Search results for: scientific data mining

Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

Abstract:

It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

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Authors: Haojie Wang, Xun Li, Rui Yin

Abstract:

In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

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Authors: Sifat Rahman Ahona, Rifat Tasnim, Naima Hassan

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Data aggregation is a helpful technique for reducing the data communication overhead in wireless sensor network. One of the important tasks of data aggregation is positioning of the aggregator points. There are a lot of works done on data aggregation. But, efficient positioning of the aggregators points is not focused so much. In this paper, authors are focusing on the positioning or the placement of the aggregation points in wireless sensor network. Authors proposed an algorithm to select the aggregators positions for a scenario where aggregator nodes are more powerful than sensor nodes.

Keywords: aggregation point, data communication, data aggregation, wireless sensor network

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

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Authors: Gueidi Afef, Gharsellaoui Hamza, Ben Ahmed Samir

Abstract:

This paper deals with the secret of the continual progression data that new data management solutions have been emerged: The NoSQL databases. They crossed several areas like personalization, profile management, big data in real-time, content management, catalog, view of customers, mobile applications, internet of things, digital communication and fraud detection. Nowadays, these database management systems are increasing. These systems store data very well and with the trend of big data, a new challenge’s store demands new structures and methods for managing enterprise data. The new intelligent machine in the e-learning sector, thrives on more data, so smart machines can learn more and faster. The robotics are our use case to focus on our test. The implementation of NoSQL for Robotics wrestle all the data they acquire into usable form because with the ordinary type of robotics; we are facing very big limits to manage and find the exact information in real-time. Our original proposed approach was demonstrated by experimental studies and running example used as a use case.

Keywords: NoSQL databases, database management systems, robotics, big data

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Authors: Jameson Mirimu, Edward Mawejje, Ibra Twinomujuni

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Introduction: Adolescent girls and young women (AGYW) are a vulnerable category whose risk of acquiring HIV is 20 times compared to the general population accounting for 25% of the new infections. Despite proven scientific evidence of preventing HIV acquisition, Oral Pre-Exposure Prophylaxis (PreP) is less used as one of the biomedical interventions among the AGYW. By 2020, only 31000-32000 of the targeted 90,000 persons in Uganda enrolled on Oral PreP LPHS-EC project employed a combination of Expanded Peer Outreach Approach (EPOA) and Effective client follow-up to increase PreP initiation (PrEP_NEW) and continuation for more than three months (PrEP_CT). Method: Quantitatively, data from National Key population Combination tracker retrospectively analyzed by M&E, focused group discussion with AGYWs and Health care workers to identify barriers. Barriers found; hesitancy of AGYW, misconceptions about Oral PrEP, inadequate knowledge and skills in handling adolescent and Data quality issues. To address the mentioned barriers, youth friendly corners initiated in study sites, identified PrEP Champions among the AGYW, oral PrEP dialogues, group Antenatal counselling, CQI Projects initiated, weekly perfomance meetings to track performance. Results: Routine program data review PrEP_NEW and PrEP_CT increased from 5% (4/80) and 4% (2/54), respectively, in July 2022 to 90% (72/80) and 79% (43/54) respectively for PrEP_NEW and PrEP_CT at the end of March 2023. Lessons Learnt: Demystifying misconception about oral Prep through provision of adequate information by involving health care workers through skills enhancement, CQI projects are critical intervention. Conclusion: With improved safe spaces, skills enhancement of health workers, stakeholders’ engagement through Oral Prep dialogues is critical in improving PreP uptake and continuity among the AGYWS.

Keywords: prep, uptake, continuation, AGYW

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Authors: Patrick Andrew McCoy

Abstract:

The intense fascination with ancient Egypt has persisted for thousands of years and across cultures globally, known popularly as Egyptomania,’ ‘Tutmania,’ ‘Mummymania,’ and ‘Orientalism. A review of the literature indicates psychological themes for its behavior are curiosity, escapism, existentialism, religiosity and spirituality, and cultural, racial, and ethnic identity. A mixed-methods study is initiated with established tools to explore these themes and discover additional motivators. Objectives: The purpose of the study is to explore the themes underlying the intense fascination of ancient Egypt. The abstract themes of the fascination of ancient Egypt are cross-cultural phenomena that motivate people in their interactions with other cultures. These interactions have both been beneficial and combative. Methodology: A mixed methods research study is designed where quantitative (QUAN) survey of participants’ strong fascination with ancient Egypt, within psychological themes derived from a review of the literature. The qualitative (QUAL) survey consists of open-ended questions to explore participants’ exposure to ancient Egypt that may have influenced their fascination and their behaviors resulting from the phenomenon. The themes are explored in QUAN data and QUAL data to discover what themes are established and inferred the psychological motivations of the phenomenon. Main Contributions: This study will provide more information on several scientific disciplines, including psychology, anthropology, Egyptology, and tourism. This study seeks to benefit the tourism industry for not only in Egypt but hopefully with generalizability of cultural tourist industries in other countries.

