Search results for: Kazakh speech dataset
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1852

Search results for: Kazakh speech dataset

892 Integration of Resistivity and Seismic Refraction Using Combine Inversion for Ancient River Findings at Sungai Batu, Lembah Bujang, Malaysia

Authors: Rais Yusoh, Rosli Saad, Mokhtar Saidin, Fauzi Andika, Sabiu Bala Muhammad

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Resistivity and seismic refraction profiling have become a common method in pre-investigations for visualizing subsurface structure. The integration of the methods could reduce an interpretation ambiguity. Both methods have their individual software packages for data inversion, but potential to combine certain geophysical methods are restricted; however, the research algorithms that have this functionality was existed and are evaluated personally. The interpretation of subsurface were improve by combining inversion data from both methods by influence each other models using closure coupling; thus, by implementing both methods to support each other which could improve the subsurface interpretation. These methods were applied on a field dataset from a pre-investigation for archeology in finding the ancient river. There were no major changes in the inverted model by combining data inversion for this archetype which probably due to complex geology. The combine data analysis provides an additional technique for interpretation such as an alluvium, which can have strong influence on the ancient river findings.

Keywords: ancient river, combine inversion, resistivity, seismic refraction

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891 On the Bias and Predictability of Asylum Cases

Authors: Panagiota Katsikouli, William Hamilton Byrne, Thomas Gammeltoft-Hansen, Tijs Slaats

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An individual who demonstrates a well-founded fear of persecution or faces real risk of being subjected to torture is eligible for asylum. In Danish law, the exact legal thresholds reflect those established by international conventions, notably the 1951 Refugee Convention and the 1950 European Convention for Human Rights. These international treaties, however, remain largely silent when it comes to how states should assess asylum claims. As a result, national authorities are typically left to determine an individual’s legal eligibility on a narrow basis consisting of an oral testimony, which may itself be hampered by several factors, including imprecise language interpretation, insecurity or lacking trust towards the authorities among applicants. The leaky ground, on which authorities must assess their subjective perceptions of asylum applicants' credibility, questions whether, in all cases, adjudicators make the correct decision. Moreover, the subjective element in these assessments raises questions on whether individual asylum cases could be afflicted by implicit biases or stereotyping amongst adjudicators. In fact, recent studies have uncovered significant correlations between decision outcomes and the experience and gender of the assigned judge, as well as correlations between asylum outcomes and entirely external events such as weather and political elections. In this study, we analyze a publicly available dataset containing approximately 8,000 summaries of asylum cases, initially rejected, and re-tried by the Refugee Appeals Board (RAB) in Denmark. First, we look for variations in the recognition rates, with regards to a number of applicants’ features: their country of origin/nationality, their identified gender, their identified religion, their ethnicity, whether torture was mentioned in their case and if so, whether it was supported or not, and the year the applicant entered Denmark. In order to extract those features from the text summaries, as well as the final decision of the RAB, we applied natural language processing and regular expressions, adjusting for the Danish language. We observed interesting variations in recognition rates related to the applicants’ country of origin, ethnicity, year of entry and the support or not of torture claims, whenever those were made in the case. The appearance (or not) of significant variations in the recognition rates, does not necessarily imply (or not) bias in the decision-making progress. None of the considered features, with the exception maybe of the torture claims, should be decisive factors for an asylum seeker’s fate. We therefore investigate whether the decision can be predicted on the basis of these features, and consequently, whether biases are likely to exist in the decisionmaking progress. We employed a number of machine learning classifiers, and found that when using the applicant’s country of origin, religion, ethnicity and year of entry with a random forest classifier, or a decision tree, the prediction accuracy is as high as 82% and 85% respectively. tentially predictive properties with regards to the outcome of an asylum case. Our analysis and findings call for further investigation on the predictability of the outcome, on a larger dataset of 17,000 cases, which is undergoing.

Keywords: asylum adjudications, automated decision-making, machine learning, text mining

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890 The Potential and Economic Viability Analysis of Grid-Connected Solar PV Power in Kenya

Authors: Remember Samu, Kathy Kiema, Murat Fahrioglu

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This present study is aimed at minimizing the dependence on fossil fuels thus reducing greenhouse gas (GHG) emissions and also to curb for the rising energy demands in Kenya. In this analysis, 35 locations were each considered for their techno-economic potential of installation of a 10MW grid-connected PV plant. The sites are scattered across the country but are mostly concentrated in the eastern region and were selected based on their accessibility to the national grid and availability of their meteorological parameters from NASA Solar Energy Dataset. RETScreen software 4.0 version will be employed for the analysis in this present paper. The capacity factor, simple payback, equity payback, the net present value (NPV), annual life cycle savings, energy production cost, net annual greenhouse gas emission reduction and the equivalent barrels of crude oil not consumed are outlined. Energy accounting is performed and compared to the existing grid tariff for an effective feasibility argument of this 10MW grid-connected PV power system.

