Search results for: violation data discovery

Authors: Jing Zhang, Daniel Nikovski

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We propose an approximation algorithm called LINKUMP to compute the Pan Matrix Profile (PMP) under the unnormalized l∞ distance (useful for value-based similarity search) using double-ended queue and linear interpolation. The algorithm has comparable time/space complexities as the state-of-the-art algorithm for typical PMP computation under the normalized l₂ distance (useful for shape-based similarity search). We validate its efficiency and effectiveness through extensive numerical experiments and a real-world anomaly detection application.

Keywords: pan matrix profile, unnormalized euclidean distance, double-ended queue, discord discovery, anomaly detection

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Authors: Julio Albuja, David Zaldumbide

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Data analysis is an important step before taking a decision about money. The aim of this work is to analyze the factors that influence the final price of the houses through data mining algorithms. To our best knowledge, previous work was researched just to compare results. Furthermore, before using the data of the data set, the Z-Transformation were used to standardize the data in the same range. Hence, the data was classified into two groups to visualize them in a readability format. A decision tree was built, and graphical data is displayed where clearly is easy to see the results and the factors' influence in these graphics. The definitions of these methods are described, as well as the descriptions of the results. Finally, conclusions and recommendations are presented related to the released results that our research showed making it easier to apply these algorithms using a customized data set.

Keywords: algorithms, data, decision tree, transformation

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Authors: Mengdi Zhang, Zhenji Gao, Ning Kang, Rongmei Liu

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Management and application of geological big data is an important part of China's national big data strategy. With the implementation of a national big data strategy, geological big data management becomes more and more critical. At present, there are still a lot of technology barriers as well as cognition chaos in many aspects of geological big data management and application, such as data sharing, intellectual property protection, and application technology. Therefore, it’s a key task to make better use of new technologies for deeper delving and wider application of geological big data. In this paper, we briefly introduce the basic principle of blockchain technology at the beginning and then make an analysis of the application dilemma of geological data. Based on the current analysis, we bring forward some feasible patterns and scenarios for the blockchain application in geological big data and put forward serval suggestions for future work in geological big data management.

Keywords: blockchain, intellectual property protection, geological data, big data management

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Authors: Ayobami P. Olatunji, Saadat Ibiyeye, Abdulaziz Ibiyeye, Tahir M. Khan

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Digital evidence has become a cornerstone in criminal investigations due to the vast amount of information available in digital form. Despite its prevalence, this evidence is often met with skepticism in court proceedings because of its inherently volatile nature. Traditional forensic processes, defined predominantly by technology experts, emphasize technical details in evidence collection while often neglecting legal procedures. This gap can pose significant challenges for legal practitioners in understanding and applying digital forensics. As digital evidence increasingly influences future cases, a cohesive framework integrating both technical and legal perspectives is essential. We propose a comprehensive techno-legal framework designed to bridge this gap. Our framework integrates key aspects of collection, preservation, examination, and documentation with legal components such as case building, certificate of compliance, cross-examination, and authorization. This balanced approach aims not to replace existing evidence presentation principles but to enhance the seamless integration of digital evidence into legal proceedings, addressing the common issues that lead to its dismissal.

Keywords: evidence presentation, warrant, digital-forensic, certificate of compliance, legal procedures, computer crime, violation, investigation cybercrime

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Authors: Tamanna Jethava, Rahul Joshi

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Frequent Item sets play an essential role in many data Mining tasks that try to find interesting patterns from the database. Typically it refers to a set of items that frequently appear together in transaction dataset. There are several mining algorithm being used for frequent item set mining, yet most do not scale to the type of data we presented with today, so called “BIG DATA”. Big Data is a collection of large data sets. Our approach is to work on the frequent item set mining over the large dataset with scalable and speedy way. Big Data basically works with Map Reduce along with HDFS is used to find out frequent item sets from Big Data on large cluster. This paper focuses on using pre-processing & mining algorithm as hybrid approach for big data over Hadoop platform.