Keywords: cross-cultural psychology, international psychology, mixed-methods, identity, ancient Egypt, phenomenology, escapism, curiosity, existentialism, religiosity, spirituality

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Authors: Svetlana Strinyuk, Viacheslav Lanin

Abstract:

Academic English has become lingua franca for international scientific community which stimulates universities to introduce English for Specific Purposes (EAP) courses into curriculum. Teaching L2 EAP students might be fulfilled with corpus technologies and digital stylistics. A special software developed to reach the manifold task of teaching, assessing and researching academic writing of L2 students on basis of digital stylistics and multidimensional analysis was created. A set of annotations (style markers) – grammar, lexical and syntactic features most significant of academic writing was built. Contrastive comparison of two corpora “model corpus”, subject domain limited papers published by competent writers in leading academic journals, and “students’ corpus”, subject domain limited papers written by last year students allows to receive data about the features of academic writing underused or overused by L2 EAP student. Both corpora are tagged with a special software created in GATE Developer. Style markers within the framework of research might be replaced depending on the relevance and validity of the result which is achieved from research corpora. Thus, selecting relevant (high frequency) style markers and excluding less relevant, i.e. less frequent annotations, high validity of the model is achieved. Software allows to compare the data received from processing model corpus to students’ corpus and get reports which can be used in teaching and assessment. The less deviation from the model corpus students demonstrates in their writing the higher is academic writing skill acquisition. The research showed that several style markers (hedging devices) were underused by L2 EAP students whereas lexical linking devices were used excessively. A special software implemented into teaching of EAP courses serves as a successful visual aid, makes assessment more valid; it is indicative of the degree of writing skill acquisition, and provides data for further research.

Keywords: corpus technologies in EAP teaching, multidimensional analysis, GATE Developer, corpus stylistics

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Authors: Haojie Wang, Xun Li, Rui Yin

Abstract:

In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

Procedia PDF Downloads 119

Authors: Seo-Hee Kim, Kee-Won Kim, Seung-Hoon Kim

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The most important elements of a novel are the characters, events and background. The background represents the time, place and situation that character appears, and conveys event and atmosphere more realistically. If readers have the proper knowledge about background of novels, it may be helpful for understanding the atmosphere of a novel and choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels because spatio-temporal background especially performs an important role in historical novels among the genre of Korean novels. To the best of our knowledge, we could not find previous study that was aimed at Korean novels. In this paper, we build a Korean historical national dictionary. Our dictionary has historical places and temple names of kings over many generations as well as currently existing spatial words or temporal words in Korean history. We also present a method for recognizing spatio-temporal background based on patterns of phrasal words in Korean sentences. Our rules utilize postposition for spatial background recognition and temple names for temporal background recognition. The knowledge of the recognized background can help readers to understand the flow of events and atmosphere, and can use to visualize the elements of novels.

Keywords: data mining, Korean historical novels, Korean linguistic feature, spatio-temporal background

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Authors: Milind Chaudhari, Suhail Balasinor

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Due to massive deforestation and an ever-increasing population, the organic content of the soil is depleting at a much faster rate. Due to this, there is a big chance that the entire food production in the world will drop by 40% in the next two decades. Vertical farming can help in aiding food production by leveraging big data and cloud computing to ensure plants are grown naturally by providing the optimum nutrients sunlight by analyzing millions of data points. This paper outlines the most important parameters in vertical farming and how a combination of big data and AI helps in calculating and analyzing these millions of data points. Finally, the paper outlines how different organizations are controlling the indoor environment by leveraging big data in enhancing food quantity and quality.

Keywords: big data, IoT, vertical farming, indoor farming

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Authors: Tomi Lois Olatunji, Frances Siebert, Ademola Emmanuel Adetunji, Brian Harvey, Johane Gericke, Josias Hamman, Frank Van Der Kooy