Keywords: photovoltaics, project viability analysis, PV module, renewable energy

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889 Flexible Cities: A Multisided Spatial Application of Tracking Livability of Urban Environment

Authors: Maria Christofi, George Plastiras, Rafaella Elia, Vaggelis Tsiourtis, Theocharis Theocharides, Miltiadis Katsaros

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The rapidly expanding urban areas of the world constitute a challenge of how we need to make the transition to "the next urbanization", which will be defined by new analytical tools and new sources of data. This paper is about the production of a spatial application, the ‘FUMapp’, where space and its initiative will be available literally, in meters, but also abstractly, at a sensed level. While existing spatial applications typically focus on illustrations of the urban infrastructure, the suggested application goes beyond the existing: It investigates how our environment's perception adapts to the alterations of the built environment through a dataset construction of biophysical measurements (eye-tracking, heart beating), and physical metrics (spatial characteristics, size of stimuli, rhythm of mobility). It explores the intersections between architecture, cognition, and computing where future design can be improved and identifies the flexibility and livability of the ‘available space’ of specific examined urban paths.

Keywords: biophysical data, flexibility of urban, livability, next urbanization, spatial application

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888 Pawn or Potentates: Corporate Governance Structure in Indian Central Public Sector Enterprises

Authors: Ritika Jain, Rajnish Kumar

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The Department of Public Enterprises had made submissions of Self Evaluation Reports, for the purpose of corporate governance, mandatory for all central government owned enterprises. Despite this, an alarming 40% of the enterprises did not do so. This study examines the impact of external policy tools and internal firm-specific factors on corporate governance of central public sector enterprises (CPSEs). We use a dataset of all manufacturing and non-financial services owned by the central government of India for the year 2010-11. Using probit, ordered logit and Heckman’s sample selection models, the study finds that the probability and quality of corporate governance is positively influenced by the CPSE getting into a Memorandum of Understanding (MoU) with the central government of India, and hence, enjoying more autonomy in terms of day to day operations. Besides these, internal factors, including bigger size and lower debt size contribute significantly to better corporate governance.

Keywords: corporate governance, central public sector enterprises (CPSEs), sample selection, Memorandum of Understanding (MoU), ordered logit, disinvestment

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887 Classification of Political Affiliations by Reduced Number of Features

Authors: Vesile Evrim, Aliyu Awwal

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By the evolvement in technology, the way of expressing opinions switched the direction to the digital world. The domain of politics as one of the hottest topics of opinion mining research merged together with the behavior analysis for affiliation determination in text which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 are constituted by Linguistic Inquiry and Word Count (LIWC) features are tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that Decision Tree, Rule Induction and M5 Rule classifiers when used with SVM and IGR feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “function” as an aggregate feature of the linguistic category, is obtained as the most differentiating feature among the 68 features with 81% accuracy by itself in classifying articles either as Republican or Democrat.

Keywords: feature selection, LIWC, machine learning, politics

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886 Acquisition of Anticipatory Coarticulation in Italian-Speaking Children: An Acoustic Study

Authors: Patrizia Bonaventura

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The aim of this study is to analyze the influence of prosody on the acquisition of temporal aspects of V-V anticipatory lingual coarticulation in productions by Italian-speaking children. Two twin 7-years old male children, native Italian speakers, interacted with the same adult, repeating nonsense disyllables containing VtV sequences where V1 = {i, a} and V2 = {a,e, i, o,u}, with different stress patterns (e.g. pi’ta, pi’ta). The duration of the VC F2 transitions and the CV/VC F2 transitions durations ratios in different V2 contexts and stress conditions were measured by spectrographic analysis and compared between pronunciations by each child vs. the adult to test whether the child was able to imitate the duration of the transitions as produced by the adult in different stress conditions. Consequences highlighted a significant difference in durations of VC transitions between children and adult: longer VC transitions durations, indicating a greater amount of coarticulation, were found for one child in every context, and for the other, only in stressed [it] sequences. The data support the hypothesis of the presence of different temporal patterns of anticipatory coarticulation in adults and children, and of a greater amount of coarticulation in children, with different strategies of implementation across different prosodic conditions.

Keywords: speech acquisition, coarticulation, Italian language, prosody

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885 Local Boundary Analysis for Generative Theory of Tonal Music: From the Aspect of Classic Music Melody Analysis

Authors: Po-Chun Wang, Yan-Ru Lai, Sophia I. C. Lin, Alvin W. Y. Su

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The Generative Theory of Tonal Music (GTTM) provides systematic approaches to recognizing local boundaries of music. The rules have been implemented in some automated melody segmentation algorithms. Besides, there are also deep learning methods with GTTM features applied to boundary detection tasks. However, these studies might face constraints such as a lack of or inconsistent label data. The GTTM database is currently the most widely used GTTM database, which includes manually labeled GTTM rules and local boundaries. Even so, we found some problems with these labels. They are sometimes discrepancies with GTTM rules. In addition, since it is labeled at different times by multiple musicians, they are not within the same scope in some cases. Therefore, in this paper, we examine this database with musicians from the aspect of classical music and relabel the scores. The relabeled database - GTTM Database v2.0 - will be released for academic research usage. Despite the experimental and statistical results showing that the relabeled database is more consistent, the improvement in boundary detection is not substantial. It seems that we need more clues than GTTM rules for boundary detection in the future.