Keywords: frequent item set mining, big data, Hadoop, MapReduce

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Authors: Hussaini Garba Mohammed

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Background/Significance: The lack of data gathering is affecting NGOs world-wide in general to have good data information about educational and health related issues among communities in any country and around the world. For example, HIV/AIDS smoking (Tuberculosis diseases) and COVID-19 virus carriers is becoming a serious public health problem, especially among old men and women. But there is no full details data survey assessment from communities, villages, and rural area in some countries to show the percentage of victims and patients, especial with this world COVID-19 virus among the people. These data are essential to inform programming targets, strategies, and priorities in getting good information about data gathering in any society.

Keywords: reliable information, data assessment, data mining, data communication

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Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

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Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: data mining, data analysis, prediction, optimization, building operational performance

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Authors: Shahnewaz Khan

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Machine learning (ML) techniques are often used in projects for creating data-driven applications. These tasks typically demand additional research and analysis. The proper technique and strategy must be chosen to ensure the success of data-driven projects. Otherwise, even exerting a lot of effort, the necessary development might not always be possible. In this post, an effort to examine the workflow of data-driven software development projects and its implementation process in order to describe how to manage a project successfully. Which will assist in minimizing the added workload.

Keywords: data, data-driven projects, data science, NLP, software project

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Authors: Vikas Kumar, Kailash Chandra, Kaomud Tyagi

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The insect order Thysanoptera includes small insects commonly called thrips. As insect vectors, only thrips are capable of Tospoviruses transmission (genus Tospovirus, family Bunyaviridae) affecting various crops. Currently, fifteen species of subfamily Thripinae (Thripidae) have been reported as vectors for tospoviruses. Frankliniella schultzei, which is reported as act as a vector for at least five tospovirses, have been suspected to be a species complex with more than one species. It is one of the historical unresolved issues where, two species namely, F. schultzei Trybom and F. sulphurea Schmutz were erected from South Africa and Srilanaka respectively. These two species were considered to be valid until 1968 when sulphurea was treated as colour morph (pale form) and synonymised under schultzei (dark form) However, these two have been considered as valid species by some of the thrips workers. Parallel studies have indicated that brown form of schultzei is a vector for tospoviruses while yellow form is a non-vector. However, recent studies have shown that yellow populations have also been documented as vectors. In view of all these facts, it is highly important to have a clear understanding whether these colour forms represent true species or merely different populations with different vector carrying capacities and whether there is some hidden diversity in 'Frankliniella schultzei species complex'. In this study, we aim to study the 'Frankliniella schultzei species complex' with molecular spectacles with DNA data from India and Australia and Africa. A total of fifty-five specimens was collected from diverse locations in India and Australia. We generated molecular data using partial fragments of mitochondrial cytochrome c oxidase I gene (mtCOI) and 28S rRNA gene. For COI dataset, there were seventy-four sequences, out of which data on fifty-five was generated in the current study and others were retrieved from NCBI. All the four different tree construction methods: neighbor-joining, maximum parsimony, maximum likelihood and Bayesian analysis, yielded the same tree topology and produced five cryptic species with high genetic divergence. For, rDNA, there were forty-five sequences, out of which data on thirty-nine was generated in the current study and others were retrieved from NCBI. The four tree building methods yielded four cryptic species with high bootstrap support value/posterior probability. Here we could not retrieve one cryptic species from South Africa as we could not generate data on rDNA from South Africa and sequence for rDNA from African region were not available in the database. The results of multiple species delimitation methods (barcode index numbers, automatic barcode gap discovery, general mixed Yule-coalescent, and Poisson-tree-processes) also supported the phylogenetic data and produced 5 and 4 Molecular Operational Taxonomic Units (MOTUs) for mtCOI and 28S dataset respectively. These results of our study indicate the likelihood that F. sulphurea may be a valid species, however, more morphological and molecular data is required on specimens from type localities of these two species and comparison with type specimens.