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Ethnopharmacological relevance: Sceletium tortuosum (L.) N.E.Br, the most sought after and widely researched species in the genus Sceletium is a succulent forb endemic to South Africa. Traditionally, this medicinal plant is mainly masticated or smoked and used for the relief of toothache, abdominal pain, and as a mood-elevator, analgesic, hypnotic, anxiolytic, thirst and hunger suppressant, and for its intoxicating/euphoric effects. Sceletium tortuosum is currently of widespread scientific interest due to its clinical potential in treating anxiety and depression, relieving stress in healthy individuals, and enhancing cognitive functions. These pharmacological actions are attributed to its phytochemical constituents referred to as mesembrine-type alkaloids. Aim of the review: The aim of this review was to comprehensively summarize and critically evaluate recent research advances on the phytochemistry, pharmacokinetics, biological and clinical activities of the medicinal plant S. tortuosum. Additionally, current ongoing research and future perspectives are also discussed. Methods: All relevant scientific articles, books, MSc and Ph.D. dissertations on botany, behavioral pharmacology, traditional uses, and phytochemistry of S. tortuosum were retrieved from different databases (including Science Direct, PubMed, Google Scholar, Scopus and Web of Science). For pharmacokinetics and pharmacological effects of S. tortuosum, the focus fell on relevant publications published between 2009 and 2021. Results: Twenty-five alkaloids belonging to four structural classes viz: mesembrine, Sceletium A4, joubertiamine, and tortuosamine, have been identified from S. tortuosum, of which the mesembrine class is predominant. The crude extracts and commercially available standardized extracts of S. tortuosum have displayed a wide spectrum of biological activities (e.g. antimalarial, anti-oxidant, immunomodulatory, anti-HIV, neuroprotection, enhancement of cognitive function) in in vitro or in vivo studies. This plant has not yet been studied in a clinical population, but has potential for enhancing cognitive function, and managing anxiety and depression. Conclusion: As an important South African medicinal plant, S. tortuosum has garnered many research advances on its phytochemistry and biological activities over the last decade. These scientific studies have shown that S. tortuosum has various bioactivities. The findings have further established the link between the phytochemistry and pharmacological application, and support the traditional use of S. tortuosum in the indigenous medicine of South Africa.

Keywords: Aizoaceae, Mesembrine, Serotonin, Sceletium tortuosum, Zembrin®, psychoactive, antidepressant

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Authors: U. V. Okpala

Abstract:

Flood is an overflow of water that submerges or ‘drowns’ land. In developing countries it occurs as a result of blocking of natural and man-made drainages and poor maintenance of water dams/reservoirs which seldom give way after persistent heavy down pours. In coastal lowlands and swamp lands, flooding is aided mainly by blocked channels and indiscriminate sand fling of coastal swamp areas and natural drainage channel for urban development/constructions. In this paper, the causes of flood and possible scientific, technological, political, economic and social impacts of flood disaster on the environment a case study of Anambra State have been studied. Often times flooding is caused by climate change, especially in the developed economy where scientific mitigating options are highly employed. Researchers have identified Green Houses Gases (GHG) as the cause of global climate change. The recent flood disaster in Anambra State which caused physical damage to structures, social dislocation, contamination of clean drinking water, spread of water-borne diseases, shortage of crops and food supplies, death of non-tolerant tree species, disruption in transportation system, serious economic loss and psychological trauma is a function of climate change. There is need to encourage generation of renewable energy sources, use of less carbon intensive fuels and other energy efficient sources. Carbon capture/sequestration, proper management of our drainage systems and good maintenance of our dams are good option towards saving the environment.

Keywords: flooding, climate change, carbon capture, energy systems

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Authors: Oualid Walid Ben Ali

Abstract:

Big Data has become one of the buzzwords today. The recent explosion of digital data has led the organization, either private or public, to a new era towards a more efficient decision making. At some point, business decided to use that concept in order to learn what make their clients tick with phrases like ‘sales funnel’ analysis, ‘actionable insights’, and ‘positive business impact’. So, it stands to reason that Big Data was viewed through green (read: money) colored lenses. Somewhere along the line, however someone realized that collecting and processing data doesn’t have to be for business purpose only, but also could be used for other purposes to assist law enforcement or to improve policing or in road safety. This paper presents briefly, how Big Data have been used in the fields of policing order to improve the decision making process in the daily operation of the police. As example, we present a big-data driven system which is sued to accurately dispatch the patrol cars in a geographic environment. The system is also used to allocate, in real-time, the nearest patrol car to the location of an incident. This system has been implemented and applied in the Emirate of Abu Dhabi in the UAE.