Keywords: dataset, GTTM, local boundary, neural network

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884 Generative Adversarial Network for Bidirectional Mappings between Retinal Fundus Images and Vessel Segmented Images

Authors: Haoqi Gao, Koichi Ogawara

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Retinal vascular segmentation of color fundus is the basis of ophthalmic computer-aided diagnosis and large-scale disease screening systems. Early screening of fundus diseases has great value for clinical medical diagnosis. The traditional methods depend on the experience of the doctor, which is time-consuming, labor-intensive, and inefficient. Furthermore, medical images are scarce and fraught with legal concerns regarding patient privacy. In this paper, we propose a new Generative Adversarial Network based on CycleGAN for retinal fundus images. This method can generate not only synthetic fundus images but also generate corresponding segmentation masks, which has certain application value and challenge in computer vision and computer graphics. In the results, we evaluate our proposed method from both quantitative and qualitative. For generated segmented images, our method achieves dice coefficient of 0.81 and PR of 0.89 on DRIVE dataset. For generated synthetic fundus images, we use ”Toy Experiment” to verify the state-of-the-art performance of our method.

Keywords: retinal vascular segmentations, generative ad-versarial network, cyclegan, fundus images

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883 The Inequality Effects of Natural Disasters: Evidence from Thailand

Authors: Annop Jaewisorn

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This study explores the relationship between natural disasters and inequalities -both income and expenditure inequality- at a micro-level of Thailand as the first study of this nature for this country. The analysis uses a unique panel and remote-sensing dataset constructed for the purpose of this research. It contains provincial inequality measures and other economic and social indicators based on the Thailand Household Survey during the period between 1992 and 2019. Meanwhile, the data on natural disasters, which are remote-sensing data, are received from several official geophysical or meteorological databases. Employing a panel fixed effects, the results show that natural disasters significantly reduce household income and expenditure inequality as measured by the Gini index, implying that rich people in Thailand bear a higher cost of natural disasters when compared to poor people. The effect on income inequality is mainly driven by droughts, while the effect on expenditure inequality is mainly driven by flood events. The results are robust across heterogeneity of the samples, lagged effects, outliers, and an alternative inequality measure.

Keywords: inequality, natural disasters, remote-sensing data, Thailand

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882 Longitudinal Study of the Phenomenon of Acting White in Hungarian Elementary Schools Analysed by Fixed and Random Effects Models

Authors: Lilla Dorina Habsz, Marta Rado

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Popularity is affected by a variety of factors in the primary school such as academic achievement and ethnicity. The main goal of our study was to analyse whether acting white exists in Hungarian elementary schools. In other words, we observed whether Roma students penalize those in-group members who obtain the high academic achievement. Furthermore, to show how popularity is influenced by changes in academic achievement in inter-ethnic relations. The empirical basis of our research was the 'competition and negative networks' longitudinal dataset, which was collected by the MTA TK 'Lendület' RECENS research group. This research followed 11 and 12-year old students for a two-year period. The survey was analysed using fixed and random effect models. Overall, we found a positive correlation between grades and popularity, but no evidence for the acting white effect. However, better grades were more positively evaluated within the majority group than within the minority group, which may further increase inequalities.

Keywords: academic achievement, elementary school, ethnicity, popularity

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881 Weed Classification Using a Two-Dimensional Deep Convolutional Neural Network

Authors: Muhammad Ali Sarwar, Muhammad Farooq, Nayab Hassan, Hammad Hassan

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Pakistan is highly recognized for its agriculture and is well known for producing substantial amounts of wheat, cotton, and sugarcane. However, some factors contribute to a decline in crop quality and a reduction in overall output. One of the main factors contributing to this decline is the presence of weed and its late detection. This process of detection is manual and demands a detailed inspection to be done by the farmer itself. But by the time detection of weed, the farmer will be able to save its cost and can increase the overall production. The focus of this research is to identify and classify the four main types of weeds (Small-Flowered Cranesbill, Chick Weed, Prickly Acacia, and Black-Grass) that are prevalent in our region’s major crops. In this work, we implemented three different deep learning techniques: YOLO-v5, Inception-v3, and Deep CNN on the same Dataset, and have concluded that deep convolutions neural network performed better with an accuracy of 97.45% for such classification. In relative to the state of the art, our proposed approach yields 2% better results. We devised the architecture in an efficient way such that it can be used in real-time.