Keywords: DNA barcoding, species complex, thrips, species delimitation

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Authors: Jake Gonzalez, Tommy Dang

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This paper proposes a temporal graph approach to visualize and analyze the evolution of gene relationships and nomenclature over time. An interactive web-based tool implements this temporal graph, enabling researchers to traverse a timeline and observe coupled dynamics in network topology and naming conventions. Analysis of a real human genomic dataset reveals the emergence of densely interconnected functional modules over time, representing groups of genes involved in key biological processes. For example, the antimicrobial peptide DEFA1A3 shows increased connections to related alpha-defensins involved in infection response. Tracking degree and betweenness centrality shifts over timeline iterations also quantitatively highlight the reprioritization of certain genes’ topological importance as knowledge advances. Examination of the CNR1 gene encoding the cannabinoid receptor CB1 demonstrates changing synonymous relationships and consolidating naming patterns over time, reflecting its unique functional role discovery. The integrated framework interconnecting these topological and nomenclature dynamics provides richer contextual insights compared to isolated analysis methods. Overall, this temporal graph approach enables a more holistic study of knowledge evolution to elucidate complex biology.

Keywords: temporal graph, gene relationships, nomenclature evolution, interactive visualization, biological insights

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Authors: Basak Ozkendirci

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The discovery of chemical dyes, the development of regenerated fibers, and warp knitting technology have enormous effects on the fashion world. The trends created by the information obtained in the context of various studies today shape the fashion world. Trend analysts must follow scientific developments as well as sociological events, political developments and artwork to obtain healthy data on trends. Digital printing technologies have changed the dynamics of textile printing production and also the style of printed designs. Fashion designers already have started design 3D printed accessories and garments. The research fields like the internet of things, artificial intelligence, hologram technologies, mechatronics, energy storage systems, nanotechnology are seen as the technologies that will change the social life and economy of the future. It is clear that research carried out in these areas will affect the textiles of the future and whereat the trends of fashion. The article aims to create a future vision for trend researchers and designers by giving clues about the changes to be experienced in the fashion world. In the first part of the article, information about the scientific studies that are thought to shape the future is given, and the forecasting about how the inventions that can be obtained from these studies can be adapted at the textile are presented. In the second part of the article, examples of how the new generation of innovative textiles will affect the daily life experience of the user are given.

Keywords: biotextiles, fashion trends, nanotextiles, new materials, smart textiles, techno textiles

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Authors: Eleni Karantzola, Athanasios Karasimos, Vasiliki Makri, Ioanna Skouvara

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Historical linguistics unveils the historical depth of languages and traces variation and change by analyzing linguistic variables over time. This field of linguistics usually deals with a closed data set that can only be expanded by the (re)discovery of previously unknown manuscripts or editions. In some cases, it is possible to use (almost) the entire closed corpus of a language for research, as is the case with the Thesaurus Linguae Graecae digital library for Ancient Greek, which contains most of the extant ancient Greek literature. However, concerning ‘dynamic’ periods when the production and circulation of texts in printed as well as manuscript form have not been fully mapped, representative samples and corpora of texts are needed. Such material and tools are utterly lacking for Early Modern Greek (16th-18th c.). In this study, the principles of the creation of EMoGReC, a pilot representative corpus of Early Modern Greek (16th-18th c.) are presented. Its design follows the fundamental principles of historical corpora. The selection of texts aims to create a representative and balanced corpus that gives insight into diachronic, diatopic and diaphasic variation. The pilot sample includes data derived from fully machine-readable vernacular texts, which belong to 4-5 different textual genres and come from different geographical areas. We develop a hierarchical linguistic annotation scheme, further customized to fit the characteristics of our text corpus. Regarding variables and their variants, we use as a point of departure the bundle of twenty-four features (or categories of features) for prose demotic texts of the 16th c. Tags are introduced bearing the variants [+old/archaic] or [+novel/vernacular]. On the other hand, further phenomena that are underway (cf. The Cambridge Grammar of Medieval and Early Modern Greek) are selected for tagging. The annotated texts are enriched with metalinguistic and sociolinguistic metadata to provide a testbed for the development of the first comprehensive set of tools for the Greek language of that period. Based on a relational management system with interconnection of data, annotations, and their metadata, the EMoGReC database aspires to join a state-of-the-art technological ecosystem for the research of observed language variation and change using advanced computational approaches.