Keywords: big data, big data analytics, patrol car allocation, dispatching, GIS, intelligent, Abu Dhabi, police, UAE

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Authors: Steven Sam, Ximena Schmidt, Hugh Dickinson, Jens Jensen

Abstract:

The goal of this study is to explore the potential of data science and citizen science approaches to develop an interactive, digital, open infrastructure that pulls together African indigenous agriculture and food systems data from multiple sources, making it accessible and reusable for policy, research and practice in modern food production efforts. The World Bank has recognised that African Indigenous Knowledge (AIK) is innovative and unique among local and subsistent smallholder farmers, and it is central to sustainable food production and enhancing biodiversity and natural resources in many poor, rural societies. AIK refers to tacit knowledge held in different languages, cultures and skills passed down from generation to generation by word of mouth. AIK is a key driver of food production, preservation, and consumption for more than 80% of citizens in Africa, and can therefore assist modern efforts of reducing food insecurity and hunger. However, the documentation and dissemination of AIK remain a big challenge confronting librarians and other information professionals in Africa, and there is a risk of losing AIK owing to urban migration, modernisation, land grabbing, and the emergence of relatively small-scale commercial farming businesses. There is also a clear disconnect between the AIK and scientific knowledge and modern efforts for sustainable food production. The study combines data science and citizen science approaches through active community participation to generate and share AIK for facilitating learning and promoting knowledge that is relevant for policy intervention and sustainable food production through a curated digital platform based on FAIR principles. The study adopts key informant interviews along with participatory photo and video elicitation approach, where farmers are given digital devices (mobile phones) to record and document their every practice involving agriculture, food production, processing, and consumption by traditional means. Data collected are analysed using the UK Science and Technology Facilities Council’s proven methodology of citizen science (Zooniverse) and data science. Outcomes are presented in participatory stakeholder workshops, where the researchers outline plans for creating the platform and developing the knowledge sharing standard framework and copyrights agreement. Overall, the study shows that learning from AIK, by investigating what local communities know and have, can improve understanding of food production and consumption, in particular in times of stress or shocks affecting the food systems and communities. Thus, the platform can be useful for local populations, research, and policy-makers, and it could lead to transformative innovation in the food system, creating a fundamental shift in the way the North supports sustainable, modern food production efforts in Africa.

Keywords: Africa indigenous agriculture knowledge, citizen science, data science, sustainable food production, traditional food system

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Authors: Ana L. Sánchez Regla, Igor A. Rivera González, María del Pilar Monserrat Pérez Hernández

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The ability of an organization to identify and get useful information from external sources, assimilate it, transform and apply to generate products or services with added value is called absorptive capacity. Absorptive capabilities contribute to have market opportunities to firms and get a leader position with respect to others competitors. The Bioprocess Development and Research Unit (UDIBI) is a Research and Development (R&D) laboratory that belongs to the National Polytechnic Institute (IPN), which is a higher education institute in Mexico. The UDIBI was created with the purpose of carrying out R and D activities for the Transferon®, a biopharmaceutical product developed and patented by IPN. The evolution of competence and scientific and technological platform made UDIBI expand its scope by providing technological services (preclínical studies and bio-compatibility evaluation) to the national pharmaceutical industry and biopharmaceutical industry. The relevance of this study is that those industries are classified as high scientific and technological intensity, and yet, after a review of the state of the art, there is only one study of absorption capabilities in biopharmaceutical industry with a similar scope to this research; in the case of Mexico, there is none. In addition to this, UDIBI belongs to a public university and its operation does not depend on the federal budget, but on the income generated by its external technological services. This fact represents a highly remarkable case in Mexico's public higher education context. This current doctoral research (2015-2019) is contextualized within a case study, its main objective is to identify and analyze the absorptive capabilities that characterise the UDIBI that allows it had become in a one of two third authorized laboratory by the sanitary authority in Mexico for developed bio-comparability studies to bio-pharmaceutical products. The development of this work in the field is divided into two phases. In a first phase, 15 interviews were conducted with the UDIBI personnel, covering management levels, heads of services, project leaders and laboratory personnel. These interviews were structured under a questionnaire, which was designed to integrate open questions and to a lesser extent, others, whose answers would be answered on a Likert-type rating scale. From the information obtained in this phase, a scientific article was made (in review and a proposal of presentation was submitted in different academic forums. A second stage will be made from the conduct of an ethnographic study within this organization under study that will last about 3 months. On the other hand, it is intended to carry out interviews with external actors around the UDIBI (suppliers, advisors, IPN officials, including contact with an academic specialized in absorption capacities to express their comments on this thesis. The inicial findings had shown two lines: i) exist institutional, technological and organizational management elements that encourage and/or limit the creation of absorption capacities in this scientific and technological laboratory and, ii) UDIBI has had created a set of multiple transfer technology of knowledge mechanisms which have had permitted to build a huge base of prior knowledge.