Keywords: deep convolution networks, Yolo, machine learning, agriculture

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880 Single Cell Analysis of Circulating Monocytes in Prostate Cancer Patients

Authors: Leander Van Neste, Kirk Wojno

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The innate immune system reacts to foreign insult in several unique ways, one of which is phagocytosis of perceived threats such as cancer, bacteria, and viruses. The goal of this study was to look for evidence of phagocytosed RNA from tumor cells in circulating monocytes. While all monocytes possess phagocytic capabilities, the non-classical CD14+/FCGR3A+ monocytes and the intermediate CD14++/FCGR3A+ monocytes most actively remove threatening ‘external’ cellular materials. Purified CD14-positive monocyte samples from fourteen patients recently diagnosed with clinically localized prostate cancer (PCa) were investigated by single-cell RNA sequencing using the 10X Genomics protocol followed by paired-end sequencing on Illumina’s NovaSeq. Similarly, samples were processed and used as controls, i.e., one patient underwent biopsy but was found not to harbor prostate cancer (benign), three young, healthy men, and three men previously diagnosed with prostate cancer that recently underwent (curative) radical prostatectomy (post-RP). Sequencing data were mapped using 10X Genomics’ CellRanger software and viable cells were subsequently identified using CellBender, removing technical artifacts such as doublets and non-cellular RNA. Next, data analysis was performed in R, using the Seurat package. Because the main goal was to identify differences between PCa patients and ‘control’ patients, rather than exploring differences between individual subjects, the individual Seurat objects of all 21 patients were merged into one Seurat object per Seurat’s recommendation. Finally, the single-cell dataset was normalized as a whole prior to further analysis. Cell identity was assessed using the SingleR and cell dex packages. The Monaco Immune Data was selected as the reference dataset, consisting of bulk RNA-seq data of sorted human immune cells. The Monaco classification was supplemented with normalized PCa data obtained from The Cancer Genome Atlas (TCGA), which consists of bulk RNA sequencing data from 499 prostate tumor tissues (including 1 metastatic) and 52 (adjacent) normal prostate tissues. SingleR was subsequently run on the combined immune cell and PCa datasets. As expected, the vast majority of cells were labeled as having a monocytic origin (~90%), with the most noticeable difference being the larger number of intermediate monocytes in the PCa patients (13.6% versus 7.1%; p<.001). In men harboring PCa, 0.60% of all purified monocytes were classified as harboring PCa signals when the TCGA data were included. This was 3-fold, 7.5-fold, and 4-fold higher compared to post-RP, benign, and young men, respectively (all p<.001). In addition, with 7.91%, the number of unclassified cells, i.e., cells with pruned labels due to high uncertainty of the assigned label, was also highest in men with PCa, compared to 3.51%, 2.67%, and 5.51% of cells in post-RP, benign, and young men, respectively (all p<.001). It can be postulated that actively phagocytosing cells are hardest to classify due to their dual immune cell and foreign cell nature. Hence, the higher number of unclassified cells and intermediate monocytes in PCa patients might reflect higher phagocytic activity due to tumor burden. This also illustrates that small numbers (~1%) of circulating peripheral blood monocytes that have interacted with tumor cells might still possess detectable phagocytosed tumor RNA.

Keywords: circulating monocytes, phagocytic cells, prostate cancer, tumor immune response

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879 Intended-Actual First Asking/Offer Price Discrepancies and Their Impact on Negotiation Behaviour and Outcomes

Authors: Liuyao Chai, Colin Clark

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Analysis of 574 participants in a simulated two-person distributive negotiation revealed that the first price 245 (42.7%) of these participants actually asked/offered for the item under negotiation (a used car) differed from the first price they previously stated they intended to ask/offer during their negotiation. This discrepancy between a negotiator’s intended first asking/offer price and his/her actual first asking/offer price had a significant and economically consequential impact on both the course and the outcomes of the negotiations studied. Participants whose actual first price remained the same as their intended first price tended to secure better negotiation outcomes. Moreover, participants who changed their intended first price tended to obtain relatively lower outcomes regardless of whether their modified first announced price had created a negotiating position that was ‘stronger’ or ‘weaker’ than if they had opened with their intended first price. Subsequent investigation of over twenty negotiation behaviours and pre-negotiation perceptual variables within this dataset indicated that the three types of first price announcers—i.e. intended first asking/offer price ‘weakeners’, ‘maintainers’ and ‘strengtheners’— comprised persons who tended to have significantly different pre-negotiation perceptions and behaved in systematically different ways during their negotiation. Typically, the most negative, outcome-compromising consequences of changing, weakening or strengthening an intended first price occurred at the very beginning of a negotiation when participants exchanged their actual first asking/offer prices.