Keywords: early modern Greek, variation and change, representative corpus, diachronic variables.

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Authors: Elkington Sibusiso Mnguni

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In South Africa, mining has been a key economic sector since the discovery of gold in 1886 in the Witwatersrand region, where the city of Johannesburg is located. However, some mines have since been decommissioned, and the continuous pumping of acid mine drainage (AMD) also stopped causing the AMD to rise towards the ground surface. This posed a serious environmental risk to the groundwater resources and river systems in the region. This paper documents the development and extent of the environmental damage as well as the measures implemented by the government to alleviate such damage. The study will add to the body of knowledge on the subject of AMD treatment to prevent environmental degradation. The method used to gather and collate relevant data and information was the desktop study. The key findings include the social and environmental impact of the AMD, which include the pollution of water sources for domestic use leading to skin and other health problems and the loss of biodiversity in some areas. It was also found that the technical intervention of constructing a plant to pump and treat the AMD using the high-density sludge technology was the most effective short-term solution available while a long-term solution was being explored. Some successes and challenges experienced during the implementation of the project are also highlighted. The study will be a useful record of the current status of the AMD treatment interventions in the region.

Keywords: acid mine drainage, groundwater resources, pollution, river systems, technical intervention, high density sludge

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Authors: Pitsanu Poonpetpun

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This research aimed to study opinions of Suan Sunandha Rajabhat University administrative personnel towards performance of the university council committee by addressing (1) personal characteristics of the committees; (2) duties designated by the university council; and (3) relationship between university council and university administrative personnel. The population of this study including the president, vice presidents, faculty deans, deputy deans, office heads, director of office of president, directors, deputy directors, division directors, made a total of 118 respondents. Frequency, percentage, mean, and standard deviation were utilized in analyzing the data. The finding on opinions of the administrative personnel towards personal characteristics of the university council committees was averagely at a high level. The characteristic items were rated and revealed that the item gaining the highest mean score was the item stating that the university council committees obtained overall appropriate qualification. The items stating that the president of the teachers’ council acting as the university council committee had impartiality and good governance reported the lowest mean score. The opinions of the administrative personnel towards duty performance of the university council committees was averagely in a high level, in which the item gaining the highest mean score was the item stating that formulating rules and regulations or assigning governmental offices to do so was practiced with governance or fairness to all stakeholders, and the item stating that the president of the teachers’ council acting as the university council committee had impartiality good governance reported the lowest mean score. Moreover, the study found that the rating of opinions of the administrative personnel towards relationship between university council and university administrative personnel was averagely high. Relationship items were rated and revealed that the highest mean score was rated for the fact that the university president was empowered by the university council to manage the university with no violation of the policies. The fact that there was the integrity of policy between the university council and the university administrative personnel was rated the lowest score.

Keywords: performance, university council, education, university administrative personnel

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Authors: M. Naidoo

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Artificial intelligence often requires large amounts of good quality data. Within important fields, such as healthcare, the training of AI systems predominately relies on health and personal data; however, the usage of this data is complicated by various layers of law and ethics that seek to protect individuals’ privacy rights. This research seeks to establish the challenges AI and data sciences pose to (i) informational rights, (ii) privacy rights, and (iii) data protection. To solve some of the issues presented, various methods are suggested, such as embedding values in technological development, proper balancing of rights and interests, and others.