Keywords: absorptive capabilities, biopharmaceutical industry, high research and development intensity industries, knowledge management, transfer of knowledge

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Authors: D. Mokhtari

Abstract:

Any variation in environmental characteristics of geomorphosites would lead to destabilisation of their geotouristic values all around the planet. The Urmia lake, with an area of approximately 5,500 km2 and a catchment area of 51,876 km2, and to which various reasons over time, especially in the last fifty years have seen a sharp decline and have decreased by about 93 % in two recent decades. These variations are not only driving significant changes in the morphology and ecology of the present lake landscape, but at the same time are shaping newly formed morphologies, which vanished some valuable geomorphosites or develop into smaller geomorphosites with significant value from a scientific and cultural point of view. This paper analyses and discusses features and evolution in several representative coastal and island geomorphosites. For this purpose, a total of 23 geomorphosites were studied in two data series (1963 and 2015) and the respective data were compared and analysed. The results showed, The total loss in geomorphosites area in a half century amounted to a loss of more than 90% of the valuable geomorphosites. Moreover, the comparison between the mean yearly value of coastal area lost over the entire period and the yearly average calculated for the shorter period (1998-2014) clearly indicates a pattern of acceleration. This acceleration in the rate of reduction in lake area was seen in most of the southern half of the lake. In the region as well, the general water-level falling is not only causing the loss of a significant water resource, which is followed by major impact on regional ecosystems, but is also driving the most marked recent (last century) changes in the geotouristic landscapes. In fact, the disappearance of geomorphosites means the loss of tourism phenomenon. In this context attention must be paid to the question of conservation. The action needed to safeguard geomorphosites includes: 1) Preventive action, 2) Corrective action, and 3) Sharing knowledge.

Keywords: geomorphosite, environmental changes, changing lake, Urmia lake, northwest of Iran

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Authors: Aref Ghafouri, Mohammad javad Mollakazemi, Farhad Asadi

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In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further.

Keywords: frequency response, order of model reduction, frequency matching condition, nonlinear experimental data

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Authors: Dina Kon Mushid, Sage Ngoie, Tshimbalanga Madiba, Kabutakapua Kakanda

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Slope stability assessment is still the biggest challenge in mining activities and civil engineering structures. The slope in an opencast mine frequently reaches multiple weak layers that lead to the instability of the pit. Faults and soft layers throughout the rock would increase weathering and erosion rates. Therefore, it is essential to investigate the stability of the complex strata to figure out how stable they are. In the Dikuluwe-Mashamba (DIMA) area, the lithology of the stratum is a set of metamorphic rocks whose parent rocks are sedimentary rocks with a low degree of metamorphism. Thus, due to the composition and metamorphism of the parent rock, the rock formation is different in hardness and softness, which means that when the content of dolomitic and siliceous is high, the rock is hard. It is softer when the content of argillaceous and sandy is high. Therefore, from the vertical direction, it appears as a weak and hard layer, and from the horizontal direction, it seems like a smooth and hard layer in the same rock layer. From the structural point of view, the main structures in the mining area are the Dikuluwe dipping syncline and the Mashamba dipping anticline, and the occurrence of rock formations varies greatly. During the folding process of the rock formation, the stress will concentrate on the soft layer, causing the weak layer to be broken. At the same time, the phenomenon of interlayer dislocation occurs. This article aimed to evaluate the stability of metasedimentary rocks of the Dikuluwe-Mashamba (DIMA) open-pit mine using limit equilibrium and stereographic methods Based on the presence of statistical structural planes, the stereographic projection was used to study the slope's stability and examine the discontinuity orientation data to identify failure zones along the mine. The results revealed that the slope angle is too steep, and it is easy to induce landslides. The numerical method's sensitivity analysis showed that the slope angle and groundwater significantly impact the slope safety factor. The increase in the groundwater level substantially reduces the stability of the slope. Among the factors affecting the variation in the rate of the safety factor, the bulk density of soil is greater than that of rock mass, the cohesion of soil mass is smaller than that of rock mass, and the friction angle in the rock mass is much larger than that in the soil mass. The analysis showed that the rock mass structure types are mostly scattered and fragmented; the stratum changes considerably, and the variation of rock and soil mechanics parameters is significant.

Keywords: slope stability, weak layer, safety factor, limit equilibrium method, stereography method

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Authors: Thuan Nguyen

Abstract:

In the present time, data to a data-driven knowledge-based economy is the same as oil to the industrial age hundreds of years ago. Data is everywhere in vast volumes! Big data analytics is expected to help firms not only efficiently improve performance but also completely transform how they should run their business. However, employing the emergent technology successfully is not easy, and assessing the roles of big data in improving firm performance is even much harder. There was a lack of studies that have examined the impacts of big data analytics on organizational performance. This study aimed to fill the gap. The present study suggested using firms’ intellectual capital as a proxy for big data in evaluating its impact on organizational performance. The present study employed the Value Added Intellectual Coefficient method to measure firm intellectual capital, via its three main components: human capital efficiency, structural capital efficiency, and capital employed efficiency, and then used the structural equation modeling technique to model the data and test the models. The financial fundamental and market data of 100 randomly selected publicly listed firms were collected. The results of the tests showed that only human capital efficiency had a significant positive impact on firm profitability, which highlighted the prominent human role in the impact of big data technology.