Keywords: business communication, negotiation, persuasion, intended first asking/offer prices, bargaining

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878 Living Arrangement of Elderly in India: An Exploration from BKPAI Study

Authors: Jitendra Gouda, Chander Shekhar

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With the addition of 27 million elderly in India in past census decade from 2001 to 2011, it is imperative to work towards exploring the issues and concerns of this increasingly aged population. In Indian society, the elderly person is assumed to be looked after by the family members, especially by children but with changing economy, society, and lifestyle, this assumption demands examining. This paper is an attempt to explore the living arrangement of the elderly and their perceptions about this in India. The findings are based on the BKPAI dataset of 2011, which was conducted in seven states – Himachal Pradesh, Kerala, Maharashtra, Odisha, Punjab, Tamil Nadu, and West Bengal. The result shows that three fourth of elderly lives with their children. Having son and staying with children is positively associated among elderly. More than 40 percent as compared to 37 percent of elderly feels comfortable living with sons and daughters respectively. Half of elderly across sexes viewed that sons are the best person to live with. The result of discriminant analysis suggest that health status and living arrangement of elderly are the good discriminators to ensure their importance in the family.

Keywords: discriminant analysis, elderly, India, living arrangment

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877 Conflict and Hunger Revisit: Evidences from Global Surveys, 1989-2020

Authors: Manasse Elusma, Thung-Hong Lin, Chun-yin Lee

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The relationship between hunger and war or conflict remains to be discussed. Do wars or conflicts cause hunger and food scarcity, or is the reverse relationship is true? As the world becomes more peaceful and wealthier, some countries are still suffered from hunger and food shortage. So, eradicating hunger calls for a more comprehensive understanding of the relationship between conflict and hunger. Several studies are carried out to detect the importance of conflict or war on food security. Most of these studies, however, perform only descriptive analysis and largely use food security indicators instead of the global hunger index. Few studies have employed cross-country panel data to explicitly analyze the association between conflict and chronic hunger, including hidden hunger. Herein, this study addresses this issue and the knowledge gap. We combine global datasets to build a new panel dataset including 143 countries from 1989 to 2020. This study examines the effect of conflict on hunger with fixed effect models, and the results show that the increase of conflict frequency deteriorates hunger. Peacebuilding efforts and war prevention initiative are required to eradicate global hunger.

Keywords: armed conflict, food scarcity, hidden hunger, hunger, malnutrition

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876 [Keynote Speech]: Simulation Studies of Pulsed Voltage Effects on Cells

Authors: Jiahui Song

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In order to predict or explain a complicated biological process, it is important first to construct mathematical models that can be used to yield analytical solutions. Through numerical simulation, mathematical model results can be used to test scenarios that might not be easily attained in a laboratory experiment, or to predict parameters or phenomena. High-intensity, nanosecond pulse electroporation has been a recent development in bioelectrics. The dynamic pore model can be achieved by including a dynamic aspect and a dependence on the pore population density into pore formation energy equation to analyze and predict such electroporation effects. For greater accuracy, with inclusion of atomistic details, molecular dynamics (MD) simulations were also carried out during this study. Besides inducing pores in cells, external voltages could also be used in principle to modulate action potential generation in nerves. This could have an application in electrically controlled ‘pain management’. Also a simple model-based rate equation treatment of the various cellular bio-chemical processes has been used to predict the pulse number dependent cell survival trends.

Keywords: model, high-intensity, nanosecond, bioelectrics

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875 Security Practices of the European Union on Migration: An Analysis of the Frontex Within the Framework of Biopolitics

Authors: Gizem Ertürk, Nursena Dinç

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The Aegean area has always been an important transit point for migration; however, the establishment of the European Union gave further impetus to the migration phenomenon and increased the significance of the area within this context. The migration waves have been more visible in the area in recent decades, and particularly after the “2015 Migration Crisis,” this issue has been subject to further securitization in the EU. In this conjuncture, the Frontex, which is an agency set up by the EU in 2005 for the purpose of managing and coordinating the border control efforts, has become more functional in the relevant area, but at the same time, have some questionable actions within the context of human rights. This paper problematizes the rationality behind the existence and practices of such a structure and attempts to make a political and legal analysis of the security practices of the European Union against migration within a framework based on the biopolitics approaches of Michel Foucault and Giorgio Agamben. The dataset of this paper, which focuses on the agency in question by taking it as a case, is formed by making use of the existing literature on the EU’s security policies, the relevant official texts of the Union and Frontex reports on migration practices in and around the Aegean Sea.