Keywords: artificial intelligence, data science, law, policy

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Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

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In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: simulation data, data summarization, spatial histograms, exploration, visualization

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Authors: Susana Almeida

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The right to adequate food is a human right protected under several international human rights treaties of universal or regional application. In addition, this social right is – as we intend to demonstrate – guaranteed under the Portuguese Constitution. Therefore, in order to assure the protection of this right, the Portuguese State must not only abstain from interfering with this human right (negative obligation) but also take action to secure the human right to adequate food (positive obligation). In this context, the Portuguese State has developed several governmental policies, such as taxing sugary drinks, setting the maximum amount of salt in the bread or creating the National Program for the Promotion of Healthy Food. Nevertheless, we intend to demonstrate that special attention should be given to advertising, as advertisements have an extreme influence on the consumers' decisions and hence on the food decisions. In this paper, besides explaining the cross construction of the human right to adequate food, we aim to examine the Advertising Portuguese Code and to study the several provisions that could be held by the Portuguese consumer to challenge some advertisements due to the violation of the right to health and the right to adequate food. Moreover, having in mind the influence of advertising on the food decisions and the serious problems that unhealthy food may bring (e.g., child obesity), one should ask if this legal framework should not be reviewed in order to lay out some restrictions on advertising, namely setting advices like in alcohol advertisements.

Keywords: advertising code, consumer law, right to adequate food, social human right

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Authors: Evelyn Asante Yeboah, Kwabena O. Asubonteng, Justice Camillus Mensah, Christine Furst

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Smallholder-dominated mosaic landscapes in rural Africa are relevant for food production, biodiversity conservation, and climate regulation. Land-use transitions threaten the multifunctionality of such landscapes, especially the production capacity of arable lands resulting in food security challenges. Using land-cover maps derived from maximum likelihood classification of Landsat satellite images for the years 2002, 2015, and 2020, post-classification change detection, landscape metrics, and key informant interviews, the study assessed the implications of rubber plantation expansion and oil business development on the food production capacity of Ahanta West District, Ghana. The analysis reveals that settlement and rubber areas expanded by 5.82% and 10.33% of the landscape area, respectively, between 2002 and 2020. This increase translates into over twice their initial sizes (144% in settlement change and 101% in rubber change). Rubber plantation spread dominates the north and southwestern areas, whereas settlement is widespread in the eastern parts of the landscape. Rubber and settlement expanded at the expense of cropland, palm, and shrublands. Land-use transitions between cropland, palm, and shrubland were targeting each other, but the net loss in shrubland was higher (-17.27%). Isolation, subdivision, connectedness, and patch adjacency indices showed patch consolidation in the landscape configuration from 2002 to 2015 and patch fragmentation from 2015 to 2020. The study also found patches with consistent increasing connectivity in settlement areas indicating the influence of oil discovery developments and fragmentation tendencies in rubber, shrubland, cropland, and palm, indicating springing up of smaller rubber farms, the disappearance of shrubland, and splitting up of cropland and palm areas respectively. The results revealed a trend in land-use transitions in favor of smallholder rubber plantation expansion and oil discovery developments, which suggest serious implications on food production systems and poses a risk for food security and landscape multifunctional characteristics. To ensure sustainability in land uses, this paper recommends the enforcement of legislative instruments governing spatial planning and land use in Ghana as embedded in the 2016 land-use and spatial planning act.

Keywords: food production systems, food security, Ghana’s west coast, land-use transitions, multifunctional rural landscapes

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Authors: Paula Verdugo-Hernandez, Patricio Cumsille

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We analyze a first-class on the convergence of real number sequences, named hereafter sequences, to foster exploration and discovery of concepts through graphical representations before engaging students in proving. The main goal was to differentiate between sequences and continuous functions-of-a-real-variable and better understand concepts at an initial stage. We applied the analytic frame of mathematical working spaces, which we expect to contribute to extending to sequences since, as far as we know, it has only developed for other objects, and which is relevant to analyze how mathematical work is built systematically by connecting the epistemological and cognitive perspectives, and involving the semiotic, instrumental, and discursive dimensions.