Keywords: big data, big data analytics, intellectual capital, organizational performance, value added intellectual coefficient

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Authors: Hitesh Tahbildar

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The cost of test data generation for a program is computationally very high. In general case, no algorithm to generate test data for all types of algorithms has been found. The cost of generating test data for different types of algorithm is different. Till date, people are emphasizing the need to generate test data for different types of programming constructs rather than different types of algorithms. The test data generation methods have been implemented to find heuristics for different types of algorithms. Some algorithms that includes divide and conquer, backtracking, greedy approach, dynamic programming to find the minimum cost of test data generation have been tested. Our experimental results say that some of these types of algorithm can be used as a necessary condition for selecting heuristics and programming constructs are sufficient condition for selecting our heuristics. Finally we recommend the different heuristics for test data generation to be selected for different types of algorithms.

Keywords: ongest path, saturation point, lmax, kL, kS

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Authors: Hatice Kübra Koç

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For academia, collecting reliable and valid data is one of the most significant issues for researchers. However, it is not the same procedure for all different target groups; meanwhile, during data collection from teenagers, young adults, or adults, researchers can use common data collection tools such as questionnaires, interviews, and semi-structured interviews; yet, for young learners and very young ones, these reliable and valid data collection tools cannot be easily designed or applied by the researchers. In this study, firstly, common data collection tools are examined for ‘very young’ and ‘young learners’ participant groups since it is thought that the quality and efficiency of an academic study is mainly based on its valid and correct data collection and data analysis procedure. Secondly, two different data collection instruments for very young and young learners are stated as discussing the efficacy of them. Finally, a suggested data collection tool – a performance-based questionnaire- which is specifically developed for ‘very young’ and ‘young learners’ participant groups in the field of teaching English to young learners as a foreign language is presented in this current study. The designing procedure and suggested items/factors for the suggested data collection tool are accordingly revealed at the end of the study to help researchers have studied with young and very learners.

Keywords: data collection instruments, performance-based questionnaire, young learners, very young learners

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Authors: S.V. Kleyn, S.Yu. Zagorodnov, А.А. Kokoulina

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Technogenic emissions of the mining and processing complex are characterized by a high content of chemical components and solid dust particles. However, each industrial enterprise and the surrounding area have features that require refinement and parameterization. Numerous studies have shown the negative impact of fine dust PM10 and PM2.5 on the health, as well as the possibility of toxic components absorption, including heavy metals by dust particles. The target of the study was the quantitative assessment of the fractional and particle size composition of ambient air dust in the area of impact by primary magnesium production complex. Also, we tried to describe the morphology features of dust particles. Study methods. To identify the dust emission sources, the analysis of the production process has been carried out. The particulate composition of the emissions was measured using laser particle analyzer Microtrac S3500 (covered range of particle size is 20 nm to 2000 km). Particle morphology and the component composition were established by electron microscopy by scanning microscope of high resolution (magnification rate - 5 to 300 000 times) with X-ray fluorescence device S3400N ‘HITACHI’. The chemical composition was identified by X-ray analysis of the samples using an X-ray diffractometer XRD-700 ‘Shimadzu’. Determination of the dust pollution level was carried out using model calculations of emissions in the atmosphere dispersion. The calculations were verified by instrumental studies. Results of the study. The results demonstrated that the dust emissions of different technical processes are heterogeneous and fractional structure is complicated. The percentage of particle sizes up to 2.5 micrometres inclusive was ranged from 0.00 to 56.70%; particle sizes less than 10 microns inclusive – 0.00 - 85.60%; particle sizes greater than 10 microns - 14.40% -100.00%. During microscopy, the presence of nanoscale size particles has been detected. Studied dust particles are round, irregular, cubic and integral shapes. The composition of the dust includes magnesium, sodium, potassium, calcium, iron, chlorine. On the base of obtained results, it was performed the model calculations of dust emissions dispersion and establishment of the areas of fine dust РМ 10 and РМ 2.5 distribution. It was found that the dust emissions of fine powder fractions PM10 and PM2.5 are dispersed over large distances and beyond the border of the industrial site of the enterprise. The population living near the enterprise is exposed to the risk of diseases associated with dust exposure. Data are transferred to the economic entity to make decisions on the measures to minimize the risks. Exposure and risks indicators on the health are used to provide named patient health and preventive care to the citizens living in the area of negative impact of the facility.