Keywords: migration, biopolitics, Frontex, security, European union, securitization

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874 SC-LSH: An Efficient Indexing Method for Approximate Similarity Search in High Dimensional Space

Authors: Sanaa Chafik, Imane Daoudi, Mounim A. El Yacoubi, Hamid El Ouardi

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Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbour search problem in high dimensional space. Euclidean LSH is the most popular variation of LSH that has been successfully applied in many multimedia applications. However, the Euclidean LSH presents limitations that affect structure and query performances. The main limitation of the Euclidean LSH is the large memory consumption. In order to achieve a good accuracy, a large number of hash tables is required. In this paper, we propose a new hashing algorithm to overcome the storage space problem and improve query time, while keeping a good accuracy as similar to that achieved by the original Euclidean LSH. The Experimental results on a real large-scale dataset show that the proposed approach achieves good performances and consumes less memory than the Euclidean LSH.

Keywords: approximate nearest neighbor search, content based image retrieval (CBIR), curse of dimensionality, locality sensitive hashing, multidimensional indexing, scalability

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873 Improved Feature Extraction Technique for Handling Occlusion in Automatic Facial Expression Recognition

Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade

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The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.

Keywords: automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection

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872 The Predictive Value of Serum Bilirubin in the Post-Transplant De Novo Malignancy: A Data Mining Approach

Authors: Nasim Nosoudi, Amir Zadeh, Hunter White, Joshua Conrad, Joon W. Shim

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De novo Malignancy has become one of the major causes of death after transplantation, so early cancer diagnosis and detection can drastically improve survival rates post-transplantation. Most previous work focuses on using artificial intelligence (AI) to predict transplant success or failure outcomes. In this work, we focused on predicting de novo malignancy after liver transplantation using AI. We chose the patients that had malignancy after liver transplantation with no history of malignancy pre-transplant. Their donors were cancer-free as well. We analyzed 254,200 patient profiles with post-transplant malignancy from the US Organ Procurement and Transplantation Network (OPTN). Several popular data mining methods were applied to the resultant dataset to build predictive models to characterize de novo malignancy after liver transplantation. Recipient's bilirubin, creatinine, weight, gender, number of days recipient was on the transplant waiting list, Epstein Barr Virus (EBV), International normalized ratio (INR), and ascites are among the most important factors affecting de novo malignancy after liver transplantation

Keywords: De novo malignancy, bilirubin, data mining, transplantation

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871 Challenges to Press Freedom in Pakistan

Authors: Awais Ahmad

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People of Khyber Pakhtunkhwa (KP) and Federally Administered Tribal Areas (FATA) remains underrepresented in Pakistan’s mainstream media and their miseries and concerns are unheard and unnoticed. Rising the incidents of human rights violation in KP province of Pakistan, and its absence in the mainstream media has raised many questions on the clause of press freedom known as 19/A in the constitution of Pakistan, that has claimed freedom of speech to all Pakistani citizens. Using a ‘think a loud’ research technique, senior most journalists of KP have been interviewed to get to know reasons of why and how Pashtun’s voices have been silenced in a democratic country where individual’s opinion is considered more powerful, and they can exercise freedom to protest and speak-up for their rights. The information collected from the journalists has been used to evaluate press freedom in KP and FATA by applying the institutional theory. The paper evaluates different recent cases where Pashtun journalists, media outlets and social activists were being punished for criticizing authorities and military establishment. This study also explores that the perception of local journalists regarding press freedom and what are the factors they consider it restrictions while they perform their duties.

Keywords: press freedom, federally administered tribal areas (fata), khyber pakhtunkhwa (kp), military establishment

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870 The Istrian Istrovenetian-Croatian Bilingual Corpus

Authors: Nada Poropat Jeletic, Gordana Hrzica

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Bilingual conversational corpora represent a meaningful and the most comprehensive data source for investigating the genuine contact phenomena in non-monitored bi-lingual speech productions. They can be particularly useful for bilingual research since some features of bilingual interaction can hardly be accessed with more traditional methodologies (e.g., elicitation tasks). The method of language sampling provides the resources for describing language interaction in a bilingual community and/or in bilingual situations (e.g. code-switching, amount of languages used, number of languages used, etc.). To capture these phenomena in genuine communication situations, such sampling should be as close as possible to spontaneous communication. Bilingual spoken corpus design is methodologically demanding. Therefore this paper aims at describing the methodological challenges that apply to the corpus design of the conversational corpus design of the Istrian Istrovenetian-Croatian Bilingual Corpus. Croatian is the first official language of the Croatian-Italian officially bilingual Istria County, while Istrovenetian is a diatopic subvariety of Venetian, a longlasting lingua franca in the Istrian peninsula, the mother tongue of the members of the Italian National Community in Istria and the primary code of informal everyday communication among the Istrian Italophone population. Within the CLARIN infrastructure, TalkBank is being used, as it provides relevant procedures for designing and analyzing bilingual corpora. Furthermore, it allows public availability allows for easy replication of studies and cumulative progress as a research community builds up around the corpus, while the tools developed within the field of corpus linguistics enable easy retrieval and analysis of information. The method of language sampling employed is kept at the level of spontaneous communication, in order to maximise the naturalness of the collected conversational data. All speakers have provided written informed consent in which they agree to be recorded at a random point within the period of one month after signing the consent. Participants are administered a background questionnaire providing information about the socioeconomic status and the exposure and language usage in the participants social networks. Recording data are being transcribed, phonologically adapted within a standard-sized orthographic form, coded and segmented (speech streams are being segmented into communication units based on syntactic criteria) and are being marked following the CHAT transcription system and its associated CLAN suite of programmes within the TalkBank toolkit. The corpus consists of transcribed sound recordings of 36 bilingual speakers, while the target is to publish the whole corpus by the end of 2020, by sampling spontaneous conversations among approximately 100 speakers from all the bilingual areas of Istria for ensuring representativeness (the participants are being recruited across three generations of native bilingual speakers in all the bilingual areas of the peninsula). Conversational corpora are still rare in TalkBank, so the Corpus will contribute to BilingBank as a highly relevant and scientifically reliable resource for an internationally established and active research community. The impact of the research of communities with societal bilingualism will contribute to the growing body of research on bilingualism and multilingualism, especially regarding topics of language dominance, language attrition and loss, interference and code-switching etc.