Keywords: convergence, graphical representations, mathematical working spaces, paradigms of real analysis, real number sequences

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Authors: Duncan Wallace, M-Tahar Kechadi

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In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

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Authors: Katarzyna Czarnota, Inga Hajdarowicz

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Political mechanisms of legal, social and economic segregation of refugees and migrants have reproduced and deepened existing hierarchies and inequalities in global labour relations. The consequences of these processes strengthened by current, so called, ‘refugee crisis’, tightening of border regimes, militarisation and closing of Balkan Route, will have a significant impact on future integration policies. One of the fields that require further research is limited access to labour rights of migrants and refugees. Although this phenomenon is experienced by a significant proportion of migrant population, these are the poorest who are also exposed to economic racism. The presentation will tackle the influence of current migration policies on increasing social and class inequalities between migrants, refugees, on the example of Syrian labours in Turkish textile factories. The authors will critically analyse examples of integration policies, especially planned changes in labour law as well as examples of violation of labour rights and exploitation of refugees and migrants in textile factories and industry. The presentation will be based on interviews with Syrian workers, conducted in Turkey and Greece in 2016.

Keywords: refugee crisis, economic racism, global labour relations, exploatation

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Authors: Shenouda Salib Hosni Rofail

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The interface between development and human rights has long been the subject of scholarly debate. As a result, a set of principles ranging from the right to development to a human rights-based approach to development has been adopted to understand the dynamics between the two concepts. Despite these attempts, the exact link between development and human rights is not yet fully understood. However, the inevitable interdependence between the two concepts and the idea that development efforts must be made while respecting human rights have gained prominence in recent years. On the other hand, the emergence of sustainable development as a widely accepted approach to development goals and policies further complicates this unresolved convergence. The place of sustainable development in the human rights discourse and its role in ensuring the sustainability of development programs require systematic research. The aim of this article is, therefore, to examine the relationship between development and human rights, with a particular focus on the place of the principles of sustainable development in international human rights law. It will continue to examine whether it recognizes the right to sustainable development. Thus, the Article states that the principles of sustainable development are recognized directly or implicitly in various human rights instruments, which is an affirmative answer to the question posed above. Accordingly, this document scrutinizes international and regional human rights instruments, as well as the case law and interpretations of human rights bodies, to support this hypothesis.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security.

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Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

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There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

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Authors: Pejman Taghibeikzadehbadr

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Background and Aim: PGC-1 alpha is a transcription factor that was first detected in brown adipose tissue. Since its discovery, PGC-1 alpha has been known to facilitate beneficial adaptations such as mitochondrial biogenesis and increased angiogenesis in skeletal muscle following aerobic exercise. Therefore, the purpose of this study was to investigate the expression of PGC-1 alpha isoforms in response to eccentric and concentric resistance training in healthy subjects. Materials and Methods: Ten healthy men were randomly divided into two groups (5 patients in eccentric group - 5 in eccentric group). Isokinetic contraction protocols included eccentric and concentric knee extension with maximum power and angular velocity of 60 degrees per second. The torques assigned to each subject were considered to match the workload in both protocols, with a rotational speed of 60 degrees per second. Contractions consisted of a maximum of 12 sets of 10 repetitions for the right leg, a rest time of 30 seconds between each set. At the beginning and end of the study, biopsy of the lateral broad muscle tissue was performed. Biopsies were performed in both distal and proximal directions of the lateral flank. To evaluate the expression of PGC1α-1 and PGC1α-4 genes, tissue analysis was performed in each group using Real-Time PCR technique. Data were analyzed using dependent t-test and covariance test. SPSS21 software and Exell 2013 software were used for data analysis. Results: The results showed that intra-group changes of PGC1α-1 after one session of activity were not significant in eccentric (p = 0.168) and concentric (p = 0.959) groups. Also, inter-group changes showed no difference between the two groups (p = 0.681). Also, intra-group changes of PGC1α-4 after one session of activity were significant in an eccentric group (p = 0.012) and concentric group (p = 0.02). Also, inter-group changes showed no difference between the two groups (p = 0.362). Conclusion: It seems that the lack of significant changes in the desired variables due to the lack of exercise pressure is sufficient to stimulate the increase of PGC1α-1 and PGC1α-4. And with regard to reviewing the answer, it seems that the compatibility debate has different results that need to be addressed.