Keywords: dust emissions, еxposure assessment, PM 10, PM 2.5

Procedia PDF Downloads 241

Authors: Sunmaila Oyetunji Raimi, Olufemi Akinloye Bolaji, Abiodun Ezekiel Adesina

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The lingering poor performance of students in basic science spells doom for a vibrant scientific and technological development which pivoted the economic, social and physical upliftment of any nation. This calls for identifying appropriate strategies for imparting basic science knowledge and attitudes to the teaming youths in secondary schools. This study, therefore, determined the impact of computer mediated power point presentations on students’ achievement in basic science in Oyo State, Nigeria. A pre-test, posttest, control group quazi-experimental design adopted for the study. Two hundred and five junior secondary two students selected using stratified random sampling technique participated in the study. Three research questions and three hypotheses guided the study. Two evaluative instruments – Students’ Basic Science Attitudes Scale (SBSAS, r = 0.91); Students’ Knowledge of Basic Science Test (SKBST, r = 0.82) were used for data collection. Descriptive statistics of mean, standard deviation and inferential statistics of ANCOVA, scheffe post-hoc test were used to analyse the data. The results indicated significant main effect of treatment on students cognitive (F(1,200)= 171.680; p < 0.05) and attitudinal (F(1,200)= 34.466; p < 0.05) achievement in Basic science with the experimental group having higher mean gain than the control group. Gender has significant main effect (F(1,200)= 23.382; p < 0.05) on students cognitive outcomes but not significant for attitudinal achievement in Basic science. The study therefore recommended among others that computer mediated power point presentations should be incorporated into curriculum methodology of Basic science in secondary schools.

Keywords: basic science, computer mediated power point presentations, gender, students’ achievement

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Authors: Yaxin Bi

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Accurate prediction and understanding of the evolution mechanisms of earthquakes remain challenging in the fields of geology, geophysics, and seismology. This study leverages Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs), a generative model tailored to time-series data, for generating synthetic time series data based on Swarm satellite data, which will be used for detecting seismic anomalies. LSTMs demonstrated commendable predictive performance in generating synthetic data across multiple countries. In contrast, the GAN models struggled to generate synthetic data, often producing non-informative values, although they were able to capture the data distribution of the time series. These findings highlight both the promise and challenges associated with applying deep learning techniques to generate synthetic data, underscoring the potential of deep learning in generating synthetic electromagnetic satellite data.

Keywords: LSTM, GAN, earthquake, synthetic data, generative AI, seismic precursors

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Authors: Prima Fithri, Lusi Susanti, Karin Bestarina

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Indonesia's electrification ratio is still around 80.1%, which means that approximately 19.9% of households in Indonesia have not been getting the flow of electrical energy. Household electricity consumptions in Indonesia are generally still dominated by the public urban. In the city of Padang, West Sumatera, Indonesia, about 94.10% are power users of government services (PLN). The most important thing of the issue is human resources efficient energy. Consumer behavior in utilizing electricity becomes significant. Intensive questioner survey, in-depth interview and statistical analysis are carried out to collect scientific evidences of the behavioral based changes instruments to reduce electricity consumption in household sector. The questioner was developed to include five factors assuming affect the electricity consumption pattern in household sector. They are: attitude, energy price, household income, knowledge and other determinants. The survey was carried out in Padang, West Sumatra Province Indonesia. About 210 questioner papers were proportionally distributed to households in 11 districts in Padang. Stratified sampling was used as a method to select respondents. The results show that the household size, income, payment methods and size of house are factors affecting electricity saving behavior in residential sector. Household expenses on electricity are strongly influenced by gender, type of job, level of education, size of house, income, payment method and level of installed power. These results provide a scientific evidence for stakeholders on the potential of controlling electricity consumption and designing energy policy by government in residential sector.