Keywords: conversational corpora, bilingual corpora, code-switching, language sampling, corpus design methodology

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869 Anomaly Detection with ANN and SVM for Telemedicine Networks

Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

Abstract:

In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines

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868 Existential Absurdity, Alienation and Death in Charles Forsman’s The End of the Fxxxing World, I Am Not Okay With This, and Slasher

Authors: Renukha Devi Anandan

Abstract:

Charles Forsman’s The End of The Fxxxing World, I Am Not Okay With This, and Slasher invariably deals with existential themes. They reflect the perplexed situation of the characters torn between the search for existence and the constraints of human conditions that impede them from such realization, ensuing a dilemma deeply-rooted in absurdity and alienation. These characters are social misfits who fail to fashion their existence and develop harmoniously. Therefore, the present paper adopts an Existential approach to examine the vignettes of alienation and absurdity vis-à-vis the characters’ speech, actions, and thoughts. Furthermore, this paper explores the role of death either as a self-destructive behavior or the eternal freedom of man in graphic novels. Findings portrayed how the characters’ absurd existence surrounded by the void, would eventually develop into death. Finally, the study revealed that Forsman’s distinctive serial illustration not only unveiled the predicaments of the characters through their hard-boiled smokescreens in the 21st-century social paradigm but also established graphic novels as part and parcel of a literary genre.

Keywords: existentialism, absurdity, alienation, death, self-destruction, eternal freedom

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867 A Motion Dictionary to Real-Time Recognition of Sign Language Alphabet Using Dynamic Time Warping and Artificial Neural Network

Authors: Marcio Leal, Marta Villamil

Abstract:

Computacional recognition of sign languages aims to allow a greater social and digital inclusion of deaf people through interpretation of their language by computer. This article presents a model of recognition of two of global parameters from sign languages; hand configurations and hand movements. Hand motion is captured through an infrared technology and its joints are built into a virtual three-dimensional space. A Multilayer Perceptron Neural Network (MLP) was used to classify hand configurations and Dynamic Time Warping (DWT) recognizes hand motion. Beyond of the method of sign recognition, we provide a dataset of hand configurations and motion capture built with help of fluent professionals in sign languages. Despite this technology can be used to translate any sign from any signs dictionary, Brazilian Sign Language (Libras) was used as case study. Finally, the model presented in this paper achieved a recognition rate of 80.4%.

Keywords: artificial neural network, computer vision, dynamic time warping, infrared, sign language recognition

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866 Drug-Drug Interaction Prediction in Diabetes Mellitus

Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe

Abstract:

Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.

Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects

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865 Imputation of Urban Movement Patterns Using Big Data

Authors: Eusebio Odiari, Mark Birkin, Susan Grant-Muller, Nicolas Malleson

Abstract:

Big data typically refers to consumer datasets revealing some detailed heterogeneity in human behavior, which if harnessed appropriately, could potentially revolutionize our understanding of the collective phenomena of the physical world. Inadvertent missing values skew these datasets and compromise the validity of the thesis. Here we discuss a conceptually consistent strategy for identifying other relevant datasets to combine with available big data, to plug the gaps and to create a rich requisite comprehensive dataset for subsequent analysis. Specifically, emphasis is on how these methodologies can for the first time enable the construction of more detailed pictures of passenger demand and drivers of mobility on the railways. These methodologies can predict the influence of changes within the network (like a change in time-table or impact of a new station), explain local phenomena outside the network (like rail-heading) and the other impacts of urban morphology. Our analysis also reveals that our new imputation data model provides for more equitable revenue sharing amongst network operators who manage different parts of the integrated UK railways.