Keywords: eccentric contraction, concentric contraction, PGC1α-1 و PGC1α-4, human subject

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Authors: Calorine Twebaze, Jesca Balinga

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Field X is located on the Eastern shores of L. Albert, Uganda, on the rift flank where the gross sedimentary fill is typically less than 2,000m. The field was discovered in 2006 and encountered about 20.4m of net pay across three (3) stratigraphic intervals within the discovery well. The field covers an area of 3 km2, with the structural configuration comprising a 3-way dip-closed hanging wall anticline that seals against the basement to the southeast along the bounding fault. Field X had been mapped on reprocessed 3D seismic data, which was originally acquired in 2007 and reprocessed in 2013. The seismic data quality is good across the field, and reprocessing work reduced the uncertainty in the location of the bounding fault and enhanced the lateral continuity of reservoir reflectors. The current study was a re-evaluation of Field X to refine fault interpretation and understand the structural uncertainties associated with the field. The seismic data, and three (3) wells datasets were used during the study. The evaluation followed standard workflows using Petrel software and structural attribute analysis. The process spanned from seismic- -well tie, structural interpretation, and structural uncertainty analysis. Analysis of three (3) well ties generated for the 3 wells provided a geophysical interpretation that was consistent with geological picks. The generated time-depth curves showed a general increase in velocity with burial depth. However, separation in curve trends observed below 1100m was mainly attributed to minimal lateral variation in velocity between the wells. In addition to Attribute analysis, three velocity modeling approaches were evaluated, including the Time-Depth Curve, Vo+ kZ, and Average Velocity Method. The generated models were calibrated at well locations using well tops to obtain the best velocity model for Field X. The Time-depth method resulted in more reliable depth surfaces with good structural coherence between the TWT and depth maps with minimal error at well locations of 2 to 5m. Both the NNE-SSW rift border fault and minor faults in the existing interpretation were reevaluated. However, the new interpretation delineated an E-W trending fault in the northern part of the field that had not been interpreted before. The fault was interpreted at all stratigraphic levels and thus propagates from the basement to the surface and is an active fault today. It was also noted that the entire field is less faulted with more faults in the deeper part of the field. The major structural uncertainties defined included 1) The time horizons due to reduced data quality, especially in the deeper parts of the structure, an error equal to one-third of the reflection time thickness was assumed, 2) Check shot analysis showed varying velocities within the wells thus varying depth values for each well, and 3) Very few average velocity points due to limited wells produced a pessimistic average Velocity model.

Keywords: 3D seismic data interpretation, structural uncertainties, attribute analysis, velocity modelling approaches

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Authors: Journey Whitfield

Abstract:

This study investigates the United States' ongoing violation of Black Americans' fundamental human rights, as evidenced by mass incarceration, social injustice, and economic deprivation. It argues that the U.S. contravenes Article 9 of the International Covenant on Civil and Political Rights through policies that uphold systemic racism. The analysis dissects current practices within the criminal justice system, social welfare programs, and economic policy, uncovering the racially disparate impacts of seemingly race-neutral policies. This study establishes a clear lineage between past systems of oppression – slavery and Jim Crow – and present-day racial disparities, demonstrating their inextricable link. The thesis proposes that only a comprehensive reparations program for Black Americans can begin to redress these systemic injustices. This program must transcend mere financial compensation, demanding structural reforms within U.S. institutions to dismantle systemic racism and promote transformative justice. This study explores potential forms of reparations, drawing upon historical precedents, comparative case studies from other nations, and contemporary debates within political philosophy and legal studies. The research employs both qualitative and quantitative methods. Qualitative methods include historical analysis of legal frameworks and policy documents, as well as discourse analysis of political rhetoric. Quantitative methods involve statistical analysis of socioeconomic data and criminal justice outcomes to expose racial disparities. This study makes a significant contribution to the existing literature on reparations, human rights, and racial injustice in the United States. It offers a rigorous analysis of the enduring consequences of historical oppression and advocates for bold, justice-centered solutions.

Keywords: Black Americans, reparations, mass incarceration, racial injustice, human rights, united states

Procedia PDF Downloads 59

Authors: Tosin Ige

Abstract:

Ethics must be a condition of the world, like logic. (Ludwig Wittgenstein, 1889-1951). As important as data mining is, it possess a significant threat to ethics, privacy, and legality, since data mining makes it difficult for an individual or consumer (in the case of a company) to control the accessibility and usage of his data. This research focuses on Current issues and the latest research and development on Privacy preserving data mining methods as at year 2022. It also discusses some advances in those techniques while at the same time highlighting and providing a new technique as a solution to an existing technique of privacy preserving data mining methods. This paper also bridges the wide gap between Data mining and the Web Application Programing Interface (web API), where research is urgently needed for an added layer of security in data mining while at the same time introducing a seamless and more efficient way of data mining.

Keywords: data, privacy, data mining, association rule, privacy preserving, mining technique

Procedia PDF Downloads 173

Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

Abstract:

Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: big data, big data analytics, Hadoop, cloud

Procedia PDF Downloads 312

Authors: AliAkbar Hafezi, Jahanbakhsh Asadi, Majid Shahbazi, Alijan Tabarraei, Nader Mansour Samaei, Hamed Sheibak, Roghaye Gharaei

Abstract:

Background: Breast cancer is the most common cancer in women. In most cancer cells, apoptosis is blocked. As for the importance of apoptosis in cancer cell death and the role of different genes in its induction or inhibition, the search for compounds that can begin the process of apoptosis in tumor cells is discussed as a new strategy in anticancer drug discovery. The aim of this study was to investigate the effect of Naringenin (NGEN) on the apoptosis in the T47D cell line of breast cancer. Materials and Methods: In this experimental study in vitro, the T47D cell line of breast cancer was selected as a sample. The cells at 24, 48, and 72 hours were treated with doses of 20, 200, and 1000 µm of Naringenin. Then, the transcription levels of the genes involved in apoptosis, including Bcl-2, Bax, Caspase 3, Caspase 8, Caspase 9, P53, PARP-1, and FAS, were assessed using Real Time-PCR. The collected data were analyzed using IBM SPSS Statistics 24.0. Results: The results showed that Naringenin at doses of 20, 200, and 1000 µm in all three times of 24, 48, and 72 hours increased the expression of Caspase 3, P53, PARP-1 and FAS and reduced the expression of Bcl-2 and increased the Bax/Bcl-2 ratio, nevertheless in none of the studied doses and times, had not a significant effect on the expression of Bax, Caspase 8 and Caspase 9. Conclusion: This study indicates that Naringenin can reduce the growth of some cancer cells and cause their deaths through increased apoptosis and decreased anti-apoptotic Bcl-2 gene expression and, resulting in the induction of apoptosis via both internal and external pathways.

Keywords: apoptosis, breast cancer, naringenin, T47D cell line

Procedia PDF Downloads 53

Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

Abstract:

The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

Procedia PDF Downloads 418