Keywords: electricity, energy saving, household, behavior, policy

Procedia PDF Downloads 511

Authors: Chuanqiao Zheng, Wei Zeng, Haozhen Lin

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As of March 2020, the number of Chinese netizens has reached 904 million. The proportion of Internet users accessing the Internet through mobile phones is as high as 99.3%. Under the background of 'Internet +', tourists have a stronger sense of independence in the choice of tourism destinations and tourism products. Tourists are more inclined to learn about the relevant information on tourism destinations and other tourists' evaluations of tourist products through the Internet. The search engine, as an integrated platform that contains a wealth of information, is highly valuable to the analysis of the characteristics of the Internet attention given to various tourism destinations, through big data mining and analysis. This article uses the Baidu Index as the data source, which is one of the products of Baidu Search. The Baidu Index is based on big data, which collects and shares the search results of a large number of Internet users on the Baidu search engine. The big data used in this article includes search index, demand map, population profile, etc. The main research methods used are: (1) based on the search index, analyzing the Internet attention given to the tourism in five cities in Northeast Sichuan at different times, so as to obtain the overall trend and individual characteristics of tourism development in the region; (2) based on the demand map and the population profile, analyzing the demographic characteristics and market positioning of the tourist groups in these cities to understand the characteristics and needs of the target groups; (3) correlating the Internet attention data with the permanent population of each province in China in the corresponding to construct the Boston matrix of the Internet attention rate of the Northeast Sichuan tourism, obtain the tourism target markets, and then propose development strategies for different markets. The study has found that: a) the Internet attention given to the tourism in the region can be categorized into tourist off-season and peak season; the Internet attention given to tourism in different cities is quite different. b) tourists look for information including tour guide information, ticket information, traffic information, weather information, and information on the competing tourism cities; with regard to the population profile, the main group of potential tourists searching for the keywords of tourism in the five prefecture-level cities in Northeast Sichuan are youth. The male to female ratio is about 6 to 4, with males being predominant. c) through the construction of the Boston matrix, it is concluded that the star market for tourism in the Northeast Sichuan Economic Zone includes Sichuan and Shaanxi; the cash cows market includes Hainan and Ningxia; the question market includes Jiangsu and Shanghai; the dog market includes Hubei and Jiangxi. The study concludes with the following planning strategies and recommendations: i) creating a diversified business format that integrates cultural and tourism; ii) creating a brand image of niche tourism; iii) focusing on the development of tourism products; iv) innovating composite three-dimensional marketing channels.

Keywords: Baidu Index, big data, internet attention, tourism

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Authors: Ruwan Gunawardane

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Second language teaching and learning is a complex process in which various factors are identified as having a negative impact on the competency in English among undergraduates of Sri Lanka. One such issue is the lack of intrinsic motivation among them to learn English despite the fact that they all know the importance of English. This study attempted to ascertain how the intrinsic motivation of undergraduates to learn English can be improved through reading out of curiosity. Humans are curious by nature, and cognitive psychology says that curiosity facilitates learning, memory, and motivation. The researcher carried out this study during the closure of universities due to the outbreak of the coronavirus through ‘Online Reading Café’, an online reading programme introduced by himself. He invited 1166 students of the Faculty of Science, University of Ruhuna, to read 50 articles taken from CNN and the BBC and posted at least two to three articles on the LMS of the faculty almost every day over a period of 23 days. The themes of the articles were based on the universe, exploration of planets, scientific experiments, evolution, etc., and the students were encouraged to collect as many words, phrases, and sentence structures as possible while reading and to form meaningful sentences using them. The data obtained through the students’ feedback was qualitatively analyzed. It was found that these undergraduates were interested in reading something out of curiosity, due to which intrinsic motivation is enhanced, and it facilitates competence in L2.

Keywords: English, competence, reading, curiosity

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Authors: Hyun-Woo Cho

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For ensuring the safety of a manufacturing process one should quickly identify an assignable cause of a fault in an on-line basis. To this end, many statistical techniques including linear and nonlinear methods have been frequently utilized. However, such methods possessed a major problem of small sample size, which is mostly attributed to the characteristics of empirical models used for reference models. This work presents a new method to overcome the insufficiency of measurement data in the monitoring and diagnosis tasks. Some quasi-measurement data are generated from existing data based on the two indices of similarity and importance. The performance of the method is demonstrated using a real data set. The results turn out that the presented methods are able to handle the insufficiency problem successfully. In addition, it is shown to be quite efficient in terms of computational speed and memory usage, and thus on-line implementation of the method is straightforward for monitoring and diagnosis purposes.

Keywords: data analysis, diagnosis, monitoring, process data, quality control

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Authors: Xiao Zhou, Jianlin Cheng

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A single amino acid mutation can have a significant impact on the stability of protein structure. Thus, the prediction of protein stability change induced by single site mutations is critical and useful for studying protein function and structure. Here, we presented a deep learning network with the dropout technique for predicting protein stability changes upon single amino acid substitution. While using only protein sequence as input, the overall prediction accuracy of the method on a standard benchmark is >85%, which is higher than existing sequence-based methods and is comparable to the methods that use not only protein sequence but also tertiary structure, pH value and temperature. The results demonstrate that deep learning is a promising technique for protein stability prediction. The good performance of this sequence-based method makes it a valuable tool for predicting the impact of mutations on most proteins whose experimental structures are not available. Both the downloadable software package and the user-friendly web server (DNpro) that implement the method for predicting protein stability changes induced by amino acid mutations are freely available for the community to use.

Keywords: bioinformatics, deep learning, protein stability prediction, biological data mining

Procedia PDF Downloads 440