next Olympics? Gold Answer for the above query as given in the GNQ dataset is “Tokyo”. Since the dataset was collected in the year 2016, and the next Olympics after 2016 were in 2020 that was in Tokyo which is absolutely correct. But if the same question is asked in 2022 then the answer is “Paris, 2024”. Consequently, any evaluation based on the GNQ dataset will be incorrect. Such erroneous predictions are usually given to human evaluators for further validation which is quite expensive and time-consuming. To address this erroneous evaluation, the present work proposes an automated approach for evaluating time-dependent question-answer pairs. In particular, it proposes a metric using the current timestamp along with top-n predicted answers from a given QA system. To test the proposed approach GNQ dataset has been used and the system achieved an accuracy of 78% for a test dataset comprising 100 QA pairs. This test data was automatically extracted using an analysis-based approach from 10K QA pairs of the GNQ dataset. The results obtained are encouraging. The proposed technique appears to have the possibility of developing into a useful scheme for gathering precise, reliable, and specific information in a real-time and efficient manner. Our subsequent experiments will be guided towards establishing the efficacy of the above system for a larger set of time-dependent QA pairs.

Keywords: web-based information retrieval, open domain question answering system, time-varying QA, QA evaluation

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Authors: Adnan H. M. Al-Helali, Hamza A. Ali

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The growth of censorship and pervasive monitoring on the Internet, Steganography arises as a new means of achieving secret communication. Steganography is the art and science of embedding information within electronic media used by common applications and systems. Generally, hiding information of multimedia within images will change some of their properties that may introduce few degradation or unusual characteristics. This paper presents a new image steganography approach for hiding information of multimedia (images, text, and audio) using generated Mandelbrot Fractal image as a cover. The proposed technique has been extensively tested with different images. The results show that the method is a very secure means of hiding and retrieving steganographic information. Experimental results demonstrate that an effective improvement in the values of the Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Normalized Cross Correlation (NCC), and Image Fidelity (IF) over the pervious techniques.

Keywords: fractal image, information hiding, Mandelbrot set fractal, steganography

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Authors: Baldev Setia, Raj Rajeshwari, Maneesh Kumar

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Present paper is an analysis of water transmission mains failed due to surge analysis by using basic software known as Surge Analysis Program (SAP). It is a real time failure case study of a pipe laid in Una, Himachal Pradesh. The transmission main is a 13 kilometer long pipe with 7.9 kilometers as pumping main and 5.1 kilometers as gravitational main. The analysis deals with mainly pumping mains. The results are available in two text files. Besides, several files are prepared with specific view to obtain results in a graphical form. These results help to observe the pressure difference and surge occurrence at different locations along the pipe profile, which help to redesign the transmission main with different but suitable safety measures against possible surge. A technically viable and economically feasible design has been provided as per the relevant manual and standard code of practice.

Keywords: surge, water hammer, transmission mains, SAP 2000

Procedia PDF Downloads 366

Authors: Alicia Yanadira Nava Fuentes, Ilse Cervantes Camacho, Amadeo José Argüelles Cruz, Ana María Balboa Verduzco

Abstract:

Augmented reality promises being present in future driving, with its immersive technology let to show directions and maps to identify important places indicating with graphic elements when the car driver requires the information. On the other side, driving is considered a multitasking activity and, for some people, a complex activity where different situations commonly occur that require the immediate attention of the car driver to make decisions that contribute to avoid accidents; therefore, the main aim of the project is the instrumentation of a platform with biometric sensors that allows evaluating the performance in driving vehicles with the influence of augmented reality devices to detect the level of attention in drivers, since it is important to know the effect that it produces. In this study, the physiological sensors EPOC X (EEG), ECG06 PRO and EMG Myoware are joined in the driving test platform with a Logitech G29 steering wheel and the simulation software City Car Driving in which the level of traffic can be controlled, as well as the number of pedestrians that exist within the simulation obtaining a driver interaction in real mode and through a MSP430 microcontroller achieves the acquisition of data for storage. The sensors bring a continuous analog signal in time that needs signal conditioning, at this point, a signal amplifier is incorporated due to the acquired signals having a sensitive range of 1.25 mm/mV, also filtering that consists in eliminating the frequency bands of the signal in order to be interpretative and without noise to convert it from an analog signal into a digital signal to analyze the physiological signals of the drivers, these values are stored in a database. Based on this compilation, we work on the extraction of signal features and implement K-NN (k-nearest neighbor) classification methods and decision trees (unsupervised learning) that enable the study of data for the identification of patterns and determine by classification methods different effects of augmented reality on drivers. The expected results of this project include are a test platform instrumented with biometric sensors for data acquisition during driving and a database with the required variables to determine the effect caused by augmented reality on people in simulated driving.

Keywords: augmented reality, driving, physiological signals, test platform

Procedia PDF Downloads 142