Keywords: big-data, micro-simulation, mobility, ticketing-data, commuters, transport, synthetic, population

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864 Artificial Intelligence Based Method in Identifying Tumour Infiltrating Lymphocytes of Triple Negative Breast Cancer

Authors: Nurkhairul Bariyah Baharun, Afzan Adam, Reena Rahayu Md Zin

Abstract:

Tumor microenvironment (TME) in breast cancer is mainly composed of cancer cells, immune cells, and stromal cells. The interaction between cancer cells and their microenvironment plays an important role in tumor development, progression, and treatment response. The TME in breast cancer includes tumor-infiltrating lymphocytes (TILs) that are implicated in killing tumor cells. TILs can be found in tumor stroma (sTILs) and within the tumor (iTILs). TILs in triple negative breast cancer (TNBC) have been demonstrated to have prognostic and potentially predictive value. The international Immune-Oncology Biomarker Working Group (TIL-WG) had developed a guideline focus on the assessment of sTILs using hematoxylin and eosin (H&E)-stained slides. According to the guideline, the pathologists use “eye balling” method on the H&E stained- slide for sTILs assessment. This method has low precision, poor interobserver reproducibility, and is time-consuming for a comprehensive evaluation, besides only counted sTILs in their assessment. The TIL-WG has therefore recommended that any algorithm for computational assessment of TILs utilizing the guidelines provided to overcome the limitations of manual assessment, thus providing highly accurate and reliable TILs detection and classification for reproducible and quantitative measurement. This study is carried out to develop a TNBC digital whole slide image (WSI) dataset from H&E-stained slides and IHC (CD4+ and CD8+) stained slides. TNBC cases were retrieved from the database of the Department of Pathology, Hospital Canselor Tuanku Muhriz (HCTM). TNBC cases diagnosed between the year 2010 and 2021 with no history of other cancer and available block tissue were included in the study (n=58). Tissue blocks were sectioned approximately 4 µm for H&E and IHC stain. The H&E staining was performed according to a well-established protocol. Indirect IHC stain was also performed on the tissue sections using protocol from Diagnostic BioSystems PolyVue™ Plus Kit, USA. The slides were stained with rabbit monoclonal, CD8 antibody (SP16) and Rabbit monoclonal, CD4 antibody (EP204). The selected and quality-checked slides were then scanned using a high-resolution whole slide scanner (Pannoramic DESK II DW- slide scanner) to digitalize the tissue image with a pixel resolution of 20x magnification. A manual TILs (sTILs and iTILs) assessment was then carried out by the appointed pathologist (2 pathologists) for manual TILs scoring from the digital WSIs following the guideline developed by TIL-WG 2014, and the result displayed as the percentage of sTILs and iTILs per mm² stromal and tumour area on the tissue. Following this, we aimed to develop an automated digital image scoring framework that incorporates key elements of manual guidelines (including both sTILs and iTILs) using manually annotated data for robust and objective quantification of TILs in TNBC. From the study, we have developed a digital dataset of TNBC H&E and IHC (CD4+ and CD8+) stained slides. We hope that an automated based scoring method can provide quantitative and interpretable TILs scoring, which correlates with the manual pathologist-derived sTILs and iTILs scoring and thus has potential prognostic implications.

Keywords: automated quantification, digital pathology, triple negative breast cancer, tumour infiltrating lymphocytes

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863 Phylogenetic Analysis and a Review of the History of the Accidental Phytoplankter, Phaeodactylum tricornutum Bohlin (Bacillariophyta)

Authors: Jamal S. M. Sabir, Edward C. Theriot, Schonna R. Manning, Abdulrahman L. Al-Malki, Mohammad, Mumdooh J. Sabir, Dwight K. Romanovicz, Nahid H. Hajrah, Robert K. Jansen, Matt P. Ashworth

Abstract:

The diatom Phaeodactylum tricornutum has been used as a model for cell biologists and ecologists for over a century. We have incorporated several new raphid pennates into a three-gene phylogenetic dataset (SSU, rbcL, psbC), and recover Gomphonemopsis sp. as sister to P. tricornutum with 100% BS support. This is the first time a close relative has been identified for P. tricornutum with robust statistical support. We test and reject a succession of hypotheses for other relatives. Our molecular data are statistically significantly incongruent with placement of either or both species among the Cymbellales, an order of diatoms with which both have been associated. We believe that further resolution of the phylogenetic position of P. tricornutum will rely more on increased taxon sampling than increased genetic sampling. Gomphonemopsis is a benthic diatom, and its phylogenetic relationship with P. tricornutum is congruent with the hypothesis that P. tricornutum is a benthic diatom with specific adaptations that lead to active recruitment into the plankton. We hypothesize that other benthic diatoms are likely to have similar adaptations and are not merely passively recruited into the plankton.

Keywords: benthic, diatoms; ecology, Phaeodactylum tricornutum, phylogeny, tychoplankton

Procedia PDF Downloads 217